This paper proposes an active learning framework to address a longstanding research question: how much data is needed for data-driven power electronics designs. The proposed method can automatically explore the optimal scenario using minimal data while achieving the desired accuracy. To demonstrate the proposed method, the reliability-oriented design (ROD) for a traction converter is used as a case study. While traditional methods achieving ROD necessitate extensive simulation and experiments, the proposed method uses surrogate models and active learning to achieve the desired accuracy with the minimal computational requirements. The performance of the proposed method has been verified by experimental measurements. The computation cost is reduced by 62.5% compared to the traditional ROD method.

A document by Marta Antunes. Click on the document to view its contents.

This review asks how variation in genome architecture impacts speciation across the plant and animal kingdoms. First, we briefly summarize what is known about speciation in these groups; importantly, the diversification rate of plants is about twice that of animals, and species barriers in plants appear to arise at an earlier stage of divergence. Next, we discuss several of the major differences in how plant and animal genomes evolve, and how they may impact the evolution of reproductive barriers and potentially speciation rates. Key differences include (1) the higher frequency of whole genome duplications and more rapid loss of synteny in plants; (2) the higher incidence and greater divergence of sex chromosomes in animals; (3) higher rates of sequence change, but slower rates of structural evolution, in animal relative to plant mitochondrial genomes; and (4) the higher abundance of transposable elements in plant genomes. Overall, we find the genomes of plants typically diverge much more rapidly in structure than those of animals (although there are many exceptions), which likely contributes to the more rapid emergence reproductive barriers in plants. However, we also found that comparisons of genome evolution between the kingdoms are hampered by inconsistency in the methods employed, and in the metrics used to report on rates of structural evolution. Another theme from our review is the huge variation in genome architecture within each kingdom. While this variation complicates broad generalizations, it also enables powerful comparative analyses that link differences in genome architecture to patterns and processes of speciation.

Urbanization is a major driver of environmental change that shapes the evolution of populations. However, the effects of environmental differences among cities on neutral and adaptive evolution remains poorly understood. We investigated evolutionary patterns in Impatiens capensis, a native wildflower that can be found in many cities in eastern North America. We used genotype-by-sequencing to evaluate genetic variation, contemporary demographic history, and local adaptation across 10 cities in Ontario, Canada. Urbanization and city size shaped the amount of genetic diversity present at sites and contributed to fine-scale spatial genetic structure. We identified a signal of repeated population bottlenecks occurring across all cities that corresponded to the timing of rapid urban expansion in the region. City size was an important environmental predictor of local adaptation, highlighting the role of cities in driving the adaptive evolution of populations. Our findings provide one of the first examples of parallel demographic shifts in response to urbanization in plants and offer insights into why I. capensis may be particularly resilient to urbanization. Taken together, our results emphasize the role that urban parks can play in maintaining genetic diversity and facilitating adaptation, suggesting that prioritizing greenspace conservation is critical for maintain urban biodiversity.

Within the same species of eusocial insects, individuals of different castes typically display widely different life-history traits: sterile workers live for a few months, while queens can live for decades. Aging theories emphasise the importance of metabolism and oxidative stress in explaining longevity, with mitochondrial bioenergetics standing at the crossroads of energy and reactive oxygen species production. The study of mitochondrial functioning is therefore of great relevance in determining the nature of the mechanisms that explain the contrasting longevities between insect social castes. We addressed this question in the eusocial black garden ant Lasius niger. Our findings reveal that caste differences in mitochondrial bioenergetics and the oxidative balance only partially align with oxidative stress theory predictions. Long-lived queens display lower metabolic rates and mitochondrial density, yet maintaining higher cellular energy availability, as reflected by a high adenylate energy charge (AEC). This may result from enhanced mitochondrial maintenance processes and specific recourse to the purine salvage pathway, promoting ATP availability while limiting oxidative cost. This perspective highlights the unique bioenergetic adaptations that may be behind the queens’ remarkable lifespan.

1) Baccharis × intermedia (Asteraceae), found in central Chile, is a naturally occurring hybrid derived from the parent species B. macraei and B. linearis. It represents an extraordinary example of admixture with additive plant chemistry; however, the genetic structure of the hybrid complex and its evolution are still unclear. 2) Intensive field sampling and Genotyping-by-Sequencing (GBS) was used to clarify the structure of the B. × intermedia hybrid complex. In addition, B. vernalis, another species that resembles the morphology of B. macraei, was subjected to analysis to ascertain its role in the hybridization process. 3) A total of 3724 SNPs and 378 individuals were analyzed using clustering, PCA, Treemix, Patterson’s D- and f-statistics. Furthermore, other genetic indicators, such as levels of heterozygosity, Tajima’s D and nucleotide diversity (π) also provided further insight into the hybrid complex. 4) Our results show that B. × intermedia consists of mainly F1-hybrids with 18 % backcrossing to both parental species. B. vernalis was not involved into recent hybridization with B. macraei and B. linearis. Additionally, a recent introgression into the Quintay population of B. macraei from B. linearis was detected during the analysis. 5) Altogether, our extensive field sampling combined with genetic analyses have provided deeper insights into the genetic structure and evolution of the B. × intermedia hybrid complex in Chile.

