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Police emergency dispatch model based on emergency level analysis and traffic planning
Emergency dispatching and rescue during emergencies have become a hot research topic in the field of transportation planning. Therefore, to address the low efficiency of cross-regional police emergency dispatch, the study carries out relevant exploration on the basis of emergency event level analysis and transportation planning. The emergency rescue demand evaluation system is constructed using the superior and inferior solution distance method to carry out the emergency hierarchy analysis. The police emergency dispatch model is constructed and solved using the improved particle swarm algorithm. The validation revealed that the improved solution algorithm improved the iteration efficiency by 54.33% on average and reduced the iteration time overhead by 56.10% on average over the particle swarm algorithm and the beetle antennae search algorithm. In the scheduling of emergency 1, the material demand satisfaction rate of all demand points was above 80%, among which the vegetable material demand satisfaction rate was 100%. In the scheduling of emergency 2, the demand for supplies at all demand points was above 91.3%, with the demand satisfaction rate for tent supplies as high as 100%. The above results indicate that the police emergency dispatch method can leverage the full advantages of transportation networks. By integrating intelligent optimization algorithms with artificial intelligence technology, the method achieves material dispatch for cross-regional emergency rescue incidents. This method is both feasible and practical.
Phenotypic variations of naturally grown Iris persica L. accessions as revealed using multivariate analytical methods
Iris persica L. is a high-value ornamental species naturally distributed across montane regions of Iran, yet its intraspecific morphological variation remains underexplored. Understanding phenotypic diversity among wild accessions is critical for identifying superior genotypes suitable for conservation and horticultural breeding. This observational study was conducted on 78 naturally occurring I. persica accessions collected from seven ecogeographical regions of Markazi Province, Iran. Each accession represented a single independently growing individual plant, and 39 morphological and colorimetric traits were evaluated using multivariate statistical analyses. The results revealed considerable variation among accessions. Descriptive statistics showed that flower diameter ranged from 34.52 to 80.56 mm, fall length from 35.39 to 57.70 mm, and spathe length from 25.86 to 64.56 mm. Principal component analysis identified ten principal components explaining 82.46% of the total variation, with the first component (33.30%) driven primarily by flower size, fall length, and spathe length. The heatmap analysis clustered accessions into four distinct morphological groups, indicating clear phenotypic differentiation. Correlation analysis revealed significant positive associations between flower diameter and flower surface ( r = 0.87, p < 0.01), fall length and flower surface (r = 0.76, p < 0.01), and flower diameter and flower length ( r = 0.76, p < 0.01). Stepwise regression analysis indicated that fall length, flower diameter, and spathe length were key predictors of flower diameter. This study demonstrates extensive morphological diversity in I. persica , providing a strong basis for the selection of superior genotypes for ornamental breeding programs. Accessions such as ‘Alibolaghi-6’, ‘Sorkhe-4’, ‘Sorkhe-14’, ‘Shahbaz-11’, ‘Sorkhe-11’, ‘Sorkhe-12’, ‘Sorkhe-6’, ‘Palangdarreh-8’, ‘Sorkhe-5’, and ‘Bolagh-8’ exhibited outstanding floral characteristics and are recommended as potential candidates for future cultivar development and conservation strategies.
Bacterial profile and antimicrobial resistance patterns of bloodstream infections at Amhara Public Health Institute, Bahir Dar, Ethiopia
Background Managing bloodstream infections in resource-constrained regions like Ethiopia is challenging due to scarce blood culture surveillance data. To guide empirical therapy, this study determines the bacterial profiles and antimicrobial resistance patterns among patients with suspected bloodstream infections at the Amhara Public Health Institute. Methods This retrospective study analyzed blood culture records from the Amhara Public Health Institute spanning January 1, 2020, to December 30, 2023. Blood samples were processed using standardized manual culture techniques in accordance with World Health Organization (WHO) protocols. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method following Clinical and Laboratory Standards Institute (CLSI) guidelines. Statistical analysis was conducted using SPSS version 20, employing descriptive statistics and regression models, with statistical significance defined as p < 0.05. Results True bacterial pathogens were isolated from 50.3% (N = 340) of the 676 patients, with Gram-negative bacteria predominating (61.2%, N = 208) over Gram-positive bacteria (38.8%, N = 132). Notably, ESKAPEE pathogens accounted for 96.5% (N = 328) of all isolates, led by Klebsiella spp. (25.9%, N = 88), Enterococcus spp. (20.9%, N = 71), and S. aureus (15.6%, N = 53). Among Gram-positive isolates, high resistance was observed against oxacillin (74.5%, N = 41), penicillin (72%, N = 36), and vancomycin (51.1%, N = 24). Gram-negative isolates exhibited critical resistance to national frontline therapeutics, including ampicillin (100%, N = 24), ceftriaxone (92.4%, N = 157), and trimethoprim-sulfamethoxazole (89.4%, N = 126). Overall, multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) profiles were detected in 43.8% (N = 149), 30.5% (N = 104) and 5.3% (N = 18) of isolates with similar distributions observed among ESKAPEE strains. Sex and age were the only independent predictors of culture positivity, with female sex reducing bloodstream infection odds by 44% (p = 0.002). Conversely, neonates (≤ 28 days) and young adults (15–24 years) had 4.7 times (p = 0.001) and 9.5-times (p = 0.001) higher odds compared to elderly patients. Conclusions This study reveals a severe 50.3% (N = 340) bloodstream infection rate dominated by highly resistant Gram-negative and ESKAPEE pathogens, disproportionately affecting males, neonates, and young adults. Combating this threat requires immediate antibiotic stewardship, updated guidelines, and advanced laboratory testing (anaerobic culture, minimum inhibitory concentration, and molecular sequencing) to track and manage resistance.
