Succession of microbial community in a small water body within the alluvial aquifer of a large river
- Kulaš, Antonija, Marković, Tamara, Žutinić, Petar, Kajan, Katarina, Karlović, Igor, Orlić, Sandi, Keskin, Emre, Filipović, Vilim, Gligora Udovič, Marija
- Authors: Kulaš, Antonija , Marković, Tamara , Žutinić, Petar , Kajan, Katarina , Karlović, Igor , Orlić, Sandi , Keskin, Emre , Filipović, Vilim , Gligora Udovič, Marija
- Date: 2021
- Type: Text , Journal article
- Relation: Water Vol. 13, no. 2 (2021), p. 115
- Full Text: false
- Reviewed:
- Description: Nitrogen is one of the essential elements limiting growth in aquatic environments. Being primarily of anthropogenic origin, it exerts negative impacts on freshwater ecosystems. The present study was carried out at the nitrate-vulnerable zone within the alluvial aquifer of the large lowland Drava River. The main aim was to investigate the ecosystem’s functionality by characterizing the bacterial and phytoplankton diversity of a small inactive gravel pit by using interdisciplinary approaches. The phytoplankton community was investigated via traditional microscopy analyses and environmental DNA (eDNA) metabarcoding, while the bacterial community was investigated by a molecular approach (eDNA). Variations in the algal and bacterial community structure indicated a strong correlation with nitrogen compounds. Summer samples were characterized by a high abundance of bloom-forming Cyanobacteria. Following the cyanobacterial breakdown in the colder winter period, Bacillariophyceae and Actinobacteriota became dominant groups. Changes in microbial composition indicated a strong correlation between N forms and algal and bacterial communities. According to the nitrogen dynamics in the alluvial aquifer, we emphasize the importance of small water bodies as potential buffer zones to anthropogenic nitrogen pressures and sentinels of the disturbances displayed as algal blooms within larger freshwater systems. Special Issue Microbial Communities in Water Environments: Dynamics and Interaction)
Policy options to regulate pv in low voltage grids-australian case with international implications
- Currie, Glen, Evans, Robin, Duffield, Colin, Mareels, Iven
- Authors: Currie, Glen , Evans, Robin , Duffield, Colin , Mareels, Iven
- Date: 2019
- Type: Text , Journal article
- Relation: Technology and economics of smart grids and sustainable energy Vol. 4, no. 1 (2019), p. 1-10
- Full Text: false
- Reviewed:
- Description: This article shows a socio-technical evaluation of the Australian case which has international implications for energy policy and regulation. Australia is one of few places globally that have faced domestic PV (photovoltaic system) adoption of above 50% of feeder connections. This leads to grid issues and is an emerging issue globally. Grid issues include over-voltage, thermal overload, frequency instability and voltage instability. This paper offers a policy process to regulate PV. This research extends earlier econometric modelling of Australian PV adoption data and extends it to focus on PV regulation in low voltage grids. This paper explores five policy options to help regulate PV in low voltage grids: the role of distribution businesses, inverter regulation, PV export limits, cost reflective pricing, and storage. Policy complexity comes from the need to incorporate many stakeholder perspectives, and this research contributes to policy clarity by seeking a consensus.
Reinforcement learning for adaptive optimal control of continuous-time linear periodic systems
- Pang, Bo, Jiang, Zhong-Ping, Mareels, Iven
- Authors: Pang, Bo , Jiang, Zhong-Ping , Mareels, Iven
- Date: 2020
- Type: Text , Journal article
- Relation: Automatica Vol. 118, no. (2020), p. 109035
- Full Text: false
- Reviewed:
- Description: This paper studies the infinite-horizon adaptive optimal control of continuous-time linear periodic (CTLP) systems, using reinforcement learning techniques. By means of policy iteration (PI) for CTLP systems, both on-policy and off-policy adaptive dynamic programming (ADP) algorithms are derived, such that the solution of the optimal control problem can be found without the exact knowledge of the system dynamics. Starting with initial stabilizing controllers, the proposed PI-based ADP algorithms converge to the optimal solutions under mild conditions. Application to the adaptive optimal control of the lossy Mathieu equation demonstrates the efficacy of the proposed learning-based adaptive optimal control algorithm.
- O'Kelly, Brendan, Soltani, Amin
- Authors: O'Kelly, Brendan , Soltani, Amin
- Date: 2022
- Type: Text , Journal article
- Relation: Engineering geology Vol. 306, no. (2022), p. 106746
- Full Text: false
- Reviewed:
- Description: he paper under discussion (Díaz et al., 2021) investigated the application of machine learning techniques to relate the Casagrande percussion-cup liquid limit (LLCUP) with the fall-cone liquid limit (LLCONE) determined using the 30°–80 g British Standard (BS) fall-cone device (BSI, 2018) for low–medium plasticity fine-grained soils (having plasticity index values of <30% and which mostly classify as CL–ML and CL) sampled from a specific site in SE Spain. As reported in their paper, the experimental LLCUP data were obtained in accordance with the UNE 103103:94 standard (AENOR, 1994), which employs a percussion-cup device having ‘hard’ base material satisfying the same hardness and resilience specification ranges as those of the ASTM percussion-cup device (ASTM, 2017). The clay mineralogy of the investigated fine-grained soils was not reported in Díaz et al. (2021); however, as explained in Haigh (2012) and O'Kelly et al. (2020a), clay mineralogy does not majorly account for dissimilarities in LLCUP and LLCONE measurements for a given fine-grained soil; rather they largely arise due to the different mechanics of the percussion-cup and fall-cone test devices (O'Kelly et al., 2018; O'Kelly, 2021; O’Kelly et al., 2022), and also due to variations in the hardness/resilience of the cup base-material (being ‘soft’ or ‘hard’) (Haigh, 2012, Haigh, 2016). The LLCUP water content is associated with the soil's specific strength (i.e., ratio of remolded undrained shear strength su to saturated bulk density
Bond properties of sand-coated gfrp bars with fly ash–based geopolymer concrete
- Tekle, Biruk, Khennane, Amar, Kayali, Obada
- Authors: Tekle, Biruk , Khennane, Amar , Kayali, Obada
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of composites for construction Vol. 20, no. 5 (2016), p.
- Full Text: false
- Reviewed:
- Description: AbstractBond behavior is an important subject in the design and performance of reinforced concrete structures. In this research, the bond property between sand-coated glass fiber–reinforced polymer (GFRP) bars, a corrosion-resistant substitute to steel bars, and fly ash–based geopolymer cement (GPC) concrete, a more environmental friendly alternative to ordinary portland cement (OPC) concrete, is investigated. Pullout test specimens containing GFRP bars embedded in GPC and OPC concrete cylinders with 100-mm diameter and 170-mm height were prepared. Three different embedment lengths were tested: three, six, and nine times the bar diameter. Average concrete compressive strengths of approximately 25 and 45 MPa and GFRP bar diameters of 12.7 and 15.9 mm were the other test parameters. For each specimen, the test results include the bond failure mode, the average bond strength, the slip at the loaded and free end, and the bond-slip relationship curves. The test results showed that GFRP-reinforced GPC concrete has similar bond strength as that of GFRP-reinforced OPC concrete. The increase in embedment length resulted in the decrease of the bond strength as well as a change in the failure mode of the specimens. Furthermore, the experimental results were used to generate a constitutive bond-slip law. Finally, finite-element modeling is performed by using the constitutive bond-slip law to investigate strain and bond distribution along the embedment length of the bar.
