Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychological Impact in Healthcare Workers During Emergencies: The Italian Experience With COVID-19 First Wave

Background The COVID-19 outbreak imposed an overwhelming workload as well as emotional burdens on Healthcare workers (HCWs). In May 2020, an online survey was administered to HCWs in Italy to assess the pandemic's psychological impact and to investigate possible predictive factors that led to individual differences. Methods The psychological experience was measured based on the prevalence of self-reported feelings during the pandemic, including negative and positive emotional states. We analyzed the relationship between factors of gender, age, geographic region, professional role, and operational unit, and the four-point scale used to rate the frequency of each emotional state experienced by performing several multinomial logistic regressions, one for each emotion. Results Our findings suggest that more than half of HCWs experienced psychological distress during the first COVID-19 outbreak in Italy. Female and younger respondents, especially those operating in northern Italy experienced more frequently negative emotional states such as irritability, anxiety, loneliness, and insecurity. However, positive feelings, first of all solidarity, were also reported especially by female and older workers. The majority of the negative as well as positive emotional states were experienced almost equally by both doctors and nurses, and independently of the operational unit in which they operated. Conclusions This study can be very useful as a contribution to the current literature on the psychological effects of this pandemic on health workers. Moreover, our findings can provide useful information in planning more tailored psychological interventions to support this category of workers in the ongoing and future emergencies.
Comparative Efficacy and Safety of 11 Drugs as Therapies for Adults With Neuropathic Pain After Spinal Cord Injury: A Bayesian Network Analysis Based on 20 Randomized Controlled Trials

Objective To provide an updated analysis of the efficacy and safety of drugs for the management of neuropathic pain (NP) after spinal cord injury (SCI) based on Bayesian network analysis. Methods A Bayesian network meta-analysis of literature searches within PubMed, Cochrane Library, Embase, and Web of Science databases from their inception to February 21 2021 was conducted without language restrictions. Paired and network meta-analyses of random effects were used to estimate the total standardized mean deviations (SMDs) and odds ratios (ORs). Results A total of 1,133 citations were identified and 20 RCTs (including 1,198 patients) involving 11 drugs and placebos for post-SCI NP selected. The 5 outcomes from all 11 drugs and placebos had no inconsistencies after Bayesian network analysis. BTX-A gave the most effective pain relief for the 4 weeks, following a primary outcome. No significant differences were found among drugs with regard to adverse events of the primary outcome. Gabapentin, BTX-A, and pregabalin were found to be the most helpful in relieving secondary outcomes of mental or sleep-related symptoms with differences in SMDs, ranging from −0.63 to −0.86. Tramadol triggered more serious adverse events than any of the other drugs with differences in ORs ranging from 0.09 to 0.11. Conclusion BTX-A, gabapentin, pregabalin, amitriptyline, ketamine, lamotrigine, and duloxetine were all effective for NP management following SCI. Lamotrigine and gabapentin caused fewer side effects and had better efficacy in relieving mental or sleep-related symptoms caused by SCI-related NP. Tramadol, levetiracetam, carbamazepine, and cannabinoids could not be recommended due to inferior safety or efficacy. Systematic Review Registration [https://inplasy.com/inplasy-2020-7-0061/], identifier [INPLASY202070061].
Evaluating Electromyography and Sonomyography Sensor Fusion to Estimate Lower-Limb Kinematics Using Gaussian Process Regression

Research on robotic lower-limb assistive devices over the past decade has generated autonomous, multiple degree-of-freedom devices to augment human performance during a variety of scenarios. However, the increase in capabilities of these devices is met with an increase in the complexity of the overall control problem and requirement for an accurate and robust sensing modality for intent recognition. Due to its ability to precede changes in motion, surface electromyography (EMG) is widely studied as a peripheral sensing modality for capturing features of muscle activity as an input for control of powered assistive devices. In order to capture features that contribute to muscle contraction and joint motion beyond muscle activity of superficial muscles, researchers have introduced sonomyography, or real-time dynamic ultrasound imaging of skeletal muscle. However, the ability of these sonomyography features to continuously predict multiple lower-limb joint kinematics during widely varying ambulation tasks, and their potential as an input for powered multiple degree-of-freedom lower-limb assistive devices is unknown. The objective of this research is to evaluate surface EMG and sonomyography, as well as the fusion of features from both sensing modalities, as inputs to Gaussian process regression models for the continuous estimation of hip, knee and ankle angle and velocity during level walking, stair ascent/descent and ramp ascent/descent ambulation. Gaussian process regression is a Bayesian nonlinear regression model that has been introduced as an alternative to musculoskeletal model-based techniques. In this study, time-intensity features of sonomyography on both the anterior and posterior thigh along with time-domain features of surface EMG from eight muscles on the lower-limb were used to train and test subject-dependent and task-invariant Gaussian process regression models for the continuous estimation of hip, knee and ankle motion. Overall, anterior sonomyography sensor fusion with surface EMG significantly improved estimation of hip, knee and ankle motion for all ambulation tasks (level ground, stair and ramp ambulation) in comparison to surface EMG alone. Additionally, anterior sonomyography alone significantly improved errors at the hip and knee for most tasks compared to surface EMG. These findings help inform the implementation and integration of volitional control strategies for robotic assistive technologies.
Effects of Classroom-Based Resistance Training With and Without Cognitive Training on Adolescents’ Cognitive Function, On-task Behavior, and Muscular Fitness

