Hasil untuk "Office management"

Wenfu Tang, Christine Wiedinmyer, Louisa K. Emmons et al.

Abstract Structure fires in the wildland–urban interface (WUI) are becoming more frequent and destructive, yet their emissions of air pollutants remain poorly quantified and are not included in national inventories. Here we present a conterminous-scale inventory of WUI-related structure fire emissions in the United States from 2000 to 2020. A small number of highly destructive events dominate structure fire emissions—the 20 most destructive fires account for 68% of total carbon monoxide emissions. Structure fire emissions are more spatially concentrated than vegetation fire emissions, and in several states emissions of specific hazardous air pollutants such as hydrochloric acid exceed those from all anthropogenic sources combined. We show that structure burning in wildfires is strongly influenced by fire-conducive weather, and destructive structure fires are more likely to occur in forested and urbanized landscapes. These results reveal structure fires as a major source of toxic air pollution, with important implications for air quality, public health, and fire management.

Guo J, Li Y, Xie D et al.

Jixiang Guo,1,2 Yiwen Li,1,2 Dongxue Xie,1,2 Mingyang Zhang,1 Simao Fu3 1Department of Surgical Anesthesiology-Division 1, Zhongshan People’s Hospital, Zhongshan City, Guangdong Province, 528403, People’s Republic of China; 2School of Nursing and Health, Henan University, Kaifeng City, Henan Province, 475004, People’s Republic of China; 3Dean’s Office, Zhongshan People’s Hospital, Zhongshan City, Guangdong Province, 528403, People’s Republic of ChinaCorrespondence: Simao Fu, Dean’s Office, Zhongshan People’s Hospital, 2 Sun Wen East Road, Zhongshan City, Guangdong Province, People’s Republic of China, Email 2059202645@qq.comObjective: The aim of this study was to comprehensively summarize the best currently available evidence by reviewing and analyzing the relevant literature in the area of care and maintenance of tracheostomy patients in the ICU. The evidence covers a wide range of aspects of postoperative care, complication prevention and management, rehabilitation support, and multidisciplinary collaboration for tracheostomy patients.Methods: Using the “ 6S” evidence-based model, we searched multiple databases. The search focused on evidence related to the care of tracheostomy patients, including maintenance, nursing measures, multidisciplinary collaboration, and quality improvement, with the time frame ranging from the inception of the databases to March 14, 2025. Two researchers independently evaluated the quality of the literature, extracted data, and summarized evidence from publications meeting the inclusion criteria.Results: A total of 12 relevant documents were retrieved, including 6 guidelines, 2 expert consensus papers, 1 best clinical practice guideline, 3 Meta-analyses. Through summarization and induction, 49 best evidence pieces were obtained across three major themes: maintenance and protection, nursing measures, and multidisciplinary collaboration and quality improvement. These were further divided into 15 sub-themes, covering equipment management, environmental optimization, infection prevention, postoperative care, airway humidification, suctioning, tracheostomy tube management, skin care, rehabilitation exercises, complication prevention, and daily assessments.Conclusion: This research systematically compiles the optimal evidence regarding the care and management of tracheostomy patients, offering a comprehensive foundation for evidence-based clinical practice. It assists healthcare professionals in developing personalized care plans, improving patient safety, reducing complications, and promoting recovery. Future research should focus on optimizing multidisciplinary collaboration, exploring nurse-led interventions, and addressing cultural and resource limitations to further enhance the standardization and personalization of tracheostomy care.Keywords: tracheostomy, care management, multidisciplinary collaboration, evidence summary, quality improvement, best practices

Qunjun Yu, Ya He, Luyan Li et al.

