Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliability and Validity Study of the Chamorro Assisted Gait Scale for People with Sprained Ankles, Walking with Forearm Crutches

Objective The aim of this study was to design and validate a functional assessment scale for assisted gait with forearm crutches (Chamorro Assisted Gait Scale—CHAGS) and to assess its reliability in people with sprained ankles. Design Thirty subjects who suffered from sprained ankle (anterior talofibular ligament first and second degree) were included in the study. A modified Delphi technique was used to obtain the content validity. The selected items were: pelvic and scapular girdle dissociation(1), deviation of Center of Gravity(2), crutch inclination(3), steps rhythm(4), symmetry of step length(5), cross support(6), simultaneous support of foot and crutch(7), forearm off(8), facing forward(9) and fluency(10). Two raters twice visualized the gait of the sample subjects which were recorded. The criterion-related validity was determined by correlation between CHAGS and Coding of eight criteria of qualitative gait analysis (Viel Coding). Internal consistency and inter and intra-rater reliability were also tested. Results CHAGS obtained a high and negative correlation with Viel Coding. We obtained a good internal consistency and the intra-class correlation coefficients oscillated between 0.97 and 0.99, while the minimal detectable changes were acceptable. Conclusion CHAGS scale is a valid and reliable tool for assessing assisted gait with crutches in people with sprained ankles to perform partial relief of lower limbs.
The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli

Understanding how brains process sensory signals in natural environments is one of the key goals of twenty-first century neuroscience. While brain imaging and invasive electrophysiology will play key roles in this endeavor, there is also an important role to be played by noninvasive, macroscopic techniques with high temporal resolution such as electro- and magnetoencephalography. But challenges exist in determining how best to analyze such complex, time-varying neural responses to complex, time-varying and multivariate natural sensory stimuli. There has been a long history of applying system identification techniques to relate the firing activity of neurons to complex sensory stimuli and such techniques are now seeing increased application to EEG and MEG data. One particular example involves fitting a filter—often referred to as a temporal response function—that describes a mapping between some feature(s) of a sensory stimulus and the neural response. Here, we first briefly review the history of these system identification approaches and describe a specific technique for deriving temporal response functions known as regularized linear regression. We then introduce a new open-source toolbox for performing this analysis. We describe how it can be used to derive (multivariate) temporal response functions describing a mapping between stimulus and response in both directions. We also explain the importance of regularizing the analysis and how this regularization can be optimized for a particular dataset. We then outline specifically how the toolbox implements these analyses and provide several examples of the types of results that the toolbox can produce. Finally, we consider some of the limitations of the toolbox and opportunities for future development and application.
Coinoculation with Hartmannella vermiformis enhances replicative Legionella pneumophila lung infection in a murine model of Legionnaires' disease

The effect of inhaled amoebae on the pathogenesis of Legionnaires' disease was investigated in vivo. A/J mice, which are susceptible to replicative Legionella pneumophila infections, were inoculated intratracheally with L. pneumophila (10(6) bacteria per mouse) or were coinoculated with L. pneumophila (10(6) bacteria per mouse) and Hartmannella vermiformis (10(6) amoebae per mouse). The effect of coinoculation with H. vermiformis on bacterial clearance, histopathology, cellular recruitment into the lung, and intrapulmonary levels of cytokines including gamma interferon and tumor necrosis factor alpha was subsequently assessed. Coinoculation with H. vermiformis significantly enhanced intrapulmonary growth of L. pneumophila in A/J mice. Histopathologic and flow cytometric analysis of lung tissue demonstrated that while A/J mice inoculated with L. pneumophila alone develop multifocal pneumonitis which resolves with minimal mortality, mice coinoculated with H. vermiformis develop diffuse pneumonitis which is associated with diminished intrapulmonary recruitment of lymphocytes and mononuclear phagocytic cells and significant mortality. Furthermore, coinoculation of mice with H. vermiformis resulted in a fourfold enhancement in intrapulmonary levels of gamma interferon and tumor necrosis factor alpha compared with mice infected with L. pneumophila alone. The effect of H. vermiformis on intrapulmonary growth of L. pneumophila in a resistant host (i.e., BALB/c mice) was subsequently evaluated. While BALB/c mice do not develop replicative L. pneumophila infections following inoculation with L. pneumophila alone, there was an eightfold increase in intrapulmonary L. pneumophila in BALB/c mice coinoculated with H. vermiformis. These studies, demonstrating that intrapulmonary amoebae potentiate replicative L. pneumophila lung infection in both a susceptible and a resistant host, have significant implications with regard to the potential role of protozoa in the pathogenesis of pulmonary diseases due to inhaled pathogens and in the design of strategies to prevent and/or control legionellosis.
Production inventory with service time and interruptions

