bluuebunny/crossref_metadata_2025 huggingface dataset:
Sustainable Tourism Policy, Destination Management and Sustainable Tourism Development: A Moderated-Mediation Model
Authors: Khan Mustafa Rehman , Khan Haseeb Ur Rehman , Lim Chen Kim , Tan Kian Lam , Ahmed Minhaz Farid
Published: November 2021

In the recent years, the rapid growth of the tourism industry has risen to prominence as a global concern. Tourism empowers communities and uplifts the economy. However, it poses social and environmental challenges, which in turn draws attention to tourism patterns. Sustainable tourism promises protection of the environment and the social-cultural elements of any given destination. Hence, this study aims to understand the complex relationship between sustainability policy, management, and tourist behavior. Thus, we examined the relationships between sustainable tourism policy and destination management, destination social responsibility, and tourist value orientation with sustainable tourism development. We recruited participants at managerial level coming from 163 Malaysian companies and conducted a cross-sectional quantitative study, using partial least square structural equation modeling. We propose that sustainable tourism policy and destination management and destination social responsibility significantly impact sustainable tourism development. Moreover, destination social responsibility partially mediates the relationship between sustainable tourism policy destination management and sustainable tourism development.
Transcranial Direct Current Stimulation over the Right Inferior Parietal Cortex Reduces Transposition Errors in a Syllabic Reordering Task
Authors: Costa Vanessa , Giglia Giuseppe , Talamanca Simona , Finocchiaro Chiara , Cosentino Giuseppe , Fierro Brigida , Brighina Filippo
Published: November 2021

Evidence derived from functional imaging and brain-lesion studies has shown a strong left lateralization for language, and a complementary right hemisphere dominance for visuospatial abilities. Nevertheless, the symmetrical functional division of the two hemispheres gives no reason for the complexity of the cognitive operations involved in carrying out a linguistic task. In fact, a growing number of neuroimaging and neurostimulation studies suggest a possible right hemisphere involvement in language processing. The objective of this work was to verify the contribution of the left and right parietal areas in a phonological task. We applied anodal transcranial direct current stimulation (tDCS) to the right or left inferior parietal lobe, during a syllabic reordering task. After having learnt a combination of images of real objects and trisyllabic pseudowords with a simple consonant–vowel (CV) syllabic structure (e.g., tu-ru-cu), participants were shown the same images paired to two different pseudowords: one correct but with transposed syllables, and one alternative, never before seen. The participant’s task was to orally produce the chosen pseudoword, after having rearranged the order of its syllables. Two types of error were considered: transposition (correct pseudoword but incorrectly reordered) and identity (incorrect pseudoword). The results showed that right anodal stimulation significantly reduced the number of transposition errors, whereas left anodal stimulation significantly reduced the number of identity errors. These results suggested that both left and right inferior parietal areas were differentially involved in a syllabic reordering task, and, crucially, they demonstrated that visuospatial processes served by the right inferior parietal area could be competent for establishing the correct syllabic order within a word.
Deep Learning Framework to Detect Ischemic Stroke Lesion in Brain MRI Slices of Flair/DW/T1 Modalities
Authors: Rajinikanth Venkatesan , Aslam Shabnam Mohamed , Kadry Seifedine
Published: November 2021

Ischemic stroke lesion (ISL) is a brain abnormality. Studies proved that early detection and treatment could reduce the disease impact. This research aimed to develop a deep learning (DL) framework to detect the ISL in multi-modality magnetic resonance image (MRI) slices. It proposed a convolutional neural network (CNN)-supported segmentation and classification to execute a consistent disease detection framework. The developed framework consisted of the following phases; (i) visual geometry group (VGG) developed VGG16 scheme supported SegNet (VGG-SegNet)-based ISL mining, (ii) handcrafted feature extraction, (iii) deep feature extraction using the chosen DL scheme, (iv) feature ranking and serial feature concatenation, and (v) classification using binary classifiers. Fivefold cross-validation was employed in this work, and the best feature was selected as the final result. The attained results were separately examined for (i) segmentation; (ii) deep-feature-based classification, and (iii) concatenated feature-based classification. The experimental investigation is presented using the Ischemic Stroke Lesion Segmentation (ISLES2015) database. The attained result confirms that the proposed ISL detection framework gives better segmentation and classification results. The VGG16 scheme helped to obtain a better result with deep features (accuracy > 97%) and concatenated features (accuracy > 98%).
Searching for the Muon Decay to Three Electrons with the Mu3e Experiment
Authors: Martin Perez Cristina , Vigani Luigi
Published: November 2021

Mu3e is a dedicated experiment designed to find or exclude the charged lepton flavor violating μ→ eee decay at branching fractions above 10−16. The search is pursued in two operational phases: Phase I uses an existing beamline at the Paul Scherrer Institute (PSI), targeting a single event sensitivity of 2·10−15, while the ultimate sensitivity is reached in Phase II using a high intensity muon beamline under study at PSI. As the μ→ eee decay is heavily suppressed in the Standard Model of particle physics, the observation of such a signal would be an unambiguous indication of the existence of new physics. Achieving the desired sensitivity requires a high rate of muons (108 stopped muons per second) along with a detector with large kinematic acceptance and efficiency, able to reconstruct the low momentum of the decay electrons and positrons. To achieve this goal, the Mu3e experiment is mounted with an ultra thin tracking detector based on monolithic active pixel sensors for excellent momentum and vertex resolution, combined with scintillating fibers and tiles for precise timing measurements.
SARS-CoV-2 Spike Protein S1-Mediated Endothelial Injury and Pro-Inflammatory State Is Amplified by Dihydrotestosterone and Prevented by Mineralocorticoid Antagonism
Authors: Kumar Nitin , Zuo Yu , Yalavarthi Srilakshmi , Hunker Kristina L. , Knight Jason S. , Kanthi Yogendra , Obi Andrea T. , Ganesh Santhi K.
Published: November 2021

