Review on Generation and Characterization of Copper Particles and Copper Composites Prepared by Mechanical Milling on a Lab-Scale.

This review aims to expose mechanical milling as an alternative method for generating copper-based particles (copper particles (CuP) and copper composites (CuC)); more specifically, via a top-down or bottom-up approach, on a lab-scale. This work will also highlight the different parameters that can affect the size distribution, the type, and the morphology of the obtained CuP or CuC, such as the type of mechanical mill, ball-to-powder ratios (BPR), the milling speed, milling time, and the milling environment, among others. This review analyzes various papers based on the Cu-based particle generation route, which begins with a pretreatment step, then mechanical milling, its approach (top-down or bottom-up), and the post-treatment. Finally, the characterization methods of the resulting CuP and CuC through mechanical milling are also discussed.

Authoritarian Crisis Response to COVID-19 in China

What explains the Chinese government's differentiated response to the COVID-19 pandemic? This chapter argues that the same sources of control in authoritarian crisis response that enable the state to mobilize resources and people hamper the flexibility and nimbleness needed to adapt amid uncertainty. It analyzes how political priorities in a predominantly top-down system and experience with past infectious disease outbreaks shape the public health approach to COVID-19 and examines the response from late 2019 through mid-2022 in three approximate phases: early missteps and institutional impediments, rapid shift in response effectiveness, and top-down control and cracks in zero-COVID. Initial reactions were dispersed and incremental as local officials wrestled with how loudly to sound the alarms on the emergence of a new respiratory virus that seemed to be spreading. Beijing eventually backed a centralized, coordinated effort. The ramped-up response was effective, if authoritarian and heavy-handed at times. Since then, the scale and speed of the state's ability to assemble testing, tracing, quarantining, and isolating capacity and other measures enabled China to generally enclose inevitable flare-ups in most of 2020 and 2021. But unyielding pursuit of dynamic zero-COVID policy through mid-2022 reveals a fragile flip side of dogged top-down control. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Drum Up SUPPORT: Systematic Analysis of Image-Schematic Conceptual Metaphors

Conceptual metaphors represent a cognitive mechanism to transfer knowledge structures from one onto another domain. Image-schematic conceptual metaphors (ISCMs) specialize on transferring sensorimotor experiences to domains. Natural language is believed to provide evidence of such metaphors. However, approaches to verify this hypothesis largely rely on top-down methods, gathering examples by way of introspection, or on manual corpus analyses. In order to contribute towards a method that is systematic and can be replicated, we propose to bring together existing processing steps in a pipeline to detect ISCMs, exemplified for the image schema SUPPORT in the COVID-19 domain. This pipeline consists of neural metaphor detection, dependency parsing to uncover construction patterns, clustering, and BERT-based frame annotation of dependent constructions to analyze ISCMs. © 2022 Association for Computational Linguistics.

Business transformation in an age of turbulence - Lessons learned from COVID-19.

The COVID-19 pandemic has caused global economic turmoil. Although many companies have suffered huge losses, some have flourished by changing their old ways of doing business. We investigate the business transformation process under drastic market changes and time pressure, with a focus on decision speed and structure in the decision & planning phase, the implementation structure and monitoring in the implementation phase, and reinforcement after the implementation. Through case studies in a variety of industries, including manufacturing, e-commerce, and finance, we explore how companies in specific contexts have dealt with the above-mentioned critical factors when transforming their business during the pandemic, whether the experienced transformation processes differ from theory, and if so, how. The examples of business transformations cover eight categories, including work from home, the use of augmented reality, internet of things, and business model redesign. Our findings reveal how these transformations are perceived and evaluated by companies one year into the pandemic. In addition, we show how decision speed, structure of the decision-making process, structure of the implementation process, and scale of the implementation impact the completion time of the transformations. Based on our results, we provide suggestions to companies for an effective business transformation in times of crisis.

