Miracle-dz/UniFAR-FTUs huggingface dataset:
Early warning signals predict emergence of COVID-19 waves

Early warning signals (EWSs) aim to predict changes in complex systems from phenomenological signals in time series data. These signals have recently been shown to precede the initial emergence of disease outbreaks, offering hope that policy makers can make predictive rather than reactive management decisions. Here, using daily COVID-19 case data in combination with a novel, sequential analysis, we show that composite EWSs consisting of variance, autocorrelation, and return rate not only pre-empt the initial emergence of COVID-19 in the UK by 14 to 29 days, but also the following wave six months later. We also predict there is a high likelihood of a third wave as of the data available on 9th June 2021. Our work suggests that in highly monitored disease time series such as COVID-19, EWSs offer the opportunity for policy makers to improve the accuracy of time critical decisions based solely upon surveillance data.
Mental Health Conditions in Lesbian, Gay, Bisexual, Transgender, Queer and Asexual Youth in Brazil: a call for action

Lesbian, Gay, Bisexual, Transgender, Queer and Asexual (LGBTQA+) youth have a greater odds of experiencing stressful life events like discrimination and violence when compared to their cisgender heterosexual peers, which can lead to mental health problems. We aimed to estimate the prevalence of mental disorders among LGBTQA+ youths from the 3rd wave of the Brazilian High-Risk Cohort for Psychiatric Disorders (n= 1,475). Mental disorders were assessed using the Brazilian version of the Development and Well-Being Behavior Assessment. Sexual orientation, gender identity and biological sex were assessed using specific questions of a self-report confidential questionnaire. Data were analyzed using sampling weights to account for attrition and our oversampling design. The mean age was 18.14 years (SD=2.00) and 15.18% of the sample described themselves as LGBTQA+ (n=221). The LGBTQA+ group presented higher rates of anxiety disorders (30.14% vs. 13.37%; OR= 3.66; 95%CI: 2.82 - 4.75; p<0.001), depressive disorders (27.75% vs. 15.34%; OR= 2.51; 95%CI: 1.92 - 3.27, p<0.001) and post-traumatic stress disorder (4.98% vs. 2.25%, OR= 4.21, 95%CI: 2.54 - 6.96, p<0.001), if compared with the cisgender heterosexual group. No difference was found for conduct disorders (2.97% vs. 5.21% OR= 0.81; 95%CI: 0.39 - 1.69; p=0.577) or attention deficit hyperactivity disorder (5.92% vs. 3.28%, OR= 1.29; 95%CI: 0.74 - 2.25; p=0.361). Our results elucidate the mental health disparities between LGBTQA+ people and cisgender heterosexuals in Brazil. It highlights the need to promote the inclusion of this population in policy formulation and to support actions to mitigate and prevent the suffering and mental health problems related to sexual orientation and gender identity.
Influence of Edge- and Basal-Plane Sites on the Vanadium Redox Kinetics for Flow Batteries

The reaction kinetics of VII/VIII and VIVO2+/VVO2+ redox on carbon electrodes in sulfuric acid limit the development of vanadium redox flow batteries (VRFB) with high power and efficiency characteristics. Cyclic voltammetry and symmetric flow cell measurements on selectively masked graphite foil and highly oriented pyrolytic graphite electrodes revealed that edge carbon sites provide faster kinetics for VII/VIII and VIVO2+/VVO2+ redox than basal carbon, especially at low vanadium concentrations. The understanding was used to explain the marked enhanced kinetics of carbon paper electrodes with heat-treatments in air relative to that without, which was supported by X-ray photoelectron spectroscopy measurements that showed much higher amounts of surface functional groups on the heat-treated carbon upon exposure to the VV species in the electrolyte. Of particular significance to note is that markedly enhanced kinetics for the VII/VIII redox for the heat-treated carbon were found at both low and high vanadium .
Long-lasting long-term potentiation (L-LTP) is a cellular mechanism of learning

Authors: 3 1. Nadiatou T. Miningou Zobon 4 Department of Chemistry and Biochemistry, George Mason University, Fairfax, VA 5 22030, USA 6 2. Joanna Jędrzejewska-Szmek 7 Laboratory of Neuroinformatic, Nencki Institute of Experimental Biology of Polish 8 Academy of Sciences, Warsaw, Poland 9 3. Kim T. Blackwell 10 Interdisciplinary Program in Neuroscience, Bioengineering Department, and Krasnow 11 Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA 12 Corresponding Author: Kim T. Blackwell, Krasnow Institute for Advance Study and 13 Department of Bioengineering, MS 2A1, George Mason University, 4400 University Drive, 14 Fairfax, VA, 22030, USA 15 Conflict of Interest: The authors declare no competing financial interests. 16 Acknowledgments: This work was supported through the joint NIH-NSF CRCNS program 17 through NSF grant 1515686 and NIMH grant R01MH 117964 18 Competing interests: The authors declare no competing interests 19
Solid-State Phase Transformation as a Route for the Simultaneous Synthesis and Welding of Single-Crystalline Mg2Si Nanowires

