Miracle-dz/UniFAR-FTUs huggingface dataset:
Robotic Exoskeleton Gait Training in Stroke: An Electromyography-Based Evaluation

The recovery of symmetric and efficient walking is one of the key goals of a rehabilitation program in patients with stroke. The use of overground exoskeletons alongside conventional gait training might help foster rhythmic muscle activation in the gait cycle toward a more efficient gait. About twenty-nine patients with subacute stroke have been recruited and underwent either conventional gait training or experimental training, including overground gait training using a wearable powered exoskeleton alongside conventional therapy. Before and after the rehabilitation treatment, we assessed: (i) gait functionality by means of clinical scales combined to obtain a Capacity Score, and (ii) gait neuromuscular lower limbs pattern using superficial EMG signals. Both groups improved their ability to walk in terms of functional gait, as detected by the Capacity Score. However, only the group treated with the robotic exoskeleton regained a controlled rhythmic neuromuscular pattern in the proximal lower limb muscles, as observed by the muscular activation analysis. Coherence analysis suggested that the control group (CG) improvement was mediated mainly by spinal cord control, while experimental group improvements were mediated by cortical-driven control. In subacute stroke patients, we hypothesize that exoskeleton multijoint powered fine control overground gait training, alongside conventional care, may lead to a more fine-tuned and efficient gait pattern.
Effects of Optimism on Work Satisfaction Among Nurses: A Mediation Model Through Work-Family Conflict

Background: Nurses are suffering from various stressors which adversely impact their work satisfaction and mental health. Research is scarce on optimism, one of the positive psychological resource which may reduce work-family conflict and improve work satisfaction. Objectives: This study aims to assess work satisfaction among Chinese nurses and to observe and illustrate the relationships among optimism, work-family conflict, and work satisfaction. Methods: This study was designed as a cross-sectional study with stratified sampling. From September 2019 to December 2020, a self-administered WeChat questionnaire was collected from 768 nurses online in China to evaluate the nurses' work satisfaction, optimism, and work-family conflict. Spearman correlation and hierarchical multiple regression analysis were applied to examine associated factors of work satisfaction. A structural equation model was employed to test the mediating effect of work-family conflict in the relationship between optimism and work satisfaction. Results: Optimism were observed to have a positive correlation with work satisfaction while the correlation between work-family conflict and work satisfaction was observed to be negative. Optimism and work-family conflict explained 4.8 and 9.2% of the incremental variances of work satisfaction, respectively. Work-family conflict served as a mediator in the relationship between optimism and work satisfaction. Conclusions: Nurses in China experienced high levels of work satisfaction. Optimism could increase the chance of higher work satisfaction while work-family conflict increased the risk of lower work satisfaction. Psychological interventions and improvement of working conditions are essential to relieve work-family conflicts and enhance work satisfaction.
Mapping Innovation Research in Organizations: A Bibliometric Analysis

This essay conducts a bibliometric study on innovation research in organizations within the three levels (i.e., individual, work team, and organizational) by using CiteSpace software to analyze 6,354 academic articles from the year 2000 to 2020 in four aspects: temporal distribution of published papers, scientific community (countries/regions/cited authors), intellectual structure (cited journals/cited references), and research hotspots. The research findings show that the total number and the growth rate of publications at the organizational level are far higher than the other two levels (individual and work team). The top three countries with the number of publications are United States, China, and United Kingdom. The top five highly cited authors are identified and listed from individual, work team, and organizational levels. Academy of Management Journal and Academy of Management Review are the top two highly cited journals at all three levels (i.e., individual, work team, and organizational levels). The most highly cited articles at the three levels are about topics of linking empowering leadership and employee creativity, team-level predictors of innovation at work, and organizational ambidexterity. The top three research hotspots are identified and listed from individual, work team, and organizational levels. These findings provide snapshots and comparisons of innovation research in management within the three levels (i.e., individual, work team, and organizational levels), which might be beneficial for researchers and scholars to understand and explore innovative behavior in organizations from a multilevel perspective.
Effects of Chronic Social Defeat Stress on Behavior and Dopamine Receptors in Adolescent Mice With 6-Hydroxydopamine Lesions of the Medial Prefrontal Cortex