Transport of solute species under unsaturated conditions, where multiple immiscible fluids coexist, is a common occurrence in various environmental and engineering applications within subsurface porous media. In this study, we integrate microfluidic experiments and direct simulation to analyze the effect of successive drainage-imbibition cycles on solute transport, a process that is not yet well understood in the context of unsaturated porous media. The spatial distribution of phases is found by experiments, and the transport process is modeled by high-fidelity direct numerical simulation, remarkably reducing computational costs and enabling individual investigation of injection cycles. We show that while the volume of percolating pathways of carrier fluid (where transport happens) stabilizes at an approximately constant level after a few cycles, the interplay between drainage-imbibition cycles and hysteresis phenomenon enhances solute spreading from cycle to cycle. Through the analysis of mobile and immobile pathways, we demonstrate that the effect of drainage-imbibition cycles on the mixing of solute species becomes negligible after one-two cycles. These results advance our understanding of the complex dynamics of unsaturated transport, providing new insights into the impacts of cyclic variations in soil water content, a critical environmental challenge.

This research work presents an advanced optimization framework for integrating Electric Vehicles (EVs) with microgrid (MG) operations, utilizing Combined Heat and Power (CHP) technologies, renewable energy sources (RES), and Battery Energy Storage Systems (BESS). Despite the benefits of CHP technologies in providing both electricity and heat, their potential in EV Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) operations remains largely unexplored. To bridge this gap, this paper proposes a hybrid electric-thermal load strategy for CHP systems that autonomously toggles between electric and thermal load-following modes, thereby maximizing environmental and economic advantages. The optimization process is augmented by the Zebra Optimization Algorithm (ZOA), which draws inspiration from zebra social behavior to effectively balance exploration and exploitation within the complex, stochastic MG environment. To further enhance solution quality and address uncertainties in RES generation, EV charging/discharging patterns, and load consumption, the Differential Evolution (DE) algorithm is introduced. The framework is validated through three case studies: the first focused solely on CHP technologies, the second on a combination of CHP and RES, and the third integrating BESS to facilitate V2G operations. The proposed hybrid ZOA-DE approach achieves a notable reduction in operational costs, decreasing by up to 25%, and CO 2 emissions, which are reduced by approximately 30%. This comprehensive approach provides a sustainable energy management solution for EVs within MGs.

jabbrv-ltwa-all.ldf jabbrv-ltwa-en.ldf This article outlines a strategy to enhance voltage profiles in power grids by managing reactive power more efficiently through the integration of HRESin a smart grid. It highlights the challenge of voltage fluctuation in power grids owing to the erratic nature of RES like wind turbines and photovoltaic systems, which leads to an unstable voltage profile across the grid. To address these voltage fluctuations, this article proposes DSTATCOM, a reactive power compensation device to supply the necessary var to the grid. DSTATCOM helps in maintaining voltage stability, ensuring that the active power flow increases by reducing the voltage drop reliably. As a result, the overall voltage profile across the power grid improves. The core of the proposed solution involves combining Convolutional Neural Networks (CNN) with Bidirectional Long Short-Term Memory (BiLSTM) to control and optimize the performance of DSTATCOM. These advanced Artificial Intelligence (AI) techniques help manage reactive power dynamically, enhancing both the performance of DSTATCOM and the voltage profile in the grid. CNNs are used for feature extraction, while BiLSTM aids in capturing temporal dependencies in the grid’s power behavior, making this approach effective for real-time voltage regulation in smart grid environments. Also, an adaptive Parrot Optimizer (APO) is employed to fine-tune the weights of the CNN-BiLSTM network. Thus, the established system enhances voltage profile, minimizes power loss, and ensures grid stability by regulating reactive power balance. The MATLAB/Simulink environment was used to implement the proposed approach, and its performance was evaluated under three distinct scenarios.

