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Guiding healthcare decision-makers through uncertainty: a quasi-experimental study on...
Anke Aarninkhof-Kamphuis
Hans Voordijk

Anke Aarninkhof-Kamphuis

and 2 more

March 12, 2025
In an era of increasing uncertainty and complexity, healthcare decision-makers must navigate dynamic environments with greater awareness and adaptability. This study explores how a Dynamic Adaptive Decision Support model (DADS) can enhance decision-making capacity by fostering adaptability, resilience, and strategic foresight. Using the concept of stewarding capacity, we assess to what extent DADS enables healthcare leaders to anticipate and manage long-term uncertainties, risks, and changes. A quasi-experimental, long-term study was conducted within a healthcare organization as it developed its real estate strategy - an area deeply affected by fluctuating demands and unpredictable external factors. The DADS intervention was applied through structured group and individual sessions, after which participants were interviewed using open-ended questions to evaluate its impact. Findings reveal that DADS significantly enhances stewarding capacity by facilitating a collaborative knowledge-generation process, strengthening self-organization across multiple levels, and fostering continuous monitoring and learning. However, the study also uncovers challenges, particularly in leveraging partnerships for knowledge-sharing and reinforcing self-organization through cross-sectoral networks. These insights suggest that while DADS holds promise as an innovative decision-support tool, its operationalization requires further refinement. Ultimately, this study demonstrates that DADS has the potential to evolve into a transformative approach for strategic planning and management in healthcare. As organizations face an era of increasing complexity, integrating adaptive decision-making frameworks like DADS may prove essential in ensuring sustainable, forward-thinking strategies.
Research Trends and Topics on Sepsis Immunosuppression: A Bibliometric and Visual Ana...
Ji Yin
Yantong Wan

Ji Yin

and 8 more

March 12, 2025
Sepsis, characterized by critical impairment of bodily organs due to a dysregulated host response to infection, stands as a major contributor to mortality worldwide, with immunosuppression playing a pivotal role in its progression and outcomes. Here, we adopt the methods of bibliometrics and knowledge mapping to visually assess the current status and emerging trends of sepsis immunosuppression research, aiming to provide science researchers in this field with a comprehensive and systematic analysis. Sepsis immunosuppression-related articles and reviews were retrieved through subject searches in the Web of Science Core Collection, and bibliometric analysis was performed in Excel 365, CiteSpace, VOSviewer, and Bibliometrix (R-Tool of R-Studio). From 1 January 2004 to 22 March 2024, 3,082 articles on sepsis immunosuppression research published by 16,545 authors in 116 institutions from 30 countries were identified. Collaborative network analysis shows that the United States emerges as the leading contributor, with leading institutions Univ Florida and Washington Univ lying in the USA. The United States and China as well as the United States and Germany, exhibit the most frequent partnerships in the field. The journal with the most publications is Frontiers in Immunology, while Critical Care receives noteworthy citation frequency. Guillaume Monneret has published the most significant number of articles and Richard S Hotchkiss is co-cited most. These publications mainly cover the fields of immunology, molecular biology, and clinical treatments. The keywords analysis reveals that the studies related to immune cells, cell death and clinical personalized treatment may be the hotspots in this field.
Comments on “Comparison of White Light With Narrow Band Imaging Using Flexible Laryng...
Francesca Boscolo Nata
Giancarlo Tirelli

Francesca Boscolo Nata

and 1 more

March 12, 2025
Comments on “Comparison of White Light With Narrow Band Imaging Using Flexible Laryngoscopy for the Detection of Local Recurrences After (Chemo)Radiation for Pharyngeal or Laryngeal Cancer: A Randomised Controlled Trial”The paper by Scholman et al. [1] is the first randomized trial to compare white light (WL) and narrow band imaging (NBI) in detecting local recurrence during the follow-up of patients treated with (chemo)radiation for pharyngeal and laryngeal cancer.The results differ substantially from those found in literature. Specifically, the authors reported no advantage in recurrence detection with the use of NBI.We agree with the authors that this discrepancy could be explained by the low number of recurrences in their cohort. However, we believe that the limited experience of the clinician performing NBI examination may have impacted the results. In fact, the authors stated, “using NBI to differentiate between pathological IPCLs and disturbed blood vessel patterns after (chemo)radiation is challenging”. Conversely, previous literature has clearly shown that post-radiotherapy (RT) vascular patterns can be mistaken for recurrence during the first six months of NBI use due to the presence of a steep learning curve [2, 3]. After this period, a trained eye can distinguish post-RT areas by their ill-defined margins and relatively low density, offering a diagnostic advantage of over 60%, with a statistically significant difference between WL and NBI in recurrence diagnosis [3, 4]. This has led to the inclusion of NBI in the latest United Kingdom National Multidisciplinary Guidelines as a screening investigation during follow-up [3].The main advantage of using NBI in follow-up is the early detention of recurrences, including at dysplastic stages, when WL examination and radiologic imaging are unable to diagnose them. Moreover, NBI functions as an “optical biopsy”, selecting patients who warrant a biopsy under general anesthesia, thereby limiting costs, diagnostic time, and patient stress. In our opinion, the timing of laryngoscopy - scheduled every six months in this study - could have negatively impacted early diagnosis. Between two examinations, cancer can grow and become visible, both with WL and NBI, with NBI use in the follow-up seemingly no more advantageous than WL.According to NCCN guidelines, a complete head and neck exam, including fiberoptic examination, should be scheduled every 1-3 months in the first year [5].Therefore, we agree with the authors’ statement “A larger multicenter study with more frequent use of NBI is needed for definitive conclusions”.In conclusion, we believe that the creation of a dedicated team to optimize the NBI learning curve and the proper timing of follow-up examinations are advisable in order to fully understand NBI utility during follow-up.
Enhancing Quality of Life and Reducing Anxiety in Children with Leukemia Through Soci...
Nesibe S. KUTAHYALIOGLU
Gamze DEMIRBAS

