Analysis Approach Research Articles

Assessing the contribution of RGB VIs in improving building extraction from RGB-UAV images

Buildings are a fundamental component of the built environment, and accurate information regarding their size, location, and distribution is vital for various purposes. The ever-increasing capabilities of unmanned aerial vehicles (UAVs) have sparked an interest in exploring various techniques to delineate buildings from the very high-resolution images obtained from UAV photogrammetry. However, the limited spectral information in UAV images, particularly the number of bands, can hinder the differentiation between various materials and objects. This setback can affect the ability to distinguish between different materials and objects. To address this limitation, vegetative ındices (VIs) have been employed to enhance the spectral strength of UAV orthophotos, thereby improving building classification. The objective of this study is to evaluate the contribution of four specific VIs: the green leaf index (GLI), red-green-blue vegetation index (RGBVI), visual atmospherically resistant index (VARI), and triangular greenness index (TGI). The significance of this contribution lies in assessing the potential of each VI to enhance building classification. The approach utilized the geographic object-based image analysis (GeoBIA) approach and a random forest classifier. To achieve this aim, five datasets were created, with each dataset comprising the RGB-UAV image and a corresponding RGB VI. The experimental results on the test dataset and a post-classification assessment indicated a general improvement in the classification when the VIs were added to the RGB orthophoto.

Causal association between 25-hydroxyvitamin D status and cataract development: A two-sample Mendelian randomization study

BACKGROUND Vitamin deficiencies are linked to various eye diseases, and the influence of vitamin D on cataract formation has been noted in prior research. However, detailed investigations into the causal relationship between 25-(OH)D status and cataract development remain scarce. AIM To explore a possible causal link between cataracts and vitamin D. METHODS In this study, we explored the causal link between 25-(OH)D levels and cataract development using Mendelian randomization. Our analytical approach included inverse-variance weighting (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods. The primary analyses utilized IVW with random effects, supplemented by sensitivity and heterogeneity tests using both IVW and MR-Egger. MR-Egger was also applied for pleiotropy testing. Additionally, a leave-one-out analysis helped identify potentially impactful single-nucleotide polymorphisms. RESULTS The analysis revealed a positive association between 25-(OH)D levels and the risk of developing cataracts (OR = 1.11, 95%CI: 1.00-1.22; P = 0.032). The heterogeneity test revealed that our IVW analysis exhibited minimal heterogeneity (P > 0.05), and the pleiotropy test findings confirmed the absence of pleiotropy within our IVW analysis (P > 0.05). Furthermore, a search of the human genotype-phenotype association database failed to identify any potentially relevant risk-factor single nucleotide polymorphisms. CONCLUSION There is a potential causal link between 25-(OH)D levels and the development of cataracts, suggesting that greater 25-(OH)D levels may be a contributing risk factor for cataract formation. Further experimental research is required to confirm these findings.

Green infant formula analysis: Optimizing headspace solid-phase microextraction of carbonyl compounds associated with lipid peroxidation using GC-MS and pentafluorophenylhydrazine derivatization

The refinement and optimization of a method combining headspace solid-phase microextraction (HS-SPME) with gas chromatography-mass spectrometry (GC-MS) was successfully performed for the first time to determine seven carbonyl and dicarbonyl compounds, including glyoxal, methylglyoxal, dimethylglyoxal, and malondialdehyde in infant formulae, related to lipid peroxidation. HS-SPME was utilized for simultaneous extraction and derivatization with pentafluorophenylhydrazine (PFPH). Critical parameters such as temperature, pH, extractive phase, and salting-out were meticulously investigated and fine-tuned by an asymmetrical 2232//9 screening design to ensure the method's efficacy and reliability. Optimal conditions included a PFPH concentration of 5 g/L, pH 5.0, head-space extraction at 60 °C within 10 min, utilizing a DVB/CAR/PDMS coating, and a 20% w/w salting-out. The analytical validation of this method, compliant with FDA guidelines, demonstrated exceptional linearity, sensitivity, specificity, precision (RSD ≤13.8%), and accuracy (84.8% ≤ recovery ≤111.5%). The metric approach AGREEprep confirms its eco-friendliness, marking a significant step towards an environmentally conscious approach in infant formula analysis. An occurrence study conducted on 25 infant formula samples revealed widespread carbonyl and dicarbonyl compounds in both powdered and liquid variants. ANOVA results exhibited variations in compound concentrations among different sample groups. Clustering analyses delineated distinct groups based on carbonyl content, indicating the potential of these compounds as markers for lipid peroxidation and food quality assessment. This method serves as a valuable tool for evaluating infant formula quality, stability towards oxidation, and safety.

