Miracle-dz/UniFAR-FTUs huggingface dataset:
Aplicación de la medida del flujo sanguíneo cerebral, mediante técnicas de ultrasonografía Doppler transcraneal funcional (fTCD), al estudio de la Sensibilización Central al Dolor y los déficits cognitivos en la fibromialgia

espanolLa fibromialgia (FM) es un trastorno de dolor cronico, de etiologia actualmente desconocida, consistente en dolor musculo-esqueletico persistente y generalizado. La opinion actual mas generalizada es que el dolor en la FM tiene que ver con procesos de Sensibilizacion Central, los cuales a su vez se podrian relacionar con los deficits cognitivos encontrados en esta enfermedad. El objetivo de esta Tesis Doctoral fue analizar la dinamica temporal de las modulaciones del flujo sanguineo cerebral (FSC) bajo estimulacion dolorosa y procesamiento aritmetico, mediante el uso de ecografia Doppler transcraneal funcional, en pacientes con FM. Los resultados encontrados anaden evidencia a la idea de que existen alteraciones en el procesamiento del dolor a nivel del SNC en la FM. Estas alteraciones se encuentran moduladas por los factores psicologicos y clinicos presentes en esta enfermedad. Ademas de ello, los resultados ponen de manifiesto la existencia de deterioro cognitivo en la FM, el cual se asocia con alteraciones en las respuestas de FSC durante el procesamiento cognitivo. Estas alteraciones vendrian moduladas a su vez por algunas caracteristicas clinicas de la FM como el dolor, apoyando la idea de que el dolor en la FM podria estar restando recursos a la cognicion, lo que explicaria la alta prevalencia de problemas cognitivos en las pacientes con FM. EnglishFibromyalgia Syndrome (FMS) is a chronic disease characterized by generalized diffuse musculoskeletal pain. The etiology and pathophysiology of FMS remain to be confirmed, although the general consensus is that Central Nervous Sensitization and deficient pain-inhibiting mechanisms may be involved, which in turn might be related to the cognitive deficits found in this disease. The aim of this Thesis was to analyze the temporal dynamics of cerebral blood flow (CBF) modulations, during painful stimulation and arithmetic processing in FMS, using functional transcranial Doppler sonography. Results add evidence to the idea of a Central Nervous Nociceptive Sensitization to Pain in FMS. These alterations are modulated by psychological and medical factors related to this disease. Furthermore, the results show the occurrence of cognitive impairments in FMS, which are associated with alterations in the CBF responses during cognitive processing. Moreover, some clinical features in FMS (like pain) might modulate these CBF abnormalities, supporting evidence regarding the intrusive effect of pain as the origin of these cognitive deficits, which would explain the high prevalence of cognitive impairments in patients with FMS.
Turkey Foreign Trade Interaction with Cross Exchange Rates: Beneath the Currency Wars

In recent years, due to global crisis and economic slowdown, major countries have been pushed to make economic actions. Currency wars have been debated and summoned again as before used in economic history to deal with economic slowdown by developed and emerging countries such as US, China, EU and Japan. Their actions on exchange rate policies would affect their bilateral trade balance as mentioned previous literature. Previous literatures have investigated bilateral country trade balance. This study, differs from previous ones, has investigated whether these countries’ cross exchange rates have an interaction with Turkey foreign trade. Data started from 2012:01 to 2019:09 which was one of milestone of currency wars. By help of ARDL econometric model, different level of stationary series have been used in same model to understand the long run and short run relationships among variables. It seems that, in long run EU, US and China economic actions on currency policies might be affected Turkey’s trade volume, externally. EUR/CNY currency has statistically insignificant results for two analyzed trade market.
A Concept for Standardized Benchmarks for the Evaluation of Control Strategies for Building Energy Management