Nesibe S. KUTAHYALIOGLU

and 1 more

March 12, 2025
Leukemia is the most common pediatric cancer and remains a leading cause of mortality in children under 15, with an estimated global incidence of approximately 400,000 cases annually among children and adolescents. Despite advancements in treatment improving survival rates, the disease and its prolonged therapeutic process impose significant physical (e.g., pain, fatigue) and psychological (e.g., anxiety, hopelessness, depression) burdens. Additionally, children with leukemia often face social and academic challenges, including difficulties with social support, adaptation, self-esteem, and educational attainment. The existing literature highlights the need for targeted interventions to address these psychological difficulties and provide holistic support. This study aimed to enhance the emotional well-being and resilience of children with leukemia by fostering a sense of solidarity and self-efficacy through mentorship from leukemia survivors. Thirteen participants (8 girls, 5 boys; mean age = 10 years) from the eastern provinces of the country engaged in structured online sessions over three months with mentors who had successfully recovered from leukemia. These mentors provided both motivational and academic support. Findings revealed statistically significant improvements in participants’ trait anxiety levels (p = 0.029), overall quality of life (p = 0.007), and coping skills related to cancer (p = 0.005). These results suggest that structured mentorship programs can positively impact the psychological and social well-being of children with leukemia. By fostering social connectedness and alleviating motivational challenges, such initiatives may contribute to improved long-term psychological health, underscoring the potential of mentorship-based interventions as a valuable component of comprehensive care strategies.
Respiratory Viruses in Febrile Seizures and Predictors of Influenza
David Ng Chun-Ern
Tharuman a/l Gnanamoorthy

David Ng Chun-Ern

and 15 more

March 12, 2025
Background: Febrile seizures are the most common pediatric seizure disorder, often triggered by viral infections, particularly respiratory viruses. This study aims to determine the frequency and spectrum of respiratory pathogens in children with febrile seizures and to identify clinical predictors of respiratory pathogen detection, with a focus on influenza. Methods: We prospectively recruited 243 children aged 6 months to 6 years hospitalized for febrile seizures at a Malaysian tertiary hospital between April to December 2024. Nasopharyngeal swabs were tested using a multiplex respiratory panel (RP) PCR for 23 respiratory pathogens. Clinical characteristics were compared between respiratory panel (RP)-positive and RP-negative cases. Two multivariate logistic regression analyses were performed: the first identified predictors of RP positivity, and the second identified predictors of influenza among RP-positive cases. Results: Respiratory pathogens were detected in 70.8% of febrile seizure cases, with influenza A (22.2%), rhinovirus/enterovirus (16.0%), SARS-CoV-2 (6.2%) and influenza B (5.3%) being the most common pathogens identified. Multivariate analysis identified cough as an independent predictor of RP positivity (aOR 2.79, 95% CI 1.14–6.81, p=0.024). Among RP-positive cases, recent sick contact (aOR 5.57, 95% CI 1.99–15.54, p=0.001) and lymphopenia (aOR 2.90, 95% CI 1.14–7.39, p=0.026) were independent predictors of influenza. Conclusion: Respiratory viruses were frequently detected in febrile seizures, with influenza being a major contributor. While routine testing is unnecessary, a targeted approach based on these clinical predictors could improve diagnostic accuracy, facilitate early antiviral treatment and reduce unnecessary antibiotic prescriptions.
Business Strategy in Fraud Migration: The Shift of Online Romance Scams from Nigeria...
Zahid Hussain

