Comparative Analysis of Different Systematic Odometry Error Correction Methods on a Differential Drive Indoor Service Robot

The COVID-19 pandemic has led to a surge of interest in research work involving the development of robotic systems that reduce human-to-human interaction, as such a technology can greatly benefit healthcare industries in preventing the spread of highly infectious diseases. An indoor service robot is built and equipped with wheel odometry and a 2D LiDAR. However, the presence of the systematic odometry errors is evident during field testing. Hence, the possibility of minimizing systematic odometry errors is inspected using various methods of calculation, namely: UMBmark, Lee's and Jung's. The methods all use the Bidirectional Square Path test, performed together with ROS. It is found that Jung's method is the most appropriate method showing a 20.4% improvement compared to the uncalibrated dead reckoning accuracy. Moreover, it is found that the presence of slippage, a nonsystematic error, greatly affects the return position errors of the robot. Consequently, it is recommended to improve the design of the wheelbase to minimize the effects of nonsystematic errors. © 2022 IEEE.

ANALYSIS OF THE EFFECT OF MACROPRUDENTIAL AND MACROPRUDENTIAL INDICATORS ON THE STOCK PRICE INDEX OF ISLAMIC BANKS IN INDONESIA USING THE ERROR CORRECTION MODEL

The experience of various crises that have occurred, including the impact of the Covid-19 pandemic, presents a challenge to implement macroprudential policies to ensure the financial system survives and continues to carry out its function in driving the economy. The existing macroprudential policies tend to be individual and focus on prudent banking and other financial institutions. Economic fluctuations that occur on the macro side will greatly impact, either directly or indirectly, the stock price index, as well as the company's internal indicators which are considered to have a major influence on the decisions of investors and potential investors to take action on the stock exchange. The type of research used in this research is quantitative research. The nature of this research is descriptive with a quantitative approach. The data collection technique in this research is Literature Study. The test carried out in this study is the multiple linear regression analysis test (multiple linear regression method), this study uses the ECM model to obtain the best model which includes the classical assumption test. The results of this study based on the partial short-term relationship test, it can be concluded that the Exchange Rate, Inflation, and TPF in the short term have no significant effect on the PNBS Stock Price Index. Meanwhile, short-term CAR has a significant positive effect on the PNBS Stock Price Index. Based on the results of the partial long-term relationship test, it can be concluded that in the long term, the Exchange Rate has a significant negative effect and TPF and CAR have a significant positive effect on the PNBS Stock Price Index while Inflation has no significant effect on the PNBS Stock Price Index. Based on the output results of the simultaneous short-term and long-term F test, it shows that all independent variables simultaneously have a significant effect on the PNBS Stock Price Index in the short term. Based on the provisions of the MUI DSN through the issued fatwas related to the Sharia capital market and Sharia shares, it is explained that Sharia stock investment to invest according to the perspective of Sharia economic law is allowed. [ FROM AUTHOR] Copyright of Jurnal Syntax Admiration is the property of Ridwan Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Story is Better Told With Collective Interests: An Experimental Examination of Misinformation Correction During the COVID-19 Pandemic.

PURPOSE: To examine strategies that help motivate social correction behaviors to combat COVID-19-related health misinformation on social media. DESIGN: 2 (message types: narrative vs statistics) x 2 (social frames: individual vs collective) between-subjects experiment. SETTING: Qualtrics-based online experiment via Lucid. SUBJECTS: The final sample consisted of 450 participants (Mage = 45.31). MEASURES: Manipulation check, discussion and correction intentions, and need for cognition (NFC). ANALYSIS: ANCOVA and PROCESS model 3 were used to analyze the data. RESULTS: Significant interaction effects emerged between message types and social frames on discussion intention, F (1, 442) = 5.26, P = .022, and correction intention, F (1, 442) = 4.85, P = .028. Collectively framed narrative correction (Mdiscussion = 3.15, Mcorrection = 3.17) was more effective than individually framed narrative correction (Mdiscussion = 2.73, Mcorrection = 2.77). Individually framed statistical correction (Mdiscussion = 3.10, Mcorrection = 2.95) was more persuasive than collectively framed statistical correction (Mdiscussion = 2.89, Mcorrection = 2.69). The interaction effects were more evident for people low on NFC, P = .031. CONCLUSION: In motivating social correction behaviors, a story is better told with an emphasis on collective interests, and numbers are better presented with personal gains and losses. Future interventions should identify the target audience based on the level of NFC.

