In Situ Monitoring the Potassium‑Ion Storage Enhancement in Iron Selenide with Ether‑Based Electrolyte

As one of the promising anode materials,iron selenide has received much attention for potassium-ion batteries(KIBs).Nevertheless,volume expansion and sluggish kinetics of iron selenide result in the poor reversibility and stability during potassiation–depotassiation process.In this work,we develop iron selenide composite matching ether-based electrolyte for KIBs,which presents a reversible specific capacity of 356 mAh g^(−1) at 200 mA g^(−1) after 75 cycles.According to the measurement of mechanical properties,it is found that iron selenide composite also exhibits robust and elastic solid electrolyte interphase layer in ether-based electrolyte,contributing to the improvement in reversibility and stability for KIBs.To further investigate the electrochemical enhancement mechanism of ether-based electrolyte in KIBs,we also utilize in situ visualization technique to monitor the potassiation–depotassiation process.For comparison,iron selenide composite matching carbonate-based electrolyte presents vast morphology change during potassiation–depotassiation process.When changing to ether-based electrolyte,a few minor morphology changes can be observed.This phenomenon indicates an occurrence of homogeneous electrochemical reaction in ether-based electrolyte,which results in a stable performance for potassium-ion(K-ion)storage.We believe that our work will provide a new perspective to visually monitor the potassium-ion storage process and guide the improvement in electrode material performance.

A Notation to Support Exploring Collaboration in Design Teams

Collaboration in large projects is a major challenge for contemporary architectural practice and this paper presents a notation for describing and analyzing how these collaborations can take place.Based on an extensive literature review some opportunities were found for the development of a notation that combined three particular aspects:network diagrams,Euler diagrams and a model from architectural design.An exploratory case study was conducted based on the collaboration during a complex architectural project,which combined three approaches:document analysis,semi-structured interviews with key stakeholders and a comparison of the documents with results from the interviews.The notation demonstrated to be suitable for two purposes:to improve the understanding of particular design events and as support material for presenting and exploring collaborations.Results indicate that the notation was suitable,comprehensible and flexible,and it demonstrated good value when used in speculative ways,such as an intermediary design artifact that supports discussion and improvements in the collaboration process,which indicates promising future directions.It can also be argued that,similar to a sketch,the notation can also support the process of planning and“designing”the interaction between teams in design fields and even in other project-based organizations.

3D visualization using pulsed and CW digital holographic tomography techniques

We outline the use of digital holographic tomography to determine the three-dimensional （3D） shapes of falling and static objects, such as lenslets and water droplets. Reconstruction of digitally recorded inline holograms is performed using multiplicative and Radon transform techniques to reveal the exact 3D shapes of the objects.

Biogenic amines detection in meat and meat products:the mechanisms,applications,and future trends

Biogenic amine is one of the main categories of hazardous compounds in meat and meat products,making its detection methods vital for the assurance of edible safety.In this sense,many biogenic amine detection techniques such as chromatographic,electrophoretic,and electrochemical methods have been developed,which play an irreplaceable role in ensuring the safety of meat and meat products.Due to the increasing demand for fast and on-site detection techniques,visual detection methods have been gradually developed compared with non-visual methods such as chromatography and electrophoresis.Herein,we comprehensively review the mechanism and the latest progress of these biogenic amine detection methods;besides,we put forward the prospects for the future development of biogenic amine detection techniques,with a view to providing support for the establishment of more accurate and efficient detection,prevention and control strategies of biogenic amines.

An enhanced cosine-based visual technique for the robust tweets data clustering

Purpose-The purpose of the paper is to study multiple viewpoints which are required to access the more informative similarity features among the tweets documents,which is useful for achieving the robust tweets data clustering results.Design/methodology/approach-Let“N”be the number of tweets documents for the topics extraction.Unwanted texts,punctuations and other symbols are removed,tokenization and stemming operations are performed in the initial tweets pre-processing step.Bag-of-features are determined for the tweets;later tweets are modelled with the obtained bag-of-features during the process of topics extraction.Approximation of topics features are extracted for every tweet document.These set of topics features of N documents are treated as multi-viewpoints.The key idea of the proposed work is to use multi-viewpoints in the similarity features computation.The following figure illustrates multi-viewpoints based cosine similarity computation of the five tweets documents(here N 55)and corresponding documents are defined in projected space with five viewpoints,say,v_(1),v_(2),v_(3),v4,and v5.For example,similarity features between two documents(viewpoints v_(1),and v_(2))are computed concerning the other three multi-viewpoints(v_(3),v4,and v5),unlike a single viewpoint in traditional cosine metric.Findings-Healthcare problems with tweets data.Topic models play a crucial role in the classification of health-related tweets with finding topics(or health clusters)instead of finding term frequency and inverse document frequency(TF-IDF)for unlabelled tweets.Originality/value-Topic models play a crucial role in the classification of health-related tweets with finding topics(or health clusters)instead of finding TF-IDF for unlabelled tweets.