Miracle-dz/UniFAR-FTUs huggingface dataset:
Vitamin D and Subclinical Cardiovascular Damage in Essential Hypertension

Vitamin D deficiency is linked to cardiac dysfunction, vascular remodeling, metabolic syndrome and insulin resistance (IR). The aim of the present study was to evaluate the association between vitamin D levels and cardiovascular (CV) organ damage in a large cohort of newly diagnosed treatment-naïve hypertensive patients, and the role of IR in this context. We enrolled 500 Caucasian individuals, without CV or renal complications. Subjects underwent a complete evaluation and measurements of vitamin D, standard laboratory determinations and instrumental examination, including echocardiography and applanation tonometry. Linear regression analyses were performed to assess the correlation between pulse wave velocity (PWV) and left ventricular mass index (LVMI) with different covariates. PWV was significantly correlated with age (p < 0.0001), LDL cholesterol (p < 0.0001), BMI (p = 0.001), pulse pressure (PP) (p = 0.005) and high sensitivity C-reactive protein (hs-CRP) (p = 0.006), while an inverse correlation was observed with vitamin D levels (p < 0.0001), Matsuda index (p < 0.0001) and estimated glomerular filtration ratio (e-GFR) (p = 0.006). LVMI significantly correlated with PP (p < 0.0001), hs-CRP (p < 0, 0001) and age (p = 0.001), while an inverse relationship was observed with vitamin D levels (p < 0.0001), Matsuda’s insulin sensitivity index (ISI) (p < 0.0001) and e-GFR (p < 0.0001). Vitamin D was the strongest predictor of PWV and LVMI, explaining, respectively, 28.3% and 19.1% of their variation. Our study suggests that low vitamin D might be a biomarker of end-organ damage.
Emotion Detection in Twitter Social Media Using Long Short-Term Memory (LSTM) and Fast Text

Emotion detection is important in various fields such as education, business, employee recruitment. In this study, emotions will be detected with text that comes from Twitter because social media makes users tend to express emotions through text posts. One of the social media that has the highest user growth rate in Indonesia is Twitter. This study will use the LSTM method because this method is proven to be better than previous studies. Word embedding fast text will also be used in this study to improve Word2Vec and GloVe that cannot handle the problem of out of vocabulary (OOV). This research produces the best accuracy for each word embedding as follows, Word2Vec produces an accuracy of 73,15%, GloVe produces an accuracy of 60,10%, fast text produces an accuracy of 73,15%. The conclusion in this study is the best accuracy was obtained by Word2Vec and fast text. The fast text has the advantage of handling the problem of out of vocabulary (OOV), but in this study, it cannot improve the accuracy of word 2vec. This study has not been able to produce very good accuracy. This is because of the data used. In future works, to get even better results, it is expected to apply other deep learning methods, such as CNN, BiLSTM, etc. It is hoped that more data will be used in future studies.
A million asteroid observations in the Sloan Digital Sky Survey

Context. The populations of small bodies of the Solar System (asteroids, comets, Kuiper-Belt objects) are used to constrain the origin and evolution of the Solar System. Both their orbital distribution and composition distribution are required to track the dynamical pathway from their regions of formation to their current locations. Aims. We aim at increasing the sample of Solar System objects that have multi-filter photometry and compositional taxonomy. Methods. We search for moving objects in the archive of the Sloan Digital Sky Survey. We attempt at maximizing the number of detections by using loose constraints on the extraction. We then apply a suite of filters to remove false-positive detections (stars or galaxies) and mark out spurious photometry and astrometry. Results. We release a catalog of 1 542 522 entries, consisting of 1 036 322 observations of 379 714 known and unique SSOs together with 506 200 observations of moving sources not linked with any known SSOs. The catalog completeness is estimated to be about 95% and the purity to be above 95% for known SSOs.
Goldilocks in Cardiac Arrest: A Scoping Review of Invasive Hemodynamic Monitoring in the Pre-Hospital Setting for Getting Adrenaline Dosing Just Right

