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With the rapid development of society, it is of paramount importance to expeditiously assess environmental pollution and provide early warning of toxicity risks. Microbial fuel cell–based self-powered biosensors (MFC-SPBs) have emerged as a pivotal technology, obviating the necessity for external power sources and aligning with the prevailing trends toward miniaturization and simplification in biosensor development. In this case, vigorous advancements in MFC-SPBs have been acquired in past years, irrespective of whether the target identification event transpires at the anode or cathode. The present article undertakes a comprehensive review of developed MFC-SPBs, categorizing them into substrate effect and microbial activity effect based on the nature of the target identification event. Furthermore, various enhancement strategies to improve the analytical performance like accuracy and sensitivity are also outlined, along with a discussion of future research trends and application prospects of MFC-SPBs for their better developments. [ABSTRACT FROM AUTHOR]

After emergencies occur, decision-makers can reference historical cases with similar causes to take similar emergency response measures. However, information about emergencies is usually recorded and stored in textual form, and it is difficult for decision-makers to obtain effective information from large amounts of textual data and make decisions that balance various factors. To address these issues, this paper presents an emergency assisted decision-making model based on a knowledge graph and many-objective optimization. First, we preprocess the information by extracting entities to construct a knowledge graph of emergencies to make the event information more structured and easier to use. A knowledge graph is also used to narrow the range of matching historical events. Second, we construct a many-objective model with four objectives: similarity, diversity, processing time, and resource cost. Finally, combining the model characteristics, we design genetic operations for duplicate location matching and substitution removal strategies to obtain the nonrepetitive VaEA algorithm. This algorithm is used to optimize the model and generate a list of reference cases in the reduced matching range to provide rescue strategy suggestions for the current situation. The experimental results show that the algorithm outperforms the comparison algorithms under all four evaluation metrics. This indicates that the method in this paper can match the higher-quality historical emergency solutions applicable to the current decision-making situation in the case base and provide support for decision-makers to respond reasonably in emergencies. [ABSTRACT FROM AUTHOR]

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Purpose: Oral squamous cell carcinomas (OSCCs) are primary head and neck malignant tumours with a high incidence and mortality. However, the molecular mechanisms involved in OSCC tumorigenesis are not fully understood. Methods: OSCC and paired para-carcinoma samples were collected and used to perform multi-omics study. Transcriptomic analysis was used to reveal significant alterations in inflammatory and immune processes in OSCC. Ingenuity Pathway Analysis (IPA) combined with the LASSO Cox algorithm was used to identify and optimize a crucial gene signature. Metabolomics analysis was performed to identify the important metabolites which linked to the crucial gene signature. The public data TCGA-HNSCC cohort was used to perform the multiple bioinformatic analysis. Results: These findings identified a FN1-mediated crucial network that was composed of immune-relevant genes (FN1, ACP5, CCL5, COL1A1, THBS1, BCAT1, PLAU, IGF2BP3, TNF, CSF2, CXCL1 and CXCL5) associated with immune infiltration and influences the tumour microenvironment, which may contribute to OSCC tumorigenesis and progression. Moreover, we integrated the relevant genes with altered metabolites identified by metabolic profiling and identified 7 crucial metabolites (Glu-Glu-Lys, Ser-Ala, Ser-Ala, N-(octadecanoyl) sphing-4-enine-1-phosphocholine, N-methylnicotinamide, pyrrhoxanthinol and xanthine) as potential downstream targets of the FN1-associated gene signature in OSCC. Importantly, FN1 expression is positively correlated with immune infiltration levels in HNSCC, which was confirmed at the single-cell level. Conclusions: Overall, these results revealed the differential genetic and metabolic patterns associated with OSCC tumorigenesis and identified an essential molecular network that plays an oncogenic role in OSCC by affecting amino acid and purine metabolism. These genes and metabolites might, therefore, serve as predictive biomarkers of survival outcomes and potential targets for therapeutic intervention in OSCC. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing is a widely used technique applied in unconventional reservoirs to generate large fracture networks. Interactions between hydraulic fracture (HF) and natural fracture (NF) can impact the fracture topology and thus the subsequent productivity. Despite a large number of studies on HF–NF interactions, the HF propagation path is normally judged based on ad-hoc criteria to decide whether crossing or deflection occurs and the mechanism behind has not yet reached a unified understanding. Here, we use a phase-field model (PFM), which is based on a unified fracture propagation criterion, to investigate the influence of in-situ stress, fracturing operational parameters and NF orientation and strength. We analyze the mechanism behind different propagation patterns resulting from different kinds of NFs—non-cemented and cemented ones under different conditions. In particular, we compare the total energies between the symmetric propagation and asymmetric propagation to verify the minimum energy propagation path. Our results indicate that a higher stress anisotropy more likely leads to HF–NF crossing and a less fracture complexity. Injection rate influences propagation speed and fracture complexity. Within a certain range (30°, 45°, 60° in this study), the larger the approaching angle is, the more complex the fractures become. With the increasing strength contrast between NF and rock matrix, the material heterogeneity increases, encouraging HF to form complex fractures. Opening more strongly cemented NFs, which act as a barrier for propagation, consumes more energy than HF propagation outside the interface. Lower stress anisotropy and higher injection rate lead to higher initiation pressure, requiring more energy for propagation. Highlights: A phase field model based on a unified fracture propagation criterion is used to study the interactions between hydraulic fractures and natural fractures. The mechanism behind different propagation patterns resulting from non-cemented and cemented natural fractures under different conditions is analyzed. A parameter denoted as complexity degree is used to describe fracturing effect through the sensitive analyses. The total energies between the symmetric propagation and asymmetric propagation are compared to verify the minimum energy propagation path. [ABSTRACT FROM AUTHOR]

