BiOSS® Clinical Programme – State Of The Art – BiOSS LIM® Stent – The Novel Option For Coronary Bifurcation Treatment

2015 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Jacek Bil ◽  
Robert J Gil ◽  
Dobrin Vassilev
Keyword(s):  
State Of The Art ◽  
The Novel ◽  
Coronary Bifurcation

scholarly journals Plant-Based Alternatives to Yogurt: State-of-the-Art and Perspectives of New Biotechnological Challenges

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 316
Author(s):  
Marco Montemurro ◽  
Erica Pontonio ◽  
Rossana Coda ◽  
Carlo Giuseppe Rizzello
Keyword(s):  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
State Of The Art ◽  
Protein Digestibility ◽  
The Novel ◽  
Sensory Features ◽  
Long Time ◽  
Biotechnological Processes ◽  
Nutritional Compounds ◽  
Increasing Demand

Due to the increasing demand for milk alternatives, related to both health and ethical needs, plant-based yogurt-like products have been widely explored in recent years. With the main goal to obtain snacks similar to the conventional yogurt in terms of textural and sensory properties and ability to host viable lactic acid bacteria for a long-time storage, several plant-derived ingredients (e.g., cereals, pseudocereals, legumes, and fruits) as well as technological solutions (e.g., enzymatic and thermal treatments) have been investigated. The central role of fermentation in yogurt-like production led to specific selections of lactic acid bacteria strains to be used as starters to guarantee optimal textural (e.g., through the synthesis of exo-polysaccharydes), nutritional (high protein digestibility and low content of anti-nutritional compounds), and functional (synthesis of bioactive compounds) features of the products. This review provides an overview of the novel insights on fermented yogurt-like products. The state-of-the-art on the use of unconventional ingredients, traditional and innovative biotechnological processes, and the effects of fermentation on the textural, nutritional, functional, and sensory features, and the shelf life are described. The supplementation of prebiotics and probiotics and the related health effects are also reviewed.

scholarly journals Translucent Answer Predictions in Multi-Hop Reading Comprehension

2020 ◽  
Vol 34 (05) ◽  
pp. 7700-7707
Author(s):  
G P Shrivatsa Bhargav ◽  
Michael Glass ◽  
Dinesh Garg ◽  
Shirish Shevade ◽  
Saswati Dana ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Question Answering ◽  
State Of The Art ◽  
Local Context ◽  
The Novel ◽  
Loose Coupling ◽  
Loosely Coupled ◽  
Neural Architecture ◽  
Coupled Networks ◽  
Novel Design

Research on the task of Reading Comprehension style Question Answering (RCQA) has gained momentum in recent years due to the emergence of human annotated datasets and associated leaderboards, for example CoQA, HotpotQA, SQuAD, TriviaQA, etc. While state-of-the-art has advanced considerably, there is still ample opportunity to advance it further on some important variants of the RCQA task. In this paper, we propose a novel deep neural architecture, called TAP (Translucent Answer Prediction), to identify answers and evidence (in the form of supporting facts) in an RCQA task requiring multi-hop reasoning. TAP comprises two loosely coupled networks – Local and Global Interaction eXtractor (LoGIX) and Answer Predictor (AP). LoGIX predicts supporting facts, whereas AP consumes these predicted supporting facts to predict the answer span. The novel design of LoGIX is inspired by two key design desiderata – local context and global interaction– that we identified by analyzing examples of multi-hop RCQA task. The loose coupling between LoGIX and the AP reveals the set of sentences used by the AP in predicting an answer. Therefore, answer predictions of TAP can be interpreted in a translucent manner. TAP offers state-of-the-art performance on the HotpotQA (Yang et al. 2018) dataset – an apt dataset for multi-hop RCQA task – as it occupies Rank-1 on its leaderboard (https://hotpotqa.github.io/) at the time of submission.

scholarly journals Finding the Perfect Match: Different Heavy-Duty Mobile Applications Call for Different Actuators

Proceedings ◽  
2020 ◽  
Vol 64 (1) ◽  
pp. 22
Author(s):  
David Fassbender ◽  
Tatina Minav
Keyword(s):  
Mobile Applications ◽  
State Of The Art ◽  
Perfect Match ◽  
The Novel ◽  
Hydraulic Systems ◽  
Heavy Duty ◽  
Different Types ◽  
Evaluation Algorithm ◽  
Novel Concept ◽  
Valve Control

