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This paper aims to prepare third-order nonlinear optical (NLO) organic materials with large nonlinear optimization value, high damage threshold and ultrafast response time.

A series of novel symmetric and asymmetric compounds possessing third-order NLO properties were synthesized using 1,3,5-tribromobenzene as the basis. The photophysical and electrochemical properties, as well as the click reactions, were characterized by means of UV–VIS–NIR absorption spectroscopy and cyclic voltammetry.

The donor–acceptor chromophores were inserted into compound, making the molecule to have a broader absorption in the near-infrared regions and a narrower optical and electrochemical band gap. It also formed an electron-delocalized organic system, which has larger effects on achieving a third-order NLO response. The third-order NLO phenomenon of benzene ring complexes was experimentally studied at 532 nm using Z-scan technology, and some compounds showed the expected NLO properties.

The click products exhibit more NLO phenomena by performing different click combinations to the side groups, opening new perspectives on using the system in a variety of photoelectric applications.

This paper aims to report the friction and wear characteristics of refined soybean oil (RSBO) blended with copper oxide (CuO) nanoparticles and zinc dialkyldithiophosphate (ZDDP) as additives.

Four different concentrations 0.04, 0.05, 0.1 and 0.2 Wt.% of CuO nanoparticles were added with ZDDP in RSBO. The friction and wear characteristics of lubricants have been investigated on a pin-on-disc tribotester under loads of 120 and 180 N, with rotating speeds of 1,200 and 1,500 rpm in half hour of operating time. The dispersion stability of CuO nanoparticles has been analyzed using ultraviolet visible (UV-Vis) spectroscopy. The wearout surface of pins has been examined by using a scanning electron microscope.

The results revealed that there is a reduction in the friction and wear by the addition of CuO nanoparticles and ZDDP in RSBO. Coefficient of friction increases at a high sliding speed for RSBO with ZDDP. From UV-Vis spectroscopy, it is observed that 100 ml of oleic acid surfactant per gram of CuO nanoparticles has stable dispersion in RSBO.

The addition of ZDDP and CuO nanoparticles in RSBO is more efficient to reduce the friction and wear in comparison to base oil. The optimum concentration of CuO nanoparticles in RSBO is 0.05 Wt.%.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

Examines the seventeenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Examines the sixteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The purpose of this study is the synthesis and characterization of a CMYK palette (cyan of Cr-BiVO₄, magenta of Pr-CeO₂, yellow of Bi-(Ce,Zr)O₂ composite and black of YMnO₃) as an eco-friendly polyfunctional palette that combines (a) high near-infrared reflectance (cool pigments) that allows moderate temperatures in indoor environments and the urban heat island effect; (b) photocatalytic activity for the degradation of organic contaminants of emerging concern of substrates in solution (such as Orange II or methylene blue) and gaseous (NO_x and volatile organic compounds such as acetaldehyde or toluene); (c) X-ray radiation attenuators associated with bismuth ions; and (d) biocidal effect combined with co-doping with bactericidal agents.

Pigments were prepared by a solid-state reaction and characterized by X-ray diffraction, diffuse reflectance spectroscopy, photocatalytic activity over Orange II and scanning electron microscopy.

The behaviour of the proposed palette was compared to that of a commercial inkjet palette, and an improvement in all functionalities was observed.

The functionalities of pigments allow the building envelope and indoor walls to exhibit temperature-moderating effects (with the additional effects of moderating global warming and increasing air conditioning efficiency), purification and disinfection of both indoor and outdoor air, and radiation attenuation.

The proposed palette and its polyfunctional characterization are novel.

Piperidine side chain-functionalized N, N′-bissalicylidene phenylene di amine di-anion (salphen) consisting of salphen-Zn and salphen-Cu are able to intercalate with nucleic base stacking of DNA and can be applied as an optical DNA hybridization detector. Attaching DNA and salphen to glass surfaces has been done via coating the surface with the silane coupling agents containing 3-aminopropyltriethoxysilane that was synthesized for acting as a high-affinity RNA carrier matrix. The Schiff base salphen-zinc (II) and salphen-Cu (II) complexes-labelled probe to target nucleic acid renders a colour change of the DNA biosensor to a green and red background colour for zinc and copper, respectively. This study aims to indicate that the DNA biosensor data with high efficiency is used for detection of dengue virus serotypes 2 (DENV-2) and Chikungunya virus (CHIKV) concentration via salphen-Zn (II) and salphen-Cu (II), respectively, in human samples.

¹H-NMR and ¹³C-NMR have been used via PerkinElmer LAMBDA 35 instrument. The authors also used a double beam spectrophotometer with (CH₃)4Si (TMS) as reference and dimethyl sulfoxide as solvent reference in pH = 7.0. Various DNA concentrations have been used for UV spectrophotometry at 300 nm and 400 nm for zinc and copper complexes, respectively. BRUKER mass spectra with DIONEX Ultimate 3000 LC model were used for all measurements. Mettler Teledo model (DSC882e) of differential scanning calorimeter (DSC) was used for measure the melting temperature of metal zinc and copper complexes. The morphology of the silica Nano spheres (SiNs) were scanned by FESEM with Model JSM-6700F from Japan.

The Cu (II) and Zn (II)-salphen-viruses DNA system for CHIKV and DENV-2, respectively, in different concentration have been investigated via various spectroscopies (Figure 3). CHIKV and DENV-2 DNA were selected from human saliva and urine samples as models for conformations of human G4-DNA. By increasing the amounts of DNAs, and G4, the UV–Vis bands of located above 300 nm, experienced a hypochromic effect. The Cu2+ complex exhibits selectivity towards the G4, and there is a similar affinity for Zn²⁺ complex binds to the G4. These results collectively suggest that the Cu²⁺ complex is stronger than the Zn2+ complex. The authors have found copper (II) and zinc (II) compounds and nucleic acid-complexes are strongly fluorescent molecules in the low energy range, from the visible to the near-infrared. Since the fluorescent emission of Zn (II) and Cu (II) complexes are enhanced by the binding to nucleic acids upon visible light exposure when bound to DNA. These complexes are important as selective fluorescent probes for nucleic acids and to highlight their potential application. UV–vis spectroscopy is an accurate for finding the extent of ligand interaction with DNA and metallic complexes–DNA binding. Generally, the binding of intercalative compounds to DNA can be characterized through absorption spectral titrations, where lowering in absorbance (hypochromism) and shift to longer wavelengths (red shift) were observed in this work.

The serum samples have been provided as citrate and collected in tubes after blood is allowed to clot. Then, it has been separated by centrifugation, and the authors have kept serum refrigerated at 4°C or frozen at –20°C. It is notable; specimens have been confirmed by Centres for Disease Control (CDC)-Dengue Branch previously. For the work, these samples have been frozen previously, and the diagnostic practiced tests at the CDC-Dengue Branch have been validated in serum and plasma. Therefore, plasma separated in lavender or heparins are suitable and acceptable for serology testing.