Expression of TIMPs and MMPs in ovarian tumors, ascites, ascites-derived cells, and cancer cell lines : characteristic modulatory response before and after chemotherapy treatment
- Escalona, Ruth, Kannourakis, George, Findlay, Jock, Ahmed, Nuzhat
- Authors: Escalona, Ruth , Kannourakis, George , Findlay, Jock , Ahmed, Nuzhat
- Date: 2022
- Type: Text , Journal article
- Relation: Frontiers in Oncology Vol. 11, no. (2022), p.
- Full Text:
- Reviewed:
- Description: Background: The tissue inhibitors of metalloproteinase (TIMPs) and their associated metalloproteinase (MMPs) are essential regulators of tissue homeostasis and are essential for cancer progression. This study analyzed the expression of TIMP-1,-2,-3 and the associated MMPs (MMP-2,-9,-11,-14) in different Stages, Grades and World Health Organization (WHO) classifications of serous ovarian tumors, ascites, ascites-derived cells from chemo-naïve (CN) and relapsed (CR) patients, and in ovarian cancer cell lines. The status of TIMPs and associated MMPs in response to chemotherapy treatment was assessed in cancer cell lines; TCGA data was interrogated to gauge TIMPs and associated MMPs as prognostic and platinum-response indicators. Methods: The levels of TIMP-1, -2 and -3 were assessed by immunohistochemistry. The mRNA expression of TIMPs and MMPs was quantified by real time PCR (qRT-PCR). The chemosensitivity (IC50 values) to Cisplatin or Paclitaxel in cell lines was evaluated by MTT assay. The levels of TIMPs in ascites and cell lysates were analyzed by an ELISA assay. Results: The expression of TIMP-2 was significantly upregulated in Type 2 compared to Type 1 tumors and normal/benign ovarian tissues. TIMP-3 expression was significantly enhanced in Stage III, Grade 3 and Type 2 tumors compared to normal/benign ovarian tissues. The mRNA expression of MMP-9,-11 and -14 was significantly upregulated in Stage IV compared to normal/benign ovarian tissues. The expression of TIMP-1 was highest, followed by TIMP-2 and then TIMP-3 in CN ascites. At the cellular level, TIMP-2 mRNA expression was significantly higher in CN compared to CR epithelial cells in patients. The expression of TIMP-1 and -2, MMPs and cancer stem cells (CSCs) were upregulated in response to chemotherapy treatments in cancer cell lines. Interrogation of the TCGA dataset suggests shifts in platinum responses in patients consistent with genetic alterations in TIMP-2, -3 and MMP-2, -11 genes in tumors; and decreased overall survival (OS) and progression-free survival (PFS) in patients with altered MMP-14 genes. Conclusions: TIMPs and related MMPs are differentially expressed in serous ovarian tumors, ascites, ascites-derived cells and ovarian cancer cell lines. Chemotherapy treatment modulates expression of TIMPs and MMPs in association with increased expression of genes related to cancer stem cells. Copyright © 2022 Escalona, Kannourakis, Findlay and Ahmed.
- Authors: Escalona, Ruth , Kannourakis, George , Findlay, Jock , Ahmed, Nuzhat
- Date: 2022
- Type: Text , Journal article
- Relation: Frontiers in Oncology Vol. 11, no. (2022), p.
- Full Text:
- Reviewed:
- Description: Background: The tissue inhibitors of metalloproteinase (TIMPs) and their associated metalloproteinase (MMPs) are essential regulators of tissue homeostasis and are essential for cancer progression. This study analyzed the expression of TIMP-1,-2,-3 and the associated MMPs (MMP-2,-9,-11,-14) in different Stages, Grades and World Health Organization (WHO) classifications of serous ovarian tumors, ascites, ascites-derived cells from chemo-naïve (CN) and relapsed (CR) patients, and in ovarian cancer cell lines. The status of TIMPs and associated MMPs in response to chemotherapy treatment was assessed in cancer cell lines; TCGA data was interrogated to gauge TIMPs and associated MMPs as prognostic and platinum-response indicators. Methods: The levels of TIMP-1, -2 and -3 were assessed by immunohistochemistry. The mRNA expression of TIMPs and MMPs was quantified by real time PCR (qRT-PCR). The chemosensitivity (IC50 values) to Cisplatin or Paclitaxel in cell lines was evaluated by MTT assay. The levels of TIMPs in ascites and cell lysates were analyzed by an ELISA assay. Results: The expression of TIMP-2 was significantly upregulated in Type 2 compared to Type 1 tumors and normal/benign ovarian tissues. TIMP-3 expression was significantly enhanced in Stage III, Grade 3 and Type 2 tumors compared to normal/benign ovarian tissues. The mRNA expression of MMP-9,-11 and -14 was significantly upregulated in Stage IV compared to normal/benign ovarian tissues. The expression of TIMP-1 was highest, followed by TIMP-2 and then TIMP-3 in CN ascites. At the cellular level, TIMP-2 mRNA expression was significantly higher in CN compared to CR epithelial cells in patients. The expression of TIMP-1 and -2, MMPs and cancer stem cells (CSCs) were upregulated in response to chemotherapy treatments in cancer cell lines. Interrogation of the TCGA dataset suggests shifts in platinum responses in patients consistent with genetic alterations in TIMP-2, -3 and MMP-2, -11 genes in tumors; and decreased overall survival (OS) and progression-free survival (PFS) in patients with altered MMP-14 genes. Conclusions: TIMPs and related MMPs are differentially expressed in serous ovarian tumors, ascites, ascites-derived cells and ovarian cancer cell lines. Chemotherapy treatment modulates expression of TIMPs and MMPs in association with increased expression of genes related to cancer stem cells. Copyright © 2022 Escalona, Kannourakis, Findlay and Ahmed.
