Miracle-dz/UniFAR-FTUs huggingface dataset:
Complexity of Reachability for Data-Aware Dynamic Systems

A formal model called database manipulating systems was introduced to model data-aware dynamic systems. Its semantics is given by an infinite labelled transition systems where a label can be an unbounded relational database. Reachability problem is undecidable over schemas consisting of either a binary relation or two unary relations. We study the reachability problem under schema restrictions and restrictions on the query language. We provide tight complexity bounds for different combinations of schema and query language, by reductions to/from standard formalism of infinite state systems such as Petri nets and counter systems. Our reductions throw light into the connections between these two seemingly unrelated models.
Spécification et mise en oeuvre d'un protocole de transport orienté Qualité de Service pour les applications multimédias

De nos jours, des applications multimedia presentant de fortes contraintes temporelles, de bande passante et de synchronisation multimedia ont ete concues. Ces applications sont aussi capables de tolerer un service de communication imparfait (c'est-a-dire un service partiellement ordonne et/ou partiellement fiable). Cependant, les services de communication actuellement disponibles au niveau transport ou reseaux ne satisfont pas entierement ces besoins complexes de Qualite de Service (QdS). Cette these propose la conception d'un protocole de transport de nouvelle generation oriente QdS : QoSTP (Quality of Service oriented Transport Protocol). Ce protocole a ete concu afin de fournir un ensemble important de mecanismes de transport repondant precisement aux exigences applicatives, tout en utilisant les ressources et les services reseaux disponibles. En outre, QoSTP a ete specifie dans le cadre d'un contexte standard de QdS capable de fournir un espace semantique extensible et une architecture composable. Ce principe de modelisation facilite l'extension et la specialisation du protocole pour repondre a un grand nombre de besoins applicatifs tout en tenant compte de l'ensemble des services offerts par le systeme de communication. La conception de QoSTP a suivi une methodologie specialisee basee sur le procede unifie de developpement ou Unified Development Process et sur l'utilisation des langages UML et SDL. Cette methodologie propose trois etapes de modelisation : la definition d'un modele global, la definition technique du service transport et la specification comportementale du protocole. Des scenarios specifiques de simulation ont ete etablis afin de valider la specification. Des experiences mettant en œuvre des applications multimedia standards ont permis d'evaluer les performances de ce protocole. Une etude proposant une methodologie de deploiement basee sur des nœuds programmables dans le cadre d'architectures multimedia distribuees a aussi ete realisee.
Military decision modeling with conflict analysis

Conflict analysis is a powerful tool to model a conflict. Military decision is a dynamic decision process. The information perceived by the army commanders is uncertain and dynamic. The question of how to express and utilize uncertain information is a very important factor in decision making. In this paper, the use of conflict analysis to model the dynamic military decision process is first discussed, then a method of ranking feasible outcomes with uncertain information is proposed. Finally, an example is provided to illustrate this method.
Hydra: A Peer to Peer Distributed Training & Data Collection Framework

The world needs diverse and unbiased data to train deep learning models. Currently data comes from a variety of sources that are unmoderated to a large extent. The outcomes of training neural networks with unverified data yields biased models with various strains of homophobia, sexism and racism. Another trend observed in the world of deep learning is the rise of distributed training. Although cloud companies provide high performance compute for training models in the form of GPU's connected with a low latency network, using these services comes at a high cost. We propose Hydra, a system that seeks to solve both of these problems in a novel manner by proposing a decentralized distributed framework which utilizes the substantial amount of idle compute of everyday electronic devices like smartphones and desktop computers for training and data collection purposes. Hydra couples a specialized distributed training framework on a network of these low powered devices with a reward scheme that incentivizes users to provide high quality data to unleash the compute capability on this training framework. Such a system has the ability to capture data from a wide variety of diverse sources which has been an issue in the current scenario of deep learning. Hydra brings in several new innovations in training on low powered devices including a fault tolerant version of the All Reduce algorithm. Furthermore we introduce a reinforcement learning policy to decide the size of training jobs on different machines on a heterogeneous cluster of devices with varying network latencies for Synchronous SGD. The novel thing about such a network is the ability of each machine to shut down and resume training capabilities at any point of time without restarting the overall training. To enable such an asynchronous behaviour we propose a communication framework inspired by the Bittorrent protocol and the Kademlia DHT.
Aspirin for recurrence prevention in bipolar disorder—Promising, yet clinically understudied?

