Politica industriale e sviluppo sostenibile

Il libro riproduce ed amplia le relazioni presentate al workshop del 3 ottobre 2014 presso il Dipartimento di Economia dell’Università di Parma, ad opera di studiosi appartenenti all’Università di Ferrara, allo Iefe-Università Bocconi di Milano, all’Università di Modena, alla Scuola Sant’Anna di Pisa, nonché alla stessa Università di Parma. I cinque contributi qui presentati fotografano cinque diversi aspetti del rapporto fra politica industriale (più in generale crescita economica diretta dalle istituzioni pubbliche) e sviluppo sostenibile: a livello nazionale, il possibile trade-off fra i due obiettivi di politica industriale e di sostenibilità ambientale nel tentativo di gerarchizzare i “settori strategici”, e la necessità che questo trade-off sia parzialmente compensato a livello di sforzo innovativo (Di Tommaso e Tassinari); a livello internazionale, la possibilità che politiche industriali nazionali non operino all’interno di un gioco a somma zero, ma diano risultati favorevoli al raggiungimento di un bene pubblico globale quale il cambiamento climatico (Fabbri e Ninni); a livello di imprese, la tendenziale riduzione delle contraddizioni fra incentivi al loro operare e “impronta” ambientale, grazie agli accordi volontari e in particolare all’importante ruolo della certificazione (Frey); a livello di istituzioni, l’esistenza di tipologie diverse di obiettivi e di strumenti a livello nazionale e a livello locale, e l’analisi in un confronto tra paesi europei delle caratteristiche delle politiche ambientali impostate a livello sub-nazionale (Croci e Molteni); a livello di mercato del lavoro, l’effetto sul tessuto industriale delle politiche di aumento della flessibilità del lavoro nella singola impresa, come aspetto particolare di una ridiscussione più ampia del concetto di sostenibilità ambientale e dei suoi rapporti con la politica nei confronti delle imprese (Giovannetti)

Arbuscular Mycorrhizal Fungi. Methods and Protocols.

Ferrol, N.; Lanfranco, L. (Eds.) 2020 Arbuscular Mycorrhizal Fungi. Methods and Protocols. Vol 2146. pp. 257. ISBN 978 1 0716-0602-

Obesity is associated with reduced orbitofrontal cortex volume: A coordinate-based meta-analysis

Neural models of obesity vary in their focus upon prefrontal and striatal differences. Animal and human studies suggest that differential functioning of the orbitofrontal cortex is associated with obesity. However, meta-analyses of functional neuroimaging studies have not found a clear relationship between the orbitofrontal cortex and obesity. Meta-analyses of structural imaging studies of obesity have shown mixed findings with regards to an association with reduced orbitofrontal cortex gray matter volume. To clarify these findings, we conducted a meta-analysis of 25 voxel-based morphometry studies, and found that greater body mass index is associated with decreased gray matter volume in the right orbitofrontal cortex (Brodmanns’ areas 10 and 11), where family-wise corrected p < .05, N = 7,612. Use of the right orbitofrontal cortex as a seed in a Neurosynth Network Coactivation analysis showed that this region is associated with activity in the left frontal medial cortex, left temporal lobe, right precuneus cortex, posterior division of the left middle temporal gyrus, and right frontal pole. When Neurosynth Network Coactivation results were submitted as regions of interest in the Human Connectome Project data, we found that greater body mass index was associated with greater activity in left frontal medial cortex response to the Gambling Task, where p < .05, although this did not survive Bonferroni-correction. Our findings highlight the importance of the orbitofrontal cortex structure and functioning in neural models of obesity. Exploratory analyses suggest more studies are needed that examine the functional significance of reduced orbitofrontal cortex gray matter volume in obesity, and the effect of age and weight changes on this relationship using longitudinal designs

The dysexecutive syndrome associated with ischaemic vascular disease and related subcortical neuropathology: A Boston Process Approach

The introduction of diagnostic criteria for vascular dementia has helped to re-define the impact of various subcortical neuropathologies on aging; however, state-of-the-art neuroimaging techniques and autopsy studies suggest that not all structural brain alterations associated with vascular dementia are exclusive to this neurodegenerative process alone. Thus, a detailed analysis of the cognitive phenotype associated with ischaemic vascular disease is key to our understanding of subcortical neuropathology and its associated behaviors. Over the past twenty years, we have operationally defined this cognitive phenotype using the Boston Process Approach to neuropsychological assessment. This has led to both an empirical, as well as a theoretical understanding of three core constructs related to the dysexecutive syndrome associated with ischaemic vascular disease affecting periventricular and deep white matter as well as subcortical structures connecting these regions with the prefrontal cortex. Thus, difficulties with mental set, cognitive control and mental manipulation negatively impact executive functioning. This review will outline the subtle markers underlying this prefrontal dysfunction, i.e., the dysexecutive phenotype, associated with ischaemic vascular disease and relate it to fundamental impairments of gating subserved by basal ganglia-thalamic pathways within and across various dementia syndromes

ConversationAlign: A Computational Pipeline for Evaluating Alignment in Natural Language Dyadic Interactions

Human communication involves synchronizing behaviors to optimize information transfer. Much of our understanding of communicative efficacy and coordination in conversation has relied upon carefully-controlled laboratory studies. Less is understood about assessing dynamics of dyadic interactions in naturalistic conversations. We introduce an computational pipeline that quantifies multidimensional (i.e., lexical, semantic, affective) alignment between interlocutors (i.e., conversation partners) in conversation transcripts of any length. This open-source R package (ConversationAlign): 1) translates raw language transcripts into a machine-readable format; 2) cleans and vectorizes input text into a one word-per-row format; 3) yokes values for up to 30 user-specified psycholinguistic dimensions to each word; and 4) computes two metrics of alignment within dyads and mean usage by interlocutor for each specified dimension by turn and conversation. We use this method to analyze linguistic hostility between US Presidential candidates in debates from 1960-2020. This computational pipeline supports interdisciplinary and multimodal analyses of naturalistic conversation