Miracle-dz/UniFAR-FTUs huggingface dataset:
Kardiale Biomarker und EKG-Veränderungen beim Schlaganfall

Zusammenfassung Kardiale Komplikationen treten bei akuten Schlaganfallpatienten häufig auf und sind eine der Haupttodesursachen nach einem Schlaganfall. Gleichzeitig sind kardiale Erkrankungen häufig Ursache für die Entstehung von Schlaganfällen. Kardiovaskuläre und zerebrovaskuläre Erkrankungen teilen viele gemeinsame Risikofaktoren, sodass nicht selten zusätzlich zum Schlaganfall auch eine KHK vorliegt. Das kontinuierliche EKG-Monitoring stellt einen wichtigen Baustein in der diagnostischen Abklärung beim Schlaganfall dar und die Leitlinien der American Heart Association (AHA) empfehlen Troponin bei Schlaganfallpatienten zu bestimmen. Häufig finden sich nach Schlaganfall EKG-Veränderungen sowie eine Erhöhung von Troponin. Beides ist mit einer schlechten Prognose assoziiert. Es gibt jedoch wenig konkrete Empfehlungen zum Umgang mit pathologischen EKG- und Laborbefunden im Alltag. Im klinischen Alltag gestaltet sich die Differenzialdiagnose von kardialen Erkrankungen bei Schlaganfallpatienten aber häufig schwierig: Kardiale Erkrankungen präsentieren sich bei Schlaganfallpatienten vielfach mit atypischen Symptomen. Bei Schlaganfallpatienten können EKG-Veränderungen oder eine Erhöhung kardialer Biomarker vorkommen, ohne dass dem eine akute koronare Ischämie zugrunde liegt. Stattdessen können sowohl chronische kardiale als auch nicht-kardiale Erkrankungen die Ursache für die Erhöhung kardialer Biomarker oder EKG-Veränderungen sein. Daneben kommt es bei einigen Schlaganfallpatienten zu einer neurogenen Myokardschädigung im Sinne einer stressinduzierten Kardiomyopathie. Dieser Artikel soll einen Überblick über die klinische Relevanz und Interpretationsmöglichkeiten häufiger EKG-Veränderungen und kardialer Biomarker bei Patienten mit akuter zerebraler Ischämie liefern.
Performance analysis of the convolutional recurrent neural network on acoustic event detection

In this study, we attempted to find the optimal hyper-parameters of the convolutional recurrent neural network (CRNN) by investigating its performance on acoustic event detection. Important hyper-parameters such as the input segment length, learning rate, and criterion for the convergence test, were determined experimentally. Additionally, the effects of batch normalization and dropout on the performance were measured experimentally to obtain their optimal combination. Further, we studied the effects of varying the batch data on every iteration during the training. From the experimental results using the TUT sound events synthetic 2016 database, we obtained optimal performance with a learning rate of 1/10000. We found that a longer input segment length aided performance improvement, and batch normalization was far more effective than dropout. Finally, performance improvement was clearly observed by varying the starting points of the batch data for each iteration during the training.
Automatic Geodata Processing Methods for Real-World City Visualizations in Cities: Skylines

The city-building game Cities: Skylines simulates urban-related processes in a visually appealing 3D environment and thus offers interesting possibilities for visualizations of real-world places. Such visualizations could be used for presentation, participation, or education projects. However, the creation process of the game model from geographical data is inaccurate, complicated, and time consuming, thus preventing the wider use of this game for non-entertainment purposes. This paper presents the automatic methods scripted in the Cities: Skylines application programming interface (API) and bundled into a game modification (commonly referred to as a game mod) named GeoSkylines, to create a geographically accurate visualization of real-world places in Cities: Skylines. Based on various geographical data, the presented methods create road and rail networks, tree coverage, water basins, planning zones, buildings, and services. Using these methods, playable models of the cities of Svit (Slovakia) and Olomouc (Czech Republic) were created in the game. The game mod GeoSkylines also provides methods for exporting game objects such as roads, buildings, and zones into a Geographic Information System (GIS) data format that can be processed further. This feature enables the game Cities: Skylines to be utilized as a data collection tool that could be used in redevelopment design projects.
Modeling a semantic recommender system for medical prescriptions and drug interaction detection