This paper considers an (s,S) production inventory system with positive service time, with time for producing each item following Erlang distribution. Customers arrive according to a Poisson process. A customer who arrives when there is no inventory in the system is considered lost. On the other hand, a customer who finds a busy server with at least one inventory in the system joins a queue of infinite capacity. When the inventory level falls to s, production process is switched on, and it is switched off when the inventory level reaches back to S. Service time to each customer also follows an Erlang distribution. The service of a customer may be interrupted, where the time for such a phenomenon follows an exponential distribution, whenever it occurs. An interrupted service, after repair, resumes from where it was stopped. The correction/repair time follows an exponential distribution. We assume that the service of a single customer may encounter any number of interruptions and that the customer being served waits there until his service is completed. Moreover, at a time the server is subject to at most one interruption. We also assume that no inventory is lost due to a service interruption. Like the service process, the production process also is subject to interruptions, where the duration to an interruption follows an exponential distribution. However, in contrast to the service interruption, in the case of interruption to production process, we assume that the item being processed is lost because of interruption. That is, the production process, on being interrupted, restarts from the beginning, after repair. The repair time of an interrupted production process follows exponential distribution. Few of the last service phases are assumed to be protected in the sense that the service will not be interrupted while being in these phases. The same is assumed for the production process also. The model is analysed as a level-independent quasi-birth–death process. We apply a novel method to obtain an explicit expression for the necessary and sufficient condition for the stability of the system under study. This method works even if we assume general phase-type distributions for the production as well as the service processes, and hence can be used to characterise the stability of inventory systems where the assumption of disallowing the customers to join the system, when there is a shortage of inventory has been made. Under stability, we apply matrix analytic methods to compute the system state distribution. In consequence to that, several system performance measures have been derived, and their dependence on the system parameters has been studied numerically.
Is mid-regional pro-atrial natriuretic peptide (MRproANP) an accurate marker of bacteremia in pyelonephritis?

Introduction: Mid-regional pro-atrial natriuretic peptide (MRproANP) increases during systemic infections and could possibly correlate with bacteremia. Methods: We determined the characteristics of MRproANP for accuracy to detect positive blood culture. Results: Bacteremia was positive in 58 (15%) of 347 patients. MRproANP levels increased in patients with bacteremia (98.4 pmol/L [interquartile range (IQR) 68.2–153.1] vs. 66.4 pmol/L [IQR 51.0-90.3], p < 0.01). Performance of MRproANP to predict bacteremia [AUC = 0.69, 95%CI: 0.61–0.77] was equivalent to C-reactive protein (0.66 [95%CI: 0.59–0.74], p = 0.53) but less accurate than procalcitonin (0.78 [95%CI: 0.72–0.84], p < 0.001). Conclusion: Although MRproANP increased in bacteremic patients with acute pyelonephritis, results of likelihood ratios discarded its use at bedside to predict bacteremia.
Assessing the Hormone Response to High Intensity Exercise and Identifying Associations with Performance

The aim of this programme of research was to add to the existing body of knowledge on the measurement of certain hormones in relation to exercise training, the response to high intensity training, and their potential influence on short-term performance. The initial studies demonstrated agreement between venous and capillary concentrations of an array of hormones, and agreement between venous and saliva concentrations of testosterone and cortisol following scaling of saliva concentrations, suggesting suitability of use in an applied exercise setting. In addition, to ensure accurate measurement of steroid hormone concentrations in saliva, it was shown that samples should be refrigerated immediately, transferred to a freezer within 24 h of collection, and analysed within 28 days. Assessment of the response to two exercise bouts of a different type within the same day indicated that it could be beneficial to perform resistance training in the afternoon preceded by interval exercise in the morning in order to stimulate a hormonal milieu that may be more conducive to stimulating muscle protein turnover. The robust increases seen in testosterone and cortisol following interval exercise performed in the morning in that study were also observed in the same cycling sprint interval protocol performed in females. In this study, the magnitude of change in DHT concentration was related to sprint cadence. In investigating the potential acute effects of hormones on performance, the penultimate study demonstrated a positive association between affect as an indicator mood and percentage testosterone concentration during high intensity cycling. Conversely, in the final study, no postactivation potentiation effect was observed to different exercise stimuli, thus no association was observed between hormone concentrations and strength and power performance. These data may suggest that the acute short-term effects of hormone concentrations on performance may be more related to mood and behaviour in the context of this research.
A universal fairness evaluation framework for resource allocation in cloud computing

