Role of artificial intelligence on green economic development: Joint determinates of natural resources and green total factor productivity

The energy consumption structure is now shifting from using fossil fuels to using renewable energy. Thus it is crucial to research if decreasing energy use can genuinely boost green total factor productivity (GTFP) and how to reconcile the link between reducing energy consumption and GTFP using various technical approaches. This study proposes the two-way influence of Artificial Intelligence (AI) and natural resources market on GTFP. It comprehensively evaluates the effects of AI on green economic development using the instance of China and a pertinent mathematical model. We found that the impacts of AI on carbon intensity vary between industries and developmental phases. Compared to the 11th Five-Year Plan, AI significantly reduced carbon intensity during the 12th. Compared to capital-intensive businesses, labor- and technology-intensive industries likely have a more significant drop in carbon intensity due to AI and natural resources market.

How Type of Office Visit Influences Attitudes and Preferences for Telemedicine?

Introduction: The COVID-19 pandemic caused significant changes in delivery of healthcare. Telemedicine emerged as a popular option. Numerous studies demonstrate a favorable opinion of telemedicine from patient and physician perspectives. What factors make it more efficient and effective This study explores how type of office visit impacts attitudes towards telemedicine and affects patient's preferences for future visits. Method(s): Surveys were delivered by mail or in person to 1,100 randomly selected patients of Sierra Nevada Gastroenterology, a community-based practice in Grass Valley, CA. Each patient (pt) had a telemedicine visit (TMV) from April 2020-October 2021. Three hundred twenty surveys were returned completed. Surveys contained a 5-point Likert scale set of questions rating the quality, communication, compassion, thoroughness and convenience of TMV. In person visits (IPV) were then directly compared to TMV for the same qualities. Demographics were recorded (Table 1). Surveys were separated into 3 categories based on type of visit: new complaint (NC), follow-up of existing problem (FU), procedure-related visit (PRV). Statistical analysis and chi-square test were used to determine statistical significance. Result(s): Quality, communication, thoroughness and compassion during TMV rated high with Likert scores of 4.3-4.7 (= 0 strongly agree) for all groups. Comparing the 3 groups (NC, FU, PRV) with chi-square testing, no statistical difference in ratings was seen. FU pts had the highest Likert scores in all categories. Pts with new complaints preferred IPV over TMV for quality, communication, thoroughness and compassion, which was rated statistically significantly higher (P< 0.05). TMV was favored for convenience in all groups with highest ranking in FU pts (73%). Conclusion(s): This study showed type of office visit did not affect satisfaction or ratings of TMV. However, type of visit did reveal preferences for either IPV or TMV. Pts with NC preferred IPV and felt compassion is important and delivered more effectively in person. This suggests non-verbal communication such as body language, facial expression and tone is conveyed more effectively in person than over phone or video calls. FU or PRV pts rated TMV as more convenient and preferable over IPV for future visits, suggesting that pts with stable or less acute problems prioritize convenience over other factors when selecting type of visit. Further studies are needed to determine what other factors will influence and improve quality of TMV.

Does financial inclusion index and energy performance index co-move?

Financing strategies and energy performance have been extensively studied previously, and researchers frequently overlook the co-movements of integration of financial inclusion and energy performance index in the E7 Context. To address this gap, current research estimates the co-movement between the financial inclusion index and sustainable energy performance index to reflect the consequences of the COVID-19 crisis. Our findings show that in E7 economies, China exceeds the other nations in terms of energy performance. With a steady score, Russia is second in the group. Indonesia and Turkey are respectively fourth and fifth, and their total results show excellent prospective performances for sustainability. Mexico and Brazil follow this ranking with bad results and the lowest scores reported in the study results. The study findings are helpful for policy formulation and assessment. The study presented recommendations about financial inclusion and energy management practices in COVID-19 and delivered insights about the energy performance index in E7 economies. © 2023 Elsevier Ltd

An Exploration of a Novice Kindergarten Teacher's Enactment of Multiliteracies Pedagogy during the Pandemic: A Case Study of a Virtual Kindergarten Classroom