Given the expected high penetration of renewable energy production in future electricity systems, it is common to consider buildings as a valuable source for the provisioning of flexibility to support the power grids. Motivated by this concept, a wide variety of control strategies for building energy management has been proposed throughout the last decades and especially for the previously mentioned components. However, these algorithms are usually implemented and evaluated for very specific settings and considerations. Thus, a neutral comparison, especially of performance measures, is nearly impossible. Inspired by recent developments in reinforcement learning research, we suggest the use of common environments (i.e. benchmarks) for filling this gap and finally propose a general concept for standardized benchmarks for the evaluation of control strategies for building energy management.
A Logic Optimization Method by Eliminating Redundant Multiple Faults from Higher to Lower Cardinality

: In this paper, we propose a logic optimization method to remove the redundancy in the circuit. The incremental Automatic Test Pattern Generation method is used to ﬁnd the redundant multiple faults. In order to remove as many redundancies as possible, instead of removing the redundant single faults ﬁrst, we clear up the redundant faults from higher cardinality to lower cardinality. The experiments prove that the proposed method can successfully eliminate more redundancies comparing to the redundancy removal command in the synthesis tool SIS.
Character-Oriented Video Summarization With Visual and Textual Cues

With the booming of content “re-creation” in social media platforms, character-oriented video summary has become a crucial form of user-generated video content. However, artificial extraction could be time-consuming with high missing rate, while traditional techniques on person search may incur heavy burden of computing resources. At the same time, in social media platforms, videos are usually accompanied with rich textual information, e.g., subtitles or bullet-screen comments which provide the multi-view description of videos. Thus, there exists a potential to leverage textual information to enhance the character-oriented video summarization. To that end, in this paper, we propose a novel framework for jointly modeling visual and textual information. Specifically, we first locate characters indiscriminately through detection methods, and then identify these characters via re-identification to extract potential key-frames, in which appropriate source of textual information will be automatically selected and integrated based on the features of specific frame. Finally, key-frames will be aggregated as the character-oriented summarization. Experiments on real-world data sets validate that our solution outperforms several state-of-the-art baselines on both person search and summarization tasks, which prove the effectiveness of our solution on the character-oriented video summarization problem.
Contrasting contributions of flows on different time scales to tropical cyclone tracks over the South China Sea

This study investigates the relative contributions of components of flows on multiple time scales to westward and eastward-moving tropical cyclones (TCs) over the South China Sea (SCS) from a local and instantaneous perspective of TC position along the TC tracks during June to October from 1965 to 2015. The total steering flows obtained by vertical integration of winds from 850 to 300 hPa averaged along the entire TC tracks are separated into climatological mean flows, interannual, intraseasonal, and synoptic time scales. For westward-moving TCs, the zonal steering flows are contributed dominantly by climatological mean easterly, whereas the meridional steering flows are contributed dominantly by climatological mean and synoptic-scale southerly winds. In contrast, for eastward-moving TCs, the zonal steering flows are contributed equally by the intraseasonal and synoptic components, while the meridional steering flows are contributed dominantly by climatological mean southerly winds along with the secondary contribution of synoptic-scale southerly winds. This work provides a better understanding of relative contributions of different time scale components of steering flows to the TC motions over the SCS.
Proposing a new method for improving RPL to support mobility in the Internet of things

The internet engineering task force working group has proposed IPv6 Routing Protocol for Low-power and Lossy (RPL) networks for the energy-constrained networks on the Internet of things. This protocol has limitations and does not pay particular attention to mobile nodes. We introduce a new method to improve the RPL protocol with the aim to provide continuous connectivity for mobile nodes. Using additional fields to RPl control packets, a parent is responsible for mobility detection and informs a mobile node for maintaining the energy of it and reduces network overheads. A mobile node chooses a new parent based on metrics namely expected transmission count, received signal strength indicator and residual energy, before disconnection from previous parent. Memory has also been defined that maintains a list of previous parents and when selecting a new parent, a mobile node gets help from this list to select stable parents. They used the Cooja simulator to evaluate the performance of the proposed protocol and the results compared with the RPL and mRPL from the aspect of packet delivery ratio, network overhead, end-to-end delay, energy consumption, and end-to-end throughput under different scenarios. The simulation results showed the effectiveness of the proposed method.
Clustering of Translation via Topic Modeling

