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The Scale of Physical and Verbal Aggressiveness has been an instrument widely used in the scientific literature to measure physical and verbal aggressiveness, both in children and adolescents as well as in parents. The original scale has shown adequate psychometric properties. However, the scale has not been previously validated in Spanish, and no confirmatory analyses have been provided yet in Spanish contexts. The aim of this paper is to validate the Spanish version of the Physical and Verbal Aggressiveness Scale via confirmatory factor analysis, with a sample of 531 secondary school adolescents from the Dominican Republic. Reliability, factorial, convergent, and discriminant validity evidence is presented. The results showed that the scale has adequate one-factor confirmatory solution, with very good reliability, and adequate validity when assessed in a sample of Dominican students. The results contrast the differentiation between verbal and physical aggression, questioning the use of the scale for this purpose.

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Utility operators face a challenging task in managing sewer networks to proactively enhance network monitoring. To address this issue, this paper develops a framework for optimized placing of sensors in sewer networks with the aim of maximizing the information obtained about the state of the network. To that end, mutual information is proposed as a measure of the evidence acquired about the state of the network by the placed sensors. The problem formulation leverages a stochastic description of the network states to analytically characterize the mutual information in the system and pose the sensor placement problem. To circumvent the combinatorial problem that arises in the placement configurations, we propose a new algorithm coined the one-step modified greedy algorithm, which employs the greedy heuristic for all possible initial sensor placements. This algorithm enables further exploration of solutions outside the initial greedy solution within a computationally tractable time. The algorithm is applied to two real sewer networks, the first is a sewer network in the south of England with 479 nodes and 567 links, and the second is the sewer network in Bellinge, a village in Denmark that contains 1020 nodes and 1015 links. Sensor placements from the modified greedy algorithm are validated by comparing their performance in estimating unmonitored locations against other heuristic placements using linear and neural network models. Results show the one-step modified greedy placements outperform others in most cases and tend to cluster sensors for efficiently monitoring parts of the network. The proposed framework and modified greedy algorithm provide wastewater utility operators with a sensor placement method that enables them, for the first time, to design the data acquisition and monitoring infrastructure for large sewer networks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Modelling academic self-concept through second-order factors or bifactor structures is an important issue with substantive and practical implications; besides, the bifactor model has not been analysed with a Chinese sample and cross-cultural studies in the academic self-concept are scarce. Likewise, latent structure validity evidence using network psychometrics has not been carried out., Aims: The aim of this study is twofold: to analyse (1) the internal structure of ASC through the Self-Description Questionnaire II-Short (SDQII-S) in Chinese and Spanish samples using two approaches, structural equation modelling and network psychometrics conducting an exploratory graph analysis; and (2) the measurement invariance of the best model across countries and investigate the cross-cultural differences in ASC., Sample: The sample was composed by 651 adolescents. Seven models of ASC were tested., Results: Results supported the multi-dimensional nature of the data as well as the reliability. The best-fitted model for the two subsamples was the three-factor ESEM model, but only the configural invariance of this model was supported across countries. The graph function shows that the school dimension appears more related to the verbal factor in the Spanish subsample and to the math dimension in the Chinese subsample. Likewise, the relationship between verbal and math factors in Spanish students is non-existent, but this connection is more relevant for Chinese students., Conclusion: These two differences may be behind the difficulty in finding invariance using SEM models. It is a question of the construct's nature, less related to analytical phenomena, and deserves deeper discussion., (© 2023 The Authors. British Journal of Educational Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.)

Compressive covariance estimation has arisen as a class of techniques whose aim is to obtain second-order statistics of stochastic processes from compressive measurements. Recently, these methods have been used in various image processing and communications applications, including denoising, spectrum sensing, and compression. Notice that estimating the covariance matrix from compressive samples leads to ill-posed minimizations with severe performance loss at high compression rates. In this regard, a regularization term is typically aggregated to the cost function to consider prior information about a particular property of the covariance matrix. Hence, this paper proposes an algorithm based on the projected gradient method to recover low-rank or Toeplitz approximations of the covariance matrix from compressive measurements. The proposed algorithm divides the compressive measurements into data subsets projected onto different subspaces and accurately estimates the covariance matrix by solving a single optimization problem assuming that each data subset contains an approximation of the signal statistics. Furthermore, gradient filtering is included at every iteration of the proposed algorithm to minimize the estimation error. The error induced by the proposed splitting approach is analytically derived along with the convergence guarantees of the proposed method. The proposed algorithm estimates the covariance matrix of hyperspectral images from synthetic and real compressive samples. Extensive simulations show that the proposed algorithm can effectively recover the covariance matrix of hyperspectral images from compressive measurements with high compression ratios ( 8-15% approx) in noisy scenarios. Moreover, simulations and theoretical results show that the filtering step reduces the recovery error up to twice the number of eigenvectors. Finally, an optical implementation is proposed, and real measurements are used to validate the theoretical findings.

