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Abstract Arginine methylation of histones plays a critical role in regulating gene expression. The writers (methyltransferases) and readers of methylarginine marks are well-known, but the erasers–arginine demethylases–remain mysterious. Here we identify Myc-induced nuclear antigen 53 (Mina53), a jumonji C domain containing protein, as an arginine demethylase for removing asymmetric di-methylation at arginine 3 of histone H4 (H4R3me2a). Using a photoaffinity capture method, we first identify Mina53 as an interactor of H4R3me2a. Biochemical assays in vitro and in cells characterize the arginine demethylation activity of Mina53. Molecular dynamics simulations provide further atomic-level evidence that Mina53 acts on H4R3me2a. In a transgenic mouse model, specific Mina53 deletion in neural stem/progenitor cells prevents H4R3me2a demethylation at distinct genes clusters, dysregulating genes important for neural stem/progenitor cell proliferation and differentiation, and consequently impairing the cognitive function of mice. Collectively, we identify Mina53 as a bona fide H4R3me2a eraser, expanding the understanding of epigenetic gene regulation.

Abstract All-optical diffractive neural networks, as analog artificial intelligence accelerators, leverage parallelism and analog computation for complex data processing. However, their low space transmission efficiency or large spatial dimensions hinder miniaturization and broader application. Here, we propose a terahertz spoof plasmonic neural network on a planar diffractive platform for direct multi-target recognition. Our approach employs a spoof surface plasmon polariton coupler array to construct a diffractive network layer, resulting in a compact, efficient, and easily integrable architecture. We designed three schemes: basis vector classification, multi-user recognition, and MNIST handwritten digit classification. Experimental results reveal that the terahertz spoof plasmonic neural network successfully classifies basis vectors, recognizes multi-user orientation information, and directly processes handwritten digits using a designed input framework comprising a metal grating array, transmitters, and receivers. This work broadens the application of terahertz plasmonic metamaterials, paving the way for terahertz on-chip integration, intelligent communication, and advanced computing systems.

Technological advancements in unmanned aerial vehicles (UAVs) have revolutionized various industries, enabling the widespread adoption of UAV-based solutions. In engineering management, UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments, surpassing traditional inspection techniques. Building on this foundation, this paper delves into the optimization of UAV inspection routing and scheduling, addressing the complexity introduced by factors such as no-fly zones, monitoring-interval time windows, and multiple monitoring rounds. To tackle this challenging problem, we propose a mixed-integer linear programming (MILP) model that optimizes inspection task assignments, monitoring sequence schedules, and charging decisions. The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem (VRP), leading to a mathematically intractable model for commercial solvers in the case of large-scale instances. To overcome this limitation, we design a tailored variable neighborhood search (VNS) metaheuristic, customizing the algorithm to efficiently solve our model. Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm, demonstrating its scalability for both large-scale and real-scale instances. Sensitivity experiments and a case study based on an actual engineering project are also conducted, providing valuable insights for engineering managers to enhance inspection work efficiency.

All-sky meteor radars have become a reliable and widely used tool for observing horizontal winds in the mesosphere and lower thermosphere (MLT) region. This provides vital data support for the study of dynamics in this region. Currently, meteor radars mainly operate in single-station observation mode with no horizontal resolution and can only estimate the average horizontal wind field in the meteor region. To obtain more abundant and accurate information about the atmospheric wind field in the MLT region, a multistatic meteor radar system located in Anhui, China was introduced in this study. The radar system consists of a monostatic meteor radar installed in Mengcheng (33.36 °N, 116.49 °E) and a remote receiver installed in Changfeng (31.98 °N, 117.22 °E) at a distance of about 167 km. Compared to the monostatic meteor radar, the multistatic meteor radar system could observe 70% more forward scatter meteor echoes and offer more than 400 km × 400 km horizontal observation area. Moreover, the multistatic meteor radar system provides more abundant viewing angles. This new multistatic system offers the feasibility of retrieving two-dimensional horizontal wind fields and the gradient of horizontal wind as well as estimating the divergence, relative vorticity, stretching and shearing deformation of the horizontal wind field. The multistatic meteor radar system provides more horizontal wind parameters, significantly contributing to the further studies of the atmospheric dynamics process in the MLT region. In addition, multistatic meteor radar observation network upcoming in the future will realize the 3-d wind field with high spatiotemporal resolution in the MLT region above central and eastern China, greatly improving our understanding of the various wave processes in the near space.

Abstract Coherent perfect absorption (CPA) and amplification of electromagnetic waves are converse phenomena, where incoming radiations are coherently dissipated or amplified by structured incidences. Realizing such two phenomena simultaneously in a single device may benefit various applications such as biological sensing, photo detection, radar stealth, solar-thermal energy sharing, and wireless communications. However, previous experimental realizations of CPA and amplification generally require precise controls to the loss and gain of a system, making dynamic switching between the absorption and amplification states a challenge. To this end, we propose a nonlinear approach to realize CPA and parametric amplification (PA) simultaneously at the same frequency and demonstrate experimentally dynamic switch from the CPA to PA states in a judiciously designed nonlinear spoof plasmonic waveguide. The measured output signal gain can be continuously tuned from −33 dB to 22 dB in a propagation length of 9.2 wavelengths. Compared to the traditional linear CPA, our approach relaxes the stringent requirements on device dimensions and material losses, opening a new route to actively modulate the electromagnetic waves with giant amplification-to-absorption contrast in a compact platform. The proposed nonlinear plasmonic platform has potential applications in on-chip systems and wireless communications.

