The Application of Public Relations in Modern Enterprise Management

With the development of global economy and society, public relations, as a new management discipline, is more and more applied to enterprise management. At the same time, the definition of public relations in the development process has always been different, each definition explains the characteristics of public relations from different aspects. Therefore, it is particularly important to discuss the role of public relations in enterprise management. Combined with the actual case analysis, public relations in enterprise management can not only build a good image for enterprises, can help enterprises deal with the crisis through difficulties, but also can coordinate the relationship between enterprises and the public.with the development and progress of modern enterprises, public relations is no longer an activity mode of external publicity, but an indispensable management mode in the process of continuous development of enterprises. The scientific management of public relations can not only create a successful brand for the enterprise, but also pave the way for the scientific management within the enterprise, and reasonably regulate the relationship between the enterprise and the outside society, as well as the relationship between the enterprise employees. This paper discusses the application of public relations in enterprise management.

Performance of Cathodes Fabricated from Mixture of Active Materials Obtained from Recycled Lithium-Ion Batteries

The cathode performance of lithium-ion batteries (LIBs) fabricated from recycled cathode active materials is studied for three scenarios. These scenarios are based on the conditions for separation of different cathode active materials in recycling facilities during the LIB’s recycling process. In scenario one, the separation process is performed ideally, and the obtained pure single cathode active material is used to make new LIBs after regeneration. In scenario two, the separation of active materials is performed with efficiencies of less than 100%, which is the actual case in the recycling process. In this scenario, a single cathode active material that contains a little of the other types of cathode active materials is used to make new LIBs after the materials’ regeneration. In scenario three, the separation has not been performed during the recycling process. In this scenario, all types of cathode active materials are regenerated together, and a mixture is used to make new LIBs. The studies are performed through modeling and computer simulation, and several experiments are conducted for validation purposes. The cathode active materials that are studied are the five commercially available cathodes made of LiMn2O4 (LMO), LiCoO2 (LCO), LiNixMnyCo(1−x−y)O2 (NMC), LiNixCoyAl(1−x−y)O2 (NCA), and LiFePO4 (LFP). The results indicate that the fabrication of new LIBs with a mixture of cathode active materials is possible when cathode active materials are not ideally separated from each other. However, it is recommended that the separation process is added to the recycling process, at least for the separation of LFP or reducing its amount in the cathode active materials mixture. This is because of the difference of the voltage level of LFP compared to the other studied active materials for cathodes.

Evaluating Pallet Investment Strategy Using Fuzzy Analytic Network Processes: A Case in Chinese Chain Supermarkets

Presently in Chinese chain supermarkets, many enterprises have built automatic equipment and information facilities in the logistics center of their supply chain systems. Modern logistics technology and equipment largely depend on the resource integration of each role in the chain (such as suppliers, manufacturers, wholesalers, and retailers), especially logistics facilities and equipment resources, to realize the circulation of products. The pallet, which is an indispensable basic tool for a supply chain system in the process of product circulation, is most often used in the handling, stacking, storage, and transportation of products. The process of building automation and informationization in the supply chain system of Chinese supermarket chains requires the solving of the problems of cost and sharing pallets in logistics operations. Large-scale enterprises often spend millions of dollars on investment, the failure of which can cause significant harm to the enterprise. Therefore, the authors of this paper adopted the fuzzy analytic network process (FANP), combining fuzzy and ANP models to evaluate our studied case. We utilized an actual case as the research object to resolve the important decisions regarding pallet resource sharing investment in the supply chain system. Importantly, it is expected that the proposed method can provide an important reference standard or a new idea for decision makers in the chain supermarket industry or related industries.

Dynamic analysis and evaluation of asymptomatic infection in the spread of COVID-19

