Miracle-dz/UniFAR-FTUs huggingface dataset:
Mycobacterium tuberculosis, but not vaccine BCG, specifically upregulates matrix metalloproteinase-1.

RATIONALE Pulmonary cavitation is fundamental to the global success of Mycobacterium tuberculosis. However, the mechanisms of this lung destruction are poorly understood. The biochemistry of lung matrix predicts matrix metalloproteinase (MMP) involvement in immunopathology. METHODS We investigated gene expression of all MMPs, proteins with a disintegrin and metalloproteinase domain, and tissue inhibitors of metalloproteinases in M. tuberculosis-infected human macrophages by real-time polymerase chain reaction. MMP secretion was measured by zymography and Western analysis, and expression in patients with pulmonary tuberculosis was localized by immunohistochemistry. RESULTS MMP-1 and MMP-7 gene expression and secretion are potently upregulated by M. tuberculosis, and no increase in tissue inhibitor of metalloproteinase expression occurs to oppose their activity. Dexamethasone completely suppresses MMP-1 but not MMP-7 gene expression and secretion. In patients with active tuberculosis, macrophages express MMP-1 and MMP-7 adjacent to areas of tissue destruction. MMP-1 but not MMP-7 expression and secretion are relatively M. tuberculosis specific, are not upregulated by tuberculosis-associated cytokines, and are prostaglandin dependent. In contrast, the vaccine M. bovis bacillus Calmette-Guérin (BCG) does not stimulate MMP-1 secretion from human macrophages, although M. tuberculosis and BCG do upregulate MMP-7 equally. BCG-infected macrophages secrete reduced prostaglandin E2 concentrations compared with M. tuberculosis-infected macrophages, and prostaglandin pathway supplementation augments MMP-1 secretion from BCG-infected cells. CONCLUSIONS M. tuberculosis specifically upregulates MMP-1 in a cellular model of human infection and in patients with tuberculosis. In contrast, vaccine BCG, which does not cause lung cavitation, does not upregulate prostaglandin E2-dependent MMP-1 secretion.
SPH Modelling of Long-term Sway-Sloshing Motion in a Rectangular Tank

This work aims to model long-term simulations of sway-sloshing motion in a partially filled rectangular tank with different water depths and enforced motion frequencies. The lateral motion frequency of the tank is chosen so as to coincide with the lowest theoretical natural frequency for the corresponding beam of the tank and initial depth of water reserve. A truly meshless method, Smoothed Particle Hydrodynamics (SPH) is used to discretize and solve the governing equations. It is shown that numerical results of the proposed SPH scheme are in good agreement with experimental and numerical ﬁndings of the literature.
Shanghai Lalas: Female Tongzhi Communities and Politics in Urban China

This is the first ethnographic study of lala (lesbian, bisexual, and transgender) communities and politics in China, focusing on the city of Shanghai. Based on several years of in-depth interviews, the volume concentrates on lalas' everyday struggle to reconcile same-sex desires with a dominant rhetoric of family harmony and compulsory marriage, all within a culture denying women active and legitimate sexual agency. Lucetta Yip Lo Kam reads discourses on homophobia in China, including the rhetoric of "Chinese tolerance," and considers the heteronormative demands imposed on tongzhi subjects. She treats "the politics of public correctness" as a newly emerging tongzhi practice developed from the culturally specific, Chinese forms of regulation that inform tongzhi survival strategies and self-identification. Alternating between Kam's own experiences with queer identity and her extensive ethnographic findings, this text offers a contemporary portrait of female tongzhi communities and politics in urban China, making an invaluable contribution to global discussions and international debates on same-sex intimacies, homophobia, coming-out politics, and sexual governance.
MMP9 cleavage of the β4 integrin ectodomain leads to recurrent epithelial erosions in mice