Aim: Participation in classroom physical activity breaks may improve children’s cognition, but few studies have involved adolescents. The primary aim of this study was to examine the effects of classroom-based resistance training with and without cognitive training on adolescents’ cognitive function. Methods: Participants were 97 secondary school students (45.4% females, mean age 15.78 ± 0.44). Four-year 10 classes from one school were included in this four-arm cluster randomized controlled trial. Classes were randomly assigned to the following groups: sedentary control with no cognitive training, sedentary with cognitive training, resistance training without cognitive training, and resistance training with cognitive training. Sessions varied in levels of both cognitive demand and resistance training (i.e., high vs. low) and were administered three times per week for 4 weeks (12 sessions). Inhibition, cognitive flexibility, episodic memory, on-task behavior, and muscular fitness were assessed at baseline and post-test. Linear mixed models were used to examine changes within and between groups. Results: In comparison with the control group, episodic memory improved significantly in the resistance training without cognitive training group (−9.87 units, 95% CI: −17.71 to −2.03, p = 0.014, d = 0.72). There were no group-by-time effects for inhibition or cognitive flexibility. Classroom activity breaks both with and without cognitive demand improved participants’ on-task behavior in comparison with the control and sedentary group. The resistance training programs did not lead to improvements in muscular fitness. Conclusion: Participation in body weight resistance training without cognitive training led to selective improvements in episodic memory. No training effects were found for inhibition or cognitive flexibility. A longer study period may be necessary to induce improvements in muscular fitness and associated changes in inhibition and cognitive flexibility. Clinical Trial Registration: https://www.anzctr. org.au/ACTRN12621001341819.aspx, Australian New Zealand Clinical Trials Registry—ACTRN12621001341819.
Study on the amplitude of RC-bridge oscillator

The references researching on RC-bridge oscillator often provide technical indicators such as the criterion of oscillation,en-oscillating condition and oscillation frequency without discussing amplitudes of output signals.In this paper,determinants of output amplitudes are studied theoretically and virtual experimentally.It found that the amplitudes of output voltage are determined by values of amplification in en-oscillating condition.In the linear region of a circuit,the larger the amplification in en-oscillating condition exceeds 3,the bigger the amplitude of output voltage is.This study is useful for systemically researching of the construction of oscillator circuits and the selection of parameters.
Whodunit? Learning to Contrast for Authorship Attribution

Authorship attribution is the task of identifying the author of a given text. The key is finding representations that can differentiate between authors. Existing approaches typically use manually designed features that capture a dataset’s content and style, but these approaches are dataset-dependent and yield inconsistent performance across corpora. In this work, we propose to learn author-specific representations by fine-tuning pre-trained generic language representations with a contrastive objective (Contra-X). We show that Contra-X learns representations that form highly separable clusters for different authors. It advances the state-of-the-art on multiple human and machine authorship attribution benchmarks, enabling improvements of up to 6.8% over cross-entropy fine-tuning. However, we find that Contra-X improves overall accuracy at the cost of sacrificing performance for some authors. Resolving this tension will be an important direction for future work. To the best of our knowledge, we are the first to integrate contrastive learning with pre-trained language model fine-tuning for authorship attribution.
Detection and Localization of F-layer Ionospheric Irregularities with Back Propagation Method Along Radio Occultation Ray Path

The back propagation (BP) method consists of diffractive integrals computed over a trajectory path, projecting a signal to different planes. It unwinds the diffraction and multipath, resulting in minimum disturbance on the BP amplitude when the auxiliary plane coincides with the region causing the diffraction. The method has been previously applied in GNSS Radio Occultation (RO) measurements showing promising results in the location estimate of ionospheric irregularities but without complementary data to validate the estimation. In this study, we investigate with wave optics propagator (WOP) simulations 5 of an equatorial C/NOFS occultation with scintillation signatures caused by an equatorial plasma bubble (EPB), which was parametrized with aid of collocated data. In addition, a few more test cases were designed to assess the BP method regarding size, intensity and placement of single and multiple irregularity regions. The results show a location estimate accuracy of 10 km (single bubble, reference case), where in multiple bubble scenarios only the strongest disturbance would be resolved properly. The minimum detectable disturbance level and the estimation accuracy depend on the receiver noise level, and in the case of 10 several bubbles on the distance between them. The remarks of the evaluation supported the interpretation of results for two COSMIC occultations.
HSV VALUE AND OPENCV BASED OBJECT TRACKER