Extracting built-up areas from spectro-textural information using machine learning
- Maqsoom, Ahsen, Aslam, Bilal, Yousafzai, Arbaz, Ullah, Fahim, Ullah, Sami, Imran, Muhammad
- Authors: Maqsoom, Ahsen , Aslam, Bilal , Yousafzai, Arbaz , Ullah, Fahim , Ullah, Sami , Imran, Muhammad
- Date: 2022
- Type: Text , Journal article
- Relation: Soft Computing Vol. 26, no. 16 (2022), p. 7789-7808
- Full Text: false
- Reviewed:
- Description: Extraction of built-up area (BUA) is essential for proper city planning and management. It enables the concerned authorities to formulate better city development policies and manage emergent disasters. However, the traditionally used optical data present spectral confusion where BUAs are mixed with other features adding to management complexities. Therefore, an advanced automated method is required to extract the spectral and textural features from satellite data for the pattern recognition of BUA. Landsat-8 Operational Land Imager (OLI) has been used in the current study to identify the pattern and extract BUA of Gujranwala, Pakistan. First, eight textural features based on the gray-level co-occurrence matrix (GLCM) are selected and combined with multispectral data. Then, feature selection methods are applied to select optimal features used to train the proposed support vector machine (SVM) classifier. Finally, the results from SVM classifiers are compared with k-nearest neighbor (k-NN) and backpropagation neural network (BP-NN) to highlight any improvements in results. The comparisons show that the proposed approach increases the overall accuracy of linear-SVM by 8.41%, radial basis function SVM by 8.3%, BP-NN by 7.63%, and k-NN by 6.6%. This can help city managers and planners to extract critical BUA information in otherwise unplanned and rapidly expanding cities to move toward smart and sustainable cities. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
- Gomez, Rapson, Stavropoulos, Vasileios, Brown, Taylor, Griffiths, Mark
- Authors: Gomez, Rapson , Stavropoulos, Vasileios , Brown, Taylor , Griffiths, Mark
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Psychiatry Research Vol. 313, no. (2022), p.
- Full Text: false
- Reviewed:
- Description: Over the past two decades, many problematic/excessive behaviours have increasingly been conceptualized as addictions due to their similarity with more traditional psychoactive substance addictions. The primary aim of the present study was to simultaneously examine the factor structure of three psychoactive substance addictions (alcohol use, cigarette smoking, and substance use) and seven behavioural addictions (sex, social media use, shopping, exercise, online gambling, internet gaming, and internet use), using exploratory factor analysis (EFA; N = 481) and confirmatory factor analysis (CFA; N = 487). A total of 968 participants completed an online survey including ten psychometric scales assessing the ten different potentially addictive behaviours. EFA supported a two-factor solution, with different factors for the psychoactive substance and behavioural addictions (excluding exercise addiction). CFA supported the two-factor model in a separate sample. There was good support for the concurrent and discriminant validities of the CFA latent factors and the reliability of the behavioural latent factor in the two-factor CFA model. While there was support for the concurrent and discriminant validities of the psychoactive substance latent factor, there was insufficient support for its reliability. The taxonomic, theoretical, and clinical implications of the findings are discussed. © 2022
Factors influencing the transition and retention of mental health nurses during the initial years of practice : scoping review
- Joseph, Bindu, Jacob, Sini, Lam, Louisa, Rahman, Muhammad Aziz
- Authors: Joseph, Bindu , Jacob, Sini , Lam, Louisa , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Journal of Nursing Management Vol. 30, no. 8 (2022), p. 4274-4284
- Full Text:
- Reviewed:
- Description: Aim: This review aims to identify the factors influencing the transition and retention of mental health nurses during the initial years of practice, recognize gaps in the literature and propose evidence-based strategies. Background: Mental health is a challenging specialty; recruitment, transition and retention of mental health nurses are known issues of concern. Evaluation: The present study undertakes a scoping review to identify factors influencing the transition and retention of mental health nurses during the initial years of practice and the gaps in that research domain. A literature search was conducted using electronic databases. To gain an understanding of the topic of interest, the review of the literature extended from 2000 to 2022. Key issues: Existing evidence focuses on specific perspectives of transition. There is limited literature on factors influencing transition and retention among mental health nurses. Findings suggested that personal and professional factors could influence the transition and retention of mental health nurses during the initial years of practice. The main themes identified were personal attributes and professional factors with a number of subthemes. Conclusion: The scoping review identified only a few studies, which showed personal and professional factors related to the transition and retention of mental health nurses at the early stages of their career. Implications for nursing management: Potential benefits of effective transition and support with the understanding of factors influencing transition and retention of early career mental health nurses will enhance staff morale, sustainability of the workforce and better patient outcomes. Additionally, a few recommendations for nurse managers and leaders to improve transitional experiences and retention of early career nurses are highlighted. © 2022 The Authors. Journal of Nursing Management published by John Wiley & Sons Ltd.
- Authors: Joseph, Bindu , Jacob, Sini , Lam, Louisa , Rahman, Muhammad Aziz
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Journal of Nursing Management Vol. 30, no. 8 (2022), p. 4274-4284
- Full Text:
- Reviewed:
- Description: Aim: This review aims to identify the factors influencing the transition and retention of mental health nurses during the initial years of practice, recognize gaps in the literature and propose evidence-based strategies. Background: Mental health is a challenging specialty; recruitment, transition and retention of mental health nurses are known issues of concern. Evaluation: The present study undertakes a scoping review to identify factors influencing the transition and retention of mental health nurses during the initial years of practice and the gaps in that research domain. A literature search was conducted using electronic databases. To gain an understanding of the topic of interest, the review of the literature extended from 2000 to 2022. Key issues: Existing evidence focuses on specific perspectives of transition. There is limited literature on factors influencing transition and retention among mental health nurses. Findings suggested that personal and professional factors could influence the transition and retention of mental health nurses during the initial years of practice. The main themes identified were personal attributes and professional factors with a number of subthemes. Conclusion: The scoping review identified only a few studies, which showed personal and professional factors related to the transition and retention of mental health nurses at the early stages of their career. Implications for nursing management: Potential benefits of effective transition and support with the understanding of factors influencing transition and retention of early career mental health nurses will enhance staff morale, sustainability of the workforce and better patient outcomes. Additionally, a few recommendations for nurse managers and leaders to improve transitional experiences and retention of early career nurses are highlighted. © 2022 The Authors. Journal of Nursing Management published by John Wiley & Sons Ltd.
