Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing tactile acuity in rheumatology and musculoskeletal medicine--how reliable are two-point discrimination tests at the neck, hand, back and foot?

OBJECTIVE Chronic pain from rheumatic and musculoskeletal conditions is associated with cortical changes and altered tactile acuity. Tactile acuity is considered a clinical signature of primary somatosensory representation. The two-point discrimination (TPD) threshold is increasingly used both clinically and in research. Remarkably, the reliability and precision of the measure at commonly used sites has not been determined. This study aimed to determine the utility, intra- and inter-rater reliability, bias and variability of TPD threshold assessment at the neck, back, hand and foot using mechanical callipers. METHODS Intra- and inter-rater reliability of TPD was assessed at the back, neck, hand and foot of 28 healthy young adults by 28 clinicians. Each clinician received training in the assessment of TPD using mechanical callipers and following a standardized protocol. Intraclass correlation coefficients (ICCs) and Bland-Altman plots were used to assess reliability, bias and variability. RESULTS Intra-rater assessments in all four regions and inter-rater assessments at the neck and foot were reliable (ICC range 0.79-0.86), but large variability was seen in all assessments. Inter-rater assessment of the back (ICC = 0.66) and hand (ICC = 0.62) was deemed unreliable. Negligible systematic bias suggested learning did not affect reliability. CONCLUSION Individual clinicians are able to reliably assess TPD threshold at the neck, back, hand and foot using mechanical callipers. Measures obtained by different clinicians were only reliable for the neck and foot. Large variability was observed in all assessments, which suggests clinicians should be cautious when interpreting changes in tactile acuity in individual patients.
Relational consistency by constraint filtering

In this paper, we propose a new algorithm for enforcing relational consistency on every set of k constraints of a finite Constraint Satisfaction Problem (CSP). This algorithm operates by filtering the constraint while leaving the topology of the graph unchanged. We study the resulting relational consistency property and compare it to existing ones. We evaluate the effectiveness of our algorithm in a search procedure for solving CSPs and demonstrate the applicability, effectiveness, and usefulness of enforcing high levels of consistency.
Solving quantile-based stochastic optimization problems with modified Stochastic Nelder-Mead Simplex Method

Quantile is one of the major metrics used in risk management. Since qauantile represents the downside risk. In this paper, we present a new variant of Nelder-Mead method (NM) for quantile-based stochastic optimization, called Stochastic Nelder-Mead Simplex Method for Quantile (SNM-Q), that aims to minimize the downside of decisions made in stochastic environments. An extensive numerical study shows that SNM-Q can efficiently and effectively control the risk and thus is worth further investigation.
Direct interaction of the Golgi V-ATPase a-subunit isoform with PI(4)P drives localization of Golgi V-ATPases in yeast

PI(4)P directly interacts with the cytosolic domain of yeast Golgi vacuolar H+-ATPase (V-ATPase) a-isoform, Stv1, and the human Golgi a-subunit isoform. Lys-84 of Stv1 is essential for PI(4)P interaction, and localization of Stv1-containing V-ATPases in vivo requires the PI(4)P interaction. We propose that phosphatidylinositol binding exerts organelle-specific control over V-ATPases.
Improved Gender Independent Speaker Recognition Using Convolutional Neural Network Based Bottleneck Features

This paper proposes a novel framework to improve performance of gender independent i-Vector PLDA based speaker recognition using convolutional neural network (CNN). Convolutional layers of a CNN offer robustness to variations in input features including those due to gender. A CNN is trained for ASR with a linear bottleneck layer. Bottleneck features extracted using the CNN are then used to train a gender-independent UBM to obtain frame posteriors for training an i-Vector extractor matrix. To preserve speaker specific information, a hybrid approach to training the i-Vector extractor matrix using MFCC features with corresponding frame posteriors derived from bottleneck features is proposed. On the NIST SRE10 C5 condition pooled trials, our approach reduces the EER and minDCF 2010 by +14.62% and +14.42% respectively compared to a standard mfcc based gender-independent speaker recognition system.
E-cecilia: implementation of a music game

This paper describes a serious game intended to teach singing to children. The system shows the students a virtual world they can explore, and the evolution of the world is based on their performance. Automatic content generation tecniques are used to present the player with different exercises, and their singing is evaluated using state of the art techniques.
Factors Affecting the Abundance of Leaf-Litter Arthropods in Unburned and Thrice-Burned Seasonally-Dry Amazonian Forests

