Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Transfer-Learning for patient specific model re-calibration: Application to sEMG-Classification

Accurate decoding of surface electromyography (sEMG) is pivotal for muscle-to-machine-interfaces (MMI) and their application for e.g. rehabilitation therapy. sEMG signals have high inter-subject variability, due to various factors, including skin thickness, body fat percentage, and electrode placement. Therefore, obtaining high generalization quality of a trained sEMG decoder is quite challenging. Usually, machine learning based sEMG decoders are either trained on subject-specific data, or at least recalibrated for each user, individually. Even though, deep learning algorithms produced several state of the art results for sEMG decoding,however, due to the limited amount of availability of sEMG data, the deep learning models are prone to overfitting. Recently, transfer learning for domain adaptation improved generalization quality with reduced training time on various machine learning tasks. In this study, we investigate the effectiveness of transfer learning using weight initialization for recalibration of two different pretrained deep learning models on a new subjects data, and compare their performance to subject-specific models. To the best of our knowledge, this is the first study that thoroughly investigated weight-initialization based transfer learning for sEMG classification and compared transfer learning to subject-specific modeling. We tested our models on three publicly available databases under various settings. On average over all settings, our transfer learning approach improves 5~\%-points on the pretrained models without fine-tuning and 12~\%-points on the subject-specific models, while being trained on average 22~\% fewer epochs. Our results indicate that transfer learning enables faster training on fewer samples than user-specific models, and improves the performance of pretrained models as long as enough data is available.
Sensor Fusion of Proprioception, Force and Vision in Estimation and Robot

Olli Alkkiomaki Sensor Fusion of Proprioception, Force and Vision in Estimation and Robot Control Lappeenranta, 2009 109 p. Acta Universitatis Lappeenrantaensis 358 Diss. Lappeenranta University of Technology ISBN 978-952-214-835-3 ISBN 978-952-214-836-0 (PDF) ISSN 1456-4491 Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision is a versatile low-cost sensory modality, but low sample rate, high sensor delay and uncertain measurements limit its usability, especially in strongly dynamic environments. Force is a complementary sensory modality allowing accurate measurements of local object shape when a tooltip is in contact with the object. In multimodal sensor fusion, several sensors measuring different modalities are combined to give a more accurate estimate of the environment. As force and vision are fundamentally different sensory modalities not sharing a common representation, combining the information from these sensors is not straightforward. In this thesis, methods for fusing proprioception, force and vision together are proposed. Making assumptions of object shape and modeling the uncertainties of the sensors, the measurements can be fused together in an extended Kalman filter. The fusion of force and visual measurements makes it possible to estimate the pose of a moving target with an end-effector mounted moving camera at high rate and accuracy. The proposed approach takes the latency of the vision system into account explicitly, to provide high sample rate estimates. The estimates also allow a smooth transition from vision-based motion control to force control. The velocity of the end-effector can be controlled by estimating the distance to the target by vision and determining the velocity profile giving rapid approach and minimal force overshoot. Experiments with a 5-degree-of-freedom parallel hydraulic manipulator and a 6-degree-of-freedom serial manipulator show that integration of several sensor modalities can increase the accuracy of the measurements significantly.
On Distinctive Properties of Universal Perturbations

We identify properties of universal adversarial perturbations (UAPs) that distinguish them from standard adversarial perturbations. Specifically, we show that targeted UAPs generated by projected gradient descent exhibit two human-aligned properties: semantic locality and spatial invariance, which standard targeted adversarial perturbations lack. We also demonstrate that UAPs contain significantly less signal for generalization than standard adversarial perturbations -- that is, UAPs leverage non-robust features to a smaller extent than standard adversarial perturbations.
Towards a Neural Model for Serial Order in Frontal Cortex: a Brain Theory from Memory Development to Higher-Level Cognition

In order to keep trace of information and grow up, the infant brain has to resolve the problem about where old information is located and how to index new ones. We propose that the immature prefrontal cortex (PFC) use its primary functionality of detecting hierarchical patterns in temporal signals as a second purpose to organize the spatial ordering of the cortical networks in the developing brain itself. Our hypothesis is that the PFC detects the hierarchical structure in temporal sequences in the form of ordinal patterns and use them to index information hierarchically in different parts of the brain. Henceforth, we propose that this mechanism for detecting patterns participates in the ordinal organization development of the brain itself; i.e., the bootstrapping of the connectome. By doing so, it gives the tools to the language-ready brain for manipulating abstract knowledge and planning temporally ordered information; i.e., the emergence of symbolic thinking and language. We will review neural models that can support such mechanisms and propose new ones. We will confront then our ideas with evidence from developmental, behavioral and brain results and make some hypotheses, for instance, on the construction of the mirror neuron system, on embodied cognition, and on the capacity of learning-to-learn.
Effects of ischemic compression and instrument-assisted soft tissue mobilization techniques in trigger point therapy in patients with rotator cuff pathology: randomized controlled study

