Practical Tool Research Articles

Methodology for comprehensive assessment of the fisheries complex enterprises' bankruptcy probability

Subject. Enterprises that are actively operating in the market are exposed to factors affecting their financial health. If the nature of the factors is negative, the enterprises will face adverse impact, like a decrease in financial stability and solvency. Objectives. The study aims at development of scientific and practical tools for information and analytical substantiation of bankruptcy probability assessment and monitoring of financial health of organizations of the fisheries complex when making management decisions. Methods. The methodological approach to assessing the probability of bankruptcy of fisheries enterprises relies on the study of multifactor models designed to predict bankruptcy. Results. The paper considers causes of bankruptcy and the influence of factors leading to loss of solvency of the enterprise, defines specific features of bankruptcy of fishing companies. We performed the analysis of financial condition of companies with 3.22.1 "Freshwater Industrial Fish Farming" core activity. On the basis of modern scientific research in the field of assessing insolvency and the probability of bankruptcy, we developed our own methodological approach for fishing companies. Conclusions. If used, the offered methodology will provide the company managers with reliable information on the possible occurrence of company's insolvency.

Diagnostic performance of blue laser imaging for early detection of gastric cancer: A systematic review and meta-analysis.

Gastric cancer (GC) is associated with a significant global health burden and high mortality rates when diagnosed at later stages. The diagnosis often occurs at advanced stages when treatment options are limited and less effective. Early detection strategies are crucial to improving survival rates and outcomes for patients. Blue laser imaging (BLI) is an image-enhanced endoscopy technique that utilizes white light and narrow-band light to detect pathological changes in the mucosal architecture. This study aims at investigating the diagnostic performance of BLI for the detection of GC. A comprehensive search was conducted across multiple databases from inception until March 2023. Studies assessing the diagnostic efficacy of BLI for GC detection were included. The sensitivity, specificity and accuracy of BLI were calculated using pooled proportions and 95% confidence intervals (CI) with a random-effects model. Heterogeneity among the included studies was assessed using the I2 statistic. Six studies were included in the pooled analysis. There were 708 patients with 380 GC lesions. Most of the lesions involved the lower two-thirds of the stomach. The pooled performance metrics of BLI for GC detection were as follows: sensitivity of 91.9% (95% CI 83.3-96.3%; I2 = 82.3%), specificity of 93.4% (95% CI 82.0-97.8%; I2 = 87.9%) and accuracy of 95.4% (95% CI 72.6-99.8%; I2 = 73.6%). BLI demonstrates high diagnostic efficacy for the detection of GC. BLI can be a valuable tool in clinical practice. However, large-scale, randomized controlled studies are needed to further establish the role of BLI in routine clinical practice for GC detection.

French Validation of the New Sexual Satisfaction Scale Short Form (NSSS-SF Fr)

This study addresses the critical need for French-language tools in assessing sexual satisfaction, an important aspect of global health, sexual health, and mental health. Its main aim is to validate the French version of the NSSS-SF scale (NSSS-SF Fr, Fr for French). The research was conducted in two phases. The first study involved 253 participants, predominantly female (77.75%), with a focus on examining the tool’s psychometric properties (factorial structure, internal consistency, convergent validity). The second study included 855 participants, with a similar gender distribution, aimed at further validation and analysis, studying links between NSSS-SF Fr and anxiety and depressive symptoms (assessed with GAD7 and MDI), and attachment style (ECR-RS). The NSSS-SF Fr demonstrated robust psychometric properties. Key findings included its strong correlation with sexual health indicators, anxiety, depression, and attachment styles confirming its effectiveness as a reliable tool for evaluating sexual satisfaction in French-speaking populations. Comparisons with international studies highlighted its universal applicability and cultural sensitivity. The NSSS-SF French version stands as a critical tool for future research and clinical practice, bridging a vital gap in the assessment of sexual satisfaction among French-speaking individuals.

Validity and Reliability of the Greek Version of Pittsburgh Sleep Quality Index in Chronic Non-Specific Low Back Pain Patients.

