Traditional Chinese medicine(TCM) is a valuable resource unique to China with a long history of human use and clinical practice, which can be analyzed to generate real-world evidence(RWE). The Chinese government has been actively promoting regulatory reform that is in line with the characteristics of TCM, optimizing the clinical evidence system for TCM, and exploring the important role of RWE in supporting the development of new drugs and regulatory decision-making for TCM. This article aims to provide a comprehensive review of the use of RWE in regulatory decisions for TCM. Based on the characteristics of TCM, this study focuses on the application scenarios, challenges and opportunities of RWE in TCM. And some suggestions are put forward to promote the wider application of RWE in TCM development and supervision.

A document by Jianzhi Ye. Click on the document to view its contents.

Profiling is one of the most effective enablers of compiler optimizations. Reports of speedups of 20-30% on top of highly optimized codes are common in the industry. Despite these gains, profiling is rarely used during development — rather, it is used during the generation of production-ready executables. Collecting profile information takes time, and reusing it across different versions of the same software leads to poor results, particularly for binary-level optimizations: small changes to the code might invalidate large portions of otherwise good data. This paper proposes a methodology to mitigate this problem. When mapping profile information from one program to a newer version of it, we use branch features, instead of addresses or hash of instructions, as anchor points between programs. Branch features have been used for decades as a way to predict the outcome of branches: they are characteristics of the branch, such as direction and opcode. By choosing good feature sets, it is possible to minimize collisions between branches, so that different branches seldom share the same features. We have modified the BOLT binary optimizer to use branch features to map profile information across programs. By optimizing three new versions of four large executables — Clang, GCC, MySQL, and PostgreSQL — we show that the new approach to reuse profile data yields speedups of about 8.00% over Clang -O3. In contrast, BOLT’s default mapping, which uses relative addresses as anchor points, yields speedups of 6.06%. Previous work based on hashing of basic blocks yields speedups of 5.02%.

Introduction:Acute intermittent porphyria (AIP) represents an autosomal dominant disorder stemming from a partial deficiency in the enzymatic activity of porphobilinogen deaminase, which is also referred to as hydroxymethylbilane synthase (HMBS), the third enzyme involved in the synthesis of heme. This deficiency leads to the accumulation of toxic heme metabolites, namely aminolevulinic acid (ALA) and porphobilinogen (PBG) (1) The precise mechanisms through which porphyrin precursors trigger the symptoms of AIP are not fully understood (1,2)AIP presents with a range of clinical manifestations that can be categorized into three distinct phases: the prodromal phase, the visceral symptom phase, and the neurological phase. Prominent clinical symptoms encompass the occurrence of acute neurovisceral episodes, marked by intense abdominal pain, mental disturbances, and heightened sympathetic activity (2)Acute attacks of porphyria can be precipitated by a range of factors, encompassing alcohol ingestion, stress, fasting, menstruation, surgical procedures, infection, and the administration of certain drugs (1,3). Preliminary assessment for AIP involves the detection of markedly elevated porphyrin levels in urinary, stool or serum during an acute attack, followed by subsequent genetic analysis to confirm the presence of HMBS gene mutations (4). The management of AIP encompasses a comprehensive approach that includes the management of acute attacks, prevention of future episodes, long-term monitoring, and the treatment of associated complications (2).Among the various acute porphyrias, AIP is recognized as a prevalent condition on a global scale, being both the most common and severe form among the acute hepatic porphyrias (5) AIP affects both males and females, however, in the context of AIP episodes, females tend to experience more severe impacts in terms of higher frequencies of attacks, longer durations of attacks, and an increased likelihood of requiring hospitalization (6).The HMBS gene is situated at the chromosomal position 11q23.3 and has been linked to more than 400 pathogenic mutations (5). Individuals harboring pathogenic variants of the HMBS gene, regardless of their symptomatic or latent status, are prone to experiencing acute attacks. Furthermore, chronic complications such as hepatocellular carcinoma, hypertension, and chronic renal failure can manifest in both symptomatic individuals with AIP and those who are asymptomatic but carry pathogenic HMBS variants (7).To date, limited knowledge exists regarding certain variants of pathogenic HMBS, particularly in low and middle-income countries such as Mexico. Consequently, there is uncertainty about the disease behavior in these individuals. Further research is warranted to address these gaps and enhance our understanding of AIP management in this specific patient population.

