Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Decision Surface Fitness on Dynamic Multilayer Perceptron Networks (DMP1)

The DMP1 (Dynamic Multi-layer Perceptron 1) network training method is based upon a divide and conquer approach which builds networks in the form of binary trees, dynamically allocating nodes and layers as needed. This paper introduces the DMP1 method, and compares the preformance of DMP1 when using the standard delta rule training method for training individual nodes against the performance of DMP1 when using a genetic algorithm for training. While the basic model does not require the use of a genetic algorithm for training individual nodes, the results show that the convergence properties of DMP1 are enhanced by the use of a genetic algorithm with an appropriate fitness function.
Flexible hybrid stores: Constraint-based rewriting to the rescue

Data management goes through interesting times1, as the number of currently available data management systems (DMSs in short) is probably higher than ever before. This leads to unique opportunities for data-intensive applications, as some systems provide excellent performance on certain data processing operations. Yet, it also raises great challenges, as a system efficient on some tasks may perform poorly or not support other tasks, making it impossible to use a single DMS for a given application. It is thus desirable to use different DMSs side by side in order to take advantage of their best performance, as advocated under terms such as hybrid or poly-stores. We present ESTOCADA, a novel system capable of exploiting side-by-side a practically unbound variety of DMSs, all the while guaranteeing the soundness and completeness of the store, and striving to extract the best performance out of the various DMSs. Our system leverages recent advances in the area of query rewriting under constraints, which we use to capture the various data models and describe the fragments each DMS stores.
Résumé de Séquences Temporelles pour le passage à l'échelle d'applications dépendantes du temps

Nous presentons dans ces travaux le concept du ``Resume de Sequence Temporelle'' dont le but est d'aider les applications dependantes du temps a passer a l'echelle sur de grandes masses de donnees. Un Resume de Sequence Temporelle s'obtient en transformant une sequence d'evenements ou les evenements sont ordonnes chronologiquement. Chaque evenement est precisement decrit par un ensemble de labels. Le resume produit est alors une sequence temporelle d'evenements, plus concise que la sequence originale et pouvant se substituer a l'originale dans les applications. Nous proposons un algorithme appele ``TSaR'' pour produire un tel resume. TSaR se base sur les principes de generalisation, de regroupement et de formation de concept. La generalisation permet d'abstraire a l'aide de taxonomies les labels qui decrivent les evenements. Le regroupement permet ensuite d'agglomerer les evenements generalises qui sont similaires. La formation de concept reduit le nombre d'evenements groupes-generalises dans la sequence en representant chaque groupe forme par un unique evenement. Le processus est concu de maniere a preserver la chronologie globale de la sequence d'entree. L'algorithme TSaR produit le resume de maniere incrementale et a une complexite algorithmique lineaire. Nous validons notre approche par un ensemble d'experiences sur une annee d'actualites financieres produites par Reuters.
Endothelial Dysfunction and 24-Hour Ambulatory Blood Pressure Monitoring in Patients with Diabetes

Abstract Arterial hypertension in patients with diabetes plays a main role in the earlier development of diabetic kidney disease (DKD), and endothelial dysfunction is considered to be a process involved in the development of diabetic complications. It is important to study the markers which gives the opportunity to identify DKD in early stage. In this article is presented a study of 24-hour Ambulatory Blood Pressure Monitoring (24hABPM) data in patients with diabetes and its interconnection with estimated glomerular filtration rate and endothelial dysfunction. The endothelial function was determined using the levels of TGF-b1(transforming growth factor-beta1) and VCAM-1 (vascular cell adhesion molecule-1). In our study, we obtained convincing results that complex including endothelial dysfunction and results of 24hABPM can be considered as early signs of DKD progression in patients with diabetes.
Clinical presentation and outcome of venous thromboembolism in COPD

