Miracle-dz/UniFAR-FTUs huggingface dataset:
Effort beats effectiveness in emotion regulation choice: Differences between suppression and distancing in subjective and physiological measures.

Emotion regulation (ER) can be implemented by different strategies which differ in their capacity to alter emotional responding. What all strategies have in common is that cognitive control must be exercised in order to implement them. The aim of the present preregistered study was to investigate whether the two ER strategies, expressive suppression and distancing, require different amounts of cognitive effort and whether effort is associated with personality traits. Effort was assessed subjectively via ratings and objectively via pupillometry and heart period. In two studies, N = 110 and N = 52 healthy adults conducted an ER paradigm. Participants used suppression and distancing during inspection of positive and negative pictures. They also had the choice to reapply either of the strategies at the end of the paradigm. Although distancing was more effective in downregulation of subjective arousal (Study 1: p < .001, η p 2 = .20; Study 2: p < .001, η p 2 = .207), about two thirds reapplied suppression, because it was perceived as less effortful. Effort was rated significantly lower for suppression compared to distancing (Study 1: p = .042, η p 2 = .04; Study 2: p = .002, η p 2 = .13). However, differences in effort were not reflected in pupillary data or heart period. Broad and narrow personality traits were neither associated with the preferred strategy nor with subjective or physiological effort measures. Findings suggest that people tend to use the ER strategy that is perceived as less effortful, even though it might not be the most effective strategy.
Neuro-immune interactions in paclitaxel-induced peripheral neuropathy

Abstract Background Paclitaxel is a taxane-based chemotherapeutic agent used as a treatment in breast cancer. There is no effective prevention or treatment strategy for the most common side effect of peripheral neuropathy. In this manuscript, we reviewed the molecular mechanisms that contribute to paclitaxel-induced peripheral neuropathy (PIPN) with an emphasis on immune-related processes. Methods A systematic search of the literature was conducted in PubMed, EMBASE and Cochrane Library. The SYRCLE’s risk of bias tool was used to assess internal validity. Results 156 studies conducted with rodent models were included. The risk of bias was high due to unclear methodology. Paclitaxel induces changes in myelinated axons, mitochondrial dysfunction, and mechanical hypersensitivity by affecting ion channels expression and function and facilitating spinal transmission. Paclitaxel-induced inflammatory responses are important contributors to PIPN. Conclusion Immune-related processes are an important mechanism contributing to PIPN. Studies in humans that validate these mechanistic data are highly needed to facilitate the development of therapeutic strategies.
Individual, Interpersonal, and Home Environmental Factors Influencing Health Behaviors Among Chinese Childhood Cancer Survivors

Background Childhood cancer survivors (CCSs) are at increased risk of chronic health conditions, which could be controlled with health behaviors. However, the health behaviors and related factors of Chinese CCSs remain unclear. Objective The aims of this study were to examine multiple health behaviors among Chinese CCSs and explore the individual, interpersonal, and home environmental factors affecting health behaviors. Methods This cross-sectional study recruited 204 participants from 3 grade-A tertiary hospitals in Guangzhou, China. Participants provided data on health behaviors (smoking, drinking, drug use, screen time, internet addiction, dietary behaviors, physical activity, and sleep behaviors) and their determining factors. Structural equation modeling was used to analyze the data. Results Chinese CCSs reported low rates of smoking, drinking, and drug use (0%–6.4%), but only 51% of survivors met screen time recommendations, and 24.5% of them had Internet addiction. Few survivors reported frequent soft-drink, sugar, and fast-food intake (2.0 to 7.4%), but many were finicky eaters (55.4%) or seldom drank milk (41.7%). In addition, 67.6% and 47.5% of survivors did not meet physical activity and sleep time recommendations. Childhood cancer survivors’ health behaviors were influenced by the individual (age, education level, and time since diagnosis), interpersonal (peer and family support), and home environmental (residential location, parents’ educations level, and household income) factors. Conclusions There were suboptimal health behaviors among Chinese CCSs. Targeted interventions should consider their individual, interpersonal, and home environmental factors. Implications for Practice Knowledge of health behaviors and related factors of Chinese CCSs would help healthcare professionals develop further interventions to improve their care of this population.
Temperature Compensated 3D Printed Strain Sensor for Advanced Manufacturing Applications