The purpose of this study was to investigate psychometric properties of the Greek translation of Pittsburgh Sleep Quality Index (GR-PSQI) in a Greek chronic non-specific low back pain (CNSLBP) sample, thus, providing insight on its clarity and acceptability as a widely used sleep assessment tool in clinical practice. Asymptomatic volunteers (n = 73) and CNSLBP volunteers (n = 47), participated in the study. For the assessment of construct validity, the known-groups method was used. Thus, all the participants (asymptomatic and CNSLBP) completed the GR-PSQI. For the assessment of concurrent validity, the CNSLBP participants additionally completed the following validated questionnaires for depression, insomnia and sleep quality: Beck Depression Inventory Questionnaire (BDI), Insomnia Severity Index (ISI), and Sleep Quality Numeric Rating Scale (SQNRS). For the assessment of test-retest reliability, the CNSLBP participants completed the GR-PSQI a second time, one week after the first time. The results showed excellent test-retest reliability (ICC = 0.969, SEM = 0.90, SDD = 2.49%) and internal consistency (Cronbach α = 0.985), moderate to good concurrent validity (from r = 0.556 to r = 0.860) among PSQI, BDI, SQNRS, and ISI, as well as excellent construct validity (p = 0.000) between the two groups. The Greek translation of PSQI could be a valuable tool for Greek healthcare professionals in both clinical and research environments.

Design and synthesis of nano-iron oxyhydroxide-based molecularly imprinted electrochemical sensors for trace-level carbendazim detection in actual samples.

Carbendazim (CBD) is widely used as a fungicide that acts as a pesticide in farming to prevent crop diseases. However, CBD can remain on crops for a long time. When consumed by humans and animals, it produces a range of toxic symptoms and poses a serious threat to their health. Therefore, the detection of CBD is necessary. Traditional assay strategies for CBD detection, although sensitive and practical, can hardly achieve fast, robust monitoring during food processing and daily life. Here, we designed a novel electrochemical sensor for CBD detection. In this method, iron oxyhydroxide nanomaterial (β-FeOOH) was first prepared by hydrothermal method. Then, a molecularly imprinted polymer (MIP) layer was electropolymerized on the surface using CBD as the template and resorcinol (RC) as the functional monomer. The synergistic interaction between β-FeOOH and MIP endows the MIP/β-FeOOH/CC-based electrochemical sensor with high specificity and sensitivity. Under optimal conditions, the MIP/β-FeOOH/CC-based sensor showed a wide linear range of 39pM-80nM for CBD and a detection limit as low as 25pM. Therefore, the as-prepared sensor can be a practical and effective tool for pesticide residue detection.

Effect of Micro Organic Fertilizer on Growth and Yield of Threatened Melientha suavis Pierre Species in Thai Nguyen Province, Vietnam

The experiment was conducted at Thai Nguyen province to evaluate the response of micro-organic fertilizer on growth of vegetative and yield of Melientha suavis Pierre species in the spring and summer season 2023. The experiment included four treatments was designed in Randomized Complete Block Design with three replications. The characteristics include height of plant, diameter of trunk, leaf number, leaf size and yield were measured. The results indicated that applying the T3 treatment greatly in response enhancing height of plant, diameter of trunk, leaf number as well as leaf size compared to untreated control. Furthermore, application of the T3 treatment have the best results in yield of 380.0 kg/ha and 313.3 kg/ha in the spring and summer season, respectively. Therefore, the result could recommend applying micro-organic fertilizer can be practical tool for increasing growth of vegetative as well as yield in Melientha suavis pierre under field conditions.

Building the Foundation for Creativity and Collaboration: Knowledge Sharing Learning Models

The integration of creativity, critical thinking, collaboration, and communication skills into 21st-century learning represents a pivotal goal in education, particularly within the realms of engineering. Despite this ambition, the actualization of creativity and collaborative capabilities among engineering students remains a significant challenge, primarily due to prevalent individualistic attitudes and apprehensions towards error in idea sharing. This study introduces and evaluates a Knowledge Sharing (KS) learning model aimed at overcoming these barriers, thereby facilitating enhanced creativity and collaboration. Employing the Akker learning stages, this model was implemented in an engineering education setting, yielding encouraging outcomes: students demonstrated increased motivation for interdisciplinary learning, acquired novel knowledge beyond their traditional curricula, and developed practical designs and tools responsive to community needs. The methodology section details the iterative process of model development, encompassing identification, design and preparation, implementation, replication, and dissemination phases, followed by a thorough validation process. Results indicate a positive impact on students' creative competencies and collaborative skills, underscoring the model's efficacy in fostering essential 21st-century skills.