Integrin α6β4 is an integral membrane protein within hemidesmosomes and it mediates adhesion of epithelial cells to their underlying basement membrane. During wound healing, disassembly of hemidesmosomes must occur for sheet movement-mediated cell migration. The mechanisms of disassembly and reassembly of hemidesmosomes are not fully understood. The current study was initiated to understand the underlying cause of recurrent corneal erosions in the mouse. Here, we show that in vivo: (1) MMP9 levels are elevated and β4 integrin is partially cleaved in epithelial cell extracts derived from debridement wounded corneas; (2) the β4 ectodomain is missing from sites where erosions develop; and (3) β4 cleavage can be reduced by inhibiting MMP activity. Although β4, α3 and β1 integrins were all cleaved by several MMPs, only MMP9 was elevated in cell extracts derived from corneas with erosions. Coimmunoprecipitation studies showed that β4 integrin associates with MMP9, and protein clustering during immunoprecipitation induced proteolytic cleavage of the β4 integrin extracellular domain, generating a 100 kDa β4 integrin cytoplasmic domain fragment. Confocal imaging with three-dimensional reconstruction showed that MMP9 localizes at erosion sites in vivo where the ectodomain of β4 integrin is reduced or absent. MMP activation experiments using cultured corneal and epidermal keratinocytes showed reduced levels of α6β4 and β1 integrins within 20 minutes of phorbol ester treatment. This report is the first to show that β4 integrin associates with MMP9 and that its ectodomain is a target for cleavage by MMP9 in vivo under pathological conditions.
HIGH-LEVEL IMAGE PRIORS IN CONFOCAL MICROSCOPY APPLICATIONS

The incorporation of high–level prior information in Bayesian imaging has been proposed via the theoretical frameworks both of Grenander and Miller (1994) and Baddeley and Van Lieshout (1993). Recent developments in Markov chain Monte Carlo algorithms for varying dimension problems (Green, 1995) have made the application of these high–level models more widely accessible, although this remains more complicated than using the usual low–level Markov random fields models. One application area in which incorporating information on the object level in a scene would be of particular benefit is in confocal microscopy. In this paper we outline two such applications, the first addresses uncertainty in segmenting confocal microscope images, and the second is an object recognition problem.
Offshoring Information Technology: Contents

Preface Part I. The Fundamentals: 1. The offshore landscape 2. Offshore economics and offshore risks 3. Beginning the offshore journey 4. The offshore country menu Part II. Managerial Competency: 5. Offshore strategy 6. Offshore legal issues 7. Managing the offshore transition 8. Overcoming distance and time 9. Dealing with cross-cultural issues Part III. Other Stakeholders: 10. Building software industries in developing nations 11. Marketing of offshore services - the provider perspective 12. Offshore politics Biographies References Index.
Unsupervised segmentation for multiple sclerosis lesions in multimodality Magnetic Resonance images

In this paper, a new unsupervised approach is proposed for the segmentation of Multiple Sclerosis (MS) lesions in multimodality Magnetic Resonance (MR) images. The proposed segmentation scheme is based on joint histogram modelling followed by false positive reduction and alpha matting, which is used to deal with the tissue density overlap problem and partial volume effects in MR images. Firstly, the joint histogram is generated by using fluid-attenuated inversion recovery (Flair), T1-weighted (T1-w) and T2-weighted (T2-w) MRI. Then the region for MS lesions in the joint histogram are located. Sub-sequently, the located region is projected back into the 2D MR images with potential MS lesions. Secondly, priori information is utilized to remove false positive volume of interests. Finally, the partial volume effect is modelled by using an alpha technique provides region level lesion refinement. Validation is performed on real multi-channel T1-w, T2-w, and Flair MR volumes. The experimental results show the proposed method can obtain better results than some state-of-the-art methods.
Systematic Reviews and Meta-and Pooled Analyses Hospitalization Fatality Risk of Influenza A ( H 1 N 1 ) pdm 09 : A Systematic Reviewand Meta-Analysis

