Miracle-dz/UniFAR-FTUs huggingface dataset:
LOW-DOSE CANDESARTAN IMPROVES RENAL BLOOD FLOW AND KIDNEY OXYGEN TENSION IN RATS WITH ENDOTOXIN-INDUCED ACUTE KIDNEY DYSFUNCTION

ABSTRACT Sepsis is associated with an activation of the renin-angiotensin system and causes acute kidney injury. The aim was to examine the effects of a low, nondepressor dose of the selective angiotensin II type 1 receptor antagonist candesartan on renal hemodynamics and function in endotoxemic rats. Endotoxemia was induced in Sprague-Dawley rats by a dose of LPS (Escherichia coli O127:B8; 7.5 mg kg−1, i.p.). At 16 h after endotoxin administration, renal clearance experiments were performed in thiobutabarbital anesthetized rats. Study groups (1) sham-saline, (2) LPS-saline, and (3) LPS-candesartan received isotonic saline or candesartan (10 &mgr;g kg−1, i.v.) after baseline measurements. Kidney function, renal blood flow (RBF), and cortical and outer medullary perfusion (laser-Doppler flowmetry) and oxygen tension (PO2; Clark-type microelectrodes) were analyzed during 2 h after drug administration. At baseline, endotoxemic rats showed an approximately 50% reduction in glomerular filtration rate and RBF (P < 0.05), a decline in cortical and outer medullary perfusion, and Po2 (P < 0.05), but no significant alterations in MAP compared with saline-injected controls. Candesartan treatment significantly improved RBF (+40% ± 6% vs. baseline), cortical perfusion (+18% ± 3% vs. baseline), and cortical (+19% ± 7% vs. baseline) and outer medullary (+22% ± 10% vs. baseline) Po2 in endotoxemic rats (P < 0.05 vs. LPS-saline). Candesartan did not significantly influence MAP or glomerular filtration rate, whereas filtration fraction was reduced by 27% ± 5% vs. baseline (P < 0.05 vs. LPS-saline). In conclusion, candesartan, in a dose that did not significantly decrease MAP, caused renal vasodilation and markedly improved RBF and intrarenal Po2 in endotoxemic rats. These findings suggest renoprotective effects of candesartan in sepsis.
Fuzzy ANP - A Analytical Network Model for Result Merging for Metasearch using Fuzzy Linguistic Quantifiers

Search Engines are tools for searching the World Wide Web or any other large data collection. Search engines typically accept a user query and returns a list of relevant documents. These documents are generally returned as a result list for the user to see. A metasearch engine is a tool that allows an information seeker to search information on the world wide web through multiple search engines. A key function of a metasearch engine is to aggregate search results returned by many search engines. Result aggregation is an important task for a metasearch engine. In this paper we propose a model for result aggregation for metasearch, Fuzzy ANP, that employs fuzzy linguistic quantifier guided approach to result merging using Saty's Analytical Network Process. We compare our model to two existing result merging models, the Borda Fuse model and the OWA model for metasearch. Our results show that our model outperforms the OWA model and Borda-Fuse model significantly.
Who to Invite Next? Predicting Invitees of Social Groups

Social instant messaging services (SMS) such as WhatsApp, Snapchat and WeChat, have significantly changed the way people work, live, and communicate, attracting increasing attention from multiple disciplinary including computer science, sociology, psychology, and physics. In SMS, social groups play a very important role in supporting communication among multiple users. An interesting question arises: what are the dynamic mechanisms underlying the group evolution? Or more specifically, in an existing group, who should be invited to join? In this paper, we formalize a novel problem of predicting potential invitees of groups. Employing WeChat, the largest social messaging service in China, as the source for our experimental data, we develop a probabilistic graph model to capture the fundamental factors that determine the probability of a user to be invited to a specific social group. Our results show that the proposed model indeed lead to statistically significant prediction improvements over several state-of-the-art baseline methods.
Insert Your Own Body in the Oculus Rift to Improve Proprioception

