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This paper integrates the action phase theory (APT) and the theory of planned behaviour (TPB) to analyse the dynamic mechanisms involved in the configuration of goals and implementation intentions throughout the entrepreneurship process.

The empirical analysis compares individuals in different phases of this process (not yet decided, potential and nascent entrepreneurs). A large sample of adults from Spain is analysed. Structural equation models and multi-group analysis (MGA) serve to test the hypotheses.

The results confirm that perceived behavioural control (PBC) is the most influential antecedent of entrepreneurial goal intention (EGI) in pre-actional phases (undecided and potential entrepreneurs), whilst attitude towards entrepreneurship (ATE) takes this role during nascency. Subjective norms (SNs) are more important in Phase 1 (establishing the goal) and in Phase 3 (performing nascent behaviour).

This study contributes to both the TPB and the APT. It provides the most relevant insight into the mental process that leads to starting up and helps explain certain previous conflicting results found in the literature. Additionally, it has important implications not only for theory building but also for support bodies and for entrepreneurship educators.

This study aims to assess the impact of participation in self-help group (SHG) on the psychological empowerment of rural tribal women.

Primary data was collected using multistage random sampling from the rural women of Jharkhand, India. The propensity score matching method was adopted using the psmatch2 command in STATA.

The results show a significant positive change in women’s self-esteem, self-confidence, self-efficacy, autonomy, knowledge and skills, reduction in agony and quality of life after participation in SHG. This reveals that participation in SHG has a significant positive impact on the psychological empowerment of rural tribal women.

Despite the numerous studies on rural women’s empowerment, there is little evidence of literature focusing on the impact of participation in SHG on psychological empowerment, specifically in the tribal context. This study primarily focuses on women belonging to the scheduled tribe category of Jharkhand, one of the poorest states of India.

This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys.

This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models.

The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations.

The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.

This study aims to assess Brazilian adult consumers’ behavior, aged 18–70, when purchasing ready-to-eat food during the first months of the Coronavirus disease 2019 (COVID-19) pandemic.

Participants answered an online questionnaire about behaviors related to the purchase of ready-to-eat food from food services: changes in usage frequency during the pandemic, reasons for altering purchase habits, types of food and beverages bought before and during the pandemic and the frequency of on-site (consumption in food services) and off-site (delivery, take-away and drive-through) service utilization at lunch and dinner.

Out of 970 individuals who participated in the study, during the pandemic, 38% of participants reduced their food service usage, whereas 18% stopped using it. The main reasons given by participants who reduced and stopped food service usage were cooking at home (52% and 59%, respectively) and feeling afraid of contracting COVID-19 (26% and 22%, respectively). The reduction was more frequent among divorced/widowed/single individuals (p = 0.001) and in total social distancing, that is, all day long (p = 0.03). A significant reduction in on-site consumption frequency occurred for lunch and dinner (p < 0.001), whereas an increase in the off-site consumption frequency service for lunch (p = 0.016) and a reduction for dinner (p = 0.01) occurred compared to pre-COVID-19. However, 48% of participants used these services at least once a week in both periods. Most consumed foods and drinks before and during the pandemic were pasta/pizza (74% and 64%, respectively), snack/burgers (66% and 59%, respectively), soft drinks (41% and 37%, respectively) and alcoholic beverages (37% and 25%, respectively).

Knowledge about food choices away from home during the pandemic is scarce. High consumption of food away from home has been associated with a greater risk of developing chronic non-communicable diseases, such as obesity, diabetes and others. Eating behavior is influenced by the cultural, social, economic and personal characteristics of each individual. Understanding the main changes related to the consumption of ready-to-eat food and what the affected consumers profile in a time of unprecedented crisis, it is important to provide scientific knowledge that allows one to anticipate the implications for the future of individuals’ health and food systems and, consequently, to develop public policy or awareness and promotion actions of public health that encourage adopting healthier and balanced eating habits.

Ulam is a traditional salad that contains high levels of antioxidants and is commonly consumed in raw form. However, the average ulam consumption among the low-income Malaysian population was only ½ serving daily. Thus, this study aimed to explore the motivators and barriers to ulam consumption among residents of low-cost housing areas (household income RM4849 or $1015.50) in Kuala Lumpur, Malaysia.

Six focus group discussions were conducted with 27 Malay residents aged 18–59 years in Kuala Lumpur, Malaysia. The researchers asked the participants a series of semi-structured questions. All the interviews were audio-recorded and transcribed verbatim. Two researchers coded the transcripts independently, and several themes were identified. The data were analysed using Nvivo version 12 software.

Three main factors for ulam consumption were identified in this study: personal, environmental and behavioural. The motivators and barriers were identified based on nine main themes and 16 sub-themes.

The results of this study identified potential areas for an effective intervention to increase ulam intake among residents in low-cost housing areas.

This work has the potential to identify the factors that have an impact on consumers' ulam preferences to help fulfil daily vegetable recommendations.

Children's food insecurity experiences are largely unrepresented in academic literature. Parents and caregivers cannot always accurately evaluate their children's attitudes or experiences, and even within the same family unit, children and their parents may report differing views and experiences of family food insecurity. The purpose of this narrative review is to identify studies that include children's voices and their perceptions, understanding, and experience of food insecurity in the household.

This narrative review aimed to address the following questions: (1) “What research studies of household food insecurity include children's voices?” and (2) “Across these studies, how do children perceive, understand and experience food insecurity in the household?”. A database search was conducted in October 2022. After inclusion and exclusion criteria were applied, 16 articles remained for review.

