Path planning research for mobile robots in dynamic environments

At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.

A roadmap for triggering the convergence of global ESG disclosure standards: lessons from the IFRS foundation and stakeholder engagement

PurposeMotivated by the growing and urgent demands for a unified set of internationally accepted, and high-quality environmental, social and governance (hereafter ESG) disclosure standards, this exploratory study aims to propose a roadmap for setting out the proper technical groundwork for global ESG disclosure standards. Design/methodology/approachAn exploratory study is conducted to gain initial understanding and insights into establishing a worldwide set of standards for reporting on sustainability, as this topic has not been extensively studied. This study examines the viewpoints of various stakeholders, including sustainability practitioners, academics and organizations focused on ESG issues, to generate knowledge that is more solid than knowledge produced when one group of stakeholders work alone. FindingsThe results revealed that there is an ongoing and incompatible debate regarding several conceptual and practical challenges for setting a unified set of ESG disclosure standards. Practical implicationsThe study results provide multidimensional insights for regulatory parties and standard-setters to develop a high-quality package of global ESG reporting standards. This, in turn, enables different groups of stakeholders to understand the firm's impact on the environment, society and economy. Originality/valueResearch into this timely and relevant global issue is considered an appealing area of study and deserves significant attention. Thereby, working on this topic merits remarkable attention. Furthermore, this exploratory article provides valuable and informative suggestions for creating a unified and high-quality set of internationally accepted sustainability reporting standards.

The spread of COVID-19 in stock returns along global value chains

This paper examines the performance of industries in the trade network in international stock markets during the onset of COVID-19. In general, the value of all industries in G20 countries declines significantly in the pandemic. Stock returns of industries in the central positions of global value chains exhibit remarkable resilience despite the economic hardship caused by COVID-19. This pattern is more pronounced when the disruptions caused by social distancing requirements are considered. We postulate that this is related to the essential services provided by the central industries.

Echocardiographic features of COVID-19 patients without significant baseline cardiovascular disease.

Objective. To assess the relationship between the severity of COVID-19 in patients without significant baseline cardiovascular pathology and various echocardiographic parameters of myocardial dysfunction. Material and methods. 46 patients with COVID-19 were included in our study: 33 patients of moderate severity and 13 - with severe disease. On days 1 and 9 upon admission, all patients underwent an echocardiographic study with standard assessment of the both ventricles function, as well as an assessment of their global longitudinal strain (GLS). Comparison of the studied parameters was carried out both between groups of patients and within each group in dynamics. Results. On day 1patients in the severe group had higher values of the systolic gradient on the tricuspid valve (22.0 [21.0;26.0] vs 30.0 [24.0;34.5] mm Hg, p = 0.02), systolic excursion of the plane of the tricuspid ring (2.3 [2.1;2.4] vs 2.0 [1.9;2.2] mm, p = 0.016), E/e' ratio (9.5 [7.7;8.9] vs 7.5 [6.8;9.3], p = 0.03). At day 9 among patients in the severe group, there was a decrease in end-diastolic (111.0 [100.0;120.0] vs 100.0 [89.0;105.0] ml, p = 0.03) and of end-systolic (35.5 [32.0;41, 2] vs 28.0 [25.0;31.8] ml, p < 0.01) volumes of the left ventricle. There was a decrease in GLS of the both ventricles compared to general accepted values. In dynamics, there was an increase in the GLS of the right ventricle in both groups, but it was more pronounced among severe group of patients (day 1 -18.5 [-15.2;-21.1] vs -20.2 [-15.8.1;-21.1] %, p = 0.03). The troponin levels were in the normal range. Conclusion. In COVID-19 patients without significant baseline cardiovascular pathology, there is a transient decrease in longitudinal strain of both ventricles, even in the absence of clinical and laboratory signs of acute myocardial injury.Copyright © Creative Cardiology 2021.

