Miracle-dz/UniFAR-FTUs huggingface dataset:
Blood Biomarkers of Hypoxic-Ischemic Brain Injury after Cardiac Arrest

Abstract Biomarkers are part of the recommended outcome predictors after cardiac arrest. In general, blood biomarkers can easily be performed as routine laboratory tests, and they are unaffected by sedation, but bear the potential risk of laboratory errors. Nonetheless, if used properly, with the potential limitations in mind, they certainly help predict outcome after cardiac arrest. Among the routinely used and available blood biomarkers, neuron-specific enolase (NSE) has the best predictive value for poor outcome if measured serially from 24 to 72 hours. Cutoff values per se should be taken with caution because there is no 100% specificity (0% false-positive rate) in clinical practice. Rather, the increase over time of high NSE values is predictive of poor outcome. Other biomarkers like protein S100 and inflammatory markers also bear a potential to predict outcome, but they are outperformed by NSE. New blood biomarkers are currently under investigation and might improve the accuracy of outcome prediction. The family of noncoding RNAs, including microRNAs, is probably the most promising as microRNAs are not only associated with outcome, but also have the potential for therapeutic implications through their mechanism of action.
Global Stabilization of Robot Control with Neural Network and Sliding Mode

This paper presents a neural network global PID-sliding mode control method for the tracking control of robot manipulators with bounded uncertainties. A certain sliding mode controller with PID sliding function is developed. In this controller, the switching gain is tuned by a single-input radial-basis-function neural network on the reachable condition of sliding mode. Thus, the effect of chattering can be alleviated. Moreover, global sliding mode is realized by designing an exponential dynamic sliding function. Mathematical proof of the stability and convergence of the control system is given. Simulation results demonstrate that the chattering and the steady state errors are eliminated and satisfactory trajectory tracking is achieved. sliding surface for robot manipulators were presented. Simulation results demonstrated that PID sliding surface provided faster response than that of traditional PD-manifold controller. In this paper, a robust neural network global sliding mode PID-controller is proposed to control a robot manipulator with parameter variations and external disturbances. The chattering phenomenon is eliminated by substituting a single-input radial-basis-function (RBF) neural network. Moreover, a theoretical proof of the stability and the convergence of the proposed scheme are provided.
A Methodology to Quantify Alterations in Human Upper Limb Movement During Co-Manipulation With an Exoskeleton

While a large number of robotic exoskeletons have been designed by research teams for rehabilitation, it remains rather difficult to analyse their ability to finely interact with a human limb: no performance indicators or general methodology to characterize this capacity really exist. This is particularly regretful at a time when robotics are becoming a recognized rehabilitation method and when complex problems such as 3-D movement rehabilitation and joint rotation coordination are being addressed. The aim of this paper is to propose a general methodology to evaluate, through a reduced set of simple indicators, the ability of an exoskeleton to interact finely and in a controlled way with a human. The method involves measurement and recording of positions and forces during 3-D point to point tasks. It is applied to a 4 degrees-of-freedom limb exoskeleton by way of example.
Alpha Oscillations Related to Anticipatory Attention Follow Temporal Expectations

Temporal expectations have been shown to enhance visual analysis of task-relevant events, especially when these are coupled with spatial expectations. Oscillatory brain activity, particularly in the alpha band, has been implicated in regulating excitability in visual areas as a function of anticipatory spatial attention. Here we asked whether temporal expectations derived from regular, rhythmic events can modulate ongoing oscillatory alpha-band activity, so that the changes in cortical excitability are focused over the time intervals at which target events are expected. The task we used involved making a perceptual discrimination about a small target stimulus that reappeared from “behind” a peripheral occluding band. Temporal expectations were manipulated by the regular, rhythmic versus irregular, arrhythmic approach of the stimulus toward the occluding band. Alpha-band activity was measured during the occlusion period, in which no stimulus was presented, but target reappearance was anticipated in conditions of high versus low temporal expectation. Time–frequency analysis showed that the amplitude of alpha-desynchronization followed the time course of temporal expectations. Alpha desynchronization increased rhythmically, peaking just before the expected reappearance of target times. Analysis of the event-related potentials evoked by the subsequent target stimuli showed enhancement of processing at both visual and motor stages. Our findings support a role for oscillations in regulating cortical excitability and suggest a plausible mechanism for biasing perception and action by temporal expectations.
A Semi-Automatic Object Extraction Tool for Querying in Multimedia Databases

