Miracle-dz/UniFAR-FTUs huggingface dataset:
Interannual variability of the Indonesian Throughflow: The salinity effect

The Indonesian Throughflow (ITF) region possesses strong mixing and experiences significant freshwater input, but the role of salinity variability in the Indonesian Seas remains unclear. The goal of this study is to understand how salinity variability influences the ITF transport on interannual time scales. The ITF transport is calculated using observations and assimilation data sets and verified using direct ITF transport estimates. We find that the halosteric component of the ITF transport contributes (36 +/- 7)% of the total ITF variability, in contrast to (63 +/- 6)% by the thermosteric component. Thus, while not dominant, this result nonetheless implies that the salinity variability in the Indonesian Seas is of remarkable importance in determining the interannual variability of ITF transport. Correlation analysis indicates that the interannual variability of the total ITF transport is mainly influenced by the El Nino-Southern Oscillation (ENSO) rather than the Indian Ocean Dipole. Under the ENSO cycle, the Walker Circulation shifts longitudinally resulting in fluctuations in precipitation over the Indonesian Seas that modulates salinity and subsequently influences the interannual variability of ITF transport. This result signals the importance of precipitation and the subsequent salinity effect in determining the interannual variability of the ITF transport. The role of wind forcing and oceanic planetary waves is also revisited using this newly calculated ITF transport series. ENSO-related wind forcing is found to modulate the ITF transport via Rossby waves through the wave guide in the Indonesian Seas, which is in agreement with previous studies.
Limits to the measurement of habitual physical activity by questionnaires

physical activity that the problem of validity, reliability, and sensitivity arises. Despite the limitations of questionnaires, they are often used, especially for large populations or studies investigating inﬂuence of lifetime physical activity. This paper gives an overview of the limitations and points out the difﬁculties associated with measurement of physical activity. Different types and patterns of physical activity are detailed, which are used to provide various indicators. It would also be interesting to have an inventory of these indicators and their use depending on the aims of the study. Another pattern that it is important to consider is the regularity of practice during speciﬁc periods of life. Bearing in mind the limitations of questionnaire studies, we are able to specify more adapted tools and to interpret more cautiously the results of the studies.
Something ’ s “ Fishy ” at Global Ways and Gill Breeders – Analysis with nSpace and GeoTime

GeoTime and nSpace are two interactive visual analytics tools that support the process of analyzing massive and complex datasets. The two tools were used to examine and interpret the 2007 VAST contest dataset. This poster paper describes how the capabilities of the tools were used to facilitate and expedite every stage of an analyst workflow. CR
The Innovation Breakthrough in Digital and Disruptive Era

This study analyzes the ease of use of consumer m-payment systems, besides that the risk factors for use are also studied related to the ease of use factor on the intention to use m-payment Gen Z to make payment transactions. The sample in this study was FEB Unmus management students with an average age of 22 years, totaling 165 respondents based on the returned questionnaire. The data were obtained using a research questionnaire adjusted to the variable construct. OLS regression was used to explain the influence of each factor. Given the increasingly advanced mobile technology and online payment instrument competition that continues to grow. The dominant consumer response to PEU2 items provides a clear picture, that privacy data security risks greatly interfere with the intention to use m-payment. Implicitly, mobile-based technology financial services are more compatible with the social behavior of Generation Z consumers, because for them using a mobile platform is a spontaneous solution. This study is certainly not perfect in explaining the role of the TAM model, further implications need to examine other factors such as subjective norms or lifestyle factors, and convenience factors because they use mobile devices anytime to make payments and m-payments quickly and easily. This means that Generation Z will use mobile payments more if they think that m-payment suits their lifestyle.
Remote Eye Tracking : State of the Art and Directions for Future Development

Recent years have seen rapid developments in the field of remote eye tracking. Whereas only a few years ago the standard in eye tracking was for systems to be intrusive, i.e. they either required the user’s head to be fixated or equipment to be mounted on the user’s head, systems have now evolved to the point where the user can move freely in front of the system (within certain limits), and good accuracy (1 degree or better) is achieved throughout the whole working range. This has been demonstrated by a number of commercial and academic systems, both multi-camera (Beymer and Flickner, 2003; LC Technologies, 2006) and singlecamera (Tobii, 2002; SMI, 2006; Hennessey et al., 2006; Guestrin and Eizenman, 2006; Meyer et al., 2006). To clarify terms, we will use the term “remote eye tracking” here to mean a system that operates without contact with the user and permits free head movement within reasonable limits without losing tracking.
Classification and Clustering of Sentence-Level Embeddings of Scientific Articles Generated by Contrastive Learning

