Operating Area Research Articles

Migración de serverbox hacia un sistema de microservicios aplicando arquitectura vertical

Efficient data management is essential in public administration for the effective operation of municipal cadastral systems. In 2010, the Multifinality Cadastral Modernization Program was implemented, a partnership between the Puebla municipality government and Sistemas de Información Geográfica S.A. de C.V. (SIGSA), which included the ServerBox platform. Over time, the monolithic architecture of ServerBox showed limitations in maintenance, updates, and change deployment. This project hypothesizes that migrating ServerBox to a distributed microservices architecture, using a vertical approach, can overcome these challenges and improve operational areas of the system. The proposed design establishes a modular and scalable structure that facilitates system maintenance and evolution. The implementation includes the development of TagHelpers in ASP.NET Core to simplify HTML element creation and the use of snippets to streamline coding. Additionally, a JSON configuration file is defined to manage multiple deployment environments. This strategic approach to migrating ServerBox to a distributed and vertical architecture offers significant advantages in terms of scalability, maintenance, and software development efficiency, and can serve as a guide for similar projects in public administration.

The V410L kdr allele in the VGSC confers higher levels of field resistance to permethrin in urban mosquito populations of Aedes aegypti (L.).

Females of Aedes aegypti transmit emerging arboviruses including Zika, dengue, yellow fever, and chikungunya. Control of these adult mosquitoes heavily relies on synthetic insecticides, including pyrethroids. However, insecticide resistance development in populations poses a significant challenge to vector control, particularly from knockdown resistance (kdr) mutations in the voltage-gated sodium channel (VGSC), the target of pyrethroids. This study investigated the field efficacy of Permanone, a pyrethroid-based insecticide, against Ae. aegypti by assessing the impact of three common kdr mutations (V410L, V1016I, F1534C) on mosquito survival under a real operational mosquito control scenario, by quantifying the pesticide delivered in the field. Field cage tests (FCTs) were conducted while conducting a realistic mosquito control application. Female mosquitoes from six operational areas from Harris County, TX, USA were exposed to Permanone delivered with a handheld sprayer. Permanone deposited near the cages was estimated from aluminum boats placed in the field during FCTs using gas chromatography-mass spectrometry (GC-MS). Mortality rates were recorded, and individual mosquitoes were genotyped for kdr mutations. A probit regression model was used to analyze the factors influencing mosquito survivorship. As the distance from the application source route increased, the amount of Permanone deposited decreased, resulting in higher survivorship frequency of Ae. aegypti females with the triple-resistant kdr genotype (LL/II/CC). The L allele at the 410-site significantly contributed to an increased resistance level when co-occurring with other kdr mutations. This study linked the survival probabilities of mosquitoes with different kdr genotypes, and the amount of pesticide they received in the field. Pesticide quantification, control efficacy results and genotyping allowed us to empirically determine the impact of genotypic resistance on vector control in the field. © 2024 Society of Chemical Industry.

Predicting atrial fibrillation within 7 years follow-up using machine learning models

Abstract Background The prevalence of atrial fibrillation (AF), the most common type of cardiac arrhythmia, has increased globally. AF is also the leading cardiac factor for several cardiovascular and cerebrovascular events. Early prediction and treatment of AF prevents major cardiovascular and cerebrovascular events. Purpose Our objective is to predict AF risk within 7-years follow-up using only twelve basic factors and applying machine learning (ML) models. Methods Data from the German epidemiological trial on ankle brachial index (getABI) were utilized in this work. GetABI includes 6,457 patients with mean age of 72.53 years. 3,985 individuals were assessed for AF of which 393 patients suffered from AF at 7-years follow-up. The feature selection was initially done manually, ending up in 45 features. The 10 best features were extracted from this dataset according to the SHAP (SHapley Additive exPlanations) values. The final features were body mass index, sensitive CRP, cholesterol, LDL-cholesterol, troponin I, NT-pro-BNP, glomerular filtration rate, ratio of triglycerides and HDL-cholesterol, gamma-GT, heart rate, including age and sex as major factors. The handling of missing values was achieved by SimpleImputer, estimating the mean values. XGBoost and Random Forest predicted AF. Logistic Regression was also used as a baseline model. The data were split into training and test set and ML models were applied for 100 iterative runs, extracting results with mean values. Results XGBoost was the most accurate model, predicting the AF with 71.19 % mean accuracy, 66.37 % mean sensitivity and 75.61 % mean specificity. Figure 1 depicts the performance of all models. Additionally, Receiver Operating Characteristic Curve (ROC) and Area Under Curve (AUC) for each model are presented in Figure 2. XGBoost also outperformed all the others models, achieving the highest mean AUC value, equal to 70.99 %. Contrariwise, logistic regression had the lowest overall performance. Conclusion ML models, specifically XGBoost, achieved accurate AF prediction in 3,985 individuals utilizing only twelve clinical-routine data.Evaluation results of each used model.ROC curve and AUC value of each model.

