Miracle-dz/UniFAR-FTUs huggingface dataset:
A RapidMiner framework for protein interaction extraction

During the last 10 years researchers have proposed many approaches to automatically extract protein-protein interactions (PPIs) from scientific papers. However, the lack of a unified implementation and evaluation framework complicates the development of new PPI methods and makes the comparison of existing methods difficult. In this paper we present such a framework that is built as an extension of RapidMiner. Next to providing a platform for evaluating and comparing different text mining methods for PPI extraction, the framework can also be leveraged to build a standalone application that can accumulate the mined interaction data and make it available to biologists for querying. We illustrate the utility of the developed framework with a prototype of a protein interaction search engine.
The Importance of Cellular VEGF Bioactivity in the Development of Glomerular Disease

The bioactivity of glomerular VEGF (or activity of available VEGF) is critical to the physiological maintenance of the glomerular filtration barrier. Disturbances in glomerular VEGF expression have been linked to numerous glomerulopathies, highlighting its importance in disease progression within the kidney. However, the changes in expression are not consistent between conditions; enhanced expression sometimes appears to have a renoprotective effect, yet at other times it appears destructive. Also, the level of expression can change with the progression of disease. This review focuses on how other cellular factors, such as TGF-β and nitric oxide, work in concert to affect the bioactivity, which is not necessarily the same as the expression of VEGF, in different glomerulopathies and attempts to explain some of the paradoxes between glomerulopathies. In conclusion, the bioactivity of glomerular VEGF is regulated by many factors that are themselves moderated by changes in the local glomerular environment, such as mechanical strain and hyperglycaemia. Thus, to understand VEGF signalling in glomerular disease progression, we must examine it in the context of other appropriate cellular factors.
Emerging Roles of Propolis: Antioxidant, Cardioprotective, and Antiangiogenic Actions

Propolis has attracted attention in recent years due to its beneficial effects, which make it a potential preventive and therapeutic agent as well as a useful additive in food and cosmetics. The aim of this review is to discuss the growing evidence that propolis may, via a diverse array of biological actions, assist in the prevention of some inflammation-mediated pathologies including cardiovascular disease. The active components of propolis that have been identified so far include polyphenols and flavonoids. These compounds have cardioprotective, vasoprotective, antioxidant, antiatherosclerotic, anti-inflammatory and antiangiogenic actions. Many studies have been undertaken to elucidate the mechanism(s) by which propolis acts, which involve cellular signaling targets and interactions at the genomic level. This review will highlight the effects of propolis that may assist in the prevention of chronic degenerative diseases, such as cardiovascular disease.
Feedback centré sur une facette de la performance et pression financière interne dans le cadre de la réalisation d’une tâche complexe : une étude dans les hôpitaux publics français

The purpose of this paper is to test the impact of feedback based on a partial evaluation of the performance on the financial pressure perceived in a complex task context. Based on a quantitative study of 578 doctors in 14 University Hospital Centers (CHU), we demonstrate that feedback based on a partial evaluation of the performance is associated with the perception of internal financial pressure. These results point to the importance of the multiple evaluation of the task dimensions in order to improve performance.
Building a minimal traffic model from mobile phone data

We investigate setting up a traﬃc simulation scenario only from a high spatial resolution set of mobile phone trajectories and an OpenStreetMap road network model. Mixed road traﬃc is modelled as the result of a choice for each user between a simulated congested car mode and a non-congested alternative mode parameterized by its speed.
Support for data-intensive computing with CloudMan

Infrastructure-as-a-Service (IaaS) compute infrastructure model has showcased its ability to transform how access to compute resources is realized; it delivered on the notion of Infrastructure-as-Code and enabled a new wave of compute adaptability. In previous work we have been developing CloudMan (usecloudman.org) as a versatile solution for enabling and managing compute clusters in cloud environments via a simple web interface or an API. However, CloudMan only supported batch processing workloads. As the magnitude of the data produced and processed in digital form grows, the need to support big data applications in clusters in the cloud becomes more evident. In this paper, we have extended the batch processing capability of CloudMan and presenteda novel architecture for supporting big data analysis workloads in cluster-in-the-cloud environment. We also implemented the details through CloudMan using established big data platforms.
Automotive LIDAR sensor development scenarios for harsh weather conditions

