Impact of La3+doping on temperature coefficient of resistivity and peak temperature of La x Ca0.89-xSr0.11MnO3 films prepared by sol-gel spin coating method

Herein, refined LaxCa0.89-xSr0.11MnO3 (LCSMO, x = 0.65, 0.68, 0.71 and 0.74) films were prepared through the sol-gel spin-coating. The influence of La3+ content on the structural properties of LCSMO films was investigated by X-ray diffraction and Atomic force microscope, demonstrating that LCSMO films can grow well on SrTiO3 (00l) substrate. Besides, X-ray photoemission spectroscopy verified the double exchange (DE) effect was weakened with La3+ dopant. The La3+ doping and interconnected grains boundaries (GBs) led to the weakening DE effect and GBs scattering, respectively. Due to superior GBs connectivity, the resistivity of LCSMO films was less than 7.1 x 10(-4) Omega.cm at low temperature of 100 K. Importantly, it is an effective control method to keep the temperature (T-k) corresponding to temperature coefficient of resistivity (TCR) at room temperature with Sr2+ content as constant in LCSMO films. At x = 0.71, the peak TCR value was found to be 8.84%/K and corresponding T-k was 283.15 K. These results are beneficial for advanced application of uncooling infrared bolometer.

Telemedicine and the Utilization of Outpatient Mental Health Services By Patients with Incident Major Depressive Disorder during the COVID-19 Pandemic

Objectives: To examine the role of telemedicine in providing access to outpatient psychotherapy for children and young adults with incident major depressive disorder (MDD) before and during the COVID-19 pandemic, overall and by race and ethnicity. Method(s): Medical claims from a large, national insurer were retrospectively analyzed to identify two cohorts of individuals aged 10-26 years old, based on incident diagnosis ("index") date of MDD (pre-COVID: March-December 2018, COVID: March-December 2020). We tracked health care utilization, utilization by site of care, modality of care, and psychotherapy Results: The majority of patients in the two cohorts (pre-COVID: N=7,758, COVID: N=8,517) were White (78.9% and 78.8%, respectively), followed by Hispanic (11.5% and 10.9%), Black (6.6% and 7.1%), and Asian (3.0% and 3.2%). While pre-index utilization was similar between cohorts, the COVID cohort had 919 psychotherapy visits per 1,000 patients compared to 735 for the pre-COVID cohort in the month post-index. The increase in visits is largely attributable to an increase in telemedicine visits for the COVID cohort. Similarly, psychotherapy visits increased for all racial and ethnic groups in the COVID cohort compared to the pre-COVID cohort in the month post-index: 22.3% for Whites (931 visits per 1,000 patients in COVID cohort vs. 759 in pre-COVID cohort), 45.0% for Asians (951 vs. 656), 20.5% for Blacks (792 vs. 657) and 46.5% for Hispanics (860 vs. 587). Conclusion(s): Telemedicine increased access to mental health services during the pandemic across races and ethnicities, but racial and ethnic disparities persisted. Health systems should capitalize on the telehealth infrastructure developed during the pandemic to sustain this increased access to care while continuing work to reduce disparities.Copyright © 2023

Adaptive Semantic Video Conferencing for Ofdm Systems

Video conferencing has become more common than ever due to the COVID-19 pandemic, which makes high-resolution video transmission a pressing issue. Although semantic video conferencing (SVC) has achieved a great success to improve the transmission efficiency by only transmitting some keypoints to represent changed expressions, its performance can still be improved by adapting to varying channel scenarios, which is lack of study when designing the whole SVC in the end-to-end manner. In this paper, we first establish a standard SVC-OFDM system. Then, the receiver part of the SVC is added with an adaptive network called Switch-SVC for varying channels and improve the accuracy of the received keypoints. Some parameters in Switch-SVC are trained online so that the receiver can adapt to the current environment. Simulation results show that the proposed method can greatly improve the keypoint reconstruction performance compared to the traditional SVC-OFDM receiver without online training.

