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Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones. [ABSTRACT FROM AUTHOR]

Background: Anthocyanins are the most important compounds for nutritional quality and economic values of blood orange. However, there are few reports on the pre-harvest treatment accelerating the accumulation of anthocyanins in postharvest blood orange fruit. Here, we performed a comparative transcriptome and metabolomics analysis to elucidate the underlying mechanism involved in seasonal drought (SD) treatment during the fruit expansion stage on anthocyanin accumulation in postharvest 'Tarocco' blood orange fruit. Results: Our results showed that SD treatment slowed down the fruit enlargement and increased the sugar accumulation during the fruit development and maturation period. Obviously, under SD treatment, the accumulation of anthocyanin in blood orange fruit during postharvest storage was significantly accelerated and markedly higher than that in CK. Meanwhile, the total flavonoids and phenols content and antioxidant activity in SD treatment fruits were also sensibly increased during postharvest storage. Based on metabolome analysis, we found that substrates required for anthocyanin biosynthesis, such as amino acids and their derivatives, and phenolic acids, had significantly accumulated and were higher in SD treated mature fruits compared with that of CK. Furthermore, according to the results of the transcriptome data and weighted gene coexpression correlation network analysis (WGCNA) analysis, phenylalanine ammonia-lyase (PAL3) was considered a key structural gene. The qRT-PCR analysis verified that the PAL3 was highly expressed in SD treated postharvest stored fruits, and was significantly positively correlated with the anthocyanin content. Moreover, we found that other structural genes in the anthocyanin biosynthesis pathway were also upregulated under SD treatment, as evidenced by transcriptome data and qRT-PCR analysis. Conclusions: The findings suggest that SD treatment promotes the accumulation of substrates necessary for anthocyanin biosynthesis during the fruit ripening process, and activates the expression of anthocyanin biosynthesis pathway genes during the postharvest storage period. This is especially true for PAL3, which co-contributed to the rapid accumulation of anthocyanin. The present study provides a theoretical basis for the postharvest quality control and water-saving utilization of blood orange fruit. [ABSTRACT FROM AUTHOR]

Background: Anthocyanins are the most important compounds for nutritional quality and economic values of blood orange. However, there are few reports on the pre-harvest treatment accelerating the accumulation of anthocyanins in postharvest blood orange fruit. Here, we performed a comparative transcriptome and metabolomics analysis to elucidate the underlying mechanism involved in seasonal drought (SD) treatment during the fruit expansion stage on anthocyanin accumulation in postharvest 'Tarocco' blood orange fruit. Results: Our results showed that SD treatment slowed down the fruit enlargement and increased the sugar accumulation during the fruit development and maturation period. Obviously, under SD treatment, the accumulation of anthocyanin in blood orange fruit during postharvest storage was significantly accelerated and markedly higher than that in CK. Meanwhile, the total flavonoids and phenols content and antioxidant activity in SD treatment fruits were also sensibly increased during postharvest storage. Based on metabolome analysis, we found that substrates required for anthocyanin biosynthesis, such as amino acids and their derivatives, and phenolic acids, had significantly accumulated and were higher in SD treated mature fruits compared with that of CK. Furthermore, according to the results of the transcriptome data and weighted gene coexpression correlation network analysis (WGCNA) analysis, phenylalanine ammonia-lyase (PAL3) was considered a key structural gene. The qRT-PCR analysis verified that the PAL3 was highly expressed in SD treated postharvest stored fruits, and was significantly positively correlated with the anthocyanin content. Moreover, we found that other structural genes in the anthocyanin biosynthesis pathway were also upregulated under SD treatment, as evidenced by transcriptome data and qRT-PCR analysis. Conclusions: The findings suggest that SD treatment promotes the accumulation of substrates necessary for anthocyanin biosynthesis during the fruit ripening process, and activates the expression of anthocyanin biosynthesis pathway genes during the postharvest storage period. This is especially true for PAL3, which co-contributed to the rapid accumulation of anthocyanin. The present study provides a theoretical basis for the postharvest quality control and water-saving utilization of blood orange fruit. [ABSTRACT FROM AUTHOR]

Some risky multi-criteria group decision making problems include payoff and probability information. To deal with these problems, this study introduces a large scale multi-criteria group decision making model based on focus theory of choice. In this model, a group of experts' linguistic evaluations on multiple criteria are first collected to form linguistic distributions. The positive foci of the linguistic distributions are computed and aggregated into the alternatives' scores. It is noted that in this process the linguistic terms and probabilities are aggregated by using different rules. The positive foci of the alternatives' scores are computed and the optimal alternative is selected. A pollution treatment evaluation problem is solved by using the proposed model, and simulation experiments and comparative analysis are given. [ABSTRACT FROM AUTHOR]

Some practical decision making problems need complex preferences. This study deals with a multi-criteria group decision making problem with preference approval structures (PASs). Each decision maker provides multi-criteria assessments in the form of linguistic distributions and a PAS of the alternatives. To ensure that the alternatives' scores computed from the multi-criteria assessments violate the ranking and approval information in the PAS to the least extent, an optimization model is constructed, and the minimum violation value is obtained. The maximum personalized individual semantics (PISs) and the minimum PISs of linguistic terms corresponding to the minimum violation value are obtained. By using the maximum and the minimum PISs of the linguistic terms, the ranking of the alternatives' scores is obtained. The approval information of the alternatives is obtained from an optimization model. Based on the ranking and approval information of the alternatives, two sequences of PASs corresponding to the maximum and the minimum PISs are obtained. An optimization model is proposed to fuse individual PASs into a collective PAS. A multi-criteria group decision making model is then proposed and applied in an example. Finally a comprehensive comparison analysis is presented to show the feasibility of the model. • Consider an MCGDM with Multi-criteria assessments and PASs. • Propose the minimum and the maximum PISs of linguistic terms. • Propose an optimization model to fuse individual PASs. [ABSTRACT FROM AUTHOR]

Background: Abnormal activation of NLRP3 inflammasome is related to a series of inflammatory diseases, including type 2 diabetes, gouty arthritis, non-alcoholic steatohepatitis (NASH), and neurodegenerative disorders. Therefore, targeting NLRP3 inflammasome is regarded as a potential therapeutic strategy for many inflammatory diseases. A growing number of studies have identified tanshinone I (Tan I) as a potential anti-inflammatory agent because of its good anti-inflammatory activity. However, its specific anti-inflammatory mechanism and direct target are unclear and need further study. Methods: IL-1β and caspase-1 were detected by immunoblotting and ELISA, and mtROS levels were measured by flow cytometry. Immunoprecipitation was used to explore the interaction between NLRP3, NEK7 and ASC. In a mouse model of LPS-induced septic shock, IL-1β levels in peritoneal lavage fluid and serum were measured by ELISA. Liver inflammation and fibrosis in the NASH model were analyzed by HE staining and immunohistochemistry. Results: Tan I inhibited the activation of NLRP3 inflammasome in macrophages, but had no effect on the activation of AIM2 or NLRC4 inflammasome. Mechanistically, Tan I inhibited NLRP3 inflammasome assembly and activation by targeting NLRP3-ASC interaction. Furthermore, Tan I exhibited protective effects in mouse models of NLRP3 inflammasome-mediated diseases, including septic shock and NASH. Conclusions: Tan I specifically suppresses NLRP3 inflammasome activation by disrupting the association of NLRP3 and ASC, and exhibits protective effects in mouse models of LPS-induced septic shock and NASH. These findings suggest that Tan I is a specific NLRP3 inhibitor and may be a promising candidate for treating NLRP3 inflammasome-related diseases. [ABSTRACT FROM AUTHOR]

At present, some studies have combined federated learning with blockchain, so that participants can conduct federated learning tasks under decentralized conditions, sharing and aggregating model parameters. However, these schemes do not take into account the trusted supervision of federated learning and the case of malicious node attacks. This paper introduces the concept of a trusted computing sandbox to solve this problem. A federated learning multi-task scheduling mechanism based on a trusted computing sandbox is designed and a decentralized trusted computing sandbox composed of computing resources provided by each participant is constructed as a state channel. The training process of the model is carried out in the channel and the malicious behavior is supervised by the smart contract, ensuring the data privacy of the participant node and the reliability of the calculation during the training process. In addition, considering the resource heterogeneity of participant nodes, the deep reinforcement learning method was used in this paper to solve the resource scheduling optimization problem in the process of constructing the state channel. The proposed algorithm aims to minimize the completion time of the system and improve the efficiency of the system while meeting the requirements of tasks on service quality as much as possible. Experimental results show that the proposed algorithm has better performance than the traditional heuristic algorithm and meta-heuristic algorithm. [ABSTRACT FROM AUTHOR]

