Constraints Of Limited Resources Research Articles

Bridging the Knowledge Divide: Journalism Education and Industry Needs in East and Southern Africa

This study explores the perceived gap between journalism education and professional practice in Tanzania and Zambia. Through interviews with educators and journalists and an analysis of 12 journalism curricula, the findings reveal that both educators and journalists acknowledged a gap, with a shared desire for improved alignment between academic programs and industry needs. Educators expressed a commitment to incorporating contemporary content, but face challenges like limited industry collaboration and resource constraints. Journalists, however, observed a hesitancy among educators in implementing recommendations from the industry. Both groups see the need for integrating theory and practice into the curricula.

Internal Audit Function And Financial Accountability Of Laikipia County Government, Kenya: Application Of Internal Audit Independence

The public sector has experienced a growing demand for accountability and the need to optimize value within the constraints of limited resources. This research sought to assess the effect of internal audit function on financial accountability in the county government of Laikipia, Kenya. The specific objective of the study was to evaluate the effect of independence of the Internal Audit function on financial accountability of Laikipia County Government. The study targeted 105 employees working in the finance and economic planning department. Out of these, a sample of 51 employees were chosen and 48 questionnaires were duly filled and qualified for analysis. Data was gathered, sorted, coded, and entered on SPSS for analysis. Descriptive statistical analysis was applied to provide a summary of the data using mean as well as standard deviation metrics. Correlation and multiple regression analysis were employed to explore relationships and provide insights into the variables. The outcomes were presented using tables and charts. The questionnaire was found to be reliable, and the data was normally distributed and homogeneous, with no intercorrelation between the variables under study. The model adopted in the study was confirmed significant using ANOVA. Independence of the audit function was found to be a positive and significant predictor of financial accountability. The study recommended that policymakers should: enhance the independence of the audit function in Laikipia County Government by structurally separating the internal audit section from the Finance and Economic Planning department to strengthen its oversight capacity; implement measures to manage conflicts of interest, minimize management interference, and ensure adherence to auditing standards. To enhance effective financial accountability in the public sector, future research should examine factors influencing internal audit effectiveness

In Search of Best Practices for Improving the Operational Efficiency of the Primary Healthcare Hospitals in Thailand through Benchmarking

Background: Thailand's public health policy emphasizes equitable access to healthcare services, leading to a rapid increase in primary healthcare demands. Enhancing efficiency has become a crucial solution to address this challenge, especially amidst the constraints of limited resources. Aims: To measure the operational efficiency of sub-district or tambon health-promoting hospitals (THPHs) in the Eastern Economic Corridor (EEC) by applying the mathematical technique of Data Envelopment Analysis (DEA) and to identify best practices from efficient THPHs that can be applied to improve the operational efficiency of other THPHs. Methods: First, the operational efficiency of 104 THPHs in Chachoengsao, a province in EEC, was measured using the DEA method. Second, 13 efficient THPHs were selected as benchmarks for operational best practices. In-depth interviews were conducted with five individuals from each selected THPH, including the director and four key stakeholders. The interview data were analyzed and synthesized using directed content analysis to formulate a list of best practices. Finally, the identified best practices were evaluated using the Delphi technique to produce a final list of best practices to improve the operational efficiency of THPHs. Results: 76 best practices were initially generated from the content analysis of the benchmark interviews. However, after the Delphi experts' evaluation, 66 best practices met the required criteria (Mdn > 3.50 and IQR < 1.50) and were ultimately accepted as potential general strategies for improving the efficiency of THPHs. Of these, 35 best practices were related to input management, and 31 were related to output management.

