Current Strengths Research Articles

Perceptions of service providers on available care for paediatric feeding disorder: A survey study.

This study aimed to describe current strengths and gaps in services for children with feeding needs in Southeast Queensland, Australiafrom the perspective of key professionals involved in service design and provision. A web-based survey was distributed to health professionals involved in providing services to children with feeding needs, staff who triaged/managed referrals, and/or service team leaders in Southeast Queensland. There were 79 responses to the survey, with 61 of these responses included in the analysis. Respondents identified several strengths in paediatric feeding disorder (PFD) service provision, particularly in the quality of care available for children who met service eligibility requirements. However, respondents also described services as disjointed, with limited coordinated multidisciplinary care available. Respondents frequently described service limitations relating to public service eligibility criteria, long waiting lists, and scant communication between services. Gaps were reported in the care available for children with 'mild' feeding difficulties and/or children who were not considered medically complex. Respondents also identified gaps in services secondary to a limited number of confident and trained professionals offering PFD care, particularly in the private sector. This study described service providers' perceptions of available care for children with PFD in Southeast Queensland. Overall, the availability of PFD services appeared to be limited by eligibility criteria, service design, and staff capacity, suggesting that children with PFD are not receiving timely, multidisciplinary care in this geographical area. Further research into ideal service design is required to support preventative PFD care.

Recent progress in atmospheric modeling over the Andes – part I: review of atmospheric processes

The Andes is the longest mountain range in the world, stretching from tropical South America to austral Patagonia (12°N-55°S). Along with the climate differences associated with latitude, the Andean region also features contrasting slopes and elevations, reaching altitudes of more than 4,000 m. a.s.l., in a relatively narrow crosswise section, and hosts diverse ecosystems and human settlements. This complex landscape poses a great challenge to weather and climate simulations. The interaction of the topography with the large-scale atmospheric motions controls meteorological phenomena at scales of a few kilometers, often inadequately represented in global (grid spacing ∼200–50 km) and regional (∼50–25 km) climate simulations previously studied for the Andes. These simulations typically exhibit large biases in precipitation, wind and near-surface temperature over the Andes, and they are not suited to represent strong gradients associated with the regional processes. In recent years (∼2010–2024), a number of modeling studies, including convection permitting simulations, have contributed to our understanding of the characteristics and distribution of a variety of systems and processes along the Andes, including orographic precipitation, precipitation hotspots, mountain circulations, gravity waves, among others. This is Part I of a two-part review about atmospheric modeling over the Andes. In Part I we review the current strengths and limitations of numerical modeling in simulating key atmospheric-orographic processes for the weather and climate of the Andean region, including low-level jets, downslope winds, gravity waves, and orographic precipitation, among others. In Part II, we review how climate models simulate surface-atmosphere interactions and hydroclimate processes in the Andes Cordillera to offer information on projections for land-cover/land-use change or climate change. With a focus on the hydroclimate, we also address some of the main challenges in numerical modeling for the region.

<span><strong>Faculties</strong> <strong>on </strong><strong>activities </strong><strong>of training </strong><strong>highly </strong><strong>qualified </strong><strong>human </strong><strong>resources</strong><strong>:</strong> <strong>Research </strong><strong>in the </strong><strong>Mekong </strong><strong>Delta</strong></span>

The Mekong Delta region currently lacks a high-quality labor force. Many universities have opened postgraduate training programs to provide high-quality labor for this region. On the systematic approach to development and practical activities, this study on the teaching staff with high-quality human resource training activities is to answer two research questions: (1) What are the researches on the teaching staff role in human resource training at the higher education focusing on? and (2) What are the gaps in this line of research on training highly qualified human resources? From there, this study assesses the current strengths and weaknesses of the teaching staff of universities in the Mekong Delta, identifies opportunities and challenges in human resource training in the new context; at the same time, it orients the activities of linking the teaching staff universities​ Open approach, increased autonomy, self-responsibility in the field of training high-quality human resources to meet the requirements of fundamental and comprehensive educational innovation.

Evaluating the Ability of External Electric Fields to Accelerate Reactions in Solution.