False data injection attack detection in smart grid
- Authors: Rashed, Muhammad
- Date: 2022
- Type: Text , Thesis , PhD
- Full Text:
- Description: Smart grid is a distributed and autonomous energy delivery infrastructure that constantly monitors the operational state of its overall network using smart techniques and state estimation. State estimation is a powerful technique that is used to determine the overall operational state of the system based on a limited set of measurements collected through metering systems. Cyber-attacks pose serious risks to a smart grid state estimation that can cause disruptions and power outages resulting in huge economical losses and are therefore a big concern to a reliable national grid operation. False data injection attacks (FDIAs), engineered on the basis of the knowledge of the network configuration, are difficult to detect using the traditional data detection mechanisms. These detection schemes have been found vulnerable and failed to detect these FDIAs. FDIAs specifically target the state data and can manipulate the state measurements in such a way that these false measurements appear real to the main control systems. This research work explores the possibility of FDIA detection using state estimation in a distributed and partitioned smart grid. In order to detect FDIAs we use measurements for residual-based testing which creates an objective function; and the probability of erroneous data is determined from this residual test. In this test, a preset threshold is determined based on the prior history of the state data. FDIA cases are simulated within a smart grid considering that the Chi-square detection state estimator fails in identifying such attacks. We compute the objective function using the standard weighted least problem and then test the objective function against the value in the Chi-square table. The gain matrix and the Jacobian matrix are computed. The state variables are computed in the form of a voltage magnitude. The state variables are computed after the inception of an attack to assess these state magnitude results. Different sizes of partitioning are used to improve the overall sensitivity of the Chi-square results. Our additional estimator is based on a Kalman estimation that consists of the state prediction and state correction steps. In the first step, it obtains the state and matrix covariance prediction, and in the second step, it calculates the Kalman gain and the state and matrix covariance update steps. The set of points is created for the state vector x at a time instant t. The initial vector and covariance matrix are based on a priori knowledge of the historical estimates. A set of sigma points is estimated by the state update function. Sigma points refer to the minimal set of sampling points that are selected and transformed using nonlinear function, and the new mean and the covariance are formed out of these transformed points. The idea behind this is that it is easier to compute a Gaussian distribution than an arbitrary nonlinear function. The filter gain, the mean and the covariance are used to estimate the next state. Our simulation results show that the combination of Kalman estimation and distributed state estimation improves the overall stability index and vulnerability assessment score of the smart grid. We built a stability index table for a smart grid based on the state estimates value after the inception of an FDIA. The vulnerability assessment score of the smart grid is based on common vulnerability scoring system (CVSS) and state estimates under the influence of an FDIA. The simulations are conducted in the MATPOWER program and different electrical bus systems such as IEEE 14, 30, 39, 118 and 300 are tested. All the contributions have been published in reputable journals and conferences.
- Description: Doctor of Philosophy
- Authors: Rashed, Muhammad
- Date: 2022
- Type: Text , Thesis , PhD
- Full Text:
- Description: Smart grid is a distributed and autonomous energy delivery infrastructure that constantly monitors the operational state of its overall network using smart techniques and state estimation. State estimation is a powerful technique that is used to determine the overall operational state of the system based on a limited set of measurements collected through metering systems. Cyber-attacks pose serious risks to a smart grid state estimation that can cause disruptions and power outages resulting in huge economical losses and are therefore a big concern to a reliable national grid operation. False data injection attacks (FDIAs), engineered on the basis of the knowledge of the network configuration, are difficult to detect using the traditional data detection mechanisms. These detection schemes have been found vulnerable and failed to detect these FDIAs. FDIAs specifically target the state data and can manipulate the state measurements in such a way that these false measurements appear real to the main control systems. This research work explores the possibility of FDIA detection using state estimation in a distributed and partitioned smart grid. In order to detect FDIAs we use measurements for residual-based testing which creates an objective function; and the probability of erroneous data is determined from this residual test. In this test, a preset threshold is determined based on the prior history of the state data. FDIA cases are simulated within a smart grid considering that the Chi-square detection state estimator fails in identifying such attacks. We compute the objective function using the standard weighted least problem and then test the objective function against the value in the Chi-square table. The gain matrix and the Jacobian matrix are computed. The state variables are computed in the form of a voltage magnitude. The state variables are computed after the inception of an attack to assess these state magnitude results. Different sizes of partitioning are used to improve the overall sensitivity of the Chi-square results. Our additional estimator is based on a Kalman estimation that consists of the state prediction and state correction steps. In the first step, it obtains the state and matrix covariance prediction, and in the second step, it calculates the Kalman gain and the state and matrix covariance update steps. The set of points is created for the state vector x at a time instant t. The initial vector and covariance matrix are based on a priori knowledge of the historical estimates. A set of sigma points is estimated by the state update function. Sigma points refer to the minimal set of sampling points that are selected and transformed using nonlinear function, and the new mean and the covariance are formed out of these transformed points. The idea behind this is that it is easier to compute a Gaussian distribution than an arbitrary nonlinear function. The filter gain, the mean and the covariance are used to estimate the next state. Our simulation results show that the combination of Kalman estimation and distributed state estimation improves the overall stability index and vulnerability assessment score of the smart grid. We built a stability index table for a smart grid based on the state estimates value after the inception of an FDIA. The vulnerability assessment score of the smart grid is based on common vulnerability scoring system (CVSS) and state estimates under the influence of an FDIA. The simulations are conducted in the MATPOWER program and different electrical bus systems such as IEEE 14, 30, 39, 118 and 300 are tested. All the contributions have been published in reputable journals and conferences.
- Description: Doctor of Philosophy
Family tourism : a New Zealand COVID-19 perspective
- Yeoman, Ian, Schänzel, Heike, Zentveld, Elisa
- Authors: Yeoman, Ian , Schänzel, Heike , Zentveld, Elisa
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Tourism Futures Vol. 8, no. 2 (2022), p. 240-244
- Full Text:
- Reviewed:
- Description: Purpose: Because of COVID-19, tourist behaviour has changed with a range of trends becoming more prominent. This paper sets out to explain the dominance of family tourism in New Zealand's domestic markets and the trends associated with it. Design/methodology/approach: This paper is based upon secondary data from academic literature, industry reports, news media and webinars associated with New Zealand during COVID-19, starting in March 2020. Findings: The paper explains the rise of family tourism in New Zealand during COVID-19 based upon the consumer behaviour trends of: (1) Simplicity: In search of slow; (2) Mercurial consumption; (3) Localism; (4) Staycation; (5) Healthy habits; and (6) Is it safe to come out? Originality/value: The usefulness of this paper is derived from explaining why the rise of family tourism occurred based upon the identified trends. © 2022, Ian Seymour Yeoman, Heike A. Schänzel and Elisa Zentveld.
- Authors: Yeoman, Ian , Schänzel, Heike , Zentveld, Elisa
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Tourism Futures Vol. 8, no. 2 (2022), p. 240-244
- Full Text:
- Reviewed:
- Description: Purpose: Because of COVID-19, tourist behaviour has changed with a range of trends becoming more prominent. This paper sets out to explain the dominance of family tourism in New Zealand's domestic markets and the trends associated with it. Design/methodology/approach: This paper is based upon secondary data from academic literature, industry reports, news media and webinars associated with New Zealand during COVID-19, starting in March 2020. Findings: The paper explains the rise of family tourism in New Zealand during COVID-19 based upon the consumer behaviour trends of: (1) Simplicity: In search of slow; (2) Mercurial consumption; (3) Localism; (4) Staycation; (5) Healthy habits; and (6) Is it safe to come out? Originality/value: The usefulness of this paper is derived from explaining why the rise of family tourism occurred based upon the identified trends. © 2022, Ian Seymour Yeoman, Heike A. Schänzel and Elisa Zentveld.
