Miracle-dz/UniFAR-FTUs huggingface dataset:
Epilepsy and Neurodevelopmental Outcomes in Children With Etiologically Diagnosed Central Nervous System Infections: A Retrospective Cohort Study

Background: Central nervous system (CNS) infection in childhood can lead to neurological sequelae, including epilepsy, and neurodevelopmental disorders, such as attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). This study investigated the association of etiologically diagnosed childhood brain infections with the subsequent risks of epilepsy and neurodevelopmental disorders. Objectives: We retrospectively analyzed the data of children aged <18 years who had definite brain infections with positive cerebrospinal fluid cultures from January 1, 2005, to December 31, 2017. These patients were followed to evaluate the risks of epilepsy and neurodevelopmental disease (ADHD and ASD) after brain infections (group 1) in comparison with the risks in those without brain infections (group 2). Results: A total of 145 patients with an average age of 41.2 months were included in group 1. Enterovirus accounted for the majority of infections, followed by group B Streptococcus, S. pneumoniae, and herpes simplex virus. A total of 292 patients with an average age of 44.8 months were included in group 2. The 12-year risk of epilepsy in group 1 was 10.7 (95% confidence interval [CI], 2.30–49; p < 0.01). Compared with group 2 (reference), the risk of ASD in the age interval of 2–5 years in group 1 was 21.3 (95% CI, 1.33–341.4; p = 0.03). The incidence of ADHD in group 1 was not significantly higher than that in group 2. Conclusions: This study identified the common etiological causes of brain infections in Taiwanese children. The highest-risk neurodevelopmental sequelae associated with brain infections was epilepsy. Children who had a diagnosis of brain infection (specially Enterovirus) should be followed since they are at greater risk of developing epilepsy and ASD.
Designing a CS1 Programming Course for a Mixed-Ability Class

First year programming-courses attract a diverse crowd of students. In the same course, we often get Computer Science (CS) and non-CS students who bring mixed-abilities and different learning needs to the classroom. Teaching the same material to all of these students present an interesting challenge to the instructor. This paper introduces a successful design of a CS1 programming course at the University of British Columbia - Okanagan. This design incorporated several teaching strategies, such as the partially-flipped classroom model and pair-programming, which were used to teach programming fundamentals by building animations and games using Processing, an open-source language that uses simplified Java syntax in a visually engaging environment. Initial results after applying the new design show improved class average grade, increased pass-rate, and higher student engagement and satisfaction.
Dialing up the Active Learning in your Classroom

Active learning has been shown to improve outcomes [1]. In this workshop, we will share our experiences with active learning in four core computer science courses from CS1 [2] to third year and with class sizes from 120 to 470. We will discuss fully flipped courses, as well as others that were "semi-flipped", and why. We will address practical issues such as doing active learning in ill-suited lecture halls, getting student buy-in, deciding what course activities to grade, and using TAs to assist in the classroom. We will provide specific examples of our own active-learning activities, including some that have been very effective, and others that have not. We will also address the challenge of designing the out-of-class activities that prepare students and create time for active learning in class. Participants will have a chance to participate in some activities from our own classrooms, to share some of their own, and to identify and discuss principles on which we can base decisions such as what course content is best suited to be learned in class vs outside of class, and what topics to prioritize for active learning. This workshop is suitable for those who want to simply dial up the amount of active learning in their classroom, as well as those interested in investing in a more significant course redesign to a semi or fully flipped format.
The FitOptiVis ECSEL project: highly efficient distributed embedded image/video processing in cyber-physical systems

Cyber-Physical Systems (CPS) are systems that are in feedback with their environment, possibly with humans in the loop. They are often distributed with sensors and actuators, smart, adaptive and predictive and react in real-time. Image- and video-processing pipelines are a prime source for environmental information improving the possibilities of active, relevant feedback. In such a context, FitOptiVis aims to provide end-to-end multi-objective optimization for imaging and video pipelines of CPS, with emphasis on energy and performance, leveraging on a reference architecture, supported by low-power, high-performance, smart devices, and by methods and tools for combined design-time and run-time multi-objective optimization within system and environment constraints.
Impression formation: the role of expressive behavior.

