Miracle-dz/UniFAR-FTUs huggingface dataset:
Tungsten-Based Composites for Nuclear Fusion Applications

This chapter provides a comprehensive knowledge about the potential role of tungstenbased composites in fusion reactors and the research work which has been done in this very important area of nuclear materials. The characteristics of tungsten, which make it the most potential candidate for plasma-facing applications, have been presented along with the shortcomings in pure tungsten. The research work that has been done so far in the field of tungsten-based composites to overcome the problems with pure tungsten has been included. The fabrication, characterization, types of reinforcements and the classes of composites have been reviewed. The behavior of tungsten-based composites under various kinds of loads (i.e. mechanical and thermal) and environments (radiations and oxidizing etc.) has been summarized.
Tissue plasminogen activator-based nanothrombolysis for ischemic stroke

ABSTRACT Introduction: Thrombolysis with intravenous tissue plasminogen activator (tPA) is the only FDA approved treatment for patients with acute ischemic stroke, but its use is limited by narrow therapeutic window, selective efficacy, and hemorrhagic complication. In the past two decades, extensive efforts have been undertaken to extend its therapeutic time window and explore alternative thrombolytic agents, but both show little progress. Nanotechnology has emerged as a promising strategy to improve the efficacy and safety of tPA. Areas covered: We reviewed the biology, thrombolytic mechanism, and pleiotropic functions of tPA in the brain and discussed current applications of various nanocarriers intended for the delivery of tPA for treatment of ischemic stroke. Current challenges and potential further directions of t-PA-based nanothrombolysis in stroke therapy are also discussed. Expert opinion: Using nanocarriers to deliver tPA offers many advantages to enhance the efficacy and safety of tPA therapy. Further research is needed to characterize the physicochemical characteristics and in vivo behavior of tPA-loaded nanocarriers. Combination of tPA based nanothrombolysis and neuroprotection represents a promising treatment strategy for acute ischemic stroke. Theranostic nanocarriers co-delivered with tPA and imaging agents are also promising for future stroke management.
Tapered Optical Fiber Functionalized with Palladium Nanoparticles by Drop Casting and Laser Radiation for H2 and Volatile Organic Compounds Sensing Purposes

A comparative study on the sensing properties of a tapered optical fiber pristine and functionalized with the palladium nanoparticles to hydrogen and volatile organic compounds (VOCs), is presented. The sensor response and, response/recovery times were extracted from the measurements of the transient response of the device. The tapered optical fiber sensor was fabricated using a single-mode optical fiber by the flame-brushing technique. Functionalization of the optical fiber was performed using an aqueous solution of palladium chloride by drop-casting technique assisted for laser radiation. The detection principle of the sensor is based on the changes in the optical properties of palladium nanoparticles when exposed to reducing gases, which causes a variation in the absorption of evanescent waves. A continuous wave laser diode operating at 1550 nm is used for the sensor characterization. The sensor functionalized with palladium nanoparticles by this technique is viable for the sensing of hydrogen and VOCs, since it shows an enhancement in sensor response and response time compared to the sensor based on the pristine optical microfiber. The results show that the fabricated sensor is competitive with other fiber optic sensors functionalized with palladium nanoparticles to the hydrogen.
A Trust-Based Coordination System for Participatory Sensing Applications

Participatory sensing (PS) has gained significant attention as a crowdsourcing methodology that allows ordinary citizens (non-expert contributors) to collect data using low-cost mobile devices. In particular, it has been useful in the collection of environmental data. However, current PS applications suffer from two problems. First, they do not coordinate the measurements taken by their users, which is required to maximise system efficiency. Second, they are vulnerable to malicious behaviour. In this context, we propose a novel algorithm that simultaneously addresses both of these problems. Specifically, we use heteroskedastic Gaussian Processes to incorporate users' trustworthiness into a Bayesian spatio-temporal regression model. The model is trained with measurements taken by participants, thus it is able to estimate the value of the phenomenon at any spatio-temporal location of interest and also learn the level of trustworthiness of each user. Given this model, the coordination system is able to make informed decisions concerning when, where and who should take measurements over a period of time. We empirically evaluate our algorithm on a real-world human mobility and air quality dataset, where malicious behaviour is synthetically produced, and show that our algorithm outperforms the current state of the art by up to 60.4% in terms of RMSE while having a reasonable runtime.
The Role of the Parietal Lobe in Visual Extinction Studied with Transcranial Magnetic Stimulation