A simple, but elegant, strategy for the simultaneous synthesis and welding of single-crystalline Mg2Si nanowires is presented. For the synthesis of Mg2Si nanowires, the solid-state phase transformation of presynthesized silicon nanowires was employed. For assembling the Mg2Si nanowires via the formation of Mg2Si bridges, the phase transformation of silica nanoparticle-decorated silicon nanowires was employed. To circumvent the formation of multiple Mg2Si nuclei and hence the phase transformation of single-crystalline Mg2Si nanowires into polycrystalline Mg2Si nanowires, solid-state reaction of silicon nanowire tips with magnesium foils at elevated temperatures of 350–400 °C was employed. In this procedure, the supersaturation of the sharp tips of the silicon nanowires with magnesium led to the formation of only one Mg2Si nucleus per nanowire. Growth of these lone nuclei led to the formation of single-crystalline Mg2Si nanowires. Extension of this procedure for the phase transformation of silica nanopartic.
Challenge 1 : Unsafe and Exclusive Urban Design

Technological advancement has brought many the convenience that the society used to lack, but unnoticed by many, a population neglected through the age of technology has been the visually impaired population. The visually impaired population has grown through ages with as much desire as everyone else to adventure but lack the confidence and support to do so. Time has transported society to a new phase condensed in big data, but to the visually impaired population, this quick-pace living lifestyle, along with the unpredictable natural disaster and COVID-19 pandemic, has dropped them deeper into a feeling of disconnection from the society. Our application uses the global positioning system to support the visually impaired in independent navigation, alerts them in face of natural disasters, and reminds them to sanitize their devices during the COVID-19 pandemic.
Supporting STEM Faculty of Large Enrollment Undergraduate Courses: A Mixed Methods Study of Impact

A plethora of literature exists identifying the importance of engaging students in learning within Science, Technology, Engineering, and Math (STEM) undergraduate courses, making professional development (PD) for faculty teaching these courses vital. Yet few studies of PD programs focus on STEM faculty, incorporate direct measures of faculty practice, and seek to understand the student experience in courses taught by these faculty. In this study, I examine the impact of a program for faculty teaching large enrollment STEM courses on their perceptions, instructional practices, and student perceptions of learning. The program included a week-long course design institute (35 hrs) and a year-long STEM Faculty Learning Community (STEM-FLC) that met monthly (14 hrs). Data included faculty surveys, course syllabi, observations of teaching, and Student Evaluations of Teaching (SETs). Results suggest the program helped instructors create more learning-focused courses and implement student-centered instructional practices to differing degrees. Despite the STEM-FLC, faculty still perceived barriers to implementing their course design. Students’ perceptions of course instruction and self-reported learning in these courses highlighted the importance of in-class activities. Finally, when the course design and instructional practice were aligned, students had more positive perceptions and reported higher learning gains compared to students in courses with misalignments in design and practice. Based on the findings of the study and connection with PD literature, I provide a set of essential PD features that may enable STEM faculty to make meaningful and lasting changes to practice.
The Link Between Malnutrition and Depression: A Review

Malnutrition is a global public health problem having negative effects on development. Despite this fact, the progress to meet the 2025 global nutrition targets is not satisfactory. The burden of deaths and disability caused by neurological disorders is increasingly being recognized as a global public health challenge. Therefore, this review aimed to identify the relationship between malnutrition and depression. There is a vice versa relationship between depression and malnutrition. Hence, addressing nutritional concerns may help alleviate symptoms of depression, and the prevention and control of depression can improve nutritional status.
Persistence of information flow: A multiscale characterization of human brain

Abstract Information exchange in the human brain is crucial for vital tasks and to drive diseases. Neuroimaging techniques allow for the indirect measurement of information flows among brain areas and, consequently, for reconstructing connectomes analyzed through the lens of network science. However, standard analyses usually focus on a small set of network indicators and their joint probability distribution. Here, we propose an information-theoretic approach for the analysis of synthetic brain networks (based on generative models) and empirical brain networks, and to assess connectome’s information capacity at different stages of dementia. Remarkably, our framework accounts for the whole network state, overcoming limitations due to limited sets of descriptors, and is used to probe human connectomes at different scales. We find that the spectral entropy of empirical data lies between two generative models, indicating an interpolation between modular and geometry-driven structural features. In fact, we show that the mesoscale is suitable for characterizing the differences between brain networks and their generative models. Finally, from the analysis of connectomes obtained from healthy and unhealthy subjects, we demonstrate that significant differences between healthy individuals and the ones affected by Alzheimer’s disease arise at the microscale (max. posterior probability smaller than 1%) and at the mesoscale (max. posterior probability smaller than 10%).
Real-Time Multi-View 3D Human Pose Estimation using Semantic Feedback to Smart Edge Sensors