Integrating AI in cause-of-death regular statistical production with human and expert system codings

Abstract Background Cause-of-death (CoD) statistics are key indicators in epidemiology and public health. These statistics are derived from death certificates completed by physicians and are usually coded by official statistics authorities according to the standards of the WHO ICD-10 classification to construct time- and cross-country-comparable statistics. For coding causes of death in free-text format in France according to ICD-10, predictions by deep neural networks (DNNs) are employed in addition to fully automatic batch coding by a rule-based expert system and to interactive coding by the coding team. Methods Seq-to-seq DNNs are trained from scratch on previously coded data to ICD-10 code multiple causes and underlying causes of death. Human coding is focused on certificates with a special public health interest or with low confidence in AI prediction quality to maximize the quality of the overall statistics disseminated when human resources are limited. DNNs also directly predict multiple causes and underlying causes of death for part of the certificates. Hence, the coding campaign aims to optimally allocate a coding mode to a given certificate. Results For deaths in 2021, 63% of the certificates are automatically batch coded by the expert system, 14% by the coding team, and 23% by DNNs. Compared to a traditional campaign that would have relied on automatic batch coding and manual coding, the present campaign reaches an accuracy of 95.7% for ICD-10 coding of the underlying cause (97.3% at the European shortlist level). Conclusions The 3-coding mode approach enables timeliness of dissemination of CoD statistics and may lead in the future to more responsive surveillance. Key messages • Deep neural networks trained on already coded data can be integrated into the regular statistical production of the CoD database in a fully controlled way. • The allocation between the different modes of coding can be optimized to achieve best quality and timeliness under the constraint of limited human resources.

How free trade pilot zones enhance agricultural green total factor productivity? Theory and evidence from China

IntroductionGiven the dual constraints of limited resources and environmental concerns, achieving green development in agriculture helps to enhance national food security, resource security, and ecological security.MethodsUtilizing panel data sourced from 30 provinces within China, spanning the years from 2001 to 2021, this paper employs the super-efficiency Slack-Based Measure (SBM) model and the Global Malmquist-Luenberger (GML) index to measure agricultural green total factor productivity (AGTFP). It utilizes methods such as the stepwise Differences in Differences (DID), mediation effect models, and moderating effect models to systematically explore the impact of the implementation of Free Trade Pilot Zones (FTPZs) on AGTFP and its mechanisms of action.ResultsThe study finds: (1) Establishing FTPZs significantly boosts AGTFP, indicating a profound positive influence; (2) The promotional effect of FTPZs on AGTFP is stronger in the eastern and central regions, as well as in major grain-producing areas; (3) FTPZs may enhance AGTFP by promoting the effect of agricultural structure upgrading, i.e., a transmission mechanism exists from FTPZs to the agricultural structure upgrading effect to AGTFP; (4) The agricultural scale effect plays a positive moderating role in the impact of FTPZs on AGTFP.DiscussionIt is advisable to optimize agricultural measures related to FTPZs, promote agricultural structural upgrading and scale enhancement, adapt strategies to local conditions to advance green agricultural development, and thereby promote the coordinated development of FTPZs and AGTFP.

A Multi-Objective Direction of Arrival Estimation Technique MinimizingEnergy Consumption in Wireless Sensor Network

Wireless Sensor Network (WSN) demand for secure communication is challenging due to its limited resource constraints. Hence, this research developed an effective distributed DOA estimation model through Direction Optimization Integrated Ranking Voting (DOIRV) to improve the performance of WSNs. The developed model comprises the multi-objective optimization model with the Whale technique for the WSN. The constructed DOIRV model uses objective function estimation with branch-and-bound for effective data transmission. The developed DOIRV model uses the Artificial Intelligence-based machine learning model for the DOA routing path computation and estimation. Finally, the DOIRV estimation is evaluated for the performance analysis with the consideration of the Cramer-Rao analysis for the data transmission in the WSN model. Simulation results stated that the proposed weighted technique significantly improves the network performance such as packet delivery ratio, throughput, and network delay. Analysis of the technique expressed that the proposed DOIRV technique exhibits effective performance rather than the conventional technique in terms of network delay, throughput, and packet delivery ratio. The comparative analysis stated that the performance of the proposed DOIRV model is ~13% higher than the conventional technique in terms of packet delivery ratio and ~18% higher for the throughput.

Structured Online Systematic Review Training for Medical Students: An Elective Module in Physiology.

