Miracle-dz/UniFAR-FTUs huggingface dataset:
How Continuous Are the “Relict” Landscapes of Southeastern Tibet?

Pervasive low-relief, high-elevation surfaces separated by incised canyons are common across the Southeastern margin of the Tibetan Plateau and have been used to define the nature of crustal deformation that drove plateau growth. A common assumption is that these surfaces were once part of a continuous low-relief paleotopography that has undergone surface uplift and dissection. Recent research, however, has questioned this assumption and the derived geodynamic models, which suggests that these surfaces formed in situ through drainage network reorganization and the piracy of upstream drainage area. Here, we test the continuity of the low-relief surfaces across SE Tibet using a new inversion scheme that also illuminates the nature of conflicting hypotheses. Our analysis is based on combining the local information contained in maps of normalized channel steepness with the more distributed and integrated information contained in maps of normalized landscape response time. This allows us to model the formation of a hypothetical landscape prior to rock uplift and dissection. We find that large variations in channel steepness are required along the trunk channels within the inferred paleotopography. This is inconsistent with a low-relief surface prior to surface uplift and indicates that a surface interpolated between remnants cannot be used to robustly measure geodynamic processes in space and time. Furthermore, our inverse framework highlights many different solutions to this ill-posed problem and thus provides an explanation as to why the topography alone cannot be used to provide a unique solution to the debate.
DeepFuseOSV: online signature verification using hybrid feature fusion and depthwise separable convolution neural network architecture

Online signature verification (OSV) is a widely utilised technique in the medical, e-commerce and m-commerce applications to lawfully bind the user. These high-speed systems demand faster writer verification with a limited amount of information along with restrictions on training and storage cost. This study makes two major contributions: (i) A competent feature fusion technique in which traditional statistical-based features are fused with deep representations from a convolutional auto-encoder; and (ii) a hybrid architecture combining depth-wise separable convolution neural network (DWSCNN) and long short term memory (LSTM) network delivering state-of-the-art performance for OSV is proposed. DWSCNN is utilised for extracting deep feature representations and LSTM is competent in learning long term dependencies of stroke points of a signature. This hybrid combination accomplishes better classification accuracy (lower error rates) even with one-shot learning, i.e. achieving higher classification accuracies with only one training signature sample per user. The authors have extensively evaluated their model using three widely used datasets MCYT-100, SVC and SUSIG. These exhaustive experimental studies confirm that the DeepFuseOSV framework results in the state-of-the-art outcome by achieving an equal error rate (EER) of 13.26, 2.58, 0.07% in Skilled 1, Skilled 10 and Random 10 categories of MCYT-100, respectively, 7.71% in Skilled 1 category of SVC, 1.70% in Random 1 category of SUSIG.
A Prototypical Semantic Annotator for A Tribuna Newspaper

The issue of recommending an appropriate piece of information has become essential for the news portals. In this context, a well founded ontological layer represents actually an indispensable artifact to suggest relevant news for the readers. However, news agencies still need to mine their data in order to discover valuable knowledge. In this paper, we present a prototypal automatic semantic annotator for the regional Brazilian newspaper called A Tri-buna. Founded on a set of inductive algorithms allowing to classify newspapers in Portuguese and extract named entities from them, our approach describes the standardized categorization and the semantic matching with DBpedia, the so-called nucleus of the Linked Open Data Cloud. We discuss the limitation of our prototype and draw some challenging perspectives to face them. Finally, our proposal paves the way to a new kind of recommendation-based systems.
Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation

Enhancing patients' engagement is of great benefit for neural rehabilitation. However, physiological and neurological differences among individuals can cause divergent responses to the same task, and the responses can further change considerably during training; both of these factors make engagement enhancement a challenge. This challenge can be overcome by training task optimization based on subjects' responses. To this end, an engagement enhancement method based on human-in-the-loop optimization is proposed in this paper. Firstly, an interactive speed-tracking riding game is designed as the training task in which four reference speed curves (RSCs) are designed to construct the reference trajectory in each generation. Each RSC is modeled using a piecewise function, which is determined by the starting velocity, transient time, and end velocity. Based on the parameterized model, the difficulty of the training task, which is a key factor affecting the engagement, can be optimized. Then, the objective function is designed with consideration to the tracking accuracy and the surface electromyogram (sEMG)-based muscle activation, and the physical and physiological responses of the subjects can consequently be evaluated simultaneously. Moreover, a covariance matrix adaption evolution strategy, which is relatively tolerant of both measurement noises and human adaptation, is used to generate the optimal parameters of the RSCs periodically. By optimization of the RSCs persistently, the objective function can be maximized, and the subjects' engagement can be enhanced. Finally, the performance of the proposed method is demonstrated by the validation and comparison experiments. The results show that both subjects' sEMG-based motor engagement and electroencephalography based neural engagement can be improved significantly and maintained at a high level.
Drug Screening and Drug Repositioning as Promising Therapeutic Approaches for Spinal Muscular Atrophy Treatment