Multitask emergency logistics planning is a complex optimization problem in practice. When a disaster occurs, relief materials or rescue teams should be dispatched to destinations as soon as possible. In a nutshell, the problem can be described as an optimization of multipoint-to-multipoint transportation delivery problem in a given multimodal traffic network. In this study, a multimodal traffic network is considered for emergency logistics transportation planning, and a mixed-integer programming (MIP) formulation is proposed to model the problem. In order to solve this model, we propose a two-layer solution method. The inner layer is to manage the single-task route recommendation, for which we develop a shortest-path algorithm with the multimodal traffic network. Here, the optimal substructure of the algorithm and its time complexity are presented. With the route of each task calculated by the single-task solver, a general optimization algorithm based on improved particle swarm optimization (PSO) is proposed at the outer layer to coordinate the execution of each task constrained by the limited transportation capacity, so as to derive solutions for multi-commodity emergency logistics planning. Extensive computational results show that the proposed method can find solutions of good quality in reasonable time. Meanwhile, through the sensitivity analysis of the algorithm, we find the appropriate parameters for general optimization algorithm to solve the problem proposed in this paper. The proposed approach is effective and practical for solving multitask emergency logistics planning problem under multimodal transportation, which can find a satisfactory solution in an acceptable time. [ABSTRACT FROM AUTHOR]

With the rapid development of flexible wearable devices, various polymer hydrogels have gained immense progress due to their adjustable mechanical properties, high conductivity, super sensitivity, good biocompatibility and adaptable wearability. Lignosulfonate (LS), generating from the sulfite pulping industry, was emerged as a promising filler in polymer hydrogels with great potential for multifunctional wearable electronics. Herein, we comprehensively review the latest research progress associated with LS-based hydrogels. Firstly, the function mechanism of lignosulfonate in diverse polymer hydrogels was introduced in detail. Then, the rational design strategies of LS filled multifunctional hydrogels was summarized as toughening filler, adhesive agent, conductive filler dispersant, UV protectant and catalysts. Finally, the future development of LS filled hydrogel for flexible wearable electronics was proposed. [ABSTRACT FROM AUTHOR]

The majority of neutron spectrometers designated for use in the China Spallation Neutron Source (CSNS) rely on position-sensitive detectors that utilize Helium-3 tube detector technology. To minimize the impact of air on neutron scattering experiments, detectors must be located inside a vacuum chamber. For these types of spectrometers, it is also advisable to house the readout electronics within the vacuum chamber to limit the number of feed-through cables required and enhance the signal-to-noise ratio. This paper proposes an application-specific integrated circuit (ASIC) dedicated to position-sensitive Helium-3 tube detectors, including front-end amplification, shaping module and readout driving buffer. The 8-channel chip, named HEROCV1 (HE lium-3 R ead O ut C ircuits), achieves an input dynamic range from 10 fC to 1 pC, with a counting rate of up to 100 kHz. The equivalent noise charge (ENC) measurement is 1297e-@15pF, and the power consumption is less than 9.9 mW per channel. The ASIC has replaced the traditional front-end circuit based on discrete components, fundamentally addressing the issue of front-end power consumption and enabling the entire detector system to operate in a vacuum environment. [ABSTRACT FROM AUTHOR]

The usage of normal alumina supports brings the uncertain and undesirable aluminum transformation to the high-silica zeolite membranes to reduce Si/Al ratio in framework. In this current study, a novel aluminum-free silica carbide (SiC) monolithic support is used for the synthesis of SSZ-13 membranes with enhanced Si/Al ratio for the first time. Moreover, this high-porosity and monolithic SiC support enables membrane to increase gas permeance and surface-to-volume ratio. High-quality SSZ-13 membranes were prepared after rational modification of synthesis parameters such as synthesis temperature and time and support material. The effects of test temperature, pressure drop, feed flow rate and humidity on separation performance of the monolithic membranes were studied. The formation mechanism of SSZ-13 membrane was also investigated. The Si/Al ratio and CO 2 permeance of SSZ-13 membranes on SiC monolith were 100% and 60% higher than that of membrane on alumina monolith, respectively. This monolithic membrane had comparable separation performance but about 2.3 times higher surface-to-volume ratios to the reported tubular zeolite membranes. This solution could be suitable to prepare other high-silica and all-silica zeolite membranes. [Display omitted] • Uniform large-area SSZ-13 membranes were fabricated on novel SiC monolith. • CO 2 permeance is 50% higher than that of membrane on alumina monolith. • Si/Al ratio of zeolite membrane on SiC support is twice of that on alumina one. • The resistance to humidity increases compared with that of membrane on alumina support. • Surface-to-volume ratio of monolithic membrane is 2.3 times higher than that of tubular one. [ABSTRACT FROM AUTHOR]

[Display omitted] • We present a novel fabrication technique for binder-free spherical granular carbon materials derived from starch. • The resulting sample exhibits outstanding performance in selectively sieving propylene from propane. • Its C 3 H 6 /C 3 H 8 selectivity reaches as high as 33.6 with C 3 H 6 uptake of 2.21 mmol/g at 298 K. • High temperature causes carbon materials to gradually graphitize, resulting in sub-angstrom pore shrinkage. • Mechanism of C 3 H 6 /C 3 H 8 adsorption on SGCs was revealed by molecular simulations. The development of new spherical granular carbon materials with excellent selectivity for the separation of propylene (C 3 H 6) and propane (C 3 H 8) is of great importance in the petrochemical industry, but remains a significant challenge due to the closely similar molecular sizes and physical property of propylene and propane. Herein, we present a novel approach to fabricate binder-free granular carbon materials exhibiting outstanding selectivity towards C 3 H 6 , while also elucidating the evolution of pore structure during the preparation process of these carbon materials. A mixture of starch and molasses was selected as carbon source, and subsequently, novel spherical granular carbon materials (SGCs) were successfully fabricated through the processes of rolling forming, pyrolysis activation and carbonization. The resulting samples were characterized and tested for separation of C 3 H 6 and C 3 H 8. These samples exhibit exceptional selectivity toward C 3 H 6. Its C 3 H 6 /C 3 H 8 selectivity reaches as high as 33.6 with C 3 H 6 uptake of 2.21 mmol/g at 298 K and 100 kPa. Breakthrough experiments confirmed its excellent dynamical separation performance, achieving complete separation of C 3 H 6 /C 3 H 8 binary mixtures. In addition, the evolutionary mechanism of the pore structure in the samples SGCs is elucidated, revealing that the microstructure of starch-based carbon materials gradually evolves towards graphitization at elevated temperature, causing shrinkage of pores at sub-angstrom level. This work presents a distinctive and promising approach for fabricating spherical granular carbon materials, and the resulting samples SGCs demonstrate great potential for industrial applications in separation of C 3 H 6 and C 3 H 8. [ABSTRACT FROM AUTHOR]

• An LD closest to an incomplete FLE is computed by optimization models. • The PISs of HFLTSs in an FLPR are computed. • Consistency and consensus of an FLPR are considered. In group decision making, flexible linguistic preference relations (FLPRs) are very useful with the pairwise comparisons taking the form of flexible linguistic expressions (FLEs). Due to the fact that different decision makers have different understandings of words, this paper investigates the personalized individual semantics (PISs) of the linguistic information in FLPRs. Two optimization models are constructed to compute a linguistic distribution which is closest to an incomplete FLE. The FLPRs are transformed into fuzzy preference relations by using optimization models which maximize consistency and consensus of the fuzzy preference relations. The PISs of linguistic terms and subsets of the linguistic term set are obtained in this process. A group decision making model based on FLPRs is presented and a green supplier selection problem in automotive industry is solved by using the proposed model. The comparative analysis is presented to show the feasibility of the group decision making model. [ABSTRACT FROM AUTHOR]