In the present study, the authors investigated structural differences between scientific articles arising from their translation from Russian to English. In the course of the research, a modal topic modelling technique was used. Each document in the assembled collection was presented in two versions: English and Russian. As a result of constructing the topic model, the bimodal matrices Φ and Θ were obtained. An analysis of the Φ matrix showed that the topics could be distinguished according to the degree of correspondence between Russian and English terms when considering words in decreasing order of probability. For 90% of the topics, the English words fully corresponded to the Russian words used. Analysis of the Θ matrix showed that for 99% of the documents a topic exists having a value greater than 0.95. Thus, the majority of documents are monotopical. Moreover, this majority does not depend on the language of the document. Although the de facto language of scientific articles nowadays is English, a considerable number of scientific works are initially published in scientists’ respective native languages and only subsequently translated into English in a more complete and in-depth form. Thus, it is possible to speak about the existence of a bilingual corpus of such documents.
Cultural and Natural Resources in Tourism Island: Bibliometric Mapping

Island ecosystems have very specific physical, economic and socio-cultural characteristics, which are shared by most of these ecosystems regardless of their geographical area. These characteristics include well defined geographical boundaries that lead to a greater degree of isolation, lack of economically exploitable resources, great external dependence for consumption, cultural and natural heritage with a high uniqueness level and a high concentration of endemic plant and animal species. All of them are responsible for the high development dependence level linked to the tourism activity of these ecosystems. Thus, island ecosystems are currently an important international tourism destination, where a great diversity of very attractive natural and cultural resources and of great heritage value are concentrated. This fact allows for the development of tourism activities of great heterogeneity among countries or regions of the world that host these island ecosystems. The aim of this research was to identify and analyze, through a bibliometric and bibliographic analysis, the scientific production indexed in the international Scopus database, which addresses the subject of use of cultural and natural resources by tourism in island ecosystems. This scientific mapping allows us to observe the evolution of scientific production in this field of study. The results show that this is a new subject (a large number of transient authors), predominantly affiliated with the United States and Spain. The most followed research lines to date are destination management followed very far by responsible environmental behavior and the impacts of sustainable development. However, the keywords with the highest co-occurrence show that the hot topics are tourism exploitation in the ecotourism field and sustainable tourism development. This research is considered the first bibliometric study carried out which is related to this thematic approach, providing a clear in-depth analysis for researchers and thereby facilitating the approach of future research work.
Cyberbullying Detection in Social Networks: A Multi-Stage Approach

Cyberbullying, deﬁned as the violent harassment of an individual towards a victim in electronic media, is a serious problem nowadays. If not prevented or mitigated, it can lead to aﬀective disorders, poor academic performance, problems in social relationships, and — ultimately — to suicide attempts in youngsters and children. Because manual supervision in social networks (a space where cyberbullying can naturally occur) is laborious, automated approaches for cyberbullying detection are desirable. However, a considerable number of approaches treat this problem as merely aggressive text message detection, without considering the frequency of the harassment. The approach proposed in this work, in contrast, views cyberbullying detection as a process of three consecutive stages: aggressive text message detection, alleged aggressor and victim detection, and cyberbullying case detection. This approach was tested using a dataset extracted from Twitter; the approach obtained an F-score of 0.947 for the positive (cyberbullying) case.
Evo Morales and Electoral Fraud in Bolivia: A Natural Experiment and Discontinuity Evidence

