scholarly journals A Review of Zein as a Potential Biopolymer for Tissue Engineering and Nanotechnological Applications

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1376
Author(s):  
Carlos Joaquín Pérez-Guzmán ◽  
Roberto Castro-Muñoz
Keyword(s):  
Tissue Engineering ◽  
Review Paper ◽  
State Of The Art ◽  
Research Community ◽  
Anatomical Structure ◽  
Natural Origin ◽  
Current State ◽  
Current Alternative ◽  
The Right ◽  
Selection Of

Tissue engineering (TE) is one of the most challenging fields of research since it provides current alternative protocols and materials for the regeneration of damaged tissue. The success of TE has been mainly related to the right selection of nano-sized biocompatible materials for the development of matrixes, which can display excellent anatomical structure, functionality, mechanical properties, and histocompatibility. Today, the research community has paid particular attention to zein as a potential biomaterial for TE applications and nanotechnological approaches. Considering the properties of zein and the advances in the field, there is a need to reviewing the current state of the art of using this natural origin material for TE and nanotechnological applications. Therefore, the goal of this review paper is to elucidate the latest (over the last five years) applications and development works in the field, including TE, encapsulations of drugs, food, pesticides and bandaging for external wounds. In particular, attention has been focused on studies proving new breakthroughs and findings. Also, a complete background of zein’s properties and features are addressed.

scholarly journals Soft Threshold Ternary Networks

2020 ◽  
Author(s):  
Weixiang Xu ◽  
Xiangyu He ◽  
Tianli Zhao ◽  
Qinghao Hu ◽  
Peisong Wang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Mobile Devices ◽  
State Of The Art ◽  
Performance Gap ◽  
Training Time ◽  
Current State ◽  
The Arts ◽  
Soft Threshold ◽  
And Storage ◽  
Selection Of

Large neural networks are difficult to deploy on mobile devices because of intensive computation and storage. To alleviate it, we study ternarization, a balance between efficiency and accuracy that quantizes both weights and activations into ternary values. In previous ternarized neural networks, a hard threshold Δ is introduced to determine quantization intervals. Although the selection of Δ greatly affects the training results, previous works estimate Δ via an approximation or treat it as a hyper-parameter, which is suboptimal. In this paper, we present the Soft Threshold Ternary Networks (STTN), which enables the model to automatically determine quantization intervals instead of depending on a hard threshold. Concretely, we replace the original ternary kernel with the addition of two binary kernels at training time, where ternary values are determined by the combination of two corresponding binary values. At inference time, we add up the two binary kernels to obtain a single ternary kernel. Our method dramatically outperforms current state-of-the-arts, lowering the performance gap between full-precision networks and extreme low bit networks. Experiments on ImageNet with AlexNet (Top-1 55.6%), ResNet-18 (Top-1 66.2%) achieves new state-of-the-art.

scholarly journals Hydrothermal Carbonization of Organic Waste and Biomass: A Review on Process, Reactor, and Plant Modeling

2020 ◽  
Author(s):  
Giulia Ischia ◽  
Luca Fiori
Keyword(s):  
Organic Waste ◽  
Review Paper ◽  
Recent Literature ◽  
State Of The Art ◽  
Hydrothermal Carbonization ◽  
Residual Biomass ◽  
Current State ◽  
Potential Applications ◽  
Intrinsic Complexity ◽  
Context Models

Abstract Hydrothermal carbonization (HTC) is an emerging path to give a new life to organic waste and residual biomass. Fulfilling the principles of the circular economy, through HTC “unpleasant” organics can be transformed into useful materials and possibly energy carriers. The potential applications of HTC are tremendous and the recent literature is full of investigations. In this context, models capable to predict, simulate and optimize the HTC process, reactors, and plants are engineering tools that can significantly shift HTC research towards innovation by boosting the development of novel enterprises based on HTC technology. This review paper addresses such key-issue: where do we stand regarding the development of these tools? The literature presents many and simplified models to describe the reaction kinetics, some dealing with the process simulation, while few focused on the heart of an HTC system, the reactor. Statistical investigations and some life cycle assessment analyses also appear in the current state of the art. This work examines and analyzes these predicting tools, highlighting their potentialities and limits. Overall, the current models suffer from many aspects, from the lack of data to the intrinsic complexity of HTC reactions and HTC systems. Therefore, the emphasis is given to what is still necessary to make the HTC process duly simulated and therefore implementable on an industrial scale with sufficient predictive margins. Graphic Abstract

Current State of the Art in Myocardial Tissue Engineering

2007 ◽  
Vol 0 (0) ◽  
pp. 070126052142001
Author(s):  
Marie-Noëlle Giraud ◽  
Christime Armbuster ◽  
Thierry Carrel ◽  
Hendrik T. Tevaearai
Keyword(s):  
Tissue Engineering ◽  
State Of The Art ◽  
Myocardial Tissue ◽  
Current State ◽  
Myocardial Tissue Engineering

scholarly journals Review of Tailoring Methods for Joints with Additively Manufactured Adherends and Adhesives

Materials ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 3949
Author(s):  
Mattia Frascio ◽  
Eduardo André de Sousa Marques ◽  
Ricardo João Camilo Carbas ◽  
Lucas Filipe Martins da Silva ◽  
Margherita Monti ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Review Paper ◽  
State Of The Art ◽  
Manufacturing Processes ◽  
Bonded Joints ◽  
Design For Additive Manufacturing ◽  
Polymeric Additive ◽  
Current State ◽  
Bonded Joint ◽  
Current Modelling

This review aims to assess the current modelling and experimental achievements in the design for additive manufacturing of bonded joints, providing a summary of the current state of the art. To limit its scope, the document is focused only on polymeric additive manufacturing processes. As a result, this review paper contains a structured collection of the tailoring methods adopted for additively manufactured adherends and adhesives with the aim of maximizing bonded joint performance. The intent is, setting the state of the art, to produce an overview useful to identify the new opportunities provided by recent progresses in the design for additive manufacturing, additive manufacturing processes and materials’ developments.