ObjectiveTo investigate the serotype distribution and antimicrobial resistance characteristics of Salmonella isolated from retail chicken in Beijing City.MethodsA total of 135 Salmonella strains were isolated from retail chicken meat collected from three large wholesale markets in Fengtai District in Beijing City from 2014 to 2015. The serotype of these Salmonella strains was identified using both a Luminex serotyping kit and a traditional serum agglutination method. Multilocus sequence typing was performed according to the recommended conditions of the Enterobase database. Antimicrobial susceptibility testing plates were used to determine the susceptibility of the isolates against 12 classes of drugs representing 25 antimicrobial agents. PCR was used to detect the prevalence of the 10 mobile colistin resistance genes （mcr） and three NDM-type carbapenemases genes （blaNDM）.ResultsAmong the 135 Salmonella strains， 6 serogroups were detected， with D1 and B being the main serogroups； 20 serotypes were detected， in which Enteritidis， Indiana， and Thompson were the dominant ones with percentages of 50.4%， 15.6%， and 8.1%， respectively； 21 ST types were obtained， and a good correspondence was observed between serotypes and ST types. 91.9% of all tested isolates showed resistance to the tested drugs and showed the highest resistance to nalidixic acid， ampicillin， ampicillin-sulbactam， tetracycline. Multi-drug resistant strains accounted for 71.1% of all strains and were resistant to as many as 18 kinds of antimicrobial compounds belonging to 10 categories. Among the 17 strains co-resistant to 8 or more classes of drugs， 16 were of the Indiana serotype. The proportion of strains with high multi-drug resistance was different in different packaging methods， different seasons， and different wholesale markets. All strains were negative for the mcr and blaNDM genes.ConclusionThe serotypes of Salmonella isolates from chicken meat in wholesale markets in Beijing City from 2014 to 2015 were complex， with the dominant serotype of Salmonella Enterititis， and the overall antimicrobial resistance level of all isolates was high. To assess the possible food safety risks， continuous monitoring for Salmonella Indiana with high levels of antimicrobial resistance must be carried out and their drug resistance and transmission mechanisms must be studied to help develop first-line and ultimate drugs for clinical treatment of Salmonella diseases.

There are two crucial resources (i.e., labor and equipment) of productivity in the construction industry. Productivity modeling of these resources would aid stakeholders in project management and improve construction scheduling and monitoring. Hence, this research aims to review machine learning (ML) applications in the process of construction productivity modeling (CPM) for construction labor productivity (CLP) and construction equipment productivity (CEP) from dataset acquisition to data analysis and evaluation, which includes their trends and applicability. An extensive analysis of 131 journals focused on the application of machine learning in construction productivity (ML-CP) from 1990 to 2024 via a mixed review methodology (bibliometric analysis and systematic review) was conducted. It can be concluded that despite the rise in automated dataset collection, the traditional method has its advantages. The review further found that the selection of ML models relies on each particular application, available data, and computational resources. Noticeably, artificial neural networks, convolutional neural networks, support vector machines, and even deep learning demonstrating have been adopted due to their effectiveness in different functionalities and processes in CPM. This study will supplement the insights gained in the review with a comprehensive understanding of how ML applications operate at each stage of CPM, enabling researchers to make future improvements.

Abstract The global‐scale empirical analysis of how renewable energy policies (REPs) affect carbon emissions and the mediating role of renewable energy development (RED) in this mechanism remains underexplored. To fill this research gap, we extracted and organized REPs data from IEA's databases for 135 countries until 2018 and conducted empirical analyses of these issues. We find that: (a) REPs significantly reduce global carbon emissions, especially through regulatory, economic, and R&D policies. (b) REPs' effectiveness in mitigating carbon emissions is enhanced by robust energy infrastructure, strong control of corruption, and adherence to the rule of law. Besides, the balance of REPs types does not influence their efficiency, but REPs prioritizing certain renewable energy (RE) types aligns better with carbon reduction goals. (c) RED displays a Janus‐faced influence on REPs' carbon reduction effect—renewable energy consumption (REC) positively mediates it, whereas renewable energy share (RES) exerts a negative mediation. Specifically, REC consistently reduces carbon emissions, while RES initially increases and then decreases carbon emissions, exhibiting an inverted U‐shape. (d) The initial rise in carbon emissions with RES is due to the low substitution of RE for fossil energy and the country‐specific heterogeneity in organizational, geographic, industrial, economic, demographic, and temporal factors.

Abstract Glycans are complex biomolecules that encode rich information and regulate various biological processes, such as fertilization, host‐pathogen binding, and immune recognition, through interactions with glycan‐binding proteins. A key driving force for glycan‐protein recognition is the interaction between the π electron density of aromatic amino acid side chains and polarized C─H groups of the pyranose (termed the CH–π interaction). However, the relatively weak binding affinity between glycans and proteins has hindered the application of glycan detection and imaging. Here, computational modeling and molecular dynamics simulations are employed to design a chemical strategy that enhances the CH–π interaction between glycans and proteins by genetically incorporating electron‐rich tryptophan derivatives into a lectin PhoSL, which specifically recognizes core fucosylated N‐linked glycans. This significantly enhances the binding affinity of PhoSL with the core fucose ligand and enables sensitive detection and imaging of core fucosylated glycans in vitro and in xenograft tumors in mice. Further, the study showed that this strategy is applicable to improve the binding affinity of GafD lectin for N‐acetylglucosamine‐containing glycans. The approach thus provides a general and effective way to manipulate glycan‐protein recognition for glycoscience applications.

The atmospheric temperatures and densities in the mesosphere and lower thermosphere (MLT) region are essential for studying the dynamics and climate of the middle and upper atmosphere. In this study, we present more than 9 years of mesopause temperatures and relative densities estimated by using ambipolar diffusion coefficient measurements observed by the Mengcheng meteor radar (33.4°N, 116.5°E). The intercomparison between the meteor radar and Thermosphere Ionosphere Mesosphere Energetics and Dynamics/Sounding of the Atmosphere by Broadband Emission Radiometry (TIMED/SABER) and Earth Observing System (EOS) Aura/Microwave Limb Sounder (MLS) observations indicates that the meteor radar temperatures and densities agree well with the simultaneous satellite measurements. Annual variations dominate the mesopause temperatures, with the maximum during winter and the minimum during summer. The mesopause relative densities also show annual variations, with strong maxima near the spring equinox and weak maxima before the winter solstice, and with a minimum during summer. In addition, the mesopause density exhibits a structure similar to that of the zonal wind: as the zonal wind flows eastward (westward), the mesopause density decreases (increases). At the same time, the meridional wind shows a structure similar to that of the mesopause temperature: as the meridional wind shows northward (southward) enhancements, the mesopause temperature increases (decreases). Simultaneous horizontal wind, temperature, and density observations provide multiple mesospheric parameters for investigating mesospheric dynamics and thermodynamic processes and have the potential to improve widely used empirical atmospheric models.