Men are disproportionately affected by the coronavirus disease-2019 (COVID-19), and face higher odds of severe illness and death compared to women. The vascular effects of androgen signaling and inflammatory cytokines in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-mediated endothelial injury are not defined. We determined the effects of SARS-CoV-2 spike protein-mediated endothelial injury under conditions of exposure to androgen dihydrotestosterone (DHT) and tumor necrosis factor-a (TNF-α) and tested potentially therapeutic effects of mineralocorticoid receptor antagonism by spironolactone. Circulating endothelial injury markers VCAM-1 and E-selectin were measured in men and women diagnosed with COVID-19. Exposure of endothelial cells (ECs) in vitro to DHT exacerbated spike protein S1-mediated endothelial injury transcripts for the cell adhesion molecules E-selectin, VCAM-1 and ICAM-1 and anti-fibrinolytic PAI-1 (p < 0.05), and increased THP-1 monocyte adhesion to ECs (p = 0.032). Spironolactone dramatically reduced DHT+S1-induced endothelial activation. TNF-α exacerbated S1-induced EC activation, which was abrogated by pretreatment with spironolactone. Analysis from patients hospitalized with COVID-19 showed concordant higher circulating VCAM-1 and E-Selectin levels in men, compared to women. A beneficial effect of the FDA-approved drug spironolactone was observed on endothelial cells in vitro, supporting a rationale for further evaluation of mineralocorticoid antagonism as an adjunct treatment in COVID-19.
Single-Cell RNAseq Profiling of Human γδ T Lymphocytes in Virus-Related Cancers and COVID-19 Disease
Authors: Cerapio Juan Pablo , Perrier Marion , Pont Fréderic , Tosolini Marie , Laurent Camille , Bertani Stéphane , Fournie Jean-Jacques
Published: November 2021

The detailed characterization of human γδ T lymphocyte differentiation at the single-cell transcriptomic (scRNAseq) level in tumors and patients with coronavirus disease 2019 (COVID-19) requires both a reference differentiation trajectory of γδ T cells and a robust mapping method for additional γδ T lymphocytes. Here, we incepted such a method to characterize thousands of γδ T lymphocytes from (n = 95) patients with cancer or adult and pediatric COVID-19 disease. We found that cancer patients with human papillomavirus-positive head and neck squamous cell carcinoma and Epstein–Barr virus-positive Hodgkin’s lymphoma have γδ tumor-infiltrating T lymphocytes that are more prone to recirculate from the tumor and avoid exhaustion. In COVID-19, both TCRVγ9 and TCRVγnon9 subsets of γδ T lymphocytes relocalize from peripheral blood mononuclear cells (PBMC) to the infected lung tissue, where their advanced differentiation, tissue residency, and exhaustion reflect T cell activation. Although severe COVID-19 disease increases both recruitment and exhaustion of γδ T lymphocytes in infected lung lesions but not blood, the anti-IL6R therapy with Tocilizumab promotes γδ T lymphocyte differentiation in patients with COVID-19. PBMC from pediatric patients with acute COVID-19 disease display similar γδ T cell lymphopenia to that seen in adult patients. However, blood γδ T cells from children with the COVID-19-related multisystem inflammatory syndrome are not lymphodepleted, but they are differentiated as in healthy PBMC. These findings suggest that some virus-induced memory γδ T lymphocytes durably persist in the blood of adults and could subsequently infiltrate and recirculate in tumors.
New Perspectives in Photocatalytic Water Treatment
Authors: Natali Sora Isabella , Bekbolet Miray
Published: November 2021

This Special Issue, entitled “New Perspectives in Photocatalytic Water Treatment”, was planned to cover all relevant topics related to photo-initiated oxidative processes in water treatment, with a special emphasis on pollutant abatement and microorganism inactivation, which were required for improving their practical uses [...]
Analysis of the Radiation Fluxes over Complex Surfaces on the Tibetan Plateau
Authors: Wang Chunxiao , Ma Yaoming , Wang Binbin , Ma Weiqiang , Chen Xuelong , Han Cunbo
Published: November 2021