Assessing the Effect of the U.S. Vaccination Program on the Coronavirus Positivity Rate With a Multivariate Framework.

The factors influencing the incidence of COVID-19, including the impact of the vaccination programs, have been studied in the literature. Most studies focus on one or two factors, without considering their interactions, which is not enough to assess a vaccination program in a statistically robust manner. We examine the impact of the U.S. vaccination program on the SARS-CoV-2 positivity rate while simultaneously considering a large number of factors involved in the spread of the virus and the feedbacks among them. We consider the effects of the following sets of factors: socioeconomic factors, public policy factors, environmental factors, and non-observable factors. A time series Error Correction Model (ECM) was used to estimate the impact of the vaccination program at the national level on the positivity rate. Additionally, state-level ECMs with panel data were combined with machine learning techniques to assess the impact of the program and identify relevant factors to build the best-fitting models. We find that the vaccination program reduced the virus positivity rate. However, the program was partially undermined by a feedback loop in which increased vaccination led to increased mobility. Although some external factors reduced the positivity rate, the emergence of new variants increased the positivity rate. The positivity rate was associated with several forces acting simultaneously in opposite directions such as the number of vaccine doses administered and mobility. The existence of complex interactions, between the factors studied, implies that there is a need to combine different public policies to strengthen the impact of the vaccination program.

Intra-Host Co-Existing Strains of SARS-CoV-2 Reference Genome Uncovered by Exhaustive Computational Search.

The COVID-19 pandemic caused by SARS-CoV-2 has had a severe impact on people worldwide. The reference genome of the virus has been widely used as a template for designing mRNA vaccines to combat the disease. In this study, we present a computational method aimed at identifying co-existing intra-host strains of the virus from RNA-sequencing data of short reads that were used to assemble the original reference genome. Our method consisted of five key steps: extraction of relevant reads, error correction for the reads, identification of within-host diversity, phylogenetic study, and protein binding affinity analysis. Our study revealed that multiple strains of SARS-CoV-2 can coexist in both the viral sample used to produce the reference sequence and a wastewater sample from California. Additionally, our workflow demonstrated its capability to identify within-host diversity in foot-and-mouth disease virus (FMDV). Through our research, we were able to shed light on the binding affinity and phylogenetic relationships of these strains with the published SARS-CoV-2 reference genome, SARS-CoV, variants of concern (VOC) of SARS-CoV-2, and some closely related coronaviruses. These insights have important implications for future research efforts aimed at identifying within-host diversity, understanding the evolution and spread of these viruses, as well as the development of effective treatments and vaccines against them.

Correcting vaccine misinformation on social media: Effect of social correction methods on vaccine skeptics' intention to take COVID-19 vaccine

This study identifies the effect of six social correction methods on vaccine skeptics' intention to take COVID-19 vaccine. In April–May 2021, we conducted a 3 (corrector on Twitter: ordinary person vs medical doctor vs nurse) × 2 (correction strategy: priming vs rebuttal) + 1 (control: misinformation only) between-subjects online experiment with 569 vaccine skeptics in the United States. Results show that exposure to priming-based corrections performed by a corrector, regardless of their expertise, is positively associated with intention to take COVID-19 vaccine if the information shared by the corrector is perceived to be trustworthy. This is evident among those with high or moderate vaccine skepticism. What is only evident among those with moderate vaccine skepticism is that exposure to corrections using priming (any corrector) or rebuttal (ordinary person or medical doctor) is positively associated with intention to take COVID-19 vaccine if the respondents perceived that the corrector was an expert. [ FROM AUTHOR] Copyright of New Media & Society is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Body Posture Correction and Hand Gesture Detection Using Federated Learning and Mediapipe

