Miracle-dz/UniFAR-FTUs huggingface dataset:
Immune activation and viral burden in acute disease induced by simian immunodeficiency virus SIVsmmPBj14: correlation between in vitro and in vivo events

The simian immunodeficiency virus SIVsmmPBj14 (SIV-PBj14) is an atypical lentivirus that causes acute disease and death in pig-tailed macaques and in vitro replicates efficiently in resting macaque lymphocytes and activates and induces proliferation of lymphocytes. The present study was conducted to test the hypothesis that production of large quantities of SIV-PBj14 induces widespread immune activation and elaboration of cytokines which lead directly to the death of infected pig-tailed macaques. Following intravenous inoculation of pig-tailed macaques with SIV-PBj14, acute disease developed and was characterized by high levels of plasma viremia, p27gag antigenemia, tumor necrosis factor alpha, and interleukin-6 (IL-6). All animals died within 10 days of infection, at which time some animals had as many as 100% CD4+ cells in the periphery and lymphoid tissues infected. During the last few days before death, titers of infectious virus in blood increased as much as 10(5)-fold. By using dual-label immunofluorescence assays for detection of cell surface activation markers, both CD4+ and CD8+ lymphocytes were shown to express the IL-2 and transferrin receptors following either in vivo or in vitro infection with SIV-PBj14. Furthermore, in vitro infection of quiescent macaque lymphocytes by SIV-PBj14 was accompanied by proliferation of both CD4+ and CD8+ lymphocyte subsets, as measured by incorporation of [3H]thymidine. Increases in numbers of activated lymphocytes and levels of proinflammatory cytokines in plasma coincided with increased amounts of detectable virus in vivo. Clinical signs of disease and pathologic findings were most consistent with death from a shock-like syndrome, in which acute-phase inflammatory cytokines are known to play a major role. Tumor necrosis factor alpha, IL-2, and IL-6 were detected in some cultures infected with SIV-PBj14, but this finding was not consistent. When cytokines were detected, their concentrations were essentially no different from those found in control cultures infected with SIVsmm9, a prototypic strain from which SIV-PBj14 was derived. The in vivo results suggest a synergistic cycle of activation of lymphocytes and monocytes, elaboration of cytokines, and virus production that accelerates uncontrolled and culminates in death. The observed correlations between in vivo and in vitro activation events following SIV-PBj14 infection validate the use of in vitro studies to clarify lentivirus-lymphocyte interactions that may contribute to the virulence of SIV-PBj14.
Role and predictive value of the hdl function for cardiovascular disease in a high risk population. Hdl function-linked markers and mechanisms

ABSTRACT Cardiovascular disease remains the first cause of death worldwide. Therefore, there is a growing interest in the study of novel surrogates to reduce the risk for future heart disease. The aim of the present thesis was to evaluate the predictive role of a cluster of HDL-properties and components for cardiovascular diseases. To have an updated record of available literature in this field, we conducted a meta-analysis of observational studies. To assess the prognostic value for CVD of HDL-functionality and composition, we analyzed the cholesterol efflux capacity, HDL oxidative-inflammatory index, platelet activating factor acetylhydrolase activity and apolipoproteinA-I, A-IV, serum amyloid A, component Complement C3, and sphingosine-1-phosphate in samples of apolipoproteinB depleted plasma. Finally, to gain deeper knowledge of the mechanisms involved in the protective role hold by HDL, we analyzed the relationships among HDL function, LDL atherogenicity, and the 10-risk for cardiovascular disease according to FRAMINGHAM-REGICOR risk score and classical risk factors. In summary, the meta-analysis study showed that CEC, and anti-inflammatory and antioxidant capacities of HDL, are inverse predictors of CVD. The association persisted for all-cause mortality risk with CEC and antioxidant capacity. These results were further confirmed in the case-cohort study nested within the PreDiMed cohort, in which cholesterol efflux capacity at baseline showed a strong and independent inverse association with the risk of ACS and AMI; ApoA-I predicted ACS, AMI, and US, and the HDL antioxidant/anti-inflammatory index proved to be a prognostic index for ACS and UA. Finally, high cardiovascular risk scores and classical risk factors for cardiovascular disease were associated with impaired HDL regarding its components, particle size, and function, and with an LDL more pro-atherogenic.
A Balanced Scorecard Approach to Enterprise Systems Performance Measurement