Annually, over 10 billion tons of construction and demolition waste is transported globally from sites to reception facilities. Optimal and effective planning of waste transportation holds the potential to mitigate cost and carbon emissions, and alleviate road congestion. A major challenge for developing an effective transportation plan is the uncertainty of the precise volume of waste at each site during the planning stage. However, the existing studies have assumed known demand in planning models but the assumption does not reflect real-world volatility. Taking advantage of the problem structure, this study adopts the stochastic programming methodology to approach the construction waste planning problem. An integer programming model is developed that adeptly addresses the uncertainty of the amount of waste in an elegant manner. The proposed stochastic programming model can efficiently handle practical scale problems. Our numerical experiments amass a comprehensive dataset comprising nearly 4300 records of the actual amount of construction waste generated in Hong Kong. The results demonstrate that incorporating demand uncertainty can reduce the transportation cost by 1% correlating with an increase in profit of 14% compared to those that do not consider the demand uncertainty.

With rapid urbanization growth, considerable amounts of construction waste are generated on an annual basis, posing significant economic and environmental challenges worldwide. Re-cycling construction waste is a sustainable way for waste disposal, leading to the necessity of meticulous planning of recycling centers. A well-designed plan for constructing recycling centers can effectively improve the recycling rate of construction waste while minimizing investment. This paper formulates a two-stage stochastic model for planning recycling centers with the objective of maximizing the recycling rate under different scenarios. This study comprehensively considers various uncertain factors, such as the amount of construction waste generated and the demand for recycled materials. A case study of Guangzhou is used for validation, which demonstrates the effectiveness of the developed model in planning recycling center construction. The comparison between the proposed model and a conventional mean value model shows the importance of accounting for uncertainties. Specifically, the derived results indicate that 7% more construction waste is recycled with the same investment in constructing recycling centers. Additionally, via a sensitivity analysis, valuable managerial insights on investing resources in recycling center construction are provided to decision makers. Ultimately, the research findings are expected to enhance the recycling rate of construction waste, thereby contributing to sustainable industry development.

Atmospheric gravity waves (GWs) can strongly modulate middle atmospheric circulation and can be a significant factor for the coupling between the lower atmosphere and the middle atmosphere. GWs are difficult to resolve in global atmospheric models due to their small scale; thus, GW observations play an important role in middle atmospheric studies. The climatology of GW variance and momentum in the low-latitude mesosphere and lower thermosphere (MLT) region are revealed using multiple meteor radars, which are located at Kunming (25.6°N, 103.8°E), Sanya (18.4°N, 109.6°E), and Fuke (19.5°N, 109.1°E). The climatology and longitudinal variations in GW momentum fluxes and variance over the low-latitude region are reported. The GWs show strong seasonal variations and can greatly control the mesospheric horizontal winds via modulation of the quasi-geostrophic balance and momentum deposition. The different GW activities between Kunming and Sanya/Fuke are possibly consistent with the unique prevailing surface winds over Kunming and the convective system over the Tibetan Plateau according to the European Centre for Medium-Range Weather Forecasts (ECMWF), Reanalysis v5 (ERA5) data, and outgoing longwave radiation (OLR) data. These findings provide insight for better understanding the coupling between the troposphere and mesosphere.

In the domain of supervised learning, interpolation and extrapolation serve as crucial methodologies for predicting data points within and beyond the confines of a given dataset, respectively. The efficacy of these methods is closely linked to the nature of the dataset, with increased challenges when multivariate feature vectors are handled. This paper introduces a novel prediction framework that integrates interpolation and extrapolation techniques. Central to this method are two main innovations: an optimization model that effectively classifies new multivariate data points as either interior or exterior to the known dataset, and a hybrid prediction system that combines k-nearest neighbor (kNN) and linear regression. Tested on the port state control (PSC) inspection dataset at the port of Hong Kong, our framework generally demonstrates superior precision in predictive outcomes than traditional kNN and linear regression models. This research enriches the literature by illustrating the enhanced capability of combining interpolation and extrapolation techniques in supervised learning.

[Objective] Cultivating innovation capability is conducive to the break through of resource dilemmas and the realization of global value chain (GVC) upgrading by manufacturing enterprises in underdeveloped areas. Therefore, it is of great significance to explore the impact of innovation capability on GVC upgrading and its mechanism from the perspective of resource orchestration. [Methods] Taking 219 questionnaire data from Yunnan automobile manufacturing enterprises, structural equation modeling was applied. Based on the resource orchestration theory, this study explored how manufacturing enterprises in underdeveloped areas can enhance their innovation capability through effective resource management and thus capture more value-added in the GVC. Dynamic capability evolution mechanism was introduced to explore the process of resource orchestration acting on innovation capability. [Results] (1) Resource orchestration facilitated enterprises to achieve GVC upgrading by enhancing innovation capabilities. (2) On the basis of effective resource management, enterprises influenced innovation capability by improving the evolution of dynamic capability, that is, the breadth, depth, and speed of dynamic capability combination, which in turn positively affected the GVC upgrading. (3) The three types of resource orchestration had heterogeneous effects on capability and upgrading. Resource utilization had the most pronounced effect on GVC upgrading by facilitating dynamic capabilities evolution. However, resource integration had the most pronounced effect on GVC upgrading through the enhancement of innovation capability. [Conclusion] In the process of enhancing innovation capability, enterprises in underdeveloped areas should pay more attention to the integration of upstream and downstream resources and the development of internal and external resources, so as to provide continuous impetus for realizing value-added in the context of resource constraints.