Analysis of long-term, ground-based observation data on the Tibetan Plateau help to enhance our understanding of land-atmosphere interactions and their influence on weather and climate in this region. In this paper, the daily, monthly, and annual averages of radiative fluxes, surface albedo, surface temperature, and air temperature were calculated for the period of 2006 to 2019 at six research stations on the Tibetan Plateau. The surface energy balance characteristics of these six stations, which include alpine meadow, alpine desert, and alpine steppe, were then compared. The downward shortwave radiation at stations BJ, QOMS, and NAMORS was found to decrease during the study period, due to increasing cloudiness. Meanwhile, the upward shortwave radiation and surface albedo at all stations were found to have decreased overall. Downward longwave radiation, upward longwave radiation, net radiation, surface temperature, and air temperature showed increasing trends on inter-annual time scales at most stations. Downward shortwave radiation was maximum in spring at BJ, QOMS, NADORS, and NAMORS, due to the influence of the summer monsoon. Upward shortwave radiation peaked in October and November due to the greater snow cover. BJ, QOMS, NADORS, and NAMORS showed strong sensible heat fluxes in the spring while MAWORS showed strong sensible heat fluxes in the summer. The monthly and diurnal variations of surface albedo at each station were “U” shaped. The diurnal variability of downward longwave radiation at each station was small, ranging from 220 to 295 W·m−2.The diurnal variation in surface temperature at each station slightly lagged behind changes in downward shortwave radiation, and the air temperature, in turn, slightly lagged behind the surface temperature.
Temperature Affects the Time Required to Discern the Relationship between Primary Production and Export Production in the Ocean
Authors: Laws Edward , Maiti Kanchan
Published: November 2021

Knowledge of the relationship between net primary production (NPP) and export production (EP) in the ocean is required to estimate how the ocean’s biological pump is likely to respond to climate change effects. Here, we show with a theoretical food web model that the relationship between NPP and EP is obscured by the following phenomena: (1) food web dynamics, which cause EP to be a weighted average of new production (NP) over a previous temperature-dependent time interval that can vary between several weeks at 25 °C to several months at 0 °C and, hence, to be much less temporally variable than NP and (2) the temperature dependence of the resiliency of the food web to perturbations, which causes the return to equilibrium to vary from roughly 50 days at 0 °C to 5–10 days at 25 °C. The implication is that the relationship between NPP and EP can be discerned at tropical and subtropical latitudes if measurements of NPP and EP are averages or climatologies over a timeframe of roughly one month. At high latitudes, however, measurements may need to be averaged over a timeframe of roughly one year because the food webs at high latitudes are very likely far from equilibrium with respect to NPP and EP much of the time, and the model can describe only the average behavior of such physically dynamic systems.
Probability of Non-Exceedance of Arsenic Concentration in Groundwater Estimated Using Stochastic Multicomponent Reactive Transport Modeling
Authors: Dalla Libera Nico , Pedretti Daniele , Casiraghi Giulia , Markó Ábel , Piccinini Leonardo , Fabbri Paolo
Published: November 2021

Stochastic multicomponent reactive transport modeling is a powerful approach to quantify the probability of non-exceedance (PNE) of arsenic (As) critical concentration thresholds in groundwater. The approach is applied to a well-characterized shallow alluvial aquifer near Venice, Italy. Here, As mobility depends primarily on rainfall-controlled redox-dependent precipitation-dissolution of iron hydroxides. A Monte-Carlo analysis based on a calibrated three-dimensional flow and transport model targeted the geochemical initial conditions as the main source of uncertainty of As concentrations in the studied aquifer. It was found that, during 115 simulated days, the fraction of the entire aquifer volume with As > 10 μgL−1 decreased on average from ~43% to ~39% and the average As concentration from ~32 μgL−1 to ~27 μgL−1. Meanwhile, PNE increased from 55% to 60% when 10 μgL−1 was set as target threshold, and from 71% to 78% for 50 μgL−1. The time dependence of As attenuation can be ascribed to the increase of oxidizing conditions during rainfall-dependent aquifer recharge, which causes As sorption on precipitating iron hydroxides. When computing the same statistics for the shallowest 6 m, As attenuation was even more evident. The volume fraction of aquifer with As > 10μgL−1 dropped from 40% to 28% and the average As concentration from 31 μgL−1 to 20 μgL−1, whereas PNE increased from 58% to 70% for As < 10 μgL−1 and from 71% to 86% for As < 50 μgL−1. Thus, the wells screen depth in the aquifer can be a critical aspect when estimating As risk, owing to the depth-dependent relative change in redox conditions during rainfall events.
Risk Analysis of Instability Failure of Earth–Rock Dams Based on the Fuzzy Set Theory
Authors: Zhang Hexiang , Li Zongkun , Li Wei , Song Ziyuan , Ge Wei , Han Ruifang , Wang Te
Published: November 2021

Determining the anti-sliding instability risk of earth–rock dams involves the analysis of complex uncertain factors, which are mostly regarded as random variables in traditional analysis methods. In fact, fuzziness and randomness are two inseparable uncertainty factors influencing the stability of earth–rock dams. Most previous research only focused on the randomness or the fuzziness of individual variables. Moreover, dam systems present a fuzzy transition from a stable state into a failure state. Therefore, both fuzziness and randomness of the influencing factors should be considered in the same framework, where the instability of an earth–rock dam is regarded as a mixed process. In this paper, a fuzzy risk model of instability of earth–rock dams is established by considering the randomness and fuzziness of parameters and the failure criteria comprehensively. We obtained the probability threshold of instability risk of earth–rock dams by Monte-Carlo simulation after the fuzzy parameters were transformed into interval numbers by cut set levels. By applying the proposed model to the instability analysis of the Longxingsi Reservoir, the calculation results showed that the lower limits of risk probability under different cut set levels exceeded the instability risk standard of grade C for earth–rock dams. Compared with the traditional risk determination value, the risk interval obtained with the proposed methods reflects different degrees of dam instability risk and can provide reference for dam structure safety assessment and management.
Prediction of Nitrate and Phosphorus Concentrations Using Machine Learning Algorithms in Watersheds with Different Landuse
Authors: Bhattarai Aayush , Dhakal Sandeep , Gautam Yogesh , Bhattarai Rabin
Published: November 2021

