Miracle-dz/UniFAR-FTUs huggingface dataset:
Trophic relationships among Southern Ocean copepods and krill: Some uses and limitations of a stable isotope approach

The use of stable isotopes to study food webs has increased rapidly, but there are still some uncertainties in their application. We examined the δ15N and δ13C values of Antarctic euphausiids and copepods from the Polar Front, Lazarev Sea, and Marguerite Bay against their foodweb baseline of particulate organic matter (POM). Interpretations of trophic level were helped by comparison with other approaches and by calibration experiments with Euphausia superba fed known diets. Results for well‐known mesozooplankters (e.g., Calanoides acutus and Metridia gerlachei) were internally consistent and corresponded to those derived from independent methods. This gave confidence in the isotope approach for copepods and probably larval euphausiids. Among the dominant yet poorly known species, it suggested mainly herbivory for Rhincalanus gigas but omnivory for Calanus simillimus and furcilia larvae of Thysanoessa spp. and Euphausia frigida. The δ15N values of adult copepods were up to 3‰ higher than those of early copepodites, pointing to ontogenetic shifts in diet. In the Lazarev Sea in autumn, the isotopic signals of E. superba larvae suggested pelagic, mainly herbivorous, feeding rather than feeding within the ice. In contrast to the mesozooplankton, some anomalous results for postlarval krill species indicated problems with this method for micronekton. The experiments showed that postlarval E. superba did not equilibriate with a new diet within 30 d. We suggest that the slower turnover of these larger species, partly in combination with their ability to migrate, has confounded trophic effects with those of a temporally/spatially changing food‐web baseline. Interpretations of food sources of micronekton could be helped by analyzing their molts or fecal pellets, which responded faster to a new diet.
Psoas compartment block

Psoas compartment block (PCB) is a peripheral regional anaesthetic technique that blocks the main components of the lumbar plexus, namely the femoral, lateral femoral cutaneous (LFC), and obturator nerves as they run within the psoas major muscle. The psoas compartment block is also known as the posterior lumbar plexus block. A posterior approach to the lumbar plexus was first described by Winnie and colleagues. They described an approach for ‘lumbosacral’ block but provided no data on the extent of neural block. The term ‘psoas compartment block’ was coined by Chayen and colleagues to describe a loss of resistance technique with injection of solution into the ‘compartment’ between the quadratus lumborum and psoas major muscles. There have been a number of other approaches described since, including an approach by Capdevila and colleagues based on modifications to Winnie’s landmarks using computed tomography.
eNOS-derived nitric oxide regulates endothelial barrier function through VE-cadherin and Rho GTPases

Summary Transient disruption of endothelial adherens junctions and cytoskeletal remodeling are responsible for increases in vascular permeability induced by inflammatory stimuli and vascular endothelial growth factor (VEGF). Nitric oxide (NO) produced by endothelial NO synthase (eNOS) is crucial for VEGF-induced changes in permeability in vivo; however, the molecular mechanism by which endogenous NO modulates endothelial permeability is not clear. Here, we show that the lack of eNOS reduces VEGF-induced permeability, an effect mediated by enhanced activation of the Rac GTPase and stabilization of cortical actin. The loss of NO increased the recruitment of the Rac guanine-nucleotide-exchange factor (GEF) TIAM1 to adherens junctions and VE-cadherin (also known as cadherin 5), and reduced Rho activation and stress fiber formation. In addition, NO deficiency reduced VEGF-induced VE-cadherin phosphorylation and impaired the localization, but not the activation, of c-Src to cell junctions. The physiological role of eNOS activation is clear given that VEGF-, histamine- and inflammation-induced vascular permeability is reduced in mice bearing a non-phosphorylatable knock-in mutation of the key eNOS phosphorylation site S1176. Thus, NO is crucial for Rho GTPase-dependent regulation of cytoskeletal architecture leading to reversible changes in vascular permeability.
When to Plummet and When to Soar: Corpus Based Verb Selection for Natural Language Generation

For data-to-text tasks in Natural Language Generation (NLG), researchers are often faced with choices about the right words to express phenomena seen in the data. One common phenomenon centers around the description of trends between two data points and selecting the appropriate verb to express both the direction and intensity of movement. Our research shows that rather than simply selecting the same verbs again and again, variation and naturalness can be achieved by quantifying writers’ patterns of usage around verbs.
TRPV4-Mediated Calcium Influx into Human Bronchial Epithelia upon Exposure to Diesel Exhaust Particles