The Management of a Private Peruvian University at Pandemic Times: Assessment of Decisions and Implications on the Key Indicators

The management of a private Peruvian university along the period 2020-2021 is presented. Special attention has been paid on the qualitative angle in the sense that were described the main actions by which have had as central point the continuity of academic activities without the breaking of communications in the form top-down between the general manager and students. Essentially all actions have targeted to keep the quality of education in all the levels. The paper presents the general methodology that has consisted in the support of university to the universe of students in order that most of them continue in their program. Therefore, the management was not only the one applied to the university apparatus itself but also in to surpass the big obstacles such as the massive desertion of students in a critic epoch where Lima city has exhibited large peaks of infections as well as fatalities at the first and the second wave of pandemic at the first semester of 2021. Noteworthy actions have been taken by the general manager to conserve the desired harmony at the university even when communications have been done through the remote mode. The conclusion from the analysis of this paper is finally given. © 2022 ACM.

Big data Citizen-centred smart city governance. Evidence from Wuhan and the Coronavirus battle

Smart City governance is a topical subject and many scholars have developed diverse top-down and bottom-up models and frameworks. This paper presents insights from a qualitative and exploratory investigation from the city of Wuhan, China. It proposes and develops a novel urban governance, citizen-oriented and leveraging different emerging technologies such as mobile, social media and Big data. Our empirical results describe the actions realized by the Wuhan local government against the coronavirus epidemic disease between January and March 2020 to monitor the temperature of the citizenship and authorize or not their displacement in order to minimize the cross-contamination and avoid a large human mortality. Our conclusions corroborate the existence of this novel ICT urban governance model. In doing so, the paper advances our understanding of modern urban organization model which comprises of a 360° citizen holistic view, a data-oriented decision-making process and a centralized perspective of the citizen during all the data life cycle. The heuristic that manages this new governance model suggests ex-ante actions at individual or group level and largely exploits public and private sector information breaking (temporarily if necessary) the individual privacy rules for the purpose of its action. © 2022 IEEE.

Digital transformation of professional healthcare practices: fitness seeking across a rugged value landscape

Digital transformation (DT) is typically described as a strategic, top-down initiative where new digital technologies fundamentally disrupt an organisation's structure, procedures, and processes to enhance its value proposition. We propose a middle-range theory which highlights that DT of professional practices in healthcare follows a different path. To build this theory, we transpose the metaphor of a "fitness landscape” from evolutionary biology to a professional healthcare context to build an intermediate conceptualisation, which is then refined through an empirical study. Our theory highlights that external events, such as the COVID-19 pandemic, changing patient behaviours or the availability of new digital resources, transform the "value landscape” upon which healthcare professionals create and deliver healthcare services to patients. Empowered by their professional autonomy and driven by their service orientation, healthcare professionals search for new paths and peaks for value creation and delivery across a rugged landscape. As digital resources are leveraged, new value propositions in practice emerge, and professional healthcare practices are digitally transformed. © The Operational Research Society 2023.

How does a Rational Agent Act in an Epidemic?

The evolution of a disease in a large population is a function of the top-down policy measures from a centralized planner and the self-interested decisions (to be socially active) of individual agents in a large heterogeneous population. This paper is concerned with understanding the latter based on a mean-field type optimal control model. Specifically, the model is used to investigate the role of partial information on an agent's decision-making and study the impact of such decisions by a large number of agents on the spread of the virus in the population. The motivation comes from the presymptomatic and asymptomatic spread of the COVID-19 virus, where an agent unwittingly spreads the virus. We show that even in a setting with fully rational agents, limited information on the viral state can result in epidemic growth. © 2022 IEEE.

