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Abstract This paper describes the role of fabric anisotropy during clayey soil deformation. A set of triaxial tests was performed on vertical and horizontal specimens of undisturbed smectite lake sediments from Jurica, Queretaro in Mexico. The results allowed to analyze the influence of bedding and discontinuities on the mechanical behavior of Jurica clays after failure. Tests with applied low strain rates allowed pore pressure equalization within specimens with different gravimetric water content and degree of saturation. Shear failure results of undrained tests showed that deformation distributes differently in both horizontal and vertical directions and that stress may be dissipated by pore collapses, fractures and particle deformation. The experimental evidence suggests that microfabric is a relevant variable in the overall mechanical response of clayey sediments that depends on the natural fabric (bedding and discontinuities), mineralogy, and water content. A detailed analysis of Young´s Moduli (E) showed the high variability of this parameter from 108 to 409 kg/cm2 (calculated at 30% of σdmax) and its dependence on the orientation of the specimen and the water content. In addition, p’-q’ graphs illustrate the relevance of considering mechanical anisotropy in clays and provide further insights to understand the role of smectites in progressive shear deformation.

Transport studies that adopt complex analyses present methodological challenges that lead to the use of innovative techniques to address the limitations of traditional methods. In the Latin American context, people consider security as a relevant variable in their daily lives. Thus, when people travel around the city and choose a mode of transport, secu-rity becomes an important factor and should therefore be included in transport studies. However, the definition of security in terms of transport in the Colombian context remains unclear. Therefore, we examined the security percep-tion effect on transport mode choice by addressing security as a latent variable consisting of three elements: environ-ment, subject and transport mode. We proposed the use of virtual reality (VR) to recreate travel routes and offer partic-ipants a scenario of choice closer to the natural conditions of a trip. The participants were provided routes in the form of immersive 3D videos recreating natural trip conditions to identify their choices and travel behaviour. Recordings were made of daily scenarios and existing urban environments portraying real and active modes of transport, giving respondents an almost-natural experience. The use of 360-degree immersive videos offers a multisensory experience allowing both the capture of socioeconomic and travel information and the collection of journey perception. The experiment evaluated two environments in Medellín, Colombia (secure (E1) and insecure (E2)) and studied the effects of lighting conditions (day (D) and night (N)). A total of four videos (E1D, E1N, E2D and E2N) depicting six transport modes in tandem were assessed by 92 participants from Medellín and Bogotá, Colombia. We found that environment-associated security perception varies depending on the time of the journey (day/night) and one’s familiarity with the environment. The research results position VR as a tool that offers high potential to support transport studies. We found that people’s movements, gestures and expressions while participating in the VR experiments resembled what was expected from journeys in reality. VR constitutes a relevant tool for transport studies, as it allows for an assessment of active transport mode perceptions. It prevents participants from being exposed to the risk associated with travel to specific places and carries out several routes in different transport modes even when participants cannot or have never undertaken journeys in the modes under assessment.

Italians were the first European citizens to experience the lockdown due to Sars-Cov-2 in March 2020. Most employees were forced to work from home. People suddenly had to share common living spaces with family members for longer periods of time and convert home spaces into workplaces. This inevitably had a subjective impact on the perception, satisfaction and preference of indoor environmental quality and work productivity. A web-based survey was designed and administered to Italian employees to determine how they perceived the indoor environmental quality of residential spaces when Working From Home (WFH) and to investigate the relationship between different aspects of users’ satisfaction. A total of 330 valid questionnaires were collected and analysed. The article reports the results of the analyses conducted using a descriptive approach and predictive models to quantify comfort in living spaces when WFH, focusing on respondents’ satisfaction. Most of them were satisfied with the indoor environmental conditions (89% as the sum of “very satisfied” and “satisfied” responses for thermal comfort, 74% for visual comfort, 68% for acoustic quality and 81% for indoor air quality), while the layout of the furniture negatively influenced the WFH experience: 45% of the participants expressed an unsatisfactory or neutral opinion. The results of the sentiment analysis confirmed this trend. Among the Indoor Environmental factors that affect productivity, visual comfort is the most relevant variable. As for the predictive approach using machine learning, the Support Vector Machine classifier performed best in predicting overall satisfaction.

The purpose of this research was to identify and evaluate the major dietary components linked with blood sugar levels in diabetic patients at UPT Puskesmas Narumonda in Toba Regency. This sort of study employs a cross-sectional descriptive analytic survey. The population in this research was 118 individuals, whereas the sample size was 54. Univariate, bivariate, and multivariate analyses were used to analyze the data. The chi-square test results indicate that the sugar level of people with diabetes mellitus is related to the number of calories p = 0.000, the type of food p = 0.000, and the eating schedule p = 0.003, indicating that there is a relationship between obesity, the number of calories, the type of food, and the eating schedule and blood sugar levels in people with diabetes mellitus. The findings of multivariate analysis indicate that the most relevant variable in this research, with an OR value of 53, is the quantity of calories. The research concluded that the quantity of calories consumed is the most important factor influencing blood sugar levels in persons with diabetes mellitus at UPT Puskesmas Narumonda, Toba Regency. To help lower the occurrence of diabetes mellitus, it is intended that the Health Service, puskesmas, and health professionals would collaborate to give frequent counseling about diabetes mellitus and a healthy and balanced diet.

