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Achieving continuous tunability, high efficiency, and outstanding thermal stability of near‐infrared (NIR) phosphors remains challenging for optoelectronic device fields. To address this issue, a strategy is proposed based on the substitution of both cations and anions in the intermediate spinel structure, which successfully achieved fine‐tuning of NIR emission of Mg1+yGa2‐yO4‐yFy:Fe3+ phosphors with prominent optical characteristics. The NIR emission contains new luminescent centers with random O/F coordination and is successfully constructed. This co‐substitution promotes further inversion of the cationic sites and induces atomic disorder, changing the crystal coordination environment and making Fe3+ breakthrough the Laporte selection rule, enabling fine‐tuning of Fe3+ emissions in the range of 707–740 nm and broadening of the full width at half maximum by 30 nm. Moreover, the Mg1.15Ga1.85O3.85F0.15:Fe3+ phosphor reached a high quantum yield of 71.6% and presented excellent thermal stability with an emission intensity retention of 81% at 493 K. The emission of the fabricated NIR phosphor‐converted light‐emitting diodes also matched well with the photosensitive pigment Pfr, demonstrating its feasibility for plant growth lighting applications. [ABSTRACT FROM AUTHOR]

Fe3+‐doped MgGa2O4 (MGO: Fe3+) spinel‐type near‐infrared (NIR) phosphor with non‐toxicity, outstanding thermal stability, and tunable emission has recently gained great concern owing to its wide applications. Nevertheless, the existence of detrimental O defects in the MgGa2O4 host and the forbidden d‐d transitions of Fe3+ lead to unsatisfactory luminescence efficiency, limiting the commercial application. In this study, a vacancy repairing engineering has been innovatively developed via F− substitution in MGO: Fe3+ (MGOF: Fe3+) for significantly enhancing NIR emission and maintaining outstanding thermal stability. Specifically, F− substitution with a similar radius effectively repairs the intrinsic O vacancy defects of MGO, thereby prohibiting the detrimental electron‐capturing effect. Meanwhile, F− incorporation can make the lattice of MGO distort and break the forbidden transition of Fe3+. Significantly, the obtained MGOF: Fe3+ presents a 16‐fold higher emission intensity than that of MGO: Fe3+. More important, the MGOF: Fe3+ can remain at 91.17% (363 K) and 85.10% (423 K). Finally, the NIR emission of MGOF: Fe3+ can be used for night vision, non‐destructive biological tissue detection, and food analysis. The proposed vacancy repairing strategy can certainly stimulate some new thoughts and concepts in designing high‐performance phosphors for wider applications. [ABSTRACT FROM AUTHOR]

In this study, metabolomics and proteomics were performed to investigate the fluctuations of non-volatile compounds and proteins in tea leaves from three tea cultivars with varying colours during withering. A total of 2798 compounds were detected, exhibiting considerable variations in amino acids, phenylpropanoids, and flavonoids. The ZH1 cultivar displayed increased levels of amino acids but decreased levels of polyphenols, which might be associated with the up-regulation of enzymes responsible for protein degradation and subsequent amino acid production, as well as the down-regulation of enzymes involved in phenylpropanoid and flavonoid biosynthesis. The FUD and ZH1 cultivars had elevated levels of flavanols and flavanol-O-glycosides, which were regulated by the upregulation of FLS. The ZJ and ZH1 cultivars displayed elevated levels of theaflavin and peroxidase. This work presents a novel investigation into the alterations of metabolites and proteins between tea cultivars during withering, and helps with the tea cultivar selection and manufacturing development. [Display omitted] • Multi-omics study on tea leaves from three different tea cultivars with distinct colours during withering. • The composition and contents of non-volatile chemicals varied with tea cultivars and withering times. • The amino acids biosynthesis was increased and the polyphenols biosynthesis was decreased in the ZH1 cultivar. • The flavonoid biosynthesis was increased in the FUD and ZJ cultivars during withering. • The levels of PODs and PPOs were elevated in the ZJ and ZH1 cultivars during withering. [ABSTRACT FROM AUTHOR]