A natural interaction in virtual reality environments, in particular when wearing head-mounted-displays, is often prevented by the lack of a visual feedback about the user’s own body. This paper aims to create a virtual environment, in which the user can visually perceive his/her own body, and can interact with the virtual objects, by using a virtual body that replicates his/her movements. To this aim, we have set up an affordable virtual reality system, which combines the Oculus Rift head-mounted-display, a Microsoft Kinect, and a Leap Motion, in order to recreate inside the virtual environments a first-person avatar, who replicates the movements of the user’s full-body and the fine movements of his/her fingers and hands. By acting in such an environment, the user is able to perceive him/herself thus improving his/her experience in the virtual reality. Here, we address and propose a solution to the issues related to the integration of the different devices, and to the alignment and registration of their reference systems. Finally, the effectiveness of the proposed system is assessed through an experimental session, in which several users report their feeling by answering to a 5-points Likert scale
PAKME: A Tool for Capturing and Using Architecture Design Knowledge

Management of architecture knowledge is vital for improving an organization's architectural capabilities. Despite the recognition of the importance of capturing and reusing architecture knowledge, there is no suitable support mechanism. We have developed a conceptual framework for capturing and using architecture design knowledge to support architecture-based software development. A Web-based knowledge management tool, process-based architecture knowledge management environment (PAKME), has been developed to support that framework. This paper describes the main architectural components and features of the PAKME. We also discuss different usages of the tool for capturing and using architecture design knowledge to support architecting process. The paper concludes with open issues that we plan to address in order to extend the tool and successfully transfer the support mechanism to industry
Digital Transcript Profile Analysis with aRNA-LongSAGE Validates FERMT1 As a Potential Novel Prognostic Marker for Colon Cancer

Purpose: To use gene transcript profiling to identify cancer-associated gene expression. Experimental Design: Methods included (i) marker discovery using laser capture microdissection (LCM)-assisted specimen preparation and antisense RNA-long serial analysis of gene expression (aRNA-LongSAGE) on matched colon cancer and uninvolved colon tissue specimens (n = 5). Candidate tumor-associated genes were selected by combining the LongSAGE libraries reported herein with our previous colon cancer LCM-microarray transcript profiling data; (ii) marker selection and validation by quantitative real-time PCR (n = 15) and immunohistochemistry (n = 31); and (iii) independent validation on multiple tissue microarray (n = 203). Results: Among 30 upregulated and 73 downregulated genes, upregulation of fermitin family member 1 (FERMT1), adenosylhomocysteinase (AHCY), secernin 1 (SCRN1), and SAC3 domain-containing protein 1 (SAC3D1) expression and downregulation of IgJ and MALL expression in colon cancer were confirmed by quantitative PCR. FERMT1 and AHCY protein expression was also upregulated in colon cancer compared with uninvolved colon mucosa, and FERMT1 expression showed upregulation in colon adenoma. Patients with moderate/strong tumor FERMT1 protein expression (n = 122) showed significantly poorer overall survival (OS; P = 0.011) and disease-free survival (DFS; P = 0.005) than patients with negative/weak tumor FERMT1 protein expression (n = 81). Multivariate Cox regression analysis showed that FERMT1 protein expression was also an independent prognostic factor for OS (P = 0.018) and DFS (P = 0.009). In addition, upregulated FERMT1 protein expression appeared to have some specificity among alimentary tract tumors. Conclusions: FERMT1 is a novel prognostic factor for colon carcinoma. Clin Cancer Res; 17(9); 2908–18. ©2011 AACR.
Sparse representation for weed seeds classification

In agricultural industry, there is a longing for highly efficient and reliable seeds classification methods. Fast implementation of the existing methods is of great economical importance. Almost all categories of weed seeds have different size, shape and texture, and even the same species are quantitatively diverse in feature. Therefore, feature extraction is a tough, time consuming and labor-intensive task. In this paper, we use the compressive sensing theory, which has been applied to the field of machine learning, to do some dimension reduction treatment such as principle component analysis, downsampling and random projection to avoid careful selection of the feature set. As long as the dimension of the extracted features is beyond the theoretical threshold, we can achieve the desired classification results. It is worth mentioning that on account of humidity, bacteria and many other factors,the seeds are prone to have mould blocks or scabs. Thus, it is extremely necessary to do some simulations like contiguous occlusion. According to the experimental results, we can see that this algorithm is fit for solving this problem.
Structure-Texture Decomposition of RGB-D Images