Scientific articles are long text documents organized into sections, each describing aspects of the research. Analyzing scientific production has become progressively challenging due to the increase in the number of available articles. Within this scenario, our approach consisted of fine-tuning transformer language models to generate sentence-level embeddings from scientific articles, considering the following labels: background, objective, methods, results, and conclusion. We trained our models on three datasets with contrastive learning. Two datasets are from the article’s abstracts in the computer science and medical domains. Also, we introduce PMC-Sents-FULL, a novel dataset of sentences extracted from the full texts of medical articles. We compare the fine-tuned and baseline models in clustering and classification tasks to evaluate our approach. On average, clustering agreement measures values were five times higher. For the classification measures, in the best-case scenario, we had an average improvement in F1-micro of 30.73%. Results show that fine-tuning sentence transformers with contrastive learning and using the generated embeddings in downstream tasks is a feasible approach to sentence classification in scientific articles. Our experiment codes are available on GitHub.
Parametric Analysis Of Fixations During Object Search

: The movement of eyes while looking at visual stimuli is termed as scan path. One of the major components of scan path is fixations. The analysis of fixations could provide understanding about individual’s area of interest and behavioral pattern. One of the prominent domains of fixation analysis is object searching amidst surrounding distractions. Fixations have generally been analyzed in terms of parameters. In this paper two parameters of fixations have been analyzed during two experiments of object searching. The parameters have been termed as number of fixations and total fixation duration. The results indicate that fixation parameters are impacted more when objects have been searched in images with low color variations than with multiple object content.
Deep Belief Network-Based Investigation Of A New Fast Mppt Technique For Pv Systems Under Non-Uniform Irradiation Conditions

– Because of the large-scale grid-connected photovoltaic (PV) power generation installations that are already in place, accurate PV power forecasting is essential for the safe and efficient functioning of electric power systems. The accuracy of predicting Renewable Energy Sources (RES) is critical since power systems rely on it. It can assist in making the required modifications to function with RES, which is widely accepted. As renewable energy penetration rises, the system may transition to a generation-dominant mode, posing serious power quality challenges. The Deep Belief Network training algorithm is the recommended approach in this study (DBN). The parameters that are utilised to configure the software are carefully examined. The goal of this paper is to identify the DBN's characteristics so that photovoltaic power may be reliably forecasted. The suggested approach is Cross-validated and comparisons are made with other training approach.
Brain Tumor Segmentation Using Fuzzy Otsu Threshold Morphological Algorithm

 Abstract —This article presents a method of segmentation for brain tumor by Fuzzy Otsu Threshold Morphological (FOTM) algorithm. Due to increases in brain tumors, the numbers of acquired magnetic resonance imaging (MRI) increase accordingly. Therefore, highly accurate algorithms being able to automatically segment and detect brain tumors would have prospective potentials for treatment planning and diagnosis. In order to solve this problem, a novel method for segmentation of brain tumors is proposed by using FOTM algorithm from the most asymmetric parts. In addition, the use of color normalization, noise removal, and intensity bias correction as a preprocessing stage, which, though not common in FOTM algorithms, demonstrated together with data segmentation to be very successful for segmentation of brain tumor in MRI images. The results clearly show that the average accuracy indexes of image gliomas, image meningiomas and image pituitary are 93.77%, 94.32% and 94.37% respectively.
The Mediating Role Of Network Service For Customer Satisfaction During COVID-19 Online Classes: Evidence From University Students

Aim of this study to examine the mediating role of network service between perceived quality, retailer service and customer satisfaction during COVID-19. Primary data gathered through adopted questionnaire from previous studies and 200 university students were asked to fill online questionnaire during COVID-19 situation in country. Structural Equation Modelling technique applied in order to test the proposed hypothesis generated from existing literature review. Findings revealed full mediation effect of network service for both perceived quality and retailer service on customer satisfaction during COVID-19. New insights of this study are key role of network services is identified and university students' satisfaction is measured for online classes in developing country, Pakistan. In future serial mediation is suggested for validity of existing results in developed and developing countries.
Automatic Hausa LanguageText Summarization Based on Feature Extraction using Naïve Bayes Model

: Automatic text summarization, a branch of natural language processing, is a technique where a computer summarizes a long text into non-redundant form in order to reduce the problem of information overload. Although there are some language independent summarizers, there is a limited research to automatically summarize text in Hausa language. Hausa, a Chadic language generally spoken in West Africa is a low resource language. This study is conducted to develop a model to automatically summarize Hausa Language text based on feature extraction using Naive Bayes model. A dataset of 10 Hausa Language documents is used in this study. The study adopts five features such as keyword, title and cue phrases in the summarization process. Moreover, Naive Bayes model is used to weigh each sentence based on its features. The system produces a set of summary sentences at 30% compression rate. Moreover, experiments are conducted to summarize the dataset using online summarizers such as Text Compactor and Free summarizers. The overall system testing having an average F-score of 78.1% outperforms the online summarizers. The result shows that automatic text summarization tested on the Hausa Language dataset is better if morphological analysis is considered.
VU Research Portal Homeownership and demand for long-term care