A range of influences, both technical and organisational, has encouraged the wide spread adoption of Enterprise Systems (ES). Nevertheless, there is a growing consensus that Enterprise Systems have in many cases failed to provide expected benefits. The increasing role of, and dependency on ES (and IT in general), and the ‘uncertainty’ of these large investments, have created a strong need to monitor and measure ES performance. This paper reports on a research project aimed at deriving an ‘Enterprise Systems benefits measurement instrument’. The research seeks to identify how Enterprise Systems benefits can be usefully measured, with a ‘balance’ between qualitative and quantitative factors.
Can hsCRP be the sole investigation for predicting the severity and outcome in women with pre-eclampsia presenting late in pregnancy?

Context: Healthcare facilities in developing countries are over burdened and proper triage of patients requiring attention more than others is needed in every sub speciality of medical sciences in them. Patients with pre-eclampsia require attention to prevent any associated complication. Aims: The aim of this study was to evaluate whether hsCRP alone or in combination could be used as an indicator of severity and predictor of outcome in women with PE presenting to a healthcare facility late in the third trimester. Settings and Design: Prospective observational study conducted at a teaching medical college and referral hospital catering primarily to rural, semi urban and tribal population. Methods and Material: 85 women with PE who reported to the hospital after completed 36 weeks of gestation were included. Patients were divided in three groups. hsCRP, biochemical and hematological investigations were performed for each patient. Results were expressed as median. Independent samples Kruskall Wallis one way ANOVA and Mann Whitney U tests were performed and correlation of hsCRP with other parameters and fetal outcome was examined. Statistical Analysis Used: Kruskall Wallis one way ANOVA and Mann Whitney U tests. Results: hsCRP was significantly elevated in severe PE as compared to PE without severe features and normal patients. Higher requirement of labour induction and caesarean section was seen in severe PE patients along with higher still births and low baby weight babies. hsCRP had positive correlation with other markers of severity of PE and negative correlation with still births and fetal weight in severe PE patients. However, although raised in every case of severe PE, a wide variation was noted in hsCRP values. Conclusions: hsCRP alone cannot be recommended as a marker of severity or a predictor of outcome in women presenting late in the third trimester of pregnancy. However, in combination with serum uric acid it can be used for that purpose.
The effects of TIS and MI on the texture features in ultrasonic fatty liver images

Nonalcoholic fatty liver disease (NAFLD) is prevalent and has a worldwide distribution now. Although ultrasound imaging technology has been deemed as the common method to diagnose fatty liver, it is not able to detect NAFLD in its early stage and limited by the diagnostic instruments and some other factors. B-scan image feature extraction of fatty liver can assist doctor to analyze the patient’s situation and enhance the efficiency and accuracy of clinical diagnoses. However, some uncertain factors in ultrasonic diagnoses are often been ignored during feature extraction. In this study, the nonalcoholic fatty liver rabbit model was made and its liver ultrasound images were collected by setting different Thermal index of soft tissue (TIS) and mechanical index (MI). Then, texture features were calculated based on gray level co-occurrence matrix (GLCM) and the impacts of TIS and MI on these features were analyzed and discussed. Furthermore, the receiver operating characteristic (ROC) curve was used to evaluate whether each feature was effective or not when TIS and MI were given. The results showed that TIS and MI do affect the features extracted from the healthy liver, while the texture features of fatty liver are relatively stable. In addition, TIS set to 0.3 and MI equal to 0.9 might be a better choice when using a computer aided diagnosis (CAD) method for fatty liver recognition.
Evidence in palliative care research: how should it be gathered?