This study investigates the catalytic effects of external electric fields (EEFs) on two reactions in solution: the Menshutkin reaction and the Chapman rearrangement. Utilizing a scanning tunneling microscope-based break-junction (STM-BJ) setup and monitoring reaction rates through high-performance liquid chromatography connected to a UV detector (HPLC-UV) and ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-q-ToF-MS), we observed no rate enhancement for either reaction under ambient conditions. Density functional theory (DFT) calculations indicate that electric field-induced changes in reactant orientation and the minimization of activation energy are crucial factors in determining the efficacy of EEF-driven catalysis. Our findings suggest that the current experimental setups and field strengths are insufficient to catalyze these reactions, underscoring the importance of these criteria in assessing the reaction candidates.

Emerging Trends and Innovations in the Treatment and Diagnosis of Atherosclerosis and Cardiovascular Disease: A Comprehensive Review towards Healthier Aging.

Cardiovascular diseases (CVDs) are classed as diseases of aging, which are associated with an increased prevalence of atherosclerotic lesion formation caused by such diseases and is considered as one of the leading causes of death globally, representing a severe health crisis affecting the heart and blood vessels. Atherosclerosis is described as a chronic condition that can lead to myocardial infarction, ischemic cardiomyopathy, stroke, and peripheral arterial disease and to date, most pharmacological therapies mainly aim to control risk factors in patients with cardiovascular disease. Advances in transformative therapies and imaging diagnostics agents could shape the clinical applications of such approaches, including nanomedicine, biomaterials, immunotherapy, cell therapy, and gene therapy, which are emerging and likely to significantly impact CVD management in the coming decade. This review summarizes the current anti-atherosclerotic therapies' major milestones, strengths, and limitations. It provides an overview of the recent discoveries and emerging technologies in nanomedicine, cell therapy, and gene and immune therapeutics that can revolutionize CVD clinical practice by steering it toward precision medicine. CVD-related clinical trials and promising pre-clinical strategies that would significantly impact patients with CVD are discussed. Here, we review these recent advances, highlighting key clinical opportunities in the rapidly emerging field of CVD medicine.

Research on maintenance decision-making approach based on dynamic opportunistic window

We have developed a maintenance decision-making approach based on the dynamic opportunistic window, utilizing algorithms such as k-mean clustering, expected maximum, and parameter estimation to address the lack of a reasonable basis for the duration and divided number of opportunistic windows in current maintenance decision-making. Firstly, we have comprehensively summarized the multi-stage opportunistic maintenance decision-making approach, focusing on its current strengths and limitations. Secondly, the modeling concept of the dynamic opportunistic window is analyzed, and the underlying assumptions are established. Furthermore, it elaborates on the theoretical foundation of the proposed approach through a detailed modeling process. Finally, we validate the proposed model by conducting experiments on tandem components from the main combustion chamber in an aero engine. The experimental results demonstrate the significant value of the proposed approach in enhancing equipment reliability and optimizing maintenance support resources.

Current situation, strengths and problems in intra- and interprofessional collaboration in German nursing homes – A holistic multiple case study

BackgroundThe increasing care complexity of nursing home residents living with dementia requires new care models that strengthen professional collaboration. To contribute to the sustainable implementation of new care models, it is important that they are linked to the care reality. However, little is known about intra- and interprofessional organization and provision of care in German nursing homes. Therefore, the aim of this study was to explore the current care situation, problems and strengths regarding intra- and interprofessional collaboration in the care of residents living with dementia.MethodsWe conducted a holistic multiple case study. The individual care units in which residents living with dementia are cared for were defined as cases. The context was built by the respective nursing homes and their regional affiliation to the federal state of North Rhine-Westphalia. We used qualitative face-to-face interviews, documents and context questionnaires for data collection. The different sources of evidence served to capture complementary perspectives and to validate the findings. First, the collected qualitative data were analyzed using deductive-inductive content analysis. Second, similarities and differences between the cases were identified to elaborate case-specific and cross-case patterns and themes. The reporting followed the EQUATOR reporting guideline for organizational case studies.ResultsWe included four care units comprising 21 professionals (nurses, physicians, social worker, physiotherapist, pharmacist) and 14 relatives of residents living with dementia. The analysis revealed four categories to describe current intra- and interprofessional collaboration in all cases: actors and their roles, service delivery, coordination and governance, and communication channel. Moreover, we identified three categories that relate to the strengths and problems of intra- and interprofessional collaboration in all cases: role understanding, teamwork, and communication and exchange. Although we examined similar care units, we found differences in the realization of professional collaboration and resulting problems and strengths that are connected to the organizational contexts and strategies used.ConclusionsEven though professional collaboration follows given patterns; these patterns do differ context-specifically and are perceived as problematic and fragmentary. Therefore, the identified differences and problems in collaboration need to be addressed in future research to develop and successfully implement tailored innovative care models.