Elderly home-owners get institutionalized less often than renters do. We hypothesize that housing tenure itself explains this behavior. Using longitudinal data from a Dutch community sample (N= 2,372) collected between 1992 and 2005, we find a negative effect of housing tenure on the probability of moving to a nursing home between two subsequent waves. This effect remains significant after controlling for health, socio-economic status and the presence of a partner and or children. We could not reduce this finding to a variety of explanations directly related to housing tenure. There was no substantial effect of higher payments for long-term care for wealthy people before 1997. Neither did we find evidence that home owners have a strategic bequest motive, and use their house to attract informal care from their children. We do find that homeowners use informal care-at-home to postpone or avoid institutionalization. Homeowners do not appear to live in houses more suitable to the needs of old age than renters, they do not have better social networks from which they can recruit informal caregivers. However, they express a greater satisfaction with their housing situation than renters, even if their health deteriorates. We therefore interpret our findings as the result of a strong desire among homeowners to stay where they are – in their own property – and better possibilities they have – as owners – to realize this desire.
Pathways-wide genetic risks in Chlamydial infections overlap between tissue tropisms: A genome-wide association scan

Chlamydia trachomatis is the most commonly diagnosed bacterial sexually transmitted infection and can lead to tubal factor infertility, a disease characterised by fibrosis of the fallopian tubes. Genetic polymorphisms in molecular pathways involving G protein coupled receptor signalling, the Akt/PI3K cascade, the mitotic cell cycle and immune response have been identified in association with the development of trachomatous scarring, an ocular form of chlamydia-related fibrotic pathology. In this case control study, we performed genome-wide association and pathways based analysis in a sample of 71 Dutch women who attended an STI clinic who were seropositive for Chlamydia trachomatis antibodies and 169 high risk Dutch women who sought similar health services but who were seronegative. We identified two regions of within-gene SNP association with Chlamydia trachomatis serological response and found that GPCR signalling and cell cycle pathways were also associated with the trait. These pathway level associations appear to be common to immunological sequelae of Chlamydial infections in both ocular and urogenital tropisms. These pathways may be central mediators of human refractoriness to chlamydial diseases.
A Survey on Convolutional Neural Networks Frameworks on Electroencephalography Data

The inception of learning was through neural networks. ANN has ushered into many fields providing solutions for critical solutions, particular in medical and health care systems. Brain neurological disorder is epilepsy; electroencephalograph is the tool to study it. EEG recordings consume lot of time and they are with uncertain frequencies. Only experts can study and diagnose epilepsy perfectly, even uncertainty rules over into ambiguities. Deep Learning has solutions to solve on the data with multivariate, temporal, uncertainty in nature. EEGs are obtained as signal data as frequency graphs from the electro-encephalography devices, digitized into images. Feature extraction and classification is the most challenging on EEG signal datasets. In this paper, a survey on EEG data sets, analyses method and contributions of CNN in EEG signal data analysis have been discussed, to provide direction for the researchers to handle the most challenging problems.
The Workplace Bullying Influence Job Burnout: The Role Of Core Self-Evaluation

The aim of this study was to examine the relationship between bullying and burnout and the mediating role of Core Self-Evaluation. Workplace bullying has received phenomenal attention in organisational behaviour research in last two decades. It is associated with number of physical and psychological consequences including sick leave and job burnout. Globally, one out of three nurses is experiencing bullying at workplace. However, limited have studies discussed the mediating role of targets’ personality between bullying and burnout. A cross-sectional quantitative study was conducted. Sample of 212 nurses working in teaching hospitals of Pakistan was taken. Data was collected through researcher-administered questionnaire in class room environment. Descriptive statistics were used for demographic analysis of respondents. To test the mediation Preacher and Hayes (2004) approach was used. Bullying has statistically significant positive relation with burnout. CSE is negatively associated with bullying and burnout; and partially mediates the relationship between bullying and burnout. It is concluded that bullying significantly influence targets’ personality and job outcomes. Core Self-Evaluation is negatively associated with bullying and targets reflect low-CSE score and likely to burnout. CSE also negatively associated with job burnout and partially mediates the relationship of bullying and burnout.
Code-Switching In Classroom: Perceived Perception Of English Medium Educational Institutions In Pakistan