Dual-mode high-sensitivity and high-resolution fluorescence thermometry have been realized by the energy transfer in Dy3+,Mn4+ co-doped phosphors. [Display omitted] • The energy transfer between Dy3+ and Mn4+ ions is verified in La 2 MgTiO 6 :Dy3+, Mn4+ phosphors. • The color of the obtained phosphor demonstrates adjustable characteristics by altering doping concentration and temperature. • The dual-mode fluorescence thermometers with excellent sensitivity and high resolution are realized. • The maximum S r increased from 1.621 % K−1 to 2.305 % K−1. • The thermochromic properties of developed films can evaluate the ambient temperature qualitatively. Fluorescent temperature measurement has become a research hotspot due to its characteristics of non-contact, miniaturization, and fast response. However, it remains a key challenge to realize excellent sensitivity and high resolution. Herein, a series of La 2 MgTiO 6 :Dy3+,Mn4+ phosphors are developed and the related energy transfer between Dy3+→Mn4+ is discovered. The coupling distance between Mn4+ and adjacent ligands is greatly affected by temperature. However, the energy differences between the emission energy levels and lower energy levels of Dy3+ hinder the multi-phonon relaxation process, which moderates the thermal quenching rate of Dy3+. Therefore, highly sensitive FIR thermometers are built according to the significant discrimination temperature dependence of Dy3+ and Mn4+. The maximum S a and S r reach 0.022 K−1(@563 K) and 2.622 %K−1(@544 K). In contrast, a thermometer based on the emission lifetime of Mn4+ is fabricated, which is extremely sensitive to temperature. Interestingly, Dy3+ can effectively promote the quenching of Mn4+, and then improve the sensitivity. The maximum S r enhances from 1.621 %K−1(@503 K) to 2.305 %K−1 (@480 K). The high sensitivity and resolution of the dual-mode fluorescence thermometry have exceeded most of the current optical thermal measurement materials. Besides, the thermochromic properties presented by the designed phosphors can be combined with PDMS films to qualitatively evaluate the ambient temperature. [ABSTRACT FROM AUTHOR]

Owing to its convenient, sustainable and green process, photocatalysis has become a feasible technique for solving environmental pollution issues. So far, significant achievements have been realized in photocatalytic pollutant elimination. Nevertheless, photocatalytic processes require a continuous external light illumination to drive photoredox reactions, seriously prohibiting their applications in darkness. In this context, exploring a photocatalyst with reliable photocatalytic activity in dark condition is therefore highly meaningful and an ultimate target of photocatalysis technique. Recently, long afterglow phosphor has aroused great attention due to its "light battery" role for driving catalytic reactions in dark conditions. To be specific, long-afterglow phosphor or long-afterglow phosphor/semiconductor composite can be used as a photocatalyst to simultaneously promote the photoredox processes and store extra photoexcited charges in the trapping states upon light irradiation. When the light illumination terminates, a gradual release of the charges from trapping states occurs in long-afterglow phosphor, which can continuously spur photoredox reactions under the dark environment and even maintains the photocatalysis around the clock. In this work, we comprehensively reviewed the recent advances of long afterglow phosphor based round-the-clock photocatalysts in environmental pollutant elimination. Meanwhile, the inherent mechanism of long afterglow photocatalysis was discussed in depth. More importantly, the relationship between the improved long afterglow photocatalytic capability and the engineering of long afterglow system is correlated systematically. Finally, the ongoing challenges and future prospects for the mass production and commercial utilization of round-the-clock photocatalysts are analyzed and outlooked. [ABSTRACT FROM AUTHOR]

