Miracle-dz/UniFAR-FTUs huggingface dataset:
Rotavirus Stimulates Release of Serotonin (5-HT) from Human Enterochromaffin Cells and Activates Brain Structures Involved in Nausea and Vomiting

Rotavirus (RV) is the major cause of severe gastroenteritis in young children. A virus-encoded enterotoxin, NSP4 is proposed to play a major role in causing RV diarrhoea but how RV can induce emesis, a hallmark of the illness, remains unresolved. In this study we have addressed the hypothesis that RV-induced secretion of serotonin (5-hydroxytryptamine, 5-HT) by enterochromaffin (EC) cells plays a key role in the emetic reflex during RV infection resulting in activation of vagal afferent nerves connected to nucleus of the solitary tract (NTS) and area postrema in the brain stem, structures associated with nausea and vomiting. Our experiments revealed that RV can infect and replicate in human EC tumor cells ex vivo and in vitro and are localized to both EC cells and infected enterocytes in the close vicinity of EC cells in the jejunum of infected mice. Purified NSP4, but not purified virus particles, evoked release of 5-HT within 60 minutes and increased the intracellular Ca2+ concentration in a human midgut carcinoid EC cell line (GOT1) and ex vivo in human primary carcinoid EC cells concomitant with the release of 5-HT. Furthermore, NSP4 stimulated a modest production of inositol 1,4,5-triphosphate (IP3), but not of cAMP. RV infection in mice induced Fos expression in the NTS, as seen in animals which vomit after administration of chemotherapeutic drugs. The demonstration that RV can stimulate EC cells leads us to propose that RV disease includes participation of 5-HT, EC cells, the enteric nervous system and activation of vagal afferent nerves to brain structures associated with nausea and vomiting. This hypothesis is supported by treating vomiting in children with acute gastroenteritis with 5-HT3 receptor antagonists.
Intelligent in-vehicle touchscreen aware of the user intent for reducing distractions: a pilot study

Intent-aware displays aim to simplify and expedite the task of selecting an icon displayed on an in-vehicle touchscreen via a free hand pointing gesture, thus, minimise the incurred effort and/or distractions. This is achieved by determining the user intent, with high confidence, notably early in the pointing gesture. This paper describes a pilot evaluative study of the benefits of employing the intent-aware display solution by assessing the workload associated with using an in-vehicle interactive display and the time required to accomplish the undertaken pointing tasks, with and with-out the intent prediction capability. The presented results are based on data collected in an instrumented car for 18 participants. They demonstrate that an intent-aware dis-play significantly reduces the workload/effort of using an in-vehicle touchscreen (it is halved) and the duration of a pointing task (it is reduced by over 20%).
Run-Time Management of Data Intensive Web Sites

An increasing number of web sites have their data extracted from relational databases. Several commercial products and research prototypes have been moving in the direction of declarative specification of the structure and content of sites. Specifically, the entire site is specified using a collection of queries describing the site's nodes (corresponding to web pages and the data contained in them) and edges (corresponding to the hyperlinks). Given this paradigm, an important issue is when to compute the site's pages. In one extreme approach, the site is precomputed in advance, while in the other extreme, the queries necessary to construct a given page are computed on demand. Both approaches have their obvious drawbacks: large space and maintenance overhead in the first approach, and poor run-time performance and unnecessary repeated computations in the second. In this paper we consider the problem of automatically optimizing the run-time management of declaratively specified web sites. In our approach, given a declarative site specification and constraints on the application, an efficient run-time evaluation policy is derived automatically. An evaluatio- n policy specifies which data to compute at a given browser request. We describe several optimizations that can be used in run-time policies, focusing mostly on optimizations that exploit the of the web site definition. We evaluate experimentally the impact of these optimizations on a web site derived from the TPC/D database. Finally, we describe a heuristic-based optimization algorithm which compiles a declarative site specification into a run-time policy that incorporates our novel optimizations.
Ofloxacin-resistant Vibrio cholerae O139 in Hong Kong.