Background: Social stress factors in schizophrenia have long-term effects, but will only induce symptoms in a portion of individuals, even if exposed to identical stress. Methods: In the current experiment, we examined mice with 6-hydroxydopamine (6-OHDA)-induced medial prefrontal cortical (mPFC) injury to select for members of a “stress-susceptible group,” and observed the changes in their behavior and the expression of D1 and D2 dopamine receptors in the amygdala and hippocampus. Results: We observed that after chronic social defeat stress, 72.6% of the 6-OHDA lesioned mice exhibited stress response to aggressors, compared to 52.3% of the blank control group. Both the 6-OHDA lesion + social defeat and social defeat groups exhibited anxiety and depression-like behavior. However, social cognitive impairment in the mice from the 6-OHDA lesion + social defeat group was more significant and the D1 expression levels in the amygdala were significantly decreased. Conclusion: These results suggest that the reason that adolescent mice with cortical injury were highly sensitive to defeat stress and had more prominent social cognitive impairment may be the decreased selectivity of D1 in the amygdala.
Nonsteroidal Anti-Inflammatory Drugs Reduce Second Cancer Risk in Patients With Breast Cancer: A Nationwide Population-Based Propensity Score-Matched Cohort Study in Taiwan

Nonsteroidal anti-inflammatory drugs (NSAIDs) reduce mortality in patients with cancer, especially breast cancer, but their influence on second cancer risk is uncertain. This study aimed to examine whether NSAID use is associated with second cancer risk in patients with breast cancer. This population-based propensity score-matched cohort study using Taiwan’s National Health Insurance Research Database enrolled patients with newly diagnosed breast cancer (n = 7356) with and without (n = 1839) NSAID therapy from 2000 to 2009. They were followed up until the diagnosis of second cancer, death, or end of 2011. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR). The NSAID cohort had a lower incidence rate of second cancer than the non-NSAID cohort (5.57 vs. 9.19 per 1,000 person-years), with an aHR of 0.63 (95% confidence interval (CI) 0.46–0.87). When compared with the non-NSAID cohort, the second cancer incidence was lower in patients taking non-cyclooxygenase 2 inhibitors (aHR 0.67, 95% CI 0.47–0.94) and in those receiving multiple NSAIDs during follow-up (aHR 0.55, 95% CI 0.37–0.84). A dose–response relationship existed in NSAID cumulative days. The findings demonstrate that NSAID use reduces second cancer risk in a dose-dependent manner in patients with primary breast cancer.
Does Influencers Popularity Actually Matter? An Experimental Investigation of the Effect of Influencers on Body Satisfaction and Mood Among Young Chinese Females: The Case of RED (Xiaohongshu)

Many studies have linked idealized body image on social media to negative psychological well-being among young females. However, social media influencers’ imagery has not attracted much research attention in either the Western or the Asian context. This study aimed to experimentally investigate the impact of high versus low popular social media influencer images on young Chinese females’ body satisfaction and mood. The participants were 420 female RED users (aged 18–35) who were randomly assigned to three groups: (1) the influencer-high group (idealized imagery alongside high engagement metrics); (2) the influencer-low group (the same idealized imagery adjusted for low engagement metrics); or (3) a control set of nature images. The results revealed that the groups exposed to influencer imagery had lower body satisfaction and more negative mood than the control group (nature images). Notably, this comparison showed no significant difference between the low-influencer and high-influencer groups in body satisfaction and mood. Additionally, this effect was moderated by individuals’ self-discrepancy between personal ideals and their own bodies. That is, exposure to idealized body images does not always produce harmful effects. For those with lower self-discrepancy, idealized body posts somewhat positively affected their body satisfaction. The current research contributes to the media effect literature by providing critical new insights into the study of body image in the context of China.
Pathway Association Studies Reveal Gene Loci and Pathway Networks that Associated With Plasma Cystatin C Levels

