Miracle-dz/UniFAR-FTUs huggingface dataset:
Geno2pheno: estimating phenotypic drug resistance from HIV-1 genotypes

Therapeutic success of anti-HIV therapies is limited by the development of drug resistant viruses. These genetic variants display complex mutational patterns in their pol gene, which codes for protease and reverse transcriptase, the molecular targets of current antiretroviral therapy. Genotypic resistance testing depends on the ability to interpret such sequence data, whereas phenotypic resistance testing directly measures relative in vitro susceptibility to a drug. From a set of 650 matched genotype-phenotype pairs we construct regression models for the prediction of phenotypic drug resistance from genotypes. Since the range of resistance factors varies considerably between different drugs, two scoring functions are derived from different sets of predicted phenotypes. Firstly, we compare predicted values to those of samples derived from 178 treatment-naive patients and report the relative deviance. Secondly, estimation of the probability density of 2000 predicted phenotypes gives rise to an intrinsic definition of a susceptible and a resistant subpopulation. Thus, for a predicted phenotype, we calculate the probability of membership in the resistant subpopulation. Both scores provide standardized measures of resistance that can be calculated from the genotype and are comparable between drugs. The geno2pheno system makes these genotype interpretations available via the Internet (http://www.genafor.org/).
Study and Application of Moving Vehicle Image Matching Methods

it proposes a SIFT-RANSAC algorithm for the object recognition of moving vehicles combining the SIFT image matching theory and RANSAC algorithm. The paper designs a detection system, the Intelligent Traffic Management, which is used to solve the difficulties, such as traffic lanes changes, large body sizes and mutual interference between vehicles and so on, in the previous frame and the update frame. The experiments demonstrate that the SIFT-RANSAC algorithm has better performance.
An Agent Model for Collaborative Ubiquitous-Computing Environments

Besides technological challenges, there is a growing interest on how pervasive computing can deeply aect the way in which people interact and accomplish collaborative tasks. Context awareness plays a crucial role for communities, where the degree of participation of a single user dynamically changes in relation to the distance from the place where practices occur and in relation with the ability of gathering the right information at the right time, and in a proper way. In this paper, we adopt an interpretation of pervasive computing as an environment, populated by interconnected smart devices, where users can interact with each other, individually or in groups, to accomplish collaborative tasks. In other words, we aim at modeling, designing and realizing Collaborative Ubiquitous Environments (CUEs). We present an agent based model, balancing the management of such a complex scenario between agents and a structured multifaceted environment.
Selbstbeteiligung als Lösung für das Moral-Hazard-Problem auf dem Arzneimittelmarkt?

Within the debate about the rise of costs in the German health system, the argument has put forth that patients' excessive demand for benefits is caused by the existence of a moral hazard problem. One way of influencing an insured person's consumer behaviour is the introduction of several copayment models. The first task of this work is to examine the role of moral hazard in an insured person's consumer demand for drugs. Empirical evidence of this phenomenon is a central aspect of this task. Furthermore, the question if copayment is a suitable means of control to reduce the exorbitant demand for drugs will be answered. The focus here lies on the criteria effectiveness of control, reconcilabilty with the welfare state and effectiveness in general.
Robust active compliance control for practical grasping of a cylindrical object via a multifingered robot hand

It is essential to devise a safe compliant control scheme for grasping robots when active multifingered robot hands are interacting with a human or a fragile object. Hence, in this study, a novel active and robust compliant control technique is proposed by employing Integral Sliding Mode Control (ISMC). The ISMC allows us to use a model reference approach for which a virtual mass-spring damper can be introduced to enable compliant control. In addition, it is vital to have practical grasping to ensure a particular grasped object is reachable. For this, a cylindrical coordinate system is exploited due to its simplicity and geometric suitability, for the shape of objects to be grasped. This cylindrical coordinate system is centered at the grasped object. The performance of the ISMC is validated for the constrained underactuated BERUL (Bristol Elumotion Robot fingers) fingers. The results show that the approach is feasible for compliant interaction with objects of different softness in cylindrical space. Moreover, the compliance results show that the ISMC is robust towards nonlinearities and uncertainties in the robot fingers in particular friction and stiction.
Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes

Introduction The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Material and methods Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. Results There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. Conclusions The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes.
The MATRICs RF-FPGA in 180nm SiGe-on-SOI BiCMOS

