Cerebral hemodynamics on MR perfusion images before and after bypass surgery in patients with giant intracranial aneurysms

Preoperative assessment of the anatomy and dynamics of cerebral circulation for patients with giant intracranial aneurysm can improve both outcome prediction and therapeutic approach. The aim of our study was to use perfusion MR imaging to evaluate cerebral hemodynamics in such patients before and after extraintracranial high-flow bypass surgery. METHODS: Five patients with a giant aneurysm of the intracranial internal carotid artery underwent MR studies before, 1 week after, and 1 month after high-flow bypass surgery. We performed MR and digital subtraction angiography, and conventional and functional MR sequences (diffusion and perfusion). Surgery consisted of middle cerebral artery (MCA)-internal carotid artery bypass with saphenous vein grafts (n = 4) or MCA-external carotid artery bypass (n = 1). RESULTS: In four patients, MR perfusion study showed impaired hemodynamics in the vascular territory supplied by the MCA of the aneurysm side, characterized by significantly reduced mean cerebral blood flow (CBF), whereas mean transit time (MTT) and regional cerebral blood volume (rCBV) were either preserved, reduced, or increased. After surgery, angiography showed good canalization of the bypass graft. MR perfusion data obtained after surgery showed improved cerebral hemodynamics in all cases, with a return of CBF index (CBFi), MTT, and rCBV to nearly normal values. CONCLUSION: Increased MTT with increased or preserved rCBV can be interpreted as a compensatory vasodilatory response to reduced perfusion pressure, presumably from compression and disturbed flow in the giant aneurysmal sac. When maximal vasodilation has occurred, however, the brain can no longer compensate for diminished perfusion by vasodilation, and rCBV and CBFi diminish. Bypass surgery improves hemodynamics, increasing perfusion pressure and, thus, CBFi. Perfusion MR imaging can be used to evaluate cerebral hemodynamics in patients with intracranial giant aneurysm.BACKGROUND AND PURPOSE: Preoperative assessment of the anatomy and dynamics of cerebral circulation for patients with giant intracranial aneurysm can improve both outcome prediction and therapeutic approach. The aim of our study was to use perfusion MR imaging to evaluate cerebral hemodynamics in such patients before and after extraintracranial high-flow bypass surgery. METHODS: Five patients with a giant aneurysm of the intracranial internal carotid artery underwent MR studies before, 1 week after, and 1 month after high-flow bypass surgery. We performed MR and digital subtraction angiography, and conventional and functional MR sequences (diffusion and perfusion). Surgery consisted of middle cerebral artery (MCA)-internal carotid artery bypass with saphenous vein grafts (n = 4) or MCA-external carotid artery bypass (n = 1). RESULTS: In four patients, MR perfusion study showed impaired hemodynamics in the vascular territory supplied by the MCA of the aneurysm side, characterized by significantly reduced mean cerebral blood flow (CBF), whereas mean transit time (MTT) and regional cerebral blood volume (rCBV) were either preserved, reduced, or increased. After surgery, angiography showed good canalization of the bypass graft. MR perfusion data obtained after surgery showed improved cerebral hemodynamics in all cases, with a return of CBF index (CBFi), MTT, and rCBV to nearly normal values. CONCLUSION: Increased MTT with increased or preserved rCBV can be interpreted as a compensatory vasodilatory response to reduced perfusion pressure, presumably from compression and disturbed flow in the giant aneurysmal sac. When maximal vasodilation has occurred, however, the brain can no longer compensate for diminished perfusion by vasodilation, and rCBV and CBFi diminish. Bypass surgery improves hemodynamics, increasing perfusion pressure and, thus, CBFi. Perfusion MR imaging can be used to evaluate cerebral hemodynamics in patients with intracranial giant aneurysm

Automatic identification of sites prone to topographic seismic amplification effects by the current seismic codes

Current seismic codes provide proxies to estimate seismic amplification effects expected in correspondence of some morphological features. To make possible any empirical validation of these proxies, these features must be univocally identified on the basis of an automatic procedure. To this purpose, based on geomorphological considerations, a GIS-based numerical approach has been developed. The results of a morphometric analysis allowed the correct identification and mapping of the landforms of concern, at a detail corresponding to the resolution of the available digital elevation model (DEM). Some case-studies are provided to show the feasibility of the proposed approach. © 2023 The Author

A Quantitative Methodology to Measure Injector Fouling Through Image Analysis

Abstract The use of vegetables oils in a compression ignited internal combustion engine presents some critical issues as the large amount of carbon deposits on the tip of injectors, which significantly influence emissions and engine performance. A previous draft methodology was developed by the authors, based on images capture and post-processing. The carbon deposit was correlated with the number of pixels in the gray scale, so it was possible to determine a Fouling Index. First results showed interesting perspectives and some limits: the aim of the present work is the optimization of the test bench and methodology. At first an improvement of image acquisition, increasing sampling frequency and image resolution, is performed, replacing the old camera with a digital microscope and improving both injector and microscope positioning. The test bench prototype has been realized with the aid of 3D printing, obtaining fundamental mechanical components. Also an alternative methodology is proposed to evaluate carbon deposits volume through a Volumetric Index. The new methodology validation was done using images sampled with the previous test bench. The performances of the Fouling index and of the new Volumetric Index were compared and fouling was examined in the real case of a diesel engine, fed with diesel and sunflower oil. Results show a greater reliability of the new Volumetric Index