Chronic obstructive pulmonary disease (COPD) is a moderate risk factor for venous thromboembolism (VTE), but neither the clinical presentation nor the outcome of VTE in COPD patients is well known. The clinical presentation of VTE, namely pulmonary embolism (PE) or deep venous thrombosis (DVT), and the outcome at 3 months (death, recurrent VTE or bleeding) were compared between 2,984 COPD patients and 25,936 non-COPD patients included in the RIETE (Registro Informatizado de la Enfermedad TromboEmbólica) registry. This ongoing international, multi-centre registry includes patients with proven symptomatic PE or DVT. PE was the more frequent VTE presentation in COPD patients (n=1,761, 59%). PE presentation was more significantly associated with COPD patients than non-COPD patients (OR 1.64, 95% CI 1.49–1.80). During the 3-month follow-up, mortality (10.8% versus 7.6%), minor bleeding (4.5% versus 2.3%) or first VTE recurrences as PE (1.5% versus 1.1%) were significantly higher in COPD patients than in non-COPD patients. PE was the most common cause of death. COPD patients presented more frequently with PE than DVT. It may explain the worse prognosis of COPD patients, with a higher risk of death, bleeding or VTE recurrences as PE compared with non-COPD patients. Further therapeutic options are needed.
Light as a Limiting Factor for Epilithic Algae in the Supralittoral Zone of Littoral Caves

In a littoral cave system, abiotic environmental properties, such as the intensity and spectral distribution of light, often change going from the exterior to the interior part of the cave, filtering the light and thus creating a deep-sea irradiance setting for marine flora. In this mini-review, we suggest that the supralittoral zone in littoral caves might provide a sanctuary for mesophotic calcifying algae. These abiotic conditions offered an opportunity for normally deep-water mesophotic species to expand their range due to their competitive advantage over shallow, open-water species. Supralittoral calcifying algae are significant for marine biodiversity but are likely to be damaged in the future by ocean acidification. We have summarized important abiotic factors regarding algae settlement and succession processes in the supralittoral zone of littoral caves, including their photosynthetic pigments and habitat requirements. We describe their zonation according to irradiance, and review previous research on epilithic alga¬¬l assemblages in littoral caves. Although we found a great deal of information on the algae of sea caves and littoral caves, no such information was published on the algae of the supralittoral zone of these caves. Nevertheless, some of the studies cited in this review have already set a good conceptual and methodological basis for the ecological research of the supralittoral algal flora of littoral caves.
Radar Target Recognition Method Using Improved Support Vector Machines Based on Polarized HRRPs

Target recognition based on high range resolution (HRR) polarized radar using support vector machines (SVMs) was studied in this paper. A fuzzy membership function was constructed based on SVM decision-making function in order to improve the performance of OAA and OAO classifiers for multi-class target, and HRR radar target recognition method using improved SVM was proposed: First, the polarized radar backscatter echoes were processed by incoherent integration and power-normalized, the location and length of target in echoes were estimated and range profiles of target were interpolated to certain radial length, then polarized profiles were integrated considering the relevancy of range profiles of same target in different polarization state, at last, the improved OAA and OAO classifiers were used for target classification. Simulation experiment results show that the proposed method has the advantage of little capacity of computation and can improve the performance of classifiers effectively
Decreasing distortion using low delay codes for bursty packet loss channels

The strict delay constraints of real-time communication applications in packet networks limit the use of automatic repeat request (ARQ) (retransmission systems) and error correction codes with extensive interleaving and decoding over long intervals. Since packet losses can introduce significant impairments, we study the effectiveness of low delay channel coding techniques to increase transmission quality across links with bursty losses. Specifically, we consider the benefits of the newly discovered class of low delay convolutional codes known as maximally short codes. By analyzing a Gaussian source transmitted over a Gilbert-Elliott channel, we demonstrate that these codes can achieve significant gains in comparison to uncoded transmission schemes or traditional coded schemes employing Reed-Solomon block codes. To complement and validate the theoretical analysis we also present results from informal listening tests with a voice-over-IP application.
Update on Methodologies Available for Ciguatoxin Determination: Perspectives to Confront the Onset of Ciguatera Fish Poisoning in Europe []

