Ru-doped 3D porous Ni3N sphere as efficient Bi-functional electrocatalysts toward urea assisted water-splitting

Developing efficient, stable and ideal urea oxide (UOR) electrocatalyst is key to produce green hydrogen in an economical way. Herein, Ru doped three dimensional (3D) porous Ni₃N spheres, with tannic acid (TA) and urea as the carbon and nitrogen resources, is synthesized via hydrothermal and low-temperature treated process (Ru–Ni₃N@NC). The porous nanostructure of Ni₃N and the nickel foam provide abundant active sites and channel during catalytic process. Moreover, Ru doping and rich defects favor to boost the reaction kinetics by optimizing the adsorption/desorption or dissociation of intermediates and reactants. The above advantages enable Ru–Ni₃N@NC to have good bifunctional catalytic performance in alkaline media. Only 43 and 270 mV overpotentials are required for hydrogen evolution (HER) and oxygen evolution (OER) reactions to drive a current of 10 mA cm^?2. Moreover, it also showed good electrocatalytic performance in neutral and alkaline seawater electrolytes for HER with 134 mV to drive 10 mA cm^?2 and 83 mV to drive 100 mA cm^?2, respectively. Remarkably, the as-designed Ru–Ni₃N@NC also owns extraordinary catalytic activity and stability toward UOR. Moreover, using the synthesized Ru–Ni₃N@NC nanomaterial as the anode and cathode of urea assisted water decomposition, a small potential of 1.41 V was required to reach 10 mA cm^?2. It can also be powered by sustainable energy sources such as wind, solar and thermal energies. In order to make better use of the earth's abundant resources, this work provides a new way to develop multi-functional green electrocatalysts.     

Synthesis and characterization of NaYF_4:Yb~(3+),Er~(3+)@silica-N=folic acid nanocomplex for bioimaginable detecting MCF-7 breast cancer cells

Upconversion nanophosphors are new promising nanomaterials to be used as biolabels for detection and imaging of cancer cells.These nanophosphors absorb long-wavelength excitation radiation in the infrared or near infrared region and emit shorter wavelength,higher energy radiation from ultraviolet to infrared.In this paper,we studied the hydrothermal method and optical properties of the functionalized NaYF_4:Yb~(3+),Er~(3+)for biomedical application.After synthesis,these NaYF_4:Yb~(3+),Er~(3+)nanophosphors were functionalized with aminosilanes and folic acid.Folic acid binds to the folate receptor on the surface of MCF-7 breast cancer cells and this binding promotes internalization of the nanophosphors via endocytosis.The sizes of the functionalized NaYF_4:Yb~(3+),Er~(3+)@silica-N=FA(folic acid) nanophosphors can be controlled with length of the rod about 300-800 nm and diameter of the rod about 100-200 nm.Phase structure of NaYF_4:Yb~(3+),Er~(3+)is in hexagonal crystal system.The photo luminescence(PL) spectra of the functionalized NaYF_4:Yb~(3+),Er~(3+)@silica-N=FA nanophosphors were measured.These nanophosphors emit in red color with the strongest band at 650 nm under 980 nm excitation.This result can provide NaYF_4:Er~(3+),Yb~(3+)@silica-N=FA complex for developing fluorescence label and image tool in cancer biology and medicine.     

Common due date assignment scheduling for a no-wait flowshop with convex resource allocation and learning effect

This article addresses the no-wait flowshop scheduling problem with simultaneous consideration of common due date assignment, convex resource allocation and learning effect in a two machine setting. The processing time of each job can be controlled by its position in a sequence and also by allocating extra resource, which is a convex function of the amount of a common continuously divisible resource allocated to the job. The objective is to determine the optimal common due date, the resource allocation and the schedule of jobs such that the total earliness, tardiness and common due date cost (the total resource consumption cost) are minimized under the constraint condition that the total resource consumption cost (the total earliness, tardiness and common due date cost) is limited. Polynomial time algorithms are developed for two versions of the problem.     