Intradialytic hypotension (IDH) is common in hemodialysis patients and can lead to several complications. Risk factors for IDH include demographic characteristics, comorbidities, dialysis procedure factors, and so on. Clinical studies on predictive models for dialysis-induced hypotension have shown inconsistent results. This systematic review aims to evaluate published prediction models for IDH, analyzing their characteristics, predictors, efficacy, and the methodological quality and applicability. The protocol has been prepared using the Preferred Items for Systematic Review and Meta-analysis Protocols (PRISMA-P) guidelines. The systematic review protocol for IDH prediction in hemodialysis patients has been registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY2023110081, DOI: 10.37766/inplasy2023.11.0081). A comprehensive search across five major databases (PubMed, Web of Science, Cochrane Library, CNKI, and Wanfang) will be conducted for studies on prediction models of IDH among hemodialysis patients. Two researchers will independently screen literature, extract data, and evaluate the bias risk and applicability of included studies using prediction modelling study tools. This systematic review will provide critical insights into the efficacy and quality of reporting of the IDH model in hemodialysis patients. This will guide clinical staff in selecting the most appropriate IDH prediction model and inform future research endeavors in IDH prediction.

Abstract Previous studies have shown that Ogt-mediated O-GlcNAcylation is essential for neuronal development and function. However, the function of O-GlcNAc transferase (Ogt) and O-GlcNAcylation in astrocytes remains largely unknown. Here we show that Ogt deficiency induces inflammatory activation of astrocytes in vivo and in vitro, and impairs cognitive function of mice. The restoration of O-GlcNAcylation via GlcNAc supplementation inhibits the activation of astrocytes, inflammation and improves the impaired cognitive function of Ogt deficient mice. Mechanistically, Ogt interacts with NF-κB p65 and catalyzes the O-GlcNAcylation of NF-κB p65 in astrocytes. Ogt deficiency induces the activation of NF-κB signaling pathway by promoting Gsk3β binding. Moreover, Ogt depletion induces the activation of astrocytes derived from human induced pluripotent stem cells. The restoration of O-GlcNAcylation inhibits the activation of astrocytes, inflammation and reduces Aβ plaque of AD mice in vitro and in vivo. Collectively, our study reveals a critical function of Ogt-mediated O-GlcNAcylation in astrocytes through regulating NF-κB signaling pathway.

Due to the advantage that the non-convex penalty accurately characterizes the sparsity of structural damage, various models based on non-convex penalties have been effectively utilized to the field of structural damage identification. However, these models generally ignore the influence of the uncertainty on the damage identification, which inevitably reduces the accuracy of damage identification. To improve the damage identification accuracy, a probabilistic structural damage identification method with a generic non-convex penalty is proposed, where the uncertainty corresponding to each mode is quantified using the separate Gaussian distribution. The proposed model is estimated via the iteratively reweighted least squares optimization algorithm according to the maximum likelihood principle. The numerical and experimental results illustrate that the proposed method improves the damage identification accuracy by 3.98% and 7.25% compared to the original model, respectively.

This study investigates an integrated yard planning and module transportation problem in modular integrated construction (MiC). A Stackelberg game model is proposed to characterize the relations between the government and contractors. The government is the leader and decides the locations and areas of temporary storage yards to facilitate the cost-effective and eco-friendly transportation of MiC modules. The contractors are the followers and decide the transport mode (i.e., road transport or intermodal transport) for modules to minimize their total transportation costs. This study provides an in-depth analysis of model properties to derive a number of useful managerial insights. The economical and environmental trade-offs between costs and emissions are observed. Our study further proves that an optimal solution is likely to simultaneously reduce the overall costs and carbon emissions, in comparison to choosing the location with the largest area to construct a temporary storage yard. These insights offer a comprehensive framework for understanding the interactions between government and contractors. Overall, this paper aims to promote the implementation of MiC by achieving the economical and sustainable transportation of MiC modules.

The existing of transmission line icing may lead to the collapse of the transmission tower and disconnection of the transmission line, which seriously threatens the safe and stable operation of power grid. In this paper, aiming at the typical icing lines in Guizhou, the simulation model of 500 kV tower-line system is established by finite element simulation method, and the simulation analysis of different icing thicknesses and different wind speeds under uniform icing is carried out. The weak point position rules of 500 kV transmission tower are obtained by counting 25 groups of simulation results. Then, based on the axial stress and node displacement of the weak components of the transmission tower, the operational risk assessment analysis of the transmission tower is carried out, and the operational risk state of the transmission tower is divided. Furthermore, the effect analysis of two kinds of reinforcement measures is carried out, and the relationship between axial stress and node displacement at different weak points of the transmission tower before and after reinforcement is obtained. The results show that the weak points of the 500 kV transmission tower are mainly distributed at the ground bracket of the tower head, the joint of the upper and lower curved arms, the bottle neck and the body of the tower. Under uniform icing and wind load, the axial stress and node displacement of key components increase nonlinearly. The critical expressions of safety, warning and dangerous state of the transmission tower are fitted. The reinforcing effect of increasing the cross-sectional area of components is better than that of changing the angle steel structure with weak points. The axial stress and joint displacement of the transmission tower at the weak point have no obvious change before and after reinforcement when changing the angle steel.

Acute pancreatitis (AP) is a common cause of emergent patients and common severe disorders of hospital admission. This review includes the characteristic of inflammatory reaction from AP, the pattern and the aetiology of AP with infection, the necessity of preventive use of antibacterials, antimicrobial treatment of AP with infection, use of antibacterials for extra-pancreatic infections, surgical intervention of anti-infective treatment. Related recognition and clinical experience in treatment of AP were provided. Extra-pancreatic infections appeared in the patients with AP indicating the increase in disease severity. Compared to the patients with aseptic necrosis, the patients with extra-pancreatic infections might have organ failure, increasing in rescue risk for into intensive care unit, and with mortality increasing. Early diagnosis, infection control and proper treatment with antibacterials will be the footing and base for the treatment of AP combined infection.