PEDIATRIC PRIMARY INTRAVENTRICULAR HEMORRHAGE: A CASE REPORT OF ISOLATED 4TH VENTRICLE HEMORRHAGE IN A 10-YEAR-OLD BOY

In recent years, Deep Neural Networks (DNNs) have been widely used for Human Gesture Recognition (HGR) based on the information obtained from inertial sensors, such as accelerometers and gyroscopes, available on smart Internet of Things (IoT) devices. Most of the recent works on HGR using motion data rely on gathering a dataset, that faces two major challenges: a) the datasets are originally stored on the smart devices at the end-users, and gathering them in one place is not feasible due to communication limitations, and b) clients are reluctant to share their private data with a central server due to privacy concerns. In this paper, we address these issues and propose a privacy-preserving framework based on Federated Learning (FL) for HGR using motion data, called Motion-based Federated Learning Gesture Recognition (MoFLeuR). Furthermore, we consider different types of data heterogeneity which have destructive effects on the performance of the global model. Accordingly, we propose a communication and computation-efficient client selection method that chooses the clients to mitigate the impact of data heterogeneity in the training process. In the proposed framework, clients are not requested to share sensitive information about their local datasets with the edge server in the FL process. Simulation results show that the proposed MoFLeuR algorithm improves the performance of the global model in the presence of different degrees of data heterogeneity, and it outperforms the baseline algorithms in terms of different metrics, namely accuracy, convergence speed, and communication and computation efficiency.

Plant communities are impacted by local (related to environmental filtering) and landscape (related to dispersal limitation) factors. While previous studies have shown that the relative importance of these factors varies depending on different aspects (i.e., spatial-temporal scale), little is known about how they are altered by urbanization—a significant threat to biodiversity. This study evaluates the relative importance of local environmental (local factors), landscape, and spatial (landscape factors) variables that influence plant communities in 34 urban green spaces comprising two different habitats (forests and grasslands) along the urban–rural gradients in the Tokyo megacity, Japan. To continuously assess the relative importance of each factor along the urban–rural gradients, we extracted 1,000 landscapes within a certain range that contained several sites. Subsequently, the relative importance of each factor and urbanization rate (proportion of artificial built-up area) was estimated at each landscape. The relative importance of the local factor increases, while the landscape factor decreases with urbanization, and the local factor becomes a primary factor in highly urbanized areas in forest habitats. However, the relative importance of the local factor decreases, whereas the landscape factor increases with urbanization in grassland habitats for native species. Collectively, these findings suggest that city size and target habitat characteristics must be considered when predicting changes in plant communities caused by urbanization.

This paper investigates the layered formation-containment control problem for multiple unmanned surface vehicles (USVs) with intermittent dynamic event-triggered protocols. Initially, the formation tracking controllers are designed for leaders to form the desired formation configuration along the reference trajectory in the first layer. In the proposed controllers, the intermittent framework is introduced to guarantee the stability of systems subject to inevitable factors including cyber-attacks or equipment constraints. Moreover, under the above intermittent framework, the dynamic event-triggered mechanism (DETM) is adopted to reduce the update frequency of control signals with positive minimum inter-event time (MIET) guarantees. Then, the containment controllers are developed for followers to converge to the convex hull spanned by leaders in the second layer. Besides, to remove the controllers’ dependency on global information, fully distributed thought is adopted in both layers. Finally, the theoretical analysis and simulation results are provided to evaluate the effectiveness of the proposed control scheme.

Scavenging by vertebrates is an important ecosystem service as they are known to remove carrion more efficiently than other taxa. How long would carrion persist bereft of vertebrate scavengers? Our study addresses this question in a forested landscape, by comparing carrion utilization by vertebrate scavengers, invertebrates, and microbes (decomposers). To understand carrion removal, we used experimental placement of chicken carcasses in a dry deciduous forest near Panna Tiger Reserve, Madhya Pradesh, India. Carcasses were placed under different treatment conditions (vertebrate scavenging, invertebrate scavenging, microbial decomposition and control to account for moisture loss), by experimentally excluding other scavengers. The daily rate of carcass utilization and proportion of carrion biomass remaining differed between treatments. Vertebrates consumed carcasses at the highest rates, removing 83% of carcass biomass in one day (CI 95%), followed by invertebrates (7.3%) and microbes (3.9%). Additionally, desiccation accounted for another 3.6% weight loss per day. The study showed drastic differences in carrion removal rates between taxa, indicating the irreplaceable role of vertebrates in the scavenging community of tropical forests, without whom carcasses would persist over prolonged periods. Our results support earlier studies that found overwhelming influence of vertebrate scavengers on carrion removal compared to other scavenging guilds.