Background Human respiratory epithelia function in airway mucociliary clearance and barrier function and have recently been implicated in sensory functions. Objective We investigated a link between chronic obstructive pulmonary disease (COPD) pathogenesis and molecular mechanisms underlying Ca2+ influx into human airway epithelia elicited by diesel exhaust particles (DEP). Methods and Results Using primary cultures of human respiratory epithelial (HRE) cells, we determined that these cells possess proteolytic signaling machinery, whereby proteinase-activated receptor-2 (PAR-2) activates Ca2+-permeable TRPV4, which leads to activation of human respiratory disease–enhancing matrix metalloproteinase-1 (MMP-1), a signaling cascade initiated by diesel exhaust particles (DEP), a globally relevant air pollutant. Moreover, we observed ciliary expression of PAR-2, TRPV4, and phospholipase-Cβ3 in human airway epithelia and their DEP-enhanced protein–protein complex formation. We also found that the chronic obstructive pulmonary disease (COPD)–predisposing TRPV4P19S variant enhances Ca2+ influx and MMP 1 activation, providing mechanistic linkage between man-made air pollution and human airway disease. Conclusion DEP evoked protracted Ca2+ influx via TRPV4, enhanced by the COPD-predisposing human genetic polymorphism TRPV4P19S. This mechanism reprograms maladaptive inflammatory and extracellular-matrix–remodeling responses in human airways. The novel concept of air pollution–responsive ciliary signal transduction from PAR-2 to TRPV4 in human respiratory epithelia will accelerate rationally targeted therapies, possibly via the inhalatory route.
Named entity recognition in titles of Chinese videos from the web

Video title is the essential source of information used to describe video content in text-based video recommendation system. Automatically recognizing the named entities such as organizations, brand, and people in the titles of video from the Web is a difficult task. Owing to the characteristics of title-naming and Chinese video-up-loaders' habits, titles' length is always very short, and they can hardly provide enough information for recognizing. The abbreviations can always be found in titles also makes recognizing performance not satisfactory. In this paper, we propose a method which utilizes title' search results returned by search engine as the supplementary of titles. To overcome shortcomings of returning no relevant search results, we also utilize topic model to generate relevant context of titles. In experiments, 62305 Chinese automotive video titles are crawled from web for testing our method. The result shows that named entities in the informal form could be recognized in most titles, and the performance of named entity recognition is satisfactory.
Inviscid flow calculation around a flexible airship

In the context of an airship development programme, inviscid flow behavior and its coupling with structure flexibility are investigated. For this purpose, we have chosen a nonlinear analysis tool relying on the unsteady Euler model for the flow part and the classical elastodynamic equations for the structure. The numerical model for the flow is based on a Mixed Element Volume discretization derived in an Arbitrary-Lagrangian- Eulerian framework in order to cope with the structural deformations. The case of low- Mach flows (natural flight regime for an airship) can be handled by a special dissipation preconditioner which improves the accuracy of the flow simulation. The structural model, coupled to the flow solver, is discretized by the finite element method in a Lagrangian formulation. In this work we have performed a series of inviscid flow calculations with the goal to evaluate accurately the global aerodynamical coefficients. We first compare the influence of different stiffeners in the airship structural model for flows with zero and nonzero (20? ) angle of attack. Then, we study the influence of the numerical dissipation and of the low-Mach preconditioning. We observe -as expected- the stabilizing effect of the stiffeners, specially longitudinal ones. The positive impact of low Mach preconditioning and numerical dissipation on the results is also evaluated.
Contribution-Based User Reputation Modeling in Collaborative Recommender Systems

User reputation is an important factor in collaborative filtering approaches, in which every user may be another's nearest neighbor and may provide recommendations. In order to generate accurate results, the recommender system assigns different weights to users according to their reputations. However, existing methods for evaluating user reputation consider only the number of feedback ratings and cannot fully reflect user experience and credibility. In this paper, we propose a method of assigning reputations to nearest neighbors on the basis of their contributions in service recommendation. The contribution is evaluated by two factors: rating accuracy and importance of influence. Rating accuracy represents the consistency in perception between a neighbor and a consumer, and importance of influence determines the weight of a neighbor's rating. Using actual contributions as bases for modeling reputations prevents a neighbor from being penalized or awarded for another's poor or excellent recommendation behaviors. Experiment results show that the proposed approach can fairly assign reputation to each neighbor, thereby enhancing the credibility of a recommender system.
Medical image super-resolution with non-local embedding sparse representation and improved IBP

This paper proposes a novel super-resolution method that exploits the sparse representation and non-local similarity of patches for the effective reconstruction of images. High-resolution images are reconstructed from low resolution observations with an efficient technique based on the alternating direction method of multipliers (ADMM). A robust iterative back-projection approach is used in a post-processing step to remove residual noise and artifacts in the reconstructed image. Experiments on benchmark medical images illustrate the advantage of our method, in terms of PSNR and SSIM, compared to state of the art approaches.
An approach for early prediction of software reliability

