Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Reinforcement Learning Based Task Scheduling in Edge Computing Networks

With the rapid development of 5G mobile networks services, massive data explodes in the network edge. Cloud computing services suffer from long latency and huge bandwidth requirement. Edge computing has become the key technology of reducing service delay and traffic load in 5G mobile networks. However, how to intelligently schedule tasks in the edge computing environment is still a critical challenge. In this paper, we define the optimization problem of minimizing the delay for task scheduling in the cloud-edge network architecture. The problem is proved NP-hard and modeled following Markov decision process. We design a cloud-edge collaboration scheduling algorithm based on asynchronous advantage actor-critic (CECS-A3C). Simulation results show that the proposed algorithm has good convergence speed and can reduce the task processing time by an average of 28.3% and 46.1% compared with the existing DQN and RL-G algorithms, while keeping the performance scalable.
Incentive-based Ramp-up Minimization in Multi-Microgrid Distribution Systems

Installation of renewable energy sources (RESs) in power systems has been dramatically increased due to clean nature and declining investment costs in recent years. This growing trend has led to new issues in the system operational management such as intense ramps inflicted on the network called system flexibility constraints. In this regard, due to decreasing the investment in bulk flexible resources, utilities would be significantly rely on local flexible ramp resources in the system to meet the supply-demand gap in each time-period. However, development of independently operated microgrids (MGs) as a result of restructuring and privatization in the power systems has imposed limitations over the access of system operators on the operational scheduling of local flexible resources. Consequently, this paper aims to provide a framework, which enables the distribution system operator (DSO) to exploit the operational scheduling of local flexible resources in MGs with the aim of decreasing the flexible ramp-up in the system. In the proposed scheme, DSO provides bonuses to MGs collaborated in alleviating the flexible ramp-up issue in the distribution system. Moreover, Stackelberg game concept is taken into account to model the bi-level optimization in the decentralized operated system, where DSO is regarded as the leader and MGs are considered as followers. Finally, the provided flexibility-based resource scheduling framework is implemented to efficiently operate a three-microgrid system considering flexibility ramp constraints.
Therapeutic targeting of nitroglycerin-mediated trigeminovascular neuronal hypersensitivity predicts clinical outcomes of migraine abortives.

Cranial hypersensitivity is a prominent symptom of migraine, exhibited as migraine headache exacerbated with physical activity, and cutaneous facial allodynia and hyperalgesia. The underlying mechanism is believed to be, in part, activation and sensitization of dural-responsive trigeminocervical neurons. Validated preclinical models that exhibit this phenotype have great utility for understanding putative mechanisms, and as a tool to screen therapeutics. We have previously shown that nitroglycerin triggers cranial allodynia in association with migraine-like headache, and this translates to neuronal cranial hypersensitivity in rats. Further, responses in both humans and rats are aborted by triptan administration, similar to responses in spontaneous migraine. Here, our objective was to study the nitroglycerin model examining the effects on therapeutic targets with newly approved treatments, specifically gepants and ditans, for the acute treatment of migraine. Using electrophysiological methods, we determined changes to ongoing firing and somatosensory-evoked cranial sensitivity, in response to nitroglycerin, followed by treatment with a CGRP receptor antagonist, gepant (olcegepant), a 5-HT1F receptor agonist, ditan (LY344864) and an NK1 receptor antagonist (GR205171). Nitroglycerin induced activation of migraine-like central trigeminocervical neurons, and intracranial and extracranial neuronal hypersensitivity. These responses were aborted by olcegepant and LY344864. However, GR205171, which failed in clinical trial for both abortive and preventive treatment of migraine, had no effect. These data support the nitroglycerin model as a valid approach to study cranial hypersensitivity and putative mechanisms involved in migraine, and as a screen to dissect potentially efficacious migraine therapeutic targets.
Longitudinal changes in mental health and the COVID-19 pandemic: evidence from the UK Household Longitudinal Study