Ciguatera fish poisoning (CFP) occurs mainly when humans ingest finfish contaminated with ciguatoxins (CTXs). The complexity and variability of such toxins have made it difficult to develop reliable methods to routinely monitor CFP with specificity and sensitivity. This review aims to describe the methodologies available for CTX detection, including those based on the toxicological, biochemical, chemical, and pharmaceutical properties of CTXs. Selecting any of these methodological approaches for routine monitoring of ciguatera may be dependent upon the applicability of the method. However, identifying a reference validation method for CTXs is a critical and urgent issue, and is dependent upon the availability of certified CTX standards and the coordinated action of laboratories. Reports of CFP cases in European hospitals have been described in several countries, and are mostly due to travel to CFP endemic areas. Additionally, the recent detection of the CTX-producing tropical genus Gambierdiscus in the eastern Atlantic Ocean of the northern hemisphere and in the Mediterranean Sea, as well as the confirmation of CFP in the Canary Islands and possibly in Madeira, constitute other reasons to study the onset of CFP in Europe [1]. The question of the possible contribution of climate change to the distribution of toxin-producing microalgae and ciguateric fish is raised. The impact of ciguatera onset on European Union (EU) policies will be discussed with respect to EU regulations on marine toxins in seafood. Critical analysis and availability of methodologies for CTX determination is required for a rapid response to suspected CFP cases and to conduct sound CFP risk analysis.
A Characterisation of Independence for Competing Markov Chains with Applications to Stochastic Petri Nets a Characterisation of Independence for Competing Markov Chains with Applications to Stochastic Petri Nets

This paper shows that recently obtained product form results for stochastic Petri nets can immediately be obtained as a special case of a simple exclusion mechanism for the product process of a collection of Markov chains. 2 Une charact erisation d'ind ependance pour les cha^ nes de Markov avec comp etition et applications aux r eseaux de Petri stochastiques R esum e Cet article montre que les formes produits r ecemment trouv ees pour les r eseaux de Petri stochastiques peuvent ^ etre etablies comme cas sp ecial d'un simple processus d'exclusion pour le processus produit d'une collection de cha^ nes de Markov.
Remote Rendering and User Interaction on Mobile Devices for Scientific Visualization

Scientific data is typically analyzed using visualizations. Large high-resolution displays can facilitate the analysis process since they offer more screen real estate than desktop monitors, which allows visualizing more data in greater detail and working collaboratively. On the other hand, mobile devices like smartphones and tablets are getting more and more popular but do not have sufficient graphics capabilities for advanced scientific visualizations. In this paper, we discuss a client application for Android devices that allows to remote control a scientific visualization framework. Combining the power of remote rendering with the availability, flexibility, and mobility of mobile devices results in a ubiquitous computing solution for scientific visualization. The user interaction with a large high-resolution display is only one possible application scenario. Other scenarios include presentation of results and remote visualization. The design of our Android application fulfills the requirement of all these application scenarios.
Mechanism of DNA organization by Mycobacterium tuberculosis protein Lsr2

Bacterial nucleoid-associated proteins, such as H-NS-like proteins in Enterobacteriaceae, are abundant DNA-binding proteins that function in chromosomal DNA organization and gene transcription regulation. The Mycobacterium tuberculosis Lsr2 protein has been proposed to be the first identified H-NS analogue in Gram-positive bacteria based on its capability to complement numerous in vivo functions of H-NS. Here, we report that Lsr2 cooperatively binds to DNA forming a rigid Lsr2 nucleoprotein complex that restricts DNA accessibility, similar to H-NS. On large DNA, the rigid Lsr2 nucleoprotein complexes can mediate DNA condensation into highly compact DNA conformations. In addition, the responses of Lsr2 nucleoprotein complex to environmental factors (salt concentration, temperature and pH) were studied over physiological ranges. These results provide mechanistic insights into how Lsr2 may mediate its gene silencing, genomic DNA protection and organization functions in vivo. Finally, our results strongly support that Lsr2 is an H-NS-like protein in Gram-positive bacteria from a structural perspective.
Decentralized privacy protection strategies for location-based services