In today's post-covid culture, where everyone works from home, there is a huge possibility of serious long-term health problems. A lot of people have started taking up exercises at home and if done incorrectly, they can have major negative effects. Another one of the main contributors to these health issues is bad sitting posture, which is only exacerbated when working for hours on end. Hand gesture detection has many useful applications in elderly healthcare, automating actions and gesture-based presentations and games. To help users with these actions, our paper proposes pinpointing the points of the error to the user in real-time and in a lightweight manner for yoga posture correction. The incorrect positions shall be shown in real-time on top of the user's video feed to help them correct it properly. The user shall be told about when they are sitting in a bad position, and the overall bad posture time will also be shown for the session, which will provide the required information to the user. To further help users in a useful manner, our paper looks to augment the hand gesture detection feature with federated learning and personalization to avoid the common pitfall of privacy concerns, while still allowing users to customize their experience. The proposed library for the implementation of these tasks is the MediaPipe library. This library is one of the key components that makes the features lightweight and easy to use. The aforementioned library also looks to implement the features in real time with no lag while keeping the resource requirements as low as possible. © 2023 IEEE.

The Differential Effects of Oil Prices on the Development of Renewable Energy in Oil-Importing and Oil-Exporting Countries in Africa

The shift to renewable sources of energy has become a critical economic priority in African countries due to energy challenges. However, investors in the development of renewable energy face problems with decision making due to the existence of multiple criteria, such as oil prices and the associated macroeconomic performance. This study aims to analyze the differential effects of international oil prices and other macroeconomic factors on the development of renewable energy in both oil-importing and oil-exporting countries in Africa. The study uses a panel vector error correction model (P-VECM) to analyze data from five net oil exporters (Algeria, Angola, Egypt, Libya and Nigeria) and five net oil importers (Kenya, Ethiopia, Congo, Mozambique and South Africa). The study finds that higher oil prices positively affect the development of renewable energy in oil-importing countries by making renewable energy more economically competitive. Economic growth is also identified as a major driver of the development of renewable energy. While high-interest rates negatively affect the development of renewable energy in oil-importing countries, it has positive effects in oil-exporting countries. Exchange rates play a crucial role in the development of renewable energy in both types of countries with a negative effect in oil-exporting countries and a positive effect in oil-importing countries. The findings of this study suggest that policymakers should take a holistic approach to the development of renewable energy that considers the complex interplay of factors, such as oil prices, economic growth, interest rates, and exchange rates.

A Time Series Forecast of COVID-19 Infections, Recoveries and Fatalities in Nigeria

The study investigated COVID-19 pandemic infections, recoveries, and fatalities in Nigeria to forecast future values of infections, recoveries, and fatalities and thus ascertain the extent to which the pandemic appeared to be converging with time. The prediction of COVID-19 infections, recoveries, and fatalities was necessitated by the impact that the pandemic had exerted in world economies since its outbreak in late 2019. The quantitative method was employed, and a longitudinal research design was applied. Data were obtained from the Nigeria Centre for Disease Control (NCDC). The least-squares test and autoregressive distributed lag (ARDL) tests were performed to forecast infections, recoveries, and fatalities. The results of the predicted infections for the last five months of the year (August–December 2020) shows that the cases of infections will narrow down within the period. The need for policymakers to implement complete unlocking of the economy for speedy economic recovery was suggested, among others.

Wild Bootstrap-Based Bias Correction for Spatial Quantile Panel Data Models with Varying Coefficients

This paper studies quantile regression for spatial panel data models with varying coefficients, taking the time and location effects of the impacts of the covariates into account, i.e., the implications of covariates may change over time and location. Smoothing methods are employed for approximating varying coefficients, including B-spline and local polynomial approximation. A fixed-effects quantile regression (FEQR) estimator is typically biased in the presence of the spatial lag variable. The wild bootstrap method is employed to attenuate the estimation bias. Simulations are conducted to study the performance of the proposed method and show that the proposed methods are stable and efficient. Further, the estimators based on the B-spline method perform much better than those of the local polynomial approximation method, especially for location-varying coefficients. Real data about economic development in China are also analyzed to illustrate application of the proposed procedure.

