Effect of food insecurity on food purchases at home

Previous research has established a relationship between income and food security. In this article, we examine the effect of food security on food purchases, specifically on five food‐at‐home groups. Using a set of Tobit models, and after controlling for a set of confounding factors, we show that food security perception leads to the purchase of fruit and vegetables, meats and eggs, and dairy products while decreasing the purchase of fat and carbohydrates. However, we cannot be certain of the actual nutritional effect.     

When Faith Moved Mountains

It is believed that Buddhism reached China through the Silk Road around the first century A.D., and subsequently, Buddhist arts and crafts arrived from countries like India, Nepal and Sri Lanka. An example would be the artworks found in grottoes built along the Silk Road in China. The Mogao Caves near the city of Dunhuang in Gansu Province in northwest China, the Longmen Grottoes near Luoyang in central China's Henan Province, and the Yungang Grottoes near Datong in Shanxi Province in north China are the three most important places in the country where Buddhist grottoes have been found.     

Lawyers' Associations and the Brazilian State, 1843-1997

This study focuses on the trajectories of the Institute of Brazilian Lawyers (Instituto dos Advogados Brasileiros, or IAB), created in 1843, and the Order of Lawyers of Brazil (Ordem dos Advogados do Brasil, or OAB), formed in 1933, extending the analysis up to 1997. The article has three objectives: (a) to point out the role played by expertise in the cohesion of the IAB-OAB, changing its public image from one of the political counterelite to that of representatives of civil society, with the "institutional vocation" to defend juridical order and, later, human and citizenship rights; (b) to describe the social ties that permeate the legal world, preventing internal disputes from becoming deep and lasting cleavages; and (c) to contrast the experience of the Brazilian bar with those of the German and French.     

加强公安信息建设发挥科技强警作用

公安工作的现代化,必须走科技强誓之路.建立信息中心要以公安信息网建设为基础,以公安业务信息共享为目标,向科技要誓力.加强信息中心建设,发挥科技强警作用.     

Cyber-Stalking Victimization: What Predicts Fear Among Portuguese Adolescents?

A large body of research clearly demonstrates that adolescents use technology to a staggering degree and that they are one of the main groups that are vulnerable to online victimization. However, the study of cyber-stalking, which is a form of cyber-harassment victimization, has been limited to the adult population and has resulted in some controversy regarding whether fear is a definitional criterion for this phenomenon. In Portugal, the study of cyber-stalking among adolescents is limited, as it is not yet a target of scientific research, public politics or social attention. The current study assessed the cyber-stalking victimization of 627 Portuguese adolescents (12- to 16-years-old). The prevalence of victimization, the cyber-victim’s profile, cyber-stalking dynamics, the cyber-stalker’s profile, parental cyber-involvement and adolescents fear reporting were analysed. The majority of the current sample admitted to having been the victim of cyber-stalking at some point in their life, and nearly half of the adolescents reported experiencing fear after the victimization. A logistic regression model was developed to predict fear reporting. Consistent with previous research, the results indicated that fear is strongly associated with female victims and shed light on the self-perception of online risk and a number of parental involvement practices. Being the target of 1) messages of exaggerated affection, 2) persistent cyber-stalking or 3) older cyber-stalkers was also associated with fear. These results underscore the importance of understanding fear as a complex emotion that results from the interaction of different variables. Thus, it is critical to adopt fear as a key criterion of the cyber-stalking definition. Implications for social, educational, political and judicial practices are also discussed.     

Multivariate Classification of Original and Fake Perfumes by Ion Analysis and Ethanol Content

The increased marketing of fake perfumes has encouraged us to investigate how to identify such products by their chemical characteristics and multivariate analysis. The aim of this study was to present an alternative approach to distinguish original from fake perfumes by means of the investigation of sodium, potassium, chloride ions, and ethanol contents by chemometric tools. For this, 50 perfumes were used (25 original and 25 counterfeit) for the analysis of ions (ion chromatography) and ethanol (gas chromatography). The results demonstrated that the fake perfume had low levels of ethanol and high levels of chloride compared to the original product. The data were treated by chemometric tools such as principal component analysis and linear discriminant analysis. This study proved that the analysis of ethanol is an effective method of distinguishing original from the fake products, and it may potentially be used to assist legal authorities in such cases.     

Deep learning for sex determination: Analyzing over 200,000 panoramic radiographs

The objective of this study is to assess the performance of an innovative AI-powered tool for sex determination using panoramic radiographs (PR) and to explore factors affecting the performance of the convolutional neural network (CNN). The study involved 207,946 panoramic dental X-rays and their corresponding reports from 15 clinical centers in São Paulo, Brazil. The PRs were acquired with four different devices, and 58% of the patients were female. Data preprocessing included anonymizing the exams, extracting pertinent information from the reports, such as sex, age, type of dentition, and number of missing teeth, and organizing the data into a PostgreSQL database. Two neural network architectures, a standard CNN and a ResNet, were utilized for sex classification, with both undergoing hyperparameter tuning and cross-validation to ensure optimal performance. The CNN model achieved 95.02% accuracy in sex estimation, with image resolution being a significant influencing factor. The ResNet model attained over 86% accuracy in subjects older than 6 years and over 96% in those over 16 years. The algorithm performed better on female images, and the area under the curve (AUC) exceeded 96% for most age groups, except the youngest. Accuracy values were also assessed for different dentition types (deciduous, mixed, and permanent) and missing teeth. This study demonstrates the effectiveness of an AI-driven tool for sex determination using PR and emphasizes the role of image resolution, age, and sex in determining the algorithm's performance.     

STR data (CD4, CSF1PO, F13A01, FES/FPS, MBPB, TH01, TPOX) from North Portugal.

Allele frequencies for seven STRs (CD4, CSF1PO, F13A01, FES/FPS, MBPB, TH01, TPOX) were estimated from samples (sized between 300 and 940) of unrelated individuals born in North Portugal.     

Genetic diversity and admixture data on 11 STRs (F13B, TPOX, CSF1PO, F13A01, D7S820, LPL, TH01, vWA, D13S317, FESFPS, and D16S539) in a sample of Rio de Janeiro European-descendants population, Brazil

Allelic frequencies, forensic parameters and admixture values for eleven STR loci (F13B, TPOX, CSF1PO, F13A01, D7S820, LPL, TH01, vWA, D13S317, FESFPS, and D16S539) were determined in a sample of unrelated individuals, European descendants from Rio de Janeiro area, Brazil.