Current State of the Art in Myocardial Tissue Engineering

2007 ◽  
Vol 13 (8) ◽  
pp. 1825-1836 ◽  
Author(s):  
Marie-Noëlle Giraud ◽  
Christine Armbruster ◽  
Thierry Carrel ◽  
Hendrik T. Tevaearai
Keyword(s):  
Tissue Engineering ◽  
State Of The Art ◽  
Myocardial Tissue ◽  
Current State ◽  
Myocardial Tissue Engineering

scholarly journals OPWUM: Opportunistic MAC Protocol Leveraging Wake-Up Receivers in WSNs

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Fayçal Ait Aoudia ◽  
Matthieu Gautier ◽  
Olivier Berder
Keyword(s):  
Power Consumption ◽  
Analytical Study ◽  
State Of The Art ◽  
Mac Protocol ◽  
Promising Technique ◽  
Improve Energy Efficiency ◽  
Current State ◽  
Unreliable Links ◽  
Careful Design ◽  
Selection Of

Opportunistic forwarding has emerged as a promising technique to address the problem of unreliable links typical in wireless sensor networks and improve energy efficiency by exploiting multiuser diversity. Timer-based solutions, such as timer-based contention, form promising schemes to allow opportunistic next hop relay selection. However, they can incur significant idle listening and thus reduce the lifetime of the network. To tackle this problem, we propose to exploit emerging wake-up receiver technologies that have the potential to considerably reduce the power consumption of wireless communications. A careful design of MAC protocols is required to efficiently employ these new devices. In this work, we propose Opportunistic Wake-Up MAC (OPWUM), a novel multihop MAC protocol using timer-based contention. It enables the opportunistic selection of the best receiver among its neighboring nodes according to a given metric (e.g., the remaining energy), without requiring any knowledge about them. Moreover, OPWUM exploits emerging wake-up receivers to drastically reduce nodes power consumption. Through analytical study and exhaustive networks simulations, we show the effectiveness of OPWUM compared to the current state-of-the-art protocols using timer-based contention.

scholarly journals How to Model Tendon-Driven Continuum Robots and Benchmark Modelling Performance

2021 ◽  
Vol 7 ◽  
Author(s):  
Priyanka Rao ◽  
Quentin Peyron ◽  
Sven Lilge ◽  
Jessica Burgner-Kahrs
Keyword(s):  
Case Studies ◽  
State Of The Art ◽  
Computation Time ◽  
Comprehensive Overview ◽  
Continuum Robots ◽  
Current State ◽  
Selection Of ◽  
Modelling Approaches

Tendon actuation is one of the most prominent actuation principles for continuum robots. To date, a wide variety of modelling approaches has been derived to describe the deformations of tendon-driven continuum robots. Motivated by the need for a comprehensive overview of existing methodologies, this work summarizes and outlines state-of-the-art modelling approaches. In particular, the most relevant models are classified based on backbone representations and kinematic as well as static assumptions. Numerical case studies are conducted to compare the performance of representative modelling approaches from the current state-of-the-art, considering varying robot parameters and scenarios. The approaches show different performances in terms of accuracy and computation time. Guidelines for the selection of the most suitable approach for given designs of tendon-driven continuum robots and applications are deduced from these results.

scholarly journals Joint epitope selection and spacer design for string-of-beads vaccines

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i643-i650
Author(s):  
Emilio Dorigatti ◽  
Benjamin Schubert
Keyword(s):  
Antigen Processing ◽  
State Of The Art ◽  
Supplementary Information ◽  
Current State ◽  
Fixed Set ◽  
Epitope Selection ◽  
High Chance ◽  
Selection Of ◽  
Design Steps

Abstract Motivation Conceptually, epitope-based vaccine design poses two distinct problems: (i) selecting the best epitopes to elicit the strongest possible immune response and (ii) arranging and linking them through short spacer sequences to string-of-beads vaccines, so that their recovery likelihood during antigen processing is maximized. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing, thus resulting in vaccines with less effective immunogenicity in vivo. Results In this work, we present a computational approach based on linear programming, called JessEV, that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte Carlo cleavage simulations to show that a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen and population coverage of the resulting vaccines by at least 2-fold. Availability and implementation The software and the data analyzed are available at https://github.com/SchubertLab/JessEV. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Joint epitope selection and spacer design for string-of-beads vaccines

2020 ◽  
Author(s):  
Emilio Dorigatti ◽  
Benjamin Schubert
Keyword(s):  
Antigen Processing ◽  
State Of The Art ◽  
Computational Approach ◽  
Population Coverage ◽  
Current State ◽  
Fixed Set ◽  
Epitope Selection ◽  
High Chance ◽  
Selection Of ◽  
Design Steps

AbstractMotivationConceptually, epitope-based vaccine design poses two distinct problems: (1) selecting the best epitopes eliciting the strongest possible immune response, and (2) arranging and linking the selected epitopes through short spacer sequences to string-of-beads vaccines so as to increase the recovery likelihood of each epitope during antigen processing. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing and resulting in vaccines with less effective immunogencity.ResultsIn this work, we present a computational approach based on linear programming that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte-Carlo cleavage simulations to show that, indeed, a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen, and population coverage of the resulting vaccines by at least two fold.AvailabilityThe software and the data analyzed are available at https://github.com/SchubertLab/JessEV

Sign in / Sign up

Export Citation Format

Share Document