Fasting status modifies the association between triglyceride and all-cause mortality : a cohort study
- Authors: Fang, Yan , Wang, Yutang
- Date: 2022
- Type: Text , Journal article
- Relation: Health Science Reports Vol. 5, no. 3 (2022), p.
- Full Text:
- Reviewed:
- Description: Background and Aims: Both fasting and non-fasting levels of triglyceride have been shown positively associated with all-cause mortality. It is unknown whether fasting status modifies this association. This study aimed to address this question. Methods: This study included 34,512 US adults (27,036 fasting and 7476 nonfasting participants). All-cause mortality was ascertained by linkage to the National Death Index records. Cox proportional hazards models were used to estimate hazard ratios of triglyceride for mortality. Results: This cohort was followed up for a mean of 13.0 years. During the follow-up, 8491 all-cause deaths were recorded. A 1-natural-log-unit increase in triglyceride was associated with an 8% higher multivariate-adjusted risk of all-cause mortality. Interaction analyses showed that fasting status interacted with triglyceride in predicting all-cause mortality. Sub-analyses showed that a 1-natural-log-unit increase in triglyceride was associated with a 17% higher multivariate-adjusted risk of all-cause mortality in the nonfasting subcohort; however, there lacked such an association in the fasting sub-cohort. Similarly, high (200–499 mg/dL) and very high levels of triglyceride (
- Authors: Fang, Yan , Wang, Yutang
- Date: 2022
- Type: Text , Journal article
- Relation: Health Science Reports Vol. 5, no. 3 (2022), p.
- Full Text:
- Reviewed:
- Description: Background and Aims: Both fasting and non-fasting levels of triglyceride have been shown positively associated with all-cause mortality. It is unknown whether fasting status modifies this association. This study aimed to address this question. Methods: This study included 34,512 US adults (27,036 fasting and 7476 nonfasting participants). All-cause mortality was ascertained by linkage to the National Death Index records. Cox proportional hazards models were used to estimate hazard ratios of triglyceride for mortality. Results: This cohort was followed up for a mean of 13.0 years. During the follow-up, 8491 all-cause deaths were recorded. A 1-natural-log-unit increase in triglyceride was associated with an 8% higher multivariate-adjusted risk of all-cause mortality. Interaction analyses showed that fasting status interacted with triglyceride in predicting all-cause mortality. Sub-analyses showed that a 1-natural-log-unit increase in triglyceride was associated with a 17% higher multivariate-adjusted risk of all-cause mortality in the nonfasting subcohort; however, there lacked such an association in the fasting sub-cohort. Similarly, high (200–499 mg/dL) and very high levels of triglyceride (
Few-shot image classification : current status and research trends
- Liu, Ying, Zhang, Hengchang, Zhang, Weidong, Lu, Guojun, Tian, Qi, Ling, Nam
- Authors: Liu, Ying , Zhang, Hengchang , Zhang, Weidong , Lu, Guojun , Tian, Qi , Ling, Nam
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Electronics (Switzerland) Vol. 11, no. 11 (2022), p.
- Full Text:
- Reviewed:
- Description: Conventional image classification methods usually require a large number of training samples for the training model. However, in practical scenarios, the amount of available sample data is often insufficient, which easily leads to overfitting in network construction. Few-shot learning provides an effective solution to this problem and has been a hot research topic. This paper provides an intensive survey on the state-of-the-art techniques in image classification based on few-shot learning. According to the different deep learning mechanisms, the existing algorithms are di-vided into four categories: transfer learning based, meta-learning based, data augmentation based, and multimodal based methods. Transfer learning based methods transfer useful prior knowledge from the source domain to the target domain. Meta-learning based methods employ past prior knowledge to guide the learning of new tasks. Data augmentation based methods expand the amount of sample data with auxiliary information. Multimodal based methods use the information of the auxiliary modal to facilitate the implementation of image classification tasks. This paper also summarizes the few-shot image datasets available in the literature, and experimental results tested by some representative algorithms are provided to compare their performance and analyze their pros and cons. In addition, the application of existing research outcomes on few-shot image classification in different practical fields are discussed. Finally, a few future research directions are iden-tified. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Liu, Ying , Zhang, Hengchang , Zhang, Weidong , Lu, Guojun , Tian, Qi , Ling, Nam
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Electronics (Switzerland) Vol. 11, no. 11 (2022), p.
- Full Text:
- Reviewed:
- Description: Conventional image classification methods usually require a large number of training samples for the training model. However, in practical scenarios, the amount of available sample data is often insufficient, which easily leads to overfitting in network construction. Few-shot learning provides an effective solution to this problem and has been a hot research topic. This paper provides an intensive survey on the state-of-the-art techniques in image classification based on few-shot learning. According to the different deep learning mechanisms, the existing algorithms are di-vided into four categories: transfer learning based, meta-learning based, data augmentation based, and multimodal based methods. Transfer learning based methods transfer useful prior knowledge from the source domain to the target domain. Meta-learning based methods employ past prior knowledge to guide the learning of new tasks. Data augmentation based methods expand the amount of sample data with auxiliary information. Multimodal based methods use the information of the auxiliary modal to facilitate the implementation of image classification tasks. This paper also summarizes the few-shot image datasets available in the literature, and experimental results tested by some representative algorithms are provided to compare their performance and analyze their pros and cons. In addition, the application of existing research outcomes on few-shot image classification in different practical fields are discussed. Finally, a few future research directions are iden-tified. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Reda, Ahmed, Sultan, Ibrahim, Shahin, Mohamed, McKee, Kristoffer, Lagat, Christopher
- Authors: Reda, Ahmed , Sultan, Ibrahim , Shahin, Mohamed , McKee, Kristoffer , Lagat, Christopher
- Date: 2022
- Type: Text , Journal article
- Relation: International Journal of Pressure Vessels and Piping Vol. 198, no. (2022), p.
- Full Text: false
- Reviewed:
- Description: This paper investigates the possible failure modes of an incident of ultrasonic (UT) pig lodged in a Corrosion Resistant Alloy (CRA) clad pipeline during a baseline in-line inspection as part of pre-commissioning pipeline activities. The paper establishes the pipeline integrity following the incident and determines whether it remains fit for the intended service. The paper also discusses the suitability of using UT pigging for in-line re-inspection of the damaged pipeline, the effect of hoop stress due to pipe-wall thinning and the possibility of crack growth. Additionally, the possibility of undetected damage is considered alongside rigorous fatigue crack growth and fracture mechanics assessments of the pipeline to ascertain the pipeline integrity. It was concluded that the probability of the pipeline sustaining flaws exceeding a minimum depth of 1.8 mm is minimal. Due to the robust manufacturing process of the CRA clad pipeline, it was also concluded that the gouges left during the pigging incident do not affect the ability of the clad layer to provide corrosion protection. © 2022 Elsevier Ltd
Five decades of research on capital budgeting – a systematic review and future research agenda
- Sureka, Riya, Kumar, Satish, Colombage, Sisira, Abedin, Mohammad
- Authors: Sureka, Riya , Kumar, Satish , Colombage, Sisira , Abedin, Mohammad
- Date: 2022
- Type: Text , Journal article
- Relation: Research in International Business and Finance Vol. 60, no. (2022), p.