Emerging Advanced Technologies for Game Engineering

In this paper, the outcomes of the 8th International Workshop on Games and Software Engineering (GAS 2024)1 are reported. The one-day workshop has been held as part of the 46th International Conference on Software Engineering (ICSE 2024) in Lisbon, Portugal on April 14, 2024. The workshop programme includes two exciting keynotes discussing topics related to harnessing video game simulations to generate content and locate bugs, and the experience of maintaining a popular FOSS library, raylib. There are three research paper sessions. The first relates to automation in game engineering; the second explores testing and quality assurance; and the third discusses specification and quality of service. The conclusion of the workshop is anchored by a panel of four researchers, educators, and practitioners discussing the current strengths and limitations of large language models in game engineering.

Dementia content and delivery in physiotherapy curricula: an international study of entry level physiotherapy programmes in Ireland the United Kingdom and New Zealand

ObjectivesPhysical impairments associated with dementia include reduced gait speed, and diminished postural control, which can lead to an increase in falls and hip fractures. Physiotherapy can play a key role in many aspects of dementia care, including falls risk prevention, gait re-education and end of life care. However, there is a lack of dementia education in entry level physiotherapy programmes. The aim of this study was to map the dementia content and delivery in the current undergraduate and entry level physiotherapy curricula in Ireland the United Kingdom and New Zealand. DesignThis cross-sectional survey-based study was distributed via the online survey tool Qualtrics XM. The survey was designed using the map of Kern’s curriculum design framework. SettingHigher educational institutes (HEIs) that offered an undergraduate (BSc) and/or MSc (entry level) physiotherapy programmes in Ireland United Kingdom and New Zealand were included. ParticipantsThe academic lead for dementia education in the HEI was invited to participate in the survey. ResultsOf the 69 eligible HEIs contacted, 49 responded, giving a response rate of 71%. Different sources informed curriculum design, including patient and public involvement, published guidelines and policies and expert clinicians. The time allocated to dementia teaching across the curricula varied, with under half of the programmes only allocating two hours. The lack of service user input was seen as a perceived weakness of many programmes as was the non-standardisation and generalisability of teaching. ConclusionWhilst dementia education is included in many HEI programmes, we need to consider more time, a curriculum that meets learner’s needs and include the patient voice. Further research is needed to develop bespoke dementia curricula specific to physiotherapy. Contribution of the Paper•The findings of this study have identified current strengths as well as weaknesses of entry level physiotherapy programmes in dementia care.•This study highlights what is most and least commonly taught at entry level physiotherapy programmes in dementia care.•More time needs to be allocated to dementia teaching, to reflect the clear work-related educational needs of physiotherapists in both the acute and community care sector.

Bioinformatics and biomedical informatics with ChatGPT: Year one review.

The year 2023 marked a significant surge in the exploration of applying large language model chatbots, notably Chat Generative Pre-trained Transformer (ChatGPT), across various disciplines. We surveyed the application of ChatGPT in bioinformatics and biomedical informatics throughout the year, covering omics, genetics, biomedical text mining, drug discovery, biomedical image understanding, bioinformatics programming, and bioinformatics education. Our survey delineates the current strengths and limitations of this chatbot in bioinformatics and offers insights into potential avenues for future developments.

Advantages and drawbacks of life cycle assessment application to the pharmaceuticals: a short critical literature review.

