COSORE: A community database for continuous soil respiration and other soil‐atmosphere greenhouse gas flux data

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil‐to‐atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of high‐frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open‐source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long‐term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soil‐atmosphere measurements (e.g. ecosystem respiration, chamber‐measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package

A Study on Quality of Life after Thoracoscopic Assistant Lobectomy for Lung Cancer

Background and objective Conventional radical surgeries for lung cancer incur a large amount of trauma, thoracoscopic surgeries can reduce trauma, and hopefully improve patients’ postoperative quality of life (QOL). The aim of this study is to evaluate the impact of thoracoscopic radical surgeries on quality of life of patients with non-small cell lung cancer (NSCLC). Methods Use Quality of Life-Core 30 Questionnaire (QLQ-C30) which was exploited by European Organization for Research and Treatment (EORTC) and Quality of Life-Lung Cancer 13 Questionnaire (QLQ-LC13) which is the supplementary questionnaire according to the lung cancer patients to evaluate QOL of 60 NSCLC patients in thoracoscopic surgery group and conventional surgery group from 3 days before operation to 24 weeks after operation. Results A total of 215 questionnaires were collected from 60 patients; 25 postoperative questionnaires were not completed because patients could not be contacted for follow-up visits. QOL declined markedly in all patients at 3 days postoperatively; preoperative and 3-day postoperative global QOL scores in the conventional surgery and thoracoscopic surgery group were 87.8±10.3 vs 38.3±13.1 (P<0.001) and 82.7±9.6 vs 56.3±14.8 (P<0.001), respectively. Thereafter, QOL recovered gradually in all patients. Patients who underwent open surgery showed the most pronounced decline in QOL; global scores were lower in this group than in the thoracoscopic surgery group (P=0.012,9) at 3 days postoperatively and was not restored to the preoperative level at 24 weeks postoperatively (P=0.012,4). QOL declined less in patients undergoing thoracoscopic surgery, and most indices had recovered to preoperative levels at 24 weeks postoperatively. Conclusion With the advantages of small trauma, faster recovery and higher postoperative QOL, thoracoscopic surgery is a preferable lung cancer surgery

UrbanKFS

Soil mode

BERT-ERC: Fine-Tuning BERT Is Enough for Emotion Recognition in Conversation

Previous works on emotion recognition in conversation (ERC) follow a two-step paradigm, which can be summarized as first producing context-independent features via fine-tuning pretrained language models (PLMs) and then analyzing contextual information and dialogue structure information among the extracted features. However, we discover that this paradigm has several limitations. Accordingly, we propose a novel paradigm, i.e., exploring contextual information and dialogue structure information in the fine-tuning step, and adapting the PLM to the ERC task in terms of input text, classification structure, and training strategy. Furthermore, we develop our model BERT-ERC according to the proposed paradigm, which improves ERC performance in three aspects, namely suggestive text, fine-grained classification module, and two-stage training. Compared to existing methods, BERT-ERC achieves substantial improvement on four datasets, indicating its effectiveness and generalization capability. Besides, we also set up the limited resources scenario and the online prediction scenario to approximate real-world scenarios. Extensive experiments demonstrate that the proposed paradigm significantly outperforms the previous one and can be adapted to various scenes

Spatial–Temporal Dynamics of Grassland Net Primary Productivity and Its Driving Mechanisms in Northern Shaanxi, China

Grasslands, a vital ecosystem and component of the global carbon cycle, play a significant role in evaluating ecosystem health and monitoring the global carbon balance. In this study, based on the Carnegie–Ames–Stanford Approach (CASA) model, we estimated the Net Primary Productivity (NPP) of grasslands in northern Shaanxi from 2000 to 2020. Employing trend analysis, stability analysis, multiple regression analysis, and residual analysis, the research examined the dynamic changes of grassland NPP and its response to climatic and human factors. Key findings include: (1) Grassland NPP showed a significant increasing trend during 2000–2020, with high-coverage grasslands showing a higher rate of increase than medium and low-coverage grasslands. (2) Most grasslands (>90%) exhibited unstable growth and high NPP fluctuation. (3) While temperature, precipitation, and radiation undulate, the trends were not significant. Rainfall and radiation emerged as dominant factors affecting NPP, with temperature suppressing NPP increase to some extent. (4) Policies like returning farmland to grassland had a positive impact on grassland recovery, vegetation productivity, and regional ecosystem health

An Analytical Approach to Ascertain Saturation-excess Versus Infiltration-excess Overland Flow in Urban and Reference Landscapes

Uncontrolled overland flow drives flooding, erosion, and contaminant transport, with the severity of these outcomes often amplified in urban areas. In pervious media such as urban soils, overland flow is initiated via either infiltration‐excess (where precipitation rate exceeds infiltration capacity) or saturation‐excess (when precipitation volume exceeds soil profile storage) mechanisms. These processes call for different management strategies, making it important for municipalities to discern between them. In this study, we derived a generalized one‐dimensional model that distinguishes between infiltration‐excess overland flow (IEOF) and saturation‐excess overland flow (SEOF) using Green–Ampt infiltration concepts. Next, we applied this model to estimate overland flow generation from pervious areas in 11 U.S. cities. We used rainfall forcing that represented low‐ and high‐intensity events and compared responses among measured urban versus predevelopment reference soil hydraulic properties. The derivation showed that the propensity for IEOF versus SEOF is related to the equivalence between two nondimensional ratios: (a) precipitation rate to depth‐weighted hydraulic conductivity and (b) depth of soil profile restrictive layer to soil capillary potential. Across all cities, reference soil profiles were associated with greater IEOF for the high‐intensity set of storms, and urbanized soil profiles tended towards production of SEOF during the lower intensity set of storms. Urban soils produced more cumulative overland flow as a fraction of cumulative precipitation than did reference soils, particularly under conditions associated with SEOF. These results will assist cities in identifying the type and extent of interventions needed to manage storm water produced from pervious areas