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An improved Newman fast division algorithm based on multi-factor correlation for dynamic traffic sub-region control

Given the ongoing expansion of urban traffic signal control coverage, it is imperative to systematically delineate sub-regions based on the topology of road networks and traffic flow characteristics to enhance the stability of traffic management systems. To enhance the rationality of dynamic control sub-region division, this paper establishes a traffic-mechanism-driven edge weight construction framework integrated with modilarity-based community detection. This model integrates traffic volume, signal cycle, and traffic density to compute a comprehensive correlation degree between adjacent intersections. Furthermore, an entropy-weighted TOPSIS framework is proposed to objectively evaluate the proximity of neighboring nodes. This proximity measure is subsequently utilized as the edge weight within an improved Newman fast partitioning algorithm, thereby augmenting modularity and guiding the delineation of sub-regions. Empirical results indicate that while the conventional Newman algorithm exhibits limited adaptability to complex traffic patterns, the proposed model yields more distinct and precise sub-region divisions that more accurately reflect actual traffic conditions. Consequently, this methodology provides a robust foundation for the development of more effective signal control strategies.

A lightweight feature fusion network for weak and small target detection in remote sensing

Interpretable crop pest and disease identification based on comparative concept tree

Deep learning provides new methods for crop pest and disease identification and control, offering unique advantages in terms of recognition accuracy and efficiency. However, deep learning models generally lack interpretability, and their internal decision-making processes are difficult to understand. This, to some extent, undermines users’ trust in the model’s predictions and hinders its large-scale application in agricultural production. Therefore, improving model transparency and interpretability has become an important research direction. To address this issue, this study proposes a novel interpretable crop pest and disease identification model, the Contrastive Prototype Tree (CPTR). The model is designed around the core structure of “concept prototypes and decision tree,” which builds clear prototype matching paths for each recognition result. This enables the model to not only have strong classification capability but also provide intuitive explanations. Additionally, the study introduces the SimCLR contrastive learning framework to enhance the model’s ability to express deep image features. SimCLR guides the model to learn more discriminative visual features by maximizing the similarity between positive sample pairs and minimizing the similarity between negative sample pairs, thereby improving overall recognition performance. This study evaluated the model on three datasets: AppleLeaf9, Cassava, and Cashew. The experimental results show that CPTR achieves accuracies of 83.74%, 94.80%, and 96.01% on the three datasets, representing improvements of 4.12%, 0.34%, and 0.51% compared to Prototype Tree, respectively. These results indicate that the proposed model achieves the highest accuracy across different datasets, demonstrating its effectiveness.

A five-dimensional geometric uniformity framework for spherical diamond grids

The impact of CPR coach presence and position on team leader and team performance during asystole simulation scenario: a randomized simulation-based trial

Background High-quality cardiopulmonary resuscitation is critical for patient survival, and its effectiveness depends on compression quality, team coordination, and leadership. The CPR coach provides real-time feedback aimed at optimizing chest compressions and enhancing the overall resuscitation process. The primary aim is to evaluate whether the presence and the position of a CPR coach are equivalent compared to the absence of a CPR coach regarding the team leader’s performance. As a secondary objective, it was investigated whether the presence and the position of the CPR coach influence the teams’ performance. Methods This is single-center, randomized, controlled, three-arm, simulation-based equivalence trial. Teams of residents participated in standardized asystole scenarios, randomized to one of three groups: Group A (CPR coach positioned near the defibrillator), Group B (CPR coach allowed to move freely), and Group C (no CPR coach). The primary outcome was assessed using the Resuscitation Team Leader Evaluation Scale. The secondary outcome was measured by the Clinical Performance Tool and a CPR execution quality score derived from simulation manikin feedback. Results A total of 42 teams were included in the analysis. With respect to the primary outcome, team leader performance was statistically equivalent across Groups A, B, and C. As for the secondary outcome, no significant differences were observed in overall team performance. Conclusion The presence and position of a CPR coach did not significantly influence team leader or team performance. Further research is needed to explore the role of CPR coaches in real-life settings and among more experienced teams. Trial registration Trial registration: NCT05309434. Registered 15/04/2022.