Abstract Purpose To compare the ischaemic compression (IC) and instrument-assisted soft tissue mobilization (IASTM) in the treatment of MTrPs in addition to standard rehabilitation program in patients with rotator cuff tears. Methods Participants with rotator cuff tears were included the study (n = 46). Patients were randomly divided into two groups; which were Group 1 (IC + standard rehabilitation program (n = 23)), and Group 2 (IASTM + standard rehabilitation program (n = 23)) groups. Pain were assessed by visual analog scale (VAS). Range of motion (ROM) was assessed by a universal goniometer. Active MTrPs were assessed according to the Travel and Simons criteria. Pressure pain threshold (PPT) were assessed by a digital algometer. Function were evaluated by the Disabilities of the Arm, Shoulder and Hand Questionnaire (DASH) and American Shoulder and Elbow Surgeons Standardised Shoulder Assessment (ASES) Form. Anxiety and depression were evaluated by the Hospital Anxiety and Depression (HAD) scale. Satisfaction was assessed by the Global Rating of Change scale after 6 weeks treatment. Results After the treatment, pain, ROM and the DASH, ASES, HAD scores improved in both groups (p < 0.05). The active MTrPs of 2 muscles, PPT of 4 muscles and DASH in Group 1 significantly improved compared to Group 2 (p < 0.05). Conclusion Although patients with low functionality accumulated in the IC group, the IC is more effective than the IASTM in increasing the PPT and functional improvement according to the results of the DASH score.
The use of endophytic growth-promoting bacteria to alleviate salinity impact and enhance the chlorophyll, N uptake, and growth of rice seedling

Abstract Soil salinity is a major limiting factor for crop productivity, which increases continuously due to climate change. This barrier can possibly be overcome with the occurrence of halotolerant endophytic bacteria which reportedly plays an important role in protecting plants against various environmental stresses. Therefore, plant growth-promoting microbes are used in agriculture as an inexpensive and eco-friendly technology to enhance crop productivity in saline areas. In this study, the three isolates with nitrogen fixation ability were applied for mitigation of salt stress. The isolates were coded as C3A1, C8D2, and K10P4 and applied to rice plants by seed priming method. Furthermore, they were given as single innoculant or combined as a consortium compared to control, which was without the addition of endophytic bacteria, while the inoculated seed was planted on saline semisolid Fahraeus media at 4 dS m−1. The results showed that the single isolate of K10P4 endophytic bacteria increased the dry weight of rice plants, N uptake, and chlorophyll of plants in saline conditions. The combination of K10P4 isolate with C8D2 was synergistic and increased the population of endophytic bacteria in root tissue and chlorophyll content compared to the combination of C3A1 or three isolates. Meanwhile, the use of the 16S ribosomal RNA method on C3A1, C8D2, and K10P4 indentified the isolates as Ochrobactrum tritici (C3A1), Pseudomonas stutzeri (C8D2), and Pseudomonas stutzeri (K10P4).
Physics-Based Motion Control Through DRL’s Reward Functions

Producing natural physically-based motions of articulated characters is a challenging problem. The animator needs to figure out high-dimensional parameters of a motion controller to get good visual quality, while still having to deal with the basic functioning of the controller. However, those parameters generally have an unintuitive relationship with the resulting motion. Deep Reinforcement Learning (DRL) has been recently explored to solve such problem. With DRL, it is possible to set a neural network with observation and action parameters and control the animation through a reward function. Nevertheless, choosing good parameters and a reward function is not a simple task. In this paper, we investigate how the animator can control the motion by manipulating simple reward functions. We propose a control structure with DRL, in which the reward function can be adapted to the desired motion and to the morphology of the controlled character. Moreover, we introduce speed in the training process so that, after training the neural network, the character is able to adapt its motion to different speeds in real time. Through a series of tests, we assess animation and speed controls of characters with different morphologies.
Dicrev-Dash: Proposal for the Design, Creation and Evaluation of a Dashboard for Data Visualization

Today there are large amounts of data that are difficult to understand in spreadsheets or textual reports, so data visualizations have become an easy and fast way to convey the ideas or objectives that you want to achieve with that data. The objective of this article is to propose a methodology for creating dashboard data visualizations, taking into account the fundamental steps in the creation of a data methodology. To this end, the following question has been posed: What are the phases that must be considered to create an efficient and effective data visualization? This question will be answered in this article with the elaboration of the proposed methodology. Having said all the above, it is proposed to follow and prove this methodology in the future to create a dashboard of data visualizations for the learning analytics observatory.
Kidney-Targeted Redox Scavenger Therapy Prevents Cisplatin-Induced Acute Kidney Injury

