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Background: A scientifically sound validated foot and ankle specific score validated ab initio for different languages is missing. The aim of a project of the European Foot and Ankle Society (EFAS) was to develop, validate, and publish a new score(the EFAS-Score) for different European languages. Methods: The EFAS Score was developed and validated in three stages: (1) item (question) identificatio
Autumn phenology plays a key role in regulating the terrestrial carbon and water balance and their feedbacks to the climate. However, the mechanisms underlying autumn phenology are still poorly understood, especially in subtropical forests. In this study, we extracted the autumn photosynthetic transition dates (APTD) in subtropical China over the period 2003–2017 based on a global, fine-resolution
Extracting speaker-dependent paralinguistic information out of a person's voice, provides an opportunity for adaptive behaviour related to speaker information in speech processing applications. For instance, in audio-based conversational applications, adapting responses to the attributes of the correspondent is an integral part in making the conversations effective. Two speaker attributes that hum
Lake ice loss has been detected worldwide due to recent climate warming, yet spatially and temporally detailed information on the changes in global ice phenology does not exist. Here, we build a global lake ice phenology database comprising three lake ice phenologies—freeze-up, break-up, and ice duration—for each year across two centuries (1900–2099). The timing of all three phenologies experience
The effects of insect herbivores on forest functioning are not well understood even though they can have important impacts on ecosystem processes by intercepting foliage before resorption and depositing nutrient-rich materials to the soil. In this thesis, I investigated the impact and drivers of insect folivores on carbon (C), nitrogen (N), phosphorus (P) and silica (Si) cycling in broadleaf fores
This study focused on improving the performance of the near real-time Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Early Run (IMERG-E) product based on a newly developed bias-correction scheme, LSCDF. The LSCDF was established by integrating the mean-based Linear Scaling (LS) and quantile-mapping Cumulative Distribution Function (CDF) matching approaches. The
Streptococcus pneumoniae (pneumococcus) is an asymptomatic colonizer of the nasopharynx in most individuals but can progress to a pulmonary and systemic pathogen upon influenza A virus (IAV) infection. Advanced age enhances host susceptibility to secondary pneumococcal pneumonia and is associated with worsened disease outcomes. The host factors driving those processes are not well defined, in part
Agricultural ecosystem water use efficiency (WUE) is an important indicator reflecting carbon-water coupling, but its control mechanisms in managed fields remain unclear. In order to reveal the influencing factors of WUE in the agricultural field under mulched drip irrigation (DM), we carried out the 8-year continuous observations in a maize field from Northwestern China. The structural equation m
Multi-source merging is an established tool for improving large-scale precipitation estimates. Existing merging frameworks typically use gauge-based precipitation error statistics and neglect the inter-dependence of various precipitation products. However, gauge-observation uncertainties at daily and sub-daily time scales can bias merging weights and yield sub-optimal precipitation estimates, part
Clouds are essential elements within Earth's atmosphere, posing a challenge for cloud-resolving models in understanding the creation of new cloud ice particles from existing ice and liquid phases. Such ice initiation determines cloud microphysical and radiative properties, influencing cloud phase, precipitation and cloud extent/properties. To address this challenge effectively, it proves beneficia
Glacio-hydrological modeling is a key task for assessing the influence of snow and glaciers on water resources, essential for water resources management. The present study aims to enhance a conceptual hydrological model (namely Glacial Snow Melt (GSM)) by data-driven and swarm computing for enhancing the accuracy of rainfall runoff prediction. The proposed framework combines the conceptual hydrolo
This work presents an assessment of the precipitation deficit in the São Francisco River Basin (SFRB) based on temporal, seasonal and regional analyses of two decades of precipitation data products derived from satellite missions launched since 1997. The temporal analyses were performed by means of three 3-month SPI time series, consisting of 250 values each derived from TRMM, CHIRPS and PERSIANN-
An Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi-global land by combining three independent precipitation products. The performance of the ETCC-merged product was then evaluated against three refere
The cosmogenic radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Combining 7Be and 10Be measurements with an atmospheric transport model can not only improve our understanding of the radionuclide transport and deposition processes but also provide an evaluation of the transport process in the model. To simulate these aerosol tracers, it is critical to evaluate the in
The remote forcing from land surface changes in the Sahara is hypothesized to play a pivotal role in modulating the intensity of the East Asian summer monsoon (EASM) through ocean-atmospheric teleconnections. This modulation has far-reaching consequences, particularly in facilitating societal shifts documented in northern China. Here, we present a well-dated lake-level record from the Daihai Lake
This paper presents a novel method for 3D human pose and shape estimation from images with sparse views, using joint points and silhouettes, based on a parametric model. Firstly, the parametric model is fitted to the joint points estimated by deep learning-based human pose estimation. Then, we extract the correspondence between the parametric model of pose fitting and silhouettes in 2D and 3D spac
Climate warming has significantly advanced plant spring phenology in temperate and boreal biomes in the northern hemisphere. However, the response of subtropical forest phenology to climate change remains largely unclear. This study aimed to determine the spatiotemporal patterns of spring photosynthetic phenology in subtropical forests in China over the period 2002-2017 and explore its underlying
A novel multi-source data fusion method based on Bayesian inference (BIF) was proposed in this study to blend the advantages of in-situ observations and remote sensing estimations for obtaining accurate chlorophyll-a (Chla) concentration in Lake Taihu (China). Two error models (additive and multiplicative) were adopted to construct the likelihood function in BIF; the BIF method was also compared w
Accurate and timely monitoring of streamflow and its variation is crucial for water resources management in watersheds. This study aimed at evaluating the performance of two process-driven conceptual rainfall-runoff models (HBV: Hydrologiska Byråns Vattenbalansavdelning, and NRECA: Non Recorded Catchment Areas) and seven hybrid models based on three artificial intelligence (AI) methods (adaptive n
This work presents an on-chip memory subsystem envisioned for real-time applications performing Oriented FAST and Rotated Brief (ORB) feature extraction for Simultaneous Localization and Mapping (SLAM) systems. For autonomous navigation of battery-powered devices, feature-based SLAM is a computationally frugal alternative to direct methods. This paper thoroughly analyses ORB multiple memory access