Network-based representations and dynamic discrete choice models for multiple discrete choice analysis

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application intractable. To overcome this challenge, we introduce directed acyclic graph (DAG) based representations of choices where each node of the DAG is associated with an elemental alternative and additional information such as the number of selected elemental alternatives. Our innovation is to show that the multi-choice model is equivalent to a recursive route choice model on the DAG, leading to the development of new efficient estimation algorithms based on dynamic programming. In addition, the DAG representations enable us to bring some advanced route choice models to capture the correlation between subset choice alternatives. Numerical experiments based on synthetic and real datasets show many advantages of our modeling approach and the proposed estimation algorithms.

An assessment of the mediating role of hypertension in the effect of long-term air pollution exposure on dementia

Background: Growing evidence links air pollution exposure to the risk of dementia. We hypothesized that hypertension may partially mediate this effect. Methods: We previously documented an association between air pollution and dementia in the Ginkgo Evaluation of Memory Study, a randomized, placebo-controlled trial of 3069 adults ≥75 years across four US sites who were evaluated for dementia every 6 months from 2000–2008. We utilized a two-stage regression approach for causal mediation analysis to decompose the total effect of air pollution on dementia into its natural direct and indirect effect through prevalent hypertension. Exposure to air pollution in the 10 or 20 years before enrollment was assigned using estimates from fine-scale spatial-temporal models for PM2.5, PM10, and NO2. We used Poisson regression models for hypertension and Cox proportional hazard models for time-to-incident all-cause dementia, adjusting for a priori confounders. Results: Participants were free of mild cognitive impairment at baseline (n = 2564 included in analyses); 69% had prevalent hypertension at baseline. During follow-up, 12% developed all-cause dementia (Alzheimer’s disease [AD] = 212; vascular dementia with or without AD [VaD/AD mixed] = 97). We did not find an adverse effect of any air pollutant on hypertension. Hypertension was associated with VaD/AD mixed (HR, 1.92 [95% CI = 1.14, 3.24]) but not AD. We did not observe mediation through hypertension for the effect of any pollutant on dementia outcomes. Conclusions: The lack of mediated effect may be due to other mechanistic pathways and the minimal effect of air pollution on hypertension in this cohort of older adults.

Analysis of the influence of communication, leadership, and work teams on nurse discipline

Introduction: The availability of quality health services for the community must receive attention from the government as one of the efforts to develop the health sector. Disappointing evidence regarding improvement in nurses' safe and quality care elevates the need to broaden our knowledge regarding the factors that enhance constant learning in nursing teams. Objective: Analyzes the effect of communication, leadership, and teamwork on nurse discipline. Methods: This quantitative research uses an analytical observational approach and a cross-sectional research design. With the analysis of the data, a linear regression test. The sample was selected using the cluster random sampling method with 36 respondents. Result: This shows the results of a linear regression test with a communication value of p = 0.024, a leadership p = 0.057, and a work team value of p = 0.004, so it can be supposed that there is an influence between the effectiveness of the work team and nurse discipline. So, it can be concluded that the point of communication and the effectiveness of the work team affect the discipline of nurses. Conclusion: the effect of the level of communication effectiveness and the effectiveness of the work team on the discipline of nurses. The story of the effectiveness of nurses can be increased by regulating the flow of information by sending authorized delegates. They are utilizing feedback to maintain organizational communication effectiveness by providing nurses with orientation, direction, and supervision.

