Airline catering supply chain performance during pandemic disruption: a Bayesian network modelling approach

PurposeThe supply chain (SC) encompasses all actions related to meeting customer requests and transferring materials upstream to meet those demands. Organisations must operate towards increasing SC efficiency and effectiveness to meet SC objectives. Although most businesses expected the coronavirus disease 2019 (COVID-19) pandemic to severely negatively impact their SCs, they did not know how to model disruptions or their effects on performance in the event of a pandemic, leading to delayed responses, an incomplete understanding of the pandemic's effects and late deployment of recovery measures. Therefore, this study aims to consider the impact of implementing Bayesian network (BN) modelling to measure SC performance in the airline catering context.Design/methodology/approachThis study presents a method for modelling and quantifying SC performance assessment for airline catering. In the COVID-19 context, the researchers proposed a BN model to measure SC performance and risk events and quantify the consequences of pandemic disruptions.FindingsThe study simulates and measures the impact of different triggers on SC performance and business continuity using forward and backward propagation analysis, among other BN features, enabling us to combine various SC perspectives and explicitly account for pandemic scenarios.Originality/valueThis study's findings offer a fresh theoretical perspective on the use of BNs in pandemic SC disruption modelling. The findings can be used as a decision-making tool to predict and better understand how pandemics affect SC performance.

Thermal Performance Assessment of Envelope Retrofits for Existing School Buildings in a Hot–Humid Climate: A Case Study in Chennai, India

This study aims to propose building envelope retrofit packages for existing naturally ventilated school buildings in the hot–humid climatic region of Chennai, India. Indoor thermal parameters were collected through field studies from nine sample classrooms of a selected school building in May 2019, between 9.00 am and 4.00 pm. The thermal performance assessment of the existing building was performed by examining the discomfort hours using the CBE thermal comfort tool. Envelope retrofit strategies gathered from the literature and building standards were applied and studied through simulation. The findings reveal the enormous potential to increase the thermal comfort of existing school buildings through envelope retrofit measures. The results demonstrate that the whole-building temperature can be reduced up to 3.2 °C in summer and up to 3.4 °C in winter. Implementing retrofit measures to the building envelopes of existing buildings will help school owners to increase the comfortable hours of whole buildings by up to 17%. In comparison, annual energy savings of up to 13% for the whole building can be made by enhancing the thermal performance of the building envelope. The findings will also help architects to optimise thermal performance and energy usage with minimal interventions.

Patient-centric soulbound NFT framework for electronic health record (EHR)

Interest in leveraging blockchain technology to boost healthcare and e-health solutions has lately increased. Blockchain has proven to have enormous promise in a range of e-health industries because of its decentralized and reliable nature, including the secure exchange of electronic health records (EHRs) and database access management among numerous medical entities. A unique paradigm known as the "patient-centric approach” places the patient at the center of the healthcare system and gives them complete control over who has access to and can share their personal health information. Strong confidentiality and safety requirements are necessary for health information. Additionally, other concerns must be resolved, such as secrecy, interoperability, scalability, cost-effectiveness, and timeliness. This paper offers a patient-centric privacy-preserving framework for an efficient and safe medical record to address these problems. Based on three parameters transaction cost, execution time, and gas cost. Three blockchain platforms are compared by using the smart contract to find out the suitable platform for the implementation of this framework. Blockchain platforms served as a benchmark for the performance assessment of a designed framework. Although blockchain will not fix every issue in healthcare organizations, it will undoubtedly assist in dramatically reducing some of the most critical ones.

Analysis of environmental performance and interactivity of ports and regions

The port is the basic support for regional economic development and the global allocation of resources. With the rapid development of China's economy and growing ecological awareness, the assessment of port and regional efficiency has received unprecedented attention. In the current context of the COVID-19 pandemic, how the port and its region will be coordinated under the common goal of development has become a hot topic. In this study, the port subsystem (P-subsystem) and the regional subsystem (R-subsystem) are unified into the port–region system (PR system), and a new meta-frontier two-stage data envelopment analysis model is constructed to evaluate the P-subsystem efficiency and the environmental efficiency of the PR system. This research also measures the port–regional coordination level using the coordination index and explores the inefficiency of the PR system with the help of management improvement and technology improvement indices. Main results show that the overall efficiency of the Chinese PR system is increasing. The technological level of the PR system in coastal areas is close to the optimal level. The inefficiency of the Chinese PR system is mainly affected by management inefficiency. The coordination of regional and port development in China is also poor. Finally, on the basis of the research findings, this study provides targeted countermeasure suggestions to promote the efficiency enhancement and coordinated development of the PR system. © 2023 Elsevier Ltd

