Effective Implementation Research Articles

Inflation in Eurozone, Converging and Diverging Countries

The paper analyses the progress eurozone members made towards the convergence of inflation rates, which is a necessary condition for the effective implementation of the common monetary policy broadly appropriate for all members. It was expected that the common monetary policy would lead to the convergence of member states’ economic performance, including inflation rates. The literature review shows that the majority of authors agree that a significant convergence process occurred before 1999, but no further progress was made after that. Our analysis indicates that inflation processes in member countries are diverse. Namely, monetary stability has been achieved in some countries, while inflation is more volatile in others. There is an insufficient correlation between inflation rates, the different transmission of shocks to inflation and different exposure to risks of rising energy and food prices. We conducted a unit root test on the series of inflation differentials for each country to determine which countries were in a process of absolute convergence. In the group of the first 12 members, we found evidence of convergence for the majority of countries, as there is no unit root. Thus, individual countries indeed made progress toward greater monetary stability (and the EMU level). We examined the standard deviations of the inflation differentials in the group of converging countries (separately for converging core and peripheral countries) and found no evidence that these groups of countries are becoming more homogeneous. In the group of new EMU members, we found evidence of convergence towards the EMU average for only four countries in the period of their membership, but not in the previous period.

Earthquake, social disorder, violence

Natural disasters appear as unexpected, traumatic events that break the normal flow of life; these events cause changes in the social structure in the region. There are two alternatives for this change. The first alternative is social unity, the other is social disorder. The purpose of the study is to explain the violent events that occurred after the earthquake in Kahramanmaraş on the 6th of February 2023, through the theory of social disorder. The literature on relevant subjects will be searched and the violent events displayed in the media will be explained in the context of social disorder theory in this study. The increased rates of violence and crime in the long-term period after disasters have been detected by the researchers and this situation has been explained with the theory of social disorder. The social disorder theory emphasizes that the increased stress burden causes an increase in domestic violence. The longitudinal studies that have been carried out on crime rates after the disaster determine that with the help of cooperation and social cooperation, there is a decrease in the crimes against property and violence and an increase in the cases of domestic violence. The disappearance of unaccompanied minors, child abuse, rapine, violence against women, and hate crimes against refugees are some of the criminal behaviors that are reflected in the media in the acute period and evaluated within the scope of this study. The Decrease of control due to social disorder and the absence of officials to provide security in the immediate aftermath of the earthquake explain that criminal behavior may occur in the acute period. The systematic, rapid, and effective implementation of the actions planned to prevent social disorder after natural disasters may be beneficial in preventing crime and violence in regions damaged by natural disasters.

ChatGPT and ELT: Exploring Teachers’ Voices

This study investigates the perceptions of English language teachers regarding the use of ChatGPT in English Language Teaching (ELT). The study aims to fill the research gap by exploring teachers' perspectives on the integration of ChatGPT as an instructional tool and its implications for ELT practices. Using a mixed methods approach, the study employed focus group discussions and an online survey to gather insights from a sample of 115 English language teachers in Metro Manila, Philippines. Findings revealed English language teachers’ perspectives on the use of ChatGPT in ELT including potential use of ChatGPT in ELT (e.g., integration for vocabulary expansion and writing practice and enhancing language fluency and communication), potential benefits of ChatGPT to English languge learners (e.g., translation and language comprehension support, conversational practice and language development, access to information and cultural understanding), and potential limitations of using ChatGPT in ELT (e.g., cheating and plagiarism, lack contextual understanding and nuance, reliability and accuracy of information). These findings shed light on teachers' perceptions of ChatGPT as a language teaching tool including ChatGPT’s integration into ELT, use of ChatGPT in writing activities, use of ChatGPT in improving language skills, and other benefits of using ChatGPT, including teachers' concerns regarding the authenticity of AI-generated content and the potential impact on language learning outcomes. The findings of this research contribute to the existing literature on the integration of AI technology in ELT and offer practical recommendations for educators seeking to leverage the potential of ChatGPT in language teaching. By giving voice to teachers' perspectives, this study underscores the importance of considering teachers' perceptions and experiences when incorporating emerging technologies like ChatGPT into the ELT classroom. Ultimately, this research aims to foster a deeper understanding of the complex dynamics between AI technology and language teaching, paving the way for informed decision-making and effective implementation in the field of ELT.