For the longest time, valve-controlled, centralized hydraulic systems have been the state-of-the-art technology to actuate heavy-duty mobile machine (HDMM) implements. Due to the typically low energy efficiency of those systems, a high number of promising, more-efficient actuator concepts has been proposed by academia as well as industry over the last decades as potential replacements for valve control—e.g., independent metering, displacement control, different types of electro-hydraulic actuators (EHAs), electro-mechanic actuators, or hydraulic transformers. This paper takes a closer look on specific HDMM applications for these actuator concepts to figure out where which novel concept can be a better alternative to conventional actuator concepts, and where novel concepts might fail to improve. For this purpose, a novel evaluation algorithm for actuator–HDMM matches is developed based on problem aspects that can indicate an unsuitable actuator–HDMM match. To demonstrate the functionality of the match evaluation algorithm, four actuator concepts and four HDMM types are analyzed and rated in order to form 16 potential actuator–HDMM matches that can be evaluated by the novel algorithm. The four actuator concepts comprise a conventional valve-controlled concept and three different types of EHAs. The HDMM types are excavator, wheel loader, backhoe, and telehandler. Finally, the evaluation of the 16 matches results in 16 mismatch values, of which the lowest indicates the “perfect match”. Low mismatch values could be found in general for EHAs in combination with most HDMMs but also for a valve-controlled actuator concept in combination with a backhoe. Furthermore, an analysis of the concept limitations with suggestions for improvement is included.

scholarly journals Protein structure and sequence re-analysis of 2019-nCoV genome does not indicate snakes as its intermediate host or the unique similarity between its spike protein insertions and HIV-1

2020 ◽  
Author(s):  
Chengxin Zhang ◽  
Wei Zheng ◽  
Xiaoqiang Huang ◽  
Eric W. Bell ◽  
Xiaogen Zhou ◽  
...  
Keyword(s):  
State Of The Art ◽  
Careful Analysis ◽  
Spike Protein ◽  
The Novel ◽  
Intermediate Hosts ◽  
Cellular Mechanisms ◽  
Computational Approaches ◽  
Link Type ◽  
Hiv 1 ◽  
Existing Data

AbstractAs the infection of 2019-nCoV coronavirus is quickly developing into a global pneumonia epidemic, careful analysis of its transmission and cellular mechanisms is sorely needed. In this report, we re-analyzed the computational approaches and findings presented in two recent manuscripts by Ji et al. (https://doi.org/10.1002/jmv.25682) and by Pradhan et al. (https://doi.org/10.1101/2020.01.30.927871), which concluded that snakes are the intermediate hosts of 2019-nCoV and that the 2019-nCoV spike protein insertions shared a unique similarity to HIV-1. Results from our re-implementation of the analyses, built on larger-scale datasets using state-of-the-art bioinformatics methods and databases, do not support the conclusions proposed by these manuscripts. Based on our analyses and existing data of coronaviruses, we concluded that the intermediate hosts of 2019-nCoV are more likely to be mammals and birds than snakes, and that the “novel insertions” observed in the spike protein are naturally evolved from bat coronaviruses.

Efficiency Optimized Pneumatic Pressure Booster

2019 ◽  
Author(s):  
Olivier Reinertz ◽  
Katharina Schmitz
Keyword(s):  
Load Distribution ◽  
State Of The Art ◽  
Analytical Description ◽  
The Novel ◽  
One Dimensional ◽  
Pneumatic Pressure ◽  
Novel Device ◽  
Working Cycle ◽  
Promising Solution ◽  
Dimensional Simulation

Abstract In the scope of this paper, a novel efficiency optimized supply pressure adaptive concept of pneumatic pressure boosters is presented. It is deduced from a profound analysis of state of the art components. The working cycle of the pump chambers can be divided into a filling, compression, pumping and decompression phase. A promising solution for efficiency improvements, which is further analyzed in the scope of this paper, is to adapt the required force of the compression chambers by nonlinear mechanics. Thus, a smaller force at the end of the stroke is required and a reduced air consumption of the driving chamber occurs. As the force demand of the compression chamber and therewith the load distribution over the stroke changes with the operational pressures, an adaptive concept needs to be implemented. The novel device and its parameterization are deduced by means of an analytical description of state of the art pressure boosters. Subsequently, it is investigated by one-dimensional simulation in DSHplus. The results show broad applicability of the method in relevant applications and huge energy saving potentials compared to state of the art products.

scholarly journals COVID-19 automatic diagnosis with CT images using the novel Transformer architecture

2021 ◽  
Author(s):  
Gabriel Sousa Silva Costa ◽  
Anselmo C. Paiva ◽  
Geraldo Braz Júnior ◽  
Marco Melo Ferreira
Keyword(s):  
Intelligent System ◽  
State Of The Art ◽  
False Negative ◽  
False Negative Rate ◽  
Ct Images ◽  
The Novel ◽  
Chain Reaction ◽  
High False Negative Rate ◽  
Polymerase Chain ◽  
Low Sensitivity