Deep Learning in COVID-19 Diagnosis, Prognosis and Treatment Selection

Deep learning is a sub-discipline of artificial intelligence that uses artificial neural networks, a machine learning technique, to extract patterns and make predictions from large datasets. In recent years, it has achieved rapid development and is widely used in numerous disciplines with fruitful results. Learning valuable information from complex, high-dimensional, and heterogeneous biomedical data is a key challenge in transforming healthcare. In this review, we provide an overview of emerging deep-learning techniques, COVID-19 research involving deep learning, and concrete examples of deep-learning methods in COVID-19 diagnosis, prognosis, and treatment management. Deep learning can process medical imaging data, laboratory test results, and other relevant data to diagnose diseases and judge disease progression and prognosis, and even recommend treatment plans and drug-use strategies to accelerate drug development and improve drug quality. Furthermore, it can help governments develop proper prevention and control measures. We also assess the current limitations and challenges of deep learning in therapy precision for COVID-19, including the lack of phenotypically abundant data and the need for more interpretable deep-learning models. Finally, we discuss how current barriers can be overcome to enable future clinical applications of deep learning. © 2023 by the authors.

Adaptive Semantic Video Conferencing for OFDM Systems

Video conferencing has become more common than ever due to the COVID-19 pandemic, which makes high-resolution video transmission a pressing issue. Although semantic video conferencing (SVC) has achieved a great success to improve the transmission efficiency by only transmitting some key-points to represent changed expressions, its performance can still be improved by adapting to varying channel scenarios, which is lack of study when designing the whole SVC in the end-to-end manner. In this paper, we first establish a standard SVC-OFDM system. Then, the receiver part of the SVC is added with an adaptive network called Switch-SVC for varying channels and improve the accuracy of the received keypoints. Some parameters in Switch-SVC are trained online so that the receiver can adapt to the current environment. Simulation results show that the proposed method can greatly improve the keypoint reconstruction performance compared to the traditional SVC-OFDM receiver without online training. © 2022 IEEE.

Leveraging virtual reality (VR) for sports public relations and sports journalism: qualitative analyses of VR content productions for 'Russia 2018' and 'Qatar 2022' FIFA World Cups

Advancements in experiential media (EM) technologies, particularly virtual reality (VR), a subset of EM, can transform the ways public relations (PR) professions tell stories about a brand, organization, or mega-events. In the context of sports, PR content productions utilize various qualities of EM to offer immersive at-home, arena-like experiences for sports spectators. However, considering the novelty of such EM tools, limited studies have focused on how and the extent to which PR and sports journalistic content productions use VR technologies. In this qualitative content analysis, we examine how and the extent to which VR is utilized in pre-game YouTube VR contents produced for the FIFA World Cups 2018 and 2022. We analyzed YouTube VR contents produced by Russia Today (RT) in the buildup to 'Russia 2018' hosted by Russia, in comparison with pre-game YouTube VR contents produced by the Road To 2022, in view of the upcoming 'Qatar 2022'. Through qualitative analyses, we identified four broad thematic categories: stadium design, technology, facilities, and locality, as well as many sub-themes through observations and memos from all the seventeen YouTube VR content productions considered for the study. This study adds to the theoretical discussions on the role VR plays in sports journalism and sports PR and provides practical recommendations on the use of virtual reality during the COVID-19 pandemic.

Design and Implementation of Pork Freshness Grading Based on Deep Learning

China is the world's largest pork production and consumption country, with the improvement of people's living standards and consumption upgrade, people's demand for fresh pork and other fresh products is stronger. With the outbreak of African Swine Fever and COVID-19 in China in the past two years, cold chain transportation of pork will replace live pigs as the main mode of pork supply chain. As one of the most important branches of machine learning, deep learning has developed rapidly in recent years and attracted extensive attention at home and abroad. In order to improve the real-time detection of pork freshness, this paper experimented with a variety of deep learning frameworks to achieve pork freshness classification. In this paper, pork freshness is divided into 5 levels according to TVB-N content, and the pictures taken are trained by different deep learning networks, including VGG, GoogLeNet and RestNet. After analyzing the training situation of each network, the advantages of different networks are absorbed and a new improved neural network is built to predict pork freshness. The final classification accuracy reached 97%, Indicating that this is a very efficient and accurate pork freshness classification method. © 2021 IEEE.