Additive Manufacturing, has evolved beyond prototyping to manufacturing end-products. The authors are involved in developing a large-scale extrusion-based 3D printer to print mining equipment - a Gravity Separation Spiral, and embedding sensors to monitor the operational conditions re-motely. This paper presents a temperature-compensated strain sensor that can be 3D printed inline within large-scale 3D printed equipment. The sensor is printed using conductive carbon filament and embedded in a Polylactic acid (PLA) base. A half-bridge setup is proposed to reduce the impact of temperature variations. Temperature-controlled tests have been conducted with the proposed half-bridge and compared with a non-temperature compensated quarter-bridge setup. Results show that the half-bridge configuration reduces the temperature impact on the strain measurement significantly (68%) compared to the quarter-bridge, in the range of 25-40 °C. Deflection testing conducted on the printed sensor shows a near-linear relationship between bending strain and voltage. Multiple bending cycles have shown that there is no significant hysteresis. ANSYS simulations are used to accurately estimate the internal temperature since embedding a temperature sensor would affect the structural integrity. Although carbon black material is naturally brittle, steps have been taken in the design to avoid undesirable cracking. Results from laser microscopy analysis of the printed traces showed no crack defects.
THE STUDIES ON UNDERSTANDING OF MIDGUT BACTERIAL COMMUNITY OF AEDES AEGYPTI COLLECTED FROM TAMILNADU, INDIA- A METAGENOMIC APPROACH

Metagenomics as a new field of research has been developed over the past decade to elucidate the genomes of the non-cultured microbes with the goal to better understand global microbial ecology on the one side, and on the other side it has been driven by the increasing biotechnological demands for novel enzymes and biomolecules. Ingestion of blood meal by female mosquitos triggers a series of physiological processes in the midgut and also exposes them to infection by these pathogens. The bacteria normally harbored in the mosquito’s midgut are known to influence physiology and can also alter the response to various pathogens. Here, we studied the bacterial diversity found in midgut part of Aedes aegypti to understand the host and microbe interaction. The adult Aedes aegypti mosquitos were collected from Chidambaram and around area using ovitrops and midgut part was extracted moreover the DNA templates were isolated and amplified by PCR. The DNA amplicons were sequenced by Illumina MiSeq gene sequence. The total 179,310 reads were classified in to 209, the bacterial genera of Aeromonas, Klebsella, Acinetobacter, Staphylococcus, Bacillus and Pseudomonas predominantly found to be high when compared to the other bacterial genera. The present data strongly encourage further investigations to verify the potential role of the detected bacteria in mosquito for the transmission several vectoral diseases.
Deep learning for segmentation in radiation therapy planning: a review

Segmentation of organs and structures, as either targets or organs‐at‐risk, has a significant influence on the success of radiation therapy. Manual segmentation is a tedious and time‐consuming task for clinicians, and inter‐observer variability can affect the outcomes of radiation therapy. The recent hype over deep neural networks has added many powerful auto‐segmentation methods as variations of convolutional neural networks (CNN). This paper presents a descriptive review of the literature on deep learning techniques for segmentation in radiation therapy planning. The most common CNN architecture across the four clinical sub sites considered was U‐net, with the majority of deep learning segmentation articles focussed on head and neck normal tissue structures. The most common data sets were CT images from an inhouse source, along with some public data sets. N‐fold cross‐validation was commonly employed; however, not all work separated training, test and validation data sets. This area of research is expanding rapidly. To facilitate comparisons of proposed methods and benchmarking, consistent use of appropriate metrics and independent validation should be carefully considered.
CircRNA WHSC1 promotes non‐small cell lung cancer progression via sponging microRNA‐296‐3p and up‐regulating expression of AKT serine/threonine kinase 3