More recently, this debate has moved to emerging research areas,such as palliative care. This discipline urgently requires a widerevidence base, but acquiring this evidence presents particularproblems.Evidence in palliative care researchIn palliative care research, methodological difficulties arise becauseof the complex physical, psychological, existential and spiritualproblems faced by patients, families and professionals.
Assessment of Depression: Using the MMPI, Millon, and Millon-II

The analysis examined how the MMPI, original Millon, and Millon-II may be used for the assessment of clinical and personality characteristics of depressed patients. High-point code-type analysis of data from 133 depressed inpatients yielded seven MMPI personality profiles (incapacitated-depressive, intropunitive-depressive, caught psychopath, hysteroid-dysphoric, schizotypal-depressive, ruminative-depressive, and psychotic-depressive) and eight Millon personality profiles (avoidant-depressive, conforming-depressive, hostile-depressive, hysteroid-depressive, disenfranchised-depressive, guilty-depressive, passive aggressive-depressive, and anaclitic-depressive). These profiles reflect important similarities in the personalities of the tested depressed inpatients and differences among them as well. Our interpretive framework is speculative but offers a basis for clinical hypothesis generation.
Threshold Anonymous Announcement in VANETs

Vehicular ad hoc networks (VANETs) allow wireless communications between vehicles without the aid of a central server. Reliable exchanges of information about road and traffic conditions allow a safer and more comfortable travelling environment. However, such profusion of information may allow unscrupulous parties to violate user privacy. On the other hand, a degree of auditability is desired for law enforcement and maintenance purposes. In this paper we propose a Threshold Anonymous Announcement service using direct anonymous attestation and one-time anonymous authentication to simultaneously achieve the seemingly contradictory goals of reliability, privacy and auditability.
Subset Infinite Relational Models

We propose a new probabilistic generative model for analyzing sparse and noisy pairwise relational data, such as friend-links on social network services and customer records in online shops. Real-world relational data often include a large portion of non-informative pairwise data entries. Many existing stochastic blockmodels suffer from these irrelevant data entries because of their rather simpler forms of priors. The proposed model incorporates a latent variable that explicitly indicates whether each data entry is relevant or not to diminish bad effects associated with such irrelevant data. Through experiments using synthetic and real data sets, we show that the proposed model can extract clusters with stronger relations among data within the cluster than clusters obtained by the conventional model.
Domains upstream of the protease (PR) in human immunodeficiency virus type 1 Gag-Pol influence PR autoprocessing

A critical step in the formation of infectious retroviral particles is the activation of the virally encoded protease (PR) and its release from the Gag-Pol precursor polyprotein. To identify factors that influence this step, the maturation of human immunodeficiency virus type 1 PR from various Gag-PR polyproteins was assayed in vitro by a using rabbit reticulocyte lysate as a coupled transcription-translation-autoprocessing system. Highly efficient autoprocessing was detected with polyproteins containing the viral nucleocapsid (NC) domain. In contrast, polyproteins consisting of only p6 and PR domains or containing a truncated NC domain exhibited no autoprocessing activity. Experiments designed to test the dimerization capability of short PR polyproteins revealed that precursors containing the NC domain exhibited very efficient homotypic protein-protein interactions while PR precursors consisting of only p6 and PR did not interact efficiently. The strong correlation between autoprocessing activity and PR polyprotein precursor dimerization suggests that NC and p6* domains play a role in PR activation by influencing the dimerization of the PR domain in the precursor.
Filters for Wi-Fi Generated Crowd Movement Data