Abstract Background The COVID-19 pandemic has had a range of negative social and economic effects that may contribute to a rise in mental health problems. In this observational population-based study, we examined longitudinal changes in the prevalence of mental health problems from before to during the COVID-19 crisis and identified subgroups that are psychologically vulnerable during the pandemic. Methods Participants (N = 14 393; observations = 48 486) were adults drawn from wave 9 (2017–2019) of the nationally representative United Kingdom Household Longitudinal Study (UKHLS) and followed-up across three waves of assessment in April, May, and June 2020. Mental health problems were assessed using the 12-item General Health Questionnaire (GHQ-12). Results The population prevalence of mental health problems (GHQ-12 score ⩾3) increased by 13.5 percentage points from 24.3% in 2017–2019 to 37.8% in April 2020 and remained elevated in May (34.7%) and June (31.9%) 2020. All sociodemographic groups examined showed statistically significant increases in mental health problems in April 2020. The increase was largest among those aged 18–34 years (18.6 percentage points, 95% CI 14.3–22.9%), followed by females and high-income and education groups. Levels of mental health problems subsequently declined between April and June 2020 but remained significantly above pre-COVID-19 levels. Additional analyses showed that the rise in mental health problems observed throughout the COVID-19 pandemic was unlikely to be due to seasonality or year-to-year variation. Conclusions This study suggests that a pronounced and prolonged deterioration in mental health occurred as the COVID-19 pandemic emerged in the UK between April and June 2020.
Omega-3 fatty acids ameliorate doxorubicin-induced cardiorenal toxicity: In-vivo regulation of oxidative stress, apoptosis and renal Nox4, and in-vitro preservation of the cytotoxic efficacy

This study examines the protective effects of omega‐3 fatty acids (OMG), a frequently used nutritional therapy in cancer patients, against doxorubicin (DOX)‐induced acute cardiorenal toxicity in rats, and evaluates the cytotoxic activity of DOX when used with OMG against breast cancer cell line. Five groups of rats were treated for 4 consecutive weeks with vehicle (groups I & II), or OMG (25, 50 or 100 mg/kg/day, po; groups III, IV & V, respectively). After twenty-four hours, the last four groups were injected with DOX (200 mg/kg, ip). In DOX-treated rats, the altered ECG, serum cardiac and renal function biomarkers, and histopathological features indicated the induction of cardiorenal toxicity. Increased oxidative and apoptotic markers in both organs was observed, with elevated renal contents of NADPH-oxidase-4 (Nox4) and renin. OMG pretreatment improved those DOX-induced impairments in a dose-dependent manner, and showed antioxidant and antiapoptotic effects with regulation of renal Nox4 expression. The in-vitro study showed preservation of the cytotoxic activity of DOX on MCF7 cell line in the presence of OMG. The data suggests OMG for protection against acute DOX‐induced cardiorenal damage without affecting the latter antitumor activity. It proposes regulation of oxidative stress, Nox4 activity and apoptosis as contributing protective mechanisms.
Underlay CR-NOMA Relaying Networks over Non-Homogeneous Generalized Fading Channels

In this paper, we studied a decode-and-forward underlay cognitive radio non-orthogonal multiple access (CR-NOMA) relaying system over non-homogeneous generalized alpha-mu fading channels. We derived accurate analytical expressions in closed form of the outage probability (OP) for two secondary end-users (E1 and E2). We considered three special cases of the alpha-mu statistical model. Moreover, we evaluated the impact of several system and fading parameters on the OP performance of the considered CR-NOMA. We also obtained simplified closed-form approximations to gain useful insights on the system performance. Finally, the analysis is verified by the good agreement with Monte Carlo simulations.
Novel Indicator to Ascertain the Status and Trend of COVID-19 Spread: Modeling Study

