Energy-environmental-economic assessment of green retrofit policy to achieve 2050 carbon-neutrality in South Korea: Focused on residential buildings

To achieve carbon emission reduction target (CERT) by 2030 and carbon-neutrality in 2050, it is important to actively reduce the emission gap in the private building sector. However, the ongoing COVID-19 pandemic and the Russian-Ukraine war are threatening the green remodeling policy (GRP) worldwide. Therefore, this study analyzed energy consumption savings, GHG emission reduction, and net present value when applying green remodeling to a private building to predict whether or not the current GRP could achieve 2030 CERT and 2050 carbon-neutrality. The main findings are as follows. First, yearly electricity and gas consumption of 84.97 m2 type households can be reduced by 6.19% and 15.58% through green remodeling. Second, based on the energy saving, yearly GHG emission can be reduced about 0.34tCO2eq. Third, the economic feasibility of green remodeling cannot be achieved via the current policy, and NPV17 decreases up to USD-51,485 depending on the credit loan interest rate and the green remodeling interest subsidy program. In other words, it is difficult to reach 2030 CERT and 2050 carbon-neutrality via the current policy. Therefore, the South Korean government is required to reorganize financial policies, establish active systems, increase public awareness of the policy, and improve energy efficiency technology. © 2023 Elsevier B.V.

Detecting Fake News about COVID-19 Infodemic Using Deep Learning and Content Analysis

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information―both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study. © 2022,Asia Pacific Journal of Information Systems.All Rights Reserved.

Spatiotemporal trends and impact of Covid-19 lockdown on eight sewage contaminants in Brisbane, Australia, from 2012 to 2020.

This study aims to investigate the spatiotemporal trends and impact of COVID-19 lockdowns to the profile of physiochemical parameters in the influent of wastewater treatment plants (WWTPs) around Brisbane, Australia. One 24-hr composite influent sample was collected from 10 WWTPs and analyzed for a range of physiochemical parameters per week (i.e., chemical oxygen demand (COD), total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), ammonia, volatile suspended solid (VSS)) and per month (i.e., Ni and Cr) from 2012 to 2020, including the period of COVID-19 lockdowns in the region. The catchments studied were urban, with a mix of domestic and industrial activities contributing towards the contaminant profile. Statistical analysis identified that industrial and commercial land use, as well as population size had a large impact to the parameter loads and profile. Per capita mass loads of Cr in one catchment were 100 times higher than in others from one industrial point source. TP demonstrated a potential monotonic decrease over time due to practical reduction policies that have been implemented for phosphorous content in household detergents, except for one catchment where trade waste from food manufacturing industries contributed to an overall increase of 6.9%/year TP. The COVID-19 lockdown (March-April 2020) posed different impact on different catchments, either decrease (7-61%) or increase (2-40%) of most parameter loads (e.g., COD, TOC, TN, TP, VSS, Ammonia), which was likely driven by catchment characteristics (i.e., the proportion of residential, commercial, and industrial land uses). This study enhances our understanding of spatiotemporal trend of contaminants in the catchments for further effective source control.

FDA-Unet: A Feature fusional U-Net with Deep Supervision and Attention Mechanism for COVID-19 Lung Infection Segmentation from CT Images

The COVID-19 infections segmentation is a challenging task due to the high variation in shape, size and position of infections or lesions in medical images. To solve it, we propose a deep learning-based segmentation method for COVID-19 chest CT images that can automatically segment COVID-19 lung lesions. Based on the U-Net model, we introduce a feature fusion and an attention block for increasing the multi-scale feature learning capacity. Moreover, the network is also equipped with a residual block and a deep supervision mechanism to improve model segmentation accuracy and completeness rate. Experimental results show that the method has a good test effect after training, and the Dice index can reach 63.26%, which is beneficial for the diagnosis of the coronary pneumonia. © 2022 ACM.

Application of MDT mode in the diagnosis and treatment of Coronavirus Disease 2019 (COVID-19) Pneumonia

To explore the effect of Multi-Disciplinary Team (MDT) mode in the diagnosis and treatment of Coronavirus Disease 2019 (COVID-19) Pneumonia. A total of 65 patients with suspected COVID-19 pneumonia were included. On February 8, 2020, our hospital officially became a designated hospital for the treatment of COVID-19, and the MDT mode was implemented throughout the diagnosis and treatment for newly admitted patients with suspected COVID-19. The patients were divided into control group and observation group according to whether received MDT mode. Our results showed that the diagnosis time in the observation group was significantly shortened than that in the control group (2.51 days vs. 3.47 days) (p < 0.05). The average daily hospitalization costs in the observation group was significantly decreased in comparison with the control group (¥766.1 vs. ¥1190.4) (p < 0.001). The average daily cost of protective materials in the observation group was significantly reduced in comparison with the control group (¥4226.90 vs. ¥5308.20) (p < 0.001). Compared with the control group, the subjective symptoms of patients in the observation group were significantly improved (p < 0.001). In conclusion, the MDT mode shortens the diagnosis time of, reduces the hospitalization costs, and improves the subjective symptoms of COVID-19. © 2022, Sociedade Brasileira de Ciencia e Tecnologia de Alimentos, SBCTA. All rights reserved.

