Fanconi Anemia: Examining Guidelines for Testing All Patients with Hand Anomalies Using a Machine Learning Approach

Background: This study investigated the questionable necessity of genetic testing for Fanconi anemia in children with hand anomalies. The current UK guidelines suggest that every child with radial ray dysplasia or a thumb anomaly should undergo further cost intensive investigation for Fanconi anemia. In this study we reviewed the numbers of patients and referral patterns, as well as the financial and service provision implications UK guidelines provide. Methods: Over three years, every patient with thumb or radial ray anomaly referred to our service was tested for Fanconi Anemia. CART Analysis and machine learning techniques using Waikato Environment for Knowledge Analysis were applied to evaluate single clinical features predicting Fanconi anemia. Results: Youden Index and Predictive Summary Index (PSI) scores suggested no clinical significance of hand anomalies associated with Fanconi anemia. CART Analysis and attribute evaluation with Waikato Environment for Knowledge Analysis (WEKA) showed no single feature predictive for Fanconi anemia. Furthermore, none of the positive Fanconi anemia patients in this study had an isolated upper limb anomaly without presenting other features of Fanconi anemia. Conclusion: As a conclusion, this study does not support Fanconi anemia testing for isolated hand abnormalities in the absence of other features associated with this blood disease.

Taxation of Grants in the Russian Federation

The purpose of the article is to find out the peculiarities of grant taxation in Russia, depending on the subject composition of persons, implementing or attracted to the implementation of the grant. The article uses the following methods of scientific knowledge: analysis and synthesis, through which the provisions on grant taxation were first divided into constituent features and subsequently combined to formulate a position on the stated issue, also used the method of mental experiment, which allows to consider different options of taxation of persons involved in the implementation of grants. The result of this article was an indication of the absence or existence of an obligation to pay taxes on the grant for different entities: organizations and individuals as grant recipients and as entities involved in the implementation of the grant project. The decision to pay tax depends not only on which entity is the recipient of the grant, but also on which entity provides the grant. The existing approach to the solution of the considered question is characterized by complexity, biased differentiation criterion and requires correction.

The Methodology of Ijtihād Tat̟bi̟qi̟ KH. Sahal Mahfudh

This article aims to examine the methodology of Ijtihād tat̟bīqī KH. Sahal Mahfudh in contextualizing and actualizing classical fiqh texts. The method used is qualitative with the theoretical approach of ijtihād tat̟bîqî by Abû Ishâq Ibrâhîm al-Syâtibi and the theory of Social Construction of Peter L. Berger and Thomas Luckmann with the basis of the Sociology of Knowledge analysis. The results of this study indicate that there are three methodologies of Ijtihād tat̟bīqī KH. Sahal Mahfudh: first, historical approach. Second, the cultural approach (culture), Third, the sociological approach. The contribution of this research is to actualize and contextualize classical fiqh texts while maintaining their relevant authenticity and then synergizing them with more positive modern scientific disciplines so that they exist and survive in the present and as the future development of Indonesian and world fiqh.

Model Prediksi Dropout Mahasiswa Menggunakan Teknik Data Mining

Salah satu permasalahan yang ada di Perguruan Tinggi XYZ adalah tingginya jumlah mahasiswa yang putus studi (dropout / DO), sehingga diperlukan upaya untuk minimalisasi jumlah mahasiswa yang dropout. Penelitian ini bertujuan untuk membangun sebuah model yang dapat memprediksi apakah seorang mahasiswa akan lulus ataukah dropout. Data diambil dari data akademis mahasiswa angkatan 2014-2019. Pemrosesan awal data dilakukan dengan Python dan pemodelan dilakukan dengan menggunakan algoritma C4.5 / J48 pada perangkat lunak WEKA (Waikato Environment for Knowledge Analysis). Hasil menunjukkan bahwa atribut yang paling menentukan apakah seorang mahasiswa DO atau lulus adalah Indeks Prestasi Semester 1 dan Indeks Prestasi Semester 2, dengan akurasi model mencapai sebesar 90.6%.