Motor Coordination and Its Importance in Practicing Performance Movement

The training of good motor coordination optimizes the motor skills, and these, over time, lead to the improvement of the motor skills specific to the practiced movement. The purpose of this study was to assess the capacity and speed of learning coordinated movements in the context of working in an online system. At the same time, we set out to evaluate the level of motor coordination achieved through training using the eLearning platform Hudl and the Teaching Games for Understanding approach. Thus, three groups of students were analyzed whose motor histories were different. The analysis of the three tested groups was performed in the first year of study and in the third year of study. The training programs have been adjusted/modified according to the COVID-19 pandemic situation, which has determined their application in the online system as well. The results of this study confirm that by assisting learning through computer programs, in the online system, these workouts can be effective. At the same time, the study shows us that, in addition to the natural evolution from childhood and adolescence, an advanced form of motor coordination appears, which is installed through the action of learning. © 2023 by the authors.

Learning assessment challenges from students and faculty perception in times of COVID-19: A case study

A mixed-method study about the perception of students and faculty around learning assessment practices was conducted in a multicampus competency-based approached Mexican private university. The objective was getting new knowledge about higher education community perception around learning assessment practices, learning outcomes production and how authentic assessment was driven while working on different modalities during the pandemic: remote learning, synchronous hybrid learning, alternate hybrid learning, and on-site modality. A questionnaire, and an interview for faculty and focus groups for students were designed, validated, and conducted. A total of 281 faculty and 908 students participated in this study. The main quantitative results indicate that students who took on-site classes evaluate the variables better than those who took hybrid classes. In addition, students who took remote classes evaluate the authenticity variable better than those who took it in alternate hybrid modality. In the case of the faculty, only the equality variable showed significant differences between the reported modalities. Besides, the main qualitative results indicate that perceptions are quite different between faculty and students while getting their perceptions from an evaluation standards scope. Thus, their perspectives around equality, authenticity, feasibility, reliability and ethics were obtained and discussed against literature. The main conclusions of the study remarked that students and faculty were positive towards most of the execution of learning assessment and learning outcomes practices during the pandemic. Nevertheless, students' preference of on-site modality was determined as the way they have more opportunities for interacting and learning more from assessment and feedback. © 2023 by authors;.

Supervisor incivility and frontline employees' performance amid the COVID-19 pandemic: A multilevel moderated mediation analysis

Underpinned by conservation of resources (COR) theory, the study examines how supervisor incivility affects in- and extra-role performance by assessing the intermediary role of self-efficacy of frontline employees (FLEs) and moderating role of person-job fit (P-J Fit) at the store-level in the COVID-19 context. The study samples 366 FLEs from 48 retail stores in India. The findings show that the association between supervisor incivility and FLEs' in- and extra-role performance through self-efficacy is only strong when the P-J Fit remains weak. The theoretical model backed by empirical findings provides potential value to the existing literature. © 2023 Elsevier Ltd

Assessing the impact of COVID-19 on the performance of organ transplant services using data envelopment analysis.

Organ transplant is one of the best options for many medical conditions, and in many cases, it may be the only treatment option. Recent evidence suggests, however, that the COVID-19 pandemic might have detrimentally affected the provision of this type of healthcare services. The main purpose of this article is to use Data Envelopment Analysis and the Malmquist Index to assess the impact that the pandemic caused by the novel coronavirus SARS-CoV-2 had on the provision of solid organ transplant services. To this purpose, we use three complementary models, each focusing on specific aspects of the organ donation and transplantation process, and data from Brazil, which has one of the most extensive public organ transplant programs in the world. Using data from 17 States plus the Federal District, the results of our analysis show a significant drop in the performance of the services in terms of the organ donation and transplantation process from 2018 to 2020, but the results also indicate that not all aspects of the process and States were equally affected. Furthermore, by using different models, this research also allows us to gain a more comprehensive and informative assessment of the performance of the States in delivering this type of service and identify opportunities for reciprocal learning, expanding our knowledge on this important issue and offering opportunities for further research.

