Cellular neural networks as a general massively parallel computational paradigm

In this paper is presented the use of the discrete-time cellular neural network (DTCNN) paradigm to develop algorithms devised for general-purpose massively parallel processing (MPP) systems. This paradigm is defined in discrete N-dimensional spaces (lattices) and is characterized by the locality of the direct information transmission between the space points (cells) and by continuous values of data and parameters; the DTCNN paradigm is thus able to express most of the typical MPP applications. A general version of a DTCNN has been implemented and optimized for three MPP architectures, namely the Connection Machines CM-2 and CM-5 and the Cray T3D. The comparison between the three machine performances with those achieved by a standard SPARC-20 workstation shows that, particularly with large lattices, the speed-up allowed in the computational times is significant and the range of solvable problem sizes is widely extended.     

Diagnostic Accuracy of CT Texture Analysis in Adrenal Masses: A Systematic Review

Adrenal incidentalomas (AIs) are incidentally discovered adrenal neoplasms. Overt endocrine secretion (glucocorticoids, mineralocorticoids, and catecholamines) and malignancy (primary or metastatic disease) are assessed at baseline evaluation. Size, lipid content, and washout characterise benign AIs (respectively, <4 cm, <10 Hounsfield unit, and rapid release); nonetheless, 30% of adrenal lesions are not correctly indicated. Recently, image-based texture analysis from computed tomography (CT) may be useful to assess the behaviour of indeterminate adrenal lesions. We performed a systematic review to provide the state-of-the-art of texture analysis in patients with AI. We considered 9 papers (from 70 selected), with a median of 125 patients (range 20–356). Histological confirmation was the most used criteria to differentiate benign from the malignant adrenal mass. Unenhanced or contrast-enhanced data were available in all papers; TexRAD and PyRadiomics were the most used software. Four papers analysed the whole volume, and five considered a region of interest. Different texture features were reported, considering first- and second-order statistics. The pooled median area under the ROC curve in all studies was 0.85, depicting a high diagnostic accuracy, up to 93% in differentiating adrenal adenoma from adrenocortical carcinomas. Despite heterogeneous methodology, texture analysis is a promising diagnostic tool in the first assessment of patients with adrenal lesions.     

Synthesis,Pharmacological Evaluation,and Docking Studies of Novel Pyridazinone‐Based Cannabinoid Receptor Type 2 Ligands

In recent years, cannabinoid type 2 receptors (CB₂R) have emerged as promising therapeutic targets in a wide variety of diseases. Selective ligands of CB₂R are devoid of the psychoactive effects typically observed for CB₁R ligands. Based on our recent studies on a class of pyridazinone 4‐carboxamides, further structural modifications of the pyridazinone core were made to better investigate the structure–activity relationships for this promising scaffold with the aim to develop potent CB₂R ligands. In binding assays, two of the new synthesized compounds [6‐(3,4‐dichlorophenyl)‐2‐(4‐fluorobenzyl)‐cis‐N‐(4‐methylcyclohexyl)‐3‐oxo‐2,3‐dihydropyridazine‐4‐carboxamide ( 2 ) and 6‐(4‐chloro‐3‐methylphenyl)‐cis‐N‐(4‐methylcyclohexyl)‐3‐oxo‐2‐pentyl‐2,3‐dihydropyridazine‐4‐carboxamide ( 22 )] showed high CB₂R affinity, with K_i values of 2.1 and 1.6 nm , respectively. In addition, functional assays of these compounds and other new active related derivatives revealed their pharmacological profiles as CB₂R inverse agonists. Compound 22 displayed the highest CB₂R selectivity and potency, presenting a favorable in silico pharmacokinetic profile. Furthermore, a molecular modeling study revealed how 22 produces inverse agonism through blocking the movement of the toggle‐switch residue, W6.48.     

Combined micro-cogeneration and electric vehicle system for household application: An energy and economic analysis in a Northern European climate

In recent years, Denmark boosted investments in renewable energy and electrification of transportation. The Danish Agenda proposed that all primary energy consumption will be covered by renewable sources such as wind, biomass and solar by 2050. These changes require significant investment and re-thinking of entire energy infrastructures and types of consumption. The Agenda also suggested, among other things, improving the efficiency of energy systems.In this paper, the interactions between charging an electric car and an innovative cogeneration system for household application (micro-solid oxide fuel cell with an integrated heating system) are investigated. The charge of the electric car by the cogenerator produces waste heat that can be used to partially cover the heat demand of the house. In this way it may be possible to increase overall efficiency and decrease total energy costs. Different innovative strategies are proposed and analyzed to manage charging an electric car and efficiently using the waste heat available. The aims of this study are to make the system grid-independent, to decrease the thermal stress of SOFCs and to determine the nominal power of an integrated heating system. The results show energy efficiency and economic profitability of the system, even if subsidies are not included.     

Environmental Innovations,Local Networks and Internationalization

This paper investigates the forces correlated with environmental innovations (EIs) introduced by firms in local production systems (LPS). The role of inter-firm network relationships, agglomeration economies and internationalization strategies is jointly analysed for a sample of 555 firms in the Emilia–Romagna (ER) region (North-East Italy). Cooperating with a certain kind of local actors—i.e. suppliers and universities—is the most important EI driver for the investigated firms, along with their training coverage and their adoption of information and communication technologies. The role of agglomeration economies is instead less clear-cut. They spur EIs only in the presence of established LPS, with idiosyncratic sector specialization, while conversely they act as EI barriers. Networking effects and agglomeration economies are instead found to strongly promote the adoption of EIs by multinational firms, thus highlighting the importance of local–global interactions. Interesting specifications for these results are found for particular kinds of EIs, in such fields as CO₂ abatement and ISO labelling, generally extending the analysis of EI drivers by joining local and international factors. In addition, the role of regulatory sector factors confirms the induced innovation hypothesis and provides a robustness check to our results.