Region-wide assessment of National Immunization Technical Advisory Groups (NITAGs) using the NITAG Maturity Assessment Tool (NMAT) – Experience from the Eastern Mediterranean Region of the World Health Organization, 2023

National Immunization Technical Advisory Groups (NITAGs) are independent bodies that help improve national immunization programmes in decision making on immunization policy. The new NITAG Maturity Assessment Tool (NMAT) provided an opportunity to conduct a region-wide assessment to improve NITAG capacity and foster institutional growth. We share experience of the Eastern Mediterranean Region (EMR) of the World Health Organization (WHO) in using NMAT and the use of findings to develop improvement plans. NITAG chairs and secretariats from 22 EMR countries attended a virtual NMAT training in 2023. They self-assessed their NITAGs using the tool and developed improvement plans. An algorithm used the data to determine maturity levels for seven indicators. We consolidated results for the region by income groups. Of 22 countries (or NITAGs), 20 (91%) submitted NITAG assessment findings and 19 an improvement plan. The proportion of criteria met per indicator varied from 36% for independence and non-bias to 74% for establishment and composition. Maturity level varied by indicator. Of 20 NITAGs, less than half had an intermediate or higher-level maturity for the indicators of independence and non-bias 1 (5%), operations 3 (15%), making recommendations 4 (20%), stakeholder recognition 6 (30%), and resources and secretariat support 7 (35%). Meanwhile 11 (55%) NITAGs had an intermediate or higher maturity level for the indicators of establishment and composition and for integration into policy making process. Participants described NMAT as a concise, useful, user-friendly tool. NMAT is a practical tool that can be used by NITAGs to provide insights and strategic direction for individual countries and regionally. Prevention and management of conflict of interest is the domain that requires the most improvement in EMR. Planned activities should be implemented, monitored and a follow up assessment conducted in 2025.

Comparing the performance of ChatGPT GPT-4, Bard, and Llama-2 in the Taiwan Psychiatric Licensing Examination and in differential diagnosis with multi-center psychiatrists.

Large language models (LLMs) have been suggested to play a role in medical education and medical practice. However, the potential of their application in the psychiatric domain has not been well-studied. In the first step, we compared the performance of ChatGPT GPT-4, Bard, and Llama-2 in the 2022 Taiwan Psychiatric Licensing Examination conducted in traditional Mandarin. In the second step, we compared the scores of these three LLMs with those of 24 experienced psychiatrists in 10 advanced clinical scenario questions designed for psychiatric differential diagnosis. Only GPT-4 passed the 2022 Taiwan Psychiatric Licensing Examination (scoring 69 and ≥ 60 being considered a passing grade), while Bard scored 36 and Llama-2 scored 25. GPT-4 outperformed Bard and Llama-2, especially in the areas of 'Pathophysiology & Epidemiology' (χ2 = 22.4, P < 0.001) and 'Psychopharmacology & Other therapies' (χ2 = 15.8, P < 0.001). In the differential diagnosis, the mean score of the 24 experienced psychiatrists (mean 6.1, standard deviation 1.9) was higher than that of GPT-4 (5), Bard (3), and Llama-2 (1). Compared to Bard and Llama-2, GPT-4 demonstrated superior abilities in identifying psychiatric symptoms and making clinical judgments. Besides, GPT-4's ability for differential diagnosis closely approached that of the experienced psychiatrists. GPT-4 revealed a promising potential as a valuable tool in psychiatric practice among the three LLMs.