Introduction A one-size-fits-all approach to adrenaline dosing is likely to be sub-optimal for out-of-hospital cardiac arrest given the diverse nature of patient age, bodyweight, frailty and intra-arrest coronary perfusion pressure. An individualised adrenaline dosing approach to cardiac arrest using invasive blood pressure monitoring has been shown to increase rates of return of spontaneous circulation in the hospital setting, but evidence for this approach has not yet been reviewed in the pre-hospital setting. Methods A scoping review was undertaken using Science Direct, ProQuest, PubMed, CINAHL Complete and GALE Health and Wellness databases with the search terms ‘arterial line’, ‘pre-hospital’, ‘cardiac arrest’ and similar derivatives. Subject matter experts and authors of articles meeting inclusion criteria were also consulted to help identify further relevant studies. Articles were included if they pertained to the use of arterial lines in cardiac arrest in the pre-hospital field, and excluded if they related to traumatic cardiac arrest, in a language other than English, Dutch or French, or not retrievable as a full text. Results A total of 1408 articles were identified using the search method, of which three remained after de-duplication, use of inclusion and exclusion criteria, and full text appraisal. The current pre-hospital literature is lacking and avenues for further research to improve the evidence for hemodynamic guided resuscitation were identified. Conclusion Paramedic-initiated invasive arterial monitoring presents a new, but as yet unproven, intervention for improving cardiac arrest outcomes.
Data Collection Maximization in IoT-Sensor Networks via an Energy-Constrained UAV

In this paper, we study sensing data collection of IoT devices in a sparse IoT-sensor network, using an energy-constrained Unmanned Aerial Vehicle (UAV), where the sensory data is stored in IoT devices while the IoT devices may or may not be within the transmission range of each other. We formulate two novel data collection problems to fully or partially collect data stored from IoT devices using the UAV, by finding a closed tour for the UAV that consists of hovering locations and the sojourn duration at each of the hovering locations such that the accumulative volume of data collected within the tour is maximized, subject to the energy capacity on the UAV, where the UAV consumes energy on both hovering for data collection and flying from one hovering location to another hovering location. To this end, we first propose a novel data collection framework that enables the UAV to collect sensory data from multiple IoT devices simultaneously if these IoT devices are within the coverage range of the UAV, through adopting the orthogonal frequency division multiple access (OFDMA) technique. We then formulate two data collection maximization problems to deal with full or partial data collection from IoT devices at each hovering location, and show that both defined problems are NP-hard. We instead devise approximation and heuristic algorithms for the problems. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrated that the proposed algorithms are promising.
Socialization of lying scale: development and validation of a parent measure of socialization of truth and lie-telling behavior

Abstract This study focused on the development of the Socialization of Lying scale for which exploratory factor analysis demonstrated four empirically interpretable subscales: Parents’ Values and Direct Socialization about Honesty, Encouragement and Modeling of Lying, Consequences for Lying, and The Child’s Problematic Lying. These emergent factors suggest that parents teach and give messages about honesty in explicit and implicit ways that may map onto the different domains in which they socialize the behavior. Future research should focus on further validation and revision of items. This measure can serve as tool for researchers to examine the influence of parent values and socialization practices on children’s truth and lie-telling behavior.
Measurement of in-plane thermal conductivity in polymer films

Measuring the in-plane thermal conductivity of organic thermoelectric materials is challenging but is critically important. Here, a method to study the in-plane thermal conductivity of free-standing films (via the use of commercial equipment) based on temperature wave analysis is explored in depth. This subject method required a free-standing thin film with a thickness larger than 10 μm and an area larger than 1 cm2, which are not difficult to obtain for most solution-processable organic thermoelectric materials. We evaluated thermal conductivities and anisotropic ratios for various types of samples including insulating polymers, undoped semiconducting polymers, doped conducting polymers, and one-dimensional carbon fiber bulky papers. This approach facilitated a rapid screening of in-plane thermal conductivities for various organic thermoelectric materials.
Accurate localization of moving objects in dynamic environment for small unmanned aerial vehicle platform using global averaging

Small unmanned aerial vehicles (UAVs) have developed rapidly and are widely used for disaster relief, traffic monitoring and military surveillance. To perform these tasks better, it is necessary to improve the environmental perception ability of UAVs in a dynamic environment, including their static and dynamic perception ability. Specifically, both three ‐ dimensional reconstruction for a static scene and localization for moving objects are required. Simultaneous Localization And Mapping technology has made great progress in static scene structure reconstruction and UAV self ‐ motion estimation. However, accurate real ‐ time localization of moving objects is still challenging. In this article, a global averaging based localization method is proposed to locate moving objects for a small UAV platform. Inspired by global structure from motion, this idea is applied to the localization of moving objects. To solve moving object localization, the relative motion estimation and global position optimisation methods are proposed. The proposed method was tested in various scenarios with a several trajectories. The extensive experimental results demonstrate the robustness and effectiveness of the proposed method.
PATIENT WITH MAJOR ENDOGENOUS DEPRESSIVE EPISODE WITH SUICIDE ATTEMPT

