Miracle-dz/UniFAR-FTUs huggingface dataset:
The human enteric nervous system

Decades of work in animal models have demonstrated that the enteric nervous system (ENS) plays a key role in controlling gut functions. Recent advances made it possible to extend such studies to the ENS of man in health and even in disease. Such studies have already provided new insights into the pathophysiology of inflammatory and possibly functional bowel diseases. Studies on human ENS revealed both important similarities and differences between the ENS of man and of experimental animals. Here we summarize the current state of knowledge of the electrophysiology and neurochemistry of the human ENS, including relevant reflex mediated functions in the human gut. Additionally, we review disease associated changes in human ENS properties. Finally, we highlight some research areas that hold special promise in advancing our understanding of the human ENS.
A novel approach towards QoS provisioning in delay-sensitive flows over wireless networks

Wireless networks are poised to support a myriad of existing as well as emerging multimedia streaming applications. With increase in use of wireless local area networks (WLANs), ranging from simple data transfer to bandwidth-intense, delay-sensitive, and loss-tolerant multimedia applications, issues regarding quality of service (QoS) have become a major research endeavor. Several challenges posed by robust video streaming over 802.11 WLANs include coping with packet losses caused by network buffer overflow, link erasures, or deadline misses. A major observation is that the retry limit settings of the MAC layer can be optimized in a way such that the overall packet loss caused by link erasure, buffer overflow, or deadline miss is minimized. In this paper, we propose a novel solution for minimizing packet loss in multimedia applications over WLANs. Simulation results justify the improved quality of the received video based on our proposed approach.
Prosodic imitation as a means of receiving and displaying a critical stance in classroom interaction

Abstract This paper investigates (Finnish) classroom interaction and explores the displays of stance and the rules of emotion in this institutional multi-party setting. The main focus of the analysis is on teacher's imitation of students' talk. The starting point is to analyze stance as a situated practice in the sequential organization of interaction, in particular in sequences that contain criticism. Although it is quite common for teachers and students to criticize each other's activities during (pedagogic) interaction, criticism is treated more or less as a delicate issue. Participants deal with the emotional elements of criticism by using, for example, various prosodic practices, including prosodic imitation. Prosodic imitation is a frequent practice among students, but the teachers imitate students' turns quite rarely and only in specific sequential environments. Teachers repeat and imitate the prosodically marked students' answers that occur subsequent to teachers' critical comments on students' behavior, and the students' self-selected turns that mimic teacher-talk and convey implicit criticism in their prosody. With the help of these prosodic practices the participants are able to receive and deal with a critical stance without jeopardizing the norms, frameworks, and “rules of emotion” valid in this specific institutional setting.
Non-uniform channelization methods for next generation SDR PMR base stations

Channelization in multi-standard Software-Defined Radio base stations presents a significant challenge. In this paper, two different channelization structures designed for a multi-standard SDR base station are studied. As a basis for comparing their computational efficiency and reconfigurability, both are applied to a specific case study of a TETRA and TEDS standards base station. Uniform narrow band spectrum division followed by channel recombination demonstrates greater flexibility than a non-uniform parallel spectrum division alternative. However, computational advantages between both structures depend on the channel allocation patterns considered.
Quantitative Evaluation of Performance and Validity Indices for Clustering the Web Navigational Sessions

Clustering techniques are widely used in Web Usage Mining to capture similar interests and trends among users accessing a Web site. For this purpose, web access logs generated at a particular web site are preprocessed to discover the user navigational sessions. Clustering techniques are then applied to group the user session data into user session clusters, where intercluster similarities are minimized while the intra cluster similarities are maximized. Since the application of different clustering algorithms generally results in different sets of cluster formation, it is important to evaluate the performance of these methods in terms of accuracy and validity of the clusters, and also the time required to generate them, using appropriate performance measures. This paper describes various validity and accuracy measures including Dunn's Index, Davies Bouldin Index, C Index, Rand Index, Jaccard Index, Silhouette Index, Fowlkes Mallows and Sum of the Squared Error (SSE). We conducted the performance evaluation of the following clustering techniques: k-Means, k-Medoids, Leader, Single Link Agglomerative Hierarchical and DBSCAN. These techniques are implemented and tested against the Web user navigational data. Finally their performance results are presented and compared.
A Murine Model of Isolated Cardiac Steatosis Leads to Cardiomyopathy