: This research shows how colour and motion may be utilised to speed up the surveillance of things. Video tracing is a technique for detecting a huge vehicle over a long distance using a camera. The main goal of video tracking is to link objects in subsequent video frames. When objects move faster than the frames per second, maintaining connection might be difficult. Using Hue saturation space values and OpenCV in separate video frames, this article shows how to follow moving objects in real-time. We begin by finding the HSV value of the object to be tested, and then we understand the steps along. The tracking of the items was shown to be 90 percent accurate.
Efficacy and Safety of Acupuncture in the Treatment of Poststroke Insomnia: A Systematic Review and Meta-Analysis of Twenty-Six Randomized Controlled Trials

Objective To evaluate the efficacy and safety of acupuncture in the treatment of poststroke insomnia. Methods PubMed, the Cochrane Library, Embase, Web of Science, China Biology Medicine (CBM), CNKI, VIP, and Wanfang databases were searched by computer from their inception to April 29, 2021, for collecting all randomized controlled trials of acupuncture in the treatment of poststroke insomnia. After two reviewers independently screened the literature, extracted the data, and evaluated the risk of bias in the included studies, the data were analyzed by RevMan 5.3 and STATA 16.0. The quality of outcomes was evaluated by the Grading of Recommendations Assessment, Development and Evaluation (GRADE). Results A total of 26 studies with 1874 cases were included, which had 942 cases in the treatment group and 932 cases in the control group. Meta-analysis results showed that, compared with oral medications alone, acupuncture alone or acupuncture combined with oral medications could improve the clinical effective rate and the sleep quality of patients, and the combined effects were RR = 1.21; 95% CI: 1.15, 1.27; P < 0.00001 and MD = 3.41; 95% CI: 2.40, 4.41; P < 0.00001, respectively. As for adverse reactions, the incidence of acupuncture alone or acupuncture combined with oral drugs was lower than that of oral drugs alone, which was safer and the combined effect was RR = 0.21; 95% CI: 0.09, 0.48; P=0.0002. Sensitivity analysis showed that the results were stable. We evaluated the quality of evidence with the GRADE system; the clinical effective rate was rated as “LOW,” the evidence grade of PSQI score was “LOW,” and the evidence grade of adverse reactions was “Very LOW. ” Conclusion Acupuncture alone or acupuncture combined with oral drugs is more effective and safer than oral drugs alone in the treatment of poststroke insomnia, which is suitable to promote in clinical practice.
Slender precast voided slabs under walking‐induced vibration

Disturbance/discomfort caused by vibrations, induced by pedestrian walking on slabs in residential/office buildings, is a typical design issue for lightweight slender slabs, including prestressed concrete ones. Precast slabs are typically made with pretensioned members which allow for only partial collaboration in the transverse slab direction, which becomes even less effective when they are dry‐assembled without cast‐in‐situ topping since it relies on the arrangement of mutual mechanical connections only. This study investigates through tests and numerical analyses the response of slender precast long‐span slabs made with voided members, dry‐assembled with mechanical connections, when subjected to vibrations generated by human activities. A parametric set of dynamic modal and time‐history analyses encompassing floor member geometry, connection arrangement, mass, and damping, is carried out. The numerical models are validated against results from an experimental test program carried out on two decks of a prototype precast building. The tests and the numerical models allowed to characterize the fundamental dynamic properties of the slab and its vibrational performance, identifying the most efficient technological solutions among those investigated to mitigate human‐induced vibrations
A realist journey through social theory and political economy: an interview with Andrew Sayer

ABSTRACT In this wide-ranging interview Andrew Sayer discusses how he became a realist and then the development of his work over the subsequent decades. He comments on his postdisciplinary approach, his early work on economy and its influences, how he came to write Method in Social Science and the transition in Realism and Social Science to normative critical social science and moral economy. The interview concludes with discussion of his three most recent books and the themes that connect them, not least the ongoing problem of a ‘diabolical double crisis’ of capitalism: extreme inequality and climate change.
Ultrasound-Guided Model Predictive Control of Needle Steering in Biological Tissue

