Machine learning-based agoraphilic navigation algorithm for use in dynamic environments with a moving goal
- Hewawasam, Hasitha, Kahandawa, Gayan, Ibrahim, Yousef
- Authors: Hewawasam, Hasitha , Kahandawa, Gayan , Ibrahim, Yousef
- Date: 2023
- Type: Text , Journal article
- Relation: Machines Vol. 11, no. 5 (2023), p. 513
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- Description: This paper presents a novel development of a new machine learning-based control system for the Agoraphilic (free-space attraction) concept of navigating robots in unknown dynamic environments with a moving goal. Furthermore, this paper presents a new methodology to generate training and testing datasets to develop a machine learning-based module to improve the performances of Agoraphilic algorithms. The new algorithm presented in this paper utilises the free-space attraction (Agoraphilic) concept to safely navigate a mobile robot in a dynamically cluttered environment with a moving goal. The algorithm uses tracking and prediction strategies to estimate the position and velocity vectors of detected moving obstacles and the goal. This predictive methodology enables the algorithm to identify and incorporate potential future growing free-space passages towards the moving goal. This is supported by the new machine learning-based controller designed specifically to efficiently account for the high uncertainties inherent in the robot’s operational environment with a moving goal at a reduced computational cost. This paper also includes comparative and experimental results to demonstrate the improvements of the algorithm after introducing the machine learning technique. The presented experiments demonstrated the success of the algorithm in navigating robots in dynamic environments with the challenge of a moving goal.
- Authors: Hewawasam, Hasitha , Kahandawa, Gayan , Ibrahim, Yousef
- Date: 2023
- Type: Text , Journal article
- Relation: Machines Vol. 11, no. 5 (2023), p. 513
- Full Text:
- Reviewed:
- Description: This paper presents a novel development of a new machine learning-based control system for the Agoraphilic (free-space attraction) concept of navigating robots in unknown dynamic environments with a moving goal. Furthermore, this paper presents a new methodology to generate training and testing datasets to develop a machine learning-based module to improve the performances of Agoraphilic algorithms. The new algorithm presented in this paper utilises the free-space attraction (Agoraphilic) concept to safely navigate a mobile robot in a dynamically cluttered environment with a moving goal. The algorithm uses tracking and prediction strategies to estimate the position and velocity vectors of detected moving obstacles and the goal. This predictive methodology enables the algorithm to identify and incorporate potential future growing free-space passages towards the moving goal. This is supported by the new machine learning-based controller designed specifically to efficiently account for the high uncertainties inherent in the robot’s operational environment with a moving goal at a reduced computational cost. This paper also includes comparative and experimental results to demonstrate the improvements of the algorithm after introducing the machine learning technique. The presented experiments demonstrated the success of the algorithm in navigating robots in dynamic environments with the challenge of a moving goal.
Malicious node detection using machine learning and distributed data storage using blockchain in WSNs
- Nouman, Muhammad, Qasim, Umar, Nasir, Hina, Almasoud, Abdullah, Imran, Muhammad, Javaid, Nadeem
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
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- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
- Authors: Nouman, Muhammad , Qasim, Umar , Nasir, Hina , Almasoud, Abdullah , Imran, Muhammad , Javaid, Nadeem
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 6106-6121
- Full Text:
- Reviewed:
- Description: In the proposed work, blockchain is implemented on the Base Stations (BSs) and Cluster Heads (CHs) to register the nodes using their credentials and also to tackle various security issues. Moreover, a Machine Learning (ML) classifier, termed as Histogram Gradient Boost (HGB), is employed on the BSs to classify the nodes as malicious or legitimate. In case, the node is found to be malicious, its registration is revoked from the network. Whereas, if a node is found to be legitimate, then its data is stored in an Interplanetary File System (IPFS). IPFS stores the data in the form of chunks and generates hash for the data, which is then stored in blockchain. In addition, Verifiable Byzantine Fault Tolerance (VBFT) is used instead of Proof of Work (PoW) to perform consensus and validate transactions. Also, extensive simulations are performed using the Wireless Sensor Network (WSN) dataset, referred as WSN-DS. The proposed model is evaluated both on the original dataset and the balanced dataset. Furthermore, HGB is compared with other existing classifiers, Adaptive Boost (AdaBoost), Gradient Boost (GB), Linear Discriminant Analysis (LDA), Extreme Gradient Boost (XGB) and ridge, using different performance metrics like accuracy, precision, recall, micro-F1 score and macro-F1 score. The performance evaluation of HGB shows that it outperforms GB, AdaBoost, LDA, XGB and Ridge by 2-4%, 8-10%, 12-14%, 3-5% and 14-16%, respectively. Moreover, the results with balanced dataset are better than those with original dataset. Also, VBFT performs 20-30% better than PoW. Overall, the proposed model performs efficiently in terms of malicious node detection and secure data storage. © 2013 IEEE.
Malignant and non-malignant oral lesions classification and diagnosis with deep neural networks
- Liyanage, V.iduni, Tao, Mengqiu, Park, Joon, Wang, Kate, Azimi, Somayyeh
- Authors: Liyanage, V.iduni , Tao, Mengqiu , Park, Joon , Wang, Kate , Azimi, Somayyeh
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Dentistry Vol. 137, no. (2023), p.
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- Description: Objectives: Given the increasing incidence of oral cancer, it is essential to provide high-risk communities, especially in remote regions, with an affordable, user-friendly tool for visual lesion diagnosis. This proof-of-concept study explored the utility and feasibility of a smartphone application that can photograph and diagnose oral lesions. Methods: The images of oral lesions with confirmed diagnoses were sourced from oral and maxillofacial textbooks. In total, 342 images were extracted, encompassing lesions from various regions of the oral cavity such as the gingiva, palate, and labial mucosa. The lesions were segregated into three categories: Class 1 represented non-neoplastic lesions, Class 2 included benign neoplasms, and Class 3 contained premalignant/malignant lesions. The images were analysed using MobileNetV3 and EfficientNetV2 models, with the process producing an accuracy curve, confusion matrix, and receiver operating characteristic (ROC) curve. Results: The EfficientNetV2 model showed a steep increase in validation accuracy early in the iterations, plateauing at a score of 0.71. According to the confusion matrix, this model's testing accuracy for diagnosing non-neoplastic and premalignant/malignant lesions was 64% and 80% respectively. Conversely, the MobileNetV3 model exhibited a more gradual increase, reaching a plateau at a validation accuracy of 0.70. The MobileNetV3 model's testing accuracy for diagnosing non-neoplastic and premalignant/malignant lesions, according to the confusion matrix, was 64% and 82% respectively. Conclusions: Our proof-of-concept study effectively demonstrated the potential accuracy of AI software in distinguishing malignant lesions. This could play a vital role in remote screenings for populations with limited access to dental practitioners. However, the discrepancies between the classification of images and the results of "non-malignant lesions" calls for further refinement of the models and the classification system used. Clinical significance: The findings of this study indicate that AI software has the potential to aid in the identification or screening of malignant oral lesions. Further improvements are required to enhance accuracy in classifying non-malignant lesions. © 2023 The Author(s)
- Authors: Liyanage, V.iduni , Tao, Mengqiu , Park, Joon , Wang, Kate , Azimi, Somayyeh
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Dentistry Vol. 137, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Objectives: Given the increasing incidence of oral cancer, it is essential to provide high-risk communities, especially in remote regions, with an affordable, user-friendly tool for visual lesion diagnosis. This proof-of-concept study explored the utility and feasibility of a smartphone application that can photograph and diagnose oral lesions. Methods: The images of oral lesions with confirmed diagnoses were sourced from oral and maxillofacial textbooks. In total, 342 images were extracted, encompassing lesions from various regions of the oral cavity such as the gingiva, palate, and labial mucosa. The lesions were segregated into three categories: Class 1 represented non-neoplastic lesions, Class 2 included benign neoplasms, and Class 3 contained premalignant/malignant lesions. The images were analysed using MobileNetV3 and EfficientNetV2 models, with the process producing an accuracy curve, confusion matrix, and receiver operating characteristic (ROC) curve. Results: The EfficientNetV2 model showed a steep increase in validation accuracy early in the iterations, plateauing at a score of 0.71. According to the confusion matrix, this model's testing accuracy for diagnosing non-neoplastic and premalignant/malignant lesions was 64% and 80% respectively. Conversely, the MobileNetV3 model exhibited a more gradual increase, reaching a plateau at a validation accuracy of 0.70. The MobileNetV3 model's testing accuracy for diagnosing non-neoplastic and premalignant/malignant lesions, according to the confusion matrix, was 64% and 82% respectively. Conclusions: Our proof-of-concept study effectively demonstrated the potential accuracy of AI software in distinguishing malignant lesions. This could play a vital role in remote screenings for populations with limited access to dental practitioners. However, the discrepancies between the classification of images and the results of "non-malignant lesions" calls for further refinement of the models and the classification system used. Clinical significance: The findings of this study indicate that AI software has the potential to aid in the identification or screening of malignant oral lesions. Further improvements are required to enhance accuracy in classifying non-malignant lesions. © 2023 The Author(s)
Management using continence products : report of the 7th international consultation on incontinence
- Murphy, Cathy, Fader, Mandy, Bliss, Donna, Buckley, Brian, Cockerell, Rowan, Cottenden, Alan, Kottner, Jan, Ostaszkiewicz, Joan
- Authors: Murphy, Cathy , Fader, Mandy , Bliss, Donna , Buckley, Brian , Cockerell, Rowan , Cottenden, Alan , Kottner, Jan , Ostaszkiewicz, Joan
- Date: 2023
- Type: Text , Journal article
- Relation: Continence Vol. 8, no. (2023), p.
