ABSTRACT In regions with water shortages, detailed planning on water resource use is essential. The use of climate models for short- and medium-range forecasts is an important strategy for obtaining early information on the water requirements of crops and the water regime of a particular basin. This study aimed to assess the performance of seasonal climate forecasts and their applicability in estimating irrigation needs. To that end, the Simulation Model for Irrigation Strategies and climate forecast data derived from the Eta model were used. To analyze simulations, five members (days 13, 14, 15, 16 and 17) of the seasonal forecasts of rainfall and reference evapotranspiration for every month between 2001 and 2012 were used. The spread for reference evapotranspiration demonstrated that the model was unable to reproduce the behavior of this variable during the dry period. Comparison between forecasts months in advance showed no significant differences between the rainfall and the reference evapotranspiration forecasts. However, the results obtained for a one-month lead-time forecast exhibited superior performance. shortages essential short mediumrange medium range basin needs end used simulations days 13 14 15 1 17 200 201 period However onemonth one leadtime lead time 20 2

RESUMO Em regiões com baixa disponibilidade hídrica é de grande importância um planejamento mais detalhado sobre o uso de recursos hídricos. A utilização de modelos climáticos destinados às previsões de curto e médio prazo se apresenta como uma estratégia importante para se obter informações antecipadas acerca da demanda hídrica de culturas e do regime hídrico de determinada bacia. Objetivou-se, neste estudo, avaliar o desempenho das previsões climáticas sazonais e sua aplicabilidade na estimativa da demanda de irrigação. Para tanto, utilizou-se o Modelo de Simulação de Estratégias de Irrigação e dados de previsão climática derivados do modelo Eta. Para análise das simulações, foi utilizado um conjunto de cinco membros (dias 13, 14, 15, 16 e 17) de previsão sazonal de precipitação e evapotranspiração de referência para cada mês entre o período de 2001 a 2012. O espalhamento para a evapotranspiração de referência demonstrou que o modelo não foi capaz de reproduzir o comportamento desta variável durante o período seco. Comparação entre previsões com os meses de antecedência não demonstraram diferenças significativas entre previsões da precipitação e da evapotranspiração de referência. Contudo, os resultados obtidos para as previsões com um mês de antecedência apresentaram melhor desempenho. hídricos bacia Objetivouse, Objetivouse Objetivou se, Objetivou-se estudo irrigação tanto utilizouse utilizou Eta simulações dias 13 14 15 1 17 200 2012 seco Contudo 20 201 2

Resumen La mayoría de los parques fotovoltaicos instalados en el territorio nacional cuentan con medios de registro y reporte, junto con la generación eléctrica, de varias variables meteorológicas que tienen influencia en su rendimiento, en particular, la radiación solar, que es medida con piranómetros. Estos instrumentos pueden presentar variaciones en sus constantes de calibración tras un uso prolongado, y requieren de un esquema de monitoreo y calibraciones periódicas. A continuación se presenta un método de validación preliminar de los datos de radiación solar en los parques fotovoltaicos, que puede ir indicando en qué parques se están reportando valores erróneos de radiación solar. El método compara los valores horarios reportados cada día en cada parque con los estimados por el modelo numérico de pronóstico WRF y en los días donde la correlación entre ambas series es superior a 0.985, calcula entones la relación entre las sumas de cada serie. Si el valor esta relación es próximo a 1, se puede considerar que el piranómetro de ese parque funciona correctamente. Se presentan los resultados de la evaluación de los reportes de radiación solar en un conjunto de parques fotovoltaicos conectados a la red eléctrica nacional.

Abstract The majority of photovoltaic parks installed in the national territory have means of recording and reporting, along with electricity generation, several meteorological variables that influence their performance, in particular, solar radiation, which is measured with pyranometers. These instruments may present variations in their calibration constants after prolonged use, and require a monitoring scheme and periodic calibrations. Below is a preliminary validation method for solar radiation data in photovoltaic parks, which can indicate in which parks erroneous solar radiation values are being reported. The method compares the hourly values reported each day in each park with those estimated by the WRF numerical forecast model and on days where the correlation between both series is greater than 0.985, it then calculates the relationship between the sums of each series. If the value of this ratio is close to 1, it can be considered that the pyranometer of that park is working correctly. The results of the evaluation of solar radiation reports in a set of photovoltaic parks connected to the national electrical grid are presented.