Lipid accumulation in the heart is associated with obesity and diabetes mellitus and may play an important role in the pathogenesis of heart failure seen in this patient population. Stored triglycerides are synthesized by the enzyme diacylglycerol acyl transferase (DGAT). We hypothesized that forced expression of DGAT1 in the cardiac myocyte would result in increased lipid accumulation and heart dysfunction. A cardiac myocyte–selective DGAT1 transgenic mouse was created and demonstrated increased lipid accumulation in the absence of hyperglycemia, plasma dyslipidemia or differences in body weight. Over time, expression of DGAT1 in the heart resulted in the development of a significant cardiomyopathy. Echocardiography revealed diastolic dysfunction with increased early mitral inflow velocity to late mitral inflow velocity ratio and decreased deceleration time, suggesting a restrictive pattern in the transgenic mice. Moderate systolic dysfunction was also seen at 52 weeks. Histological analysis showed increased cardiac fibrosis and increased expression of procollagen type 1A, matrix metalloproteinase 2, and tissue inhibitor of matrix metalloproteinase 2 in the transgenic mice. Mitochondrial biogenesis was reduced in the transgenic hearts, as was expression of cytochrome c oxidase 1 and cytochrome c. Expression of key transcription factors important in the regulation of mitochondrial biogenesis were reduced. These findings suggest that triglyceride accumulation, in the absence of systemic metabolic derangement, results in cardiac dysfunction and decreased mitochondrial biogenesis.
Routing and Admission Control in IEEE 802.16 Distributed Mesh Networks

QoS provisioning in wireless mesh networks has been known to be a challenging issue. In this paper, we propose a new routing method (using SWEB as metrics) that is well-suited in IEEE 802.16 distributed, coordinated mesh mode. Also, an admission control algorithm (TAC) which utilizes the token bucket mechanism is proposed. The token bucket is used for controlling the traffic patterns for easy estimating the bandwidth required by a connection. In the TAC algorithm, we apply the bandwidth estimation by taking into account the hop count and delay requirements of real-time traffics. TAC is designed to guarantee the delay requirements of real-time traffics, and avoid the starvations of low priority traffics. With the proposed routing metrics, the admission control algorithm and the inherent QoS support for the IEEE 802.16 mesh mode, a QoS-enabled environment can be established. Finally, extensive simulations are carried out to validate our algorithms, and show good performance results.
Genetic basis of olfactory communication in primates

The genes involved in olfactory communication in mammals via the vomeronasal system are summarized, and studies investigating these genes in primates are reviewed. Only five potentially functional vomeronasal receptor genes (V1RL s) have been found in humans, and only one of these (V1RL1) has been studied in other primates. V1RL1 has become a pseudogene repeatedly during primate evolution, but patterns of natural selection on primate V1RL genes demonstrate that this gene family diverged under natural selection throughout at least part of primate evolution. Evolution of the TRP2 gene, which encodes for an ion channel that is important in vomeronasal organ (VNO) signalling, strongly suggests that this signalling function was lost in ancestral Catarrhines. Overall, much work remains to be done to elucidate the repertoire of genes that are involved in pheromonal communication, particularly in Strepsirhines. Such studies promise unique insights into the evolution of this modality. Am. J. Primatol. 68:559–567, 2006. © 2006 Wiley‐Liss, Inc.
Enterprise network Node Discovery and Topology Analysis : An experience Report

Most existing network management systems have partial support for network discovery and topology analysis, but are usually either vendor-specific or lack functionality for a flexible network model comparison. We posit an architecture for versatile network discovery and analysis, which supports (1) efficient creation and synchronization of network topology information (2) accurate recognition of new, replaced and upgraded nodes, including rogue nodes that may exhibit malicious behavior, and (3) provides an extension of an existing vendor-neutral enterprise network management and provisioning system developed at Netadmin Systems AB. The approach described in this paper is a step towards a more flexible way of tackling the increasingly difficult problem of node discovery and topology analysis in enterprise networks. An initial evaluation of our implementation shows evidence of accurate discovery and classification of unmatched hosts in a live customer production network with over 400 nodes, and presents data on performance and scalability levels.
Single-Molecule Patch-Clamp FRET Microscopy Studies of NMDA Receptor Ion Channel Dynamics in Living Cells: Revealing the Multiple Conformational States Associated with a Channel at Its Electrical Off State

Conformational dynamics plays a critical role in the activation, deactivation, and open–close activities of ion channels in living cells. Such conformational dynamics is often inhomogeneous and extremely difficult to be directly characterized by ensemble-averaged spectroscopic imaging or only by single channel patch-clamp electric recording methods. We have developed a new and combined technical approach, single-molecule patch-clamp FRET microscopy, to probe ion channel conformational dynamics in living cell by simultaneous and correlated measurements of real-time single-molecule FRET spectroscopic imaging with single-channel electric current recording. Our approach is particularly capable of resolving ion channel conformational change rate process when the channel is at its electrically off states and before the ion channel is activated, the so-called “silent time” when the electric current signals are at zero or background. We have probed NMDA (N-methyl-d-aspartate) receptor ion channel in live HEK-293 cell, especially, the single ion channel open–close activity and its associated protein conformational changes simultaneously. Furthermore, we have revealed that the seemingly identical electrically off states are associated with multiple conformational states. On the basis of our experimental results, we have proposed a multistate clamshell model to interpret the NMDA receptor open–close dynamics.
Growth Type and Functional Trajectories: An Empirical Study of Urban Expansion in Nanjing, China