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- Description: Aim: To summarise the available evidence on the use of continence products to manage urinary or faecal incontinence published since the 6th International Consultation on Incontinence (2017) and provide key recommendations for the use of products in each group. Methods: A series of systematic reviews (grouped according to pre-determined topics) and evidence updates were undertaken and reported descriptively by members of an international committee to update the 6th Consultation. Results: The available evidence is presented for 13 categories of continence management products. Some categories (female mechanical urinary incontinence devices, products for preventing/treating incontinence-associated dermatitis and urinary catheters) had at least one new randomised controlled trial. Other categories had small-scale or qualitative studies, reviews or no new associated evidence. A summary of key research priorities is provided. Discussion: This paper provides a summary of the evidence available for a range of continence management products. Some product categories have a larger body of new and existing evidence than others, but there continues to be a lack of research to guide decision-making on the wide range of continence management products. Clinicians and other decision-makers remain largely dependent on expert opinion and individual user circumstances and preferences. We summarise specific areas where more. © 2023 The Authors
- Authors: Murphy, Cathy , Fader, Mandy , Bliss, Donna , Buckley, Brian , Cockerell, Rowan , Cottenden, Alan , Kottner, Jan , Ostaszkiewicz, Joan
- Date: 2023
- Type: Text , Journal article
- Relation: Continence Vol. 8, no. (2023), p.
- Full Text:
- Reviewed:
- Description: Aim: To summarise the available evidence on the use of continence products to manage urinary or faecal incontinence published since the 6th International Consultation on Incontinence (2017) and provide key recommendations for the use of products in each group. Methods: A series of systematic reviews (grouped according to pre-determined topics) and evidence updates were undertaken and reported descriptively by members of an international committee to update the 6th Consultation. Results: The available evidence is presented for 13 categories of continence management products. Some categories (female mechanical urinary incontinence devices, products for preventing/treating incontinence-associated dermatitis and urinary catheters) had at least one new randomised controlled trial. Other categories had small-scale or qualitative studies, reviews or no new associated evidence. A summary of key research priorities is provided. Discussion: This paper provides a summary of the evidence available for a range of continence management products. Some product categories have a larger body of new and existing evidence than others, but there continues to be a lack of research to guide decision-making on the wide range of continence management products. Clinicians and other decision-makers remain largely dependent on expert opinion and individual user circumstances and preferences. We summarise specific areas where more. © 2023 The Authors
Managing depression with complementary and alternative medicine therapies: a scientometric analysis and visualization of research activities
- Zhao, Fei-Yi, Xu, Peijie, Zheng, Zhen, Conduit, Russell, Xu, Yan, Yue, Li-Ping, Wang, Hui-Ru, Wang, Yan-Mei, Li, Yuan-Xin, Li, Chun-Yan, Zhang, Wen-Jing, Fu, Qiang-Qiang, Kennedy, Gerard
- Authors: Zhao, Fei-Yi , Xu, Peijie , Zheng, Zhen , Conduit, Russell , Xu, Yan , Yue, Li-Ping , Wang, Hui-Ru , Wang, Yan-Mei , Li, Yuan-Xin , Li, Chun-Yan , Zhang, Wen-Jing , Fu, Qiang-Qiang , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychiatry Vol. 14, no. (2023), p.
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- Description: Background: Complementary and Alternative Medicine (CAM) interventions may prove to be an attractive option for the treatment of depression. The aim of this scientometric analysis is to determine the global scientific output of research regarding managing depression with CAM and identify the hotspots and frontiers within this theme. Methods: Publications regarding the utilization of CAM for treating depression were collected from the Web of Science Core Collection from 1993 to 2022, and analyzed and visualized by Bibliometrix R-package, VOSviewer, and CiteSpace. Results: A total of 1,710 publications were acquired. The number of annual publications showed an overall rapid upward trend, with the figure peaking at 179 in 2021. The USA was the leading research center. Totally 2,323 distinct institutions involving 7,638 scholars contributed to the research theme. However, most of the cooperation was limited to within the same country, institution or research team. The Journal of Alternative and Complementary Medicine was the most productive periodical. The CAM therapies of most interest to researchers were acupuncture and body–mind techniques, such as yoga, meditation and mindfulness. Systematic review and meta-analysis are commonly used methods. “Inflammation,” “rating scale” and “psychological stress” were identified as the most studied trend topics recently. Conclusion: Managing depression with evidence-based CAM treatment is gaining attention globally. Body–mind techniques and acupuncture are growing research hotspots or emerging trending topics. Future studies are predicted to potentially investigate the possible mechanisms of action underlying CAM treatments in reducing depression in terms of modulation of psychological stress and inflammation levels. Cross-countries/institutes/team research collaborations should be encouraged and further enhanced. Copyright © 2023 Zhao, Xu, Zheng, Conduit, Xu, Yue, Wang, Wang, Li, Li, Zhang, Fu and Kennedy.
- Authors: Zhao, Fei-Yi , Xu, Peijie , Zheng, Zhen , Conduit, Russell , Xu, Yan , Yue, Li-Ping , Wang, Hui-Ru , Wang, Yan-Mei , Li, Yuan-Xin , Li, Chun-Yan , Zhang, Wen-Jing , Fu, Qiang-Qiang , Kennedy, Gerard
- Date: 2023
- Type: Text , Journal article
- Relation: Frontiers in Psychiatry Vol. 14, no. (2023), p.
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- Reviewed:
- Description: Background: Complementary and Alternative Medicine (CAM) interventions may prove to be an attractive option for the treatment of depression. The aim of this scientometric analysis is to determine the global scientific output of research regarding managing depression with CAM and identify the hotspots and frontiers within this theme. Methods: Publications regarding the utilization of CAM for treating depression were collected from the Web of Science Core Collection from 1993 to 2022, and analyzed and visualized by Bibliometrix R-package, VOSviewer, and CiteSpace. Results: A total of 1,710 publications were acquired. The number of annual publications showed an overall rapid upward trend, with the figure peaking at 179 in 2021. The USA was the leading research center. Totally 2,323 distinct institutions involving 7,638 scholars contributed to the research theme. However, most of the cooperation was limited to within the same country, institution or research team. The Journal of Alternative and Complementary Medicine was the most productive periodical. The CAM therapies of most interest to researchers were acupuncture and body–mind techniques, such as yoga, meditation and mindfulness. Systematic review and meta-analysis are commonly used methods. “Inflammation,” “rating scale” and “psychological stress” were identified as the most studied trend topics recently. Conclusion: Managing depression with evidence-based CAM treatment is gaining attention globally. Body–mind techniques and acupuncture are growing research hotspots or emerging trending topics. Future studies are predicted to potentially investigate the possible mechanisms of action underlying CAM treatments in reducing depression in terms of modulation of psychological stress and inflammation levels. Cross-countries/institutes/team research collaborations should be encouraged and further enhanced. Copyright © 2023 Zhao, Xu, Zheng, Conduit, Xu, Yue, Wang, Wang, Li, Li, Zhang, Fu and Kennedy.
Matching the model to the available data to predict wheat, barley, or canola yield : a review of recently published models and data
- Clark, Robert, Dahlhaus, Peter, Robinson, Nathan, Larkins, Jo-ann, Morse-McNabb, Elizabeth
- Authors: Clark, Robert , Dahlhaus, Peter , Robinson, Nathan , Larkins, Jo-ann , Morse-McNabb, Elizabeth
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Agricultural Systems Vol. 211, no. (2023), p.