Resumen La investigación tiene como objetivo la elaboración de un modelo agrometeorológico de pronóstico del rendimiento agrícola azucarero. Se tomaron los rendimientos por cepas y totales, área de cada cepa y total, y edad de la plantación de 13 Unidades Empresariales de Base de las provincias Cienfuegos, Sancti Spíritus y Ciego de Ávila en el período 1980-2015; así como, registros mensuales de precipitación, temperatura media y evapotranspiración de siete estaciones meteorológicas. Se calculó el Índice Potencial Productivo según la fase fenológica en la que se encuentre para comprobar su grado de efectividad. Para el procesamiento estadístico se utilizó el tabulador Excel, STATISTICA versión 8.0.5 y el módulo matemático SciPy. La efectividad de las estimaciones de rendimiento agrícola obtenidas con el modelo presentado para las zafras 2011 - 2015, se comparó usando el coeficiente de determinación R2, analizando la relación establecida entre las variables regresoras y el predictando. El modelo de regresión lineal múltiple permite realizar pronósticos de rendimiento agrícola con precisión y ajuste, en dependencia de los escenarios comerciales concretos de la producción cañera del país. La provincia Ciego de Ávila revela, de las tres en estudio, el mayor grado de efectividad en la estimación del rendimiento agrícola de la caña de azúcar.

Abstract The objective of the research is the development of an agrometeorological model for forecasting sugar agricultural yield. The yields by strains and totals, area of each strain and total, and age of the plantation were taken from 13 Management Business Units in the Cienfuegos, Sancti Spíritus and Ciego de Ávila provinces in the period 1980-2015; as well as monthly records of precipitation, average temperature and evapotranspiration from seven meteorological stations. The Productive Potential Index was calculated according to the phenological phase in which it is found to verify its degree of effectiveness. For statistical processing, the Excel tabulator, STATISTICA version 8.0.5 and the SciPy mathematical module were used. The effectiveness of the agricultural yield estimates obtained with the model presented for the 2011 - 2015 harvests was compared using the coefficient of determination R2, analyzing the relationship established between the regressor variables and the predictand. The multiple linear regression model allows agricultural performance forecasts to be made with precision and adjustment, depending on the specific commercial scenarios of the country's sugarcane production. The province of Ciego de Ávila reveals, of the three under study, the highest degree of effectiveness in estimating the agricultural yield of sugar cane.

Resumen Los efectos desfavorables de las condiciones meteorológicas sobre la salud de la población cubana están aumentando en frecuencia e intensidad, debido a los impactos ya visibles del cambio climático sobre Cuba, problema que demanda realizar la evaluación de la vulnerabilidad de la población cubana ante los peligros regionales asociados a los procesos meteorológicos que influyen sobre el país. Se realiza una adaptación de la metodología utilizada en Cuba para los estudios de peligro, vulnerabilidad y riesgo, aplicada en este caso a la estimación del riesgo meteoro-trópico, a partir de establecer la línea base de la mortalidad general diaria en exceso para el período 2001-2020, como indicador de la vulnerabilidad de las poblaciones residentes en las mitades occidental y oriental de Cuba; para después estimar el peligro asociado a los procesos sinópticos de escala global y regional que influyen sobre esas mismas porciones del territorio. Se demuestra que existe una relación bien definida entre la mortalidad en exceso y los peligros analizados, lo cual permitió estimar satisfactoriamente la magnitud del riesgo meteoro-trópico diario y llegar a un modelo estadístico que facilita su pronóstico a corto plazo. Se comprueba la génesis meteoro-trópica de los días con mayor mortalidad en exceso, tanto en invierno como en verano, demostrando el relevante papel que tienen algunos procesos y condiciones meteorológicas sobre la salud de la población cubana, hecho que justifica la necesidad de su pronóstico y mitigación.