Ensuring the safety of workers and machinery during operations is a critical task in the construction sites. However, an inevitable circumstance in construction sites is the complex and dynamic environment, which often leads to occlusions. When detecting occluded objects in construction sites, general vision-based approaches tend to exhibit lower accuracy and may even miss detections, resulting in potential safety hazards. To handle this issue, this paper proposes a vision-based approach for detecting occluded objects in construction sites. Firstly, the proposed detection algorithm adopts the state-of-the-art YOLOv7 as its backbone. To enhance its capability in capturing contextual information of occluded objects, a novel channel attention mechanism is employed. Then, a design scheme for the detector head is provided by integrating a novel loss function Scylla-Intersection over Union (SIoU) and the non-maximum suppression (NMS) strategy. With the help of the loss function SIoU, the network can compute the loss values of occluded objects more accurately. To ensure that the network can select the right predicted box which closely aligns with the ground truth, the Euclidean distance is utilized as spatial penalty factor during the NMS stage. By implementing these two strategies, the proposed method can preserve both the category information and bounding boxes of occluded objects, which makes them possible to be detected. Finally, detailed experiments are done to verify the proposed method. Experimental results demonstrate that the proposed method has the potential for improving the detection accuracy. Moreover, it shows a better performance in detecting occluded objects in the dynamic construction sites compared to the existing baselines. [ABSTRACT FROM AUTHOR]

The engineering design of cemented paste backfill (CPB) typically relies on technical data obtained from tests conducted on CPB samples cured under conventional laboratory conditions. However, these methods often fall short in capturing the complex multiaxial stress curing conditions that CPB masses experience in many underground mines, particularly in deep underground mines. In these mining environments, CPB is subjected to multi-axial stress conditions during the curing process that are challenging to replicate in a controlled laboratory setting. No lab-scale apparatus can currently accurately reproduce these actual field multiaxial stress conditions, especially the intricate interplay of horizontal rockwall closure stresses, vertical self-weight stress, and overburden stresses from upper layers. Moreover, the impact of these conditions on the key engineering properties of CPB is unknown. To address this significant challenge and technology gap, this study has developed a new apparatus for curing and monitoring CPB under realistic multiaxial compressive loading conditions, simulating the complex stress environment encountered in underground mines. The developed apparatus was then utilized to assess the impact of multiaxial stress curing conditions, including vertical stress and horizontal stresses induced by rockwall closures, on key engineering properties (strength, deformation behaviour, self-desiccation) of CPB at early ages. The research results clearly indicate that the application of multiaxial stresses leads to a significant enhancement in the mechanical and physical properties of CPB. This enhancement is supported by observable densification of the pore structure in CPB subjected to multiaxial compressive stresses. In addition, a comprehensive analysis of deformation and strain patterns establishes a direct correlation between multiaxial stresses and the progressive increase in stiffness and hardness of CPB over time. Furthermore, the evolution of matric suction and degree of saturation provides compelling evidence of the significant impact of multiaxial stresses on pore water consumption or self-desiccation. The development of this new apparatus fills a substantial void in CPB research capabilities. Furthermore, the results obtained provide a better understanding of the complex behavior of CPB in multi-stress loading environments, paving the way for the design and optimization of backfill solutions that effectively address the unique challenges posed by deep underground mining operations. • A new apparatus for backfill curing under field multiaxial stress conditions developed. • Multiaxial curing stresses enhance cemented backfill strength and density. • Backfill pore structure is refined by field multiaxial stress conditions. • Start of self-desiccation is delayed by multiaxial stress conditions. • Correlation between multiaxial stresses and increase in stiffness and hardness exists. [ABSTRACT FROM AUTHOR]

[Display omitted] • Pilot-scale SSZ-13 membranes were used for field test of CO 2 removal of biogas for the first time. • Ten SSZ-13 membranes displayed average CO 2 permeance of 2100 GPU and average CO 2 /CH 4 selectivity of 103. • Increasing the feed flow rate reduces the effect of concentration polarization. Large-area SSZ-13 membranes were reproducibly prepared on 50-cm-long commercial and alumina tubes by secondary growth. Separation performance of the long membranes were higher than that of most small-area membranes. The effects of operation parameters such as pressure, temperature, feed flow rate and CO 2 concentration on the separation performance of membranes were investigated. A mathematic model for concentration polarization index was established to evaluate the extent of concentration polarization in the single-tube and the muti-module test. A separation system with four single-tube modules connected in series was applied to field test of real biogas. The biogas could be purified to pipeline-grade natural gas (>98 mol%) by this small system at feed flow rate of 12 standard liter per minute at 1.4 MPa pressure drop. The membrane displayed long-term stability in the wet and dry biogas. This work has made an important progress toward the industrialization of zeolite membranes for gas separation. [ABSTRACT FROM AUTHOR]

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility. [ABSTRACT FROM AUTHOR]

Current understanding holds that Klinefelter syndrome (KS) is not inherited, but arises randomly during meiosis. Whether there is any genetic basis for the origin of KS is unknown. Here, guided by our identification of some USP26 variations apparently associated with KS, we found that knockout of Usp26 in male mice resulted in the production of 41, XXY offspring. USP26 protein is localized at the XY body, and the disruption of Usp26 causes incomplete sex chromosome pairing by destabilizing TEX11. The unpaired sex chromosomes then result in XY aneuploid spermatozoa. Consistent with our mouse results, a clinical study shows that some USP26 variations increase the proportion of XY aneuploid spermatozoa in fertile men, and we identified two families with KS offspring wherein the father of the KS patient harbored a USP26‐mutated haplotype, further supporting that paternal USP26 mutation can cause KS offspring production. Thus, some KS should originate from XY spermatozoa, and paternal USP26 mutations increase the risk of producing KS offspring. Synopsis: Klinefelter syndrome (KS) is believed to be not inherited, and whether there is a genetic basis for the origin of KS is unknown. Here, paternal USP26 mutations are found to produce XY spermatozoa, thus greatly increase the risk for producing KS offspring.Whole‐genome sequencing‐based mutational scanning in KS patients shows that USP26 variants are likely to affect the etiology of KS.Loss of Usp26 in male mice results in the production of 41, XXY offspring.The disruption of Usp26 causes incomplete sex chromosome pairing by destabilizing TEX11, thus producing XY aneuploid spermatozoa.Paternal USP26 mutations increase the proportion of XY aneuploid sperm and cause KS offspring production. [ABSTRACT FROM AUTHOR]

To meet the standards of effluent quality in wastewater treatment processes (WWTPs), a dynamic concurrent kernel partial least squares (DCKPLS) method is proposed for process monitoring. After integrating the augmented matrices and kernel technique, the proposed method can be used to handle the dynamic and nonlinear characteristics of WWTP data simultaneously. Besides, the inherent limitation of PLS decomposition can be overcome by DCKPLS model, which concurrently partitions the feature space data and output variables into five subspaces. Monitoring performance is evaluated by simulated sensor faults of industrial WWTP data. Specifically, the fault detection rates of bias fault and drifting fault using DCKPLS are increased by 22.65 % and 8.06 %, respectively, in comparison with CKPLS. It is also shown that the DCKPLS model provides better monitoring performance than the other counterparts. [ABSTRACT FROM AUTHOR]

As a green and renewable nanomaterial, cellulose nanocrystals (CNC) have received numerous attention due to the unique structural features and superior physicochemical properties. Conventionally, CNC was isolated from lignocellulosic biomass mostly depending on sulfuric or hydrochloric acid hydrolysis. Although this approach is effective, some critical issues such as severe equipment corrosion, excessive cellulose degradation, serious environmental pollution, and large water usage are inevitable. Fortunately, solid acid hydrolysis is emerging as an economical and sustainable CNC production technique and has achieved considerable progress in recent years. Herein, the preparation of CNC by solid acid hydrolysis was summarized systematically, including organic solid acids (citric, maleic, oxalic, tartaric, p-toluenesulfonic acid) and inorganic solid acids (phosphotungstic, phosphoric, and Lewis acid). The advantages and disadvantages of organic and inorganic solid acid hydrolysis methods were evaluated comprehensively. Finally, the challenges and opportunities in the later exploitation and application of solid acid hydrolysis to prepare CNC in the industrial context are discussed. Considering the future development of this technology in the large-scale CNC production, much more efforts should be made in lowering CNC processing cost, fabricating high-solid-content and re-dispersible CNC, developing value-added applications of CNC, and techno-economic analysis and life cycle assessment on the whole process. [Display omitted] • Sustainable solid acid hydrolysis processes for the preparation of CNC are analyzed and summarized. • Preparation methods include organic solid acid hydrolysis and inorganic solid acid hydrolysis. • Advantages and disadvantages of organic and inorganic solid acid hydrolysis methods are evaluated. • Key knowledge gaps for the sustainable and economically feasible preparation of CNC are proposed. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to provide an automatic parallelization toolkit for unstructured mesh-based computation. Among all kinds of mesh types, unstructured meshes are dominant in engineering simulation scenarios and play an essential role in scientific computations for their geometrical flexibility. However, the high-fidelity applications based on unstructured grids are still time-consuming, no matter for programming or running. Design/methodology/approach: This study develops an efficient UNstructured Acceleration Toolkit (UNAT), which provides friendly high-level programming interfaces and elaborates lower level implementation on the target hardware to get nearly hand-optimized performance. At the present state, two efficient strategies, a multi-level blocks method and a row-subsections method, are designed and implemented on Sunway architecture. Random memory access and write–write conflict issues of unstructured meshes have been handled by partitioning, coloring and other hardware-specific techniques. Moreover, a data-reuse mechanism is developed to increase the computational intensity and alleviate the memory bandwidth bottleneck. Findings: The authors select sparse matrix-vector multiplication as a performance benchmark of UNAT across different data layouts and different matrix formats. Experimental results show that the speed-ups reach up to 26× compared to single management processing element, and the utilization ratio tests indicate the capability of achieving nearly hand-optimized performance. Finally, the authors adopt UNAT to accelerate a well-tuned unstructured solver and obtain speed-ups of 19× and 10× on average for main kernels and overall solver, respectively. Originality/value: The authors design an unstructured mesh toolkit, UNAT, to link the hardware and numerical algorithm, and then, engineers can focus on the algorithms and solvers rather than the parallel implementation. For the many-core processor SW26010 of the fastest supercomputer in China, UNAT yields up to 26× speed-ups and achieves nearly hand-optimized performance. [ABSTRACT FROM AUTHOR]