كچ ي هد :فده وجت ي ز اهوراد ي ارب بسانم ي ب ي نارام ساسا زا ي رت ي ن هسورپ اه ي نآ نامرد اه تسا و ن ي دنمزا مصت ي م گ ي ر ي قد ي ق رب ساسا ارش ي ط لعف ي ب ي رام و مئلاع و قباوس و ي م ي دشاب ن وراد کي زا شيب ناراميب تسا نکمم دراوم زا يرايسب رد . ي زا هولاع اي هتشاد رب نتشاد يراميب يلبق و تفايرد وراد ي نچ هک دنشاب هتشاد ديدج ياهوراد هب زاين ديدج يراميب يارب ،نآ ي ن ارش ي ط ي ا ناکما ي داج اطخ ي کشزپ ي وجت رد ي ز وراد فرصم ءوس تارثا زورب و وراد يي (ADE) ( وراد تلاخادت دننام يي ارب ار ) ي ب ي رام ازفا ي ش م ي هد د . شور و داوم :اه ا رد ي ن لدم هلاقم زاس ي هناماس ي صوت ي ه رگ انعم يي وجت ي ز ئوراد تلاخادت فشک و کشزپ ي هدش هئارا تسا . پ ي ش رت ن ي دنمزا ي اه ي صفت هب و جارختسا هناماس ي ل هداد حرش هدش و رد ا ي ن رب ،هلاقم ن ساسا ي دنمزا ي اه ي جارختسا هدش هب لدم زاس ي اب هناماس نابز زا هدافتسا ي ک هچراپ لدم زاس ي UML2.0 هدش هتخادرپ تسا . تهج زرا ي با ي اهدرکراک ي صوت ي ه فشک و
Optimizing anticoagulant therapy in non-Valvular atrial fibrillation

be around 3% of the population above 20 years of age, and increases with age, hypertension, cardiovascular disease, diabetes and obesity. Besides a 1.5to 2-fold increase in mortality in people suffering from AF, they also have an increase in morbidity from heart failure and stroke. In fact, 20-30% of all ischaemic strokes are thought to be secondary to AF. The CHA2DS2-VASc score is a useful tool to quantify the yearly risk of stroke. One should note that the risk of stroke is independent of whether the AF is paroxysmal, persistent or permanent.1 Guidelines published by the European Society of Cardiology2 (ESC) give a class I A indication for the prescription of oral anticoagulants (OACs) to males with a CHA2DS2-VASc score ≥ 2 and females with a score ≥ 3. One should also consider giving OACs to males with a score of 1 and females with a score of 2 (IIa B indication). No anticoagulants should be given to males or females with no additional risk factors, and anti-platelet monotherapy is not recommended whatever the stroke risk. A careful analysis of the patient’s bleeding risk should be carried out before prescribing these drugs. Naturally, OACs should be avoided in patients with active bleeding, and concomitant antiplatelets should only be prescribed if indication is strong. Vitamin K antagonists (VKAs) such as warfarin have been used for many years to reduce the risk of stroke and mortality in patients with AF. VKAs are limited by their narrow therapeutic interval, with patients needing frequent monitoring and dose adjustments. They are only effective optImIzIng antIcoagulant therapy In non-ValVular atrIal fIbrIllatIon andrew cassar
Multimodal Interaction-Aware Trajectory Prediction in Crowded Space

Accurate human path forecasting in complex and crowded scenarios is critical for collision avoidance of autonomous driving and social robots navigation. It still remains as a challenging problem because of dynamic human interaction and intrinsic multimodality of human motion. Given the observation, there is a rich set of plausible ways for an agent to walk through the circumstance. To address those issues, we propose a spatio-temporal model that can aggregate the information from socially interacting agents and capture the multimodality of the motion patterns. We use mixture density functions to describe the human path and predict the distribution of future paths with explicit density. To integrate more factors to model interacting people, we further introduce a coordinate transformation to represent the relative motion between people. Extensive experiments over several trajectory prediction benchmarks demonstrate that our method is able to forecast various plausible futures in complex scenarios and achieves state-of-the-art performance.
Wilms' tumor gene 1 in leukemia: Prognostic or predictive biomarker

Wilms' tumor is common in children and is caused by Wilms' tumor gene 1 (WT1). The WT1 mutation has been reported in a variety of hematologic malignancies. Changing expression of miRNA molecules has also been shown to play a role in the development of Wilms' tumor. Considering the fact that WT1 can be used as a clinical biomarker in leukemia cases, it can be a basis for immunotherapy of leukemia. WT1 is a gene that can be used as a prognostic biomarker for minimal residual disease, as well as the detection of relapse for clinical remission in leukemia. Furthermore, it can be considered as a predictive biomarker for the treatment of leukemic patients after allogeneic transplantation. This study aimed to review WT1 expression in leukemia, its involvement in miRNAs expression, as well as its importance in prognosis and treatment of leukemia.
TRATAMENTO CLÍNICO DA APENDICITE AGUDA: RELATO DE CASO