Abstract The unfavorable effects of meteorological conditions on the health of the Cuban population are increasing in frequency and intensity, due to the already visible impacts of climate change on Cuba, a problem that demands an evaluation of the vulnerability of the Cuban population to regional dangers. Associated with the meteorological processes that influence the country. An adaptation of the methodology used in Cuba for studies of danger, vulnerability and risk is carried out, applied in this case to the estimation of meteor-tropic risk, based on establishing the baseline of the general daily excess mortality for the period. 2001-2020, as an indicator of the vulnerability of the populations residing in the western and eastern halves of Cuba; to then estimate the danger associated with global and regional synoptic processes that influence those same portions of the territory. It is demonstrated that there is a well-defined relationship between excess mortality and the hazards analyzed, which allowed us to satisfactorily estimate the magnitude of the daily meteor-tropic risk and arrive at a statistical model that facilitates its short-term forecast. The meteor-tropic genesis of the days with the highest excess mortality is verified, both in winter and summer, demonstrating the relevant role that some meteorological processes and conditions have on the health of the Cuban population, a fact that justifies the need for its forecast and mitigation.

Resumen: Durante la construcción, los recursos no controlados impactan el desempeño del proyecto. La Gestión del Valor Ganado (GVG) es un método ampliamente utilizado para la gestión de proyectos basado en el control de tiempos y costos. Los avances en las Tecnologías de la Información (TI) brindan opciones para mejorar el método GVG. El GVG es un método a nivel de proyecto que excluye detallar el comportamiento de los parámetros del proyecto a nivel de operaciones de construcción, se manejan en términos económicos agregados a lo largo del tiempo. Por lo tanto, este trabajo estudia la mejora del GVG utilizando TI para expresar el manejo de variables operativas. Este artículo utiliza un proyecto de construcción de carreteras como caso de estudio, para evaluar tres enfoques (es decir, Red Bayesiana (RB), Red Neuronal Artificial (RNA) y EVM-RNA Híbrida) como opciones de mejora para el método GVG. Se encontró que la RNA proporciona la mejor mejora de los resultados del GVG. El uso de la RNA y los parámetros del proyecto mejora el manejo del GVG. Al tener una mayor efectividad en los pronósticos, se espera que mejore la calidad y disponibilidad de los datos para la toma de decisiones, una condición que a su vez puede mejorar la agilidad y adaptabilidad de los resultados del proyecto tal como está construido. El modelo EVM-ANN utiliza parámetros que influyen en la finalización de la implementación del proyecto, lo que facilita la evaluación del desempeño del tiempo del proyecto en función de diversas condiciones en el campo para que el proyecto pueda obtener la mejor estrategia para garantizar su finalización a tiempo.

Abstract: During construction, uncontrolled resources impact project performance. Earned Value Management (EVM) is a widespread method used for project management based on time and cost control. Advances in Information Technology (IT) provide options to improve the EVM method. The EVM is a project-level method that excludes detailing the behavior of project parameters at the level of construction operations, they are handled in aggregated economic terms over time. Thus, this work studies the improvement of EVM using IT to express the handling of operational variables. This article uses a road construction project as a case study, to evaluate three approaches (i.e., Bayesian Network (BN), Artificial Neural Network (ANN), and Hybrid EVM-ANN) as improvement options for the EVM method. It was found that the ANN provides the best improvement of EVM results. The use of ANN and project parameters improves the handling of EVM. By mayor forecast effectiveness, is expected to improve the quality and availability of data for decision making, a condition which in turn may improve agility and adaptability of the project as-built outcomes. The model EVM-ANN uses parameters that influence project implementation completion, making it easier to assess project time performance based on various conditions in the field so that the project can obtain the best strategy to ensure project completion on time.

