Do Homicide Perpetrators Have Higher Rates of Delayed-Suicide Than the Other Offenders? Data from a Sample of the Inmate Population in Italy

Homicide-suicide can be defined as homicide followed by the suicide of the perpetrator shortly afterward. In the so-called "homicide-delayed suicide", homicide and suicide occur but within a wide and not strictly defined timeframe. This study analyzes data concerning the suicide of 667 inmates in Italy between 2002 and 2015, considering homicide perpetrators compared to all offenders. The analyses revealed that inmates who had committed homicide were more likely to commit suicide (71% versus 45%; chi 2 = 10.952, p = 0.001) and the odds of suicide increase concerning 1.58 times among homicide perpetrators. The time-to-suicide interval after homicide ranges between 0 to 9.125 days (mean = 1.687,9; SD = 2.303,1). Moreover, the intimate-homicide offenders who committed suicide had a significantly shorter survival time after the offense than did the other non-intimate offenders who died by suicide (t test, t = -3.56, df = 90, p = 0.001). The link between homicide and higher suicide risk in homicide perpetrators should be highlighted because of all the homicide offenders passing through the criminal justice system. Superior knowledge about the path of homicide-delayed suicide will be of particular use to professionals in evaluating and treating homicide inmates. © 2022 by the authors

Child brides: the age estimation problem in young girls

The aim of this work is to study a sample of girls from 15 different countries using Third Molar Maturity Index (I3M ), to assess the probability that a girl has reached the legal age of 18 years. The studied sample consisted of 3228 Orthopantomograms of healthy female subjects from 15 different countries. The cut- off value of I3M = 0.08 was tested to discriminate adults (≥18 years) and minors (<18 years). X-ray images were processed by computer-aided drafting program ImageJ. The information on sensitivity and specificity of I3M coming from the 15 countries was pooled together using a bivariate Bayesian modeling approach. Specificity of the I3M test did not change when the country was considered, and its value remains greater than 85% for each studied country. This method is useful to estimate the age of the girls involved in suspected early marriage because of the high probability of correctly identifying a minor with similar results observed among tested populations

A machine learning pipeline for discriminant pathways identification

Motivation: Identifying the molecular pathways more prone to disruption during a pathological process is a key task in network medicine and, more in general, in systems biology. Results: In this work we propose a pipeline that couples a machine learning solution for molecular profiling with a recent network comparison method. The pipeline can identify changes occurring between specific sub-modules of networks built in a case-control biomarker study, discriminating key groups of genes whose interactions are modified by an underlying condition. The proposal is independent from the classification algorithm used. Three applications on genomewide data are presented regarding children susceptibility to air pollution and two neurodegenerative diseases: Parkinson's and Alzheimer's. Availability: Details about the software used for the experiments discussed in this paper are provided in the Appendix

Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms

Motivation :Reconstructing the topology of a gene regulatory network is one of the key tasks in systems biology. Despite of the wide variety of proposed methods, very little work has been dedicated to the assessment of their stability properties. Here we present a methodical comparison of the performance of a novel method (RegnANN) for gene network inference based on multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER), focussing our analysis on the prediction variability induced by both the network intrinsic structure and the available data. Results: The extensive evaluation on both synthetic data and a selection of gene modules of "Escherichia coli" indicates that all the algorithms suffer of instability and variability issues with regards to the reconstruction of the topology of the network. This instability makes objectively very hard the task of establishing which method performs best. Nevertheless, RegnANN shows MCC scores that compare very favorably with all the other inference methods tested. Availability: The software for the RegnANN inference algorithm is distributed under GPL3 and it is available at the corresponding author home page (http://mpba.fbk.eu/grimaldi/regnann-supmat

Ensure traceability in european food supply chain by using a blockchain system

This paper proposes a generic agri-food supply chain traceability system based on blockchain technology implementing the 'from-farm-to-fork' (F2F) model currently used in the European Union, which can integrate current traceability rules and processes. The proposed system allows the consumer to reconstruct the product history up to the origin in order to verify product health and quality by simple QR code scan. The blockchain chosen for this purpose is Hyperledger Sawtooth, issued with writing permissions and rules to guarantee access only to members recognized as legitimate participants in the process. The whole system has been realized according to an agile methodology (ABCDE), recently devised for designing a general blockchain system with software engineering practices by mean of User Stories and UML diagrams, in order to obtain a higher software quality. All of the involved operators are able to identify any participants along the entire supply chain, increasing the degree of trust between organizations and individuals, with autonomous management of temporal sequence of activities

Waste management: A comprehensive state of the art about the rise of blockchain technology

In the last century, the increased urbanization and population growth produced a dramatic increase in waste production, causing serious problems for the environment and human health like never before. Currently, correct waste management represents a serious challenge that can be faced through the use of new technologies. Blockchain technology is a disruptive and emerging ICT solution. Because of its ability to ensure transparency, data immutability, and consensus among stakeholders involved, this shared distributed data structure has grown in popularity in a variety of industrial sectors, including finance, health, and supply chain. The purpose of this study is to analyze the current state of the art in the use of blockchain technology in the waste management sector with a focus on the literature state of the art and on ongoing or soon to be launched industrial project cases. This paper investigates blockchain-based waste management systems; their benefits for the circular economy and in terms of social, environmental, economic, and health dimensions; as well as limitations and drawbacks that could prevent the use of blockchain in the waste sector

Ethereum smart contracts as blockchain-oriented microservices

We propose a model of software architecture where microservices are implemented by mean of Smart Contracts deployed in a blockchain, discussing similarities among the two paradigms and presenting an example of the implementation of an e-commerce platform