Rapid industrialization and population growth have elevated the concerns over water quality. Excessive nitrates and phosphates in the water system have an adverse effect on the aquatic ecosystem. In recent years, machine learning (ML) algorithms have been extensively employed to estimate water quality over traditional methods. In this study, the performance of nine different ML algorithms is evaluated to predict nitrate and phosphorus concentration for five different watersheds with different land-use practices. The land-use distribution affects the model performance for all methods. In urban watersheds, the regular and predictable nature of nitrate concentration from wastewater treatment plants results in more accurate estimates. For the nitrate prediction, ANN outperforms other ML models for the urban and agricultural watersheds, while RT-BO performs well for the forested Grand watershed. For the total phosphorus prediction, ensemble-BO and M-SVM outperform other ML models for the agricultural and forested watershed, while the ANN performs better than other ML models for the urban Cuyahoga watershed. In predicting phosphorus concentration, the model predictability is better for agricultural and forested watersheds. Regarding consistency, Bayesian optimized RT, ensemble, and GPR consistently yielded good performance for all watersheds. The methodology and results outlined in this study will assist policymakers in accurately predicting nitrate and phosphorus concentration which will be instrumental in drafting a proper plan to deal with the problem of water pollution.
A Brain-Inspired Dynamic Environmental Emergency Response Framework for Sudden Water Pollution Accidents
Authors: Zhao Ying , Pan Yilin , Wang Wensong , Guo Liang
Published: November 2021

Sudden water pollution accidents happen frequently in China, and the number of treated accidents is low, due to the slow response speed. In addition, there is a lack of decision support systems that can follow up the whole process instead of just giving a one-time method. This study constructs a framework suitable for China that has both the ability of quick responses and full-time dynamic decision support, such as an experienced expert, while not being affected by pressure, to be used an emergency response for sudden water pollution accidents. To allow new decisionmakers to integrate into this professional decision-making role more quickly, a brain-inspired system is realized through combining the machine learning algorithm KNN and the idea of iteration and dynamic programming. The feasibility of our framework is further tested through a major water pollution happened recently. The results show that this framework can be well connected with the emergency response technology system that has been completed before, while also supporting the rapid and robust decision making such as the decisionmaker’s second brain, reducing the demand for professional background and experience of emergency decisionmakers, thus effectively shorten the waiting period for response.
Perancangan Presensi Perkuliahan Berbasis Mobile Pada Universitas Dinamika Bangsa
Authors: Abdul
Published: November 2021

Dinamika Bangsa University is one of the universities in the city of Jambi. The attendance process for student lecture meetings is currently still being done manually. This has an impact on the process of recapitulation of lecture attendance to be longer and makes it difficult for the parties involved in it. In this study, an analysis was carried out related to the presence process in the dynamic university of the nation, the results of the analysis were used to design applications. This research produces a mobile-based application that can be used by lecturers and students for lecture attendance.
Metode Importance Performa Analisys (IPA) sebagai Penentuan Kepuasan dan Kenyamanan Pengguna Website Universitas PGRI Madiun
Authors: Fatim  , Kelik
Published: November 2021

PGRI Madiun University is an institution in the city of Madiun in its development using the website as a tool to promote. Today's technology is very advanced and has many benefits for life in our environment. Website is an effective promotional media, providing information and receiving information speed is very fast. Therefore, PGRI Madiun University uses the website for promotional purposes in addition to academic activities so far. Correct and accurate information will have an impact on society, and the trust given to the community will also increase. Analysis of the quality of use and utilization of the website to see visitor satisfaction with information and services when viewed from user satisfaction is needed to measure user satisfaction. This study analyzes how much user satisfaction is with the university website using the Importance Performance Analysis (IPA) approach. The results of the Importance Performance Analysis (IPA) analysis show that several recommendations are obtained from the results of the analysis of this research which are the priority and the main thing to be maintained is the quality of information. So that visitors feel faster and more accurate in obtaining information with the PGRI Madiun University website.

Keywords: Website. Importance Performance Analysis, Analysis.
Queering Dementia
Authors: Shildrick Margit
Published: November 2021

In dementia care, it is rarely questioned that the condition signals a breakdown in normative communicative competence that diminishes and finally renders the subjectivity of the sufferer beyond reach. More radical approaches may explore beyond verbal capacity to elicit a recognisable interaction through the use of music, touch, and movement, but could queering dementia offer a more flourish- ing scenario? In recent years there has been an upsurge in potential biotechno- logical interventions in the form of prostheses that claim to offer to those with dementia some tools for maintaining contact with their previous sense of self. Some of these are purely mechanical aids, such as robotic carers or quasi-animal companions, but I want to look too at the significance of some of the more organ- ic dimensions – such as the microbiome and microchimerism – that I also classas prostheses in the sense that they augment an existing materiality. I understand dementia not as an exceptional state marked by a loss of independence, but in terms of the prosthetic nature of all embodiment. What makes that queer is that the entanglement of all bodies with an array of external and internal prosthetic elements is irreducible and unstable, and already constitutes the assemblage that is identified as a person.
СЛУЖБА ПІДТРИМКИ ВЧИТЕЛІВ ПОЧАТКОВОГО НАВЧАННЯ: ДОСВІД КНР
Authors: Шулін Ніу
Published: November 2021