Current available maintenance pharmacotherapy for bipolar disorder (BD) leaves ample room for improvement. Up to 50% of patients with BD do not respond adequately to available treatments and still suffer from manic and/or depressive episodes. In this perspective article, we will give an overview of the neuropharmacodynamics of (low-dose) aspirin, reflect on the published clinical studies and argue that aspirin is a promising, yet understudied option for recurrence prevention This article is protected by copyright. All rights reserved.
Treinamento muscular inspiratório e exercícios respiratórios em crianças asmáticas

OBJETIVO: Avaliar efeitos do treinamento muscular inspiratorio (TMI) e exercicios respiratorios na forca muscular, pico de fluxo expiratorio (PFE) e variaveis de gravidade em criancas asmaticas. METODOS: Estudo analitico, experimental aleatorio em 50 criancas asmaticas alocadas aleatoriamente em dois grupos: um grupo composto de 25 criancas que realizaram TMI em um programa de assistencia e educacao em asma (grupo TMI); e um grupo controle, composto de 25 criancas que foram submetidas apenas as consultas medicas mensais e educacao em asma. O TMI foi realizado com o threshold com a carga de 40% da pressao inspiratoria maxima (PImax). A analise dos resultados foi realizada atraves da analise da variância, teste de qui-quadrado e teste exato de Fisher, sendo considerado significante o valor de p > 0,05. RESULTADOS: Na analise comparativa, observou-se aumento significativo da PImax, da pressao expiratoria maxima (PEmax) e do PFE pre- e pos-intervencao no grupo TMI, como se segue: PImax de -;48,32 ± 5,7 para -;109,92 ± 18 (p < 0,0001); PEmax de 50,64 ± 6,5 para 82,04 ± 17(p < 0,0001); e PFE de 173,6 ± 50 para 312 ± 54 (p < 0,0001). Entretanto, nao houve aumento significativo da PImax e PEmax no grupo controle, somente no PFE, de 188 ± 43,97 para 208,80 ± 44,283 (p < 0,0001). Houve melhora significativa das variaveis de gravidade no grupo TMI (p < 0,0001). CONCLUSOES: O TMI e exercicios respiratorios proporcionam uma melhora na eficiencia mecânica nos musculos respiratorios, no PFE e variaveis de gravidade.
Edge preserving super-resolution algorithm using multi-stage cascaded joint bilateral filter

Super-resolution (SR) algorithms address the inabilities of poor imaging devices, there by producing high quality images with enhanced resolution. We propose a new SR approach which produces sharp high resolution (HR) image using its low resolution (LR) counterparts. The proposed method uses geometric duality for spatially adapting covariance-based interpolation (CBI). To preserve edge information, a multi-stage cascaded joint bilateral filter (MSCJBF) is proposed as an intermediary stage. These edges are incorporated in the high frequency subbands obtained by the stationary wavelet transform (SWT), through nearest neighbor interpolation (NNI) method. Prior to the NNI process, the high frequency subbands undergo two-lobed lanczos interpolation to achieve the desired resolution enhancement. The quantitative and qualitative analysis for various test images prove the superiority of our method.
Low-loss Loaded Line Phase Shifter for Radar Application in X Band

Losses in the phase shifters of phased arrays are one of the main limitations of these reconfigurable antennas. This contribution presents the design and measured results of variable phase shifters on triplicate suspended transmission lines in the microwave X-band for variable pointing radar applications. The antenna assembly remains passive and with a very low level of losses in the power distribution network and the phase shifters. PIN or varactor diodes are used to control the load on the transmission line. Each of these components has advantages and disadvantages that are discussed are presented in the communication.
Few are as Good as Many: An Ontology-Based Tweet Spam Detection Approach

Due to the high popularity of Twitter, spammers tend to favor its use in spreading their commercial messages. In the context of detecting twitter spams, different statistical and behavioral analysis approaches were proposed. However, these techniques suffer from many limitations due to: 1) ongoing changes to Twitter’s streaming API which constrains access to a user’s list of followers/followees; 2) spammer’s creativity in building diverse messages; 3) use of embedded links and new accounts; and 4) need for analyzing different characteristics about users without their consent. To address the aforementioned challenges, we propose a novel ontology-based approach for spam detection over Twitter during events by analyzing the relationship between ham user tweets versus spams. Our approach relies solely on public tweet messages while performing the analysis and classification tasks. In this context, ontologies are derived and used to generate a dictionary that validates real tweet messages from random topics. Similarity ratio among the dictionary and tweets is used to reflect the legitimacy of the messages. Experiments conducted on real tweet data illustrate that message-to-message techniques achieved a low detection rate compared with our ontology-based approach which outperforms them by approximately 200%, in addition to promising scalability for large data analysis.
Efficient Configuration for a Scalable Spiking Neural Network Platform by means of a Synchronous Address Event Representation bus