A dynamic kernel extreme learning machine (DKELM) is proposed for wastewater treatment modeling by introducing dynamic technique and kernel function into ELM. It could achieve better prediction performance than conventional modeling methods. • Dynamic kernel extreme learning machine (DKELM) is proposed for a wastewater treatment process. • Dynamic technique is used to obtain time-varying characteristics in processes. • Kernel function is adopted to improve the generalization ability of the model. • DKELM achieves better prediction performance than conventional modeling methods. Papermaking wastewater accounts for a large proportion of industrial wastewater, and it is essential to obtain accurate and reliable effluent indices in real-time. Considering the complexity, nonlinearity, and time variability of wastewater treatment processes, a dynamic kernel extreme learning machine (DKELM) method is proposed to predict the key quality indices of effluent chemical oxygen demand (COD). A time lag coefficient is introduced and a kernel function is embedded into the extreme learning machine (ELM) to extract dynamic information and obtain better prediction accuracy. A case study for modeling a wastewater treatment process is demonstrated to evaluate the performance of the proposed DKELM. The results illustrate that both training and prediction accuracy of the DKELM model is superior to other models. For the prediction of the quality indices of effluent COD, the determinate coefficient of the DKELM model is increased by 27.52 %, 21.36 %, 10.42 %, and 10.81 %, compared with partial least squares, ELM, dynamic ELM, and kernel ELM, respectively. [ABSTRACT FROM AUTHOR]

Ischemic stroke is one of the most intractable diseases of the central nervous system and is also a major cause of mortality and disability in adult humans. Unfortunately, current therapies target vessel recanalization, which has a narrow treatment window, and the potential adverse effects lead to a low rate of clinical employment; in addition, neuroprotective strategies are not effective for stroke treatment. It is necessary to discover new approaches to develop neuroprotective, neuroregenerative treatment strategies for stroke. At present, accumulating evidence suggests that adult neurogenesis is a novel topic with extensive research on its potential to be harnessed for therapy in various neurologic disorders, and the neurogenesis capacity in the subventricular zone was shown to be increased in response to brain ischemic stroke. In this review, we describe the cellular and molecular mechanisms underlying potential adult neurogenesis and review current preclinical and clinical cell-based therapies for enhancing neural regeneration after adult ischemic stroke. Although stroke-induced neurogenesis in humans does not seem to translate to neurofunctional recovery, we also summarize factors of potential treatment strategies with transplanted cells, including transplantation time, cell dosage, and administration route, to achieve optimum and effective cell-based therapy, thereby harnessing this neuroregenerative response to improve neurofunctional recovery after ischemic stroke. [ABSTRACT FROM AUTHOR]

Silicon has received much attention due to its high theoretical capacity as the electrode of lithium-ion batteries (LIBs). However, the poor stability caused by the volume expansion problem affects the cycle life of batteries, thus severely limiting the application of the silicon anode. In the present work, we engineered silicon nanotubes with hollow-structure to accommodate the volume expansion of silicon and improve the electrochemical stability of lithium ion batteries. Hollow silicon nanotubes were in situ synthesized on carbon cloth (HSiNTs/CC) by reducing silicon oxide and corroding zinc oxide nanorod templates and directly used as the anode of lithium-ion batteries without any binders or conductive additives. The results of electrochemical measurements indicated that HSiNTs/CC exhibits superior LIB performance with excellent cycling stability and good rate capability. At a current density of 100 mA g−1, a reversible capacity of 1420 mA h g−1 was achieved and the fabricated LIB could retain 93.7% of the initial capacity after 100 cycles. Even at a decoupled current density of 1000 mA g−1, the LIB still possesses a capacity of 1026 mA h g−1 and 98.3% capacity retention after 100 cycles. The results demonstrated that the thin hollow structures were well suited to accommodate the volume expansion of silicon and improve the stability of the HSiNTs/CC anode during the lithiation–delithiation cycles, which shines some light on the reasonable design and preparation of silicon anodes for ultra-stable lithium-ion batteries. [ABSTRACT FROM AUTHOR]

• The scopes of hesitant fuzzy linguistic preference relations are introduced. • The best consensus level and the worst consensus level of hesitant fuzzy linguistic preference relations are introduced. • Three consistency and consensus improvement algorithms are introduced for three actual situations. • A group decision making model based on hesitant fuzzy linguistic preference relations is introduced. Hesitant fuzzy linguistic preference relations (HFLPRs) are commonly used by decision makers when they are hesitant to express preferences. The use of HFLPRs in group decision-making (GDM) requires that the consistency of each HFLPR and consensus of the HFLPRs be acceptable. To ensure the reliability of using HFLPRs in GDM, a novel GDM model based on HFLPRs integrating the consistency and consensus improvement process is introduced. First, some novel consistency and consensus improvement methods by using an optimization technique are proposed for three actual cases: (1) the decision makers refuse to modify their opinions and the problem is without time pressure; (2) the decision makers are willing to modify their opinions and the problem is without time pressure; (3) the decision-making problem is under time pressure. For the former two cases, two iterative consistency and consensus improvement methods are introduced, and, for the last case, a method based on optimization models is introduced to modify the decision makers' weights. A novel GDM model is given based on the proposed methods. Finally, an example is solved by using the proposed GDM model, and a comparison analysis is given. [ABSTRACT FROM AUTHOR]

BACKGROUND: For the treatment of intertrochanteric fracture in elderly patients, if there is no operative contraindication, surgical treatment is recommended. Operative methods include internal fixation and joint replacement. Surgical techniques are mature, but the choice of surgical methods is controversial. OBJECTIVE: To compare the efficacy of artificial femoral head arthroplasty and proximal femoral nail antirotation in elderly patients with injured lateral wall femoral intertrochanteric fracture so as to provide the basis of clinical method selection and to provide the original data for the systematic analysis of large sample. METHODS: According to the case criterion, 48 cases of AO classification of type A2.2, A2.3 intertrochanteric fractures were selected in Department of Orthopedics, the 71 Group Army Hospital of Chinese PLA from January 2012 to December 2017. They were divided into femoral head arthroplasty group (n=29) and proximal femoral nail antirotation group (n=19). All patients signed the informed consent. This study was approved by the Hospital Ethics Committee. The patients were followed up for 1-3 years. Operation time, bleeding volume, hospitalization expenses, the incidence of complications, and Harris hip score at 1 month and 1 year after the surgery were compared between the two groups. RESULTS AND CONCLUSION: (1) After statistical analysis, operation time was significantly shorter in the femoral head arthroplasty group than in the proximal femoral nail antirotation group (P < 0.05). There was no statistically significant in bleeding volume between the two groups (P > 0.05). The cost of hospitalization was significantly more in the femoral head arthroplasty group than in the proximal femoral nail antirotation group (P < 0.05}. (2) Harris hip score was significantly better in the femoral head arthroplasty group than in the proximal femoral nail antirotation group at 1 month after operation (P < 0.05}. There was no significant difference in Harris hip score between the two groups at 1 year after operation (P > 0.05). (3) There was no significant difference in the incidence of complications between the two groups (P > 0.05}. (4) For the patients over 70 years old with intertrochanteric fracture of injured lateral wall, artificial femoral head replacement has the advantages of early getting out of bed, high quality of life and quick recovery of joint function. It is suggested to choose artificial femoral head replacement first. [ABSTRACT FROM AUTHOR]