This research examined the effects of personality/social skills and individual differences in expressive style on impression formation. Particular attention was given to the role of nonverbal behaviors in the formation of initial impressions. Sixty-two subjects were measured on self-report personality and communication skill scales, on posed emotional sending ability, and on physical attractiveness. Subjects were then videotaped while giving a spontaneous "explanation. " Trained coders measured five separate nonverbal cue factors displayed by the subjects in the videotapes. Groups of untrained judges viewed the tapes and rated their impressions of the subjects on scales of likability, speaking effectiveness, and expressivity-confidence. Male subjects who were nonverbally skilled and extraverted tended to display more outwardly focused and fluid expressive behaviors, and made more favorable impressions on judges, than did males who scored low on the measures of nonverbal skills and extraversion. Females who were nonverbally skilled displayed more facial expressiveness, which led to more favorable initial impressions. Sex differences may reflect basic differences in the acquisition and use of expressive nonverbal cues by males and females.
An adaptive concurrent priority queue for NUMA architectures

Designing scalable concurrent priority queues for contemporary NUMA servers is challenging. Several NUMA-unaware implementations can scale up to a high number of threads exploiting the potential parallelism of the insert operations. In contrast, in deleteMin-dominated workloads, threads compete for accessing the same memory locations, i.e. the first item in the priority queue. In such cases, NUMA-aware implementations are typically used, since they reduce the coherence traffic between the nodes of a NUMA system. In this work, we propose an adaptive priority queue, called SmartPQ, that tunes itself by automatically switching between NUMA-unaware and NUMA-aware algorithmic modes to provide the highest available performance under all workloads. SmartPQ is built on top of NUMA Node Delegation (Nuddle), a low overhead technique to construct NUMA-aware data structures using any arbitrary NUMA-unaware implementation as its backbone. Moreover, SmartPQ employs machine learning to decide when to switch between its two algorithmic modes. As our evaluation reveals, it achieves the highest available performance with 88% success rate and dynamically adapts between a NUMA-aware and a NUMA-unaware mode, without overheads, while performing up to 1.83 times better performance than Spraylist, the state-of-the-art NUMA-unaware priority queue.
A Novel Method for Single Infrared Dim Small Target Detection Based on ROI extraction and Matrix Recovery

Low-rank and sparse matrix recovery method based on Robust Principal Component Analysis (RPCA) model are widely used in infrared small target detection. In order to solve the problem of time consuming and difficulty in parameter selection when using this method, a novel method for infrared dim small target detection under complex background based on Region of Interest (ROI) extraction and matrix recovery is presented. Calculate the Variance Weighted Information Entropy (VWIE) of every sub-block and extract the ROI firstly; then use Adaptive Parameter Inexact Augmented Lagrange Multiplier (APIALM) algorithm to recover target image from extracted ROI; finally segmenting and calibrating the target using an adaptive threshold method. Experiments results demonstrate that the proposed method can significantly decline the running time and retain most properties of traditional detection method based on low-rank and sparse matrix recovery.
Individual Differences in the Neural Basis of Response Inhibition After Sleep Deprivation Are Mediated by Chronotype

Sleep deprivation (SD) has been reported to severely affect executive function, and interindividual differences in these effects may contribute to the SD-associated cognition impairment. However, it is unclear how individual differences in chronotypes (morning-type, MT; evening-type, ET) influence neurobehavioral functions after SD. To address this question, we used functional magnetic resonance imaging (fMRI) to evaluate whether 24 h of SD differentially affect response inhibition, a core component of executive function, in MT and ET individuals. Accordingly, MT and ET participants were instructed to follow their preferred 7–9-h sleep schedule for 2 weeks at home both prior to and throughout the course of the study, and then performed a go/no-go task during fMRI scanning at 08:00 a.m. both at rested wakefulness (RW) and following SD. We also examined whether the neurobehavioral inhibition differences in the chronotypes in each session can be predicted by subjective ratings (sleepiness, mood, and task) or objective attention. Behaviorally, SD led to an increased response time of go trials (hit RT), more attentional lapses, higher subjective sleepiness, and worse mood indices, but it did not impair the accuracy of go trials (hit rate) and no-go trials (stop rate). Regardless of the presence of SD, ET individuals exhibited a lower stop rate, higher subjective ratings of sleepiness, exhausted mood, and task difficulty in comparison with MT individuals. On the neural level, SD resulted in decreased inhibition-related activation of the right lateral inferior frontal gyrus (rIFG) in MT individuals and increased rIFG activation in ET individuals. Moreover, the rIFG activation in ET individuals after SD was positively correlated to the subjective ratings of sleepiness and effort put into the task, which was considered as a compensatory response to the adverse effects of SD. These findings suggest that individual differences in inhibition-related cerebral activation after SD are influenced by chronotypes. In addition, ET individuals may be vulnerable to response inhibition. Thus, it is essential to take into consideration the chronotype in SD research and sleep medicine.
Listening in a Noisy Environment: Integration of active noise control in audio products