Zahid Hussain

March 12, 2025
In recent years, there has been a noticeable shift in the operations of romance scam networks from Nigeria to Ghana. This study explores the business strategies employed by fraudsters in this migration, analyzing the economic, regulatory, and technological factors that have contributed to this geographical shift. The research examines how stricter law enforcement measures and increased international scrutiny in Nigeria have forced cybercriminals to relocate their activities to Ghana, where regulatory frameworks and enforcement mechanisms are still developing. Fraudsters exploit Ghana's growing digital economy, relatively lax cybersecurity policies, and expanding internet infrastructure to continue executing romance scams with minimal risk of prosecution. Additionally, the study investigates the role of organized criminal networks in facilitating this migration, including the recruitment of local actors and the establishment of new operational hubs. Through case studies and law enforcement reports, this research identifies the key tactics used in romance scams, such as social engineering, identity theft, and emotional manipulation, which enable scammers to deceive victims into transferring large sums of money. The findings highlight that while fraud prevention efforts in Nigeria have been effective to some extent, the lack of coordinated regional cybersecurity policies allows scammers to relocate and resume operations with ease. This study underscores the need for enhanced cross-border collaboration, stricter enforcement mechanisms, and increased public awareness to combat online romance scams effectively. Addressing this issue requires a proactive approach, leveraging technology, regulatory reforms, and international cooperation to disrupt fraud networks and protect potential victims from financial and emotional exploitation.
Cryptocurrency Fraud and Financial Crime: Analyzing Convicted Fraudsters in Digital A...
Waseem Nasir

Waseem Nasir

March 12, 2025
Cryptocurrency has revolutionized financial transactions, offering decentralization, anonymity, and borderless transfers. However, these very features have also made digital assets a prime target for fraudsters and financial criminals. This study explores the profiles, methods, and legal outcomes of convicted individuals involved in cryptocurrency-related fraud. It examines highprofile cases, including Ponzi schemes, phishing attacks, fraudulent Initial Coin Offerings (ICOs), and ransomware operations, to understand the patterns and motivations behind such crimes. Through an analysis of case studies and legal proceedings, this research identifies key tactics used by fraudsters, such as social engineering, rug pulls, pump-and-dump schemes, and identity theft. The findings highlight that many perpetrators exploit regulatory loopholes, leveraging the lack of legal oversight in certain jurisdictions to defraud investors. Additionally, the paper discusses the role of emerging technologies like artificial intelligence and blockchain analytics in detecting and preventing digital asset fraud. The study further investigates the impact of these scams on investors and financial markets, revealing substantial financial losses, erosion of trust, and regulatory challenges faced by global law enforcement agencies. By assessing legal frameworks and enforcement mechanisms, the research evaluates the effectiveness of current laws in prosecuting cryptocurrency fraud and suggests policy improvements to enhance financial security. Ultimately, this research contributes to a deeper understanding of cryptocurrency fraudsters' operational strategies and their legal repercussions. It underscores the urgent need for stricter regulations, enhanced cybersecurity measures, and international cooperation to combat digital asset scams. Addressing these issues is crucial for fostering a safer cryptocurrency ecosystem and protecting investors from financial crime.
Self-Adjusting AI-Driven Morphing Tires for Dynamic Terrain Adaptation
Ragav Gupta

Ragav Gupta

March 12, 2025
With the rapid advancements in Artificial Intelligence (AI) and smart material technologies, the concept of self-adjusting, and morphing tires is emerging as a revolutionary solution for dynamic terrain adaptation. Traditional tires face limitations in handling multiple road conditions, leading to traction, fuel consumption, and vehicle stability inefficiencies. This research explores an AI-integrated approach to morphing tire technology, where real-time terrain sensing, shape-memory alloys (SMA), elastomers, and adaptive tread patterns enable tires to automatically adjust to different surfaces such as highways, off-road terrains, icy roads, and wet conditions. The proposed system leverages machine learning (ML) algorithms, AI-powered sensors, and predictive analytics to detect terrain characteristics and dynamically modify the tire structure for optimal grip, stability, and durability. Such technology holds significant applications in autonomous vehicles, military transportation, and high-performance sports cars. This paper comprehensively analyzes AI-driven morphing tire architecture, material innovations, real-world feasibility, and future research directions.
Trends in gestational weight gain from 2007-2019: A prospective cohort study
Belle Martin
David E. Cantonwine