Background: The early-life microbiota exerts a profound and lifelong impact on host health. Longitudinal studies in humans have been informative but are mostly based on the analysis of fecal samples and cannot shed direct light on the early development of mucosa-associated intestinal microbiota and its impact on GI function. Using piglets as a model for human infants, we assess here the succession of mucosa-associated microbiota across the intestinal tract in the first 35 days after birth. Results: Although sharing a similar composition and predicted functional profile at birth, the mucosa-associated microbiome in the small intestine (jejunum and ileum) remained relatively stable, while that of the large intestine (cecum and colon) quickly expanded and diversified by day 35. Among detected microbial sources (milk, vagina, areolar skin, and feces of sows, farrowing crate, and incubator), maternal milk microbes were primarily responsible for the colonization of the small intestine, contributing approximately 90% bacteria throughout the first 35 days of the neonatal life. Although maternal milk microbes contributed greater than 90% bacteria to the large intestinal microbiota of neonates upon birth, their presence gradually diminished, and they were replaced by maternal fecal microbes by day 35. We found strong correlations between the relative abundance of specific mucosa-associated microbes, particularly those vertically transmitted from the mother, and the expression levels of multiple intestinal immune and barrier function genes in different segments of the intestinal tract. Conclusion: We revealed spatially specific trajectories of microbial colonization of the intestinal mucosa in the small and large intestines, which can be primarily attributed to the colonization by vertically transmitted maternal milk and intestinal microbes. Additionally, these maternal microbes may be involved in the establishment of intestinal immune and barrier functions in neonates. Our findings strengthen the notion that studying fecal samples alone is insufficient to fully understand the co-development of the intestinal microbiota and immune system and suggest the possibility of improving neonatal health through the manipulation of maternal microbiota. [ABSTRACT FROM AUTHOR]

• A method to compute missing elements of IHFLPRs is introduced. • An additive consistency improvement method of IHFLPRs is proposed. • A GDM model based on IHFLPRs is introduced. Incomplete hesitant fuzzy linguistic preference relations (IHFLPRs) are useful in decision making which combine advantages of hesitant fuzzy linguistic term sets and incomplete fuzzy preference relations. The existing researches on IHFLPRs pay little attention to missing elements, and the consistency improvement processes change original information greatly. Inspired by the worst and the best consistency indexes of hesitant fuzzy linguistic preference relations, this paper constructs several optimization models to calculate the missing elements of IHFLPRs. As a result, a complete hesitant fuzzy linguistic preference relation is obtained. Furthermore, an algorithm is introduced to improve the additive consistency of the hesitant fuzzy linguistic preference relation to an acceptable level. Finally a group decision making model based on IHFLPRs is introduced and an example is presented. [ABSTRACT FROM AUTHOR]

Coccidiosis, caused by the infection of Eimeria parasites, is one of the most common diseases in domestic rabbits. Live anticoccidial vaccine formulated with attenuated precocious lines of pathogenic eimerian parasites is expected to be valuable for the control of rabbit coccidiosis as a similar strategy to produce anticoccidial vaccines against chicken coccidiosis has being used for several decades. Eimeria media, moderate pathogenic, is widespread in China. Therefore, attenuated anticoccidial vaccines against rabbit coccidiosis should contain vaccine strain(s) of E. media. In this study, a precocious line of E. media (Empre) was selected by collecting and propagating the early excreted oocysts with 16 successive generations. The prepatent period of Empre reduced from 108 h of its parental strain (Emwt) to 70 h. The fecundity of Empre was about 1/10 to 1/3 lower than that of Emwt. Each sporocyst of Empre sporulated oocyst contained only one large refractile body instead of two smaller ones seen in the parental strain. When vaccinated with 1 × 103 or 1 × 104 precocious line oocysts, the rabbits were completely protected against homologous challenge with the parental strain 14 days post challenge by terms of body weight gain and oocyst output counting, indicating the efficacy of Empre. Meanwhile, all immunized rabbits showed no clinical sign post immunization, indicating the safety of Empre. For co-immunization, 1 × 103Empre oocysts and 5 × 102 oocysts of a precocious line of E. intestinalis (EIP8) were inoculated to each rabbit in a trial. No diarrhea or mortality was found after vaccination, and the weight gains of the vaccinated group were similar to that of unvaccinated-unchallenged control (UUC) group, while the weight gains of the vaccinated group were similar to that of unvaccinated-unchallenged control (UUC) group (P > 0.05), but significantly higher than that of UCC group (P < 0.01) after challenge, indicating it is safe and effective when using co-immunization. These results together show that Empre, as a precocious line, is a good candidate of precocious line of E. media for anticoccidial vaccine development. [ABSTRACT FROM AUTHOR]

Nowadays, nanocellulose production processes with numerous merits of green, eco-friendly, and cost-effective are in urgent need. Acidic deep eutectic solvent (ADES), as an emerging green solvent, has been widely applied in the preparation of nanocellulose over the past few years, owing to its unique advantages, including non-toxicity, low cost, easy synthesis, recyclability, and biodegradability. At present, several studies have explored the effectiveness of ADESs in nanocellulose production, particularly those based on choline chloride (ChCl) and carboxylic acids. Various acidic deep eutectic solvents have been employed, with representative ones such as ChCl-oxalic/lactic/formic/acetic/citric/maleic/levulinic/tartaric acid. Herein, we comprehensively reviewed the latest progress of these ADESs, focusing on the treatment procedures and key superiorities. In addition, the challenges and outlooks of ChCl/carboxylic acids-based DESs implementation in the fabrication of nanocellulose were discussed. Finally, some suggestions were proposed to advance the industrialization of nanocellulose, which would help for the roadmap of sustainable and large-scale production of nanocellulose. [ABSTRACT FROM AUTHOR]

Multidistance is an extension of conventional distance and is used to measure distance for more than two points. It has been applied to some practical problems since its appearance. In order to enrich the family of multidistances and facilitate further applications of multidistances, a new multidistance based on the generalized OWA (GOWA) operator is introduced in this paper. Some of its properties, including regularity, stability, strong multidistance, super-additivity, homogeneity, are investigated. A power average operator is then proposed, whose support function is calculated by using the proposed GOWA-based multidistance. A numerical example is then presented to show the performance of this operator. [ABSTRACT FROM AUTHOR]

Highlights • Concentration-discharge (C-Q) dynamics may vary across alternative time-scales. • Anthropogenic inputs and stormflow were investigated by using C-Q approach. • Temporal relationships between fertilizer input and watershed flux were identified. Abstract Impacts of agricultural activities and hydrologic variables on nitrogen (N) loads have been investigated previously, but interactions among these factors are still poorly addressed across alternative time-scales. The concentration-discharge (C-Q) dynamics at short time-scales could be useful to disentangle the impacts of agricultural activities because it can provide more information about the interaction between N export and input. In this study, total dissolved N (TDN) concentrations/fluxes-discharge dynamics across different time-scales (annual, daily and hourly) were used to investigate the potential influences of agricultural activities and the interaction with hydrologic variables. At the long-term scale, streamflow and instream TDN concentrations exhibited the same inter-annual variations. At daily scale, higher temporal variations of streamflow (compared to instream TDN concentrations) occurred during stormflow-dominated periods. It highlighted the importance that stormflow may have substantial impact over N concentration changes over time. At the smaller time scale, direct influence of fertilizer application on watershed N export was unraveled by the difference in stream TDN concentrations and export fluxes between the early growing period (with more fertilizer application) and the later period (with less). In addition, the differences may increase with increasing flow conditions, which indicated that the impact of agricultural activities could be affected by hydrologic variables. These findings provide important information for improved best management practices (BMPs) to reduce N pollution from nonpoint sources (NPS). [ABSTRACT FROM AUTHOR]