Considering the complexity and huge volume of image and/or video data, efficient methods need to be developed for querying multimedia databases. A well-known technique used for querying multimedia data is query-by-feature (e.g. color, shape, texture, size) of the objects residing in images and/or video frames. In this paper, we propose a tool for extracting objects from images and/or video frames, called Object Extractor, as well as the ways of coping with the object features within extracted objects. The tool is semiautomatic in the sense that the user specifies the colors on the object by clicking the mouse to make the tool capture object pixels. In order to extract objects, an improved version of the Flood Fill algorithm for polygon filling is provided. The extraction algorithm uses filtered images to perform better. Moreover, the experimental results obtained for evaluating the performance of the tool in extracting objects are presented. It is shown through these results that a few mouse clicks would suffice to extract objects effectively.
Modulated fibring and the collapsing problem

Abstract Fibring is recognized as one of the main mechanisms in combining logics, with great significance in the theory and applications of mathematical logic. However, an open challenge to fibring is posed by the collapsing problem: even when no symbols are shared, certain combinations of logics simply collapse to one of them, indicating that fibring imposes unwanted interconnections between the given logics. Modulated fibring allows a finer control of the combination, solving the collapsing problem both at the semantic and deductive levels. Main properties like soundness and completeness are shown to be preserved, comparison with fibring is discussed, and some important classes of examples are analyzed with respect to the collapsing problem.
Wireless Routing Protocol Based on Auto -- Learning Algorithm

Given the highly dynamic nature of wireless ad hoc network, routing is one of the most challenging tasks. Among the routing protocols that are in the process of normalisation is AODV (Ad hoc on demand Distance Vector). AODV is a reactive source based on routing protocol whose performance is very sensitive to several fixed parameters, such as. ACTIVE_ROUTE_TIMEOUT, HELLO_INTERVAL, MY_ROUTE_TIMEOUT, NET_DIAMETER, RREQ_RETRIES, . In this paper we propose an adaptive version of AODV (A^2ODV) where the protocol regularly adapts its routing decision to the state of the behaviour and the state of the network. In A^2ODV each node maintains an estimation of the reliability as well as an expected residual uptime of its interfaces. A route is characterized by two metrics: (1) reliability defined as the product of its constituent links; and (2) Route residual lifetime estimated by the residual lifetime of its weakest link. Route selection is a function of these two metrics. Simulation shows that A^2ODV clearly outperforms AODV with respect to packet delivery ratio and overhead traffic.
Blind signal separation for convolutive mixing environments using spatial-temporal processing

In this paper we extend the infomax technique of Bell and Sejnowski (see Neural Computation, vol.7, no.6, p.1129-59, 1995) for blind signal separation from the instantaneous mixing case to the convolutive mixing case. Separation in the convolutive case requires an unmixing system which uses present and past values of the observation vector, when the mixing system is causal. Thus, in developing an infomax process, both temporal and spatial dependence of the observations must be considered. We propose a stochastic gradient based structure which accomplishes this task. The performance of the proposed method is verified by subjective listening tests and quantitative measurements.
Synthesis methods and experiment validation of compliant force controller based inner position loop

Compliant force control in space docking is studied. Compliant force control strategy is developed based on the inner loop position control of 6-dof parallel robot in order to simulate push and pull process of forcible alignment in space docking. Compliant force control structure based on the inner position loop is introduced. The more systematic design methods of a serial PID type controller and a robust controller are presented in detail. Simulation and experiment results indicate efficiency of the designed force controllers and superiority of robust force controller.
Increased Copper in Individuals with Autism Normalizes Post Zinc Therapy More Efficiently in Individuals with Concurrent GI Disease

