Information and communication technologies have had a significant impact on people's quality of life in recent years. But, its educational potential has yet to be fully realized. In the wake of the covid-19 outbreak, this article presents an examination of the digital competence of university professors. The development of these talents among university professors was studied. To collect data, Google Forms was used to create online surveys. Requests were sent to the 240 professors of the Universidad Nacional Santiago Antunez de Mayolo via institutional email, and the responses of the 187 professors were included in the SPSS V26 database as a result of the outbreak. The findings show that university professors have sufficient digital skills, but their use in non-face-to-face classrooms is restricted, requiring a review of training programs in public institutions in this context of the COVID-19 epidemic. Las tecnologías de la información y la comunicación han tenido un impacto significativo en la calidad de vida de las personas en los últimos años. Pero, su potencial educativo aún no se ha realizado plenamente. A raíz del brote de covid-19, en este artículo se presenta un examen de la competencia digital de los profesores universitarios. Se estudió el desarrollo de estos talentos entre los profesores universitarios. Para recopilar datos, se utilizó Google Forms para crear encuestas en línea. Se enviaron solicitudes a los 240 profesores de la Universidad Nacional Santiago Antunez de Mayolo a través del correo electrónico institucional, y las respuestas de los 187 profesores se incluyeron en la base de datos SPSS V26 como resultado del brote. Los hallazgos muestran que los profesores universitarios tienen suficientes habilidades digitales, pero su uso en aulas no presenciales está restringido, lo que requiere una revisión de los programas de capacitación en instituciones públicas en este contexto de epidemia de COVID-19

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PurposeWith the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC managementDesign/methodology/approachPreferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.FindingsAs a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.Practical implicationsMany sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.Originality/valueThis paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

La investigación tuvo como objetivo determinar la cantidad de residuos de plásticos generados durante la pandemia. Se basa en la metodología descriptiva longitudinal, en donde se empleó el método de Kunitoshi Sakurai y se elaboraron cuestionarios sobre qué actitud toman al momento de reciclar, caracterización y cuantificación de residuos. Los resultados determinaron que en noviembre sobresalió con 57.32 %, per cápita de residuos sólidos domiciliarios el jueves con 0.49 kg/habitante/ día, porcentaje de residuos plásticos por mes con 7.48 % en noviembre, porcentaje en relación al per cápita el viernes con 10.85 % y actitud de reciclar con 61 % no reciclan. Se concluye que, en noviembre destacó con 7.48 %; es decir que en 100 Kg de residuos 7.48 Kg son plásticos. Por lo tanto, se establece como un indicador porcentual, para que se tome conciencia ecológica al momento de reciclar con el fin de reducir la contaminación.

Purpose The e-health services came up as an effective tool to mitigate effects of COVID-19 and following social distance norms. This study highlighted an issue of contentious usage intentions of e-health services among Thai older citizens. This study aims to examine the relationship of social influence (SI), information quality (IQ) and the digital literacy (DL) to contentious usage intentions. Design/methodology/approach This study follows quantitative techniques, and the sample size is 140 to analyze, that is collected from the older Thai citizens. The convenient sampling technique was used to collect the data and the items were measured by using a five-point Likert scale. Findings The findings of this study are having mixed results. The effect of DL and satisfaction (SAT) on continuous usage intention (CUI) is significant. The effect of IQ and SI on CUI is non-significant. The effect of IQ and SI on SAT is significant. Further, the mediating effect of SAT between IQ and CUI is non-significant. However, the mediating effect of SAT between SI and CUI is significant. Originality/value This study contributes to knowledge by empirical testing of DL and usage of the medicine. Furthermore, to the best of the authors’ knowledge, this study is one of the rare studies that incorporate technological intervention for drug usage intentions.