Automatic evaluation of open-ended questions for online learning. A systematic mapping

The assessment of students' performances in Higher Education is one of the essential components of teaching activities. Open-ended tasks allow a more in-depth assessment of students' learning levels, but their evaluation and grading are time-consuming and prone to subjective bias. Since the Covid-19 pandemic, most traditional Higher Education courses converted to online courses;automatic grading and feedback tools and methods (AGFTM) have become critical components of online learning systems, especially with regards to short answers and essays assessment. This work frames the recent advancement in AGFTM through a systematic mapping of the research field and a literature review. This analysis gives an overview of the trends, specific goals, methods, quality of proposals, challenges and limitations in this research area. The results indicate that it is a growing research area, with a large set of techniques involved, but still not mature, where practical implementations have yet to come. © 2023 Elsevier Ltd

Tea Culture Tourism Perception: A Study on the Harmony of Importance and Performance

Tea culture tourism is a product of the combination of agricultural tourism and ecotourism. After the COVID-19 period, this product is more and more popular. Tourism performance is an important index for measuring the development level of tourist destinations, and research on the influencing factors of tourism performance is an important way to promote the high-quality development of tea culture tourism. Using the tea tourism town of Wushan as a case study, 452 valid questionnaires were used as research data, and exploratory factor analysis, paired sample t-test and IPA analysis were applied. The results indicate that: (1) tourism performance is mainly divided into 5 dimensions and 22 specific indicators, including service quality, resource environment, tourism transportation, tourism-supporting facilities and tea tourism products;(2) there is a significant difference between the degree of importance and performance of visitors to each indicator, and the overall tourism performance of the case sites at an average level;(3) convenient service, professional service, business management, park traffic, parking conditions, environmental design, shopping environment, tea quality, and tea culture characteristics are potential advantageous factors, and ‘service with a smile', accessibility, trail layout, overall image, air quality, natural scenery, landscape vignettes, network communication, public toilets, sanitation facilities, tourist service centers, tea travel activities, and tourism souvenirs are areas in need of improvement. © 2023 by the authors.

Application of "Behind the Barriers" Model at Neighbourhood Scale to Improve Water Management under Multi-Risks Scenarios: A Case Study in Lyon, France.

In modern urban areas, water management highly depends on the socio-ecological urban water cycle (UWC) that heavily relies on water infrastructures. However, increasing water-related hazards, natural and/or human-based, makes it difficult to balance water resources in the socio-ecological UWC. In the last decade, urban infrastructure resilience has rapidly become a popular topic in disaster risk management and inspired many studies and operational approaches. Among these theories and methods, the "Behind the Barriers" model (BB model), developed by Barroca and Serre in 2013, is considered a theory that allows effective and comprehensive analysis of urban infrastructure resilience through cognitive, functional, correlative, and organisational dimensions. Moreover, this analysis can be a reference to develop actions that improve infrastructure resilience under critical scenarios. Therefore, this study aims to study resilience design actions based on the BB model to achieve socio-ecological water balance and assess the performance of these actions. The study focuses on water management on a neighbourhood scale, which is considered the essential urban unit to study and improve the resilience of critical infrastructures, such as water services. The Part-Dieu neighbourhood in Lyon, France is selected as a case study, and it highlights the need to develop indicators to assess the performance of implemented actions in a structural and global resilience framework, to understand urban systems as complex and dynamic systems to provide decision support, and to strengthen crisis prevention and management perspectives in a dynamic approach.

How can banks and finance companies incorporate value chain factors in their risk management strategy? The case of agro-food firms

A value chain framework for guiding the financial firms in their credit decisions is urgent, as the current COVID-19 pandemic has highlighted, but missing in the extant literature, particularly for those that lend to industries sensitive to value and supply chain bottlenecks. This study creates knowledge in value chain finance, a big untapped and un-researched market. It constructs, confirms, and validates a value chain framework for assessing risks in lending to Agro and Food Processing firms in which value chain risks are major business concerns globally. To pursue the objectives of the study, we use a novel methodology that integrates the Modified Delphi technique, exploratory factor analysis, confirmatory factor analysis, and discriminant analysis. Based on testing and analysis of primary data, including loan data, a framework comprising six factors is proposed for use in conjunction with existing risk assessment models of finance companies to improve the quality of their credit decisions, contributing to their performance sustainability. © 2022 ERP Environment and John Wiley & Sons Ltd.