Resumo Introdução: A epidemic intelligence (EI) assegura a deteção precoce, a avaliação e a comunicação das ameaças para a saúde pública para definir prioridades e mobilizar recursos para a investigação, vigilância, prevenção e controlo. Em Portugal, a Direção-Geral da Saúde (DGS) é responsável pela EI e publica semanalmente um relatório de ameaças para a saúde pública (RONDA) que é partilhado com a rede de autoridades de saúde, instituições e profissionais de saúde pública. As alterações nas ameaças comunicadas em relatórios periódicos de ameaças desde a COVID-19 não foram descritas anteriormente. Métodos: Comparámos as ameaças reportadas na RONDA entre 2016 a 2022 em três períodos sequenciais: antes da COVID-19 (janeiro de 2016 - março de 2020), P2 durante as restrições (abril de 2020 - fevereiro de 2022) e P3 na fase pós-aguda da COVID-19 (fevereiro de 2022 - setembro de 2022). Comparamos a frequência média mensal de ameaças não COVID-19 relatadas entre todas as ameaças relatadas nesses períodos, considerando diferentes categorias dentro do grupo de doenças, foco geográfico e fontes de informação. Resultados: As ameaças não-COVID-19 tiveram uma diminuição na frequência média mensal de reporte no Período2 (14,7 vs. 2,3 p < 0.001) em comparação com o Período1, antes da COVID-19. Houve um retorno ao padrão pré-pandêmico de notificação no Período 3 (14,67 vs. 17,63 p < 0.208) para ameaças não COVID-19 com um aumento nas doenças virais emergentes (2,20 vs. 7,62 p < 0.001). O ECDC e a OMS são as fontes de informação mais frequentes, seguidas das fontes nacionais de saúde pública. Conclusões: Durante a COVID-19, houve alterações no reporte de ameaças em Portugal. A COVID-19 possivelmente afetou a EI e os relatórios de ameaças epidémicas globais, possivelmente desviando a atenção e os recursos de outras ameaças para a pandemia. No entanto, a quantidade de ameaças que justificam o acompanhamento e a comunicação pode estar a aumentar. É necessária investigação em comunicação de ameaças detetadas no âmbito da EI a fim de assegurar que todas as ameaças relevantes são avaliadas e comunicadas de acordo com os objetivos da EI, garantindo simultaneamente o investimento em recursos e a preparação para a prevenção e resposta.

Abstract Background: Epidemic intelligence (EI) ensures early detection, assessment, and communication of public health threats. Threat reporting defines priorities and mobilize resources for surveillance, prevention, and control. In Portugal, the Directorate-General of Health (DGS) is responsible for EI and publishes a weekly public health threat report (RONDA). Changes in threats in regular threat reports since COVID-19 have not been previously described. We analysed changes in non-COVID threat reporting in the weekly threat report. Methods: Using the DGS Emergency Operations Centre’s threat reporting database, we compared threats reported in RONDAs from 2016 to 2022 in three sequential periods: P1 before COVID-19 (January 2016-March 2020), P2 during acute COVID-19 restrictions (April 2020-February 2022), and P3 in post-acute COVID-19 phase (February 2022-September 2022). We described the monthly average frequency of reports on non-COVID-19 threats in those periods considering different disease groups, geographical focus, and information sources. We estimated expected non-COVID-19 reports on threats using a forecast model fitted to the time series until March 2020 and compared observed and expected values. Results: Non-COVID-19 threats had a decrease in the monthly average frequency of reporting in period 2 (14,7 vs. 2,3 p < 0.001) compared to period 1. Using the forecast methods, there were 114 fewer non-COVID threats than the 162 expected (−70%) in period 2. In period 3, there were 105 more threats than expected (+256%). The ECDC and the WHO were the most frequent sources of information followed by national Public Health sources. Conclusions: During COVID-19, there was a decrease in reports on non-COVID threats in Portugal. COVID-19 possibly affected global EI, by shifting attention and resources from other threats to the pandemic. However, the number of threats that warrant follow-up and communication is increasing. Further research is necessary to inform the EI research and development agenda, to ensure that all relevant threats are detected, accessed, and communicated according to evolving EI objectives and priorities while resources and preparedness are guaranteed.

Abstract The objective of this research is to determine a model to help municipalities estimate their performance in fiscal evaluations and implement actions to improve the results in their local management. The EVIEWS software was used to calculate the estimated model through multiple linear regression. The results indicate the fiscal capacity, tax autonomy, and property tax are the ones that best explain the fiscal performance of municipalities and also the impact that each of these indicators has on the final result of the evaluations.

Resumen La presente investigación tiene como objetivo la determinación de un modelo para ayudar a los municipios a estimar su desempeño en evaluaciones fiscales e implementar acciones para mejorar los resultados en su gestión local. Se utilizó el software EViews para el cálculo del modelo estimativo mediante una regresión lineal múltiple. Los resultados indican que la capacidad fiscal, la autonomía tributaria y el predial son las variables que mejor explican el desempeño fiscal de los municipios; además, muestran el impacto que tiene cada uno de estos indicadores en el resultado final de las evaluaciones.