Eğitim Yönetiminde İzleme ve Değerlendirme Süreçlerinin İncelenmesi

Summary Producing an education policy does not consist only of writing, legislating and implementing legal texts. The policy process is also looking for answers to questions such as whether the desired goals have been achieved after these stages, what are the effects and consequences of law enforcement and whether there is a need for another change, what is the validity of the policy, whether there is a justification for changes in policy for the future. The process by which these answers are sought is the evaluation process. At this stage, the outputs and results obtained as a result of the application are evaluated in all dimensions. The goal of policy practitioners is always to achieve the desired results. However, there may usually be some deviations in achieving the goals. Even in cases where the policy process is fully functioning and all kinds of resources are fully available for effective implementation, there may be deviations in the desired goals to be achieved. The implementation phase is not the last step in the policy process. The effectiveness of the policy needs to be evaluated over certain time periods, and steps should be taken to provide the tools and resources to maintain a successful policy. The evaluation of education management can be considered as the last stage and the most important crucial part of policy analysis. Key Words: Education Management, Education Monitoring, Education Evaluation

Analysis of Multimodal Data in Project Management: Prospects for Using Machine Learning

The modern project environment is characterized by high complexity, uncertainty, speed and depth of changes that affect the project during its life cycle. However, the project’s change management processes do not take into account the need to implement analytical procedures for dynamic processing of multimodal data arrays. The purpose of the study is to determine the content of analytical procedures for project management and substantiate the use of machine learning technologies for their effective implementation. The methodological basis was project management methods, theory of change, concepts of artificial intelligence and machine learning, as well as analytical approaches. Methods of descriptive modeling of the project management process and expert assessments of the prospects for using machine learning technologies were also used in the work. The information base was made up of scientific materials on the topic under consideration, as well as expert assessments. The results of the study allowed us to conclude that for the analysis of multimodal data, natural language processing and intellectual decision support technologies are most in demand, which can serve as the basis for new technological solutions in the field of project management.

Mobilising Communities Prior to Healthcare Interventions: Reflections on the Role of Public Health Midwives Working With Vulnerable Communities of Sri Lanka.

Background: Public health midwives (PHMs) play a frontline role in the Sri Lankan public healthcare system, ensuring the health of children and women at the community level. However, cultural differences in diverse social contexts necessitate PHMs for customised interventions to ensure optimum child and maternal health, particularly in most vulnerable communities.Purpose: The objective of the present study is to explore how PHMs have adapted their roles as community change agents to facilitate community mobilisation before implementing healthcare interventions for children and mothers in the estate sector (a marginalised and vulnerable community) of Sri Lanka.Research Design and methods: Using an exploratory qualitative research design, data were collected through in-depth interviews with 16 participants. The thematic analysis revealed two main themes that describe how PHMs engage in community mobilisation in addition to their designated role as healthcare officials in the estate sector of Sri Lanka.Results: The first theme highlights PHMs'involvement in community mobilisation through context-relevant advocacy for effective service implementation. The second theme illustrates how PHMs'role has been reshaped as advocates to intervene in making the family a supportive institution for child and maternal health. PHMs who work in the estate sector in the country are morally committed to engaging in community mobilisation and advocacy. However, this obligation can be neglected due to the lack of formal arrangements and training in sociocultural determinants of health and working with vulnerable communities.Conclusions: The role of a PHM in the estate sector differs significantly from that in the urban and rural sectors, given the significance of their interventions in family health. Also, community mobilisation is a prerequisite for implementing health policies for child and maternal health in vulnerable communities. Both community-level and family-level advocacy interventions and mobilisation efforts are equally important to establishing a supportive environment, without which any child and maternal healthcare interventions are difficult to implement.

Differential Privacy Preservation for Continuous Release of Real-Time Location Data.

Continuous real-time location data is very important in the big data era, but the privacy issues involved is also a considerable topic. It is not only necessary to protect the location privacy at each release moment, but also have to consider the impact of data correlation. Correlated Laplace Mechanism (CLM) is a sophisticated method to implement differential privacy on correlated time series. This paper aims to solve the key problems of applying CLM in continuous location release. Based on the finding that the location increment is approximately stationary in many scenarios, a location correlation estimation method based on the location increment is proposed to solve the problem of nonstationary location data correlation estimation; an adaptive adjustment model for the CLM filter based on parameter quantization idea (QCLM) as well as its effective implementation named QCLM-Lowpass utilizing the lowpass spectral characteristics of location data series is proposed to solve the problem of output deviations due to the undesired transient response of the CLM filter in time-varying environments. Extensive simulations and real data experiments validate the effectiveness of the proposed approach and show that the privacy scheme based on QCLM-Lowpass can offer a better balance between the ability to resist correlation-based attacks and data availability.