Multi-objective evolutionary algorithms based on decomposition (MOEA/Ds) convert a multi-objective optimization problem (MOP) into a set of scalar subproblems, which are then optimized in a collaborative manner. However, when tackling imbalanced MOPs, the performance of most MOEA/Ds will evidently deteriorate, as a few solutions will replace most of the others in the evolutionary process, resulting in a significant loss of diversity. To address this issue, this paper suggests a localized decomposition evolutionary algorithm (LDEA) for imbalanced MOPs. A localized decomposition method is proposed to assign a local region for each subproblem, where the inside solutions are associated and the solution update is restricted inside (i.e., solutions are only replaced by offspring within the same local region). Once off-spring are generated within an originally empty region, the best one is reserved for this subproblem to extend diversity. Meanwhile, the subproblem with the largest number of associated solutions will be found and one of its associated solutions with the worst aggregated value will be removed. Moreover, to speed up convergence for each subproblem while balancing the population's diversity, LDEA only evolves the best-associated solution in each subproblem and correspondingly tailors two decomposition methods in the environmental selection. When compared to nine competitive MOEAs, LDEA has shown the advantages in tackling two benchmark sets of imbalanced MOPs, one benchmark set of balanced yet complicated MOPs, and one real-world MOP. • LDEA proposes a localized decomposition algorithm for imbalanced MOPs. • The proposed decomposition method assigns local regions to subproblems. • Mating selection, operators, and environmental selection are modified to cooperate with LDEA. • LDEA outperforms other competitive MOEAs on imbalanced and complicated MOPs. [ABSTRACT FROM AUTHOR]

To explore the relationship between the moisture content of withered tea leaves and their physical properties (i.e., elasticity, plasticity, flexibility, and texture) during withering, texture analyzer was employed to test the elasticity and flexibility of withered tea leaves with different moisture contents. The texture was evaluated by computer vision technology. The withered tea leaves with different moisture contents were used to process congou black tea, which was then subjected to sensory evaluation. Results showed that good elasticity, optimal flexibility, and plasticity were achieved when the moisture content of the withered tea leaves of Fudingdabai comprising two leaves and one bud varied arranging from 65.51 to 61.48%. The sensory evaluation of congou black tea revealed that moderate withering was better than long‐term withering and that both moderate and long‐term withering were better than no withering during processing. The moisture content was significantly correlated with the flexibility and plasticity of the withered tea leaves. Fresh tea leaves undergoing moderate withering with moisture content of 65.51–61.48% to process congou black tea, good tea shape and liquor color were achieved. This study provided new evidence that the moisture content of withered tea leaves significantly affected the quality of black tea. [ABSTRACT FROM AUTHOR]

In this study, 36.8% (28/76) of tissue samples collected from domestic pigs (Sus scrofa) contained sarcocysts, as determined by light microscopy. The organisms were identified as Sarcocystis miescheriana and Sarcocystis suihominis based on their morphological and molecular characteristics. Four genetic markers, i.e., 18S rDNA, 28S rDNA, ITS-1 region (ITS-1), and the mitochondrial COX1 gene (COX1), of the two parasites were sequenced and analyzed, and the 28S rDNA and ITS-1 of S. suihominis obtained from pigs constituted the first records of these markers in GenBank. The sequences of the four loci (18S rDNA, 28S rDNA, ITS-1, and COX1) of S. miescheriana shared high identities with those of S. miescheriana obtained from domestic and/or wild pigs in GenBank, with similarities of 99.6%, 99.6%, 95.9%, and 95.4%, respectively. The 18S rDNA sequences of S. suihominis exhibited 99.4% identity with those of S. suihominis from domestic and wild pigs. The comparison of the newly obtained sequences of the four genetic markers between the two parasites revealed that the interspecific similarities of 18S rDNA, 28S rDNA, ITS-1, and COX1 were 97.7%, 96.6%, 80.3%, and 81.2%, respectively. Therefore, the two species could be better discriminated with ITS-1 and mitochondrial COX1 compared with 18S rDNA or 28S rDNA. The phylogenetic analysis using 28S rDNA indicated that the two Sarcocystis species in domestic pigs had a close relationship. [ABSTRACT FROM AUTHOR]

The presence of Sarcocystis cysts in the muscle tissue of domestic dogs (Canis familiaris), which normally serve as definitive hosts, is unusual and infrequent. Here, S. caninum sarcocysts were identified for the first time in two of 37 dogs (2.7%) from China. Examination using light microscopy found that the S. caninum sarcocysts were up to 1520 μm long and up to 147 μm wide and contained numerous 1.5-3.3 μm wedge-like villar protrusions (vp). Transmission electron microscopy revealed that the sarcocysts had pleomorphic vp that closely resembled those of “type 9c.” Five loci, 18S rDNA, 28S rDNA, mitochondrial cox1, ITS1 and ropB, were sequenced and characterized in S. caninum sarcocysts. The sequences of the five loci shared similarities of 99.9-100%, 99.0-100%, 99.4-100%, 99.6-100%, and 99.7-100%, respectively, with those of S. arctica. Phylogenetic analysis based on the sequences of 28S rDNA and mitochondrial cox1 indicated that S. caninum and S. arctica are closely related to Sarcocystis species that use a raptorial bird as their definitive host. [ABSTRACT FROM AUTHOR]