"The greedy I that gives"-The paradox of egocentrism and altruism: Terror management and system justification perspectives on the interrelationship between mortality salience and charitable donations amid the COVID-19 pandemic.

Why do people give and help others in face of their own mortality salience? The existential struggle with the awareness of death impacts the gamut of human cognition, emotion, and behavior. This multi-method research (∑N = 1,219) explains the psychosocial impact of COVID-19-related mortality salience on altruism. Drawing from terror management theory, two studies tested death-thought accessibility, mortality salience, and anxiety buffer hypotheses. Study 1 (cross-sectional survey), using structural equation modeling, confirms death anxiety and fear are predictors of powerlessness and materialism which, in turn, predict charitable donations. Study 2 (between-subjects experiment) confirms the causal effects of COVID-19-induced mortality salience on altruism. Controlling income and socioeconomic status, people in the mortality salience treatment condition indicate greater monetary donations ($), ratio of prosocial (altruistic) to proself (egocentric) spending (%), donation of time (hour), monetary valuation of time (hourly rate = $/hour), and economic value of donated time (hourly rate*hour) than the controls. These effects are mediated by powerlessness. Moderating effects of relevant individual difference factors are significant: the greedier, more selfish, narcissistic, materialistic, and system-justifying the donor is, the higher monetary donations, volunteer time, and perceived value of donated time are, only when the COVID-19-induced mortality is made salient but not in the controls. Environmental and dispositional factors jointly influence vulnerability to mortality salience. The paradox of egocentrism and altruism, as an evolutionarily adaptive protective buffer against existential insecurity for social and cultural animals, can help revitalize resilience, thus shedding some lights on the sociopsychological mechanism of consumers' subjective well-being. Implications for consumer affairs, social marketers, and policymakers are discussed.

“They bought it, therefore I will buy it”: The effects of peer users' conversion as sales performance and entrepreneurial sellers' number of followers as relationship performance in mobile social commerce

Drawing from social learning theory and the mobile advertising literature on key performance indicators (KPIs), two experiments examined the influence of peer users' conversion in mobile social commerce. Experiment 1 (N = 211, between-subjects [high vs. low number of “sold items”]) tested the effects of peer users' conversion, operationalized as the number of “sold items” in the seller's profile, on the seller-and-profile-related outcomes. The main effect of peer users' conversion was found such that high conversion induced greater cognitive and affective appraisals, higher seller credibility, a more positive profile attitude, greater perceived entrepreneurial talent of the seller, and stronger social commerce conversion intentions. The mediating effect of social learning (mainly affective appraisal) was found. Experiment 2 (N = 348, 2 [high vs. low number of “sold items”] x 2 [high vs. low “followers”] between-subjects factorial design) showed the interaction effects of the number of “sold items” (seller's sales performance) and the number of “followers” (seller's relationship performance) on cognitive and affective appraisals, seller credibility, and profile attitude. Moderated mediation analyses revealed that peer users' conversion exerts a positive impact on the outcome variables through cognitive and affective appraisals when the number of followers is high but not when it is low. © 2022 Elsevier Ltd

Reconceptualising Youth Poverty through the Lens of Precarious Employment during the Pandemic: The Case of Creative Industry

Risks of youth poverty in relation to employment have largely been overlooked both internationally and locally, especially amid the COVID-19 pandemic. Moving beyond the concepts of income, economic factors and in-work poverty as applied to the general population, we examine the multi-scalar employment risk confronting highly educated working youth (aged eighteen to twenty-nine) in Hong Kong by assessing the intersection of precarious employment and in-work poverty, which is crucial to understanding youth poverty. Drawing on in-depth interview research on creative workers, this study calls for the reconceptualisation of in-work poverty through the lens of precarious employment, which is not viewed as a separate economic entity, but as an organic whole encompassing a multi-scalar risk in economic, social, psychological and political terrains generating an existential problem shaping young people's sense of future and work-life meaning. This article sheds light on the policy implications of high-educated youth suffering from in-work poverty in the creative industry.