Interhemispheric competition between homologous areas in the human brain is believed to be involved in a wide variety of human behaviors from motor activity to visual perception and particularly attention. For example, patients with lesions in the posterior parietal cortex are unable to selectively track objects in the contralesional side of visual space when targets are simultaneously present in the ipsilesional visual field, a form of visual extinction. Visual extinction may arise due to an imbalance in the normal interhemispheric competition. To directly assess the issue of reciprocal inhibition, we used fMRI to localize those brain regions active during attention-based visual tracking and then applied low-frequency repetitive transcranial magnetic stimulation over identified areas in the left and right intraparietal sulcus to asses the behavioral effects on visual tracking. We induced a severe impairment in visual tracking that was selective for conditions of simultaneous tracking in both visual fields. Our data show that the parietal lobe is essential for visual tracking and that the two hemispheres compete for attentional resources during tracking. Our results provide a neuronal basis for visual extinction in patients with parietal lobe damage.
Renyi Entropy Estimation Revisited

We revisit the problem of estimating entropy of discrete distributions from independent samples, studied recently by Acharya, Orlitsky, Suresh and Tyagi (SODA 2015), improving their upper and lower bounds on the necessary sample size n. For estimating Renyi entropy of order alpha, up to constant accuracy and error probability, we show the following * Upper bounds n = O(1) 2^{(1-1/alpha)H_alpha} for integer alpha>1, as the worst case over distributions with Renyi entropy equal to H_alpha. * Lower bounds n = Omega(1) K^{1-1/alpha} for any real alpha>1, with the constant being an inverse polynomial of the accuracy, as the worst case over all distributions on K elements. Our upper bounds essentially replace the alphabet size by a factor exponential in the entropy, which offers improvements especially in low or medium entropy regimes (interesting for example in anomaly detection). As for the lower bounds, our proof explicitly shows how the complexity depends on both alphabet and accuracy, partially solving the open problem posted in previous works. The argument for upper bounds derives a clean identity for the variance of falling-power sum of a multinomial distribution. Our approach for lower bounds utilizes convex optimization to find a distribution with possibly worse estimation performance, and may be of independent interest as a tool to work with Le Cam’s two point method.
Designing a Sequential Choice Architecture to Reduce Choice Overload

Previous studies have demonstrated that a multitude of options can lead to choice overload, reducing decision quality. Through controlled experiments, we examine sequential choice architectures that enable the choice set to remain large while potentially reducing the effect of choice overload. A specific tournament-style architecture achieves this goal. An alternate architecture in which subjects compare each subset of options to the most preferred option encountered thus far fails to improve performance due to the status quo bias. Subject preferences over different choice architectures are negatively correlated with performance, suggesting that providing choice over architectures might reduce the quality of decisions.
“Active listening” in written online communication - a case study in a course on “soft skills for computer scientists”

"Active listening" is a well-known ingredient in contexts that involve gathering information and solving problems. Demanding both verbal and nonverbal skills, this way of communication improves mutual understanding by using techniques like paraphrasing. The benefits are manifold and crucial for computer scientists. For instance, it avoids misunderstandings, as people verify they do really understand. Our study investigates active listening in an online educational setting using written communication, which is a novel asset. We explore whether active listening is effective in written online communication and examine this mediumpsilas capacity to fully exploit this conceptpsilas benefits. The study was conducted in a technology-enhanced course on ldquoSoft Skills for Computer Scientistsrdquo. Interestingly, analysis reveals that active listening techniques do have positive effects on communication in the analyzed setting of online communication. Furthermore, it appears that instant messaging tools facilitate to let the other completely verbalize his or her thought before responding.
Neuroscience and Biobehavioral Reviews Linking Neocortical, Cognitive, and Genetic Variability in Autism with Alterations of Brain Plasticity: the Trigger-threshold-target Model

Keywords: Autism Asperger Perception Language Speech Intellectual disability Cross-modal plasticity Synaptic plasticity Cortical reallocation Double-hit mechanism Syndromic autism Enhanced perceptual functioning Veridical mapping a b s t r a c t The phenotype of autism involves heterogeneous adaptive traits (strengths vs. disabilities), different domains of alterations (social vs. non-social), and various associated genetic conditions (syndromic vs. nonsyndromic autism). Three observations suggest that alterations in experience-dependent plasticity are an etiological factor in autism: (1) the main cognitive domains enhanced in autism are controlled by the most plastic cortical brain regions, the multimodal association cortices; (2) autism and sensory deprivation share several features of cortical and functional reorganization; and (3) genetic mutations and/or environmental insults involved in autism all appear to affect developmental synaptic plasticity, and mostly lead to its upregulation. We present the Trigger-Threshold-Target (TTT) model of autism to organize these findings. In this model, genetic mutations trigger brain reorganization in individuals with a low plasticity threshold, mostly within regions sensitive to cortical reallocations. These changes account for the cognitive enhancements and reduced social expertise associated with autism. Enhanced but normal plasticity may underlie non-syndromic autism, whereas syndromic autism may occur when a triggering mutation or event produces an altered plastic reaction, also resulting in intellectual disability and dysmorphism in addition to autism. Differences in the target of brain reorganization (perceptual vs. language regions) account for the main autistic subgroups. In light of this model, future research should investigate how individual and sex-related differences in synaptic/regional brain plasticity influence the occurrence of autism. 1. Introduction: Genetically determined high plasticity is associated with both the strengths of autistic people and variability in the autistic phenotype
Highly Pathogenic Avian Influenza Virus (H5N8) Clade 2.3.4.4 Infection in Migratory Birds, Egypt