This paper uses a unique data set and a natural experiment based on the shutdown in the official preliminary vote counting system to identify and estimate the size of electoral fraud in the 2019 Bolivian presidential elections. The 2016 Constitutional Referendum and the participation of other political parties serve as controls to estimate various difference-in-differences and difference-in-difference-in-differences specifications. The results show evidence of a statistically significant electoral case of fraud that increased the votes of the incumbent Movimiento al Socialismo and decreased the votes of the runner up Comunidad Ciudadana. We estimate that the extent of the fraud is 2.50% of valid votes, sufficient to change the outcome of the election. We report a break in trend and evidence of fraud beyond the shutdown. Our results are robust to polling-station-level shocks common across 2019 and 2016, as well as 2019 specific shocks. This controls for geography (e.g., rural vs. urban), unobserved voting preferences, voter's last names, and endogeneity in the arrival of the polling stations. We document a statistically significant discontinuous jump in the gap between the incumbent and the runner up during the shutdown.
CLUES model calibration: residual analysis to investigate potential sources of model error

ABSTRACT This paper presents the results of the latest calibrations of the CLUES model for each of total nitrogen, total phosphorus and Escherichia coli. The model provides estimates of in-stream annual loads of these contaminants for every river reach in the New Zealand River Environments Classification and has been used in New Zealand for catchment planning and policy development. CLUES has been calibrated nationally against loads estimated from data collected from water quality monitoring stations located across the country which could lead to parameter bias. To ascertain whether there is any systematic bias, the calibration residuals were evaluated against regional (geographical) location and a range of upstream catchment characteristics, namely land use, soil drainage properties, slope, network order, proportion of baseflow in total stream flow, climate, geology and source of flow. We found that CLUES gives reasonable load estimates at the catchment scale (Nash-Sutcliff efficiencies >0.8 for all the contaminants). However, there was significant uncertainty in the parameterisation. While several significant relationships were found between upstream catchment characteristics and the model residuals, these relationships were weak and are unlikely to point to any systematic bias in the calibration.
A modified shank for below knee prosthesis

A below knee (BK) prosthesis is a device used to compensate for missing limb segments in patients with BK amputations as an aid for locomotive and other daily activities It consists of three main parts: socket, shank, and artificial foot. The shank is merely a shaft of a suitable length to serve as a frame structure to transfer biomechanical forces between the socket and foot. In traditional BK prostheses, the shank is made from rigid metallic or composite material tube (Teflon), while in the current work, a modified version is suggested with internal stiffness and damping characteristics to act as energy storage and shock absorber. A mathematical model was thus employed to analyse the impact behaviour from walking gait, and the main parameters studied were the effective mass of impact, loading rate, and knee pre-swing angular velocity. The modified prosthesis was tested with a BK amputation patient and compared with a traditional prosthesis in force platform and treadmill tests. The results showed some improvement in patient gait parameters; at stance phase, it smoothed the GRF curve; at heel strike, both the effective mass of impact and loading rate increased by 16% and 22%, indicating good impact reduction, and at pre swing, it increased the initial flexion angle and angular velocity by 13% and 15%, respectively, enhancing the swing phase.
A Hybrid Learning Approach to Stochastic Routing

Increasingly available trajectory data enables detailed capture of traffic conditions. We consider an uncertain road network graph, where each graph edge is associated with a travel time distribution, and we study probabilistic budget routing that aims to find the path with the highest probability of arriving within a given time budget. In this setting, a fundamental operation is to compute the travel cost distribution of a path from the cost distributions of the edges in the path. Solutions that rely on convolution generally assume independence among the edges’ distributions, which often does not hold and thus incurs poor accuracy. We propose a hybrid approach that combines convolution and machine learning-based estimation to take into account dependencies among distributions in order to improve accuracy. Next, we propose an efficient routing algorithm that is able to utilize the hybrid approach and that features effective pruning techniques to enable faster routing. Empirical studies on a substantial real-world trajectory set offer insight into the properties of the proposed solution, indicating that it is promising.
A CRIMINALIZAÇÃO DOS PROTESTOS DO MOVIMENTO PASSE LIVRE EM SÃO PAULO (2013-2015)