The purpose of this paper is to evaluate the perceptions of Greeks-farmers regarding success and to investigate the factors that are considered as indicators to explain, predict, and determine perceptional entrepreneurial success. This research focuses on existing agricultural enterprises as more than 400 randomly selected agricultural enterprises compose the survey’s sample. The main research method is through structured questionnaires. A series of multivariate analyses were conducted to examine the data. A stepwise procedure was used to identify the relevant variable and the significant ones were identified based on the ‘F’ test. The results of a discriminant analysis indicate that seven predictors (internal LOC, pull motivation, push motivation, internal funding, innovativeness, entrepreneurial capacity, and educational background) have a significant impact on the dependent variable “perceived entrepreneurial success”. Pull motivation is the most important variable to discriminate the groups. The value of this study lies in the fact that it is an original attempt to assess the parameters that could explain the perceived entrepreneurial success of agripreneurs; a focus that is lacking in previous studies.

Target prices are often provided as a support for stock recommendations by sell-side analysts which represent an explicit estimate of the expected future value of a company’s stock. This research focuses on mean target prices for stocks contained in the Standard and Poor’s Global Clean Energy Index during the time period from 2009 to 2020. The accuracy of mean target prices for these global clean energy stocks at any point during a 12-month period (Year-Highest) is 68.1% and only 46.6% after exactly 12 months (Year-End). A random forest and an SVM classification model were trained for both a Year-End and a Year-Highest target and compared to a random model. The random forest demonstrates the best results with an average accuracy of 73.24% for the Year-End target and 81.15% for the Year-Highest target. The analysis of the variables shows that for all models the mean target price is the most relevant variable, whereas the number of target prices appears to be highly relevant as well. Moreover, the results indicate that following the rare positive predictions of the random forest for the highest target return groups (“30% to 70%” and “Above 70%”) may potentially represent attractive investment opportunities.

Road rage is a serious phenomenon around the world in the driving context and may contribute to risky driving behavior, further increasing the probability of collisions. Among several factors, trait anger is the most relevant variable towards road rage. This research aims to interpret how trait anger influences risky driving behavior in detail. We used an online questionnaire, which contains trait anger scale (TAS), executive function index (EFI), hazard cognition scale (HCS; represents attitudes towards risky driving behavior), driver behavior questionnaire (DBQ), and self-reported traffic violations (e.g., accidents, penalty points, fines). The linear regression model showed that trait anger is a medium but statistically significant predictor of risky driving behavior and drivers’ attitude towards risky situations can significantly predict risky driving behavior in statistics up to medium effect. But risky driving behavior cannot be predicted by executive function. Interestingly, for the objective indicators, the zero-inflated Poisson regression or negative binomial regression results suggested that age is a small protective factor towards accidents/penalty points/fines, and trait anger also is a small protective factor in accidents/fines. While executive function alleviates penalty points and fines, whereas hazard cognition alleviates penalty points only. They all represented a small effect on risky driving behavior. Path analysis suggested that trait anger influences risky driving behavior through executive function and hazard cognition. This study provides a theoretical framework for further research about road rage and offers some possible intervene towards road rage.

Ambidexterity has been linked to firm structures that are typical of organizations with a larger size. However, further research is needed to analyze whether the effect of firm size on ambidexterity is contingent on other aspects. We argue that micro and small firms that have developed some competitive intelligence routines (CIRs) may foster ambidextrous behavior and compensate for the limitations arising from a smaller size and lack of resources. We test our proposal on a sample of 200 firms in the furniture sector. Our results show that CIRs compensate for size constraints in that size is no longer a relevant variable to increase ambidextrous behavior in firms that achieve higher levels in these routines. Our results provide new and important insights into how ambidexterity may be fostered in small firms that lack resource slack or the ability to use separate units to develop knowledge exploration and exploitation activities. JEL CLASSIFICATION: M10, M21, O3

Introduction. Dengue, a vector-borne viral illness, shows worldwide widening spatial distribution beyond its point of origination, namely, the tropical belt. The persistent hyperendemicity in Malaysia has resulted in the formation of the dengue early warning system. However, weather variables are yet to be fully utilized for prevention and control activities, particularly in east-coast peninsular Malaysia where limited studies have been conducted. We aim to provide a time-based estimate of possible dengue incidence increase following weather-related changes, thereby highlighting potential dengue outbreaks. Method. All serologically confirmed dengue patients in Kelantan, a northeastern state in Malaysia, registered in the eDengue system with an onset of disease from January 2016 to December 2018, were included in the study with the exclusion of duplicate entry. Using a generalized additive model, climate data collected from the Kota Bharu weather station (latitude 6°10 ′ N, longitude 102°18 ′ E) was analysed with dengue data. Result. A cyclical pattern of dengue cases was observed with annual peaks coinciding with the intermonsoon period. Our analysis reveals that maximum temperature, mean temperature, rainfall, and wind speed have a significant nonlinear effect on dengue cases in Kelantan. Our model can explain approximately 8.2% of dengue incidence variabilities. Conclusion. Weather variables affect nearly 10% of the dengue incidences in Northeast Malaysia, thereby making it a relevant variable to be included in a dengue early warning system. Interventions such as vector control activities targeting the intermonsoon period are recommended.

Criminology theories imply that time is a relevant variable, especially for the prevention and intervention of criminal occurrences. Thus, the study of criminal temporal patterns has been described as being of great relevance. The present study focuses on describing and exploring the influence of temporal and seasonal variables on the occurrence of different types of theft in the Historic Centre of Porto through the analysis of official records of the Public Security Police. Significant differences were found regarding the time of day and season of occurrence, even though it is not observed for all the types of theft analysed. Overall, theft was more prevalent at night and less frequent during winter, which is congruent with previous literature and the routine activity theory. Being the first case study in Porto city, Portugal, this research may be of extreme importance for both designing prevention and intervention policies in the area, and for inspiring future research on a criminal time analysis.