Microwave and pulsed electric field assisted extractions of polyphenols from defatted canola seed cake

The incorporation of microwave and pulsed electric field (PEF) technologies in optimising the extraction of polyphenols from defatted canola seed cake was determined by Box‐Behnken response surface methodology, using three parameters of microwave treatment (power, time and liquid: solid (L:S) ratio) and four parameters of PEF (ethanol concentration, time, frequency and voltage). After microwave and PEF pretreatments, the polyphenols of defatted canola seed cake were extracted by ultrasound treatment under fixed variables (200 W of ultrasonic power, 70 °C of water bath and 20 min of extraction time). The measured responses were total phenolics, total flavonoids, the DPPH˙ scavenging activity and ferric reducing antioxidant power (FRAP). The maximum yields of all responses were achieved under optimum conditions of microwave processing (5 min, L:S ratio of 6.0 and 633.3 W) and PEF‐assisted extraction (30 V, 30 Hz, 10% ethanol concentration and 10 s).     

Phosphoproteomics by mass spectrometry and classical protein chemistry approaches

The general fields of biological sciences have seen phenomenal transformations in the past two decades at the level of data acquisition, understanding biological processes, and technological developments. Those advances have been made partly because of the advent of molecular biology techniques (which led to genomics) coupled to the advances made in mass spectrometry (MS) to provide the current capabilities and developments in proteomics. However, our current knowledge that approximately 30,000 human genes may code for up to 1 million or more proteins disengage the interface between the genome sequence database algorithms and MS to generate a major interest in independent de novo MS/MS sequence determination. Significant progress has been made in this area through procedures to covalently modify peptide N- and C-terminal amino-acids by sulfonation and guanidination to permit rapid de novo sequence determination by MS/MS analysis. A number of strategies that have been developed to perform qualitative and quantitative proteomics range from 2D-gel electrophoresis, affinity tag reagents, and stable-isotope labeling. Those procedures, combined with MS/MS peptide sequence analysis at the subpicomole level, permit the rapid and effective identification and quantification of a large number of proteins within a given biological sample. The identification of proteins per se, however, is not always sufficient to interpret biological function because many of the naturally occurring proteins are post-translationally modified. One such modification is protein phosphorylation, which regulates a large array of cellular biochemical pathways of the biological system. Traditionally, the study of phosphoprotein structure-function relationships involved classical protein chemistry approaches that required protein purification, peptide mapping, and the identification of the phosphorylated peptide regions and sites by N-terminal sequence analysis. Recent advances made in mass spectrometry have clearly revolutionized the studies of phosphoprotein biochemistry, and include the development of specific strategies to preferentially enrich phosphoproteins by covalent-modifications that incorporate affinity tags that use the physicochemical properties of phosphoaminoacids. The phosphoserine/phosphothreonine-containing proteins/peptides are derivatized under base-catalyzed conditions by thiol agents; mono- and di-thiol reagents both have been used in such studies. The thiol agent may have: (i) an affinity tag for protein enrichment; (ii) stable-isotopic variants for relative quantitation; or (iii) a combination of the moieties in (i) and (ii). These strategies and techniques, together with others, are reviewed, including their practical application to the study of phosphoprotein biochemistry and structure-function. The consensus of how classical protein chemistry and current MS technology overlap into special case of proteomics, namely "phosphoproteomics," will be discussed.     

Prediction of postpartum depression using machine learning techniques from social media text

Early screening of mental disorders plays a crucial role in diagnosis and treatment. This study explores how data‐driven methods can leverage the information available on social media platforms to predict postpartum depression (PPD). A generalized approach is proposed where linguistic features are extracted from user‐generated textual posts on social media and categorized as general, depressive, and PPD representative using multiple machine learning techniques. We find that techniques used in our study exhibit strong predictive capabilities for PPD content. Holdout validation showed that multilayer perceptron outperformed other techniques such as support vector machine and logistic regression used in this study with 91.7% accuracy for depressive content identification and up to 86.9% accuracy for PPD content prediction. This work adopts a hierarchical approach to predict PPD. Therefore, the reported PPD accuracy represents the performance of the model to correctly classify PPD content from non‐PPD depressive content.     