Spinal muscular atrophy (SMA) is the most common genetic disease affecting infants and young adults. Due to mutation/deletion of the survival motor neuron (SMN) gene, SMA is characterized by the SMN protein lack, resulting in motor neuron impairment, skeletal muscle atrophy and premature death. Even if the genetic causes of SMA are well known, many aspects of its pathogenesis remain unclear and only three drugs have been recently approved by the Food and Drug Administration (Nusinersen—Spinraza; Onasemnogene abeparvovec or AVXS-101—Zolgensma; Risdiplam—Evrysdi): although assuring remarkable results, the therapies show some important limits including high costs, still unknown long-term effects, side effects and disregarding of SMN-independent targets. Therefore, the research of new therapeutic strategies is still a hot topic in the SMA field and many efforts are spent in drug discovery. In this review, we describe two promising strategies to select effective molecules: drug screening (DS) and drug repositioning (DR). By using compounds libraries of chemical/natural compounds and/or Food and Drug Administration-approved substances, DS aims at identifying new potentially effective compounds, whereas DR at testing drugs originally designed for the treatment of other pathologies. The drastic reduction in risks, costs and time expenditure assured by these strategies make them particularly interesting, especially for those diseases for which the canonical drug discovery process would be long and expensive. Interestingly, among the identified molecules by DS/DR in the context of SMA, besides the modulators of SMN2 transcription, we highlighted a convergence of some targeted molecular cascades contributing to SMA pathology, including cell death related-pathways, mitochondria and cytoskeleton dynamics, neurotransmitter and hormone modulation.
What Happens Before Book Reading Starts? an Analysis of Teacher–Child Behaviours With Print and Digital Books

A body of research documents teacher–child reading behaviors in educational settings. Few will disagree that the potential for word and narrative comprehension increases when children’s prior knowledge is activated and when children’s focus is fully on the reading session. Despite this, little is known about the potential for establishment of joint attention and activation of prior knowledge in an early childhood education and care setting and how early childhood educators prepare young children to participate in shared book reading sessions before formal reading starts. Based on video data of teachers (N = 12) and small groups of children (N = 72) reading picture books and picture book apps in kindergarten, we sought to shed light on what behaviors occur before reading starts. The analyses were conducted in two phases. The first phase was based on 48 videotaped readings and followed a descriptive quantitative approach to investigate early childhood teachers’ time use before the reading session, with readings of both print books and picture book apps. The second phase was based on two app readings in which the pre-reading phases stood out for their long duration. A qualitative analytical approach was applied to describe the teacher–child behavior, establishment of joint attention, and activation of prior knowledge during the two specific pre-reading events. Even though the sample is small, we find clear examples of pre-reading strategies specific to app readings. In this study, we discuss teachers’ strategies to promote joint attention and activation of prior knowledge in new ways and how teachers exploit the pre-reading phase, for instance taking advantage of the books paratext, while adapting to the medium. Nevertheless, there remains a knowledge gap concerning app readings with short or no pre-reading phases.
Mechanotransduction and Adrenergic Stimulation in Arrhythmogenic Cardiomyopathy: An Overview of in vitro and in vivo Models

Arrhythmogenic Cardiomyopathy (AC) is a rare inherited heart disease, manifesting with progressive myocardium degeneration and dysfunction, and life-threatening arrhythmic events that lead to sudden cardiac death. Despite genetic determinants, most of AC patients admitted to hospital are athletes or very physically active people, implying the existence of other disease-causing factors. It is recognized that AC phenotypes are enhanced and triggered by strenuous physical activity, while excessive mechanical stretch and load, and repetitive adrenergic stimulation are mechanisms influencing disease penetrance. Different approaches have been undertaken to recapitulate and study both mechanotransduction and adrenergic signaling in AC, including the use of in vitro cellular and tissue models, and the development of in vivo models (particularly rodents but more recently also zebrafish). However, it remains challenging to reproduce mechanical load stimuli and physical activity in laboratory experimental settings. Thus, more work to drive the innovation of advanced AC models is needed to recapitulate these subtle physiological influences. Here, we review the state-of-the-art in this field both in clinical and laboratory-based modeling scenarios. Specific attention will be focused on highlighting gaps in the knowledge and how they may be resolved by utilizing novel research methodology.
Effect of Low Intensity Transcranial Ultrasound (LITUS) on Post-traumatic Brain Edema in Rats: Evaluation by Isotropic 3-Dimensional T2 and Multi-TE T2 Weighted MRI