In order to clarify the relationship between withering process and green tea quality, dynamic changes in the major chemical components of green tea, including amino acids, catechins, caffeine (CAF) and gallic acid (GA), were investigated during withering at different times (ranging from 0 h to 21 h) and temperatures (15, 20 and 25 °C). One-way and two-way analyses of variance (ANOVA) with Duncan’s test were used to analyse the change of chemical components. Results showed that during the withering process, contents of most free amino acids increased with increasing withering time and temperature. Theanine (Thea) contents decreased slightly with fluctuations, glutamic acid (Glu) and aspartic acid (Asp) contents presented an increase–decrease pattern, whereas proline (Pro) contents remained almost constant. Total free amino acids increased up to 18 h but declined thereafter. Most catechins decreased with increasing withering time and temperature. In addition, GA contents increased with increasing time and temperature; while CAF contents increased with increasing withering time, but were only slightly correlated with withering temperature. This experiment recommended withering for 15–18 h below 25 °C to produce high quality green tea. [ABSTRACT FROM AUTHOR]

Dynamic multi-objective optimization problems (DMOPs) typically contain multiple conflicting objectives that vary over time, requiring the optimization algorithms to quickly track the changing Pareto-optimal solutions (POS). Recently, prediction-based dynamic multi-objective evolutionary algorithms (DMOEAs) using transfer learning ideas have been considered promising, which could accelerate the search towards the POS by transferring information from previous environments to estimate the location of the POS in the next environment. However, most of the existing methods only transfer the search experiences from one or two previous environments to construct the prediction model for the next moment, which may ignore the effective information in the earlier search process thereby degrading the prediction accuracy in some cases. In this paper, a knowledge-guided Bayesian classification for DMOEA, called KGB-DMOEA, is proposed, which aims to achieve a robust prediction by fully exploiting the information from all historical environments. Particularly, when an environmental change is detected, a knowledge reconstruction–examination strategy is designed to divide all historical optimal solutions into useful and useless ones, which are used as positive and negative samples, respectively, for training the prediction model in subsequent steps. Then, a non-linear probabilistic classifier, i.e., naive Bayesian classifier, is constructed by using the above training samples, which can fully mine the effective knowledge from all historical environments and predict a high-quality initial population for the new environment. Experimental results on multiple DMOPs test suits demonstrate that KGB-DMOEA is superior to several state-of-the-art DMOEAs in solving various DMOPs. • A knowledge-guided dynamic multi-objective evolutionary algorithm is proposed. • A knowledge reconstruction–examination strategy is devised. • A knowledge-guided Bayesian classification strategy is designed. • The experimental results show the merits of the proposed algorithm. [ABSTRACT FROM AUTHOR]

• We use the Elman neural network (ENN) to obtain an accurate forecast of future based on historical data. • The proposed crosstalk-aware intra-core resource allocation can reduce the inter-core crosstalk. • The proposed horizon-based inter-core spectrum allocation can reduce the fragmentation and improve spectrum utilization. As network traffic is expected to continue to grow at high rates for the foreseeable future, it becomes imperative to introduce space division multiplexing elastic optical networks (SDM-EONs) into the optical transport network. However, spectrum fragmentation and crosstalk present significant challenges that may negatively impact the performance of SDM-EONs. In this paper, we leverage machine learning techniques to enhance the transmission performance of SDM-EONs, and make two contributions. Specifically, we use an Elman neural network to forecast traffic demands, and use a two-dimensional rectangular packing model to allocate spectrum so as to decrease unnecessary spectrum fragmentation (and, in turn, increase resource utilization). We also present a novel spectrum partition scheme to reduce crosstalk. Our evaluation study confirms that the proposed strategy is effective in improving spectrum utilization while reducing blocking probability and crosstalk. [ABSTRACT FROM AUTHOR]