- Ondrasek, Gabrijel, Kranjčec, Filip, Filipović, Lana, Filipović, Vilim, Bubalo Kovačić, Marina, Badovinac, Ivana Jelovica, Peter, Robert, Petravić, Mladen, Macan, Jelena, Rengel, Zed
- Authors: Ondrasek, Gabrijel , Kranjčec, Filip , Filipović, Lana , Filipović, Vilim , Bubalo Kovačić, Marina , Badovinac, Ivana Jelovica , Peter, Robert , Petravić, Mladen , Macan, Jelena , Rengel, Zed
- Date: 2021
- Type: Text , Journal article
- Relation: The Science of the total environment Vol. 753, no. (2021), p. 141902-141902
- Full Text: false
- Reviewed:
- Description: One of negative side-effects of usage of bio-renewables might be generation of mineral (ash) material, potential source of environmental pollution. A hypothesis was that bottom ash (BA from biomass cogeneration facility) could be efficiently (re) used in soil chemical conditioning similarly to widely-used dolomite-based soil conditioner (DO from Croatian Dinaric-coastal region) which we tested by: i) physicochemical characterisation of BA and DO, and ii) bioassay with Raphanus sativus cultivated in acidic soil amended with BA or DO. Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX) confirmed complex chemical/physical structures and morphology between amendments, X-ray diffraction (XRD) showed their distinctive mineralogy with predominantly dolomite (in DO) vs. quartz and calcite (in BA), while secondary ion mass spectrometry (SIMS) revealed their diverse elemental/isotopic composition. The BA or DO amendments ameliorated soil acidity, increased available P, K and most other nutrients, but not Cd. The BA or DO amendments improved vegetative growth and edible hypocotyl yield. However, both amendments also increased Cd accumulation in all radish tissues, which was unexpected given the alkaline matrix of bio-ash and dolomite that would be likely to facilitate retention and immobilisation of toxic Cd. Thus, thorough characterisation and evaluation of BA- and/or DO-based materials and relevant soils (with an emphasis on metal sorption/immobilisation) prior to application in (agro) ecosystems is crucial for producing food clean of toxic metals. [Display omitted] •Biomass bottom ash (BA) & dolomite (DO) are very alkaline (pHKCl = 10.2–11.2) matrices.•BA & DO ameliorated soil acidity quickly (by >1.5 pH units) & nutrient availability.•BA & DO improved radish vegetative growth & nutrition accumulation.•BA & DO increased Cd uptake and accumulation in all radish tissues.
Stability and bifurcations in low inertia PV rich power networks
- Vinaya Mohanan, Vishnu, Mareels, Iven, Evans, Robin, Morton, Anthony, Kolluri, Ramachandra
- Authors: Vinaya Mohanan, Vishnu , Mareels, Iven , Evans, Robin , Morton, Anthony , Kolluri, Ramachandra
- Date: 2020
- Type: Text , Journal article
- Relation: IET generation, transmission & distribution Vol. 14, no. 25 (2020), p. 6122-6132
- Full Text: false
- Reviewed:
- Description: The present trend of inserting increasingly more solar photovoltaic (PV) sources into the electricity grid leads to a significant reduction in mechanical inertia. Inertia represents energy reserve in the grid, that inherently and instantaneously supports frequency stability. Therefore, recent studies have re-examined the frequency stability of the grid. Most of these consider scenarios where the participation from grid-following inverters remains relatively low. More importantly, these studies include an infinite bus in their analyses. The infinite bus acts as a very stiff voltage source which has a significantly stabilising influence, the more so as all control refers back to the infinite bus. Here, the frequency stability of a grid with significant generation from grid-tied PV inverters is considered without reference to an infinite bus. In the proposed simplified grid model, all the synchronous generators (SGs) are lumped as one large SG complete with classically operating controls. Similarly, all the PV generators are lumped as one large, quasi-instantaneous, non-linear power source. In this simplified network, the feasible operating region is identified using bifurcation techniques. It transpires that the stable operating region is bounded by a locus of Hopf bifurcations linked (inter-alia) to the fraction of power generated by grid-tied PV inverters.
Hyperaccumulators for potentially toxic elements: A scientometric analysis
- Zhang, Dongming, Dyck, Miles, Filipović, Lana, Filipović, Vilim, Lv, Jialong, He, Hailong
- Authors: Zhang, Dongming , Dyck, Miles , Filipović, Lana , Filipović, Vilim , Lv, Jialong , He, Hailong
- Date: 2021
- Type: Text , Journal article
- Relation: Agronomy (Basel) Vol. 11, no. 9 (2021), p. 1729
- Full Text:
- Reviewed:
- Description: Phytoremediation is an effective and low-cost method for the remediation of soil contaminated by potentially toxic elements (metals and metalloids) with hyperaccumulating plants. This study analyzed hyperaccumulator publications using data from the Web of Science Core Collection (WoSCC) (1992–2020). We explored the research status on this topic by creating a series of scientific maps using VOSviewer, HistCite Pro, and CiteSpace. The results showed that the total number of publications in this field shows an upward trend. Dr. Xiaoe Yang is the most productive researcher on hyperaccumulators and has the broadest international collaboration network. The Chinese Academy of Sciences (China), Zhejiang University (China), and the University of Florida (USA) are the top three most productive institutions in the field. China, the USA, and India are the top three most productive countries. The most widely used journals were the International Journal of Phytoremediation, Environmental Science and Pollution Research, and Chemosphere. Co-occurrence and citation analysis were used to identify the most influential publications in this field. In addition, possible knowledge gaps and perspectives for future studies are also presented.
- Authors: Zhang, Dongming , Dyck, Miles , Filipović, Lana , Filipović, Vilim , Lv, Jialong , He, Hailong
- Date: 2021
- Type: Text , Journal article
- Relation: Agronomy (Basel) Vol. 11, no. 9 (2021), p. 1729
- Full Text:
- Reviewed:
- Description: Phytoremediation is an effective and low-cost method for the remediation of soil contaminated by potentially toxic elements (metals and metalloids) with hyperaccumulating plants. This study analyzed hyperaccumulator publications using data from the Web of Science Core Collection (WoSCC) (1992–2020). We explored the research status on this topic by creating a series of scientific maps using VOSviewer, HistCite Pro, and CiteSpace. The results showed that the total number of publications in this field shows an upward trend. Dr. Xiaoe Yang is the most productive researcher on hyperaccumulators and has the broadest international collaboration network. The Chinese Academy of Sciences (China), Zhejiang University (China), and the University of Florida (USA) are the top three most productive institutions in the field. China, the USA, and India are the top three most productive countries. The most widely used journals were the International Journal of Phytoremediation, Environmental Science and Pollution Research, and Chemosphere. Co-occurrence and citation analysis were used to identify the most influential publications in this field. In addition, possible knowledge gaps and perspectives for future studies are also presented.