Abstract The effects of long-term animal manure application and crop straw incorporation on the migration of carbon (C) and nitrogen (N) deep into the soil profile and the associated N leaching risk in particular have not been thoroughly elucidated to date. Soil profile samples were collected from depths of up to 200 cm from the following four treatments in a 27-year field experiment on the North China Plain: N + phosphorus (P) + potassium (K) fertilizers (NPK), NPK + 22.5 t ha−1 swine manure (NPKM), NPK + 33.7 t ha−1 swine manure (NPKM+) and NPK + straw incorporation (NPKS). The results revealed that long-term manure application and straw incorporation significantly enhanced the soil organic C (SOC) and total N (TN) contents in the upper 20 cm and that this effect was weaker in the deeper soil layers (P < 0.05). Residual nitrate-N (NO 3 −-N) contents at 0 to 40 cm and 120 to 200 cm in the NPKM and NPKM+ were 4–16 and 2–9 times higher than those in the NPK and NPKS, respectively. These results indicated a greater potential for N leaching from manure addition and a higher propensity for NO 3 −-N leaching out of the 40–100 cm soil layer. Pearson relationship analysis demonstrated that NO 3 −-N content was clearly affected by SOC and dissolved organic N (DON) contents along the soil profile (20–200 cm), implying that the higher residual NO 3 −-N contents in the deeper soil from manure addition were partially attributable to the mineralization and nitrification of the downward SOC and DON. Interestingly, a low level of residual NO 3 −-N combined with negative mineralization in the 120–200 cm soil layers of the NPKS treatment was observed, suggesting that straw incorporation promotes soil NO 3 −-N retention. Thus, we concluded that long-term manure application is beneficial for soil NO 3 −-N content retention, whereas long-term straw incorporation benefits NO 3 −-N retention. Graphical abstract Unlabelled Image Highlights • Soil organic C and total N contents were significantly enhanced after manure and straw added in the upper 20 cm. • High nitrate-N contents found in deeper soil associated with manure addition may lead to a greater N leaching risk. • Nitrate-N contents did not increase in deeper soil applied with straw N, indicating retention of NO 3 −-N in the soil. • In North China Plain, nitrate-N is readily to lose from the 40–100 cm layer of fluvo-aquic soil. [ABSTRACT FROM AUTHOR]

Recent evidence suggests an association exists between resistance to epigenetic therapy (EGT) and the expression of programmed cell death protein 1 (PD-1) and programmed death-ligand 1 (PD-L1) in myeloid malignancies. Biomarkers are required to predict resistance to EGT in myeloid malignancies, which together with the delineation of associated molecular mechanisms, may provide additional understanding for novel treatment strategies when investigating resistance to EGT. The present study aimed to investigate the in vivo effects of EGT on the expression of PD-1, PD-L1 and orphan nuclear receptor NUR77 with clinical responses in patients with myeloid malignancies. In addition, in vitro and in vivo characterization of the effects of EGT on the expression of NF-κB and Bcl-xL, potential downstream targets of PD-L1 reverse signaling, were evaluated to determine components of the molecular mechanism responsible for these effects. The in vivo effects of EGT on the expression of PD-1, PD-L1 and a previously identified molecular marker of response to EGT, NUR77 was characterized in peripheral blood mononuclear cells (PBMC) from patients with myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) treated with either azacytidine (Aza) alone or a combination of Aza and the histone deacetylase inhibitor (HDACi) LBH-589 during the first cycle of therapy. The correlation of clinical responses to treatment with EGT with the expression of PD-1, PD-L1 and NUR77 demonstrated that the induction of PD-L1 mRNA levels was associated with resistance to EGT despite the concurrent augmentation of NUR77 expression. The characterization of potential downstream effector molecules of reverse PD-L1 signaling identified EGT-mediated induction of Bcl-xL and NF-κB mRNA expression in vitro and in vivo, suggesting a potential anti-apoptotic molecular mechanism was responsible for PD-L1-mediated resistance to EGT. Taken together, these observations suggest that enhanced PD-L1 expression may confer resistance to EGT over known EGT response markers in myeloid malignancies, and provides a potential molecular mechanism involving the modulation of effectors of PD-L1 reverse signaling, which may in-part, be responsible for these effects. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Reducing fertilizer significantly decreased annual TN leaching losses, while maintaining the yield. • Reducing fertilizer increased the downward trend of annual TN leaching factor year by year. • Annual TN leaching losses increased linearly with N input. • Managing irrigation and fertilization to mitigate N leaching. Abstract Nitrogen (N) leaching is an important factor that threatens groundwater safety in intensive greenhouse vegetable production regions. However, managing irrigation and fertilization to reduce nitrate leaching has rarely been carried out in long-term experiments. In this study, N leaching in two typical greenhouse vegetable systems (a cucumber-cucumber system in Shandong and a cucumber-tomato system in Ningxia) from 2008 to 2013 investigated should be studied using a lysimeter monitoring method. The total N fertilization rate was 0 to 2508 kg N ha−1 which included three treatments: no fertilizer (CK: 0 kg N ha-1), conventional treatment (CON: Shandong 2508 kg N ha-1 and Ningxia 2239 kg N ha-1) and reduced fertilizer application (RF: Shandong 2164 kg N ha-1 and Ningxia 1716 kg N ha-1). The irrigation amount was 590–2919 mm year-1 according to vegetable water demand. The results indicated that the annual total N leaching were 344.8 kg ha−1 (192.3–508.3 kg ha−1) in Shandong and 170.7 kg ha−1 (134.9–203.7 kg ha−1) in Ningxia for the CON treatments. Compared with CON treatment, RF significantly decreased ANLL, while simultaneously maintaining the yield and increasing the downward trend of the annual TN leaching factor (ANLF) year by year. Meanwhile, a concomitant annual cost reductions associated with the RF treatment estimated at $187 million USD for Shandong and $20 million USD for Ningxia. ANLL increased linearly with the N input ( p < 0.05). More than half of ANLL came from fertilizer N (including chemical and manure fertilizer) under CON treatments, while more than half of ANLL came from soil and water N under RF treatments. The results indicated that mitigation measures for N leaching pollution from greenhouse vegetable fields should consider regulations on irrigation and fertilization. [ABSTRACT FROM AUTHOR]

Little is known about the mechanisms that regulate the assembly of microbial communities in the river–sea continuum. Here, we performed HiSeq paired‐end sequencing of the V4 region of 18S rRNA gene, using both DNA and RNA extracts, to identify protist communities in the surface and bottom water layers along a transect of the Pearl River–South China Sea Continuum (PSC) during the wet (summer) and dry (winter) seasons. We found that during the summer but not during the winter, protist communities, identified from their DNA or RNA signatures, could be better explained by mass effects and species sorting, respectively. Moreover, protist diversity in the DNA and RNA surveys exhibited similar trends along the transect, that is, a linear upstream‐to‐downstream decrease during the summer and a weakly U‐shaped curve during the winter. In contrast, the taxonomic compositions in the DNA‐ and RNA‐derived communities were remarkably different during either the summer or the winter. In summary, the results of our DNA and RNA surveys revealed the temporal assembly of protist communities in the PSC, which suggests that protist diversity and composition are highly responsive to the hydrographic conditions of the river–sea continuum. [ABSTRACT FROM AUTHOR]

This article proposes a combined principal component analysis (PCA) and local Fisher discriminant analysis (LFDA) scheme to improve the fault diagnosis performance of the indoor air quality (IAQ) measuring devices in subway stations. The combined scheme employs PCA for fault detection step and subsequently utilizes LFDA for diagnosing faulty IAQ sensors. A fault discriminant index based on LFDA discriminant components is proposed for fault diagnosis. Effectiveness of the proposed approach is demonstrated on the IAQ measuring system, where three types of IAQ sensor faults including bias fault, drifting fault, and complete failure fault are involved. Results demonstrate that diagnosing performance of LFDA is better than that of conventional Fisher discriminant analysis. The combined method has the capability of detecting and discriminating the sensor faults in the subway system. [ABSTRACT FROM AUTHOR]

Highlights • Gaussian process regression (GPR) is proposed to predict particulate matter (PM 2.5) in a subway. • Compositional structure of different base kernels of GPR is proposed to model PM 2.5. • GPR with sum of squared-exponential and periodic kernels provides the best modeling performance. • The proposed GPR was compared with other soft sensors including PLS, ANN, and SVM. Abstract Soft sensor modeling of indoor air quality (IAQ) in subway stations is essential for public health. Gaussian process regression (GPR), as an efficient nonlinear modeling method, can effectively interpret the complicated features of industrial data by using composite covariance functions derived from base kernels. In this work, an accurate GPR soft sensor with the sum of squared-exponential covariance function and periodic covariance function is proposed to capture the time varying and periodic characteristics in the subway IAQ data. The results demonstrate that the prediction performance of the proposed GPR model is superior to that of the traditional soft sensors consisting of partial least squares, back propagation artificial neural networks, and least squares support vector regression (LSSVR). More specifically, the values of root mean square error, mean absolute percentage error, and coefficient of determination are improved by 12.35%, 9.53%, and 40.05%, respectively, in comparison with LSSVR. [ABSTRACT FROM AUTHOR]