Background In the fight against the pandemic of COVID-19, it is important to ascertain the status and trend of the infection spread quickly and accurately. Objective The purpose of our study is to formulate a new and simple indicator that represents the COVID-19 spread rate by using publicly available data. Methods The new indicator K is a backward difference approximation of the logarithmic derivative of the cumulative number of cases with a time interval of 7 days. It is calculated as a ratio of the number of newly confirmed cases in a week to the total number of cases. Results The analysis of the current status of COVID-19 spreading over countries showed an approximate linear decrease in the time evolution of the K value. The slope of the linear decrease differed from country to country. In addition, it was steeper for East and Southeast Asian countries than for European countries. The regional difference in the slope seems to reflect both social and immunological circumstances for each country. Conclusions The approximate linear decrease of the K value indicates that the COVID-19 spread does not grow exponentially but starts to attenuate from the early stage. The K trajectory in a wide range was successfully reproduced by a phenomenological model with the constant attenuation assumption, indicating that the total number of the infected people follows the Gompertz curve. Focusing on the change in the value of K will help to improve and refine epidemiological models of COVID-19.
Early Occupational Intervention for People with low back pain in Physically Demanding jobs: 1-year Follow-up Results of the Randomized Controlled GOBACK Trial.

STUDY DESIGN Randomized controlled trial with 1-year follow up. OBJECTIVE To assess whether people with low back pain (LBP) and self-reported physically demanding jobs, benefit from an occupational medicine intervention, in addition to a single hospital consultation and an MRI, at 1 year of follow-up. Secondly, to examine whether the positive health effects, found in both groups at 6 months, persist at 1-year follow-up. SUMMARY OF BACKGROUND DATA The prevalence of LBP is high in the working population, resulting in a substantial social and economic burden. Although there are many guidelines available on the management of LBP, including multidisciplinary biopsychosocial rehabilitation, they provide limited guidance on the occupational medicine aspects. METHODS As reported previously, 305 participants with LBP and self-reported physically demanding jobs were enrolled in the randomized controlled study and randomly allocated to clinical care with additional occupational medicine intervention or clinical care alone. Data was collected at baseline, 6 months and 1 year. Outcomes included in the present 1-year follow up study are changes in neuropathic pain (painDETECT questionnaire), severity of pain (0-10 numerical rating scale), disability (Roland Morris Disability Questionnaire), fear-avoidance beliefs (FABQ), physical, and mental quality of life (SF-36). RESULTS The study showed no effect of an occupational intervention on neuropathic pain, fear-avoidance beliefs, physical and mental quality of life nor disability measured after one year. The positive effects found at 6 months in both groups, remained at 1-year follow-up. CONCLUSIONS The results suggest that a thorough clinical consultation, with focus on explaining the cause of pain and instructions to stay active, can promote long-lasting physical and mental health in individuals with LBP. Therefore, additional occupational interventions could focus on altering occupational obstacles on a structural level. LEVEL OF EVIDENCE 2.
Matches Made With Information: Fitting Measurement Models to Adult Attachment Data

Many self-report inventories in social/personality psychology are developed and scored using dominance-based assumptions. Specifically, they assume that the relationship between item endorsement and the latent trait is monotonically increasing; thus, individuals with high standings on the trait would be likely to endorse all items. It is possible, however, that the item response process for these inventories follows an ideal point process in which respondents only endorse items that best describe them, leading to nonmonotonic relations between item responses and latent traits. This research examined whether the item response process underlying the Experiences in Close Relationships–Revised—a commonly used self-report measure of adult attachment styles—is best understood as a dominance or ideal point process. Study 1 showed that the ideal point model provided a good account of the response process and provided better interpretability for the full trait continuum than a dominance model. Importantly, people who were the most insecure were the most likely to be scored differently under these two item response models. In Study 2, the association between attachment anxiety and subjective well-being scores was higher using ideal point than dominance-based scoring, and this was especially the case among subsets of people who were highly insecure. Study 3 demonstrated a similar pattern using simulation data. In summary, when dominance-based methods are used to measure adult attachment, people who are extremely insecure may be assessed in suboptimal ways.
Properties of PMMA end cap holders affect FE stiffness predictions of vertebral specimens

