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Piezoelectric materials are smart materials which converts mechanical energy into electric energy on the application of stress or strain and vice-versa. Automotive technology is currently the second largest market for piezoelectric products. Piezoelectric technologies are being used in actuators, fuel injectors, sensors and various safety systems in various automobile industries. Piezoelectric actuators convert electrical signal into mechanical movement which are used for adjusting mirrors, lenses and other automotive parts. Fuel injectors using piezo technology are said to be more accurate than their conventional equivalents and has provided more fuel efficiency and less emission results. Fuel atomizer, keyless door entry, seat belt buzzers air bag sensor, air flow sensor, audible alarms, knock sensors, tire pressure sensors are one of the major employers of Piezoelectric material applications. This paper focusses on exploring new frontiers where the piezoelectric materials can improve the performance of the existing products

In this work, a computational fluid dynamics (CFD) modelling has been performed to analyze pulverized coal combustion in a vertical pilot-scale furnace. The furnace with swirl burner is located at the Institute of Heat and Mass Transfer at RWTH Aachen University, where O-2/CO2 combustion environment was adopted to study pulverized coal combustion experimentally (Toporov et al., 2008). A two-dimensional axisymmetric domain has been used in this work with a Lagrangian method to track coal particles. Performances of different Reynolds-Averaged-Navier-Stokes (RANS) turbulence models have been investigated. The radiative heat transfer using discrete ordinate (DO) model coupled with variants of weighted-sum-of-grey-gases (WSGGM) methods has been examined. The results obtained by these models have been compared with the experimental data. The DO radiation model with domain based WSGGM and SST k-omega turbulence model showed a very good match with the experimental data among other tested models. The accuracy of predicted results was comparable to LES results available in the literature. It is observed that to get preliminary results the current simplified model is good enough with accuracy comparable to LES modelling. By using this validated model, the influence of combustion environments such as air, oxy-steam (O-2/H2O) and oxy-RFG (O-2/CO2) on temperature and NO concentration distribution has been investigated. NOx produced was least in the oxy-steam environment. (C) 2017 Elsevier Ltd. All rights reserved.

In this issue of Blood, Yu et al have demonstrated that acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins activate complement by engaging the alternative pathway (AP) and that blocking this process by inhibiting factor D or C5 could mitigate SARS-CoV-2–induced immunopathology.1

News has become an important part of our lives. It comes in different forms, right from morning newspaper to online pop ups while surfing on net. News presented to us in sporadic fashion. Presenting personalized news based on individual’s likings, mood and emotional preferences is need of time. News unknowingly creates desired or undesired psychological impact. Right from title, presentation and sequencing to filtering and personalization – machine learning and cognitive sciences can play a key role in news computing and processing. This paper looks into research carried out in the area of cultural and news computing in elaborate way and proposes a model for personalized sequencing and presentation of news. This personalized newspaper aims to present news of your liking and suitable to your emotional makeup so that the overall desired impact will be achieved. The personalization will take care of personal context, emotional context along with individuals likings. Further presentation of news considering emotional make-up can help in producing overall positive impact.

Customers take buying decisions on many factors. The emotional impact of the product on customer is one of the most important factors. Cognitive ergonomics tries to strike the balance between work, product and environment with human needs and capabilities. The utmost need to integrate emotions in the product cannot be denied. The idea is that product should be able to engage the customer on emotional and behavioral platform. While achieving this objective there is need to learn about customer behavior and use computational psychology while building product. This paper based on Machine Learning tries to map behavior of the customer with the products and also provide inputs for affective value for building personalized products. The affective value of the products is determined and products are mapped to customer. The algorithm suggests the most suitable product for customers while understanding emotional traits required for personalization. This work can be used to improve customer satisfaction through embedding emotions in the product. It can be used to map personal product range, personalized programs and ranking programs, products with reference to individuals.