Belle Martin

and 5 more

March 12, 2025
Objective: To evaluate temporal trends in total gestational weight gain (GWG) from 2007 to 2019 in a large pregnancy cohort. Design: Prospective cohort study. Setting: LIFECODES study, Brigham and Women’s Hospital, Boston, MA. Sample: 3,675 pregnant participants, with 29,037 weight measures. Methods: Using self-reported pre-pregnancy weight and serial weight measurements, we applied a mixed effects model to predict maternal weight at delivery. Total GWG (kg) was defined as the difference between predicted delivery weight and pre-pregnancy weight, classified based on the 2009 guidelines by pre-pregnancy BMI. Main Outcome Measures: Trends in proportions of GWG categories, both overall and stratified by maternal characteristics; Trends in covariate-adjusted geometric means (GMs) of GWG. Results: The proportion of participants with total GWG within the guidelines decreased from 46% in 2007-2008 to 24% in 2018-2019, which was driven by an increase in those gaining above the guidelines (40% to 73%). Trends were consistent across maternal characteristics, though the largest relative increases of proportions above the guidelines were observed among those of normal pre-pregnancy BMI (19% to 62%) and of non-Hispanic Black (48% to 85%) or non-Hispanic White (37% to 74%) race/ethnicity. Adjusted GMs increased from 8.3 kg (95% confidence interval [CI]: 6.3, 10.8) in 2007-2008 to 10.9 kg (95% CI: 7.9, 14.9) in 2018-2019. Conclusions: Over time, fewer women have been meeting the revised 2009 GWG guidelines, and this trend is driven by increasing proportions of pregnant individuals gaining weight above the recommendations.
A FIRST-IN-HUMAN STUDY TO EVALUATE THE SAFETY, PHARMACOKINETICS AND PHARMACODYNAMICS...
Thijs van Iersel
Jiyun Chen

Thijs van Iersel

and 10 more

March 12, 2025
Aims: ALTB-268 is an agonist antibody targeting the immune checkpoint regulator P-selectin glycoprotein ligand-1 (PSGL 1) to down-regulate pathogenic T-cells. ALTB-268 is a tetravalent antibody and more potent in vitro than ALTB-168 (neihulizumab) which has shown to be efficacious in phase 2 studies for T-cell-mediated autoimmune diseases and acute graft-versus-host disease (GvHD). This dose escalation study evaluated tolerability, safety, pharmacokinetic (PK), and pharmacodynamics (PD) in healthy subjects. Methods: Fifty-six subjects were randomly assigned to single subcutaneous (SC) doses of 25, 75, 225, or 675 mg, or multiple weekly SC doses of 75 mg or 225 mg on Days 1, 8, 15 and 22, or a loading dose of 500 mg on Day 1, followed by doses of 250 mg on the remaining days. Results: No clinically meaningful adverse events (AEs) were observed. Plasma exposure increased more than dose-proportionally after single doses across the entire dose range. After repeated exposure steady-state conditions were reached by Day 29. The level of receptor occupancy (RO) in T-cells showed a clear relationship to dose, with full RO observed after a single 675mg SC dose and after repeated administration of 225 mg SC weekly. Additional doses did not appear to further increase the level of receptor occupancy. Conclusions: ALTB-268 was safe and well-tolerated by healthy subjects. Full and durable RO over the 4-week treatment period was achieved with a loading dose of 500 mg SC followed by weekly dosing with 250 mg SC. These study results support the further clinical development of ALTB-268.
Evaluation of the VIDAS® Cytomegalovirus (CMV)-IGRA for Assessing CMV-Specific T-Cell...
Estela Giménez
Eliseo Albert

Estela Giménez

and 9 more

March 12, 2025
We compared the performance of the VIDAS® Cytomegalovirus (CMV)-Interferon-gamma release assay (IGRA) with that of laboratory-developed flow cytometry for intracellular cytokine staining (FC-ICS) for the assessment of CMV-specific interferon-gamma (IFN-γ)-producing T-cell responses (CMV-CMI). A total of 147 blood specimens from 78 adult participants were collected: 11 healthy controls, 34 hematological patients (HP), of which 32 had undergone allogeneic hematopoietic cell transplantation (allo-HCT), and 33 Kidney transplant recipients. Of the 147 specimens, 96 tested positive, 24 negative, 25 indeterminate, and 2 were invalid by the VIDAS® CMV IGRA. A total of 137 specimens were tested by FC-ICS, of which 107 returned positive results. There were 27 discrepancies across the assays among specimens yielding interpretable results, of which 14 tested VIDAS® CMV IGRA-positive/FC-ICS-negative and 12 VIDAS® CMV IGRA-negative/FC-ICS-positive. The overall agreement between immunoassays was 78%, and the Kappa coefficient was 0.34 (0.52 for HP). Differences in identifying CMV-infected (CMV IgG-positive) and uninfected participants (CMV IgG-negative) were noticed across both assays. The overall correlation (rho values) between IFN-γ concentrations (IU/ml) measured by the VIDAS® CMV IGRA and CMV-specific IFN-γ-producing T-cell frequencies were 0.27 for CD4 + and 0.33 for CD8 + T cells ( P=0.001). In HP, the correlation was stronger (0.48 for CD4 + and 0.49 for CD8 + T cells). A trend toward a direct association between the presence of undetectable VIDAS® CMV IGRA or FC-ICS responses and subsequent occurrence of CMV DNAemia was observed. In summary, our data lend support to the potential utility of the VIDAS® CMV IGRA to assess CMV-CMI in transplant recipients.
Real-Time Data Drift Detection in Energy Demand Using Efficient Change-Point Analysis
Nikhil  Pawar
Guilherme  Hollweg

