Miracle-dz/UniFAR-FTUs huggingface dataset:
Re-description of external morphology and factors affecting body and tail shape of the stone frog tadpoles

Ecological studies testing the preponderance of environmental filters on ontogeny to explain the variation in tadpole morphology are scarce for Neotropical anurans. We used tadpoles of the stone frog Limnomedusa macroglossa (Alsodidae): (1) to assess the variation in body and tail shape; (2) to examine the effect of streamlet depth and allometry on tadpole shape, and (3) to re-describe and compare the tadpole external morphology with closely related species. We obtained the body shape and size from 150 tadpoles. The re-description was based on 57 qualitative and 24 quantitative characters, from 19 tadpoles between stages 30 and 37 and 31 to 37, respectively. Allometry was the major factor influencing the lateral view of body shape: smaller tadpoles had round bodies and eyes and nostrils positioned more laterally in comparison with larger ones. Thus, the power of ontogenetic variations reported here makes the tadpole developmental “climax” period a questionable concept that deserves additional attention. The depth gradient of streamlets also affected the shape: in shallower environments, the tadpoles presented a decrease in height of the body, fins and tail muscles, and an increase in body width. These results may indicate adaptations allowing better swimming performance in lotic environments with intense water flow. The external morphological characterization of L. macroglossa presented here differed from that previously reported, mainly due to coloration, body shape, nostril, anal tube, tail, shape and position of nostrils and snout. Additionally, we presented unknown traits for this species, making comparisons with closely related species within the Alsodidae family.
Massive obstetric hemorrhage: Current approach to management (cid:2)

Massive obstetric hemorrhage is a major cause of maternal mortality and morbidity worldwide. It is deﬁned (among others) as the loss of >2500 ml of blood, and is associated to a need for admission to critical care and/or hysterectomy. The relative hemodilution and high cardiac output found in normal pregnancy allows substantial bleeding before a drop in hemoglobin and/or hematocrit can be identiﬁed. Some comorbidities associated with pregnancy can contribute to the occurrence of catastrophic bleeding with consumption coagulopathy, which makes the situation even worse. Optimization, preparation, rational use of resources and protocolization of actions are often useful to improve outcomes in patients with postpartum hemorrhage. Using massive obstetric hemorrhage protocols is useful for facilitating rapid transfusion if needed, and can also be cost-effective. If hypoﬁbrinogenemia during the bleeding episode is identiﬁed, early ﬁbrinogen administration can be very useful. Other coagulation factors in addition to ﬁbrinogen may be necessary during postpartum hemorrhage replacement measures in order to effectively correct coagulopathy. A hysterectomy is recommended if the medical and surgical measures prove ineffective.
Life Cycle Agent Beyond Intelligent Manufacturing

—In this paper, a model is proposed where a software agent will be tied to a product during all parts of its life-cycle. This agent will enhance the possibilities of the product itself but will also play a role in collecting important data from the device that can be used by the manufacturer, as well as the end user. The software agent will be the basis for the device to participate in the Internet of Things (IoT) concept. The motivation to use agent technology, the architecture as well as the implementation in two different products are presented.
Vibration Isolation Design for Periodical Stiffened Shells by the Wave Finite Element Method

Abstract Periodically stiffened shell structures are widely used due to their excellent specific strength, in particular for aeronautical and astronautical components. This paper presents an improved Wave Finite Element Method (FEM) that can be employed to predict the band-gap characteristics of stiffened shell structures efficiently. An aero-engine casing, which is a typical periodically stiffened shell structure, was employed to verify the validation and efficiency of the Wave FEM. Good agreement has been found between the Wave FEM and the classical FEM for different boundary conditions. One effective wave selection method based on the Wave FEM has thus been put forward to filter the radial modes of a shell structure. Furthermore, an optimisation strategy by the combination of the Wave FEM and genetic algorithm was presented for periodically stiffened shell structures. The optimal out-of-plane band gap and the mass of the whole structure can be achieved by the optimisation strategy under an aerodynamic load. Results also indicate that geometric parameters of stiffeners can be properly selected that the out-of-plane vibration attenuates significantly in the frequency band of interest. This study can provide valuable references for designing the band gaps of vibration isolation.
Optimal Integration of Multi Distributed Generation Sources in Radial Distribution Networks Using a Hybrid Algorithm