Aim To assess plasma zinc and copper concentration in individuals with autism. Subjects and Methods Plasma from 79 autistic individuals, and 18 age and gender similar neurotypical controls, were tested for plasma zinc and copper using inductively-coupled plasma-mass spectrometry. Results Autistic individuals had significantly elevated plasma levels of copper and Cu/Zn and lower, but not significantly lower, plasma Zn compared to neurotypical controls. Zn levels increased significantly in autistic individuals with and without GI disease after zinc therapy. Cu decreased significantly after zinc therapy in the GI disease group but not in the autistic group without GI disease. Autistic children significantly improved with respect to hyperactivity and stimming after zinc therapy in autistic children with GI disease. Autistic children without GI disease did not improve in these symptoms after the same therapy. Discussion These results suggest an association between zinc and copper plasma levels and autism, and they suggest that zinc therapy may be most effective at lowering copper levels in autistic children with GI disease.
Beam propagation modeling of arbitrarily bent waveguides

A numerical method for computing the wave fields in arbitrarily bent waveguides is developed based on a curvilinear coordinate system and the beam propagation method. Unlike earlier approaches based on the conformal mapping or the polar coordinate system, waveguides with arbitrary bends can be conveniently modeled. The new method is accurate for bends with any curvature, since it avoids the small curvature approximation.
Large scale food retailing as an intervention for diet and health: quasi-experimental evaluation of a natural experiment

Objectives: To assess the effect on fruit and vegetable consumption, self reported, and psychological health of a “natural experiment”—the introduction of large scale food retailing in a deprived Scottish community. Design: Prospective quasi-experimental design comparing baseline and follow up data in an “intervention” community with a matched “comparison” community in Glasgow, UK. Participants: 412 men and women aged 16 or over for whom follow up data on fruit and vegetable consumption and GHQ-12 were available. Main outcome measures: Fruit and vegetable consumption in portions per day, poor self reported health, and poor psychological health (GHQ-12). Main results: Adjusting for age, sex, educational attainment, and employment status there was no population impact on daily fruit and vegetable consumption, self reported, and psychological health. There was some evidence for a net reduction in the prevalence of poor psychological health for residents who directly engaged with the intervention. Conclusions: Government policy has advocated using large scale food retailing as a social intervention to improve diet and health in poor communities. In contrast with a previous uncontrolled study this study did not find evidence for a net intervention effect on fruit and vegetable consumption, although there was evidence for an improvement in psychological health for those who directly engaged with the intervention. Although definitive conclusions about the effect of large scale retailing on diet and health in deprived communities cannot be drawn from non-randomised controlled study designs, evaluations of the impacts of natural experiments may offer the best opportunity to generate evidence about the health impacts of retail interventions in poor communities.
Problem-Solving and Mental Health Outcomes of Women and Children in the Wake of Intimate Partner Violence

The environmental stress of intimate partner violence is common and often results in mental health problems of depression, anxiety, and PTSD for women and behavioral dysfunctions for their children. Problem-solving skills can serve to mitigate or accentuate the environmental stress of violence and associated impact on mental health. To better understand the relationship between problem-solving skills and mental health of abused women with children, a cross-sectional predictive analysis of 285 abused women who used justice or shelter services was completed. The women were asked about social problem-solving, and mental health symptoms of depression, anxiety, and PTSD as well as behavioral functioning of their children. Higher negative problem-solving scores were associated with significantly (P < 0.001) greater odds of having clinically significant levels of PTSD, anxiety, depression, and somatization for the woman and significantly (P < 0.001) greater odds of her child having borderline or clinically significant levels of both internalizing and externalizing behaviors. A predominately negative problem-solving approach was strongly associated with poorer outcomes for both mothers and children in the aftermath of the environmental stress of abuse. Interventions addressing problem-solving ability may be beneficial in increasing abused women's abilities to navigate the daily stressors of life following abuse.
Influences of Communication Disruptions on Decentralized Routing in Transport Logistics