Respiratory rate-oxygenation index on the 3rd day is the best predictor of treatment failure in COVID-19 patients.

Predictors of outcomes are essential to identifying severe COVID-19 cases and optimizing treatment and care settings. The respiratory rate-oxygenation (ROX) index, originally introduced for predicting the failure of non-invasive support in acute hypoxemic respiratory failure (AHRF), has not been extensively studied over time during hospitalization. This multicenter prospective observational study analyzed COVID-19-related AHRF patients admitted to eight Italian hospitals during the second pandemic wave. The study assessed the ROX index using receiver operator characteristic curves and areas under the curve with 95% confidence intervals to predict treatment failure, defined as endotracheal intubation (ETI) or death. A total of 227 patients (69.2% males) were enrolled, with a median arterial partial pressure of oxygen (PaO2)/fraction of inspired oxygen (FiO2) ratio at admission of 248 (interquartile range: 170-295). Nearly one-third (29.5%) required ETI or died during hospitalization. Those who experienced treatment failure were older (median age 70 versus 61 years, p<0.001), more likely to be current or former smokers (8.5% versus 6.4% and 42.4% versus 25.5%, p=0.039), had a higher prevalence of cardiovascular diseases (74.6% versus 46.3%, p<0.001), and had a lower PaO2/FiO2 ratio at presentation (median 229 versus 254, p=0.014). Gender, body mass index, and other comorbidities showed no significant differences. In patients who failed treatment, the ROX index was higher at presentation and worsened sharply by days 3 and 4. Conversely, in patients who survived without requiring ETI, the ROX index remained stable and reduced after 5-6 days. The ROX index's predictive ability improved notably by the third day of hospitalization, with the best cut-off value identified at 8.53 (sensitivity 75%, specificity 68%). Kaplan-Meier curves indicated that a ROX index of 8.53 or lower on days 1, 2, or 3 was associated with a higher risk of treatment failure. Thus, a single ROX index assessment on day 3 is more informative than its variability over time, with values of 8.53 or lower predicting non-invasive respiratory support failure in hospitalized COVID-19 patients.

Examining thedrivers of forest cover change and deforestation susceptibility in Northeast India using multicriteria decision-makingmodels.

The increasing rates of forest cover change and heightened vulnerability to deforestation present significant environmental challenges in Northeast India. This study investigates the dynamics of forest cover changeand susceptibility to deforestation in this region from 2001 to 2021, utilizing data from the Hansen Global Forest Change (HGFC) productonthe Google Earth Engine (GEE) platform. A suite of multicriteria decision-making (MCDM) models-including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), and Weighted Aggregates Sum Product Assessment (WASPAS)-was employed to assess changes in forest cover and deforestation susceptibility across varied zones. Multicollinearity tests confirmed the relevance of the factors influencing deforestation. Statistical validations, such as the Wilcoxon Signed Ranks Test, underscored the models' robustness, revealing statistically significant outcomes. Additionally, Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) analysis demonstrated the superior fit of the VIKOR model (AUC = 0.938) compared to SAW (AUC = 0.901), EDAS (AUC = 0.895), and WASPAS (AUC = 0.864) in predicting current deforestation susceptibility. Validation affirmed the reliability of all MCDM methods, with VIKOR displaying high sensitivity (True Positive Rate, TPR = 0.878) and optimal AUC (0.938). Correlation analyses among the models identified significant inter-relationships, notably a positive correlation between EDAS and SAW, and a negative correlation between VIKOR and SAW. The regions of Assam, Nagaland, Mizoram, and Arunachal Pradesh were identified as experiencing significant forest cover loss, indicating a pronounced susceptibility to future deforestation. These findings underscore the need for immediate intervention to address this critical environmental issue.

