Disastri Naturali e Dynamic Capabilities nel Commercio

Il presente contributo descrive i primi risultati emersi da un’indagine esplorativa volta ad esaminare l’impatto che il terremoto del 2012 ha prodotto sulle attività commerciali al dettaglio della bassa emiliana. L’obiettivo specifico è quello di analizzare la capacità di risposta di tali tipologie di imprese all’evento critico adottando la prospettiva teorica delle capacità dinamiche. Si tratta di temi che la letteratura corrente non ha affrontato in modo sistematico ed adeguato in condizioni di criticità, soprattutto con riferimento al contesto della distribuzione al dettaglio. La metodologia scelta si è basata sull’utilizzo di strumenti di analisi qualitativa quali focus group e interviste semi-strutturate a un campione di dettaglianti colpiti dal sisma, caratterizzati da diverse specializzazioni merceologiche e parametri dimensionali. I primi risultati hanno evidenziato le risorse e le competenze ritenute necessarie per essere competitivi prima del sisma (qualità del servizio e assistenza alla clientela nel momento della vendita), nella gestione dell’evento critico (tempestività di reazione, creatività e flessibilità nella gestione dell’emergenza, sia nei rapporti con la clientela che con i fornitori; la necessità di rivedere l’offerta e di modificare l’assortimento) e in prospettiva futura (capacità di lettura del mercato, innovazione, acquisizione di nuove competenze tramite percorsi di formazione). Ne emergono alcune implicazioni manageriali e di policy

The INSIDEOUT framework provides precise signatures of the balance of intrinsic and extrinsic dynamics in brain states

Finding precise signatures of different brain states is a central, unsolved question in neuroscience. We reformulated the problem to quantify the 'inside out' balance of intrinsic and extrinsic brain dynamics in brain states. The difference in brain state can be described as differences in the detailed causal interactions found in the underlying intrinsic brain dynamics. We used a thermodynamics framework to quantify the breaking of the detailed balance captured by the level of asymmetry in temporal processing, i.e. the arrow of time. Specifically, the temporal asymmetry was computed by the time-shifted correlation matrices for the forward and reversed time series, reflecting the level of non-reversibility/non-equilibrium. We found precise, distinguishing signatures in terms of the reversibility and hierarchy of large-scale dynamics in three radically different brain states (awake, deep sleep and anaesthesia) in electrocorticography data from non-human primates. Significantly lower levels of reversibility were found in deep sleep and anaesthesia compared to wakefulness. Non-wakeful states also showed a flatter hierarchy, reflecting the diversity of the reversibility across the brain. Overall, this provides signatures of the breaking of detailed balance in different brain states, perhaps reflecting levels of conscious awareness

Antioxidant and Angiotensin I-Converting Enzyme (ACE) Inhibitory Peptides Obtained from Alcalase Protein Hydrolysate Fractions of Hemp (Cannabis sativa L.) Bran

Proteins from hemp bran (HPB), a byproduct of the hemp seed food-processing chain, were chemically extracted, hydrolyzed by Alcalase, and separated by membrane ultrafiltration into four fractions (MW <1, 1-3, 3-5, and >5 kDa). The antioxidant and antihypertensive properties of the initial extract and the fractions were evaluated by in vitro assays for their ability to scavenge radical species, bind with metal ions, reduce ferric ions, and inhibit angiotensin-converting enzyme (ACE) activity. Bioactive peptides were identified by high-resolution mass spectrometry and sequence comparison with BIOPEP and BioPep DB databases. The hydrolysate was strongly antioxidant and ACE-inhibiting; the most bioactive peptides were further concentrated by ultrafiltration. Of the 239 peptides identified, 47 (12 antioxidant and 35 ACE-inhibitory) exhibited structural features correlated with the specific bioactivity. These results highlight the promise of hydrolysate and size-based HPB fractions as natural functional ingredients for the food or pharmaceutical industry

Strength-dependent perturbation of whole-brain model working in different regimes reveals the role of fluctuations in brain dynamics

Despite decades of research, there is still a lack of understanding of the role and generating mechanisms of the ubiquitous fluctuations and oscillations found in recordings of brain dynamics. Here, we used whole-brain computational models capable of presenting different dynamical regimes to reproduce empirical data's turbulence level. We showed that the model's fluctuations regime fitted to turbulence more faithfully reproduces the empirical functional connectivity compared to oscillatory and noise regimes. By applying global and local strength-dependent perturbations and subsequently measuring the responsiveness of the model, we revealed each regime's computational capacity demonstrating that brain dynamics is shifted towards fluctuations to provide much-needed flexibility. Importantly, fluctuation regime stimulation in a brain region within a given resting state network modulates that network, aligned with previous empirical and computational studies. Furthermore, this framework generates specific, testable empirical predictions for human stimulation studies using strength-dependent rather than constant perturbation. Overall, the whole-brain models fitted to the level of empirical turbulence together with functional connectivity unveil that the fluctuation regime best captures empirical data, and the strength-dependent perturbative framework demonstrates how this regime provides maximal flexibility to the human brain

Data-driven discovery of canonical large-scale brain dynamics

Human behavior and cognitive function correlate with complex patterns of spatio-temporal brain dynamics, which can be simulated using computational models with different degrees of biophysical realism. We used a data-driven optimization algorithm to determine and classify the types of local dynamics that enable the reproduction of different observables derived from functional magnetic resonance recordings. The phase space analysis of the resulting equations revealed a predominance of stable spiral attractors, which optimized the similarity to the empirical data in terms of the synchronization, metastability, and functional connectivity dynamics. For stable limit cycles, departures from harmonic oscillations improved the fit in terms of functional connectivity dynamics. Eigenvalue analyses showed that proximity to a bifurcation improved the accuracy of the simulation for wakefulness, while deep sleep was associated with increased stability. Our results provide testable predictions that constrain the landscape of suitable biophysical models, while supporting noise-driven dynamics close to a bifurcation as a canonical mechanism underlying the complex fluctuations that characterize endogenous brain activity

Pomegranate extract affects fungal biofilm production: consumption of phenolic compounds and alteration of fungal autoinducers release

Candida albicans expresses numerous virulence factors that contribute to pathogenesis, including its dimorphic transition and even biofilm formation, through the release of specific quorum sensing molecules, such as the autoinducers (AI) tyrosol and farnesol. In particular, once organized as biofilm, Candida cells can elude conventional antifungal therapies and the host’s immune defenses as well. Accordingly, biofilm-associated infections become a major clinical challenge underlining the need of innovative antimicrobial approaches. The aim of this in vitro study was to assess the effects of pomegranate peel extract (PomeGr) on C. albicans growth and biofilm formation; in addition, the release of tyrosol and farnesol was investigated. The phenolic profile of PomeGr was assessed by high-performance liquid chromatography coupled to electrospray ionization mass spectrometry (HPLC-ESI-MS) analysis before and after exposure to C. albicans. Here, we showed that fungal growth, biofilm formation and AI release were altered by PomeGr treatment. Moreover, the phenolic content of PomeGr was substantially hampered upon exposure to fungal cells; particularly pedunculagin, punicalin, punicalagin, granatin, di-(HHDP-galloyl-hexoside)-pentoside and their isomers as well as ellagic acid–hexoside appeared highly consumed, suggesting their role as bioactive molecules against Candida. Overall, these new insights on the anti-Candida properties of PomeGr and its potential mechanisms of action may represent a relevant step in the design of novel therapeutic approaches against fungal infections