Even though vaccines are already in use worldwide, the COVID-19 pandemic is far from over, with some countries re-establishing the lockdown state, the virus has taken over 2 million lives until today, being a serious health issue. Although real-time reverse transcription-polymerase chain reaction (RTPCR) is the first tool for COVID-19 diagnosis, its high false-negative rate and low sensitivity might delay accurate diagnosis. Therefore, fast COVID-19 diagnosis and quarantine, combined with effective vaccination plans, is crucial for the pandemic to be over as soon as possible. To that end, we propose an intelligent system to classify computed tomography (CT) of lung images between a normal, pneumonia caused by something other than the coronavirus or pneumonia caused by the coronavirus. This paper aims to evaluate a complete selfattention mechanism with a Transformer network to capture COVID-19 pattern over CT images. This approach has reached the state-of-the-art in multiple NLP problems and just recently is being applied for computer vision tasks. We combine vision transformer and performer (linear attention transformers), and also a modified vision transformer, reaching 96.00% accuracy.

scholarly journals The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks

2019 ◽  
pp. 243-290 ◽  
Author(s):  
Phuong Ha Nguyen ◽  
Durga Prasad Sahoo ◽  
Chenglu Jin ◽  
Kaleel Mahmood ◽  
Ulrich Rührmair ◽  
...  
Keyword(s):  
Machine Learning ◽  
Detailed Analysis ◽  
Open Problem ◽  
State Of The Art ◽  
Fundamental Problem ◽  
The Novel ◽  
Physical Unclonable Function ◽  
The Stability

The design of a silicon Strong Physical Unclonable Function (PUF) that is lightweight and stable, and which possesses a rigorous security argument, has been a fundamental problem in PUF research since its very beginnings in 2002. Various effective PUF modeling attacks, for example at CCS 2010 and CHES 2015, have shown that currently, no existing silicon PUF design can meet these requirements. In this paper, we introduce the novel Interpose PUF (iPUF) design, and rigorously prove its security against all known machine learning (ML) attacks, including any currently known reliability-based strategies that exploit the stability of single CRPs (we are the first to provide a detailed analysis of when the reliability based CMA-ES attack is successful and when it is not applicable). Furthermore, we provide simulations and confirm these in experiments with FPGA implementations of the iPUF, demonstrating its practicality. Our new iPUF architecture so solves the currently open problem of constructing practical, silicon Strong PUFs that are secure against state-of-the-art ML attacks.

scholarly journals DIY Interface for Enhanced Service Customization of Remote IoT Devices: A CoAP Based Prototype

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Sohail Khan ◽  
DoHyeun Kim
Keyword(s):  
General Public ◽  
Development Process ◽  
State Of The Art ◽  
Communication Link ◽  
The Novel ◽  
Xml Document ◽  
Iot Devices ◽  
Visual Interface ◽  
Programming Interface ◽  
Service Customization

DIY vision for the design of a smart and customizable world in the form of IoT demands the involvement of general public in its development process. General public lacks the technical depths for programming state-of-the-art prototyping and development kits. Latest IoT kits, for example, Intel Edison, are revolutionizing the DIY paradigm for IoT and more than ever a DIY intuitive programming interface is required to enable masses to interact with and customize the behavior of remote IoT devices on the Internet. This paper presents the novel implementation of such a system enabling general public to customize the behavior of remote IoT devices through a visual interface. The interface enables the visualization of the resources exposed by a remote CoAP device in the form of graphical virtual objects. The VOs are used to create service design through simple operations like drag-and-drop and properties settings. The design is maintained as an XML document, thus being easily distributable and recognizable. CoAP proxy acts as an operation client for the remote device and also provides communication link between the designer and the device. The paper presents the architecture, detailed design, and prototype implementation of the system using state-of-the-art technologies.

scholarly journals Unsupervised Learning of KB Queries in Task-Oriented Dialogs

2021 ◽  
Vol 9 ◽  
pp. 374-390
Author(s):  
Dinesh Raghu ◽  
Nikhil Gupta ◽  
Mausam
Keyword(s):  
Reinforcement Learning ◽  
Knowledge Base ◽  
State Of The Art ◽  
The Novel ◽  
Generate System ◽  
User Intent ◽  
Research Challenges ◽  
Policy Optimization ◽  
Task Oriented ◽  
And Training

Abstract Task-oriented dialog (TOD) systems often need to formulate knowledge base (KB) queries corresponding to the user intent and use the query results to generate system responses. Existing approaches require dialog datasets to explicitly annotate these KB queries—these annotations can be time consuming, and expensive. In response, we define the novel problems of predicting the KB query and training the dialog agent, without explicit KB query annotation. For query prediction, we propose a reinforcement learning (RL) baseline, which rewards the generation of those queries whose KB results cover the entities mentioned in subsequent dialog. Further analysis reveals that correlation among query attributes in KB can significantly confuse memory augmented policy optimization (MAPO), an existing state of the art RL agent. To address this, we improve the MAPO baseline with simple but important modifications suited to our task. To train the full TOD system for our setting, we propose a pipelined approach: it independently predicts when to make a KB query (query position predictor), then predicts a KB query at the predicted position (query predictor), and uses the results of predicted query in subsequent dialog (next response predictor). Overall, our work proposes first solutions to our novel problem, and our analysis highlights the research challenges in training TOD systems without query annotation.

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