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- Description: CONTEXT: Continued increases in global population and rising living standards in many countries are driving a surge in demand for energy and protein-rich foods. Wheat, barley, and canola are important crops that are grown and traded globally. However, climate change, geopolitical tensions and competition from other crops threaten the ability to satisfy global demand. Accurate predictions of crop production and its spatial variation can play a significant role in their reliable and efficient production, marketing, and distribution. OBJECTIVE: This review examined recently published models and data used to predict wheat, barley, and canola yield to identify which factors produced the best yield predictions. METHODS: A literature search was conducted across the Scopus, EBSCOhost and Web of Science databases over seven years between 2015 and 2021. Data extracted from the papers identified by the literature search were investigated using graphical and quantitative analytical techniques to determine if the type of algorithm, input data, prediction timing, output scale or extent and climate variability both in isolation and in combination affected the model's predictive ability. RESULTS AND CONCLUSIONS: The literature search produced 11, 908 results which was reduced to 118 papers after applying the review criteria (peer reviewed papers focussed on models predicting yield at greater than plot scale across extensive areas using accessible data). China produced almost one third of all yield prediction models over the study period and 87% of models were used to predict wheat yield. Statistical models were the most common algorithm in most regions and in total. However, there was a surge in machine learning models after 2018. They were the most common model from 2019 to 2021, with one third developed in China. The review concluded that only the choice of modelling technique and the input data had a significant effect on model performance with the machine learning techniques Random Forest, Boosting algorithms and Deep Learning models as well as process-based Light Use Efficiency models that used a combination of remotely sensed and agrometeorological data performing best. SIGNIFICANCE: The review showed that matching the model to the available data could improve the ability to predict wheat, barley or canola yield. The use of quantitative statistical techniques in this review, should give modellers trying to predict wheat, barley or canola yield more confidence in matching their approach to the available data than previous reviews that relied on visual interpretation of data. © 2023 The Authors
- Authors: Clark, Robert , Dahlhaus, Peter , Robinson, Nathan , Larkins, Jo-ann , Morse-McNabb, Elizabeth
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Agricultural Systems Vol. 211, no. (2023), p.
- Full Text:
- Reviewed:
- Description: CONTEXT: Continued increases in global population and rising living standards in many countries are driving a surge in demand for energy and protein-rich foods. Wheat, barley, and canola are important crops that are grown and traded globally. However, climate change, geopolitical tensions and competition from other crops threaten the ability to satisfy global demand. Accurate predictions of crop production and its spatial variation can play a significant role in their reliable and efficient production, marketing, and distribution. OBJECTIVE: This review examined recently published models and data used to predict wheat, barley, and canola yield to identify which factors produced the best yield predictions. METHODS: A literature search was conducted across the Scopus, EBSCOhost and Web of Science databases over seven years between 2015 and 2021. Data extracted from the papers identified by the literature search were investigated using graphical and quantitative analytical techniques to determine if the type of algorithm, input data, prediction timing, output scale or extent and climate variability both in isolation and in combination affected the model's predictive ability. RESULTS AND CONCLUSIONS: The literature search produced 11, 908 results which was reduced to 118 papers after applying the review criteria (peer reviewed papers focussed on models predicting yield at greater than plot scale across extensive areas using accessible data). China produced almost one third of all yield prediction models over the study period and 87% of models were used to predict wheat yield. Statistical models were the most common algorithm in most regions and in total. However, there was a surge in machine learning models after 2018. They were the most common model from 2019 to 2021, with one third developed in China. The review concluded that only the choice of modelling technique and the input data had a significant effect on model performance with the machine learning techniques Random Forest, Boosting algorithms and Deep Learning models as well as process-based Light Use Efficiency models that used a combination of remotely sensed and agrometeorological data performing best. SIGNIFICANCE: The review showed that matching the model to the available data could improve the ability to predict wheat, barley or canola yield. The use of quantitative statistical techniques in this review, should give modellers trying to predict wheat, barley or canola yield more confidence in matching their approach to the available data than previous reviews that relied on visual interpretation of data. © 2023 The Authors
Maternal attachment state of mind and perinatal emotional wellbeing : findings from a pregnancy cohort study
- Galbally, Megan, Watson, Stuart, Lewis, Andrew, Power, Josephine, Buus, Niels, van Ijzendoorn, Marinus
- Authors: Galbally, Megan , Watson, Stuart , Lewis, Andrew , Power, Josephine , Buus, Niels , van Ijzendoorn, Marinus
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Affective Disorders Vol. 333, no. (2023), p. 297-304
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- Description: Objectives: Maternal attachment state of mind is an important potential predictor of risk and resilience to perinatal emotional wellbeing and early parenting. To explore maternal attachment in relation to perinatal depression and emotional wellbeing. Methods: This study drew on data collected within an ongoing cohort from 170 women recruited in early pregnancy, including 67 who met criteria for Major Depression. Maternal attachment state of mind was assessed with the Adult Attachment Interview (AAI) in pregnancy. Additional measures included the Structured Clinical Interview for the DSM (SCID), at 12 months the Strange Situation Procedure (SSP), Child Trauma Questionnaire (CTQ), Parenting Stress Index, and antenatal maternal hair cortisol concentrations (HCC). Limitations: Sample size to be able to undertake all analyses using the 4 way classifications, cortisol measurement is limited to hair only and there is no prospectively collected measure of childhood trauma in mothers. Conclusions: This study found that maternal attachment, specifically the Non-Autonomous states of mind, adjusted for clinical depression, was associated with higher cortisol in pregnancy and higher depressive symptoms across pregnancy and the postpartum. Furthermore, separately those with depression and Non-Autonomous states of mind also had higher postpartum parenting stress. There was no significant intergenerational concordance between AAI and SSP attachment classifications. Our findings support future research exploring the role of maternal attachment state of mind in understanding perinatal depression and emotional wellbeing. © 2023 The Author(s)
- Authors: Galbally, Megan , Watson, Stuart , Lewis, Andrew , Power, Josephine , Buus, Niels , van Ijzendoorn, Marinus
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Affective Disorders Vol. 333, no. (2023), p. 297-304
- Full Text:
- Reviewed:
- Description: Objectives: Maternal attachment state of mind is an important potential predictor of risk and resilience to perinatal emotional wellbeing and early parenting. To explore maternal attachment in relation to perinatal depression and emotional wellbeing. Methods: This study drew on data collected within an ongoing cohort from 170 women recruited in early pregnancy, including 67 who met criteria for Major Depression. Maternal attachment state of mind was assessed with the Adult Attachment Interview (AAI) in pregnancy. Additional measures included the Structured Clinical Interview for the DSM (SCID), at 12 months the Strange Situation Procedure (SSP), Child Trauma Questionnaire (CTQ), Parenting Stress Index, and antenatal maternal hair cortisol concentrations (HCC). Limitations: Sample size to be able to undertake all analyses using the 4 way classifications, cortisol measurement is limited to hair only and there is no prospectively collected measure of childhood trauma in mothers. Conclusions: This study found that maternal attachment, specifically the Non-Autonomous states of mind, adjusted for clinical depression, was associated with higher cortisol in pregnancy and higher depressive symptoms across pregnancy and the postpartum. Furthermore, separately those with depression and Non-Autonomous states of mind also had higher postpartum parenting stress. There was no significant intergenerational concordance between AAI and SSP attachment classifications. Our findings support future research exploring the role of maternal attachment state of mind in understanding perinatal depression and emotional wellbeing. © 2023 The Author(s)
Maximal and submaximal intensity isometric knee extensions induce an underestimation of time estimates with both younger and older adults : a randomized crossover trial
- Graham, Andrew, Gardner, Hayley, Chaabene, Helmi, Talpey, Scott, Alizadeh, Shahab, Behm, David
- Authors: Graham, Andrew , Gardner, Hayley , Chaabene, Helmi , Talpey, Scott , Alizadeh, Shahab , Behm, David
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Sports Science and Medicine Vol. 22, no. 3 (2023), p. 405-415
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- Description: Our perception of time plays a critical role in nearly all daily activities and especially in sports. There are no studies that have investigated and compared time perception during exercise in young and older adults. Thus, this study aimed to compare the effects of exercise on time perception between younger and older adult populations. Thirty-three recreationally active participants were recruited and assigned to either the younger (university students, 9 males and 10 females) or older adults (>60 years, 8 males and 6 females). All participants completed four exercise conditions over two sessions on separate days: approximately 30-seconds of knee extensors 100%, 60% and 10% of maximum voluntary isometric contraction (MVIC), and control (no contractions). Prospective time perception was estimated (at 5-, 10-, 20-, and 30-seconds) at the beginning of each session and while performing the exercise. A main effect for condition (p < 0.001, d = 1.06) with subsequent post-hoc tests indicated participants significantly underestimated (estimated time was shorter than chronological time) time in all three exercise conditions compared to the control. There were no significant age group differences. In conclusion, exercise underestimated time estimates regardless of intensity or age. This questions the postulated intensity-dependent relationship between exercise and time perception. While older adults were expected to be less accurate in their time estimates, they may have been able to adopt alternative strategies for agerelated changes in their internal clock, resulting in no significant age group differences. © 2023, Journal of Sport Science and Medicine. All rights reserved.
