Spatiotemporal Variability and Environmental Controls of Temperature Sensitivity of Ecosystem Respiration across the Tibetan Plateau

Warming-induced carbon loss via ecosystem respiration(R_(e))is probably intensifying in the alpine grassland ecosystem of the Tibetan Plateau owing to more accelerated warming and the higher temperature sensitivity of R_(e)(Q_(10)).However,little is known about the patterns and controlling factors of Q_(10)on the plateau,impeding the comprehension of the intensity of terrestrial carbon-climate feedbacks for these sensitive and vulnerable ecosystems.Here,we synthesized and analyzed multiyear observations from 14 sites to systematically compare the spatiotemporal variations of Q_(10)values in diverse climate zones and ecosystems,and further explore the relationships between Q_(10)and environmental factors.Moreover,structural equation modeling was utilized to identify the direct and indirect factors predicting Q_(10)values during the annual,growing,and non-growing seasons.The results indicated that the estimated Q_(10)values were strongly dependent on temperature,generally,with the average Q_(10)during different time periods increasing with air temperature and soil temperature at different measurement depths(5 cm,10 cm,20 cm).The Q_(10)values differentiated among ecosystems and climatic zones,with warming-induced Q_(10)declines being stronger in colder regions than elsewhere based on spatial patterns.NDVI was the most cardinal factor in predicting annual Q_(10)values,significantly and positively correlated with Q_(10).Soil temperature(Ts)was identified as the other powerful predictor for Q_(10),and the negative Q_(10)-Ts relationship demonstrates a larger terrestrial carbon loss potentiality in colder than in warmer regions in response to global warming.Note that the interpretations of the effect of soil moisture on Q_(10)were complicated,reflected in a significant positive relationship between Q_(10)and soil moisture during the growing season and a strong quadratic correlation between the two during the annual and non-growing season.These findings are conducive to improving our understanding of alpine grassland ecosystem carbon-climate feedbacks under warming climates.

LncRNA IDH1-AS1 sponges miR-518c-5p to suppress proliferation of epithelial ovarian cancer cell by targeting RMB47

Long noncoding RNA(lncRNA)IDH1 antisense RNA 1(IDH1-AS1)is involved in the progression of multiple cancers,but its role in epithelial ovarian cancer(EOC)is unknown.Therefore,we investigated the expression levels of IDH1-AS1 in EOC cells and normal ovarian epithelial cells by quantitative real-time PCR(qPCR).We first evaluated the effects of IDH1-AS1 on the proliferation,migration,and invasion of EOC cells through cell counting kit-8,colony formation,EdU,transwell,wound-healing,and xenograft assays.We then explored the downstream targets of IDH1-AS1 and verified the results by a dual-luciferase reporter,qPCR,rescue experiments,and Western blotting.We found that the expression levels of IDH1-AS1 were lower in EOC cells than in normal ovarian epithelial cells.High IDH1-AS1 expression of EOC patients from the Gene Expression Profiling Interactive Analysis database indicated a favorable prognosis,because IDH1-AS1 inhibited cell proliferation and xenograft tumor growth of EOC.IDH1-AS1 sponged miR-518c-5p whose overexpression promoted EOC cell proliferation.The miR-518c-5p mimic also reversed the proliferation-inhibiting effect induced by IDH1-AS1 overexpression.Furthermore,we found that RNA binding motif protein 47(RBM47)was the downstream target of miR-518c-5p,that upregulation of RBM47 inhibited EOC cell proliferation,and that RBM47 overexpressing plasmid counteracted the proliferation-promoting effect caused by the IDH1-AS1 knockdown.Taken together,IDH1-AS1 may suppress EOC cell proliferation and tumor growth via the miR-518c-5p/RBM47 axis.

High-Resolution Recognition of Orbital Angular Momentum Modes in Asymmetric Bessel Beams Assisted by Deep Learning

Fractional orbital angular momentum(OAM) vortex beams present a promising way to increase the data throughput in optical communication systems. Nevertheless, high-precision recognition of fractional OAM with different propagation distances remains a significant challenge. We develop a convolutional neural network(CNN)method to realize high-resolution recognition of OAM modalities, leveraging asymmetric Bessel beams imbued with fractional OAM. Experimental results prove that our method achieves a recognition accuracy exceeding 94.3% for OAM modes, with an interval of 0.05, and maintains a high recognition accuracy above 92% across varying propagation distances. The findings of our research will be poised to significantly contribute to the deployment of fractional OAM beams within the domain of optical communications.