Distributed generation (DG) can be integrated into any radial distribution network (RDN) to meet the increasing demand for electric power. Instead of integrating a single large size DG, two or more than two small DGs (multi DGs) are usually placed. These DGs must be placed in appropriate buses/nodes with suitable size to ensure better performance of the system. The purpose of this paper is to implement an established hybrid optimization algorithm to place multi DGs with suitable size at each site. The proposed hybrid ABC-CS optimization algorithm combines the behaviour of the artificial bee colony (ABC) and cuckoo search (CS) algorithms. The multi DGs are optimally placed by considering objectives like power loss, penalty function (PE) and voltage profile (VP). The outcomes of two different types of radial distribution networks obtained by the suggested method for placement of multi DGs have been correlated to that obtained by using genetic algorithm (GA), particle swarm optimization (PSO) and GA-PSO. The proposed method has also been correlated with the other published methods to indicate its strength.
Array radar resource management

The operation of an electronically steered array (ESA) antenna is highly flexible in that a range of control parameters can be reconfigured nearly instantaneously. Consequently, an ESA is capable of executing numerous tasks supporting multiple functions, multiplexed in time and angle. However, this flexibility creates a challenging operation and resources management problem, in that a new radar dwell complete with beam direction and transmit waveform must be chosen within the time taken to execute the previous radar dwell. As controlling the operation of an ESA is beyond the capability of a human operator, automated management techniques are required, which are emerging as key performance factors for the next generation of multifunction radar systems. This chapter gives an overview of automated techniques for managing the operation and resources of an ESA.
The rapid response of 2/1 tearing mode to electrode biasing in J-TEXT experiments

Electrode biasing (EB) has been applied to modulate the m/n = 2/1 tearing modes (TM) in the J-TEXT tokamak, where m and n are the poloidal and toroidal mode numbers. According to the response time, the response of 2/1 TM frequency to EB can be divided into two processes, the rapid response and the slow response. In the rapid response, experimental results show that the variation of mode frequency is ahead of the variation of plasma rotation, which is analogous to the result mentioned in paper (Liu et al 2017 Nucl. Fusion 57 016003). Statistical results indicate that the rapid response coefficient of TM frequency to EB current is a constant. The detailed analysis of rapid response obtained by auto-conditional average shows that the mode frequency varying lags about 13 μs behind the variation of current. Additionally, the mode frequency derivative increases in proportion with the increase of the EB current value. A heuristic mechanism of the rapid response of 2/1 TM to EB is presented, which is relevant to the rotation difference between magnetic island and edge plasma layer rather than the flow shear around the magnetic island. The experimental results suggest that the application of EB can modulate the TM frequency in a small amount of time, which is a possible method for the avoidance of mode locking and disruption.
Lessons from tropical storms Urduja and Vinta disasters in the Philippines