High quality AA6101 aluminum cables are critical to electrical industry to meet the energy consumption requests. In the present work, the influence of Mg/Si ratios on the electrical conductivity and mechanical properties of AA6101 aluminum alloy was investigated. Wheatstone Bridge method and tensile test were employed to characterize the mechanical properties. X-ray Diffraction (XRD), Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM) were used to understand the morphology of the precipitation and the mechanism of age hardening. It is found that excessive Si benefits high strength and high conductivity while excessive Mg plays a negative role in the strength and the conductivity of AA6101 cables. Excessive Si elements promote both the precipitating rate and quantity of β ″ phase therefore increase the tensile strength. Excessive Si elements also help with decreasing the lattice distortion, which contributes to the enhancement of the conductivity. Excessive Mg elements lead to more dissolved Mg after aging treatment, therefore increase lattice distortion of the matrix and promote the deposit of coarse Mg-enriched secondary phase. [ABSTRACT FROM AUTHOR]

Background: There has been considerable confusion concerning the number and classification of Sarcocystis spp. in chickens. Scarce nucleotide data of Sarcocystis spp. from chickens are provided in GenBank. The study aimed to investigate the morphological and molecular characteristics of Sarcocystis spp. found in chickens in China. Methods: Tissues from 33 chickens were collected in 2019. Sarcocysts were observed using light (LM) and transmission electron microscopy (TEM). Individual sarcocysts from different chickens were selected for DNA extraction, and five loci, 18S rDNA, 28S rDNA, ITS1 region, the mitochondrial cox1 gene and the apicoplastic rpoB gene, were amplified from each sarcocyst, sequenced and analyzed. Results: Only S. wenzeli was found in 14 of 33 (42.4%) chickens. Under LM, the sarcocysts were microscopic and exhibited palisade-like villar protrusions measuring 1.5–2.8 μm. Ultrastructurally, the sarcocyst wall contained numerous stubby hill-like villar protrusions. The protrusions included scattered microtubules, which extended from the tips of the protrusions into the ground substance. The five loci were successfully sequenced and the sequences deposited in GenBank. At 18S rDNA, ITS1 and cox1, the most similar sequences in GenBank were those of Sarcocystis sp. obtained from the brains of chickens, i.e. 99.9–100%, 98.1–98.5% and 99.3% identity, respectively. The five loci (18S rDNA, 28S rDNA, ITS1, cox1 and rpoB) showed different levels of interspecific sequence similarity with other closely related species of Sarcocystis (e.g. 99.8%, 99.0–99.2%, 89.3–89.7%, 98.5%, and 97.5%, respectively, with S. anasi). Phylogenetic analysis based on four of the loci (18S rDNA, cox1, rpoB and ITS1) revealed that S. wenzeli formed an independent clade with Sarcocystis spp. that utilize geese or ducks as intermediate hosts and canines as the known or presumed definitive host. Conclusions: To our knowledge, the sequences of 28S rDNA and rpoB reported here constitute the first records of genetic markers of Sarcocystis spp. in chickens. Based on molecular analysis, S. wenzeli might be responsible for the neurological disease in chickens, and ITS1 and rpoB are more suitable for discriminating it from closely related Sarcocystis spp. Phylogenetic analysis revealed that S. wenzeli presents a close relationship with Sarcocystis spp. in geese or ducks. [ABSTRACT FROM AUTHOR]