У 2020 році Китай став першою країною світу, яка зіткнулася з усіма викликами пандемії COVID-19, включаючи ті, що стосувалися освіти. Вони були першими, хто запропонував обмежену та дистанційну освіту як єдину освітню реальність, а також першими, хто зіткнувся з усіма позитивними та негативними наслідками згаданого процесу. Ось чому китайський досвід (як негативний, так і позитивний) варто представити та дослідити. Є ще одна особливість китайської освітньої системи, яка робить її унікальною і дозволяє країні за короткий період зробити систему дистанційної освіти конкурентною з традиційною офлайновою, навіть для початкової освіти. Це система підтримки вчителів, яка включає не лише систему підготовки вчителів (діяльність із професійного навчання), а й фінансову підтримку, використання різних інструментів онлайн-освіти, безпосередню допомогу групи фахівців під час підготовки та проведення уроків, психологічну підтримку тощо. Мета дослідження – представити позитивний освітній та організаційний досвід в галузі роботи вчителів початкової освіти, який вже використовується в Китаї. Під час написання статті такі методи, як спостереження, вивчення нормативної та наукової літератури, були використані для комплексного аналізу нової педагогічної реальності – служби підтримки вчителів.
СТРУКТУРНО-КОМПОНЕНТНИЙ АНАЛІЗ ПОНЯТТЯ «МЕДІАГРАМОТНІСТЬ УЧИТЕЛІВ МИСТЕЦЬКИХ ДИСЦИПЛІН»
Authors: Хмарна Л. В.
Published: November 2021

Актуальність формування й розвитку медіаграмотності вчителів, пов’язана з активізацією інформаційного протистояння України із країною-агресором, збільшенням впливу медіазасобів, зокрема New Media, на формування особистості, недостатня увага до медіаосвіти вчителів мистецьких дисциплін спричинили занурення автора статті у сутність поняття «медіаграмотність», усвідомлення специфіки медіаграмотності вчителів мистецтва та її структурування. Аналіз вітчизняної нормативно-правової бази (Концепції впровадження медіаосвіти в Україні, Законів України «Про освіту», «Про вищу освіту»), міжнародних документів ЮНЕСКО (Media and information literacy: policy and strategy guidelines; Global Media and Information Literacy (MIL) Assessment Framework; Paris Declaration on Media and Information Literacy in the Digital Era) з різних аспектів розвитку медіаграмотності, вивчення наукових розвідок українських та зарубіжних учених дозволили виокремити найбільш точне визначення феномену медіаграмотності: це сукупність мотивів, знань, умінь і можливостей, що сприяють добиранню, використанню, критичному аналізові, оцінюванню, створюванню та передаванню медіатекстів різних форм, жанрів, а також аналізові складних процесів функціонування медіа в суспільстві. Відзначено, що на сьогодні зміст поняття медіаграмотність значно змінився через розвиток цифрових технологій. Наразі ЮНЕСКО пропонує концептуальне поняття медіаінформаційної грамотності (МІГ), що об’єднує в одному понятті інформаційну та медіаграмотність, а також ІКТ та цифрову грамотність як такі, що взаємодоповнюють одна одну. На підставі вивчення наявних підходів до структурування медіаграмотності та медіакомпетентності, з урахуванням специфіки професійної діяльності сучасних учителів освітньої галузі «Мистецтво» запропоновано структуру медіаграмотності вчителів мистецьких дисциплін в єдності когнітивного, праксеологічного та емоційно-ціннісного компонентів. Розтлумачено зміст кожного із компонентів. Окреслено перспективи подальшого дослідження, які полягають у практичній реалізації завдань формування медіаграмотності вчителів мистецьких дисциплін в системі післядипломної освіти вчителів.
Knowledge and Attitudes About Travel Medicine in Latin America in the Context of COVID-19: A Cross-Sectional Study
Authors: Castillo Santana Esmailyn , Varela Margareth Catoia , de Jesús Arámboles Yocastia , Suarez-Rodríguez Anderson , da Costa Marcellus Dias
Published: November 2021

Introduction: Travel Medicine specialty has existed in Latin American for more than 25 years. The creation of the Latin American Society of Travel Medicine (SLAMVI) stimulated medical education in this discipline, through research and scientific publications. However, Travel Medicine is practically unknown to Latin Americans. Methods: Latin Americans (n=9487) completed an online survey of ten questions from nine countries of the region to determine the knowledge of the population about the existence of this specialty and their attitudes about it. Results: Although more than 90% of those surveyed knew that traveling to certain countries requires to receive certain vaccines, less than 30% had heard of the specialty of Travel Medicine. After knowing the definition and objectives of the specialty, more than 90% of the participants considered it important to carry out a pre-travel consultation with a specialist. Conclusion: The lack of knowledge of the specialty is the main barrier to Latin Americans to have access to Travel Medicine consultation. It is necessary to publicize the specialty, make the population aware of the importance of pre- and post-travel consultation, as well as the creation of this service in more public hospitals in Latin America.
A Study of Prognostic Markers for Dengue Infection
Authors: Ajmera Ronak Parag , Kulkarni Sanjay V.
Published: November 2021