As the digital world becomes the main complement to the physical world, establishing a solid line of defense against cyber attacks becomes critical and arduous. The intrusion detection systems (IDSs) based on the supervised learning method have achieved excellent performance, which requires a large amount of labeled data in the training phase. However, attacks occur much less frequently than normal behaviors, and it is difficult to obtain accurate labels. In addition, IDSs based on supervised learning cannot identify unknown attacks. At the same time, the problem that detection accuracy varies greatly with different applications is very significant in traditional unsupervised learning methods. Therefore, it is necessary to perform high-precision anomaly detection on unlabeled samples. This paper proposes a traffic anomaly detection model using K-means and Active Learning Method (ALM), which is mainly composed of a feature extraction module and an anomaly detection module. Firstly, the Pearson correlation coefficient and Light Gradient Boosting Machine (LightGBM) are used in the feature extraction module to select important features. Secondly, K-means divides the characteristic-processed traffic into normal or abnormal categories. Finally, the results of K-means are diffused through ALM, and new classification results are obtained after defuzzification, thereby improving the accuracy of anomaly detection. The latest CICDDoS2019 data set is used in the experiment. Experimental results show that the detection accuracy of the proposed model is above 90%, and the F1 score is above 95%, regardless of whether it is a binary classification of a single attack or a mixed classification of multiple attacks. Compared with three unsupervised learning methods K-means, Auto-encoder and short-term memory (LSTM) and three supervised learning methods Naive Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT), the proposed model has higher classification accuracy and better generalization effect. This article is very helpful for exploring the application of unsupervised learning methods in network intrusion detection systems based on the characteristics of the data itself. [ABSTRACT FROM AUTHOR]

Environmental values are key factors influencing consumers' purchase intentions and improving consumers' willingness to buy green products is crucial for the sustainable development of ecological environments. Based on environmental values and green product trust, the present study classified environmental values into egoistic, altruistic, and biospheric values and discussed the influence mechanisms of environmental values on green product purchase intention. On this basis, the study verified the mediating role of environmental concern and the moderating role of green trust on the relationship between environmental concern and green product purchase intention. The research results revealed that (1) altruistic and biospheric values had a significant positive impact on green product purchase intention, while egoistic values had a negative impact on green product purchase intention; (2) environmental concern had a partial mediating effect on the relationship between environmental values and green product purchase intention; and (3) green trust had a positive moderating effect on the relationship between environmental concern and green product purchase intention. The present study expanded on the existing research on green product purchase intention driven by values, and the conclusions provided theoretical guidance for green marketing by enterprises and the establishment of customers' trust in the green attributes of products. [ABSTRACT FROM AUTHOR]

The application of thermal-responsive Janus particles as emulsion stabilizers in oil–water systems has attracted increasing attention in recent years. This work reported a novel Janus silica nanoparticle with one silanol side and one poly(N-isopropylacrylamide) (PNIPAM) side, which was fabricated via combining interfacial synthesis method and single-electron transfer living radical polymerization (SET-LRP) process. Their structure and surface properties were identified by SEM, TEM, 1H NMR, FTIR, and TGA. The thermo-responsive performance of Janus nanoparticles in oil–water Pickering emulsion systems was also investigated as well as their emulsification properties in both the tetradecane–water and crude oil–water systems. The solubility of both Janus and symmetric PNIPAM-modified silica nanoparticles in water presents reversible thermal-responsive properties. Notably, the Janus nanoparticles show a higher phase transition temperature than the symmetric nanoparticles because the presence of silanol on one side of the Janus nanoparticles enhances its hydrophilicity due to the stronger hydrogen bond at high temperature. In comparison with symmetric nanoparticles, Janus nanoparticles exhibit superior emulsification performance in the tetradecane–water system as a result of their lower surface tension. Janus nanoparticles also present excellent thermal-responsive emulsification performance in the crude oil–water system, showing a prospective future in industrial application as a surfactant. [ABSTRACT FROM AUTHOR]