As a marker for glomerular filtration, plasma cystatin C level is used to evaluate kidney function. To decipher genetic factors that control the plasma cystatin C level, we performed genome-wide association and pathway association studies using United Kingdom Biobank data. One hundred fifteen loci yielded p values less than 1 × 10−100, three genes (clusters) showed the most significant associations, including the CST8-CST9 cluster on chromosome 20, the SH2B3-ATXN2 gene region on chromosome 12, and the SHROOM3-CCDC158 gene region on chromosome 4. In pathway association studies, forty significant pathways had FDR (false discovery rate) and or FWER (family-wise error rate) ≤ 0.001: spermatogenesis, leukocyte trans-endothelial migration, cell adhesion, glycoprotein, membrane lipid, steroid metabolic process, and insulin signaling pathways were among the most significant pathways that associated with the plasma cystatin C levels. We also performed Genome-wide association studies for eGFR, top associated genes were largely overlapped with those for cystatin C.
Augmented Reality, Multimodal Literacy and Mobile Technology: An Experiment in Teacher Engagement

Abstract The use of AR in education has already been found to be valuable although its use presents technical and management difficulties. The reality is that teachers often need to be enticed by a tempting range of potential benefits before investing precious time and effort in new technology. Challenges can cloud vision of greater potential. This ongoing project, essentially an experiment in encouraging professional learning, is proving successful in engaging educators with leading edge AR technology. Such an activity can provide a multi-dimensional catalyst for addressing a host of demands that face typical Australian teachers, particularly integrating mobile devices and multimodal texts in teaching and learning. The project – incorporating the location-aware FreshAiR app, Quick Response codes and image-triggered Aurasma – has been undertaken voluntarily by some Independent Schools in Western Australia. It includes developing teacher skills with AR (and other apps) and the development of a “model” AR tour (excursion/field trip). The experiment has generated trans-national collaborative conversations, positively impacting on both professional practice and app design. Participating schools have already provided valuable feedback that supports and expands existing research and perhaps generates some new ideas. The AISWA project has been funded by the Australian Government Quality Teacher Program.
Comparative Microbiota Composition Across Developmental Stages of Natural and Laboratory-Reared Chironomus circumdatus Populations From India

Chironomids are aquatic insects that undergo a complete metamorphosis of four life stages. Here we studied, for the first time, the microbiota composition of Chironomus circumdatus, a tropical midge species, both from the Mula and Mutha Rivers in Pune, India and as a laboratory-reared culture. We generated a comparative microbial profile of the eggs, larvae and pupae, the three aquatic life stages of C. circumdatus. Non-metric multidimensional scaling analysis (NMDS) demonstrated that the developmental stage had a more prominent effect on the microbiota composition compared to the sampling location. Notably, the microbiota composition of the egg masses from the different sampling points clustered together and differed from laboratory culture larvae. Proteobacteria was the dominant phylum in all the environmental and laboratory-reared egg masses and pupal samples, and in the laboratory-reared larvae, while Fusobacteria was the dominant phylum in the larvae collected from the field environment. The most abundant genera were Cetobacterium, Aeromonas, Dysgonomonas, Vibrio, and Flavobacterium. The ten amplicon sequence variants (ASVs) that most significantly contributed to differences in microbiota composition between the three sampled locations were: Burkholderiaceae (ASVs 04 and 37), C39 (Rhodocyclaceae, ASV 14), Vibrio (ASV 07), Arcobacter (ASV 21), Sphaerotilus (ASV 22), Bacteroidia (ASVs 12 and 28), Flavobacterium (ASV 29), and Gottschalkia (ASV 10). No significant differences were found in the microbial richness (Chao1) or diversity (Shannon H’) of the three sampled locations. In contrast, significant differences were found between the microbial richness of the three life stages. Studying the microbiota of this Chironomus species may contribute to a better understanding of the association of C. circumdatus and its microbial inhabitants.
Clustering of Spontaneous Recurrent Seizures in a Mouse Model of Extended Hippocampal Kindling