Bone cement is often used, in experimental biomechanics, as a potting agent for vertebral bodies (VB). As a consequence, it is usually included in finite element (FE) models to improve accuracy in boundary condition settings. However, bone cement material properties are typically assigned to these models based on literature data obtained from specimens created under conditions which often differ from those employed for cement end caps. These discrepancies can result in solids with different material properties from those reported. Therefore, this study aimed to analyse the effect of assigning different mechanical properties to bone cement in FE vertebral models. A porcine C2 vertebral body was potted in bone cement end caps, μ CT scanned, and tested in compression. DIC was performed on the anterior surface of the specimen to monitor the displacement. Specimen stiffness was calculated from the load-displacement output of the materials testing machine and from the machine load output and average displacement measured by DIC. Fifteen bone cement cylinders with dimensions similar to the cement end caps were produced and subjected to the same compression protocol as the vertebral specimen and average stiffness and Young moduli were estimated. Two geometrically identical vertebral body FE models were created from the μ CT images, the only difference residing in the values assigned to bone cement material properties: in one model these were obtained from the literature and in the other from the cylindrical cement samples previously tested. The average Youngs modulus of the bone cement cylindrical specimens was 1177 ± 3 MPa, considerably lower than the values reported in the literature. With this value, the FE model predicted a vertebral specimen stiffness 3% lower than that measured experimentally, while when using the value most commonly reported in similar studies, specimen stiffness was overestimated by 150%.
A Telesimulation Elective to Provide Medical Students With Pediatric Patient Care Experiences During the COVID Pandemic

Objectives/Introduction The Association of American Medical Colleges suggested that medical students not be involved in direct patient care activities in the United States because of the COVID pandemic. Our objectives are to (1) describe the rapid creation and implementation of a fully online simulation-based pediatric emergency medicine training intervention for medical student learners using existing simulation center staff (faculty, technicians, actors) and resources (simulation technology, scenario files) and (2) report student and faculty feedback on the intervention. Methods The sessions involved the use of our existing simulation center faculty, staff, and resources. Feedbacks on the sessions were collected via a survey from faculty and students at the end of each session. Results Sixteen simulation sessions were conducted (8 febrile infant, 8 anaphylactic toddler). Forty-eight students, 2 technicians, 2 actors, and 10 faculty participated. Ninety percent of the students agreed with the statements, “I am more comfortable with pediatrics after this session,” “participating improved my pediatric knowledge/skills,” “this session was more useful than other learning activities I am involved in at this time. ” Seventy percent of the students agreed with the statement, “I learned as much from observing as when I was actively involved. ” All faculty agreed with the statement, “this was an effective educational strategy compared to other distance learning. ” Most faculty (60%) disagreed with the statement, “virtual simulation was equal to or superior to in-person simulation. ” All students and faculty strongly agreed with the statement, “I would highly recommend this to others. ” Conclusions A telesimulation intervention involving all medical students, staff, and facilitators interacting remotely for pediatric emergency training during COVID was associated with high levels of satisfaction by the majority of learners and faculty.
Two-Dimensional Silicon Carbide: Emerging Direct Band Gap Semiconductor

As a direct wide bandgap semiconducting material, two-dimensional, 2D, silicon carbide has the potential to bring revolutionary advances into optoelectronic and electronic devices. It can overcome current limitations with silicon, bulk SiC, and gapless graphene. In addition to SiC, which is the most stable form of monolayer silicon carbide, other compositions, i.e., SixCy, are also predicted to be energetically favorable. Depending on the stoichiometry and bonding, monolayer SixCy may behave as a semiconductor, semimetal or topological insulator. With different Si/C ratios, the emerging 2D silicon carbide materials could attain novel electronic, optical, magnetic, mechanical, and chemical properties that go beyond those of graphene, silicene, and already discovered 2D semiconducting materials. This paper summarizes key findings in 2D SiC and provides insight into how changing the arrangement of silicon and carbon atoms in SiC will unlock incredible electronic, magnetic, and optical properties. It also highlights the significance of these properties for electronics, optoelectronics, magnetic, and energy devices. Finally, it will discuss potential synthesis approaches that can be used to grow 2D silicon carbide.
Discovery of the Similarities for Parasites

