A Simplified Mathematical Model for Two-Sided Market Systems With an Intervening Engineered Platform

A two-sided market involves two different user groups whose interactions are enabled over a platform that provides a distinct set of values to either side. In such market systems, one side's participation depends on the value created by presence of the other side over the platform. Two-sided market platforms must acquire enough users on both sides in appropriate proportions to generate value to either side of the user market. In this paper, we present a simplified, generic mathematical model for two-sided markets with an intervening platform that enables interaction between the two different sets of users with distinct value propositions. The proposed model captures both the same side as well as cross-side effects (i.e., network externalities) and can capture any behavioral asymmetry between the different sides of the two-sided market system. The cross-side effects are captured using the notion of affinity curves while same side effects are captured using four rate parameters. We demonstrate the methodology on canonical affinity curves and comment on the attainment of stability at the equilibrium points of two-sided market systems. Subsequently a stochastic choice-based model of consumers and developers is described to simulate a two-sided market from grounds-up and the observed affinity curves are documented. Finally we discuss how the two-sided market model links with and impacts the engineering characteristics of the platform

2,6-Diphenyl-imidazopyridine derivatives as novel prototypes of anticancer agents targeting aldehyde dehydrogenase

Aldehyde dehydrogenase (ALDH) superfamily comprises 19 different enzyme types located in specific subcellular districts, including cytosol and mitocondria. Their main function is to oxidize endogenous and exogenous aldehydes produced in human cells. In particular, isoforms 1A1, 1A2 and 1A3 catalyze the transformation of retinal into retinoic acid, which is a potent differentiation tissue factor for cellular development. Overexpression of these three isoforms in cancer stem cells (CSC), underlined in recent studies, is to date extremely important in cancer field, as it offers the chance to use these proteins both as prognostic marker and as novel targets in the fight against cancer. Here we present a novel series of 2,6-diphenyl-imidazol[1,2-a]pyridines, designed as aldehyde dehydrogenase inhibitors by means of a structured-based optimizations of a previously developed lead, GA11. The novel compounds were evaluated in vitro for their activity and selectivity against the three isoforms of the ALDH1A family, and investigated through crystallization and modeling studies for their ability to interact with the catalytic site of the 1A3 isoform. Tested in vitro on different populations of CSCs, obtained from glioma, colorectal and prostate tissue specimens, they exhibited a relevant anti-proliferative efficacy, thus paving the way for treating cancer by means of the still untapped aldehyde dehydrogenases

Development of a discontinuous Galerkin solver for the simulation of turbine stages

A high-order Discontinuous Galerkin (DG) solver is assessed in the computation of the flow through an Organic Rankine Cycle turbine nozzle and stage. The flow features are predicted with a RANS (Reynolds averaged Navier­Stoke) approach and the k-log() turbulence model in a multi reference frame, where interfaces between fixed and rotating zones are treated with a mixing plane approach, and non reflecting boundary conditions are used. Primitive variables based on pressure and temperature logarithms are adopted to ensure non-negative thermodynamic variables at a discrete level. The fluid can be modeled with the polytropic ideal gas law and the Peng-Robinson equation of state

Remote sensing-based estimation of gross primary production in a subalpine grassland

This study investigates the performances in a terrestrial ecosystem of gross primary production (GPP) estimation of a suite of spectral vegetation indexes (VIs) that can be computed from currently orbiting platforms. Vegetation indexes were computed from near-surface field spectroscopy measurements collected using an automatic system designed for high temporal frequency acquisition of spectral measurements in the visible near-infrared region. Spectral observations were collected for two consecutive years in Italy in a subalpine grassland equipped with an eddy covariance (EC) flux tower that provides continuous measurements of net ecosystem carbon dioxide (CO2) exchange (NEE) and the derived GPP. Different VIs were calculated based on ESA-MERIS and NASA-MODIS spectral bands and correlated with biophysical (Leaf area index, LAI; fraction of photosynthetically active radiation intercepted by green vegetation, f IPARg), biochemical (chlorophyll concentration) and ecophysiological (green light-use efficiency, LUEg) canopy variables. In this study, the normalized difference vegetation index (NDVI) was the index best correlated with LAI and f IPARg (r = 0.90 and 0.95, respectively), the MERIS terrestrial chlorophyll index (MTCI) with leaf chlorophyll content (r = 0.91) and the photochemical reflectance index (PRI551), computed as (R531 −R551)/(R531 +R551) with LUEg (r = 0.64). Subsequently, these VIs were used to estimate GPP using different modelling solutions based on Monteith’s lightuse efficiency model describing the GPP as driven by the photosynthetically active radiation absorbed by green vegetation (APARg) and by the efficiency (") with which plants use the absorbed radiation to fix carbon via photosynthesis. Results show that GPP can be successfully modelled with a combination of VIs and meteorological data or VIs only. Vegetation indexes designed to be more sensitive to chlorophyll content explained most of the variability in GPP in the ecosystem investigated, characterised by a strong seasonal dynamic of GPP. Accuracy in GPP estimation slightly improves when taking into account high frequency modulations of GPP driven by incident PAR or modelling LUEg with the PRI in model formulation. Similar results were obtained for both measured daily VIs and VIs obtained as 16-day composite time series and then downscaled from the compositing period to daily scale (resampled data). However, the use of resampled data rather than measured daily input data decreases the accuracy of the total GPP estimation on an annual basis.JRC.H.4-Monitoring Agricultural Resource