Increasing Electric Vehicle (EV) possession has resulted in an abundance of Charging Stations (CSs), which nurtures load demands and causes grid interruptions in peak hours. By using an effective Energy Management Strategy (EMS), microgrids provide a workable solution to these problems with the electrical distribution infrastructure. The goal of this research is to avoid storage device degradation too soon and to guarantee a steady power supply regardless of generation differences using a hybrid optimization technique. For Micro Grid (MG) with EV operation, a CS system based on Fuzzy integrated with Dwarf Mongoose based Zebra Optimization tuned Proportional Integral controller (DMZO-PI+Fuzzy) is advised to establish dependable power balancing. The introduced DC MG, which combines Renewable Energy Sources (RES) as sources, is built, evaluated, and validated through simulations using MATLAB simulink. The proposed hybrid optimization strategy outperforms the popular traditional algorithms on Power Management (PM) with respect to convergence speed and steadiness. The enhanced response characteristics show that DMZO-PI+Fuzzy maximizes the use of energy resources by managing power in the DC microgrid in an effective manner. The significance of the approach’s configuration for economical PM in DC MGs is highlighted using these results.

A challenge for rover systems is identifying wheel slippage, especially on deformable terrain such as sand or regolith. There are several approaches used to identify slippage, but, there is still a lack of tools for rovers to reduce or mitigate its effects. This paper investigates adaptive wheel grouser lengths based on virtual slippage measurements. We conduct two sets of experiments, the first evaluating the effect of uniformly extending grousers and the second on extending a section of grousers. Results from these experiments demonstrate that the ability to adaptively change the length of grouser based on virtual slippage measurements can significantly reduce slippage, offering potential improvements in rover traction and mobility. This paper demonstrates the concept of adaptive wheel mechanisms and paves the way for future development into adaptive wheel mechanisms. Future work will focus on adaptive wheel design and control strategies for multi-wheel rovers and further testing in real-world scenarios.

Aim To evaluate and summarize the evidence that cognitive behavioral therapy for insomnia improves sleep quality in patients with chronic insomnia and provide reference for clinical practice. Design The PIPOST model from the Center for Evidence-Based Nursing at Fudan University was used to retrieve evidence and integrate it through structured evidence-based questions. Methods Current literatures were systematically searched for the best evidence that cognitive behavioral therapy for insomnia improves sleep quality in patients with chronic insomniaLiterature types included clinical guidelines,best practice information sheets, expert consensuses, systematic reviews, evidence summaries and cohort studies. Data Sources UpToDate,BMJ Best Practice,Joanna Briggs Institute,Guidelines International Network,National Institute for Health and Care Excellence,Registered Nurses Association of Ontario,Scottish Intercollegiate Guidelines Network,the Cochrane Library, Embase,PubMed, Sinomed,Web of Science,DynaMed,MEDLINE, CNKI, WanFang database, Chinese Medical Journal Full-text Database,The search period was from build to December 10, 2024 Results A total of 28 papers were included,including 5 guidelines,3 expert consensus papers,12 systematic evaluations, and 8 Meta-analyses, and the overall quality of the included papers was high.Forty-one pieces of best evidence were summarized in terms of diagnostic criteria for sleep disorders,assessment conditions, timing of initiation of multicomponent cognitive behavioral therapy for sleep (CBT-I), treatment format,composition of components,assessment metrics,assessment tools, symptom improvement metrics, comparisons of implementers, and adverse effects. Conclusion The study summarizes the best evidence that CBT-I improves sleep quality in patients with chronic insomnia and recommends that clinical staff should fully assess the patient’s overall condition before implementing the therapy and develop a personalized CBT-I treatment plan for the patient based on their assessment.

A document by Rowena Cooper. Click on the document to view its contents.

Optineurin (OPTN) is a novel protein discovered by yeast two-hybrid screening. It has been linked to neurodegenerative illnesses such as glaucoma and amyotrophic lateral sclerosis (ALS) via its involvement in numerous signaling pathways. Research shows that this protein regulates the NF-κB, TBK1, and interferon signaling pathways, contributing to the body’s innate immune response. In this review, we consolidate recent research findings, define the role of OPTN in the innate immune response, outline its regulatory interactions with major innate immunity components, and address OPTN’s possible involvement in illness via innate immune processes.

Acquired immunodeficiency syndrome (AIDS), resulting from infection with the human immunodeficiency virus (HIV), remains a major global health threat. Multiple studies have demonstrated the presence of anti-HIV IgG in the urine of HIV-positive individuals without evident renal pathology. Despite the availability of HIV urine test kits and initial investigations into the origins of anti-HIV antibodies in urine, the underlying mechanism remains inadequately defined. This paper reviews the literature on IgG production pathways within humoral and mucosal immunity, non-B lymphocytes, and relevant transport receptors, such as the neonatal Fc receptor (FcRn), aiming to provide insights into the mechanism driving antibody excretion in urine.