Improved HardNet and Stricter Outlier Filtering to Guide Reliable Matching

As the fundamental problem in the computer vision area,image matching has wide applications in pose estimation,3D reconstruction,image retrieval,etc.Suffering from the influence of external factors,the process of image matching using classical local detectors,e.g.,scale-invariant feature transform(SIFT),and the outlier filtering approaches,e.g.,Random sample consensus(RANSAC),show high computation speed and pool robustness under changing illumination and viewpoints conditions,while image matching approaches with deep learning strategy(such as HardNet,OANet)display reliable achievements in large-scale datasets with challenging scenes.However,the past learning-based approaches are limited to the distinction and quality of the dataset and the training strategy in the image-matching approaches.As an extension of the previous conference paper,this paper proposes an accurate and robust image matching approach using fewer training data in an end-to-end manner,which could be used to estimate the pose error This research first proposes a novel dataset cleaning and construction strategy to eliminate the noise and improve the training efficiency;Secondly,a novel loss named quadratic hinge triplet loss(QHT)is proposed to gather more effective and stable feature matching;Thirdly,in the outlier filtering process,the stricter OANet and bundle adjustment are applied for judging samples by adding the epipolar distance constraint and triangulation constraint to generate more outstanding matches;Finally,to recall the matching pairs,dynamic guided matching is used and then submit the inliers after the PyRANSAC process.Multiple evaluation metrics are used and reported in the 1st place in the Track1 of CVPR Image-Matching Challenge Workshop.The results show that the proposed method has advanced performance in large-scale and challenging Phototourism benchmark.

Low-Temperature Growing Anatase TiO2/SnO2 Multi-dimensional Heterojunctions at MXene Conductive Network for High-Efficient Perovskite Solar Cells

A multi-dimensional conductive heterojunction structure,composited by TiO2,SnO2,and Ti3C2TX MXene,is facilely designed and applied as electron transport layer in efficient and stable planar perovskite solar cells.Based on an oxygen vacancy scramble effect,the zero-dimensional anatase TiO2 quantum dots,surrounding on two-dimensional conductive Ti3C2TX sheets,are in situ rooted on three-dimensional SnO2 nanoparticles,constructing nanoscale TiO2/SnO2 heterojunctions.The fabrication is implemented in a controlled lowtemperature anneal method in air and then in N2 atmospheres.With the optimal MXene content,the optical property,the crystallinity of perovskite layer,and internal interfaces are all facilitated,contributing more amount of carrier with effective and rapid transferring in device.The champion power conversion efficiency of resultant perovskite solar cells achieves 19.14%,yet that of counterpart is just 16.83%.In addition,it can also maintain almost 85%of its initial performance for more than 45 days in 30–40%humidity air;comparatively,the counterpart declines to just below 75%of its initial performance.

Study of future power interconnection scheme in ASEAN

The current energy supply trajectory in the Association of Southeast Asian Nations(ASEAN)region is not sustainable.Factors such as rising standards of living and demographic patterns,including population growth,lead to continuous increase in power demand,which is difficult to meet using limited fossil fuel resources.Thus,a transition toward clean energy sources is needed in the region.While ASEAN member countries are rich in clean energy resources,such resources are located far from demand centers;thus,allocation of clean energy is necessary to increase its utilization.In this study,power demand is forecasted using a combination of prediction methods.A model to evaluate the installed capacity and power exchange potential is proposed to deal with mismatch between the location of the clean energy base and the load center.Furthermore,the concept of cross-regional allocation of clean energy between the ASEAN region,China,and South Asia is presented.A power interconnection scheme among the ASEAN member countries as well as neighboring countries is proposed based on the power exchange potential.The proposed grid interconnection scheme contributes to the utilization of clean energy in the ASEAN region,increasing the proportion of clean energy in the generation mix,which ensures that the region becomes a sustainable and resilient society with a clean and low carbon development route.Furthermore,the proposed power interconnection scheme will generate valuable economic,social,environmental,and resource allocation benefits.

