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This paper presents a finite element simulation of the hot fiat rolling of steel. An elastoplastic behaviour of steel and plane strain are assumed. The results presented here were calculated with the finite element program MARC and they have shown good agreement with experimental data.

Climate change negatively affects agriculture and food security, and jeopardizes Myanmar's agriculture, which is vital to ensure food security, rural livelihoods, and the economy. This study explores the asymmetric impacts of climate change on Myanmar's agricultural sector.

We utilize the nonlinear autoregressive distributed lag (NARDL) approach for the years 1991–2020, the Wald test to validate the asymmetric relationship between climate change and agriculture, and the FMOLS and DOLS approaches to confirm the validity of the outcomes.

Our findings reveal that temperature has a positive impact on Myanmar's agriculture, whereas rainfall and CO2 have negative effects over the long and short terms. Evidently, decreasing temperatures more favorably impact agriculture than increasing temperatures, while increasing rainfall more negatively impacts agriculture than decreasing rainfall. Increasing carbon emissions have a more detrimental effect on agriculture than decreasing them.

We gathered data over periods longer than 30 years to provide more robust findings. However, owing to data limitations, such as missing values or unavailability, the study period spans from 1991 to 2020.

This study contributes to the existing literature on the asymmetric effects of climatic and non-climatic factors on agriculture. It is the first study in Myanmar to use the NARDL approach to measuring the effects of climate change on both the agricultural gross production index and value, providing robust findings.

Post-occupancy evaluation (POE) demonstrates relevance nowadays. Because of the wide competition between construction companies, it is necessary to be assertive, so satisfied clients bring new clients through communication amongst the users. This paper aims to assist a construction company, evaluating apartment owner’s perceptions regarding the built environment, the perceived quality of services, the satisfaction and the value in use, in the context of multifamily buildings.

This paper presents quantitative research of POE, applying confirmatory factor analysis and multiple linear regression. These methods analyse how the attributes behave in each theoretical dimension and evaluate the relationship between the dimensions of the built environment and services including customer satisfaction and value in use.

The results demonstrate that the constructs associated with management aspects such as service, cause higher levels of satisfaction and, therefore, higher value in use. The results become guidelines for constructors, supporting management and project decision-making.

This study’s limitation is related to the number of questionnaires applied. The survey was applied to the apartment owners in all five buildings from a constructor, considered as the entire population of the research. For that reason, there were not used a sample. Further studies are required to improve the results, even more, using the present research in a larger sample, seeking a better generalisation. Also, future studies might evaluate other types of constructions and environments.

This paper used marketing constructs related to satisfaction, value in use and service, applied in the construction field of multifamily residential buildings.

Despite the importance of investigating the impact of cloud computing on the e-learning process, the relationship development between the two is not examined well. Thus, the main goal of this research is to assess how to improve the e-learning process by using cloud services. This paper aims to attempt to investigate the impact of cloud computing on e-learning development.

The paper is based on both quantitative and qualitative methodologies. For review-related work and statistical analysis of questionnaires, the SPSS 22 and SMART-PLS 3.2 software package are used.

The results from the study show that e-learning development is significantly influenced by the quality of services, cloud features, university readiness and users’ readiness.

The adoption of cloud technology within an instructional environment has the capacity of offering new opportunities for improvement and innovation for gaining knowledge of the process.

This study aims to examine the asymmetric effects of average temperature (TP) and rainfall (RF) on the Moroccan food security, measured by the food production index (FPI), using annual data from 1961 to 2020.

The study uses the Climate Change and Food Security Framework (CCFS) developed by the Food and Agriculture Organization (FAO) and employs the nonlinear auto-regressive distributed lag (NARDL) model and various econometric techniques to show the effects of climate variability in the short and long-term. It also examines if the impacts on Moroccan food security are asymmetric by analyzing the positive and negative partial sums of mean temperature and rainfall.

The study shows that RF has a long-term relationship with FPI, with increased RF leading to increased FPI and decreased RF leading to decreased FPI. FPI responds more strongly and persistently to a positive shock in RF than to an adverse shock. The study also identifies an asymmetric relationship between FPI and RF, with increased TP enhancing food output in the long run and a decrease reducing food production in the long run.

The current study could have some limitations. For instance, there are several other non-climate factors that might potentially impact food security. In particular, CO2 emissions which from the literature is a key variable that represent climate change impact on food security, was not included. The present research has not included those factors mainly because adding more variables to the model reduces the degree of freedom available to estimate the parameters, resulting in inaccurate results.

This paper contributes to the food security literature by utilizing the latest asymmetry methodology to decompose climate changes into their positive and negative trends and examining the contrasting impacts food production.

This paper examines the transmission of global food (GF) and global energy (GE) volatilities to the Moroccan food market, focusing on both aggregated and specific commodities such as dairy, meat and oils and fats.

Using monthly data from September 2009 to June 2024, a vector error correction model (VECM) was estimated to capture short-run and long-run dynamics. The analysis is complemented by impulse response functions (IRFs) and forecast error variance decomposition (FEVD) to provide insights into the transmission mechanisms.