Numerical investigation of the effects of short-crested irregular waves on the performance of a floating power capture platform

This paper presents a novel power capture platform concept consisting of a semi-submersible platform and multiple point-absorber wave energy converters (WECs). The primary objective of the current study is to investigate the dynamic behavior of the power capture platform under short-crested irregular wave conditions. A spreading function is used to modify the JONSWAP spectrum into a wave spectrum that accounts for both frequency and direction. To ensure the reliability of the numerical analysis, three-dimensional potential flow theory and boundary element method (BEM) are utilized to perform mesh convergence analysis and hydrodynamic validation of the platform and WEC models. Time-domain simulations are conducted to evaluate the effects of wave directionality on the platform motion, mooring line tension, and power absorption of the WEC array. In addition, three models, “single WEC”, “WEC array” and “fixed power capture platform” are defined. The influence of hydrodynamic interactions and platform motion are predicted by comparing the power absorption of individual WEC, WEC row, and WEC array among these models. The results show that the effects of wave directionality on the performance of the floating power capture platform cannot be ignored. The findings of this study may provide some insights into the design of power capture platforms. Meanwhile, it is recommended to determine the wave characteristics of the target operational area in advance, in order to find out the optimal design for system stability and power absorption.

Spatiotemporal Analysis of Complex Emission Dynamics in Port Areas Using High-Density Air Sensor Network.

Cargo terminals, as pivotal hubs of mechanical activities, maritime shipping, and land transportation, are significant sources of air pollutants, exhibiting considerable spatiotemporal heterogeneity due to the complex and irregular nature of emissions. This study employed a high-density air sensor network with 17 sites across four functional zones in two Shanghai cargo terminals to monitor NO and NO2 concentrations with high spatiotemporal resolution post sensor data validation against regulatory monitoring stations. Notably, NO and NO2 concentrations within the terminal surged during the night, peaking at 06:00 h, likely due to local regulations on heavy-duty diesel trucks. Spatial analysis revealed the highest NO concentrations in the core operational areas and adjacent roads, with significantly lower levels in the outer ring, indicating strong emission sources and limited dispersion. Employing the lowest percentile method for baseline extraction from high-resolution data, this study identified local emissions as the primary source of NO, constituting over 80% of total emissions. Elevated background concentrations of NO2 suggested a gradual oxidation of NO into NO2, with local emissions contributing to 32-70% of the total NO2 concentration. These findings provide valuable insights into the NO and NO2 emission characteristics across different terminal areas, aiding decision-makers in developing targeted emission control policies.

Comparison of Multi-Armed Bandit Algorithms in Advertising Recommendation Systems

In today's rapidly evolving online environment, advertising recommendation systems utilize multi-armed bandit algorithms like dynamic collaborative filtering Thompson sampling (DCTS), upper confidence bound based on recommender system (UCB-RS), and dynamic -greedy algorithm (DEG) to optimize ad displays and enhance click-through rates (CTR). These algorithms must adapt to limited information and update strategies based on immediate feedback.This study employs an experimental comparison to assess the performance of the DCTS, UCB-RS, and DEG algorithms using the click-through rate prediction database from Kaggle. Five experimental sets under varied parameter settings were analyzed, employing the Receiver Operating Characteristic (ROC) curve, accuracy, and area under the curve (AUC) metrics.Results show that the DEG algorithm consistently outperforms the others, achieving higher AUC values and demonstrating robust sample identification capabilities. DEG also exhibits superior precision at high recall levels, showcasing its potential in dynamic advertising environments. Its dynamic adjustment strategy effectively balances exploration and exploitation, optimizing ad displays.The findings suggest that DEG's adaptability and stability make it particularly suitable for dynamic ad recommendation scenarios. Future research should focus on optimizing DEG's parameter settings and possibly integrating UCB-RS's exploration mechanisms to enhance performance and develop more effective strategies for advertising recommendation systems.