A global review of the woody invasive alien species mimosa pigra (giant sensitive plant): Its biology and management implications
- Welgama, Amali, Florentine, Singarayer, Roberts, Jason
- Authors: Welgama, Amali , Florentine, Singarayer , Roberts, Jason
- Date: 2022
- Type: Text , Journal article
- Relation: Plants Vol. 11, no. 18 (2022), p. 2366
- Full Text:
- Reviewed:
- Description: Populations of invasive alien plants create disruptive plant communities that are extremely adaptable, imposing severe ecological impacts on agriculture, biodiversity and human activities. To minimise these impacts, prevention and effective weed management strategies are urgently required, including the identification of satellite populations before they invade new areas. This is a critical element that allows weed management practices to become both successful and cost-effective. Mimosa pigra L. (Giant sensitive plant) is an invasive weed that has spread across various environments around the world and is considered one of the world’s top 100 most invasive plant species. Being adaptable to a wide range of soil types, in addition to its woody protective prickles and low palatability, M. pigra has quickly spread and established itself in a range of habitats. Current control methods of this species include biological, chemical and physical methods, together with attempts of integrated application. Reports suggest that integrated management appears to be the most effective means of controlling M. pigra since the use of any single method has not yet proved suitable. In this regard, this review synthesises and explores the available global literature and current research gaps relating to the biology, distribution, impacts and management of M. pigra. The contribution of this work will help guide land managers to design appropriate and sustainable management programs to control M. pigra.
- Authors: Welgama, Amali , Florentine, Singarayer , Roberts, Jason
- Date: 2022
- Type: Text , Journal article
- Relation: Plants Vol. 11, no. 18 (2022), p. 2366
- Full Text:
- Reviewed:
- Description: Populations of invasive alien plants create disruptive plant communities that are extremely adaptable, imposing severe ecological impacts on agriculture, biodiversity and human activities. To minimise these impacts, prevention and effective weed management strategies are urgently required, including the identification of satellite populations before they invade new areas. This is a critical element that allows weed management practices to become both successful and cost-effective. Mimosa pigra L. (Giant sensitive plant) is an invasive weed that has spread across various environments around the world and is considered one of the world’s top 100 most invasive plant species. Being adaptable to a wide range of soil types, in addition to its woody protective prickles and low palatability, M. pigra has quickly spread and established itself in a range of habitats. Current control methods of this species include biological, chemical and physical methods, together with attempts of integrated application. Reports suggest that integrated management appears to be the most effective means of controlling M. pigra since the use of any single method has not yet proved suitable. In this regard, this review synthesises and explores the available global literature and current research gaps relating to the biology, distribution, impacts and management of M. pigra. The contribution of this work will help guide land managers to design appropriate and sustainable management programs to control M. pigra.
A validated injury surveillance and monitoring tool for fast jet aircrew: Translating sports medicine paradigms to a military population
- Wallace, James, Osmotherly, Peter, Gabbett, Tim, Spratford, Wayne, Niyonsenga, Theo, Newman, Phil
- Authors: Wallace, James , Osmotherly, Peter , Gabbett, Tim , Spratford, Wayne , Niyonsenga, Theo , Newman, Phil
- Date: 2022
- Type: Text , Journal article
- Relation: Sports medicine - open Vol. 8, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: Background Military populations, including fast jet aircrew (FJA - aka fighter aircrew/pilots), commonly suffer from musculoskeletal complaints, which reduce performance and operational capability. Valid surveillance tools and agreed recordable injury definitions are lacking. Our objective was to develop and then evaluate the validity of a musculoskeletal complaints surveillance and monitoring tool for FJA. Methods A Delphi study with international experts sought consensus on recordable injury definitions and important content for use in a surveillance and monitoring tool for FJA. Using these results and feedback from end-users (FJA), the University of Canberra Fast Jet Aircrew Musculoskeletal Questionnaire (UC-FJAMQ) was developed. Following its use with 306 Royal Australian Air Force (RAAF) FJA over 4 × five-month reporting periods, validity of the UC-FJAMQ was evaluated via multi-level factor analysis (MFA) and compared with routine methods of injury surveillance. Results Consensus was achieved for: eight words/descriptors for defining a musculoskeletal complaint six definitions of recordable injury and 14 domains important for determining overall severity. The UC-FJAMQ was developed and refined. MFA identified three distinct dimensions within the 11 items used to determine severity: operational capability, symptoms, and care-seeking. MFA further highlighted that symptom severity and seeking medical attention were poor indicators of the impact musculoskeletal complaints have upon operational capability. One hundred and fifty-two episodes of time loss were identified, with the UC-FJAMQ identifying 79% of these, while routine methods identified 49%. Despite modest weekly reporting rates (61%), the UC-FJAMQ outperformed routine surveillance methods. Conclusions The UC-FJAMQ was developed to specifically address the complexities of injury surveillance with FJA, which are similar to those noted in other military and sporting populations. The results demonstrated the UC-FJAMQ to be sensitive and valid within a large group of FJA over 4 × five-month reporting periods. Adoption of consistent, sensitive, and valid surveillance methods will strengthen the FJA injury prevention literature, ultimately enhancing their health, performance, and operational capability.
- Authors: Wallace, James , Osmotherly, Peter , Gabbett, Tim , Spratford, Wayne , Niyonsenga, Theo , Newman, Phil
- Date: 2022
- Type: Text , Journal article
- Relation: Sports medicine - open Vol. 8, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: Background Military populations, including fast jet aircrew (FJA - aka fighter aircrew/pilots), commonly suffer from musculoskeletal complaints, which reduce performance and operational capability. Valid surveillance tools and agreed recordable injury definitions are lacking. Our objective was to develop and then evaluate the validity of a musculoskeletal complaints surveillance and monitoring tool for FJA. Methods A Delphi study with international experts sought consensus on recordable injury definitions and important content for use in a surveillance and monitoring tool for FJA. Using these results and feedback from end-users (FJA), the University of Canberra Fast Jet Aircrew Musculoskeletal Questionnaire (UC-FJAMQ) was developed. Following its use with 306 Royal Australian Air Force (RAAF) FJA over 4 × five-month reporting periods, validity of the UC-FJAMQ was evaluated via multi-level factor analysis (MFA) and compared with routine methods of injury surveillance. Results Consensus was achieved for: eight words/descriptors for defining a musculoskeletal complaint six definitions of recordable injury and 14 domains important for determining overall severity. The UC-FJAMQ was developed and refined. MFA identified three distinct dimensions within the 11 items used to determine severity: operational capability, symptoms, and care-seeking. MFA further highlighted that symptom severity and seeking medical attention were poor indicators of the impact musculoskeletal complaints have upon operational capability. One hundred and fifty-two episodes of time loss were identified, with the UC-FJAMQ identifying 79% of these, while routine methods identified 49%. Despite modest weekly reporting rates (61%), the UC-FJAMQ outperformed routine surveillance methods. Conclusions The UC-FJAMQ was developed to specifically address the complexities of injury surveillance with FJA, which are similar to those noted in other military and sporting populations. The results demonstrated the UC-FJAMQ to be sensitive and valid within a large group of FJA over 4 × five-month reporting periods. Adoption of consistent, sensitive, and valid surveillance methods will strengthen the FJA injury prevention literature, ultimately enhancing their health, performance, and operational capability.