Temporal trends in children pertussis burden in China and worldwide from 1990 to 2023: An analysis of the Global Burden of Disease Study 2023
Objective To evaluate the burden trends of children pertussis worldwide and in China from 1990 to 2023, and predict the disease burden for the next 10 years using a secondary analysis of Global Burden of Disease (GBD) 2023 data. Methods The primary metrics were mortality, disability-adjusted life - years (DALYs), prevalence, and incidence. A join – point regression model was used to estimate the average annual percentage change (AAPC). The autoregressive integrated moving average (ARIMA) model was used to predict the disease burden of pertussis from 2024 to 2033, and its adequacy was confirmed by the Ljung‑Box test. Results From 1990 to 2023, childhood pertussis mortality, DALYs, prevalence, and incidence declined sharply worldwide and in China. The global mortality rate in infants aged 1–5 months decreased by 57.7%, from 108.09 per 100,000 in 1990 to 45.73 per 100,000 population in 2023. Global age-standardized rates for both sexes, as well as those in all SDI regions, also showed steady downward trends. The rates of all four metrics peaked among infants aged 1–5 months in China and declined steadily with increasing age. For this infant group, the APC of pertussis prevalence and incidence in China decreased significantly during three different periods (1995–2004, 2009–2018, 2018–2021), but rose in two intervals (2004–2009, 2021–2023). ARIMA model projections revealed that age-standardized mortality and DALY rates will rise over the next decade, while prevalence and incidence will continue to decline. Notably, prevalence and incidence among infants aged 1–5 months are expected to increase slightly, rising from 277.59 and 2,026.43 per 100,000 in 2024 to 284.04 and 2,073.46 per 100,000 in 2033, respectively. Conclusion These findings underscore the disproportionate and persistent burden of pertussis in infants, indicating that prevention and treatment strategies should be adjusted to prevent further increase.
Leveraging free-text clinical records for heart disease classification through structured feature mapping
Hypertension and diabetes are major risk factors for heart disease, which remains among the leading causes of morbidity and mortality worldwide. Heart disease includes heart failure, myocardial infarction, stroke, and atherosclerosis. The identification and monitoring of these risk factors are crucial for early intervention and effective management. Machine learning techniques have the potential to improve the management and prevention of heart disease by enabling the automatic detection of risk factors, which in turn can help doctors personalize treatment and facilitate preventive interventions. In this study, heart disease risk factors were automatically extracted using a combination of multimodal data: both unstructured clinical narratives (e.g., the PrevComp corpus) and structured datasets (e.g., the UCI heart disease dataset) were used to predict the presence or absence of heart disease. The classification model is based on the Light Gradient Boosting Machine (LightGBM), a state-of-the-art implementation of the gradient boosting framework that employs tree-based learning algorithms. The developed classification model demonstrated a robust predictive accuracy of 83% for the presence/absence of heart disease, supporting its potential to accurately identify high-risk patients and improve clinical outcomes.