Detecting Traces of Narrative Evolution on Telegram: Inductive Methods from Corpus-Based Discourse Analysis

In the face of world-changing events, narratives on the messaging platform Telegram, including instances of disinformation, tend to arise and evolve at high speeds. However, key signals of this process, including newly emerging or idiosyncratic concepts, often elude traditional, top-down analyses. Addressing the need for inductive approaches to narrative evolution on Telegram, this paper operationalizes quantitative methods from the field of corpus-based discourse analysis. On a technical and methodological level, the paper discusses how data from Telegram's messages and images can be collected and preprocessed for the purposes of a ‘keyness' (Log Ratio) analysis that surfaces salient nouns and verbs for further investigation. On an empirical level, this method is then applied to a case study of 225 predominantly Dutch-speaking Telegram channels (spanning the period March 2017- March 2022), revealing some of the dynamics that govern their recent shift from propagating narratives about the coronavirus pandemic to narratives concerning the war in Ukraine. This case study is accompanied by an interactive demonstrator that enables readers to further explore the processed dataset. The paper concludes with a reflection on the status of and future avenues for this ‘distant reading' approach in relation to established interpretative practices. © 2022 Copyright for this paper by its authors.

LEARNING LAB METHODOLOGY FOR EXPANSIVE LEARNING AND INCLUSIVE EDUCATION DURING THE COVID-19 PANDEMIC IN BRAZIL

The global policies of inclusive education often ignored local knowledge and cultural-historical ecologies. As a result, the top-down policies become either irrelevant or oppressive. This study presents a formative intervention study, Learning Lab, conducted in Brazil to design a new system at specialized school for blind and visually impaired students. Fourteen practitioners engaged in nine meetings with the final goal of producing a new system of inclusive education for students with multiple disabilities during the COVID-19 Pandemic. We will present the expansive learning actions, which educators took as a conduit for critical dialogue, collective agency and expansive learning for designing the future of their school. © ISLS.

Experiencing the COVID-19 Emergency: Age-Related Disequilibrating Event for Identity.

The experience linked to the COVID-19 emergency constituted a turning point in the biography of most Italians. The suspension of usual activities, the redefinition of life contexts and the restriction of relationships have opened up wide spaces and time for thinking and reflecting on oneself, which may have triggered processes of redefinition of personal identity. The general aim of this study was to explore the impact of pandemic on daily life in the life span, in order to support the hypothesis that the pandemic experience could be considered a disequilibrating life-event and a turning point in the biography of most Italians. A mixed research approach was adopted, with 14 closed and open questions created ad hoc. 41 participants (87% women, average age 40.71), resident in the Campania region, in southern Italy, responded to the online written interview. The data were analyzed by two independent coders, using categorical content analysis with a top-down approach. Membership of the different age groups (young adults, adults, elderly) was assessed as a comparison variable. Findings qualify pandemic-related experiences as a disequilibrating life event, potentially capable of activating, alongside emotionally dense experiences, adaptive and functional resources for identity reconsideration, with differences being age based. The dimensions of change, the affective dimensions, the resources and the areas of risk identified, allowed us to identify three different clusters, showing a differentiation according to age groups, which identifies young adults and the elderly as the subjects most at risk.

Hybrid Education in Higher Education on the Example of Academic Teachers' Experiences in Post-pandemic Reality

The article concerns the experiences of academic teachers related to hybrid education at the end of the SARS-CoV-2 coronavirus pandemic. The aim of the study was to understand the lecturers' perspective on hybrid education implemented in the first semester of the 2021/2022 academic year at The Maria Grzegorzewska University and an attempt to compare it with traditional education and distance education. The subject of the research was, among others, readiness to implement hybrid teaching, university support for lecturers in the field of hybrid teaching and the diversity of experiences of academic teachers. The research used the method of diagnostic survey. The obtained results indicate that the lecturers declare their readiness to conduct hybrid teaching, especially in the case of their own or students' illness, or random factors that make it impossible to conduct full-time classes or top-down legal regulations. They appreciate the organizational support of their immediate supervisor and the opportunity to make up for classes that have not taken place in a hybrid form. The lecturers highly assess the level of their own involvement in the preparation and conduct of classes, as well as the quality of their didactic work. They see the possibility of using a hybrid approach not only in teaching but also in their self-improvement, work organization and maintaining health. At the same time, they indicate the shortcomings and difficulties related to didactics, social, technical, and organizational aspects, as well as systemic deficiencies. Based on the results, recommendations related to the use of hybrid education in post-pandemic academic education were developed. © The Author(s).