The Concept of Electronic Pensioner in Some Countries Versus Romania

We aim to introduce the concept of e-pensioner (EP) with the intention of having this term used as a document within the European Union’s strategy on Artificial Intelligence (AI) for the period 2023-2027 and after implemented into the legislation of member countries. The relationship between older generations and emerging forms of digitalization and artificial intelligence is the focal point, aiming to provide an easily approachable dimension for pensioners. This article presents an analytical framework and approaches for integrating pensioners into the digital era. Following the exposition of theoretical foundations, the article delineates the use of pensioner cards in select countries worldwide. The intersection of pensioners with the digital era proves to be a fertile entry point for examining regulatory ordinances in the digital realm. A novel digital form, the AI-based digital portal, involves a technique of facial authentication for pensioners to send digital life certificates. Two key factors are named across all examined countries. The primary driver of digital transformation is propelled by the desire to enhance the efficiency and efficacy of public administration, which becomes particularly crucial as populations age, leading to increased demand for social services and competition for limited resources in the developed public sector. The innovative application of technology presents opportunities for streamlining processes, enhancing productivity, and reducing costs while concurrently improving service quality. The use of artificial intelligence (AI) in the management and administration of public pension funds stands for a natural progression of technology in the public domain. In an environment characterized by complexity and volatility, AI can provide a level of analysis and prediction that exceeds human ability. Presently, there exists a wide array of AI-powered tools for object detection, natural language processing, understanding and inference, optical character recognition, predictive analytics, anomaly detection, noise elimination, model forecasting, recommendation systems, and monitoring and observability.

Work motivation of implementing nurses to improve the quality of health services

Introduction: The motivation of the implementing nurse is essential to improving the quality of health services. Implementing nurses plays a vital role in providing quality services to patients. High work motivation is crucial in enhancing nurses' performance and commitment to providing the best care. Objective: Knowing the motivation behind implementing nurses can improve the quality of health services. Method: This research is quantitative, with a cross-sectional study design using a quantitative analytical approach. The number of samples was 81 people using total sampling. The research instrument used was a questionnaire with a Likert scale. The analysis method uses the Fisher's exact test. Results: Based on the results of the analysis, these employees have discipline that is still lacking in completing work, while of the 5 respondents who have low work motivation, three respondents (3.7%) have good performance. This is because employees have effectiveness, efficiency, authority, responsibility, discipline, and good work initiative. The statistical test results using Fisher's exact test obtained p = 0.009, smaller than a = 0.05 (p < 0.05), which means Ho is accepted and Ha is rejected. This suggests there is a meaningful relationship between work motivation and. Conclusion: The researchers found that the work motivation of implementing nurses can improve the quality of health services. Implementing nurses can enhance healthcare quality, build team spirit, and achieve organisational goals. These efforts help increase patient satisfaction and improve job satisfaction and nurses' well-being. Therefore, understanding and applying compelling work motivation is the key to improving the quality of health services.

Arslantepe in the foreground: The economic and social role of the large blades at the end of the 4th millennium BC

This paper focuses on the study of large blade assemblages made from chert raw materials at the site of Arslantepe VI-A period (3500–3200 BCE). By applying an analytical approach combining raw material characterization (NM-PCI protocol), technological and use-wear analyses, and experimental archaeology, we discuss our results from a double perspective. At first glance, we demonstrate the great potential that this proxy offers for the reconstruction of technical systems and routine activities in late prehistoric sites. Secondly, we highlight the contribution of large blades for understanding socio-economic dynamics in case-oriented debates. Specifically, large chert blade study provides further pieces of the puzzle to characterize technical and economic behaviors of the social group settled on the mound of Arslantepe at the end of the 4th millennium BC. At this time, a palatine complex with centralized administration and symbols of power, were tools to boost social inequality.