In the early stages of development, failure information is not available to quantitatively measure reliability of a software product. In this context, we propose an approach to predict software reliability early in the product development stages from design metrics. First we predict reliabilities of the components of a system. For this, we categorize the different kinds of faults that can occur in a component during its development and identify the design metrics that correlate to these faults. We construct a Bayesian Belief Network (BBN) model to predict reliabilities of the components using the identified design metrics. Based on predicted reliabilities and usage frequencies of the components of a system, we determine the reliability of the system. The applicability of our proposed model is illustrated through a case study. Results obtained from our case study indicate the effectiveness of our approach
Selective Estrogen Receptor Modulators Suppress Hif1α Protein Accumulation in Mouse Osteoclasts

Anti-bone resorptive drugs such as bisphosphonates, the anti-RANKL antibody (denosumab), or selective estrogen receptor modulators (SERMs) have been developed to treat osteoporosis. Mechanisms underlying activity of bisphosphonates or denosumab in this context are understood, while it is less clear how SERMs like tamoxifen, raloxifene, or bazedoxifene inhibit bone resorption. Recently, accumulation of hypoxia inducible factor 1 alpha (Hif1α) in osteoclasts was shown to be suppressed by estrogen in normal cells. In addition, osteoclast activation and decreased bone mass seen in estrogen-deficient conditions was found to require Hif1α. Here, we used western blot analysis of cultured osteoclast precursor cells to show that tamoxifen, raloxifene, or bazedoxifene all suppress Hif1α protein accumulation. The effects of each SERM on osteoclast differentiation differed in vitro. Our results suggest that interventions such as the SERMs evaluated here could be useful to inhibit Hif1α and osteoclast activity under estrogen-deficient conditions.
Refined clothing texture parsing by exploiting the discriminative meanings of sparse codes

Texture parsing benefits attribute-based clothing analysis and related applications, such as clothing retrieval and recognition. To deal with the large variations of clothing textures, in this paper, a new method is presented in which refined texture attributes are parsed. Based on the characteristics of clothing textures, refined texture attributes are proposed and parameterized. To estimate the attribute parameters, we exploit the discriminative meanings of sparse codes: the underlying connections between the attribute parameters and each component of sparse codes. The attribute parameters are mapped from the dominating components of sparse codes. Our experiments demonstrate the effectiveness of the proposed method.
Delineation of QRS-complex, P and T-wave in 12-lead ECG

Summary An accurate and efficient method of detection and delineation of QRS-complexes, P-waves and T-waves in 12-lead ECG is presented in this paper. The delineation process is completely automatic and is based on detections done on the basis of adaptive quantized threshold of the QRS and non-QRS feature signal. The feature extraction is done using a modified definition of slope of the ECG signal. Due to the inclusion of slope and threshold, of ECG and feature signal respectively, the filtering of the raw ECG signal for noise removal and baseline drift removal become pre-requisite. The delineation performance of the proposed algorithm is validated using original ECG recordings from the dataset-3 of the CSE multi-lead measurement library. The delineation results obtained clearly indicate a high degree of agreement with the manual annotations done by the referees of CSE dataset-3.
BlueLearn: Low-Cost Interactive Learning System

In this paper, we describe BlueLearn, an interactive, location-aware learning environment, which can be utilized with minimum hardware investment from the learner’s side. The system is an extension and an application of the BlueInfo “automatic helpdesk” system we have demonstrated earlier. We outline a system that extends the basic idea of the BlueInfo to cover spatially and temporally wider applications, suitable for implementing interactive games and educational systems with reasonable cost.
Exploration and Study of Chinese Thesaurus Automation Construction for Digital Libraries

The paper aims to explore Chinese thesaurus automation construction based on the freely available digital library resources. The key methods and study results are presented in the paper. The study adopted the technology of natural language processing to analysis the linguistics characteristics of terms, and combined with statistical analysis to extract the terms from technical literatures. Our method consists of automatic extracting and filtering terms, judging and building relationship among terms. The study experiments run on the Java test platform. The study obtains the following conclusions: Finding the similarities and differences between the Chinese thesaurus standard and International thesaurus standard. The methods for the automatic extraction of terms and building relationship among them are presented. The study results show that the proposed methods can obtain better performance. The paper proposes a new thinking on thesaurus automation construction in the digital age. The presented method based on linguistics and statistics is a new attempt. According to the experiment results, this exploration and study is innovative and valuable. In addition, these thinking and methods give a good start for improving information services of the PRC’s National Science and Technology Digital Library.
Does JoiTech Messi dream of RoboCup Goal ?