We aim to gain insight into technology-enhanced literacy learning for kindergarten students during the COVID-19 pandemic by exploring a novice kindergarten teacher's practice of multiliteracies pedagogy in his virtual kindergarten classroom. This qualitative case study collected data from multiple sources such as virtual interviews and classroom observations, the Kindergarten Program (KP) document, teacher's reflective notes, lesson plans, students' artefacts, and researchers' observational notes and reflective journals. This study found that although the novice kindergarten teacher provided various multimodal learning opportunities for students, his literacy practice emphasized phonological awareness, phonemic awareness, and letter-sound correspondence. Also, he faced numerous challenges due to inadequate teacher preparation and professional development, inconsistency of the quality and utility of technology, constraints of virtual learning for young learners, varying degrees of parental support, and challenges of implementing multiliteracies pedagogy with young children virtually. This study contributes to the existing literature on online learning for kindergarten students and expands the burgeoning multiliteracies research from physical to virtual learning environments. Also, this study demonstrates how virtual learning opens up opportunities to advance the multiliteracies pedagogy and highlights the importance of strengthening teacher education programs and providing continuous professional development for teachers. © 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings.

Evaluating economic recovery by measuring the COVID-19 spillover impact on business practices: evidence from Asian markets intermediaries

The COVID-19 outbreak significantly affected the global economy and energy markets. To mitigate the shock, maintain financial market stability, and encourage economic recovery, this study investigates the influence of post-COVID-19 on monetary policy transmission to business practices and financial market indicators for green economic recovery. We utilised 37 Asian markets' panel data from 1 January 2020, through 30 December 2020. The empirical findings demonstrate that the pandemic's emergence impeded monetary policy transmission, business practices, and financial markets. Our empirical contribution is to examine the size, sectoral allocation, and implementation options of three leading countries' (China, Japan, and Thailand) green recovery spending plans, which range significantly. However, this effect mainly affects the medium-and-long-term effects, and short-term spillover effects are primarily unaffected by Asian monetary policy uncertainty. Our findings have significant implications for green economic recovery among market players and regulators in the Asian market.

Demographic and clinical characteristics of pediatric COVID-19 in Arkansas: March-December 2020.

The COVID-19 pandemic reached the United States in early 2020 and spread rapidly across the country. This retrospective study describes the demographic and clinical characteristics of 308 children presenting to an Arkansas Children's emergency department (ED) or admitted to an Arkansas Children's hospital with COVID-19 in the first 10 months of the COVID-19 pandemic, prior to the emergence of clinically significant variants and available vaccinations. Adolescents aged 13 and older represented the largest proportion of this population. The most common presenting symptoms were fever, gastrointestinal symptoms, and upper respiratory symptoms. Patients with multisystem inflammatory syndrome in children (MIS-C) had a longer length of stay (LOS) than patients with acute COVID-19. Children from urban zip codes had lower odds of admission but were more likely to be readmitted after discharge. Nearly twenty percent of the study population incidentally tested positive for COVID-19. Despite lower mortality in children with COVID than in adults, morbidity and resource utilization are significant. With many Arkansas children living in rural areas and therefore far from pediatric hospitals, community hospitals should be prepared to evaluate children presenting with COVID-19 and to determine which children warrant transport to pediatric-specific facilities.

NON-ENGLISH LANGUAGE PROFICIENCY AND ENGAGEMENT WITH OUTPATIENT SPECIALTY MEDICAL CARE FOLLOWING ICU ADMISSION FOR COVID-19: A RETROSPECTIVE COHORT STUDY