Effects of steel bolts on retrofitting the buckling performance of storage rack system uprights

Storage rack systems, essential for product storage, encounter design challenges, particularly for uprights under axial loading. Despite being produced from thin-walled steel sheets, these systems are required to support excessive loads. Extensive research has focused on maximizing the load-bearing capacity of rack uprights in recent years. This study aims to enhance the axial load capacity of upright profiles through a retrofitting method of installing steel bolts and spacers. Experimental, numerical, and analytical evaluations were conducted to assess the effectiveness of bolt installation in enhancing axial strength of the uprights. Bolt installation altered buckling modes, suppressing distortional buckling. Results consistently showed an increase in axial load capacity with bolt installation, particularly notable in taller uprights. Comparison of experimental, numerical, and analytical results revealed good alignment, highlighting the positive impact of bolt installation on structural stability. Numerical analysis slightly underestimated experimental outcomes, especially for longer lengths, while the analytical approach showed a combination of overestimation and underestimation, with significant overestimation for longer lengths. The study concludes that bolt installation effectively increases the axial load capacity, especially for taller uprights. These findings offer remarkable insights on the positive effect of bolt installation for optimizing storage rack systems by enhancing structural stability and eliminating distortional buckling.

Accident black spots identification based on association rule mining

This paper presents an analytical approach to identifying the important characteristics of accident black spots on Moroccan rural roads. An association rule mining method is applied to extract road spatial characteristics associated with fatal accidents. The weighted severity index was calculated for each section, which was then used to determine the severity levels of black spots. The apriori algorithm is applied to find the correlation between road characteristics and the severity levels of black spots. Then, a general rule selection method is proposed to identify the rules strongly associated with each severity level. The results show that the proposed approach is effective in identifying the most important factors contributing to accidents. Furthermore, it shows that the combination of several road characteristics, such as road width, road surface, and bridge presence, may contribute to fatal accidents. The general rule selection found that wet, bad surfaces, and narrow shoulders were significantly associated with accidents on rural roads. The findings of the present study can help develop effective strategies to reduce road accidents and thus improve road safety in the country.

An Analytical Approach for Buckling of FG Cylindrical Nanopanels Resting on Pasternak’s Foundations in the Thermal Environment

An Analytical Approach for Buckling of FG Cylindrical Nanopanels Resting on Pasternak’s Foundations in the Thermal Environment

The thermodynamic properties of diatomic gases. A rigorous analytical approach

The paper reports a closed-form analytical representation of the thermodynamic functions of diatomic molecules in the ground electronic state. For this purpose, analytical formulas for vibrational and rotational partition functions are derived. A rigorous method is proposed for factorizing the vibrational and rotational contributions to the ro-vibrational partition function using an average vibrational quantum number. The behavior of thermodynamic functions as a function of temperature is discussed for carbon monoxide as a test system. The reliability of the analytical method is verified by comparison with experimental data and with the direct summation method, which uses theoretical values of energy levels.

Testing the Significance of Ranked Gene Sets in Genome-wide Transcriptome Profiling Data Using Weighted Rank Correlation Statistics

Background: Popular gene set enrichment analysis approaches assumed that genes in the gene set contributed to the statistics equally. However, the genes in the transcription factors (TFs) derived gene sets, or gene sets constructed by TF targets identified by the ChIP-Seq experiment, have a rank attribute, as each of these genes have been assigned with a p-value which indicates the true or false possibilities of the ownerships of the genes belong to the gene sets. Objective: Popular gene set enrichment analysis approaches assumed that genes in the gene set contributed to the statistics equally. However, the genes in the transcription factors (TFs) derived gene sets, or gene sets constructed by TF targets identified by the ChIP-Seq experiment, have a rank attribute, as each of these genes have been assigned with a p-value which indicates the true or false possibilities of the ownerships of the genes belong to the gene sets. Methods: A method was proposed by first creating ranked gene sets and gene lists and then applying weighted Kendall's tau rank correlation statistics to the test. After introducing top-down weights to the genes in the gene set, a new software called "Flaver" was developed. Results: Theoretical properties of the proposed method were established, and its differences over the GSEA approach were demonstrated when analyzing the transcriptome profiling data across 55 human tissues and 176 human cell-lines. The results indicated that the TFs identified by our method have higher tendency to be differentially expressed across the tissues analyzed than its competitors. It significantly outperforms the well-known gene set enrichment analyzing tools, GOStats (9%) and GSEA (17%), in analyzing well-documented human RNA transcriptome datasets. Conclusions: The method is outstanding in detecting gene sets of which the gene ranks were correlated with the expression levels of the genes in the transcriptome data.