ABSTRACT Global solar radiation (Qg) is of paramount importance for several functions, such as photosynthesis and other biological processes, technologies based on solar energy (production of electricity and hot water), estimation of evapotranspiration (irrigation management), and forecast of crops, among other activities, at zero cost. This study aimed to develop a new methodology to estimate the daily and monthly value of global solar radiation based on the power generated by a 10 W photovoltaic solar panel. The methodology performance was assessed by comparing the Qg values estimated by the new method and the Qg values observed in a weather station, and also calculated by the SunDATA software and observed in the NASA POWER system. High r, R2, and Willmott coefficient values (close to 1), a low mean absolute error (MAE) of 0.202 kWh m−2 per day, a low mean bias error (MBE) of −0.146 kWh m−2 per day, a low mean percentage error (MPE) of 3.25%, and a low root mean square error (RMSE) of 0.292 kWh m−2 per day were obtained, confirming the excellent accuracy and reliability of the proposed methodology to estimate Qg. The NASA POWER system and SunDATA software presented similar values for the entire study period compared to the observed data, but not as good as the proposed technique. Thus, the proposed methodology had high performance in estimating Qg. (Qg functions processes production water, water , water) irrigation management, management management) crops activities cost 1 panel station r R2 R close 1, 1) MAE (MAE 0202 0 202 0.20 m2 m 2 m− MBE (MBE 0146 146 −0.14 MPE (MPE 325 3 25 3.25% RMSE (RMSE 0292 292 0.29 obtained data technique Thus 020 20 0.2 014 14 −0.1 32 3.25 029 29 02 0. 01 −0. 3.2 −0 3. −

RESUMO A radiação solar global (Qg) é de suma importância para diversas funções, como fotossíntese e outros processos biológicos, tecnologias baseadas em energia solar (produção de eletricidade e água quente), estimativa da evapotranspiração (manejo da irrigação), previsão de cultivos, entre outras atividades, a custo zero. Este estudo teve como objetivo desenvolver uma nova metodologia para estimar o valor diário e mensal da radiação solar global com base na potência gerada por um painel solar fotovoltáico de 10 W. O desempenho da metodologia foi avaliado pela comparação entre os valores de Qg estimados pelo novo método e os valores de Qg observados em uma estação metereológica, e também pelos valores calculados pelo software SunDATA e os observados no sistema NASA POWER. Altos valores de r, R2 e coeficiente de Willmott (próximos de 1), baixo erro médio absoluto (MAE) de 0,202 kWh m-2 por dia, baixo erro médio da estimativa (MBE) de -0,146 kWh m-2 por dia, baixo erro médio percentual (MPE) de 3,25% e baixa raiz do erro quadrático médio (RMSE) de 0,292 kWh m-2 por dia foram obtidos, confirmando a excelente acurácia e confiabilidade da metodologia proposta para estimar o Qg. O sistema NASA POWER e o software SunDATA apresentaram valores semelhantes para todo o período de estudo em relação aos dados observados, mas os da presente metodologia foram melhores. Assim, a metodologia proposta apresentou alto desempenho na estimativa da Qg. (Qg funções biológicos produção quente, quente , quente) manejo irrigação, irrigação irrigação) cultivos atividades zero 1 W metereológica r R próximos 1, 1) MAE (MAE 0202 0 202 0,20 m2 m 2 m- MBE (MBE 0,146 0146 146 -0,14 MPE (MPE 325 3 25 3,25 RMSE (RMSE 0292 292 0,29 obtidos melhores Assim 020 20 0,2 0,14 014 14 -0,1 32 3,2 029 29 02 0, 0,1 01 -0, 3, -0 -

Abstract The objective of this paper is to analyze the historical behavior of student enrollment in a technological high mid-level school, in Ciudad Juárez, Chihuahua, in order to estimate future demand, to identify the required infrastructure capacity in the institution, in terms of classrooms and teaching staff and calculate the student-teacher and student-classroom ratios and compare them with the international and Mexican average ratios. This is due to the fact that at the beginning of the school cycles, there were situations of lack of capacity to serve the students on time, having to improvise in the adequacy of the facilities and teaching staff. Different methods of quantitative forecasts were reviewed that, according to the historical behavior of the data, the one that most closely adheres to mentioned behavior was used. Data from 15 school periods available since its inauguration were collected. Data treatment begins with normality tests in order to establish the statistic that was used. Once the appropriate forecast model was used, it was validated with 5 periods to check if the calculated forecasts adhered to the real data that was presented from period 16 to 20, likewise, the statistical hypothesis tests were carried out for validation of the models used. Tests were performed with different level and trend smoothing factors, using the one that showed the lowest error per period, which ranged from 0.21% to 8.88%. The ratios student-teacher and student-class found were 36 and 38 respectively.