Background Recently, elective posting has been introduced by the National Medical Commission (NMC) of India in the undergraduate competency-based medical education (CBME) curriculum. To successfully implement it in medical colleges, facilitators (medical teachers) need to commit extra time. Hence, this study aimed to evaluate the impact of online teaching-learning methods for implementing an elective module for undergraduate medical students at Burdwan Medical College and Hospital, West Bengal, India. Methods An online module for systematic review methods was developed using the Delphi method. This module was used to train 30 medical students divided into six groups. One resident and one facultyfacilitated each group. After the elective program of 15 days, program feedback and evaluation using the Kirkpatrick model were obtained from the students. Results A total of 30 undergraduate medical students with a mean age of 22.7±0.95 years participated in the study. All of them successfully conducted a systematic review per group. The students' feedback was 86.33% positive, and the project evaluation showed an 84% positive opinion. The highest score was for understanding, facilitators' knowledge, and experience. The lowest score was for the immediate applicability of the knowledge. Conclusion An online systematic review training module can be used for elective teaching-learning for final-year medical students, particularly within limited time and resource constraints. Students appreciated the module's clear objectives, appropriate complexity, and facilitators' expertise, leading to improved communication, engagement, and critical-thinking skills. Despite some limitations, these findings suggest that online learning can complement traditional methods and address logistical challenges in medical education, warranting further research on its long-term impact and broader applicability.

How the Global Burden of Animal Diseases links to the Global Burden of Crop Loss: a food systems perspective.

Food systems comprise interconnected webs of processes that together transform inputs (land, labour, water, nutrients and genetics, to mention just a few) into outputs such as nutrition and revenue for human societies. Perfect systems do not exist; rather, global food systems operate in the presence of hazards, biotic and abiotic alike, and under the constraint of limited resources to mitigate these hazards. There are, therefore, inefficiencies in these systems, which lead to losses in terms of monetary, nutritional, health and environmental values and create additional negative externalities in the health, social and environmental spaces. Health hazards in the food system do not respect arbitrary distinctions between the crop and livestock sectors, which are highly interconnected. These linkages exist where one sector provides inputs to another or through substitution effects where supply in one sector influences demand in another. The One Health approach advocates investigating the intersectoral hazards in a highly interdisciplinary manner. This article provides a conceptual framework for integrating the methodologies developed by the Global Burden of Crop Loss and Global Burden of Animal Diseases initiatives to generate burden estimates for hazards in food systems that better account for interconnectivity and foster an improved understanding of food systems that is aligned with the interdisciplinary nature of the One Health approach. A case study related to maize and poultry sector linkages in the wider context of public and environmental health is presented.

The Implementation of Senior High School Alternative Learning System: Basis for a Proposed Professional Development Plan for Teachers

The study assessed the Alternative Learning System (ALS) in Bulacan, focusing on learning delivery, resources, environment, and assessment to propose a professional development plan for teachers. Utilizing a mixed-methods approach, data were collected from 342 ALS implementers and learners through surveys and interviews. Findings revealed a diverse teacher demographic, predominantly female and single, with most having less than five years of experience and no recent seminar attendance. Most teachers held Bachelor's degrees, with some possessing Master's degrees, and a majority had passed the LET exam. Respondents rated ALS implementation as “fully implemented,” except for learners who rated the learning delivery and learning resources as “implemented”. As for significant differences among the respondents, ALS implementation has no significant differences among the four learning domains. Challenges included limited interaction, ineffective communication, curriculum mismatches, resource constraints, and high workloads. Overall, there was consensus on ALS implementation across respondent groups, highlighting strengths and areas needing improvement to enhance the program's effectiveness and teacher support. To effectively address the challenges the ALS program faces, it is essential to enhance instructional delivery through increased face-to-face interaction between students and teachers, alongside providing targeted training on ALS pedagogy for educators. Developing effective learning materials, ensuring adequate facilities, creating a separate ALS curriculum, and establishing clear assessment policies will help minimize distractions, support student engagement, and improve overall learning outcomes.

Pyrometallurgical Approach to Extracting Valuable Metals from a Combination of Diverse Li-Ion Batteries' Black Mass.