In this paper we report on a study for discovering hidden patterns in commonly seen parasites by using abstracts from MEDLINE database. Parasites affect millions of people in the world and cause tremendous morbidity and mortality. Diagnosing parasites can be difficult because some symptoms and related to gene-proteins can be common to some of them. We utilize a web based biomedical text mining tool to find symptoms and gene-proteins. After selecting the most common symptoms and gene-proteins, we create two datasets with the frequencies of symptoms and gene-proteins for each parasite. For this work we selected the k-means algorithm for clustering analysis and apply it on the datasets. In addition, we compared different algorithms to observe the performance of k-means. Clustering analysis generated different types of groups of parasites. Although the results are not 100% certain, they can make positive contributions to medical researchers and experts for the diagnosis of parasites.
A 400 year reconstruction of July relative air humidity for the region Vienna (eastern Austria) based on carbon and oxygen stable isotope ratios in tree-ring latewood cellulose of oaks

Stable isotope chronologies and correlation to climate. We present the stable isotope chronologies of carbon (δClw) and oxygen (δOlw) for the period from 1600 to 2003 respectively of non-exchangeable hydrogen (δHlw) for the last century constructed base upon tree-ring latewood cellulose from oaks (Quercus petraea Matt. Liebl.) grown in the region Vienna (Austria). The stable isotope ratios correspond mainly to the summer climate conditions. For the calibration period (1900-2003) we found high significant correlations (p < 0.001) between δClw and relative air humidity (RH) of July (-0.66), between δOlw and RHV I−V II (-0.61) and between δHlw and RHV I−V III (-0.56). In the case of temperatures high significant correlations between the growing season temperature and δClw (0.55), between the annual mean temperatures and δOlw ratios (0.45) and between summer mean temperatures (June to August) and δHlw values (0.49) were estimated.
Social Distancing Detection with Deep Learning Model

The paper presents a methodology for social distancing detection using deep learning to evaluate the distance between people to mitigate the impact of this coronavirus pandemic. The detection tool was developed to alert people to maintain a safe distance with each other by evaluating a video feed. The video frame from the camera was used as input, and the open-source object detection pre-trained model based on the YOLOv3 algorithm was employed for pedestrian detection. Later, the video frame was transformed into top-down view for distance measurement from the 2D plane. The distance between people can be estimated and any noncompliant pair of people in the display will be indicated with a red frame and red line. The proposed method was validated on a pre-recorded video of pedestrians walking on the street. The result shows that the proposed method is able to determine the social distancing measures between multiple people in the video. The developed technique can be further developed as a detection tool in realtime application.
The effect of different levels of dietary calcium, phosphorus and vitamin D3 on broiler blood and osseous factors

The present study examined the effect of different levels of calcium, phosphorus and vitamin D 3 on performance of Ross-308 broilers. The diets were NRC (1994) levels for control diet, calcium and phosphorus at 10% lower of NRC levels and vitamin D 3 as in control diet, calcium, phosphorus and vitamin D 3 at 10% higher of NRC levels, calcium and phosphorus at 10% lower of NRC levels and vitamin D 3 as in control diet, calcium and phosphorus at 10% lower of NRC levels and vitamin D 3 at 10% higher of NRC levels, calcium and phosphorus as in control diet and vitamin D 3 at 10% higher of NRC levels. The experimental design was a completely randomized design test (factorial experiment) with 5 treatments and 3 replicates in 56 days containing starter phase (d 1 to d 21), grower phase (d 22 to d 42) and finisher phase (d 43 to d 56). Calcium and phosphorus of tibia bone and calcium and phosphorus of blood serum were determined. The results indicated that calcium and phosphorus of serum were not affected significantly, but decreasing 10% calcium and phosphorus and increasing 10% vitamin D 3 levels had significant effect on calcium of tibia bone.