Sustainability assessment of crops' production in India: empirical evidence from ARDL-ECM approach

PurposeThe study aims to evaluate the long- vs short-run relationships between crops' production (output) and crops' significant inputs such as land use, agricultural water use (AWU) and gross irrigated area in India during the period 1981–2018.Design/methodology/approachThe study applied the autoregressive distributed lag (ARDL) bounds testing approach to estimate the co-integration among the variables. The study uses the error correction model (ECM), which integrates the short-run dynamics with the long-run equilibrium.FindingsThe ARDL bounds test of co-integration confirms the strong evidence of the long-run relationship among the variables. Empirical results show the positive and significant relationship of crops' production with land use and gross irrigated area. The statistically significant error correction term (ECT) validates the speed of adjustment of the empirical models in the long-run.Research limitations/implicationsThe study suggests that the decision-makers must understand potential trade-offs between human needs and environmental impacts to ensure food for the growing population in India.Originality/valueFor a clear insight into the impact of climate change on crops' production, the current study incorporates the climate variables such as annual rainfall, maximum temperature and minimum temperature. Further, the study considered agro-chemicals, i.e. fertilizers and pesticides, concerning their negative impacts on increased agricultural production and the environment.

Long-COVID Inducement Mechanism Based on the Path Module Correlation Coefficient

As the number of COVID-19 cases increases, the long-COVID symptoms become the focus of clinical attention. Based on the statistical analysis of long-COVID symptoms in European and Chinese populations, this study proposes the path module correlation coefficient, which can estimate the correlation between two modules in a network, to evaluate the correlation between SARS-CoV-2 infection and long-COVID symptoms, providing a theoretical support for analyzing the frequency of long-COVID symptoms in European and Chinese populations. The path module correlation coefficients between specific COVID-19-related genes in the European and Chinese populations and genes that may induce long-COVID symptoms were calculated. The results showed that the path module correlation coefficients were completely consistent with the frequency of long-COVID symptoms in the Chinese population, but slightly different in the European population. Furthermore, the cathepsin C (CTSC) gene was found to be a potential COVID-19-related gene by a path module correlation coefficient correction rate. Our study can help to explore other long-COVID symptoms that have not yet been discovered and provide a new perspective to research this syndrome. Meanwhile, the path module correlation coefficient correction rate can help to find more species-specific genes related to COVID-19 in the future.

Validation and Spatiotemporal Analysis of the Modis 1 Km Aerosol Product over China during the Covid-19 Pandemic

The Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km aerosol product based on the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has great potential in understanding the interaction between human activities and the atmospheric environment. In this paper, the MODIS 1 km aerosol product over China during the Coronavirus Disease 2019 (COVID-19) pandemic was validated against with the ground measured data collected from the Aerosol Robotic Network (AERONET). The result shows a good agreement between the two datasets. The spatiotemporal analyses of three selected regions, which are Beijing-Tianjin-Hebei, Hubei and Guangdong-Hong Kong-Macao, indicate that the COVID-19 pandemic has a significant impact on human activities and aerosol loadings.

Learning torus PCA-based classification for multiscale RNA correction with application to SARS-CoV-2

Three-dimensional RNA structures frequently contain atomic clashes. Usually, corrections approximate the biophysical chemistry, which is computationally intensive and often does not correct all clashes. We propose fast, data-driven reconstructions from clash-free benchmark data with two-scale shape analysis: microscopic (suites) dihedral backbone angles, mesoscopic sugar ring centre landmarks. Our analysis relates concentrated mesoscopic scale neighbourhoods to microscopic scale clusters, correcting within-suite-backbone-to-backbone clashes exploiting angular shape and size-and-shape Frechet means. Validation shows that learned classes highly correspond with literature clusters and reconstructions are well within physical resolution. We illustrate the power of our method using cutting-edge SARS-CoV-2 RNA.