Cisplatin-induced acute kidney injury (CI-AKI) is a significant co-morbidity of chemotherapeutic regimens. While this condition is associated with substantially lower survival and increased economic burden, there is no pharmacological agent to effectively treat CI-AKI. The disease is hallmarked by acute tubular necrosis of the proximal tubular epithelial cells primarily due to increased oxidative stress. We investigated a drug delivery strategy to improve the pharmacokinetics of an approved therapy that does not normally demonstrate appreciable efficacy in CI-AKI, as a preventive intervention. In prior work, we developed a kidney-selective mesoscale nanoparticle (MNP) that targets the renal proximal tubular epithelium. Here, we found that the nanoparticles target the kidneys in a mouse model of CI-AKI with significant damage. We evaluated MNPs loaded with the reactive oxygen species scavenger edaravone, currently used to treat stroke and ALS. We found a marked and significant therapeutic benefit with edaravone-loaded MNPs, including improved renal function, which we demonstrated was likely due to a decrease in tubular epithelial cell damage and death imparted by the specific delivery of edaravone. The results suggest that renal-selective edaravone delivery holds potential for the prevention of acute kidney injury among patients undergoing cisplatin-based chemotherapy.
Peer Relationships and Depressive Symptoms Among Adolescents: Results From the German BELLA Study

Background: Poor mental health affects adolescent development and is associated with health and social outcomes in later life. The current study uses cross-sectional data to explore the understudied aspects of peer relationships as a predictor of depressive symptom severity of adolescents in Germany. Method: Data from the German BELLA study were analyzed. We focused on the most recent measurement point of the BELLA study and analyzed data of 446 adolescents (aged 14–17 years). Peer relationship was measured using four items from the internationally established Patient-Reported Outcome Measurement Information System (PROMIS). Depressive symptoms were assessed via seven items of the German version of the Centre for Epidemiological Studies Short Depression Scale (CES-D). Hierarchical linear regression models were computed to explore the association between depressive symptoms and peer relationships. Hierarchical linear regression models served to determine the added predictive effects of each aspect of peer relationships. Result: The regression model showed that 22% of the variance of the severity of depressive symptoms could be explained by the quality of adolescents’ peer relationships (F(1,444) = 125.65, p < 0.001). Peer acceptance has the most substantial unique contribution to peer relationship as a predictor of depressive symptom severity (Change in R2 = 0.05; Change in F = 27.01, p < 0.001). The gender-specific analysis shows different trends for boys and girls. Conclusion: The quality of peer relationships is a significant predictor of adolescents’ depressive symptoms severity. Improved peer acceptance, dependability, and ease of making new friends are significantly associated with reduced depression symptoms for Germany’s adolescent population.
Genetic Structure and Forensic Feature of 38 X-Chromosome InDels in the Henan Han Chinese Population

Insertion/deletion (InDel) polymorphisms, as ideal forensic markers, show useful characteristics of both SNPs and STRs, such as low mutation rate, short amplicon size and general applicability of genotyping platform, and have been used in human identification, population genetics and biogeographic research in recent years. X-chromosome genetic markers are significant in population genetic studies and indispensable complements in some complex forensic cases. However, the population genetic studies of X-chromosome InDel polymorphisms (X-InDels) still need to be explored. In this study, the forensic utility of a novel panel including 38 X-InDel markers was evaluated in a sample of Han population from Henan province in China. It is observed that the heterozygosities ranged from 0.0054 to 0.6133, and the combined discrimination power was 1–9.18 × 10−17 for males and 1–7.22 × 10−12 for females respectively. The mean exclusion chance in trios and duos were 0.999999319 and 0.999802969 respectively. Multiple biostatistics methods, such as principal component analysis, genetic distances analysis, phylogenetic reconstruction, and structure analysis was used to reveal the genetic relationships among the studied Henan Han group and other 26 reference groups from 1,000 Genomes Project. As expected, the Henan Han population was clustered with East Asian populations, and the most intimate genetic relationships existed in three Han Chinese populations from Henan, Beijing and South China, and showed significant differences compared with other continental groups. These results confirmed the suitability of the 38 X-InDel markers both in individual identification and parentage testing in Han Chinese population, and simultaneously showed the potential application in population genetics.
Tertiary Control for Energy Management of EV Charging Station Integrated With PV and Energy Storage