Exploring a GIS-based analytic hierarchy process for spatial flood risk assessment in Egypt: a case study of the Damietta branch

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm.

Application of experimental planning methods for an analytical description of the areas of operability of marine electromechanical systems

The topic of the study is to consider the possibility of using experimental planning methods to mathematically describe areas of performance in relation to marine electromechanical systems. A definition is given and a graphic illustration of the field of operability is provided. It is shown that information about the boundary of the field of operability allows solving the most important tasks of controlling the state of ship electromechanical systems of various functional purposes. Possible ways of solving the problem of constructing a field of efficiency and the difficulties of their practical implementation are given. The method of analytical description of the operability domain is considered, which assumes an independent approximation of each hypersurface that makes up the operability domain. It is shown that for such an approximation it is convenient to use polynomial dependencies, which can be obtained as a result of using experimental planning methods. The main advantages of this approach are considered, including the possibility of solving the problem in the case of a high dimension of the space of primary parameters, in the space of which the area of operability is built. It is noted that in order to obtain a unified analytical description of the field of operability, the properties of logical R-functions can be used, which make it possible to make the transition from logical functions to analytical dependencies. It is proved that polynomial dependencies have the properties of R-functions and can be used in such a transformation. The resulting analytical description of the health area is universal and does not depend on the configuration of the area itself. Unlike the known methods of analytical approximation of the field of operability, it is characterized by an exceptionally low methodological error and allows us to solve with high reliability the problem of parametric synthesis of marine electromechanical systems according to the criterion of the reserve of operability, as well as the tasks of evaluating and predicting their condition during operation. The considered example clearly demonstrated the sequence of solving the problem of analytical description of the field of operability and allowed us to conclude about the complex configuration of this area even for special cases and the simplest electromechanical systems.

Seasonality in Sonoran pronghorn survival and movement within a managed rangeland

AbstractThe endangered Sonoran pronghorn (Antilocapra americana sonoriensis) has a large portion of its range within a military operations area in southwestern Arizona, USA. Sonoran pronghorn have been actively managed in this region for more than 20 years. Recovery efforts have included release of captive‐born pronghorn into areas both currently and historically occupied by wild pronghorn. These areas provide habitat for federally endangered essential and experimental non‐essential, referred to as 10(j), pronghorn populations. More than 20 years of monitoring efforts have resulted in a large dataset on their spatial occurrence and movement within these areas. To synthesize long‐term trends and seasonality in Sonoran pronghorn movement and mortality, we employed a suite of quantitative analyses that characterized the pronghorns' 1) individual and population‐level home ranges, 2) occurrence near active military targets, 3) trends in seasonal group sizes and composition, 4) sex‐ and group‐specific survivorship, and 5) changes in movement‐based behavior following release from captivity. We found strong seasonal trends throughout, including sex‐specific differences in seasonal movement rates, home ranges, survival, and group composition. Further, captive‐born pronghorn released into the endangered population exhibited markedly higher survival compared to those released in 10(j) areas. Captive‐born pronghorn exhibited significant seasonal use of active military target areas. These analyses, which represent the most comprehensive analysis of Sonoran pronghorn movement and survival to date, have important implications for the future conservation and management of this endangered species. Our results indicate that active management of endangered Sonoran pronghorn has successfully increased survival, and we recommend maintaining or increasing current recovery efforts, such as captive breeding and placement of supplemental resources throughout their range (e.g., freestanding water and supplemental forage), to further boost the survivorship of both wild‐ and captive‐born pronghorn. Moreover, future management efforts could use our seasonality results to create dynamic prediction models of when and where pronghorn are likely to overlap with military activities to best manage interactions. Our methods have added application to other mobile species of conservation interest occurring in disturbed and resource‐limited landscapes.

