scholarly journals New Trends in Biopolymer-Based Membranes for Pervaporation

Molecules ◽  
2019 ◽  
Vol 24 (19) ◽  
pp. 3584 ◽  
Author(s):  
Roberto Castro-Muñoz ◽  
José González-Valdez

Biopolymers are currently the most convenient alternative for replacing chemically synthetized polymers in membrane preparation. To date, several biopolymers have been proposed for such purpose, including the ones derived from animal (e.g., polybutylene succinate, polylactic acid, polyhydroxyalcanoates), vegetable sources (e.g., starch, cellulose-based polymers, alginate, polyisoprene), bacterial fermentation products (e.g., collagen, chitin, chitosan) and specific production processes (e.g., sericin). Particularly, these biopolymer-based membranes have been implemented into pervaporation (PV) technology, which assists in the selective separation of azeotropic water-organic, organic-water, organic-organic mixtures, and specific separations of chemical reactions. Thereby, the aim of the present review is to present the current state-of-the-art regarding the different concepts on preparing membranes for PV. Particular attention is paid to the most relevant insights in the field, highlighting the followed strategies by authors for such successful approaches. Finally, by reviewing the ongoing development works, the concluding remarks and future trends are addressed.

Author(s):  
Sohel Anwar

An overview of the drive by wire technology is presented along with in-depth coverage of salient drive by systems such as throttle-by-wire, brake-by-wire, and steer-by-wire systems, and hybrid-electric propulsion. A review of drive by wire system benefits in performance enhancements and vehicle active safety is then discussed. This is followed by in-depth coverage of technological challenges that must be overcome before drive-by-wire systems can be production ready. Current state of the art of possible solutions to these technological hurdles is then discussed. Future trends in the drive-by-wire systems and economic and commercialization aspects of these system are presented at the conclusion of the chapter.


2018 ◽  
Vol 6 (7) ◽  
pp. 1664-1690 ◽  
Author(s):  
Mahboubeh Jafarkhani ◽  
Zeinab Salehi ◽  
Reza Kowsari-Esfahan ◽  
Mohammad Ali Shokrgozar ◽  
M. Rezaa Mohammadi ◽  
...  

This review presents the current state-of-the-art, emerging directions and future trends to direct cells for building functional heart parts.


2018 ◽  
Vol Volume 13 ◽  
pp. 3145-3161 ◽  
Author(s):  
Muhammad Farhan Sohail ◽  
Mubashar Rehman ◽  
Hafiz Shoaib Sarwar ◽  
Sara Naveed ◽  
Omer Salman Qureshi ◽  
...  

1984 ◽  
Vol 1 (2) ◽  
pp. 18-27 ◽  
Author(s):  
F. Hayes-Roth

SummaryThis paper aims to describe the current state of knowledge systems technology and its commercialisation in the US. First, knowledge systems are defined and placed in a historical context. The introduction is concluded with a preview of major ideas. The paper will assess the technological state of the art and will survey the current state of commercialisation. Finally, some anticipated future trends will be discussed.


2021 ◽  
Author(s):  
Cheka Kehelpannala ◽  
Thusitha Rupasinghe ◽  
Thomas Hennessy ◽  
David Bradley ◽  
Berit Ebert ◽  
...  

In this review, we provide a critical appraisal of the key developments, current state and future trends in liquid-chromatography–mass spectrometry-based workflows for plant lipid analysis.


Author(s):  
Cyril Laurier ◽  
Perfecto Herrera

Creating emotionally sensitive machines will significantly enhance the interaction between humans and machines. In this chapter we focus on enabling this ability for music. Music is extremely powerful to induce emotions. If machines can somehow apprehend emotions in music, it gives them a relevant competence to communicate with humans. In this chapter we review the theories of music and emotions. We detail different representations of musical emotions from the literature, together with related musical features. Then, we focus on techniques to detect the emotion in music from audio content. As a proof of concept, we detail a machine learning method to build such a system. We also review the current state of the art results, provide evaluations and give some insights into the possible applications and future trends of these techniques.


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