Motivation: Suicide is a major psychiatric emergency, men being more inclined to successful suicide, not to attempts and to approach it by abrupt and aggressive means. Objectives: To present a male patient who developed a major depressive episode, in which the reactive component had a significant contribution in return for endogeny. The suicide attempt quickly escalated changes in thymic function over several days. Results: The patient corresponds to the age at which major depressive disorder begins. There remains a clinical discussion between a genuine suicide attempt, carried out with a plan, internal turmoil, rumination or a parasuicide, in which the person in question needed a change in the field of consciousness to try to throw himself in front of the subway. Note the high internal tension, the absence of the search for alternative solutions, the narcissistic wound, the endo-psychic vulnerability, the elements of correctness such as structural mental rigidity. Conclusions: Early responsiveness to medication emphasizes the endogenous potential and the potential of vulnerability, after the approach through a combination of antidepressants and antipsychotics, the latter developing a clearer perspective on reality and decisions.
Technology as a Tool for Transnational Organized Crime

Using technology to commit crimes is becoming much more prevalent. The internet has provided organized criminal entities anonymity and accessibility to criminal networks across the world to expand their illicit businesses. Technology is allowing for different organizations to co-exist and assist one another to achieve their goals. Organized crime entities are not only utilizing cyberspaces to communicate with networks across the globe but are also utilizing these spaces to aid in money laundering. Money laundering processes have begun to move online to better obscure assets in relation to criminal activity. Therefore, technology is creating a more dynamic and complex world to combat organized crime.
Smallholder adoption of technology: Evidence from the context of climate smart agriculture in South Africa

Climate change represents a serious threat to African agriculture, consequently leading to water scarcity and climate variability. These challenges negatively impact agricultural production. Climate-smart Agriculture (CSA) technologies, such as drought-tolerant seed varieties (DTSVs), can provide a solution. However, effective adoption and use of these technologies within smallholder communities is not straight forward. This study investigated the factors determining adoption of CSA technologies by exploring the farmers’ characteristics, contextual factors, and considered additional factors extracted from farmers’ perceptions of CSA technology-specific attributes. The study was carried out in Limpopo Province, South Africa. Quantitative and qualitative data from farmers’ cross-sectional survey (n=196) and focused group discussions (n=5), was subjected to descriptive and inferential statistical analysis. Factor analysis reduced 19 identified CSA technologies specific attributes to 5 factors that were used in the multinomial logistic regression model. Results show a range of drivers and barriers influencing DTSVs adoption. The adoption of DTSVs by sampled smallholder farmers were influenced by training and demonstration; knowledge and benefits related to DTSVs; necessary requirements like receiving tractor services on time, knowledge on better dates of DTSVs and weather information; enabling factors like additional training on DTSVs and information including knowledge about other CSA technologies other than DTSVs, gender, marital status and credit access. These results have policy implications for various stakeholders which reinforce multi-actor approach to climate change adaptation and building of functional institutions, enhancing training of smallholder farmers, improving on access to sufficient demonstrations, climate change information and credit support amongst other support. Key words: Climate smart agriculture, smallholder farmers, drought-tolerant seeds technology adoption, multinomial logit regression.
Synchrotron Radiation Soft X-ray Induced Reduction in Graphene Oxide Characterized by Time-Resolved Photoelectron Spectroscopy

Synchrotron radiation soft X-ray was employed to reduce graphene oxide (GO) films in ultrahigh vacuum. The dissociation of oxygen-containing functional groups, and the formation of sp2 C–C bonds were revealed by time-resolved in situ X-ray photoelectron spectroscopy, demonstrating the X-ray reduction of GO. The number of C–O bonds of GO exhibited an exponential decay with exposure time. The X-ray reduction rate of GO was positively correlated with the intensity of low-energy secondary electrons excited from substrates by soft X-ray, indicating the C–O bonds were dissociated by secondary electrons.
Music, Computing, and Health: A Roadmap for the Current and Future Roles of Music Technology for Health Care and Well-Being

The fields of music, health, and technology have seen significant interactions in recent years in developing music technology for health care and well-being. In an effort to strengthen the collaboration between the involved disciplines, the workshop “Music, Computing, and Health” was held to discuss best practices and state-of-the-art at the intersection of these areas with researchers from music psychology and neuroscience, music therapy, music information retrieval, music technology, medical technology (medtech), and robotics. Following the discussions at the workshop, this article provides an overview of the different methods of the involved disciplines and their potential contributions to developing music technology for health and well-being. Furthermore, the article summarizes the state of the art in music technology that can be applied in various health scenarios and provides a perspective on challenges and opportunities for developing music technology that (1) supports person-centered care and evidence-based treatments, and (2) contributes to developing standardized, large-scale research on music-based interventions in an interdisciplinary manner. The article provides a resource for those seeking to engage in interdisciplinary research using music-based computational methods to develop technology for health care, and aims to inspire future research directions by evaluating the state of the art with respect to the challenges facing each field.
Capital structure of COOP group in the Czech Republic