The development of prefabricated buildings is a major change in the way of building construction, which is of great significance to the supply-side reform and urbanization development. Assembly building wall panel is an important part, but due to the lack of heat and wet coupling transmission performance parameters, the performance research of wall board is blocked. Through theoretical analysis and physical test, the thermal-wet coupling transfer performance of low-carbon materials in Inner Mongolia.

Worker assignment is a classic topic in infrastructure construction. In this study, we developed an integer optimization model to help decision-makers make optimal worker assignment plans while maximizing the daily productivity of all workers. Our proposed model considers the professional skills and physical fitness of workers. Using a real-world dataset, we adopted a machine learning method to estimate the maximum working tolerance time for different workers to carry out different jobs. The real-world dataset also demonstrates the effectiveness of our optimization model. Our work can help project managers achieve efficient management and save labor costs.

A meteor radar chain located along the 120°E meridian in the Northern Hemisphere from low to middle latitudes provides long-term horizontal wind observations of the mesosphere and lower thermosphere (MLT) region. In this study, we report a seasonal variation and its latitudinal feature in the horizontal mean wind in the MLT region observed by six meteor radar instruments located at Mohe (53.5°N, 122.3°E), Beijing (40.3°N, 116.2°E), Mengcheng (33.4°N, 116.5°E), Wuhan (30.6°N, 114.4°E), Kunming (25.6°N, 108.3°E), and Fuke (19.5°N, 109.1°E) stations. In addition, we compare the wind in the MLT region measured by the meteor radar stations with those simulated by the Whole Atmosphere Community Climate Model (WACCM). In general, the WACCM appears to capture well the seasonal and latitudinal variations in the zonal wind component. In particular, the temporal evolution of the eastward zonal wind maximum shifts from July to May as the latitude decreases. However, the simulated WACCM meridional wind exhibits differences from the meteor radar observations.

Numerical experiment is an essential part of academic studies in the field of transportation management. Using the appropriate sample size to conduct experiments can save both the data collecting cost and computing time. However, few studies have paid attention to determining the sample size. In this research, we use four typical regression models in machine learning and a dataset from transport infrastructure workers to explore the appropriate sample size. By observing 12 learning curves, we conclude that a sample size of 250 can balance model performance with the cost of data collection. Our study can provide a reference when deciding on the sample size to collect in advance.

In this study, the neutral density and horizontal wind observed by the four meteor radars, as well as the temperature measured by the Microwave Limb Sounder (MLS) onboard the Aura satellite are used to examine the response of neutral density, wind, and temperature in the MLT region to the stratospheric sudden warmings (SSWs) during 2005 to 2021 in the Northern Hemisphere. The four meteor radars include the Svalbard (78.3°N, 16°E) and Tromsø (69.6°N, 19.2°E) meteor radars at high latitudes and the Mohe (53.5°N, 122.3°E) and Beijing (40.3°N, 116.2°E) meteor radars at middle latitudes. The superposed epoch analysis results indicate that: 1) the neutral density over Svalbard and Tromsø at high latitude increased at the beginning of SSWs and decreased after the zonal mean stratospheric temperature reached the maximum. However, the neutral density over Mohe at midlatitudes decreased in neutral density at the beginning of SSW and increase after the zonal mean stratospheric temperature reached the maximum. 2) The zonal wind at high latitudes show a westward enhancement at the beginning of SSWs and then shows an eastward enhancement after the stratospheric temperature reaches maximum. However, the zonal wind at midlatitudes shows an opposite variation to at high latitudes, with an eastward enhancement at the onset and changing to westward enhancements after the stratospheric temperature maximum. The meridional winds at high and midlatitudes show a southward enhancement after the onset of SSW and then show a northward enhancement after the stratospheric temperature maximum. 3) In general, the temperature in the MLT region decreased throughout SSWs. However, as the latitudes decrease, the temperature cooling appears to lag a few days to the higher latitudes, and the degree of cooling will decrease relatively.

BackgroundPineapple is the only commercially grown fruit crop in the Bromeliaceae family and has significant agricultural, industrial, economic, and ornamental value. GRF (growth-regulating factor) proteins are important transcription factors that have evolved in seed plants (embryophytes). They contain two conserved domains, QLQ (Gln, Leu, Gln) and WRC (Trp, Arg, Cys), and regulate multiple aspects of plant growth and stress response, including floral organ development, leaf growth, and hormone responses. The GRF family has been characterized in a number of plant species, but little is known about this family in pineapple and other bromeliads.Main discoveriesWe identified eight GRF transcription factor genes in pineapple, and phylogenetic analysis placed them into five subfamilies (I, III, IV, V, VI). Segmental duplication appeared to be the major contributor to expansion of the AcGRF family, and the family has undergone strong purifying selection during evolution. Relative to that of other gene families, the gene structure of the GRF family showed less conservation. Analysis of promoter cis-elements suggested that AcGRF genes are widely involved in plant growth and development. Transcriptome data and qRT-PCR results showed that, with the exception of AcGRF5, the AcGRFs were preferentially expressed in the early stage of floral organ development and AcGRF2 was strongly expressed in ovules. Gibberellin treatment significantly induced AcGRF7/8 expression, suggesting that these two genes may be involved in the molecular regulatory pathway by which gibberellin promotes pineapple fruit expansion.ConclusionAcGRF proteins appear to play a role in the regulation of floral organ development and the response to gibberellin. The information reported here provides a foundation for further study of the functions of AcGRF genes and the traits they regulate.