INTRODUCAO: A apendicite aguda e uma causa comum de dor abdominal aguda e a causa mais frequente de cirurgia abdominal de emergencia. Sabe-se que seu manejo tradicional e a apendicectomia, mas que o uso de antibioticos apresenta papel fundamental no seu manejo seja como antibioticoterapia ou somente na profilaxia. O objetivo desse relato e apresentar caso clinico de paciente com apendicite aguda tratada clinicamente e discutir aspectos relevantes. CASO: I.U. D.S, masculino, 58 anos, hemofilico, diabetico, ex-etilista/tabagista deu entrada no pronto socorro com queixa de dor abdominal, em fossa iliaca direita ha quatro dias. Negava alteracao do habito intestinal, nauseas, vomitos, febre e/ou disuria. Ao exame fisico apresentava abdome plano e doloroso a palpacao da fossa iliaca direita com massa palpavel endurecida na mesma regiao, ruidos hidroaereos diminuidos e descompressao brusca negativa. Tambem era evidente a presenca de hernia inguinal bilateral sem sinais de encarceramento. A primeira hipotese diagnostica foi tumor de colon direito e para tal finalidade diagnostica solicitou-se tomografia de abdome. Esta apresentou laudo sugestivo de apendicite aguda bloqueada. Optou-se por tratamento nao operatorio, visando diminuir complicacoes devido condicao hemofilica do paciente, alem do mesmo apresentar-se clinicamente estavel, sem sinais de sepse grave, plastrao palpavel e com pequena colecao bloqueada. Foi iniciado antibioticoterapia com Ceftriaxone e Metronidazol por sete dias e o paciente teve evolucao clinica satisfatoria. Realizou-se tomografia computadorizada de controle ao final desse periodo que apresentou melhora radiologica significativa em comparacao com exame anterior. Nesta data, o paciente teve alta com prescricao de Ciprofloxacino e Metronidazol por via oral, alem de ser orientado a retornar em sete dias para controle tomografico. Ao retorno, o paciente permanecia assintomatico e a tomografia computadorizada nao evidenciou sinais inflamatorios ou infecciosos, demonstrando resolucao radiologica e clinica com o uso de antibioticoterapia. CONCLUSAO: O manejo da apendicite aguda permanece controverso, tanto na discussao da necessidade ou nao de cirurgia quanto em relacao a via de acesso, laparoscopica ou aberta. Ate o momento, sabe-se que a escolha do tratamento dependera das caracteristicas clinicas de cada paciente e dos recursos disponiveis e que, o tratamento nao cirurgico da apendicite como unica estrategia, tem como objetivo reduzir os custos e diminuir as complicacoes relacionadas a cirurgia ou a resseccao do orgao. PALAVRAS-CHAVES: apendicite, apendicectomia, antibioticos, cirurgia
What Is Thinking with Images?

Similar operations could be conducted in extramental images as well. If an architect designs a house, then he or she will design the house with the help of drawings. If an engineer wants to build a motor engine, he or she will start with a blueprint of the motor engine. If one tries to get from a point A to a point B, one can use a map. If I want to present an argument in court that John killed Marry, then, if I possess one, I can point at a photograph that represents John killing Marry. All of these examples are instantiations of what can be called “thinking with images. ” Listing examples of this is an easy task. The hard task, however, is to say exactly what “thinking with images” might be.
An Integrated Agriculture, Atmosphere, and Hydrology Modeling System for Ecosystem Assessments