In this paper, we study the problem of separating texture from structure in RGB-D images. Our structure preserving image smoothing operator is based on the region covariance smoothing (RCS) method in [16] that we present a number of modifications to this framework to make it depth-aware and increase its effectiveness. In particular, we propose to incorporate three geometric depth features, namely height above ground, angle with gravity and horizontal disparity to the pool of image features used in that study. We also suggest to use a new kernel function based on KL-divergence between the distributions of extracted features. We demonstrate our approach on challenges images from NYU-Depth v2 Dataset [24], achieving more accurate decompositions than the state-of-the-art approaches which do not utilize any depth information.
PS Move API : A Cross-Platform 6 DoF Tracking Framework

With the introduction of 6DoF motion controllers for game consoles, low cost hardware for 3D interaction became widely available. However, no fully-featured software solution for 6DoF tracking exists that takes advantage of the PlayStation (PS) Move Motion Controller without additional hardware. We designed, developed and evaluated a library the PS Move API that enables developers to use the PS Move Motion Controller as 6DoF input device in combination with a camera. Initially we solved hardware related problems such as pairing and communication over USB and Bluetooth. In this paper we describe how we perform visual tracking and sensor fusion, combining visual and inertial data. Performance results show that multiple controllers can be tracked simultaneously in real time. Developers using the library can choose between a low-level C API or higher-level abstractions in Python, Java, C# or the Processing framework. The library is open source, has been developed and tested on Windows, Mac OS X and Linux, and is released under a Simplified BSD License. It also runs on mobile Linux distributions such as MeeGo 1.2 Harmattan and Android. The full source code is available on the PS Move API website at http://thp.io/2010/psmove/.
Sunlight‐induced DNA damage in human mononuclear cells

In this study of 301 blood samples from 21 subjects, we found markedly higher levels of DNA damage (nonpyrimidine dimer types) in the summer than in the winter detected by single‐cell gel electro‐phoresis. The level of DNA damage was influenced by the average daily influx of sunlight < 50 days prior to blood sampling. The 3 and 6 day periods before sampling influenced DNA damage the most. The importance of sunlight was further emphasized by a positive association of the DNA damage level to the amount of time the subjects had spent in the sun over a 3 day period prior to the sampling. The effect of sunlight was comparable to the interindividual variation, indicating that sunlight exposure and the individual's background were the two most important determinants for the basal level of DNA damage. Influence of other lifestyle factors such as exercise, intake of foods, infections, and age could not be detected. Our results suggest that sunlight penetrates the outer layer of the human epidermis and damages the DNA in mononuclear cells circulating in the vessels of the skin. —Møller, P., Wallin, H. , Holst, E. , Knudsen, L. E. Sunlight‐induced DNA damage in human mononuclear cells. FASEB J. 16, 45–53 (2002)
Ninjurin1 Enhances the Basal Motility and Transendothelial Migration of Immune Cells by Inducing Protrusive Membrane Dynamics*

Background: Ninjurin1 promotes leukocyte trafficking during inflammation through homotypic binding. Results: Changes in Ninjurin1 expression in macrophages regulate protrusive membrane dynamics, motility, and in turn transendothelial migration. Conclusion: The pro-migratory function and binding activity of Ninjurin1 are important for modulating immune responses during inflammation. Significance: This study provides additional insights into the understanding of Ninjurin1-mediated inflammation. Ninjurin1 is involved in the pathogenesis of experimental autoimmune encephalomyelitis, an animal model of multiple sclerosis, by mediating leukocyte extravasation, a process that depends on homotypic binding. However, the precise regulatory mechanisms of Ninjurin1 during inflammation are largely undefined. We therefore examined the pro-migratory function of Ninjurin1 and its regulatory mechanisms in macrophages. Interestingly, Ninjurin1-deficient bone marrow-derived macrophages exhibited reduced membrane protrusion formation and dynamics, resulting in the impairment of cell motility. Furthermore, exogenous Ninjurin1 was distributed at the membrane of filopodial structures in Raw264.7 macrophage cells. In Raw264.7 cells, RNA interference of Ninjurin1 reduced the number of filopodial projections, whereas overexpression of Ninjurin1 facilitated their formation and thus promoted cell motility. Ninjurin1-induced filopodial protrusion formation required the activation of Rac1. In Raw264.7 cells penetrating an MBEC4 endothelial cell monolayer, Ninjurin1 was localized to the membrane of protrusions and promoted their formation, suggesting that Ninjurin1-induced protrusive activity contributed to transendothelial migration. Taking these data together, we conclude that Ninjurin1 enhances macrophage motility and consequent extravasation of immune cells through the regulation of protrusive membrane dynamics. We expect these findings to provide insight into the understanding of immune responses mediated by Ninjurin1.
Multiclass Contour-Preserving Classification with Support Vector Machine (SVM)