The increase in worldwide vegetable oil consumption has produced a large increase in hazardous waste cooking oil (WCO) production. The improper disposal of WCO has been a significant problem from both an environmental and economic perspective. Therefore, it is advantageous to transform WCOs into valuable products efficiently and effectively in order to contribute towards the establishment of a circular economy. In this review, the current state of WCO is discussed in relation to WCO production and valorisation. The valorisation rate of each country can be categorised into three groups related to the consumption of vegetable oil, production and valorisation of WCO, as well as the production, conversion and valorisation factors. Before any valorisation and processing of WCO can be carried out, pretreatments are crucially needed in refining and upgrading WCOs, specifically to reduce their free fatty acid (FFA) contents. This could help to produce refined WCOs with appropriate feedstock properties suitable for value-added applications in oleochemical industries. Hence, several pretreatment methods (e.g., solid impurities removal, FFA reduction, moisture removal) have been summarized and evaluated in depth. The transformation of WCO into valuable products including alkyd resin, green solvent, soap, plastics and plasticizer are also reviewed. Recent technological advances have made WCO feasible as sustainable feedstocks for oleochemical production, but not limited to biofuel production which in turn maximizes the value of this hazardous waste and turns WCO into a sustainable source.

A new mechanism for the generation of high intensity speckles by coupling of overlapping beams is discovered and studied in detail. Using three-dimensional simulations, the coupling of overlapping beams smoothed by phase plates and by polarization smoothing are investigated in the regime relevant to inertial confinement fusion studies. It is found that the intensity distribution of the laser beam spot can be changed by nonuniform spatial phase modulation, and the speckles formed by the phase plate can be split into smaller speckles with higher intensities, which is favorable for the generation of laser plasma instabilities. Stimulated Brillouin scattering is compared in simulations with and without coupling of the overlapping incident beams, and the results confirm the enhancement of stimulated Brillouin scattering due to this mechanism.

PurposeThe current study aimed to investigate whether red blood cell distribution width (RDW) can predict the prognosis of patients with breast cancer (BC).MethodsWe searched four databases, including PubMed, Embase, Cochrane Library databases, and CNKI, from inception to Jun 13, 2022. The primary outcome was overall survival (OS), and the secondary outcome was disease-free survival (DFS). A subgroup analysis was conducted based on different treatments. This meta-analysis was performed with RevMan 5.3 (The Cochrane Collaboration, London, United Kingdom).ResultsA total of seven studies including 4,884 BC patients were identified. The high RDW group had a larger tumor size (OR = 2.12, 95% CI = 1.67 to 2.68, P

BackgroundBody image concerns are prevalent among young adults, who may be vulnerable to developing body image concerns because of particular risk factors associated with this life period. With technological advancements, digital mobile health (mHealth) apps are cost-effective and scalable interventions. Thus, mHealth apps can be explored as a form of prevention effort to alleviate body image concerns in young adults. ObjectiveIn this randomized controlled trial, we examined the effectiveness of a self-guided mHealth app in improving body image and self-compassion in a sample of university students. MethodsParticipants (N=310) were randomized to a 9-day self-guided body image and self-compassion mHealth app (n=149) and to an active waitlist control group (n=161), where they completed a similarly structured 9-day program on cooperation. Both programs consisted of content learning and activities such as quizzes, with the number and length of activities matched for both programs. Measures were obtained at baseline, upon completion of the programs (after the intervention), and at 4-week follow-up. ResultsThe intervention group for female participants reported significant reduction in body dissatisfaction (P

A recently proposed octahedral spherical hohlraum with six laser entrance holes (LEHs) is an attractive concept for an upgraded laser facility aiming at a predictable and reproducible fusion gain with a simple target design. However, with the laser energies available at present, LEH size can be a critical issue. Owing to the uncertainties in simulation results, the LEH size should be determined on the basis of experimental evidence. However, determination of LEH size of an ignition target at a small-scale laser facility poses difficulties. In this paper, we propose to use the prepulse of an ignition pulse to determine the LEH size for ignition-scale hohlraums via LEH closure behavior, and we present convincing evidence from multiple diagnostics at the SGIII facility with ignition-scale hohlraum, laser prepulse, and laser beam size. The LEH closure observed in our experiment is in agreement with data from the National Ignition Facility. The total LEH area of the octahedral hohlraum is found to be very close to that of a cylindrical hohlraum, thus successfully demonstrating the feasibility of the octahedral hohlraum in terms of laser energy, which is crucially important for sizing an ignition-scale octahedrally configured laser system. This work provides a novel way to determine the LEH size of an ignition target at a small-scale laser facility, and it can be applied to other hohlraum configurations for the indirect drive approach.

Circadian dysregulation can be involved in the development of malignant tumors, though its relationship with the progression of hepatocellular carcinoma is not yet fully understood. We identified genes related to circadian rhythms from the Cancer Genome Atlas (TCGA), measured gene expression, and conducted genomic difference analysis to construct a circadian rhythm-related signature. The resulting prognosis model proved to be an effective biomarker, as demonstrated by Kaplan-Meier survival analysis for both the training (n = 370, P = 2.687e-10) and external validation cohorts (n = 230, P = 1.45e-02). Further, we found that patients considered ‘high risk’, with an associated poor prognosis, displayed elevated levels of immune checkpoint genes and immune filtration. We also conducted functional enrichment, which indicated that the risk model showed a significant positive correlation with certain malignant phenotypes, including G2M checkpoint, MYC targets, and the MTORC1 signaling pathway. In summary, we identified a novel circadian rhythm-related signature allowing assessment of prognosis for hepatocellular carcinoma patients, and further can be used to predict immune infiltration sensitivity.

Mouse embryonic stem cells (mESCs) possess the remarkable characteristics of unlimited self-renewal and pluripotency, which render them highly valuable for both fundamental research and clinical applications. A comprehensive understanding of the molecular mechanisms underlying mESC function is of the utmost importance. The Human Silence Hub (HUSH) complex, comprising FAM208A, MPP8, and periphilin, constitutes an epigenetic silencing complex involved in suppressing retroviruses and transposons during early embryonic development. However, its precise role in regulating mESC pluripotency and differentiation remains elusive. In this study, we generated homogenous miniIAA7-tagged Mpp8 mouse ES cell lines. Upon induction of MPP8 protein degradation, we observed the impaired proliferation and reduced colony formation ability of mESCs. Furthermore, this study unveils the involvement of MPP8 in regulating the activity of the LIF/STAT3 signaling pathway and Nanog expression in mESCs. Finally, we provide compelling evidence that degradation of the MPP8 protein impairs the differentiation of mESC.