This article focuses on development baseline for a novel LIDAR for future autonomous cars, which require perception not only in clear weather, but also under harsh weather conditions such as fog and rain. Development of automotive laser scanners is bound to the following requirements: maximize sensor performance, assess the performance level and keep the scanner component costs reasonable (<;1000 €) even if more expensive optical and electronic components are needed. The objective of this article is to review the existing automotive laser scanners and their capabilities to pave the way for developing new scanner prototypes, which are more capable in harsh weather conditions. Testing of scanner capabilities has been conducted in the northern part of the Finland, at Sodankylä Airport, where fog creates a special problem. The scanner has been installed in the airport area for data gathering and analyzes if fog, snow or rain are visible in the scanner data. The results indicate that these conditions degrade sensor performance by 25%, and therefore, future work in software module development should take this into account with in-vehicle system performance estimations concerning the visual range of the scanner. This allows the vehicle to adapt speed, braking distance and stability control systems accordingly.
St Reading Nonlinear Feature Extraction Using Fisher Criterion

In this paper the problem of nonlinear feature extraction based on the optimization of the Fisher criterion is analyzed. A new nonlinear feature extraction method is proposed. The 15 method does not make use of numerical algorithms and it has an analytical (closed-form) solution. Moreover, no assumptions on the class probability distribution functions are 17 imposed. The proposed method is applied to some standard pattern recognition problems and compared with other classical methodologies already proposed in the literature. The 19 performance of the proposed method turned out to be superior when compared with the other methods studied. 21
Tunable THz surface plasmon polariton based on a topological insulator/layered superconductor hybrid structure

We theoretically investigate the surface plasmon polariton (SPP) at the interface between a three-dimensional strong topological insulator (TI) and a layered superconductor/magnetic insulator structure, within the random phase approximation. The tunability of the SPP through electronic doping can be enhanced when the magnetic permeability of the layered structure becomes higher. When the interface is gapped by superconductivity or perpendicular magnetism, the SPP dispersion is further distorted, accompanied by a shift of group velocity and penetration depth. Such a shift of the SPP reaches a maximum when the magnitude of the Fermi level approaches the gap value, and may lead to observable effects. The tunable SPP at the interface between layeredsuperconductor and magnetic materials in proximity to the TI surface may provide new insight in the detection of Majorana fermions.
Dynamic Heterogeneous Scheduling Decisions Using Historical Runtime Data

Heterogeneous systems often employ processing units with a wide spectrum of performance capabilities. Allowing individual applications to make greedy local scheduling decisions leads to imbalance, with underutilization of some devices and excessive contention for others. If we instead allow the system to make global scheduling decisions and assign some applications to a slower device, we can both increase overall system throughput and decrease individual application runtimes. We present a method for dynamically scheduling applications running on heterogeneous platforms in order to maximize overall throughput. The key to our approach is accurately estimating when an application would finish execution on a given device based on historical runtime information, allowing us to make scheduling decisions that are both globally and locally efficient. We evaluate our approach with a set of OpenCL applications running on a system with a multicore CPU and a discrete GPU. We show that scheduling decisions based on historical data can decrease the total runtime by 39% over GPU-only scheduling and 29% over scheduling that places each application on its preferred device.
Maximum Likelihood trajectory estimation of a mobile node from RSS measurements

In this paper we present a Maximum Likelihood (ML) trajectory estimation of a mobile node from Received Signal Strength (RSS) measurements. The reference scenario includes a number of nodes in fixed and known positions (anchors) and a target node (blind) in motion whose instantaneous position is unknown. We first consider the dynamic estimation of the channel parameters from anchor-to-anchor measurements, statistically modeled according to the well-known Path-Loss propagation model. Then, we address the ML estimation problem for the position and velocity of the blind node based on a set of blind-to-anchor RSS measurements. We compare also the algorithm with a ML-based single-point localization algorithm, and discuss the applicability of both methods for slowly moving nodes. We present simulation results to assess the accuracy of the proposed solution in terms of localization error and velocity estimation (modulus and angle). The distribution of the localization error on the initial and final point is analyzed and closed-form expressions are derived.
Complementary effect of regulatory environment and accounting conservatism on investment efficiency

This paper analyses the impact of regulatory environments and accounting conservatism on the investment efficiency of Chinese listed firms for the period of 2007-2011. Unlike the existing studies which neglect the combined effect of regulatory environments and accounting conservatism on investment efficiency, this study figures out whether complementary or alternative effect regulatory environments and accounting conservatism have on the investment efficiency. Results show that in the case of insufficient investment, regulatory environments and accounting conservatism improve the investment efficiency respectively, and when interacting, regulatory environments enlarge the effect of accounting conservatism complementarily.
Dual-Band Resistance Compression Networks for Improved Rectifier Performance

In this work, the concept of dual-band resistance compression networks is introduced and applied to the design of rectifier circuits with improved performance. The use of resistance compression networks (RCNs) minimizes the sensitivity of rectifier circuits to variations in the surrounding environment, such as input power level and changes in the rectifier load. The proposed dual-band RCN can be used as the matching network located between the antenna and the rectifying element of a dual-band rectifier for energy harvesting applications. A dual-band ( 915 MHz /2.45 GHz) rectifier based on RCN is designed and characterized showing improved performance in comparison with a conventional dual-band envelope detector by exhibiting improved RF-dc conversion efficiency and reduced sensitivity versus output load and input power variations.
Anatomical variations of the celiac trunk and hepatic arterial system: an analysis using multidetector computed tomography angiography*