These are the first reported human cases of West Nile fever in Central Europe (5); an extensive outbreak occurred in Romania in 1996, with approximately 500 patients hospitalized and a 4% to 8% fatality rate (6,7). West Nile virus should be viewed as a potential agent of local sporadic cases, clusters, or outbreaks, even in temperate Europe. Environmental factors (including human activities) that enhance vector population densities (heavy rains followed by floods, irrigation, higher than usual temperatures due to global warming) might produce an increased incidence of West Nile fever and other new or reemerging mosquito-borne diseases. Surveillance for West Nile fever should monitor population density and infection rate of principal vectors, antibodies in vertebrates and exposed human groups, and routine diagnosis of human infections.
Disulfide Bonding in Neurodegenerative Misfolding Diseases

In recent years an increasing number of neurodegenerative diseases has been linked to the misfolding of a specific protein and its subsequent accumulation into aggregated species, often toxic to the cell. Of all the factors that affect the behavior of these proteins, disulfide bonds are likely to be important, being very conserved in protein sequences and being the enzymes devoted to their formation among the most conserved machineries in mammals. Their crucial role in the folding and in the function of a big fraction of the human proteome is well established. The role of disulfide bonding in preventing and managing protein misfolding and aggregation is currently under investigation. New insights into their involvement in neurodegenerative diseases, their effect on the process of protein misfolding and aggregation, and into the role of the cellular machineries devoted to disulfide bond formation in neurodegenerative diseases are emerging. These studies mark a step forward in the comprehension of the biological base of neurodegenerative disorders and highlight the numerous questions that still remain open.
TLLB: Two-Level Load Balanced Algorithm for Static Meta-Task Scheduling in Grid Computing

Doing computation on the collection of computer resources from multiple locations to reach a common goal is knows as grid computing. Task scheduling is very important problem in complex grid environment. Prior, there are numerous number of algorithms were proposed to do effective task scheduling. Among them the min-min algorithm is simple and well known scheduling algorithm. Even it works efficiently, some drawbacks in this with respect of load balancing and in resource utilization. To overcome these drawbacks, a new Two Level Load Balanced (TLLB) grid scheduler algorithm is proposed. In First Level min-min algorithm is used to create ITQ and in Second Level a new Transformation technique is used to reschedule. The performance analyses show that the proposed algorithm improves the performance in both make span and effective utilization of resources.
Natural Language Processing and Language Learning

As a relatively young field of research and development that began with work on crypt-analysis and machine translation around 50 years ago, natural language processing (NLP) is concerned with the automated processing of human language. Keywords: CALL; computational linguistics; corpora; ICALL; natural language processing
Material transformation designing shape changing interfaces enabled by programmable material anisotropy

This thesis takes a material perspective on designing transformable interfaces. The structure of material and mechanical properties such as stiffness, can determine not only its static performances, but also, with the help of external forces, support dynamic shape change. By encoding structural or stiffness distribution in the actuated materials, we can partially offload the shape-changing control from actuators (digital) to the material itself (analogue), in order to achieve expressive transformations that current modularized actuation system cannot easily provide. The implementation of this thesis will be three series of material primitives and three application prototypes that demonstrate the real world potential of this research.
FlexRay™ electrical physical layer: Theory, components and examples

Modern passenger cars are no longer imaginable without using technologies to broadcast local acquired data. The vehicle speed for example is used by many well-known functions: the anti-blocking system, the radio, the dash board, the cruise control, the electronic stability program etc. Usually these local acquired data is distributed among vehicle's electronic control units by various electrical serial communication systems. The paper introduces one of their newest designs named FlexRay™. The development of FlexRay™ began in the early nineties of the last century driven by the requirements expected for drive-by-wire systems. The referenced section focuses on the FlexRay™ electrical physical layer; it can be seen as evolution of the widely-used CAN electrical physical layer. This electrical physical layer evolution had been driven mainly by one kernel requirement: enabling a tenfold maximal communication speed. The broad range from topologies and hardware components up to simulation approaches is covered. Selected comparisons between CAN and FlexRay™ support the comprehensibility of the indicated evolution approach.
Adenovirus infection after allogeneic stem cell transplantation

Adenovirus infection after allogeneic hematopoietic stem cell transplantation (HSCT) is an emerging pathogen causing relevant morbidity and mortality, with preponderance in children. During the last years, basic research on the biology of the virus and host immune response ameliorated the diagnostic, surveillance, and therapeutic strategies. Risk factors for infection commonly have an impact on T-cell reconstitution, such as T-cell depleted graft, unrelated or HLA-mismatched donor transplantation, and GvHD. Weekly surveillance by PCR in stool and blood till day 100 or longer post-HSCT and pre-emptive therapy with cidofovir are the mainstay of the current approach to adenoviral infections post-HSCT. Since a sufficient host T-cell response is essential to clear the virus, diagnostic procedures for detection of virus-specific T-cells have recently been developed to assess the risk of the infection. Furthermore, adoptive immunotherapy is a new treatment option for patients with absent specific T-cell response and present systemic adenoviral infection.
D-stability and D-stabilization of descriptor discrete time-delay systems with poytopic uncertainties