Classification of COVID-19 in CT Scans Using Image Smoothing and Improved Deep Residual Network

The global spread of coronavirus disease has become a major threat to global public health. There are more than 137 million confirmed cases worldwide at the time of writing. The spread of COVID-19 has resulted in a huge medical load due to the numerous suspected examinations and community screening. Deep learning methods to automatically classify COVID-19 have become an effective assistive technology. However, the current researches on data quality and the use of CT data to diagnose COVID-19 with convolutional neural networks are poor. This study is based on CT scan data of COVID-19 patients, patients with other lung diseases, and healthy people. In this work, we find that data smoothing can improve the quality of CT images of COVID-19 and improve the accuracy of the model. Specifically, an interpolation smoothing method is proposed using the bilinear interpolation algorithm. Besides, we propose an improved ResNet structure to improve the model feature extraction and fusion by optimizing the structure of the input stem and downsampling parts. Compared with the baseline ResNet, the model improves the accuracy of the three-class classification by 3.8% to 93.83%. Our research has particular significance for research on the automatic diagnosis of COVID-19 infectious diseases. © 2021, Springer Nature Switzerland AG.

Bone Marrow versus Peripheral Blood Grafts for Haploidentical Hematopoietic Cell Transplantation with Post-Transplantation Cyclophosphamide.

In the coronavirus disease 19 (COVID-19) pandemic era, the number of haploidentical hematopoietic cell transplantations (HCTs) with peripheral blood (PB) grafts increased significantly compared with HCTs with bone marrow (BM) grafts, which may be associated with adverse outcomes. We compared outcomes of HCT in BM graft and PB graft recipients age ≥18 years with hematologic malignancies who underwent T cell- replete haploidentical HCT and received graft-versus-host disease (GVHD) prophylaxis with post-transplantation cyclophosphamide, tacrolimus, and mycophenolate mofetil. Among the 264 patients, 180 (68%) received a BM graft and 84 (32%) received a PB graft. The median patient age was 50 years in both groups. The majority (n = 199; 75%) received reduced-intensity conditioning. The rate of acute leukemia or myelodysplastic syndrome was higher in the BM graft recipients compared with the PB graft recipients (85% [n = 152] versus 55% [n = 46]; P < .01). The median times to neutrophil and platelet engraftment and the incidence of grade II-IV and grade III-IV acute GVHD (aGVHD) were comparable in the 2 groups. Among the patients with grade II-IV aGVHD, the rate of steroid-refractory aGVHD was 9% (95% confidence interval [CI], 5% to 18%) in the BM group versus 32% (95% CI, 19% to 54%) in the PB group (hazard ratio [HR], 3.7, 95% CI, 1.5 to 9.3; P = .006). At 1 year post-HCT, the rate of chronic GVHD (cGVHD) was 8% (95% CI, 4% to 13%) in the BM group versus 22% (95% CI, 14% to 36%) in the PB group (HR, 3.0; 95% CI, 1.4-6.6; P = .005), and the rate of systemic therapy-requiring cGVHD was 2.5% (95% CI, 1% to 7%) versus 14% (95% CI, 7% to 27%), respectively (HR, 5.6; 95% CI, 1.7 to 18; P = .004). The PB group had a significantly higher risk of bacterial and viral infections, with no appreciable advantage in the duration of hospitalization, immune reconstitution, relapse, nonrelapse mortality, or survival. Our data suggest a benefit of the use of BM grafts over PB grafts for haplo-HCT.