Deep‐Ultraviolet Hyperbolic Metacavity Laser

Given the high demand for miniaturized optoelectronic circuits, plasmonic devices with the capability of generating coherent radiation at deep subwavelength scales have attracted great interest for diverse applications such as nanoantennas, single photon sources, and nanosensors. However, the design of such lasing devices remains a challenging issue because of the long structure requirements for producing strong radiation feedback. Here, a plasmonic laser made by using a nanoscale hyperbolic metamaterial cube, called hyperbolic metacavity, on a multiple quantum‐well (MQW), deep‐ultraviolet emitter is presented. The specifically designed metacavity merges plasmon resonant modes within the cube and provides a unique resonant radiation feedback to the MQW. This unique plasmon field allows the dipoles of the MQW with various orientations into radiative emission, achieving enhancement of spontaneous emission rate by a factor of 33 and of quantum efficiency by a factor of 2.5, which is beneficial for coherent laser action. The hyperbolic metacavity laser shows a clear clamping of spontaneous emission above the threshold, which demonstrates a near complete radiation coupling of the MQW with the metacavity. This approach shown here can greatly simplify the requirements of plasmonic nanolaser with a long plasmonic structure, and the metacavity effect can be extended to many other material systems.     

A computationally efficient cohesive zone model for fatigue

A cohesive zone model has been developed for the simulation of both high and low cycle fatigue crack growth. The developed model provides an alternative approach that reflects the computational efficiency of the well‐established envelop‐load damage model yet can deliver the accuracy of the equally well‐established loading‐unloading hysteresis damage model. A feature included in the new cohesive zone model is a damage mechanism that accumulates as a result of cyclic plastic separation and material deterioration to capture a finite fatigue life. The accumulation of damage is reflected in the loading‐unloading hysteresis curve, but additionally, the model incorporates a fast‐track feature. This is achieved by “freezing in” a particular damage state for one loading cycle over a predefined number of cycles. The new model is used to simulate mode I fatigue crack growth in austenitic stainless steel 304 at significant reduction in the computational cost.     

中碳多元合金钢破碎机锤头的研制

对采用Cr、Mo、Ni及Mn等元素多元合金化中碳合金钢锤式破碎机锤头的组织、力学性能及耐冲击磨损性能进行了试验研究。锤头采用自硬树脂砂工艺铸造 ,对所研制的锤头进行了现场装机试验。试验结果表明 :合金元素含量分别为 :w(Cr) =4～ 5 %、w(Mo) =0 5～ 0 7%、w(Ni) =0 3～ 0 5 %、w(Mn) =0 6～ 0 9% ,含碳量为 :w(C) =0 4～ 0 5 %的中碳多元合金钢锤头具有高耐冲击磨损和良好韧性相结合的特点 ,其工作寿命为高锰钢锤头的 1 5 5倍     

Green Adeptness in the Synthesis and Stabilization of Copper Nanoparticles: Catalytic,Antibacterial, Cytotoxicity,and Antioxidant Activities

Copper nanoparticles (CuNPs) are of great interest due to their extraordinary properties such as high surface-to-volume ratio, high yield strength, ductility, hardness, flexibility, and rigidity. CuNPs show catalytic, antibacterial, antioxidant, and antifungal activities along with cytotoxicity and anticancer properties in many different applications. Many physical and chemical methods have been used to synthesize nanoparticles including laser ablation, microwave-assisted process, sol-gel, co-precipitation, pulsed wire discharge, vacuum vapor deposition, high-energy irradiation, lithography, mechanical milling, photochemical reduction, electrochemistry, electrospray synthesis, hydrothermal reaction, microemulsion, and chemical reduction. Phytosynthesis of nanoparticles has been suggested as a valuable alternative to physical and chemical methods due to low cytotoxicity, economic prospects, environment-friendly, enhanced biocompatibility, and high antioxidant and antimicrobial activities. The review explains characterization techniques, their main role, limitations, and sensitivity used in the preparation of CuNPs. An overview of techniques used in the synthesis of CuNPs, synthesis procedure, reaction parameters which affect the properties of synthesized CuNPs, and a screening analysis which is used to identify phytochemicals in different plants is presented from the recent published literature which has been reviewed and summarized. Hypothetical mechanisms of reduction of the copper ion by quercetin, stabilization of copper nanoparticles by santin, antimicrobial activity, and reduction of 4-nitrophenol with diagrammatic illustrations are given. The main purpose of this review was to summarize the data of plants used for the synthesis of CuNPs and open a new pathway for researchers to investigate those plants which have not been used in the past.

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Graphical abstract Proposed Mechanism for Antibacterial activity of copper nanoparticles.