During the 2009 influenza pandemic, uncertainty surrounding the severity of human infections with the influenza A(H1N1)pdm09 virus hindered the calibration of the early public health response. The case fatality risk was widely used to assess severity, but another underexplored and potentially more immediate measure is the hospitalization fatality risk (HFR), defined as the probability of death among H1N1pdm09 cases who required hospitalization for medical reasons. In this review, we searched for relevant studies published in MEDLINE (PubMed) and EMBASE between April 1, 2009, and January 9, 2014. Crude estimates of the HFR ranged from 0% to 52%, with higher estimates from tertiary-care referral hospitals in countries with a lower gross domestic product, but in wealthy countries the estimate was 1%–3% in all settings. Point estimates increased substantially with age and with lower gross domestic product. Early in the next pandemic, estimation of a standardizedHFRmay provide a picture of the severity of infection, particularly if it is presented in comparison with a similarly standardized HFR for seasonal influenza in the same setting.
A Joint Deployment and Routing Strategy for Directional Wireless Mesh Networks

For the emerging wireless mesh networks with multiple radios and directional antennas, this paper first proposes a position-based deployment and routing strategy, and then gives a concrete approach under this strategy. The main idea of this strategy is to deploy the network in certain kind of geometric graph and then design a position-based routing protocol accordingly, so as to achieve efficiency and scalability for the mesh networks. The proposed approach comprises two parts: (1) a topology generation algorithm based on Delaunay triangulations and (2) a routing protocol based on the greedy forwarding algorithm. Both parts have low complexity of computation, as well as possess appealing properties for deployment or routing. Formal proofs to these claims are provided when applicable. The extensive simulation results show that our proposed approach is indeed efficient and scalable.
Love on the Rocks: Alcohol Abuse and Domestic Violence in Rural Mexico

What causes alcohol abuse and domestic violence and how can we stop them? These behaviors have multiple determinants, making the effects of changes in wife's and husband's income ambiguous. This paper estimates the effects of exogenous changes in wife's and husband's income on husband alcohol abuse and alcohol-induced violence using new data from rural Mexico. A long-lasting 20 dollar monthly increase in wife income decreases husbands' alcohol abuse by 15% and aggressive behavior by 21%; the extra money increase the wife's freedom and security, is spent on individual and household goods, and it crowds out transfers from the husband only for 5% of the wives whose income increases. Alcohol abuse and violence are insensitive to short-term fluctuations in husband's income. These findings suggest that the wife uses her higher income to reduce the consumption of goods that lower her utility, that alcohol abuse responds more to changes in permanent than in temporary income, and that targeting women as recipients of micro-credit or of other welfare programs may have beneficial effects in reducing alcohol dependence and domestic violence.
The Non-Linear Stochastic Wave Equation in High Dimensions

We propose an extension of Walsh's classical martingale measure stochastic integral that makes it possible to integrate a general class of Schwartz distributions, which contains the fundamental solution of the wave equation, even in dimensions greater than 3. This leads to a square-integrable random-field solution to the non-linear stochastic wave equation in any dimension, in the case of a driving noise that is white in time and correlated in space. In the particular case of an affine multiplicative noise, we obtain estimates on $p$-th moments of the solution ($p\geq 1$), and we show that the solution is Holder continuous. The Holder exponent that we obtain is optimal.
Analytical Modeling of Reactive Autonomic Management Techniques in IaaS Clouds

Cloud computing infrastructures provide services to a wide number of users whose behavior can deeply change at the occurrence of particular events. To correctly handle such situations a cloud infrastructure have to be reconfigured in a way that does not cause degradation in the overall performance. Otherwise, the quality of service specified in the service level agreement could be violated. To prevent such situations, the infrastructure could be organized as an autonomic system where self-adaptation and self-configuration techniques are implemented. Appropriate design choices become important in order not to fail in this goal. We propose a technique, based on a Petri net model and a specific analytical analysis approach, to represent Infrastructure-as-a-Service (IaaS) systems in the case in which the load conditions can suddenly change and reactive autonomic management techniques are applied to mitigate the consequences of the change. The model we propose is able to appropriately evaluate performance metrics in such critical situations making it suitable as a design tool for IaaS cloud systems.
Adaptive Denoising of CFA Images for Image Demosaicking