Introduction: Early diagnosis and prognostication of infections such as dengue are crucial for better patient outcomes, as they help predict the likelihood of patients developing severe dengue, allowing more comprehensive patient triage and therapeutic interventions. This study aimed to determine clinical, laboratory, and radiological factors predicting prognosis in dengue infection. Methods: This prospective observational study included 250 patients seropositive for dengue. They were classified into dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS); and evaluated both on admission and at the end of their hospital course, the latter was performed for factors responsible for the progression of dengue to severe dengue. Data were statistically analyzed using R 3.6.1, with P<0.05 considered statistically significant. Results: Final diagnosis correlated significantly with systolic blood pressure (P=0.004), lowest platelet count (P<0.001), serum glutamic-oxaloacetic transaminase (P=0.001), urine protein (P<0.001), urine red blood cells (P<0.001), pleural effusion (P=0.0064), serositis (P<0.001), vomiting (P<0.001), rash (P<0.001), restlessness (P<0.001), and bleeding manifestations (P<0.001). Conclusion: The prognosis of dengue is significantly associated with blood pressure, lowest platelet count, serum transaminases, serum creatinine, proteinuria, hematuria, pleural effusion, abdominal pain, persistent vomiting, rash, restlessness, serositis, and bleeding manifestations. Monitoring these parameters is useful for the effective management of dengue.
Sıcaklık Şoku Uygulaması ile Triploid Karadeniz Alabalığı (Salmo trutta labrax) Üretimi ve Kuluçka Performansının Belirlenmesi[*]
Authors: DELİHASAN SONAY Fatma , BAŞÇINAR Nadir , AKHAN Süleyman
Published: November 2021

Bu çalışmada, triploid Karadeniz alabalığı (Salmo trutta labrax) üretmek için termal şok protokolünün optimizasyonu belirlenmiştir. Triploidizasyon işlemi için döllenmeden sonra 10, 15 ve 20. dakikalarda dört farklı sıcaklıkta (26, 28, 30 ve 32 ºC) şok uygulanmıştır. Ploidi oranı NOR (Nükleolar Organizatör Bölgeleri) boyama ve eritrosit büyüklüğü yöntemleri ile belirlenmiştir. En yüksek triploid oranları, döllendikten 15 dakika sonra 10 dakika sıcaklık şoku uygulamasıyla 32 ºC (%86,15) ve 28 ºC (%81,26)’lerde tespit edilmiştir. Fakat, çıkış oranı ve kuluçka randımanı 28 ºC sıcaklık şoku grubunda daha başarılı bulunmuştur. Çalışmadan elde edilen bulgular, Karadeniz alabalığı triploid uygulamalarında kullanılabilir.
Consideraciones breves sobre la ciencia médica actual e implicaciones éticas
Authors: Esquivel Estrada Noé Héctor
Published: November 2021

Este trabajo de investigación tiene como objetivo presentar algunas reflexiones sobre el funcionamiento de la ciencia médica actual acompañadas de algunas implicaciones éticas. Está conformado por cuatro apartados que buscan diseñar el contenido del mismo, a saber: el sentido del cuerpo humano; consideraciones acerca de la salud; sobre el tratamiento médico y el diálogo con el paciente; y, por último, ética y conocimiento científico de la medicina. Palabras clave: ciencia médica, ética, cuerpo, salud, enfermedad.
Bioética y alimentación al final de la vida en pediatría: dos perspectivas complementarias sobre un mismo tema
Authors: Arenas-Rivera Jorge Jacobo , Portilla-Segura Javier , Apolinar-Jiménez Evelia
Published: November 2021

Con los avances en las terapias curativas se espera que los niños, aun enfermos, sobrevivan a sus padres; sin embargo, existen condiciones imposibles de curar, que limitan la esperanza de vida. Los cuidados paliativos pediátricos se refieren al cuidado activo y total del cuerpo, mente y espíritu de los niños, e incluyen soporte a su familia. La alimentación e hidratación artificial pueden ser una alternativa al final de la vida que contribuya con el control de los síntomas; estas tienen connotaciones psicológicas, culturales, religiosas y, por tanto, bioéticas. Es necesaria la reflexión, pues además de contar con conocimientos técnicos y científicos, la atención de niños y adolescentes con enfermedades imposibles de curar implica la comprensión integral de principios y valores éticos. Esta revisión pretende invitar a la reflexión al abordar el tema de la muerte y del papel de la alimentación al final de la vida en pediatría, desde las perspectivas de la bioética y de la práctica clínica. A partir de la perspectiva bioética se detallan los principios de beneficencia, autonomía, justicia y no maleficencia, mismos que en la atención de menores enfermos en fase terminal se deben potenciar con la benevolencia, la autonomía asistida, la magnanimidad y la no malevolencia. Estos conceptos permitirán ver, desde la óptica bioética, la trascendencia de las decisiones prácticas, esa sutil diferencia entre intentar el soporte nutricional, que limita el sufrimiento y busca mejorar la calidad de vida, y promover terapias fútiles, que pueden alargar la agonía y el sufrimiento, incrementar el desgaste económico y generar falsas expectativas. Palabras clave: bioética, alimentación al final de la vida, niños, adolescentes, calidad de vida.
Dilemas éticos en la investigación en salud y nutrición
Authors: Kaufer-Horwitz Martha
Published: November 2021