Synchronization Functions of “Mickey-Mousing” in Animation Film Rhapsody Rabbit

Synchronization between visual animation and music has been widely known as mickey-mousing. Notable old animation films have used this particular technique to reinforce action with a musical flourish and convey a certain meaning. Furthermore, animation music is commonly based on popular music, such as The Hungarian Rhapsody No.2 in Rhapsody Rabbit. The music is utilized not just as a scoring aspect but to dictate every Bugs Bunny's action when playing the piano. This research aims to study the implementation of the mickey-mousing technique in Rhapsody Rabbit film. It uses a qualitative content analysis approach to analyze visual and aural aspects—primary data is sourced from the Rhapsody Rabbit film and the Hungarian Rhapsody No. 2 music sheet. Secondary data is collected from literature studies related to the topic. Data collection is conducted through observation, interview, and documentation study. The data is analyzed using Klaus Krippendorf's content analysis technique which divided into six steps. The result of this study is that the mickey-mousing technique is implemented through a combination of a fast pace of visual and musical play altogether. Animation adapts to several parts of the musical composition so that articulation, illustration, and accentuation occur as a function of the mickey-mousing technique.

Unveiling the patient-centered approach: exploring the needs of Javanese stroke patients in home health services

Home-based care can be effective, efficient, safe, and affordable, if this care is performed using a patient-centered approach. Patient-centered care prioritizes the patient’s needs and preferences. The issue of patient-centered care remains the focus of various parties. This study aimed to explore the expectations of patients who have experienced a stroke, their family caregivers as recipients of home-based care services and healthcare workers as home-based care providers. This study used a qualitative explorative model. Semi-structured interviews were conducted with 19 participants, in addition to 4 focus group discussions. Data was analyzed using a content analysis approach with open code 13 software and the results were presented in COREQ systematics for qualitative studies. There were four main themes present in the results: physical well-being, self-actualization, psychological condition and balance between family burden and coping. Physical limitations were highlighted as the most burden some for the majority of the participants. At the time of the study, the majority of the patients, their family and health workers were diligently working towards to achieving the best outcome regarding physical well-being. Physical well-being is a fundamental need. Reaching this goal, could lead to better self-actualization, better physiological condition and improving the burden on families. This study may be useful as preliminary data to compile a home-based care construct indicators for stroke patients.

Financial medicine: A multi-dimensional concept moving towards contextually specific working definitions for use in the South African prehospital setting

IntroductionThe phenomenon that has been described as Financial Medicine has been occurring within the South African Healthcare sector for at least the last decade. Despite the ongoing effect of this phenomenon, there is no organised body of knowledge or formulated working definitions to guide knowledge sharing and theorisation within this research focus area. The practice of Financial Medicine exerts a deleterious effect on the South African prehospital healthcare system, and represents an area in dire need of focused research efforts. Establishing appropriate working definitions and associated taxonomy is an important first step in supporting further research efforts into this aspect of South African prehospital healthcare systems. MethodsA qualitative research methodology following a constructivist grounded theory design was used. Participants voluntarily consented to be enrolled into one-on-one in-depth interviews, and were selected using purposive and theoretical sampling techniques. Data was subjected to validated coding procedures and analysed using the constant comparative analysis approach, analytical diagramming, and supported by researcher theoretical sensitivity. ResultsA working definition for Financial Medicine is provided. Six new terms are introduced, with associated working definitions, namely Financial Medicine Practices, Treatment-based profiteering, Cost-of-care-aversion, Personal-gain-at-patient-expense, Money-racketeering-in-healthcare, and Impoverishing-healthcare-earning. ConclusionThe working definitions and suggested taxonomy presented in this article are the first step in formally conceptualising and theorising the phenomenon of Financial Medicine, in order to support further research and collaboration in this space.