We present a novel method for estimation of 3D human poses from a multi-camera setup, employing distributed smart edge sensors coupled with a backend through a semantic feedback loop. 2D joint detection for each camera view is performed locally on a dedicated embedded inference processor. Only the semantic skeleton representation is transmitted over the network and raw images remain on the sensor board. 3D poses are recovered from 2D joints on a central backend, based on triangulation and a body model which incorporates prior knowledge of the human skeleton. A feedback channel from backend to individual sensors is implemented on a semantic level. The allocentric 3D pose is backprojected into the sensor views where it is fused with 2D joint detections. The local semantic model on each sensor can thus be improved by incorporating global context information. The whole pipeline is capable of real-time operation. We evaluate our method on three public datasets, where we achieve state-of-the-art results and show the benefits of our feedback architecture, as well as in our own setup for multi-person experiments. Using the feedback signal improves the 2D joint detections and in turn the estimated 3D poses.
Classical biological control against insect pests in Europe, North Africa, and the Middle East: What influences its success?

Many factors can affect the success and failure of classical biological control. However, these factors have mainly been studied independently of each other, which leaves their relative importance within the complexity of classical biological control (CBC) programmes unknown. Therefore, we set out to take a more holistic view on the factors that may impact the outcome of CBC of insect pests by insect predators and parasitoids. To this end, we filtered the BIOCAT catalogue to extract entries for the Greater Western Palearctic ecozone and added 15 new explanatory variables. These mainly concerned traits of released biological control agents, target pests, and host plants of the target, but also included the number of introductions for specific agent-target combinations as a management aspect. We then analysed the data regarding three levels of success: agent establishment, impact on the target population, and complete control of the target. Between 1890 and 2010 a total of 780 introductions of insects for biological control were undertaken in the analysed area, constituting 416 agent-target combinations. Overall success of agent establishment was 32%, successful impact of single agents on their target was 18%, and success of complete control was 11%. The number of factors significantly influencing the outcome of CBC decreased with increasing level of success. Remarkably few agent-related factors influenced the success: insect predators as agents decreased the probability of establishment and using oligophagous parasitoids significantly decreased the chances of complete control. Other significant factors were related to traits of target pests or their host plants. For example, sap feeders and target pests attacking reproductive plant parts were more likely to be successfully controlled. The rate of success increased with the number of introductions of CBC agents, in particular against univoltine target pests. These findings suggest that a focus on agent-related traits to increase the chances of successful CBC is not fully justified and should be complemented with the consideration of lower trophic levels and other aspects of CBC, such as abiotic factors and management. NeoBiota 65: 169–191 (2021) doi: 10.3897/neobiota.65. 66276 https://neobiota.pensoft. net Copyright M. Lukas Seehausen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. RESEARCH ARTICLE Advancing research on alien species and biological invasions A peer-reviewed open-access journal
GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels

Tool use requires reasoning about the fit between an object's affordances and the demands of a task. Visual affordance learning can benefit from goal-directed interaction experience, but current techniques rely on human labels or expert demonstrations to generate this data. In this paper, we describe a method that grounds affordances in physical interactions instead, thus removing the need for human labels or expert policies. We use an efficient sampling-based method to generate successful trajectories that provide contact data, which are then used to reveal affordance representations. Our framework, GIFT, operates in two phases: first, we discover visual affordances from goal-directed interaction with a set of procedurally generated tools; second, we train a model to predict new instances of the discovered affordances on novel tools in a self-supervised fashion. In our experiments, we show that GIFT can leverage a sparse keypoint representation to predict grasp and interaction points to accommodate multiple tasks, such as hooking, reaching, and hammering. GIFT outperforms baselines on all tasks and matches a human oracle on two of three tasks using novel tools.
Combined action observation- and motor imagery-based brain computer interface (BCI) for stroke rehabilitation: a case report