In single sensor digital color cameras at each pixel it captures only one of the three primary colors so the full color image is obtained by interpolating all other missing color samples at that pixel this process is the color demosaicking process. When we capture the images using digital cameras there is some sensor noise is introduced in image. This type of noise is introduced in all type of digital cameras that is low cost to high cost. So in reconstructing the images there are different strategies used to obtain the good quality images. Basically there are three different strategies, first strategy is demosaicking the image and after that denoise the image but in that process the artifacts occurs in initial color demosaicking method is hard to remove in subsequent denoising process. Second strategy is joint denoising demosaicking and third strategy is denoising before demosaicking so here last strategy is used. In this paper here first denoise the CFA image to remove sensor noise for that here use PCA based adaptive denoising method and after that demosaicking the image with nonlocal adaptive thresholding method. So here main advantage of this implementation is that by the use of Principal component analysis (PCA) based denoising this algorithm remove the sensor noise and by using the Nonlocal adaptive thresholding for demosaicking it reconstruct good quality images which having sharp color transition in it.
Multi-Level Feature Descriptor for Robust Texture Classification via Locality-Constrained Collaborative Strategy

This paper introduces a simple but highly efficient ensemble for robust texture classification, which can effectively deal with translation, scale and changes of significant viewpoint problems. The proposed method first inherits the spirit of spatial pyramid matching model (SPM), which is popular for encoding spatial distribution of local features, but in a flexible way, partitioning the original image into different levels and incorporating different overlapping patterns of each level. This flexible setup helps capture the informative features and produces sufficient local feature codes by some well-chosen aggregation statistics or pooling operations within each partitioned region, even when only a few sample images are available for training. Then each texture image is represented by several orderless feature codes and thereby all the training data form a reliable feature pond. Finally, to take full advantage of this feature pond, we develop a collaborative representation-based strategy with locality constraint (LC-CRC) for the final classification, and experimental results on three well-known public texture datasets demonstrate the proposed approach is very competitive and even outperforms several state-of-the-art methods. Particularly, when only a few samples of each category are available for training, our approach still achieves very high classification performance.
TASS - Workshop on Sentiment Analysis at SEPLN

This paper describes TASS, an experimental evaluation workshop within SEPLN to foster the research in the field of sentiment analysis in social media, specifically focused on Spanish language. The main objective is to promote the application of existing state-of-the-art algorithms and techniques and the design of new ones for the implementation of complex systems able to perform a sentiment analysis based on short text opinions extracted from social media messages (specifically Twitter) published by representative personalities. The paper presents the proposed tasks, the contents, format and main statistics of the generated corpus, the participant groups and their different approaches, and, finally, the overall results achieved.
A 3-D Time-Dependent Green's Function Approach to Modeling Electromagnetic Noise in On-Chip Interconnect Networks

We present a methodology for investigating the response of a complex on-chip interconnect network to external and internal noise, through the development of a 3-D solver based on creating a lumped element model of an interconnect network and solving for its impulse responses. Our method exhibits a lower computational cost than SPICE and allows the user the flexibility to work on a wide variety of interconnect network geometries as well as to include as many parasitic effects as desired for the application
Mutation in utp15 Disrupts Vascular Patterning in a p53-Dependent Manner in Zebrafish Embryos