Abstract Background There is currently no robust prognostic model for sarcomatous renal cell carcinoma (sRCC), which could help physicians make better decisions. Objectives To build an accurate predictive model for patients who have sRCC by investigating the important characteristics that influence the overall survival of patients. Design and Methods The Surveillance, Epidemiology and Results (SEER) database of the U.S. National Cancer Institute was used for gathering the dataset of sRCC patients. Following data preprocessing, the data was separated into the training set and the test set in an 8:2 ratio. Mann-Whitney U test and Chi-square test were used to verify whether the data set was evenly divided. Univariate Cox proportional hazard model, Kaplan-Meier analysis and machine learning (ML) algorithm were employed to identify the risk features on overall survival (OS). 10 reliable features were selected to construct six ML models. Model performance, predictive accuracy, and clinical benefits were evaluated by the receiver operating characteristic curves (ROC), calibration plots, and decision curve analysis (DCA) respectively. Results After data preprocessing, 692 patients with sRCC from 1975 to 2019 were included in this study. Ten variables including stage group, T stage, M stage, age, surgery, N stage, tumor size, chemotherapy, histological grade, and radiotherapy were selected as reliable features for machine learning model training. All the models show good prediction performance, among which XGBoost has the best prediction accuracy and stability. The DCA showed that all models except Adaboost could be used to support clinical decision-making with the 90-day, 1-, 2-, 3- and 5-year OS model. Conclusions Six machine learning models were developed to predict 90-day, 1-, 2-, 3- and 5-year overall survival in patients with sRCC. Model evaluations showed that the XGBoost model had the best predictive accuracy and clinical net benefit. These models can help make treatment decisions for patients with sRCC.

Rationale: Peak detection is an important step in mass spectrometry, accurately identifying characteristic peaks is key to data analysis. However, the spectrum being analyzed often contains random noise and baseline variations, which present significant challenges in the process of peak detection. In order to address the issue of false peak detection, while simultaneously ensuring accurate detection of weak and overlapped peaks, this paper introduces an improved algorithm for mass spectrometry integrating weighted continuous wavelet transform with particle swarm optimization-based Otsu (WWTPO). Methods: The algorithm utilizes the Mexican hat wavelet as the mother wavelet and applies the weighted continuous wavelet transform (WCWT) to compress the frequency spectrum signal into a smaller scale range, which allows for the acquisition of more distinct and informative peak information. Moreover, the algorithm employs the particle swarm optimization (PSO) algorithm to iteratively optimize the optimal image segmentation threshold, which addresses the challenge of inaccurate Otsu image segmentation. Furthermore, the algorithm effectively utilizes the information of ridge lines, valley lines and the original spectrum in the wavelet space to enable accurate identification of peak positions. Results: The proposed method was applied to detect simulated peaks as well as MALDI-TOF datasets. The performance evaluation was conducted using receiver operating characteristic (ROC) curves, F1 measure and F-scores. Through comparison with continuous wavelet transform (CWT) and genetic algorithm-based threshold segmentation (WSTGA), multi-scale peak detection (MSPD) and CWT and image segmentation (CWT-IS), the results demonstrated that the WWTPO method exhibits high performance in peak detection. Conclusions: This method not only maintains a low false peak identification rate but also detects more weak peaks and overlapping peaks, further improving the accuracy and efficiency of peak detection in mass spectrometry. It possesses a higher capability for efficient peak detection.