Code-switching is a phenomenon of alteration of two languages. The study aimed to find how the English-Urdu code-switching impact on students’ learning at higher education level. The population of the study contained of the faculty members and students studying at public sector universities in Pakistan. However, this study was delimited to the faculty members and students at Ghazi University in Dera Ghazi Khan. Population size was consisted upon 22 academic departments, 150 faculty members and 12000 students. Multistage random sampling was used. At first stage 4 academic departments were randomly selected and at the second stage 120 faculty members and 380 students were randomly selected to make the sample of 500. This study used quantitative methods to survey. Two self-developed questionnaires at 5-point Likert scale were used for gathering information. The research tool was validated through Cronbach alpha. The Cronbach value of the questionnaire for the teachers was . 841 and for the students was . 862 respectively. Percentage, mean score, standard deviation and standard error were calculated by using SSPS-20. The study found that teachers frequently shift from English to Urdu in their instructional process in English medium classes at higher education level. Shifting from English medium to their national language helps students in understanding their concepts in more clear way. Therefore, it helps students to improve their learning. However, the study
Speech Signal in Short-Term Observation

Recently, there has been a signiﬁcant amount of work on the recognition of emotions from visual, verbal or physiological information. Most approaches to emotion recognition so far concentrate, however, on a single modality while work on the integration of multimodal information, in particular on fusing physiological signals with verbal or visual data, is scarce. In this paper, we analyze various methods for fusing physiological and vocal information and compare the recognition results of the bimodal recognition approach with the results of the unimodal approach.
Vitamin C and glutathione supplementation: a review of their additive effects on exercise performance

[Purpose] This review aimed to investigate the effects of vitamin C and glutathione supplementation on exercise performance. [Methods] We conducted a literature search across the PubMed, Google Scholar, and Web of Science databases using the keywords vitamin C, glutathione, antioxidants, exercise, and oxidative stress. [Results] The effects of vitamin C supplementation on exercise performance and oxidative stress levels are inconsistent. Glutathione, with its diverse forms of supplementation and methods, presents mixed outcomes. Vitamin C and glutathione have deeply interconnected antioxidant functions and are mutually essential to each other. Research investigating the combined intake of these two substances, which are intricately linked biochemically, and their effects on exercise performance remain largely unexplored. [Conclusion] Studies on the effects of vitamin C and glutathione intake on exercise have been conducted using diverse approaches; however, the results have not been consistent. Although an additive effect is anticipated with the combined intake of vitamin C and glutathione, research on this topic is currently insufficient, and further studies are required.
Clinical effectiveness of semaglutide on weight loss, body composition, and muscle strength in Chinese adults.

OBJECTIVE The aim of this study was to investigate the clinical effectiveness of semaglutide on weight loss, body composition and muscle strength in the Chinese population with obesity. PATIENTS AND METHODS Data were retrospectively analyzed for participants prescribed semaglutide in 2021 and 2022 from a Chinese weight management clinic. Changes in weight, body composition, biochemical indicators, calf circumference and handgrip strength were collected. Body fat and skeletal muscle were also measured using the bioelectrical impedance analysis. Paired t-test was used to compare the values after 6 months of treatment with the baseline values. RESULTS A total of 53 obese patients received 24 weeks of lifestyle intervention plus semaglutide treatment. 10 patients who failed to adhere to the follow-up were excluded, and 43 patients were studied. The average baseline body mass index (BMI) was 33.0 kg/m2, and the average body weight was 90.0 kg. After 6 months of treatment, the patient's weight was significantly reduced by 9.9 ± 3.9 kg (p < 0.001), and the weight loss percentage was 11.2 ± 4.5% (p< 0.001). The proportion of patients with weight loss ≥ 5% and ≥ 10% was 93% and 54%, respectively. Fasting blood glucose, fasting insulin, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) index, blood uric acid and blood lipid levels also decreased after treatment. Body composition analysis showed that the loss of skeletal muscle mass was 1.4 ± 1.3 kg (p < 0.001), which was significantly less than the loss of fat mass of 5.6 ± 3.7 kg (p < 0.001). By percentage, the fat mass loss was 15.6 ± 10.1%, and the muscle mass loss was 4.8 ± 4.4% (p < 0.001). The visceral fat area was significantly reduced by 24.4 ± 17.7 cm (p < 0.001). There was no significant change in skeletal muscle index (8.1 ± 1.0 kg/m2 at baseline and 7.9 ± 1.0 kg/m2 at 24 weeks). The calf circumference (42.6 ± 3.6 cm at baseline, 41.2 ± 3.8 cm at 24 weeks) and grip strength (33.3 ± 9.5 kg at baseline, 32.3 ± 9.0 kg at 24 weeks) did not decrease significantly. The main adverse reactions were mild gastrointestinal dysfunction (nausea, diarrhea and vomiting), without ketoacidosis. CONCLUSIONS In a real-world setting, semaglutide can reduce the weight and fat of obese patients while effectively maintaining muscle mass and muscle strength.
UvA-DARE ( Digital Academic Repository ) Inelastic bouncing and optical trapping of cold atoms

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