Miracle-dz/UniFAR-FTUs huggingface dataset:
Lack of association between an estrogen receptor 1 gene polymorphism and Parkinson's disease with dementia

Objective– To test for an association between an estrogen receptor 1 (ESR1) gene polymorphism and Parkinson's disease with dementia (PDD) in Finnish subjects. Subjects and methods– Forty‐one clinically demented and pathologically confirmed PDD patients and 59 cognitively intact aged individuals with normal neuropathology were genotyped for the ESR1 PvuII polymorphism. Results– We found no significant differences in the genotype or allele frequencies when the PDD patients were compared with the controls. Nor were there any significant differences in these frequencies when the PDD patients with coexisting Alzheimer's disease pathology were compared with the control group. Conclusion– We failed to demonstrate an association between dementia‐associated PD and the ESR1 PvuII polymorphism in Finnish subjects.
Choosing The Right Power MOSFET Package

Introduction Power levels and power density requirements continue to increase for many types of end equipment such as personal computers, servers, network and telecom systems. It demands higher performance from the components that make up the power management system. Until recently silicon has been the most important factor in improving power management system performance. However, improvements in silicon technology over the years have significantly reduced MOSFET RDS(on) and the amount of heat generated by power semiconductors to the point where packaging becomes the limit to higher performance devices. As system current requirements increase exponentially, many advanced power MOSFET packages have been introduced to the market. The popular packages include DPAK, SO-8, CopperStrapTM SO-8, PowerPakTM, LFPAKTM, DirectFETTM, iPOWIRTM, etc. While offering more design freedom, too many choices can also be confusing, especially to an embedded power supply designer, who has limited resources to experiment with all these unfamiliar devices. This article will compare each package, and simplify the component selection by highlighting the performance difference in the embedded applications.
Is the auditory evoked P2 response a biomarker of learning?

Even though auditory training exercises for humans have been shown to improve certain perceptual skills of individuals with and without hearing loss, there is a lack of knowledge pertaining to which aspects of training are responsible for the perceptual gains, and which aspects of perception are changed. To better define how auditory training impacts brain and behavior, electroencephalography (EEG) and magnetoencephalography (MEG) have been used to determine the time course and coincidence of cortical modulations associated with different types of training. Here we focus on P1-N1-P2 auditory evoked responses (AEP), as there are consistent reports of gains in P2 amplitude following various types of auditory training experiences; including music and speech-sound training. The purpose of this experiment was to determine if the auditory evoked P2 response is a biomarker of learning. To do this, we taught native English speakers to identify a new pre-voiced temporal cue that is not used phonemically in the English language so that coinciding changes in evoked neural activity could be characterized. To differentiate possible effects of repeated stimulus exposure and a button-pushing task from learning itself, we examined modulations in brain activity in a group of participants who learned to identify the pre-voicing contrast and compared it to participants, matched in time, and stimulus exposure, that did not. The main finding was that the amplitude of the P2 auditory evoked response increased across repeated EEG sessions for all groups, regardless of any change in perceptual performance. What’s more, these effects are retained for months. Changes in P2 amplitude were attributed to changes in neural activity associated with the acquisition process and not the learned outcome itself. A further finding was the expression of a late negativity (LN) wave 600–900 ms post-stimulus onset, post-training exclusively for the group that learned to identify the pre-voiced contrast.
A Ranking-Oriented Hybrid Approach to QoS-Aware Web Service Recommendation

Nowadays, more and more service consumers pay great attention to QoS (Quality of Service) when they find and select appropriate Web services. For most of the approaches to QoS-aware Web service recommendation, the list of Web services recommended to target users is generally obtained based on rating-oriented predictions, aiming at predicting the potential ratings that a target user may assign to the unrated services as accurately as possible. However, in some scenarios, high accuracy of rating predictions may not necessarily lead to satisfactory recommendation results. In this paper, we propose a ranking-oriented hybrid approach by combining item-based collaborative filtering techniques and latent factor models to address the problem of Web services ranking. In particular, the similarity between two Web services is measured in terms of the correlation coefficient between their rankings instead of between their ratings. Comprehensive experiments on the QoS data set composed of real-world Web services are conducted to test our approach, and the experimental results demonstrate that our approach outperforms other competing approaches.
PLSA-Based Sparse Representation for Object Classification