This paper is concerned with the problems of D-stability and D-stabilization for descriptor discrete time-delay systems with poytopic uncertainties. In terms of LMIs, sufficient conditions based on parameter-dependent Lyapunov functions are presented. These conditions guarantee all the poles of a corresponding system in a specified circular region. A numerical example illustrates the validity of our approach.
RIGOROUS ENCLOSURES OF SLOW MANIFOLDS

Slow-fast dynamical systems have two time scales and an explicit parameter representing the ratio of these time scales. Locally invariant slow manifolds along which motion occurs on the slow time scale are a prominent feature of slow-fast systems. This paper introduces a rigorous numerical method to compute enclosures of the slow manifold of a slow-fast system with one fast and two slow variables. A triangulated first order approximation to the two dimensional invariant manifold is computed “algebraically”. Two translations of the computed manifold in the fast direction that are transverse to the vector field are computed as the boundaries of an initial enclosure. The enclosures are refined to bring them closer to each other by moving vertices of the enclosure boundaries one at a time. As an application we use it to prove the existence of tangencies of invariant manifolds in the problem of singular Hopf bifurcation and to give bounds on the location of one such tangency.
Analysing and Optimizing Strongly Typed Object-oriented Languages: A Generic Approach and its Application to Oberon-2

Object oriented programming is going to replace the imperative programming paradigm as the state of the art paradigm for large industrial software projects The bene ts o ered however come at the price of intricate new problems for optimizing compilers In contrast to the imperative paradigm where abstract interpretation is well established as a uniform and theoretically well founded framework for analysis and optimization for the object oriented paradigm the situation is still characterized by approaches being quite speci c or ad hoc Here we show how to enhance the framework of abstract interpretation to the object oriented setting considering an Oberon like language for illustration We arrive at a generic framework whose generality and exibility is demonstrated by a hierarchy of type analysis algorithms of di erent power and precision Their results can directly be used for various optimizations like inlining type bound procedure calls or eliminating unnecessary type tests and assertions Moreover we show how a previously proposed approach for type analysis by Corney and Gough which is restricted to the intraprocedural setting can be modeled in our approach and even interprocedurally be enhanced underlining thus the generality and exibility of our approach
Nanotechnology versus stem cell engineering: in vitro comparison of neurite inductive potentials

Purpose Innovative nerve conduits for peripheral nerve reconstruction are needed in order to specifically support peripheral nerve regeneration (PNR) whenever nerve autotransplantation is not an option. Specific support of PNR could be achieved by neurotrophic factor delivery within the nerve conduits via nanotechnology or stem cell engineering and transplantation. Methods Here, we comparatively investigated the bioactivity of selected neurotrophic factors conjugated to iron oxide nanoparticles (np-NTFs) and of bone marrow-derived stem cells genetically engineered to overexpress those neurotrophic factors (NTF-BMSCs). The neurite outgrowth inductive activity was monitored in culture systems of adult and neonatal rat sensory dorsal root ganglion neurons as well as in the cell line from rat pheochromocytoma (PC-12) cell sympathetic culture model system. Results We demonstrate that np-NTFs reliably support numeric neurite outgrowth in all utilized culture models. In some aspects, especially with regard to their long-term bioactivity, np-NTFs are even superior to free NTFs. Engineered NTF-BMSCs proved to be less effective in induction of sensory neurite outgrowth but demonstrated an increased bioactivity in the PC-12 cell culture system. In contrast, primary nontransfected BMSCs were as effective as np-NTFs in sensory neurite induction and demonstrated an impairment of neuronal differentiation in the PC-12 cell system. Conclusion Our results evidence that nanotechnology as used in our setup is superior over stem cell engineering when it comes to in vitro models for PNR. Furthermore, np-NTFs can easily be suspended in regenerative hydrogel matrix and could be delivered that way to nerve conduits for future in vivo studies and medical application.
Semi-supervised intrusion detection via online laplacian twin support vector machine

Network security has become one of the well-known concerns in the last decades. Machine learning techniques are robust methods in detecting malicious activities and network threats. Most previous works learn offline supervised classifiers while they require large amounts of labeled examples and also should update models because the data change over time in real world applications. To alleviate these problems, we propose a novel online version of laplacian twin support vector machine classifier, which can exploit the geometry information of the marginal distribution embedded in unlabeled data to construct a more accurate and faster semi-supervised classifier. The results of experiments on large network datasets show that Online Lap-TSVM combined by two nonparallel hyper planes improves the accuracy with the comparable computing time and storage to Lap-TSVM.
Resource-constrained non-operational testing of software