Parameters Sensitivity Analysis and Correction for Concrete Damage Plastic Model

In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through a convenient cube unit test was conducted. The results showed that the peak strength strain was independent of the hardening ductility parameter DH,but affected by AH,BH,and CH. The softening ductility was mainly related to the softening ductility parameter AS,but not affected by the damage ductility exponent BS. In case that the model with default parameters failed to match the AS-controlled damage softening phase,an optimized model with an AS correction was developed. The corrected model with the AS value of 2 matched well with the code model,and exhibited good feasibility in predicting the stress-strain curve of different grades of concrete. Moreover,the practicability of the corrected model was further validated by the conventional triaxial test. The simulated curve exhibited favorable consistence with the trial curve. Therefore,the model with parameter correction could provide a prospective reference for predicting the mechanical properties of concrete.

Research on Satisfaction of ex situ Relocated Households

Based on the survey data of ex situ relocated households in Hubei and Hunan provinces in 2017,the specific satisfaction levels of the relocated farmers in the two provinces and the influencing factors were analyzed in this paper. It is found that the ex situ relocated farmers in Hubei and Hunan provinces have higher levels of satisfaction. The satisfaction of farmers who have been relocated to poverty alleviation is obviously affected by the characteristics of relocation and support policies. Even after controlling the farmer individual characteristic variables and family characteristic variables,the relocation characteristics and support policies still have a significant impact on the satisfaction of the farmers in the anti-poverty relocation,indicating that the relocated farmers with different backgrounds have a similar understanding of the satisfaction of the ex situ anti-poverty relocation.

Diffusion induced by bounded noise in a two-dimensional coupled memory system

The diffusion behavior driven by bounded noise under the influence of a coupled harmonic potential is investigated in a two-dimensional coupled-damped model. With the help of the Laplace analysis we obtain exact descriptions for a particle’s two-time dynamics which is subjected to a coupled harmonic potential and a coupled damping. The time lag is used to describe the velocity autocorrelation function and mean square displacement of the diffusing particle. The diffusion behavior for the time lag is also discussed with respect to the coupled items and the amplitude of bounded noise.

Study on Pinus elliottii Plantations in Pengchang Forest Farm of Jingmen City

[Objectives]This study was conducted to improve the ecological and economic benefits of Pinus elliottii plantations in Pengchang Forest Farm, Jingmen City. [Methods] P. elliottii plantations in Pengchang Forest Farm in Jingmen City were selected as the research object, and the appearance and quantitative characteristics of P. elliottii community were studied and analyzed by a sampling method. [Results] Phanerophytes were the most in the P. elliottii community, accounting for 50%. In the community, except P. elliottii, the importance values of native plants were higher. The order of species diversity of P. elliottii community in Pengchang Forest Farm was herb layer, tree layer and shrub layer. The stress resistance of the community was weak, and strong intraspecific competition existed in P. elliottii. It is recommended to thin P. elliottii trees with insufficient lighting, poor growth potential and severely damaged tree body, and interplant Phoebe zhennan after thinning the P. elliottii plantations, so as to create a coniferous and broad-leaved evergreen mixed forest. [Conclusions] This study provides scientific support for thinning, tending, and forest management of P. elliottii plantations.

The High Surface Ratio Micro-MoS₂Grain Composed of MoS₂Nanosheet Prepared with One-Step Hydrothermal Synthesis

Micro molybdenum disulfide was prepared with one-step hydrothermal method;the influence of reactant concentration and temperature on the surface ratio of micro-MoS2 grain was investigated. Raman spectroscopy (Raman), X-ray diffraction (XRD), and Scanning electron microscopy (SEM) were used to characterize the structure, composition and morphology of MoS2. The results show that micro-MoS2 grains were synthesized with one-step hydrothermal synthesis, and the morphology of micro-MoS2 grains is like flower and sphere. The SEM figures indicate that the surface ratio of micro-MoS2 grains is different and also show that the surface ratio of micro-MoS2 grains can be improved by regulating reactant concentration and temperature. This research showed a method to improve the surface ratio of micro-MoS2 grains.