- Full Text: false
- Reviewed:
- Description: This study synthesizes and reviews the existing literature on capital budgeting (CB) practices and their application to theories, contexts, characteristics and methodology. It aims to identify the prevalent issues and gaps in the literature and provide potential avenues for future research. After comprehensive search and rigorous scrutiny, this review encompasses 185 articles. A systematic literature review (SLR), triangulated with the bibliometric method, is carried out, adopting a meticulous approach to achieve a comprehensive overview of the field. Based on cluster analysis, four distinct themes are identified. Additionally, a conceptual framework is developed that shows the antecedents, moderators and outcomes of research on capital budgeting. Grounded on the detailed content analysis, 11 actionable future research directions are proposed to advance this field of research. © 2021 Elsevier B.V.
- Nguyen, Duc, Javidan, Fatemeh, Attar, Mohammadmahdi, Natarajan, Sundarajan, Yang, Zhenjun, Ooi, Ean Hin, Song, Chongmin, Ooi, Ean Tat
- Authors: Nguyen, Duc , Javidan, Fatemeh , Attar, Mohammadmahdi , Natarajan, Sundarajan , Yang, Zhenjun , Ooi, Ean Hin , Song, Chongmin , Ooi, Ean Tat
- Date: 2022
- Type: Text , Journal article
- Relation: Theoretical and Applied Fracture Mechanics Vol. 118, no. (2022), p.
- Full Text: false
- Reviewed:
- Description: This paper develops the scaled boundary finite element method to analyse fracture of functionally graded magneto-electro-elastic materials. Polygon meshes are employed to discretize the domain. No asymptotic solution, local mesh refinement or other special treatments around a crack tip are required to calculate the intensity factors. When the material gradients of the coefficients in the constitutive matrix are expressed as a series of power functions of the scaled boundary coordinates, the stiffness matrices can be integrated analytically. The formulation enables the generalized intensity factors of stress, electric displacement and magnetic induction fields along the radial direction to be represented analytically. This permits the calculation of the generalized intensity factors directly from the scaled boundary finite element solution of the singular stress, electric displacement and magnetic induction fields by following the standard stress recovery procedures in the finite element method. Several numerical benchmarks are presented to validate the proposed technique with the results reported in the literature. © 2022 Elsevier Ltd
- Nguyen, Duc, Javidan, Fatemeh, Attar, Mohammadmahdi, Natarajan, Sundararajan, Yang, Zhenjun, Ooi, Ean Hin, Song, Chongmin, Ooi, Ean Tat
- Authors: Nguyen, Duc , Javidan, Fatemeh , Attar, Mohammadmahdi , Natarajan, Sundararajan , Yang, Zhenjun , Ooi, Ean Hin , Song, Chongmin , Ooi, Ean Tat
- Date: 2022
- Type: Text , Journal article
- Relation: Theoretical and Applied Fracture Mechanics Vol. 118, no. (2022), p.
- Full Text: false
- Reviewed:
- Description: This paper develops the scaled boundary finite element method to analyse fracture of functionally graded magneto-electro-elastic materials. Polygon meshes are employed to discretize the domain. No asymptotic solution, local mesh refinement or other special treatments around a crack tip are required to calculate the intensity factors. When the material gradients of the coefficients in the constitutive matrix are expressed as a series of power functions of the scaled boundary coordinates, the stiffness matrices can be integrated analytically. The formulation enables the generalized intensity factors of stress, electric displacement and magnetic induction fields along the radial direction to be represented analytically. This permits the calculation of the generalized intensity factors directly from the scaled boundary finite element solution of the singular stress, electric displacement and magnetic induction fields by following the standard stress recovery procedures in the finite element method. Several numerical benchmarks are presented to validate the proposed technique with the results reported in the literature. © 2022 Elsevier Ltd
- Authors: Théra, Michel
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of Optimization Theory and Applications Vol. 193, no. 1-3 (2022), p. 5-20
- Relation: http://purl.org/au-research/grants/arc/DP160100854
- Full Text: false
- Reviewed:
Gambling disorder in the UK : key research priorities and the urgent need for independent research funding
- Bowden-Jones, Henrietta, Hook, Roxanne, Grant, Jon, Ioannidis, Konstantinos, Corazza, Ornella, Fineberg, Naomi, Singer, Bryan, Roberts, Amanda, Bethlehem, Richard, Dymond, Simon, Romero-Garcia, Rafa, Robbins, Trevor, Cortese, Samuele, Thomas, Shane, Sahakian, Barbara, Dowling, Nicki, Chamberlain, Samuel
- Authors: Bowden-Jones, Henrietta , Hook, Roxanne , Grant, Jon , Ioannidis, Konstantinos , Corazza, Ornella , Fineberg, Naomi , Singer, Bryan , Roberts, Amanda , Bethlehem, Richard , Dymond, Simon , Romero-Garcia, Rafa , Robbins, Trevor , Cortese, Samuele , Thomas, Shane , Sahakian, Barbara , Dowling, Nicki , Chamberlain, Samuel
- Date: 2022
- Type: Text , Journal article , Review
- Relation: The Lancet Psychiatry Vol. 9, no. 4 (2022), p. 321-329
- Full Text:
- Reviewed:
- Description: Gambling in the modern era is pervasive owing to the variety of gambling opportunities available, including those that use technology (eg, online applications on smartphones). Although many people gamble recreationally without undue negative effects, a sizeable subset of individuals develop disordered gambling, which is associated with marked functional impairment including other mental health problems, relationship problems, bankruptcy, suicidality, and criminality. The National UK Research Network for Behavioural Addictions (NUK-BA) was established to promote understanding of, research into, and treatments for behavioural addictions including gambling disorder, which is the only formally recognised behavioural addiction. In this Health Policy paper, we outline the status of research and treatment for disordered gambling in the UK (including funding issues) and key research that should be conducted to establish the magnitude of the problem, vulnerability and resilience factors, the underlying neurobiology, long-term consequences, and treatment opportunities. In particular, we emphasise the need to: (1) conduct independent longitudinal research into the prevalence of disordered gambling (including gambling disorder and at-risk gambling), and gambling harms, including in vulnerable and minoritised groups; (2) select and refine the most suitable pragmatic measurement tools; (3) identify predictors (eg, vulnerability and resilience markers) of disordered gambling in people who gamble recreationally, including in vulnerable and minoritised groups; (4) conduct randomised controlled trials on psychological interventions and pharmacotherapy for gambling disorder; (5) improve understanding of the neurobiological basis of gambling disorder, including impulsivity and compulsivity, genetics, and biomarkers; and (6) develop clinical guidelines based on the best contemporary research evidence to guide effective clinical interventions. We also highlight the need to consider what can be learnt from approaches towards mitigating gambling-related harm in other countries. © 2022 Elsevier Ltd
- Authors: Bowden-Jones, Henrietta , Hook, Roxanne , Grant, Jon , Ioannidis, Konstantinos , Corazza, Ornella , Fineberg, Naomi , Singer, Bryan , Roberts, Amanda , Bethlehem, Richard , Dymond, Simon , Romero-Garcia, Rafa , Robbins, Trevor , Cortese, Samuele , Thomas, Shane , Sahakian, Barbara , Dowling, Nicki , Chamberlain, Samuel