In traffic flow, the relationship between speed and density exhibits decreasing monotonicity and continuity, which is characterized by various models such as the Greenshields and Greenberg models. However, some existing models, i.e., the Underwood and Northwestern models, introduce bias by incorrectly utilizing linear regression for parameter calibration. Furthermore, the lower bound of the fitting errors for all these models remains unknown. To address above issues, this study first proves the bias associated with using linear regression in handling the Underwood and Northwestern models and corrects it, resulting in a significantly lower mean squared error (MSE). Second, a quadratic programming model is developed to obtain the lower bound of the MSE for these existing models. The relative gaps between the MSEs of existing models and the lower bound indicate that the existing models still have a lot of potential for improvement.

Electronegative guest‐filled skutterudites (EN‐SKDs) are considered one of the most promising thermoelectric materials for next‐generation thermoelectric generators (TEGs). However, the practical application of EN‐SKDs in TEGs is still a huge challenge because of their unsatisfactory zT value (less than 1.0). Herein, Ge, Te‐codoped electronegative sulfur‐filled skutterudites of S x Co4Sb11Ge0.2Te0.8 (x = 0, 0.05, 0.1, 0.2, 0.25) are synthesized. The optimal zT value of as high as 1.45 at 823 K with a low room‐temperature lattice thermal conductivity of 1.98 W m−1 K−1 is achieved by S0.25Co4Sb11Ge0.2Te0.8. Such performance is competitive with those of traditional TE materials and among one of the best EN‐SKDs. The excellence is attributed to the synergistic effect of the disorder caused by Ge, Te co‐doping at Sb‐site and the “rattling” effect of electronegative element S. Furthermore, a novel EN‐SKD‐based TEG is prepared for the first time through an integrated welding process and exhibits a high efficiency of 6.0% at the temperature difference of 475 K. This work provides valuable guidance for designing advanced thermoelectric materials and paves a way toward high‐performance EN‐SKD‐based TEGs.

Background: Walk tests are common gait speed and endurance assessments. Shorter test versions could benefit adults with intellectual disability. Thus, the concurrent validity of shorter tests was studied. Methods: Thirty-five adults with mild to moderate intellectual disability, aged 21-64 years, were assessed with the 4-m walk test, 10-m walk test for gait speed, 2-min walk test, and 6-min walk test for endurance. Correlation and Bland--Altman plots analyses were used to establish concurrent validity between shorter and standard tests. Results: Strong positive relationships were found for gait speed tests, r = 0.94, p < 0.001, and endurance tests, r = 0.83, p < 0.001, and differences between shorter and standard tests were within limits of agreement. Conclusions: The concurrent validity of shorter walk tests was established in this study. This would mean that adults with intellectual disability with lower levels of fitness could be assessed.

In response to the deformation resistance deficiency and poor toughness characteristics of soil after microbial curing, a combination of fibre reinforcement technology and microbial curing technology was used to conduct microbial curing tests using basalt fibres and denitrifying bacteria. In this paper, the effects of fibre on the strength and toughness of soil consolidation were analysed by unconfined compressive strength test and direct shear test, and the stability of reinforced slope was analysed by numerical simulation. The results show the following. (1) Basalt fibre can effectively improve the characteristics of brittle damage of microbially consolidated soil while increasing the compressive and shear strength. (2) Fibre dosing and fibre length have important effects on the mechanical properties of microbially consolidated soil. (3) The appropriate amount of basalt fibre can promote the generation of calcium carbonate. (4) The plastic strain area of the slope decreases after microbial reinforcement and the maximum equivalent plastic stress decreases by 65 kPa.

By using atmospheric wind data in the mesopause and lower thermosphere (MLT) region, features of seasonal variations in the quasi-6-day wave (6DW) at different latitudes are analyzed, and modulation of the 6DW by the diurnal tide and solar 27-day period is discussed. The data used in the analysis are extracted from a wind dataset collected by a meteor radar chain from December 2008 to November 2017. The meteor radar chain includes four stations, in Mohe, Beijing, Wuhan, and Sanya. Features of seasonal variations in the 6DW indicate that in summer the 6DW is usually strongest during July and August, followed by stronger variations in January and April. At certain altitudes over Wuhan and Sanya, the 6DW is slightly different in different years and altitudes. In our analysis of seasonal variations in the 6DW, we find that it is generally affected by annual oscillations and semiannual oscillations. The annual oscillations of the 6DW in the mid-low latitudes are modulated by the quasibiennial oscillation in the diurnal tide, resulting in seasonal features that are different from those at other latitudes. In addition, the 6DW amplitude at mid-high latitudes has a significant 27-day solar rotation variation, which was prominent in 2016.

Abstract Background Hepatocellular carcinoma (HCC) is the most common type of liver tumour, and is closely related to liver cirrhosis. Previous studies have focussed on the pathogenesis of liver cirrhosis developing into HCC, but the molecular mechanism remains unclear. The aims of the present study were to identify key genes related to the transformation of cirrhosis into HCC, and explore the associated molecular mechanisms. Methods GSE89377, GSE17548, GSE63898 and GSE54236 mRNA microarray datasets from Gene Expression Omnibus (GEO) were analysed to obtain differentially expressed genes (DEGs) between HCC and liver cirrhosis tissues, and network analysis of protein–protein interactions (PPIs) was carried out. String and Cytoscape were used to analyse modules and identify hub genes, Kaplan–Meier Plotter and Oncomine databases were used to explore relationships between hub genes and disease occurrence, development and prognosis of HCC, and the molecular mechanism of the main hub gene was probed using Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis. Results In total, 58 DEGs were obtained, of which 12 and 46 were up- and down-regulated, respectively. Three hub genes (CDKN3, CYP2C9 and LCAT) were identified and associated prognostic information was obtained. CDKN3 may be correlated with the occurrence, invasion, and recurrence of HCC. Genes closely related to changes in the CDKN3 hub gene were screened, and Kyoto Encyclopedia of Genes and Genomes (KEGGs) pathway analysis identified numerous cell cycle-related genes. Conclusion CDKN3 may affect the transformation of liver cirrhosis into HCC, and represents a new candidate molecular marker of the occurrence and progression of HCC.