The rapid development of the integration of cloud computing and location-based services have drawn so much attention currently. With the increasing number of users who own smart phones, significant amount of data that describe user surrounding information and interests have become widely available. However, significant attentions have been raised on the privacy issues. The existing approaches mainly focus on a centralized approach which brings tremendous security concerns. To prevent a centralized query processor from being attached by malicious hackers, we propose a decentralized approach to protect the sensitive location information of users who request for location-based services. Our system provides an approximate computing and an exact computing mechanism for different scenarios and requirements.
Min Morse: Approximability & Applications

We resolve an open problem posed by Joswig et al. by providing an $\tilde{O}(N)$ time, $O(\log^2(N))$-factor approximation algorithm for the min-Morse unmatched problem (MMUP) Let $\Lambda$ be the no. of critical cells of the optimal discrete Morse function and $N$ be the total no. of cells of a regular cell complex K. The goal of MMUP is to find $\Lambda$ for a given complex K. To begin with, we apply an approx. preserving graph reduction on MMUP to obtain a new problem namely the min-partial order problem (min-POP)(a strict generalization of the min-feedback arc set problem). The reduction involves introduction of rigid edges which are edges that demand strict inclusion in output solution. To solve min-POP, we use the Leighton- Rao divide-&-conquer paradigm that provides solutions to SDP-formulated instances of min-directed balanced cut with rigid edges (min-DBCRE). Our first algorithm for min-DBCRE extends Agarwal et al.'s rounding procedure for digraph formulation of ARV-algorithm to handle rigid edges. Our second algorithm to solve min-DBCRE SDP, adapts Arora et al.'s primal dual MWUM. In terms of applications, under the mild assumption1 of the size of topological features being significantly smaller compared to the size of the complex, we obtain an (a) $\tilde{O}(N)$ algorithm for computing homology groups $H_i(K,A)$ of a simplicial complex K, (where A is an arbitrary Abelian group.) (b) an $\tilde{O}(N^2)$ algorithm for computing persistent homology and (c) an $\tilde{O}(N)$ algorithm for computing the optimal discrete Morse-Witten function compatible with input scalar function as simple consequences of our approximation algorithm for MMUP thereby giving us the best known complexity bounds for each of these applications under the aforementioned assumption. Such an assumption is realistic in applied settings, and often a characteristic of modern massive datasets.
Author ' s personal copy Commentary Theory of mind and schizophrenia q

