La scissione societaria: aspetti economico-aziendali e contabili. Il caso Fiat

La scissione di società è un istituto relativamente giovane, introdotto nel nostro ordinamento con l'art. 18 del D.L. n.22 del 16 gennaio 1991. Essa si identifica come un complesso fenomeno economico e gestionale attraverso la quale l'azienda trasferisce la totalità, o una parte, del proprio patrimonio ad altre aziende già esistenti o all'uopo costituite. Data la poliedricità di tale istituto, la scissione societaria consente di plasmare gli effetti di tale operazione sulla compagine sociale e sul relativo patrimonio per ottenere una pluralità di obiettivi e per adattarsi al contesto competitivo sempre in continua evoluzione. Il seguente elaborato si articola in due parti delineando le principali tematiche di questa operazione straordinaria ed esaminando un caso pratico. Nella prima parte,infatti, verrà dato particolare risalto ai profili economico-aziendali, giuridici,contabili e fiscali dell'operazione. Nella seconda parte sarà esaminata, con particolare attenzione, una scissione societaria del contesto italiano, ovvero il Caso Fiat; andando a delineare l'evoluzione storica, le fasi dell'operazione e i risultati ottenuti

The Community Order and the Mental Health Treatment Requirement

Just a few months into 2008, a convergence of unfortunate circumstances has brought the plight of offenders with mental health problems into sharp focus. Figures released by the Ministry of Justice showed there were 92 apparently self-inflicted deaths among prisoners in England and Wales in 2007, compared with 67 in 2006. This 37% increase in suicides in prison has been associated with the overcrowding that has continued inexorably.This article discusses the application of mental health services to offenders in the prison and the community contexts

Effectiveness of work skills programmes for offenders with mental disorders: a systematic review

Background: Academic literature and government initiatives have emphasised the importance of work as a means of improving health and reducing reoffending among offenders with mental disorders. Whilst a number of work skills programmes have shown promise for offenders more generally, evaluation of evidence for their effectiveness for those with a mental disorder is lacking, particularly in relation to improving employment outcomes. Aims: To assess the evidence on the effectiveness of work skills programmes for mentally disordered offenders. Method: A systematic review of the literature was conducted by searching the following databases: PsycINFO, CINAHL, Cochrane Library (Trials Register), Embase and Medline, using search terms which included Work Skills Programme*, Offend* and Mental*. Any empirical comparison study of work skills programmes was included in this review. The primary outcome was employment. Secondary outcomes included employment outcomes, reoffending, education, mental state, substance misuse, global functioning, quality of life, acceptability, leaving the study early and cost effectiveness or other economic outcomes. Results: Six articles met the inclusion criteria. Collectively they provided limited evidence that work skills programmes increase the likelihood of people with mental disorder who are offenders obtaining employment in the short term, but there are insufficient studies to determine the long-term impact of work skills programmes. Conclusions: There is modest evidence to support inclusion of specific work skills programmes in the treatment of offenders with mental disorder. Future studies should be of theoretically driven programmes, such as Individual Placement Support (IPS), use a standard set of relevant outcome measures and long enough follow-up for testing the effectiveness of any programme on engagement in competitive, paid employment as, even if skilled, offenders with mental disorder must constitute a hard to place group

POPNASv2: An Efficient Multi-Objective Neural Architecture Search Technique

Automating the research for the best neural network model is a task that has gained more and more relevance in the last few years. In this context, Neural Architecture Search (NAS) represents the most effective technique whose results rival the state of the art hand-crafted architectures. However, this approach requires a lot of computational capabilities as well as research time, which make prohibitive its usage in many real-world scenarios. With its sequential model-based optimization strategy, Progressive Neural Architecture Search (PNAS) represents a possible step forward to face this resources issue. Despite the quality of the found network architectures, this technique is still limited in research time. A significant step in this direction has been done by Pareto-Optimal Progressive Neural Architecture Search (POPNAS), which expand PNAS with a time predictor to enable a trade-off between search time and accuracy, considering a multi-objective optimization problem. This paper proposes a new version of the Pareto-Optimal Progressive Neural Architecture Search, called POPNASv2. Our approach enhances its first version and improves its performance. We expanded the search space by adding new operators and improved the quality of both predictors to build more accurate Pareto fronts. Moreover, we introduced cell equivalence checks and enriched the search strategy with an adaptive greedy exploration step. Our efforts allow POPNASv2 to achieve PNAS-like performance with an average 4x factor search time speed-up. The official version of this tool is located in the following link: AndreaFalanti/popnas-v2 (github.com

SGDE: Secure Generative Data Exchange for Cross-Silo Federated Learning

Privacy regulation laws, such as GDPR, impose transparency and security as design pillars for data processing algorithms. In this context, federated learning is one of the most influential frameworks for privacy-preserving distributed machine learning, achieving astounding results in many natural language processing and computer vision tasks. Several federated learning frameworks employ differential privacy to prevent private data leakage to unauthorized parties and malicious attackers. Many studies, however, highlight the vulnerabilities of standard federated learning to poisoning and inference, thus raising concerns about potential risks for sensitive data. To address this issue, we present SGDE, a generative data exchange protocol that improves user security and machine learning performance in a cross-silo federation. The core of SGDE is to share data generators with strong differential privacy guarantees trained on private data instead of communicating explicit gradient information. These generators synthesize an arbitrarily large amount of data that retain the distinctive features of private samples but differ substantially. In this work, SGDE is tested in a cross-silo federated network on images and tabular datasets, exploiting beta-variational autoencoders as data generators. From the results, the inclusion of SGDE turns out to improve task accuracy and fairness, as well as resilience to the most influential attacks on federated learning

Tackling obesity in mental health secure units: a mixed method synthesis of available evidence

Background: The prevalence and incidence of obesity are high in people with severe mental illness (SMI). In England, around 6000 people with SMI access care from secure mental health units. There is currently no specific guidance on how to reduce the risk of obesity-related morbidity and mortality in this population. Aims: To identify international evidence that addresses the issue of obesity in mental health secure units. Method: A mixed method review of evidence (published 2000-2015) was carried out to assess obesity prevalence, intervention and policy change, as well as barriers to change. Results: Evidence from 22 mainly small, non-comparator studies (reported in 21 papers) using a range of methods was reviewed. Dietary, physical activity and cultural interventions being implemented within secure units to address the problem of obesity showed some promising outcomes for physical health and health education. These were facilitated by adequate organisational resources, staff training and motivated staff. Holistic interventions that included a social and/or competitive element were more likely to be taken up. Involving patients in decision-making mediated the tension between facilitating behaviour change and imposing control. Barriers to successful outcomes included patient movement in and out of units, severity of mental health condition and resistance to change by patients and staff. Conclusions: Despite the promising outcomes reported, further assessment is needed of the feasibility, acceptability and effectiveness of interventions and policies targeting the obesogenic environment, using robust research methods. Declaration of interest: None