- Authors: Graham, Andrew , Gardner, Hayley , Chaabene, Helmi , Talpey, Scott , Alizadeh, Shahab , Behm, David
- Date: 2023
- Type: Text , Journal article
- Relation: Journal of Sports Science and Medicine Vol. 22, no. 3 (2023), p. 405-415
- Full Text:
- Reviewed:
- Description: Our perception of time plays a critical role in nearly all daily activities and especially in sports. There are no studies that have investigated and compared time perception during exercise in young and older adults. Thus, this study aimed to compare the effects of exercise on time perception between younger and older adult populations. Thirty-three recreationally active participants were recruited and assigned to either the younger (university students, 9 males and 10 females) or older adults (>60 years, 8 males and 6 females). All participants completed four exercise conditions over two sessions on separate days: approximately 30-seconds of knee extensors 100%, 60% and 10% of maximum voluntary isometric contraction (MVIC), and control (no contractions). Prospective time perception was estimated (at 5-, 10-, 20-, and 30-seconds) at the beginning of each session and while performing the exercise. A main effect for condition (p < 0.001, d = 1.06) with subsequent post-hoc tests indicated participants significantly underestimated (estimated time was shorter than chronological time) time in all three exercise conditions compared to the control. There were no significant age group differences. In conclusion, exercise underestimated time estimates regardless of intensity or age. This questions the postulated intensity-dependent relationship between exercise and time perception. While older adults were expected to be less accurate in their time estimates, they may have been able to adopt alternative strategies for agerelated changes in their internal clock, resulting in no significant age group differences. © 2023, Journal of Sport Science and Medicine. All rights reserved.
MCSNet+ : enhanced convolutional neural network for detection and classification of tribolium and sitophilus sibling species in actual wheat storage environments
- Yang, Haiying, Li, Yanyu, Xin, Liyong, Teng, Shyh, Pang, Shaoning, Zhao, Huiyi, Cao, Yang, Zhou, Xiaoguang
- Authors: Yang, Haiying , Li, Yanyu , Xin, Liyong , Teng, Shyh , Pang, Shaoning , Zhao, Huiyi , Cao, Yang , Zhou, Xiaoguang
- Date: 2023
- Type: Text , Journal article
- Relation: Foods Vol. 12, no. 19 (2023), p.
- Full Text:
- Reviewed:
- Description: Insect pests like Tribolium and Sitophilus siblings are major threats to grain storage and processing, causing quality and quantity losses that endanger food security. These closely related species, having very similar morphological and biological characteristics, often exhibit variations in biology and pesticide resistance, complicating control efforts. Accurate pest species identification is essential for effective control, but workplace safety in the grain bin associated with grain deterioration, clumping, fumigator hazards, and air quality create challenges. Therefore, there is a pressing need for an online automated detection system. In this work, we enriched the stored-grain pest sibling image dataset, which includes 25,032 annotated Tribolium samples of two species and five geographical strains from real warehouse and another 1774 from the lab. As previously demonstrated on the Sitophilus family, Convolutional Neural Networks demonstrate distinct advantages over other model architectures in detecting Tribolium. Our CNN model, MCSNet+, integrates Soft-NMS for better recall in dense object detection, a Position-Sensitive Prediction Model to handle translation issues, and anchor parameter fine-tuning for improved matching and speed. This approach significantly enhances mean Average Precision (mAP) for Sitophilus and Tribolium, reaching a minimum of 92.67 ± 1.74% and 94.27 ± 1.02%, respectively. Moreover, MCSNet+ exhibits significant improvements in prediction speed, advancing from 0.055 s/img to 0.133 s/img, and elevates the recognition rates of moving insect sibling species in real wheat storage and visible light, rising from 2.32% to 2.53%. The detection performance of the model on laboratory-captured images surpasses that of real storage facilities, with better results for Tribolium compared to Sitophilus. Although inter-strain variances are less pronounced, the model achieves acceptable detection results across different Tribolium geographical strains, with a minimum recognition rate of 82.64 ± 1.27%. In real-time monitoring videos of grain storage facilities with wheat backgrounds, the enhanced deep learning model based on Convolutional Neural Networks successfully detects and identifies closely related stored-grain pest images. This achievement provides a viable solution for establishing an online pest management system in real storage facilities. © 2023 by the authors.
- Authors: Yang, Haiying , Li, Yanyu , Xin, Liyong , Teng, Shyh , Pang, Shaoning , Zhao, Huiyi , Cao, Yang , Zhou, Xiaoguang
- Date: 2023
- Type: Text , Journal article
- Relation: Foods Vol. 12, no. 19 (2023), p.
- Full Text:
- Reviewed:
- Description: Insect pests like Tribolium and Sitophilus siblings are major threats to grain storage and processing, causing quality and quantity losses that endanger food security. These closely related species, having very similar morphological and biological characteristics, often exhibit variations in biology and pesticide resistance, complicating control efforts. Accurate pest species identification is essential for effective control, but workplace safety in the grain bin associated with grain deterioration, clumping, fumigator hazards, and air quality create challenges. Therefore, there is a pressing need for an online automated detection system. In this work, we enriched the stored-grain pest sibling image dataset, which includes 25,032 annotated Tribolium samples of two species and five geographical strains from real warehouse and another 1774 from the lab. As previously demonstrated on the Sitophilus family, Convolutional Neural Networks demonstrate distinct advantages over other model architectures in detecting Tribolium. Our CNN model, MCSNet+, integrates Soft-NMS for better recall in dense object detection, a Position-Sensitive Prediction Model to handle translation issues, and anchor parameter fine-tuning for improved matching and speed. This approach significantly enhances mean Average Precision (mAP) for Sitophilus and Tribolium, reaching a minimum of 92.67 ± 1.74% and 94.27 ± 1.02%, respectively. Moreover, MCSNet+ exhibits significant improvements in prediction speed, advancing from 0.055 s/img to 0.133 s/img, and elevates the recognition rates of moving insect sibling species in real wheat storage and visible light, rising from 2.32% to 2.53%. The detection performance of the model on laboratory-captured images surpasses that of real storage facilities, with better results for Tribolium compared to Sitophilus. Although inter-strain variances are less pronounced, the model achieves acceptable detection results across different Tribolium geographical strains, with a minimum recognition rate of 82.64 ± 1.27%. In real-time monitoring videos of grain storage facilities with wheat backgrounds, the enhanced deep learning model based on Convolutional Neural Networks successfully detects and identifies closely related stored-grain pest images. This achievement provides a viable solution for establishing an online pest management system in real storage facilities. © 2023 by the authors.
Mental fatigue does not affect static balance under both single and dual task conditions in young adults
- Salihu, Abubakar, Usman, Jibrin, Hill, Keith, Zoghi, Maryam, Jaberzadeh, Shapour
- Authors: Salihu, Abubakar , Usman, Jibrin , Hill, Keith , Zoghi, Maryam , Jaberzadeh, Shapour
- Date: 2023
- Type: Text , Journal article
- Relation: Experimental Brain Research Vol. 241, no. 7 (2023), p. 1769-1784
- Full Text:
- Reviewed:
- Description: The ability to control balance and prevent falls while carrying out daily life activities may require a predominantly controlled (cognitive) or automatic processing depending on the balance challenge, age, or other factors. Consequently, this process may be affected by mental fatigue which has been shown to impair cognitive abilities. Controlling static balance in young adults is a relatively easy task that may proceed automatically with minimal cognitive input making it insusceptible to mental fatigue. To investigate this hypothesis, static single and dual task (while concurrently counting backward by seven) balance was assessed in 60 young adults (25.2 ± 2.4 years) before and after 45 min of Stroop task (mental fatigue condition) and watching documentary (control), presented in a randomized counterbalanced order on separate days. Moreover, because mental fatigue can occur due to task underload or overload, participants carried out two different Stroop tasks (i.e., all congruent, and mainly incongruent trials) on separate days in the mental fatigue condition. Results of the study revealed a significantly higher feeling of mental fatigue after the mental fatigue conditions compared to control (p < 0.001). Similarly, the performance on congruent Stroop trials decreases with time indicating objective mental fatigue (p < 0.01). However, there was no difference in balance or concurrent task performance under both single and dual task assessments between the three conditions (p > 0.05) indicating lack of effect of mental fatigue on static balance in this population. Therefore, future studies investigating this phenomenon in occupational or sport settings in similar population should consider using more challenging balance tasks. © 2023, The Author(s).