Dispositional optimism and suicide among trans and gender diverse adults
- Snooks, Matthew Paul, McLaren, Suzanne
- Authors: Snooks, Matthew Paul , McLaren, Suzanne
- Date: 2022
- Type: Journal article
- Relation: Death Studies Vol. 46, no. 8 (2022), p. 1954-1962
- Full Text:
- Reviewed:
- Description: Trans and gender diverse adults are at increased suicide risk. Optimism protects against suicide across multiple populations. Applying the Interpersonal-Psychological Theory of Suicide (IPTS), we examined both factors among 237 adults recruited via social media and online platforms, 79.3% of whom reported serious suicide ideation. Dispositional optimism predicted suicidal ideation and behaviors (SIB), but did not moderate the relationship between the IPTS components and SIB. After controlling for depressive symptoms, hormone therapy and gender-affirming surgery did not predict SIB. Promoting dispositional optimism within a therapeutic framework may reduce SIB in this vulnerable population.
- Authors: Snooks, Matthew Paul , McLaren, Suzanne
- Date: 2022
- Type: Journal article
- Relation: Death Studies Vol. 46, no. 8 (2022), p. 1954-1962
- Full Text:
- Reviewed:
- Description: Trans and gender diverse adults are at increased suicide risk. Optimism protects against suicide across multiple populations. Applying the Interpersonal-Psychological Theory of Suicide (IPTS), we examined both factors among 237 adults recruited via social media and online platforms, 79.3% of whom reported serious suicide ideation. Dispositional optimism predicted suicidal ideation and behaviors (SIB), but did not moderate the relationship between the IPTS components and SIB. After controlling for depressive symptoms, hormone therapy and gender-affirming surgery did not predict SIB. Promoting dispositional optimism within a therapeutic framework may reduce SIB in this vulnerable population.
Action research to implement an Indigenous health curriculum framework
- Wilson, Cath, Heinrich, Liesl, Heidari, Parvaneh, Adams, Karen
- Authors: Wilson, Cath , Heinrich, Liesl , Heidari, Parvaneh , Adams, Karen
- Date: 2020
- Type: Text , Journal article
- Relation: Nurse education today Vol. 91, no. (2020), p. 104464-104464
- Full Text: false
- Reviewed:
- Description: In recent decades Indigenous health curriculum frameworks have been developed, however, few studies about their implementation exist. This study aimed to employ critical theory and action research to understand how an Indigenous health curriculum framework could be applied and associated learning and teaching iteratively improved. Three action research cycles where conducted from 2017 to 2019. Student reaction (satisfaction and engagement) was collected via survey 2017–2019. Student learning was collated 2018–2019 via self-perception survey (knowledge, attitude, confidence, commitment) multi-choice questions (knowledge) and content analysis of apply and analyse activities (skill). The teaching team met annually to reflect on findings and plan enhancements to learning and teaching. Over 2017–2019 there was a pattern of improved student reaction and learning. Connecting this research to Faculty level committees led to widening success and improved sustainability of the practice. The online unit and workshop delivery were scalable, overcame a barrier of educator skill and confidence to teach this area, allowed for quality content control and provided data for analysis. Interestingly, learning gained from this unit matched that described as occurring from student placements in health settings with high numbers of Indigenous people. Student learning occurred across the Framework three levels (novice, intermediate and entry to practice) suggesting that the taxonomy of the Framework does not necessarily align with the reality of learning and teaching. Vertical implementation of the five learning domains would benefit from alignment with training evaluation models and validated assessment to understand learning that has occurred rather than the teaching that has been taught. In this study health profession accreditation bodies had driven the imperative for an Indigenous health program and curriculum. Research on Indigenous health learning and teaching relating to behaviour and results in workplaces is needed.
Attribute weighted Naive Bayes classifier using a local optimization
- Taheri, Sona, Yearwood, John, Mammadov, Musa, Seifollahi, Sattar
- Authors: Taheri, Sona , Yearwood, John , Mammadov, Musa , Seifollahi, Sattar
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing & Applications Vol.24, no.5 (2013), p.995-1002
- Full Text:
- Reviewed:
- Description: The Naive Bayes classifier is a popular classification technique for data mining and machine learning. It has been shown to be very effective on a variety of data classification problems. However, the strong assumption that all attributes are conditionally independent given the class is often violated in real-world applications. Numerous methods have been proposed in order to improve the performance of the Naive Bayes classifier by alleviating the attribute independence assumption. However, violation of the independence assumption can increase the expected error. Another alternative is assigning the weights for attributes. In this paper, we propose a novel attribute weighted Naive Bayes classifier by considering weights to the conditional probabilities. An objective function is modeled and taken into account, which is based on the structure of the Naive Bayes classifier and the attribute weights. The optimal weights are determined by a local optimization method using the quasisecant method. In the proposed approach, the Naive Bayes classifier is taken as a starting point. We report the results of numerical experiments on several real-world data sets in binary classification, which show the efficiency of the proposed method.
- Authors: Taheri, Sona , Yearwood, John , Mammadov, Musa , Seifollahi, Sattar
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing & Applications Vol.24, no.5 (2013), p.995-1002
- Full Text:
- Reviewed:
- Description: The Naive Bayes classifier is a popular classification technique for data mining and machine learning. It has been shown to be very effective on a variety of data classification problems. However, the strong assumption that all attributes are conditionally independent given the class is often violated in real-world applications. Numerous methods have been proposed in order to improve the performance of the Naive Bayes classifier by alleviating the attribute independence assumption. However, violation of the independence assumption can increase the expected error. Another alternative is assigning the weights for attributes. In this paper, we propose a novel attribute weighted Naive Bayes classifier by considering weights to the conditional probabilities. An objective function is modeled and taken into account, which is based on the structure of the Naive Bayes classifier and the attribute weights. The optimal weights are determined by a local optimization method using the quasisecant method. In the proposed approach, the Naive Bayes classifier is taken as a starting point. We report the results of numerical experiments on several real-world data sets in binary classification, which show the efficiency of the proposed method.