Implications of Design Assumptions for Pressure Sewer Network Performance: A New Zealand Study

Pressure sewer networks offer a flexible alternative to more traditional gravity-based systems for the conveyance of wastewater. Some of the issues associated with pressure sewer networks (e.g., odor, septicity) arise from inappropriate design assumptions. Daily inflow volumes are a crucial part of the design of pressure sewer systems;gravity design parameters are presently used to design pressure sewer networks in New Zealand. This study analyzed flow data from six representative pressure sewer networks (approximately 24% of operating pump units in New Zealand) to identify the daily inflow volumes per connected pump unit. The results indicated that the median inflow volume was approximately 410 L/pump unit/day. This inflow is much lower than current council design standard assumptions, which range from 650 to 1,000 L/pump unit/day. Pressure sewer network designs using higher daily loading rates may result in oversized networks that are detrimental to the network's operation and performance, especially for meeting minimum self-cleansing velocities and wastewater retention times. The data collection period included the first COVID-19 lockdown in New Zealand. Four lockdown levels were introduced, with Level 4 and Level 3 being the most restrictive and requiring all but essential workers to stay and work from home. Levels 1 and 2 allowed people to return to their place of work. The data indicated that the Level 4 lockdown period caused a 25% increase in daily inflow volumes. In comparison, the Level 3 and 2 lockdown periods increased the daily inflow volumes by 20% and 15%, respectively. The analysis also included the networks' wet-weather responses. Minor rain events did not significantly affect the daily inflow volumes. However, gravity networks that have been retrofitted with pressure sewer networks may be more subject to aging or damaged laterals and illegal stormwater connections, both of which are likely to result in a more significant wet-weather response. The paper also discusses the issues associated with an overreliance on standardized design methods without understanding their proper application and the pitfalls of adopting gravity sewer design assumptions for pressure sewer network designs. The findings of this paper will further allow determination of the sensitivity of network design outcomes, performance, and maintenance requirements to the design methods and assumptions for pressure sewer networks, not only in New Zealand but in any country that uses the technology. © 2022 American Society of Civil Engineers.

Curriculum, instruction, and assessment: A snapshot of world language education in Massachusetts

This large-scale study used a survey to collect data on K-12 world language classrooms in Massachusetts public schools, focusing on core instructional practices, curriculum, and assessment. The study resulted in 383 individual teacher completed responses, representing 188 districts, which was analyzed using descriptive statistics. Results indicate encouraging signs in the adoption of core proficiency-based instructional practices, thematic curriculum design, and the use of performance-based assessments. Further support for teachers in how to implement these practices is needed, along with attention to school leaders who may have no background in world language education but are tasked with supporting and evaluating world language teachers. Survey data were collected at the beginning of school closures due to COVID-19, capturing a picture of K-12 world language education and a point of comparison for future research.

Application of machine learning approaches to predict the impact of ambient air pollution on outpatient visits for acute respiratory infections

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R2 = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R2 = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases. © 2022 Elsevier B.V.

Status of the health information system in Ireland and its fitness to support health system performance assessment: a multimethod assessment based on stakeholder involvement.

BACKGROUND: Between 2019 and 2021, the first Irish health system performance assessment (HSPA) framework was developed. As routinely collected health data are necessary to continuously populate indicators of an HSPA framework, a purpose-driven assessment of the health information system (HIS) in Ireland and its fitness to support the implementation of an HSPA framework was conducted. This study reports on the status of the Irish HIS through a multimethod assessment based on continuous broad stakeholder involvement. METHODS: Between May and November 2020, over 50 informants were engaged in individual and group interviews and stakeholder consultation workshops as part of the HIS assessment process. Descriptive themes and high-level data availability heatmaps were derived from interview and workshop data using thematic analysis. Indicator "passports" for the HSPA framework were populated during stakeholder consultation workshops and analysed using univariate descriptive statistics. RESULTS: The HIS in Ireland was able to provide administrative, survey and registry-based data for public sector acute care services, focusing on structure, process and output metrics. Significant data availability gaps, most notably from primary care, private hospitals and community care, were reported, with little availability of electronic health record and people-reported data. Data on outcome metrics were mostly missing, as were linkage possibilities across datasets for care pathway monitoring. The COVID-19 pandemic highlighted the national HIS's shortcomings but also the capacity for rapid development and improvement. CONCLUSIONS: A tailor-made assessment of the HIS in Ireland, involving a broad set of relevant stakeholders, revealed strengths, weaknesses and areas for improvement in the Irish health data landscape. It also contributed to the development of a national HSPA framework and momentum to further strengthen data infrastructure and governance, while working towards a more data-driven and person-centred healthcare system. This work demonstrates the utility of an inclusive HIS assessment process and is applicable beyond Ireland, where this case study was conducted.