In needle-based medical procedures, beveled tip flexible needles are steered inside soft tissue to reach the desired target locations. In this paper, we have developed an autonomous image-guided needle steering system that enhances targeting accuracy in needle insertion while minimizing tissue trauma. The system has three main components. First is a novel mechanics-based needle steering model that predicts needle deflection and accepts needle tip rotation as an input for needle steering. The second is a needle tip tracking system that determines needle deflection from the ultrasound images. The needle steering model employs the estimated needle deflection at the present time to predict needle tip trajectory in the future steps. The third component is a nonlinear model predictive controller (NMPC) that steers the needle inside the tissue by rotating the needle beveled tip. The MPC controller calculates control decisions based on iterative optimization of the predictions of the needle steering model. To validate the proposed ultrasound-guided needle steering system, needle insertion experiments in biological tissue phantoms are performed in two cases–with and without obstacle. The results demonstrate that our needle steering strategy guides the needle to the desired targets with the maximum error of 2.85mm.
[Activity Report 2021].

loss combining a connectionist temporal classiﬁcation loss with a cross entropy loss. The encoder is trained with the ﬁrst loss function, while the decoder is trained with the second. We tested our architecture on modern English handwritten text and obtained results close to the state-of-the-art. The architecture we proposed has less than 10M parameters and is much smaller compared to other transformer-based architecture, which might use up to 100M parameters. With the proposed architecture, we are able to obtain results at the level of other transformer-based architectures, without additional data. Such additional data are crucial for some architectures. We presented the results during Doctoral Consortium of the 2021 International Conference on Document Analysis and Recognition (ICDAR) which resulted in the best poster award and a publication [3]
Link level performance analysis of Satellite High Speed Downlink Packet Access (S-HSDPA)

We investigate the physical layer performance of HSDPA via GEO satellites for use in S-UMTS and SDMB. The impact of large round trip delay on link adaptation is discussed and link-level results are presented on the performance of HARQ for a variable number of retransmissions and different categories of UE in a rich multipath urban environment with three IMRs. It is shown that the N-channel SAW HARQ protocol can significantly increase the average throughput particularly for 16-QAM but the large round trip delay also requires an increase in the number of parallel HARQ channels resulting in high memory requirements at the UE. Receive antenna diversity with varying degrees of antenna correlation is also investigated as a possible performance enhancing method. The results presented here will help in specifying the physical layer of satellite HSDPA. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
Workflow assessing the effect of Achilles tendon rupture on gait function and metatarsal stress: Combined musculoskeletal modeling and finite element analysis

Achilles tendon rupture (ATR) incidence has increased among badminton players in recent years. The foot internal stress was hard to obtain through experimental testing. The purpose of the current research is to develop a methodology that could improve the finite element model derived foot internal stress prediction for ATR clinical and rehabilitation applications. A subject-specific musculoskeletal model was combined with a 3D finite element model to predict the metatarsal stress. The 80% point during the push-off phase of walking was selected for the comparing between injured and uninjured sides. The surgical repaired Achilles tendon (AT) after 12 months was elongated by 5.5% than the uninjured tendon. At 80% point of stance phase, the ankle plantarflexion angle and AT force decreased by 39.6% and 21.9% on the injured side, respectively. The foot inversion degree increased by 22.9% and was accompanied by the redistribution of metatarsals von Mises stress. The stresses on the fourth and fifth metatarsals were increased by 59.5% and 85.9% on the injured side. The workflow is available to assess musculoskeletal disorders and obtain foot internal stress after ATR. The decreased ankle plantar flexor force may be affected by triceps surae muscle atrophy and weakened force transmission ability of elongated AT. The increased von Mises stress on fourth and fifth metatarsals accompanied by higher foot inversion may increase the ankle lateral sprain injury risk.
Habitat fragmentation and logging affect the occurrence of lesser mouse‐deer in tropical forest reserves

Abstract Due to rapid urbanization, logging, and agricultural expansion, forest fragmentation is negatively affecting native wildlife populations throughout the tropics. This study examined the effects of landscape and habitat characteristics on the lesser mouse‐deer, Tragulus kanchil, populations in Peninsular Malaysia. We conducted camera‐trap survey at 315 sampling points located within 8 forest reserves. An assessment of site‐level and landscape variables was conducted at each sampling point. Our study provides critical ecological information for managing and conserving understudied populations of T. kanchil. We found that the detection of T. kanchil was attributed to forest fragmentation in which forest patches had four times greater detection of T. kanchil than continuous forest. The detection of T. kanchil was nearly three times higher in peat swamp forest compared to lowland dipterocarp forests. Surprisingly, the detection of T. kanchil was higher in logged forests (logging ceased at least 30 years ago) than unlogged forests. The detection of T. kanchil increased with the presence of trees, particularly those with DBH of 5 cm to 45 cm, canopy cover, number of saplings and palms, number of dead fallen trees, and distance from nearest roads. However, detection decreased with a greater number of trees with DBH greater than 45 cm and higher elevations, and greater detections where creeping bamboo was abundant. We recommend that conservation stakeholders take the necessary steps (e.g., eradicating poaching, habitat degradation, and further deforestation) to support the conservation of mouse‐deer species and its natural habitats.