Understanding the specific factors associated with poor health is critical to improve the health of homeless people. This study aimed to analyze the influence of personal variables, interpersonal relationships, and the influence of social services on the health of homeless people. A secondary analysis was applied to cross-sectional data from a sample of 1382 homeless people living in the Basque Country (Spain) (75.69% male). Multinomial logistic regression modelling was used to analyze the relationship between health and personal variables, interpersonal variables, perceived help and use of the social services. Relationships with the family, using a day center, and a sufficient and high perceived help of the social services were significant factors associated with good health. On the other hand, spending the day alone or using mental and health care services are associated with poor health. In the same way, the longer a person has been homeless, the worse their expected state of health is. Addressing housing exclusion, promoting interpersonal relationships, using a day center, and developing the use and perceived helpfulness of social services stand out as key factors in improving health status. Social policies are usually focused on housing. However, this paper also highlights the relevance of developing interpersonal relationships and using day centers to improve homeless people's health.

The aim of this study was to analyze the influence of some personal characteristics, health variables, and social support on the self-rated health of people in housing exclusion in Spain. For that purpose, we used the FOESSA Survey of Social Integration and Needs database, with a final sample of 1574 households. Being more educated and reporting a good life satisfaction stood out as the main factors preventing worse health status. Furthermore, results showed that being female, experiencing poverty-related food insecurity, not having health insurance, experiencing widowhood or partner bereavement, and having caring responsibilities for others or having a disabled person in the household are associated with increased reporting of regular or poor health. On the other hand, being young, having a diagnosed/long-term illness, and a big household size are preventive factors for good health. These results allowed identifying risk and prevention factors to inform interventions to improve the health of those living in housing exclusion. Promoting better education levels, social support, and overall life satisfaction could be important to improve health in this population. Developing social support policies for caring responsibilities and food insecurity must be a priority to improve the health of people living in housing exclusion.

The purpose of this research was to analyze the development of self-concept during adolescence. Participants included 484 teenagers (226 boys and 258 girls) from middle-class families in the Basque Country region of Spain (M age  = 14.99, SD = 1.81 in Time 1 and M age  = 15.64, SD = 1.80 in Time 2). Longitudinal analysis found differences in the general school dimension. Six dimensions (math, verbal, general school, physical abilities, parent relationships and same-sex relationships) reported a linear trend with a decreasing monotonic pattern; self-esteem fit a cubic trend and physical appearance a quadratic trend line. Males showed higher means in self-esteem, math, physical abilities, physical appearance, emotional stability and parent relationships; and females had higher values in verbal and general school., (© 2018 Society for Research on Adolescence.)

Purpose: The main purpose of this research was to examine the longitudinal measurement invariance of the Satisfaction With Life Scale (SWLS) in adolescence., Method: The sample was composed by 484 adolescents from Spain, 46.7% were males. All participants belonged to six academic levels from Grade 7 to Grade 12, and answered the questionnaires at two different times: at the beginning (M age1  = 14.95, SD 1  = 1.81) and at the end of the school year (M age2  = 15.61, SD 2  = 1.81). The reliability of the scale was obtained through Cronbach's alpha, Guttman lambda, and MacDonald's Omega total. The multiple group confirmatory factor analysis (MGCFA) was used to examine the fit of the unifactorial model to data and to test the measurement of longitudinal invariance of the scale across two time points (at the beginning T1, and the end T2, of the academic year), and the time points and groups (gender and age)., Results: The values of the single-factor SWLS structure were T1 (CFI 1  = 1.000, TLI 1  = .997, RMSEA 1  = .080, and SRMR 1  = .028), and T2 (CFI 2  = .997, TLI 2  = .995, RMSEA 2  = .032, and SRMR 2  = .034). On the other hand, values of the reliability and composite reliability when analyzing both time points together as well as separately were as follows: Cronbach's alpha = .86, Guttman's lambda = .84, McDonald's Omega total = .89. Results confirmed the longitudinal invariance of SWLS. The differences in gender and age were not significant and the small differences across time points showed that the means of the latent factor remained the same over time in both variables., Conclusion: The present study confirmed the single-factor structure of the SWLS in Spanish adolescents, as well as a good reliability and composite reliability. The full longitudinal measurement invariance was also found and there were negligible differences across time points considering gender and age. If these findings are further replicated, the scale could be used to compare the life satisfaction across two time points considering different age and gender groups.