Cities represent large groups of people that share a common infrastructure, common social groups and/or common interests. With the development of new technologies current cities aim to become what is known as smart cities, in which all the small details of these large constructs are controlled to better improve the quality of life of its inhabitants. One of the important gears that powers a city is given by traffic, be it vehicular or pedestrian. As such traffic is closely related to all other activities that take place inside of a city. Understanding traffic is still a difficult process as we have to be able to not only measure it in the sense of how many people are using a particular path but also in analyzing where people are going and when, while still maintaining individual privacy. And all this has to be done at a scale that would cover most if not all individuals in a city. With the high increase in smartphones adoption we can reliably assume that a large part of the population in cities are carrying with them, at all times, at least one Wi-Fi enabled device. Because Wi-Fi devices are regularly transmitting signals we can rely on these devices to detect individual's movements unobtrusively without identifying or tracking any particular individual. Special sensors that monitor Wi-Fi frequencies can be placed around a city to gather data that can later be used to identify patterns in the traffic flows. We present a set of filters that can be used to minimize the amount of data needed for processing and without negatively impacting the result or the information that can be extracted from this data. Part of the filters we present can be deployed at the sensor level, making the entire system more scalable, while a different part can be executed before data processing thus enabling real time information extraction and a broader temporal and spatial range for data analysis. Some of these filters are particular to Wi-Fi but some of them can be applied to any detection system.
A likelihood reformulation method in non‐normal random effects models

In this paper, we propose a practical computational method to obtain the maximum likelihood estimates (MLE) for mixed models with non‐normal random effects. By simply multiplying and dividing a standard normal density, we reformulate the likelihood conditional on the non‐normal random effects to that conditional on the normal random effects. Gaussian quadrature technique, conveniently implemented in SAS Proc NLMIXED, can then be used to carry out the estimation process. Our method substantially reduces computational time, while yielding similar estimates to the probability integral transformation method (J. Comput. Graphical Stat. 2006; 15:39–57). Furthermore, our method can be applied to more general situations, e.g. finite mixture random effects or correlated random effects from Clayton copula. Simulations and applications are presented to illustrate our method. Copyright © 2007 John Wiley & Sons, Ltd.
Mechanical and perceptual analyses of human foot movements in pedal operation

A human can maneuver mechanical systems by adjusting his/her own body naturally and effectively according to a target task by utilizing the kinematical and dynamic characteristics of operating systems acquired through sensory organs. If such human sensory and motor characteristics changing in the task can be quantitatively described, it would be useful to design and develop a novel human-machine system so that humans can manipulate a machine more instinctively and comfortably. This paper investigates the interaction between human sensory and motor properties at the foot during the operation of an automobile pedal, as an example of human-machine systems, and demonstrates the close relationship between the perceptual properties of force resistance at the foot and the loads for foot joints much depending on the pedal layout. Finally, based on biomechanical and perceptual analyses, a human-inspired design method of pedal dynamic properties is discussed.
MRI Gastric Images Processing using a Multiobjective Fly Algorithm

When dealing with rare and sparse data, like the ones collected during a long and expensive experimental process, machine learning is used in a different perspective. In this context, optimisation-based approaches combined with user visualisation and interactions are sometimes the best way to cope with modelling issues. We present here an example related to an experimental project aiming at understanding the kinetics of gastric emptying using MRI images of the stomach of healthy volunteers. We show how a cooperation/co-evolution algorithm, the “Fly Algorithm”, can be made multi-objective, and its output, a complex Pareto Front, analysed using interactive Information Visualisation (InfoVis) and clustering.
Reconstructing the Indian Origin and Dispersal of the European Roma: A Maternal Genetic Perspective

Previous genetic, anthropological and linguistic studies have shown that Roma (Gypsies) constitute a founder population dispersed throughout Europe whose origins might be traced to the Indian subcontinent. Linguistic and anthropological evidence point to Indo-Aryan ethnic groups from North-western India as the ancestral parental population of Roma. Recently, a strong genetic hint supporting this theory came from a study of a private mutation causing primary congenital glaucoma. In the present study, complete mitochondrial control sequences of Iberian Roma and previously published maternal lineages of other European Roma were analyzed in order to establish the genetic affinities among Roma groups, determine the degree of admixture with neighbouring populations, infer the migration routes followed since the first arrival to Europe, and survey the origin of Roma within the Indian subcontinent. Our results show that the maternal lineage composition in the Roma groups follows a pattern of different migration routes, with several founder effects, and low effective population sizes along their dispersal. Our data allowed the confirmation of a North/West migration route shared by Polish, Lithuanian and Iberian Roma. Additionally, eleven Roma founder lineages were identified and degrees of admixture with host populations were estimated. Finally, the comparison with an extensive database of Indian sequences allowed us to identify the Punjab state, in North-western India, as the putative ancestral homeland of the European Roma, in agreement with previous linguistic and anthropological studies.
Lateral inhibitory networks: Synchrony, edge enhancement, and noise reduction