A New Intelligent System for Evaluating and Assisting Students in Laboratory Learning Management System

Due to the Covid-19 epidemic the need for digital E-learning systems become mandatory. Also, most sectors that faced a shortage in E-learning systems are performing laboratory experiments remotely. For this reason, this research paper focuses on providing a complete Laboratory Learning Management System (LLMS) with generic and intelligent performance evaluation for experiments. The new LLMS offers many services from intelligently and automatically doing performance assessments and assistance for the students while performing the experiments online. The new performance assessment module provides regular assessment for experimental steps added to it the intelligent automatic assessment that detects if the students performed the experiments correctly from their mouse dynamics using an AI algorithm. Moreover, the new LLMS uses an analytic module to provide the teachers with analyzed results and charts to describe the behavior of students in various performed experiments. Regarding, the new performance assistant module provides students with complete assistance by pressing the help button to trigger the virtual tutor to explain any experimental steps. Furthermore, it intelligently to collects the mouse dynamics of the student performing the experiments and uses AI algorithms to detect if students face difficulties and provide them with suitable help automatically. Moreover, it can open a chat session with a real teaching assistant or a classmate to help the students. Furthermore, the new performance assessment and assistant services are considered generic because they used the mouse dynamic behavior of students which is suitable for any type of software used in the laboratory, without the need for a special device or extra cost. © 2022 IEEE.

Towards a global One Health index: a potential assessment tool for One Health performance.

BACKGROUND: A One Health approach has been increasingly mainstreamed by the international community, as it provides for holistic thinking in recognizing the close links and inter-dependence of the health of humans, animals and the environment. However, the dearth of real-world evidence has hampered application of a One Health approach in shaping policies and practice. This study proposes the development of a potential evaluation tool for One Health performance, in order to contribute to the scientific measurement of One Health approach and the identification of gaps where One Health capacity building is most urgently needed. METHODS: We describe five steps towards a global One Health index (GOHI), including (i) framework formulation; (ii) indicator selection; (iii) database building; (iv) weight determination; and (v) GOHI scores calculation. A cell-like framework for GOHI is proposed, which comprises an external drivers index (EDI), an intrinsic drivers index (IDI) and a core drivers index (CDI). We construct the indicator scheme for GOHI based on this framework after multiple rounds of panel discussions with our expert advisory committee. A fuzzy analytical hierarchy process is adopted to determine the weights for each of the indicators. RESULTS: The weighted indicator scheme of GOHI comprises three first-level indicators, 13 second-level indicators, and 57 third-level indicators. According to the pilot analysis based on the data from more than 200 countries/territories the GOHI scores overall are far from ideal (the highest score of 65.0 out of a maximum score of 100), and we found considerable variations among different countries/territories (31.8-65.0). The results from the pilot analysis are consistent with the results from a literature review, which suggests that a GOHI as a potential tool for the assessment of One Health performance might be feasible. CONCLUSIONS: GOHI-subject to rigorous validation-would represent the world's first evaluation tool that constructs the conceptual framework from a holistic perspective of One Health. Future application of GOHI might promote a common understanding of a strong One Health approach and provide reference for promoting effective measures to strengthen One Health capacity building. With further adaptations under various scenarios, GOHI, along with its technical protocols and databases, will be updated regularly to address current technical limitations, and capture new knowledge.

Impact of Coronavirus Disease 2019 Pandemic on Providing the Objective Structured Clinical Examination: A Faculty of Pharmacy Guidance

The outbreak of the Coronavirus 2019 pandemic presented a challenge for every Faculty of pharmacy that conducts objective structured clinical examinations throughout the academic year. It is necessary to ensure that pharmacy students are welltrained and prepared to enter the clinical workforce during the crisis caused by this pandemic. Due to the pandemic, the Faculty of Pharmacy at King Abdulaziz University embraces the challenge of ensuring that the upcoming pharmacy students will complete their academic year requirements, including the objective structured clinical examination. This paper provides details of how the objective structured clinical examination was designed and managed during the coexisting Coronavirus 2019 pandemic. It also assists other faculties of pharmacy that need to plan objective structured clinical examinations to ensure the validity and reliability of performance assessments while protecting the safety of all participants.

Calculation and Assessment of CO2e Emissions in Road Freight Transportation: A Greek Case Study

Road freight transportation is already contributing significantly to global warming, and its emissions are predicted to grow dramatically in the following years. Carbon footprint calculation can be used to assess CO2e emissions to understand how an organization’s activities impact global sustainability. To this end, the main objective of this paper is initially to assess the impact of Green House Gas (GHG) emissions stemming from road freight transportation. Subsequently, we adopt the EN 16258 standard to calculate the carbon footprint of a truck fleet of a freight transport operator in Greece. Based on the obtained results, we assess the performance of the company’s fleet by adopting relevant sustainability indicators. We also evaluate the use of CNG as an alternative fuel and its impact on CO2e emissions and operational costs. The paper concludes with a list of additional measures toward further reduction and offsetting of CO2e emissions.