Pharmaceuticals are among the most challenging products to assess by life cycle assessment (LCA). The main drawback highlighted by LCA practitioners is the lack of inventory data, both regarding the synthesis of active pharmaceutical ingredient (API) precursors (upstream) and the details concerning the downstream phases (use and end of life). A short critical review of pharma-LCAs found in the literature is here proposed, with discussion of several tools and models used to predict the environmental impacts derived from the life cycle of pharmaceuticals, emphasizing current strengths and weaknesses, and exploring the possibilities for improvements. The case of antibiotics is selected as a representative class of pharmaceuticals, due to their massive use worldwide and the growing related issue of antimicrobial resistance enrichment, which is generally not included in most of LCAs. Also, we comment on drafting product category rules (PCRs) in the relevant field to develop standard methodologies and enhance the comparability of the studies, ultimately advocating collaboration with companies and improving inventory data quality and availability for the whole value chain of products.

Analisis Strategi Pemasaran terhadap Penjualan Minyak Kelapa Sawit (CPO) pada PT. Perkebunan Nusantara III (PERSERO)

One critical commodity in Indonesia is crude palm oil, or CPO. In order to boost palm oil sales, this research use SWOT analysis to identify the most effective marketing methods. Things like assessing possibilities in the market, creating marketing strategies, designing marketing programs, and coordinating marketing activities are essentially the focus of the company's marketing strategy. This study combines primary and secondary sources to provide a descriptive account of the phenomena under investigation. Using the IFAS and EFAS matrices, a number of tests are conducted, including SWOT analysis tests. According to the study's findings, the x-axis of the SWOT diagram is the IFAS matrix value of 0.06, and the y-axis is the EFAS matrix test result value of 1.12. When the IFAS and EFAS matrices are applied to the SWOT diagram, the findings show that the company's internal factors are strong in area I. Based on the SWOT analysis, PT Perkebunan Nusantara III Medan has an aggressive approach that aims to build on current strengths while also improving and maintaining them. The firm is in kudran I, according to the SWOT diagram

The newborn individualised developmental care and assessment program: A model of care for infants and families in hospital settings.

The Newborn Individualised Developmental Care and Assessment Program (NIDCAP) is an intervention and education programme that uses developmental observation for multidisciplinary healthcare professionals (HCP) caring for high-risk infants and families. Infants prosper with the ongoing co-regulation process of infant and family that is influenced by the physical and social environment. The Template for Intervention Description and Replication (TIDieR) Guidelines were applied to the NIDCAP intervention. The estimation of the individual infant's current goals is described from direct observation of behaviour in the context of ongoing care delivery. The infant's behaviour guides all caregivers to articulate current strengths and functioning for the development of individualised plans of care and support. The NIDCAP Nursery Program supports the full integration of NIDCAP into the healthcare system. NIDCAP is a system-based, process-oriented, attuned and responsive intervention for individualised developmental care for infants and families. Evidence shows NIDCAP significantly improves medical outcomes, with less time on the ventilator, improved weight gain, decreased length of stay, improved developmental outcomes and enhanced infant and family relationships. Evidence suggests that NIDCAP as an intervention improves parental competence, decreases stress for HCP teams and improves HCP satisfaction. NIDCAP improves outcomes for infants and families requiring hospital care.

Modern learning paradigms: A bibliometric analysis of augmented reality and virtual reality in vocational education

This bibliometric analysis aims to explore the publication trends of the last decade, especially on modern learning paradigms that focus on implementing Augmented Reality (AR) and Virtual Reality (VR) in vocational education. This research specifically addresses the analysis of current technology trends, gaps, challenges, strengths, and opportunities of AR and VR during (2015-2024). This research method uses the "Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)" protocol to collect data from publications focusing on high-quality research results. Data acquisition was analyzed and identified using MS Excel software and VOSciewer to visualize various critical metadata obtained in the Scopus database. Notably, publication trends and distribution patterns, the contributions of authors, the geographical spread of publications, and the identification of significant publication sources are all essential for analyzing the opportunities and challenges within the context of vocational education. The results of this study identified an augmenting growth of publication trends from 2015-2023, including the country of origin of prominent authors such as Bacca et al. (Spain), Babu et al. (India), and Lerner et al. (Germany), whose research results have been proven to impact the primary reference in the field of vocational education in the utilization of AR and VR. It is widely cited and has become the primary reference for other authors. Consequently, this bibliometric-based research underscores the potential of AR and VR technologies to improve vocational education by enhancing motivation, educational access, personalized learning, collaboration, and reducing operational costs.