A Decision Support Model for Mitigating Supply Chain Risks Based on a Modified FMEA, Multi-Objective Optimization and Multi-Criteria Decision-Making Approach

Abstract Recent years have seen a huge development in the subject of supply chain risk management. In this increasingly uncertain world, the use of practical and effective tools for decision making and risk mitigation has become more necessary than ever. In this research, mitigation strategies for a tier one multinational company operating in the automotive industry and providing an assembly operation to final customer Renault Tanger and Renault SOMACA were prioritized according to their effectiveness, as well as their implementation costs. Based on research in the literature and the opinions of experts in the field. 44 risks and 55 mitigation strategies were identified. FMEA (Failure Modes and Effects Analysis) method was used based on the latest AIAG 2019 edition to filter and identify the risks to be prioritized, we used then a multi-objective optimization approach to identify the mitigation strategies that constitute the Pareto front for each of the risks and finally used the EDAS method for the final ranking of the strategies. Our case revealed that strategies like ensuring elaborating a contingency planning and defining the responsibilities, imposing contractual obligations on subcontractors, applying a flexible supply contract were found to be relevant risk mitigation strategies for the company. Managers interested in mitigating risk can deploy this model to prioritize risk mitigation strategies.

Visualization of temperature distribution and flow behavior in water evaporation using water‐soluble spiropyran

AbstractUnderstanding the convection flows driven by the uneven temperature distribution in heated aqueous solutions is fascinating and meaningful both in fundamental and industrial aspects. Therefore, it is desirable to develop a simple and convenient method for real‐time tracking of surface temperature distribution and the solvent flow state. Herein, we designed and screened a water‐soluble spiropyran derivative (BS‐SP1) that contains benzothiazole and sulfonic acid groups. The BS‐SP1 molecule was found to exceptionally maintain the reversible photochromic characteristics in water, and then served as a photo‐responsive indicator for visualizing the temperature distribution and flow behavior on water surface with high resolution. This study provides feasible guidance on the dynamic self‐assembly and thermodynamics occurring in the water evaporation system and offers a practical tool for investigating these behaviors.

Optimized systems of multi-layer perceptron predictive model for estimating pile-bearing capacity

The primary goal of this research is to leverage the advancements in machine learning techniques to forecast the bearing capacity of piles effectively. Accurately predicting load-bearing capability is an indispensable aspect in the field of substructure engineering. It is worth noting that determining load-bearing capability via in-place burden tests is a resource-intensive and labor-intensive process. This study presents a pragmatic soft computing methodology to tackle the aforementioned challenge, employing a multi-layer perceptron (MLP) for the estimation of load-bearing capacity. The dataset employed in this research encompasses a multitude of field-based pile load tests, with a meticulous selection of the most impactful factors influencing pile-bearing capacity as input variables. For a comprehensive comparative analysis, genetic algorithm-based optimizers (Crystal Structure Algorithm (CSA) and Fox Optimization (FOX)) were incorporated with MLP, leading to the development of hybrid models referred to as MLFO and MLSC, both structured with three layers. The performance of these models was rigorously evaluated using five key performance indices. The findings indicated a consistent superiority of MLFO over MLSC across all three layers. Remarkably, MLFO exhibited exceptional performance in the second layer (MLFO (2)), boasting an impressive R2 value of 0.992, an RMSE of 33.470, and a minimal SI value of 0.031. On the other hand, MLCS (1) registered the lowest accuracy in predicting the process with the least R2 value related to the validation phase of the model with 0.953. Taken together, these results affirm that the optimized MLP model stands as a valuable and practical tool for accurately estimating pile-bearing capacity in civil engineering applications.

Designing for identity: how and when brand visual aesthetics enable consumer diasporic identity

Purpose This paper aims to investigate how and when visual referents in brand visual aesthetics (i.e. colours, shapes, patterns and materials) serve as design applications that enable consumer diasporic identity. Design/methodology/approach This paper uses an innovative methodology that triangulates 58 in-depth interviews with diasporic consumers, 9 interviews with brand managers and designers and a visual analysis of brands (food retailer, spices and nuts, skincare, hair and cosmetics, ice cream and wine) to provide a view of the phenomenon from multiple perspectives. Findings This study illustrates how and when particular applications and compositions of product and design referents support diasporic identity for Middle Eastern consumers living outside the Middle East. Specifically, it illustrates how the design applications of harmonising (applying separate ancestral homeland and culture of living product and design referents simultaneously), homaging (departing from the culture of living product and design referents with a subtle tribute to ancestral homeland culture) and heritaging (departing from the ancestral homeland culture product and design referents with slight updates to a culture of living style) can enable diasporic identity in particular social situations. Research limitations/implications Although applied to the Middle Eastern diaspora, this research opens up interesting avenues for future research that assesses diasporic consumers’ responses to brands seeking to use visual design to engage with this market. Moreover, future research should explore these design applications in relation to issues of cultural appreciation and appropriation. Practical implications The hybrid design compositions identified in this study can provide brand managers with practical tools for navigating the design process when targeting a diasporic segment. The design applications and their consequences are discussed while visually demonstrating how they can be crafted. Originality/value While previous research mainly focused on how consumption from the ancestral homeland occurred, to the best of the authors’ knowledge, this study is the first to examine how hybrid design compositions that combine a diaspora’s ancestral homeland culture and their culture of living simultaneously and to varying degrees resonate with diasporic consumers.

