Analysis and design of planar and non-planar wings for induced drag minimization

The goal of the work was to develop and validate computational tools to be used for the design of planar and non-planar wing geometries for minimum induced drag. Because of the iterative nature of the design problem, it is important that, in addition to being sufficiently accurate for the problem at hand, they are reasonably fast and computationally efficient. Toward this end, a method of predicting induced drag in the presence of a non-rigid wake is coupled with a panel method. The induced drag prediction technique is based on the Kutta-Joukowski law applied at the trailing edge. Until recently, the use of this method has not been fully explored and pressure integration and Trefftz-plane calculations favored. As is shown in this report, however, the Kutta-Joukowski method is able to give better results for a given amount of effort than the more common techniques, particularly when relaxed wakes and non-planar wing geometries are considered. Using these tools, a workable design method is in place which takes into account relaxed wakes and non-planar wing geometries. It is recommended that this method be used to design a wind-tunnel experiment to verify the predicted aerodynamic benefits of non-planar wing geometries

Analysis and design of planar and non-planar wings for induced drag minimization

The goal of the work reported herein is to develop and validate computational tools to be used for the design of planar and non-planar wing geometries for minimum induced drag. Because of the iterative nature of the design problem, it is important that, in addition to being sufficiently accurate for the problem at hand, these tools need to be reasonably fast and computationally efficient. Toward this end, a method of predicting induced drag in the presence of a free wake has been coupled with a panel method. The induced drag prediction technique is based on the application of the Kutta-Joukowski law at the trailing edge. Until now, the use of this method has not been fully explored and pressure integration and Trefftz-plane calculations favored. As is shown in this report, however, the Kutta-Joukowski method is able to give better results for a given amount of effort than the more commonly used techniques, particularly when relaxed wakes and non-planar wing geometries are considered. Using these methods, it is demonstrated that a reduction in induced drag can be achieved through non-planar wing geometries. It remains to determine what overall drag reductions are possible when the induced drag reduction is traded-off against increased wetted area. With the design methodology that is described herein, such trade studies can be performed in which the non-linear effects of the free wake are taken into account

A Deep Learning Approach to Examine Ischemic ST Changes in Ambulatory ECG Recordings.

Patients with suspected acute coronary syndrome (ACS) are at risk of transient myocardial ischemia (TMI), which could lead to serious morbidity or even mortality. Early detection of myocardial ischemia can reduce damage to heart tissues and improve patient condition. Significant ST change in the electrocardiogram (ECG) is an important marker for detecting myocardial ischemia during the rule-out phase of potential ACS. However, current ECG monitoring software is vastly underused due to excessive false alarms. The present study aims to tackle this problem by combining a novel image-based approach with deep learning techniques to improve the detection accuracy of significant ST depression change. The obtained convolutional neural network (CNN) model yields an average area under the curve (AUC) at 89.6% from an independent testing set. At selected optimal cutoff thresholds, the proposed model yields a mean sensitivity at 84.4% while maintaining specificity at 84.9%

Business model configuration and dynamics for technology commercialization in mature markets.

Purpose The food industry is a well-established and complex industry. New entrants attempting to penetrate it via the commercialization of a new technological innovation could face high uncertainty and constraints. The capability to innovate through collaboration and to identify suitable strategies and innovative business models (BMs) can be particularly important for bringing a technological innovation to this market. However, although the potential for these capabilities has been advocated, we still lack a complete understanding of how new ventures could support the technology commercialization process via the development of BMs. The paper aims to discuss these issues. Design/methodology/approach To address this gap, this paper builds a conceptual framework that knits together the different bodies of extant literature (i.e. entrepreneurship, strategy and innovation) to analyze the BM innovation processes associated with the exploitation of emerging technologies; determines the suitability of the framework using data from the exploratory case study of IT IS 3D – a firm which has started to exploit 3D printing in the food industry; and improves the initial conceptual framework with the findings that emerged in the case study. Findings From this analysis it emerged that: companies could use more than one BM at a time; hence, BM innovation processes could co-exist and be run in parallel; the facing of high uncertainty might lead firms to choose a closed and/or a familiar BM, while explorative strategies could be pursued with open BMs; significant changes in strategies during the technology commercialization process are not necessarily reflected in a radical change in the BM; and firms could deliberately adopt interim strategies and BMs as means to identify the more suitable ones to reach the market. Originality/value This case study illustrates how firms could innovate the processes of their BM development to face the uncertainties linked with the entry into a mature and highly conservative industry (food)

Alpine gullies system evolution : erosion drivers and control factors. Two examples from the western Italian Alps