Retinoblastoma (RB) is a genetically predetermined intraocular malignant tumor, common in childhood, initiated by a mutation in the retnoblastoma gene (RB1), located on the long arm of chromosome13 (13q14). The lack of information on the genetics of RB in Bukavu motivated this study, with the aim of presenting the spectrum of mutations. Materials and methods This is an analytical cross-sectional study of 10 individuals, including 5 RB carrier children and 5 parents. Their deoxyrubonucleic acid (DNA) was extracted and 11 exons within the RB1 gene were amplified by Polymerase chain reaction, sequenced and analyzed by various bioinformatics tools. Result All the children had unilateral RB, diagnosed mostly at an age ≥2 years, male gender predominated, history of RB was absent in all subjects. A total of 11 of the 27 most frequently mutated exons that make up RB1 had been analyzed. The types of deleterious mutations found in exons 8 and 20 alone, in the 5 children and one parent, were of the following types: missense (26.6% vs. 16.7%), deletion (11.1% vs. 50%) and insertion (66.7% vs. 33.3%), generally associated with a frameshift and a splice site change. Disruption of protein synthesis was observed in all the children and in only one parent. Conclusion The deleterious genetic mutations identified by the study were known. The study suggested additional studies, integrating environmental factors that are currently believed to be involved in the occurrence of RB.

Rationale: Impurities refer to any substances that affect the purity of pharmaceuticals. Controlling impurities has always been a significant concern during drug development. Impurities impact the drug’s purity, diminish the efficacy of pharmaceuticals, and alter their appearance, physical, and chemical properties. Additionally, impurities can compromise the stability of pharmaceuticals and elevate their toxic and side effects. Methods: Impurity source analysis is the basis of drug impurity control. To clarify the source of impurity can optimize the synthesis process, prescription process, packaging and storage conditions of the pharmaceuticals, and control the impurity within a reasonable limit to achieve the ultimate goal of impurity research. Results: Analysis method is a means to obtain impurity information, and diversified analysis methods are also possible for effective control of different types of impurities. At present, there are relatively many quantitative studies on impurities, but there are still some challenges for the structure analysis of impurities, especially trace impurities. Conclusion: The research progress of drug impurity control and evaluation from the sources of various drug impurities and impurity analysis techniques was reviewed in this article, with the aim of providing references for the related research.

Systemic EBV positive T-cell lymphoma of childhood (S-EBV-TCL) is a rare disease for which there is no standard of care. S-EBV-TCL is often associated with hemophagocytic lymphohistiocytosis (HLH) and is generally thought of on the spectrum of Epstein-Barr Virus (EBV) related disease. For the few reported cases of cure in the literature, hematopoietic stem cell transplant (HSCT) has been required. Here, we present the case of one patient who was successfully cured with a modified regimen of dose adjusted EPOCH (etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin), followed by HSCT using a reduced intensity conditioning regimen.

Stable isotopes of the water molecule have emerged as powerful tracers of the sources and trajectories of water leading to precipitation, at different spatial and temporal scales. However, the high cost of commercially available rain samplers for isotopic analysis, have made using them for high spatial resolution networks and for studies being conducted in developing countries prohibitively expensive. We have designed a low-cost, simple, and robust rain sampler capable of sampling precipitation for isotopic analysis on the event and monthly scale, based on the existing designs provided in the literature. The event rain samplers were tested to determine the minimum amount of rainfall to minimize isotopic fractionation, both from post-sampling evaporation and equilibration. These new rain samplers will enable isotopic sampling of precipitation at high spatial resolutions. All the instructions for constructing and using these samplers are made openly accessible to the scientific community so they can easily be repeated and adapted to the needs of each project. This open access and low-cost methodology will help democratize the use of isotopes for hydrological studies in developing countries.

The traditional van Krevelen diagram, the nominal oxidation of organic carbon, and several aromaticity indexes generally considered C, H, O, N, P, and S factors, or just C, H, and O. However, these evaluated methods may provide incorrect interpretation for high-resolution mass data of organics containing halogen elements. Therefore, we adapted the van Krevelen diagram and the other indexes with halogen elements and verified with 2235 model organics. The results demonstrated that the modified van Krevelen diagram and the adjusted indexes were more accurate for the analysis of mass data, either in the compound classification or in the evaluation of oxidation state of organic matter.