Nikhil Pawar

and 3 more

March 12, 2025
Accurate electricity demand forecasting is crucial for grid stability and resource optimization, yet predictive models degrade over time due to data drift caused by market fluctuations, policy changes, and infrastructure shifts. Undetected drift leads to forecasting errors, inefficiencies in energy distribution, and increased operational costs. This paper presents a deep learning-based framework for detecting data drift in electric load time series, leveraging statistical and machine learning-based approaches with a focus on the Pruned Exact Linear Time (PELT) algorithm for efficient change-point detection. Our method is scalable and highly efficient, making it suitable for real-time applications. Unlike traditional drift detection techniques, our approach dynamically adjusts to evolving patterns, mitigating both gradual and abrupt changes in consumption behavior. By leveraging both synthetically generated multivariate data and realworld univariate data for electricity load-related time series, the effectiveness of PELT is evaluated demonstrating its ability to capture structural shifts with high accuracy. The proposed framework achieved F1 score of 82% and 98% for generated temperature and humidity time series, respectively. Similarly, it achieved F1 score of 94% for real-world electricity demand data. We also assessed the quality of PELT’s detection by applying time series smoothing techniques that provided additional insights.
Experimental evidence for photosynthetic dependency of phloem sap generation in minor...
Guillaume Tcherkez
Louis Broussard

Guillaume Tcherkez

and 8 more

March 12, 2025
Factors controlling plant photosynthesis and primary production include parameters dictating photosynthetic activity together with export and allocation properties. In fact, phloem loading activity as well as phloem sap redistribution and velocity are considered as important players in plant carbon acquisition. But surprisingly, there is almost no information about how phloem sap properties such as sugar concentration and velocity, are controlled by photosynthetic rate. Here, we carried out gas exchange experiments coupled to isotopic labelling on sunflower leaves to monitor photosynthate export rate when photosynthesis was varied with CO 2 mole fraction. We took advantage of a compartmental isotope model to obtain an experimental estimate of phloem sugar pool size and thus sap concentration and velocity. Phloem sugar concentration was found to increase relatively slowly (from very low values to about 1 mol L -1) with photosynthesis and export rate, while sap velocity remained in the same order of magnitude (0.2-0.6 mm s -1). This phenomenon could be explained using a simple one-dimensional model of phloem sap generation and movement suggesting that at fixed photosynthesis, phloem sap was in a steady-state reflecting the balance between xylem-to-phloem and sieve tube hydraulic conductance, turgor pressure and osmotic pressure due to loading. Our study also shows that phloem sap composition was not invariant with photosynthetic conditions but rather, adjusted to leaf export while maintaining sap flow even at very low CO 2.
Specific haplotypes of the lipid-related OsGELP gene family are present in rice adapt...
Kayyis Muayadah Lubba
Koichi Yamamori

Kayyis Muayadah Lubba

and 2 more

March 12, 2025
Rice ( Oryza sativa) originated in tropical regions and has adapted to higher latitudes; these adaptations affect photoperiod sensitivity and cold tolerance. Lipids are essential membrane components and function in sensing and responding to environmental conditions. Members of the lipid-related GDSL esterase/lipase (GELP) family have been implicated in stress responses. Here, to investigate the relationship between OsGELP genes and rice adaptation to high latitudes, we identified the haplotypes of each of the 115 OsGELP genes in 3000 rice accessions and sorted them based on latitude data and single-nucleotide polymorphisms, designating haplotypes present at an average latitude >35°N as high-latitude haplotypes (HLHs) and selecting 10 OsGELP genes with 11 HLHs for further analysis. Haplotype network and amino acid sequence analyses suggested that rapid changes involving a few amino acids encoded by genes with HLHs likely helped plants adapt to high latitudes. HLH-containing OsGELPs are often expressed in roots, suggesting that roots function in the adaptation of rice to high latitudes. Apart from OsGELPs, only 3 of the 14 known cold tolerance genes in rice have HLHs. We suggest that the 10 OsGELP genes with HLHs play crucial roles in the adaptation of rice to high latitudes.
The impact of perinatal factors on executive function development in 30 months infant...
Belén Almansa
Anna Miró-Padilla