Acute repetitive seizures or seizure clusters are common in epileptic patients. Seizure clusters are associated with a high risk of developing status epilepticus and increased morbidity and mortality. Seizure clusters are also recognizable in spontaneous recurrent seizures (SRS) that occur in animal models of epilepsy. The electrical kindling of a limbic structure is a commonly used model of temporal lobe epilepsy. Although classic kindling over the course of a few weeks does not generally induce SRS, extended kindling over the course of a few months can induce SRS in several animal species. SRS in kindled cats often occur in clusters, but the existence of seizure clusters in rodent models of extended kindling remains to be demonstrated. We explored the existence of seizure clusters in mice following extended hippocampal kindling. Adult male mice (C57BL/6) experienced twice daily hippocampal stimulations and underwent continuous 24-hour electroencephalogram (EEG)-video monitoring after ≥80 stimulations. SRS events were recognized by EEG discharges and associated motor seizures. Seizure clusters, defined as ≥4 seizures per cluster and intra-cluster inter-seizure intervals ≤ 120 min, were observed in 19 of the 20 kindled mice. Individual mice showed variable seizure clusters in terms of cluster incidence and circadian-like expression patterns. For clusters consisting of 4–7 seizures and intra-seizure intervals ≤ 20 min, no consistent changes in inter-seizure intervals, EEG discharge duration, or motor seizure severity scores were observed approaching cluster termination. These results suggested that seizure clustering represents a prominent feature of SRS in hippocampal kindled mice. We speculate that, despite experimental limitations and confounding factors, systemic homeostatic mechanisms that have yet to be explored may play an important role in governing the occurrence and termination of seizure clusters.
Dynamic control for the task/posture coordination of humanoids: Toward synthesis of complex activities

The research developed in this PhD thesis deals with the general problem of dynamic control of ''task-oriented'' under-actuated and redundant systems considering more specifically the humanoid robotic systems. This research brings contributions to the problem of motor activities synthesis for constrained systems by their intrinsic capacities and by particular physical interactions with the environment. More specific issues that were addressed relate to: 1) the dynamic control of humanoid systems for carrying out basic activities requiring task/posture coordination perturbed by physical interactions, 2) the building of sequences of continuous dynamic activities based on a repertoire of motor coordination, 3) the planning and the adaptation of activities in the aim of a supervised automatic sequencing for complex non-deterministic tasks. The first chapter of this thesis is devoted to the description of a physical simulation engine and control laws for the development of dynamic behaviors. The second chapter provides a generic command based on the completion of several tasks under constraints. The third chapter develops an implementation of this controller on generic activities through the virtual model of the iCub robot. The fourth chapter develops a high-level controller to plan and adapt a sequence for the realization of more complex activities based on a predetermined repertoire of actions and monitoring their performance, while ensuring the control variables continuity.
Interleukin-5 (IL-5) Therapy Prevents Allograft Rejection by Promoting CD4+CD25+ Ts2 Regulatory Cells That Are Antigen-Specific and Express IL-5 Receptor