ANC offers an effective, low-cost, lightweight, and compact solution to noise problems in audio and health-care products. As these products are used in noisy environments, audio-integrated ANC systems are essential for enhancing the audio quality and canceling annoying noise. In this article, audio-integrated ANC algorithms were briefly explained and several potential audio-integrated ANC products were discussed. Realtime experiments were conducted to verify the performance of noise reduction. We hope this article will motivate the development of more and more practical ANC applications in audio products in the future.
Reduced Neurosteroid Exposure Following Preterm Birth and Its’ Contribution to Neurological Impairment: A Novel Avenue for Preventative Therapies

Children born preterm are at an increased risk of developing cognitive problems and neuro-behavioral disorders such as attention deficit hyperactivity disorder (ADHD) and anxiety. Whilst neonates born at all gestational ages, even at term, can experience poor cognitive outcomes due to birth-complications such as birth asphyxia, it is becoming widely known that children born preterm in particular are at significant risk for learning difficulties with an increased utilization of special education resources, when compared to their healthy term-born peers. Additionally, those born preterm have evidence of altered cerebral myelination with reductions in white matter volumes of the frontal cortex, hippocampus and cerebellum evident on magnetic resonance imaging (MRI). This disruption to myelination may underlie some of the pathophysiology of preterm-associated brain injury. Compared to a fetus of the same post-conceptional age, the preterm newborn loses access to in utero factors that support and promote healthy brain development. Furthermore, the preterm ex utero environment is hostile to the developing brain with a myriad of environmental, biochemical and excitotoxic stressors. Allopregnanolone is a key neuroprotective fetal neurosteroid which has promyelinating effects in the developing brain. Preterm birth leads to an abrupt loss of the protective effects of allopregnanolone, with a dramatic drop in allopregnanolone concentrations in the preterm neonatal brain compared to the fetal brain. This occurs in conjunction with reduced myelination of the hippocampus, subcortical white matter and cerebellum; thus, damage to neurons, astrocytes and especially oligodendrocytes of the developing nervous system can occur in the vulnerable developmental window prior to term as a consequence reduced allopregnanolone. In an effort to prevent preterm-associated brain injury a number of therapies have been considered, but to date, other than antenatal magnesium sulfate and corticosteroid therapy, none have become part of standard clinical care for vulnerable infants. Therefore, there remains an urgent need for improved therapeutic options to prevent brain injury in preterm neonates. The actions of the placentally derived neurosteroid allopregnanolone on GABAA receptor signaling has a major role in late gestation neurodevelopment. The early loss of this intrauterine neurotrophic support following preterm birth may be pivotal to development of neurodevelopmental morbidity. Thus, restoring the in utero neurosteroid environment for preterm neonates may represent a new and clinically feasible treatment option for promoting better trajectories of myelination and brain development, and therefore reducing neurodevelopmental disorders in children born preterm.
The parameter optimization based on LVPSO algorithm for detecting multi-step attacks

How to detect intrusion attacks is a big challenge for network administrators since the attacks involve multi-step nowadays. The hidden markov model (HMM) is widely used in the field of multi-step attacks detection. However, the existing traditional Baum-Welch algorithm of HMM has two shortcomings: one is the number of attack states need to be determined in advance, the other is the algorithm may make the parameters converge to a local (not overall) optimal solution. In this paper, we propose a novel LVPSO-HMM algorithm based on variable length particle swarm optimization, which solves the shortcomings mentioned above. Concretely, it can optimize the number of attack states when the attacks state is unknown and it can make the model parameters converge to a global optimal solution. Then, we present a multi-step attack detection model architecture whose main idea is, when the number of attack states is unknown in the actual network environment LVPSO-HMM algorithm is used to solve the problem of relying on prior knowledge in current detection. Experiments on the well-known Darpa2000 dataset verify the efficiency of the method.
Molecular Mechanism Involved in the Pathogenesis of Early-Onset Epileptic Encephalopathy

Recent studies have shown that neurologic inflammation may both precipitate and sustain seizures, suggesting that inflammation may be involved not only in epileptogenesis but also in determining the drug-resistant profile. Extensive literature data during these last years have identified a number of inflammatory markers involved in these processes of “neuroimmunoinflammation” in epilepsy, with key roles for pro-inflammatory cytokines such as: IL-6, IL-17 and IL-17 Receptor (IL-17R) axis, Tumor-Necrosis-Factor Alpha (TNF-α) and Transforming-Growth-Factor Beta (TGF-β), all responsible for the induction of processes of blood-brain barrier (BBB) disruption and inflammation of the Central Nervous System (CNS) itself. Nevertheless, many of these inflammatory biomarkers have also been implicated in the pathophysiologic process of other neurological diseases. Future studies will be needed to identify the disease-specific biomarkers in order to distinguish epilepsies from other neurological diseases, as well as recognize different epileptic semiology. In this context, biological markers of BBB disruption, as well as those reflecting its integrity, can be useful tools to determine the pathological process of a variety of neurological diseases. However; how these molecules may help in the diagnosis and prognostication of epileptic disorders remains yet to be determined. Herein, authors present an extensive literature review on the involvement of both, systemic and neuronal immune systems, in the early onset of epileptic encephalopathy.
The Case for I/O-Device-as-a-Service