This paper investigates how layers of spiking neurons can be connected using lateral inhibition in different ways to bring about synchrony, reduce noise, and extract or enhance features. To illustrate the effects of the various connectivity regimes spectro-temporal speech data in the form of isolated digits is employed. The speech samples are preprocessed using the Lyon's Passive Ear cochlear model, and then encoded into tonotopically arranged spike arrays using the BSA spiker algorithm. The spike arrays are then subjected to various lateral inhibitory connectivity regimes configured by two connectivity parameters, namely connection length and neighbourhood size. The combination of these parameters are demonstrated to produce various effects such as transient synchrony, reduction of noisy spikes, and sharpening of spectro-temporal features.
Serenity Spirituality Sessions: A Descriptive Qualitative Exploration of a Christian Resource Designed to Foster Spiritual Well-Being among Older People in Nursing Homes in Ireland

This paper reports on a descriptive qualitative study that explored the value and benefit of Serenity Spirituality Sessions programme for older nursing home residents. The research was carried out in six nursing homes in the Republic of Ireland. The facilitators of these sessions, who worked in the nursing homes, were interviewed about their experiences of delivering the programme and their views on the impact that the programme had on resident participants. Emergent themes revealed benefits of the intervention for clients, including inducing a calming effect, increased sense of belonging and benefits of ritual use. The programme yielded positive results, and appears suited to the predominantly Christian population, and as such is deemed a useful adjunct to holistic and spiritual care in these settings.
Enhanced Precision Through Multiple Reads for LDPC Decoding in Flash Memories

Multiple reads of the same Flash memory cell with distinct word-line voltages provide enhanced precision for LDPC decoding. In this paper, the word-line voltages are optimized by maximizing the mutual information (MI) of the quantized channel. The enhanced precision from a few additional reads allows frame error rate (FER) performance to approach that of full-precision soft information and enables an LDPC code to significantly outperform a BCH code. A constant-ratio constraint provides a significant simplification in the optimization with no noticeable loss in performance. For a well-designed LDPC code, the quantization that maximizes the mutual information also minimizes the FER in our simulations. However, for an example LDPC code with a high error floor caused by small absorbing sets, the MMI quantization does not provide the lowest frame error rate. The best quantization in this case introduces more erasures than would be optimal for the channel MI in order to mitigate the absorbing sets of the poorly designed code. The paper also identifies a trade-off in LDPC code design when decoding is performed with multiple precision levels; the best code at one level of precision will typically not be the best code at a different level of precision.
Towards Building Error Resilient GPGPU Applications

GPUs (Graphics Processing Units) have gained wide adoption as accelerators for general purpose computing. They are widely used in error-sensitive applications, i.e. General Purpose GPU (GPGPU) applications However, the reliability implications of using GPUs are unclear. This paper presents a fault injection study to investigate the end-to-end reliability characteristics of GPGPU applications. The investigation showed that 8% to 40% of the faults result in Silent Data Corruption (SDC). To reduce the percentage of SDCs, we propose heuristics to selectively protect specific elements of the application and design fault detectors based on heuristics. We evaluate the efficacy of the detectors in reducing SDCs and measure performance overheads of the detectors. Our results show that the heuristics are able to reduce the SDC causing faults by 60% on average, while incurring reasonable performance overheads (35% to 95%).