Smartphone sensor data for identifying and monitoring symptoms of mood disorders : a longitudinal observational study
- Braund, Taylor, Zin, May, Boonstra, Tjeerd, Wong, Quincy, Larsen, Mark, Christensen, Helen, Tillman, Gabriel, O'Dea, Bridianne
- Authors: Braund, Taylor , Zin, May , Boonstra, Tjeerd , Wong, Quincy , Larsen, Mark , Christensen, Helen , Tillman, Gabriel , O'Dea, Bridianne
- Date: 2022
- Type: Text , Journal article
- Relation: JMIR Mental Health Vol. 9, no. 5 (2022), p.
- Full Text:
- Reviewed:
- Description: Background: Mood disorders are burdensome illnesses that often go undetected and untreated. Sensor technologies within smartphones may provide an opportunity for identifying the early changes in circadian rhythm and social support/connectedness that signify the onset of a depressive or manic episode. Objective: Using smartphone sensor data, this study investigated the relationship between circadian rhythm, which was determined by GPS data, and symptoms of mental health among a clinical sample of adults diagnosed with major depressive disorder or bipolar disorder. Methods: A total of 121 participants were recruited from a clinical setting to take part in a 10-week observational study. Self-report questionnaires for mental health outcomes, social support, social connectedness, and quality of life were assessed at 6 time points throughout the study period. Participants consented to passively sharing their smartphone GPS data for the duration of the study. Circadian rhythm (ie, regularity of location changes in a 24-hour rhythm) was extracted from GPS mobility patterns at baseline. Results: Although we found no association between circadian rhythm and mental health functioning at baseline, there was a positive association between circadian rhythm and the size of participants' social support networks at baseline (r=0.22; P = .03; R2=0.049). In participants with bipolar disorder, circadian rhythm was associated with a change in anxiety from baseline; a higher circadian rhythm was associated with an increase in anxiety and a lower circadian rhythm was associated with a decrease in anxiety at time point 5. Conclusions: Circadian rhythm, which was extracted from smartphone GPS data, was associated with social support and predicted changes in anxiety in a clinical sample of adults with mood disorders. Larger studies are required for further validations. However, smartphone sensing may have the potential to monitor early symptoms of mood disorders. © Taylor A Braund, May The Zin, Tjeerd W Boonstra, Quincy J J Wong, Mark E Larsen, Helen Christensen, Gabriel Tillman, Bridianne O'Dea.
- Authors: Braund, Taylor , Zin, May , Boonstra, Tjeerd , Wong, Quincy , Larsen, Mark , Christensen, Helen , Tillman, Gabriel , O'Dea, Bridianne
- Date: 2022
- Type: Text , Journal article
- Relation: JMIR Mental Health Vol. 9, no. 5 (2022), p.
- Full Text:
- Reviewed:
- Description: Background: Mood disorders are burdensome illnesses that often go undetected and untreated. Sensor technologies within smartphones may provide an opportunity for identifying the early changes in circadian rhythm and social support/connectedness that signify the onset of a depressive or manic episode. Objective: Using smartphone sensor data, this study investigated the relationship between circadian rhythm, which was determined by GPS data, and symptoms of mental health among a clinical sample of adults diagnosed with major depressive disorder or bipolar disorder. Methods: A total of 121 participants were recruited from a clinical setting to take part in a 10-week observational study. Self-report questionnaires for mental health outcomes, social support, social connectedness, and quality of life were assessed at 6 time points throughout the study period. Participants consented to passively sharing their smartphone GPS data for the duration of the study. Circadian rhythm (ie, regularity of location changes in a 24-hour rhythm) was extracted from GPS mobility patterns at baseline. Results: Although we found no association between circadian rhythm and mental health functioning at baseline, there was a positive association between circadian rhythm and the size of participants' social support networks at baseline (r=0.22; P = .03; R2=0.049). In participants with bipolar disorder, circadian rhythm was associated with a change in anxiety from baseline; a higher circadian rhythm was associated with an increase in anxiety and a lower circadian rhythm was associated with a decrease in anxiety at time point 5. Conclusions: Circadian rhythm, which was extracted from smartphone GPS data, was associated with social support and predicted changes in anxiety in a clinical sample of adults with mood disorders. Larger studies are required for further validations. However, smartphone sensing may have the potential to monitor early symptoms of mood disorders. © Taylor A Braund, May The Zin, Tjeerd W Boonstra, Quincy J J Wong, Mark E Larsen, Helen Christensen, Gabriel Tillman, Bridianne O'Dea.
Soil moisture, organic carbon, and nitrogen content prediction with hyperspectral data using regression models
- Datta, Dristi, Paul, Manoranjan, Murshed, Manzur, Teng, Shyh Wei, Schmidtke, Leigh
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
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- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
- Authors: Datta, Dristi , Paul, Manoranjan , Murshed, Manzur , Teng, Shyh Wei , Schmidtke, Leigh
- Date: 2022
- Type: Text , Journal article
- Relation: Sensors (Basel, Switzerland) Vol. 22, no. 20 (2022), p.
- Full Text:
- Reviewed:
- Description: Soil moisture, soil organic carbon, and nitrogen content prediction are considered significant fields of study as they are directly related to plant health and food production. Direct estimation of these soil properties with traditional methods, for example, the oven-drying technique and chemical analysis, is a time and resource-consuming approach and can predict only smaller areas. With the significant development of remote sensing and hyperspectral (HS) imaging technologies, soil moisture, carbon, and nitrogen can be estimated over vast areas. This paper presents a generalized approach to predicting three different essential soil contents using a comprehensive study of various machine learning (ML) models by considering the dimensional reduction in feature spaces. In this study, we have used three popular benchmark HS datasets captured in Germany and Sweden. The efficacy of different ML algorithms is evaluated to predict soil content, and significant improvement is obtained when a specific range of bands is selected. The performance of ML models is further improved by applying principal component analysis (PCA), a dimensional reduction method that works with an unsupervised learning method. The effect of soil temperature on soil moisture prediction is evaluated in this study, and the results show that when the soil temperature is considered with the HS band, the soil moisture prediction accuracy does not improve. However, the combined effect of band selection and feature transformation using PCA significantly enhances the prediction accuracy for soil moisture, carbon, and nitrogen content. This study represents a comprehensive analysis of a wide range of established ML regression models using data preprocessing, effective band selection, and data dimension reduction and attempt to understand which feature combinations provide the best accuracy. The outcomes of several ML models are verified with validation techniques and the best- and worst-case scenarios in terms of soil content are noted. The proposed approach outperforms existing estimation techniques.