Rationale: Many insect species undertake multi-generational migrations in the Afro-tropical and Palearctic ranges, and understanding their migratory connectivity remains challenging due to their small size, short life span and large population sizes. Hydrogen isotope ( δ 2H) can be used to reconstruct the movement of dispersing or migrating insects, but applying δ 2H for provenance requires a robust isotope baseline map (i.e., isoscape) for the Afro-Palearctic. Methods: We analysed the δ 2H in the wings ( δ 2H wing) of 142 resident butterflies from 56 sites across the Afro-Palearctic. The δ 2H wing values were compared to the predicted local growing-season precipitation δ 2H values ( δ 2H GSP) using a linear regression model to develop an insect wing δ 2H isoscape. We used multivariate linear mixed models and high-resolution and time-specific remote sensing climate and environmental data to explore the controls of the residual δ 2H wing variability. Results: A strong linear relationship was found between δ 2H wing and δ 2H GSP values (r 2=0.53). The resulting isoscape showed strong patterns across the Palearctic but limited variation and high uncertainty for the Afro-tropics. Positive residuals of this relationship were correlated with dry conditions for the month preceding sampling whereas negative residuals were correlated with more wet days for the month preceding sampling. High intra-site δ 2H wing variance was associated with lower relative humidity for the month preceding sampling and higher elevation. Conclusion: The δ 2H wing isoscape is applicable to trace butterflies, moths and other terrestrial herbivorous insects that migrate across the Afro-Palearctic range but has limited geolocation potential in the Afro-tropics. The spatial analysis of uncertainty using high-resolution climatic data demonstrated that many African regions with highly variable evaporation rates and relative humidity have δ 2H wing values that are less related to δ 2H GSP values. Increasing geolocation precision will require new modeling approaches using more time-specific environmental data and/or independent geolocation tools.

High-pressure natural gas pipeline transportation has the advantages of large gas transmission capacity, low transportation cost, whereas physical explosion of the pipeline may cause casualties and property losses. Based on the theory of conversion of physical explosion energy and TNT equivalent of high-pressure natural gas pipeline, this research uses HyperMesh software to build a physical explosion model of high-pressure natural gas pipeline. The crater generated by physical explosion of pipeline was simulated and analyzed using LS-DYNA software. It can be concluded that the crater building process was completed in 0.038 s, forming spindle shaped cavity crater (9.27 m×4.86 m×3.0 m). The overpressure value of the shock wave at the center of the ground burst is 6.64 MPa according to the simulation of the generation and attenuation process of the physical explosion shock wave. Based on Sadovsky’s research conclusion on shock wave attenuation, the minimum distance required for shock wave attenuation on the ground to the safe overpressure value (0.02 MPa) is 33 m. The research conclusion is of great significance to the prediction of the consequences of physical explosion damage of high-pressure natural gas pipeline and the determination of the safe laying scheme.

Bilateral tubal pregnancy (BTP) is the most uncommon form of tubal ectopic pregnancy. Complications are associated with maternal morbidity and mortality. We reported a case with a left tubal pregnancy and laparascopic salpingostomy was done. During the follow up the contralateral ectopic pregnancy was discovered and treated with MTX.

Age is necessary information for the study of life history of wild animals. A general method to estimate the age of odontocetes is counting dental growth layer groups (GLGs). However, this method is highly invasive as it requires the capture and handling of individuals to collect their teeth. Recently, the development of DNA-based age estimation methods has been actively studied as an alternative to such invasive methods, of which many have used biopsy samples. However, if DNA-based age estimation can be developed from fecal samples, age estimation can be performed without touching or disrupting individuals, thus establishing an entirely non-invasive method. We developed an age estimation model using the methylation rate of two gene regions, GRIA2 and CDKN2A, measured through methylation-sensitive high-resolution melting (MS-HRM) from fecal samples of wild Indo-Pacific bottlenose dolphins (Tursiops aduncus). The age of individuals was known through conducting longitudinal individual identification surveys underwater. Methylation rates were quantified from 36 samples. Both gene regions showed a significant correlation between age and methylation rate. The age estimation model was constructed based on the methylation rates of both genes which achieved sufficient accuracy (after LOOCV: MAE = 5.08, R2 = 0.34) for the ecological studies of the Indo-Pacific bottlenose dolphins, with a lifespan of 40-50 years. This is the first study to report the use of non-invasive fecal samples to estimate the age of marine mammals.