Along with the rapid increase in the number of electric vehicles, more and more EV charging stations tend to have charging infrastructure, rooftop photovoltaic and energy storage all together for energy saving and emission reduction. Compared with individual design for each of the components in such kind of systems, an integrated design can result in higher efficiency, increased reliability, and lower total capital cost. This paper mainly focuses on the tertiary control strategy for dynamic state operation, such as PV generation fluctuation and random arrival/leave of EVs. The tertiary control aims to achieve stable operation under dynamic states, as well as to optimize the energy flow in the station to realize maximal operational benefits with constraints such as peak/valley price of electricity, state of discharge limitation of battery, etc. In this paper, four energy management functions in tertiary control level are proposed, and their performance is verified by simulations. By using prediction of PV power and EV load in the following 72 h, a novel tertiary control logic is proposed to optimize PVC and ESC power flow by changing their droop characteristics, so that minimum operational cost for the station can be achieved. Furthermore, a sensitivity analysis is conducted for three parameters, including ES battery capacity, weather influence, and PV and EV load prediction error. The results from sensitivity analysis indicate that ES battery capacity and weather condition lead to a great impact on the operational cost of the integrated charging station, while a typical prediction error of PV power and EV load will not influence the optimization result significantly.
Single-Cell Analysis Reveals the Immune Characteristics of Myeloid Cells and Memory T Cells in Recovered COVID-19 Patients With Different Severities

Despite many studies on the immune characteristics of Coronavirus disease 2019 (COVID-19) patients in the progression stage, a detailed understanding of pertinent immune cells in recovered patients is lacking. We performed single-cell RNA sequencing on samples from recovered COVID-19 patients and healthy controls. We created a comprehensive immune landscape with more than 260,000 peripheral blood mononuclear cells (PBMCs) from 41 samples by integrating our dataset with previously reported datasets, which included samples collected between 27 and 47 days after symptom onset. According to our large-scale single-cell analysis, recovered patients, who had severe symptoms (severe/critical recovered), still exhibited peripheral immune disorders 1–2 months after symptom onset. Specifically, in these severe/critical recovered patients, human leukocyte antigen (HLA) class II and antigen processing pathways were downregulated in both CD14 monocytes and dendritic cells compared to healthy controls, while the proportion of CD14 monocytes increased. These may lead to the downregulation of T-cell differentiation pathways in memory T cells. However, in the mild/moderate recovered patients, the proportion of plasmacytoid dendritic cells increased compared to healthy controls, accompanied by the upregulation of HLA-DRA and HLA-DRB1 in both CD14 monocytes and dendritic cells. In addition, T-cell differentiation regulation and memory T cell–related genes FOS, JUN, CD69, CXCR4, and CD83 were upregulated in the mild/moderate recovered patients. Further, the immunoglobulin heavy chain V3-21 (IGHV3-21) gene segment was preferred in B-cell immune repertoires in severe/critical recovered patients. Collectively, we provide a large-scale single-cell atlas of the peripheral immune response in recovered COVID-19 patients.
Self-Focusing Property of Partially Coherent Beam With Non-Uniform Correlation Structure in Non-Linear Media

Coherence in a light beam has the potential to serve as a degree of freedom for manipulating the beam. In this work, the self-focusing property of a partially coherent beam with a non-uniform correlation structure propagating in a non-linear medium is investigated. The analysis of the evolution of beam width reveals that the coherence structure plays a vital role in the self-focusing formation. A threshold condition for the coherence radius is proposed for the first time, and the relation of self-focusing length and initial coherence radius is studied numerically and analytically. It is shown that a feasible approach for manipulating the self-focusing length by adjusting the initial coherence radius is achieved.
Psychedelic Mushrooms in the USA: Knowledge, Patterns of Use, and Association With Health Outcomes

Introduction: Popular media coverage of psychedelics use, growing research into this class of compounds for psychiatry and decriminalization initiatives, are transforming the public perception of psychedelics. However, little is known about levels of knowledge and psychedelic mushroom (PM) use among American adults. Methods: We examined PM use and various measures of health status, quality of life, and self-reported mental health outcome measures obtained through a national on-line, cross-sectional survey of adults with a demographic composition representative of the US adult population by region, gender, age, and race (weighted N = 251,297,495) from November 2020–March 2021. Results: General mental health and well-being were popular reasons for PM use (63.6%), although use for medically-diagnosed (31.8%) and self-diagnosed (19.0%) conditions was also common. PM users reported more depression and anxiety as reflected in higher GAD-7 and PHQ-9 scores. Factors predictive of PM use included being male [OR 1.54 95%CI 1.09–2.15] and having higher Charlson Comorbidity Index scores [OR 1.42; 95%CI 1.22–1.65]. Self-reported PM use was less likely among participants with health insurance [OR = 0.50 (0.35–0.72)], increased age [OR = 0.92 (0.90–0.93)] and, relative to those living in the west US census region, living in the northeast [OR = 0.27 (0.15–0.50)], midwest [OR = 0.34 (0.20–0.56)], and south [OR = 0.38 (0.26–0.55)]. Discussion and Conclusions: A significant number of Americans are already “self-medicating” with PM and as growing positive media coverage of psychedelics drives public interest in the health benefits of PM, this number will increase. The association between PM use and poor mental health requires further research to inform policy.