This paper proposes a novel object classification method which uses the concept of probabilistic latent semantic analysis (pLSA) to overcome the problem of sparse representation in data classification. Sparse representation is widely used and quite successful in many vision-based applications. However, it needs to calculate the sparse reconstruction cost (SRC) of each sample to find the best candidate. Because an optimization process is involved, it is very inefficient. In addition, it uses only the residual and does not consider the arrangement (or distribution) of combination coefficients of visual codes in classification. Thus, it often fails to classify categories if they are similar. In this paper, the pLSA concept is first introduced into the sparse representation to build a new classifier without using the SRC measure. The weakness of the pLSA scheme is the use of EM algorithm for updating the posteriori probability of latent class. Because it is very time-consuming, a novel weighting voting strategy is introduced to improve the pLSA scheme for recognizing objects in real time. The advantages of this classifier are: the accuracy is much higher than the SRC scheme and the efficiency is real-time in data classification. Two applications are demonstrated in this paper to prove the superiority of the new classifier, i.e., vehicle make and model recognition, and action analysis.
Stochastic Measurement Models for Quantifying Lymphocyte Responses Using Flow Cytometry

Adaptive immune responses are complex dynamic processes whereby B and T cells undergo division and differentiation triggered by pathogenic stimuli. Deregulation of the response can lead to severe consequences for the host organism ranging from immune deficiencies to autoimmunity. Tracking cell division and differentiation by flow cytometry using fluorescent probes is a major method for measuring progression of lymphocyte responses, both in vitro and in vivo. In turn, mathematical modeling of cell numbers derived from such measurements has led to significant biological discoveries, and plays an increasingly important role in lymphocyte research. Fitting an appropriate parameterized model to such data is the goal of these studies but significant challenges are presented by the variability in measurements. This variation results from the sum of experimental noise and intrinsic probabilistic differences in cells and is difficult to characterize analytically. Current model fitting methods adopt different simplifying assumptions to describe the distribution of such measurements and these assumptions have not been tested directly. To help inform the choice and application of appropriate methods of model fitting to such data we studied the errors associated with flow cytometry measurements from a wide variety of experiments. We found that the mean and variance of the noise were related by a power law with an exponent between 1.3 and 1.8 for different datasets. This violated the assumptions inherent to commonly used least squares, linear variance scaling and log-transformation based methods. As a result of these findings we propose a new measurement model that we justify both theoretically, from the maximum entropy standpoint, and empirically using collected data. Our evaluation suggests that the new model can be reliably used for model fitting across a variety of conditions. Our work provides a foundation for modeling measurements in flow cytometry experiments thus facilitating progress in quantitative studies of lymphocyte responses.
Editorial: Biodegradable Materials

This Special Issue “Biodegradable Materials” features research and review papers concerning recent advances on the development, synthesis, testing and characterisation of biomaterials. These biomaterials, derived from natural and renewable sources, offer a potential alternative to existing non-biodegradable materials with application to the food and biomedical industries amongst many others. In this Special Issue, the work is expanded to include the combined use of fillers that can enhance the properties of biomaterials prepared as films. The future application of these biomaterials could have an impact not only at the economic level, but also for the improvement of the environment.
WSEmail: secure Internet messaging based on Web services

Web services offer an opportunity to redesign a variety of older systems to exploit the advantages of a flexible, extensible, secure set of standards. In this paper we explore the objective of improving Internet messaging (email) by redesigning it as a family of Web services, an approach we call WSEmail. We illustrate an architecture and describe some applications. Since increased flexibility often mitigates against security and performance, we focus on steps for proving security properties and measuring the performance of our system with its security operations. In particular, we demonstrate an automated proof using TulaFale and ProVerif of a correspondence theorem for an application called on-demand attachments. We also provide performance measures for the basic WSEmail functions in a prototype we have implemented using . NET. Our experiments show a latency of about a quarter of a second per transaction under load.
Is Sniping A Problem For Online Auction Markets?

A common complaint about online auctions for consumer goods is the presence of ``snipers,'' who place bids in the final seconds of sequential ascending auctions with predetermined ending times. The literature conjectures that snipers are best-responding to the existence of ``incremental" bidders that bid up to their valuation only as they are outbid. Snipers aim to catch these incremental bidders at a price below their reserve, with no time to respond. As a consequence, these incremental bidders may experience regret when they are outbid at the last moment at a price below their reservation value. We measure the effect of this experience on a new buyer's propensity to participate in future auctions. We show the effect to be causal using a carefully selected subset of auctions from eBay.com and instrumental variables estimation strategy. Bidders respond to sniping quite strongly and are between 4 and 18 percent less likely to return to the platform.
From Requirements to Features: An Exploratory Study of Feature-Oriented Refactoring

More and more frequently successful software systems need to evolve into families of systems, known as Software Product Lines (SPLs), to be able to cater to the different functionality requirements demanded by different customers while at the same time aiming to exploit as much common functionality as possible. As a first step, this evolution demands a clear understanding of how the functional requirements map into the features of the original system. Using this knowledge, features can be refactored so that they are reused for building the new systems of the evolved SPL. In this paper we present our experience in refactoring features based on the requirements specifications of a small and a medium size systems. Our work identified eight refactoring patterns that describe how to extract the elements of features which were subsequently implemented using Feature Oriented Software Development (FOSD) a novel modularization paradigm whose driving goal is to effectively modularize features for the development of variable systems. We argue that the identification of refactoring patterns are a stepping stone towards automating Feature-Oriented Refactoring, and present some open issues that should be addressed to that avail.
Quantitative assessment of left ventricular volume and ejection fraction using two-dimensional speckle tracking echocardiography.