Purpose Tropical storms Urduja and Vinta battered the Philippines in December 2017. Despite advances in disaster risk reduction efforts of the country, the twin December storms caused numerous deaths in the Visayas and Mindanao regions. Analysis of these events shows that alerts raised during the Pre-Disaster Risk Assessment (PDRA) for both storms were largely ineffective because they were too broad and general calling for forced evacuations in too many provinces. Repeated multiple and general warnings that usually do not end up in floods or landslides, desensitize people and result in the cry-wolf effect where communities do not respond with urgency when needed. It was unlike the previous execution of PDRA from 2014 to early 2017 by the National Disaster Risk Reduction and Management Council (NDRRMC), which averted mass loss of lives in many severely impacted areas because of hazard-specific, area-focused and time-bound warnings. PDRA must reinstate specific calls, where mayors of communities are informed by phone hours in advance of imminent danger to prompt and ensure immediate action. Mainstreaming Climate Change Adaptation and Disaster Risk Reduction information using probabilistic (multi-scenario) hazard maps is also necessary for an effective early warning system to elicit appropriate response from the community. The paper aims to discuss these issues. Design/methodology/approach Methods of early warning through the PDRA of the National Disaster Mitigation and Management Council (NDRRMC) of the Philippines during tropical storm Urduja and Typhoon Vinta were assessed in this study and compared to the previous PDRA system from 2014 to early 2017. Findings It was found out that the numerous casualties were due to inadequate warning issued during the approach of the tropical cyclones. During an impending hazard, warnings must be accurate, reliable, understandable and timely. Despite the availability of maps that identified safe zones for different communities, warnings raised during the PDRA for both tropical cyclones were deemed too general calling for evacuations of whole provinces. As such, not all communities were evacuated in a timely manner because of failure in the key elements of an effective early warning system. Originality/value To avoid future disasters from happening, it is recommended that the PDRA reinstate its hazards-specific, area-focused and time-bound warnings. Similarly, to increase the resilience of communities, more work on mainstreaming of Climate Change Adaptation and Disaster Risk and Vulnerability Reduction systems for communities must be done as well. Learning from the lessons of these previous disasters will enable communities, their leaders and every stakeholder, not to repeat the same mistakes in the future.
Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips

The development of a trip distribution model requires a massive data collection task, such as expensive travel surveys to identify trip makers’ origin and destination zones. Intra-zonal trips are usually ignored in the development of trip distribution models because of the difficulty associated with measuring travel costs. However, ignoring intra-zonal trips leads to incomplete model estimation especially when the zone size is large, and thus, the number of intra-zonal trips is substantial. This is especially important, with the growing interest around the world on creating more walkable and bikeable cities where a high share of those trips is intra-zonal. In this paper, we use mobile phone data to derive country-wide mobility trends. A set of doubly constrained trip distribution models that integrates intra-zonal trips was estimated for 123-district-level traffic analysis zones. We present two approaches to estimate the intra-zonal travel costs measured in terms of trip distance. Our analysis reveals that the average intra-zonal trip distances obtained from the two approaches provide different levels of sensitivity to the distance-decay effect. Our result also shows that model estimation in the absence of intra-zonal trips produces biased estimates.
The genotypic profile of milk proteins in Holstein cows raised in South of Brazil

Genotyping in dairy cattle allows knowing the alleles and genotypes associated with milk proteins that affect yield and milk quality. This study aimed to verify the genotype profile for κ-casein I and II (κ-CN), α-s1-casein (α-CN) and β-lactoglobulin (β-LG), for Holstein cows raised in southern Brazil, where there is no scientific evidence on the presence of these alleles in dairy herds. Hair follicles samples from each animal were used for DNA extraction and genotyping. We calculated the allelic and genotypic frequencies for four types of milk protein variants in the population, and a chi-square test was employed to see whether the population of animals used was in Hardy-Weinberg equilibrium. Allele A and AA genotype showed the highest frequency for both κ-CN (56.77 to 80.36%). For α-s1-CN and β-LG, the B allele was the most frequent, as BB (80.26%) and AB (47.15%), respectively. Due to the presence of alleles associated with protein levels in milk, we concluded that these herd cows present milk technological properties interesting to produce dairy products.
REPRODUCING DISTRIBUTIONS FOR MACHINE LEARNING

Abstract : A model is proposed for learning the nature and value of an unknown parameter, or unknown parameters, in a probability distribution which forms part of a body of statistics related to some system or process. The model is Bayesian, involving the assumption of an a priori probability distribution over the possible values of the unknown parameters; the performance of experiments to gain information about the parameters; and the alteration of the a priori probabilities by Bayes' rule. In the limit, as the number of experiments approaches infinity, the a posteriori distribution in most cases encountered in practice approaches a delta function at the true values of the unknown parameters, so the system learns the values of the parameters exactly. The learning process developed in the paper is shown to be technically feasible if the a priori and a posteriori distributions are of the same form, with the learning accomplished by calculating new parameters for these distributions. It is shown that a necessary and sufficient condition for fulfillment of this feasibility criterion is for a sufficient statistic of fixed dimension to exist. If such a sufficient statistic exists, the a posteriori distributions may vary in form initially, but they eventually become of fixed form. The techniques developed indicate logical methods for choosing a priori probabilities and are applied in pattern recognition, estimation, and other problems.
State-of-the-Art Deep Learning Methods on Electrocardiogram Data: Systematic Review

Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic tools that can provide useful information regarding a patient’s health status. Deep learning (DL) is an area of intense exploration that leads the way in most attempts to create powerful diagnostic models based on physiological signals. Objective This study aimed to provide a systematic review of DL methods applied to ECG data for various clinical applications. Methods The PubMed search engine was systematically searched by combining “deep learning” and keywords such as “ecg,” “ekg,” “electrocardiogram,” “electrocardiography,” and “electrocardiology. ” Irrelevant articles were excluded from the study after screening titles and abstracts, and the remaining articles were further reviewed. The reasons for article exclusion were manuscripts written in any language other than English, absence of ECG data or DL methods involved in the study, and absence of a quantitative evaluation of the proposed approaches. Results We identified 230 relevant articles published between January 2020 and December 2021 and grouped them into 6 distinct medical applications, namely, blood pressure estimation, cardiovascular disease diagnosis, ECG analysis, biometric recognition, sleep analysis, and other clinical analyses. We provide a complete account of the state-of-the-art DL strategies per the field of application, as well as major ECG data sources. We also present open research problems, such as the lack of attempts to address the issue of blood pressure variability in training data sets, and point out potential gaps in the design and implementation of DL models. Conclusions We expect that this review will provide insights into state-of-the-art DL methods applied to ECG data and point to future directions for research on DL to create robust models that can assist medical experts in clinical decision-making.
Application of business intelligence for analyzing vulnerabilities to increase the security level in an academic CSIRT

espanolEsta investigacion tuvo como objetivo disenar una solucion para la toma de decisiones mediante Inteligencia de Negocios, que permite adquirir datos e informacion de una amplia variedad de fuentes y utilizarlos en la toma de decisiones en el analisis de vulnerabilidades de un equipo de respuesta ante incidentes informaticos (CSIRT). Este estudio se ha desarrollado en un CSIRT Academico que agrupa varias universidades miembros del Ecuador. Para llevarlo a cabo se aplico la metodologia de Investigacion-Accion con un enfoque cualitativo, dividido en tres fases: Primera, se realizo una evaluacion comparativa de dos herramientas de analisis de intrusos: Passive Vulnerability Scanner y Snort, que son utilizadas por el CSIRT, para verificar sus bondades y verificar si son excluyentes o complementarias; enseguida se han guardado los logs en tiempo real de los incidentes registrados por dichas herramientas en una base de datos relacional MySQL. Segunda, se aplico la metodologia de Ralph Kimball para el desarrollo de varias rutinas que permitan aplicar el proceso “Extraer, Transformar y Cargar” de los logs no normalizados, que luego serian procesados por una interfaz grafica. Tercera, se construyo una aplicacion de software mediante la metodologia Agil Scrum, que realice un analisis inteligente con los logs obtenidos mediante la herramienta Pentaho BI, con el proposito de generar alertas tempranas como un factor estrategico. Los resultados muestran la funcionalidad de esta solucion que ha generado alertas tempranas y que, en consecuencia, ha incrementado el nivel de seguridad de las universidades miembros del CSIRT academico. EnglishThis study aimed at designing a potential solution through Business Intelligence for acquiring data and information from a wide variety of sources and utilizing them in the decision-making of the vulnerability analysis of an Academic CSIRT (Computer Security Incident Response Team). This study was developed in a CSIRT that gathers a variety of Ecuadorian universities. We applied the Action-Research methodology with a qualitative approach, divided into three phases: First, we qualitatively evaluated two intrusion detection analysis tools (Passive Scanner and Snort) to verify their advantages and their ability to be exclusive or complementary; simultaneously, these tools recorded the real-time logs of the incidents in a MySQL related database. Second, we applied the Ralph Kimball's methodology to develop several routines that allowed applying the "Extract, Transform, and Load" process of the non-normalized logs that were subsequently processed by a graphical user interface. Third, we built a software application using Scrum to connect the obtained logs to the Pentaho BI tool, and thus, generate early alerts as a strategic factor. The results demonstrate the functionality of the designed solution, which generates early alerts, and consequently, increases the security level of the CSIRT members.
Enfaixamento em oito como recurso fisioterapêutico para reabilitação do desempenho funcional após acidente vascular encefálico