The increase of complexity and dynamics leads to new challenges in transport logistics networks. Current routing algorithms of central control are pushed to their limits in handling these new challenges. This leads to the development of an autonomously controlled routing protocol, the Distributed Logistics Routing Protocol (DLRP), which allows a better handling of the new requirements. Within the DLRP, the logistic entities perform routing decisions on their own. For that a high degree of knowledge exchange between the logistics entities is essential. Within the work presented in this paper the influences of communication disruptions are investigated. Communication disruptions can lead to partial knowledge for the logistic entities, which has negative influences on their routing decisions. This paper presents the influences of different degrees of communication disruptions on the routing processes. Key-Words: Autonomous control Distributed logistics routing protocol (DLRP) – Transport logistics – Routing algorithms – Communication disruptions
Augmented vision for medical applications

Computer vision techniques for tracking real objects as surgical tools and organs of patients are been integrated in medical scenarios. We present a marker-based approach followed by a rigid registration procedure to align real and virtual objects. A maxillofacial surgery is being used as case study and our method provides virtual and augmented aid to the surgeon while performing osteotomy tasks. Results reached with the proposed system shows to be acceptable when compared with previous work.
The link between CD8+ T-cell antigen-sensitivity and HIV-suppressive capacity depends on HLA restriction, target epitope and viral isolate

Background:Although it is established that CD8+ T-cell immunity is critical for the control of HIV replication in vivo, the key factors that determine antiviral efficacy are yet to be fully elucidated. Antigen-sensitivity and T-cell receptor (TCR) avidity have been identified as potential determinants of CD8+ T-cell efficacy. However, there is no general consensus in this regard because the relationship between these parameters and the control of HIV infection has been established primarily in the context of immunodominant CD8+ T-cell responses against the Gag263–272 KK10 epitope restricted by human leukocyte antigen (HLA)-B27. Methods:To investigate the relationship between antigen-sensitivity, TCR avidity and HIV-suppressive capacity in vitro across epitope specificities and HLA class I restriction elements, we used a variety of techniques to study CD8+ T-cell clones specific for Nef73–82 QK10 and Gag20–29 RY10, both restricted by HLA-A3, alongside CD8+ T-cell clones specific for Gag263–272 KK10. Results:For each targeted epitope, the linked parameters of antigen-sensitivity and TCR avidity correlated directly with antiviral efficacy. However, marked differences in HIV-suppressive capacity were observed between epitope specificities, HLA class I restriction elements and viral isolates. Conclusions:Collectively, these data emphasize the central role of the TCR as a determinant of CD8+ T-cell efficacy and demonstrate that the complexities of antigen recognition across epitope and HLA class I boundaries can confound simple relationships between TCR engagement and HIV suppression.
Wavelet Entropy and Directed Acyclic Graph Support Vector Machine for Detection of Patients with Unilateral Hearing Loss in MRI Scanning

Highlights We develop computer-aided diagnosis system for unilateral hearing loss detection in structural magnetic resonance imaging. Wavelet entropy is introduced to extract image global features from brain images. Directed acyclic graph is employed to endow support vector machine an ability to handle multi-class problems. The developed computer-aided diagnosis system achieves an overall accuracy of 95.1% for this three-class problem of differentiating left-sided and right-sided hearing loss from healthy controls. Aim: Sensorineural hearing loss (SNHL) is correlated to many neurodegenerative disease. Now more and more computer vision based methods are using to detect it in an automatic way. Materials: We have in total 49 subjects, scanned by 3.0T MRI (Siemens Medical Solutions, Erlangen, Germany). The subjects contain 14 patients with right-sided hearing loss (RHL), 15 patients with left-sided hearing loss (LHL), and 20 healthy controls (HC). Method: We treat this as a three-class classification problem: RHL, LHL, and HC. Wavelet entropy (WE) was selected from the magnetic resonance images of each subjects, and then submitted to a directed acyclic graph support vector machine (DAG-SVM). Results: The 10 repetition results of 10-fold cross validation shows 3-level decomposition will yield an overall accuracy of 95.10% for this three-class classification problem, higher than feedforward neural network, decision tree, and naive Bayesian classifier. Conclusions: This computer-aided diagnosis system is promising. We hope this study can attract more computer vision method for detecting hearing loss.
Dopamine suppresses persistent network activity via D1-like dopamine receptors in rat medial entorhinal cortex