BackgroundAchieving universal health coverage remains a global health priority. Understanding factors that influence individuals' willingness to enroll in basic medical insurance is essential for system sustainability.ObjectivesThis study aims to examine the impact of policy awareness and institutional trust on the willingness of urban and rural residents to enroll in the Urban and Rural Residents Basic Medical Insurance (URRBMI), with implications for policy refinement. The goal is to improve the precision of policy implementation and encourage broader insurance enrollment, supporting system sustainability.MethodsA survey of 563 residents was conducted in a county of Yunnan Province, China. Descriptive analysis of respondent demographics was followed by multiple linear regression, using policy awareness, policy expectation and institutional trust as independent variables, and demographics as control variables, to identify significant factors affecting enrollment willingness.ResultsThe results of the survey showed that 87.4% of respondents were enrolled in the URRBMI. The regression model, with an adjusted R2 of 0.322, showed policy awareness (coefficient = 0.243, P < 0.001) and institutional trust (coefficient = 0.354, P < 0.001) significantly and positively influenced enrollment willingness. Age and annual household income were also significant factors.ConclusionPolicy awareness and institutional trust are key determinants of enrollment willingness, with age and income playing roles. Policy education and communication should be refined, leveraging big data for targeted outreach and flexible payment options to enhance enrollment and system sustainability.

Tat'yana S. Smolentseva

The article provides an overview of operations of the London office of the All-Russian Cooperative Society Limited (ARСOS Ltd.) in 1920–27. The author has analyzed the activities of the trade organization in the period from the beginning of its existence in June 1920 to the restriction of its operations because of the police raid on Arcos in May 1927. Special attention is paid to the years 1921–22, since ARСOS Ltd. had greater independence and represented the most unified structure at that time. The author has prepared diagrams showing the organizational structure of Arcos according to the data from the State Archive of the Russian Federation and the Archive of Foreign Policy of the Russian Federation. The article analyzes changes in the structure of the organization during that period, the processes of accepting orders for importing goods to Soviet Russia, and personnel policy, and also briefly describes the trading activities of the company, and enumerates some subsidiaries of Arcos. The author has come to the conclusion that the frequent change of the company’s structure is associated with a number of reasons, the simplest, most direct and working mechanism of records management in the first place. Within the framework of the organization’s personnel policy, priority was given to Soviet citizens or people ideologically loyal to Soviet Russia. From the very beginning of Arcos existence, and especially in 1923 and later, some departments that were engaged in narrowly focused work became more independent and left the company. The aspirations of the Trade Delegation to subjugate ARCOS Ltd. also played a role in the process of regular transformations in the organization’s structure. The author has concluded that despite all the differences in organizational, clerical, and personnel policy, the company achieved a significant increase in working capital and became the largest foreign trading association in the UK.

CAI Huiwen, LIU Lihong, YU Jing et al.

Innovative marine talents are the cornerstone of developing a leading maritime nation. Cultivating high-quality talent in marine science has become an urgent priority for higher education. Within this process, pedagogy remains a critical determinant of educational quality. Based on the theory of “micro-thinking”, this paper re-evaluates the fundamental concepts of teaching. From this perspective, innovation in higher education should originate from the core components of education: educators and students, teaching materials, and instructional processes. The aim of this paper is to further promote the course reform in environmental oceanography and foster educational innovations that contribute to cultivating highly qualified, well-trained marine science professionals for the society.

Emmanuel BOMBA DI MASUANGI, P. Atuba, S. Mulumba et al.

Introduction Sexual violence is a major public health issue with immeasurable consequences for survivors. In the Democratic Republic of Congo (DRC), sexual violence is strongly linked to armed conflicts, particularly in the eastern regions, where several studies have been conducted. However, less is known about the situation in the western part of the country. Purpose This study aimed to describe the epidemiological features, management, and health outcomes of sexual violence cases at the N’djili General Reference Hospital (HGR N’djili). Methods This was a retrospective descriptive study involving 483 consecutive survivors of sexual violence received at HGR N’djili between January 1 and December 31, 2021. Data were analysed using SPSS version 21. Qualitative variables were expressed as percentages, and quantitative variables as means with standard deviations. Results The mean age of survivors was 15.1 ± 5.4 years. The prevalence was higher among women (99.2%) than men. Rape was the main type of sexual violence (84.7%). The perpetrators had a mean age of 24.3 ± 10.2 years; 96% were male, of whom 82.4% were known to the victims (39.9% boyfriends, 20.1% neighbours, and 6.8% family members). Unintended pregnancies were recorded in 7.9% of cases, and HIV testing was positive in seven victims (1.5% of 475 tests performed). Victims were mainly referred to the care centre by the Public Prosecutor’s Office (37.7%) and the Congolese National Police (32.9%). Conclusion Sexual violence remains a serious public health problem, given the associated health outcomes, including sexually transmitted infections, HIV infection, hepatitis B virus, and unintended pregnancies. The survivors were mainly women and minors.