MATRICs (Microwave Array Technology for Reconfigurable Integrated Circuits) is a DC-to-20 GHz general purpose reconfigurable array of RF circuits embedded in a flexible switch fabric. Fabricated in a commercial SiGe-on-SOI BiCMOS process, the MATRICs IC employs SiGe HBTs for high-linearity (> + 10 dBm IIP3) amplification and low phase-noise frequency generation, and SOI FETs for low-loss switching. It achieves high on-chip RF isolation (>80 dB at 16 GHz) due to the high-resistivity SOI substrate, differential signalling, and chip-scale flip-chip bump packaging. MATRICs will allow fixed-function RF systems to have the size, weight, and power benefits of a custom RF ASIC without the associated long development cycle and high NRE, and enable future RF subsystems to be dynamically reconfigured on-the-fly, adapting to changing environments.
The Evaluation of Preprocessing Choices in Single-Subject BOLD fMRI Using NPAIRS Performance Metrics

This work proposes an alternative to simulation-based receiver operating characteristic (ROC) analysis for assessment of fMRI data analysis methodologies. Specifically, we apply the rapidly developing nonparametric prediction, activation, influence, and reproducibility resampling (NPAIRS) framework to obtain cross-validation-based model performance estimates of prediction accuracy and global reproducibility for various degrees of model complexity. We rely on the concept of an analysis chain meta-model in which all parameters of the preprocessing steps along with the final statistical model are treated as estimated model parameters. Our ROC analog, then, consists of plotting prediction vs. reproducibility results as curves of model complexity for competing meta-models. Two theoretical underpinnings are crucial to utilizing this new validation technique. First, we explore the relationship between global signal-to-noise and our reproducibility estimates as derived previously. Second, we submit our model complexity curves in the prediction versus reproducibility space as reflecting classic bias-variance tradeoffs. Among the particular analysis chains considered, we found little impact in performance metrics with alignment, some benefit with temporal detrending, and greatest improvement with spatial smoothing.
Near-optimal lower bounds on the multi-party communication complexity of set disjointness

We study the communication complexity of the set disjointness problem in the general multiparty model. For t players, each holding a subset of a universe of size n, we establish a near-optimal lower bound of /spl Omega/(n/(t log t)) on the communication complexity of the problem of determining whether their sets are disjoint. In the more restrictive one-way communication model, in which the players are required to speak in a predetermined order, we improve our bound to an optimal /spl Omega/(n/t). These results improve upon the earlier bounds of /spl Omega/(n/t/sup 2/) in the general model, and /spl Omega/((/spl epsiv//sup 2/n)/t/sup 1+/spl epsiv//) in the one-way model, due to Bar-Yossef, Jayram, Kumar, and Sivakumar (2002). As in the case of earlier results, our bounds apply to the unique intersection promise problem. This communication problem is known to have connections with the space complexity of approximating frequency moments in the data stream model. Our results lead to an improved space complexity lower bound of /spl Omega/(n/sup 1-2/k//log n) for approximating the k/sup th/ frequency moment with a constant number of passes over the input, and a technical improvement to /spl Omega/(n/sup 1-2/k/) if only one pass over the input is permitted. Our proofs rely on the information theoretic direct sum decomposition paradigm of Bar-Yossef et al. [2002]. Our improvements stem from novel analytical techniques, as opposed to earlier techniques based on Hellinger and related distances, for estimating the information cost of protocols for one-bit functions.
Restoration of blur & noisy images using hybrid kernel-padding algorithm with transformation technique

Digital world is a dire need of the current scenario. Now these days equipments take the digital snapshots which may be blur due to bad focus of camera, relative motion between camera and scene to be capture etc. This is an extensive problem to restore this sort of images. This paper proposed a hybrid methodology to recover these images in order to improve the quality. This work uses the basic concept of kernel and padding. This work also applies the Haar wavelet Transform for filtering the image in order to reconstruct image which have the noise and blur. The results of this paper show that the proposed method gives the better result from the previous methods. It seems to be that the PSNR, Mean Square Rate and execution time is better in the proposed scheme.
Multiple Time Scales Recurrent Neural Network for Complex Action Acquisition