Introduction: Upper extremity impairment is a problem usually found in poststroke patients, and it is seldom completely improved even following conventional physical therapy. Motor imagery (MI) and action observation (AO) therapy are mental practices that may regain motor function in poststroke patients, especially when integrating them with brain-computer interface (BCI) technology. However, previous studies have always investigated the effects of an MI- or AO-based BCI for stroke rehabilitation separately. Therefore, in this study, we aimed to propose the effectiveness of a combined AO and MI (AOMI)-based BCI with functional electrical stimulation (FES) feedback to improve upper limb functions and alter brain activity patterns in chronic stroke patients.Case presentation: A 53-year-old male who was 12 years post stroke was left hemiparesis and unable to produce any wrist and finger extension.Intervention: The participant was given an AOMI-based BCI with FES feedback 3 sessions per week for 4 consecutive weeks, and he did not receive any conventional physical therapy during the intervention. The Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and active range of motion (AROM) of wrist extension were used as clinical assessments, and the laterality coefficient (LC) value was applied to explore the altered brain activity patterns affected by the intervention.Outcomes: The FMA-UE score improved from 34 to 46 points, and the AROM of wrist extension was increased from 0 degrees to 20 degrees. LC values in the alpha band tended to be positive whereas LC values in the beta band seemed to be slightly negative after the intervention.Conclusion: An AOMI-based BCI with FES feedback training may be a promising strategy that could improve motor function in poststroke patients; however, its efficacy should be studied in a larger population and compared to that of other therapeutic methods.Trial registration: Thai Clinical Trial Registry: TCTR20200821002. Registered 17 August 2020, http://www.thaiclinicaltrials. org
HGKT: Introducing Hierarchical Exercise Graph for Knowledge Tracing

Knowledge tracing (KT) which aims at predicting learner’s knowledge mastery plays an important role in the computer-aided educational system. In recent years, many deep learning models have been applied to tackle the KT task, which have shown promising results. However, limitations still exist. Most existing methods sim-plify the exercising records as knowledge sequences, which fail to explore rich information existed in exercises. Besides, the existing diagnosis results of knowledge tracing are not convincing enough since they neglect prior relations between exercises. To solve the above problems, we propose a hierarchical graph knowledge tracing model called HGKT to explore the latent hierarchical relations between exercises. Specifically, we introduce the concept of problem schema to construct a hierarchical exercise graph that could model the exercise learning dependencies. Moreover, we employ two attention mechanisms to highlight important historical states of learners. In the testing stage, we present a K&S diagnosis matrix that could trace the transition of mastery of knowledge and problem schema, which can be more easily applied to different applications. Extensive experiments show the effectiveness and interpretability of our proposed models.
Blockchain for the Trustworthy Decentralized Web Architecture

The Internet was created as a decentralized and autonomous system of interconnected computer networks used for data exchange across mutually trusted participants. The element technologies on the Internet, such as inter-domain and intra-domain routing and DNS, operated in a distributed manner. With the development of the Web, the Web has become indispensable in daily life. The existing web applications allow us to form online communities, generate private information, access big data, shop online, pay bills, post photos or videos, and even order groceries. This is what has led to centralization of the Web. This centralization is now controlled by the giant social media platforms that provide it as a service, but the original Internet was not like this. These giant companies realized that the decentralized network’s huge value involves gathering, organizing, and monetizing information through centralized web applications. The centralized Web applications have heralded some major issues, which will likely worsen shortly. This study focuses on these problems and investigates blockchain’s potentials for decentralized web architecture capable of improving conventional web services' critical features, including autonomous, robust, and secure decentralized processing and traceable trustworthiness in tamper-proof transactions. Finally, we review the decentralized web architecture that circumvents the main Internet gatekeepers and controls our data back from the giant social media companies.
Effect of Weight Loss on Pro-inflammatory Cytokines Post Sleeve Gastrectomy among Obese Children and Adolescents

Introduction: Low-grade inflammation is a common occurrence in obesity, type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). In obesity, increased levels of interleukins and other inflammatory cytokines in the circulation may partly reflect a spillover from the adipose tissue. Methodology: A prospective study was carried out to assess the levels of pro-inflammatory factors (TNF-α, IL-1β, and IL-6), dietary intake, fasting blood glucose and lipid profile before and 6 months after sleeve gastrectomy (SG), among 21 morbidly obese children and adolescents aged ≤ 18 years. Results: Subjects achieved significant decrease in all anthropometric measurements and sleep apnea 6 months after SG. A significant increase in high density lipoprotein (HDL) and a significant decrease in fasting glucose (FG) levels and IL-1β levels was observed 6 months post-surgery (p ≤ 0.05). The reductions in body mass index (BMI), hip circumference and triglyceride (TG) levels significantly correlated with IL-6 concentrations and the reduction in hip circumference and mid arm circumference correlated significantly with IL-1β levels post-surgery. Linear regression showed the role of BMI and energy intake to predict the decreased level of IL-1β after surgery. Conclusion: Sleeve gastrectomy represents a safe method for downregulating the inflammatory state that could lead to CVD and insulin resistance (IR) in obese children and adolescents. The significant decrease in IL-1β, increase in HDL and resolution of sleep apnea after SG can reduce CVD risk factors among morbidly obese children and adolescent, whereas the significant decrease in FG can reduce IR risk factors.