An improved sir model for covid-19 epidemic in Malaysia

This research study demonstrates a numerical model intended for comprehension the COVID-19 spread of the year 2020 by utilizing the improved SIR model. The paper focuses on deceased rates rather than confirmed cases. A model derived from the standard SIR epidemiological model including asymptomatic and hospitalized, is presented, but includes symptomatic and critical states as well, for better simulate real disease dynamics. A three-dimensional nonlinear differential equation is formulated and solved numerically utilizing the Runge-Kutta’s method in MS excel. It appears from the research study that, by looking at the impact of varying people contact rates in populations shown that reducing contact rates by 50%, COVID-19 should be controllable to levels like the seasonal flu. It is additionally indicated numerically that the pandemic can be reduced to a less dangerous level when there are less infected people in contact in the populace. © 2006-2021. Asian Research Publishing Network (ARPN). All rights reserved.

Research on accurate temperature control algorithm of agarose gel sol apparatus for nucleic acid detection

Affected by COVID-19, the demand for nucleic acid detection at home and abroad is gradually increasing, and nucleic acid detection generally requires qualitative analysis of PCR amplification products. At present, the commonly used analysis method of amplification products is agarose gel electrophoresis. In this paper, the whole process of agarose gel production is analyzed, and a fuzzy-neural network PID joint control scheme is proposed for different concentrations of agarose solution reagents to realize different temperature control strategies for different stages of the same concentration solution reagents and different concentration solution reagents. For the glue-making process with the same concentration of reagent, fuzzy control is used to improve the heating power when the temperature difference is large. On the contrary, the BP neural network is used to train the best PID parameter for gelatinizing at the current concentration, so as to realize the temperature control of the whole process of agarose heating and gelatinizing at different concentrations. The sol instrument experimental platform built by this algorithm realizes the glue preparation experiment of different concentration solution and the remelting experiment of the same concentration solution, which achieves the temperature control precision of ±1 ć and achieves a better glue preparation effect. © 2020 Institution of Engineering and Technology. All rights reserved.

Feasibility Analysis of COVID-19 Response Guidelines at Construction Sites in South Korea Using CYCLONE in Terms of Cost and Time

The emergence of the coronavirus disease 2019 (COVID-19) pandemic has led to a cost and time crisis for most construction projects around the world. Adherence to COVID-19 response guidelines for construction sites may prevent the occurrence of COVID-19 cases, which eliminates the risk of site closure. However, adding a disinfection process to the construction process, as mandated in COVID-19 response guidelines, increases overall construction cost and time. Conversely, however, not adding a disinfection process may result in COVID-19 cases among construction workers, which would delay construction and perhaps even cause closure of the construction site. Therefore, this study analyzed the feasibility of COVID-19 response guidelines for construction sites, especially the addition of a disinfection process, in terms of cost and time. To this end, CYClic Operations NEtwork (CYCLONE) models were developed to simulate the construction process, and a case study was conducted to validate the applicability of the suggested approach. The results showed that compliance with COVID-19 response guidelines increased the number of working days and the construction costs of the subject construction project, but because there was no more risk of construction site closure, the construction delays were short, and the liquidated damages were minimized. Through the method proposed in this study, it is possible to estimate construction cost and time before and after the COVID-19 pandemic;this method could be used to provide data for both owners and contractors to pro-actively recognize and respond to situations or damage caused by the COVID-19 pandemic. The data could also be used as evidence in case of future damages or disputes.

Determinants for competitiveness in the context of international integration pressure: Case of small and medium enterprises in emerging economy–Vietnam