We isolated highly pathogenic avian influenza virus (H5N8) of clade 2.3. 4.4 from the common coot (Fulica atra) in Egypt, documenting its introduction into Africa through migratory birds. This virus has a close genetic relationship with subtype H5N8 viruses circulating in Europe. Enhanced surveillance to detect newly emerging viruses is warranted.
Tuning the Anti-Phase Mode Sensitivity to Vibrations of a MEMS Gyroscope

This paper proposes a stiffness correction method to improve the resilience to vibration of a dual-mass MEMS gyroscope with a particular focus near the resonance frequency of the anti-phase drive mode (fDa), i.e., its operational mode. Because of its balanced shape, this operating mode is ideally insensitive to vibrations. However, fabrication imperfections generates a residual sensitivity to parasitic vibrations that can disturb normal operation of the sensor. This work shows that the application of a DC voltage (Vtr) at the drive actuation electrode enables to decrease this sensitivity by a factor of at least 30 because of the stiffness tuning of the dual-mass structure. Experiments are performed to confirm this assumption and an efficient stiffness correction method is proposed to improve device operation.
Slice Sampling Particle Belief Propagation

Inference in continuous label Markov random fields is a challenging task. We use particle belief propagation (PBP) for solving the inference problem in continuous label space. Sampling particles from the belief distribution is typically done by using Metropolis-Hastings (MH) Markov chain Monte Carlo (MCMC) methods which involves sampling from a proposal distribution. This proposal distribution has to be carefully designed depending on the particular model and input data to achieve fast convergence. We propose to avoid dependence on a proposal distribution by introducing a slice sampling based PBP algorithm. The proposed approach shows superior convergence performance on an image denoising toy example. Our findings are validated on a challenging relational 2D feature tracking application.
Modeling depth uncertainty of desynchronized multi-camera systems

Accurately recording motion from multiple perspectives is relevant for recording and processing immersive multi-media and virtual reality content. However, synchronization errors between multiple cameras limit the precision of scene depth reconstruction and rendering. In order to quantify this limit, a relation between camera de-synchronization, camera parameters, and scene element motion has to be identified. In this paper, a parametric ray model describing depth uncertainty is derived and adapted for the pinhole camera model. A two-camera scenario is simulated to investigate the model behavior and how camera synchronization delay, scene element speed, and camera positions affect the system's depth uncertainty. Results reveal a linear relation between synchronization error, element speed, and depth uncertainty. View convergence is shown to affect mean depth uncertainty up to a factor of 10. Results also show that depth uncertainty must be assessed on the full set of camera rays instead of a central subset.
Long‐term administration of oral macrolides for acne treatment increases macrolide‐resistant Propionibacterium acnes

Macrolide‐resistant Propionibacterium acnes are frequently isolated from patients with acne vulgaris, and the most resistant isolates (>90% resistance) have the 23S rRNA mutation. An increase in resistant P. acnes with this mutation is thought to be caused by the inappropriate use of antimicrobials. Therefore, we studied the mutation frequency of macrolide resistance in P. acnes in vitro. When P. acnes mutants were exposed to clarithromycin after being incubated in broth without antimicrobials, resistant mutants with the 23S rRNA mutation were not isolated. However, the mutants were obtained at the frequency of 10−6 after being pre‐incubated with 0.03 μg/mL of antimicrobials. This is the estimated epidermal concentration of clarithromycin after p.o. administration. The resistant mutants had the 23S rRNA mutations A2058G, A2059G and C2611G. When pre‐incubated with clarithromycin, C2611G mutants which showed resistance to clarithromycin were obtained 32.1% more often than pre‐incubated with clindamycin (P < 0.01). By contrast, when pre‐incubated with clindamycin, A2058G mutants, which show high‐level resistance to both clarithromycin and clindamycin, were more frequently obtained than pre‐incubated with clarithromycin (87.5%, P < 0.01). No difference in the isolation rate of A2059G mutants, which show high‐level resistance to macrolides but low‐level resistance to clindamycin, was found with either treatment. These results indicate the possibility that long‐term use of oral macrolides for acne treatment facilitate the increase of macrolide‐resistant P. acnes.
Recent Advances in Microstructural Tailoring of Silicon Nitride Ceramics and the Effects on Thermal Conductivity and Fracture Properties