USING SHEEP FACIAL GRIMACE SCALE, INFRARED THERMOGRAPHY AND CORTISOL HORMONE TO MEASURE PAIN IN SHEEP INFECTED WITH MASTITIS DISEASE

The purpose of this study was to apply sheep pain facial expression scales (SPFES) to sheep infected with mastitis, measuring peripheral temperatures and serum cortisol hormone. Twenty-three healthy ewes and 23 infected ewes with clinical mastitis were included in this research from January 2022 to April 2023. Images were taken from each ewe to detect facial grimace scales of ewes. Nasal, eye and ear temperatures were collected using infrared thermal imaging camera. Moreover, serum cortisol hormone was collected from the blood. It was found that there was a significant decrease (p&lt;0.01) in nasal, eye and ear temperatures of infected ewes in comparison to healthy ewes. Additionally, cortisol hormone was found significantly (p&lt;0.01) higher in infected ewes at day 1 and day 7 compared to non-infected animals. The changes in facial expressions for all the determined five regions were significantly (p&lt;0.01) different than healthy ewes. The total pain score was significantly (p&lt;0.05) higher on day 1 and day 7, compared to healthy ewes. It was concluded that sheep facial grimace scale was a useful and practical tool for measuring pain in sheep. In addition, cortisol from the serum and peripheral temperatures were found to be useful pain indicators.

A Novel Domination in Vague Influence Graphs with an Application

Vague influence graphs (VIGs) are well articulated, useful and practical tools for managing the uncertainty preoccupied in all real-life difficulties where ambiguous facts, figures and explorations are explained. A VIG gives the information about the effect of a vertex on the edge. In this paper, we present the domination concept for VIG. Some issues and results of the domination in vague graphs (VGs) are also developed in VIGs. We defined some basic notions in the VIGs such as the walk, path, strength of In-pair , strong In-pair, In-cut vertex, In-cut pair (CP), complete VIG and strong pair domination number in VIG. Finally, an application of domination in illegal drug trade was introduced.

Fluid retention in endoscopes: A real-world study on drying effectiveness

Outbreaks linked to inadequate endoscope drying have infected numerous patients, and current standards and guidelines recommend at least 10minutes of forced air for drying channels. This study evaluated a new forced-air drying system (FADS) for endoscopes. Drying was assessed using droplet detection cards; visual inspection of air/water connectors, suction connectors, and distal ends; and borescope examinations of endoscope interiors. Assessments were performed after automated endoscope reprocessor (AER) alcohol flush and air purge cycles and after 10-minute FADS cycles. Researchers evaluated drying during encounters with 22 gastroscopes and 20 colonoscopes. After default AER alcohol and air purge cycles, 100% (42/42) of endoscopes were still wet. Substantial fluid emerged from distal ends during the first 15seconds of the FADS cycle, and droplets also emerged from air/water and suction connectors. Following FADS cycle completion, 100% (42/42) were dry, with no retained fluid detected by any of the assessment methods. Multiple endoscope ports and channels remained wet after AER cycles intended to aid in drying but were dry after the FADS cycle. This study reinforced the need to evaluate the effectiveness of current drying practices and illustrated the use of practical tools in a real-world setting.

"Giving Me the Self-Confidence to Tackle It": Mothers' Experiences Participating In The Engaged Eaters Program, A Caregiver-Mediated Feeding Intervention.