Li-ion batteries (LIBs) are widely used nowadays. Because of their limited lifetimes and resource constraints in manufacturing them, it is essential to develop effective recycling routes to recover their valuable elements. This study focuses on the pyrometallurgical recycling of black mass (BM) from a mixture of different LIBs. In this study, the high-temperature behavior of two types of mixed BM is initially examined. Subsequently, the effect of mechanical activation on the BM reduction kinetics is investigated. Finally, hematite is added to the BM to first be reduced by the excess graphite in the BM and second to form an Fe-based alloy containing Co and Ni. This study demonstrates that mechanical activation does not necessarily affect the kinetics of BM high-temperature behavior. Furthermore, it demonstrates that alloy-making by the addition of hematite is a successful method to simultaneously utilize the graphite in the BM and recover Co and Ni, regardless of the LIB type.

CFE-YOLOv8s: Improved YOLOv8s for Steel Surface Defect Detection

Due to the low detection accuracy in steel surface defect detection and the constraints of limited hardware resources, we propose an improved model for steel surface defect detection, named CBiF-FC-EFC-YOLOv8s (CFE-YOLOv8s), including CBS-BiFormer (CBiF) modules, Faster-C2f (FC) modules, and EMA-Faster-C2f (EFC) modules. Firstly, because of the potential information loss that convolutional neural networks (CNN) may encounter when dealing with miniature targets, the CBiF combines CNN with Transformer to optimize local and global features. Secondly, to address the increased computational complexity caused by the extensive use of convolutional layers, the FC uses the FasterNet block to reduce redundant computations and memory access. Lastly, the EMA is incorporated into the FC to design the EFC module and enhance feature fusion capability while ensuring the light weight of the model. CFE-YOLOv8s achieves mAP@0.5 values of 77.8% and 69.5% on the NEU-DET and GC10-DET datasets, respectively, representing enhancements of 3.1% and 2.8% over YOLOv8s, with reductions of 22% and 18% in model parameters and FLOPS. The CFE-YOLOv8s demonstrates superior overall performance and balance compared to other advanced models.

The Role of Metacognition in Character Education: A Case Study on Students’ Moral and Ethical Formation Strategies

Character education is essential in shaping students’ morals and ethics. This study aims to examine the role of metacognition in character education through a comprehensive literature review. Metacognition, encompassing metacognitive knowledge and skills, enhances the effectiveness of character education by providing strategies such as self-reflection, goal setting, self-monitoring, and self-assessment. The research employs a literature review approach, selecting articles and studies from credible and relevant sources. Data analysis addresses the main question of how metacognitive strategies can be applied to shape students’ morals and ethics. Key findings indicate that metacognition significantly contributes to character education, although challenges such as limited teacher understanding and resource constraints persist. Identified opportunities include developing teacher training programs focused on metacognition and character education and the potential for improved student learning outcomes. This study concludes that integrating metacognition into character education not only enhances the formation of students’ morals and ethics but also offers practical strategies for implementation in schools. Practical recommendations and areas for further research are presented for ongoing development in this field.

Integrated assessment of crop planting suitability: A case study in the Hetao Irrigation District of China using HJ-1A/1B satellite data

The increasing demand for food due to population growth and climate change poses significant challenges to achieve the Sustainable Development Goal of zero hunger by 2030. A key aspect in overcoming these challenges is to determine appropriate planting patterns for various crops, aimed at enhancing regional-scale crop water productivity despite the constraints of limited water and land resources. Remote sensing data and models provide the possibility for accurately estimating water productivity of different crops on a regional scale, but studies on remote sensing-based assessments of regional crop water productivity and its applications in agricultural management are still limited. In this study, we present a satellite-based integrated approach to assess crop planting suitability based on regional crop water productivity estimation. Focusing on the Hetao Irrigation District (HID) in the upper Yellow River basin, a representative irrigation district in arid region of Northwest China, we first use remote sensing data (HJ-1A/1B) to estimate water productivity for the two major crops, maize and sunflower, within the HID from evapotranspiration and yield estimates. Additionally, we introduce a novel crop planting suitability index based on the frequency distribution of crop water productivity, facilitating the determination of appropriate crop planting patterns. Our findings reveal that Dengkou, the periphery of Hangjinhouqi, and the southern part of Linhe are optimal for maize cultivation, while Wuyuan and the northern part of Linhe are ideal for sunflower cultivation. This is attributed to higher water productivity levels for maize in Dengkou (2.46 kg/m³) and Linhe (2.15 kg/m³), and for sunflower in Wuyuan (0.86 kg/m³). Following the optimization of crop planting distribution, the average water productivity for maize and sunflower increases by 7.6 % and 5.0 %, respectively. The proposed method can be generalized to other regions, and the results offer valuable insights for local governments in decision-making to regulate cropping pattern and maximize regional crop water productivity.