Flexoelectrically Induced Polar Topology in Twisted SrTiO ₃ Membranes

ABSTRACT The recent realization of freestanding membranes of perovskite oxides has enabled their deterministic mechanical assembly into twisted homo bilayers. Twisted oxide interfaces feature a non‐homogeneous pattern of shear strains determined by the atomic registry through the strong ionic‐covalent bonding of this family of compounds. Twisted ferroelectrics open an unprecedented opportunity to tailor topological polar landscapes in a way determined by the flexoelectric coupling of polarization to the large strain gradients developing with the modulation of the moiré coincidence pattern. Yet, flexoelectricity is a universal phenomenon which may render polar landscapes in non‐ferroelectric materials. Here we report a polar topology in twisted membranes of SrTiO 3 (STO), a paraelectric centrosymmetric compound. The polar landscape is generated by the flexoelectrically induced polarization driven by the strain modulation triggered by twisting, as also supported by machine‐learned force fields based on first‐principles calculations. We further show that the strain and polarization patterns in top and bottom layers are correlated in a way which breaks inversion and mirror symmetries as dictated by the emergent chirality imposed by twisting. This finding opens exciting opportunities for the exploration of novel physical effects and functionalities.

Machining performance investigation on 17-4PH steel material with innovative textured tools

Abstract The machinability characteristics during turning process are noticeably influenced by the texture design particularly single pattern or dual pattern about surface textured tools. In this context, novel dual pattern textured tools were developed in the present work and compared its machinability performance with conventional tools respectively in tuning of 17-4PH steel under wet cooling conditions. Dual pattern textured tools consists of continuous microgrooves which are combination of parallel and perpendicular to the chip flow direction and also, have microgrooves parallel to principal cutting edge and secondary cutting-edge to enhance. In this work, investigation was done at different cutting velocity. Cutting temperature (T), surface roughness (R a ), and tool flank wear (V b ) were shown to be significantly decreased by hybrid textured tools compared to conventional tools, with maximum values of 26%, 28%, and 21%, respectively. Further, developed textured tools found with low adhesion and abrasion wear when compared to conventional tool. Moreover, interaction effect of input process variables on outputs was studied via interaction plots. From results it was retrieved that hybrid textured tools served as coolant storages sites to supply coolant to the cutting zone effectively.

Analysis of temperature adaptability of Eocanthecona furcellata (Wolff) (Hemiptera: Pentatomidae) based on age-stage, two-sex life table and predatory functional response

Eocanthecona furcellata (Wolff) (Hemiptera: Pentatomidae) is a key natural predator of agricultural and forestry pests. In nature, temperature affects the growth, development and predation ability of predators. Therefore, this study assessed the growth, development, and reproduction of E. furcellata at 20, 23, 26, 29, and 32°C. Age-stage, two-sex life table analysis showed that the development duration of each stage decreased with increasing temperature. At 20°C, individuals reached adulthood but females did not oviposit. At 29°C, intrinsic and finite rates of increase and fecundity were higher, with values of 0.12, 1.13 and 41.59, respectively. Moreover, the mean generation time was relatively short at 29.98 d. Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae) is a highly destructive invasive pest that causes severe economic losses to crops. Therefore, this study evaluated the potential of E. furcellata to control S. frugiperda by predation functional response and interference effects. The functional response of adults to fourth-instar larvae of S. frugiperda followed the Holling II equation across all tested temperatures. Predation ability ( a/T h ) and maximum daily predation ( 1/T h ) were the highest at 32°C (female: a/T h  = 52.7149, 1/T h  = 51.8135; male: a/T h  = 46.2538, 1/T h  = 44.8430), but adult search efficiency was negatively correlated with prey density. At constant prey density, search efficiency increased with temperature. Intraspecific competition and mutual interference were also observed among adults. Across temperatures and prey ratios, adults consistently exhibited strong predation preference for fourth-instar larvae of S. frugiperda . These results provide a theoretical basis for the practical use of E. furcellata in pest management.