The increasing spread of marine non-indigenous species (NIS) due to the growth in global shipping traffic is causing widespread concern for the ecological and economic impacts of marine bioinvasions. Risk management authorities need tools to identify pathways and source regions of priority concern in order to better target efforts for preventing NIS introduction. The probability of a successful NIS introduction is affected by the probability that a marine species entrained in a transport vector will survive the voyage between origin and destination locations, and establish an independently reproducing population at the destination. Three important risk factors are voyage duration, range of environmental conditions encountered during transit, and environmental similarity between origin and destination. In this study, we aimed for a globally comprehensive approach of assembling quantifications of source-destination risk factors from every potential origin to every potential destination. To derive estimates of voyage-related marine biosecurity risk, we used computer-simulated vessel paths between pairs of ecoprovinces in the Marine Ecoregions Of the World biogeographic classification system. We used the physical length of each path to calculate voyage duration risk, and the cross-latitudinal extent of the path to calculate voyage path risk. Environmental similarity risk was based on comparing annual average sea surface temperature and salinity within each ecoprovince to those of other ecoprovinces. We derived three separate sets of risk quantifications, one each for voyage duration, voyage path, and environmental similarity. Our quantifications can be applied to studies that require source-destination risk estimates. They can be used separately or combined, depending on the importance of the types of source-destination risks that might be relevant to particular scientific or risk management questions or applications.

This paper describes the design of a hybrid coupler with a continuously variable output phase difference. This is achieved by using reconfigurable transmission lines with electrically tunable lengths controlled by two biasing voltages through varactor diodes placed across the coupler branches. The design of the coupler is based on the quadrature hybrid structure for the case where the output phase difference is 90° and on the asymmetric structure for the other cases. The proposed coupler can achieve a tunable output phase difference from 52 to 128 while keeping a coupling coefficient of -3dB (± 0.5dB) over the entire desired frequency band. To validate the simulated results, a prototype working at 3.5 GHz was fabricated and tested. The measurement results show good correspondence with the simulation results, especially when the output phase difference is 90° while a phase mismatch of less than 7° was observed for the other cases. The presented coupler would be a great asset for antenna feeding arrays, especially the Butler matrix.

In this paper, the problem of state estimation for a fractional-order neural networks system with uncertainties is studied by a sampled-data controller. First, considering the convenience of digital field, such as anti-interference, not affected by noise, a novel sampled-data controller is designed for the fractional-order neural network system of uncertainties with changeable sampling time. In the light of the input delay approach, the sampled-data control system of fractional-order is simulated by the delay system. The main purpose of the presented method is to obtain a sampled-data controller gain K to estimate the state of neurons, which can guarantee the asymptotic stability of the closed-loop fractional-order system. Then, the fractional-order Razumishin theorem and linear matrix inequalities (LMIs) are utilized to derive the stable conditions. Improved delay-dependent and order-dependet stability conditions are given in the form of LMIs. Furthermore, the sampled-data controller can be acquired to promise the stability and stabilization for fractional-order system. Finally, two numerical examples are proposed to demonstrate the effectiveness and advantages of the provided method.

Ecological stoichiometry is an important approach to understand the nutrient cycling and balance through the leaf-litter-soil system of Mongolian pine among different stand origins in desert regions. To reveal the variations in Mongolian pine carbon (C), nitrogen (N), and phosphorus (P) stoichiometry and stoichiometric homeostasis among different stand origins, we measured C, N, and P concentrations of leaves, litter, and soil, and analyzed the nutrient resorption efficiencies of leaves in differently aged plantations and natural forests from semi-arid and dry sub-humid regions. The results showed that (a) the stand origin had a significant effect on the C-N-P stoichiometry, and also significantly affected leaf N and P reabsorption efficiencies. Leaf N/P ratios indicated that Mongolian pine was co-limited by N and P in the NF, HB and HQ, and was mainly limited by P in MU. (2) With increasing stand age, C concentrations in the leaf-litter-soil system initially increased and then decreased, the N and P concentrations and reabsorption efficiencies in the leaf-litter-soil system were gradually increased. Overall, stand age had a significant effect on N concentrations, C/N and C/P ratios in the leaf-litter-soil system. (3) The C and N elements between the leaf-litter-soil system had a strong coupling relationship, and the P element between litter-soil had a strong coupling relationship. In addition, plantations exhibited greater N/P homeostasis than natural forests, and N/P exhibited greater homeostasis than N and P alone, which may be a nutrient utilization strategy for forests to alleviate N or P limitation. (4) Environmental factors have a significant influence on C-N-P stoichiometry in the leaf-litter-soil system, the most important soil properties and meteorological factors being soil water content and precipitation, respectively. These results will be essential to provide guidance for plantation restoration and management in desert regions.