Objective To analyze the prevalence of anatomical variations of celiac arterial trunk (CAT) branches and hepatic arterial system (HAS), as well as the CAT diameter, length and distance to the superior mesenteric artery. Materials and Methods Retrospective, cross-sectional and predominantly descriptive study based on the analysis of multidetector computed tomography images of 60 patients. Results The celiac trunk anatomy was normal in 90% of cases. Hepatosplenic trunk was found in 8.3% of patients, and hepatogastric trunk in 1.7%. Variation of the HAS was observed in 21.7% of cases, including anomalous location of the right hepatic artery in 8.3% of cases, and of the left hepatic artery, in 5%. Also, cases of joint relocation of right and left hepatic arteries, and trifurcation of the proper hepatic artery were observed, respectively, in 3 (5%) and 2 (3.3%) patients. Mean length and caliber of the CAT were 2.3 cm and 0.8 cm, respectively. Mean distance between CAT and superior mesenteric artery was 1.2 cm (standard deviation = 4.08). A significant correlation was observed between CAT diameter and length, and CAT diameter and distance to superior mesenteric artery. Conclusion The pattern of CAT variations and diameter corroborate the majority of the literature data. However, this does not happen in relation to the HAS.
Courage in the workplace: The effects of organizational level and gender on the relationship between behavioral courage and job performance

Abstract This study examines the relationship between behavioral courage and job performance, and explores the possible effects of organizational level and gender on this relationship. With a sample of managers from mid- to large-sized for-profit organizations in the United States, we found that behavioral courage was positively associated with job performance. Our results also revealed significant differences in supervisors’ ratings of behavioral courage between employees at low and high organizational levels. The effects of behavioral courage on job performance did not vary by organizational level. In turn, the moderating effect of gender on the association between behavioral courage and job performance was supported. The study results provide important theoretical and practical implications in the fields of organizational behavior, leadership studies, and human resource development. Recommendations for future research are discussed.
Centered complexity one Hamiltonian torus actions

We consider symplectic manifolds with Hamiltonian torus actions which are “almost but not quite completely integrable”: the dimension of the torus is one less than half the dimension of the manifold. We provide a complete set of invariants for such spaces when they are “centered” and the moment map is proper. In particular, this classifies the preimages under the moment map of all sufficiently small open sets, which is an important step towards global classification. As an application, we construct a full packing of each of the Grassmannians Gr(2,R5) and Gr(2,R6) by two equal symplectic balls.
The Optimal Mechanism for Selling to a Budget-Constrained Buyer

This paper finds an optimal mechanism for selling an indivisible good to consumers who may be budget-constrained. Unlike the case where buyers are not budget constrained, a single posted price is not typically optimal. An optimal mechanism generally consists of a continuum of lotteries indexed by the probability of comsumption and the entry fee.
Ambulatory Multi-Drug Resistant Tuberculosis Treatment Outcomes in a Cohort of HIV-Infected Patients in a Slum Setting in Mumbai, India

Background India carries one quarter of the global burden of multi-drug resistant TB (MDR-TB) and has an estimated 2.5 million people living with HIV. Despite this reality, provision of treatment for MDR-TB is extremely limited, particularly for HIV-infected individuals. Médecins Sans Frontières (MSF) has been treating HIV-infected MDR-TB patients in Mumbai since May 2007. This is the first report of treatment outcomes among HIV-infected MDR-TB patients in India. Methods HIV-infected patients with suspected MDR-TB were referred to the MSF-clinic by public Antiretroviral Therapy (ART) Centers or by a network of community non-governmental organizations. Patients were initiated on either empiric or individualized second-line TB-treatment as per WHO recommendations. MDR-TB treatment was given on an ambulatory basis and under directly observed therapy using a decentralized network of providers. Patients not already receiving ART were started on treatment within two months of initiating MDR-TB treatment. Results Between May 2007 and May 2011, 71 HIV-infected patients were suspected to have MDR-TB, and 58 were initiated on treatment. MDR-TB was confirmed in 45 (78%), of which 18 (40%) were resistant to ofloxacin. Final treatment outcomes were available for 23 patients; 11 (48%) were successfully treated, 4 (17%) died, 6 (26%) defaulted, and 2 (9%) failed treatment. Overall, among 58 patients on treatment, 13 (22%) were successfully treated, 13 (22%) died, 7 (12%) defaulted, two (3%) failed treatment, and 23 (40%) were alive and still on treatment at the end of the observation period. Twenty-six patients (45%) experienced moderate to severe adverse events, requiring modification of the regimen in 12 (20%). Overall, 20 (28%) of the 71 patients with MDR-TB died, including 7 not initiated on treatment. Conclusions Despite high fluoroquinolone resistance and extensive prior second-line treatment, encouraging results are being achieved in an ambulatory MDR-T- program in a slum setting in India. Rapid scale-up of both ART and second-line treatment for MDR-TB is needed to ensure survival of co-infected patients and mitigate this growing epidemic.
MIMO Radar Moving Target Detection in Homogeneous Clutter