INTRODUCTION: The role of noninvasive positive pressure ventilation (NIPPV) in patients with stable chronic obstructive pulmonary disease (COPD) in the home-setting remains controversial. Despite studies suggesting potential benefits, there is an apparent under-utilization of such therapy in patients with stable COPD in a domiciliary setting. AREAS COVERED: The reasons for under-utilization in the home-setting are multi-factorial, and we provide our perspective on the adequacy of scientific evidence and implementation barriers that may underlie the observed under-utilization. In this article, we will discuss continuous PAP, bilevel PAP, and non-invasive positive pressure ventilation using a home ventilator (NIPPV). EXPERT COMMENTARY: Many patients with stable COPD and chronic respiratory failure do not receive NIPPV therapy at home despite supportive scientific evidence. Such under-utilization suggests that there are barriers to implementation that include provider knowledge, health services and payor policies. For patients with stable COPD without chronic respiratory failure, there is inadequate scientific evidence to support domiciliary NIPPV or CPAP therapy. In patients with stable COPD without chronic respiratory failure, studies aimed at identifying patient characteristics that determine effectiveness of domiciliary NIPPV therapy needs further study. Future implementation and health-policy research with appropriate stakeholders are direly needed to help improve patient outcomes.

When a right person is working on a right task with appropriate context, he/she can do wonders. It has always been a challenge to select the most suitable person for a given task. When we are talking about suitability, apart from skills, cultural and behavioral suitability is required to be considered. This paper tries to identify cultural and behavioral properties of individuals along with skills to assess suitability of person for the mission. Paper proposes a new technique using multilevel context based machine learning using expressions and interactions. Suitability of a person for a given task determines how that person contributes to given task and its objectives. The available candidates can be ranked against the task at hand on the basis of suitability index (SI). Learning based on properties of the task as well as behavioral traits of candidates is used here. The algorithm is tested with responses collected for over one thousand candidates with reference to expert opinions and rankings. We have run experiments to compare proposed methods with skill based classification methods.

Selection of team for match, mission or project is always challenging since every mission is different and every match brings new uncertainties. Your best resource may not be the right choice for the given task. It is the context of task, behaviours of individuals and above all constitution of the team in that scenario contribute to the outcome. The context vector convergence (CVC) of behavioural vectors helps in deriving the actual effect of two vectors in overall team performance. The personality vector is used to derive behavioural context while mission vector is used to derive the scenario context. These two vectors are graphically associated in convergence to identify and recommend the best team combinations. While formulating the vector, cultural aspects and behaviours are captured through expressions and interactions. Top three combinations are compared to validate hypotheses. The promising results reinforce the premise to establish further research directions.

Object recognition technology has matured to a point at which exciting applications have become possible. Indeed, industry has created a variety of computer vision products and services from the traditional area of machine inspection to more recent applications such as object detection, video surveillance, or face recognition. This paper is about achieving the goal of object recognition through advanced techniques like deep learning on handy devices like smartphones and tablets. Deep learning algorithms (Convolutional Neural Networks (CNN)) are used for the primary aim of object recognition. Images are clicked through the camera of the smartphone during experimentation and are fed to the CNN network. The top four results predicted by the network are depicted on the smartphone screen in the audio and the visual form i.e. predicted object name and the probability of predicted object being the one actually clicked in the decreasing order of probabilities. The accuracy obtained in object recognition is about 93% through the application.

In many real life situations end results and basic starting data are known. To deduce conclusive evidence or to build holistic picture one needs to find out hidden information and missing text. This research paper delivers a novel algorithm (Probabilistic Intent-Action Ontology and Tone Matching Algorithm) to map multiple events on time line by determining their interdependency to predict the most probable series of events that might have occurred. Various aspects of flow of events, continuity, negation, shift of emotions etc. are considered. This algorithm is based on analyzing multidimensional intent and action relationships, application of naive Bayes theorem to text, plotting relative hyperbolic probability and plotting the tone matching graph and calculating deviations. The proposed method shows very promising results. This approach can be used to solve many real life problems like solving criminal cases, completing stories, and identifying gaps in data.

Randomized controlled trials involving natriuretic peptide administration in solid organ transplantation setting have shown inconsistent effects for renal endpoints. We conducted a systematic review and meta-analysis of these trials to ascertain the role of natriuretic peptides in the management of solid organ transplantation associated acute kidney injury (AKI). MEDLINE, EMBASE, and Google scholar were searched independently by two authors for randomized trials evaluating renal effects of natriuretic peptides in solid organ transplantation settings. Two reviewers independently assessed the studies for eligibility and extracted the relevant data. The pooled estimate showed that natriuretic peptide administration is associated with a reduction in AKI requiring dialysis (odds ratio = 0.50 [0.26–0.97]), a statistically nonsignificant trend toward improvement in posttransplant creatinine clearance (weighted mean difference = 5.5 mL/min, [−1.3 to 12.2 mL/min]), and reduction in renal replacement requirement duration (weighted mean difference −44.0 hours, [−60.5 to −27.5 hours]). There were no mortality events and no adverse events related to natriuretic peptides. In conclusion, administration of natriuretic peptides in solid organ transplantation may be associated with significant improvements in renal outcomes. These observations need to be confirmed in an adequately powered, prospective multicenter study.