Deconcentrating regulation in low- and middle-income country health systems: a proposed ambidextrous solution to problems with professional regulation for doctors and nurses in Kenya and Uganda

BackgroundRegulation can improve professional practice and patient care, but is often weakly implemented and enforced in health systems in low- and middle-income countries (LMICs). Taking a de-centred and frontline perspective, we examine national regulatory actors’ and health professionals’ views and experiences of health professional regulation in Kenya and Uganda and discuss how it might be improved in LMICs more generally.MethodsWe conducted large-scale research on professional regulation for doctors and nurses (including midwives) in Uganda and Kenya during 2019–2021. We interviewed 29 national regulatory stakeholders and 47 subnational regulatory actors, doctors, and nurses. We then ran a national survey of Kenyan and Ugandan doctors and nurses, which received 3466 responses. We thematically analysed qualitative data, conducted an exploratory factor analysis of survey data, and validated findings in four focus group discussions.ResultsKenyan and Ugandan regulators were generally perceived as resource-constrained, remote, and out of touch with health professionals. This resulted in weak regulation that did little to prevent malpractice and inadequate professional education and training. However, interviewees were positive about online licencing and regulation where they had relationships with accessible regulators. Building on these positive findings, we propose an ambidextrous approach to improving regulation in LMIC health systems, which we term deconcentrating regulation. This involves developing online licencing and streamlining regulatory administration to make efficiency savings, freeing regulatory resources. These resources should then be used to develop connected subnational regulatory offices, enhance relations between regulators and health professionals, and address problems at local level.ConclusionProfessional regulation for doctors and nurses in Kenya and Uganda is generally perceived as weak. Yet these professionals are more positive about online licencing and regulation where they have relationships with regulators. Building on these positive findings, we propose deconcentrating regulation as a solution to regulatory problems in LMICs. However, we note resource, cultural and political barriers to its effective implementation.

Use of mHealth in promoting maternal and child health in "BIMARU" states of India "A health system strengthening strategy": Systematic literature review.

Low-middle income countries like India bear a heavier burden of maternal, childcare, and child mortality rates when compared with high-income countries, which highlights the disparity in global health. Numerous societal, geopolitical, economic, and institutional issues have been linked to this inequality. mHealth has the potential to ameliorate these challenges by providing health services and health-related information with the assistance of frontline workers in the provision of prepartum, delivery, and postnatal care to improve maternal and child health outcomes in hard-to-reach areas in low- and middle-income countries (LMICs). However, there is limited evidence to support how mHealth can strengthen maternal and child health in India. The scoping review guideline in the Cochrane Handbook was used to retrieve studies from 4 international databases: CINAHL, Embase, Medline Ovid, and PubMed. This search strategy used combined keywords (MeSH terms) related to maternal and child healthcare, mHealth, and BIMARU in conjunction with database-controlled vocabulary. Out of 278 records, 8 publications were included in the review. The included articles used mHealth for data collection, eLearning, communication, patient monitoring, or tracking to deliver maternal and neonatal care. The results of these papers reflected a favourable effect of mHealth on the target population and found that it altered their attitudes and behaviours about healthcare. Higher job satisfaction and self-efficiency were reported by mHealth user care providers. Multiple barriers to the acceptance of mHealth exist, but the majority of the evidence points towards the feasibility of the intervention in a clinical setting. The mHealth has positive potential for improving maternal and child health outcomes in low-resource settings in India's BIMARU states by strengthening the healthcare system. The results of the study could be used in the tailoring of an effective mHealth intervention and implementation strategy in a similar context. However, there is a need for economic evaluation in the future to bridge the knowledge gap regarding the cost-effectiveness of mHealth interventions.

Self-Reported Preparedness and Factors Influencing AI Tools Integration in Teaching Among Master's Degree Students in a Selected Teachers Education College

Against the backdrop of the transformative potential of artificial intelligence (AI) in various sectors, its increasing integration in the field of education has garnered attention for its potential to enhance teaching effectiveness and overall academic quality (Rosales et al., 2020; Wartman, 2018; Chassignol et al., 2018; Chen et al., 2020). This study focuses on the self-preparedness of Master’s degree students and the factors influencing the integration of AI tools in teaching practices within a selected Teacher Education college, recognizing the critical role of AI in shaping the future of education (Fitria, 2021). The findings revealed a positive correlation between self-preparedness and various factors, emphasizing Ai’s transformative potential in education. Recommendations include inclusive professional development, gender-responsive training, and ongoing support for educators. Collaborative networks, research and development, policy guidelines for ethical AI use are suggested. The study underscores the need for ongoing research on AI’s long-term impact and cultural influences in education, prioritizing diversity and ethical considerations for effective implementation.