CD4+CD25+Foxp3+T cell population is heterogenous and contains three major sub-groups. First, thymus derived T regulatory cells (tTreg) that are naïve/resting. Second, activated/memory Treg that are produced by activation of tTreg by antigen and cytokines. Third, effector lineage CD4+CD25+T cells generated from CD4+CD25- T cells’ activation by antigen to transiently express CD25 and Foxp3. We have shown that freshly isolated CD4+CD25+T cells are activated by specific alloantigen and IL-4, not IL-2, to Ts2 cells that express the IL-5 receptor alpha. Ts2 cells are more potent than naïve/resting tTreg in suppressing specific alloimmunity. Here, we showed rIL-5 promoted further activation of Ts2 cells to Th2-like Treg, that expressed foxp3, irf4, gata3 and il5. In vivo, we studied the effects of rIL-5 treatment on Lewis heart allograft survival in F344 rats. Host CD4+CD25+T cells were assessed by FACS, in mixed lymphocyte culture and by RT-PCR to examine mRNA of Ts2 or Th2-like Treg markers. rIL-5 treatment given 7 days after transplantation reduced the severity of rejection and all grafts survived ≥60d whereas sham treated rats fully rejected by day 31 (p<0.01). Treatment with anti-CD25 or anti-IL-4 monoclonal antibody abolished the benefits of treatment with rIL-5 and accelerated rejection. After 10d treatment with rIL-5, hosts’ CD4+CD25+ cells expressed more Il5ra and responded to specific donor Lewis but not self. Enriched CD4+CD25+ cells from rIL-5 treated rats with allografts surviving >60 days proliferated to specific donor only when rIL-5 was present and did not proliferate to self or third party. These cells had more mRNA for molecules expressed by Th2-like Treg including Irf4, gata3 and Il5. These findings were consistent with IL-5 treatment preventing rejection by activation of Ts2 cells and Th2-like Treg.
M|G|∞ system parameters for a particular collection of service time distributions

In this paper we present the problems that arise when we compute the moments of service time distributions, for which the M|G|∞ busy period and busy cycle become very easy to study. We show how to overcome them. We also compute the busy cycle renewal function and the “peak” and the “modified peak” for the M|G|∞ busy period and busy cycle in the case of those service time distributions.
Artificial Intelligence Algorithms in Visual Evoked Potential-Based Brain-Computer Interfaces for Motor Rehabilitation Applications: Systematic Review and Future Directions

Brain-Computer Interface (BCI) is a technology that uses electroencephalographic (EEG) signals to control external devices, such as Functional Electrical Stimulation (FES). Visual BCI paradigms based on P300 and Steady State Visually Evoked potentials (SSVEP) have shown high potential for clinical purposes. Numerous studies have been published on P300- and SSVEP-based non-invasive BCIs, but many of them present two shortcomings: (1) they are not aimed for motor rehabilitation applications, and (2) they do not report in detail the artificial intelligence (AI) methods used for classification, or their performance metrics. To address this gap, in this paper the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was applied to prepare a systematic literature review (SLR). Papers older than 10 years, repeated or not related to a motor rehabilitation application, were excluded. Of all the studies, 51.02% referred to theoretical analysis of classification algorithms. Of the remaining, 28.48% were for spelling, 12.73% for diverse applications (control of wheelchair or home appliances), and only 7.77% were focused on motor rehabilitation. After the inclusion and exclusion criteria were applied and quality screening was performed, 34 articles were selected. Of them, 26.47% used the P300 and 55.8% the SSVEP signal. Five applications categories were established: Rehabilitation Systems (17.64%), Virtual Reality environments (23.52%), FES (17.64%), Orthosis (29.41%), and Prosthesis (11.76%). Of all the works, only four performed tests with patients. The most reported machine learning (ML) algorithms used for classification were linear discriminant analysis (LDA) (48.64%) and support vector machine (16.21%), while only one study used a deep learning algorithm: a Convolutional Neural Network (CNN). The reported accuracy ranged from 38.02 to 100%, and the Information Transfer Rate from 1.55 to 49.25 bits per minute. While LDA is still the most used AI algorithm, CNN has shown promising results, but due to their high technical implementation requirements, many researchers do not justify its implementation as worthwile. To achieve quick and accurate online BCIs for motor rehabilitation applications, future works on SSVEP-, P300-based and hybrid BCIs should focus on optimizing the visual stimulation module and the training stage of ML and DL algorithms.
Optimal preventive maintenance with repair

A minimal preventive-maintenance model is developed for repairable, continuously-operating devices whose conditions deteriorate with the time in service. The times to preventive maintenance have an Erland distribution and can be, in a limiting case, deterministic. The optimal value of the mean time a preventive maintenance is determined by minimizing the unavailability of the device due to preventive maintenance, to Poisson-distributed failures, and to deterioration failures. The model is useful for many devices, including electric power-system components such as coal pulverizers, circuit breakers, and transformers. >