Denudation processes affecting mountain slopes may vary according to different factors (e.g., lithology and structural setting of bedrock, climate, relief features), which may be very diverse at the local scale. Gully complex systems, characterised by morphological features similar to those developing in other climate contexts (i.e., pseudo-badlands) are also becoming common at higher altitudes and latitudes. The selected study cases of Gran Gorgia (Susa Valley) and Saint Nicolas (Aosta Valley), in the Western Italian Alps, are sites of geomorphological interest as they are specifically relevant for their scientific features. The aims of this work are (i) reconstructing the morphometric evolution of gully systems and vegetation colonisation time by means of multitemporal spatial analysis on surface morphological changes under water erosion; (ii) reconstructing in detail, through dendrogeomorphological analysis, the progressive spatial surface denudation and changes in erosion rates, by analysing trees and exposed roots and using different indicators (i.e., compression wood, traumatic resin ducts); (iii) obtaining data on successive aggradation/degradation episodes along slopes surrounding such hotspots through geopedological investigations; and (iv) identifying which control factors exert a predominant role on denudation patterns in such contexts. Multidisciplinary analyses regarding the study sites allowed for detailing of erosional history of the studied slopes detecting the prevailing drivers of their evolution. According to the results and considering the common climate and bedrock conditions, the structural background seems to have more influence on slope evolution at the Saint Nicolas site, while superficial geomorphic processes seem to be more relevant at the Gran Gorgia site. Because the sites have already been recognised as part of geoheritage by local authorities, the data obtained in the present research on their genesis, evolution, and local drivers affecting the rates of denudation (i.e., scientific relevance of the site) suggests that description of the sites for dissemination purposes should include links to the entire slope history

acetyl l carnitine is an anti angiogenic agent targeting the vegfr2 and cxcr4 pathways

Abstract Carnitines play an important role in the energy exchange in cells, and are involved in the transport of fatty acids across the inner mitochondrial membrane. l -Acetylcarnitine (ALCAR) is an acetic acid ester of carnitine that has higher bioavailability and is considered a fat-burning energizer supplement. We previously found that in serum samples from prostate cancer (PCa) patients, 3 carnitine family members were significantly decreased, suggesting a potential protective role of carnitine against PCa. Several studies support beneficial effects of carnitines on cancer, no study has investigated the activities of carnitine on tumor angiogenesis. We examined whether ALCAR acts as an "angiopreventive" compound and studied the molecular mechanisms involved. We found that ALCAR was able to limit inflammatory angiogenesis by reducing stimulated endothelial cell and macrophage infiltration in vitro and in vivo. Molecularly, we show that ALCAR downregulates VEGF, VEGFR2, CXCL12, CXCR4 and FAK pathways. ALCAR blocked the activation of NF-κB and ICAM-1 and reduced the adhesion of a monocyte cell line to endothelial cells. This is the first study showing that ALCAR has anti-angiogenic and anti-inflammatory properties and might be an attractive candidate for cancer angioprevention

Human RNASET2: A Highly Pleiotropic and Evolutionary Conserved Tumor Suppressor Gene Involved in the Control of Ovarian Cancer Pathogenesis

Ovarian cancer represents one of the most malignant gynecological cancers worldwide, with an overall 5-year survival rate, being locked in the 25–30% range in the last decade. Cancer immunotherapy is currently one of the most intensively investigated and promising therapeutic strat- egy and as such, is expected to provide in the incoming years significant benefits for ovarian cancer treatment as well. Here, we provide a detailed survey on the highly pleiotropic oncosuppressive roles played by the human RNASET2 gene, whose protein product has been consistently reported to estab- lish a functional crosstalk between ovarian cancer cells and key cellular effectors of the innate immune system (the monocyte/macrophages lineage), which is in turn able to promote the recruitment to the cancer tissue of M1-polarized, antitumoral macrophages. This feature, coupled with the ability of T2 ribonucleases to negatively affect several cancer-related parameters in a cell-autonomous manner on a wide range of ovarian cancer experimental models, makes human RNASET2 a very promising candidate to develop a “multitasking” therapeutic approach for innovative future applications for ovarian cancer treatment

Production of crystallizable human chymase from a Bacillus subtilis system

AbstractA Bacillus subtilis strain deficient in seven extracellular proteases was used to produce human mast cell chymase and is a viable expression system for serine proteases and other classes of proteins. Chymase is produced at 0.3–0.5 mg/l and is purified by three chromatography steps. Two crystal forms of PMSF-treated chymase were optimized. The first is C2 with a=47.94 Å, b=85.23 Å, c=174.18 Å, β=96.74°, and diffracts to at least 2.1 Å, while the second is P212121, with cell dimensions a=43.93 Å, b=58.16 Å, and c=86.09 Å, and a diffraction limit of approximately 1.9 Å. The first crystal form has either three or four molecules/asymmetric unit, while the second has one molecule/asymmetric unit