This paper presents novel results of complex action learning experiments based on the use of extended multiple timescales recurrent neural networks (MTRNN). The experiments were carried out with the iCub humanoid robot, as a model of the developmental learning of motor primitives as the basis of sensorimotor and linguistic compositionality. The model was implemented through the Aquila cognitive robotics toolkit, which supports the CUDA architecture and makes use of massively parallel GPUs (graphics processing units). The results presented herein show that the model was able to learn and successfully reproduce multiple behavioural sequences of actions in an object manipulation task scenario using large-scale MTRNNs. This forms the basis on ongoing experiments on action and language compositionality
Deterministic Regenerating Codes for Distributed Storage Yunnan

It is well known that erasure coding can be used in storage systems to efficiently store data while protecting against failures. Conventionally, the design of erasure codes has focused on the tradeoff between redundancy and reliability; under this criterion, an Maximum Distance Separable (MDS) code is optimal. However, practical storage systems call for additional considerations. In particular, the codes must be properly maintained to recover from node failures. Previous work by Dimakis et al. studied the problem of properly maintaining erasure codes to reduce the incurred network bandwidth, established fundamental bounds on the minimum repair bandwidth for maintaining MDS codes, and showed that the repair bandwidth can be reduced further at the cost of higher storage. In this paper we present techniques for constructing codes that achieve the optimal tradeoffs between storage efficiency and repair bandwidth.
An enhanced stage performance of Noh-Kyogen using motion data and sensor interactions

We produced "A Spider's Thread", a live stage performance employing live actors, CG characters and interactive technologies. The production integrated traditional Japanese dance expression of Noh and Kyogen classical theater, narrated text, and CG animations projected on screens. To present collaborative scenes of both real and virtual actors, we used CG characters created with motion data obtained from a professional Noh dancer in consistent of Noh style. Our experimental system enabled actors and spectators to interactively control the projected CG animations through their motions, which were obtained by three-axis accelerometers or cameras. The results of a questionnaire confirmed that CG animations and interactions were effective for live stage performances.
Proliferation of Keratinocytes Induced by Adipose-Derived Stem Cells on a Chitosan Scaffold and Its Role in Wound Healing, a Review

In the field of tissue engineering and reconstruction, the development of efficient biomaterial is in high demand to achieve uncomplicated wound healing. Chronic wounds and excessive scarring are the major complications of tissue repair and, as this inadequate healing continues to increase, novel therapies and treatments for dysfunctional skin repair and reconstruction are important. This paper reviews the various aspects of the complications related to wound healing and focuses on chitosan because of its unique function in accelerating wound healing. The proliferation of keratinocytes is essential for wound closure, and adipose-derived stem cells play a significant role in wound healing. Thus, chitosan in combination with keratinocytes and adipose-derived stem cells may act as a vehicle for delivering cells, which would increase the proliferation of keratinocytes and help complete recovery from injuries.
No evidence for an association between genetic variation at the MMP 2 and MMP 9 loci and aneurysmal subarachnoid haemorrhage

The matrix metalloproteinases (MMP) can degrade extracellular matrix (ECM) components, and alteration of the ECM leads to changes of the vessel wall. There is evidence that matrix remodelling plays a role in the formation and rupture of IA. MMP9 levels has been found to be increased in the aneurysmal wall [3], and both MMP2 and MMP9 was found to be overexpressed in cerebral ruptured aneurysms compared with unruptured aneurysms [4].
Cut-based classification for user behavioral analysis on social websites

Everyday millions of users can share or exchange their opinion through messages on social web sites. In various domains behavior analysis is critical for decision making. The behavioral data on social website can provide an economical and effective way to expose public opinion timely. The public behavior in messages can be used to obtain user feedback towards different company products; it can be utilized for marketing of different products or to track the popularity of different things. So there must be some methodologies to analyze user behavioral variations on social web sites and extract possible reasons behind such variations. This paper focuses on the analysis of user behavior on social networking sites. The analysis is carried out over various messages or text exchanged on the social network. Such analysis is helpful for taking certain decisions related to the trend prediction. The evaluation of the proposed methodology for behavior analysis is carried out in this paper on the basis of identified sentiments from the exchanged messages. A cut-based classification approach is proposed for analyzing the user's behavior in this paper.
How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data