Global Governance in the New Era: Concepts and Approaches

This book mainly introduces the concepts and approaches of global governance from the viewpoints of Chinese and Russian scholars and is divided into four parts. The first one deals with the concept of a new type of global governance, namely "Globalization 2.0". The second one is dedicated to institutions and multilateralism, including the importance and effectiveness of international institutions. The third part focuses on the important countries and regions in the new era, as well as such issues as the current global status quo, processes in Eurasia, the prospects of the U.S.-China-Russia trilateral relationship. The last part analyzes the future development of global governance and possible solutions of how it might be improved. Climate change, digital era, cyber security, financial and economic regimes, COVID-19 are all involved in this part. In short, this book is a profound and cutting-edge research on global governance. © China Social Sciences Press 2023.

Exploring Social Media for Early Detection of Depression in COVID-19 Patients

The COVID-19 pandemic has caused substantial damage to global health. Even though three years have passed, the world continues to struggle with the virus. Concerns are growing about the impact of COVID-19 on the mental health of infected individuals, who are more likely to experience depression, which can have long-lasting consequences for both the affected individuals and the world. Detection and intervention at an early stage can reduce the risk of depression in COVID-19 patients. In this paper, we investigated the relationship between COVID-19 infection and depression through social media analysis. Firstly, we managed a dataset of COVID-19 patients that contains information about their social media activity both before and after infection. Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression. Thirdly, we proposed a deep neural network for early prediction of depression risk. This model considers daily mood swings as a psychiatric signal and incorporates textual and emotional characteristics via knowledge distillation. Experimental results demonstrate that our proposed framework outperforms baselines in detecting depression risk, with an AUROC of 0.9317 and an AUPRC of 0.8116. Our model has the potential to enable public health organizations to initiate prompt intervention with high-risk patients. © 2023 ACM.

Studying the impact of COVID-19 on the European Air Transportation Network

The European Air Transportation Network was significantly impacted by the COVID-19 pandemic, resulting in an unprecedented loss of flight connections. Utilizing a combination of graph representation learning and time series analysis, this paper studies the evolution of both the global connectivity as well as the structure of the European Air Transportation Network from January 2020 to December 2022. Specifically, it finds strong differences in recovery rates for flights across six different market segments. In terms of network structure, the study finds that structural roles that are present in the pre-covid network have seen a loss in performance over the course of the pandemic, but have recovered to pre-covid levels. Using regional changes in structural roles, this study identifies Italy as the region with the strongest increase and the United Kingdom as the region with the strongest decrease in structural role, finding substantial differences in recovery rates per market segment. Lastly, this study pays special attention on the effect of the Russia-Ukrainian war on the European Air Transportation Network. © 2023 IEEE.

Competitiveness-the engine that boosts economic growth and revives the economy

Competitiveness is a concept that shows up in all aspects of human life, both at the micro level, in personal, social, and professional life, and at the macro level, linked to organizational and national competitiveness with long-term effects on global competitiveness. In this paper, we aim to address competitiveness in Romania in the current context, before and after the COVID-19 pandemic, highlighting its role in reviving the economy. While until the onset of the pandemic Romania's competitiveness performance was growing, more recently, because of the global health crisis, it dropped a few places, according to the Global Competitiveness Index report. In order to have a clear picture of the degree of competitiveness in Romania, we have presented a series of statistical data for the most relevant macroeconomic indicators for our study for the 2017-2022 timeframe: the global competitiveness index, the minimum wage, labor productivity, the evolution of real labor productivity per employed person, the economic growth rate, the unemployment rate, the inflation rate, the European innovation index, gross domestic expenditure on research and development, export of goods and services as a share of GDP, etc. The methodology used involves the use of quantitative techniques, performing an econometric analysis, and correlating how the most important macroeconomic indicators can influence the degree of competitiveness at both the national and international level. For the post-pandemic timeframe, the analysis switches focus, just as the economic reality did, looking at energy costs and energy use as determinants of competitiveness. Since notions like circular economy and sustainable development correlate being energy-efficient with being competitive, however, at the same time, the high cost of investments necessary for individual businesses and countries to switch from polluting energies to clean energies impedes or at the very least heavily impacts their ability to compete with entities that don't make that same switch, it becomes apparent that the energy market impacts competitiveness metrics. Competitiveness promotes valuable contributors and underpins performance at group and company level, and the effects from the micro level will propagate, with an emission effect, to the entire national economy with obvious implications at the international level, through real growth in macroeconomic indicators, increased labor productivity, increased economic performance (market share, export share, return on capital), raising living standards and economic and social wellbeing (life expectancy index, human development index, poverty rate), education (skills, knowledge, abilities, managerial and marketing skills, corporate culture), competitive potential (innovation, R&D, promotion), and in raising the Global Competitiveness Index by focusing on factors of production, efficiency, and innovation, etc.