Neuronal correlates of spatial memory updating: c-Fos and GAD67 expression in the object-place recognition task

Abstract The retrieval of spatial memory is behaviorally often assessed in tasks like the classical Object-Place-Recognition (OPR) task that requires an updating of memory. The neural dynamics across interconnected brain regions underlying retrieval processing in such tasks, are not well understood. Here, we examined in rats the neural correlates of retrieval processing in the OPR task by comparing a condition of successful OPR retrieval, in which the displaced object during the retrieval phase (3-hours after encoding) induced a spatial memory updating (OPR condition), with a stationary (STA) control condition in which the object configuration at retrieval was identical to encoding and, therefore, did not require spatial updating. Importantly, both conditions involved re-exposure to the previously encountered objects and context, but only the OPR condition imposed demands on updating the stored spatial representation. Expression of c-Fos (as an activity marker) and GAD67 (to identify inhibitory interneurons) was assessed at retrieval in hippocampal subfields, mPFC areas, thalamic nuclei, and posterior cortical regions. Rats in the OPR condition exhibited robust object-place discrimination and enhanced rearing behavior compared to the STA condition. Regional c-Fos activation levels were largely comparable between OPR and STA conditions across hippocampal, cortical, and thalamic regions. However, the OPR condition showed a region-specific increase in the proportion of GAD67-positive active neurons in proximal CA1. Together, these findings identify a specific pattern of inhibitory engagement implicating selective hippocampal inhibitory recruitment in supporting retrieval-driven spatial memory updating rather than elevated global activation.

Association between nurses’ knowledge and attitudes and caring behaviors toward people with opioid use disorder

Background Hospital nurses are crucial in inpatient OUD care, but knowledge gaps and negative attitudes may affect care quality. Few studies have examined the relationship between nurses’ knowledge and attitudes and their caring behaviors toward patients with OUD in hospital settings. Method We conducted a descriptive, exploratory cross-sectional study among hospital nurses at two northeast U.S hospitals. To explore nurses’ perspectives, we used validated instruments to assess knowledge and attitudes [DDPPQ] and caring behaviors [CBI-6]. DDPPQ and CBI-6 scores were treated as ordinal composite measures and summarized using medians and interquartile ranges. Group differences were examined across demographic and work-related factors using Mann–Whitney U and Kruskal–Wallis tests. Associations between DDPPQ and CBI-6 scores were analyzed using Spearman’s rank correlation with bootstrapped confidence intervals. Median (quantile) regression (τ = 0.50) was used to assess adjusted associations. Results A total of 125 nurses completed the survey. Most nurses were female (94%), white (82%), and employed full-time (87%). Higher DDPPQ scores, indicating lower knowledge and more negative attitudes, differed by years of experience and hospital site. CBI-6 scores varied by shift type, with permanent night-shift nurses reporting the highest median caring behaviors. Higher DDPPQ scores were significantly associated with lower caring behaviors (ρ = –0.42; 95% CI: –0.52 to –0.30; p  < 0.0001). Even after adjusting for shift type, years of experience, and hospital site, higher DDPPQ score remained significantly associated with lower CBI-6 score (β = –0.11; 95% CI: –0.16 to –0.06). Conclusion Hospital nurses with lower knowledge and more negative attitudes reported lower caring behaviors toward patients with OUD. These findings identify knowledge and attitudes as potential modifiable factors in inpatient OUD care and support future research to clarify causal pathways and explore the potential of educational and empathy-based strategies to improve OUD care.

Statistical optimization for removal of basic dyes from aqueous solutions using chitosan-assembled zinc oxide nanocomposite

Blood donation practices and behavioral intentions: A scoping review using the theory of planned behavior