The impact of psychological flexibility on family dynamics amidst the COVID-19 pandemic: A longitudinal perspective.

Background: Health risks associated with contracting COVID-19, stay-at-home orders, and pandemic-related economic and social hardships created unique challenges for individuals throughout the pandemic, and in particular for families whose daily routines were disrupted at the start of the pandemic. This study applied a contextual behavioral science lens to Family Systems Theory to examine the impact of COVID-19 stressors on family and individual functioning. Methods: A sample of 742 coparents (86% married/engaged; 84% Caucasian; 71% female; M = 40.7 years old, SD = 8.1; M income = $82,435, SD income = $27,604) of school-aged children (5-18 years old) completed a baseline survey from late March to late April 2020. Of the initial sample, 556 coparents completed weekly diaries for 8 weeks. Results: Mediation models were tested within a multilevel path modeling framework to evaluate both the stable, between-family differences (i.e., at level 2) and the within-family changes from week to week (i.e., at level 1). Across both levels of the model, parent psychological inflexibility was robustly linked to poorer functioning across all levels of the family system, showing direct links to a majority of the processes assessed. The results further supported a top-down spillover cascade in which parent inflexibility was proximally linked to greater COVID-19 related stress and parent depressive symptoms, which were proximally linked to poorer romantic functioning (greater negative conflict, lower satisfaction), which were proximally linked to poorer family functioning (greater coparent discord and family chaos), which were proximally linked to poorer parenting (greater angry/reactive parenting), which was proximally linked to greater child distress. Multi-group models suggested that the results were largely stable across (1) parent race (white vs non-white), (2) family size (1 child vs 2 or more), (3) child age (less than 10 years old vs 10 or older), (4) parent age (under 40 vs. 40 or older), (5) perceived COVID-19 risk, (6) parent gender (mothers vs fathers), (7) household income groups (less than $100k vs $100k or more), and (8) perceived economic stress/uncertainty (low vs high). However, a handful of moderated effects emerged from those multi-group models suggesting that fathers might be slightly more prone to negative spillover effects across the family systems and that wealthier families might have experienced the stress of new demands (e.g., homeschooling, remote working) as more disruptive. Conclusions: Results highlight the crucial role parental psychological flexibility and inflexibility play in families managing the stress of COVID-19, as well as key mechanisms for how those stressors may either reverberate or become dampened throughout the family system.

COVID-19 Social Distance Surveillance Using Deep Learning

COVID-19 disease discovered from the novel corona virus can spread through close contact with a COVID-19 infected person. One of the measures advised to contain the spread of the virus is to maintain social distancing by minimizing contact between potentially infected individuals and healthy individuals or between population groups with high rates of transmission and population groups with no or low-levels of transmission. Motivated by this practice, we propose a deep learning framework for social distance detection and monitoring using surveillance video that can aid in reducing the impact of COVID-19 pandemic. This work utilizes YOLO, Detectron2 and DETR pre-trained models for detecting humans in a video frame to obtain bounding boxes and their coordinates. Bottom-centre points of the boxes were determined and were then transformed to top-down view for accurate measurement of distances between the detected humans. Based on the depth of each bottom-centre point estimated using monodepth2, dynamic distance between pairs of bounding boxes and corresponding distance threshold (safe distance) to prevent violation of social distancing norm were computed. Bounding boxes which violate the distance threshold were categorized as unsafe. All the experiments were conducted on publicly available Oxford Town Center, PETS2009 and VIRAT dataset. Results showed that Detectron2 with top-down view transformation and distance thresholding using pixel depth estimation outperformed other state-of-the-art models. The major contribution of this work is the estimation and integration of variable depth information in obtaining the distance threshold for evaluating social distances between humans in videos. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Heuristics Approach Based Expert System for Covid-19 Infection Susceptibility

A heuristic approach-based top-down automaton for assessing the potential risk of covid-19 is presented here. A set of non-obvious factors are employed to assess the risk of covid-19 infection in a person. A minimum of five factors are used as input factors for this algorithmic flow. One example is the number of close relatives the person has being taken as a input for risk calculation of covid-19.