We focus on two critical features in big size robot soccer. First, efficient training is one of the important issues for RoboCup teams to adapt their robots on site. Real robot’s training takes time and may damage the hardware while simulated one may miss the important factors to be improved. Second, to predict behavior of opponent robots is necessary for big size robots because they cannot move quickly so far. To overcome the issues we developed a versatile simulator and a smart strategy to improve accuracy of shoot and block. The former consists of multiple channels of inputs such as a real live video image stream, a real but already recorded one, and virtual one. The two kinds of outputs are real robot motor commands and virtual ones. We can have any combination of input/output to reduce the amount of training (less damage to real robot hardware) while improving the robot behavior. The latter, a strategy, consists of opponent recognition and adaptive action planning. The opponent (goalie or shooter) is detected by simple background subtraction, and its behavior is predicted based on the velocity in the image. This enables a shooter to find the space to shoot a ball, and for a goalie to block the goal from the opponent player’s shooting. We successfully applied the system to the RoboCup 2013 humanoid league adult size, and got the championship as well as the best humanoid award (”Louis Vuitton Cup”).
Parallel event-driven neural network simulations using the Hodgkin-Huxley neuron model

Neural systems are composed of a large number of highly-connected neurons and are widely simulated within the neurological community. In this paper, we examine the application of parallel discrete event simulation techniques to networks of a complex model called the Hodgkin-Huxley neuron. We describe the conversion of this model into an event-driven simulation, a technique that offers the potential of much greater performance in parallel and distributed simulations compared to time-stepped techniques. We report results of an initial set of experiments conducted to determine the feasibility of this parallel event-driven Hodgkin-Huxley model and analyze its viability for large-scale neural simulations.
Timed High-Order p Calculus and Multi-resolution Time Constraints

With the expansion of real-time software system scale, component-based real-time software is becoming mainstream. Timed π calculus and High-order π calculus as the software calculus system both can not describe dynamic nature of component-based real-time software. They also give the THO-π calculus which is time-character. According to making constraint to high-order process’s activities, They give the evolution rules of THO-π calculus, they give an new weak-time mutual simulation which is among the high-order process and they also give the concept about multi-resolution time constraint for the system-level calculus application. This article’s research paves the way for the dynamic architecture of component-based real-time software and the establishment of component-based real-time software’s description language.
STUDENT ENGAGEMENT IN COLLEGE: CONCEPT AND ASSESSMENT

STUDENT ENGAGEMENT IN COLLEGE: CONCEPT AND ASSESSMENT May 1 987 Victor M. H. Borden, B. A. University of Rochester M. S. , University of Massachusetts Ph. D. , University of Massachusetts Directed by: Professor George Levinger A student engagement model is proposed to provide a conceptual framework for understanding the bond between student and college. The impetus for developing this model originated from examining the literature on college student attrition; a literature that is diffuse and negative. The present model focuses attention away from attrition perse and toward a broader array of college outcomes. It also provides a rationale and a method for measuring student engagement. The validity of the model is examined in a study that tracks entering students through their first year in college. The model has two components. First, the engagement schema depicts students' psychological attachment to college. Second, the social context denotes social factors that influence psychological attachment. Four dimensions of engagement are described to facilitate measurement.
Quality, value, satisfaction and loyalty amongst race groups: A study of customers in the South African fast food industry

The retention of customers has become a key concern for many businesses. Various drivers of loyalty such as satisfaction, loyalty and commitment have, over time, been studied with the objective to improve customer retention. This study reports on the empirical findings in respect of the relationships between various dimensions of a loyalty model for the South African fast food sector and considers differences amongst race groups in respect of perceived quality, value, satisfaction and loyalty. Respondents in this empirical study were consumers drawn randomly from the seven major metropolitan areas of South Africa. The respondents are all customers of a national firm in the South African fast food sector and they were required to respond to items from (mostly) the American Customer Satisfaction Index (ACSI) scales. The empirical findings provide support for the theoretical model proposed but there is not much difference in how the various race groups’ loyalty intentions are shaped.
MicroRNA Profiling in Patients with Upper Tract Urothelial Carcinoma Associated with Balkan Endemic Nephropathy

Balkan endemic nephropathy (BEN) is a disease that affects people that live in the alluvial plains along the tributaries of the Danube River in the Balkan region. BEN is a chronic tubulointerstitial disease with a slow progression to terminal renal failure and has strong association with upper tract urothelial carcinoma (UTUC). There are several hypotheses about the etiology of BEN, but only the toxic effect of aristolochic acid has been confirmed as a risk factor in the occurrence of the disease. Aberrantly expressed miRNAs have been shown to be associated with many types of cancers. A number of studies have investigated the expression of microRNAs in urothelial carcinoma, mainly on urothelial bladder cancer, and only a few have included patients with UTUC. Here we present the first study of microRNA profiling in UTUC tissues from patients with BEN (BEN-UTUC) and patients with UTUC from nonendemic Balkan regions (non-BEN-UTUC) in comparison to normal kidney tissues. We found 10 miRNAs that were differentially expressed in patients with BEN-UTUC and 15 miRNAs in patients with non-BEN-UTUC. miRNA signature determined in BEN-UTUC patients differs from the non-BEN-UTUC patients; only miR-205-5p was mutual in both groups.