Vital Signs as Predictors of Oxygen Requirements in COVID-19 Outpatients: The Development of a Streamlined Risk Score.

With COVID-19 becoming a common disease, primary care facilities such as clinics are required to efficiently triage patients at high risk of severe illness within the constraints of limited medical resources. However, existing COVID-19 severity risk scores require detailed medical history assessments, such as evaluating the severity of pneumonia via chest CT and accounting for past and comorbid conditions. Therefore, they may not be suitable for practical use in clinical settings with limited medical resources, including personnel and equipment. The goal is to identify key variables that predict the need for oxygen therapy in COVID-19 patients and develop a simplified clinical risk score based solely on vital signs to predict oxygen requirements. A retrospective observational study of 584 outpatients with COVID-19 confirmed by polymerase chain reaction test visited Sasebo Chuo Hospital between April 28, 2022, and August 18, 2022. Analyses were conducted after adjustment for background factors of age and sex with propensity score matching. We used the Fisher test for nominal variables and the Kruskal-Wallis test for continuous variables. After adjusting for age and sex, several factors significantly correlated with the need for oxygen within seven days including body temperature (p < 0.001), respiratory rate (p = 0.007), SpO2 (p < 0.001), and the detection of pneumonia on CT scans (p = 0.032). The area under the receiver-operating characteristic curve for the risk score based on these vital signs and CT was 0.947 (95% confidence interval: 0.911-0.982). The risk score based solely on vital signs was 0.937 (0.900-0.974), demonstrating the ability to predict oxygen administration with no significant differences. Body temperature, advanced age, increased respiratory rate, decreased SpO2, and the presence of pneumonia on CT scans were significant predictors of oxygen need within seven days among the study participants. The risk score, based solely on vital signs, effectively and simply assesses the likelihood of requiring oxygen therapy within seven days with high accuracy. The risk score, which utilizes only age and vital signs and does not require a detailed patient history or CT scans, could streamline hospital referral processes for admissions.

Floating Solar Panel on Agriculture Pond

Floating solar power plants present an innovative solution for farmers facing constraints of limited land and water resources. This study assesses the feasibility of on-grid floating solar power plants for farmers, offering a sustainable and cost-effective energy source while conserving land area and improving water quality. Through technical, economic, and environmental analyses, this study demonstrates the viability of on-grid floating solar power plants, highlighting their potential to enhance farmers' livelihoods and contribute to rural sustainable development. Additionally, this paper introduces a novel approach by estimating the technical potential of floating photovoltaic systems (FPV) at the province/municipality level, focusing on water irrigation ponds, thus offering insights for localized implementation strategies.

Assessment the urbanization sustainability and its driving factors in Chinese urban agglomerations: An urban land expansion - Urban population dynamics perspective