- Authors: Salihu, Abubakar , Usman, Jibrin , Hill, Keith , Zoghi, Maryam , Jaberzadeh, Shapour
- Date: 2023
- Type: Text , Journal article
- Relation: Experimental Brain Research Vol. 241, no. 7 (2023), p. 1769-1784
- Full Text:
- Reviewed:
- Description: The ability to control balance and prevent falls while carrying out daily life activities may require a predominantly controlled (cognitive) or automatic processing depending on the balance challenge, age, or other factors. Consequently, this process may be affected by mental fatigue which has been shown to impair cognitive abilities. Controlling static balance in young adults is a relatively easy task that may proceed automatically with minimal cognitive input making it insusceptible to mental fatigue. To investigate this hypothesis, static single and dual task (while concurrently counting backward by seven) balance was assessed in 60 young adults (25.2 ± 2.4 years) before and after 45 min of Stroop task (mental fatigue condition) and watching documentary (control), presented in a randomized counterbalanced order on separate days. Moreover, because mental fatigue can occur due to task underload or overload, participants carried out two different Stroop tasks (i.e., all congruent, and mainly incongruent trials) on separate days in the mental fatigue condition. Results of the study revealed a significantly higher feeling of mental fatigue after the mental fatigue conditions compared to control (p < 0.001). Similarly, the performance on congruent Stroop trials decreases with time indicating objective mental fatigue (p < 0.01). However, there was no difference in balance or concurrent task performance under both single and dual task assessments between the three conditions (p > 0.05) indicating lack of effect of mental fatigue on static balance in this population. Therefore, future studies investigating this phenomenon in occupational or sport settings in similar population should consider using more challenging balance tasks. © 2023, The Author(s).
Mental health nurses' attitudes towards mental illness and recovery-oriented practice in acute inpatient psychiatric units : a non-participant observation study
- Sreeram, Anju, Cross, Wendy, Townsin, Louise
- Authors: Sreeram, Anju , Cross, Wendy , Townsin, Louise
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Mental Health Nursing Vol. 32, no. 4 (2023), p. 1112-1128
- Full Text:
- Reviewed:
- Description: National mental health policies accentuate the importance of having positive attitudes, skills, and knowledge among mental health professionals to facilitate recovery-oriented practices in all areas of mental health care. However, evidence suggests that mental health professionals' negative attitudes towards mental illness are still evident and that recovery-oriented practice in acute inpatient units may be poorly implemented. At the same time, there is also a paucity of research to understand Mental Health Nurses' attitudes towards mental illness and recovery-oriented practice specifically. Therefore, this non-participant observation study aimed to explore Mental Health Nurses' attitudes towards mental illness and recovery-oriented practice in acute inpatient units by observing the interactions between the consumers and nurses. The Mental Illness Clinicians Attitudes Scale-v4 and The Recovery Attitudes Questionnaire inspired the development of a non-participant observation chart for this study and the observations were recorded on the chart. Six observations were conducted in three acute inpatient units. Observations focused on Mental Health Nurses' knowledge about mental illness, communication, dignity, respect, anxiety, fear, punishment, facilitation of real choices for consumers, physical care, cooperation with consumers' families and others and recovery orientation. Interpretive descriptive analysis was used to analyse the data. The results show that Mental Health Nurses generally have positive attitudes towards mental illness and recovery-oriented practice. Some deficits in the physical care of people with mental illness in the acute inpatient units were observed. Therefore, future research could address the adequate preparation of Mental Health Nurses to provide physical care to people with mental illnesses. © 2023 The Authors. International Journal of Mental Health Nursing published by John Wiley & Sons Australia, Ltd.
- Authors: Sreeram, Anju , Cross, Wendy , Townsin, Louise
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Mental Health Nursing Vol. 32, no. 4 (2023), p. 1112-1128
- Full Text:
- Reviewed:
- Description: National mental health policies accentuate the importance of having positive attitudes, skills, and knowledge among mental health professionals to facilitate recovery-oriented practices in all areas of mental health care. However, evidence suggests that mental health professionals' negative attitudes towards mental illness are still evident and that recovery-oriented practice in acute inpatient units may be poorly implemented. At the same time, there is also a paucity of research to understand Mental Health Nurses' attitudes towards mental illness and recovery-oriented practice specifically. Therefore, this non-participant observation study aimed to explore Mental Health Nurses' attitudes towards mental illness and recovery-oriented practice in acute inpatient units by observing the interactions between the consumers and nurses. The Mental Illness Clinicians Attitudes Scale-v4 and The Recovery Attitudes Questionnaire inspired the development of a non-participant observation chart for this study and the observations were recorded on the chart. Six observations were conducted in three acute inpatient units. Observations focused on Mental Health Nurses' knowledge about mental illness, communication, dignity, respect, anxiety, fear, punishment, facilitation of real choices for consumers, physical care, cooperation with consumers' families and others and recovery orientation. Interpretive descriptive analysis was used to analyse the data. The results show that Mental Health Nurses generally have positive attitudes towards mental illness and recovery-oriented practice. Some deficits in the physical care of people with mental illness in the acute inpatient units were observed. Therefore, future research could address the adequate preparation of Mental Health Nurses to provide physical care to people with mental illnesses. © 2023 The Authors. International Journal of Mental Health Nursing published by John Wiley & Sons Australia, Ltd.
Metabolic syndrome is associated with similar long-term prognosis in those living with and without obesity : an analysis of 45 615 patients from the nationwide LIPIDOGRAM 2004-2015 studies
- Osadnik, Kamila, Osadnik, Tadeusz, Gierlotka, Marek, Windak, Adam, Tomasik, Tomasz, Mastej, Miroslaw, Kuras, Agnieszka, Jóźwiak, Kacper, Penson, Peter, Lip, Gregory, Mikhailidis, Dimitri, Toth, Peter, Catapano, Alberico, Ray, Kausik, Howard, George, Tomaszewski, Maclej, Charchar, Fadi, Sattar, Naveed, Williams, Bryan, MacDonald, Thomas, Banach, Maclej, Jóźwiak, Jacek
- Authors: Osadnik, Kamila , Osadnik, Tadeusz , Gierlotka, Marek , Windak, Adam , Tomasik, Tomasz , Mastej, Miroslaw , Kuras, Agnieszka , Jóźwiak, Kacper , Penson, Peter , Lip, Gregory , Mikhailidis, Dimitri , Toth, Peter , Catapano, Alberico , Ray, Kausik , Howard, George , Tomaszewski, Maclej , Charchar, Fadi , Sattar, Naveed , Williams, Bryan , MacDonald, Thomas , Banach, Maclej , Jóźwiak, Jacek
- Date: 2023
- Type: Text , Journal article
- Relation: European Journal of Preventive Cardiology Vol. 30, no. 12 (2023), p. 1195-1204
- Full Text:
- Reviewed:
- Description: Aims: We aimed to evaluate the association between metabolic syndrome (MetS) and long-term all-cause mortality. Methods and results: The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006, and 2015. MetS was diagnosed based on the National Cholesterol Education Program, Adult Treatment Panel III (NCEP/ATP III), and Joint Interim Statement (JIS) criteria. The cohort was divided into four groups: non-obese patients without MetS, obese patients without MetS, non-obese patients with MetS, and obese patients with MetS. Differences in all-cause mortality were analysed using Kaplan-Meier and Cox regression analyses. A total of 45 615 participants were enrolled (mean age 56.3, standard deviation: 11.8 years; 61.7% female). MetS was diagnosed in 14 202 (31%) by NCEP/ATP III criteria and 17 216 (37.7%) by JIS criteria. Follow-up was available for 44 620 (97.8%, median duration 15.3 years) patients. MetS was associated with increased mortality risk among the obese {hazard ratio, HR: 1.88 [95% confidence interval (CI) 1.79-1.99] and HR: 1.93 [95% CI 1.82-2.04], according to NCEP/ATP III and JIS criteria, respectively} and non-obese individuals [HR: 2.11 (95% CI 1.85-2.40) and 1.7 (95% CI 1.56-1.85) according to NCEP/ATP III and JIS criteria, respectively]. Obese patients without MetS had a higher mortality risk than non-obese patients without MetS [HR: 1.16 (95% CI 1.10-1.23) and HR: 1.22 (95% CI 1.15-1.30), respectively in subgroups with NCEP/ATP III and JIS criteria applied]. Conclusions: MetS is associated with increased all-cause mortality risk in non-obese and obese patients. In patients without MetS, obesity remains significantly associated with mortality. The concept of metabolically healthy obesity should be revised. © 2023 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved.