Este artigo apresenta resultados de uma pesquisa que teve por objetivo: (i) suprir lacunas conceituais e analíticas para o estudo da criminalização dos protestos; (ii) compreender os processos de criminalização e os sentidos de práticas e discursos de instituições e agentes de segurança e justiça criminal, movimentos sociais, manifestantes e imprensa, empiricamente verificados na análise de dinâmicas, discursos, documentos e procedimentos administrativos e judiciais de repressão dos protestos. O estudo é focado especificamente nos protestos liderados pelo Movimento Passe Livre em junho de 2013 e janeiro de 2015 na cidade de São Paulo. Por meio de uma análise qualitativa aberta e interpretativa de fluxos processuais, discursos e eventos de protesto, buscou-se identificar a ocorrência dos processos de criminalização, criminação e incriminação de manifestantes e atos de protesto por agentes e instituições estatais.
Optimal Duplex Mode Selection for D2D-Aided Underlaying Cellular Networks

Both Device-to-device (D2D) and full-duplex (FD) have been widely recognized as spectral efficient techniques in the fifth-generation wireless communications systems. By enabling FD mode in D2D communications, the attainable spectrum efficiency can be (in theory) up to twice as high as that of conventional half-duplex (HD) mode D2D technology, provided that the self-interference signal in the former can be sufficiently suppressed. Considering the fact that FD technology does not always outperform the HD technology in arbitrary channel condition, we will delve into the FD gain as well as its preconditions for acquisition in this paper. In particular, the performance of D2D-aided underlaying cellular networks is investigated by assuming that the D2D users are capable of operating at both HD and FD modes. Under a given user workload, the sum throughput in each DU is shown to be always improved by activating D2D links despite an extra DU-induced interference could be imposed on its co-spectrum cellular users. Numerical results show that the FD-D2D mode exhibits its superiority in terms of sum throughput than the HD-D2D mode in a light-workload scenario even if a non-ideal SI cancellation has been implemented in the former, but the latter pulls back a game in a heavy-workload scenario. Furthermore, to maximize the sum throughput, an appropriate mode-selection scheme (i.e., by choosing either FD or HD mode in the current time-slot for each individual D2D user) should be implemented for sufficiently exploiting the FD gain according to the instantaneous radio frequency environment.
Near reef abundance and on–offshore distribution of tuna larvae around Minicoy Island in Lakshadweep Sea, India

ABSTRACT Near reef abundance and coast–offshore distribution of tuna larvae around Minicoy Island were studied based on three cruises carried out on board FORV Sagar Sampada during 2014–15. The samples were collected by oblique tows using bongo twin nets (300 micron) for three seasons (Fall inter-monsoon (FIM), Spring inter-monsoon (SIM) and Summer monsoon (SM)) in six on–offshore stations ranging from 1 to 20 km off-shore of the Minicoy. Results indicated that the tuna larvae aggregate in the near reef waters and total tuna larvae abundance (all the species combined) shows a decreasing trend towards off-shore. Tuna larvae are found to be more abundant during SM and FIM. Comparison of the species-wise variation in tuna larvae for one season (SM) indicated that the larvae of Euthunnus affinis (32.5%) dominated among the tuna species, followed by Auxis spp. (31.6%), Thunnus spp. (3.9%) and Katsuwonus pelamis (2.7%). A pattern of highest larvae abundance in the near reef areas was observed except for Thunnus larvae. GAM indicated that mean seawater temperature and mean seawater salinity are the major environmental factors that significantly influence the larvae abundance, particularly for Thunnus followed by Katsuwonus pelamis, E. affinis and Auxis spp. The study confirms that the environmental parameters show high variation between stations and among transects as a result of the complex oceanographic characteristics around the islands. Further studies with better understanding of the larvae dynamics and their association with the environmental parameters including physical processes are essential to elucidate these relationships more clearly.