The purpose of this study was to understand caregivers' experience of participating in a caregiver-mediated in-home feeding intervention, the Engaged Eaters Program, for their young autistic child. This qualitative study utilized a thematic approach to analyze post-intervention semi-structured interviews with thirteen mothers of autistic children between the ages of 2 to 7years after they participated in the intervention. Interview questions focused on the child and family experience, what worked well, what could be improved, and how the intervention integrated into family routines. Four major themes were identified: In-Home Intervention, Parent Skill and Knowledge, Increased Social Participation, and Parent Responsibilities and Challenges. Sub-themes provided descriptions of learning practical tools to support their child, increasing self-efficacy, and impacts on family life. Mothers described an increase in tangible skills that were easily practiced in the home environment that improved their confidence and self-efficacy in feeding their children. They also described how participation did require more work and time commitment for them beyond their regular responsibilities. The caregiver experience is essential to understand for intervention effectiveness while simultaneously addressing child, caregiver, and family needs. By focusing on the mothers' experiences, individualized needs, and self-efficacy, we were able to better understand how integrating an intervention into the family context and daily routines may be beneficial for the whole family.

Enhancing Rigor in Literature Reviews for Business and Management Research: Avoiding Prevalent Errors

The literature review is a crucial component of academic research, providing a comprehensive understanding of the current state of knowledge and guiding future research agendas. However, researchers often make common mistakes that compromise the rigor and effectiveness of their literature reviews. This study aims to identify and discuss these prevalent errors in literature reviews for business and management research and provide researchers with a step-by-step guide to enhance the rigor of their literature reviews. The study highlights common mistakes such as a lack of systematic search strategy, failure to critically evaluate and synthesize the literature, unclear research objectives and questions, and overreliance on outdated or biased sources. By following a systematic approach and avoiding these prevalent errors, researchers can ensure that their literature reviews contribute to the overall rigor and quality of research in the field, facilitating the generation of new ideas, identifying research gaps, and enhancing the understanding of business and management phenomena. This study is vital for researchers, scholars, and business and management research practitioners, providing practical tools to improve the rigor and effectiveness of their literature reviews.

Construction and application of the "Internet + public health service" supply evaluation index system.

To construct an index system for evaluating the supply of Internet+ public health services, and to provide a practical tool for assessing the supply of Internet+ public health services in an objective and scientific manner. The research team drafted the index system framework by combing the literature. The Delphi method was used to determine the content and weight of the index through two rounds of expert consultations. At the same time, the Cronbach coefficient and factor analysis were adopted to test the reliability and validity. What's more, the analytic hierarchy process and the TOPSIS method were applied to analyze the empirical data of 15 counties and cities in the eastern, central, and western regions of China. The constructed indicator system includes 3 first-level indicators, 6 second-level indicators and 29 third-level indicators. Through reliability and validity tests, the stability and practicability of the index system are demonstrated in empirical research. The evaluation index system constructed in this article can be applied to the performance evaluation of Internet + public health service.

Many nonnormalities, one simulation: Do different data generation algorithms affect study results?

Monte Carlo simulation studies are among the primary scientific outputs contributed by methodologists, guiding application of various statistical tools in practice. Although methodological researchers routinely extend simulation study findings through follow-up work, few studies are ever replicated. Simulation studies are susceptible to factors that can contribute to replicability failures, however. This paper sought to conduct a meta-scientific study by replicating one highly cited simulation study (Curran et al., Psychological Methods, 1, 16-29, 1996) that investigated the robustness of normal theory maximum likelihood (ML)-based chi-square fit statistics under multivariate nonnormality. We further examined the generalizability of the original study findings across different nonnormal data generation algorithms. Our replication results were generally consistent with original findings, but we discerned several differences. Our generalizability results were more mixed. Only two results observed under the original data generation algorithm held completely across other algorithms examined. One of the most striking findings we observed was that results associated with the independent generator (IG) data generation algorithm vastly differed from other procedures examined and suggested that ML was robust to nonnormality for the particular factor model used in the simulation. Findings point to the reality that extant methodological recommendations may not be universally valid in contexts where multiple data generation algorithms exist for a given data characteristic. We recommend that researchers consider multiple approaches to generating a specific data or model characteristic (when more than one is available) to optimize the generalizability of simulation results.