Background: Internationally, acute homelessness is commonly associated with complex health and social care needs. While homelessness can be understood as an outcome of structural housing exclusion requiring housing led solutions, the health care issues faced by homeless people equally require attention. A substantive evidence base on the health needs of homeless people exists, but relatively little is known about what influences the self-rated health of homeless people. This article presents new evidence on whether drug use (alcohol consumption, ever having used drugs), health variables (visiting a hospital once in the last year, visiting the doctor in the last month, having a health card, sleeping difficulties, and having a disabling impairment) and sociodemographic characteristics are significantly associated with Self-Rated Health (SRH) among Spanish homeless people., Method: The approach applies secondary analysis to cross-sectional data from a sample of 2437 homeless adults in Spain (83.8% were male). Multinomial logistic regression modelling was used to analyse the relationships between drug use, other health variables and SRH., Results: Being male, an abstainer, having a health card and being in the youngest age groups were significant factors associated with perceived good health. On the other hand, ever having used drugs, having been a night in hospital, having gone to the doctor in the last month, having sleeping difficulties, having a disabling impairment and being in the older age group were all significant risk factors associated with perceived poor health., Conclusions: These results help to improve understanding of the key factors that influence the SRH among homeless people. The findings can contribute to development and delivery of preventive policies, suggesting that interventions to reduce drug consumption and ensure access to a health card/health services, as well as enhancing services for older, female and disabled homeless people are all measures which could improve health and well-being for those who face homelessness. Effective housing interventions (e.g. Housing First or Permanent Supported Housing programmes) are equally important to underpin the effectiveness of measures to improve the self-rated health of homeless people.

Background: For the diagnosis of attention-deficit/hyperactivity disorder (ADHD), the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) proposes that adherence to six symptoms in either group (inattention and hyperactivity/impulsivity) will lead to the diagnosis of one of three presentations of the disorder. Underlying this diagnostic algorithm is the assumption that the 18 symptoms have equal relevance for the diagnosis of ADHD, all are equally severe, and all have the same power to detect the presence of the disorder in all its degrees of severity, without considering the possibility of using marker symptoms. However, several studies have suggested that ADHD symptoms differ in both their power to discriminate the presence of the disorder and the degree of severity they represent. The aim of the present study was to replicate the results of previous research by evaluating the discriminative capacity and relative severity of ADHD symptoms, as well as to extend the investigation of this topic to Spanish-speaking Latin American samples., Methods: The properties of ADHD symptoms rated by the parents of 474 Chilean children were analyzed. Symptom parameters were estimated using the graded response model., Results: The results suggest that symptoms of ADHD differ substantially in both the accuracy with which they reflect the presence of the disorder, and their relative severity. Symptoms "easily distracted by extraneous stimuli" and "have difficulty sustaining attention in tasks" (inattention) and "is on the go, acting as if driven by motor" (hyperactivity/impulsivity) were the most informative, and those with relatively lower severity thresholds., Discussion: The fact that symptoms differ substantially in the probability of being observed conditionally to the trait level suggests the need to refine the diagnostic process by weighting the severity of the symptom, and even to assess the possibility of defining ADHD marker symptoms, as has been done in other disorders., Competing Interests: The authors declare there are no competing interests.

Background: Although the Satisfaction With Life Scale (SWLS) is the most widely used instrument to measure life satisfaction with its validation having been carried out across ages and countries, few studies have analyzed SWLS measurement cross-cultural invariance with adolescents. With respect to Spanish adolescents, measurement invariance across gender has not been found and the one-factor structure has not been confirmed in Mexican adolescents through Structural Equation Modeling., Method: The main purpose of this study was to explore the measurement invariance of the SWLS in a sample of 701 adolescents (Mage = 14.93, SD = 1.83), 47.1% boys and 52.9% girls, from two different countries: Spain (74.2%) and Mexico (25.8%). A multigroup confirmatory factorial analysis is performed to test the invariance of the unifactorial structure. of SWLS with respect to the variables country, gender and age., Results: Results support a single-factor structure as well as the internal consistency of the SWLS. Similarly, the tests of measurement invariance support its strict invariance regarding country and gender, and strong invariance regarding age., Conclusions: These results suggest that the SWLS is a useful single-factor measure of life satisfaction in Spanish and Mexican adolescents.

Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

Background/Objective : The objective of this ex post facto study is to analyze both the direct relationships between perceived social support, self-concept, resilience, subjective well-being and school engagement. Method : To achieve this, a battery of instruments was applied to 1,250 Compulsory Secondary Education students from the Basque Country (49% boys and 51% girls), aged between 12 and 15 years ( M  = 13.72, SD =1.09), randomly selected. We used a structural equation model to analyze the effects of perceived social support, self-concept and resilience on subjective well-being and school engagement. Results : The results provide evidence for the influence of the support of family, peer support and teacher support on self-concept. In addition, self-concept is shown as a mediating variable associated with resilience, subjective well-being and school engagement. Conclusions : We discuss the results in the context of positive psychology and their practical implications in the school context.