Post-translational modifications of phosphoglycerate kinase 1 (PGK1), a glycoytic enzyme, contribute to cancer progression. Here, the authors show that PGK1 is O-GlcNAcylated at T255, which induces its translocation into mitochondria to suppress the tricarboxylic acid cycle for colorectal cancer growth.

This study presents the observations of midlatitude plasma irregularities over Eastern Asia during a moderate magnetic storm on 16 July 2003. Multi-instrumental observations, including the ground-based ionosondes, the GNSS networks, and the CHAMP and ROCSAT-1 satellites, were utilized to investigate the occurrence and characteristics of midlatitude plasma irregularities. The midlatitude strong spread F (SSF) mainly occurred in the midnight–morning sector as observed by ionosondes over Japan during this storm. SSF was related to plasma depletions, which is also recorded by GNSS network in the form of the enhancement of the rate of total electron content (TEC) change index (ROTI). The possible mechanism for the generation of SSF is that the enhanced eastward electric fields, associated with the prompt penetration electric fields and disturbance dynamo electric fields, cause the uplift and latitudinal extension of equatorial plasma bubbles (EPBs) to generate the observed midlatitude SSF further. Meanwhile, plasma density increased significantly under the influence of this storm. In addition, other common type of spread F, frequency spread F (FSF), was observed over Japan on the non-storm day and/or at high latitude station WK545, which seems to be closely related to the coupling of medium-scale traveling ionospheric disturbances (MSTIDs) and sporadic E (Es) layer. The above results indicate that various types of midlatitude spread F can be produced by different physical mechanisms. It is found that SSF can significantly affect the performance of radio wave propagation compared with FSF. Our results show that space weather events have a significant influence on the day-to-day variability of the occurrence and characteristics of ionospheric F-region irregularities at midlatitudes.

In this study, we present nearly 9 years of the quasi16-day wave (Q16DW) in the mesosphere and lower thermosphere (MLT) wind at middle latitudes based on long-term wind observations between April 2014 and December 2022 by the Mengcheng (33.4°N, 116.5°E) meteor radar. There are two maxima in the Q16DW amplitude in the winter and early spring (near the equinox) and a minimum during the summer. The Q16DWs are relatively weak in meridional winds with no obvious seasonal variations. On average, the phase of the zonal Q16DW is larger than the meridional components with a mean difference that is slightly less than 90°, which suggests that there are orthogonal relationships between them. During the bursts of Q16DW, the periods in winter range between 15 and 18 d, whereas in summer, the periods of the planetary waves have a wider range. The wintertime Q16DW anomalies are, on average, amplified when the zonal wind shear anomalies increase, suggesting that barotropic instability may be a source of the Q16DW. Although the interannual variability of Q16DW amplitudes has been suggested observationally, there is no significant relationship between the interannual wind shear variability and Q16DW at most altitudes.

This paper considers promoting off-site construction using government subsidy. A three-stage Stackelberg game model is formulated for the optimal subsidy design for the government, accounting for the decisions of government, suppliers (owners of off-site construction yards), and customers (entities that buy precast concrete from the suppliers). The government has two objectives: one is to maximize the use of precast concrete produced by regional yards and the other is to reduce green-house gas emissions from the transport of precast concrete. A number of properties of the three-stage Stackelberg game framework have been analyzed. We find that an inappropriately designed subsidy scheme may decrease the use of precast concrete produced by regional yards and increase green-house gas emissions from the transport of precast concrete, compared with a no-subsidy benchmark.

This paper considers the transportation of prefabricated products in the construction industry. Prefabricated products can be transported by road transport or intermodal transport, the latter of which incurs lower carbon emissions. A construction contractor always selects the transport mode with a lower cost rather than one with a lower carbon emission. A bi-level programming model was formulated to decide the optimal subsidy for intermodal transport to achieve the lowest carbon emissions while accounting for the cost minimization decisions faced by construction contractors who use prefabricated products. A numerical example was conducted to demonstrate the effectiveness of the proposed model. This research is important with regard understanding carbon emissions and how they relate to transportation options for industry.

More than ten billion tons of construction waste are generated every year in the world. The large volume of construction waste not only increases costs for contractors, but also poses a threat to the environment. A significant proportion of construction waste consists of off-cuts of raw materials. Therefore, to reduce construction waste, this study builds an optimization model to reduce the volume of off-cuts of raw materials. We then develop two solution methods—a mixed-integer linear programming method and a column generation method—to solve the proposed optimization model. We conduct numerical experiments to test the efficiency and applicability of our proposed model. The mixed-integer linear programming method obtains optimal solutions and is suitable for solving small-scale instances, whereas the column generation method gives high-quality solutions within seconds and is suitable for solving large-scale instances. In the large-scale instances, the column generation method reduces waste by over 10% compared to the use of two straightforward decisions rules. Our findings will help construction projects decrease material off-cuts, reduce costs, and achieve sustainable construction.

A huge amount of construction waste is generated in construction sites every day that needs to be transported by vehicle to disposal facilities for processing. Unlike in most typical transportation problems, once these vehicles are loaded with construction waste, they must travel directly to the disposal facility. Moreover, there are different types of construction waste that may require handling by different disposal facilities. In this paper, we develop a model and algorithm for identifying the optimal transportation routes specific to construction waste transportation. Our results can not only minimize the overall costs for both the logistics company and the contractor but also minimize the distance traveled, thus reducing urban traffic emissions.