Path planning for mobile robots by fusing ant colony optimization and dynamic window approach
To address the problems of low global optimization efficiency and insufficient safety in local obstacle avoidance when mobile robots perform path planning in dynamic and complex environments, this paper proposes a path planning method fusing the ant colony optimization (ACO) and dynamic window approach (DWA), namely the ACO-DWA-DPP algorithm. Firstly, the environment is modeled using a 2D grid map. A potential field force-based heuristic function is introduced to optimize the guidance of path search, and a pheromone reward-punishment strategy and an adaptive evaporation mechanism are designed to improve the algorithm’s convergence speed and global optimization capability. Then, the planned path is subjected to secondary optimization, where redundant turning points are eliminated through connectivity checks to reduce the path length. Secondly, a dynamic collision risk coefficient is incorporated into the dynamic window approach, and the local obstacle avoidance evaluation function is improved to enhance the algorithm’s real-time response capability to dynamic obstacles. Simulation results show that, compared with the traditional ant colony optimization, the improved algorithm reduces the final converged longest path length by 41.26% ~ 48.28%, shortens the shortest path by 10.68% ~ 12.64%, decreases the number of iterations by 83.37% ~ 89.51%, and reduces the number of turning points by 66.94% ~ 81.37%. Moreover, the fused algorithm demonstrates the capability to respond to unknown obstacles in real time within the simulation environment, successfully avoiding them and meeting the requirements for the safe driving of mobile robots. The fused algorithm achieves an effective combination of global path optimization and local dynamic obstacle avoidance, providing a feasible solution for mobile robot path planning in complex scenarios.
An evaluation of a breastfeeding peer support service in North East England: A qualitative study with service users, practitioners and volunteers
Background Breastfeeding has health benefits for women and infants. Although the WHO recommends that infants are breastfed exclusively for the first six months, exclusive breastfeeding rates remain low in the UK, with many women stopping breastfeeding within six weeks of their infant’s birth. Many women face challenges initiating and continuing breastfeeding, including low confidence, limited support and misinformation. Breastfeeding peer support (BPS) services play a vital role in supporting women to continue to breastfeed by connecting new mothers with trained volunteers who offer advice, emotional encouragement and reliable information. Methods This study aimed to undertake a formative evaluation of the BPS service in Newcastle upon Tyne from the perspective of those who deliver the services, the wider healthcare team and mothers’ experiences of utilising the service. This evaluation used a qualitative design, consisting of one-to-one semi-structured interviews with practitioners, volunteers, healthcare professionals and service users. Recruitment took place between 28 th March – 14 th May 2025. Recorded interview data were transcribed verbatim and analysed using Braun and Clarke’s coding reliability thematic analysis. Results Twenty-two interviews were conducted (n = 11 practitioners, volunteers and healthcare professionals and n = 11 service users). Analysis identified four themes: mechanisms of the service; support offered by the service; outcomes of the service, and challenges to service delivery. Overall, the BPS was considered a supportive service by participants. Conclusions The normalisation of breastfeeding was seen as crucial to the service, while service users described that the emotional support provided helped to increase their confidence in breastfeeding. Challenges were identified for the service, including engaging those aged under 25 years and those for whom English is a second language. These findings will be used to inform the future development of the service.
The effectiveness of a knowledge graph-based lifestyle intervention recommendation system in improving body composition, muscle strength, and physical function in sarcopenic obesity: Study protocol for a randomized controlled trial
Background Sarcopenic obesity (SO) is a complex condition characterized by the coexistence of sarcopenia and obesity, with pathophysiological mechanisms extending beyond the additive effects of either condition alone. Lifestyle intervention is considered an effective management strategy for SO; however, substantial interindividual variability in physiological status and behavioral preferences limits the implementation of personalized intervention. This study aims to evaluate the effectiveness of a knowledge graph-based lifestyle recommendation system in improving skeletal muscle mass and related outcomes in patients with SO. Methods This randomized controlled trial will recruit 208 patients with SO, who will be randomly assigned in a 1:1 ratio to an intervention or control group. In addition to routine lifestyle guidance, the intervention group will receive a 24-week personalized intervention delivered through the Sarcopenic Obesity-Knowledge Graph Care System (SO-KGCS), whereas the control group will receive routine health education and lifestyle advice only. The intervention period is defined as the 24-week intervention period from baseline to week 24. The primary outcome measure is skeletal muscle mass. Secondary outcome measures include grip strength, skeletal muscle mass index, body fat percentage, physical function, and quality of life. Outcomes will be assessed at baseline before randomization and at weeks 8, 16, and 24 during the 24-week intervention period. The intervention will end at week 24, after which participants will enter a 24-week post-intervention follow-up period without systematic intervention. Follow-up outcome data will be collected at week 48. Discussion This study will evaluate the effectiveness of a knowledge graph-based recommendation system in enhancing body composition, muscle strength, physical function, and quality of life in patients with SO. If effective, the SO-KGCS may provide a feasible intelligent approach for personalized chronic disease management. Trial registration ChiCTR, ChiCTR2500111882.