Global research on syndemics: A meta-knowledge analysis (2001-2020)

Syndemics or synergies of cooccurring epidemics are widely studies across health and social sciences in recent years. We conducted a meta-knowledge analysis of articles published between 2001 to 2020 in this growing field of academic scholarship. We found a total of 830 articles authored by 3025 authors, mostly from high-income countries. Publications on syndemics are gradually increasing since 2003, with rapid development in 2013. Each article was cited more than 15 times on average, whereas most (n = 604) articles were original studies. Syndemics research focused on several areas, including HIV/AIDS, substance abuse, mental health, gender minority stressors, racism, violence, chronic physical and mental disorders, food insecurity, social determinants of health, and COVID-19. Moreover, biopsychosocial interactions between multiple health problems were studied across medical, anthropological, public health, and other disciplines of science. The limited yet rapidly evolving literature on syndemics informs transdisciplinary interests to understand complex coexisting health challenges in the context of systematic exclusion and structural violence in vulnerable populations. The findings also suggest applications of syndemic theory to evaluate clinical and public health problems, examine the socioecological dynamics of factors influencing health and wellbeing, and use the insights to alleviate health inequities in the intersections of synergistic epidemics and persistent contextual challenges for population health.

Caracterização de Cicatrizes de Queimadas nas Mesorregiões do Sertão e São Francisco Pernambucano a partir de dados do Sensor MODIS

As mesorregiões do Sertão e São Francisco Pernambucano apresentam clima semiárido, que podem afetar a produção agrícola, em função do clima quente e seco, com temperaturas elevadas e regime pluviométrico irregular. O bioma predominante da região é a Caatinga, que vem sofrendo ao longo dos anos com várias ações antrópicas, incluindo além do desmatamento eventos de queimadas. O objetivo deste artigo foi mapear, caracterizar e quantificar a incidência de focos de calor nas mesorregiões acima relacionadas, bem como a capacidade de recuperação e/ou regeneração natural da vegetação por meio do sensoriamento remoto e técnicas de mineração de dados. Imagens do sensor Moderate Resolution Imaging Spectroradiometer (MODIS) a bordo da plataforma TERRA foram utilizadas para analisar o estado da vegetação nos períodos pré, durante e pós-queima. Para avaliar as condições necessárias para que ocorra a regeneração natural da superfície vegetal foi utilizado o software de mineração de dados Waikato Environment for Knowledge Analysis (WEKA) a partir do cruzamento dos dados do Índice de Vegetação da Diferença Normalizada (NDVI) e precipitação local. Os resultados demonstram um aumento na ocorrência dos focos no período analisado. Existe uma correlação de 91,76% entre o NDVI durante e 48 dias após o evento da queima. Além disso, os parâmetros NDVI 30 e 48 dias após a queima apresentaram um coeficiente de correlação de 83,96%. Portanto, as técnicas de sensoriamento remoto e mineração de dados permitiram avaliar as relações existentes entre o NDVI e a precipitação local para que ocorra a regeneração vegetal. Characterization of Burning Scars in the Sertão and São Francisco Pernambucano Mesoregions from MODIS Sensor dataA B S T R A C T The Sertão and São Francisco Pernambucano mesoregions have a semi-arid climate, which can affect agricultural production, due to the hot and dry climate, with high temperatures and irregular rainfall. The predominant biome of the region is the Caatinga, which has been suffering over the years with several anthropic actions, including in addition to deforestation, burning events. The purpose of this article was to map, characterize and quantify the incidence of hot spots in the mesoregions listed above, as well as the capacity for recovery and / or natural regeneration of vegetation through remote sensing and data mining techniques. Images from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the TERRA platform were used to analyze the state of vegetation in the pre, during and post-firing periods. To assess the conditions necessary for the natural regeneration of the plant surface to occur, the data mining software Waikato Environment for Knowledge Analysis (WEKA) was used, by crossing the data from the Normalized Ddifference Vegetation Index (NDVI) and precipitation. The results demostrate an increase in the occurrence of outbreaks in the analyzed period. There is a 91.76% correlation between NDVI during and 48 days after burning event. In addition, the NDVI parameters 30 and 48 days after burning presented a correlation coefficient of 83.96%. Therefore, the techniques of remote sensing and data mining allowed to evaluate the existing relationships between NDVI and local precipitation so that plant regeneration to occurs.Keywords: remote sensing, vegetation indexes, hot spots, data mining.