The findings from this review were organised into three themes: Theme 1: Ways children coped with accessing food or money for food; Theme 2: Food-related strategies children used to avoid hunger; and Theme 3: Children attempt to mask food insecurity.

Future research should further explore the long-term consequences of social pressures and informal economic engagement on children's well-being and social development. By addressing the social determinants of food insecurity, this study can strive to create supportive environments that enable all children to access adequate nutrition and thrive.

Overall, the findings of this review demonstrate the significant social pressures that shape children's responses to food insecurity. Results suggest that children's decision-making processes are influenced by the desire to maintain social standing and avoid the negative consequences of being food insecure. As such, this review underscores the need for a comprehensive understanding of the social context in which food insecurity occurs and the impact it has on children's lives. Understanding these dynamics is crucial for developing effective interventions and policies addressing the multifaceted challenges food insecure children face.

This review has highlighted a need for interventions to incorporate trauma-informed strategies to protect children from and respond to the psychologically distressing experiences and impact of living in food insecure households.

Efforts to reduce farmers' market risks and improve buyers' access to farm commodities have encouraged contract farming (CF) in Ghana's cashew sector in recent years. Consequently, the existence of CF shows that farmers who use it may be benefiting from it, as it is their economic responsibility to decide how to sell agricultural products. However, the magnitudes of these benefits or otherwise have been inadequately explored. This paper aims to empirically estimate the impact of CF on farm performance and welfare of smallholder cashew farmers.

The study used probit-two-stage least square (probit-2sls) as a primary estimator to account for self-selection bias and endogeneity that could arise from both observed and unobserved heterogeneities among farming households to estimate the causal effects of CF on farm performance and household welfare.

The results indicated that participation in CF contribute significantly to the gains in farm performance (price margins, yields and net farm revenue) and welfare (consumption expenditure per capita), and that the non-participants of CF would have benefited substantially if they had participated. An analysis of the farm size disaggregated into small, medium and large with regards to the outcome variables produces mixed results.

It can be concluded that participating in CF enhances farm performance and household welfare.

While many other studies do not account for changes in farm performance and welfare due to differences in farm size or other observed factors, this study fills a crucial void.

Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.

In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.

Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.

In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.

This purpose of this study was to assess dietary diversity among women of reproductive age (WRA) and the associations between consumption of a diversified diet and overweight/obesity statuses in Ekiti State, Nigeria.

Cross-sectional study of 207 WRA from six local government areas in Ekiti State, Nigeria, was done. A validated interviewer-administered questionnaire was used to collect data on sociodemographic characteristics, dietary intake and anthropometry. Dietary intake was assessed with 24-h dietary recall to calculate the Minimum Dietary Diversity Score for Women (MDD-W). Data were analyzed using descriptive statistics, Spearman rank correlation and Chi square test at α_0.05.

Majority of the participants (65.2%) were aged between 19 and 34 years, 58.5% were married and 49.8% had high school as their highest level of education. Mean MDD-W and body mass index (BMI) were 3.8 ± 0.9 and 25.46 ± 6.4 kg/m², respectively. All participants (100%) consumed foods from the “grains, white roots and tubers” group and majority also from the “meat and poultry” group (79.7%) but ranked low in the consumption of foods from other food groups. Many were overweight (34.8%), obese (14.0%) and a few (1.9%) had morbid obesity. MDD-W was significantly associated with marital status (X² = 7.7, P = 0.022) and BMI (X² = 11.4, P = 0.023) and had a weak positive correlation with BMI (r = 0.189, P = 0.007).

Study shows that both undernutrition and overweight/obesity coexist in the population, indicating a case of double burden of malnutrition (DBM) at a population level. However, further studies may be needed to investigate the extent of DBM at individual levels. Although there was a positive correlation between MDD-W and BMI, it cannot be used to predict causality. Study further reveals that the micronutrient intake of the WRA population in Ekiti is inadequate. Considering the importance of the 10 food groups highlighted in MDD_W to nutrition and health, the promotion of the consumption of foods from these food groups with more attention to the micronutrient-rich ones needs to be heightened.

Diet of participants was not diverse enough, indicating micronutrient inadequacy. Promotion of the consumption of a diverse diet, particularly from the food groups rich in micronutrient, needs to be heightened, while food groups high in calorie should be minimally consumed to forestall DBM.

This study aims to introduce a novel noise filter module designed for LiDAR simultaneous localization and mapping (SLAM) systems. The primary objective is to enhance pose estimation accuracy and improve the overall system performance in outdoor environments.

Distinct from traditional approaches, MCFilter emphasizes enhancing point cloud data quality at the pixel level. This framework hinges on two primary elements. First, the D-Tracker, a tracking algorithm, is grounded on multiresolution three-dimensional (3D) descriptors and adeptly maintains a balance between precision and efficiency. Second, the R-Filter introduces a pixel-level attribute named motion-correlation, which effectively identifies and removes dynamic points. Furthermore, designed as a modular component, MCFilter ensures seamless integration into existing LiDAR SLAM systems.

Based on rigorous testing with public data sets and real-world conditions, the MCFilter reported an increase in average accuracy of 12.39% and reduced processing time by 24.18%. These outcomes emphasize the method’s effectiveness in refining the performance of current LiDAR SLAM systems.

In this study, the authors present a novel 3D descriptor tracker designed for consistent feature point matching across successive frames. The authors also propose an innovative attribute to detect and eliminate noise points. Experimental results demonstrate that integrating this method into existing LiDAR SLAM systems yields state-of-the-art performance.