Belén Almansa

and 9 more

March 12, 2025
Abstract Objective Infants born after threatened preterm labour (TPL) are at heightened risk for executive function (EF) deficits. This study examined the association between perinatal factors and infants EF development, focusing on prematurity. Design A prospective cohort study Setting Obstetrics Hospitalization Unit at La Fe University and Polytechnic Hospital in Valencia (Spain) Population A total of 179 mother-child pairs from pregnancy to 30-months-of-age, concretely 60 controls compared to 119 TPL-group: 27 full-term, 55 late-preterm, 37 very-preterm. Methods Assessments occurred at three times: during TPL or control visit, after delivery and at 30-months-of-age (infant’s EF via BRIEF-P). Data included medical records, sociodemographic and maternal scores (STAI, BDI, TQ). Main Outcome Measures A Bayesian network analysis of perinatal factors (infant sex, maternal age, multiple pregnancy, IVF, parental education, birthweight, TPL-group, and maternal scores) influencing EF (inhibition, shifting, emotional control, planning, and working memory). Results TPL groups exhibited reduced EF performance compared to controls being very-preterm infants most affected. Other predictors of EF deficits included increased maternal anxiety at TPL, lower birthweight percentile, male sex, maternal age, and parents without university education. A history of trauma exacerbated maternal anxiety, which negatively impacted birthweight percentile and birth timing. Conclusions The manifestation of EF deficits in TPL infants at higher risk for EF problems exhibits a phenotype influenced by prematurity. Maternal anxiety at TPL is a key perinatal risk factor that must be managed for prevention. Funding Authors receipted support by Carlos III Health Institute, Spanish Ministry of Science and Innovation, and European Regional Development Fund.
An Empirical Study on the Effectiveness of Adversarial Examples in Window PE Malware...
Manju Dhull1
* Chhavi Rana2

Manju Dhull1

and 1 more

March 12, 2025
Malware detection is an important part of cybersecurity that concentrates on detecting and eliminating harmful software intended to harm computer systems or data. Early conventional Malware detection technologies that depend on recognized malware patterns have limitations in recognizing code obfuscation with dynamically increasing threats. Recent research has shown that current Machine Learning (ML) Techniques are highly effective at identifying newly discovered and previously unknown malware which are more vulnerable in terms of adversarial examples. These examples are intentionally created by making tiny and deliber- ate modifications to authentic inputs to cause the models to act incorrectly. To tackle this issue, the study is centred on improving the resilience of models by employing quality of datasets and adversarial training techniques. This System- atic Literature Review (SLR) addresses malware detection with the file format of Portable Executable (PE) belongs to the family of Window Operating System by examining 50 Scientific Papers selected from various Publications present in Scopus Database. It provides the classification on Windows PE features, various Datasets, basic framework of the Malware detection model and ML and DL algo- rithms along with survey of evaluation Metrics. The main contribution of this paper is to find the problem and research gaps in this area of interest. Finally, the paper conclude with the future directions and opportunities.
Echocardiography and the unmet clinical needs in chronic heart failure
Massimo Iacoviello

Massimo Iacoviello

March 12, 2025
Commentary to “Left ventricular outflow indices in chronic systolic heart failure: thresholds and prognostic value”
T5-Driven Neural Network for Optimized Sentiment Classification: Enhancing User Feedb...
Md. Faishal Ahmed Rudro
Md. Shahriar Rahman Bhuiyan

Md. Faishal Ahmed Rudro

and 2 more

March 12, 2025
Proper sentiment categorization is required to comprehend user opinions and optimize AI-based systems. Conventional machine learning techniques are usually hindered by the lack of context understanding and imbalance in classes, resulting in inferior predictions. The present work advocates the use of a T5-based sentence embedding technique for sentiment categorization wherein reviews are grouped into Positive, Neutral, and Negative classes based on review ratings. The preprocessing routine consists of text cleaning, tokenization, and stopword removal prior to proceeding with feature extraction from the T5 and reducing dimensions through Truncated SVD in order to decrease computation. Class imbalance was addressed through SMOTE-ENN balancing to determine strong generalizability of the models. Some various classifiers were utilized and cross-tested against the data set such as optimized neural networks, familiar classifiers like XGBoost, SVM, CatBoost, LightGBM, and Random Forest. The proposed deep neural network model produced the maximum validation accuracy of 97.01%, surpassing all the baseline models in precision (0.972), recall (0.970), F1-score (0.971), and AUC-ROC (0.992). Furthermore, a comparison with BERT, RoBERTa, and DistilBERT proved that T5 embeddings coupled with an optimized neural network gave better classification accuracy without losing out on computation. These results demonstrate the power of using transformer-based feature extraction with deep learning optimizations for sentiment classification tasks.
Incubation behaviour in a double-nesting alpine species Alectoris graeca saxatilis: s...
Ariane Bernard-Laurent
Guillelme Astruc