AgroDetect Smart Plant Pathology is a Web-App-based solution and an innovative system that utilizes image processing techniques to analyze plant diseases based on leaf images. This technology aims to revolutionize agriculture by offering a rapid and precise method of identifying and managing plant diseases, ultimately improving crop yield and reducing losses. The Convolutional Neural Network (CNN) model, augmented with Rectified Linear Unit (ReLU) activation functions, was employed to discern the condition of plants by analyzing leaf images. The accuracy of the performance of the designed models is evaluated using four categories of plant leaves from the PlantVillage database. The average accuracy of the designed models is around 97% and is further compared with state-of-art works and also designed a web application using the Streamlit Python library for user interaction with minimal effort.

A document by Jordyn Hollander. Click on the document to view its contents.

ABSTRACT:   Background: Pegaspargase (PEG-ASP) and calaspargase pegol (CAL-PEG) are long acting asparaginase formulations used to treat acute leukemia. As of December 2022, CAL-PEG became the standard formulation for pediatric patients less than 22 years of age. The objective of this study was to compare real-world safety and efficacy of the two formulations in pediatric patients at a single institution.       Procedure: A three-year retrospective evaluation of PEG-ASP and CAL-PEG utilization was completed. Patients treated at stand-alone children’s hospital for acute leukemia who received at least one dose of long acting asparaginase therapy were included. Incidence and severity of hypersensitivity reactions, silent inactivation, thromboembolism, bleeding, pancreatitis, hepatotoxicity, and hypertriglyceridemia were collected.   Results: A total of 103 patients were included, of whom 50 received CAL-PEG and 58 received PEG-ASP. In the CAL-PEG group, 10 patients experienced a symptomatic hypersensitivity reaction, compared to six patients in the PEG-ASP group (20.0% vs. 10.3%; p = 0.16). Eight patients receiving CAL-PEG had a silent inactivation while compared to three patients receiving PEG-ASP (16.0% vs. 5.2%; p = 0.18). There was a higher rate of hyperbilirubinemia noted with PEG-ASP compared to CAL-PEG (58.6% vs. 34.0%; p = 0.01). Other adverse effects, including hypertriglyceridemia, thrombosis, bleeding, transaminitis, and pancreatitis were comparable between the two groups.     Conclusions: There were no significant differences found between CAL-PEG and PEG-ASP in terms of hypersensitivity reactions and silent inactivation. Most other adverse effects associated with asparaginase therapy were also similar between the two groups. Monitoring and preventative measures should continue for patients to help prevent the adverse effects associated with CAL-PEG.

Background: Suicide rates among Iraqis, is rising, with many analysts attributing it to political instability, exposure to trauma, economic hopelessness, social stigma surrounding mental health as well as cultural and societal pressures. However, the prevalence of suicidal ideation and associated risk factors in Iraqi youth is unknown, requiring urgent attention and effective public health initiatives. Thus, the aim of the study was to explore rates of suicidal ideation and associated risk factors among female secondary school students in Baghdad, Iraq. Method: A cross-sectional study was conducted, utilising quantitative survey data collected in four girls’ secondary schools across Baghdad, Iraq, between August and December 2023. The survey consisted of questions relating to their demographic characteristics (age, gender, school) and a series of measures pertaining to participants’ levels of suicidal ideation, as well as factors commonly identified in the literature as predictors of suicide. Results: Four-hundred and two female participants took part. Participants were aged between 13 and 17 years ( M = 15.50; SD = 1.22). 11.3% of the students scored in the at-risk range for suicidal behaviour and only 20.1% (n=91) said they had not had some thoughts of suicide in the previous two weeks. Previous diagnoses of anxiety, high levels of depression and hopelessness, and poor quality of life were significant risk factors for suicidal ideation. On average, students reported moderate levels of depression and high levels of hopelessness. Conclusion: Female Iraqi secondary school students experience high levels of suicidality, alongside several other known risk factors for suicide ideation. Findings emphasise the importance of developing targeted school-based interventions to support students’ mental health. Increasing research and attention in this area is vital to not only improving the mental health of students in Iraq but also reduce the stigma around mental health and suicide.