Analysis of a European general wildlife health surveillance program: Chances, challenges and recommendations.

In a One Health perspective general wildlife health surveillance (GWHS) gains importance worldwide, as pathogen transmission among wildlife, domestic animals and humans raises health, conservation and economic concerns. However, GWHS programs operate in the face of legal, geographical, financial, or administrative challenges. The present study uses a multi-tiered approach to understand the current characteristics, strengths and gaps of a European GWHS that operates in a fragmented legislative and multi-stakeholder environment. The aim is to support the implementation or improvement of other GWHS systems by managers, surveillance experts, and administrations. To assess the current state of wildlife health investigations and trends within the GWHS, we retrospectively analyzed 20 years of wildlife diagnostic data to explore alterations in annual case numbers, diagnosed diseases, and submitter types, conducted an online survey and phone interviews with official field partners (hunting administrators, game wardens and hunters) to assess their case submission criteria as well as their needs for post-mortem investigations, and performed in-house time estimations of post-mortem investigations to conduct a time-per-task analysis. Firstly, we found that infectious disease dynamics, the level of public awareness for specific diseases, research activities and increasing population sizes of in depth-monitored protected species, together with biogeographical and political boundaries all impacted case numbers and can present unexpected challenges to a GWHS. Secondly, we found that even a seemingly comprehensive GWHS can feature pronounced information gaps, with underrepresentation of common or easily recognizable diseases, blind spots in non-hunted species and only a fraction of discovered carcasses being submitted. Thirdly, we found that substantial amounts of wildlife health data may be available at local hunting administrations or disease specialist centers, but outside the reach of the GWHS and its processes. In conclusion, we recommend that fragmented and federalist GWHS programs like the one addressed require a central, consistent and accessible collection of wildlife health data. Also, considering the growing role of citizen observers in environmental research, we recommend using online reporting systems to harness decentrally available information and fill wildlife health information gaps.

Evaluating Large Language Models with RAG Capability: A Perspective from Robot Behavior Planning and Execution

After the significant performance of Large Language Models (LLMs) was revealed, their capabilities were rapidly expanded with techniques such as Retrieval Augmented Generation (RAG). Given their broad applicability and fast development, it's crucial to consider their impact on social systems. On the other hand, assessing these advanced LLMs poses challenges due to their extensive capabilities and the complex nature of social systems. In this study, we pay attention to the similarity between LLMs in social systems and humanoid robots in open environments. We enumerate the essential components required for controlling humanoids in problem solving which help us explore the core capabilities of LLMs and assess the effects of any deficiencies within these components. This approach is justified because the effectiveness of humanoid systems has been thoroughly proven and acknowledged. To identify needed components for humanoids in problem-solving tasks, we create an extensive component framework for planning and controlling humanoid robots in an open environment. Then assess the impacts and risks of LLMs for each component, referencing the latest benchmarks to evaluate their current strengths and weaknesses. Following the assessment guided by our framework, we identified certain capabilities that LLMs lack and concerns in social systems.

Analisis Metode Anodizing Aluminium dengan Variasi Kuat Arus sebagai Material Velg Kendaraan