Chemical exchange saturation transfer MRI shows low cerebral 2-deoxy-D-glucose uptake in a model of Alzheimer's Disease

Glucose is the central nervous system's only energy source. Imaging techniques capable to detect pathological alterations of the brain metabolism are useful in different diagnostic processes. Such techniques are also beneficial for assessing the evaluation efficacy of therapies in pre-clinical and clinical stages of diseases. Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a possible alternative to positron emission tomography (PET) imaging that has been widely explored in cancer research in humans and animal models. We propose that pathological alterations in brain 2-deoxy-D-glucose (2DG) uptake, typical of neurodegenerative diseases, can be detected with CEST MRI. Transgenic mice overexpressing a mutated form of amyloid precusrsor protein (APP23), a model of Alzheimer's disease, analyzed with CEST MRI showed a clear reduction of 2DG uptake in different brain regions. This was reminiscent of the cerebral condition observed in Alzheimer's patients. The results indicate the feasibility of CEST for analyzing the brain metabolic state, with better image resolution than PET in experimental models

I.S.Mu.L.T - Rotator cuff tears guidelines

Despite the high level achieved in the field of shoulder surgery, a global consensus on rotator cuff tears management is lacking. This work is divided into two main sessions: in the first, we set questions about hot topics involved in the rotator cuff tears, from the etiopathogenesis to the surgical treatment. In the second, we answered these questions by mentioning Evidence Based Medicine. The aim of the present work is to provide easily accessible guidelines: they could be considered as recommendations for a good clinical practice developed through a process of systematic review of the literature and expert opinion, in order to improve the quality of care and rationalize the use of resources

Superconformal indices at large N and the entropy of AdS5 x SE5 black holes

The large N limit of the four-dimensional superconformal index was computed and successfully compared to the entropy of a class of AdS5 black holes only in the particular case of equal angular momenta. Using the Bethe ansatz formulation, we compute the index at large N with arbitrary chemical potentials for all charges and angular momenta, for general four-dimensional conformal theories with a holographic dual. We conjecture and bring some evidence that a particular universal contribution to the sum over Bethe vacua dominates the index at large N. For SYM, this contribution correctly leads to the entropy of BPS Kerr-Newman black holes in AdS5 x S5 for arbitrary values of the conserved charges, thus completing the microscopic derivation of their microstates. We also consider theories dual to AdS5 x SE5, where SE5 is a Sasaki-Einstein manifold. We first check our results against the so-called universal black hole. We then explicitly construct the near-horizon geometry of BPS Kerr-Newman black holes in AdS5 T^{1,1}, charged under the baryonic symmetry of the conifold theory and with equal angular momenta. We compute the entropy of these black holes using the attractor mechanism and find complete agreement with the field theory predictions

Bulbar involvement and cognitive features in amyotrophic lateral sclerosis: a retrospective study on 347 patients

BackgroundThis study aimed at clarifying the role of bulbar involvement (BI) as a risk factor for cognitive impairment (CI) in non-demented amyotrophic lateral sclerosis (ALS) patients.MethodsData on N = 347 patients were retrospectively collected. Cognition was assessed via the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). On the basis of clinical records and ALS Functional Rating Scale-Revised (ALSFRS-R) scores, BI was characterized as follows: (1) BI at onset—from medical history; (2) BI at testing (an ALSFRS-R-Bulbar score ≤11); (3) dysarthria (a score ≤3 on item 1 of the ALSFRS-R); (4) severity of BI (the total score on the ALSFRS-R-Bulbar); and (5) progression rate of BI (computed as 12-ALSFRS-R-Bulbar/disease duration in months). Logistic regressions were run to predict a below- vs. above-cutoff performance on each ECAS measure based on BI-related features while accounting for sex, disease duration, severity and progression rate of respiratory and spinal involvement and ECAS response modality.ResultsNo predictors yielded significance either on the ECAS-Total and -ALS-non-specific or on ECAS-Language/-Fluency or -Visuospatial subscales. BI at testing predicted a higher probability of an abnormal performance on the ECAS-ALS-specific (p = 0.035) and ECAS-Executive Functioning (p = 0.018). Lower ALSFRS-R-Bulbar scores were associated with a defective performance on the ECAS-Memory (p = 0.025). No other BI-related features affected other ECAS performances.DiscussionIn ALS, the occurrence of BI itself, while neither its specific features nor its presence at onset, might selectively represent a risk factor for executive impairment, whilst its severity might be associated with memory deficits