Enterprise Resource Planning Based Mobile Application For Hospitals To Manage Covid-19 Division

The introduction of Enterprise Resources Planning or ERP-based mobile application was initiated in hospitals to manage the COVID-19 infections which are represented here to procure, allocate as well as alert those health care experts who are involved in various kinds of resources such as oxygen supply, drugs as well as the availability of beds. A very simple top-down information is the main basis on which the application is performing. At least one other person will be updating various resources and the data which is validated. The application will also include different profiles of various health care experts such as doctors, nurses as well as ward attendees. Shortly after work, various portfolios could be provided to those individuals who are the personal attendees of any patient.

Anthropogenic CO2 emission reduction during the COVID-19 pandemic in Nanchang City, China.

China is the largest CO2 emitting country on Earth. During the COVID-19 pandemic, China implemented strict government control measures on both outdoor activity and industrial production. These control measures, therefore, were expected to significantly reduce anthropogenic CO2 emissions. However, large discrepancies still exist in the estimated anthropogenic CO2 emission reduction rate caused by COVID-19 restrictions, with values ranging from 10% to 40% among different approaches. Here, we selected Nanchang city, located in eastern China, to examine the impact of COVID-19 on CO2 emissions. Continuous atmospheric CO2 and ground-level CO observations from January 1st to April 30th, 2019 to 2021 were used with the WRF-STILT atmospheric transport model and a priori emissions. And a multiplicative scaling factor and Bayesian inversion method were applied to constrain anthropogenic CO2 emissions before, during, and after the COVID-19 pandemic. We found a 37.1-40.2% emission reduction when compared to the COVID-19 pandemic in 2020 with the same period in 2019. Carbon dioxide emissions from the power industry and manufacturing industry decreased by 54.5% and 18.9% during the pandemic period. The power industry accounted for 73.9% of total CO2 reductions during COVID-19. Further, emissions in 2021 were 14.3-14.9% larger than in 2019, indicating that economic activity quickly recovered to pre-pandemic conditions.

Super-resolution wavelets for recovery of arbitrarily close point-masses with arbitrarily small coefficients