From the Bretton Woods system to the global non-system: The trials and tribulations of slow learning

In this paper we analyse why an understanding of the global ‘non-system', in which we now live, took so long to arrive after the Bretton Woods system collapsed in 1971. We first describe how knowledge of how an inflation-targeting regime would operate—what we call ‘Taylor-rule macroeconomics'—was only gradually created during the 1970s, 1980s, and 1990s. We then describe how, subsequent to this, an awareness emerged, also gradually, of how the international non-system might work, depending, as it does, on Taylor-rule macroeconomics being already in place. We then discuss the Great Moderation, making clear that a well-functioning global non-system would require not just inflation targeting and floating exchange rates in each country, but also adequate fiscal discipline, and a satisfactory form of financial regulation. We describe how a well-functioning version of this global non-system would actually fit together. We then discuss how this non-system has responded to two enormous challenges of the last 15 years, namely the Global Financial Crisis and the Covid pandemic. This discussion of what has happened in the recent past provides the background to a discussion, in the companion paper by Subacchi and Vines in this issue of the Oxford Review of Economic Policy, of the challenges that the global non-system will face in the future. © The Author(s) 2023. Published by Oxford University Press.

Control System for Indoor Safety Measures Using a Faster R-CNN Architecture

This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.

Analyzing the research trends of COVID-19 using topic modeling approach

PurposeThe COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences.Design/methodology/approachThe current study identifies the focus areas of the research conducted on the COVID-19 pandemic. s of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation.FindingsBased on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research.Originality/valueWhile similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.

Editorial: Post-COVID-19 global trade and business environment and maritime supply chain

Since January 2020, the COVID-19 pandemic has caused widespread impacts on virtually every sector of the global economy, including world trade and global supply chains. [...]it has been argued that the existing globalised economies might require to be restructured in the aftermath of the COVID-19 pandemic when governments and firms start to re-strategize their critical supply chains through various disruption and resilience management strategies. [...]other shipping intermediaries, i.e. freight forwarders and logistics service providers, who play crucial roles in connecting demand and supply of maritime supply chains also suffered due to reduced business transactions. [...]the focus of this special issue is on understanding the impact of the COVID-19 pandemic on various players in the maritime supply chain, as well as possible trends of global trade and maritime supply chains and strategies and policies in the aftermath of the pandemic.

Economic Aspects of a Resource Sharing Manufacturing Network under Turbulences

Nowadays, manufacturing companies face more difficulties than ever. Unrest in global supply chains triggered by fluctuating customer demand, raw material shortages and crises (Covid pandemic, global warming, wars) complicate the utilization of production resources necessary for economic success. Also, the rapidly changing environment causes existing production plans to be adapted, which results in order changes, causing additional costs for manufacturers. One solution to cope with these problems is cooperation and sharing resources: requesting capacity from partners when having shortages and offering them temporarily in case of excess capacity. In this paper, a platform-based resource sharing mechanism is investigated from the economic perspective. In the mechanism, requests and offers are matched by a central platform applying a complex matching logic. The platform provides valid alternatives based on the incoming ordersthat the requesting company can choose from. Companies are rating each other's performance after each interaction based on delivery accuracy;choosing between resource offers is made based on the cumulated rating about the offeror and the price of the offer. Within this paper, the aim is to investigate the resource sharing mechanism from the economic point of view based on an approach to the responsiveness of a supply chain structure to turbulence, to support decision-makers trying to cope with unexpected changes. For this purpose, here the mechanism is briefly introduced, and basic concepts about turbulences in supply chains are also presented. Cost types related to resource sharing manufacturing companies are distinguished, and the model is validated with agent-based simulation. A simulation experiment is performed to investigate the use-case of outsourced jobs having different price levels. Based on the experiment, it can be concluded that there is a price level limit in such a resource sharing federation, under which it is worth it to collaborate with partners by outsourcing certain jobs to them. © 2022 Authors. All rights reserved.