A city of exceptional risks? A critical policy analysis of Hong Kong unemployment insurance

The COVID-19 pandemic engenders unemployment risks globally and locally. Reflectively engaging in Beck's risk society debates, this paper critically reviews the discursive effects of „risks“ when employed by the government in debates about unemployment insurance since the 1997 sovereignty handover. We break down the concept of risk into four layers: moral risk, financial risk, socio-economic risk and political risk and bring to light the contradictory outcomes that colour the nuanced attitudes among the state, the NGOs and the affected subjects. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Telemedicine Utilization and Perceptions of Multiple Sclerosis Health Care Providers

Background: Many patients with MS (PwMS) are separated by geographic distance and disability from MS clinical centers in the US with 30% not receiving specialty MS care. Telemedicine, defined broadly as the use of telehealth technologies to provide clinical care when distance separates patients and providers, has the potential to fill some of the gap in the provision of specialty MS services. The COVID-19 pandemic has forced providers to use telemedicine for most outpatient care to maintain social distancing. Objectives: To obtain a representative sample of opinions on the use of telemedicine among a diverse group of providers involved in the care of PwMS. Methods: A 34 question survey was created after reviewing the literature and piloting a set of questions with a small group of PwMS. The survey was placed on the Qualtrex web-platform, and then distributed to a multidisciplinary group of MS providers across the US. Responses were analyzed using Qualtrex web-analytical software and SAS. Results: A total of 100 participants signed on and began answering the survey with 91 completing the full survey. The breakdown of providers was: neurologists (40.7%), nurse practitioners and Physicians Assistants (28.6%) nurses (14.3%), Psychologist/Neuropsychologist (7.7%), Social Workers (3.3%), Physiatrist 2.2%, Physical Therapist, Occupational therapist, and Pharmacist 1.1% each. The survey was open from November 2019 until September 2020. The majority of providers (75.8%) indicated they used telemedicine to care for PwMS with clinical video telemedicine (CVT) 87% being the most common platform, followed closely by telephone telemedicine 71%. Conversely, other forms of telemedicine were employed more rarely: store and forward telemedicine (10.1%) and remote patient monitoring (1.4%). The rate of telemedicine utilization increased from 15% of practice encounters pre-COVID-19 pandemic to 72.8% of encounters during the COVID-19 pandemic. 92.8% of respondents were very or somewhat satisfied with their last telemedicine visit and 94.2% of providers reported a desire to continue to use telemedicine. The most common drawback of telemedicine was not being able to complete a full neurological exam according to 84.6% of respondents. Conclusions: MS health care providers predominately utilized CVT as their main form of telemedicine and were satisfied with its use. There was an increase in CVT and telephone-based platforms during the COVID-19 pandemic and more limited use of other forms of telemedicine. telemedicine can provide a valid alternative to in person visits. Further study is needed to evaluate how opinions on telemedicine have continued to evolve as providers become more and more accustomed to its use and what barriers may exist that are limiting the utilization of store and forward and remote patient monitoring.

Quantitative Analysis on the Communication of COVID-19 Related Social Media Rumors

The outbreak of the COVID -19 pandemic is accompanied by numerous rumors spreading on the social media platform, which seriously affects the stability of society and the safety of public. Existing quantitative analyses of COVID -19 related social media rumors only focus on single element of communication, such as content, while ignoring other basic elements of communication, including communicator, audience, and effect. Besides, compared with the real social media rumor data, the rumor data of these studies have distribution bias and lack of information. Therefore, we conduct a more comprehensive quantitative analysis on the communication of COVID -19 related social media rumors based on the Sina Weibo platform. Specifically, we first analyze the communication content of rumors, including the analysis of the topic, involved regions, event tendency and sentiment. Further, we investigate the users engaged in rumor communication and divide the users into three categories, namely, rumor posters, rumor spreaders, and rumor informers. We explore the basic attributes, topic preferences, individual sentiments, and self-network characteristics of the engaged users. Finally, we study the public opinion triggered by rumors, including the overall sentiment distribution, its correlation with topics, keywords and regions, as well as the evolution of sentiment. To conclude, this study first quantitatively analyzes COVID -19 related social media rumors from the perspective of different basic elements in communication. It provides a more comprehensive and profound understanding of COVID -19 related social media rumors and is of great value for both research and management of rumor in public emergencies. © 2021, Science Press. All right reserved.