We present a regional‐scale integrated modeling system (IMS) that includes Environmental Policy Integrated Climate (EPIC), Weather Research and Forecast (WRF), Community Multiscale Air Quality (CMAQ), and Soil and Water Assessment Tool (SWAT) models. The centerpiece of the IMS is the Fertilizer Emission Scenario Tool for CMAQ (FEST‐C), which includes a Java‐based interface and EPIC adapted to regional applications along with built‐in database and tools. The SWAT integration capability is a key enhanced feature in the current release of FEST‐C v1.4. For integrated modeling demonstration and evaluation, FEST‐C EPIC is simulated over three individual years with WRF/CMAQ weather and N deposition. Simulated yearly changes in water and N budgets along with yields for two major crops (corn grain and soybean) match those inferred from intuitive physical reasoning and survey data given different‐year weather conditions. Yearlong air quality simulations with an improved bidirectional ammonia flux modeling approach directly using EPIC‐simulated soil properties including NH3 content helps reduce biases of simulated gas‐phase NH3 and NH4+ wet deposition over the growing season. Integrated hydrology and water quality simulations applied to the Mississippi River Basin show that estimated monthly streamflow and dissolved N near the outlet to the Gulf of Mexico display similar seasonal patterns as observed. Limitations and issues in different parts of the integrated multimedia simulations are identified and discussed to target areas for future improvements.
A INFLUÊNCIA DAS DIMENSÕES DE CONFIANÇA E RISCO NO COMPORTAMENTO DE COMPRA ONLINE.

Ha alguns anos a internet vem impulsionando importantes modificacoes nas organizacoes, dentre elas, a maneira de fazer negocios. No entanto, especialistas acreditam que a internet ainda tem algum caminho a percorrer antes de atingir seu verdadeiro potencial e-commerce , visto que, alguns consumidores ainda nao realizam compras online por considerarem-na um ambiente de incerteza. Acredita-se que compreender fatores como a propensao a confianca, a confianca no vendedor, a confianca na certificacao, o ambiente cultural de confianca, as atitudes dos consumidores em relacao as compras online e a intencao de continuidade de uso de compras online, pode clarificar o entendimento do que determina, ou nao, a utilizacao e reutilizacao das compras online . Entretanto, as dimensoes relacionadas a confianca e risco, nao sao alvo de muitas pesquisas, principalmente no Brasil, onde a grande maioria das pesquisas sobre o comportamento do consumidor abarcam construtos relacionados a utilidade, facilidade, diversao, expectativas e atitudes. Neste sentido, o objetivo do artigo foi investigar a influencia das dimensoes de confianca e risco no comportamento de compra online e como esses fatores influenciam a probabilidade de continuidade de compra online . Em termos especificos, objetivou-se validar o modelo de Bianchi e Andrews (2012). Para tanto, desenvolveu-se uma pesquisa quantitativa e descritiva, aplicada junto a academicos do Curso de Administracao de uma instituicao publica de ensino superior da regiao central do Rio Grande do Sul. Formularam-se seis hipoteses, sao elas: H1: A atitude dos consumidores para a compra online tem influencia positiva sobre a sua intencao de continuar a comprar online ; H2: O risco percebido tem influencia negativa sobre as atitudes dos consumidores em relacao a continuidade de compra online ; H3: A confianca em vendedores online tem influencia positiva sobre as atitudes dos consumidores no sentido de continuar a comprar online ; H4: A confianca em garantias de terceiros tem influencia positiva sobre a atitude dos consumidores no sentido de continuar a comprar online ; H5: A propensao dos consumidores a confianca tem uma influencia positiva sobre a intencao do consumidor de continuar a comprar online ; H6: A confianca no ambiente cultural tem uma influencia positiva sobre a intencao do consumidor para continuar comprando online. As hipoteses foram testadas por meio de regressao multipla, sendo que confirmou-se H1 e H2, rejeitou-se H4, H5 e H6 e, excluiu-se H3 do modelo. Conclusivamente, os resultados indicaram a influencia positiva da atitude do consumidor sobre a intencao de compra online e a influencia negativa do risco percebido na atitude do consumidor em relacao a continuidade de compra online .
Efficient fine-grain parallelism in shared memory for real-time avionics

: Multi-task/parallel software design methods for critical embedded systems often enforce space and/or time isolation properties, which constrain resource sharing to facilitate the design process. For instance, ensuring that computing cores only interfere with each other during dedicated communication phases largely simplifies the timing analysis of parallel code. The downside of isolation is efficiency loss – longer latencies, smaller throughput, increased memory use. We focus on hard real-time applications (or parts thereof) inside which isolation is not a requirement. We show that, in this case, fine-grain parallelism can be more efficiently exploited without isolation, while still providing the levels of safety and hard real-time guarantees required in critical industrial applications. Resulting implementations allow multiple computations and communications to take place at the same time, provided that interferences can be controlled (which is possible on timing compositional platforms). We demonstrated this approach on two large avionics applications in a dedicated shared memory context, using an automatic parallelization method. Our method provides good parallelization results and, in one context, has reached TRL4.
Two-Dimensional Multiple-Snapshot Grid-Free Compressive Beamforming Using Alternating Direction Method of Multipliers