Supply chain analytics and post-pandemic performance: mediating role of triple-A supply chain strategies

PurposeThe abrupt outbreak of coronavirus disease (COVID-19) hit every nation in 2020–2021, causing a worldwide pandemic. The worldwide COVID-19 epidemic, described as a "black swan”, has severely disrupted manufacturing firms' supply chain. The purpose of this study is to investigate how supply chain data analytics enable the effective deployment of agility, adaptability and alignment (3As) strategies, resulting in improving post-COVID disruption performance. It also analyses the indirect effect of supply chain data analytics on disruption performance through the 3As supply chain strategies.Design/methodology/approachThe hypothesis and theoretical framework were tested using a questionnaire survey. The authors employed structural equation modelling through the SMART PLS version 3.2.7 to analyse data from 163 textile firms located in Pakistan.FindingsThe results revealed that the supply chain data analytics contributed positively and significantly to the agility and adaptability, while all 3As supply chain strategies impacted the PPERF substantially. Further, the connection between supply chain data analytics (SCDA) and disruption performance has substantially been influenced through 3As supply chain strategies.Practical implicationsThe results imply that in the event of low likelihood, high effect disruptions, managers and decision-makers should focus their efforts on integrating data analytics capabilities with 3As supply chain policies to ensure long-term company success.Originality/valueThis research sheds fresh light on the importance of data analytics in effectively implementing 3As strategies for sustaining company performance amid COVID-19 disruptions.

Political economy of vaccine diplomacy: explaining varying strategies of China, India, and Russia's COVID-19 vaccine diplomacy

The COVID-19 pandemic and global responses to this crisis reveal the changing landscape of global health governance. As countries around the world struggle to secure COVID-19 vaccines for their citizens, some non-Western powers have actively distributed vaccines internationally – an act broadly recognized as vaccine diplomacy. While existing literature suggests that geopolitical concerns affect the selection of recipient countries, it has yet to explain other aspects of vaccine diplomacy. Why are some countries focused on vaccine sales while others are more open to donation? Why do some prefer bilateral to multilateral channels in distributing vaccines? Through comparative analysis of China, India, and Russia, this article shows that political economic factors, in addition to geopolitics, shape the ways non-Western powers conduct vaccine diplomacy. We argue that these countries adjust their strategies in line with their relative advantages in development, manufacturing, and delivery of vaccines. Each country has unique strengths and weakness, which gives rise to the varied patterns in vaccine diplomacy. Our findings suggest that their strategies of vaccine diplomacy are enabled as well as constrained by their economic realities, and the rise of these countries in this field does not necessarily mean an outright challenge to the existing international system. [ FROM AUTHOR] Copyright of Review of International Political Economy is the property of Routledge 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.)

Online Educational Ecosystem, Sustainability and Resiliency in Bangladesh: Scaffolding Pathways?

How is online tertiary education opening the student/teacher mind-set, particularly during the transitional learning/teaching process? The question is tested through a country-wide survey of students/teachers conducted against Independent University, Bangladesh's (IUB's) own transition. Students reported two broad changes: (a) micro-level infrastructural and resource issues resonating with macro-level interventions;and (b) the quality of learning vis-à-vis teaching amid-online platform transition merely exacerbating both teacher-level and student-level pressures. Accordingly, the chapter illustrates a handful of micro-level leverage points, based upon learner characteristics, needs, and university online ecosystem (including infrastructures, teacher's competency challenges, and Covid-19 impacts on the learning-teaching community), for future relevance. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Design and development of a mobile application for level monitoring of oxygen cylinders using block chain technology