A number of cognitive and behavioral variables influence the performance in tasks of theory of mind (ToM). Since two of the most important variables, memory and explicit expression, are impaired in schizophrenic patients, the ToM appears inconsistent in these patients. An ideal instrument of ToM should therefore account for deficient memory and impaired ability of these patients to explicitly express intentions. If such an instrument is developed, it should provide information that can be used not only to understand the pathophysiology but also to monitor patients. 2008 Elsevier Inc. All rights reserved. Even though the theory of mind (ToM) is recognized as an important cognitive ability (Premack & Woodruff, 1978) and is considered an important determinant of social skill, its scope remains largely undefined. There is therefore, no consensus on the methodological approach that would best reveal deficits. The approach proposed by Bosco and colleagues in the Th.o. m.a.s. assessment scale (Bosco et al., 2009) may have a broader scope and is distinct from that used in other scales. The Th.o. m.a.s. scale is based on the assumption that ToM is essentially a function of a number of dissociable components and each component can be separately assessed. This assumption may give the scale an edge over other scales, particularly for evaluation of psychiatric patients. Most tests use direct methods for evaluation of ToM abilities and all of these tests are generally very efficient in detecting deficits in autistic patients who have significantly impaired social skills (Baron-Cohen, Leslie, & Frith, 1985). The ability of these tests to detect deficit in other conditions is however, less clear. In most conditions, including schizophrenia, investigators have acquired inconsistent data because performance in tests of ToM depends on the integrity of a number of cognitive and behavioral variables. Since most of these variables are compromised at varying degrees in individual patients, task performance is often inconsistent (Brune, 2005). The inconsistency in schizophrenia is revealed in meta-analyses. For example, a recent analysis (Harrington, Siegert, & McClure, 2005) indicated that most (80%) patients with behavioral symptoms are impaired in ToM tasks. About half of those with paranoid symptoms are also impaired but no impairment is reported in patients with delusions and hallucinations. The analysis indicates that the tests elicit fairly consistent results in patients who have behavioral, delusional or hallucinatory symptoms, but detect deficits in only half of the paranoid schizophrenics, sug1053-8100/$ see front matter 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.concog. 2008.10. 008 q Commentary on Bosco et al. (2009). Th.o. m.a.s. : An exploratory assessment of Theory of Mind in schizophrenic subjects. Consciousness and Cognition, 18,
ON THE ENERGETICS OF THE PHOTOSYNTHESES IN GREEN SULFUR BACTERIA

The quantum efficiency of photosynthesis by the green sulfur bacterium, Chlorobium thiosulfatophilum, has been determined in systems in which thiosulfate, tetrathionate, and molecular hydrogen served as electron donors. It was found that about 10 ± 1 quanta are used for the assimilation of 1 molecule of CO2, and that the quantum number is independent of the nature of the electron donor. These results are considered as support for the view that also in the bacterial photosyntheses the primary photochemical reaction consists in the photolysis of H2O, and that the chemical energy released during the oxidation of the electron donor is not utilized for CO2 assimilation. Hence the photosynthetic processes of the green sulfur bacteria are thermodynamically less efficient than is green plant photosynthesis.
Cultural Contexts of Ebola in Northern Uganda

Technical guidelines for the control of Ebola hemorrhagic fever (EHF) indicate that understanding local views and responses to an outbreak is essential. However, few studies with such information exist. Thus, we used qualitative and quantitative methods to determine how local residents of Gulu, Uganda, viewed and responded to the 2000–2001 outbreak of EHF. Results indicated that Acholi people used at least three explanatory models to explain and respond to the outbreak; indigenous epidemic control measures were often implemented and consistent with those being promoted by healthcare workers; and some cultural practices amplified the outbreak (e.g., burial practices). However, most persons were willing to modify and work with national and international healthcare workers.
Moving objects detection method based on a fast convergence Gaussian mixture model

Background Modeling is the normal method on the moving objects detection, it plays a key role in the moving objects detection and tracking, the Gaussian mixture model is one of the most successful methods on the detection. But it converges slowly in the complex scene. This paper proposes a new method named “additive increase” and the “additive decrease” to adjust the weight of the matched distributions and the unmatched distributions respectively. The method can speed up the mixture model convergence process. In order to reduce the noise, “noise restraint base on the adjacent region” approach is using to increase the probability of classifying each pixel correctly during the moving objects detection.
Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA

Concurrent electroencephalograph (EEG) and functional magnetic resonance image (fMRI) led researchers to acquire neuronal activities in detail over the past few decades. Regardless of the advantages of combining these modalities, artifacts posed a greater challenge to attain good quality data. One such problematic artifact which contaminates EEG recordings is Ballistocardiogram (BCG) artifact. A reference-free composite algorithm which combines empirical mode decomposition (EMD) and principal component analysis (PCA) named as EMD-PCA has been introduced in this study. The results show that the algorithm can efficiently reduce the BCG artifact by preserving original neuronal signals. The proposed algorithm showed improvement in reducing the BCG artifact as well as in the preservation of brain activities, when compared with two renowned existing methods that are average artifact subtraction (AAS) and optimal basis set (OBS).