Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the Structure of Negative Affect Regulation and Its Association With Hedonic and Psychological Wellbeing

The present study examines the structure of negative affect regulation strategies by confirmatory factor analysis. A total of 264 students (n = 187 women, 65 men) (M = 24 years; SD = 9.32) took part in this study. Results show a good fit indices for a three facets model: (1) modification of situation (problem-directed action, seeking emotional and instrumental social support, psychological abandonment and social isolation); (2) attentional deployment and cognitive change (distraction, acceptance, gratitude, rumination, reappraisal, spirituality, and social comparison); and (3) response modification (suppression, active and passive physiological, humor and warmth, venting, confrontation, and regulated emotional expression). The scale validity is confirmed through correlations between the expanded of Mood Affect Regulation Scale dimensions including dimensions of dispositional reappraisal and suppression, and hedonic and psychological well-being. Participants report an adaptive profile with high psychological well-being, even if they report low positive affect, suggesting a greater relevance of eudaimonic than hedonic well-being for affect regulation.
Generative Adversarial Networks for Hyperspectral Image Classification

A generative adversarial network (GAN) usually contains a generative network and a discriminative network in competition with each other. The GAN has shown its capability in a variety of applications. In this paper, the usefulness and effectiveness of GAN for classification of hyperspectral images (HSIs) are explored for the first time. In the proposed GAN, a convolutional neural network (CNN) is designed to discriminate the inputs and another CNN is used to generate so-called fake inputs. The aforementioned CNNs are trained together: the generative CNN tries to generate fake inputs that are as real as possible, and the discriminative CNN tries to classify the real and fake inputs. This kind of adversarial training improves the generalization capability of the discriminative CNN, which is really important when the training samples are limited. Specifically, we propose two schemes: 1) a well-designed 1D-GAN as a spectral classifier and 2) a robust 3D-GAN as a spectral–spatial classifier. Furthermore, the generated adversarial samples are used with real training samples to fine-tune the discriminative CNN, which improves the final classification performance. The proposed classifiers are carried out on three widely used hyperspectral data sets: Salinas, Indiana Pines, and Kennedy Space Center. The obtained results reveal that the proposed models provide competitive results compared to the state-of-the-art methods. In addition, the proposed GANs open new opportunities in the remote sensing community for the challenging task of HSI classification and also reveal the huge potential of GAN-based methods for the analysis of such complex and inherently nonlinear data.
BiSME: A Hardware Coprocessor to Perform Signature Matching at Multi-Gigabit Rates

Hardware acceleration of signature matching is essential to perform content aware networking at predictable rates in modern network processors. Existing hardware accelerators either cannot perform signature matching at predictable rates due to the storage organization of the signatures or do not compress the signatures effectively resulting in inefficient on-chip memory usage. Addressing these problems, a bitmap based signature matching engine called BiSME is proposed in this paper, which is a flexible, programmable and scalable hardware coprocessor to perform signature matching at fixed, but guaranteed rates. The storage architectures proposed as part of BiSME, allows to efficiently store the compressed signatures in a flexible and programmable manner in on-chip memories. Each BiSME instance is fine-tuned to perform signature matching at 9.3 Gbps, with multiple instances capable of supporting increasing signature counts as well as increasing throughput. The BiSME was synthesized on a commercial 28nm technology library and only occupies 1.43 mm2of silicon area and consumes 155mW of power. The BiSME hardware implementation was thoroughly verified on the Cadence Palladium platform. Over 2GB of network traffic was injected simultaneously into BiSME and a software based signature matching solution and the identical signature matching results further validated the correctness of the design.
Modified Current Speed Estimator MRASCCfor Induction Motor Drives

In this paper the specific modification of the MRASCCspeed estimator for induction motor drive is analyzed and tested. This modification is based on the introduction of an auxiliary variable in the mathematical model of the estimator. The modified and classical MRASCCspeed estimators were analyzed in simulation and experimental tests, under motoring and regenerating modes of the drive system, in open and closed-loop operation as well as under rotor time constant mismatch. It has been shown that the modified speed estimator with additional variable is stable in the regenerating mode on contrary to the classical solution.
Role for Growth Regulation by Estrogen in Breast Cancer 1 (GREB1) in Hormone-Dependent Cancers