Wearable sensor technology to predict core body temperature : a systematic review
- Dolson, Conor, Harlow, Ethan, Phelan, Dermot, Gabbett, Tim, Gaal, Benjamin, McMellen, Christopher, Geletka, Benjamin, Calcei, Jacob, Voos, James, Seshadri, Dhruv
- Authors: Dolson, Conor , Harlow, Ethan , Phelan, Dermot , Gabbett, Tim , Gaal, Benjamin , McMellen, Christopher , Geletka, Benjamin , Calcei, Jacob , Voos, James , Seshadri, Dhruv
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Sensors Vol. 22, no. 19 (2022), p.
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- Description: Heat-related illnesses, which range from heat exhaustion to heatstroke, affect thousands of individuals worldwide every year and are characterized by extreme hyperthermia with the core body temperature (CBT) usually > 40 °C, decline in physical and athletic performance, CNS dysfunction, and, eventually, multiorgan failure. The measurement of CBT has been shown to predict heat-related illness and its severity, but the current measurement methods are not practical for use in high acuity and high motion settings due to their invasive and obstructive nature or excessive costs. Noninvasive predictions of CBT using wearable technology and predictive algorithms offer the potential for continuous CBT monitoring and early intervention to prevent HRI in athletic, military, and intense work environments. Thus far, there has been a lack of peer-reviewed literature assessing the efficacy of wearable devices and predictive analytics to predict CBT to mitigate heat-related illness. This systematic review identified 20 studies representing a total of 25 distinct algorithms to predict the core body temperature using wearable technology. While a high accuracy in prediction was noted, with 17 out of 18 algorithms meeting the clinical validity standards. few algorithms incorporated individual and environmental data into their core body temperature prediction algorithms, despite the known impact of individual health and situational and environmental factors on CBT. Robust machine learning methods offer the ability to develop more accurate, reliable, and personalized CBT prediction algorithms using wearable devices by including additional data on user characteristics, workout intensity, and the surrounding environment. The integration and interoperability of CBT prediction algorithms with existing heat-related illness prevention and treatment tools, including heat indices such as the WBGT, athlete management systems, and electronic medical records, will further prevent HRI and increase the availability and speed of data access during critical heat events, improving the clinical decision-making process for athletic trainers and physicians, sports scientists, employers, and military officers. © 2022 by the authors.
- Authors: Dolson, Conor , Harlow, Ethan , Phelan, Dermot , Gabbett, Tim , Gaal, Benjamin , McMellen, Christopher , Geletka, Benjamin , Calcei, Jacob , Voos, James , Seshadri, Dhruv
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Sensors Vol. 22, no. 19 (2022), p.
- Full Text:
- Reviewed:
- Description: Heat-related illnesses, which range from heat exhaustion to heatstroke, affect thousands of individuals worldwide every year and are characterized by extreme hyperthermia with the core body temperature (CBT) usually > 40 °C, decline in physical and athletic performance, CNS dysfunction, and, eventually, multiorgan failure. The measurement of CBT has been shown to predict heat-related illness and its severity, but the current measurement methods are not practical for use in high acuity and high motion settings due to their invasive and obstructive nature or excessive costs. Noninvasive predictions of CBT using wearable technology and predictive algorithms offer the potential for continuous CBT monitoring and early intervention to prevent HRI in athletic, military, and intense work environments. Thus far, there has been a lack of peer-reviewed literature assessing the efficacy of wearable devices and predictive analytics to predict CBT to mitigate heat-related illness. This systematic review identified 20 studies representing a total of 25 distinct algorithms to predict the core body temperature using wearable technology. While a high accuracy in prediction was noted, with 17 out of 18 algorithms meeting the clinical validity standards. few algorithms incorporated individual and environmental data into their core body temperature prediction algorithms, despite the known impact of individual health and situational and environmental factors on CBT. Robust machine learning methods offer the ability to develop more accurate, reliable, and personalized CBT prediction algorithms using wearable devices by including additional data on user characteristics, workout intensity, and the surrounding environment. The integration and interoperability of CBT prediction algorithms with existing heat-related illness prevention and treatment tools, including heat indices such as the WBGT, athlete management systems, and electronic medical records, will further prevent HRI and increase the availability and speed of data access during critical heat events, improving the clinical decision-making process for athletic trainers and physicians, sports scientists, employers, and military officers. © 2022 by the authors.
A scoping review of community-based adult suicide prevention initiatives in rural and regional australia
- Dabkowski, Elissa, Porter, Joanne, Barbagallo, Michael, Prokopiv, Valerie, Jackson, Megan
- Authors: Dabkowski, Elissa , Porter, Joanne , Barbagallo, Michael , Prokopiv, Valerie , Jackson, Megan
- Date: 2022
- Type: Text , Journal article , Review
- Relation: International Journal of Environmental Research and Public Health Vol. 19, no. 12 (2022), p.
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- Description: The need for continued research into suicide prevention strategies is undeniable, with high global statistics demonstrating the urgency of this public health issue. In Australia, approximately 3000 people end their lives each year, with those living in rural and regional areas identified as having a higher risk of dying by suicide. Due to decreased access and support services in these areas, community-based suicide prevention initiatives provide opportunities to educate and support local communities. A scoping review was conducted to explore the literature pertaining to such programs in rural and/or regional communities in Australia. This review follows the five-stage Arksey and O’Malley (2005) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Nine databases were searched, from which studies were considered eligible if suicide prevention programs were community-based and catered for adults (aged
- Authors: Dabkowski, Elissa , Porter, Joanne , Barbagallo, Michael , Prokopiv, Valerie , Jackson, Megan
- Date: 2022
- Type: Text , Journal article , Review
- Relation: International Journal of Environmental Research and Public Health Vol. 19, no. 12 (2022), p.
- Full Text:
- Reviewed:
- Description: The need for continued research into suicide prevention strategies is undeniable, with high global statistics demonstrating the urgency of this public health issue. In Australia, approximately 3000 people end their lives each year, with those living in rural and regional areas identified as having a higher risk of dying by suicide. Due to decreased access and support services in these areas, community-based suicide prevention initiatives provide opportunities to educate and support local communities. A scoping review was conducted to explore the literature pertaining to such programs in rural and/or regional communities in Australia. This review follows the five-stage Arksey and O’Malley (2005) framework and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Nine databases were searched, from which studies were considered eligible if suicide prevention programs were community-based and catered for adults (aged
Knock down of TIMP-2 by siRNA and CRISPR/Cas9 mediates diverse cellular reprogramming of metastasis and chemosensitivity in ovarian cancer
- Escalona, Ruth, Chu, Simon, Kadife, Elif, Kelly, Jason, Kannourakis, George, Findlay, Jock, Ahmed, Nuzhat
- Authors: Escalona, Ruth , Chu, Simon , Kadife, Elif , Kelly, Jason , Kannourakis, George , Findlay, Jock , Ahmed, Nuzhat
- Date: 2022
- Type: Text , Journal article
- Relation: Cancer Cell International Vol. 22, no. 1 (2022), p.