Background Blood donation is vital for health systems, yet global shortages persist due to low donor participation. Understanding the psychological determinants of donation is critical to improving recruitment and retention. The Theory of Planned Behavior has been widely applied to predict donation intention and behavior. Objective This review aimed to map and synthesize the evidence on blood donation practices and behavioral intentions through the lens of the Theory of Planned Behavior, identifying key determinants, barriers, facilitators, and research gaps. Methods We conducted a scoping review guided by PRISMA-ScR. Major databases (PubMed, Web of Science, CINAHL, Cochrane, Hinari, and the WHO library) and grey literature were searched for studies published between January 1, 2004, and August 31, 2025. Eligible studies applied the theory of planned behavior constructs to blood donation practices across different populations and settings. Results Nineteen studies met the inclusion criteria. Most (n = 12) focused on students, while others examined healthcare workers or established donors. Cross-sectional designs predominated. Theory of planned behavior constructs, including attitude, perceived behavioral control, self-efficacy, moral norms, and anticipated regret were strong predictors of intention to donate blood. However, intention alone was insufficient to consistently predict actual donation behavior. Reported barriers included fear, low self-efficacy, and systemic challenges; facilitators included altruism, positive attitudes, social influence, and prior donation experience. Conclusion Theory of planned behavior provides a robust framework for understanding blood donation intentions, but augmenting it with moral norms and past behavior may improve the prediction of actual behavior. Interventions should target attitudes, perceived behavioral control, self-efficacy, and supportive social norms, while addressing systemic barriers, to strengthen voluntary donor recruitment and retention.

Concurrent Toxoplasma gondii infection and neuroinflammation in traumatic brain injury patients in a referral hospital in Douala Cameroon

Abstract Studies on murine models show that Toxoplasma gondii infection reduces cerebral microvascular perfusion and induces neuroinflammation by activating cerebral endothelial cells, which could affect traumatic brain injury (TBI) outcomes. Whether TBI inflammatory profile and outcomes differ in persons with concurrent latent infection with Toxoplasma gondii has not yet been elucidated in TBI patients, constituting the core of this study. Understanding the impact of chronic T. gondii infection on neuroinflammation after TBI may ensure better management and prognosis of TBI. This study aimed to investigate the inflammatory profile in TBI patients and investigate the influence of concurrent T. gondii infection on inflammatory markers and TBI outcomes. The level of inflammatory markers [interleukin (IL)-1β, IL-6, IL-10, interferon-gamma (INF-ɣ), Tumour necrosis factor-alpha (TNF-α)], and Toxoplasma gondii infection were detected in serum obtained < 24 h post-injury. Glasgow Outcome Scale-Extended (GOSE) was used to evaluate the 6-month outcome post-discharge. The Wilcoxon and Kruskal-Wallis’s rank sum tests were used to compare concentrations of inflammatory markers to T. gondii infection and TBI outcome. T. gondii infection was detected in 33% (52/160) of TBI cases. There was a significant increase ( p  < 0.001) in the concentrations of all inflammatory markers (IM) in TBI patients compared with the healthy controls. Higher levels of IL-6, INF-ɣ, and TNF-α were associated with mortality. Findings from this study show an increase in IM levels for all the T. gondii-positive TBI cases, which were significant for IL-1β ( P  < 0.001) and TNF-α ( P  < 0.001). IL-1β and TNF-α, had significantly greater density values, above 30pg/mL and 90pg/mL, respectively, in TBI patients infected with T. gondii , compared to greater density values, below 30 pg/mL and 90 pg/mL, respectively, for TBI patients seronegative to T. gondii. Concurrent T. gondii infection in TBI significantly influenced the inflammation profile of patients. Further multicenter studies with larger sample sizes will provide more insights into T. gondii induced neuropathology and prognostication in TBI care.

Factors influencing methamphetamine use among Lahu hill tribe youth in Chiang Rai, Thailand: A case‒control study