Los dilemas éticos se refieren a preguntas sin respuesta o a preguntas con varias respuestas, cuyas consideraciones varían según el contexto. No existe una metodología específica para resolver los dilemas éticos; estos deben ser un ejercicio de reflexión del investigador y de los comités de ética. En el campo de la salud, y específicamente de la investigación en temas nutriológicos, los dilemas se asocian con el descuido del rigor metodológico de las investigaciones, no tomar en cuenta a los participantes de los estudios, descuidar la ponderación de los riesgos y los beneficios de las investigaciones, no definir los procedimientos para anticipar los conflictos derivados de la investigación, ser poco críticos ante la definición de confidencialidad, el tema de la omisión del consentimiento informado en situaciones de emergencia, el uso que se da a la información que se genera en la investigación y los dilemas relacionados con los investigadores. El objetivo del presente artículo es mostrar algunos ejemplos de los dilemas éticos planteados por Figueroa, extrapolados al campo de la nutrición clínica. Se presentan algunos ejemplos en el terreno de la investigación en nutrición, y más específicamente en obesidad. Palabras clave: dilema ético, investigación, consentimiento informado, nutrición.
Reducing Forgetting Rate in EFL Students Using a Spaced Repetition-Powered Digital Game-Based Learning Application
Authors: Rahman Farah Aulia , Amalia Talitha , Lutfi Muhammad
Published: November 2021

Spaced repetition has been widely investigated as an effective technique to enhance human learning. However, a limitation of previous research is that most previous studies on spaced repetition in the English as a foreign language (EFL) learning contexts were dominated by in-class implementation and relied on small-scale controlled experiments. To fill this gap in the literature, in the present study, we conducted a large-scale natural experiment on spaced repetition using data from a digital game-based learning (DGBL) application, Dawn of Civilization. Specifically, we examined learners’ natural learning repetition patterns in the game app and their effects on the forgetting rate of the learned words. The data were analyzed based on the identified repetition patterns, and differences in the forgetting rate of these patterns were analyzed. The results revealed that learners who closely followed the recommended spaced repetition schedule of the game had significantly lower forgetting rates, indicating better knowledge retention.
Short-period internal waves on the steep shelf of the Вlack sea in summer 2018
Authors: Khimchenko Elizaveta , Serebryany Andrey , Konukhova Anastasia
Published: November 2021

The results of the analysis of data on observation of short-period internal waves on the northeastern shelf of the Black Sea in June 2018 are presented. The study area is distinguished by a narrow shelf with a sharp drop in depths, the bottom slope is 23°. The measurements were carried out from the stationary marine platform of The Institute of Ecology of the Academy of Sciences of the Abkhazian Republic, where the depth of the site reaches 13 m. An anchored station was installed, equipped with autonomous point temperature sensors at a depth of 52 m. At the platform, the variability of the sea temperature structure was monitored using point temperature sensors, an autonomous line temperature sensor (LTS), and vertical hourly profiling using a probe. In addition, coastal currents were measured by the acoustic Doppler current profiler ADCP equipped near the platform. As a result of the analysis, a frequent approach of near-inertial internal waves close to the coast was revealed. Trains of short-period internal waves and solitary waves related to the first mode, as well as individual manifestations of internal waves of the second mode, were recorded. Examples of observed waves and their parameters are given. During the entire observation period, internal waves with a period of 5–10 min and a height of 1–2 m were most often recorded. Solitary waves were distinguished by a large period and height. It was found that short-period internal waves at the measurement site are predominantly tied to near-inertial internal waves which approach the coast.
DEVELOPMENT OF A TELEGRAM BOT FOR RECEIVING DATA FROM OPC SERVERS
Authors: Khmelik Oleg , Galkin Pavlo
Published: November 2021

Abstract It is important to develop programming of the embedded control system which allows the real-time system to change and actually program the built-in control system based on the PLC. Chatbot is a computer program developed on the basis of neural networks and machine learning technologies, which can be used to communicate in audio or text format , but chatbot can also be used to program embedded systems without changing the PLC program itself. The purpose of the work is to develop a chatbot in the Telegram service, which can be used to obtain information from embedded systems based on the OPC server and send the necessary information at the request of the user. Keywords: OPC, PLC, Telegram bot, Chatbot, embedded control system, data, servers, IoT, IIoT, machine learning technologies.
Faktor Risiko Terjadinya Covid-19 Pada Penderita Diabetes Melitus Tipe 2
Authors: Panua Apin A. , Zainuddin Ricky , Ahmad Ekayanti Hafidah , Sangkala Fitriani
Published: November 2021

Pendahuluan: Covid-19 merupakan penyakit menular yang muncul pertama kali di kota Wuhan China dan disebabkan oleh SARS-CoV-2. Tujuan mengidentifikasi faktor risiko terjadinya Covid-19 pada penderita DM tipe 2. Metode: Deskriptif analitis desain literature review. Data diperoleh melalui hasil pencarian artikel menggunakan lima database eletronik yaitu Pubmed, ProQuest, ScienceDirect, Cochrane Library dan Google Scholar diidentifikasi 10.951 artikel dengan jumlah sampel keseluruhan 5.464.617 responden. Analisis menggunakan peta data yang diekstraksi dalam tabel sintesis grid termasuk penulis, tahun publikasi, negara, tujuan, sampel, desain, durasi, hasil dan kesimpulan penelitian. Hasil: Enam artikel teridentifikasi dalam tinjauan ini menunjukkan bahwa, satu studi melaporlakan risiko terjadinya Covid-19 pada penderita DM tipe 2 sebesar 1.369 kali, satu studi 2,180 kali, satu studi 4.7 kali, dan satu studi lainnya hingga16.5 kali. Pasien yang berjenis kelamin laki-laki dan berusia ≥53 tahun memiliki risiko sebesar 1,395 kali lebih tinggi dibandingkan dengan orang yang berusia lebih muda dan berjenis kelamin perempuan. Kesimpulan: bahwa penderita DM tipe 2 secara signifikan memiliki risiko lebih tinggi terkena Covid-19 dibandingkan dengan orang yang tidak memiliki penyakit diabetes, terutama pada pasien yang berusia ≥53 tahun dan berjenis kelamin laki-laki.
Sistem Rekomendasi Pembelian Sepeda Motor Bekas Menggunakan Metode Fuzzy Tahani
Authors: Murdianingsih Yuli , Sitiumayah Ulfah
Published: November 2021