Hardware architectures for Spiking Neural Networks (SNNs) emulation exhibit accelerated processing thanks to their massive parallelism. However, configuring multichip platforms and setting up a neural application can be an abstract and rigid procedure. In this paper, a simple and efficient centralized configuration solution for a scalable multichip platform based on FPGA and PSoC devices is presented. For this purpose, a dedicated Master Device (MD) node has been used to configure a scalable network of Neuromorphic Devices (NDs). The NDs are general purpose devices which can be programmed to execute any neural algorithm based on spikes with a customized synapse topology. In the proposed approach, the communication channel is re-utilized and the Address Representation Event (AER) protocol modified to configure the entire system. This approximation allows achieving area and power consumption optimization since it eliminates the need to implement a specific instance per chip. Simulations shown demonstrate the performance and temporal characterization of this proposal.
Cost-effectiveness of the Matlab MCH-FP Project in Bangladesh

The cost-effectiveness of maternal-child health (MCH) care and family planning activities in Matlan Bangladesh is assessed at the individual activity level. The assessment employs simplified methods and is based upon data from the period 1986-89. Projects have improved the status of MCH in Matlab by introducing and maintaining a comprehensive package of family planning and MCH services. Activities have been taken in the following areas: family planning immunization maternity care he control of acute respiratory infection (ARI) the control of dysentery vitamin A capsule distribution oral rehydration therapy nutrition education and rehabilitation and curative services. Only recurrent provider costs for service delivery were considered. Cost/death averted and cost/birth averted were measured with respect to a comparison area using cause-specific death and birth rates respectively. Incremental costs and average costs were also measured for some activities. Among activities in the 9 services areas the immunization goals of the Expanded Program of Immunization are closest to being realized. Accordingly the recurrent costs for the activity have increased. Family planning ARI control and the control of dysentery activities otherwise seem to have proved relatively cost-effective. Their comparative cost-effectiveness has resulted from either decreasing incremental costs or by achieving and maintaining low average costs. The findings suggest the need to restructure present resource allocation patterns of activities which have already come close to reaching their respective goals.
Face verification system based on texture feature with single sample per person

This paper introduces a face verification system implementation. In feature extraction, the algorithm is based on a classical texture descriptor, Local Binary Patterns (LBP). In decision making, a new method is proposed to determine the Client Dependent threshold (CD-th). Compared with the traditional fixed threshold, it significantly reduces error rate. Moreover, a symmetry factor is defined to increase frontal face detection rate. And a storage mode is designed to reduce time consumption in feature extraction. The implemented face verification system requires only one sample per person, and overcomes the difficulties appearing in multi-sample face verification system, including image capture problem, storage limitation and time-consumption. The experiments demonstrate the effectiveness of our proposed system.
Cultural evolution, the postbiological universe and SETI

The Biological Universe (Dick 1996) analysed the history of the extraterrestrial life debate, documenting how scientists have assessed the chances of life beyond Earth during the 20th century. Here I propose another option – that we may in fact live in a postbiological universe, one that has evolved beyond flesh and blood intelligence to artificial intelligence that is a product of cultural rather than biological evolution. MacGowan & Ordway (1966), Davies (1995) and Shostak (1998), among others, have broached the subject, but the argument has not been given the attention it is due, nor has it been carried to its logical conclusion. This paper argues for the necessity of long-term thinking when contemplating the problem of intelligence in the universe. It provides arguments for a postbiological universe, based on the likely age and lifetimes of technological civilizations and the overriding importance of cultural evolution as an element of cosmic evolution. And it describes the general nature of a postbiological universe and its implications for the search for extraterrestrial intelligence.
Understanding the Bone in Cancer Metastasis