Many computer systems, especially mobile and IoT systems, use a large number of I/O devices. A contemporary OS acts as a security guard for these devices, which trust the OS to correctly implement the "perimeter defense. " Moreover, the OS also trusts these devices and their drivers to be well-behaved and bug-free. This interwoven trust model complicates the security of the system as a single vulnerable component can undermine all security guarantees. Not surprising, this architecture has failed to achieve strong security as evident by attacks that have targeted I/O devices or their drivers. In this paper, we call for a radically new approach, called I/O-Device-as-a-Service (IDaaS), where each I/O device acts a separate service and is responsible for its own security. Inspired by Service-Oriented Architecture (SOA), IDaaS requires every device to be equipped with its own software stack and provide an externalizable API that can be safely exposed to untrusted software. We discuss the design decisions in IDaaS, highlight its security benefits and research challenges, and present a case study.
Understanding the Nano-bio Interfaces: Lipid-Coatings for Inorganic Nanoparticles as Promising Strategy for Biomedical Applications

Inorganic nanoparticles (NPs) exhibit relevant physical properties for application in biomedicine and specifically for both the diagnosis and therapy (i.e. theranostic) of severe pathologies, such as cancer. The inorganic NP core is often not stable in aqueous suspension and can induce cytotoxic effects. For this reason, over the years, several coating strategies were suggested to improve the NP stability in aqueous solutions as well as the NP biocompatibility. Among the various components which can be used for NP coatings, lipids, and in particular phospholipids emerged as versatile molecular building blocks for the production of NP coatings suitable for biomedical application. The recent synthetic efforts in NP lipid coatings allows today to introduce on the NP surface a large variety of lipid molecules eventually in mixture with amphiphilic or hydrophobic drugs or active molecules for cell targeting. In this review, the most relevant examples of NP lipid-coatings are presented and grouped in two main categories: supported lipid bilayers (SLB) and hybrid lipid bilayers (HLB). The discussed scientific cases take into account the most commonly used inorganic NP for biomedical applications in cancer therapy and diagnosis.
Workload Characterization of a Software-as-a-Service Web Application Implemented with a Microservices Architecture

We study the workload of an Online Invoicing application with clients in the Andean region in South America. The application is offered to clients with a Software-as-a-Service model, has a microservices architecture and runs on a containerized environment on a public cloud provider. The cloud application workload described in this paper can be used as part of a workload suite comprised of different application workloads, when evaluating microservices architectures. To the best of our knowledge, this is a novel workload in the web domain and it complements other workloads publicly available. Though we make no claim of the general applicability of this workload as a “microservices benchmark”, its inclusion in evaluations could aid researchers and practitioners enrich their evaluations with tests based on a real microservices-based web application. Finally, we provide some insights regarding best-practices in microservice design, as a result of the observed workload.
Molecular Events Occurring During Softening of Strawberry Fruit

Changes in fruit texture taking place during ripening, described as softening, are mainly due to alterations in structure and/or composition of the cell wall. Several non-covalent interactions between the three carbohydrate polymers of the cell wall, cellulose, pectins and hemicellulose, and many structural proteins and ions, enable a complex structure. During softening, the disassembly of the cell wall structure takes place, mediated by a complete set of cell wall degrading enzymes or proteins. Softening is a coordinated event that requires the orchestrated participation of a wide variety of proteins. Plant hormones and a set of transcription factors are the organizers of this multi-protein effort. Strawberry is a non climacteric fruit that softens intensively during the last stages of development. The Chilean strawberry fruit (Fragaria chiloensis), the maternal relative of the commercial strawberry (F. × ananassa), softens even faster than commercial strawberry. Softening of the Chilean strawberry fruit has been studied at different levels: changes in cell wall polymers, activity of cell wall degrading enzymes and transcriptional changes of their genes, providing a general view of the complex process. The search for the ‘orchestra director’ that could coordinate softening events in strawberry fruit has been focussed on hormones like ABA and auxins, and more precisely the relation ABA/AUX. These hormones regulate the expression of many cell wall degrading enzyme genes, and this massive transcriptional change that takes place involves the participation of key transcriptional factors (TF). This review provides an update of the present knowledge regarding the softening of strawberry fruit. Nevertheless, the entire softening process is still under active research especially for the great influence of texture on fruit quality and its high impact on fruit shelf life, and therefore it is expected that new and promising information will illuminate the field in the near future.