The recipe to sweet success: competitive advantages for a Spanish chocolatier, 1874–1910

Purpose The purpose of this paper is to unravel the success story of a family business, while engaging with debates in business and management research through the application of corporate strategy frameworks. Implement a structured methodology to evaluate a company’s strategic efforts and explore how businesses historically achieved competitive advantages over time. Design/methodology/approach This company analysis adopts a longitudinal approach on competitive advantages, moving beyond traditional cross-sectional business to transform static models into dynamic ones. It adheres to Michael Porter’s Value Chain model (1985) and his subsequent revisions (1996, 2001) to explore how competitive advantages emerge and are sustained. Data exploration leverages an extensive archival corporate collection comprising approximately 100,000 documents, enabling a thorough examination of value chain activities through primary and secondary sources. Findings Chocolates Amatller effectively channelled its competitive advantages through strategic operational areas, including purchasing cocoa at prices below market value, using strong marketing tools such as illustrative collectible cards and posters and implementing skilful financial strategies. Originality/value Examine why, when and how a Spanish chocolatier achieved a position of prominence among Spain’s foremost industrial figures by constructing Barcelona’s iconic Casa Amatller.

GENERAL RECOMMENDATIONS FOR THE SEARCH AND DETECTION OF EXPLOSIVE ORDNANCE IN THE CONDITIONS OF HIGH CONTAMINATION OF THE AREA WITH METAL FRAGMENTS

Currently, the enemy is using new mining tactics, when other sources of danger are additionally installed during mining, in particular with anti-personnel mines (APMs). This leads to accidents among sappers during operational demining. Therefore, there is an urgent problem of determining the procedure for searching for UXOs when the area is highly contaminated with metal fragments. An analysis of specialized literature has shown that the problem of searching, detecting and identifying UXOs both on land and in the water is the subject of close attention by both military specialists and researchers. Considerable attention has been paid to the testing and evaluation of metal detectors. However, the issue of searching for UXOs in highly contaminated areas with metal fragments, especially in areas of combat operations, has not been covered. The purpose of this article is to determine the procedure for organizing and conducting search and detection operations for UXOs in a highly contaminated area with nearby mines and metal fragments. At the same time, the risk of an emergency should be minimized. In this study, taking into account the fact of an increase in the number of accidents among deminers, it is proposed to adhere to the following recommendations when searching for and detecting UXOs in a highly contaminated area with metal fragments every working day before the start of the search for UXO, calibrate the metal detector to ensure confidence in the ability of the metal detector to distinguish between signals from the source of the hazard and nearby targets. Record the calibration of each metal detector in the calibration log; it is recommended to carry out work on the search for UXO using a metal detector within a 1-meter wide clearance strip using a base rail; it is recommended to mark the source of the hazardous signal along the edge of the search element of the metal detector, rather than determine the center of the signal; when searching for UXOs with high contamination of the area with metal fragments, it is recommended not to use probes, but to excavate the soil around the marked UXO using a shovel (scraper).

Charity Navigator launches new platform for donor portfolios

Charity Navigator, a leading nonprofit evaluator, has introduced a new platform designed to help simplify charitable giving and increase donor impact on the causes they care about. The platform, dubbed Causeway, will be managed by Charity Navigator's analysts, who select what the organization deems to be the most effective and efficient charities for inclusion in an individual donor's portfolio. Similar to investing in mutual funds, the group said, donors can create a giving portfolio of specific cause funds, with added assurance that their contributions will go to effective, vetted nonprofit organizations making documented progress in their areas of operation.