Hot compression testing was used to investigate the hot deformation behavior of 7475 aluminum alloy in a temperature range of 573-723 K and a strain rate range of 0.01-10 s−1. The hot workability was studied by means of constitutive analysis, three-dimensional processing maps, and microstructure characterizations using optical microscopy, electron back-scattered diffraction, and transmission electron microscopy. The results showed that the flow stress was increased with the increment of strain rates or the decrement of deformation temperature. Based on 3D processing, a temperature range of 623-673 K and a strain rate range of 0.01-0.1 s−1 were proposed to domain the process. Dynamic softening mechanisms were found to be associated with different contributions of dynamic recovery, dynamic recrystallization, and grain boundary sliding in various deformation conditions. These findings, along with the microstructure observation, suggested that the safe-deformation regimes with higher dissipation efficiency could be attributed to the continuous dynamic recrystallization and grain boundary sliding. The flow-instability regimes could be caused by the flow localizations and the adiabatic shear bands. [ABSTRACT FROM AUTHOR]

Maternal effects are one of the most interesting topics in evolutionary ecology as they can affect the rate of evolution and population dynamics by phenotypic manipulation of offspring related to fitness. At present, studies examining the interaction between maternal environment effects and maternal age (birth order) effects are scarce. We designed an experiment to reveal whether environmentally induced maternal manipulation works equally on offspring across birth orders in rotifer Brachionus calyciflorus. In the experiment, newborn amictic mothers (F0) were cultured parallelly in low (LD) and high (HD) population density. Offspring (F1) of young (YF0) and old (OF0) mothers in both LD and HD groups were cultured under a crowded condition and the mixis ratios of both F1 and F2 were examined. Results show that F1 from HD-YF0 had a significantly higher mixis ratio and those amictic ones produced daughters (F2) with higher mixis ratio in response to crowding than those from HD-OF0. In contrast, no such differences among F1 siblings were found in the LD-F0 group. Therefore, the effect of maternal age on the sexual propensity of the offspring can be affected independently by the maternal population density. [ABSTRACT FROM AUTHOR]

High-quality VO films with precisely controlled thicknesses were grown on sapphire substrates by plasma-assisted oxide molecular beam epitaxy (MBE). To evaluate the degradation of semiconductor-metal transition (SMT) behavior of VO films under solar radiation, the temperature-driven SMT was investigated by measuring the electrical resistance during heating and cooling processes under solar simulator AM1.5, which provided illumination approximately matching the natural sunlight. The distinct reversible SMTs were observed for all the samples, whereas a remarkably conflicting trend in resistance change for extremely thin and thick samples was observed after exposure to the sunlight soaking system. The corresponding mechanism was proposed based on sunlight-induced resistance changes due to the transformation in the electron correlation and structural symmetry. The results might be especially attractive for some specific applications of VO films where solar radiation was inevitable. [ABSTRACT FROM AUTHOR]

VO films with precisely controlled thickness on the nanoscale ranging from 15 to 60 nm were grown on single crystal sapphire substrates by molecular beam epitaxy. X-ray diffraction and atomic force microscopy measurements indicated that high quality single phase VO films with condense and smooth surface and free of cracks could be achieved only when the film was thicker than 30 nm. The temperature-dependent resistance measurement indicated a drastic modification of metal-insulator transition (MIT) properties which was achieved through the variation of film thickness, especially the transition magnitude and curve abruptness. The corresponding mechanism was supposed to be associated with the tensile stress relaxation effect with increasing thickness caused by thermal mismatch within VO films, as demonstrated by Raman spectra. Our present finding provides an effective and convenient alternative to modulate the MIT properties of VO films. [ABSTRACT FROM AUTHOR]

Vanadium oxide (VO) thin films were grown on single crystal sapphire substrates by pulsed laser deposition under various O partial pressures. In situ AlN layer was inserted between the substrate and VO films as induced stress layer. The significant influences of AlN layer on the structural, electric, and optical properties of the as-grown films were investigated systemically. The results indicated that pure monoclinic phase VO film with (020) preferred orientation was successfully achieved under the optimized O partial pressure. Moreover, a lowered semiconductor-to-metal transition temperature and a higher optical transmittance in visible and near-infrared regions were achieved due to the introduction of AlN-induced stress layer. Our achievements suggested that it might be a promising method to modulate VO transition characteristics by inducing AlN-induced stress layer. [ABSTRACT FROM AUTHOR]