In cloud computing, fairness is one of the most significant indicators to evaluate resource allocation algorithms, which reveals whether each user is allocated as much as that of all other users having the same bottleneck. However, how fair an allocation algorithm is remains an urgent issue. In this paper, we propose Dynamic Evaluation Framework for Fairness (DEFF), a framework to evaluate the fairness of an resource allocation algorithm. In our framework, two sub-models, Dynamic Demand Model (DDM) and Dynamic Node Model (DNM), are proposed to describe the dynamic characteristics of resource demand and the computing node number under cloud computing environment. Combining Fairness on Dominant Shares and the two sub-models above, we finally obtain DEFF. In our experiment, we adopt several typical resource allocation algorithms to prove the effectiveness on fairness evaluation by using the DEFF framework.
Construction of type II1 factors with prescribed countable fundamental group

Abstract In the context of Free Probability Theory, we study two different constructions that provide new examples of factors of type II1 with prescribed countable fundamental group. First we investigate state-preserving group actions on the almost periodic free Araki-Woods factors satisfying both a condition of mixing and a condition of free malleability in the sense of Popa. Typical examples are given by the free Bogoliubov shifts. Take an ICC w-rigid group G such that ℱ(L(G)) = {1} (e.g., G = ℤ2 ⋊ SL(2, ℤ)). For any countable subgroup S ⊂ , we construct an action of G on L(𝔽∞) such that the associated crossed product L(𝔽∞) ⋊ G is a type II1 factor and its fundamental group is S. The second construction is based on a free product. Take (B(H),ψ) any factor of type I endowed with a faithful normal state and denote by S ⊂ the subgroup generated by the point spectrum of ψ. We show that the centralizer (L(G) ∗ B(H)) τ * ψ is a type II1 factor and its fundamental group is S. Our proofs rely on Popa's deformation/rigidity strategy using his intertwining-by-bimodules technique.
Data embedding in /spl mu/-law speech with spread spectrum techniques

This paper explores data embedding in G.711 mu-law speech signals with the spread spectrum techniques. Based on an optimized spread spectrum scheme, a simple but effective solution is presented for high-capacity embedding. Simulations show that the proposed scheme, when incorporated with the measure of the frequency masking effects, can achieve an embedding rate of about 100 bits per second with a 7% bit error rate (BER), or 1000 bps with a 10% BER
On Large Execution Traces and Trace Abstraction Techniques

Preprint of paper published in: Journal of Software Maintenance and Evolution (Wiley), 2008 Program comprehension is an important concern in the context of software maintenance tasks because these activities generally require a certain degree of knowledge of the system at hand. Although the use of dynamic analysis for information gathering has become increasingly popular, the literature indicates that dealing with the excessive amounts of data resulting from dynamic analysis remains a formidable challenge. Although various trace abstraction techniques have been proposed to address these scalability concerns, such techniques are typically not discussed in terms of properties such as complexity and information preservation, and lack thorough evaluation of technique-specific parameters. Moreover, the absence of a common execution trace repository makes matters even worse, as most researchers test their techniques only on their own particular traces. Consequently, it is very difficult to make a fair comparison between the abstraction techniques known from literature. In this paper, we present a characterization of large execution traces in which a set of key properties is extracted from a series of seven representative traces from six different object-oriented systems. Having highlighted the key issues in this context, we propose an assessment methodology for the quantitative evaluation and comparison of trace abstraction techniques. We apply this methodology on a selection of three light-weight abstraction methods, assessing them on the basis of metrics that are relevant in their evaluation.We discuss the results, compare the techniques, and relate the measurements to the trace characteristics found earlier. Our findings provide a valuable insight into factors that play an important role in coping with large execution traces, and we consider our work a significant step towards a systematic assessment of (new) trace abstraction techniques.
Review of the Application of RNA Interference Technology in the Pharmaceutical Industry

Ribonucleic acid (RNA) interference (RNAi) is a recently discovered phenomenon whereby the introduction of double stranded (ds) RNA into the cytoplasm of the cell results in the specific and efficient degradation of complementary messenger (m) RNA and, therefore, reduced protein production. It was discovered by chance during attempts to develop flowers with increased colour intensity. The specific nature of the inhibition of protein production of cells has resulted in an explosion of research to understand and exploit RNAi. The technique is now established in in vitro systems, and much work is focussed in adapting RNAi for in vivo application. The potential of the technology in understanding physiological and pathological processes is significant, while its development as a therapeutic agent holds much promise as targeted agents. This review will describe the basic biological processes that drive RNAi, indicate current areas of areas research, and forecast future areas of development.
Visual fall detection for intelligent spaces