The aim of this paper is to evaluate the capital structure and its determinants in consumer cooperatives in the Czech Republic. Consumer co-operatives are associated in the COOP Group, which is the largest retail network of food stores in the country. This analysis uses quantitative data from the financial statements for the years 2014 to 2018 from the database of information on Czech economic entities Albertina. Financial indicators, regression as well as correlation analysis are all used to analyse the data. This paper reveals that the leverage of the entire group is low, as more than twothirds of the assets are financed by equity. Internal financing from retained profits is prevalent. From the results of multiple linear regression analysis is apparent that tangibility and total assets turnover both have a positive effect on leverage while liquidity and retained profits negative.
Design and development of zolmitriptan niosomal in situ nasal gel for the treatment of migrain

Anilkumar J. Shinde*1, Karan B. Swami1, Firoj A. Tamboli2, Harinath N. More3 1Department of Pharmaceutics, Bharati Vidyapeeth College of Pharmacy, Near Chitranagari, Kolhapur, Maharashtra, India 2Department of Pharmacognosy, Bharati Vidyapeeth College of Pharmacy, Near Chitranagari, Kolhapur, Maharashtra, India 3Bharati Vidyapeeth College of Pharmacy, Near Chitranagari, Kolhapur, Maharashtra, India
Protein folding, misfolding, and coping mechanism of cells–A short discussion

Proteins are not rigid structures, they are long polypeptide chains of ~50 or more “residues”. Proteins are generally thought to adopt unique structures determined by their amino acid sequences. However, proteins are not strictly static objects, but rather populate ensembles of (sometimes similar) conformations. Transitions between these states occur on a variety of length scales (tenths of Å to nm) and time scales (ns to s), and have been linked to functionally relevant phenomena such as enzyme catalysis [1] and allosteric signaling [2].
A Comparative Study of P-Possum Vs Apache II Scoring System in Predicting Postoperative Mortality and Morbidity in Gastrointestinal Surgeries

Surgical morbidity and mortality can be avoided or minimized by diligent preoperative evaluation, clinical condition optimization, effective control of anaesthetics and surgery, and adequate postoperative support. There are many available morbidity and mortality predictors (ASA, APACHE, SAPS II). The POSSUM Score uses both a pre-operative assessment of the severity of pre-existing concomitant medical conditions and information collected during the peri-operative period, i.e., the severity of surgical insults, intraoperative blood loss, etc., to predict the post-operative course of patients. The applicability of the POSSUM Score for specific medical conditions has been tested by a variety of tests, and a number of varieties have also arisen, i.e., the P-Possum-Score or the V-POSSUMScore. The development of APACHE II scoring system for use in intensive care units specifically, in patients it is evident who were undergoing different surgeries, it can predict peri-operative events. This study was undertaken to compare p-possum and APACHE II scoring system for identifying gastrointestinal surgeries outcomes in our setup and, if the outcome is low, what are the different causes for it to be analysed among the group with this high-risk. In our study we found that 11 0ut of 33 (33.3%) patient of age less than 60 years, 4 out of 12 (33.3%) patients of age between 61-70 years and 4 out of 5 (80 %) patients of age more than 70 years expired. Among older adults, the risk of complications and early death after commonly performed abdominal procedures is greater and statistically significant which is similar to previously done studies.
HydroLang: An open-source web-based programming framework for hydrological sciences

This paper presents HydroLang, an open-source and integrated community-driven computational web framework to support research and education in hydrology and water resources. HydroLang uses client-side web technologies and standards to perform different routines which aim towards the acquisition, management, transformation, analysis and visualization of hydrological datasets. HydroLang is comprised of four main high-cohesion low-coupling modules for: (1) retrieving, manipulating, and transforming raw hydrological data, (2) statistical operations, hydrological analysis, and creating models, (3) generating graphical and tabular data representations, and (4) mapping and geospatial data visualization. Two extensive case studies (i.e., evaluation of lumped models and development of a rainfall disaggregation model) have been presented to demonstrate the framework’s capabilities, portability, and interoperability. HydroLang’s unique modular architecture and open-source nature allow it to be easily tailored into any use case and web framework and promote iterative enhancements with community involvement to establish the comprehensive next-generation hydrological software toolkit.