Sex hormones play important roles in the onset and progression of several cancers, such as breast, ovarian, and prostate cancer. Although drugs targeting sex hormone function are useful in treating cancer, tumors often develop resistance. Thus, we need to define the downstream effectors of sex hormones in order to develop new treatment strategies for these cancers. Recent studies unearthed one potential mediator of steroid hormone action in tumors: growth regulation by estrogen in breast cancer 1 (GREB1). GREB1 is an early estrogen-responsive gene, and its expression is correlated with estrogen levels in breast cancer patients. Additionally, GREB1 responds to androgen in prostate cancer cells, and can stimulate the proliferation of breast, ovarian, and prostate cancer cells. Recent studies have shown that GREB1 also responds to progesterone in human endometrial cells, suggesting that GREB1 is a pan steroid-responsive gene. This mini-review examines evidence that GREB1 participates in several hormone-dependent cancers and could be targeted to treat these cancers.
Efficacy of Auditory versus Motor Learning for Skilled and Novice Performers

Humans must learn a variety of sensorimotor skills, yet the relative contributions of sensory and motor information to skill acquisition remain unclear. Here we compare the behavioral and neural contributions of perceptual learning to that of motor learning, and we test whether these contributions depend on the expertise of the learner. Pianists and nonmusicians learned to perform novel melodies on a piano during fMRI scanning in four learning conditions: listening (auditory learning), performing without auditory feedback (motor learning), performing with auditory feedback (auditory–motor learning), or observing visual cues without performing or listening (cue-only learning). Visual cues were present in every learning condition and consisted of musical notation for pianists and spatial cues for nonmusicians. Melodies were performed from memory with no visual cues and with auditory feedback (recall) five times during learning. Pianists showed greater improvements in pitch and rhythm accuracy at recall during auditory learning compared with motor learning. Nonmusicians demonstrated greater rhythm improvements at recall during auditory learning compared with all other learning conditions. Pianists showed greater primary motor response at recall during auditory learning compared with motor learning, and response in this region during auditory learning correlated with pitch accuracy at recall and with auditory–premotor network response during auditory learning. Nonmusicians showed greater inferior parietal response during auditory compared with auditory–motor learning, and response in this region correlated with pitch accuracy at recall. Results suggest an advantage for perceptual learning compared with motor learning that is both general and expertise-dependent. This advantage is hypothesized to depend on feedforward motor control systems that can be used during learning to transform sensory information into motor production.
Spinal cord injury and male infertility—a review of current literature, knowledge gaps, and future research

Spinal cord injury (SCI) affects nearly half a million new patients worldwide, with 17,700 in the US each year, and disproportionately impacts young males of reproductive age. Almost every aspect of male reproduction is affected by SCI, resulting in: erectile, endocrine and sexual dysfunction, decreased sperm motility despite an often-normal count, and abnormal semen emission and ejaculation. The aim of this review is to focus on how SCI impacts testicular spermatogenesis, sperm function, semen quality, and overall fecundity while discussing what is not known, and future avenues for research.
Lipid Paradox in Statin-Naïve Acute Ischemic Stroke But Not Hemorrhagic Stroke

Background: Low lipid level is associated with better cardiovascular outcome. However, lipid paradox indicating low lipid level having worse outcomes could be seen under acute injury in some diseases. The present study was designed to clarify the prognostic significance of acute-phase lipid levels within 1 day after admission for stroke on mortality in first-ever statin-naïve acute ischemic stroke (IS) and hemorrhagic stroke (HS). Methods: This observational study was conducted using the data collected from Stroke Registry In Chang-Gung Healthcare System (SRICHS) between 2009 and 2012. Patients with recurrent stroke, onset of symptoms >1 day, and history of the use of lipid-lowering agents prior to index stroke were excluded. Stroke was classified into IS and hypertension-related HS. The primary outcomes were 30-day and 1-year mortality identified by linkage to national death registry for date and cause of death. Receiver operating characteristic (ROC) curve analysis and multivariate Cox proportional hazard models were used to examine the association of lipid profiles on admission with mortality. Results: Among the 18,268 admitted stroke patients, 3,746 IS and 465 HS patients were eligible for analysis. In IS, total cholesterol (TC) <163.5 mg/dL, triglyceride (TG) <94.5 mg/dL, low-density lipoprotein (LDL) <100 mg/dL, non-high-density lipoprotein cholesterol (non-HDL-C) <130.5 mg/dL, and TC/HDL ratio <4.06 had significantly higher risk for 30-day/1-year mortality with hazard ratio (HR) of 2.05/1.37, 1.65/1.31, 1.68/1.38, 1.80/1.41, and 1.58/1.38, respectively, compared with high TC, TG, LDL, non-HDL-C, and TC/HDL ratio (p < 0.01 in all cases). In HS, lipid profiles were not associated with mortality, except HDL for 30-day mortality (p = 0.025) and high uric acid (UA) concentrations for 30-day and 1-year mortality (p = 0.002 and 0.012, respectively). High fasting glucose and high National Institute of Health Stroke Scale (NIHSS) score at admission were associated with higher 30-day and 1-year mortality in both IS and HS and low blood pressure only in IS (p < 0.05). Synergic effects on mortality were found when low lipids were incorporated with high fasting glucose, low blood pressure, and high NIHSS score in IS (p < 0.05). Conclusions: Lipid paradox showing low acute-phase lipid levels with high mortality could be seen in statin-naïve acute IS but not in HS. The mortality in IS was increased when low lipids were incorporated with high fasting glucose, low blood pressure, and high NIHSS score.
LIF-dependent survival of embryonic stem cells is regulated by a novel palmitoylated Gab1 signalling protein