Lifang Guo, Rabia Bibi, Abeer Alshejari et al.

This paper introduces the idea of a cone <i>m</i>-hemi metric space, which extends the idea of an <i>m</i>-hemi metric space. By presenting non-trivial examples, we demonstrate the superiority of cone <i>m</i>-hemi metric spaces over <i>m</i>-hemi metric spaces. Further, we extend the Banach contraction principle and Krasnoselskii, Meir–Keeler, Boyd–Wong, and some other fixed-point results in the setting of complete and compact cone <i>m</i>-hemi metric spaces. Furthermore, we provide several non-trivial examples and applications to the Fredholm integral equation and dynamic market equilibrium to demonstrate the validity of the main results.

Inma Juan Pardo

AbstractCommunication is essential for organisations. The interaction of institutions with their publics and their reputation management depend on it. ‘An organisation that does not listen, or listens badly to its stakeholders and publics, will fail in its public communication,’ as Jim Macnamara says. This article deals with the listening work of the Opus Dei Information Office of the Basque Country and Navarra carried out in different phases: initiation, identification of interest groups, open listening, analysis of the findings, conclusions and transmission. It is offered as a good communication practice at the service of government that could be applied, with the necessary adjustments, to other institutions, especially Church communication offices. The text is divided into two parts: in the first, we review some concepts on institutional communication, governance, intangibles, reputation and listening, which serve as a framework; in the second, we summarise the case study, relying on interviews with people who were directly involved in the unfolding of events – Juan Carlos Mújika, the then director of the Office; Jesús Juan, who worked in the Prelature’s delegation; and Juan Manuel Mora, Vice Rector for Communication at the University of Navarra.

Larisa B. Mandzhikova

Introduction. The mid-to-late nineteenth century was witnessing further integration of Kalmyk Steppe and its society into the Russian state system. During the period under review, it was the Horde [Affairs] Department at Astrakhan Chamber of State Property (1848–1881) that became in charge of the administrative reform, with activities guided by the Kalmyk People’s Governance Regulations of 23 April 1847. The agency’s documents had compiled Collection И-6 (‘Horde [Affairs] Department at Astrakhan Chamber of State Property, 1832–1881’) at the National Archive of Kalmykia. Goals. The study seeks to investigate the reference apparatus to Collection И-6, analyze its structure and types of documents, identify common and distinctive features in record keeping at the newly created government body after the introduction of the 1847 Regulations, and the former’s source potential for historical research of state institutions in prerevolutionary Kalmykia. Results. The Regulations of 1847 established a clear division of powers between the Governor’s Office and Kalmyk elites, and sought to articulate certain division of powers in Kalmyk self-governance too. The Regulations specified directions of activity for structural units of the Horde [Affairs] Department, which had its impacts on workflow management essentials of the Kalmyk people’s governing body. The documents that resulted from the latter’s activities are related to official record keeping and their formatting patterns meet the requirements of that era. The archival documents included in Collection И-6 are a valuable source for further historical insights into how local public institutions in Russia would develop throughout the prerevolutionary period, and how Kalmykia’s administrative structures would evolutionize accordingly.

Shuochen Bi, Wenqing Bao

With the rapid growth of technology, especially the widespread application of artificial intelligence (AI) technology, the risk management level of commercial banks is constantly reaching new heights. In the current wave of digitalization, AI has become a key driving force for the strategic transformation of financial institutions, especially the banking industry. For commercial banks, the stability and safety of asset quality are crucial, which directly relates to the long-term stable growth of the bank. Among them, credit risk management is particularly core because it involves the flow of a large amount of funds and the accuracy of credit decisions. Therefore, establishing a scientific and effective credit risk decision-making mechanism is of great strategic significance for commercial banks. In this context, the innovative application of AI technology has brought revolutionary changes to bank credit risk management. Through deep learning and big data analysis, AI can accurately evaluate the credit status of borrowers, timely identify potential risks, and provide banks with more accurate and comprehensive credit decision support. At the same time, AI can also achieve realtime monitoring and early warning, helping banks intervene before risks occur and reduce losses.