Pyrolysis of Olive Stone for Energy Purposes

Abstract Pyrolysis of biomass is a promising technology for the production of distributed and renewable energy on small and micro-scale since it produces a gas with relatively high calorific value, which can be burned in an internal combustion engine or in a microturbine; pyrolysis also generates by products (char and tar) which can be used to provide energy to the process or for cogeneration purposes. This research is aimed at the exploitation of waste from agricultural production processes, in particular olive mill wastes whose management has critical environmental and disposal costs; the yields of pyrogas, tar and char obtained from the pyrolysis of olive stone in a batch reactor was measured. Pyrogas produced is sampled through a line for the sampling of condensable substances in accordance with existing regulations, CEN/TS 15439, and once purified from water vapor and tars is analyzed with micro-GC. The data collected is used to perform mass and energy balances and to determine the content of tars and the Low Heating Value (LHV) of the gas produced

Cognitive analytics management of the customer lifetime value: an artificial neural network approach

Purpose: The purpose of this study is to show that the use of CAM (cognitive analytics management) methodology is a valid tool to describe new technology implementations for businesses. Design/methodology/approach: Starting from a dataset of recipes, we were able to describe consumers through a variant of the RFM (recency, frequency and monetary value) model. It has been possible to categorize the customers into clusters and to measure their profitability thanks to the customer lifetime value (CLV). Findings: After comparing two machine learning algorithms, we found out that self-organizing map better classifies the customer base of the retailer. The algorithm was able to extract three clusters that were described as personas using the values of the customer lifetime value and the scores of the variant of the RFM model. Research limitations/implications: The results of this methodology are strictly applicable to the retailer which provided the data. Practical implications: Even though, this methodology can produce useful information for designing promotional strategies and improving the relationship between company and customers. Social implications: Customer segmentation is an essential part of the marketing process. Improving further segmentation methods allow even small and medium companies to effectively target customers to better deliver to society the value they offer. Originality/value: This paper shows the application of CAM methodology to guide the implementation and the adoption of a new customer segmentation algorithm based on the CLV

i rexfo life an innovative business model to reduce food waste

Abstract Every year the food produced and wasted consumes a volume of water equal to 250 km3, requires around 30% of the world agricultural land, and it is responsible for the emission of 3,3 billion tons of greenhouse gases. The direct economic consequences of food waste are ranging around 750 billion dollars per year (FAO source). i-REXFO designs an innovative business model with the objective of reducing significantly the amount of landfilled food waste. The actions are economically sustained by public incentives, tax reductions and private revenues from energy valorization of residual food waste. Uptaking the good practices from other EU countries (Denmark) the project will develop a tool to design the integrated model, optimize it from a technical, economic and environmental point of view and transfer it to other EU regions. i-REXFO will increase consumer awareness on food waste reduction in retail malls and HORECA while facilitating the sale and donation to charities and food banks of close to expiration and aesthetically not adequate food; it will also remove the barriers that hamper the use of food residues in biogas plants. The actions are economically sustained from energy valorization of food waste in biogas plant that use the digestate as fertilizer, closing the cycle. I-REXFO will achieve an overall reduction of 17000 tons/year of food waste landfilled during the project duration and in the after life phase. This will correspond to an overall reduction of 41000 tons of CO2 equivalent emissions

Automatic Cyclic Alternating Pattern (CAP) analysis: Local and multi-trace approaches

The Cyclic Alternating Pattern (CAP) is composed of cycles of two different electroencephalographic features: an activation A-phase followed by a B-phase representing the background activity. CAP is considered a physiological marker of sleep instability. Despite its informative nature, the clinical applications remain limited as CAP analysis is a time-consuming activity. In order to overcome this limit, several automatic detection methods were recently developed. In this paper, two new dimensions were investigated in the attempt to optimize novel, efficient and automatic detection algorithms: 1) many electroencephalographic leads were compared to identify the best local performance, and 2) the global contribution of the concurrent detection across several derivations to CAP identification. The developed algorithms were tested on 41 polysomnographic recordings from normal (n = 8) and pathological (n = 33) subjects. In comparison with the visual CAP analysis as the gold standard, the performance of each algorithm was evaluated. Locally, the detection on the F4-C4 derivation showed the best performance in comparison with all other leads, providing practical suggestions of electrode montage when a lean and minimally invasive approach is preferable. A further improvement in the detection was achieved by a multi-trace method, the Global Analysis—Common Events, to be applied when several recording derivations are available. Moreover, CAP time and CAP rate obtained with these algorithms positively correlated with the ones identified by the scorer. These preliminary findings support efficient automated ways for the evaluation of the sleep instability, generalizable to both normal and pathological subjects affected by different sleep disorders