Application of manure is reported to effectively improve agricultural soil fertility. However, the potential of annual manure applications to increase stocks of soil organic carbon (SOC) and total nitrogen (TN) needs to be better understood. In this study, we evaluated the long-term (1991–2012) effects of various fertilization regimes on crop yield, and SOC and TN in the topsoil (0–20 cm) of a fluvo-aquic soil in a wheat ( Triticum aestivum L.)-maize ( Zea mays L.) cropping system in the North China Plain. The treatments included no N fertilizer (PK), chemical N, P, K fertilizers (NPK), NPK plus 22.5 t ha −1 swine manure (NPKM), and NPK plus 33.75 t ha −1 swine manure (NPKM+). Compared with NPK and PK, both NPKM and NPKM+ significantly increased crop yields, with no significant difference between NPKM and NPKM+. NPKM and NPKM+ treatments had a lower N use efficiency (NUE) than NPK through the whole period and the average NUE were 30.1%, 14.8% and 12.3% in NPK, NPKM and NPKM+ treatments, respectively. Compared with the initial value of 17.2–17.4 Mg C ha −1 and 2.01–2.07 Mg N ha −1 , SOC and TN stocks in NPKM and NPKM+ increased by 94.7–114.2% and 83.0–98.0% over the 22 experimental years, respectively, without any indication of C or N saturation in the soil. Furthermore, TN stock was positively correlated to SOC stock ( P  <  0.01) added with manure, indicating the significance of more organic C input from manure to build up TN pool. In conclusion, long-term application of organic manure in combination with conventional chemical fertilization could increase crop yield and soil C and N stocks in the wheat-maize cropping system of the North China Plain, but it should be noted that large amounts of manure N could also lead to elevated risk of environmental N losses. [ABSTRACT FROM AUTHOR]

The impacts of manure application on soil ammonia (NH 3 ) volatilization and greenhouse gas (GHG) emissions are of interest for both agronomic and environmental reasons. However, how the swine manure addition affects greenhouse gas and N emissions in North China Plain wheat fields is still unknown. A long-term fertilization experiment was carried out on a maize-wheat rotation system in Northern China ( Zea mays L - Triticum aestivum L.) from 1990 to 2017. The experiment included four treatments: (1) No fertilizer (CK), (2) single application of chemical fertilizers (NPK), (3) NPK plus 22.5 t/ha swine manure (NPKM), (4) NPK plus 33.7 t/ha swine manure (NPKM+). A short-term fertilization experiment was conducted from 2016 to 2017 using the same treatments in a field that had been abandoned for decades. The emissions of NH 3 and GHGs were measured during the wheat season from 2016 to 2017. Results showed that after long-term fertilization the wheat yields for NPKM treatment were 7105 kg/ha, which were higher than NPK (3880 kg/ha) and NPKM+ treatments (5518 kg/ha). The wheat yields were similar after short-term fertilization (6098–6887 kg/ha). The NH 3 -N emission factors (EF amm ) for NPKM and NPKM+ treatments (1.1 and 1.1–1.4%, respectively) were lower than NPK treatment (2.2%) in both the long and short-term fertilization treatments. In the long- and short-term experiments the nitrous oxide (N 2 O) emission factors (EF nit ) for NPKM+ treatment were 4.2% and 3.7%, respectively, which were higher than for the NPK treatment (3.5% and 2.5%, respectively) and the NPKM treatment (3.6% and 2.2%, respectively). In addition, under long and short-term fertilization, the greenhouse gas intensities for the NPKM+ treatment were 33.7 and 27.0 kg CO 2 -eq/kg yield, respectively, which were higher than for the NPKM treatment (22.8 and 21.1 kg CO 2 -eq/kg yield, respectively). These results imply that excessive swine manure application does not increase yield but increases GHG emissions. [ABSTRACT FROM AUTHOR]

The release of silver nanoparticles (AgNPs) to wastewater caused by over-generation and poor treatment of the remaining nanomaterial has raised the interest of researchers. AgNPs can have a negative impact on watersheds and generate degradation of the effluent quality of wastewater treatment plants (WWTPs). The aim of this research is to design and analyze an integrated model system for the removal of AgNPs with high effluent quality in WWTPs using a systematic approach of removal mechanisms modeling, optimization, and control of the removal of silver nanoparticles. The activated sludge model 1 was modified with the inclusion of AgNPs removal mechanisms, such as adsorption/desorption, dissolution, and inhibition of microbial organisms. Response surface methodology was performed to minimize the AgNPs and total nitrogen concentrations in the effluent by optimizing operating conditions of the system. Then, the optimal operating conditions were utilized for the implementation of control strategies into the system for further analysis of enhancement of AgNPs removal efficiency. Thus, the overall AgNP removal efficiency was found to be slightly higher than 80%, which was an improvement of almost 7% compared to the BSM1 reference value. This study provides a systematic approach to find an optimal solution for enhancing AgNP removal efficiency in WWTPs and thereby to prevent pollution in the environment. [ABSTRACT FROM AUTHOR]

Purpose Adopting large eddy simulation (LES) to simulate the complex flow in turbomachinery is appropriate to overcome the limitation of current Reynolds-Averaged Navier–Stokes modelling and it provides a deeper understanding of the complicated transitional and turbulent flow mechanism; however, the large computational cost limits its application in high Reynolds number flow. This study aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation.Design/methodology/approach Compared to the central processing units (CPUs), graphics processing units (GPUs) can provide higher computational speed. This work aims to develop a three-dimensional GPU-enabled parallel-unstructured solver to speed up the high-fidelity LES simulation. A set of low-dissipation schemes designed for unstructured mesh is implemented with compute unified device architecture programming model. Several key parameters affecting the performance of the GPU code are discussed and further speed-up can be obtained by analysing the underlying finite volume-based numerical scheme.Findings The results show that an acceleration ratio of approximately 84 (on a single GPU) for double precision algorithm can be achieved with this unstructured GPU code. The transitional flow inside a compressor is simulated and the computational efficiency has been improved greatly. The transition process is discussed and the role of K-H instability playing in the transition mechanism is verified.Practical/implications The speed-up gained from GPU-enabled solver reaches 84 compared to original code running on CPU and the vast speed-up enables the fast-turnaround high-fidelity LES simulation.Originality/value The GPU-enabled flow solver is implemented and optimized according to the feature of finite volume scheme. The solving time is reduced remarkably and the detail structures including vortices are captured. [ABSTRACT FROM AUTHOR]

• Ecological pressures increase in Northern Xinjiang. • There is greater pressure on water resources supply and demand in industrial cities. • The construction land in Northern Xinjiang exceeded the limit by 2.75 times, and continues to rise. • The planetary boundary theory could be used to evaluate sustainability in arid region. One of the core issues of sustainable development evaluation is how to precisely quantify the impact of human activities and keep it within the ecological carrying capacity. The planetary boundary theory is based on the Earth system view and measures the maximum impact of human activities on the Earth as a whole, providing a new perspective for ecological sustainability evaluation. In this study, we improved the traditional ecological footprint method and evaluated the ecological footprint of Northern Xinjiang from 2000 to 2020 based on the ecological footprint-planetary boundary system, and clarified the boundaries and status of construction land, water resources, and carbon emissions. The results show that: (1) Ecological pressures increase throughout the study area, led by industrial cities and dominated by energy footprints. (2) The state of water resources exploitation and utilization in the study area is safe, and there is greater pressure on water resources supply and demand in industrial cities. (3) The construction land in Northern Xinjiang expanded by 1.95 times, exceeded the limit by 2.75 times, and continues to rise. (4) The study area changed from a carbon sink to a carbon source, and the carbon emission rose 7.93 times. Compared with the traditional model, the improved model improved the parameter scheme, optimized the ecological account type, and constructed the water consumption footprint. [ABSTRACT FROM AUTHOR]