COVID-19 has spread worldwide for nearly two years. Many countries have experienced repeated epidemics, that is, after the epidemic has been controlled for a period of time, the number of new cases per day is low, and the outbreak will occur again a few months later. In order to study the relationship between this low level of infection and the number of asymptomatic infections, and to evaluate the role of asymptomatic infections in the development of the epidemic, we have established an improved infectious disease dynamics model that can be used to evaluate the spread of the COVID-19 epidemic, and fitted the epidemic data in the three flat periods in England. According to the obtained parameters, according to the calculation of the model, the proportion of asymptomatic infections in these three flat periods are 41%, 53% and 58% respectively. After the first flat period, the number of daily newly confirmed cases predicted by the model began to increase around July 1, 2020. After more than four months of epidemic spread, it reached a peak on November 12, which is consistent with the actual case situation. Unanimous. After the second flat period, the model predicts that the number of new confirmed cases per day will increase from about May 7, 2021, and after about 73 days of epidemic development, it will reach a peak on July 20, showing the overall trend of the epidemic. In the above, the predicted results of the model are consistent with the actual cases. After the third flat period, the number of daily newly diagnosed cases predicted by the model began to increase around December 1, 2021, and reached a peak in December, and the number of cases will drop to a very low level after May 2022. According to our research results, due to the large number of asymptomatic infections, the spread of the epidemic is not easy to stop completely in a short time. However, when the epidemic enters a period of flat time, nucleic acid testing is performed, and asymptomatic infections are isolated at home for 14 days (the recovery period of symptomatic infection is about 10 days) may be an option that can be considered to interrupt the transmission of the case.

A Multistate Comparison Study of COVID-19 Cases Among Accredited and Nonaccredited Nursing Homes

Widely acknowledged is the disproportionate number of COVID-19 cases among nursing home residents. This observational study examined the relationship between accreditation status and COVID-19 case rates in states where the numbers and proportions of Joint Commission accredited facilities made such comparisons possible (Illinois (IL), Florida (FL), and Massachusetts (MA)). COVID-19 data were accessed from the Centers for Medicare & Medicaid Services (CMS) Nursing Home Compare Public Use File, which included retrospective COVID-19 data submitted by nursing homes to the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network. The outcome variable was the total number of nursing home-identified COVID-19 cases from June 2020 to January 2021. Joint Commission accreditation status was the independent variable. Mediating factors included state, and county-level case rates. Increases in the county rate had a significant association with higher nursing home COVID-19 case rates ( p < .001). After adjusting for county case rates, no differences were observed in the mean group case rates for accredited and nonaccredited nursing homes. However, comparing predicted case rates to actual case rates revealed that accredited nursing homes were more closely aligned with their predicted rates. Performance of the nonaccredited nursing homes was more variable and had proportionally more outliers compared to accredited nursing homes. Community prevalence of COVID-19 is the strongest predictor of nursing home cases. While accreditation status did not have an impact on overall mean group performance, nonaccredited nursing homes had greater variation in performance and a higher proportion of negative outliers. Accreditation was associated with more consistent performance during the COVID-19 pandemic, despite being located in counties with a higher prevalence of COVID-19.

COVID-19 infection dynamics revealed by SARS-CoV-2 wastewater sequencing analysis and deconvolution

The use of RNA sequencing from wastewater samples is proven to be a valuable way for estimating infection dynamics and circulating lineages of SARS-CoV-2. This approach has the advantage of being independent from patient population testing and symptomatic disease courses. However, it is equally important to develop easily accessible and scalable tools which can highlight critical changes in infection rates and dynamics over time across different locations given the sequencing data from the wastewater. Here we provide the first analysis of variant dynamics in Germany using wastewater sequencing and present PiGx SARS-CoV-2, a bit-by-bit reproducible end-to-end pipeline with comprehensive reports. To our knowledge, this is the first pipeline that includes all steps from raw-data to shareable reports, additional taxonomic analysis, deconvolution and geospatial time series analysis. Using our pipeline on a dataset of wastewater samples, from different locations across Berlin, over the time period from February 2021 to June 2021, we could reconstruct the dynamic of the Variant of Concern (VoC) B.1.1.7 (alpha). Additionally, we detected the unique signature mutation M:T26767C for the VoC B.1.617.2 (delta) and its raise in early June. We also show that SARS-CoV-2 mutation load measured from wastewater sequencing is correlated with actual case numbers and it has potential to be used in a predictive manner. All in all, our study provides additional evidence that systematic wastewater analysis using sequencing and computational methods can be used for modeling the infection dynamics of SARS-CoV-2. In addition, the results show that our tool can be used to tease out new mutations and to detect any emerging new lineages of concern before clinical detection. Our approach can support efforts for establishing continuous monitoring and early-warning projects for COVID-19 or any other infectious disease.