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- Description: Background: The endogenous tissue inhibitor of metalloproteinase-2 (TIMP-2), through its homeostatic action on certain metalloproteinases, plays a vital role in remodelling extracellular matrix (ECM) to facilitate cancer progression. This study investigated the role of TIMP-2 in an ovarian cancer cell line in which the expression of TIMP-2 was reduced by either siRNA or CRISPR/Cas9. Methods: OVCAR5 cells were transiently and stably transfected with either single or pooled TIMP-2 siRNAs (T2-KD cells) or by CRISPR/Cas9 under the influence of two distinct guide RNAs (gRNA1 and gRNA2 cell lines). The expression of different genes was analysed at the mRNA level by quantitative real time PCR (qRT-PCR) and at the protein level by immunofluorescence (IF) and western blot. Proliferation of cells was investigated by 5-Ethynyl-2′-deoxyuridine (EdU) assay or staining with Ki67. Cell migration/invasion was determined by xCELLigence. Cell growth in vitro was determined by 3D spheroid cultures and in vivo by a mouse xenograft model. Results: Approximately 70–90% knock down of TIMP-2 expression were confirmed in T2-KD, gRNA1 and gRNA2 OVCAR5 ovarian cancer cells at the protein level. T2-KD, gRNA1 and gRNA2 cells exhibited a significant downregulation of MMP-2 expression, but concurrently a significant upregulation in the expression of membrane bound MMP-14 compared to control and parental cells. Enhanced proliferation and invasion were exhibited in all TIMP-2 knocked down cells but differences in sensitivity to paclitaxel (PTX) treatment were observed, with T2-KD cells and gRNA2 cell line being sensitive, while the gRNA1 cell line was resistant to PTX treatment. In addition, significant differences in the growth of gRNA1 and gRNA2 cell lines were observed in in vitro 3D cultures as well as in an in vivo mouse xenograft model. Conclusions: Our results suggest that the inhibition of TIMP-2 by siRNA and CRISPR/Cas-9 modulate the expression of MMP-2 and MMP-14 and reprogram ovarian cancer cells to facilitate proliferation and invasion. Distinct disparities in in vitro chemosensitivity and growth in 3D culture, and differences in tumour burden and invasion to proximal organs in a mouse model imply that selective suppression of TIMP-2 expression by siRNA or CRISPR/Cas-9 alters important aspects of metastasis and chemosensitivity in ovarian cancer. © 2022, The Author(s).
- Authors: Escalona, Ruth , Chu, Simon , Kadife, Elif , Kelly, Jason , Kannourakis, George , Findlay, Jock , Ahmed, Nuzhat
- Date: 2022
- Type: Text , Journal article
- Relation: Cancer Cell International Vol. 22, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: Background: The endogenous tissue inhibitor of metalloproteinase-2 (TIMP-2), through its homeostatic action on certain metalloproteinases, plays a vital role in remodelling extracellular matrix (ECM) to facilitate cancer progression. This study investigated the role of TIMP-2 in an ovarian cancer cell line in which the expression of TIMP-2 was reduced by either siRNA or CRISPR/Cas9. Methods: OVCAR5 cells were transiently and stably transfected with either single or pooled TIMP-2 siRNAs (T2-KD cells) or by CRISPR/Cas9 under the influence of two distinct guide RNAs (gRNA1 and gRNA2 cell lines). The expression of different genes was analysed at the mRNA level by quantitative real time PCR (qRT-PCR) and at the protein level by immunofluorescence (IF) and western blot. Proliferation of cells was investigated by 5-Ethynyl-2′-deoxyuridine (EdU) assay or staining with Ki67. Cell migration/invasion was determined by xCELLigence. Cell growth in vitro was determined by 3D spheroid cultures and in vivo by a mouse xenograft model. Results: Approximately 70–90% knock down of TIMP-2 expression were confirmed in T2-KD, gRNA1 and gRNA2 OVCAR5 ovarian cancer cells at the protein level. T2-KD, gRNA1 and gRNA2 cells exhibited a significant downregulation of MMP-2 expression, but concurrently a significant upregulation in the expression of membrane bound MMP-14 compared to control and parental cells. Enhanced proliferation and invasion were exhibited in all TIMP-2 knocked down cells but differences in sensitivity to paclitaxel (PTX) treatment were observed, with T2-KD cells and gRNA2 cell line being sensitive, while the gRNA1 cell line was resistant to PTX treatment. In addition, significant differences in the growth of gRNA1 and gRNA2 cell lines were observed in in vitro 3D cultures as well as in an in vivo mouse xenograft model. Conclusions: Our results suggest that the inhibition of TIMP-2 by siRNA and CRISPR/Cas-9 modulate the expression of MMP-2 and MMP-14 and reprogram ovarian cancer cells to facilitate proliferation and invasion. Distinct disparities in in vitro chemosensitivity and growth in 3D culture, and differences in tumour burden and invasion to proximal organs in a mouse model imply that selective suppression of TIMP-2 expression by siRNA or CRISPR/Cas-9 alters important aspects of metastasis and chemosensitivity in ovarian cancer. © 2022, The Author(s).
A probabilistic reverse power flows scenario analysis framework
- Demazy, Antonin, Alpcan, Tansu, Mareels, Iven
- Authors: Demazy, Antonin , Alpcan, Tansu , Mareels, Iven
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE open access journal of power and energy Vol. 7, no. (2020), p. 524-532
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- Description: Distributed Energy Resources (DER), mainly residential solar PV, are embedded deep within the power distribution network and their adoption is fast increasing globally. As more customers participate, these power generation units cause Reverse Power Flow (RPF) at the edge of the grid, directed upstream into the network, thus violating one of the traditional design principles for power networks. The effects of a single residential solar PV system is negligible, but as the adoption by end-consumers increases to high percentages, the aggregated effect is no longer negligible and must be considered in the design and configuration of power networks. This article proposes a framework that helps to predict the RPF intensity probability for any given scenario of DER penetration within the distribution network. The considered scenario parameters are the number and location of each residential DERs, their capacity and the daily net-load profiles. Classical simulation-based approach for this is not scalable as it relies on solving the load-flow equations for each individual scenario. The framework leverages machine learning techniques to make fast and precise RPF prediction within the network for each scenario. The framework enables the Distribution Network Service Providers (DNSPs) to assess DERs penetration scenarios at a granular level, derive and localise the RPF risks and assess the respective impacts on the installed assets for network planning purpose. The framework is illustrated with scenario analysis conducted on an IEEE 123 bus system and OpenDSS and shown that it can lead to multiple orders of magnitude savings in computational time while retaining an accuracy of 94% or above compared to classical brute force simulations.