气候作用对沥青混合料性能的影响

气候作用(如雨、日、冰)是沥青路面老化的主要原因之一,这些气候因子对沥青混合料影响可能是长期雨天或晴天的老化过程,也可能是由于温度变化范围大而引起的一系列冻融循环,然而,室内研究主要集中在气候作用的短期效应上。因此,本文针对两种不同的沥青混合料(密级配和开级配),分析长期受潮、多次冻融循环和不同热老化时间下其强度和刚度的变化规律。研究发现:在水分作用下空隙率对沥青混合料的长期性能演变有显著影响,这是一个不同于其他两种气候因子的可逆过程。另一方面,冻融循环对密级配沥青混合料的影响更大,无论空隙率如何,冻融循环都是一个短期过程,而热老化对两种沥青混合料的性能变化最小。

几何偏差对可控扩散叶型性能影响规律及机理

为了研究几何偏差对叶型性能的影响规律和机理,采用Hicks-Henne函数模化叶型轮廓度偏差、轮廓度变化率偏差,并叠加在可控扩散叶型(CDA)上,对偏差叶型进行了S1流面数值计算。计算结果表明,轮廓度变化率较小时,叶型性能随正负轮廓度偏差幅值的变化趋势是对称的,但轮廓度变化率较大时,正负轮廓度偏差均会导致叶型性能下降,正偏差的影响超过负偏差。几何偏差造成的附面层局部分离甚至提前转捩是叶型性能降低的主要原因。基于上述研究建立了CDA叶型几何偏差敏感区,敏感区域包括距离前缘5%弦长以内的叶型区域及附面层转捩点之前的吸力面区域。偏差敏感区有利于改进加工公差准则,降低压气机气动性能风险。

Sulfation of chondroitin and bile acids converges to antagonize Wnt/β-catenin signaling and inhibit APC deficiency-induced gut tumorigenesis

Sulfation is a crucial and prevalent conjugation reaction involved in cellular processes and mammalian physiology.3’-Phosphoadenosine 5’-phosphosulfate(PAPS)synthase 2(PAPSS2)is the primary enzyme to generate the universal sulfonate donor PAPS.The involvement of PAPSS2-mediated sulfation in adenomatous polyposis coli(APC)mutation-promoted colonic carcinogenesis has not been reported.Here,we showed that the expression of PAPSS2 was decreased in human colon tumors along with cancer stages,and the lower expression of PAPSS2 was correlated with poor prognosis in advanced colon cancer.Gut epithelial-specific heterozygous Apc deficient and Papss2-knockout(Apc^(Δgut-Het)Papss2^(Δgut))mice were created,and the phenotypes were compared to the spontaneous intestinal tumorigenesis of Apc^(Δgut-Het)mice.Apc^(Δgut-Het)Papss2^(Δgutmice) were more sensitive to gut tumorigenesis,which was mechanistically accounted for by the activation of Wnt/β-catenin signaling pathway due to the suppression of chondroitin sulfation and inhibition of the farnesoid X receptor(FXR)-transducin-like enhancer of split 3(TLE3)gene regulatory axis.Chondroitin sulfate supplementation in Apc^(Δgut-Het)Papss2^(Δgutmice) alleviated intestinal tumorigenesis.In summary,we have uncovered the protective role of PAPSS2-mediated chondroitin sulfation and bile acids-FXR-TLE3 activation in the prevention of gut carcinogenesis via the antagonization of Wnt/β-catenin signaling.Chondroitin sulfate may be explored as a therapeutic agent for Papss2 deficiency-associated colonic carcinogenesis.