Background Angiogenesis is the process by which the highly branched and functional vasculature arises from the major vessels, providing developing tissues with nutrients, oxygen, and removing metabolic waste. During embryogenesis, vascular patterning is dependent on a tightly regulated balance between pro- and anti-angiogenic signals, and failure of angiogenesis leads to embryonic lethality. Using the zebrafish as a model organism, we sought to identify genes that influence normal vascular patterning. Methodology and Principal Findings In a forward genetic screen, we identified mutant LA1908, which manifests massive apoptosis during early embryogenesis, abnormal expression of several markers of arterial-venous specification, delayed angiogenic sprouting of the intersegmental vessels (ISV), and malformation of the caudal vein plexus (CVP), indicating a critical role for LA1908 in cell survival and angiogenesis. Genetic mapping and sequencing identified a G to A transition in the splice site preceding exon 11 of utp15 in LA1908 mutant embryos. Overexpression of wild type utp15 mRNA suppresses all observed mutant phenotypes, demonstrating a causative relationship between utp15 and LA1908. Furthermore, we found that injecting morpholino oligonucleotides inhibiting p53 translation prevents cell death and rescues the vascular abnormalities, indicating that p53 is downstream of Utp15 deficiency in mediating the LA1908 phenotypes. Conclusions and Significance Taken together, our data demonstrate an early embryonic effect of Utp15 deficiency on cell survival and the normal patterning of the vasculature and highlight an anti-angiogenic role of p53 in developing embryos.
SEM12 at the NTCIR-10 INTENT-2 English Subtopic Mining Subtask

Users express their information needs in terms of queries in search engines to find some relevant documents on the Internet. However, search queries are usually short, ambiguous and/or underspecified. To understand user’s search intent, subtopic mining plays an important role and has attracted attention in the recent years. In this paper, we describe our approach to identifying, and then ranking user’s intents for a query (or topic) from query logs, which is an english subtopic mining subtask of the NTCIR-10 Intent-2 task. We extract subtopics that are semantically and lexically related to the topic, and measure their weights based on co-occurrence of a subtopic across search engine query logs, and edit distance between a topic and a subtopic. These weighted subtopic strings are ranked to represent themselves as the candidates of subtopics (or intents). In the experiment section, we show the revised subtopic mining results of our method evaluated by the organizers. The best performance of our system achieves an I-rec@10 (Intent Recall) of 0.3780, a D-nDCG@10 of 0.4250, and a D#-nDCG@10 of 0.4014.
Are maximizers really unhappy? The measurement of maximizing tendency

Recent research suggesting that people who maximize are less happy than those who satisfice has received considerable fanfare. The current study investigates whether this conclusion reflects the construct itself or rather how it is measured. We developed an alternative measure of maximizing tendency that is theory-based, has good psychometric properties, and predicts behavioral outcomes. In contrast to the existing maximization measure, our new measure did not correlate with life (dis)satisfaction, nor with most maladaptive personality and decision-making traits. We conclude that the interpretation of maximizers as unhappy may be due to poor measurement of the construct. We present a more reliable and valid measure for future researchers to use.
Understanding Police Use of Force: Officers, Suspects, and Reciprocity

Introduction: the context of police use of force 1. Police use of force: the history of research 2. The crucial element: finding research sites 3. Findings from Miami-Dade Police Department study 4. The sequential steps in use of force incidents 5. MDPD: inconsistencies between officer and suspect accounts of the use of force 6. Findings from Prince George's County Police Department 7. Findings and summary 8. Explaining police use of force: the breakdown of an authority maintenance ritual.
Entropy-Based Distributed Fault-Tolerant Event Boundary Detection Algorithm for Wireless Sensor Networks

Wireless sensor networks observe the occurrences of concerned events by the collaboration between sensor nodes via wireless communication. Sensors are usually prone to errors due to the unstable conditions they are exposed to. The goal is to solve event boundary detection with faulty sensors (EBDF) problem which is to successfully identify the sensor nodes close to the event boundary when faulty sensors exist in wireless sensor networks. Some previous works proposed solutions based on 0/1 decision predicate for which only values 0 or 1 (true or false) are used to represent the sensing values which may ignore local variations. Others require centralized mechanism to retrieve the threshold or it may not be applied to dynamic situation efficiently. A novel distributed event boundary detection algorithm, EBD_Entropy, using entropy is proposed which applies system entropy concept from both thermodynamics and information theory points of view. EBD_Entropy accepts scalar values as input. It's also distributed and localized and thus is scalable. Simulation results show that EBD Entropy is effective in enhancing the performance of boundary detection and can be applied to more dynamic environments.