Components of the Ascorbate-Glutathione Complex and Phenylpropanoid Pathway in the Implementation of the Protective Effect of Salicylic Acid on Wheat Plants under Salinity

Components of the Ascorbate-Glutathione Complex and Phenylpropanoid Pathway in the Implementation of the Protective Effect of Salicylic Acid on Wheat Plants under Salinity

Cobot selection using hybrid AHP-TOPSIS based multi-criteria decision making technique for fuel filter assembly process

The choice of a suitable collaborative robot (cobot) for a real-time industrial process is one of the obstacles to effective robot implementation in terms of energy and cost. The cobot selection process for an application have become more complex due to increasing sophisticated features and capabilities in cobots offered by the manufacturers. The paper presents a hybrid Multi-Criteria Decision-Making (MCDM) technique based on Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches for selecting cobots for fuel filter assembly operation. The product design methodology, manufacturing method, and associated cost are directly influencing the decision on cobot selection. The most appropriate robot to accomplish the desired task at the lowest possible cost and capability can be selected by AHP with prospective criterion weight for subsequent processing. The TOPSIS approach orders alternatives based on the prominence of criteria. A diesel fuel filter assembly process case was considered for validating the proposed technique of cobot selection process. An expert knowledge base was generated for 12 advocated cobots and the best cobot was selected using the proposed hybrid MCDM technique.

Implementing health system and the new federalism in Somalia: challenges and opportunities.

In the 21st century, healthcare stands out as a formidable, contentious social responsibility for governments due to its high costs. This study delves into Somalia's healthcare system under Federal Government leadership, scrutinizing the complexities of health governance and financing. The Federal Government (FGS), along with governmental states (FMS) and regional authorities, collectively shoulder leadership and governance roles within Somalia's healthcare framework. Vital to resilient and inclusive development, the health sector holds a pivotal role. A strategic investment in healthcare not only drives substantial demographic dividends through enhanced life expectancy and reduced fertility rates, but also paves Somalia's trajectory toward progress. The Federal Government of Somalia confronts a multitude of challenges in its pursuit of effective healthcare implementation. A prominent obstacle lies in health financing. Somalia relies heavily on international and private sources for health support, primarily due to limited government revenue generation. This financial shortfall restrains the government's capacity to allocate ample funds for public services and critical investments, including healthcare. This paper sheds light on the present healthcare landscape in Somalia and expounds on the hurdles confronted by healthcare systems under federal governance. Moreover, it delves into the historical evolution of Somalia's healthcare system and the advent of new federalist principles. In doing so, this study comprehensively examines the dynamics of healthcare governance, financing, and historical progression in Somalia.

An Improved Dual-Gate Compact Model for Carbon Nanotube Field Effect Transistors with a Back-Gate Effect and Circuit Implementation

Compared to single-gate CNTFET, dual-gate structures have better electrostatic control over nanowire conductive channels. However, currently, there is insufficient research on the back-gate effect in a compact model of dual-gate CNTFET. This paper presents an improved dual-gate carbon nanotube field effect transistor (CNTFET) compact model. The functional relationship between the back-gate voltage (Vbg) and threshold voltage (Vth) is derived. And a voltage reference regulation mechanism is adopted so that the back-gate effect can be accurately reflected in the DC transfer characteristics. The influence of gate voltage and drain voltage on transmission probability is analyzed. Meanwhile, the drain current is optimized by modifying the mobility equation. This compact model is built based on Verilog-A hardware language and supports the Hspice simulation tool. Within the supply voltage of 2 V, the simulation results of the proposed compact model are in good agreement with the measurement results. Finally, based on the compact model, an operational amplifier is designed to verify its correctness and feasibility in analog integrated circuits. When the power supply voltage is 1.8 V, and the load capacitance is 2 pF, the gain is 11.8 dB, and the unit-gain-bandwidth (UGB) is 214 kHz, which proves the efficiency of our compact model.

Current perspectives on fecal microbiota transplantation in inflammatory bowel disease.