The bone is the third most common site of metastasis for a wide range of solid tumors including lung, breast, prostate, colorectal, thyroid, gynecologic, and melanoma, with 70% of metastatic prostate and breast cancer patients harboring bone metastasis.1 Unfortunately, once cancer spreads to the bone, it is rarely cured and is associated with a wide range of morbidities including pain, increased risk of fracture, and hypercalcemia. This fact has driven experts in the fields of bone and cancer biology to study the bone, and has revealed that there is a great deal that each can teach the other. The complexity of the bone was first described in 1889 when Stephen Paget proposed that tumor cells have a proclivity for certain organs, where they “seed” into a friendly “soil” and eventually grow into metastatic lesions. Dr. Paget went on to argue that although many study the “seed” it would be paramount to understand the “soil. ” Since this original work, significant advances have been made not only in understanding the cell‐autonomous mechanisms that drive metastasis, but also alterations which drive changes to the “soil” that allow a tumor cell to thrive. Indeed, it is now clear that the “soil” in different metastatic sites is unique, and thus the mechanisms that allow tumor cells to remain in a dormant or growing state are specific to the organ in question. In the bone, our knowledge of the components that contribute to this fertile “soil” continues to expand, but our understanding of how they impact tumor growth in the bone remains in its infancy. Indeed, we now appreciate that the endosteal niche likely contributes to tumor cell dormancy, and that osteoclasts, osteocytes, and adipocytes can impact tumor cell growth. Here, we discuss the bone microenvironment and how it impacts cancer cell seeding, dormancy, and growth. © 2018 American Society for Bone and Mineral Research.
Selected Methods for non-Gaussian Data Analysis

The basic goal of computer engineering is the analysis of data. Such data are often large data sets distributed according to various distribution models. In this manuscript we focus on the analysis of non-Gaussian distributed data. In the case of univariate data analysis we discuss stochastic processes with auto-correlated increments and univariate distributions derived from specific stochastic processes, i.e. Levy and Tsallis distributions. Deep investigation of multivariate non-Gaussian distributions requires the copula approach. A copula is an component of multivariate distribution that models the mutual interdependence between marginals. There are many copula families characterised by various measures of the dependence between marginals. Importantly, one of those are `tail' dependencies that model the simultaneous appearance of extreme values in many marginals. Those extreme events may reflect a crisis given financial data, outliers in machine learning, or a traffic congestion. Next we discuss higher order multivariate cumulants that are non-zero if multivariate distribution is non-Gaussian. However, the relation between cumulants and copulas is not straight forward and rather complicated. We discuss the application of those cumulants to extract information about non-Gaussian multivariate distributions, such that information about non-Gaussian copulas. The use of higher order multivariate cumulants in computer science is inspired by financial data analysis, especially by the safe investment portfolio evaluation. There are many other applications of higher order multivariate cumulants in data engineering, especially in: signal processing, non-linear system identification, blind sources separation, and direction finding algorithms of multi-source signals.
Quantifying Inorganic Nitrogen Assimilation by Synechococcus Using Bulk and Single-Cell Mass Spectrometry: A Comparative Study

Microorganisms drive most of the major biogeochemical cycles in the ocean, but the rates at which individual species assimilate and transform key elements is generally poorly quantified. One of these important elements is nitrogen, with its availability limiting primary production across a large proportion of the ocean. Nitrogen uptake by marine microbes is typically quantified using bulk-scale approaches, such as Elemental Analyzer-Isotope Ratio Mass Spectrometry (EA-IRMS), which averages uptake over entire communities, masking microbial heterogeneity. However, more recent techniques, such as secondary ion mass spectrometry (SIMS), allow for elucidation of assimilation rates at the scale at which they occur: the single-cell level. Here, we combine and compare the application of bulk (EA-IRMS) and single-cell approaches (NanoSIMS and Time-of-Flight-SIMS) for quantifying the assimilation of inorganic nitrogen by the ubiquitous marine primary producer Synechococcus. We aimed to contrast the advantages and disadvantages of these techniques and showcase their complementarity. Our results show that the average assimilation of 15N by Synechococcus differed based on the technique used: values derived from EA-IRMS were consistently higher than those derived from SIMS, likely due to a combination of previously reported systematic depletion as well as differences in sample preparation. However, single-cell approaches offered additional layers of information, whereby NanoSIMS allowed for the quantification of the metabolic heterogeneity among individual cells and ToF-SIMS enabled identification of nitrogen assimilation into peptides. We suggest that this coupling of stable isotope-based approaches has great potential to elucidate the metabolic capacity and heterogeneity of microbial cells in natural environments.
Random Walks and the Temporal Dimension of Risk

The assumption that stock prices follow a random walk has critical implications for investors and firms. Among those implications is the fact that data frequencies and investment horizons are irrelevant (as defined below) when evaluating the risk of a security. However, if stock prices do not follow a random walk, ignoring either issue may lead investors to make misleading decisions. Using data from the first half of _the decade for thirteen European securities markets, I first argue that stock prices in these markets (not surprisingly) do not follow a random walk. Then, I show that investors that assume otherwise are bound to underestimate the total and systematic risk (and overestimate the compound and risk-adjusted returns) of European stocks. The underestimation of risk ranges between . 53% and 2.94% a month, and averages 1.25% a month.