Nanocellulose-based films and their emerging applications

Extensive research has been directed towards the reinvention of paper for advanced applications. Nanocellulose-based films, a novel class of specialty paper primarily made of nanocellulose, demonstrate an ideal combination of sustainability and enhanced or novel properties. Enormous efforts have been devoted to enhancing these intrinsic properties and/or creating novel functions to expedite and expand the use of these materials in high-end fields such as touchscreen, solar cells, and nanogenerators. We review state-of-the-art advances in nanocellulose-based films and their utilization in several emerging and promising fields. We begin with an introduction of four types of nanocellulose-based films distinguished by their functional material loads (e.g., synthetic macromolecular polymers, 0D, 1D, and 2D nanomaterials), which involves their manufacturing techniques, structure design, properties, novel functions, and underlying principles. Additionally, we summarize the value-added applications of nanocellulose-based films in flexible electronics, energy converting or harvesting devices, and water treatment. Finally, we provide a critical viewpoint on the remaining challenges and future opportunities in this field.     

Determination of drivers for investing in cryptocurrencies through a fuzzy full consistency method-Bonferroni (FUCOM-F’B) framework

Cryptocurrencies have brought many innovations and discussions to economic life. Digital assets, which are very popular by investors, are frequently used for many purposes such as store of value, exchange, and speculation. It creates a research area that intentions cryptocurrency experts prioritize in crypto investments. In this paper, therefore, the fuzzy Full Consistency Method-Bonferroni (FUCOM-F’B) model is conducted to determine the priorities of drivers for investing in cryptocurrencies. The selected twenty-three drivers are classified based on five aspects, including functionality, financial, legal infrastructure, technology, and security. Based on the findings, “strong electronic encryption” and “use of digital signature” are the most significant drivers for preferring a cryptocurrency. A validation check is performed to verify the reliability, usefulness, and stability of the proposed approach. Further, the introduced approach allows taking the ambiguities and subjectivity into account which exist in the decision-making procedure. The suggested framework can be a helpful decision support tool for regulators, policymakers, practitioners, and cryptocurrency investors.     

Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology

This work intends to develop an online experimental system for screening of deoxynivalenol (DON) contamination in whole wheat meals by visible/near-infrared (Vis/NIR) spectroscopy and computer vision coupling technology. Spectral and image information of samples with various DON levels was collected at speed of 0.15 m s⁻¹ on a conveyor belt. The two-type data were then integrated and subjected to chemometric analysis. Discriminant analysis showed that samples could be classified by setting 1000 μg kg⁻¹ as the cut-off value. The best correct classified rate obtained in prediction was 93.55% based on fusion of spectral and image features, with reduced prediction uncertainty as compared to single feature. However, quantification of DON by quantitative analysis was not successful due to poor model performance. These results indicate that, although not accurate enough to provide conclusive result, this coupling technology could be adopted for rapid screening of DON contamination in cereals and feeds during processing.     

‘I am not a number’: Conceptualising identity in digital surveillance

Surveillance, now a commonplace phenomenon in everyday life, has been explored from various disciplines over three decades. Today's surveillance practices depend primarily upon many software technologies that collect, store and process personal data for the purposes of influence, management, protection or detection. The identification and categorisation of data have thus emerged as the technical signature of surveillance. An individual has many identities belonging to different contexts of his/her life, but in this paper, we explore the relationship between surveillance and identity in virtual contexts only. We argue that an understanding of identity purely as data is fundamental to understanding surveillance. We propose abstract general definitions of surveillance and identity that together create a conceptual framework, capturing key features common to many disparate surveillance situations. Our work concludes that the essence of surveillance is that of a surveillance context, which is precisely and solely defined by the availability of data about the behaviour and identity of its entities. The data that distinguishes the entities of the context we call identifiers; we explore the creation, provenance, comparison and transformation of identifiers. Abstractly, surveillance is a process that tests for properties of data, and sorts identifiers into categories.