Ariane Bernard-Laurent

and 5 more

March 12, 2025
In double-nesting species with uniparental incubation, such as the rock partridge (Alectoris graeca saxatilis), the male incubates one clutch and the female the other clutch. A previous study has shown no difference in hatching and predation rates on rock partridge nests incubated by each sex. Therefore we hypothesised that the incubation rhythms would be similar between the sexes. To test this hypothesis, incubation rhythms of 40 nests incubated by females and 41 by males of Alpine rock partridge were monitored in the French Alps between 2011 and 2020. Temperature data loggers were placed, one inside the nest and the other outside, to measure ambient temperatures. The timing and duration of incubation recesses were quantified for each monitored bird by analysing the temperature curves. Statistical modelling was used to assess the effects of incubating bird sex, minimum ambient temperature, incubation day, clutch size and recess rank on incubation parameters. The daily timing of recesses, total recess duration, number of recesses and nest temperature are similar between the sexes. Birds made an average of 2.5 recesses per day, averaging 75 min each. On average, they spend 87.9% of their time incubating eggs. Recesses occurred throughout the day, with a peak 15-30 min after sunrise and a second, less pronounced maximum, before sunset. Nocturnal recesses were rare caused by disturbance of the incubating bird. Modelling showed only slight differences in mean recess duration between sexes throughout incubation. Other modelling results showed that both sexes adapted in a similar way their rhythms to incubation progress and to daily minimum temperature. Low temperatures might force parents to spend more time foraging outside the nest to meet energy requirements. Rock partridge nest attendance was lower than that of grouse species, a difference probably related to the rock partridge’s lower body reserves compared to grouse.
Synthesis and characterization of ES/Fe(OH)3 nanocomposites: A novel and highly effec...
Elaheh Mosaddegh
Yalda Asnaashari Kahnouji

Elaheh Mosaddegh

and 3 more

March 12, 2025
The novel waste-based eggshell/Fe(OH) 3 plate-like nanocomposites were synthesized using the mild co-precipitation method, and their catalytic properties were investigated. These nanocomposites demonstrated high catalytic activity, stability, and reusability as multifunctional and heterogeneous catalysts for the green multi-component synthesis of 2 H-indazolo[2,1- b]-phthalazine-trione derivatives under solvent-free and thermal conditions. The synthesized nanocomposites’ morphology, nanoparticle size, structure, crystalline nature, and thermal stability were characterized using FESEM, TEM, FT-IR, XRD, and TGA analyses. The results indicate that these nanocomposites are efficient, cost-effective, and environmentally friendly catalysts, highlighting their potential for sustainable chemical and industrial processes.
“Exploring the Connection: How Learning Styles Influence Burnout in Medical Students...
Roopashree Ramakrishna

Roopashree Ramakrishna

March 12, 2025
IntroductionA Student learns in many ways, consciously or unconsciously a learner uses a learning style model. [1] A Learning Style (LS) model is usually based on what the learner is seeing and hearing; reflecting and acting; reasoning logically and intuitively; memorizing and visualizing; drawing analogies and building mathematical models in a given learning environment. These Learning style models act as factors of learning efficacy and develop into an individual’s learning preference. [2] Learning Style refers to how the learner prefers to manipulate the information to attain retention of the knowledge gained either Visually, Auditorily, Read/ Write, Or Kinesthetic(VARK). Every learner has different learning styles based on their unique abilities; they may learn information primarily in one of the above ways. It is possible that once the learnt information is attempted for reinforcement of the information, it may use one or more ways of our sensory inputs. Since the introduction of VARK learning styles by the educational psychologist, it has benefited educationists of all walks to explore the students’ learning styles and to introduce apt teaching styles, modalities, and methods.[3] The VARK Model profiles the learners. During our literature review, it is found that medical students are usually multimodal in nature.The VARK model helps us better understand how people refer to take-in and process information, recognizing that many learners can use more than one style at once. It’s made up of 16 questions that look at how individuals like to receive information and communicate with others. In a cognitive sense, it is a tool that shapes perception, processes information, and builds concepts and principles.[4] Researchers like Alfarsi et.al., and Chae et.al., have observed and reported that learners have different learning styles Visual learners tend to absorb material best when they can see it, so they often benefit from charts, diagrams, mind maps, and videos. Auditory learners, on the other hand, grasp information more easily through listening, so lectures, recordings, and discussions are ideal for them. Read/write learners prefer learning through written words-they excel when they can take notes, read, and revisit textbooks several times. Kinesthetic learners, meanwhile, thrive on hands-on experiences, learning best when they can actively practice or engage with real-life applications of the material.[5],[6] Based on how they learn, the learning styles can be categorised into Unimodal if they use single modes; Bimodal if the learning happens in combinations modes like VK, VR, VA, AK, RK; lastly Multimodal, if the combinations of learning modes are more than two or three modes. In Multimodal learning styles, learners are inclined to more than one learning style, combining visual, auditory, reading/writing, and kinesthetic approaches to understand and retain information. One of the prime intents of the educator is to determine students’ learning styles. It provides information about learner’s specific preferences [7].  The Knowledge of their learning styles makes it easier to create, modify, and develop more efficient curriculum and educational programs. It can also encourage students’ participation in these programs and motivate them to gain professional knowledge. Hence, the educators must identify the difficulties of learning patterns in students, which could be failures in the education system. This promotes necessary learning interventions.[1], [6], [8]The term Burnout (BO) was introduced in 1962[9] Burnout syndrome is characterized by depersonalisation, impaired personal accomplishments and is often induced by repeated stressors personal and professional.[10], [11] Academic burnout in Learners are one of the common challenges that affects students’ motivation and academic inquisitiveness. It impedes the learner from achieving academic goals, which might lead to academic fall out[12].   Medical education is a rigorous journey, often marked by high stress and limited time for personal recovery.  Medical students are the ideal target of academic burnout (Vincenzo)[13]. Burnout in medical student community most often presents itself as, a state of physical, emotional, and mental exhaustion. It is prevalent among medical students and does negatively impact their academic performance and well-being.The operational definition of Burnout (BO), and its corresponding measures to assess it, was developed by Susan Jackson and Maslach.     It is made up of three components based on how Burnout, manifests. They are Emotional Exhaustion (EE), Cynicism (E), and decreased Academic Efficiency (AE).  The knowledge of the interplay between LS and BO could help educators develop targeted strategies to support students and mitigate the BO risks.  Based on the psychometric research measures available then, Maslach and his team developed an inventory of questionnaires called the Maslach Burnout Inventory-Student Survey (MBI-SS). This measure was designed to assess the three components of Burnout Syndrome: emotional exhaustion, depersonalization, and reduced personal accomplishment. It has twenty-two items, which are divided into three EE, C, and AE subscales. (Maslach). [14] Educators guide students in their learning journey to understanding the complex modern healthcare delivery system, as well as the undergraduate medical education curriculum. we should help them navigate into becoming innovative learners, and recognize acknowledge, and support students with different learning styles and their preferences. Understanding the interplay between LS and BO could help educators develop targeted strategies to support students and mitigate burnout risks.Despite significant research on LS and BO independently. The relationship between LS and BO levels remains unexplored. This brings us to investigate the primary research question of whether there is a relationship between type of learning style and burnout. This study seeks to bridge this gap, offering insights into how educational practices can better align with students’ learning preferences to enhance their learning experiences and overall mental health.
The covalent channel effect: How covalent metal-oxygen bond reduces bandgap and boost...
Zhi-Hao He
Yun-Jie Wang