Due to improvements in information and communication technology and growth of sensor technologies, Internet of Things is now widely used in medical field for optimal resource management and ubiquitous sensing. In hospitals, many IoT devices are linked together via gateways. Importance of gateways in modernization of hospitals cannot be overstated, but their centralized nature exposes them to a variety of security threats, including integrity, certification, and availability. Block chain technology for level monitoring in oxygen cylinders is a scattered record containing the data related to oxygen levels in the cylinder, patient's name, patient's ID number, patient's medical history, and all connected information carried out and distributed among the hospitals (nodes) present in the locality (network). Designing an oxygen level monitoring technique in an oxygen cylinder used as the support system for COVID-19-affected patients is a challenging task. Monitoring the level of oxygen in the cylinders is very important because they are used for saving the lives of the patients suffering from COVID-19. Not only the COVID-19 patients are dependent on this system, but this system will also be helpful for other patients who require oxygen support. The present scenario many COVID-19 hospitalized patients rely upon oxygen supply through oxygen cylinders and manual monitoring of oxygen levels in these cylinders has become a challenging task for the healthcare professionals due to overcrowding. If this level monitoring of oxygen cylinders are automated and developed as a mobile App, it would be of great use to the medical field, saving the lives of the patients who are left unmonitored during this pandemic. This proposal is entitled to develop a system to measure oxygen level using a smartphone App which will send instantaneous values about the level of the oxygen inside the cylinder. Pressure sensors and load cell are fitted to the oxygen cylinders, which will measure the oxygen content inside the cylinder in terms of the pressure and weight. The pressure sensors and load cells are connected to the Arduino board and are programmed to display the actual level of oxygen inside the cylinder in terms of numerical values. A beep sound is generated as an indicator to caution the nurses and attendants of the patients regarding the level of the oxygen inside the cylinder when it is only 15% of the total oxygen level in the cylinder in correlation to the pressure and weight. The signal with respect to the level corresponding to the measured pressure and weight of the cylinder is further transmitted to the monitoring station through Global System for Mobile communication (GSM). Graphical display is used at monitoring end to indicate the level of oxygen inside all oxygen cylinders to facilitate actions like 100% full, 80% full, 60% full, 40% full, 20% full which states that either the oxygen cylinder is in good condition, or requires a replacement of empty cylinders with filled ones in correlation to the pressure and weight being sensed by the sensors. The levels of the oxygen monitored inside the cylinder and other related data can also be stored on a cloud storage which will facilitate the retrieval of the status at any point of time, as when required by the physicians and nurses. These results reported, are valued in monitoring the level of the oxygen cylinder remotely connected to the patients, affected by COVID-19, using a smartphone App. This mobile phone App is an effective tool for investigating the oxygen cylinder level used as a life-support system for COVID-19-affected patients. A virtual model of the partial system is developed using TINKER CAD simulation package. In real time, the sensor data analysis with cloud computing will be deployed to detect and track the level of the oxygen cylinders. © 2023 Elsevier Inc. All rights reserved.

Spatial Epidemiology of COVID-19 Pandemic: Disease Risk, Prognosis, and Complications

Why do some populations display a higher attack and mortality rate from the current coronavirus disease 2019 (COVID-19) pandemic than others? Are there geographic, environmental, behavioral, genetic, and comorbidity differences that influence spatial dynamics of COVID-19 transmission and outcomes? Where are the regional and country-level hotspots, and what drives those hotspots? These are some of the questions the current chapter strives to answer. The dynamics of transmission and consequences of COVID-19 are not homogeneous but instead have a geographical and spatial clustering. Population-level genetic, vaccination rates, health care disparities, SARS-CoV-2 variants, and meteorological factors are all underlying determinants of the disease dynamics globally, regionally, nationally, and locally. Disease surveillance frameworks to control, mitigate, and prevent the SARS- CoV-2 infections, particularly in low- and middle-income countries, are critical. Lastly, we highlight the spatial differences in the consequences of the pandemic focusing on behavioral and post-acute sequelae of SARS-CoV-2 infection. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.