- Date: 2022
- Type: Text , Journal article , Review
- Relation: The Lancet Psychiatry Vol. 9, no. 4 (2022), p. 321-329
- Full Text:
- Reviewed:
- Description: Gambling in the modern era is pervasive owing to the variety of gambling opportunities available, including those that use technology (eg, online applications on smartphones). Although many people gamble recreationally without undue negative effects, a sizeable subset of individuals develop disordered gambling, which is associated with marked functional impairment including other mental health problems, relationship problems, bankruptcy, suicidality, and criminality. The National UK Research Network for Behavioural Addictions (NUK-BA) was established to promote understanding of, research into, and treatments for behavioural addictions including gambling disorder, which is the only formally recognised behavioural addiction. In this Health Policy paper, we outline the status of research and treatment for disordered gambling in the UK (including funding issues) and key research that should be conducted to establish the magnitude of the problem, vulnerability and resilience factors, the underlying neurobiology, long-term consequences, and treatment opportunities. In particular, we emphasise the need to: (1) conduct independent longitudinal research into the prevalence of disordered gambling (including gambling disorder and at-risk gambling), and gambling harms, including in vulnerable and minoritised groups; (2) select and refine the most suitable pragmatic measurement tools; (3) identify predictors (eg, vulnerability and resilience markers) of disordered gambling in people who gamble recreationally, including in vulnerable and minoritised groups; (4) conduct randomised controlled trials on psychological interventions and pharmacotherapy for gambling disorder; (5) improve understanding of the neurobiological basis of gambling disorder, including impulsivity and compulsivity, genetics, and biomarkers; and (6) develop clinical guidelines based on the best contemporary research evidence to guide effective clinical interventions. We also highlight the need to consider what can be learnt from approaches towards mitigating gambling-related harm in other countries. © 2022 Elsevier Ltd
Generating population estimates for migratory shorebird species in the world’s largest flyway
- Hansen, Birgita, Rogers, Danny, Watkins, Doug, Weller, Dan, Clemens, Robert, Newman, Mike, Woehler, Eric, Mundkur, Taej, Fuller, Richard
- Authors: Hansen, Birgita , Rogers, Danny , Watkins, Doug , Weller, Dan , Clemens, Robert , Newman, Mike , Woehler, Eric , Mundkur, Taej , Fuller, Richard
- Date: 2022
- Type: Text , Journal article
- Relation: Ibis Vol. 164, no. 3 (2022), p. 735-749
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- Reviewed:
- Description: Population estimates are widely used to underpin conservation decisions. However, determining accurate population estimates for migratory species is especially challenging, as they are often widespread and it is rarely possible to survey them throughout their full distribution. In the East Asian–Australasian Flyway (EAAF), this problem is compounded by its size (85 million square kilometres) and the number of migratory species it supports (nearly 500). Here, we provide analytical approaches for addressing this problem, presenting a revision of the EAAF population estimates for 37 migratory shorebird species protected under Australian national environmental legislation. Population estimates were generated by (1) summarizing existing count data in the non-breeding range, (2) spatially extrapolating across uncounted areas, and (3) modelling abundance on the basis of estimates of breeding range and density. Expert review was used to adjust modelled estimates, particularly in under-counted areas. There were many gaps in shorebird monitoring data, necessitating substantial use of extrapolation and expert review, the extent of which varied among species. Spatial extrapolation to under-counted areas often produced estimates that were much higher than the observed data, and expert review was used to cross-check and adjust these where necessary. Estimates of population size obtained through analyses of breeding ranges and density indicated that 18 species were poorly represented by counts in the non-breeding season. It was difficult to determine independently the robustness of these estimates, but these breeding ground estimates were considered the best available data for 10 species that mostly use poorly surveyed freshwater or pelagic habitats in the non-breeding season. We discuss the rationale and limitations of these approaches to population estimation, and how they could be modified for other applications. Data available for population estimates will vary in quality and extent among species, regions and migration stage, and approaches need to be flexible enough to provide useful information for conservation policy and planning. © 2021 British Ornithologists' Union.
- Authors: Hansen, Birgita , Rogers, Danny , Watkins, Doug , Weller, Dan , Clemens, Robert , Newman, Mike , Woehler, Eric , Mundkur, Taej , Fuller, Richard
- Date: 2022
- Type: Text , Journal article
- Relation: Ibis Vol. 164, no. 3 (2022), p. 735-749
- Full Text:
- Reviewed:
- Description: Population estimates are widely used to underpin conservation decisions. However, determining accurate population estimates for migratory species is especially challenging, as they are often widespread and it is rarely possible to survey them throughout their full distribution. In the East Asian–Australasian Flyway (EAAF), this problem is compounded by its size (85 million square kilometres) and the number of migratory species it supports (nearly 500). Here, we provide analytical approaches for addressing this problem, presenting a revision of the EAAF population estimates for 37 migratory shorebird species protected under Australian national environmental legislation. Population estimates were generated by (1) summarizing existing count data in the non-breeding range, (2) spatially extrapolating across uncounted areas, and (3) modelling abundance on the basis of estimates of breeding range and density. Expert review was used to adjust modelled estimates, particularly in under-counted areas. There were many gaps in shorebird monitoring data, necessitating substantial use of extrapolation and expert review, the extent of which varied among species. Spatial extrapolation to under-counted areas often produced estimates that were much higher than the observed data, and expert review was used to cross-check and adjust these where necessary. Estimates of population size obtained through analyses of breeding ranges and density indicated that 18 species were poorly represented by counts in the non-breeding season. It was difficult to determine independently the robustness of these estimates, but these breeding ground estimates were considered the best available data for 10 species that mostly use poorly surveyed freshwater or pelagic habitats in the non-breeding season. We discuss the rationale and limitations of these approaches to population estimation, and how they could be modified for other applications. Data available for population estimates will vary in quality and extent among species, regions and migration stage, and approaches need to be flexible enough to provide useful information for conservation policy and planning. © 2021 British Ornithologists' Union.