Understanding the underuse: Barriers to vacuum-assisted birth among clinicians in Tanzania: An exploratory qualitative study
Background Vacuum-assisted birth (VAB) is a critical obstetric intervention for saving the lives of the mothers and newborns, particularly in cases of prolonged second-stage labor, maternal exhaustion, or fetal distress. Despite its proven benefits, VAB remains underutilized, contributing to an increased rate of unnecessary cesarean sections, some of which could be avoided with timely vacuum extraction. This study aimed to explore the barriers to the use of VAB among clinicians at a tertiary hospital in Tanzania. Materials and Methods An exploratory qualitative study using in-depth interviews (IDIs) was employed. Twelve clinicians with relevant experience in vacuum-assisted birth were recruited purposively into the study. A semi-structured IDI guide was used to facilitate the interviews. Data were analyzed inductively using thematic analysis to identify key patterns and categories related to barriers in the use of VAB. Results Organizational and individual barriers were identified as key challenges to the use of VAB. Organizational barriers included insufficient availability of VAB equipment, ineffectiveness of the available devices, and poor team dynamics that hindered collaborative decision-making regarding VAB use. Individual barriers centered on clinicians’ apprehension about potential adverse outcomes, along with limited skills and practical experience in performing VAB procedures. Conclusion The utilization of VAB by clinicians is hindered by both organizational and individual barriers. Addressing these challenges through improved availability of functional equipment, enhanced training to build clinicians’ skills, and improving working conditions has the potential to increase the use of VAB. Strengthening these areas could help reduce the rate of unnecessary caesarean deliveries.
Pilot study: The effect of eight weeks of aerobic training in the two phases of light and dark circadian rhythm on genes (OCT4, NANOG, SOX2, REX1) in bone tissue of diabetic mice
Introduction Diabetes mellitus impairs bone metabolism through chronic hyperglycemia, oxidative stress, and inflammation, leading to reduced osteoblast activity and downregulation of key pluripotency genes such as Octamer-binding transcription factor 4 (OCT4), Nanog homeobox (NANOG), SRY-box transcription factor 2 (SOX2), and Reduced expression protein 1 (REX1).The present study investigated whether the timing of aerobic exercise (morning vs. evening) influences the expression of pluripotency genes in the bone tissue of diabetic mice. Methods Eighteen male NMRI mice were assigned to healthy control, diabetic control, or diabetic exercise groups. Diabetes was induced using a high-fat diet combined with low-dose streptozotocin. Aerobic training was performed for eight weeks at either ZT3 (morning) or ZT15 (evening), five sessions per week, at 50–60% Vmax. Blood glucose, insulin, HOMA-IR, and maximum running speed were assessed, and gene expression in bone tissue was measured using qRT-PCR. Data were analyzed using one-way ANOVA with Tukey post hoc testing (p < 0.05). Results Diabetic mice exhibited significant increases in glucose, insulin, and HOMA-IR, along with marked reductions in pluripotency gene expression, particularly at ZT3. Aerobic exercise significantly improved metabolic parameters and partially restored gene expression, with the greatest enhancement observed at ZT15. SOX2 and REX1 showed the most robust recovery under evening training conditions. Conclusion The findings indicate that circadian timing modulates the beneficial effects of aerobic exercise on pluripotency gene expression in diabetic bone tissue. Evening exercise (ZT15) exerts superior restorative effects, suggesting that chronobiology aligned training may serve as an effective strategy for improving bone regenerative potential in diabetes.
Impact of semaglutide withdrawal on cardiometabolic profile and physiology of energy balance: Recovery effects after semaglutide termination – The REST trial study protocol
Background Glucagon-like peptide-1 (GLP-1) receptor agonists such as semaglutide have been shown to induce substantial weight loss and improve cardiometabolic risk factors in patients living with obesity. However, most individuals regain weight after abrupt withdrawal of semaglutide, with reversal of its beneficial cardiometabolic effects. Methods We propose a randomized controlled trial to determine whether a gradual dose reduction of semaglutide prior to complete discontinuation is associated with differential changes in weight and cardiometabolic profile as compared to immediate treatment cessation. Individuals living with obesity without preexisting cardiovascular disease who are receiving semaglutide for weight management and have achieved prior weight reduction of at least 10% with no further weight loss over past 12 weeks will be randomized to either gradual dose reduction over 16 weeks or abrupt treatment discontinuation. The primary outcome will be the difference in body weight change (%) between the study groups. Secondary outcomes will include 24-hour ambulatory blood pressure and fasting ghrelin levels. Discussion We hypothesize that gradual reduction of semaglutide will be associated with less weight regain and cardiometabolic deterioration compared with immediate cessation. This study addresses an important real-world problem regarding treatment discontinuation strategies and may inform future approaches for long-term obesity management. Trial registration NCT07294950 (ClinicalTrials.gov).