Abstract Multiclass contour-preserving classification (MCOV) has been used to preserve the contour of the data set and improve the classification accuracy of a feed-forward neural network. It synthesizes two types of new instances, called fundamental multiclass outpost vector (FMCOV) and additional multiclass outpost vector (AMCOV), in the middle of the decision boundary between consecutive classes of data. This paper presents a comparison on the generalization of an inclusion of FMCOVs, AMCOVs, and both MCOVs on the final training sets with support vector machine (SVM). The experiments were carried out using MATLAB R2015a and LIBSVM v3.20 on seven types of the final training sets generated from each of the synthetic and real-world data sets from the University of California Irvine machine learning repository and the ELENA project. The experimental results confirm that an inclusion of FMCOVs on the final training sets having raw data can improve the SVM classification accuracy significantly.
Discrimination of eight chicken Eimeria species using the two-step polymerase chain reaction.

A method was developed for the discrimination of 8 Eimeria species of chickens, i.e., E. acervulina, E. brunetti, E. mitis, E. maxima, E. necatrix, E. praecox, E. tenella, and E. hagani using the 2-step polymerase chain reaction (PCR). In the first PCR, the small subunit ribosomal RNA (srRNA) gene was amplified from the parasite genome using conserved sequences for the Apicomplexa srRNA gene as the primers. The srRNA gene amplified from the parasite genome was discriminated in the second step by random-amplified polymorphic DNA (RAPD) PCR using 10 arbitrary primers. Each arbitrary primer produced species-specific RAPD patterns that provided a simple method for species identification from the srRNA genes of the 8 Eimeria species. This method should be useful for discrimination of the parasite species for diagnosis or epidemiological surveys of chicken coccidiosis.
Impact des aménagements sur la morphodynamique du complexe lagunaire de Nador, Maroc

Resume : Le complexe lagunaire de Nador (littoral mediterraneen oriental), presente un interet particulier dans la region, aussi bien sur le plan scientifique que sur le plan socioeconomique. Le suivi de l’evolution morphodynamique de ce complexe durant la periode 2005-2010, a ete realise dans le but de connaitre l’incidence des amenagements recents : fermeture de l’ancienne passe en vue de sa transformation en un port de plaisance et ouverture d’une nouvelle passe. Il fait suite et s’appuie sur les resultats de l’etude morphostructurale et geomorphologique qui a ete menee dans le cadre du projet COLASU a la fois dans : le complexe lagunaire, son arriere pays et le proche plateau
Random walks for probabilistic robustness

In this paper, we explore the use of Markov chain sampling techniques for applications in probabilistic robustness of control systems. First, we analyze the general hit-and-run (HR) method for uniform sampling in convex bodies, and discuss several key issues related to the so called mixing rate of this process and to Hoeffding-type inequalities for dependent samples. Then, we apply the HR method for uniform sampling in the interior of a generic LMI feasible set. Two specific applications of this latter problem which are relevant in probabilistic robust control are studied: the uniform generation of stable transfer functions bounded in the H/sub /spl infin// norm, and uniform sampling in matrix spectral (maximum singular value) norm balls.
CS 6180 Lecture 26 – Automated Reasoning and Ultra-Intuitionism