Genomic diversity and antimicrobial resistance among non-typhoidal Salmonella associated with human disease in The Gambia
- Darboe, Saffiatou, Bradbury, Richard, Phelan, Jody, Kanteh, Abdoulie, Muhammad, Abdul-Khalie, Worwui, Archibald, Yang, Shangxin, Nwakanma, Davis, Perez-Sepulveda, Blanca, Kariuki, Samuel, Kwambana-Adams, Brenda, Antonio, Martin
- Authors: Darboe, Saffiatou , Bradbury, Richard , Phelan, Jody , Kanteh, Abdoulie , Muhammad, Abdul-Khalie , Worwui, Archibald , Yang, Shangxin , Nwakanma, Davis , Perez-Sepulveda, Blanca , Kariuki, Samuel , Kwambana-Adams, Brenda , Antonio, Martin
- Date: 2022
- Type: Text , Journal article
- Relation: Microbial Genomics Vol. 8, no. 3 (2022), p.
- Full Text:
- Reviewed:
- Description: Non-typhoidal Salmonella associated with multidrug resistance cause invasive disease in sub-Saharan Africa. Specific lineages of serovars Typhimurium and Enteritidis have been implicated. Here we characterized the genomic diversity of 100 clinical non-typhoidal Salmonella collected from 93 patients in 2001 from the eastern, and in 2006–2018 from the western regions of The Gambia respectively. A total of 93 isolates (64 invasive, 23 gastroenteritis and six other sites) representing a single infection episode were phenotypically tested for antimicrobial susceptibility using the Kirby–Bauer disc diffusion technique. Whole genome sequencing of 100 isolates was performed using Illumina, and the reads were assembled and analysed using SPAdes. The Salmonella in Silico Typing Resource (SISTR) was used for serotyping. SNP differences among the 93 isolates were determined using Roary, and phylogenetic analysis was performed in the context of 495 African strains from the European Nucleotide Archive. Salmonella serovars Typhimurium (26/64; 30.6%) and Enteritidis (13/64; 20.3%) were associated with invasive disease, whilst other serovars were mainly responsible for gastroenteritis (17/23; 73.9%). The presence of three major serovar Enteritidis clades was confirmed, including the invasive West African clade, which made up more than half (11/16; 68.8%) of the genomes. Multidrug resistance was confined among the serovar Enteritidis West African clade. The presence of this epidemic virulent clade has potential for spread of resistance and thus important implications for systematic patient management. Surveillance and epidemiological investigations to inform control are warranted. © 2022 The Authors.
- Authors: Darboe, Saffiatou , Bradbury, Richard , Phelan, Jody , Kanteh, Abdoulie , Muhammad, Abdul-Khalie , Worwui, Archibald , Yang, Shangxin , Nwakanma, Davis , Perez-Sepulveda, Blanca , Kariuki, Samuel , Kwambana-Adams, Brenda , Antonio, Martin
- Date: 2022
- Type: Text , Journal article
- Relation: Microbial Genomics Vol. 8, no. 3 (2022), p.
- Full Text:
- Reviewed:
- Description: Non-typhoidal Salmonella associated with multidrug resistance cause invasive disease in sub-Saharan Africa. Specific lineages of serovars Typhimurium and Enteritidis have been implicated. Here we characterized the genomic diversity of 100 clinical non-typhoidal Salmonella collected from 93 patients in 2001 from the eastern, and in 2006–2018 from the western regions of The Gambia respectively. A total of 93 isolates (64 invasive, 23 gastroenteritis and six other sites) representing a single infection episode were phenotypically tested for antimicrobial susceptibility using the Kirby–Bauer disc diffusion technique. Whole genome sequencing of 100 isolates was performed using Illumina, and the reads were assembled and analysed using SPAdes. The Salmonella in Silico Typing Resource (SISTR) was used for serotyping. SNP differences among the 93 isolates were determined using Roary, and phylogenetic analysis was performed in the context of 495 African strains from the European Nucleotide Archive. Salmonella serovars Typhimurium (26/64; 30.6%) and Enteritidis (13/64; 20.3%) were associated with invasive disease, whilst other serovars were mainly responsible for gastroenteritis (17/23; 73.9%). The presence of three major serovar Enteritidis clades was confirmed, including the invasive West African clade, which made up more than half (11/16; 68.8%) of the genomes. Multidrug resistance was confined among the serovar Enteritidis West African clade. The presence of this epidemic virulent clade has potential for spread of resistance and thus important implications for systematic patient management. Surveillance and epidemiological investigations to inform control are warranted. © 2022 The Authors.
Gifted education in Lebanon : time to rethink teaching the gifted
- Antoun, Maya, Plunkett, Margaret, Kronborg, Leonie
- Authors: Antoun, Maya , Plunkett, Margaret , Kronborg, Leonie
- Date: 2022
- Type: Text , Journal article
- Relation: Roeper Review Vol. 44, no. 2 (2022), p. 94-110
- Full Text: false
- Reviewed:
- Description: Lebanon is a country that places a high value on education, with the culture specifically rewarding effort and achievement. Despite this, no educational policies for gifted students exist in the country. This article outlines findings from a mixed method case study investigating the perceptions of more than 280 Lebanese teachers about educational approaches used to identify and teach highly able/gifted primary school students. Findings acknowledge reservations among teacher participants in relation to offering special services for gifted students. Although the analysis illustrated an overall lack of awareness of practices that have been identified in international research as effective for identifying and providing for gifted students, there was ample evidence of the desire of teacher participants to become more informed about evidence-based practice. This suggests the time is ripe for a revised focus on gifted education in Teacher Education within Lebanon. © 2022 The Roeper Institute.