Achieving urbanization sustainability is considered to be both an important component of the Sustainable Development Goals and a key way to address the conflict between limited resource constraints and urban continued growth. Regarding the urbanization sustainability, the impact of ecological environment and resource consumption has been widely discussed, while the holistic effect of urban land expansion and urban population dynamics is under-researched. This paper evaluated the urbanization sustainability of 15 urban agglomerations in China from 2000 to 2020, and applied the Geodetector model to investigate its impact mechanism. The results show that at the national level, the level of urbanization sustainability exhibited a trend of first increasing and then decreasing, accompanied by significant spatial differentiation. Spatially, the level of urbanization sustainability in urban agglomerations located in the northeast regions had strong variability during the study period. In contrast, urban agglomerations located in the central region had a lower level of urbanization sustainability due to the unrestricted expansion of urban land. In addition, urbanization sustainability varied according to the development stage of urban agglomerations. Specifically, urbanization sustainability showed a downward trend in the initial development stage, early growth stage and later growth stage of urban agglomeration, and upward trend in mature stage. Economic development level, foreign direct investment, industrial structure and urbanization level were the primary determinants of differences in urbanization sustainability at both national and regional levels. These findings may help to formulate the urban sustainable development planning and differentiated land use policies.

Enhancing patient safety: a system-based analysis of morbidity and mortality conferences in managing postoperative bleeding following gastric and pancreatic cancer surgery

Morbidity and mortality conferences (MMCs) have evolved beyond their traditional educational role to become instrumental in enhancing patient safety. System-based MMCs offer a unique perspective on patient safety by dissecting...

The Network Security in Wireless Sensor Networks: A Review

Wireless Sensor Networks (WSN) is an innovative technology predicts to be used ever more in the next to future due to their data achievement and data processing capability. Security for WSN requires to be considered in order to defend the functionality of this network such as the information it communicate and the position of nodes. The safety models &amp; protocols used in traditional networks are not appropriate to WSNs because of its limited resource constraints.

Utility of pudendal nerve electrodiagnostics in cases of bladder-bowel dysfunction- A retrospective study from a tertiary care center in Pakistan

Background and Objective:&#x0D; Electrodiagnostic studies play a crucial role in identifying neurogenic and non-neurogenic causes of bladder and bowel dysfunction. Such data is scarce in Pakistan. The objective of this study was to evaluate utility of pudendal nerve assessment in bladder-bowel dysfunction.&#x0D; Methods: &#x0D; A retrospective observational study was carried out at the neurophysiology lab in Aga Khan University Hospital. Patients referred for electromyography/nerve conduction studies (EMG/NCS) for pudendal nerve assessment from June 2013 to June 2023 were included. Clinical data, EMG/NCS results, and demographic information were analyzed using SPSS.&#x0D; Results: &#x0D; Twenty patients (11 male and nine female) were included. Five patients experienced backache radiating to one or both lower extremities, along with urinary or fecal incontinence. Three patients had urinary incontinence, and additional three presented with both urinary and fecal incontinence. Three patients reported perianal numbness. Four patients had fecal incontinence, while one patient each reported painful defecation and backache along with perianal numbness. Three patients were diagnosed with pudendal neuropathy, out of which one had a coexisting lumbosacral radiculopathy as well. Five patients had isolated lumbosacral radiculopathy. Twelve patients exhibited normal EMG/NCS results.&#x0D; Conclusion: &#x0D; This study highlights the diagnostic utility of EMG/NCS in diagnosing pudendal nerve injuries. Despite its widespread use worldwide, the utilization of these tests in Pakistan is hindered by factors such as limited awareness, inadequate training, and resource constraints.

Cluster-based RSU deployment strategy for vehicular ad hoc networks with integration of communication, sensing and computing

The integration of communications, sensing and computing (I-CSC) has significant applications in vehicular ad hoc networks (VANETs). A roadside unit (RSU) plays an important role in I-CSC by performing functions such as information transmission and edge computing in vehicular communication. Due to the constraints of limited resources, RSU cannot achieve full coverage and deploying RSUs at key cluster heads of hierarchical structures of road networks is an effective management method. However, direct extracting the hierarchical structures for the resource allocation in VANETs is an open issue. In this paper, we proposed a network-based renormalization method based on information flow and geographical location to hierarchically deploy the RSU on the road networks. The renormalization method is compared with two deployment schemes: genetic algorithm (GA) and memetic framework-based optimal RSU deployment (MFRD), to verify the improvement of communication performance. Our results show that the renormalization method is superior to other schemes in terms of RSU coverage and information reception rate.