AIMS Two-dimensional speckle tracking echocardiography (2DSTE) allows measurements of left ventricular (LV) volumes and LV ejection fraction (LVEF) without manual tracings. Our goal was to determine the accuracy of 2DSTE against real-time 3D echocardiography (RT3DE) and against cardiac magnetic resonance (CMR) imaging. METHODS AND RESULTS In Protocol 1, 2DSTE data in the apical four-chamber view (iE33, Philips) and CMR images (Philips 1.5T scanner) were obtained in 20 patients. The 2DSTE data were analysed using custom software, which automatically performed speckle tracking analysis throughout the cardiac cycle. LV volume curves were generated using the single-plane Simpson's formula, from which end-diastolic volume (LVEDV), end-systolic volume (LVESV), and LVEF were calculated. In Protocol 2, the 2DSTE and RT3DE data were acquired in 181 subjects. RT3DE data sets were acquired, and LV volumes and LVEF were measured using QLab software (Philips). In Protocol 1, excellent correlations were noted between the methods for LVEDV (r=0.95), ESV (r=0.95), and LVEF (r=0.88). In Protocol 2, LV volume waveforms suitable for analysis were obtained from 2DSTE images in all subjects. The time required for analysis was <2 min per patient. Excellent correlations were noted between the methods for LVEDV (r=0.95), ESV (r=0.97), and LVEF (r=0.92). However, 2DSTE significantly underestimated LVEDV, resulting in a mean of 8% underestimation in LVEF. Intra- and inter-observer variabilities of 2DSTE were 7 and 9% in LV volume and 6 and 8% in LVEF, respectively. CONCLUSIONS Two-dimensional speckle tracking echocardiography measurements resulted in a small but significant underestimation of LVEDV and EF compared with RT3DE. However, the accuracy, low intra- and inter-observer variabilities and speed of analysis make 2DSTE a potentially useful modality for LV functional assessment in the routine clinical setting.
Unsupervised Modeling of Player Style With LDA

Computational analysis of player style has significant potential for video game design: it can provide insights into player behavior, as well as the means to dynamically adapt a game to each individual's style of play. To realize this potential, computational methods need to go beyond considerations of challenge and ability and account for aesthetic aspects of player style. We describe here a semiautomatic unsupervised learning approach to modeling player style using multiclass linear discriminant analysis (LDA). We argue that this approach is widely applicable for modeling player style in a wide range of games, including commercial applications, and illustrate it with two case studies: the first for a novel arcade game called Snakeotron, and the second for Rogue Trooper, a modern commercial third-person shooter video game.
The Bayesian Echo Chamber: Modeling Social Influence via Linguistic Accommodation

We present the Bayesian Echo Chamber, a new Bayesian generative model for social interaction data. By modeling the evolution of people's language usage over time, this model discovers latent influence relationships between them. Unlike previous work on inferring influence, which has primarily focused on simple temporal dynamics evidenced via turn-taking behavior, our model captures more nuanced influence relationships, evidenced via linguistic accommodation patterns in interaction content. The model, which is based on a discrete analog of the multivariate Hawkes process, permits a fully Bayesian inference algorithm. We validate our model's ability to discover latent influence patterns using transcripts of arguments heard by the US Supreme Court and the movie "12 Angry Men. " We showcase our model's capabilities by using it to infer latent influence patterns from Federal Open Market Committee meeting transcripts, demonstrating state-of-the-art performance at uncovering social dynamics in group discussions.
Low-complexity distributed fair scheduling for wireless multi-hop networks

Max-min fair bandwidth allocation is a meaningful objective whenever the level of user satisfaction cannot be clearly expressed as a function of the allocated bandwidth. In this work, we address the issue of approximating maxmin fairness in a wireless network without the requirement for network-wide node coordination and we present a lowoverhead greedy distributed algorithm for reaching this goal. The algorithm is based on distributed computation of a maximum weighted matching based on appropriately defined flow weights and subsequent scheduling of link flows in an effort to provide max-min rates to them. An inherent feature of our approach is its immunity to topology changes as well as to flow traffic variations. Our method is shown to outperform significantly the centralized (yet, conservative) algorithm of max-min fair rate computation in general topologies in terms of total resulting throughput, minimum shares and node resource utilization.
Effects of reverse transcriptase inhibitors on telomere length and telomerase activity in two immortalized human cell lines