Background: Brain edema is one of the important factors affecting the prognosis of traumatic brain injury (TBI). Low-intensity transcranial ultrasound (LITUS) has significant anti-cerebral edema effect. T2-weighted image-based volume and T2 value measurements can sensitively reflect tissue edema. Purpose: To evaluate the effect and possible mechanisms of LITUS on brain edema by iso-voxel 3-dimensional T2WI (iso-3D T2WI) and multi-TE T2WI. Methods: Forty-five rats were randomly divided into sham control, TBI and TBI + LITUS groups (n = 15, respectively). Iso-voxel 3-dimensional T2WI and multi-TE T2WI sequences at 3.0T to obtain T2 value and edema volume of the injury cortex. T2 values were obtained on days 1, 7, 14, 21, 28, 35, and 42 after TBI and brain edema volume were obtained on days 7 and 14. Results: The T2 values of the damaged cortex in the TBI group showed a slow decreasing trend after a significant increase. For TBI+LITUS group, T2 values decreased with continuous LITUS treatment. At day 28, the T2 values were not significantly longer than the control group (adjusted P = 0.0535), but were significantly shorter than the TBI group at day 42 (adjusted P = 0.0003). The edema volume at day 7 and 14 in the LITUS group was significantly lower than the TBI group (P = 0.0004 and P < 0.0001, respectively). AQP-4 and β-APP protein staining showed a strong positive reaction near the CCI point, TBI+LITUS group showed a medium positive reaction, and the sham control group showed a weak positive reaction. Conclusion: The therapeutic effect of LITUS on post-traumatic brain edema was confirmed through T2 value and edema volume, and the mechanism may be related to inhibiting the expression of AQP-4 and promoting the removal of β-APP.
Dual Crosslinking of Alginate Outer Layer Increases Stability of Encapsulation System

The current standard treatment for Type 1 diabetes is the administration of exogenous insulin to manage blood glucose levels. Cellular therapies are in development to address this dependency and allow patients to produce their own insulin. Studies have shown that viable, functional allogenic islets can be encapsulated inside alginate-based materials as a potential treatment for Type 1 diabetes. The capability of these grafts is limited by several factors, among which is the stability and longevity of the encapsulating material in vivo. Previous studies have shown that multilayer Alginate-Poly-L-Ornithine-Alginate (A-PLO-A) microbeads are effective in maintaining cellular function in vivo. This study expands upon the existing encapsulation material by investigating whether covalent crosslinking of the outer alginate layer increases stability. The alginate comprising the outer layer was methacrylated, allowing it to be covalently crosslinked. Microbeads with a crosslinked outer layer exhibited a consistent outer layer thickness and increased stability when exposed to chelating agents in vitro. The outer layer was maintained in vivo even in the presence of a robust inflammatory response. The results demonstrate a technique for generating A-PLO-A with a covalently crosslinked outer layer.
Three-Dimensional Separation and Characterization of Fractures in X-Ray Computed Tomographic Images of Rocks

Open fractures can affect petrophysical properties of their host rock masses, as well as fluid transport and storage, so characterization of them is important to both industrial and research scientists. X-ray Computed Tomography (CT), a non-destructive technique for 3D imaging of various materials, shows such fractures well in rock samples. However, separation and characterization of fractures in CT data is complicated when a scanned sample contains narrow and intersecting fractures, because narrow fractures become blurred when thinner than the scanner resolution and their value approximates that of the matrix, and because intersecting features are difficult to individually characterize. In this paper, we present a new approach for an objective and efficient characterization of the fracture network inside CT scans of rock samples. We have developed algorithms, implemented as Python scripts, that measure fracture aperture-related parameters, and that separate connected fractures and fracture intersections within CT images of the sample. The CT images are composed of stacks of 2D images in the plane parallel to X-Y (equally spaced), where each pixel has a value related to the attenuation of the X-rays within the materials that make up the sample at that location and is generally displayed using a gray-scale colormap. As the gray values in the reconstructed images drop within fractures, our algorithm is able to identify such drops and record the lowest gray value in every drop as a Fracture Trace Point (FTP). For every FTP, parameters related to the local fracture width and the three-dimensional orientation of the FTPs surrounding it are measured. A second step involves the separation of individual fractures and their intersections points. This allows information about a number of FTP measurements on the same fracture (or intersections) to be combined to characterize that feature. We demonstrate that our methods better quantify fractures and their intersections through analysis of an experimentally-deformed granite sample, within which we characterize fracture size, orientation, and intensity. The methodologies can be also used to characterize sub-planar features in other types of datasets. Python implementations of our algorithms are freely available on GitHub repositories.
Cell Surface Biosynthesis and Remodeling Pathways in Mycobacteria Reveal New Drug Targets