Aluminum Alloy 6061 is widely used in various engineering applications, including automotive vehicle wheels. The selection of aluminum alloy wheels involves aspects such as corrosion resistance. To enhance corrosion resistance, there are several methods, one of which is anodizing. Anodizing is a process that involves an electrolytic coating process that transforms the surface of aluminum into aluminum oxide (Al2O3), which the main process of aluminum anodizing requires a solution of sulfuric acid, chromic acid, or a mixture of sulfuric acid and oxalic acid. The sulfuric acid used must be concentrated acid, and acid is an oxidizing substance. The thickness of the oxide is approximately twice the thickness of the lost aluminum. The purpose of this research is to determine the characteristic such as surface roughness values, corrosion rates, and changes in morphology in Aluminum 6061 after undergoing anodizing. In this study, various current strengths were used, namely 0.75 Amperes, 1.5 Amperes, 2.25 Amperes, and 3 Amperes. The highest surface roughness value was obtained at 0.447 μm in the third specimen of the 0.75 Ampere variation, while the lowest was 0.075 μm in the first specimen of the 3 Ampere variation. The highest corrosion rate was observed in the 0.75 Ampere variation, with a rate of 17.724004 mpy, and the lowest was 0.0731653 mpy in the 3 Ampere variation. SEM results show that, in general, Aluminum 6061 tends to have a bright gray color, which is a surface that has been coated by cathode.

Enhanced network inference from sparse incomplete time series through automatically adapted L1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L_1$$\\end{document} regularization

Reconstructing dynamics of complex systems from sparse, incomplete time series data is a challenging problem with applications in various domains. Here, we develop an iterative heuristic method to infer the underlying network structure and parameters governed by Ising dynamics from incomplete spin configurations based on sparse and small-sized samples. Our method iterates between imputing missing spin states given current coupling strengths and re-estimating couplings from completed spin state data. Central to our approach is the novel application of adaptive l1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$l_1$$\\end{document} regularization on updating coupling strengths, which features an automatic adjustment of the regularization strength throughout the iterative inference process. By doing so, we aim at preventing over-fitting and enforcing the sparsity of couplings without access to ground truth parameters. We demonstrate that this approach accurately recovers parameters and imputes missing spins even with substantial missing data and short time series, providing improvements in the inference of Ising model parameters even for relatively small sample sizes.

Electronic Current Density Induced by Uniform Magnetic Fields in Clarenes.

Some planar and non-planar clarenes have been studied using maps of magnetically induced quantum-mechanical current density and tools from differential topology to assess their magnetic response in connection with recent results by Du and Wang. Bond current strengths have been computed to estimate quantitative measures. Isosurfaces of the divergence of induced Lorentz force density have been shown to provide useful additional criteria, especially in the case of non-planar clarenes.

Performance of ChatGPT on the Taiwan urology board examination: insights into current strengths and shortcomings.

To compare ChatGPT-4 and ChatGPT-3.5's performance on Taiwan urology board examination (TUBE), focusing on answer accuracy, explanation consistency, and uncertainty management tactics to minimize score penalties from incorrect responses across 12 urology domains. 450 multiple-choice questions from TUBE(2020-2022) were presented to two models. Three urologists assessed correctness and consistency of each response. Accuracy quantifies correct answers; consistency assesses logic and coherence in explanations out of total responses, alongside a penalty reduction experiment with prompt variations. Univariate logistic regression was applied for subgroup comparison. ChatGPT-4 showed strengths in urology, achieved an overall accuracy of 57.8%, with annual accuracies of 64.7% (2020), 58.0% (2021), and 50.7% (2022), significantly surpassing ChatGPT-3.5 (33.8%, OR = 2.68, 95% CI [2.05-3.52]). It could have passed the TUBE written exams if solely based on accuracy but failed in the final score due to penalties. ChatGPT-4 displayed a declining accuracy trend over time. Variability in accuracy across 12 urological domains was noted, with more frequently updated knowledge domains showing lower accuracy (53.2% vs. 62.2%, OR = 0.69, p = 0.05). A high consistency rate of 91.6% in explanations across all domains indicates reliable delivery of coherent and logical information. The simple prompt outperformed strategy-based prompts in accuracy (60% vs. 40%, p = 0.016), highlighting ChatGPT's limitations in its inability to accurately self-assess uncertainty and a tendency towards overconfidence, which may hinder medical decision-making. ChatGPT-4's high accuracy and consistent explanations in urology board examination demonstrate its potential in medical information processing. However, its limitations in self-assessment and overconfidence necessitate caution in its application, especially for inexperienced users. These insights call for ongoing advancements of urology-specific AI tools.