The frequency with which scientists fabricate and falsify data, or commit other forms of scientific misconduct is a matter of controversy. Many surveys have asked scientists directly whether they have committed or know of a colleague who committed research misconduct, but their results appeared difficult to compare and synthesize. This is the first meta-analysis of these surveys. To standardize outcomes, the number of respondents who recalled at least one incident of misconduct was calculated for each question, and the analysis was limited to behaviours that distort scientific knowledge: fabrication, falsification, “cooking” of data, etc… Survey questions on plagiarism and other forms of professional misconduct were excluded. The final sample consisted of 21 surveys that were included in the systematic review, and 18 in the meta-analysis. A pooled weighted average of 1.97% (N = 7, 95%CI: 0.86–4.45) of scientists admitted to have fabricated, falsified or modified data or results at least once –a serious form of misconduct by any standard– and up to 33.7% admitted other questionable research practices. In surveys asking about the behaviour of colleagues, admission rates were 14.12% (N = 12, 95% CI: 9.91–19.72) for falsification, and up to 72% for other questionable research practices. Meta-regression showed that self reports surveys, surveys using the words “falsification” or “fabrication”, and mailed surveys yielded lower percentages of misconduct. When these factors were controlled for, misconduct was reported more frequently by medical/pharmacological researchers than others. Considering that these surveys ask sensitive questions and have other limitations, it appears likely that this is a conservative estimate of the true prevalence of scientific misconduct.
An analytic study of a distributed EDCA-based QoS mapping for layered video delivery in WLAN

One of the key challenges in multimedia networks is video delivery over wireless channels. MRC (Multi-Resolution Coding) Layered video, divides video into a base layer and multiple enhancement layers. In this paper, we aim to improve video quality, impacted by high channel contention, through mapping individual video layers to EDCA (Enhanced Distributed Channel Access) access categories in order to maximize the average number of reconstructed video layers. We propose an adaptive cross layer video layers mapping technique that optimally enhances the QoS of wireless video transmission over IEEE 802.11e EDCA priority queues. The optimization is based on a dynamic program that takes into account the EDCA parameters and the layered dependency nature of layered video delivery. Our proposed technique makes use of a channel delay estimation model and an estimation of average video useful layers delivered. The optimal mapping strategies are selected by an optimization module based on the information from the analytical model. The accuracy of our optimized mapping technique performance is verified through extensive simulations. The obtained results illustrate significant trade-off between complexity and delivered video quality for canonical mapping schemes.
Stability of Java interfaces: a preliminary investigation

The attribute of stability is regarded by some as an important attribute of software. Some claims regarding software design quality imply that what are called interfaces in Java are stable. This paper introduces some new metrics for investigating such claims, and presents some preliminary measurements from these metrics, which indicate that developers do not consistently develop stable interfaces.
Vision: mapping the world in 3d through first-person vision devices with mercator

Many vision-based applications, especially in the domain of augmented reality, must align the camera position in the observed scene. However, traditional cameras only register textures of the observed scene. The reconstruction of depth information from 2D images is compute intensive and inevitably results in loss of accuracy. In this article, we present Mercator, a cloudlet-based system to build a 3D model of the world on which other applications can be built. The model is continuously updated, refined and expanded by crowd-sourcing depth data from 3D cameras on head-mounted devices such as Google Glass. Mercator scales up to a worldwide system by distributing the model over the network edge in geographically close cloudlets. We present the software building blocks of the system, and discuss challenges related to data management, privacy and programming model.
Monetary Policy Shifts and the Term Structure

We estimate the effect of shifts in monetary policy using the term structure of interest rates. In our no-arbitrage model, the short rate follows a version of the Taylor (1993) rule where the coefficients on the output gap and inflation vary over time. The monetary policy loading on the output gap has averaged around 0.4 and has not changed very much over time. The overall response of the yield curve to output gap components is relatively small. In contrast, the inflation loading has changed substantially over the last 50 years and ranges from close to zero in 2003 to a high of 2.4 in 1983. Long-term bonds are sensitive to inflation policy shifts with increases in inflation loadings leading to higher short rates and widening yield spreads.
Design Optimization of Short-Stroke Single-Phase Tubular Permanent-Magnet Motor for Refrigeration Applications

This paper describes a design methodology to achieve optimal performance for a short-stroke single-phase tubular permanent-magnet motor which drives a reciprocating vapor compressor. The steady-state characteristic of the direct-drive linear-motor compressor system is analyzed, an analytical formula for predicting iron loss is presented, and a motor-design procedure which takes into account the effect of compressor loads under nominal operating condition is formulated. It is shown that the motor efficiency can be optimized with respect to two leading dimensional ratios. Experimental results validate the proposed design methodology.