Background Methamphetamine (MA) use presents a significant public health issue that strongly affects human health and social security. Marginalized populations, including youth from the Lahu tribe, which represents the second-largest hill tribe living in the remote border areas of northern Thailand, are among the most vulnerable to MA use. This study aimed to determine the factors associated with MA use among Lahu youths aged 15–24 years who lived in Chiang Rai Province, Thailand. Methods A case‒control study was conducted to determine the factors associated with MA use among Lahu youths aged 15–24 years. The Lahu youths who used MA were considered cases of MA use, and those who never used MA were considered controls. The participants were randomly recruited from Mae Suai, Mae Chan, Mae Fah Luang, and Muang Districts, Chiang Rai Province, Thailand, the areas of Thailand most commonly populated by the Lahu people. A validated questionnaire was used to collect data, and multiple logistic regression was used to detect association factors with a statistical significance set at α = 0.05. Results A total of 136 cases and 272 controls were included in the study. The majority of the participants were male (79.4%), 77.9% held a Thai national identification card, and 24.0% had completed primary school. After controlling for age, those females were 5.29-fold (95% CI = 2.02–13.89) more likely to use MA than males. Those with easy-to-access MA had a 2.28-fold (95% CI = 1.14–4.54) higher likelihood of MA use than those who had difficulty accessing. Those who had no schooling had a 4.29-fold (95% CI = 1.17–15.73) higher likelihood of MA use than those who had vocational and university education. Those who were unemployed had a 3.92-fold (95% CI = 1.14–13.37) higher likelihood of MA than those who were students. Those who smoked or had ever smoked had a 29.08-fold (95% CI = 11.57–73.12) greater likelihood of MA use than those who never smoked. Those who drank alcohol had a 2.53-fold (95% CI = 1.05–6.11) higher likelihood of MA use than those who did not. Those who had high knowledge scores of MA prevention and control would be more likely to use MA than those who had lower scores (AOR = 1.29; 95% CI = 1.11–1.50). Conclusions An effective intervention and policy that focuses on females with low levels of education, unemployed, and having a history of substance use should be urgently developed and implemented to reduce MA use among Lahu youths.

Task difficulty influences heart rate variability: evidence from a pilot study using a multi-level mental arithmetic task

Validity of distress thermometer for caregivers of cancer patients in Saudi Arabia

Background Caregivers of cancer patients often face high levels of psychological distress, yet routine screening in clinical settings remains limited. The Distress Thermometer (DT) offers a brief and practical tool for identifying distress; however, its use among caregivers in Saudi Arabia has not been well studied. This study aims to validate the Arabic version of the DT in this population, determine its optimal cutoff scores, and explore associations with anxiety, depression, and demographic factors. Methods A cross-sectional study was conducted at King Saud University Medical City (KSUMC), enrolling 275 caregivers. Participants completed the Arabic versions of the DT and the Hospital Anxiety and Depression Scale (HADS). Receiver Operating Characteristic (ROC) curve analysis was used to assess the DT’s predictive validity for anxiety and depression, while multivariable regression identified predictors of distress. Results Clinically significant distress (DT ≥ 5) was reported by 44% of caregivers. Anxiety symptoms were present in 24%, and depression in 25%. DT scores were strongly correlated with HADS total (ρ = 0.618), HADS-anxiety (ρ = 0.537), and HADS-depression (ρ = 0.562) scores (all p < 0.001). The DT demonstrated excellent predictive validity, with an area under the curve (AUC) of 0.816 for anxiety and 0.818 for depression. The optimal cutoff scores were ≥5.5 and ≥6.5 for anxiety and depression, respectively. Female caregivers and those supporting patients with advanced-stage cancer reported significantly higher distress. Conclusion The Arabic version of the DT is a valid and practical tool for identifying psychological distress among cancer caregivers in Saudi Arabia. Its brevity makes it suitable for routine clinical use. Further research is necessary to develop effective distress screening and intervention programs, particularly for caregivers of patients with advanced cancer, to ensure timely psychological support.