Christofel Rio Goenawan

In the modern world, the development of Artificial Intelligence (AI) has contributed to improvements in various areas, including automation, computer vision, fraud detection, and more. AI can be leveraged to enhance the efficiency of Autonomous Smart Traffic Management (ASTM) systems and reduce traffic congestion rates. This paper presents an Autonomous Smart Traffic Management (STM) system that uses AI to improve traffic flow rates. The system employs the YOLO V5 Convolutional Neural Network to detect vehicles in traffic management images. Additionally, it predicts the number of vehicles for the next 12 hours using a Recurrent Neural Network with Long Short-Term Memory (RNN-LSTM). The Smart Traffic Management Cycle Length Analysis manages the traffic cycle length based on these vehicle predictions, aided by AI. From the results of the RNN-LSTM model for predicting vehicle numbers over the next 12 hours, we observe that the model predicts traffic with a Mean Squared Error (MSE) of 4.521 vehicles and a Root Mean Squared Error (RMSE) of 2.232 vehicles. After simulating the STM system in the CARLA simulation environment, we found that the Traffic Management Congestion Flow Rate with ASTM (21 vehicles per minute) is 50\% higher than the rate without STM (around 15 vehicles per minute). Additionally, the Traffic Management Vehicle Pass Delay with STM (5 seconds per vehicle) is 70\% lower than without STM (around 12 seconds per vehicle). These results demonstrate that the STM system using AI can increase traffic flow by 50\% and reduce vehicle pass delays by 70\%.

Di Wu, Haibo Zeng, Chao Lu et al.

Abdulrazak Mohammed, Jamila Yusuf, Mustapha Adeshina Ahmed

This study looked at the ICT manipulative competencies that OTM lecturers require for effective instructional delivery in public tertiary institutions in Niger State. One research question and a research hypothesis were formulated for the study. The study used a descriptive survey and included 36 OTM lecturers from three government-owned tertiary institutions in Niger State, Nigeria (Federal and State Polytechnics and Federal and State Colleges of Education). Due to the small population, the study has no sampling, but it was ultimately based on the 35 questionnaires that were retrieved after administration. The research instrument was validated by two research experts from Kwara State University, Malete. For reliability of the instrument, the research instrument was pilot tested at Kwara State College of Education, Ilorin, and Kwara State Polytechnic, Ilorin, and the data obtained was analyzed using Cronbach Alpha and the result gave 0.86. Data were gathered through the use of a questionnaire called “ICT Competencies Required (ICTCR)”. The research question was answered using the descriptive statistics Mean and Standard Deviation, and the inferential statistics t-test was used to test the hypotheses at a significance level of 0.05. The findings revealed a non-significant difference in the mean ratings of OTM lecturers on the ICT manipulative competencies required for effective instructional delivery in public tertiary institutions in Niger State, Nigeria, in the 21st century. This led to the conclusion that OTM requires a number of ICT manipulative competencies for effective instructional delivery in public tertiary institutions in Niger States, Nigeria, in the 21st century. Therefore, it was recommended, among other things, that, OTM lecturers should receive on-the-job training, particularly on how to operate information and communication technologies and how to use them for effective classroom instruction in the 21st century. In addition, the relevant regulatory bodies (NCCE, NBTE, and NUC) should add more ICT manipulative activities to the OTM curriculum to keep up with current ICT trends and prepare students for active roles in the 21st-century office.

Xiaosu Chen, Yanli Xu, Yan Xie et al.

Jiangnan Zhang, Hai Wang, Fengjuan Cui et al.

The establishment of ship trajectory prediction is critical in analyzing trajectory data. It serves as a critical reference point for identifying abnormal behavior and potential collision risks for ships. Accurate and real-time ship trajectory prediction is essential during navigation. Since the timing of automatic identification system (AIS) data is irregular, traditional methods usually use time calibration to simulate the data of uniform sequencing before analysis. Inevitably, this increases the chances of error and time delays. To address this issue, we propose a time-aware LSTM (T-LSTM) single-ship trajectory model combined with the generative adversarial network (GAN) to predict multiple ship trajectories. These analysis methods are capable of directly analyzing AIS data and have demonstrated better performance in both single-ship and multi-ship trajectories. Our experimental results show that the proposed method achieves high accuracy and can meet the practical navigation requirements of ships.