Fire is frequently used as a land management tool for cattle ranching and annual crops in the Amazon. However, these maintenance fires often escape into surrounding forests, with potentially severe impacts for forest biodiversity. We examined the effect of experimental fires on leaf-litter arthropod abundance in a seasonally-dry forest in the Brazilian Amazon. The study plots (50 ha each) included a thrice-burned forest and an unburned control forest. Pitfall-trap samples were collected at 160 randomly selected points in both plots, with sampling stratified across four intra-annual replicates across the dry and wet seasons, corresponding to 6, 8, 10 and 12 months after the most recent fire. Arthropods were identified to the level of order (separating Formicidae). In order to better understand the processes that determine arthropod abundance in thrice-burned forests, we measured canopy openness, understory density and litter depth. All arthropod taxa were significantly affected by fire and season. In addition, the interactions between burn treatment and season were highly significant for all taxa but Isoptera. The burned plot was characterized by a more open canopy, lower understory density and shallower litter depth. Hierarchical partitioning revealed that canopy openness was the most important factor explaining arthropod order abundances in the thrice-burned plot, whereas all three environmental variables were significant in the unburned control plot. These results reveal the marked impact of recurrent wildfires and seasonality on litter arthropods in this transitional forest, and demonstrate the overwhelming importance of canopy-openness in driving post-fire arthropod abundance.
Mediodorsal Thalamic Neurons Mirror the Activity of Medial Prefrontal Neurons Responding to Movement and Reinforcement during a Dynamic DNMTP Task

Abstract The mediodorsal nucleus (MD) interacts with medial prefrontal cortex (mPFC) to support learning and adaptive decision-making. MD receives driver (layer 5) and modulatory (layer 6) projections from PFC and is the main source of driver thalamic projections to middle cortical layers of PFC. Little is known about the activity of MD neurons and their influence on PFC during decision-making. We recorded MD neurons in rats performing a dynamic delayed nonmatching to position (dDNMTP) task and compared results to a previous study of mPFC with the same task (Onos et al., 2016). Criterion event-related responses were observed for 22% (254/1179) of neurons recorded in MD, 237 (93%) of which exhibited activity consistent with mPFC response types. More MD than mPFC neurons exhibited responses related to movement (45% vs. 29%) and reinforcement (51% vs. 27%). MD had few responses related to lever presses, and none related to preparation or memory delay, which constituted 43% of event-related activity in mPFC. Comparison of averaged normalized population activity and population response times confirmed the broad similarity of common response types in MD and mPFC and revealed differences in the onset and offset of some response types. Our results show that MD represents information about actions and outcomes essential for decision-making during dDNMTP, consistent with evidence from lesion studies that MD supports reward-based learning and action-selection. These findings support the hypothesis that MD reinforces task-relevant neural activity in PFC that gives rise to adaptive behavior.
Name that Percussive Tune: Associative Memory and Amplitude Envelope†

A series of experiments demonstrated novel effects of amplitude envelope on associative memory, with tones exhibiting naturally decaying amplitude envelopes (e.g., those made by two wine glasses clinking) better associated with target objects than amplitude-invariant tones. In Experiment 1 participants learned associations between household objects and 4-note tone sequences constructed of spectrally matched pure tones with either “flat” or “percussive” amplitude envelopes. Those hearing percussive tones correctly recalled significantly more sequence–object associations. Experiment 2 demonstrated that participants hearing percussive tones learned the associations more quickly. Experiment 3 used “reverse percussive” tones (percussive tones played backwards) to test whether differences in overall energy might account for this effect, finding they did not lead to the same level of performance as percussive tones. Experiment 4 varied the envelope at encoding and retrieval to determine which stage of the task was most affected by the envelope manipulation. Participants hearing percussive tones at both encoding and retrieval performed significantly better than the other three groups (i.e., flat at encoding/percussive at retrieval, etc.). We conclude that amplitude envelope plays an important role in learning and memory, a finding with relevance to psychological research on audition and associative memory, as well as practical relevance for improving human–computer interface design.
Structural Investigation by Atomic Force Microscopy

Nanotechnology is an emerging field of research that has been widely applied in different fundamental science and engineering areas. An example of a nano-based device is the atomic force microscope, which is a widely used surface scanning apparatus capable of reconstructing at a nanometric scale resolution the 3D morphology of a wide variety of samples. Therefore, due to its versatility, sensitivity and unique capability to reveal the nanoscale structure of the samples, atomic force microscopy (AFM) produced, in the last years, a vast increase of reports of its use to determine the topography, electric properties, nanomechanics and even nanomanipulations of various samples in the fields of materials science, chemistry, physics, biology, microbiology, medicine, engineering, food products, forensic, etc.
A Novel Architecture for Trademark Image Retrieval Systems