The ribonucleoprotein telomerase, a specialized cellular reverse transcriptase, synthesizes one strand of the telomeric DNA of eukaryotes. We analyzed telomere maintenance in two immortalized human cell lines: the B-cell line JY616 and the T-cell line Jurkat E6-1, and determined whether known inhibitors of retroviral reverse transcriptases could perturb telomere lengths and growth rates of these cells in culture. Dideoxyguanosine (ddG) caused reproducible, progressive telomere shortening over several weeks of passaging, after which the telomeres stabilized and remained short. However, the prolonged passaging in ddG caused no observable effects on cell population doubling rates or morphology. Azidothymidine (AZT) caused progressive telomere shortening in some but not all T- and B-cell cultures. Telomerase activity was present in both cell lines and was inhibited in vitro by ddGTP and AZT triphosphate. Prolonged passaging in arabinofuranyl-guanosine, dideoxyinosine (ddI), dideoxyadenosine (ddA), didehydrothymidine (d4T), or phosphonoformic acid (foscarnet) did not cause reproducible telomere shortening or decreased cell growth rates or viabilities. Combining AZT, foscarnet, and/or arabinofuranyl-guanosine with ddG did not significantly augment the effects of ddG alone. Strikingly, with or without inhibitors, telomere lengths were often highly unstable in both cell lines and varied between parallel cell cultures. We propose that telomere lengths in these T- and B-cell lines are determined by both telomerase and telomerase-independent mechanisms.
A dual-view approach to interactive network visualization

Visualizing network data, from tree structures to arbitrarily connected graphs, is a difficult problem in information visualization. A large part of the problem is that in network data, users not only have to visualize the attributes specific to each data item, but also the links specifying how those items are connected to each other. Past approaches to resolving these difficulties focus on zooming, clustering, filtering and applying various methods of laying out nodes and edges. Such approaches, however, focus only on optimizing a network visualization in a single view, limiting the amount of information that can be shown and explored in parallel. Moreover, past approaches do not allow users to cross reference different subsets or aspects of large, complex networks. In this paper, we propose an approach to these limitations using multiple coordinated views of a given network. To illustrate our approach, we implement a tool called DualNet and evaluate the tool with a case study using an email communication network. We show how using multiple coordinated views improves navigation and provides insight into large networks with multiple node and link properties and types.
2-D Graphical representation of proteins based on virtual genetic code

We consider a novel 2-D graphical representation of proteins in which individual nucleic acids are represented as “spots” within a square frame distributed according to specific construction rules. The resulting “images” of proteins can not only serve to facilitate visual comparison of similarities and dissimilarities between lengthy protein sequences, but also offer a way for mathematical characterization of protein sequences, analogous to similar considerations for lengthy DNA sequences. Basically the approach is based on the concept of virtual genetic code, which is a hypothetical string of RNA nucleic acid bases, A, C, U and G, which generates reported protein sequences, without the knowledge of the actual genetic code that produces the protein.
An ABC transport system that maintains lipid asymmetry in the Gram-negative outer membrane

The outer membranes (OMs) of Gram-negative bacteria have an asymmetric lipid distribution with lipopolysaccharides at the outer leaflet and phospholipids (PLs) at the inner leaflet. This lipid arrangement is essential for the barrier function of the OM and for the viability of most Gram-negative bacteria. Cells with OM assembly defects or cells exposed to harsh chemical treatments accumulate PLs in the outer leaflet of the OM and this disrupts lipopolysaccharide organization and increases sensitivity to small toxic molecules. We have identified an ABC transport system in Escherichia coli with predicted import function that serves to prevent PL accumulation in the outer leaflet of the OM. This highly conserved pathway, which we have termed the Mla pathway for its role in preserving OM lipid asymmetry, is composed of at least 6 proteins and contains at least 1 component in each cellular compartment. We propose that the Mla pathway constitutes a bacterial intermembrane PL trafficking system.
An impossibility result for process discrimination

Two series of binary observations x<inf>1</inf>; x<inf>1</inf>,… and y<inf>1</inf>, y<inf>2</inf>,… are presented: at each time n ∈ ℕ we are given x<inf>n</inf> and y<inf>n</inf>. It is assumed that the sequences are generated independently of each other by two stochastic processes. We are interested in the question of whether the sequences represent a typical realization of two different processes or of the same one. We demonstrate that this is impossible to decide in the case when the processes are B-processes. It follows that discrimination is impossible for the set of all (finite-valued) stationary ergodic processes in general. This result means that every discrimination procedure is bound to err with non-negligible frequency when presented with sequences from some of such processes. It contrasts earlier positive results on B-processes, in particular those showing that there are consistent d̅-distance estimates for this class of processes.