Fecal microbiota transplantation (FMT) has emerged as a promising therapeutic modality within the domain of inflammatory bowel disease (IBD). While FMT has secured approval and demonstrated efficacy in addressing recurrent and refractory Clostridioides difficile infection, its application in IBD remains an area of active exploration and research. The current status of FMT in IBD reflects a nuanced landscape, with ongoing investigations delving into its effectiveness, safety and optimal implementation. Early-stage clinical trials and observational studies have provided insights into the potential of FMT to modulate the dysbiotic gut microbiota associated with IBD, aiming to mitigate inflammation and promote mucosal healing. However, considerable complexities persist, including variations in donor selection, treatment protocols and outcome assessments. Challenges in standardizing FMT protocols for IBD treatment are compounded by the dynamic nature of the gut microbiome and the heterogeneity of IBD itself. Despite these challenges, enthusiasm for FMT in IBD emanates from its capacity to address gut microbial dysbiosis, signifying a paradigm shift towards more comprehensive approaches in IBD management. As ongoing research progresses, an enhanced understanding of FMT's role in IBD therapy is anticipated. This article synthesizes the current status of FMT in IBD, elucidating the attendant challenges and aspiring towards the refinement of its application for improved patient outcomes.

Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study

BackgroundUnderstanding women’s perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to explore...

Interlocal collaborative processes and network position: the combined effects on environmental performance

ABSTRACT This study investigates how network actors’ participation in collaborative processes improves environmental outcomes and how their closeness centrality moderates these relationships. Relying on a city-level panel dataset for 76 cities from six urban regions that participate in China’s joint atmospheric pollution mitigation programs, we found that participation in joint meetings, interlocal agreements, and joint implementations positively influences a city’s air quality. These effects differ for cities in dominant and peripheral positions with unbalanced power and resources within the network. Our findings deepen our understanding of intergovernmental networks and provide practical insights for equitable and effective collaboration implementation.

Eight-channel signal synchronous acquisition system based on PCI and LabVIEW

In response to the multi-channel acquisition of the power grid simulator data collection system, this article builds a 8-channel signal synchronization acquisition system based on PCI-1706U and LabView, which introduces the characteristics of PCI-1706U hardware and LabView software DAQ system. A LabView DAQ program that uses the PCI-1706U to collect 8-way signal from the signal generator, complete the experiments of multi-channel synchronous acquisition and delayed start to collection, verify the feasibility and stability of the system, and analyzed the collected signals. Finally, the main work and innovation points of the thesis are summarized, and suggestions and outlook for future improvement are given. This study provides an effective implementation method based on PCI-1706U and LabView multi-channel signal synchronous acquisition system and delay acquisition function, with certain application value and promotion space.

Does ERA5-land capture the changes in the terrestrial hydrological cycle across the globe?

Changes in the terrestrial hydrological cycle determine the future water availability across the globe with profound impacts in different facets of society. Precise estimation of such changes is vital for the effective implementation of water management policies. Among the numerous data products that describe the hydrological cycle components, ERA5-Land is one of the most increasingly used dataset. Still, there has been no assessment of its ability capacity to represent the water cycle shifts variability over land. This study endeavors to bridge this gap by comparing the magnitude and direction of change in precipitation minus evaporation (P—E) and runoff, as estimated globally by the ERA5-Land data product. Our findings reveal significant inconsistencies in the changes identified, with the climatological mean of P—E decreasing more substantially than runoff for numerous regions. Consequently, ERA5 presents a declining water availability for most of the regions, but the magnitude of change is incompatible to the change between P—E and runoff. To further validate, the estimates provided by the ERA5-Land product, two different hydrologic models (TerraClimate and Global Land Data Assimilation System, GLDAS-Noah) are also utilized. TerraClimate demonstrates a more reasonable alignment between changes in P—E and runoff, followed by GLDAS-Noah, particularly for the arid regions lying in the parts of Northern Africa and Southern Asia, the European continent, and the northern parts of Asia. Inconsistencies remain high for the tropical regions for both data products. Still, the estimates of change in water availability are better represented by the hydrologic model-based data sources for most parts of the globe, especially for the regions with low precipitation, such as the regions with arid and continental climates. Our results imply that ERA5-Land should be used with extreme caution when assessing the long-term changes in the terrestrial water cycle. Additionally, pinpointing the regions of the highest bias can help to improve the hydrological coupling of ERA5-Land in future versions of the reanalysis.

Developing a Business Maturity Framework (BMF) in the Oil and Gas Industry

This study explores the utility of business maturity models in navigating dynamic business landscapes. It assesses existing models, develops an industry-specific Business Maturity Framework (BMF), and emphasizes foundational considerations for effective implementation aligned with organizational goals. The study concludes by highlighting the perpetual nature of business maturity and the BMF's efficacy in enhancing operational excellence, competitiveness, and sustainable growth in the oil and gas sector. The paper contributes to specialized literature by introducing a novel dimension that evaluates market and customer readiness for future digitalization levels, thereby providing a comprehensive approach to business maturity.
 Keywords: business transformation, digital process maturity, business maturity framework (BMF), incremental changes, maturity assessment, disruptive changes, oil and gas industry