Graph self-supervised learning : a survey
- Liu, Yixin, Jin, Ming, Pan, Shirui, Zhou, Chuan, Zheng, Yu, Xia, Feng, Yu, Philip
- Authors: Liu, Yixin , Jin, Ming , Pan, Shirui , Zhou, Chuan , Zheng, Yu , Xia, Feng , Yu, Philip
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Transactions on Knowledge and Data Engineering Vol. , no. (2022), p. 1-1
- Full Text:
- Reviewed:
- Description: Deep learning on graphs has attracted significant interests recently. However, most of the works have focused on (semi-) supervised learning, resulting in shortcomings including heavy label reliance, poor generalization, and weak robustness. To address these issues, self-supervised learning (SSL), which extracts informative knowledge through well-designed pretext tasks without relying on manual labels, has become a promising and trending learning paradigm for graph data. Different from SSL on other domains like computer vision and natural language processing, SSL on graphs has an exclusive background, design ideas, and taxonomies. Under the umbrella of graph self-supervised learning, we present a timely and comprehensive review of the existing approaches which employ SSL techniques for graph data. We construct a unified framework that mathematically formalizes the paradigm of graph SSL. According to the objectives of pretext tasks, we divide these approaches into four categories: generation-based, auxiliary property-based, contrast-based, and hybrid approaches. We further describe the applications of graph SSL across various research fields and summarize the commonly used datasets, evaluation benchmark, performance comparison and open-source codes of graph SSL. Finally, we discuss the remaining challenges and potential future directions in this research field. IEEE
- Authors: Liu, Yixin , Jin, Ming , Pan, Shirui , Zhou, Chuan , Zheng, Yu , Xia, Feng , Yu, Philip
- Date: 2022
- Type: Text , Journal article
- Relation: IEEE Transactions on Knowledge and Data Engineering Vol. , no. (2022), p. 1-1
- Full Text:
- Reviewed:
- Description: Deep learning on graphs has attracted significant interests recently. However, most of the works have focused on (semi-) supervised learning, resulting in shortcomings including heavy label reliance, poor generalization, and weak robustness. To address these issues, self-supervised learning (SSL), which extracts informative knowledge through well-designed pretext tasks without relying on manual labels, has become a promising and trending learning paradigm for graph data. Different from SSL on other domains like computer vision and natural language processing, SSL on graphs has an exclusive background, design ideas, and taxonomies. Under the umbrella of graph self-supervised learning, we present a timely and comprehensive review of the existing approaches which employ SSL techniques for graph data. We construct a unified framework that mathematically formalizes the paradigm of graph SSL. According to the objectives of pretext tasks, we divide these approaches into four categories: generation-based, auxiliary property-based, contrast-based, and hybrid approaches. We further describe the applications of graph SSL across various research fields and summarize the commonly used datasets, evaluation benchmark, performance comparison and open-source codes of graph SSL. Finally, we discuss the remaining challenges and potential future directions in this research field. IEEE
GraphLearning’22: 1st International Workshop on Graph Learning
- Xia, Feng, Lambiotte, Renaud, Aggarwal, Charu
- Authors: Xia, Feng , Lambiotte, Renaud , Aggarwal, Charu
- Date: 2022
- Type: Text , Conference proceedings
- Relation: WWW '22: Companion Proceedings of the Web Conference 2022, Virtual Event, Lyon France April 25 - 29, 2022 p. 1004-1005
- Full Text:
- Reviewed:
- Description: The First Workshop on Graph Learning aims to bring together researchers and practitioners from academia and industry to discuss recent advances and core challenges of graph learning. This workshop will be established as a platform for multiple disciplines such as computer science, applied mathematics, physics, social sciences, data science, complex networks, and systems engineering. Core challenges in regard to theory, methodology, and applications of graph learning will be the main center of discussions at the workshop.
- Authors: Xia, Feng , Lambiotte, Renaud , Aggarwal, Charu
- Date: 2022
- Type: Text , Conference proceedings
- Relation: WWW '22: Companion Proceedings of the Web Conference 2022, Virtual Event, Lyon France April 25 - 29, 2022 p. 1004-1005
- Full Text:
- Reviewed:
- Description: The First Workshop on Graph Learning aims to bring together researchers and practitioners from academia and industry to discuss recent advances and core challenges of graph learning. This workshop will be established as a platform for multiple disciplines such as computer science, applied mathematics, physics, social sciences, data science, complex networks, and systems engineering. Core challenges in regard to theory, methodology, and applications of graph learning will be the main center of discussions at the workshop.
Green demand aware fog computing : a prediction-based dynamic resource provisioning approach
- Khadhijah, Pg, Newaz, S., Rahman, Fatin, Lee, Gyu, Karmakar, Gour, Au, Thien-Wan
- Authors: Khadhijah, Pg , Newaz, S. , Rahman, Fatin , Lee, Gyu , Karmakar, Gour , Au, Thien-Wan
- Date: 2022
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 11, no. 4 (2022), p.
- Full Text:
- Reviewed:
- Description: Fog computing could potentially cause the next paradigm shift by extending cloud services to the edge of the network, bringing resources closer to the end-user. With its close proximity to end-users and its distributed nature, fog computing can significantly reduce latency. With the appearance of more and more latency-stringent applications, in the near future, we will witness an unprecedented amount of demand for fog computing. Undoubtedly, this will lead to an increase in the energy footprint of the network edge and access segments. To reduce energy consumption in fog computing without compromising performance, in this paper we propose the Green-Demand-Aware Fog Computing (GDAFC) solution. Our solution uses a prediction technique to identify the working fog nodes (nodes serve when request arrives), standby fog nodes (nodes take over when the computational capacity of the working fog nodes is no longer sufficient), and idle fog nodes in a fog computing infrastructure. Additionally, it assigns an appropriate sleep interval for the fog nodes, taking into account the delay requirement of the applications. Results obtained based on the mathematical formulation show that our solution can save energy up to 65% without deteriorating the delay requirement performance. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Khadhijah, Pg , Newaz, S. , Rahman, Fatin , Lee, Gyu , Karmakar, Gour , Au, Thien-Wan
- Date: 2022
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 11, no. 4 (2022), p.
- Full Text:
- Reviewed:
- Description: Fog computing could potentially cause the next paradigm shift by extending cloud services to the edge of the network, bringing resources closer to the end-user. With its close proximity to end-users and its distributed nature, fog computing can significantly reduce latency. With the appearance of more and more latency-stringent applications, in the near future, we will witness an unprecedented amount of demand for fog computing. Undoubtedly, this will lead to an increase in the energy footprint of the network edge and access segments. To reduce energy consumption in fog computing without compromising performance, in this paper we propose the Green-Demand-Aware Fog Computing (GDAFC) solution. Our solution uses a prediction technique to identify the working fog nodes (nodes serve when request arrives), standby fog nodes (nodes take over when the computational capacity of the working fog nodes is no longer sufficient), and idle fog nodes in a fog computing infrastructure. Additionally, it assigns an appropriate sleep interval for the fog nodes, taking into account the delay requirement of the applications. Results obtained based on the mathematical formulation show that our solution can save energy up to 65% without deteriorating the delay requirement performance. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.