Resumo O objetivo deste artigo é analisar o comportamento histórico da matrícula de alunos em uma escola secundária tecnológica em Ciudad Juárez, Chihuahua, a fim de estimar a demanda futura. O objetivo é determinar a capacidade de infraestrutura necessária na instituição em termos de salas de aula e pessoal docente, e calcular as proporções aluno-professor e aluno-sala de aula para compará-las com as proporções médias internacionais e mexicanas. Isto porque, no início dos ciclos escolares, costumam surgir situações de falta de capacidade para atender os alunos atempadamente, razão pela qual foi necessário improvisar na adaptação das instalações e do corpo docente. Para este estudo, foram revisados diferentes métodos de previsão quantitativa; A partir disso, e de acordo com o comportamento histórico dos dados, foi utilizado aquele que mais aderiu a esse comportamento. Especificamente, foram coletados dados de 15 períodos letivos disponíveis desde a sua inauguração. O tratamento dos dados iniciou-se com testes de normalidade para estabelecer as estatísticas utilizadas. Uma vez utilizado o modelo de previsão adequado, foi validado com 5 períodos para verificar se as previsões calculadas estão de acordo com os dados reais que foram apresentados do período 16 ao 20; Da mesma forma, foram realizados testes de hipóteses estatísticas para validar o modelo utilizado. Além disso, foram realizados testes com diferentes níveis e fatores de suavização de tendência, sendo utilizado aquele que apresentou menor erro por período, que variou de 0,21% a 8,88%. As proporções aluno-professor e aluno-sala encontradas foram de 36 e 38, respectivamente.

Resumen El objetivo de este artículo es analizar el comportamiento histórico de la matrícula estudiantil en un bachillerato tecnológico de Ciudad Juárez, Chihuahua, con la finalidad de estimar la demanda futura. El propósito es determinar la capacidad requerida de infraestructura en la institución en lo referente a aulas y personal docente, y calcular las proporciones alumnos-maestro y alumnos-aula para compararlos con las proporciones medias internacionales y de México. Esto se debe a que, en los inicios de los ciclos escolares, se suelen presentar situaciones de falta de capacidad para atender al alumnado en tiempo, por lo que se tuvo que improvisar en la adecuación de las instalaciones y personal docente. Para este estudio, se revisaron diferentes métodos de pronósticos cuantitativos; a partir de esto, y de acuerdo con el comportamiento histórico de los datos, se utilizó el que más se apegaba a dicho comportamiento. En concreto, se colectaron datos de 15 periodos lectivos disponibles desde su inauguración. El tratamiento de los datos inició con pruebas de normalidad con el objetivo de establecer el estadístico que se utilizó. Una vez utilizado el modelo de pronósticos apropiado, se validó con 5 periodos para comprobar si los pronósticos calculados se apegan a los datos reales que se presentaron del periodo 16 al 20; asimismo, se realizaron las pruebas de hipótesis estadísticas para validación del modelo utilizado. Además, se efectuaron pruebas con diferentes factores de suavización de nivel y tendencia, y se empleó el que mostró el menor error por periodo, el cual varió desde 0.21 % a 8.88 %. Las proporciones alumnos-maestro y alumnos-aula encontradas fueron de 36 y 38, respectivamente.

Higher Education needs to be reimagined considering the exciting developments within virtual reality and artificial intelligence. As a new generation, Generation Alpha, better known as Gen Alpha,1 is preparing for higher education, and educators are challenged to create opportunities to meet their needs. In this study, we explore an existing paradigm, scenario planning, but within an unfamiliar context - the future of higher education. We pose the question: What are the possible future scenarios within higher education that will appeal to the Gen Alpha student and a millennial parent in a post-pandemic world? As a result, we present a scenario matrix with four learning and teaching models forecast to be successful in 2030 in higher education institutions. These four learning and teaching models are based on two axes: Social connect vs social disconnect in learning and teaching and a single career option or multiple career options as the end goal for the student. Respondents of this longitudinal study are millennial parents of Gen Alpha students. Results indicate that the three main themes that will influence the learning and teaching models of the future are learning spaces and places, glass learning, and techceptance. In line with the three themes, the three major findings were that (1) millennial parents are open to hybrid learning approaches, (2) learning on screens is important, but it should be regulated and based on set standards, and lastly (3) millennial parents are accepting technology (techceptance) as a supportive tool and learning place in higher education. Overall, there was a positive shift in perspectives on higher education regardless of the impact of the pandemic. The outcomes of the research will assist higher educational institutions to strategically align the learning and teaching offerings with the needs and resources of the future student, namely Gen Alpha.