Lung cancer is the most commonly diagnosed cancer and leading cause of cancer death, with 80%–85% of non‐small cell lung cancer (NSCLC). Circular RNAs (circRNAs) have been shown to be promising early diagnostic and therapeutic molecular biomarkers for NSCLC. However, biological role and regulatory mechanism of circRNA WHSC1 (circWHSC1) in NSCLC are unknown. Therefore, we aim to explore the function and mechanism of circWHSC1 in NSCLC oncogenesis and progression.
IVS-Caffe—Hardware-Oriented Neural Network Model Development

This article proposes a hardware-oriented neural network development tool, called Intelligent Vision System Lab (IVS)-Caffe. IVS-Caffe can simulate the hardware behavior of convolution neural network inference calculation. It can quantize weights, input, and output features of convolutional neural network (CNN) and simulate the behavior of multipliers and accumulators calculation to achieve the bit-accurate result. Furthermore, it can test the accuracy of the chosen CNN hardware accelerator. Besides, this article proposes an algorithm to solve the deviation of gradient backpropagation in the bit-accurate quantized multipliers and accumulators. This allows the training of a bit-accurate model and further increases the accuracy of the CNN model at user-designed bit width. The proposed tool takes Faster region based CNN (R-CNN) + Matthew D. Zeiler and Rob Fergus (ZF)-Net, Single Shot MultiBox Detector (SSD) + VGG, SSD + MobileNet, and Tiny you only look once (YOLO) v2 as the experimental models. These models include both one-stage object detection and two-stage object detection models, and base networks include the convolution layer, the fully connected layer, and the modern advanced layers, such as the inception module and depthwise separable convolution. In these experiments, direct quantization of layer-I/O fixed-point models to bit-accurate models will have a 2% mean average precision (mAP) drop of accuracy in the constraint that all layers’ accumulators and multipliers are quantized to less or equal to 14 and 12 bit, respectively. After retraining of these quantized models with the proposed IVS-Caffe, we can achieve less than 1% mAP drop in accuracy in the constraint that all layers’ accumulators and multipliers are quantized to less or equal to 14 and 11 bit, respectively. With the proposed IVS-Caffe, we can analyze the accuracy of the target model when it is running at hardware accelerators with different bit widths, which is beneficial to fine-tune the target model or customize the hardware accelerators with lower power consumption. Code is available at https://github.com/apple35932003/IVS-Caffe.
CRISPR gene editing in pluripotent stem cells reveals the function of MBNL proteins during human in vitro myogenesis

Abstract Alternative splicing has emerged as a fundamental mechanism for the spatiotemporal control of development. A better understanding of how this mechanism is regulated has the potential not only to elucidate fundamental biological principles, but also to decipher pathological mechanisms implicated in diseases where normal splicing networks are misregulated. Here, we took advantage of human pluripotent stem cells to decipher during human myogenesis the role of muscleblind-like (MBNL) proteins, a family of tissue-specific splicing regulators whose loss of function is associated with myotonic dystrophy type 1 (DM1), an inherited neuromuscular disease. Thanks to the CRISPR/Cas9 technology, we generated human-induced pluripotent stem cells (hiPSCs) depleted in MBNL proteins and evaluated the consequences of their losses on the generation of skeletal muscle cells. Our results suggested that MBNL proteins are required for the late myogenic maturation. In addition, loss of MBNL1 and MBNL2 recapitulated the main features of DM1 observed in hiPSC-derived skeletal muscle cells. Comparative transcriptomic analyses also revealed the muscle-related processes regulated by these proteins that are commonly misregulated in DM1. Together, our study reveals the temporal requirement of MBNL proteins in human myogenesis and should facilitate the identification of new therapeutic strategies capable to cope with the loss of function of these MBNL proteins.
Automatic methods of hoof-on and -off detection in horses using wearable inertial sensors during walk and trot on asphalt, sand and grass