This lecture will briefly consider two topics. The main one is the relationship between automated reasoning, an AI topic, and constructive type theory. The other topic is a brief mention of a radical approach to the foundations of mathematics called ultra-intuitionism and a discussion of impredicativity, a feature of logics considered dangerous and even unacceptable to some excellent mathematicians and logicians. Ultra-intuitionism denies the existence of infinite types or sets, accordingly mathematics is concerned with constructive reasoning about relatively small finite types (less than 10 elements). 1 Automated Reasoning The study of automated reasoning originated in Artificial Intelligence (AI) [29], and it continues to have strong ties to AI through the increasing use of proof assistants and the efforts to make them “smarter”. 1 Proof assistants such as Agda, Coq, Nuprl, and Lean are designed to help users create formal proofs and formally correct theorems and software that provably meets precise specifications. Recent applications of proof assistants have focused on creating provably correct software as featured in the Software Foundations Project [31]. There is direct and immediate economic value to this activity, and it is thus possible to find support from industry as well as from NSF and other science funding agencies.2 It is assumed that some of the funding for applied work will enhance the effectiveness of proof assistants. To some extent this is born out in practice. Other applications that have gathered attention are uses of proof assistants to check solutions to famous problems in mathematics such as the Four Color Theorem [16] and a machine checked proof of the Odd Order Theorem in group theory [17]. Recently Hales and colleagues checked his proof of the Kepler Conjecture using HOL [13]. There is other high profile work using proof assistants in mathematics, especially in formalizing elements of homotopy theory [33, 34] and in applications to cyber physical systems [3]. We have seen an example of this with the results of Dr. Bickford and his collaborators Coquand and Anders as they confirmed the constructive validity of the Univalence Axiom in homotopy theory. Steven Pinker’s book, How the Mind Works [32], provides an engaging glimpse of the AI side of automated reasoning. He discusses a “computational theory of mind” and compares the results of Some historians credit a summer meeting at Cornell in 1957 as the beginning of AI. The paper by Newell, Shaw, and Simon cited above was presented at that meeting. Some software companies have paid consulting firms to evaluate the cost effectiveness of this practice, and the results have so far confirmed its value.
Histologic Features Predicting Postoperative Crohn's Disease Recurrence

Abstract:Recurrence of Crohn's disease (CD) after ileal or colonic resection is common. Many studies have tried to identify predictors of postoperative recurrence (POR) in CD. A wide range of histologic features have been identified, but for most of them, the literature provided conflicting data. In last years, several studies have suggested that histologic findings including inflammatory changes within the enteric nervous system of the resection margin may be associated with CD recurrence. Herein, after briefly summarizing pathophysiology of POR, we review all histological features that have been studied so far: granulomas, histologic appearance at the margin of resection, plexitis, lymphatic vessel density in proximal margin of resection, and morphological analysis of Paneth cells. Granulomas and chronic inflammation at the margin of resection do not seem to predict POR in CD. Active disease at the margin of resection, plexitis, lymphatic vessels density, morphological analysis of Paneth cells may predict POR. Most of these histological features await replication in independent studies. Available evidence indicates that histological findings may be taken into account when developing strategies aimed at preventing postoperative CD recurrence.
Exploiting Recurrent Retrieval Needs in Querying Heterogeneous and Dynamic Graph Dataspaces

Querying data sources containing heterogeneous and dynamic information is a complex task: high quality answers need to be produced in a limited response time. Dynamic contexts preclude user involvement in interpreting the request and thus solutions should be devised, relying either on additional knowledge about the current execution (e.g., query context or user profile) or previous executions of the same request [? ]. The aim of this discussion paper is to exploit similar requests recurring over time for improving query processing, in terms of result quality and processing time, and to provide a general framework for representing and managing information collected in the executions of (sets of) recurring queries. Our approach relies on the enabling concept of Profiled Graph Query Pattern (PGQP), which represents a set of (previously executed) queries associated with information about their executions. Differently from apparently similar proposals (materialized views, smart caching), the proposed approach approximately matches queries with profiled patterns with the aim of retrieving various kinds of information, related to past executions of similar queries, and improving the processing of the