In the last few years, subways have rapidly spread in many countries and have replaced different modes of commuting in some important areas. Despite the fact that passengers only spend a short time in the subway, pollution in the subway is devastating to human health and can cause various diseases, including respiratory diseases. With the development of artificial intelligence (AI), more and more scholars are keen to use this technology to predict and monitor pollution focuses, which in turn can screen the air quality in subways. This paper reviews the application of AI in prediction and control of indoor air quality (IAQ) in subways during 2010–2022. The results show that most of the prediction studies analyzed were conducted for PM 10 and PM 2.5 , and most of the control studies were conducted to optimize the subway ventilation system. Fewer studies have been conducted on the prediction of other air pollutants and on IAQ control facilities. This study attempts to provide guidelines for future AI to manage IAQ in subways. [ABSTRACT FROM AUTHOR]

Real world decision making problems under uncertainty face different challenges. These challenges include lack of information, the necessity of quick decisions, and problems may change across time. When the uncertainty involved is due to fuzziness and vagueness, the use of fuzzy linguistic information can facilitate the elicitation of decision makers’ preferences of alternatives by allowing assessment of alternatives in unipolar scales. However, in some cases decision makers need to express negative, positive and neutral attitudes that cannot be modeled by unipolar scales. This paper aims at developing a dynamic linguistic multi-criteria decision making model dealing with bipolar linguistic scales in which both alternatives and criteria may vary across time. In order to consider the historical evolution of alternatives leading up to the current assessments, a fusion process based on transformation functions and uninorm aggregation operator is proposed to deal with the membership functions of bipolar linguistic assessments. Finally the performance of this model is compared with a non-dynamic method in a supplier selection problem. [ABSTRACT FROM AUTHOR]

Planktonic protists, including both autotroph and heterotroph, have been recognized as a major contributor to primary production and consumers of bacteria, archaea and picophytoplankton. However, the understanding of protistan diversity is typically impeded by the large amount of metazoans when employing universal primers to environmental samples. In this study, we developed 3 blocking primers to inhibit the amplification of metazoan DNA in PCR. First, we optimized the design and concentration of blocking primers by using 2 metazoans and 3 protists in quantitative PCR. No significant difference ( q > 0.05) was found in protistan community structure at phylum, family or OTU levels and genetic diversity between samples amplified with and without adding blocking primers, indicating that the blocking primer does not alter the composition of protistan community. An application to samples with a high abundance of metazoans showed that the blocking primer can reduce 42.1-72.4% of metazoan sequences, resulting the retrieval of a higher protistan richness and diversity. The use of the blocking primer helped to identify protistan community composition from a large size fraction, which is usually dominated by metazoans. Protistan community from the small (0.2-10 μm) and large (> 10 μm) size fractions exhibited a low similarity of 36.6% and shared 14.7% OTUs. About 63.8% of the OTUs were unique to the large fraction. Species from groups, such as Lepidodinium, Warnowia, Kareniaceae, Torodiniales, Phaeocystis, Chrysochromulina and Chrysophyceae, were enriched in the large fraction, indicating that they could be largely underestimated in studies that exclude the large-sized cells. Blocking primers are a promising tool to increase the efficiency for the characterization of protistan diversity in aquatic planktonic ecosystems. [ABSTRACT FROM AUTHOR]

Synechococcus are important and widely distributed picocyanobacteria that encompass a high pigment diversity. In this study, we developed a primer set (peBF/peAR) for amplifying the cpeBA operon sequence from Synechococcus genomic DNA to study Synechococcus pigment diversity along two turbidity gradients in the China seas. Our data revealed that all previously reported pigment types occurred in the South (SCS) and East (ECS) China Seas. In addition, a novel pigment genetic type (type 3f), represented by the high phycourobilin Synechococcus sp. strain KORDI-100 (Exc495:545 = 2.35), was detected. This pigment genetic type differs from the 3c/3d types not only for a very high PUB/PEB ratio but also for a different intergenic spacer sequence and gene organization of the phycobilisome. Synechococcus of different pigment types exhibited clear niche differentiation. Type 2 dominated in the coastal waters, whereas type 3c/3d and 3f were predominant in oceanic waters of the SCS in summer. In the ECS, however, type 3a was the major pigment type throughout the transect. We suggest that in marine environment, various pigment types often co-occur but with one type dominant and PUB/PEB ratio is related to geographic distribution of Synechococcus pigment types. The two marginal seas of China have markedly different Synechococcus pigment compositions. [ABSTRACT FROM AUTHOR]

Viruses and dissolved organic matter (DOM) are major top-down and bottom-up factors, respectively, which control the abundance and diversity of bacterial communities. However, the relative strength and interaction between these two regulators in different marine ecosystems are not fully understood. We applied viral reduction and cross-transplantation of eutrophic estuarine and pristine coastal waters to examine the separate and combined effects of viruses and DOM on the bacterial community composition. We showed that bacteria were more abundant in the virus-depleted groups, particularly in those from the eutrophic estuarine water (i.e., > 7 times higher, when compared with the virus-rich groups). Cluster analyses showed that the bacterial communities in the virus-rich groups were most similar to the in situ populations. Bacterial community richness, evenness and diversity were reduced at high DOM concentrations but were sustained by viruses. This allowed bacteria that were less vulnerable to viral infection to thrive (such as those in the families Alteromonadaceae, Rhodobacteraceae, Flavobacteriaceae, and SAR11), while suppressing those capable of fast growth at elevated DOM concentrations but which were more vulnerable to viral attack (such as those from the family Vibrionaceae). Our results showed that viral regulation occurring at the strain level can affect the bacterial community structure at higher phylogenetic levels. In addition, some less abundant groups, such as Vibrio and Alteromonas, might actually win the competition for resources, providing viral control is removed. Our results also showed that the population dynamics of certain bacterial groups was controlled by viruses, and the strength of such control was modulated by the concentration of DOM. We suggest that the composition of the bacterial community in aquatic environments results from the interactive regulation by DOM and viruses among other regulators. [ABSTRACT FROM AUTHOR]

Rabbit coccidiosis is caused by infection with one or usually several Eimeria species, parasitizing in hepatobiliary ducts or intestinal epithelium of rabbits. To date, 11 species of rabbit coccidia have been well documented. Here we report a new species of Eimeria from rabbits. Sporulated oocysts were ellipsoidal to slightly ovoidal, 37.4 (32.6–41.2) μm in length, 23.5 (20.9–25.5) μm in width, with a shape index (length/width) 1.6 (1.43–1.91) and smooth, bilayered, homogeneously thick wall. The micropyle was obvious and with an inner diameter of 6.2 (5.0–7.5) μm. Both oocyst residuum and polar granule were absent. Sporocysts were ellipsoidal to elongate, 17.2 (13.2–20.0) μm long and 8.4 (7.5–9.1) μm wide, with a shape index (length/width) of 2.1 (1.74–2.21) and the presence of Stieda body and sporocyst residuum. The prepatent period was 132 h. Phylogenetic analysis showed that 18S rDNA sequence of the new species clustered together with the 11 rabbit Eimeria species into a clade. However, ITS-1 sequence of the new species shared low similarities (27.1%–30%) with those of 11 rabbit Eimeria species. As the data above supported the erection of a new species, we named it as Eimeria kongi n. sp., in honor of Fanyao Kong, a Chinese parasitologist. The finding of the new species has important implications for the diagnosis and prevention of rabbit coccidiosis. [ABSTRACT FROM AUTHOR]

Before use as medicines, most traditional Chinese medicine (TCM) plants are processed and decocted. During processing, there may be some changes in pesticide residues in TCM. In recent years, reports have studied the changes of pesticides during the processes of boiling, drying and peeling of TCM materials but have rarely involved special processing methods for TCM, such as ethanol extraction and volatile oil extraction. The changes of carbendazim, carbofuran, pyridaben and tebuconazole residues in common processing methods for P. cablin products were systemically assessed in this study. After each processing step, the pesticides were quantitated by UPLC-MS/MS. The results showed amount decreases in various pesticides to different extents after each processing procedure. Processing factor (PF) values for the four pesticides after decoction, 75% ethanol extraction and volatile oil extraction were 0.02~0.75, 0.40~0.98 and 0~0.02, respectively, which indicated that residual pesticide concentrations may depend on the processing technique. A risk assessment according to the hazard quotient with PF values showed that residual pesticide amounts in P. cablin were substantially lower than levels potentially posing a health risk. Overall, these findings provide insights into the safety assessment of P. cablin. [ABSTRACT FROM AUTHOR]