This paper describes the first phase of an ongoing research project aimed at implementing a trademark retrieval system using an associative memory neural network. The novel aspect of the work described in this paper is the presentation of a new integrated methodology for employing multiple interpretations from different analytical levels of images for image retrieval. In achieving this objective, we extract local features as well as features of the closed figures of images. In deriving alternative interpretations of the images, a segment level gestalt grouping method based on a modification of Sarkar and Boyer’s method is used. In designing the search engine of the system we have adopted a novel similarity assessment criteria based on local features as well as features of the closed figures, which may feasibly be implemented using an associative memory neural network to achieve high performance in retrieval.
Management of opioid addiction with buprenorphine: French history and current management

The way in which opioid addiction is managed in France is unique, as it is based on the prescription of buprenorphine by general practitioners and is dispensed by retail pharmacies. This policy has had a direct, positive impact on the number of deaths caused by heroin overdose, which was reduced by four-fifths between 1994 and 2002. In addition, certain associated comorbidities, such as infection with the human immunodeficiency virus, have also been reduced; the incidence of acquired immune deficiency syndrome in intravenous drug users fell from 25% in the mid-1990s to 6% in 2010. Since the implementation of this French model of opioid management, major scientific progress has been made, leading to a better understanding of the pathophysiologic mechanisms of addiction and of the management modalities required for its treatment. However, despite notable advances in scientific knowledge and in the implementation of devices, opioid addiction remains a major public health care issue in France, with 275,000–360,000 “problem drug users” being reported in 2011. The situation is still particularly worrying due to psychoactive substance use and misuse of opioid substitution treatments. Since 2003, there has been a persistent increase in the number of deaths and comorbidities related to opioid addiction, principally hepatitis C virus infection, which affects up to 40% of intravenous drug users. In France, the direct involvement of general practitioners in the management of opioid addiction is indisputable. Nevertheless, management could be optimized through better understanding of the pathophysiologic mechanisms of the disease, better knowledge of the pharmacology of opioid substitution treatments, and clear definition of short-, medium- and long-term treatment objectives. Data related to the management of opioid addiction by general practitioners in France have been published in 2005. Since then, the context has changed, other drugs were launched on the market such as generics of buprenorphine, methadone capsule, and Suboxone. Thus, an update seems necessary. This paper provides a description of opioid addiction management objectives and treatment modalities for general practitioners, based on currently available knowledge.
Utility function optimization based joint user association and content placement in heterogeneous networks

The rapid growth of traffic demands has posed challenges and difficulties on both the radio access networks (RANs) and the backhaul links. To stress these problems, caching technology, more specifically, caching user contents at the infrastructures of different RANs is proposed as an effective approach. In this paper, we consider the joint user association and cache content placement problem in cache-enabled heterogeneous networks (HetNets). Stressing the tradeoff between user download delay and caching cost, we define a utility function which characterizes the joint network performance as the weighted sum of user download delay and the caching cost and formulate the joint user association and cache content placement problem as a network utility optimization problem. As the formulated optimization problem is a nonlinear integer optimization problem which cannot be solved conveniently using traditional optimization tools, we transform the original optimization problem equivalently into three convex subproblems by applying McCormick envelopes and Lagrange partial relaxation, and then solve the subproblems by means of Kuhn-Munkres (K-M) algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm.
Long-Term Exposure to Cigarette Smoke Extract Induces Hypomethylation at the RUNX3 and IGF2-H19 Loci in Immortalized Human Urothelial Cells

Cigarette smoking is the single most important epidemiological risk factor for bladder cancer but it is not known whether exposure of urothelial cells to the systemic soluble contents of cigarette smoke is directly causative to bladder cancer and the associated epigenetic changes such as tumor suppressor gene hypermethylation. We undertook this study to investigate if long-term treatment of human urothelial cells with cigarette smoke extract (CSE) results in tumor suppressor gene hypermethylation, a phenotype that was previously associated with long-term constant CSE treatment of airway epithelial cells. We chronically treated an immortalized human urothelial cell line UROtsa with CSE using a cyclic daily regimen but the cells were cultured in CSE-free medium between daily treatments. Bisulfite sequencing and real-time PCR array-based methylation profiling were employed to evaluate methylation changes at tumor suppressor gene loci in the chronically CSE-treated cells versus the passage-matched untreated control cells. The RUNX3 tumor suppressor gene promoter was hypomethylated with a significant increase in proportion of the completely unmethylated haplotype after the long-term CSE treatment; whereas RUNX3 promoter hypermethylation was previously reported for bladder cancers of smokers. Hypomethylation induced by the long-term CSE treatment was also observed for the IGF2-H19 locus. The methylation status at the PRSS8/prostasin and 16 additional loci however, was unaffected by the chronic CSE treatment. Transient CSE treatment over 1 daily regimen resulted in transcriptional down-regulation of RUNX3 and H19, but only the H19 transcription was down-regulated in the chronically CSE-treated urothelial cells. Transcription of a key enzyme in one-carbon metabolism, dihydrofolate reductase (DHFR) was greatly reduced by the long-term CSE treatment, potentially serving as a mechanism for the hypomethylation phenotype via a reduced supply of methyl donor. In conclusion, chronic cyclic CSE treatment of urothelial cells induced hypomethylation rather than hypermethylation at specific loci.
Purification and partial characterization of a penicillin-binding protein from Mycobacterium smegmatis