Drawing upon the Landsat satellite images of Nanjing from 1985, 1995, 2001, 2007, and 2013, this paper integrates the convex hull analysis and common edge analysis at double scales, and develops a comprehensive matrix analysis to distinguish the different types of urban land expansion. The results show that Nanjing experienced rapid urban expansion, dominated by a mix of residential and manufacturing land from 1985 to 2013, which in turn has promoted Nanjing’s shift from a compact mononuclear city to a polycentric one. Spatial patterns of three specific types of growth, namely infilling, extension, and enclave were quite different in four consecutive periods. These patterns result primarily from the existing topographic constraints, as well as government-oriented urban planning and policies. By intersecting the function maps, we also reveal the functional evolution of newly-developed urban land. Moreover, both self-enhancing and mutual promotion of the newly developed functions are surveyed over the last decade. Our study confirms that the integration of a multi-scale method and multi-perspective analysis, such as the spatiotemporal patterns and functional evolution, helps us to better understand the rapid urban growth in China.
The Complexity of the Boolean Formula Value Problem

We examine the complexity of the formula value problem for Boolean formulas, which is the following decision problem: Given a Boolean formula without variables, does it evaluate to true? We show that the complexity of this problem is determined by certain closure properties of the connectives allowed to build the formula, and achieve a complete classification: The formula value problem is either in LOGTIME, complete for one of the classes NLOGTIME, coNLOGTIME or NC, or equivalent to counting modulo 2 under very strict reductions.
Estimating Covariance for Privacy Case under Interval (and Fuzzy) Uncertainty

One of the main objectives of collecting data in statistical databases (medical databases, census databases) is to find important correlations between different quantities. To enable researchers to looks for such correlations, we should allow them them to ask queries testing different combinations of such quantities. However, when we receive answers to many such questions, we may inadvertently disclose information about individual patients, information that should be private. One way to preserve privacy in statistical databases is to store ranges instead of the original values. For example, instead of an exact age of a patient in a medical database, we only store the information that this age is, e.g., between 60 and 70. This idea solves the privacy problem, but it make statistical analysis more complex. Different possible values from the corresponding ranges lead, in general, to different values of the corresponding statistical characteristic; it is therefore desirable to find the range of all such values. It is known that for mean and variance, there exist feasible algorithms for computing such ranges. In this paper, we show that similar algorithms are possible for another important statistical characteristic – covariance, whose value is important in computing correlations.
Hybrid-BCI: Classification of auditory and visual related potentials

The brain computer interface (BCI) is a technology that utilizes neurophysiological signals recorded from brain to control external machines or computers, and has become widespread in the last decade due to technical and mechanical developments. A P300-based BCI, often called P300 speller, is one of the most successful paradigm, which has shown advantages in terms of high accuracy and short training time. However, the existing P300-based BCI employs single type of external stimuli, such as visual stimuli, which limits their application domains. In this paper, we propose a hybrid-BCI system based on multiple modality of P300 evoked by simultaneous auditory and visual stimuli. The experimental results show the significant difference in ERPs between visual stimuli and multiple types of stimuli. The classification results demonstrate the effectiveness of our new BCI paradigm, which outperforms the visual P300 in terms of higher accuracy.
Collocations in Corpus‐Based Language Learning Research: Identifying, Comparing, and Interpreting the Evidence

This article focuses on the use of collocations in language learning research (LLR). Collocations, as units of formulaic language, are becoming prominent in our understanding of language learning and use; however, while the number of corpus-based LLR studies of collocations is growing, there is still a need for a deeper understanding of factors that play a role in establishing that two words in a corpus can be considered to be collocates. In this article we critically review both the application of measures used to identify collocability between words and the nature of the relationship between two collocates. Particular attention is paid to the comparison of collocability across different corpora representing different genres, registers, or modalities. Several issues involved in the interpretation of collocational patterns in the production of first language and second language users are also considered. Reflecting on the current practices in the field, further directions for collocation research are proposed.
Graphically Speaking Editor : Miguel Encarnação Toward Visualization in Policy Modeling