Active disturbance rejection motion control of spherical robot with parameter tuning

Purpose The characteristics of spherical robots, such as under-drive, non-holonomic constraints and strong coupling, make it difficult to establish its motion control model accurately. To improve the anti-interference performance of spherical robots in practical engineering, this paper proposes a spherical robot motion controller based on auto-disturbance rejection control (ADRC) with parameter tuning. Design/methodology/approach This paper considers the influences of the spherical shell, internal frame and pendulum on the movement of the spherical robot during the rotation to establish the multi-body dynamics model of the XK-I spherical robot. Due to the serious coupling problem of the dynamic model, the motion control state equation is constructed using linearization and decoupling. The XK-I spherical robot PSO-ADRC motion controller with parameter tuning function is designed by combining the state equation with the particle swarm optimization (PSO) algorithm. Finally, experiments are performed to evaluate the feasibility of PSO-ADRC in an actual case compared to ADRC, PSO-PID and PID. Findings By analyzing the required time to reach the expected value, the control stability and the fluctuation range of the standard deviation after reaching the expected value, the superiority of PSO-ADRC to ADRC, PSO-PID and PID is demonstrated in terms of the speed and anti-interference ability. Practical implications The proposed method can be applied to the robot control field. Originality/value A parameter-tuning method for auto-disturbance-rejection motion control of the spherical robot is proposed. According to the experimental results, the anti-interference ability of the spherical robot moving on uneven ground is improved. Therefore, it provides a foundation for the autonomous environmental monitoring of the spherical robot equipped with sensors.

A statistical model of COVID-19 testing in populations: effects of sampling bias andtesting errors

We develop a statistical model for the testing of disease prevalence in a population. The model assumes a binary test result, positive or negative, but allows for biases in sample selection and both type I (false positive) and type II (false negative) testing errors. Our model also incorporates multiple test types and is able to distinguish between retesting and exclusion after testing. Our quantitative framework allows us to directly interpret testing results as a function of errors and biases. By applying our testing model to COVID-19 testing data and actual case data from specific jurisdictions, we are able to estimate and provide uncertainty quantification of indices that are crucial in a pandemic, such as disease prevalence and fatality ratios. This article is part of the theme issue ‘Data science approach to infectious disease surveillance’.

Reconsolidation behavioral updating of human emotional memory: A comprehensive review and unified analysis of successes, replication failures, and clinical translation

The annulment of a human emotional memory through reconsolidation behavioral updating has been documented in over twenty laboratory studies since the first such report in 2010. However, fourteen studies have reported non-replication, the cause(s) of which remain unclear. This review examines all successful and unsuccessful studies in detail, in an attempt to identify (a) the specific probable causes of non-replication and (b) how clinical translation might optimally be designed. For analyzing non-replications, a set of criteria is defined for principled identification of specific moments of prediction error (PE) in experimental procedures, including latent cause transitions, based on a preponderance of empirical evidence. A previously overlooked element of experimental procedure is in that way identified as being potentially decisive, and a unified, testable explanation is proposed for behavioral updating successes and failures in terms of the presence or absence of a PE experience. That in turn allows successful studies to be compared for the internal experiences induced in subjects, rather than compared for their external procedures, revealing an invariant set of three experiences shared by all successful updating studies despite their diverse procedures. Clinical translation, defined as replication of those experiences, not any particular procedure, is illustrated by an actual case, one of many published cases that have documented prompt transformational change produced by that specific methodology, suggesting memory reconsolidation as the mechanism of change. Lastly, the core empirical findings of successful reconsolidation updating studies are compared with previously proposed frameworks of memory reconsolidation in psychotherapy, exposing significant departures from scientific fidelity.

The Application of Lean Methods in Corporate Sustainability—A Systematic Literature Review

This paper reviews the application of lean methods for corporate sustainability and highlights demands for future research. With the help of a systematic literature review, papers at the interface of lean and sustainability were identified and matched to a standardized list of lean methods to assess their frequency in the context of sustainability. In a further step, papers containing actual case studies were analyzed in more detail regarding specific application settings, sustainability dimensions, measurability of sustainability impact, and other criteria. The quantitative analysis of 363 publications shows frequent use of lean methods such as just in time and value stream mapping in the context of sustainability, and a surprisingly low use of other approaches such as karakuri, milk run, or chaku chaku. The in-depth analysis of 81 case studies reveals the primacy of intra-company and ecological assessments in the lean context, while social and inter-company aspects remain rather underexposed. This study complements existing research on lean and sustainability by systematically analyzing specific lean methods in the context of sustainability and by further exploring the sustainability characteristics of such lean applications.