Georgios I. Papayiannis

The problem of asset liability management (ALM) is a classic problem of the financial mathematics and of great interest for the banking institutions and insurance companies. Several formulations of this problem under various model settings have been studied under the Mean-Variance (MV) principle perspective. In this paper, the ALM problem is revisited under the context of model uncertainty in the one-stage framework. In practice, uncertainty issues appear to several aspects of the problem, e.g. liability process characteristics, market conditions, inflation rates, inside information effects, etc. A framework relying on the notion of the Wasserstein barycenter is presented which is able to treat robustly this type of ambiguities by appropriate handling the various information sources (models) and appropriately reformulating the relevant decision making problem. The proposed framework can be applied to a number of different model settings leading to the selection of investment portfolios that remain robust to the various uncertainties appearing in the market. The paper is concluded with a numerical experiment for a static version of the ALM problem, employing standard modelling approaches, illustrating the capabilities of the proposed method with very satisfactory results in retrieving the true optimal strategy even in high noise cases.

Felix Lanfermann, Qiqi Liu, Yaochu Jin et al.

Implementing resource efficient energy management systems in facilities and buildings becomes increasingly important in the transformation to a sustainable society. However, selecting a suitable configuration based on multiple, typically conflicting objectives, such as cost, robustness with respect to uncertainty of grid operation, or renewable energy utilization, is a difficult multi-criteria decision making problem. The recently developed concept identification technique can facilitate a decision maker by sorting configuration options into semantically meaningful groups (concepts). In this process, the partitioning of the objectives and design parameters into different sets (called description spaces) is a very important step. In this study we focus on utilizing the concept identification technique for finding relevant and viable energy management configurations from a very large data set of Pareto-optimal solutions. The data set consists of 20000 realistic Pareto-optimal building energy management configurations generated by a many-objective evolutionary optimization of a high quality Digital Twin energy management simulator. We analyze how the choice of description spaces, i.e., the partitioning of the objectives and parameters, impacts the type of information that can be extracted. We show that the decision maker can introduce constraints and biases into that process to meet expectations and preferences. The iterative approach presented in this work allows for the generation of valuable insights into trade-offs between specific objectives, and constitutes a powerful and flexible tool to support the decision making process when designing large and complex energy management systems.

Paul Alexander Bilokon

In academic literature portfolio risk management and hedging are often versed in the language of stochastic control and Hamilton--Jacobi--Bellman~(HJB) equations in continuous time. In practice the continuous-time framework of stochastic control may be undesirable for various business reasons. In this work we present a straightforward approach for thinking of cross-asset portfolio risk management and hedging, providing some implementation details, while rarely venturing outside the convex optimisation setting of (approximate) quadratic programming~(QP). We pay particular attention to the correspondence between the economic concepts and their mathematical representations; the abstractions enabling us to handle multiple asset classes and risk models at once; the dimensional analysis of the resulting equations; and the assumptions inherent in our derivations. We demonstrate how to solve the resulting QPs with CVXOPT.

J. Jackson, L. Nowell

Abstract Aim The purpose of this study was to understand the experiences of nurse managers during the COVID‐19 pandemic. Background There is a growing body of knowledge about the experiences of clinical nurses during COVID‐19. However, there is less evidence about the experiences of nurse managers during the pandemic. Methods Eight nurse managers, from acute care and outpatient settings, completed semistructured interviews about how their roles had changed during the pandemic, how they felt about these changes, and what had gone well or been difficult. Each participant was interviewed once, for 20–60 min. We used thematic analysis methods to analyse the interview transcripts. Findings Nurse managers had to coordinate care in a context of uncertainty and guidance that changed frequently. Participants found that their roles and responsibilities either expanded to include more duties, or they were asked to take on a completely new role, with no orientation or training. Nurse managers were expected to provide support to their staff and patients, but did not necessarily receive support themselves. Participants were expected to plan simultaneously for care during the pandemic and for a return to normal working conditions. These factors contributed to challenging and difficult participant experiences of managing during COVID‐19. Conclusion Nurse managers' experiences during COVID‐19 are influenced by changes to their roles and the support they received. Nurse managers continue to support high‐quality care despite working a difficult context. Implications for nursing management Where possible, nurse managers can be supported to extend their roles or receive additional education and support if they are required to take on new responsibilities. Nurse managers require support in order to be a resource for their staff.