Compressive beamforming with planar microphone arrays is capable of estimating the two-dimensional direction-of-arrivals (DOAs) and quantifying the strengths of acoustic sources effectively. The multiple-snapshot grid-free method has recently been concerned due to the advantages that it can circumvent the basis mismatch conundrum of the conventional grid-based method and improve the performance of the single-snapshot grid-free method. The existing atomic norm minimization based strategy uses an off-the-peg interior point method (IPM) based solver to solve the positive semidefinite programming equivalent to the atomic norm minimization. We present an alternative algorithm based on alternating direction method of multipliers (ADMM) in this paper. Both simulations and experiments demonstrate that whether a standard uniform rectangular array or a non-uniform array constituted by a small number of microphones is employed, the two-dimensional multiple-snapshot grid-free compressive beamforming using our ADMM based algorithm can estimate the DOAs and quantify the strengths of acoustic sources well, and reaching the same or even better DOA estimation accuracy as the one using the IPM based solver, our ADMM based algorithm is distinctly faster.
Prevention of Gender-based violence through coeducation. An educational proposal aimed at Secondary School

The present dissertation discusses the education of teenagers in gender-based violence issues through coeducational strategies and the implementation of tasks in which a natural learning of English as a Second Language is put forward. This is fulfilled by designing lesson plans that use certain media content, specially if the students are familiar with it, and make them question broader social issues by analysing a well-known-among-teenagers TV show and the most popular sport in the world. By means of analysing and evaluating closely the content they are constantly exposed to on the media, the students will develop their critical thinking and awareness on social matters, sexism, misogyny and gender-based violence particularly gender equality in society, accelerating media consumption, gender bias in and social in
An idea based on sequential pattern mining and deep learning for text summarization

One of the Natural Language Processing (NLP) studies that has been widely researched is automatic text summarization. There are a lot of techniques and methods that are proposed for text summarization. However, not much attention has been given on the coherence and cohesion in text. The aim of this study is to present an idea to combine Sequential Pattern Mining (SPM) and Deep Learning (DL) for better text summarization process and result. In text summarization, it is important to produce understable and readable summary, and SPM as text representation extracting algorithm is capable to maintain the meaning of text by giving attention of the order of words appearance. Whereas DL is a popular and powerful machine learning technique widely used recently in various data mining studies. This study uses descriptive research methodology that collects all of the facts and information which are related to SPM and DL for text summarization, where NLP as the body of knowledge, SPM and DL as the method, and text summarization as the domain problem that need to be solved. The findings of the study are presented as a logical design and mapping of current text representation that can be implemented to further improve automatic text summarization results, in particular, to improve its coherence and cohesion.
Evolution of Modern Deep Learning Methods of Object Recognition

Vision is a very complex work of our brain. 90% of the information entered to our brain is related to vision. In computer vision engineers and scientists are trying to give the computers the ability of vision. Object recognition is one of the most exciting fields of computer vision and AI. There is no rarity of problems and challenges in object recognition, from image classification to key-point detection. But like many other problems in the world, there is still no obvious and “Best” way to resolve these problems. But the recent advancement in GPU technology propelled the success and accuracy of deep learning algorithms. In this paper, we will study about the evolution of deep learning methods in object recognition. We will also go through some of the classical machine learning methods for object recognition and talk about multimodal approaches to solving these issues.
A double forward-backward algorithm using linesearches for minimization problem

In this paper, we introduce a novel forward-backward algorithm involving linesearches for solving nonsmooth optimization problems in Hilbert spaces. The convergence including the complexity are proved under mild conditions.Further, some numerical experiments are tested to show the efficiency and the implementation of our algorithms. It reveals that the proposed method has a good convergence in terms of CPU time and number of iterations.
Obstructive Sleep Apnea

Individuals with obstructive sleep apnea may experience interrupted sleep with frequent awakenings and loud snoring. Repeated pauses in breathing lead to episodes of lowerthan-normal oxygen levels (hypoxemia) and a buildup of carbon dioxide (hypercapnia) in the bloodstream. Interrupted and poor quality sleep can lead to daytime sleepiness and fatigue, impaired attention and memory, headaches, depression, and sexual dysfunction. Daytime sleepiness leads to a higher risk of motor vehicle accidents in individuals with obstructive sleep apnea. Obstructive sleep apnea is also associated with an increased risk of developing insulin resistance, which is an inability to regulate blood sugar levels effectively; high blood pressure (hypertension); heart disease; and stroke.