- Authors: Osadnik, Kamila , Osadnik, Tadeusz , Gierlotka, Marek , Windak, Adam , Tomasik, Tomasz , Mastej, Miroslaw , Kuras, Agnieszka , Jóźwiak, Kacper , Penson, Peter , Lip, Gregory , Mikhailidis, Dimitri , Toth, Peter , Catapano, Alberico , Ray, Kausik , Howard, George , Tomaszewski, Maclej , Charchar, Fadi , Sattar, Naveed , Williams, Bryan , MacDonald, Thomas , Banach, Maclej , Jóźwiak, Jacek
- Date: 2023
- Type: Text , Journal article
- Relation: European Journal of Preventive Cardiology Vol. 30, no. 12 (2023), p. 1195-1204
- Full Text:
- Reviewed:
- Description: Aims: We aimed to evaluate the association between metabolic syndrome (MetS) and long-term all-cause mortality. Methods and results: The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006, and 2015. MetS was diagnosed based on the National Cholesterol Education Program, Adult Treatment Panel III (NCEP/ATP III), and Joint Interim Statement (JIS) criteria. The cohort was divided into four groups: non-obese patients without MetS, obese patients without MetS, non-obese patients with MetS, and obese patients with MetS. Differences in all-cause mortality were analysed using Kaplan-Meier and Cox regression analyses. A total of 45 615 participants were enrolled (mean age 56.3, standard deviation: 11.8 years; 61.7% female). MetS was diagnosed in 14 202 (31%) by NCEP/ATP III criteria and 17 216 (37.7%) by JIS criteria. Follow-up was available for 44 620 (97.8%, median duration 15.3 years) patients. MetS was associated with increased mortality risk among the obese {hazard ratio, HR: 1.88 [95% confidence interval (CI) 1.79-1.99] and HR: 1.93 [95% CI 1.82-2.04], according to NCEP/ATP III and JIS criteria, respectively} and non-obese individuals [HR: 2.11 (95% CI 1.85-2.40) and 1.7 (95% CI 1.56-1.85) according to NCEP/ATP III and JIS criteria, respectively]. Obese patients without MetS had a higher mortality risk than non-obese patients without MetS [HR: 1.16 (95% CI 1.10-1.23) and HR: 1.22 (95% CI 1.15-1.30), respectively in subgroups with NCEP/ATP III and JIS criteria applied]. Conclusions: MetS is associated with increased all-cause mortality risk in non-obese and obese patients. In patients without MetS, obesity remains significantly associated with mortality. The concept of metabolically healthy obesity should be revised. © 2023 The Author(s). Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved.
MICFuzzy : a maximal information content based fuzzy approach for reconstructing genetic networks
- Gamage, Hasini, Chetty, Madhu, Lim, Suryani, Hallinan, Jennifer
- Authors: Gamage, Hasini , Chetty, Madhu , Lim, Suryani , Hallinan, Jennifer
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 7 July (2023), p.
- Full Text:
- Reviewed:
- Description: In systems biology, the accurate reconstruction of Gene Regulatory Networks (GRNs) is crucial since these networks can facilitate the solving of complex biological problems. Amongst the plethora of methods available for GRN reconstruction, information theory and fuzzy concepts-based methods have abiding popularity. However, most of these methods are not only complex, incurring a high computational burden, but they may also produce a high number of false positives, leading to inaccurate inferred networks. In this paper, we propose a novel hybrid fuzzy GRN inference model called MICFuzzy which involves the aggregation of the effects of Maximal Information Coefficient (MIC). This model has an information theory-based pre-processing stage, the output of which is applied as an input to the novel fuzzy model. In this preprocessing stage, the MIC component filters relevant genes for each target gene to significantly reduce the computational burden of the fuzzy model when selecting the regulatory genes from these filtered gene lists. The novel fuzzy model uses the regulatory effect of the identified activator-repressor gene pairs to determine target gene expression levels. This approach facilitates accurate network inference by generating a high number of true regulatory interactions while significantly reducing false regulatory predictions. The performance of MICFuzzy was evaluated using DREAM3 and DREAM4 challenge data, and the SOS real gene expression dataset. MICFuzzy outperformed the other state-of-the-art methods in terms of F-score, Matthews Correlation Coefficient, Structural Accuracy, and SS_mean, and outperformed most of them in terms of efficiency. MICFuzzy also had improved efficiency compared with the classical fuzzy model since the design of MICFuzzy leads to a reduction in combinatorial computation. Copyright: © 2023 Nakulugamuwa Gamage et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Authors: Gamage, Hasini , Chetty, Madhu , Lim, Suryani , Hallinan, Jennifer
- Date: 2023
- Type: Text , Journal article
- Relation: PLoS ONE Vol. 18, no. 7 July (2023), p.
- Full Text:
- Reviewed:
- Description: In systems biology, the accurate reconstruction of Gene Regulatory Networks (GRNs) is crucial since these networks can facilitate the solving of complex biological problems. Amongst the plethora of methods available for GRN reconstruction, information theory and fuzzy concepts-based methods have abiding popularity. However, most of these methods are not only complex, incurring a high computational burden, but they may also produce a high number of false positives, leading to inaccurate inferred networks. In this paper, we propose a novel hybrid fuzzy GRN inference model called MICFuzzy which involves the aggregation of the effects of Maximal Information Coefficient (MIC). This model has an information theory-based pre-processing stage, the output of which is applied as an input to the novel fuzzy model. In this preprocessing stage, the MIC component filters relevant genes for each target gene to significantly reduce the computational burden of the fuzzy model when selecting the regulatory genes from these filtered gene lists. The novel fuzzy model uses the regulatory effect of the identified activator-repressor gene pairs to determine target gene expression levels. This approach facilitates accurate network inference by generating a high number of true regulatory interactions while significantly reducing false regulatory predictions. The performance of MICFuzzy was evaluated using DREAM3 and DREAM4 challenge data, and the SOS real gene expression dataset. MICFuzzy outperformed the other state-of-the-art methods in terms of F-score, Matthews Correlation Coefficient, Structural Accuracy, and SS_mean, and outperformed most of them in terms of efficiency. MICFuzzy also had improved efficiency compared with the classical fuzzy model since the design of MICFuzzy leads to a reduction in combinatorial computation. Copyright: © 2023 Nakulugamuwa Gamage et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Modeling cyclic crack propagation in concrete using the scaled boundary finite element method coupled with the cumulative damage-plasticity constitutive law
- Alrayes, Omar, Könke, Carsten, Ooi, Ean Tat, Hamdia, Khader
- Authors: Alrayes, Omar , Könke, Carsten , Ooi, Ean Tat , Hamdia, Khader
- Date: 2023
- Type: Text , Journal article
- Relation: Materials Vol. 16, no. 2 (2023), p.
- Full Text:
- Reviewed:
- Description: Many concrete structures, such as bridges and wind turbine towers, fail mostly due to the fatigue rapture and bending, where the cracks are initiated and propagate under cyclic loading. Modeling the fracture process zone (FPZ) is essential to understanding the cracking behavior of heterogeneous, quasi-brittle materials such as concrete under monotonic and cyclic actions. The paper aims to present a numerical modeling approach for simulating crack growth using a scaled boundary finite element model (SBFEM). The cohesive traction law is explored to model the stress field under monotonic and cyclic loading conditions. In doing so, a new constitutive law is applied within the cohesive response. The cyclic damage accumulation during loading and unloading is formulated within the thermodynamic framework of the constitutive concrete model. We consider two common problems of three-point bending of a single-edge-notched concrete beam subjected to different loading conditions to validate the developed method. The simulation results show good agreement with experimental test measurements from the literature. The presented analysis can provide a further understanding of crack growth and damage accumulation within the cohesive response, and the SBFEM makes it possible to identify the fracture behavior of cyclic crack propagation in concrete members. © 2023 by the authors.
- Authors: Alrayes, Omar , Könke, Carsten , Ooi, Ean Tat , Hamdia, Khader
- Date: 2023
- Type: Text , Journal article
- Relation: Materials Vol. 16, no. 2 (2023), p.
- Full Text:
- Reviewed:
- Description: Many concrete structures, such as bridges and wind turbine towers, fail mostly due to the fatigue rapture and bending, where the cracks are initiated and propagate under cyclic loading. Modeling the fracture process zone (FPZ) is essential to understanding the cracking behavior of heterogeneous, quasi-brittle materials such as concrete under monotonic and cyclic actions. The paper aims to present a numerical modeling approach for simulating crack growth using a scaled boundary finite element model (SBFEM). The cohesive traction law is explored to model the stress field under monotonic and cyclic loading conditions. In doing so, a new constitutive law is applied within the cohesive response. The cyclic damage accumulation during loading and unloading is formulated within the thermodynamic framework of the constitutive concrete model. We consider two common problems of three-point bending of a single-edge-notched concrete beam subjected to different loading conditions to validate the developed method. The simulation results show good agreement with experimental test measurements from the literature. The presented analysis can provide a further understanding of crack growth and damage accumulation within the cohesive response, and the SBFEM makes it possible to identify the fracture behavior of cyclic crack propagation in concrete members. © 2023 by the authors.
Modeling the effects of particle shape on damping ratio of dry sand by simple shear testing and artificial intelligence
- Baghbani, Abolfazl, Costa, Susanga, Faradonbeh, Roohoollah, Soltani, Amin, Baghbani, Hasan
- Authors: Baghbani, Abolfazl , Costa, Susanga , Faradonbeh, Roohoollah , Soltani, Amin , Baghbani, Hasan
- Date: 2023
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 13, no. 7 (2023), p.