Tailoring the microstructure and the composition of silicon nitride ceramics can have profound effects on their properties. Here it is shown that the grain growth behavior, in particular its anisotropy, is a function of the specific additives, which allow one to tune the microstructure from one consisting of more equiaxed grains to one with very elongated grains. Recent studies are discussed that provide an understanding of the atomic level processes by which these additives influence grain shapes. Next the microstructural (and compositional) parameters are discussed that can be used to modify the thermal conductivity, as well as fracture toughness of silicon nitride ceramics. As a result of the open 〈0001〉 channels in β-Si₃N₄, the c-axis conductivity can be exceptionally high. Thus, the formation of elongated c-axis grains, particularly when aligned can result in conductivity values approaching those of AlN ceramics. In addition, the controlled formation of elongated grains can also be used to significantly enhance the fracture toughness. At the same time, both properties are shown to be affected by the composition of the densification additives. Utilizing such understanding, one will be able to tailor the ceramics to achieve the properties desired for specific applications.
Multi-Cell Performance of Grant-Free and Non-Orthogonal Multiple Access

The compressive sensing-based random access may get impacted largely by other cell interference (OCI), which may shatter the sparsity of the received signal model unless the signature space assignment among interfering cells is carefully handled. In this paper, we investigate the performance of multi-sequence spreading-based random access (MSRA) scheme under multi-cell environment. In particular, a grant-free random access scenario is considered to indicate its particular attributes that fundamentally affect the cellular performance. We also give the performance of MSRA in comparison with sparse code multiple access (SCMA). We show that if a proper signature assignment is undertaken, the OCI in MSRA and other CS-based schemes can be modeled as a dispersed noise which does not critically undermine the underlying sparsity.
Yarn spun from carbon nanotube forests:Production,structure,properties and applications

The discovery of drawable carbon nanotube forests opened up the possibility of constructing a wide range of pure carbon nanotube macrostructures and sparked interests in developing applications from these structures,especially pure carbon nanotube yarns.This review examines the various facets of the drawable carbon nanotube forests,synthesis and drawability,and their resulti ng yarns,structure,production,properties and applications.The structure,formation and properties of carbon nanotube yarns are compared with those of conventional textile yarns in order to obtain a better understanding of the science,structural mechanics and processing technology involved in carbon nanotube yarns.
Plasma total thiol pool in children with asthma: Modulation during montelukast monotherapy

Background: Inflammation, which is a hallmark of asthma, is one of the main sources of oxidative stress in the human body. Thiols are powerful antioxidants that protect cells against the consequences of oxidative stress. We aimed to investigate whether asthma and montelukast monotherapy affect the total plasma thiol pool in children. Methods: A total of 60 children with asthma and 35 healthy controls participated in the study. Group I consisted of newly diagnosed asthmatics who did not have regular anti-asthmatic therapy previously. Group II consisted of patients who had been undertaking montelukast monotherapy regularly for at least 4 months. Plasma total antioxidant status (TAS) and plasma total thiol (PTT) were measured using spectrophotometric methods. Results: Bronchial asthma patients in both groups I and II had decreased median TAS levels compared with the control group (1.59 [interquartile range, 1.04–1.70] and 1.67 [1.50–1.75] vs. 2.98 [2.76–3.16] Trolox equiv./L, respectively;P <0.001). Group I had decreased PTT concentrations compared with the control group (0.18 [0.16–0.20] vs. 0.21 [0.19–0.22] mmol/L; P <0.001), and group II had similar PTT levels to the control group (0.20 [0.17–0.22] mmol/L; P >0.05). In addition, the median TAS and PTT levels for groups I and II were not statistically different (P >0.05). There was a positive correlation between TAS and PTT levels (rho = 0.38, P <0.05) in group I. Conclusion: In order to balance the oxidative stress, both TAS and PTT which are markers of the antioxidant system are reduced in children with asthma. Montelukast monotherapy can limit oxidative stress and thus restore PTT levels but not TAS levels in asthmatic children.
Hallucination: A Mixed-Initiative Approach for Efficient Document Reconstruction

We introduce a mixed-initiative approach for document reconstruction that can significantly reduce the amount of time and effort required to reassemble a document from shredded pieces or an artifact from broken fragments. We focus in particular on the hardest subproblem, which is the problem of identifying a matching neighbor for any given piece. Our approach, called hallucination, combines human and machine intelligence by leveraging people’s ability to draw what a neighboring piece may look like, and then using the drawing as a template based on which the computer computes likely matches. Experiments on a puzzle from the DARPA Shredder Challenge demonstrate that the hallucination approach significantly reduces the search space for identifying a match, outperforming humans and computers working in isolation.