A used motorcycle is an option in the quest to buy a motorcycle, reliability is one factor. Accessibility means the size and the sum of the installment. Affordability is very important given the Covid-19 pandemic and economic recession, particularly in an environment of economic downturn. This research aims to establish a used motorcycle purchase recommendation system using the year's criteria for the manufacture of used motorcycles, prices,Â  and installments in the purchase of used motorcycles, as well as to assess how high the reliability of the used motorcycle purchase recommendation system is. Firstly, twenty used motor data were obtained which were used to analyze recommendations, secondly to determine the domain size, thirdly to determine the function and degree of membership for each parameter, fourth to measure fire intensity and fifth to determine recommendations for the purchase of used motorbikes. Testing device reliability using the MAE tool. The framework was implemented using the interface MySQL DBMS and PHP. Using the Fuzzy Tahani method, the search for used motorbikes can be carried out, with the benefit of providing the installment quantity parameter and fifty-eight percent of the device reliability for buying used motorcycles. Â
Analisis Penyakit Tanaman Bawang Merah Menggunakan Metode Teorema Bayes
Authors: Basysyar Fadhil Muhamad , Rinaldi Ade Rizky
Published: November 2021

Shallot plants or in Latin Alliumascalonicum L is a horticultural plant that gets a lot of attention from both the public and the government. Over the past few years shallots are included in the top six vegetable commodities that are exported together with cabbage, cabbage or flower cabbage, chili, tomatoes, potatoes. Onion plants are very susceptible to disease that can strike at any time. Some diseases that can attack the onion plant include Onion Caterpillar Disease, Leaf Snorer Disease, Trip, Moler Disease, Trotol, Dew Feather and Anthracnose. In this study using the Bayes theorem expert system, each symptom has a density value to the disease which is then calculated using the formula of the Bayes Theorem Method and processed using certain rules and inference using Forword Chaining. This research is expected to help the onion farmers in diagnosing the disease so that it can reduce the material losses with less than 60%.
Klasifikasi Status Calon Pendonor Darah Menggunakan Algoritma Support Vector Machine dan Kernel RBF
Authors: Suryadi Usep Tatang , Andriyani Nindi Azis
Published: November 2021

To donate blood, generally must qualify the requirements, including physically and mentally healthy, aged 17-65 years, minimum body weight of 45kg, Hb levels 12.5g% - 17.0g%, upper tension (systole) 100-170mmHg, under tension (diastole) 70-100mmHg, 36.6-37.5 degrees Celsius body temperature, never had hemophilia, pulse range 50-100 times/minute, and the timescales 3 months after a previous blood donors. The problem that arises is the small number of officers who often have difficulty recording donor data on the form sheets. Thus allowing unwanted error occurred when registering the identity or the results of the initial examination of prospective donors. Based on these problems, the classification of potential donors is needed as a step to determine the status of potential donors, whether the prospective donors are accepted as donors or rejected based on predetermined requirements. According to this research that using primary data which obtained from The Indonesian Red Cross Subang Regency, the data are using a plenty 50 of the data has accepting and 50 of the data has rejected. Afterwards required to doing continued analysis toward a method capability based on age, Hb level, body weight, sistolik dan diastolik, that using SVM (Support Vector Machine) algorithm.and using Sequential method for training phase in SVM and Kernel RBF for calculating the dot product value. The algotirhm accuration reached 90% / excellent categories with the value gamma = 0.5, C = 1, epsilon = 0.001.
Backpropagation Neural Network Untuk Prediksi Kesuksesan Film Secara Finansial
Authors: Rahmani Ani , Edwin Muhammad
Published: November 2021

A film is one of the entertainment media in human life. It makes the film industry becomes a potential business to get promising income. Prediction of success of a film financially supports film producers, production houses, distributors, and stakeholders in making decisions. The existing research on film predictions is from a popularity point of view. There is also research to predict success from a financial point of view, but using social media film rating data, which has been released. This paper is a study to find a predictive model for the success of films from the financial aspect of films that have not been released. The prediction model uses the Backpropgation neural network (BNN) algorithm by calculating the accuracy, precision, recall, and f-score. The observed variablesÂ  are a combination of film success parameters, namely, budget, genre, production company, holiday, runtime, and competition factor. The study results show that the use of more recent data, although less data, can produce better accuracy values, compared to using more data, films released in older years. From a financial point of view, the difference in the year the film was released, especially if it was tens of years, significantly affects the prediction results. Finally, the number of hidden layers and hidden nodes has a significant non-linear role in determining the prediction results.