ABSTRACT The cytokine leukaemia inhibitory factor (LIF) promotes self-renewal of mouse embryonic stem cells (ESCs) through activation of the transcription factor Stat3. However, the contribution of other ancillary pathways stimulated by LIF in ESCs, such as the MAPK and PI3K pathways, is less well understood. We show here that naive-type mouse ESCs express high levels of a novel effector of the MAPK and PI3K pathways. This effector is an isoform of the Gab1 (Grb2-associated binder protein 1) adaptor protein that lacks the N-terminal pleckstrin homology (PH) membrane-binding domain. Although not essential for rapid unrestricted growth of ESCs under optimal conditions, the novel Gab1 variant (Gab1β) is required for LIF-mediated cell survival under conditions of limited nutrient availability. This enhanced survival is absolutely dependent upon a latent palmitoylation site that targets Gab1β directly to ESC membranes. These results show that constitutive association of Gab1 with membranes through a novel mechanism promotes LIF-dependent survival of murine ESCs in nutrient-poor conditions. Highlighted Article: Embryonic stem cells rely upon expression of a novel lipid-modified Gab1 adaptor protein to promote survival under nutrient-poor conditions.
High-Performance Deep Neural Network-Based Tomato Plant Diseases and Pests Diagnosis System With Refinement Filter Bank

A fundamental problem that confronts deep neural networks is the requirement of a large amount of data for a system to be efficient in complex applications. Promising results of this problem are made possible through the use of techniques such as data augmentation or transfer learning of pre-trained models in large datasets. But the problem still persists when the application provides limited or unbalanced data. In addition, the number of false positives resulting from training a deep model significantly cause a negative impact on the performance of the system. This study aims to address the problem of false positives and class unbalance by implementing a Refinement Filter Bank framework for Tomato Plant Diseases and Pests Recognition. The system consists of three main units: First, a Primary Diagnosis Unit (Bounding Box Generator) generates the bounding boxes that contain the location of the infected area and class. The promising boxes belonging to each class are then used as input to a Secondary Diagnosis Unit (CNN Filter Bank) for verification. In this second unit, misclassified samples are filtered through the training of independent CNN classifiers for each class. The result of the CNN Filter Bank is a decision of whether a target belongs to the category as it was detected (True) or not (False) otherwise. Finally, an integration unit combines the information from the primary and secondary units while keeping the True Positive samples and eliminating the False Positives that were misclassified in the first unit. By this implementation, the proposed approach is able to obtain a recognition rate of approximately 96%, which represents an improvement of 13% compared to our previous work in the complex task of tomato diseases and pest recognition. Furthermore, our system is able to deal with the false positives generated by the bounding box generator, and class unbalances that appear especially on datasets with limited data.
Interaction Model for Hand Tracking Based on the Cognitive Theory

The VITE (vector integration to end point) model is prone to be affected by the object's size, orientation and distance during the arm movement and gripping process. To address these problems, we aim to minimize the number of disturbed basic components of arm movement, grip aperture and hand orientation. Based on the cognitive theory and the characteristics of the operational 3-D hand tracking cognitive model, this paper proposes a divide-and-conquer model capable of indicating the current grasping status and switching on/off the three basic components. This model is a token ring-based status classifier. After being integrated into the VITE model, it can simulate kinetic features during arm movement and grasping process more effectively, and it is more intelligent when we construct mutually independent simulation modules of arm movement and hand orientation for the visual channels. Simulation results demonstrate the superiority of the proposed model over other models mentioned in this paper in terms of disturbance resistance.
Skill and knowledge retention after training in cardiopulmonary ultrasound in Ghana: an impact assessment of bedside ultrasound training in a resource-limited setting