Age cohorts stratified according to age-distributions of COVID-19 lymphocytopenia in COVID-19 patients without comorbidities on admission

If age boundaries are arbitrarily or roughly defined, age-related analyses can result in questionable findings. Here, we aimed to delineate the uniquely age-dependent immune features of coronavirus disease 2019 (COVID-19) in a retrospective study of 447 patients, stratified according to age distributions of COVID-19 morbidity statistics into well-defined age-cohorts ( 2-25y, 26-38y, 39-57y, 58-68y, and 69- 79y). Agedependent susceptibilities and severities of the disease were observed in COVID-19 patients. A comparison of the lymphocyte counts among the five age- groups indicated that severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infection led to age-dependent lymphopenia. Among the lymphocyte subsets, the CD8(+) T cell count alone was significantly and age-dependently decreased (520, 385, 320, 172, and 139 n/ mu l in the five age-groups, respectively). In contrast, the CD4(+) T cell, B cell, and natural killer cell counts did not differ among age-cohorts. Age and CD8(+) T cell counts ( r=.0.435, p<0.0001) were negatively correlated in COVID- 19 patients. Moreover, SARS-CoV-2 infection age-dependently increased the plasma C-reactive protein concentrations (2.0, 5.0, 9.0, 11.6, and 36.1 mg/L in the five age-groups, respectively). These findings can be used to elucidate the role of CD8+ T cells in age-related pathogenesis and to help develop therapeutic strategies for COVID-19.

Telemedicine utilization trends among patients with multiple sclerosis and controls in the United States Veterans Health Administration: 2008-2020

Background: Patients with multiple sclerosis (PwMS) face barriers accessing specialty care for evaluation and treatment. Recently, clinical medicine in the U.S. has been transformed by the COVID- 19 pandemic and social distancing measures have fueled a transition to non-face-to-face visits as a means of providing patient care. Telemedicine is an important tool to help fill this gap. Objectives: The goal of this analysis is to use a large U.S. population- based administrative dataset to evaluate telemedicine utilization and determine intra- and inter-county variation of telemedicine utilization among PwMS and controls between 2008 and 2020. We will also examine health disparities in telemedicine utilization among PwMS to identify at-risk patient populations. Methods: We conducted a population-based nested case-control study with a large cohort of PwMS in the VA healthcare system between 2008-2020. A validated algorithm was used to identify MS cases which were matched to controls (n=5) on age, sex and location at entry to VA. Utilization of telemedicine was assessed annually from 2008-2020 for cases and controls. Records were evaluated to show demographic variability in the study cohort and estimate odds ratios for any telemedicine utilization and subtype of telemedicine utilization using conditional logistic regression. Results: The number of MS cases and controls was 16,788/74,044 (case/control) in 2008 and slowly increased to 26266/143087 in 2020. Overall, telemedicine utilization increased for both MS cases and controls over the study period (2008-2020), but PwMS had consistently higher annual telehealth encounter rates compared to controls. Conditional logistic regression analyses revealed increased adjusted odds ratio for telemedicine utilization for 2010 (aOR=1.26 95% CI: 1.18-1.33), 2016 (aOR=1.65 95% CI: 1.51-1.80), and 2020 (aOR=2.06 95% CI: 1.78-2.40) after adjusting for county and census tract-level social determinants of health. Specific geographic regions for higher telemedicine use included eastern and west coast metropolitan regions. Poverty, crowded housing, race/ethnicity, living in a rural environment, and being enrolled for medical care in 2020 during the CoVID-19 pandemic were independently associated with higher odds of telemedicine utilization. Conclusions: PwMS have high utilization rates of telemedicine within the VA healthcare system with large increases in 2020. Our data demonstrate inter-county variation in telemedicine by key epidemiological risk factors, with a clustering of counties in certain states, allowing better characterization and support for PwMS with high telemedicine use. Further research is required to understand barriers and benefits in telemedicine and how telemedicine can optimize the healthcare for PwMS.