This paper aims to intensively explore the factors that affect competitiveness for small and medium enterprises (SMEs) and how SMEs can improve their competitiveness in the context of an emerging economy like Vietnam. This study combined qualitative and quantitative methods and employed covariance base structural equation model (CB-SEM). The originality of this study is of great contributions including (1) Proposing the latest model for SMEs for improving their competitiveness, taking internal and external factors aggregation into consideration;(2) Research context particularly on emerging economy like Vietnam, an emerging economy with great economic and medical achievements that has received special attention from the world after a long period of fighting against the global Covid19 pandemic. More importantly, in the context of increasing competitive pressure due to global integration;(3) Deliverable of this study disclosed the overall decisive factors for firm’s competitiveness, both internal and external. More importantly, it revealed the impact mechanism of each factor to contribute to increasing firm’s competitiveness in some ways. This study provides the implications of this study are expected to make breakthrough contributions for SMEs in Vietnam to gain higher achievement, towards sustainability. Furthermore, the contributions of this study are also expected to be a valuable source of reference for SMEs in other emerging countries, as long as in similar economic settings. The findings are interested to business practitioners, economics and policy maker as an attempt to boost SMEs’ competitiveness in a systematic and sustainable manner by integrating multilevel powers of firm, industry and nation. © 2021 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

Silver lining of a very dark cloud: Telehealth virtually perfect in the COVID-19 era

Background and Aim: Public hospital outpatient departments are a critical interface between acute and specialist hospital services and primary care. Failure of patients to attend is an expensive and persistent issue worldwide, with reported did-not-attend (DNA) rates of up to 30% in some centers. Non-attendance is influenced by many factors, such as logistics in getting to the hospital, work commitments, financial hardship, transportation access, and competing health interests. Telehealth has been available for some years, but its implementation and uptake have been limited. Telehealth is defined as “information and communications technologies to deliver health and transmit health information over both long and short distances,”1 and it can be conducted via videoconferencing or telephone. It represents an attractive model to increase outpatient clinic appointments, which is important given the long waiting times for many clinics. Telehealth also provides avenues to continue critical outpatient management during the coronavirus disease 2019 (COVID-19) pandemic and for ongoing clinical management for furloughed or isolated staff who can still be engaged in outpatient care. At our institution, the COVID-19 pandemic stimulated the immediate and almost universal implementation of the telehealth model of care for outpatient appointments. We aimed to evaluate the experience of the telehealth model in the first 3 months of the COVID-19 pandemic in Victoria, focusing on the impact of telehealth on the number of scheduled appointments and clinic DNA rates. Methods: Over a 9-week period during the first COVID-19 lockdown in Melbourne, scheduled appointment numbers and patient attendance rates at 13 gastroenterology and hepatology outpatient clinics at a single tertiary hospital were evaluated through the hospital's online patient administration system, following rapid implementation of the telehealth model of outpatient care. Appointment numbers and attendance were compared with the average attendance rate over the same period in the preceding 5 years. Data collected included patient DNA rates for every scheduled clinic and appointment type (videoconferencing, telephone, or face-to-face consultation). Results: A total of 2626 outpatient clinic appointments were scheduled during the first 9-week COVID-19 lockdown, with 2237 appointments (85%) attended and 389 DNAs (15%), an improvement of 2.2% in attendance rate compared with the average attendance rate during the same 9-week period in the preceding 5 years (P = 0.035). Of the 2626 appointments, 1319 (50%) were video consultations, and 1307 (50%) were telephone consultations. In the preceding 5 years, an average of 2304 outpatient clinic appointments (322 fewer appointments) were scheduled during the same 9-week period, with 1912 appointments (83%) attended and 392 (17%) not attended. Of these 2304 appointments, 2271 (99%) were face-to-face consultations and only 33 (1%) were video consultations. Attendance rates differed according to clinic type. Compared with previous years, outpatient clinics with significantly lower DNA rates during COVID-19 included combined general gastroenterology (15% vs 20%, P = 0.014), satellite inflammatory bowel disease (2% vs 10%, P = 0.033), satellite liver clinic (20% vs 28%, P = 0.198), and privatized liver clinic (13% vs 18%, P = 0.051). Clinics with higher numerical DNA rates included hepatoma (18% vs 12%, P = 0.731) and weight management (20% vs 15%, P = 0.343). When evaluating the appointment type, we found that consultations carried out by telephone resulted in a significantly lower DNA rate, compared with video consultations (9% vs 21%;P < 0.001). Furthermore, an additional 37 clinic lists occurred during this 9-week period, equivalent to four additional lists per week, compared with the average number in the preceding 5 years. Conclusion: Despite the upheaval of clinical services during the COVID-19 pandemic, the major and rapid systems change to overhaul outpatient clinics to an almost exclusively telehealth model was highly succes ful. A total of 1319 video consultations occurred during the 9-week period, compared with just 43 in the preceding year, demonstrating the rapid and widespread implementation of telehealth. Importantly, there was a significant overall reduction in DNA rates, by 2.2%, using the telehealth model. Phone calls were particularly effective for clinic consultations, with DNA rates of only 9.0%. Telehealth has the potential to improve outpatient clinic attendance and efficiency, and our data strongly advocate for ongoing support for telehealth models, including both video and telephone consultation, beyond the COVID-19 era.