South Sudan is expansive and sparsely populated with over 80% of the population living in rural areas. The country has no national grid connecting its cities and towns, thus making rural areas "good candidates" for stand-alone renewable energy systems. This study was conducted to determine the technical feasibility and economic viability of a stand-alone photovoltaic (PV) system compared to a diesel generator. A techno-economic model was developed to forecast the performance of the PV system. The system was initially designed using the IEEE Recommended Practice for Sizing of Stand-Alone Photovoltaic Systems (IEEE P1562-2021) and the IEEE Recommended Practice for Sizing Lead-Acid Batteries for Stand-Alone Photovoltaic Systems (IEEE 1013-2019). The solar radiation data used for modeling were acquired from the Ineichen clear sky model and then transposed to the plane of array irradiation using pvlib python. The system optimization and sensitivity analysis was performed under various diesel fuel costs using the Hybrid Optimization of Multiple Energy Resources (HOMER) software. Results show that at a fuel price of $ 2 per liter, the levelized cost of electricity (LCOE) of the PV system is 64% lower than that of the diesel generator and that the system can earn 11% return on investment (ROI) and recover the investment in about 5.5 years. With a drop in price of diesel fuel to $1 per liter, the payback period increases to about 7 years. These results show that standalone PV systems are technically feasible and economically viable in rural and peri-urban areas of South Sudan.

ABSTRACT This article describes the esential characteristics of the 2022-2023 winter season in Cuba. To create it, the summaries provided by each Provincial Meteorological Center after the passage of the cold fronts through the provinces of the country were used. In addition, the documents of the General Weather made by the Forecast Center of the Institute of Meteorology were used, as well as chronological data of cold fronts from the archive also belongs to this center. The 2022-2023 winter season began on October 19, 2022, with the arrival in Cuba of the first cold front and extended until April 30, 2023, the day on which the FF No 15 and last of this winter season affected. It was classified as not very active in relation to the climatic value (19 FF per season), finding 10 cold fronts that were classified as classic, 2 revesinos and one secondary due to its type. Regarding intensity, 13 cold fronts were weak and 2 moderate, without presenting any strong cold front this season. In addition, only two of the season's cold fronts affected the entire national territory, with 60% of these winter systems dissipating in the central region.

RESUMEN En este artículo se describen las principales características de la temporada invernal 2022-2023 en Cuba. Para la conformación del mismo se utilizaron los resúmenes que cada Centro Meteorológico Provincial tras el paso de los frentes fríos por las provincias del país. Además, se utilizaron los Estados Generales del Tiempo realizados por el Centro de Pronósticos del Instituto de Meteorología, así como los datos cronológicos sobre los frentes fríos del archivo que también lleva a cabo este centro. La temporada invernal 2022-2023 se inició el día 19 de octubre de 2022, con la llegada a Cuba del primer frente frío y se extendió hasta el 30 de abril de 2023, día en que afectó el FF No. 15 y último de esta temporada invernal. La misma fue clasificada como poco activa con relación al valor climático (19 FF por temporada), encontrándose en ella 10 frente fríos que fueron clasificados como clásicos, 2 revesinos y uno secundario por su tipo. En cuanto a la intensidad, 13 frentes fríos fueron débiles y 2 moderados, sin presentarse ningún frente frío fuerte en esta temporada. Además, solo dos de los frentes fríos de la temporada afectaron todo el territorio nacional, encontrándose que el 60 % de estos sistemas invernales se disiparon en la región central.