SESSION TITLE: Post-COVID-19 Outcomes SESSION TYPE: Rapid Fire Original Inv PRESENTED ON: 10/19/2022 11:15 am - 12:15 pm PURPOSE: Minority populations, including non-English language proficient individuals, experience a disproportionate burden of morbidity and mortality from COVID-19.1,2 While these same populations have historically experienced disparities in critical illness, less is known about disparities in post-acute care following critical illness3. Here, we investigate if non-English language proficiency is associated with differential access to dedicated post-COVID-19-clinic care among intensive care unit (ICU) survivors. METHODS: We retrospectively collected demographic (self-identified), clinical, and utilization data from electronic health records for all patients with COVID-19 admitted to an ICU at three Mass General Brigham hospitals between March 11-May 31, 2020. We performed multivariable logistic regression, adjusting for age, gender, race and ethnicity, insurance status, area deprivation index (a marker of geographic socioeconomic deprivation), medical comorbidities, and discharge destination, to examine if non-English language proficiency, defined as “Needs Interpreter” in the medical record, was associated with access to outpatient post-COVID care (composite of dedicated post-ICU pulmonary, neurology, or physical medicine and rehabilitation clinic visit). RESULTS: Of 481 patients in our cohort, 61% (n=292) survived to one month after hospital discharge. The majority (71.2%) were discharged to a facility. Within 12 months after discharge, most patients had at least one primary care visit (84.7%), but far fewer were seen in a dedicated post-COVID clinic (27.1%). In multivariable analyses, non-English language proficiency was associated with no difference in primary care follow up (adjusted OR = 0.83, 95% CI 0.30-2.25, p=0.71), but was associated with decreased odds of a dedicated post-COVID clinic visit (aOR = 0.73, 95% CI 0.61-0.87, p < 0.001). CONCLUSIONS: Although we identified no difference in access to primary care, non-English language proficiency was associated with decreased odds of visiting a dedicated post-COVID clinic. Further research is needed to understand the system, provider, and patient factors contributing to these disparities and how to decrease barriers to subspecialty care among non-English language proficient ICU survivors. CLINICAL IMPLICATIONS: As the number of COVID-19 critical illness survivors increase, it will become increasingly important to not only develop multi-disciplinary interventions to support their recovery, but also ensure equity in access to these services. In our cohort of ICU survivors, we identified no difference in access to primary care according to preferred language language, but decreased odds of access to post-COVID clinics among survivors with non English language proficiency, pointing towards a need for further research to understand and mitigate these disparities. DISCLOSURES: No relevant relationships by George Alba No relevant relationships by Lisa Bebell No relevant relationships by Leslie Chang No relevant relationships by Nupur Dandawate No relevant relationships by Alexander Gavralidis No relevant relationships by Patrick Gordan no disclosure on file for Kathryn Hibbert;No relevant relationships by Cher Huang No relevant relationships by Sirus Jesudasen no disclosure on file for Aran Kadar;no disclosure on file for Peggy Lai;No relevant relationships by Emily Moin No relevant relationships by Daniel Okin Consultant relationship with United Therapeutics Please note: 1 day Added 04/03/2022 by Alison Witkin, value=Consulting fee

Facial mask detection system based on YOLOv4 algorithm

This paper mainly addresses the detection of facial mask wear under the new COVID-19. To meet this demand, this paper performs facial mask wear detection on specific targets through a model trained based on the YOLOv4 algorithm. It has the characteristics of fast detection and light weight, and the application of this system to daily mask wear detection requires high real-time system performance. YOLOv4 meets this requirement, so the system designed based on this model has practical significance. This paper further demonstrates that the facial mask detection system designed based on the YOLOv4 algorithm is capable of working in multiple scenes of daily life, successfully detecting whether the target is wearing a mask in many scenes such as routine, multi-person and occlusion environment. © 2022 IEEE.