Research on AGV Path Planning Based on Improved Directed Weighted Graph Theory and ROS Fusion

This article addresses the common issues of insufficient computing power and path congestion for automated guided vehicles (AGVs) in real-world production environments, as well as the shortcomings of traditional path-planning algorithms that mainly consider the shortest path while ignoring vehicle turning time and stability. We propose a secondary path-planning method based on an improved directed weighted graph theory integrated with an ROS. Firstly, the production environment is modeled in detail to identify the initial position of the AGV. Secondly, the operational area is systematically divided, key nodes are selected and optimized, and a directed weighted graph is constructed with optimized weights. It is integrated with the ROS for path planning, using the Floyd algorithm to find the optimal path. The effectiveness and superiority of this method have been demonstrated through simulation verification and actual AGV operation testing. The path planning strategy and fusion algorithm proposed in this article that comprehensively considers distance and angle steering are simple and practical, effectively reducing production costs for enterprises. This method is suitable for logistics sorting and small transport AGVs with a shorter overall path-planning time, higher stability, and limited computing power, and it has reference significance and practical value.

Design of SRAM cell using an optimized D-latch in quantum-dot cellular automata (QCA) technology

A newer nanoscale technology called quantum-dot cellular automata (QCA) has been used by researchers to design digital circuits in place of the more traditional complementary metal–oxide semiconductor (CMOS) technology. This recent development in the technology change is due to the problems faced by CMOS technology in terms of power consumption and physical limitations. The advantages of QCA technology over CMOS technology are high density, low power consumption, high-speed operation, and less footprint area. This research provides a novel circuit for D-latch and static random access memory (SRAM) cells based on QCA technology. Initially, a D-latch circuit is proposed with a layout area of 0.01 μm2, a 0.5 clock cycle delay (latency), and a cell count of 18 QCA cells. Furthermore, an SRAM cell is proposed using the same D-latch circuit, which uses cell counts of 26 QCA cells and contributes to a layout area of 0.02 μm2 with a 0.75 clock cycle delay (latency). It is observed that our proposed circuits have a smaller layout area, fewer QCA cell counts, and a lower clock cycle delay (latency) than existing circuits.

Fine spatio-temporal prediction of fishing time using big data

Overfishing, bycatch, and other anthropogenic threats may lead to the destruction of fragile habitats and substantial losses of marine life. Marine fishery resources can be protected by adjusting fishing intensity and establishing marine reserves. Currently, China adopts the closed fishing season management approach to protect traditional fishing grounds, where fine spatio-temporal prediction is essential to efficiently supervise the wide scope. Fishing vessel behaviors reflect fishers’ experience as well as the information provided by fish detection radar, while the fishery resource distribution is relevant to the marine environment. In this study, we identified fishing vessel behaviors (gillnets, trawls, purse seines, and abnormal behaviors) and qualitatively assessed and predicted fishing time of different fishing vessel behaviors to search for high intensity fishing operation areas by constructing a time-space prediction model. The model was based on big data of fishing vessel automatic identification systems and3 the marine environment, and was verified in the East China Sea. The prediction results generally corresponded with the distribution of traditional fishery resources in the East China Sea and the fishing efforts provided by the Global Fishing Watch. This model can provide an accurate and effective refined fishing vessel operation time prediction, and benefits fishing management and fishery resources protection.

Implementation of independent learning campus independent certified internship program for strengthening 21st century skills

Implementation of the Merdeka Belajar Campus Merdeka Certified Internship Program in Strengthening 21st Century Skills is a way to strengthen skills in using media information as well as career and life skills. The aim of this research is to; (1) Describe the implementation of the MBKM certified internship program in universities, (2) Describe the mastery of 21st century skills among students participating in certified internships. This research is qualitative research with an analytical study approach. The results of this research show that first, in the implementation of MBKM, the certified internship program was implemented in three areas of activity, namely marketing, finance and operations, both in banking and companies. In implementing a certified internship, there are several stages, namely conversion of 20 credits, internship activities for 18 weeks, experience in the world of work and the professional world, a series of skills, mentoring, and obtaining a certificate of recognition for the skills and experience gained. Apart from that, during the implementation of the certified internship program there is an evaluation. Evaluation is carried out by following up on reports, providing mentoring, checking recaps of internship activities, sharing lessons, and conducting a final assessment of student performance. Second, the mastery of 21st century skills by students participating in certified internships focuses on the skills of mastering the use of technology, including the use of marketplace applications, the use of Microsoft office applications, the use of e-learning systems, e-commerce, design and so on. Meanwhile, mastery of career abilities and life skills is carried out through strengthening adaptation and social abilities, productivity and accountability, and providing leadership abilities and responsibility

Comparison of the efficacy of tibial transverse transfer and periosteal distraction techniques in the treatment of diabetic foot refractory ulcers.

