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There are different types of violence which intersect in occurrences of sexist violence. This article, while granting that structural and symbolic violence are intertwined in a synergic relationship, focuses its attention on structural violence with three purposes in mind: first, to situate reflections made on sexist violence within the framework of epochal changes at the social, economic and political levels; secondly, to investigate in this new context if they are only reproduced, or if they reconfigure the same gender-sex orderings and patterns of inequality and violence that they trigger and legitimize; and, thirdly, to explore the ways in which contemporary socio-political transformations that undermine the functionality of institutions are having an impact on rising sexist violence trends today. Finally, based on the social and subjective changes that have come about in the face of adverse conditions produced through the insertion of social agents, progress is being made toward a differentiation of the forms of occurrence and functionality of sexist violence. In short, the purpose is to develop more specific approaches that will allow us to understand the scourge of sexist violence in our day and contribute to designing intervention strategies.
This article presents a bioinspired pneumatic soft actuator designed to mimic the flexo-extension movement of the human finger, with a particular focus on stiffness modulation through granular jamming. Three-chamber geometries – honeycomb, rectangular, and half-round – were evaluated to optimize curvature performance, utilizing Mold Star 15 Slow elastomer for actuator fabrication. Granular jamming, both passive and active, was implemented within the inextensible layer using chia and quinoa grains to enhance stiffness modulation. Experimental results revealed that the honeycomb geometry most closely aligned with the natural index finger trajectory. Stiffness evaluations demonstrated a range of 0–0.47 N/mm/° for quinoa and 0–0.9 N/mm/° for chia. The actuator’s force output increased by 16% for quinoa and 71% for chia compared to the nonjammed configuration. This enhanced performance is particularly beneficial for applications such as hand rehabilitation, where adaptive stiffness and force modulation are critical. Granular jamming, especially with active chia, provided superior adaptability for tasks requiring variable stiffness and resistance, making it a promising candidate for wearable robotic applications in rehabilitation.
This paper, building on new archival research and the social table method, presents comprehensive estimates of income inequality in Mexico in 1895, 1910, 1930 and 1940. Inequality grew from 1895 to 1910, driven by economic expansion within the context of an oligarchic economy. While real income increased for the lower classes during this period, the main beneficiaries were large landowners and entrepreneurs. In the revolutionary period from 1910 to 1930 inequality decreased especially as a result of land reforms, benefitting peasants at the expense of the large landowners. However, the economic structure of the country was not fundamentally changed, and in the 1930s inequality raised as incomes of peasants and those in the informal sector fell behind manufacturing and other high-earning sectors. The Mexican case shows the complex interaction of economics, demography and politics in determining economic inequality.
Empathy is an essential skill in the doctor-patient relationship since it contributes to improve aspects of health care and patient satisfaction. Nevertheless, burnout research projects have been developed in recent years.
Objectives
To examine the predictive capacity that empathy has on burnout syndrome in health professionals.
Methods
A non-experimental, cross-sectional design was proposed. The type of study was correlational-descriptive since it was sought out to explore a functional relation through the prognosis of a criterion variable. Sample: 200 (100 female and 100 male).
Results
First, the variance of cognitive and Affective Empathy was dug out in the emotional exhaustation criterion scale. Results accounted for 15% of variability in emotional exhaustation. (Corrected R 2 = .15, F = 17,56, p = 0,00). The best predictor of emotional exhaustation refers to Cognitive Empathy. (B = -.27, p = 0.00). It does not seem that Affective Empathy acts as a predictor variable of Emotional Exhaustation. (Table 1).Table 1
Multiple linear regression analysis considering Emotional Exhaustation as a criterion.
TECA
Corrected R2
F
B
p
Cognitive Empathy
.15
17,5
-.27**
0,00
Affective Empathy
-.14
.13
The predictive capacity of Empathy in relation to Depersonalization was estimated (Corrected R 2 = .20, F = 25,4, p = 0.00). Cognitive and affective empathy were included as predictor variables and MBI as a criterion variable (Table 2). On one hand, the best predictor of Depersonalization is the Cognitive Empathy. On the other hand, regarding Affective Empathy, it does not act as a predictor of Depersonalization.Table 2
Multiple linear regression analysis considering Depersonalization as a criterion.