Hope for Resuming Our In-Person Events [President's Message]

The hybrid format of IEEE Applied Power Electronics Conference and Exposition (APEC) 2022, held 20-24 March in Houston, Tx, USA, was a refreshing change from the virtual conferences of the last two years due to the COVID-19 pandemic. Thanks to the tremendous efforts of hundreds of organizers and volunteers, APEC 2022 signals the return to our in-person events. It was a joyful reunion of IEEE Power Electronics Society (PELS) members, volunteers and exhibitors. The breakfast event of 'WiE, YP, and You: How to become involved with PELS and PSMA too' was a huge success, the fruit of the tireless work of the PELS Women in Engineering (WiE) and Young Professionals (YP) Committees. You can find detailed materials including FAQs of many programs of the PELS, prepared by dozens of PELS volunteers on the WiE events website: https://www.ieee-pels.org/membership/wie/wie-events. The 'YP Reception at APEC 2022' cosponsored by PELS and Industry Applications Society (IAS) attracted over 100 young professionals and students to a social gathering at The Grotto, Houston. Our hybrid Spring Administrative Committee (AdCom) Meeting and several PELS standing committee meetings held during APEC 2022 presented a venue for our volunteers and friends to catch up. © 2014 IEEE.

Augmenting Convolution Neural Networks by Utilizing Attention Mechanism for Knowledge Tracing

The devastating, ongoing Covid-19 epidemic has led to many students resorting to online education. In order to better guarantee the quality, online education faces severe challenges. There is an important part of online education referred to as Knowledge Tracing (KT). The objective of KT is to estimate students’ learning performance using a series of questions. It has garnered widespread attention ever since it was proposed. Recently, an increasing number of research efforts have concentrated on deep learning (DL)-based KT attributing to the huge success over traditional Bayesian-based KT methods. Most existing DL-based KT methods utilize Recurrent Neural Network and its variants, i.e. Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) etc. Recurrent neural networks are good at modeling local features, but underperforms at long sequence modeling, so the attention mechanism is introduced to make up for this shortcoming. In this paper, we introduce a DL-based KT model referred to as Convolutional Attention Knowledge Tracing (CAKT) utilizing attention mechanism to augment Convolutional Neural Network (CNN) in order to enhance the ability of modeling longer range dependencies. © 2022, IFIP International Federation for Information Processing.

Study on the Correlation Between Indoor Light Environment and Human Fatigue

Due to the continuing impact of COVID-19, people spend an increasing amount of time on working or studying from home. The indoor light environment became quite important since it can affect people's physical and mental health. In order to reduce human fatigue resulting from continuous indoor working or studying and to improve work efficiency, and also hope to contribute to the research of indoor light environment design, this paper explores the correlation between indoor light environments and fatigue. Through laboratory simulation of indoor light environment. Participants are asked to complete the task stimulation test and filled in the subjective fatigue questionnaire with three different illumination levels. Their EEG (ElectroEncephaloGraphy), eye movement, and other physiological data are also monitored at the same time. The participants’ fatigue degree is statistically analyzed under the 300 lx, 570 lx, and 870 lx illumination. The results showed that the lighting environment has a strong correlation with human fatigue. Fatigue degree varies the most from 570 to 870 lx. There is a largest error rate gap of task test up to 20% under 300 lx and 870 lx illumination. As the illuminance increases, the fatigue degree has a visible trend of increase as well, and it is the most obvious under the 870 lx illumination. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Ear Talk Project: Participatory co-composition on YouTube and the Web

In this article, we present Ear Talk - a co-composition and live performance project that enables remote music collaboration through technologically mediated systems. The Ear Talk project currently exists in two distinct implementations, one that repurposes YouTube's live-streaming technology, and one that utilises a stand-alone website. Although Ear Talk was conceived prior to the 2020 COVID-19 pandemic, the necessity for remote collaboration became more apparent during the lockdown, when a vast majority of live events and music concerts were cancelled. The Ear Talk project enables a socially distanced form of online musical collaboration and offers a platform through which to respond to such a crisis, and has grown to be adopted and presented by many different performing groups across the world. In addition to describing the technical implementations of these two systems, we discuss issues that arise from our participatory practice: from musical quality concerns in regard to social aesthetics and artistic ingenuity, to accessibility concerns when designing technologically mediated collaborative systems. Ear Talk embraces continuous musical loops as well as highly asynchronous (i.e., perpetual) collaborative paradigms among remote participants, which raises a conceptual inquiry as to which part of its sonic and social experience constitutes music in the end. Finally, we evaluate performer-audience relationships (i.e., hierarchical versus horizontal interactions) and the efficacy of the Ear Talk systems at enabling socially engaged co-composition.