In "classical" testing approaches, "learning" is said to occur if testers dynamically improve the efficiency of their testing as they progress through a testing phase. However, the pressures of modern business and software development practices seem to favor an approach to testing which is very akin to a "sampling without replacement" of a relatively limited number of pre-determined structures and functions conducted under significant schedule and resource constraints. The primary driver is often the desire to "cover" ONLY previously "untested" functions, operations or code constructs, and to meet milestones. We develop and evaluate a model that describes the fault detection and removal process in such an environment. Results indicate that in environments where "coverage" based testing is promoted, but resources and decisions are constrained, very little dynamic "learning" takes place, and that it may be an artifact of program structure or of the test case sequencing policy.
Childhood adversity and allostatic overload of the hypothalamic–pituitary–adrenal axis: A vulnerability model for depressive disorders

Abstract Childhood adversity is associated with increased risk for onset of depressive episodes. This review will present evidence that allostatic overload of the hypothalamic–pituitary–adrenal axis (HPAA) partially mediates this association. The HPAA is the physiological system that regulates levels of the stress hormone cortisol. First, data from animals and humans has shown that early environmental adversity is associated with long-term dysregulation of the HPAA. This may occur due to permanent epigenetic modification of the glucocorticoid receptor. Second, data from humans has demonstrated that HPAA dysregulation is associated with increased risk of future depression onset in healthy individuals, and pharmacological correction of HPAA dysregulation reduces depressive symptoms. HPAA dysregulation may result in corticoid-mediated abnormalities in neurogenesis in early life and/or neurotoxicity on neural systems that subserve emotion and cognition.
New high-speed prime-factor algorithm for discrete Hartley transform

Fast algorithms for computing the DHT of short transform lengths (N = 2, 3, 4, 5, 7, 8, 9 and 16) are derived. A new prime-factor algo- rithm is also proposed to compute the long-length DHTs from the short-length DHT algorithms. The short-length algorithms (except for N = 8 and N = 16) are such that the even and the odd parts of the DHT components are obtained directly, without any additional computation. This feature of the short-length algorithms makes the proposed prime-factor DHT algorithm more attractive and efficient. It is found that the proposed algorithm is more efficient compared to the radix-2 FHT in terms of the computational requirements, as well as the execution time for transform lengths higher than 30. It is also observed that the number of operations required for the computation of DHT by the prime-factor FFT algorithm for real-valued data is the same as those of the proposed algo- rithm for certain transform lengths, e.g. N = 30, 60, 252 etc., which do not contain 8 or 16 as a cofactor. However, for all other transform lengths the proposed algorithm has a lower computa- tional complexity. It is further observed that the proposed algorithm is faster than the prime-factor FFT algorithm for real-valued series.
Positive selection identifies an in vivo role for FimH during urinary tract infection in addition to mannose binding

FimH, the type 1 pilus adhesin of uropathogenic Escherichia coli (UPEC), contains a receptor-binding domain with an acidic binding pocket specific for mannose. The fim operon, and thus type 1 pilus production, is under transcriptional control via phase variation of an invertible promoter element. FimH is critical during urinary tract infection for mediating colonization and invasion of the bladder epithelium and establishment of intracellular bacterial communities (IBCs). In silico analysis of FimH gene sequences from 279 E. coli strains identified specific amino acids evolving under positive selection outside of its mannose-binding pocket. Mutating two of these residues (A27V/V163A) had no effect on phase variation, pilus assembly, or mannose binding in vitro. However, compared to wild-type, this double mutant strain exhibited a 10,000-fold reduction in mouse bladder colonization 24 h after inoculation and was unable to form IBCs even though it bound normally to mannosylated receptors in the urothelium. In contrast, the single A62S mutation altered phase variation, reducing the proportion of piliated cells, reduced mannose binding 8-fold, and decreased bladder colonization 30-fold in vivo compared to wild-type. A phase-locked ON A62S mutant restored virulence to wild-type levels even though in vitro mannose binding remained impaired. Thus, positive selection analysis of FimH has separated mannose binding from in vivo fitness, suggesting that IBC formation is critical for successful infection of the mammalian bladder, providing support for more general use of in silico positive selection analysis to define the molecular underpinnings of bacterial pathogenesis.
Predicting the Three Major Dimensions of the Learner-s Emotions from Brainwaves

This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner's emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners' three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner's emotions and integrate it into a brainwave- sensing Intelligent Tutoring System.