Penicillin-binding proteins (PBPs), although characterized from several organisms, have so far not been studied in mycobacteria. The present study is the first characterization of a PBP from Mycobacterium smegmatis. The PBP was purified by solubilization of the membranes with Triton X-100 and successive chromatography of the solubilized proteins on ampicillin-linked CH Sepharose 4B and DE-52. The purified PBP (M(r), 49,500) catalyzed a model transpeptidase reaction with the tripeptide acetyl2-L-Lys-D-Ala-D-Ala as the substrate and Gly-Gly as the acceptor. The transpeptidase activity was inhibited by 50% at a benzylpenicillin concentration of 1.8 x 10(-7) M, which was similar to the concentration (1.1 x 10(-7) M) of benzylpenicillin required to saturate to 50% this PBP. Of several antibiotics tested, the concentration of antibiotic required to inhibit [35S]penicillin binding by 90% was found to be the lowest for cefoxitin and Sch 34343.
Lessons Learned from Quantitative Dynamical Modeling in Systems Biology

Due to the high complexity of biological data it is difficult to disentangle cellular processes relying only on intuitive interpretation of measurements. A Systems Biology approach that combines quantitative experimental data with dynamic mathematical modeling promises to yield deeper insights into these processes. Nevertheless, with growing complexity and increasing amount of quantitative experimental data, building realistic and reliable mathematical models can become a challenging task: the quality of experimental data has to be assessed objectively, unknown model parameters need to be estimated from the experimental data, and numerical calculations need to be precise and efficient. Here, we discuss, compare and characterize the performance of computational methods throughout the process of quantitative dynamic modeling using two previously established examples, for which quantitative, dose- and time-resolved experimental data are available. In particular, we present an approach that allows to determine the quality of experimental data in an efficient, objective and automated manner. Using this approach data generated by different measurement techniques and even in single replicates can be reliably used for mathematical modeling. For the estimation of unknown model parameters, the performance of different optimization algorithms was compared systematically. Our results show that deterministic derivative-based optimization employing the sensitivity equations in combination with a multi-start strategy based on latin hypercube sampling outperforms the other methods by orders of magnitude in accuracy and speed. Finally, we investigated transformations that yield a more efficient parameterization of the model and therefore lead to a further enhancement in optimization performance. We provide a freely available open source software package that implements the algorithms and examples compared here.
Estimating service resource consumption from response time measurements

We propose a linear regression method and a maximum likelihood technique for estimating the service demands of requests based on measurement of their response times instead of their CPU utilization. Our approach does not require server instrumentation or sampling, thus simplifying the parameterization of performance models. The benefit of this approach is further highlighted when utilization measurement is difficult or unreliable, such as in virtualized systems or for services controlled by third parties. Both experimental results from an industrial ERP system and sensitivity analyses based on simulations indicate that the proposed methods are often much more effective for service demand estimation than popular utilization based linear regression methods. In particular, the maximum likelihood approach is found to be typically two to five times more accurate than utilization based regression, thus suggesting that estimating service demands from response times can help in improving performance model parameterization.
A note on modifications to the methodology for components in the complex technical systems reliability structure importance evaluation

The paper presents State-of-the-Art in topic of reliability importance analysis for components and groups of components in complex technical systems (CTS). Basic importance evaluation measures for finding so called “weak links” in system structure have been discussed. Quantitative and qualitative importance analysis methods have been presented. Range of applicability of these methods have been pointed out. Some results of importance evaluation with use of Birnbaum’s and Vesseley-Fussell’s measures based on the example of 2-phased complex marine system have been shown. Critically conclusions on currently known importance analysis methods have been presented.