Eating disorders (ED) require more effective psychological interventions, in light of evidence saying that treatment response is often incomplete, and dropout rates are significant. One possible avenue to improve treatment effectiveness is address the frequent comorbidity with personality disorders (PD). When persons suffer from both ED and PD they would present with complex manifestations and serious interpersonal problems. In parallel, their capacity to form a solid working alliance can be limited. They are likely to have difficulty trusting clinicians and engaging in the necessary work needed to counteract their maladaptive ideas about food, weight and body image, and to change their problematic eating habits. This introduction of the issue of the Journal of Clinical Psychology: In Session devoted to treating patients with comorbid ED and PD describe the rationale for why it is necessary to assess and treat PD symptoms integrated with appropriate ED focused treatment.

Objectives: To evaluate the performance of the Tokuhashi, Tomita, SORG machine learning (SORG ML), and OPTImodel algorithms as survival predictors for vertebral metastases in clinical practice. Materials and Methods: A retrospective study (2013–2023) analyzed 573 patients from Cabueñes University Hospital (Asturias, Spain). Thirty-two demographic, epidemiological, clinical, and analytical variables were considered, including diagnosis chronology and survival. Results: Among the 573 patients studied, 272 (47.4%) presented visceral metastases at the time of diagnosis. A total of 362 patients (63.2%) had associated comorbidities. The most frequent primary histological diagnoses in these patients were lung 147, (25.7%), prostate 146 (25.5%), breast 118 (20.6%), kidney 30 (5.2%), and colorectal 29 (5.1%). The median survival of the cohort was 185 days. The accuracy rates for the Tokuhashi, SORG ML, OPTImodel, and Tomita algorithms were 0.5509, 0.4812, 0.3404, and 0.3858, respectively. The models with the highest accuracy rates in specific time segments were Tokuhashi (77.5% for less than 6 months) and OPTImodel (90.8% for more than 1 year). The areas under the curve (AUC) for survival intervals were as follows: Tokuhashi at 42 days (73.19%), 90 days (79.3%), and 365 days (82.73%); Tomita at 42 days (69.27%), 90 days (76.82%), and 365 days (78.79%); SORG ML at 42 days (52.77%), 90 days (51.69%), and 365 days (51.38%). Conclusions: All models showed relatively low accuracy. The newer models (OPTImodel, SORG ML) did not outperform the traditional Tomita and Tokuhashi in predicting survival for vertebral metastases patients.

In this study, we examined the relationships between water quality, land use, and optical properties of dissolved organic matter (DOM) in the Doce River Basin in Southeast Brazil. By highlighting the profound impacts of human activities, such as agriculture, mining, and urbanization, we aim to provide a comprehensive assessment of water quality. We utilized the optical properties of DOM to recognize the inadequacy of traditional indicators such as chlorophyll-a, especially in turbid waters. We collected water samples from 27 sites along the Doce River and its tributary, the Santo Antônio River, during both the dry and wet seasons, revealing notable seasonal variations. Our analysis identified predominant protein-like DOM components, underscoring the significant influence of land use changes. We found that DOM optical properties such as fluorescence and absorbance serve as reliable proxies for water quality parameters. Humic-like substances are correlated with nutrients such as total nitrogen and nitrate. Furthermore, we observed significant relationships between DOM optical compounds and the percentage of surrounding land use, particularly forested areas, which play a crucial role in determining water quality. The significant correlations between DOM fluorescence indices and physicochemical parameters suggest that optical metrics provide a comprehensive water quality assessment. This study highlights the need to integrate the optical, chemical, and biological metrics for effective water quality management in tropical river systems. This approach offers a detailed understanding of the ecological impacts of human activities and guides conservation strategies for the Doce River Basin.

The treatment of refractory autoimmune hemolytic anemia (AIHA) in childhood remains a significant challenge in hematology practice. Steroids, intravenous immunoglobulin (IVIG), rituximab, various immunosuppressants, and chemotherapeutic agents are commonly used. In highly refractory cases, hematopoietic stem cell transplantation may even be considered. Here, we describe a pediatric AIHA case that was highly refractory to conventional therapies but responded dramatically to bortezomib without any adverse effects. The patient showed a remarkable recovery starting from the first doses of the drug. Bortezomib may be considered as an alternative treatment option in such cases.

We report the case of a 32-year-old woman from São Paulo, Brazil, who was exposed to HIV but did not acquire the infection. This case demonstrates unique immune control characterized by transient viremia and the absence of seroconversion over a 10-year follow-up period. Genetic analysis revealed protective HLA alleles, a robust IFN-γ response to p24/Nef peptides, persistently high CD4+ T cell counts, and normal immune responses to other pathogens (e.g., Hepatitis A, CMV). These findings suggest that the inability to establish persistent HIV infection may be linked to the interaction of multiple factors, including a potent and sustained CD4+ T cell and cytotoxic response.