A multiple-input multiple-output (MIMO) radar approach employing widely dispersed transmit and receive antennas is studied for the detection of moving targets. The MIMO radar transmits orthogonal waveforms from the different transmit antennas so these waveforms can be separated at each receive antenna. For a moving target in colored Gaussian noise-plus-clutter, we quantify the gains from having widely dispersed antennas that allow the overall system to "view" the target simultaneously from several different directions. The MIMO radar performance is contrasted with that of a traditional phased-array approach, which employs closely spaced antennas for this purpose. The MIMO radar approach is well suited to handle targets that have small radial velocities for scenarios in which colocated sensors cannot separate the target from the background clutter. Both a centralized processing and a simple distributed processing form of the MIMO radar approach are developed and studied, and the gains from the centralized version, which come at the price of additional complexity, are clearly demonstrated and explained intuitively. The constant false alarm rate (CFAR) property of an adaptive version of the MIMO moving target detector is also demonstrated for homogeneous clutter.
University of Huddersfield Repository Using visual analytics to make sense of railway Close Calls

In the big data era large and complex data sets will exceed scientists' capacity to make sense of them in the traditional way. New approaches in data analysis, supported by computer science, will be necessary to address the problems that emerge with the rise of big data. The analysis of the Close Call database, which is a text-based database for near-miss reporting on the GB railways provides a test case. The traditional analysis of Close Calls is time-consuming and prone to differences in interpretation. This paper investigates the use of visual analytics techniques, based on network text analysis, to conduct data analysis and extract safety knowledge from 500 randomly selected Close Call records relating to worker slips, trips and falls. The results demonstrate a straightforward, yet effective, way to identify hazardous conditions without having to read each report individually. This opens up new ways to perform data analysis in safety science.
Workspace Analysis and Singularity-free Path Planning of Parallel Manipulators

This paper presents a new technique for path planning inside the workspace of parallel manipulators avoiding singularity or voids. The paper rst describes a generic numerical algorithm for the analysis of reachable workspace of parallel manipulators. It gives a clear visualization of boundary of the workspace with voids inside it. Then the singularity points are determined inside this workspace by using a numerical method. These points are distributed to several clusters by using a density based clustering algorithm which are then modeled as obstacles. Subsequently, a path planning algorithm is used to nd an optimal path avoiding these obstacles. In case, any singularity point lies on the path or the path comes too close to a singular point, the path is restructured to avoid that point till it again joins the optimal path. The algorithm is uniformly applicable to any combinations of revolute and prismatic joints in the con guration of the leg. A three-legged modular parallel manipulator is taken to demonstrate the e ectiveness of the algorithm. From the results obtained, the algorithm is found to be e ective.
Supporting personalized top-k skyline queries using partial compressed skycube

As near-infinite amount of data are becoming accessible on the Web, it is getting more and more important to support intelligent query mechanisms, to help each user to identify the ideal results of manageable size. As such mechanism, skyline queries have gained a lot of attention lately for its intuitive query formulation. This intuitiveness, however, has a side-effect of generating too many results, especially for high-dimensional data, to satisfy a wide range of user's needs. Our goal is to support personalized skyline queries as identifying "truly interesting" objects based on user-specific preference and retrieval size k. While this problem has been studied previously, the proposed solution identifies top-k results by navigating a "skycube", which incurs exponential storage overhead to data dimensionality and excessive one-time computational overhead for skycube construction. In contrast, we develop novel techniques to significantly reduce both storage and computation overhead. Our extensive evaluation results validate this framework on both real-life and synthetic data.
Analytics for Software Project Management -- Where are We and Where do We Go?

Software project management is a decision intensive process. Success or failure of the project is highly dependent on these decisions. Analytical techniques and tools can support project managers throughout the software project life cycle by increasing the predictability and chance of success in these projects. In this paper, we report the results of a systematic mapping study within which we investigate the usage of different types of analytics for software project management. We analyze the accessibility of the data as well as the degree of validation reported in the 115 studies selected for final analysis. This resulted in a picture of the status quo (Where are we? ) of analytics in software project management. From comparing this status quo with the results of an industrial survey on the industrial needs of different types of analysis, we propose an agenda on future work (Where do we go? ).