Towards Accurate and Lightweight Masked Face Recognition: an Experimental Evaluation

Given the current COVID-19 pandemic, most people wear a mask to effectively prevent the spread of the contagious disease. This sanitary measure has caused a significant drop in the effectiveness of current face recognition methods when handling masked faces on practical applications such as face access control, face attendance, and face authentication-based mobile payment. Under this situation, recent efforts have been focused on boosting the performance of the existing face recognition technology on masked faces. Some solutions trying to tackle this issue fine-tune the existing deep learning face recognition models on synthetic masked images, while others use the periocular region as a naive manner to eliminate the adverse effect of COVID-19 masks. Although the accuracy of masked face recognition remains an important issue, in the last few years, the development of efficient and lightweight face recognition methods has received an increased attention in the research community. In this paper, we study the effectiveness of three state-of-the-art lightweight face recognition models for addressing accurate and efficient masked face recognition, considering both fine-tuning on masked faces and periocular images. For the experimental evaluation, we create both real and simulated masked face databases as well as periocular datasets. Extensive experiments are conducted to determine the most effective solution and state further steps for the research community. The obtained results disclose that fine-tuning exiting state-of-the-art face models on masked images achieves better performance than using periocular-based models. Besides, we evaluate and analyze the effectiveness of the trained masked-based models on well-established unmasked benchmarks for face recognition and asses the efficiency of the used lightweight architectures in comparison with state-of-the-art face models. Author

PERCEPTIONS OF TELEMEDICINE OFFICE VISITS DURING THE COVID-19 PANDEMIC

The COVID-19 pandemic has dramatically changed the way physicians interact with patients. During the pandemic numerous constraints were implemented to reduce the risk of transmitting the virus. Telemedicine, defined as either phone or video calls, emerged as a replacement to in-person office visits. Prior to the pandemic 8% of physician offices used telemedicinetools as compared to 84% today. Previous studies have reported favorable patient impressions of telemedicine visits. This study defined which aspects of the interactions were favorable, determined factors influencing opinion, compared telemedicine quality directly to in-person visits and determined preferences for future visits. METHODS Surveys were delivered by mail or in person to 1000 randomly selected patients (pts) of Sierra Endoscopy Center and Sierra Nevada Gastroenterology Medical Assoc, a community based gastroenterology practice in Grass Valley, CA. Each pt had a telemedicine visit (TMV) from April 1-Aug 30, 2020. 330 surveys were returned. Surveys contained a 5 point Likert scale set of questions rating the quality, communication effectiveness, physician compassion/empathy, thoroughness and convenience of the visit. TMV was directly compared to in person visits (IPV) for the same qualities, as well as future preference. Demographics, distance from office, insurance, employment status, previous experience with office and reason for office visit were recorded. RESULTS Overall satisfaction with quality of TMV=4.5 on Likert scale, 5 being strongly agree. Satisfaction with communication=4.7, physician compassion/empathy=4.6,thoroughness= 4.3, convenience=3.8. Acceptance of future TMV=4.0. Direct comparison of TMV to IPV significantly favored in person in overall quality (78 vs 12 vs 10% either), communication (66 vs 20%), physician compassion (73 vs 11%), thoroughness (69 vs 14%). TMV rated higher in convenience (67 vs 29%). Preference for future visits was 48% in person and 46% TMV. Distance >20miles preferred TMV. Retirees and age >70yo strongly favored IPV. DISCUSSION Previous studies have reported high pt satisfaction with TMV. This study supports those findings but also shows a strong preference for in-person visits when comparing quality, communication, compassion and thoroughness. Distance >20 miles favored TMV, whereas retirees and age >70yo favored IPV. Choice for future visits were fairly equally divided between telemedicine and in-person, with telemedicine preferred in 46% of pts. This may be due to a desire for convenience and a concern about the increased risk of exposure to COVID-19 inherent to an in-person office visit. We speculate that when the pandemic resolves, a majority of pts will prefer to resume in-person visits while some will prefer to continue telemedicine.. Further studies are needed to determine the future role of telemedicine in patient care.(Table Presented) (Table Presented) (Figure Presented)