Cortical networks display persistent activity in the form of periods of sustained synchronous depolarizations (‘UP states’) punctuated by periods of relative hyperpolarization (‘DOWN states’), which together form the slow oscillation. UP states are known to be synaptically generated and are sustained by a dynamic balance of excitation and inhibition, with fast ionotropic glutamatergic excitatory and GABAergic inhibitory conductances increasing during the UP state. Previously, work from our group demonstrated that slow metabotropic GABA receptors also play an important role in terminating the UP state, but the effects of other neuromodulators on this network phenomenon have received little attention. Given that persistent activity is a neural correlate of working memory and that signalling through dopamine receptors has been shown to be critical for working memory tasks, we examined whether dopaminergic neurotransmission affected the slow oscillation. Here, using an in vitro model of the slow oscillation in rat medial entorhinal cortex, we showed that dopamine strongly and reversibly suppressed cortical UP states. We showed that this effect was mediated through D1‐like and not D2‐like dopamine receptors, and we found no evidence that tonic dopaminergic transmission affected UP states in our model.
An effective matrix compression method for GPU-accelerated thermal analysis

Three-dimensional integrated circuits are expected to face increasingly severe thermal challenges and cost issues as the number of stacked ICs increases. Thermal analysis for 3D ICs is urgently required to assist system designers at the early phase of design to identify hot zones. Most thermal analyses obtain detailed temperature distribution by large matrix operations, and hence reduce analysis performance. Accordingly, we propose a compressed and combined sparse row (CCSR) matrix format to be used in the proposed effective matrix compression (EMC) method for matrix multiplication on GPU. The experimental results show EMC using CCSR is on average 44.93 times faster than matrix multiplication without any special compression format and on average at least 3.09 times faster than other compression formats.
FBW7 regulates DNA interstrand cross-link repair by modulating FAAP20 degradation

Mutations that deregulate protein degradation lead to human malignancies. The SCF ubiquitin E3 ligase complex degrades key oncogenic regulators, thereby limiting their oncogenic potential. FBW7 is a substrate recognition subunit of SCFFBW7 and is among the most commonly mutated ubiquitin-proteasome system proteins in cancer. FBW7-mutated cancer cells display increased genome instability, but the molecular mechanism by which FBW7 preserves genome integrity remains elusive. Here, we demonstrate that SCFFBW7 regulates the stability of FAAP20, a critical component of the Fanconi anemia (FA) DNA interstrand cross-link (ICL) repair pathway. Phosphorylation of the FAAP20 degron motif by GSK3β provides a platform for recognition and polyubiquitination of FAAP20 by FBW7, and its subsequent degradation by the proteasome. Accordingly, enhanced GSK3β-FBW7 signaling disrupts the FA pathway. In cells expressing non-phosphorylatable FAAP20 mutant, the turnover of its binding partner, FANCA, is deregulated in the chromatin during DNA ICL repair, and the FA pathway is compromised. We propose that FAAP20 degradation, which is prompted by its phosphorylation, controls the dynamics of the FA core complex required for completing DNA ICL repair. Together, this study provides insights into how FBW7-mediated proteolysis regulates genome stability and how its deregulation is associated with tumorigenesis.