- Full Text:
- Reviewed:
- Description: This study investigates the effects of sand particle shape, in terms of roundness, sphericity and regularity, on the damping ratio of a dry sand material. Twelve different cyclic simple shear testing scenarios were considered and applied using vertical stresses of 50, 150 and 250 kPa and cyclic stress ratios (CSR) of 0.2, 0.3, 0.4 and 0.5 in both constant- and controlled-stress modes. Each testing scenario involved five tests, using the same sand that was reconstructed from its previous cyclic test. On completion of the cyclic tests, corresponding hysteresis loops were established to determine the damping ratio. The results indicated that the minimum and maximum damping ratios for this sand material were 6.9 and 25.5, respectively. It was observed that the shape of the sand particles changed during cyclic loading, becoming progressively more rounded and spherical with an increasing number of loading cycles, thereby resulting in an increase in the damping ratio. The second part of this investigation involved the development of artificial intelligence models, namely an artificial neural network (ANN) and a support vector machine (SVM), to predict the effects of sand particle shape on the damping ratio. The proposed ANN and SVM models were found to be effective in predicting the damping ratio as a function of the particle shape descriptors (i.e., roundness, sphericity and regularity), vertical stress, CSR and number of loading cycles. Finally, a sensitivity analysis was conducted to identify the importance of the input variables; the vertical stress and regularity were, respectively, ranked as first and second in terms of importance, while the CSR was found to be the least important parameter. © 2023 by the authors.
- Authors: Baghbani, Abolfazl , Costa, Susanga , Faradonbeh, Roohoollah , Soltani, Amin , Baghbani, Hasan
- Date: 2023
- Type: Text , Journal article
- Relation: Applied Sciences (Switzerland) Vol. 13, no. 7 (2023), p.
- Full Text:
- Reviewed:
- Description: This study investigates the effects of sand particle shape, in terms of roundness, sphericity and regularity, on the damping ratio of a dry sand material. Twelve different cyclic simple shear testing scenarios were considered and applied using vertical stresses of 50, 150 and 250 kPa and cyclic stress ratios (CSR) of 0.2, 0.3, 0.4 and 0.5 in both constant- and controlled-stress modes. Each testing scenario involved five tests, using the same sand that was reconstructed from its previous cyclic test. On completion of the cyclic tests, corresponding hysteresis loops were established to determine the damping ratio. The results indicated that the minimum and maximum damping ratios for this sand material were 6.9 and 25.5, respectively. It was observed that the shape of the sand particles changed during cyclic loading, becoming progressively more rounded and spherical with an increasing number of loading cycles, thereby resulting in an increase in the damping ratio. The second part of this investigation involved the development of artificial intelligence models, namely an artificial neural network (ANN) and a support vector machine (SVM), to predict the effects of sand particle shape on the damping ratio. The proposed ANN and SVM models were found to be effective in predicting the damping ratio as a function of the particle shape descriptors (i.e., roundness, sphericity and regularity), vertical stress, CSR and number of loading cycles. Finally, a sensitivity analysis was conducted to identify the importance of the input variables; the vertical stress and regularity were, respectively, ranked as first and second in terms of importance, while the CSR was found to be the least important parameter. © 2023 by the authors.
Mothering ideology : a qualitative exploration of mothers’ perceptions of navigating motherhood pressures and partner relationships
- Williamson, Tricia, Wagstaff, Danielle, Goodwin, Jane, Smith, Naomi
- Authors: Williamson, Tricia , Wagstaff, Danielle , Goodwin, Jane , Smith, Naomi
- Date: 2023
- Type: Text , Journal article
- Relation: Sex Roles Vol. 88, no. 1-2 (2023), p. 101-117
- Full Text:
- Reviewed:
- Description: Good mother ideology refers to beliefs that women are only ‘good’ mothers if they adhere to the tenets of dominant parenting discourse, such as intensive mothering ideology, which prioritizes children’s needs and child-raising above all else. Undergirded by this ideology, mothers’ attempts to navigate the transition to motherhood are fraught with pressures, and the transition is associated with negative health outcomes for mothers and children; yet existing research gives little attention to the quality or dynamics of the partner relationship as part of this transition. The current study examined motherhood pressure and the impact on partner relationships through individual, semi-structured interviews with 19 mothers living in Australia who were 18 years or older in a heterosexual relationship with at least one child under the age of five. Thematic analysis revealed four key themes: discourses on motherhood: criticisms of mothers and internalised guilt; transformation of identity; entrenchment of gender roles through childrearing; and positive relationship dynamics: supportive fathers and challenging gender roles. This study contributes to the larger body of literature highlighting the complexity of dominant mothering ideology and its entanglement with and impact on partner relationships. Further, this study includes mothers’ perceptions of how they navigate these pressures within the relationship with their partner and the family unit. These findings have implications for programs to support mothers and other caregivers, as well as challenge unrealistic standards for motherhood. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
- Authors: Williamson, Tricia , Wagstaff, Danielle , Goodwin, Jane , Smith, Naomi
- Date: 2023
- Type: Text , Journal article
- Relation: Sex Roles Vol. 88, no. 1-2 (2023), p. 101-117
- Full Text:
- Reviewed:
- Description: Good mother ideology refers to beliefs that women are only ‘good’ mothers if they adhere to the tenets of dominant parenting discourse, such as intensive mothering ideology, which prioritizes children’s needs and child-raising above all else. Undergirded by this ideology, mothers’ attempts to navigate the transition to motherhood are fraught with pressures, and the transition is associated with negative health outcomes for mothers and children; yet existing research gives little attention to the quality or dynamics of the partner relationship as part of this transition. The current study examined motherhood pressure and the impact on partner relationships through individual, semi-structured interviews with 19 mothers living in Australia who were 18 years or older in a heterosexual relationship with at least one child under the age of five. Thematic analysis revealed four key themes: discourses on motherhood: criticisms of mothers and internalised guilt; transformation of identity; entrenchment of gender roles through childrearing; and positive relationship dynamics: supportive fathers and challenging gender roles. This study contributes to the larger body of literature highlighting the complexity of dominant mothering ideology and its entanglement with and impact on partner relationships. Further, this study includes mothers’ perceptions of how they navigate these pressures within the relationship with their partner and the family unit. These findings have implications for programs to support mothers and other caregivers, as well as challenge unrealistic standards for motherhood. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Moxonidine increases uptake of oxidised low-density lipoprotein in cultured vascular smooth muscle cells and inhibits atherosclerosis in apolipoprotein E-deficient mice
- Wang, Yutang, Nguyen, Dinh, Anesi, Jack, Alramahi, Ahmed, Witting, Paul, Chai, Zhonglin, Khan, Abdul, Kelly, Jason, Denton, Kate, Golledge, Jonathan
- Authors: Wang, Yutang , Nguyen, Dinh , Anesi, Jack , Alramahi, Ahmed , Witting, Paul , Chai, Zhonglin , Khan, Abdul , Kelly, Jason , Denton, Kate , Golledge, Jonathan
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Molecular Sciences Vol. 24, no. 4 (2023), p.
- Relation: https://purl.org/au-research/grants/nhmrc/1062671
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- Description: This study aimed to investigate the effect of the sympatholytic drug moxonidine on atherosclerosis. The effects of moxonidine on oxidised low-density lipoprotein (LDL) uptake, inflammatory gene expression and cellular migration were investigated in vitro in cultured vascular smooth muscle cells (VSMCs). The effect of moxonidine on atherosclerosis was measured by examining aortic arch Sudan IV staining and quantifying the intima-to-media ratio of the left common carotid artery in apolipoprotein E-deficient (ApoE
- Authors: Wang, Yutang , Nguyen, Dinh , Anesi, Jack , Alramahi, Ahmed , Witting, Paul , Chai, Zhonglin , Khan, Abdul , Kelly, Jason , Denton, Kate , Golledge, Jonathan
- Date: 2023
- Type: Text , Journal article
- Relation: International Journal of Molecular Sciences Vol. 24, no. 4 (2023), p.
- Relation: https://purl.org/au-research/grants/nhmrc/1062671
- Full Text:
- Reviewed:
- Description: This study aimed to investigate the effect of the sympatholytic drug moxonidine on atherosclerosis. The effects of moxonidine on oxidised low-density lipoprotein (LDL) uptake, inflammatory gene expression and cellular migration were investigated in vitro in cultured vascular smooth muscle cells (VSMCs). The effect of moxonidine on atherosclerosis was measured by examining aortic arch Sudan IV staining and quantifying the intima-to-media ratio of the left common carotid artery in apolipoprotein E-deficient (ApoE
MSCET : a multi-scenario offloading schedule for biomedical data processing and analysis in cloud-edge-terminal collaborative vehicular networks
- Ni, Zhichen, Chen, Honglong, Li, Zhe, Wang, Xiaomeng, Yan, Na, Liu, Weifeng, Xia, Feng
- Authors: Ni, Zhichen , Chen, Honglong , Li, Zhe , Wang, Xiaomeng , Yan, Na , Liu, Weifeng , Xia, Feng
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 20, no. 4 (2023), p. 2376-2386
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- Description: With the rapid development of Artificial Intelligence (AI) and Internet of Things (IoTs), an increasing number of computation intensive or delay sensitive biomedical data processing and analysis tasks are produced in vehicles, bringing more and more challenges to the biometric monitoring of drivers. Edge computing is a new paradigm to solve these challenges by offloading tasks from the resource-limited vehicles to Edge Servers (ESs) in Road Side Units (RSUs). However, most of the traditional offloading schedules for vehicular networks concentrate on the edge, while some tasks may be too complex for ESs to process. To this end, we consider a collaborative vehicular network in which the cloud, edge and terminal can cooperate with each other to accomplish the tasks. The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge. We further construct the virtual resource pool which can integrate the resource of multiple ESs since some regions may be covered by multiple RSUs. In this paper, we propose a Multi-Scenario offloading schedule for biomedical data processing and analysis in Cloud-Edge-Terminal collaborative vehicular networks called MSCET. The parameters of the proposed MSCET are optimized to maximize the system utility. We also conduct extensive simulations to evaluate the proposed MSCET and the results illustrate that MSCET outperforms other existing schedules. © 2004-2012 IEEE.