TECA
Corrected R2
F
B
p
Cognitive Empathy
.20
25,4
-.32**
0,00
Affective Empathy
-.15
.84
Lastly, the predictive capacity of Empathy in relation to Personal Achievement was figured out. (Corrected R 2 = .19, F = 23,4, p = 0.00). Cognitive Empathy is the best predictor for Personal Fulfillment (Table 3).Table 3
Multiple linear regression analysis considering Personal Fullfilment as a criterion.
TECA
Corrected R2
F
β
p
Cognitive Empathy
.20
25,4
.43**
0,00
Affective Empathy
.00
.96
Conclusions
It was noticed that through a linear multiple regression analysis, the variable that best explains Emotional Exhaustation is Cognitive Empathy. Those results are replicated for Depersonalization and Personal Fullfilment.
According to Bisquerra Alzina (2003),competencies are defined as a set of knowledge, capabilities, skills and attitudes, necessary to understand, express and regulate emotional phenomena appropriately and which are fundamental in the teaching profesion since they are closely related to students´performance and mental health.
Objectives
compare socio-emotional skills in two groups of participants: female and male
Methods
A non-experimental,cross-sectional design was proposed for this study. The scope of this research is descriptive, in the sense,that it seeks to establish measures in regard to specific variables. Sample (100 female and 100 male).
Results
Results revealed that the evaluated teachers show average level of socio-emotional competencies, (Table 1).The highest scores were encountered in relation to the optimism competence. It suggests that teachers have the ability to obtain favorable balances from adverse situations presented in their daily lives.Table 1:
Distribution of socio-emotional competency levels in the professionals evaluated
LOW %
MEDIUM %
HIGHT %
EMOTIONAL AWARENESS
19
80
1
SELF EFFICACY
32
66
2
EMOTIONAL REGULATION
17
81
2
EMOTIONAL EXPRESSION
6
85
9
PROSOCIALITY
6
85
9
ASSERTIVENESS
6
82
12
OPTIMISM
0
21
79
EMOTIONAL AUTONOMY
25
71
4
EMPATHY
8
85
7
Findings showed that there exists a statiscally significative difference (P=0,000) in the empathy and self-efficacy dimensions. Women obtained higher scores in these two abilities in regard to men. (Table 2). No differences were observed in the rest of the competences evaluated.Table 2:
Differences according to men and women
FEMALE
MALE
SELF EFFICACY
1,78
1,61
EMPATHY
2,02
1,96
Conclusions
Although teachers´s socio-emotional competences were classified in medium levels, it is necessary to implement an intervention design that allows to streghten those dimensions since they could improve not only the relationships with their students but also teachers´ mental health.
The generation of organic compounds relevant to the origin of living beings is easily achieved if reducing conditions exist in the environment; however, proposed models of primitive atmospheres do not favour these conditions. This work considers the quantity and possible size of the cosmic bodies that could have impacted the Earth between 4.2 and 3.8 Ga. Different atmospheres (with gases such as CO2, CO, N2, CH4) were experimentally irradiated by an Nd-YAG laser (used to simulate the energy of a shock wave produced by the interaction of a cosmic body with the atmosphere). Although the main products are short-chain, saturated and unsaturated hydrocarbons, hydrogen cyanide (HCN) is the most abundant in some atmospheres. HCN is an important precursor of the organic molecules relevant to chemical evolution. According to our calculations, between 1023 and 1025 g of HCN could have been produced by the energy released to the atmosphere from the entry of cosmic objects between 4.2 and 3.8 Ga. Therefore, this shock wave energy could play an important role in the processes of chemical evolution.