- Authors: Demazy, Antonin , Alpcan, Tansu , Mareels, Iven
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE open access journal of power and energy Vol. 7, no. (2020), p. 524-532
- Full Text:
- Reviewed:
- Description: Distributed Energy Resources (DER), mainly residential solar PV, are embedded deep within the power distribution network and their adoption is fast increasing globally. As more customers participate, these power generation units cause Reverse Power Flow (RPF) at the edge of the grid, directed upstream into the network, thus violating one of the traditional design principles for power networks. The effects of a single residential solar PV system is negligible, but as the adoption by end-consumers increases to high percentages, the aggregated effect is no longer negligible and must be considered in the design and configuration of power networks. This article proposes a framework that helps to predict the RPF intensity probability for any given scenario of DER penetration within the distribution network. The considered scenario parameters are the number and location of each residential DERs, their capacity and the daily net-load profiles. Classical simulation-based approach for this is not scalable as it relies on solving the load-flow equations for each individual scenario. The framework leverages machine learning techniques to make fast and precise RPF prediction within the network for each scenario. The framework enables the Distribution Network Service Providers (DNSPs) to assess DERs penetration scenarios at a granular level, derive and localise the RPF risks and assess the respective impacts on the installed assets for network planning purpose. The framework is illustrated with scenario analysis conducted on an IEEE 123 bus system and OpenDSS and shown that it can lead to multiple orders of magnitude savings in computational time while retaining an accuracy of 94% or above compared to classical brute force simulations.
Photosynthetic activity and water use efficiency of Salvia verbenaca L. under elevated CO2 and water‐deficit conditions
- Javaid, Muhammad Mansoor, Florentine, Singarayer, Ashraf, Muhammad, Mahmood, Athar, Sattar, Abdul, Wasaya, Allah, Li, Feng‐Min
- Authors: Javaid, Muhammad Mansoor , Florentine, Singarayer , Ashraf, Muhammad , Mahmood, Athar , Sattar, Abdul , Wasaya, Allah , Li, Feng‐Min
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of agronomy and crop science Vol. 208, no. 4 (2022), p. 536-551
- Full Text:
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- Description: Investigating the combined effects of elevated CO2 concentration and water‐deficit on weed plants is crucial to gaining a thorough understanding of plant performance and modifying agricultural processes under changing climate conditions. This study examined the effect of elevated CO2 concentration and water‐deficit conditions on leaf gas exchange, water use efficiency, carboxylation efficiency and the photosystem II (PSII) activity of two Salvia verbenaca L., varieties. These varieties were grown under two CO2 concentrations (ambient conditions of 400 ppm and elevated conditions of 700 ppm) and two water regimes (well‐watered [100% field capacity] and water‐deficit conditions [60% field capacity]) in laboratory growth chambers. For 12 days, at 2‐day intervals, (i) leaf gas exchange parameters (photosynthesis rate, stomatal conductance, transpiration rate (E) and intercellular CO2 concentration (Ci)), (ii) water use efficiency (WUE), (iii) intrinsic water use efficiency (IWUE), (iv) instantaneous carboxylation efficiency and (v) PSII activity (fluorescence, quantum yield of PSII, photochemical efficiency of PSII, photochemical quenching and photosynthetic electron transport) were measured. Water‐deficit conditions had negative effects on studied parameters of both varieties, whereas elevated CO2 concentration had positive effects on the gas exchange, water use efficiency and PSII activity of both. Salvia verbenaca varieties grown under water‐deficit conditions from Day 0 to Day 5 showed a partial recovery in most of the parameters when the resumption of the well‐watered regime was reinstituted on Day 6. Salvia verbenaca varieties grown under water‐deficit conditions were re‐watered on day 6 and indicated a partial recovery in all the parameters. A comparison of the two varieties showed that var. vernalis recorded higher values of gas exchange, quantum yield of PSII and photochemical efficiency of PSII than var. verbenaca, but the water use efficiency of var. verbenaca was higher than that of var. vernalis. These differences serve to illustrate the complexity of such studies and suggest that a detailed understanding of the nature of weed infestations is essential if optimum management control is to be practiced. Elevated CO2 concentration mitigated the adverse effects of water‐deficit conditions and thereby enhanced the adaptive mechanism of this weed by improving its water use efficiency. It is thus likely that S. verbenaca has the potential to take advantage of climate change by increasing its relative competitiveness with other plants in drought‐prone areas, suggesting that it could significantly expand its invasive range under such conditions.
- Authors: Javaid, Muhammad Mansoor , Florentine, Singarayer , Ashraf, Muhammad , Mahmood, Athar , Sattar, Abdul , Wasaya, Allah , Li, Feng‐Min
- Date: 2022
- Type: Text , Journal article
- Relation: Journal of agronomy and crop science Vol. 208, no. 4 (2022), p. 536-551
- Full Text:
- Reviewed:
- Description: Investigating the combined effects of elevated CO2 concentration and water‐deficit on weed plants is crucial to gaining a thorough understanding of plant performance and modifying agricultural processes under changing climate conditions. This study examined the effect of elevated CO2 concentration and water‐deficit conditions on leaf gas exchange, water use efficiency, carboxylation efficiency and the photosystem II (PSII) activity of two Salvia verbenaca L., varieties. These varieties were grown under two CO2 concentrations (ambient conditions of 400 ppm and elevated conditions of 700 ppm) and two water regimes (well‐watered [100% field capacity] and water‐deficit conditions [60% field capacity]) in laboratory growth chambers. For 12 days, at 2‐day intervals, (i) leaf gas exchange parameters (photosynthesis rate, stomatal conductance, transpiration rate (E) and intercellular CO2 concentration (Ci)), (ii) water use efficiency (WUE), (iii) intrinsic water use efficiency (IWUE), (iv) instantaneous carboxylation efficiency and (v) PSII activity (fluorescence, quantum yield of PSII, photochemical efficiency of PSII, photochemical quenching and photosynthetic electron transport) were measured. Water‐deficit conditions had negative effects on studied parameters of both varieties, whereas elevated CO2 concentration had positive effects on the gas exchange, water use efficiency and PSII activity of both. Salvia verbenaca varieties grown under water‐deficit conditions from Day 0 to Day 5 showed a partial recovery in most of the parameters when the resumption of the well‐watered regime was reinstituted on Day 6. Salvia verbenaca varieties grown under water‐deficit conditions were re‐watered on day 6 and indicated a partial recovery in all the parameters. A comparison of the two varieties showed that var. vernalis recorded higher values of gas exchange, quantum yield of PSII and photochemical efficiency of PSII than var. verbenaca, but the water use efficiency of var. verbenaca was higher than that of var. vernalis. These differences serve to illustrate the complexity of such studies and suggest that a detailed understanding of the nature of weed infestations is essential if optimum management control is to be practiced. Elevated CO2 concentration mitigated the adverse effects of water‐deficit conditions and thereby enhanced the adaptive mechanism of this weed by improving its water use efficiency. It is thus likely that S. verbenaca has the potential to take advantage of climate change by increasing its relative competitiveness with other plants in drought‐prone areas, suggesting that it could significantly expand its invasive range under such conditions.