The results indicate an increased sensitivity of the Moroccan food market, particularly following the 2021 price spikes. The study identifies energy input costs, particularly related to fertilizers and transportation, as primary transmission mechanisms. Additionally, the real effective exchange rate (REER) also significantly influences the Moroccan food market.

Further research could explore the transmission from oil derivatives, such as gasoline and fuel, which are directly used in agricultural activities, to provide a more comprehensive understanding.

Understanding the transmission of global shocks to domestic markets can help in developing strategies to enhance food security and protect consumers from price volatility.

This study contributes to the literature by comprehensively analyzing the direct and indirect transmission mechanisms from global food and energy markets to the Moroccan food market, with policy implications to enhance price stability.

The study analyzes return spillovers among key financial markets, including equity indices (NIFTY50, NIKKEI225, KOSPI, ASX200, Shanghai-Composite and Hang-Seng), exchange rates (USD-INR, USD-YEN, USD-WON, USD-AUD and USD-RNMB) and Brent crude oil prices (Brent) in the Asia-Pacific region as well as the NASDAQ index from the US market.

This study utilizes the time-varying parameter vector autoregressive (TVP-VAR) connectedness approach to analyze the return spillovers in the Asia-Pacific region covering the period from March 2, 2005 to February 29, 2024.

The findings reveal that NASDAQ and NIFTY50R are significant transmitters of financial shocks, exerting a strong influence on other markets. In contrast, the Shanghai Composite Index and the South Korean Won act as net receivers, indicating their vulnerability to external influences. The interconnectedness between Brent crude oil prices and regional financial markets underscores the impact of global commodity price fluctuations on the financial stability of energy-dependent economies.

The study shows heightened interconnectedness during global financial crises, suggesting that market shocks can propagate more intensely across interconnected systems during such periods. These insights contribute to a better understanding of financial spillovers and highlight the need for effective risk management and policy coordination in the Asia-Pacific region.

The TVP-VAR connectedness approach is deployed to analyze return spillovers among key financial markets, including equity indices, exchange rates and Brent crude oil prices in the Asia-Pacific region as well as the NASDAQ index from the US market.

• (1)

  We analyze return spillovers among key financial markets indicators in the Asia-Pacific region.

• (2)

  The analysis covers the period from March 2, 2005, to February 29, 2024.

• (3)

  The findings reveal that NASDAQ and NIFTY50R are significant transmitters of financial shocks, exerting a strong influence on other markets.

• (4)

  The study shows heightened interconnectedness during global financial crises, suggesting that market shocks can propagate more intensely across interconnected systems during the study periods.

• (5)

  We find a better understanding of financial spillovers and highlight the need for effective risk management and policy coordination in the Asia-Pacific region.

We analyze return spillovers among key financial markets indicators in the Asia-Pacific region.

The analysis covers the period from March 2, 2005, to February 29, 2024.

The findings reveal that NASDAQ and NIFTY50R are significant transmitters of financial shocks, exerting a strong influence on other markets.

The study shows heightened interconnectedness during global financial crises, suggesting that market shocks can propagate more intensely across interconnected systems during the study periods.

We find a better understanding of financial spillovers and highlight the need for effective risk management and policy coordination in the Asia-Pacific region.

This paper explores the influence between intellectual capital (IC) and the risk of stock price crashes by using company performance as an intervening variable.

This study empirically analyzes the impact of the efficiency of IC on stock price crash risk using a sample size of 152 companies listed on the Indonesia Stock Exchange (IDX) during 2018. To test the research hypotheses, regression analysis and path analysis were applied. In addition, the researchers added exploration to several studies to strengthen the results of this study.

This study’s findings indicate that investors' optimistic (pessimistic) sentiment regarding stock price volatility has obscured aspects of the financial performance of listed companies. This finding implies that investor sentiment has dominated influence on stock price crash risk so that the aspects of IC are obscured.

This research provides new information that IC disclosure in the stock market needs to include knowledge of the volatility of stock prices in order to reveal stock price crash risk.

This work reports on a developing method time measurement system for measuring manufacturing and assembly processes automatically. This automatic system enables the production engineers and management to detect, process, and display concise and accurate information about the operations in real time.

This system is based on Internet of things technology and RFID-antenna. This methodology consists of seven main steps and one final optimization step. Mainly, the operator is equipped by RFID reader, and the work station tools and devices are provided by RFID tags. Responding the RFID tags to the reader will refer to the certain operations, the difference time between start and end of the operations will be collected immediately and calculated by the microprocessor of the system.

This automatic system is promising, considering the accurate time measurements and recommendations that obtained from the case study which includes measuring manual assembly operations to be followed in order to overcome the limitations which are not only technical but also managerial, legal and organizational.

The acquired data about timing and duration of individual operations are anonymized to guarantee the compliance with respect to the privacy laws (GDPR and Italian work's laws).

This work presents a unique system to measure the time instead of traditional methods in the factories environment and satisfies the requirements to study the recommendations in order to overcome the challenges.