Dicarbonyl compounds are highly reactive precursors of advanced glycation end products (AGE), produced endogenously, present in certain foods and formed during food processing. AGE contribute to the development of adverse metabolic outcomes, but health effects of dietary dicarbonyls are largely unexplored. We investigated associations between three dietary dicarbonyl compounds, methylglyoxal (MGO), glyoxal (GO) and 3-deoxyglucosone (3-DG), and body weight changes in European adults. Dicarbonyl intakes were estimated using food composition database from 263 095 European Prospective Investigation into Cancer and Nutrition–Physical Activity, Nutrition, Alcohol, Cessation of Smoking, Eating Out of Home in Relation to Anthropometry participants with two body weight assessments (median follow-up time = 5·4 years). Associations between dicarbonyls and 5-year body-weight changes were estimated using mixed linear regression models. Stratified analyses by sex, age and baseline BMI were performed. Risk of becoming overweight/obese was assessed using multivariable-adjusted logistic regression. MGO intake was associated with 5-year body-weight gain of 0·089 kg (per 1-sd increase, 95 % CI 0·072, 0·107). 3-DG was inversely associated with body-weight change (–0·076 kg, −0·094, −0·058). No significant association was observed for GO (0·018 kg, −0·002, 0·037). In stratified analyses, GO was associated with body-weight gain among women and older participants (above median of 52·4 years). MGO was associated with higher body-weight gain among older participants. 3-DG was inversely associated with body-weight gain among younger and normal-weight participants. MGO was associated with a higher risk of becoming overweight/obese, while inverse associations were observed for 3-DG. No associations were observed for GO with overweight/obesity. Dietary dicarbonyls are inconsistently associated with body weight change among European adults. Further research is needed to clarify the role of these food components in overweight and obesity, their underlying mechanisms and potential public health implications.
This chapter establishes an explicit link between foreign aid inflows and development indicators classified in the multidimensional setting of the SDGs. This linkage is not a black box as it takes advantage of the model’s causal chains describing budget allocations and indicator performance. First, we create counterfactuals by removing aid flows. Hence, we can estimate aid impacts and assess their statistical significance at the indicator or country levels during the first decade of the 21st century. Second, we produce a validation exercise comparing our results with econometric evidence found in a well-known sector-level study (access and sanitation of water) using a subset of our data.
This chapter introduces a model in which a government allocates financial resources across several policy issues (development dimensions), and a set of public servants (or agencies) that, through government programmes, transform public spending into policy outcomes. We start by describing the macro-level dynamics and the relevant equations involved. Then, we introduce a political economy game between the government and its officials (or public servants). First, we describe the public servants’ decision making in an environment of uncertainty through reinforcement learning. Second, we elaborate on the problem of the government (or central authority) and how we can specify its heuristic strategy. Finally, we provide an overview of the entire structure of the model.
This chapter elaborates on the calibration and validation procedures for the model. First, we describe our calibration strategy in which a customised optimisation algorithm makes use of a multi-objective function, preventing the loss of indicator-specific error information. Second, we externally validate our model by replicating two well-known statistical patterns: (1) the skewed distribution of budgetary changes and (2) the negative relationship between development and corruption. Third, we internally validate the model by showing that public servants who receive more positive spillovers tend to be less efficient. Fourth, we analyse the statistical behaviour of the model through different tests: validity of synthetic counterfactuals, parameter recovery, overfitting, and time equivalence. Finally, we make a brief reference to the literature on estimating SDG networks.
This chapter introduces the reader to the problem of policy prioritisation and why quantitative/computational analytic frameworks are much needed. We explain the various academic- and policy-oriented motivations for developing the Policy Priority Inference research programme. We apply this computational framework in the study of the SDGs and the feasibility of the 2030 Agenda of sustainable development.
This chapter formulates an analytical toolkit that incorporates an intricate – yet realistic – chain of causal mechanisms to explain the expenditure–development relationship. First, we explain several reasons why we take a complexity perspective for modelling the expenditure–development link and why we choose agent-based modelling as a suitable tool for assessing policy impacts in sustainable development. Second, we introduce the concept of social mechanisms and explain how we apply them to measure the impact of budgetary allocations when systemic effects are relevant. Third, we compare different concepts of causality and explain the advantages of an account that simulates counterfactual scenarios where policy interventions are absent.
This chapter provides a comprehensive framework to understand and quantify structural bottlenecks in a setting of multidimensional sustainable development. First, we formalise the idea of an idiosyncratic bottleneck when thinking in a hypothetical situation where a government has all the necessary resources to guarantee the success of its existing programmes (i.e., the budgetary frontier). Second, we compare the development gaps between the baseline and counterfactual outputs to assess how sensitive are the different indicators when they operate at the budgetary frontier. Third, we combine this information with the historical performance of indicators to develop a methodology that identifies idiosyncratic bottlenecks. Finally, we elaborate on a flagging system to differentiate between idiosyncratic bottlenecks according to the ‘urgency’ to unblock them.