Abstract This study compares the performance of univariate and multivariate Long Short-Term Memory (LSTM) to predict next-day closing prices on four stocks in the consumer retail sector of the Mexican Stock Exchange. Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Median Absolute Percentage Error (MdAPE), and Root Mean Squared Error (RMSE) are used to test the networks’ performance. Results show a better performance on multivariate price forecasts when using 20-day and 15-day length sequences, generating consistent results for the sample, including illiquid and liquid stocks. On the other hand, univariate LSTM discloses lower forecast performance when predicting the price of illiquid stocks.

Resumen Este trabajo compara el desempeño de la memoria de corto y largo plazo (LSTM, por sus siglas en inglés) univariada y multivariada en la predicción de los precios de cierre del día siguiente de cuatro acciones del sector de consumo minorista en la Bolsa Mexicana de Valores. El error absoluto medio (MAE, por sus siglas en inglés), el error porcentual absoluto medio (MAPE, por sus siglas en inglés), la mediana del error porcentual absoluto (MdAPE, por sus siglas en inglés) y la raíz del error cuadrático medio (RMSE, por sus siglas en inglés) se utilizan para probar el desempeño de las redes. Por un lado, los resultados muestran un mejor desempeño en el pro nóstico multivariado de precios cuando se utilizan secuencias de 20 y 15 días de duración, generando resultados coherentes para la muestra, incluidas las acciones líquidas e ilíquidas. Por otro lado, la LSTM univariada revela un desempeño de pronóstico menor para la predicción del precio de acciones ilíquidas.

Probability-based empirical methods were employed as an alternative approach to predicting uncertainties associated with rock mass properties. The focus was on developing probabilistic spreadsheets to forecast rock mass classification indexes. Histograms were constructed to describe the best distribution in predicting rock mass properties. The developed models also offer utility in predicting the impact of discontinuities within the rock mass on rock strength and rock mass classification systems. Statistical analyses identified volumetric joint count, joint spacing, joint frequency, and rock strength as the most influential parameters. Moreover, the statistical analysis revealed varying degrees of correlation among different rock mass properties. While some properties demonstrated significant correlations suitable for modelling, others did not align well with any correlation model. The results highlight the need for a comprehensive approach to rock mass characterization, considering multiple factors beyond volumetric joint count. Geological complexities, including tectonic activity and weathering processes, may obscure direct correlations. These results emphasize the importance of empirical modelling and detailed site investigations for accurate assessment of rock mass quality and stability in the Himalaya.

ABSTRACT In this work, the implementation of solar panels in the Villa Clara Dairy Products Company, UEB Sagua la Grande, is evaluated. Measurements of the structures were made and optimal orientations were chosen to improve performance. The free software of the European commission PVGIS was used to facilitate the study of the solar resource and photovoltaic potential. It is a very useful tool for carrying out feasibility studies of photovoltaic systems. With the performance analysis, an annual generation of 648.5 MWh is forecast. This approach is not only energy efficient, but environmentally significant, as it will avoid the emission of 9,453 tons of CO2, 53 tons of SO2 and 18 tons of NO2 into the atmosphere. In addition, it is highlighted that the project will contribute to saving the country 2,882 tons of fuel. These results underline the importance and potential of renewable energy, not only to reduce dependence on fossil fuels, but also to mitigate climate change by reducing greenhouse gas emissions.

RESUMEN En el presente trabajo se evalúa la implementación de paneles solares en la Empresa de Productos Lácteos Villa Clara, UEB Sagua la Grande. Se realizaron mediciones de las estructuras y se eligieron las orientaciones óptimas para mejorar el rendimiento. Se utilizó el software gratuito de la comisión europea PVGIS, para facilitar el estudio del recurso solar y el potencial fotovoltaico. Se trata de una herramienta muy útil para hacer estudios de viabilidad de sistemas fotovoltaicos. Con el análisis de rendimiento, se pronostica una generación anual de 648,5 MWh. Este enfoque no solo es energéticamente eficiente, sino ambientalmente significativo, ya que evitará la emisión de 9453 toneladas de CO2, 53 toneladas de SO2 y 18 toneladas de NO2 a la atmósfera. Además, se destaca que el proyecto contribuirá al ahorro de 2882 toneladas de combustible al país. Estos resultados subrayan la importancia y el potencial de las energías renovables, no solo para reducir la dependencia de los combustibles fósiles, sino también para mitigar el cambio climático al reducir las emisiones de los gases de efecto invernadero.