This article reports the fabrication of hybrid silica nanoparticles using surface-initiated atom transfer radical polymerization (SI-ATRP) technique. The surface of silica nanoparticles were densely grafted with 2-(dimethylamino) ethyl methacrylate (DMAEMA) and then quaternized with 1-bromohexane via two methods. FTIR, H NMR, XPS, SEM, TGA, and GPC were used to determine the chemical structure, morphology, and other properties of the products. SEM images of nanocomposites showed spherical shaped morphology with an average diameter of ∼50 nm and they were direct evidences that the hybrid silica nanoparticles had uniform core-shell morphology. Evolution of GPC traces of grafted polyDMAEMA showed that the SI-ATRP could be conducted in a well-controlled manner. [ABSTRACT FROM AUTHOR]

To demonstrate the utility of the emotional intelligence (EI) construct in organizational studies, this study focuses on the effect of EI on job performance among research and development scientists in China. We argue that EI is a significant predictor of job performance beyond the effect of the General Mental Ability (GMA) battery on performance. This predictor effect is supported by results on a study of research and development scientists working for a large computer company in China. Our results also show that a self-reported EI scale developed for Chinese respondents, the WLEIS, is a better predictor of job performance than the scale developed in the U.S., the MSCEIT. Implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

Intelligent indicators can display the quality status of food through the color change of dyes and have received increasing attention in recent years due to their convenience and accuracy in detection. Nowadays, intelligent indicators are mainly composed of a matrix and pH-responsive dyes. Anthocyanins are water-soluble natural pigments widely present in fruits and vegetables, showing different colors under different pH conditions. Chitosan is a product of the partial deacetylation of natural polysaccharide chitin. It has good biodegradability, biocompatibility, non-toxicity, and antibacterial properties. In terms of physiological functions, it has multiple functions such as anti-cancer, lipid-lowering, and enhancing immunity. Therefore, it has a wide range of applications in the field of food packaging. This article reviews the research of intelligent freshness indicators based on chitosan and anthocyanins in monitoring the freshness of packaged foods in recent years and compares the performance of indicators with different matrix types. Moreover, this article also focuses on the working mechanism of intelligent indicators, the extraction methods of anthocyanins, and a summary of their advantages and disadvantages. In addition, the preparation, properties, and applications of new indicators, including hydrogels, multilayer structure film, metal–organic framework (MOF), and inkjet printing technology, are reviewed. Finally, this study lists the applications of intelligent indicators in typical foods such as fruits and vegetables, meat, seafood, and dairy products; analyzes the current shortcomings; and proposes future research priorities. [ABSTRACT FROM AUTHOR]

A colorimetric and visual assay is described for the herbicide aminotriazole (ATZ). It is based on the etching of gold nanorods (AuNRs) by iodine which is formed on oxidation of iodide via H2O2. Longitudinal etching of the AuNRs occurs quickly and is accompanied by a color change from dark blue to red. In the absence of ATZ and the presence of active catalase (CAT), H2O2 is quickly decomposed into water, and the AuNRs will not be etched. In the presence of ATZ, CAT is partially deactivated, and this affects the amount of available H2O2 and, consequently, of the iodine. Hence, the color is significantly changed. The color changes can be easily detected with bare eyes. The assay has a linear response in the 5 to 70 μM concentration range, with a detection limit of 1.3 μM and high selectivity for ATZ. It was applied to the determination of ATZ in water and food samples. [ABSTRACT FROM AUTHOR]

Homeostasis maintains serum metabolites within physiological ranges. For glucose, this requires insulin, which suppresses glucose production while accelerating its consumption. For other circulating metabolites, a comparable master regulator has yet to be discovered. Here we show that, in mice, many circulating metabolites are cleared via the tricarboxylic acid cycle (TCA) cycle in linear proportionality to their circulating concentration. Abundant circulating metabolites (essential amino acids, serine, alanine, citrate, 3-hydroxybutyrate) were administered intravenously in perturbative amounts and their fluxes were measured using isotope labelling. The increased circulating concentrations induced by the perturbative infusions hardly altered production fluxes while linearly enhancing consumption fluxes and TCA contributions. The same mass action relationship between concentration and consumption flux largely held across feeding, fasting and high- and low-protein diets, with amino acid homeostasis during fasting further supported by enhanced endogenous protein catabolism. Thus, despite the copious regulatory machinery in mammals, circulating metabolite homeostasis is achieved substantially through mass action-driven oxidation., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)