Artificial vision provides a remarkable good sensor when developing applications for intelligent spaces. Cameras are passive sensors that supply a great amount of information and are quite cheap. This paper presents an application for elderly care that detects falls or faints and automatically triggers the health alarm. It promotes the independent lifestyle of elder people at their homes as the monitoring application will call for timely health assistance when needed. The system extracts 3D information from several cameras and performs 3D tracking of the people in the intelligent space. It uses an evolutive multimodal algorithm to continuously estimate the 3D position in real time and learns the visual appearance of the persons. The system has been validated with some experiments in different real environments.
A Strategy for O-Glycoproteomics of Enveloped Viruses—the O-Glycoproteome of Herpes Simplex Virus Type 1

Glycosylation of viral envelope proteins is important for infectivity and interaction with host immunity, however, our current knowledge of the functions of glycosylation is largely limited to N-glycosylation because it is difficult to predict and identify site-specific O-glycosylation. Here, we present a novel proteome-wide discovery strategy for O-glycosylation sites on viral envelope proteins using herpes simplex virus type 1 (HSV-1) as a model. We identified 74 O-linked glycosylation sites on 8 out of the 12 HSV-1 envelope proteins. Two of the identified glycosites found in glycoprotein B were previously implicated in virus attachment to immune cells. We show that HSV-1 infection distorts the secretory pathway and that infected cells accumulate glycoproteins with truncated O-glycans, nonetheless retaining the ability to elongate most of the surface glycans. With the use of precise gene editing, we further demonstrate that elongated O-glycans are essential for HSV-1 in human HaCaT keratinocytes, where HSV-1 produced markedly lower viral titers in HaCaT with abrogated O-glycans compared to the isogenic counterpart with normal O-glycans. The roles of O-linked glycosylation for viral entry, formation, secretion, and immune recognition are poorly understood, and the O-glycoproteomics strategy presented here now opens for unbiased discovery on all enveloped viruses.
String quantization: Fock vs. LQG Representations

We set up a unified framework to compare the quantization of the bosonic string in two approaches: One proposed by Thiemann, based on methods of loop quantum gravity, and the other using the usual Fock space quantization. Both yield a diffeomorphism invariant quantum theory. We discuss why there is no central charge in Thiemann's approach but a discontinuity characteristic for the loop approach to diffeomorphism invariant theories. Then we show the (un)physical consequences of this discontinuity in the example of the harmonic oscillators such as an unbounded energy spectrum. On the other hand, in the continuous Fock representation, the unitary operators for the diffeomorphisms have to be constructed using the method of Gupta and Bleuler representing the diffeomorphism group up to a phase given by the usual central charge.
Prognostic Significance of Cerebral Metabolic Abnormalities in Patients With Congestive Heart Failure

Background—Cerebral metabolic abnormalities were proposed as a potential marker of disease severity in congestive heart failure (CHF), but their prognostic significance remains uncertain. Methods and Results—We investigated the prognostic value of cerebral metabolic abnormalities in 130 consecutive patients with advanced CHF (100 men aged 42.6±11.9 years; left ventricular ejection fraction, 22.2±6.2%). Proton magnetic resonance spectroscopy data were obtained from localized regions (≈8 mL) of the occipital gray matter and the parietal white matter. The primary end point was the occurrence of death after the proton magnetic resonance spectroscopy. During follow-up (18.5±14.4 months), 21 patients died and 15 underwent urgent heart transplantation. In the Cox proportional model, occipital metabolites (N-acetylaspartate, creatine, choline, and myoinositol), parietal N-acetylaspartate level, and the duration of CHF symptoms (>12 months) were validated as univariate predictors of death. In multivariate Cox analyses, however, the occipital N-acetylaspartate level was an independent predictor of death (hazard ratio, 0.52; 95% CI, 0.41 to 0.67;P <0.001). An analysis with respect to the combined end point of death or urgent transplantation showed similar results. The best cutoff value (9.0 mmol/kg) for occipital N-acetylaspartate level had 75% sensitivity and 67% specificity to predict mortality. Conclusions—The occipital N-acetylaspartate level is a powerful and independent predictor of CHF mortality, suggesting that cerebral metabolic abnormalities may be used as a new prognostic marker in the assessment of patients with CHF.