Detection of hoof-on and -off events are essential to gait classification in horses. Wearable sensors have been endorsed as a convenient alternative to the traditional force plate-based method. The aim of this study was to propose and validate inertial sensor-based methods of gait event detection, reviewing different sensor locations and their performance on different gaits and exercise surfaces. Eleven horses of various breeds and ages were recruited to wear inertial sensors attached to the hooves, pasterns and cannons. Gait events detected by pastern and cannon methods were compared to the reference, hoof-detected events. Walk and trot strides were recorded on asphalt, grass and sand. Pastern-based methods were found to be the most accurate and precise for detecting gait events, incurring mean errors of between 1 and 6ms, depending on the limb and gait, on asphalt. These methods incurred consistent errors when used to measure stance durations on all surfaces, with mean errors of 0.1 to 1.16% of a stride cycle. In conclusion, the methods developed and validated here will enable future studies to reliably detect equine gait events using inertial sensors, under a wide variety of field conditions.
Effects of Surfactants on Solubilization of Perchloroethylene (PCE) and Trichloroethylene (TCE)

Enhanced solubilization of dense nonaqueous phase liquids (DNAPLs) especially chlorinated hydrocarbons using four types of surfactants was investigated. The solubilization kinetics of perchloroethylene PCE (100 mg/L solubility in water) and trichloroethylene TCE (1000 mg/L) in anionic (sodium dodecyl sulfate (SDS)), nonionic (Triton X-100), cationic (cetyltrimethylammonium bromide (CTAB)), and a biosurfactant (UH biosurfactant) were investigated at room temperature in continuously stirred batch reactors. The size distribution of surfactant micelles were measured using the dynamic light scattering device (DLS). The mean size of SDS, CTAB, Triton X-100, and UH biosurfactant micelles were 4.2 nm, 3.8 nm, 4.5 nm, and 59.1 nm, respectively. Micelle partition coefficients (Km) and molar solubility ratio (MSR) for PCE and TCE in 10 g/L of surfactant solutions have been quantified, and the solubility of PCE and TCE in the surfactant solutions increased by about 10-fold. Solubilization kinetics for PCE and TCE in .
Comparison of Parametric and Non-Parametric Operational Modal Analysis Methods on Crack Aluminum Beam

Background: It is essential to recognise modal parameters of any system in order to avoid failure and provide any necessary prevention measure. In this paper, an attempt to investigate the dynamic characteristics of crack aluminum beam using various identification algorithms of Operational Modal Analysis methods (OMA) such as Frequency Domain Decomposition (FDD), Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (Time parameterization technique) are applied to evaluate the accuracy of each method. Free-free end beam condition is used. Comparison of the results of these techniques will be shown based on practical issues in using each technique.
Robust Visual Tracking via Multitask Sparse Correlation Filters Learning

In this article, a novel multitask sparse correlation filters (MTSCF) model, which introduces multitask sparse learning into the CFs framework, is proposed for visual tracking. Specifically, the proposed MTSCF method exploits multitask learning to take the interdependencies among different visual features (e.g., histogram of oriented gradient (HOG), color names, and CNN features) into account to simultaneously learn the CFs and make the learned filters enhance and complement each other to boost the tracking performance. Moreover, it also performs feature selection to dynamically select discriminative spatial features from the target region to distinguish the target object from the background. A $l_{2,1}$ regularization term is considered to realize multitask sparse learning. In order to solve the objective model, alternating direction method of multipliers is utilized for learning the CFs. By considering multitask sparse learning, the proposed MTSCF model can fully utilize the strength of different visual features and select effective spatial features to better model the appearance of the target object. Extensive experiment results on multiple tracking benchmarks demonstrate that our MTSCF tracker achieves competitive tracking performance in comparison with several state-of-the-art trackers.
Effects of control temperature, ablation time, and background tissue in radiofrequency ablation of osteoid osteoma: A computer modeling study