O Acidente Vascular Encefalico (AVE) pode deixar sequelas neurologicas, motoras e sensitivas, interferindo na funcao dos movimentos e culminando em alteracoes na marcha e no equilibrio. Sendo assim, ha a necessidade de se comprovar cientificamente a eficacia do enfaixamento em oito, uma tecnica de baixo custo que tem como funcao fornecer informacoes proprioceptivas e promover o alinhamento biomecânico do tornozelo, agindo contra os mecanismos que levam ao pe equinovaro. O objetivo deste estudo foi determinar o efeito imediato do enfaixamento em oito como recurso fisioterapeutico para a reabilitacao do desempenho funcional apos AVE. Para tanto, participaram deste estudo 22 pacientes que foram capazes de deambular sozinhos, sem auxilio de orteses, que realizaram o teste de mobilidade funcional Timed Up and Go (TUG), a avaliacao da velocidade da marcha e da escala de Equilibrio de Berg, com e sem o enfaixamento em oito no tornozelo do membro inferior paretico. Quando comparados os resultados antes e apos o enfaixamento em oito, foi evidenciada diferenca estatisticamente significante (p<0,05) em todas as variaveis avaliadas. Apos analise dos resultados, foi possivel concluir que apos uma unica aplicacao do enfaixamento em oito, e possivel identificar melhora estatisticamente significante na velocidade da marcha, mobilidade funcional e equilibrio de hemipareticos cronicos pos-AVE.
Grazing and topography control nutrient pools in low Arctic soils of Southwest Greenland

Soil nutrient pools in the dry low Arctic are likely to be released under climatic change and this bioavailability has the potential to increase both terrestrial and aquatic productions. As well as the direct effect of warming, external disturbances such as nutrient deposition and grazing can also drive ecosystem change. This study in the low Arctic Kangerlussuaq area of southwest Greenland compared soil nutrient pools in terms of both topographic position on a catena and by soil depth in two small catchments with contrasting muskox abundance. We tested the hypotheses that there were differences between soil carbon (C), nitrogen (N) and phosphorus (P) across a soil catena (ridge ‐ slope ‐ valley) and by soil depth (litter ‐ 0–5 cm ‐ 25–30 cm) for the two sites (SS17b, muskox present, versus ‐ SS85, no muskox). Total C and N concentrations of soils were on average lower at SS17b compared to SS85. Moreover, the soil N concentration increased downslope in the catena with higher amounts in the valleys compared to the slopes and ridges. Soil P concentration (0.70 g P kg−1) was similar between catchments; however, litter P content was substantially different. The difference in soil nutrients between the two catchments was most likely due to the presence of muskox at SS17b, and hence grazing associated processes (defecation, altered microbiology and nutrient cycling). This study emphasises the heterogeneity of arctic landscapes and need for ecosystem specific research.
Cardiovascular , Pulmonary and Renal Pathology tPA Activates LDL Receptor-Related Protein 1-Mediated Mitogenic Signaling Involving the p 90 RSK and GSK 3 Pathway

From the Division of Nephrology,* Department of Medicine, Penn State University College of Medicine, Hershey, Pennsylvania; the Department of Pediatrics, Cell Biology, and Physiology, Washington University School of Medicine, St. Louis, Missouri; the Department of Pathology, University of Pittsburgh, Pittsburgh, Pennsylvania; and the Department of Orthopedic Surgery, University of Tokyo Faculty of Medicine, Tokyo, Japan