Information visualization and visual analytics (VA) have become widely recognized research fields applied to a variety of domains and data-related challenges. This development’s main driver has been the rapidly increasing amount of data that must be dealt with daily. Virtually every industry or business, or any political or personal activity, generates vast amounts of data. At the same time, citizens, shareholders, and customers expect highly efficient, informed decision-making based on increasingly complex, dynamic, and interdependent data and information. All this applies in many ways to public-policy modeling. As the recent financial crisis has shown, policy making and regulation are highly challenging tasks. The outcomes of policy choices and individual behavior aren’t easily predictable in our complex society. Ubiquitous computing, crowdsourcing, and open data, to name just a few examples, are creating masses of data that governments struggle to make sense of for policy modeling. Increasingly, policy makers are perceiving visualization and data analysis as critical to this sense-making process. Current practice uses visualization mainly during postprocessing. Although this is an important step in the right direction, a more promising trend is the integration of visualization tools with simulation and automated analysis. This is clearly in line with the general approach employed by various domains that apply VA techniques for interactive analysis. Here, we examine the current and future roles of information visualization, semantics visualization, and VA in policy modeling. Many experts believe that you can’t overestimate visualization’s role in this respect. For example, the recent EU roadmap for this area goes as far as saying that “ensuring appropriate visualisations can . be considered a key component of a mature democracy. ”1
Effects of tirofiban on haemostatic activation in vitro.

BACKGROUND Thrombin plays a critical role in normal haemostasis and pathological thrombosis. Heparin has long been a mainstay choice of antithrombotic regimen in cardiac patients, but persistent thrombin generation seems to occur during heparin therapy. Because platelets are integral to primary haemostasis and clot formation, we evaluated the use of tirofiban (Aggrastat),a platelet inhibitor, as a therapy to improve heparin sensitivity and delay thrombin formation. METHODS Blood samples were obtained from healthy subjects (n=8) and cardiac surgical patients (n=34). Thrombin formation was measured in platelet-rich plasma with a Thrombogram-Ascent fluorescent plate reader system. Platelet inhibition by tirofiban was evaluated with Plateletworks, and the interaction of tirofiban and heparin (>1.5 U ml(-1)) on clot formation was evaluated with Sonoclot Analyzer or kaolin activated clotting times (ACTs). RESULTS Addition of tirofiban (70-280 ng ml(-1)) progressively delayed onset of thrombin generation triggered by adenosine diphosphate (ADP). Plateletworks showed platelet inhibition with tirofiban (>35 ng ml(-1)), whereas heparin per se failed to produce platelet inhibition at 7 U ml(-1). Heparin (1.5 U ml(-1)) slowed the onset and rate of fibrin formation on Sonoclot analyses, and this was further slowed after addition of tirofiban (70 ng ml(-1)) to heparin-containing blood samples. Significant increases in ACT at all heparin concentrations were observed with the addition of tirofiban (70 ng ml(-1)). The addition of antithrombin (0.2 units/ml) to heparinized blood samples further prolonged ACTs, but the difference was not statistically significant when compared with heparin alone. CONCLUSION Tirofiban delays platelet activation-mediated thrombin generation and prolongs ACT in heparinized blood.
Image Duplication and Rotation Algorithms for Storage Utilization

In this era, there is high end storage with high storage capacity. However, due to ethic issues, this development has rapidly increased the cost of hardware every year. In order to prevent the rapid increase of the hardware cost, pattern detection methods are introduced to optimize the storage utilization by detecting image duplication and inappropriate image. Pattern detection is usually applied before pattern recognition. The accuracy of pattern detection can give impact to pattern recognition. Therefore, it plays an important role on a digital image. This paper is based on scale invariant feature transform (SIFT) for image near-duplication detection and V-J face detection. V-J method refers to Viola Jones’s method. Both methods have been successfully applied to the real world problem. Since the V-J face detection method is not trained with rotated features, it has limitiation to rotation invariant, whereas the SIFT method detects many feature keypoints, affecting the speed performance. In order to overcome the issues above, this paper proposed a new method by enhancing the SIFT with speed performance and V-J face detection with high rotation invariant. The comparison result of the experiment shows that the proposed solutions produce better performance
Contrasting Objective and Subjective Portuguese Texts from Heterogeneous Sources

This paper contrasts the content and form of objective versus subjective texts. A collection of on-line newspaper news items serve as objective texts, while parliamentary speeches (debates) and blog posts form the basis of our subjective texts, all in Portuguese. The aim is to provide general linguistic patterns as used in objective written media and subjective speeches and blog posts, to help construct domain-independent templates for information extraction and opinion mining. Our hybrid approach combines statistical data along with linguistic knowledge to filter out irrelevant patterns. As resources for subjective classification are still limited for Portuguese, we use a parallel corpus and tools developed for English to build our subjective spoken corpus, through annotations produced for English projected onto a parallel corpus in Portuguese. A measure for the saliency of n-grams is used to extract relevant linguistic patterns deemed "objective" and "subjective". Perhaps unsurprisingly, our contrastive approach shows that, in Portuguese at least, subjective texts are characterized by markers such as descriptive, reactive and opinionated terms, while objective texts are characterized mainly by the absence of subjective markers.