Dynamic Organization of Large-scale Functional Brain Networks Supports Interactions Between Emotion and Executive Control

Emotion and executive control are often conceptualized as two distinct modes of human brain functioning.Little,however,is known about how the dynamic organization of large-scale functional brain networks that support flexible emotion processing and executive control,especially their interactions.The amygdala and prefrontal systems have long been thought to play crucial roles in these processes.Recent advances in human neuroimaging studies have begun to delineate functional organization principles among the large-scale brain networks underlying emotion,executive control,and their interactions.Here,we propose a dynamic brain network model to account for interactive competition between emotion and executive control by reviewing recent resting-state and task-related neuroimaging studies using network-based approaches.In this model,dynamic interactions among the executive control network,the salience network,the default mode network,and sensorimotor networks enable dynamic processes of emotion and support flexible executive control of multiple processes;neural oscillations across multiple frequency bands and the locus coeruleus−norepinephrine pathway serve as communicational mechanisms underlying dynamic synergy among large-scale functional brain networks.This model has important implications for understanding how the dynamic organization of complex brain systems and networks empowers flexible cognitive and affective functions.

Structure and mechanical properties of windmill palm fiber with different delignification treatments

The removal of lignin from natural cellulose fibers is a crucial step in preparing high-performance materials,such as compressed high-toughness composites.This process can eliminate non-cellulosic impurities,create abundant compressible pores,and expose a greater number of active functional groups.In this study,biomass waste windmill palm fiber was used as the raw mate-rial to prepare holocellulose fibers through various chemical treatments.The structure,chemical composition,Fourier transform infrared spectroscopy analysis,X-ray diffraction analysis,ther-mal properties,and mechanical properties,particularly fatigue performance,were studied.The sodium chlorite treated fiber had the highest crystallinity index(61.3%)and the most complete appearance structure.The sodium sulfite treated fiber had the highest tensile strength(227.34±52.27)MPa.Hydroxide peroxide treatment removed most of the lignin and hemicellulose,increas-ing the cellulose content to 68.83%±0.65%.However,all the chemical treatments decreased the thermal property of the fibers.

LDTR:Transformer-based lane detection with anchor-chain representation

Despite recent advances in lane detection methods,scenarios with limited-or no-visual-clue of lanes due to factors such as lighting conditions and occlusion remain challenging and crucial for automated driving.Moreover,current lane representations require complex post-processing and struggle with specific instances.Inspired by the DETR architecture,we propose LDTR,a transformer-based model to address these issues.Lanes are modeled with a novel anchorchain,regarding a lane as a whole from the beginning,which enables LDTR to handle special lanes inherently.To enhance lane instance perception,LDTR incorporates a novel multi-referenced deformable attention module to distribute attention around the object.Additionally,LDTR incorporates two line IoU algorithms to improve convergence efficiency and employs a Gaussian heatmap auxiliary branch to enhance model representation capability during training.To evaluate lane detection models,we rely on Fr´echet distance,parameterized F1-score,and additional synthetic metrics.Experimental results demonstrate that LDTR achieves state-of-the-art performance on well-known datasets.

Identification of TMEM217 as a novel prognostic biomarker and potential therapeutic target in acute myeloid leukemia

Despite remarkable advances in molecular and cell biology of acute myeloid leukemia(AML),AML patients still frequently relapse and have low 5-year overall survival(OS)rates.1 It is worth noting that a recent study from the registry or clinical trial compilation has reported an improvement in the OS of adult AML patients,especially those under 60 years of age.

ASCFL:Accurate and Speedy Semi-Supervised Clustering Federated Learning

The influence of non-Independent Identically Distribution(non-IID)data on Federated Learning(FL)has been a serious concern.Clustered Federated Learning(CFL)is an emerging approach for reducing the impact of non-IID data,which employs the client similarity calculated by relevant metrics for clustering.Unfortunately,the existing CFL methods only pursue a single accuracy improvement,but ignore the convergence rate.Additionlly,the designed client selection strategy will affect the clustering results.Finally,traditional semi-supervised learning changes the distribution of data on clients,resulting in higher local costs and undesirable performance.In this paper,we propose a novel CFL method named ASCFL,which selects clients to participate in training and can dynamically adjust the balance between accuracy and convergence speed with datasets consisting of labeled and unlabeled data.To deal with unlabeled data,the prediction labels strategy predicts labels by encoders.The client selection strategy is to improve accuracy and reduce overhead by selecting clients with higher losses participating in the current round.What is more,the similarity-based clustering strategy uses a new indicator to measure the similarity between clients.Experimental results show that ASCFL has certain advantages in model accuracy and convergence speed over the three state-of-the-art methods with two popular datasets.