Operating Area Research Articles

Evaluation of barcode-assisted medication preparation technology for liquid medication doses

Abstract Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose The purpose of this study was to evaluate the outcomes associated with barcode-assisted medication preparation (BCMP) technology and practice workflows for oral syringe dose preparation in a health-system pharmacy department. Methods This evaluative study was conducted at a flagship quaternary academic medical center. An electronic medical record (EMR)–integrated BCMP workflow was implemented in the central pharmacy operational area to enhance the safety of oral syringe dose preparation. The primary endpoints assessed compliance with BCMP implementation and the rate at which potential preparation errors were identified. The secondary endpoints evaluated operational markers of dose preparation batching, information technology enhancement needs, and medication waste avoidance. Results A 95% rate of compliance with the BCMP workflow was observed over 2 years. The composite near-miss detection rate improved from year 1 to year 2 of implementation (0.89% vs 0.94%). The composite rate was influenced by increased yearly compliance with BCMP (93.8% vs 95.3%). A total of 176,679 preparations were reviewed in the 2-year period, including 81,240 in year 1 and 89,638 in year 2. The rate at which orders were rejected by pharmacists decreased over time (0.26% in year 1 vs 0.24% in year 2). Of the 1,005 wrong ingredient warnings, only 4 were overridden; in all other instances, the order was rejected at pharmacist checking due to use of an incorrect product in the preparation history. Wrong ingredient warnings led to canceled preparations in 96.1% of alert instances. Conclusion EMR-integrated BCMP technology aligned with safety efforts in the oral syringe dose preparation process reduced potential waste of medications and allowed insight into operational performance and volume indicators.

Controller influence on the fatigue of a floating wind turbine and load case impact assessment

Abstract The assessment of fatigue in Floating Offshore Wind Turbines (FOWT) is a complex and widely debated topic within the industry. The dynamic behaviour of FOWT is heavily influenced by sea and wind conditions, which can significantly challenge the achievement of structural integrity and performance objectives. Additionally, the interaction of blade aerodynamics and control strategies further complicates this assessment. This study evaluates the impact of different control strategies and blade formulations on both the expected real performance and the estimated fatigue of FOWT. While control strategies can influence both the expected real performance and fatigue estimations, the blade formulation primarily affects the accuracy of performance estimations without altering the actual expected performance. However, the blade formulation can significantly modify the fatigue estimation of the FOWT. Damage Equivalent Loads (DEL) calculation is a commonly used method for assessing fatigue. However, while individual DEL calculations are useful, they do not show the contribution of each load case to the overall fatigue, since they do not consider the probability of occurrence. Therefore, this paper proposes a new method of normalising DEL, allowing for comparison of loading cases and identifying operational areas that pose greater fatigue risks. The findings underscore the substantial impact that different control strategies and blade designs can have on fatigue and overall performance. Essentially, there is a trade-off between maximising power output and minimising fatigue damage.

Test Methodology for Short-Circuit Assessment and Safe Operation Identification for Power SiC MOSFETs

The short-circuit (SC) immunity of power silicon carbide (SiC) MOSFETs is critical for high-reliability applications, where robust monitoring and protection strategies are essential to ensure system safety. Despite their superior voltage blocking capabilities and high energy efficiency, SiC MOSFETs exhibit greater sensitivity to SC-induced degradation compared to their silicon counterparts. This increased vulnerability necessitates the precise assessment of the key SC performance metrics, such as short-circuit withstand time (TSCWT), as well as a deeper understanding of the failure mechanisms. In this study, a comprehensive experimental methodology for evaluating the SC behavior of SiC MOSFETs is presented and validated using industrial references. The investigation further explores the concept of a Safe Operating Area (SOA) under SC conditions, highlighting the significant impact of quasi-simultaneous SC events on device lifetime. Additionally, an application case study demonstrates how these events can drastically reduce the device’s lifespan.

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.

Remote patient-reported outcome measure triage score for monitoring disease activity and allocation of consultations in rheumatoid arthritis patients

Objective Currently, expedited by the coronavirus disease 2019 pandemic, there is high demand for allocating patients in a state of low disease activity to telehealth, ideally based on remote measurements. This cross-sectional study assesses the discriminative accuracy of the Rheumatoid Arthritis Impact of Disease (RAID) questionnaire regarding high and low disease activity. Furthermore, we aimed to optimize this classification, developing a remote triage score based on RAID and other patient-reported outcome measures (PROMs). Method Data were acquired from an outpatient clinic cohort of chronic rheumatoid arthritis patients at a large trainee hospital in the Netherlands. Patients were divided into high and low disease categories, based on 28-joint Disease Activity Score–C-reactive protein. Least absolute shrinkage and selection operator logistic regression were performed, including RAID item scores and other PROMs. Receiver operating characteristics curves and areas under the curve (AUCs) were obtained, and cut-off scores were based on predefined criteria of 90% and 95% sensitivity. Results In total, 278 patients were analysed, of whom 77.2% were identified as having low disease activity. RAID results correlated with DAS28-CRP, showing good performance. The regression model included the RAID items pain and functional disability assessment, and the self-reported swollen joint count (SR-SJC). With an AUC of 0.88 (95% confidence interval 0.84–0.92), this model performed better than the RAID total score. Conclusion A remote triage score based on a composite score of pain, functional disability assessment, and SR-SJC can detect a sufficient proportion of patients with low disease activity who can be allocated to remote consultations.