Dealing imbalance dataset problem in sentiment analysis of recession in Indonesia

<span lang="EN-US">Global recession news dominates social media, particularly in Indonesia, with social news platforms on Twitter generating public responses and <br /> re-tweetings on the issue. Mining these opinions from Twitter using a sentiment analysis approach yields invaluable insights. The research stages included data collection, pre-processing, data labeling using the <br /> lexical-based method like valence aware dictionary and sentiment reasoner (VADER) and TextBlob, sampling techniques using synthetic minority oversampling technique (SMOTE) and random over sampling (ROS) before and after splitting data, and modeling using machine learning such as support vector machines (SVM), k-nearest neighbour (KNN), naive Bayes, and model evaluation. The problem is that almost 300,000 data collected from NodeXL are unbalanced. The findings show that models with balanced datasets show better model evaluation results. The sampling technique was carried out before and after splitting the data. The model evaluation results show that the Bernoulli-naive Bayes algorithm, with the VADER labeling technique, and the SMOTE sampling technique after splitting data, obtains the best accuracy of 84%, and using the ROS technique obtains an accuracy of 81%. On the other hand, with the SMOTE and ROS technique before splitting data on the SVM algorithm, it gets the best accuracy of 93% from before if only using SVM only reached 84%.</span>

Dynamic Thermal Rating in Diverse Climatic Conditions: Uncertainty Analysis and Fuzzy Logic Approach

Abstract: In recent times, there has been a significant rise in the need for electricity, a trend expected to continue. This surge in demand has resulted in transmission lines operating at much higher capacities, which in turn exposes them to increased thermal and mechanical stress, ultimately impacting the reliability of the transmission network. In this paper presents a comprehensive analysis of the static thermal rating (STR) and dynamic thermal rating (DTR) of power lines across varied climatic conditions. The study encompasses a thorough investigation into the thermal behavior of power lines during both summer and winter seasons over a 24-hour period. Through rigorous computational simulations and empirical data collection, the STR and DTR profiles are determined to assess the real-time capacity of power lines under changing environmental conditions. Furthermore, the research introduces a novel approach utilizing fuzzy logic to model the dynamic thermal rating (FDTR) based on the IEEE 738 standard, in regions characterized by diverse climatic patterns. By integrating fuzzy logic with meteorological data, the FDTR model offers enhanced accuracy in predicting the thermal performance of power lines, considering factors such as ambient temperature, wind speed, and solar radiation. The proposed methodology aims to provide utilities and grid operators with a reliable tool for optimizing power transmission capacity, mitigating the risk of overheating, and ensuring grid reliability in regions with complex and fluctuating weather conditions. This study contributes to the advancement of smart grid technology and facilitates efficient energy management in diverse climate zones

Decoding Gender Representation and Bias in Voice User Interfaces (VUIs)

This article offers a thorough exploration of gender representation and bias within Voice User Interfaces (VUIs), delving into their intricate impact on technology design, user interaction, and broader societal dynamics. It scrutinizes the entrenched gender stereotypes inherent in VUI design, revealing the intricate interplay between technology, cultural norms, and gender expectations[1]. It highlights the ethical implications of such biases, emphasizing the need for diverse perspectives in the development of VUIs[2], [3]. the article advocates for a multifaceted approach to understanding and identifying bias in VUIs, incorporating methodologies such as data analysis, algorithmic auditing, and user testing[4]. Beyond individual interactions, it discusses how gender bias in VUIs can erode trust, diminish user satisfaction, and perpetuate systemic inequalities[1]. Proposing a shift towards gender-neutral design principles, it advocates for inclusivity and equity, championing personalized experiences and diverse representation. Looking ahead, the article outlines future directions in VUI technology aimed at advancing gender equality through enhanced natural language understanding, sentiment analysis, and collaborative design approaches[4]. By unraveling and addressing gender representation and bias in VUIs, this article lays a robust foundation for fostering a more inclusive and equitable landscape in voice technology.