To investigate the efficacy of comparing tibia transverse transport (TTT) and periosteal distraction in treating diabetic foot ulcers. A retrospective analysis of 19 patients with diabetic foot ulcers treated with both procedures between February 2020 and November 2022, 8 of whom were treated with the tibial transverse transfer technique (transfer group) and 11 with the osteochondral distraction technique (distraction group), was performed to compare and analyze the clinical efficacy of the two methods. All wounds were healed in both groups, and the healing time ranged from 15 to 41days with a mean of 28d. The limb preservation rate was 100%. The operative time, intraoperative bleeding, and pain score in the operative area were significantly less in the distraction group than in the removal group, with statistically significant differences (P < 0.05). Intra-group comparison between the two groups of patients after surgery revealed that the skin temperature, ABI, TcPO2, SWM and VAS of the affected limb were significantly improved compared with those before surgery, and the difference was statistically significant (P < 0.05). The expression levels of VEGF, bFGF, EGF and PDGF were significantly higher than before surgery in both groups, and the difference was statistically significant (P < 0.05). No statistically significant differences were found in skin temperature, ABI, TcPO2, SWM, VAS, VEGF, bFGF, EGF and PDGF between the two groups at the corresponding time points preoperatively and postoperatively (P > 0.05). The Periosteal distraction technique can significantly promote the healing of diabetic foot ulcers. It has the same efficacy as TTT in promoting the healing of diabetic foot ulcer wounds and improving the peripheral circulation of affected limbs. In addition, the periosteal distraction technique has the advantages of small trauma, simple operation, few complications, and convenient nursing care.

Predictive Value of Current Perception Threshold for Prognosis of Pulsed Radiofrequency in Patients with Acute Herpetic Neuralgia.

This study aimed to evaluate the prognostic accuracy of the Current Perception Threshold (CPT) in Acute Herpetic Neuralgia (AHN) patients receiving Pulsed Radiofrequency (PRF) therapy and to develop a corresponding prognostic model. We retrospectively analyzed data from 106 AHN patients treated with PRF between January 2022 and May 2023. The occurrence of Postherpetic Neuralgia (PHN) after treatment categorized patients into non-PHN and PHN groups. The predictive role of CPT indices for PRF outcomes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under Curve (AUC). Then the dataset was split into a training set (n=74) and a validation set (n=32). Factors associated with PHN development were identified using univariate and multivariate logistic regression. A nomogram model was developed using significant predictors and internal validation was performed using valid set data. Among the 106 patients, 45had a poor prognosis. Significant differences in age, preoperative Numerical Rating Scale (NRS) score, and 5Hz CPT ratio were observed between the groups (p<0.05). Logistic regression identified these factors as independent predictors for PRF prognosis (p<0.05). The 5Hz CPT ratio demonstrated predictive value (AUC= 0.764, 95% CI: 0.674-0.855). The nomogram model, incorporating these predictors, showed high AUC in both the training (0.863, 95% CI: 0.776-0.950) and validation sets (0.859, 95% CI: 0.721-0.998). Calibration curves indicated good model fit, and the Hosmer-Lemeshow test confirmed this (p>0.05). Decision Curve Analysis (DCA) highlighted the model's predictive advantage. The 5Hz CPT ratio can predict the prognosis of PRF in AHN patients. The nomogram model has high precision and clinical utility. It can help identify AHN patients with a poor PRF prognosis at an early stage and assist in clinical decision-making.