Psychological Aid to Victims of War and the Covid Pandemic 19 in Ukraine

The article reflects theoretical, methodological and methodical bases of psychological aid to victims of unexpected crisis-military situations on the background of coronovirus pandemics spreading. The essence of psychological self-help as a factor of stress-resistance and internal psychological potential of resisting psychological traumas in the conditions of war and viral pandemics with the propositions of effective methodological means of its conducting is revealed. In providing psychological aid, the cognitive-behavioral approach was deemed effective as the basic one, and it was suggested that integrative psychotherapeutic and comprehensive psychological approaches to crisis counseling in conditions of military conflict be applied, depending on the specifics of survivors' experience of acute emotional reactions and the complexity of the course of posttraumatic stress disorders of resistance to the action of a psychotraumatic factor. Neuropsychological correction deserves special attention in providing psychological aid in conditions of military conflict and pandemics, which allows a combination of an integrated bodyoriented psychological approach with neuro-psycho-correctional techniques and psychotherapeutic methods for effective restoration of the tone of the nervous system and stabilization of the psycho-emotional state. The main provisions of practical psychology that in conditions of war and pandemic COVID-19 the adaptive potential of psychological health of each person and psychological self-help is love, faith and hope. Psychological recommendations of educational character for the formation of basic skills to ensure psychological health in conditions of war and pandemic COVID-19 have been developed.

BIRCH: An Automated Workflow for Evaluation, Correction, and Visualization of Batch Effect in Bottom-Up Mass Spectrometry-Based Proteomics Data.

Recent surges in large-scale mass spectrometry (MS)-based proteomics studies demand a concurrent rise in methods to facilitate reliable and reproducible data analysis. Quantification of proteins in MS analysis can be affected by variations in technical factors such as sample preparation and data acquisition conditions leading to batch effects, which adds to noise in the data set. This may in turn affect the effectiveness of any biological conclusions derived from the data. Here we present Batch-effect Identification, Representation, and Correction of Heterogeneous data (BIRCH), a workflow for analysis and correction of batch effect through an automated, versatile, and easy to use web-based tool with the goal of eliminating technical variation. BIRCH also supports diagnosis of the data to check for the presence of batch effects, feasibility of batch correction, and imputation to deal with missing values in the data set. To illustrate the relevance of the tool, we explore two case studies, including an iPSC-derived cell study and a Covid vaccine study to show different context-specific use cases. Ultimately this tool can be used as an extremely powerful approach for eliminating technical bias while retaining biological bias, toward understanding disease mechanisms and potential therapeutics.

Psychological Characteristics of Children and Adolescents Who Have Undergone COVID-19: Possibilities of Correction.

The article is about topical issues of the psychological features of the long-term consequences of post-COVID syndrome in children and adolescents. We have described the most frequent residual manifestations of SARS-CoV-2 infection alongside with an analysis of the characteristics of the emotional and behavioral health of children and adolescents. The authors of article have analyzed modern approaches and recommendations for changing the lifestyle, psychological support of patients with the elimination of stress factors and body stress resistance increase. Also in article are presented main symptoms and signs associated with emotional and behavioral responses to stress in children and adolescents. The necessity of early detection and psychological correction of the symptoms of post-COVID syndrome and its inherent stress manifestations is substantiated as well as the stress resistance increase using physiological approaches of micronutrient correction with bioorganic magnesium substances.Copyright © 2022, Professionalnye Izdaniya. All rights reserved.

Osteopathic rehabilitation of patients after community-acquired pneumonia

Introduction. During the COVID-19 pandemic, the effective medical rehabilitation of patients who have suffered community-acquired pneumonia is crucial, and the osteopathic correction can take its rightful place along with other rehabilitation methods. The studies of osteopathic approaches in the treatment of pneumonia are described in available sources for the inpatient stay of patients. The issues of the effectiveness of osteopathic correction in more distant periods of rehabilitation after community-acquired pneumonia are poorly covered and therefore became the basis for the presented work. The aim of the study is to research the effectiveness of the osteopathic correction inclusion in the outpatient rehabilitation program for patients after community-acquired pneumonia. Materials and methods. A prospective, controlled, randomized study was conducted at the Clinic of the Eurasian Institute of Osteopathic Medicine (Bishkek, Kyrgyz Republic) from January to June 2021. 30 patients who have suffered community-acquired pneumonia of mild and moderate severity were examined, including 15 people of the main group who received osteopathic correction every 7 days for 3–4 weeks and simultaneously performed the recommended set of exercises of physical therapy (exercise therapy);15 people of the control group, without osteopathic correction, only a set of exercise therapy exercises was recommended for these patients. The evaluation of the effectiveness of osteopathic correction was carried out on the basis of the analysis of spirometry, pulse oximetry, functional tests of the Stange and Genchi, and the life quality by the MOS SF-36 questionnaire. Results. The study showed that the inclusion of osteopathic correction in the rehabilitation of patients who have suffered community-acquired pneumonia significantly (p<0,05) improves the indicators of the external respiration function, namely, the vital capacity of the lungs, increases the body′s resistance to hypoxia and hypercapnia, and improves the life quality. Conclusion. The obtained results allow us to reasonably recommend the inclusion of osteopathic correction in outpatient rehabilitation programs for patients who have suffered community-acquired pneumonia. © Baktygul′ Sh. Usupbekova, Sabina S. Sartmyrzaeva, Sholpan A. Murzakhmetova, 2023.