Three families of super-resolution (SR) wavelets Ψv,ng(x), Ψu,n,ms(x) and Ψw,n,mds(x), to be called Gaussian SR (GSR), spline SR (SSR) and dual-spline SR (DSSR) wavelets, respectively, are introduced in this paper for resolving the super-resolution problem of recovering any point-mass h(y)=∑ℓ=1Lcℓδ(y−σℓ), with ;σℓ−σk;≥η for ℓ≠k, σℓ≠0, and ;cℓ;>η⁎ for all ℓ,k=1,…,L, where η>0 and η⁎>0 are allowed to be arbitrarily small. Let Ψα,n=Ψv,ng, Ψu,n,ms or Ψw,n,mds, with α=v,u or w, respectively, where m=12,1,2,⋯ is suppressed. The SR wavelets are designed to have the n-th order of vanishing moments, with Fourier transform of their complex conjugates Ψ¯ˆα,n(x) to possess the following properties: (i) Ψ¯ˆα,n(x)≥0 for all x∈R, (ii) maxx⁡Ψ¯ˆα,n(x)=Ψ¯ˆα,n(κ)=ξn, where κ≐2.331122371 and ξ≐1.449222080 are positive constants independent of n,α and m, and (iii) the widths (or standard deviations) of Ψ¯ˆα,n(x), with center at κ, tends to 0 very fast for large values of α. While the most popular approach to resolve this super-resolution problem is to consider the Fourier transform d(x)=∑ℓ=1Lcℓe−iσℓx of h(y) as the “data function” for solving the inverse problem of recovering L, σ1,⋯,σL and c1,⋯,cL of the point-mass d(x), our proposed approach is to consider the “enhanced data function” D(a;α,n):=FΨα,n(a)=∑ℓ=1LcℓΨ¯ˆα,n(aσℓ), where FΨα,n(a), to be called the search function in this paper, is obtained by taking the continuous wavelet transform (CWT): (WΨα,nd)(t,a)=∫−∞∞Ψα,n(y−ta)‾d(y)dya of the data function d(x), with Ψα,n as the analysis wavelet, followed by applying wavelet thresholding to “de-noise” the data function d(x), by choosing an appropriate thresholding parameter γ>0, with γ<η⁎×ξn, in order not to remove any of the coefficients cℓ, where ℓ=1,⋯,L;and finally by setting t=0. Hence, the enhanced data function D(a;α,n) is at least cleaner than the data function d(x). In our proposed approach, instead of directly recovering σ1,⋯,σL as in the published literature, we propose a “divide and conquer” strategy: first by applying “bottom-up thresholding” of the search function FΨα,n(a), with thresholding parameter γ⁎>0 close to but not exceeding η⁎×ξn, to separate the set of the local extrema locations aℓ:=κσℓ of the function FΨα,n(a) in {a∈R:a≠0} into disjoint intervals of clusters, with more and smaller intervals and less number of local extrema aℓ in each interval for larger values of α;and secondly, by applying “top-down thresholding” to extract, one-by-one, of all local maxima, followed by all local minima (after a sign change), for each and every cluster. A desired leeway Δ>0 and lower bounds of the choice of the width parameter α are derived for the iterative application of top-down thresholding. Extension to Rs for s≥2 is also studied in this paper. For s=2, we observe that the imagery of the enhanced data function for a single point-mass at (σ1,σ2) where σ1,σ2≠0, resembles that of an “Airy disk” with center at (κ/σ1,κ/σ2) in light microscopy and celestial telescopy of point-masses.

Mechanisms of the Chinese Government's Efforts to Fight COVID-19: Integration of Top-Down Interventions and Local Governance.

The experiences and lessons of China's response to COVID-19 have been described in several studies, but the mechanisms of the Chinese government's efforts to fight COVID-19 have not been well characterized. Despite strong policy directives and orders from the central government, the response and handling of the epidemic also reflected distinctive characteristics of local governments in terms of their governance systems and capacities. In this article, we analyze public health policies and mechanisms of the Chinese government's response to COVID-19 based on the integration of top-down and local governance. A compendium of key events and measures provides the foundation for our analysis. Mechanisms related to leadership, emergency response, centralized mobilization, and accountability fully reflect the decisive measures for top-down interventions in the face of emergencies. China's policies and mechanisms to address the COVID-19 pandemic are consistent with its party-state bureaucracy and socioeconomic context. However, lower levels of government have used "repeated increments" and "one-size-fits-all" practices in the implementation of antiepidemic policies. Conservative local officials are more averse to social innovation and favor strict controls to manage the pandemic. Moreover, even under a unified system, there are substantial differences in the capacity and level of crisis management among local governments, especially in the mobilization of nonprofit organizations and volunteers. In this case study, we aim to expand the existing understanding of the tension between top-down interventions and local governance innovations.

Fostering Engagement of Underserved Communities with Credible Health Information on Social Media

The COVID-19 pandemic has necessitated rapid top-down dissemination of reliable and actionable information. This presents unique challenges in engaging low-literate communities that live in poverty and lack access to the Internet. We describe the design and deployment of a voice-based social media platform, accessible over simple phones, for actively engaging such communities in Pakistan with reliable COVID information. We developed three strategies to overcome users' hesitation, mistrust, and skepticism in engaging with COVID content. Users were: (1) encouraged to listen to reliable COVID advisory, (2) incentivized to share authentic content with others, and (3) prompted to critically think about COVID-related information behaviors. Using a mixed-methods evaluation, we show that users approached with all three strategies had a significantly higher engagement with COVID content compared to others. We discuss how new designs of social media can enable users to engage with and propagate authentic information. © 2022 ACM.