Abstract: BACKGROUND: Gas chromatography–olfactometry (GC–O) is the most frequently used method to estimate the sensory contribution of single odorant, but disregards the interactions between volatiles. In order to select the key volatiles responsible for the aroma attributes of Congou black tea (Camellia sinensis), instrumental, sensory and multivariate statistical approaches were applied. RESULTS: Using sensory analysis, nine panellists developed eight descriptors: floral, sweet, fruity, green, roasted, oil, spicy, and off‐odour. Linalool, (E)‐furan linalool oxide, (Z)‐pyran linalool oxide, methyl salicylate, β‐myrcene, and phenylethyl alcohol, which were identified from the most representative samples by the GC–O procedure, were the essential aroma‐active compounds in the formation of basic Congou black tea aroma. In addition, 136 volatiles were identified by gas chromatography–mass spectrometry (GC–MS), among which 55 compounds were determined as the key factors for six sensory attributes by partial least‐square regression (PLSR) with variable importance of projection scores. CONCLUSION: Our results demonstrated that headspace solid‐phase microextraction/GC–MS/GC–O was a fast approach for isolation and quantification aroma‐active compounds. The PLSR method was also considered to be a useful tool in selecting important variables for sensory attributes. These two strategies, which allowed us to comprehensively evaluate the sensorial contribution of a single volatile from different perspectives, can be applied to related products for comprehensive quality control. © 2018 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Dynamic multimodal optimization problems (DMMOPs) have to search multiple global optimal solutions with the objectives and constraints dynamically changing over time. In recent years, dynamic optimization problems and multimodal optimization problems have been extensively studied in the field of evolutionary computation. However, DMMOPs have not yet been paid significant attention and only a few studies have been designed for dynamic multimodal optimization. The key issue in optimizing DMMOPs is to address the challenges induced by both the multimodal nature and the dynamic nature. Existing works perform poorly in locating all global optima in static environments and tracking global optima with various change modes. Therefore, in this paper, a Kriging Model-based Evolutionary Algorithm with Support Vector Machine called KMEA-SVM is proposed for tackling DMMOPs. Two important operators are designed in this algorithm, including a Kriging-based preselection and a support vector machine (SVM)-based prediction. The aim of Kriging-based preselection is to search all global optimal solutions more efficiently by preselecting promising solutions with a trained Kriging model, while the purpose of SVM-based prediction is to predict more outstanding solutions as the initial population for new environment when the environment changes. The proposed KMEA-SVM is compared with several state-of-the-art evolutionary algorithms on twenty-four test DMMOPs and the experimental results validate the advantages of KMEA-SVM on seeking more multiple optima in dynamic environments. [ABSTRACT FROM AUTHOR]

Salmonella Senftenberg is an important nontyphoidal Salmonella serovar that causes gastrointestinal disease worldwide. In total, 130 Salmonella Senftenberg strains obtained from humans, food, and the environment in Shanghai, People's Republic of China, were characterized for antimicrobial susceptibility and subjected to molecular typing. Our findings indicated that most (96 of 130, 73.8%) of the strains were susceptible to all 13 antimicrobial compounds tested, whereas only two strains (1.5%) were resistant to two antimicrobial compounds. In total, 56 pulsed-field gel electrophoresis profiles were identified, including four main pulsed-field gel electrophoresis profiles (X2, X3, X4, and X5) that showed 95.7% genetic similarity. Our study revealed that the strains of Salmonella Senftenberg from food and the environment shared a high correlation of genetic similarity with those from humans, highlighting the potential links that exist among the strains recovered from different sources in Shanghai. [ABSTRACT FROM AUTHOR]

Withering is a necessary step to improve the flavors during the manufacturing of black tea. Fresh tea leaves of Fuding Dabai were subjected to withering (kept for 0–28 h at room temperature of 25 °C) to observe corresponding morphological changes. In addition, dynamic changes in proteinaceous amino acids, especially taste-related proteinaceous amino acids and their corresponding driving proteins, were investigated using targeted metabolomics and data-independent acquisition (DIA) proteomics. The results indicated that tea leaves gradually withered and shrunk, and their color deepened with the extension of withering time. Furthermore, the contents of umami amino acids were always higher during the withering process. Sweet and bitter amino acids exhibited a significant cumulative effect at the middle and late withering stages. A total of 31 driving proteins were detected that were involved in the metabolic regulation of Ser, Thr, Phe, Trp, and His amino acids. The functional analysis of 776 differential expressed proteins revealed that the tea leaf cells maintained the maximum possible cellular activity during the withering process, and the toxins were decomposed at the end of withering. These findings can provide the metabolic basis for room temperature withering during black tea processing to further enhance the quality of tea. • Targeted metabolomics can reveal the profile of proteinaceous amino acids in black tea during withering. • Data-independent, acquisition-based quantitative proteome profiling of black tea was performed during withering. • A combination of metabolomics and proteomics can decipher the driving proteins of sweet and bitter amino acids. [ABSTRACT FROM AUTHOR]