Comparative Study on NDT Techniques for Evaluation of Concrete Quality Exposed to Marine Environment

Concrete, the primary material used in quay walls, is directly exposed to saline environments. Coping concrete, particularly in areas where periodic berthing and loading/unloading occur, is prone to rapid quality deterioration. Current facility safety and maintenance guidelines assess concrete durability at specific points through sampling, which are intended to represent the entire inspection unit. This paper explores quality management strategies from an areal perspective by applying various non-destructive scanning methods to extensive areas of coping concrete. Ultrasonic array imaging and ground-penetrating radar scanning images revealed significant quality degradation in berthing operation areas, whereas sampling-based ultrasonic pulse velocity and rebound hardness values were less effective in detecting this degradation.

Knowledge Mapping of the Auxiliary Police: A Basis for Crafting a Capability Training Program

The auxiliary police force, particularly barangay tanods in the Philippines, faces significant challenges in effectively performing their roles due to limited formally training and capacity-building opportunities. This study was conducted to assess the level of knowledge among barangay tanods regarding their duties, responsibilities, roles as first responders, and patrolling and hazard identification and to develop a Capability Training Program tailored to address identified deficiencies. The need for this research arises from the observed gaps in advanced patrolling strategies and emergency response protocols, which hinder their effectiveness as community enforcers. Using a descriptive-quantitative research design, data were analyzed through regression analysis and descriptive statistics, including mean and standard deviation, using SPSS. The study employed adapted questionnaires targeting knowledge in key areas, such as duties and responsibilities, first responder actions, patrolling techniques, and hazard identification. Simple random sampling was applied, resulting in 140 barangay tanods participating as respondents. Findings revealed that although the overall knowledge of the respondents was high, specific gaps were evident in advanced emergency response and proactive patrolling strategies. These insights were instrumental in the development of a comprehensive Capability Training Program aimed at enhancing the effectiveness of police auxiliary services in critical operational areas.

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.

Improved A-STAR Algorithm for Power Line Inspection UAV Path Planning

The operational areas for unmanned aerial vehicles (UAVs) used in power line inspection are highly complex; thus, the best path planning under known obstacles is of significant research value for UAVs. This paper establishes a three-dimensional spatial environment based on the gridding and filling of two-dimensional maps, simulates a variety of obstacles, and proposes a new optimization algorithm based on the A-STAR algorithm, considering the unique dynamics and control characteristics of quadcopter UAVs. By utilizing a novel heuristic evaluation function and uniformly applied quadratic B-spline curve smoothing, the planned path is optimized to better suit UAV inspection scenarios. Compared to the traditional A-STAR algorithm, this method offers improved real-time performance and global optimal solution-solving capabilities and is capable of planning safer and more realistic flight paths based on the operational characteristics of quadcopter UAVs in mountainous environments for power line inspection.

Arithmetic Proficiency of Pre-Service Science Teachers: An Empirical Study

Mastery of arithmetic operations is fundamental for students pursuing science education, as these skills are essential in solving complex problems in physics, chemistry, and biology. However, gaps in students' arithmetic proficiency can hinder their academic and professional development. This study aims to examine the arithmetic skills of pre-service science teachers in solving mathematical problems across six domains: addition, subtraction, multiplication, division, exponentiation, and mixed operations. A total of 37 short-answer questions were administered, and the results were analyzed by domain. The findings indicate that students demonstrate proficiency in basic operations involving whole numbers, particularly in addition and subtraction. However, challenges persist in the areas of fractions, decimals, and mixed operations, where accuracy rates were notably lower. These gaps in understanding may affect students' ability to apply mathematical concepts in their science courses and future teaching roles. The study's limitations include a focus on quantitative results without exploring the cognitive processes behind student errors. Future research should investigate intervention strategies to address these weaknesses, potentially through targeted instructional approaches or the use of technology to enhance learning outcomes

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.

TECNOLOGIA DA INFORMAÇÃO E VANTAGENS COMPETITIVAS DE UMA EMPRESA NA CIDADE DE URUÇUÍ-PI

The environment of commercial activities is shaped by major developments in the world, such as globalization, the various commercial blocks, information technology, the diversity of the workforce, the status of emerging economies, the unstable political situation in various parts of the world, all this requires the manager / administrator / director of organizations to have adequate knowledge to deal with numerous situations. Selling more and with the best strategy is the pursuit of all organizations. The study in question aims to analyze your sales strategies and identify within your strategies, what are your competitive advantages, using information technology. The study was carried out from a bibliographic research, with analysis of a case study, in a qualitative approach, describing its process and its importance, as well as bringing suggestions for improvement for the company. The availability of technology allows companies of almost all sizes, sizes, stage of development, area of operation, in short, all, to have access to the most diversified types of technology, and this information regarding these technologies is much easier and accessible than in other times. E-commerce has won consumer confidence and results in an increase in the number of operations carried out by the large chain, mainly with the emergence of the pandemic. Using the right technology, companies have discovered the possibility of creating an e-commerce system that best meets customer expectations. Only possible, through information technology.

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.