Model-free predictive control for PMSM based on a nonlinear autoregressive exogenous model and an adaptive recursive least squares algorithm
This paper proposes a novel nonlinear autoregressive with exogenous input-based adaptive recursive least squares model-free predictive control (NARX-ARLS-MFPC) strategy for permanent magnet synchronous motor (PMSM) drives. The core challenge addressed is the performance degradation of conventional model predictive control (MPC) under inevitable motor parameter mismatches. The proposed method integrates the NARX model with an ARLS algorithm featuring a variable forgetting factor to dynamically track system changes. Comprehensive simulation studies validate the superior robustness of the strategy. Under significant inductance and flux linkage mismatches, the proposed method reduces current total harmonic distortion (THD) by 28.3% and 12.3% compared to conventional finite-control-set model predictive control (FCS-MPC) and a baseline control method, respectively. It maintains stable performance under moderate sensor noise with appropriate tuning. During load transients combined with resistance and inductance mismatches, it achieves THD reductions of 24.1% and 15.7% versus the two benchmark methods, respectively. Statistical analysis under parameter perturbations confirms its overall superior performance across key dynamic and steady-state metrics. The results demonstrate that the synergistic integration of the nonlinear model and adaptive identification effectively suppresses current harmonics caused by model inaccuracies while enhancing dynamic performance.
Chiral Phosphoric Acid-Catalyzed Asymmetric Hydrogenolysis of C–O Bonds
Experimental emergence of conventions in human dyads
Conventions can be defined as arbitrary and self-sustaining practices that emerge in a population and facilitate solving coordination problems. A recent study traced the formation of simple conventions in captive baboons in a touch-screen-based color-matching ‘game’. We replicated this task with human pairs under different conditions (with/without visual access to the partner’s screen; with/without prior information on the task structure) to assess their effects on the formation and stability of conventions. We found that more information delayed the formation of conventions (arbitrary rankings of colors that determined choices in any given color pairing). Analysis of self-reported strategies did not reveal a clear effect of condition on levels of elicited strategic behavior. Interestingly, pairs maintained their conventions even when given visual access to their partner’s screen, despite the availability of an alternative, potentially simpler, cognitive strategy. In a follow-up variant of the task that paired up experienced subjects with a naïve partner, conventions emerged faster but did not replicate the color hierarchy convention of the experienced player, demonstrating the transmission of “know-how” but not “know-what” information. We discuss the implications of our results for understanding the cognitive mechanisms necessary to support the formation, maintenance, and transmission of conventions.
Trimethylammonium-Substituted Amphiphilic Pillar[ <i>n</i> ]arene Channels for Selective Water Permeation
In vivo changes in zebrafish anesthetic sensitivity in response to the loss of kif5Aa are associated with the alteration of mitochondrial motility
Anesthetic and sedative drugs are small compounds known to bind to hundreds of proteins. One intriguing binding partner of propofol is the motor domain of a neuronal mitochondrial transport kinesin, kif5A. Here, we used zebrafish wild type (WT) and kif5Aa knockout (KO) larval behavioral assays to assess anesthetic sensitivity and combined that with zebrafish primary neuronal cell culture to probe for alterations in mitochondrial motility. We found that the loss of kif5Aa increases behavioral sensitivity to propofol and etomidate, with etomidate hypersensitivity greater than propofol. In contrast, kif5Aa KO animals were resistant to the behavioral effects of dexmedetomidine. Finally, WT and kif5Aa KO larvae responded similarly to the behavioral effects of ketamine. Propofol inhibited the anterograde motility of mitochondria in WT zebrafish neurons, while etomidate inhibited mitochondrial motility in both anterograde and retrograde directions; neither drug altered mitochondrial motility in the kif5Aa knockout (KO) neurons. In contrast, dexmedetomidine enhanced retrograde mitochondrial motility in both WT and kif5Aa KO animals. Finally, ketamine had little significant effect on mitochondrial motility in either mutant or WT animals. These data demonstrate that each anesthetic/sedative drug affects the motor protein machinery uniquely and is associated with unique changes in behavior. Understanding how different anesthetic compounds alter neuron motor proteins will be important in defining how anesthetics alter neuronal signaling and energetic dynamics.