To study the effects of the control temperature, ablation time, and the background tissue surrounding the tumor on the size of the ablation zone on radiofrequency ablation (RFA) of osteoid osteoma (OO). Finite element models of non‐cooled temperature‐controlled RFA of typical OOs were developed to determine the resulting ablation radius at control temperatures of 70, 80, and 90°C. Three different geometries were used, mimicking common cases of OO. The ablation radius was obtained by using the Arrhenius equation to determine cell viability. Ablation radii were larger for higher temperatures and also increased with time. All geometries and control temperatures tested had ablation radii larger than the tumor. The ablation radius developed rapidly in the first few minutes for all geometries and control temperatures tested, developing slowly towards the end of the ablation. Resistive heating and the temperature distribution showed differences depending on background tissue properties, resulting in differences in the ablation radius on each geometry. The ablation radius has a clear dependency not only on the properties of the tumor but also on the background tissue. Lower background tissue's electrical conductivity and blood perfusion rates seem to result in larger ablation zones. The differences observed between the different geometries suggest the need for patient‐specific planning, as the anatomical variations could cause significantly different outcomes where models like the one here presented could help to guarantee safe and successful tumor ablations.
Semi-Interpenetrating Polymer Network Hydrogel Blend Microspheres of Gelatin and Hydroxyethyl Cellulose for Controlled Release of Theophylline

Semi-interpenetrating polymer network (semi-IPN) hydrogel blend microspheres of gelatin and hydroxyethyl cellulose were prepared by a water-in-oil (w/o) emulsion technique and used to investigate the controlled release (CR) of theophylline (THP), an antiasthamatic drug. About 74% encapsulation of THP was achieved, and the drug release profiles were analyzed in terms of gelatin and hydroxyethyl cellulose blend composition, amount of cross-linking agent, and percentage drug loading. Fourier transform infrared (FTIR) spectroscopy confirmed the formation of the IPN blend matrix, as well as chemical stability of the drug in the microsphere. The physical state of the drug in the IPN matrix as evaluated by differential scanning calorimetry (DSC) and X-ray diffraction (XRD) remained undisturbed. The size of the microspheres varied from 98 to 144 μm as measured by laser light scattering. Scanning electron microscopy (SEM) indicated the smooth surface morphology of the microspheres. Equilibrium and dynamic swelling.
Systematic Review and Meta-analysis of Outcome after Mild Traumatic Brain Injury in Older People

Abstract Objective: Older age is often identified as a risk factor for poor outcome from traumatic brain injury (TBI). However, this relates predominantly to mortality following moderate–severe TBI. It remains unclear whether increasing age exerts risk on the expected recovery from mild TBI (mTBI). In this systematic review of mTBI in older age (60+ years), a focus was to identify outcome through several domains – cognition, psychological health, and life participation. Methods: Fourteen studies were identified for review, using PRISMA guidelines. Narrative synthesis is provided for all outcomes, from acute to long-term time points, and a meta-analysis was conducted for data investigating life participation. Results: By 3-month follow-up, preliminary findings indicate that older adults continue to experience selective cognitive difficulties, but given the data it is possible these difficulties are due to generalised trauma or preexisting cognitive impairment. In contrast, there is stronger evidence across time points that older adults do not experience elevated levels of psychological distress following injury and endorse fewer psychological symptoms than younger adults. Meta-analysis, based on the Glasgow Outcome Scale at 6 months+ post-injury, indicates that a large proportion (67%; 95% CI 0.569, 0.761) of older adults can achieve good functional recovery, similar to younger adults. Nevertheless, individual studies using alternative life participation measures suggest more mixed rates of recovery. Conclusions: Although our initial review suggests some optimism in recovery from mTBI in older age, there is an urgent need for more investigations in this under-researched but growing demographic. This is critical for ensuring adequate health service provision, if needed.