Prediction-based attack detection and mitigation mechanism in power system

Enhancing recruitment and retention strategies in human tobacco research

Introduction Recruitment and retention of study participants in tobacco research studies is challenging, and many studies are not able to meet desired sample sizes, particularly since the COVID-19 pandemic. This survey study explored tobacco users’ motivations and expectations when considering participation in tobacco research and identifies common barriers to participation. Methods Participants were adult (21+) tobacco users recruited from a registry of potential research participants. In 2023, participants were emailed a survey to ascertain their motivations for participating in tobacco and health research, their expectations for participation, including compensation and barriers to participating. Means, medians, and proportions were calculated to describe the study population and outcomes. A binary variable for compensation importance was created and analyzed using logistic regression adjusting for demographic and tobacco use factors. Results Participants (n = 267) had a mean age of 46.9 years (SD 11.47) and were 67.4% female, 91.0% White, and 3.4% Hispanic. The majority smoked cigarettes (84.3%), while 34.5% reported electronic cigarette use. Most participants (79.4%) indicated interest in tobacco research because they wanted to quit or reduce smoking/tobacco use. Anticipated median compensation for completing a visit lasting one hour with questionnaires was $25, or $50 if a blood draw was included. Two-thirds (66.7%, n = 178) of participants viewed compensation as important. Younger age was associated with the perceived importance of higher compensation (OR=0.971, 95% CI: 0.949–0.993, p = 0.011). The most commonly reported barriers to participation were related to current work schedule issues (41.6%) and not having the ability to take off work when the research center was open (38.6%). Conclusion Most participants were interested in tobacco and health research for the intrinsic benefit of quitting or reducing smoking. Removing scheduling and transportation issues with remote research when possible, may increase participation rates. When intrinsic benefit is not available, appropriate compensation should be utilized to boost recruitment and retention rates.

Modeling discourse structure with 2D similarity-based random walks for improved understanding of online conversations

Abstract The proliferation of social media has made automated classification of online discourse, such as hate speech detection and polarity prediction, an essential task for maintaining digital safety and constructive discussions. However, online conversations are complex, context-dependent, and often structured in branching discourse trees, making such tasks especially challenging. Existing classification models typically rely on limited context sampling strategies that overlook the broader structure of discussions and the semantic relevance to the target utterance. In this paper, we introduce the 2D Similarity-based Random Walk, a novel context sampling method that explores multiple paths within discourse graphs to capture more comprehensive contextual information. Through empirical analysis, we show that the proposed 2D-walk covers a wider range of branches in the discourse compared to the traditional single-path (1D) baseline, resulting in samples that are structurally richer and contain a larger number of utterances. We evaluate our method on two benchmark datasets: Guest, for detecting misogynistic hate speech, and Kialo, for predicting the polarity of argumentative replies. Extensive experiments using GPT-4, a Multi-Head Attention model, and BERT confirm that 2D-walk consistently improves classification performance across both datasets compared to several baselines, including the 1D-walk, the no-context (0D) setting, and the random sampling strategy. Our findings underscore the importance of discourse-aware sampling and suggest that leveraging both structural and semantic relationships in conversation graphs is key to advancing robust language understanding in social media contexts.

Working conditions, job stress and work-related consequences among hospital employees—differences by professional group, working hours and job levels: A cross-sectional study

Objective Hospital employees face significant occupational stress that negatively impacts both their well-being and organizational outcomes. This challenge is amplified during times of staff shortages, economic difficulties and conflicting roles. To support hospital workers effectively and create a positive work environment, it is crucial to identify specific groups experiencing greater challenges. This study examines how working conditions, job stress, and related consequences vary across professional groups, working hours, and job levels within hospitals. Methods The study analyzed data from 406 employees (66% female) across three German hospitals, collected between December 2019 and January 2020 as part of the SEEGEN (Mental Health at the Hospital Workplace) study on mental health in hospital workplaces. Group differences in target variables were investigated via between-group one-way independent analyses of variance. Results Results showed that nurses, part-time employees, and non-leadership staff reported the most significant needs for improvement. Nurses experienced the lowest effort-reward balance, reduced job satisfaction, and the highest intention to leave their jobs. Part-time workers felt less control over their work decisions, perceived poorer cooperation among occupational groups, and reported a weaker psychosocial safety climate compared to full-time employees. They were also more irritated, less satisfied, and more inclined to consider leaving their jobs. Additionally, part-time workers rated their employers as less attractive and were less likely to recommend them. Leadership positions appeared to offer a protective effect against some of these negative outcomes. Conclusions In conclusion, this study provides a comprehensive view of the differing work stressors and consequences faced by hospital staff based on their roles, work hours, and job levels. These insights emphasize the importance of tailoring interventions to target specific groups within hospitals to enhance occupational health and create supportive work environments. Trial registration German Clinical Trial Register (DRKS): DRKS-ID DRKS00017249 (Registration Date: 8 th October 2019).