An increasing research interest has been directed toward nanoparticle-based drug delivery systems for their advantages. The appropriate amalgamation of pH sensitivity and tumor targeting is a promising strategy to fabricate drug delivery systems with high efficiency, high selectivity and low toxicity.A novel pH sensitive Cremophor-free paclitaxel formulation, Nanoxel(TM), was developed in which the drug is delivered as nanomicelles using a polymeric carrier that specifically targets tumors. The efficiency and mechanism of intracellular paclitaxel delivery by Nanoxel(TM) was compared with two other commercially available paclitaxel formulations: Abraxane(TM) and Intaxel(TM), using different cell lines representing target cancers [breast, ovary and non-small cell lung carcinoma (NSCLC)] by transmission electron microscopy and quantitative intracellular paclitaxel measurements by high performance liquid chromatography.The data obtained from the present study revealed that the uptake of nanoparticle-based formulations Nanoxel(TM) and Abraxane(TM) is mediated by the process of endocytosis and the uptake of paclitaxel was remarkably superior to Intaxel(TM) in all cell lines tested. Moreover, the intracellular uptake of paclitaxel in Nanoxel(TM)- and Abraxane(TM)-treated groups was comparable. Hence, the nanoparticle-based formulations of paclitaxel (Nanoxel(TM) and Abraxane(TM)) are endowed with higher efficiency to deliver the drug to target cells as compared to the conventional Cremophor-based formulation.Nanoxel(TM) appears to be of great promise in tumor targeting and may provide an advantage for paclitaxel delivery into cancer cells.

This preliminary study was designed to explore a new method for nutritional assessment by measuring oral mucosal cell apoptosis or proliferation.Forty-two consecutive patients with gastrointestinal malignant tumors were hospitalized on the surgical wards and studied prospectively. Patient-Generated Subjective Global Assessment was used to identify malnourished patients. Anthropometric measurements including weight, body mass index, triceps skinfold thickness, and midarm muscle circumference were recorded. The serum proteins measured were retinol-binding protein (RBP), transferrin, prealbumin (PA), and albumin. Simultaneously, the rates of oral epithelial cell apoptosis and proliferation were measured by flow cytometry. Of the 20 malnourished patients, 14 were followed up in a serial study with a 3-d nutritional support therapy. Nutritional indices and oral epithelial cell apoptosis rate were measured after 3 d of nutritional support.Malnutrition was diagnosed in 20 of 42 patients (47.6%). Oral epithelial apoptosis and proliferation rates were significantly decreased (P0.01 and P0.05, respectively) in malnourished compared with non-malnourished patients, although there were no significant differences between their anthropometric data. Malnourished patients had lower serum levels of RBP, albumin, and PA and rates of oral epithelial cell apoptosis and proliferation. The rate of oral epithelial cell apoptosis positively correlated with serum RBP (R = 0.32, P0.05) and PA (R = 0.33, P0.05). The rate of oral epithelial cell apoptosis and serum RBP and PA increased significantly in the malnourished patients who received nutritional support for 3 days.Measuring the rate of oral epithelial cell apoptosis may be another non-invasive technique to determine nutritional assessment and is worthy of further exploration.

e17505 Background: Generic substitution may lead to increased access to cancer drugs. Little data have been published on cost savings in emerging markets. Methods: Estimate of cost and savings per cycle, per patient, and for India with generic drugs. Cost of paclitaxel, docetaxel, gemcitabine, irinotecan and oxaliplatin was obtained for originator branded and generic versions from a distributor in India. Costs are depicted in 2012 Rupees. Utilization was based on a BSA of 1.7, standard doses, expected lenght of treatment for common oncology indications and incidence data from GLOBOCAN. Results: Generic drugs cost from 8.9% to 36% of their equivalent branded originator drug, resulting in cost-savings of approximately INR 11,000 to 90,000 [US$ 200-1,600] per each drug per cycle; and approximately INR 50,000 to 240,000 [US$ 900-4,300] per patient treated. Overall, potential yearly savings for health systems in India were nearly INR 47 billion [US$ 843 million]. Conclusions: Generic substitution for commonly used chemotherapy agents has an enormous potential to generate significant cost-savings and increase access to cancer treatments in India and other low and middle income countries. [Table: see text]