Zhi-Hao He

and 5 more

March 12, 2025
Text:Apatite is a versatile and important mineral group with significant roles in geology, biology, and industry. This study employs density functional theory (DFT) to investigate the electronic structures and optical properties of three centrosymmetric (CS) crystals: Ca 10(PO 4) 6F 2(FA), Ca 10(PO 4) 6Cl 2(ClA), and Ca 10(PO 4) 6Br 2(BrA), and two non-centrosymmetric (NCS) crystals: Ca 10(PO 4) 6(OH) 2(HA) and Ca 10(PO 4) 6O(OA). Despite the strong structural resemblance, the optical properties of OA show discrepancy among other apatite analogs. Specifically, the bandgap of OA is reduced from over 6.0 eV to 4.328 eV, and a significant second-harmonic generation (SHG) response ( d 11 = 0.824 pm/V and d 22 = 1.327 pm/V) compared with NCS analog HA ( d 15 = -0.021 pm/V and d 33 = -0.026 pm/V). The main reason for these disparities is that in other compounds the bonds between Ca and X tend to be ionic, whereas in OA, the bonds formed between Ca and O C exhibit covalent character, and almost all of the charge obtained by O C comes from Ca. This not only reduces the bandgap but also enhances the internal charge transfer capability, leading to an increase in the SHG coefficient.
Thin LiPON Layer on Graphite Electrode: An Almost-Solid-State Battery System
Julia Cipo
Sandra Hansen

Julia Cipo

and 12 more

March 12, 2025
Solid-state batteries offer a promising alternative to conventional lithium-ion batteries, addressing key safety and performance limitations. This study introduces a novel almost-solid-state battery system, implementing a thin 55 nm lithium phosphorous oxynitride (LiPON) layer on slurry-based graphite electrodes. By leveraging LiPON’s dual functionality as both a solid-state electrolyte and a separator, the system eliminates the need for a conventional separator, while requiring only 5-10% of the liquid electrolyte used in equivalent systems. This design significantly reduces internal resistance and prevents contact loss during cyclic volume changes. Electrochemical analyses, including cyclic voltammetry, galvanostatic cycling and impedance spectroscopy, demonstrate electrode impedance of a few 10 Ω cm2, efficient lithium-ion transport and stable cycling behavior at room temperature. Furthermore, X-ray photoelectron spectroscopy and scanning transmission electron microscopy confirm the structural integrity of LiPON and the formation of a solid-liquid electrolyte interface, which enhances charge transfer and long-term stability. These findings highlight the potential of almost-solid-state batteries for safer, more compact and cost-effective energy storage solutions.
Stronger together: intact soil translocation increases the resilience of inoculated m...
Shawn Peddle

Shawn Peddle

and 8 more

March 12, 2025
A document by Shawn Peddle. Click on the document to view its contents.
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