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), remains the leading cause of death from an infectious bacterium and is responsible for 1.8 million deaths annually. The emergence of drug resistance, together with the need for a shorter more effective regimen, has prompted the drive to identify novel therapeutics with the bacterial cell surface emerging as a tractable area for drug development. Mtb assembles a unique, waxy, and complex cell envelope comprised of the mycolyl-arabinogalactan-peptidoglycan complex and an outer capsule like layer, which are collectively essential for growth and pathogenicity while serving as an inherent barrier against antibiotics. A detailed understanding of the biosynthetic pathways required to assemble the polymers that comprise the cell surface will enable the identification of novel drug targets as these structures provide a diversity of biochemical reactions that can be targeted. Herein, we provide an overview of recently described mycobacterial cell wall targeting compounds, novel drug combinations and their modes of action. We anticipate that this summary will enable prioritization of the best pathways to target and triage of the most promising molecules to progress for clinical assessment.
Isolation, Expression Profiling, and Regulation via Host Allelochemicals of 16 Glutathione S-Transferases in the Chinese White Pine Beetle, Dendroctonus armandi

The Chinese white pine beetle (Dendroctonus armandi) is undoubtedly one of the most important pests causing ecological damage in the Qinling Mountains. When bark beetles invade conifers, they must overcome host tree defenses, including primary resistance and induced resistance responses. Moreover, this induced resistance occurs following herbivory by bark beetles. Bark beetles have a corresponding defense mechanism for degrading toxic compounds, and glutathione S-transferases (GSTs) can catalyze the binding of endogenous substances that reduce glutathione (GSH) to various harmful electrophilic substrates, increasing their solubility and facilitating their excretion from cells. In this experiment, we successfully obtained sixteen full-length sequences of D. armandi, which belonged to four GST categories (delta, epsilon, sigma, and theta). The transcript levels of sixteen GSTs in D. armandi were compared at four developmental stages (larvae, pupae, teneral adults, and adults), three different tissues (antennae, gut, and reproductive organs), and under various levels of terpenoid stimuli during feeding on phloem tissue to evaluate the various relevant modes of action. This study aids in the understanding of the interaction between monoterpenes and beetles, and beetles’ detoxification through GSTs.
Effects of Motor Versus Cognitive Task Prioritization During Dual-Task Practice on Dual-Task Performance in Young Adults

Background: Previous studies have reported positive effects of concurrent motor and cognitive task practice compared to motor or cognitive task practice only on dual-task performance in young adults. Knowledge about the effect of motor vs. cognitive task prioritization during practice on dual-task performance remains unclear and has not been investigated in depth so far. Thus, we examined the effects of motor task compared to cognitive task prioritization during dual-task practice on motor-cognitive performance in healthy young adults. Methods: Healthy young adults were randomly assigned to dual-task (DT; i.e., concurrent motor and cognitive practice) or single-task (ST; i.e., motor or cognitive task practice only) practice groups. In DT practice, subjects were instructed to either prioritize the motor or the cognitive task. The motor task required subjects to keep a stabilometer in a horizontal position. The cognitive task involved serial three subtractions. Outcome variables were the root-mean-square error (RMSE) for the motor task and the total number of correct calculations for the cognitive task. All participants practiced for 2 consecutive days under their respective treatment condition and were tested under DT condition 24 h later (i.e., retention on day 3) without providing instructions on task prioritization. Results: Irrespective of prioritization (i.e., prioritize the motor task or the cognitive task), the DT practice groups similarly improved their DT motor and cognitive task performance. The ST groups also improved motor or cognitive performance depending on their respective training contents (i.e., motor practice improved RMSE and cognitive practice improved number of correct calculations but not vice versa). Conclusion: We conclude that DT compared to ST practice is well-suited to improve DT performance, irrespective of task-prioritization. DT but not ST practice resulted in an improved modulation of both domains (i.e., motor and cognitive) during DT performance. Our findings might be explained by freeing up central resources following DT practice that can be used to effectively perform the concurrent execution of motor and cognitive processing demands. However, this process is not further enhanced by the prioritized task domain.