Objective Brief training courses in bedside ultrasound are commonly done by visiting faculty in low-income and middle-income countries, and positive short-term effects have been reported. Long-term outcomes are poorly understood. We held a training course on a cardiopulmonary ultrasound (CPUS) protocol over two separate 10-day periods in 2016. In 2017, 9–11 months after the initial training, we assessed skill and knowledge retention as well as perceived impact on local practice. Methods A written test using six clinical vignettes and an observed structured clinical examination were used to assess theoretical knowledge and practical skills. Additionally, in-person interviews and a written survey were completed with the physicians who had participated in the initial training. Results All 20 participants passed the written and clinical examination. The median follow-up test score was 10 out of 12, compared with a median score of 12 on a test completed immediately after the initial training. Physicians identified the ability to narrow their differential diagnosis and to initiate critical interventions earlier than without ultrasound as a key benefit of the CPUS training. They rated the cardiac, abdominal and inferior vena cava components of the CPUS protocol as most relevant to their everyday practice. Conclusion Long-term ultrasound knowledge and skill retention was high after a brief and intensive training intervention at an academic tertiary hospital in Ghana. Clinicians reported improvements in patient care and local practice patterns.
Large-scale Cloze Test Dataset Created by Teachers

Cloze tests are widely adopted in language exams to evaluate students’ language proficiency. In this paper, we propose the first large-scale human-created cloze test dataset CLOTH, containing questions used in middle-school and high-school language exams. With missing blanks carefully created by teachers and candidate choices purposely designed to be nuanced, CLOTH requires a deeper language understanding and a wider attention span than previously automatically-generated cloze datasets. We test the performance of dedicatedly designed baseline models including a language model trained on the One Billion Word Corpus and show humans outperform them by a significant margin. We investigate the source of the performance gap, trace model deficiencies to some distinct properties of CLOTH, and identify the limited ability of comprehending the long-term context to be the key bottleneck.
Burnout, job satisfaction, and stress levels of PAs

Objective: The main goal of this study was to assess burnout, job satisfaction, and stress to gain insight into the work lives of female and male PAs. Methods: Data were obtained from the 2016 American Academy of PAs salary survey. Descriptive statistics were used to assess questions related to burnout, happiness, and stress and to compare responses by sex. Results: Analysis revealed that, in general, PAs experience modest levels of burnout but are happy at work. More than half (55.6%) rated spending too many hours at work as an important contributor to stress. A higher percentage of female PAs than male PAs (32.2% versus 25.6%) have quit a job due to stress. Conclusions: Overall, PAs rate aspects of work life favorably. Further research on factors that contribute to the PA work experience may help inform interventions aimed at improving job satisfaction among healthcare professionals.
Massive MIMO for SWIPT: A Measurement-Based Study of Precoding

Massive multiple-input multiple-output transfer (MaMIMO) has been shown to be a viable technology for improving spectrum and energy efficiency of future wireless generations, both using theoretical and measurement-based approaches. While the benefits of Massive MIMO for simultaneous wireless information and power transfer (SWIPT) have been established in theory, no practical evaluations have been reported. In this paper, we evaluate the power transfer efficiency of various established precoding algorithms, using random data signals and two methods to deal with the necessity of channel state information. A first method relies on uplink pilots transmitted by the energy harvesting receiver, while for the second method we use channel beacons to avoid that every sensor has to consume power to transmit pilots. We experimentally evaluate the efficiency of both approaches as function of the number of antennas and the precoder used and show that increasing the amount of antennas from 2 to 64 while fixing total transmit power results in a 10 fold increase in rectifier output voltage. When using a channel beacon, we show that receive power can be sacrificed to construct broader beams, which can be shared by different wirelessly powered sensors. All measurements report rectifier output voltage, as measured in our facility.
Case of primary central nervous system histiocytic sarcoma with prominent proliferation of histiocytic cells between the trabeculae of reactive glial cells

Histiocytic sarcoma (HS) is an extremely rare malignant neoplasm that exhibits morphologic and immune‐phenotype evidence of histiocytic differentiation. The disease most commonly involves the lymph nodes, gastrointestinal tract, skin, and soft tissue, as well as in the central nervous system (CNS) being relatively rare. Here we report a case of primary CNS HS with unusual histopathological characteristics. A 65‐year‐old woman presented with CNS HS in the left frontal lobe region, showing two distinct histological patterns. Approximately half of the lesion displayed histological characteristics typical of HS, including diffuse invasion of large round‐to‐ovoid pleomorphic cells, with mitotic figures (Ki‐67 index: 30%) and coagulative necrotic foci. The other half exhibited prominent proliferation of histiocytic cells between the trabeculae of reactive glial cells, with rare mitotic figures (Ki‐67 index: < 1%) and no necrotic foci. There were transitions between two morphologies. The HS tumor cells and the histiocytic cells between the trabeculae of reactive glial cells possessed nearly identical histomorphologic and immunophenotypic features, although the HS tumor cells showed a more pronounced degree of cytologic atypia and mitotic activity. To our knowledge, this is the first reported case of HS with prominent proliferation of the histiocytic cells between the trabeculae of reactive glial cells. Here we present the detailed histological, immunohistochemical, and molecular findings. Investigating cases of HS may provide insight into the pathogenesis of this disease.