- Authors: Ni, Zhichen , Chen, Honglong , Li, Zhe , Wang, Xiaomeng , Yan, Na , Liu, Weifeng , Xia, Feng
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 20, no. 4 (2023), p. 2376-2386
- Full Text:
- Reviewed:
- Description: With the rapid development of Artificial Intelligence (AI) and Internet of Things (IoTs), an increasing number of computation intensive or delay sensitive biomedical data processing and analysis tasks are produced in vehicles, bringing more and more challenges to the biometric monitoring of drivers. Edge computing is a new paradigm to solve these challenges by offloading tasks from the resource-limited vehicles to Edge Servers (ESs) in Road Side Units (RSUs). However, most of the traditional offloading schedules for vehicular networks concentrate on the edge, while some tasks may be too complex for ESs to process. To this end, we consider a collaborative vehicular network in which the cloud, edge and terminal can cooperate with each other to accomplish the tasks. The vehicles can offload the computation intensive tasks to the cloud to save the resource of edge. We further construct the virtual resource pool which can integrate the resource of multiple ESs since some regions may be covered by multiple RSUs. In this paper, we propose a Multi-Scenario offloading schedule for biomedical data processing and analysis in Cloud-Edge-Terminal collaborative vehicular networks called MSCET. The parameters of the proposed MSCET are optimized to maximize the system utility. We also conduct extensive simulations to evaluate the proposed MSCET and the results illustrate that MSCET outperforms other existing schedules. © 2004-2012 IEEE.
Multi-aspect annotation and analysis of Nepali tweets on anti-establishment election discourse
- Rauniyar, Kritesh, Poudel, Sweta, Shiwakoti, Shuvam, Thapa, Surendrabikram, Rashid, Junaid, Kim, Jungeun, Imran, Muhammad, Naseem, Usman
- Authors: Rauniyar, Kritesh , Poudel, Sweta , Shiwakoti, Shuvam , Thapa, Surendrabikram , Rashid, Junaid , Kim, Jungeun , Imran, Muhammad , Naseem, Usman
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 143092-143115
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- Description: In today's social media-dominated landscape, digital platforms wield substantial influence over public opinion, particularly during crucial political events such as electoral processes. These platforms become hubs for diverse discussions, encompassing topics, reforms, and desired changes. Notably, in times of government dissatisfaction, they serve as arenas for anti-establishment discourse, highlighting the need to analyze public sentiment in these conversations. However, the analysis of such discourse is notably scarce, even in high-resource languages, and entirely non-existent in the context of the Nepali language. To address this critical gap, we present Nepal Anti Establishment discourse Tweets (NAET), a novel dataset comprising 4,445 multi-aspect annotated Nepali tweets, facilitating a comprehensive understanding of political conversations. Our contributions encompass evaluating tweet relevance, sentiment, and satire, while also exploring the presence of hate speech, identifying its targets, and distinguishing directed and non-directed expressions. Additionally, we investigate hope speech, an underexplored aspect crucial in the context of anti-establishment discourse, as it reflects the aspirations and expectations from new political figures and parties. Furthermore, we set NLP-based baselines for all these tasks. To ensure a holistic analysis, we also employ topic modeling, a powerful technique that helps us identify and understand the prevalent themes and patterns emerging from the discourse. Our research thus presents a comprehensive and multi-faceted perspective on anti-establishment election discourse in a low-resource language setting. The dataset is publicly available, facilitating in-depth analysis of political tweets in Nepali discourse and further advancing NLP research for the Nepali language through labeled data and baselines for various NLP tasks. The dataset for this work is made available at https://github.com/rkritesh210/NAET. © 2013 IEEE.
- Authors: Rauniyar, Kritesh , Poudel, Sweta , Shiwakoti, Shuvam , Thapa, Surendrabikram , Rashid, Junaid , Kim, Jungeun , Imran, Muhammad , Naseem, Usman
- Date: 2023
- Type: Text , Journal article
- Relation: IEEE Access Vol. 11, no. (2023), p. 143092-143115
- Full Text:
- Reviewed:
- Description: In today's social media-dominated landscape, digital platforms wield substantial influence over public opinion, particularly during crucial political events such as electoral processes. These platforms become hubs for diverse discussions, encompassing topics, reforms, and desired changes. Notably, in times of government dissatisfaction, they serve as arenas for anti-establishment discourse, highlighting the need to analyze public sentiment in these conversations. However, the analysis of such discourse is notably scarce, even in high-resource languages, and entirely non-existent in the context of the Nepali language. To address this critical gap, we present Nepal Anti Establishment discourse Tweets (NAET), a novel dataset comprising 4,445 multi-aspect annotated Nepali tweets, facilitating a comprehensive understanding of political conversations. Our contributions encompass evaluating tweet relevance, sentiment, and satire, while also exploring the presence of hate speech, identifying its targets, and distinguishing directed and non-directed expressions. Additionally, we investigate hope speech, an underexplored aspect crucial in the context of anti-establishment discourse, as it reflects the aspirations and expectations from new political figures and parties. Furthermore, we set NLP-based baselines for all these tasks. To ensure a holistic analysis, we also employ topic modeling, a powerful technique that helps us identify and understand the prevalent themes and patterns emerging from the discourse. Our research thus presents a comprehensive and multi-faceted perspective on anti-establishment election discourse in a low-resource language setting. The dataset is publicly available, facilitating in-depth analysis of political tweets in Nepali discourse and further advancing NLP research for the Nepali language through labeled data and baselines for various NLP tasks. The dataset for this work is made available at https://github.com/rkritesh210/NAET. © 2013 IEEE.
Multi-dataset hyper-cnn for hyperspectral image segmentation of remote sensing images
- Liu, Li, Awwad, Emad, Ali, Yasser, Al-Razgan, Muna, Maarouf, Ali, Abualigah, Laith, Hoshyar, Azadeh
- Authors: Liu, Li , Awwad, Emad , Ali, Yasser , Al-Razgan, Muna , Maarouf, Ali , Abualigah, Laith , Hoshyar, Azadeh
- Date: 2023
- Type: Text , Journal article
- Relation: Processes Vol. 11, no. 2 (2023), p.
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- Description: This research paper presents novel condensed CNN architecture for the recognition of multispectral images, which has been developed to address the lack of attention paid to neural network designs for multispectral and hyperspectral photography in comparison to RGB photographs. The proposed architecture is able to recognize 10-band multispectral images and has fewer parameters than popular deep designs, such as ResNet and DenseNet, thanks to recent advancements in more efficient smaller CNNs. The proposed architecture is trained from scratch, and it outperforms a comparable network that was trained on RGB images in terms of accuracy and efficiency. The study also demonstrates the use of a Bayesian variant of CNN architecture to show that a network able to process multispectral information greatly reduces the uncertainty associated with class predictions in comparison to standard RGB images. The results of the study are demonstrated by comparing the accuracy of the network’s predictions to the images. © 2023 by the authors.
- Authors: Liu, Li , Awwad, Emad , Ali, Yasser , Al-Razgan, Muna , Maarouf, Ali , Abualigah, Laith , Hoshyar, Azadeh
- Date: 2023
- Type: Text , Journal article
- Relation: Processes Vol. 11, no. 2 (2023), p.
- Full Text:
- Reviewed:
- Description: This research paper presents novel condensed CNN architecture for the recognition of multispectral images, which has been developed to address the lack of attention paid to neural network designs for multispectral and hyperspectral photography in comparison to RGB photographs. The proposed architecture is able to recognize 10-band multispectral images and has fewer parameters than popular deep designs, such as ResNet and DenseNet, thanks to recent advancements in more efficient smaller CNNs. The proposed architecture is trained from scratch, and it outperforms a comparable network that was trained on RGB images in terms of accuracy and efficiency. The study also demonstrates the use of a Bayesian variant of CNN architecture to show that a network able to process multispectral information greatly reduces the uncertainty associated with class predictions in comparison to standard RGB images. The results of the study are demonstrated by comparing the accuracy of the network’s predictions to the images. © 2023 by the authors.