Psychophysiological Correlates of Coping Behavior in Adolescents Who Have Undergone COVID-191

The global nature of the epidemiological situation associated with the spread of the new coronavirus infection COVID-19 and the multidisciplinary nature of the problem of psychophysiological disorders in people who have suffered from this disease has led to the need for a comprehensive study of the factors affecting postcovid recovery. Taking into account the nature of the problem posed, the purpose of the presented work was to study the relationship of psychophysiological parameters with indicators of stress-overcoming (coping) behavior in adolescents who have undergone COVID-19. The study included 54 students of Kemerovo State University, who were divided into a group of COVID-19 patients and a group without symptoms of the disease. To assess coping behavior, the questionnaire «Ways of Coping Questionnaire» was used (Folkman, Lazarus;adaptation of Kryukova et al.). An automated computer complex "PFK” was used to study psychophysiological indicators. The following psychophysiological indicators were evaluated: simple visual-motor reaction, complex visual-motor reaction, anticipations and delays in assessing the reaction to a moving object, concentration and volume of attention, brain performance, the level of functional mobility of nervous processes, short-term memory for numbers and words, random access memory. According to the results of the correlation analysis, the interrelations between avoidant forms of coping behavior, such as "distancing”, "escape-avoidance”, "positive reassessment” with indicators of memory, attention, mobility of nervous processes, the number of inaccurate reactions to a moving object and the working capacity of the brain were recorded, which indicates a link between the increase in psychophysiological and cognitive disorders and preference in choosing care from stressful situations after a disease. Deterioration of memory and functioning of the nervous system lead to more frequent requests for support from others to receive additional help from them. The weakening of the nervous system also leads to more frequent use of productive coping strategies "taking responsibility” and "planning problem solving”, which, at the same time, additionally make it possible to compensate for cognitive impairments by performing tasks more accurately. In the group that did not have symptoms of COVID-19, no significant correlations were found between coping avoidance strategies and psychophysiological or cognitive impairments. Based on the results obtained, it can be assumed that the restoration of cognitive functions during psychocorrective work will make it possible to actualize the patient's choice of productive coping strategies and switch to a healthy behavior model. © 2022 Tomsk State University. All rights reserved.

Aquaculture Production in the Midst of GHG Emissions in South Africa

The study ascertained the relationship between aquaculture production and greenhouse gas (GHG) emissions in South Africa. The study used the Autoregressive Distributed Lag—Error Correction Model (ARDL-VECM) with time series data between 1990 and 2020. The results showed that the mean annual aquaculture production, GHG emissions, and Gross Domestic Product (GDP) in the period were 5200 tonnes, 412 tonnes, and US$447 billion, respectively. There was a long-run relationship between GHG emissions and GDP. In the short run, GHG emissions had a positive relationship with GDP and a negative relationship with beef production. Furthermore, there was a bi-directional relationship between aquaculture production and GHG emissions. In addition, beef production and GDP had a bi-directional relationship. Beef production also had a positive relationship with aquaculture production. The study concludes that aquaculture production is affected and tends to affect GHG emissions. Aquaculture legislation should consider GHG emissions in South Africa and promote sustainable production techniques.