Impact of Green Financing on Carbon Drifts to Mitigate Climate Change: Mediating Role of Energy Efficiency

Climate change mitigation (CCM) has not been mainly understood and assessed in the terms of carbon drifts persisting at provincial level of China, and to respond the question that how green financing is better financing option for CCM. Thus, our study intends to test the role of green finance on carbon drifts to manage for the mitigation of climate change. For this, unit root test and panel co-integration technique is applied. Study findings reported that the intricate connection between place-and-time-specific GHG emission reduction responsibilities is significant with 18% and the 'production', trading and consumption of carbon allowances with 21% and offsets across vast time-space stretches related carbon drift is significant with 19.5% for climate change mitigation. For such significance, green financing is found imperative indicators which is significant at 27.1% with carbon drifts, and mitigates the climate change with 31.3%, which is, relatively high than usual climate change control practices. Our study also provides detailed policy implication on this topicality for associated stakeholder.

Impact of sample pooling strategy on 2019-nCoV RNA detection results

Objective: To evaluate the impact of sample pooling strategy on 2019-nCoV RNA detection results. Methods: Ten negative swabs were stored in 6 ml virus transport medium, mixed thoroughly and diluted 1:2 and 1:10. Inactivated 2019-nCoV culture medium was added to simulate pooling samples: 10 pooling samples, 5 pooling samples and 1 swab sample. Extraction and amplification were made using three nucleic acid extraction reagents a, b, and c with different extraction methods and systems, as well as five 2019-nCoV detection reagents A-E with various template loading volumes and sensitivities respectively. Results: For the same sample, the Ct values of extracted templates a were 2.10±0.47 and 3.46±0.62 earlier than extracted templates b and c. For samples with identical amplifying, the Ct valves of N and ORF1ab gene of A reagent were 1.16±0.48 and 2.36±0.54 earlier than that of reagent B. Adding nucleic acid of 10 negative swabs to the amplification system lagged the Ct values of reagent A by about 1.36±0.32 Ct, while Ct values of reagent B were not affected. Extracted by regent a, a lag of 1.66±0.39 Ct on average was observed in C, D, and E reagents in detecting pooling samples of ten swabs as compared with one swab sample. When extracting 400 copies/ml pooling samples of ten swabs by reagent a, N gene could be detected by reagents C and E, but not by reagent D. Conclusion: Large amount of extraneous DNA is introduced by sample pooling, which could interfere the effiency of extraction and amplification. Strategies of using extraction reagents with large loading volume and high effiency, together with amplification reagents with large template volume and low limit of detection are helpful for ensuring detection sensitivity of pooling samples, and greatly reducing the risk of false negative results.

Pharmacological research and clinical applications progress of Lianhua Qingwen capsules/granules in respiratory diseases

Lianhua Qingwen capsules/granules is an innovative Chinese medicine developed under the guidance of the TCM collateral disease theory. It has the efficacy of "clearing heat and removing toxin, ventilating the lungs and discharging heat". In 2003, it was approved as a new drug by the China National Medical Products Administration, through expedited approval during/SARS, and now, it has become a representative proprietary Chinese medicine for the treatment of infectious diseases of the respiratory system. Pharmacodynamic studies have revealed that LianhuaQingwen has broad-spectrum antiviral, antibacterial and anti-inflammatory, antipyretic, cough-relieving and immunoregulation effects. Clinically it has been used in the treatment of communicable and infectious respiratory diseases such as COVID-19, influenza, upper respiratory infection, pulmonary infections, acute exacerbation of chronic obstructive pulmonary disease, etc. and has achieved remarkable curative effects.