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Sugarcane production supports the livelihoods of millions of small‐scale farmers in developing countries, and the bioenergy needs of millions of consumers. Yet, future sugarcane yields remain uncertain due to differences in climate projections, and because the sensitivity of sugarcane ecophysiology to individual climate drivers (i.e. temperature, precipitation, shortwave radiation, VPD and CO2) and their interactions is largely unresolved. Here we ask: how sensitive is sugarcane yield to future climate change, including climate extremes, and what are its key climate drivers? We combine the Soil‐Plant‐Atmosphere model with detailed time‐series measurements from experimental plots in Guangxi, China, and São Paulo State, Brazil. We first calibrated and validated modelled carbon and water cycling against field flux and biometric data. Second, we simulated sugarcane growth under the historical climate (1980–2018), and six future climate projections (2015–2100). We computed the ‘yield‐effect’ of each climate driver by generating synthetic climate forcings in which the driver time series was alternated to that of the historical median. In Guangxi, median yield and yield lows (i.e. lower decile) were relatively insensitive to forecast climate change. In São Paulo, median yield and yield lows decreased under all future climates projections (urn:x-wiley:17571693:media:gcbb12797:gcbb12797-math-0001 = −4% and −12% respectively). At Guangxi, where moisture stress was low, radiation was the principal driver of yield variability (yield‐effect urn:x-wiley:17571693:media:gcbb12797:gcbb12797-math-0002 = −1.2%). Conversely, high moisture stress at São Paulo raised yield sensitivity to temperature (yield‐effect urn:x-wiley:17571693:media:gcbb12797:gcbb12797-math-0003 = −7.9%). In contrast, a number of other modelling studies report a positive effect of increased temperatures on sugarcane yield. We ascribe the disparity between model predictions to the representation of key phenological processes, including the link between leaf ageing and thermal time, and the role of ageing in driving leaf senescence. We highlight climate sensitivity of phenological processes as a key focus for future research efforts.

During the next decades, combustion driven cars will be completely replaced by electrical vehicles (EVs) and it seems quite obvious that liquid electrolyte lithium-ion batteries (LIBs) will be the dominating energy storage system for the next at least 5 to 10 years. As a consequence, in Europe numerous Gigafactories have recently been planned with this state of technology. However, the current lithium-ion battery technology suffers so far from some restrictions like the inability to combine high power and high energy operations at the same time. This limitation is mainly attributed to the cathode architecture and respective mass loading. In addition, the further demand for a significantly enhanced fast charging mainly requires an optimization of the anode design flanked by a high areal capacity. Advanced 3D electrode architectures based on a thick film electrode concept seem to be the most promising approach to overcome the current limitations in battery performances. However, respective technology innovations need to provide a high compatibility grade to existing manufacturing routes in order to enable the required integration in existing and planned factories. For so-called “generation 3” materials, i.e., nickel-rich lithium nickel manganese cobalt oxide (NMC) cathode and silicon-based anode materials, structuring technologies using cutting edge ultrafast high power lasers, are being developed in order to manufacture 3D electrode architectures with high areal capacity. Multibeam laser processing using diffractive optical elements and dual scanner approaches were established in order to enable high processing speeds in roll-to-roll electrode handling systems. The technology readiness level (TRL 6) is demonstrated for pouch cells geometries. For water-based NMC 622 and silicon-graphite composites the laser structuring process was developed. Different structures including hole, grid, and line patterns, were studied regarding their impact on electrochemical performances such as high-rate capability and cell lifetime. Lithium concentration profiles of unstructured and structured electrodes were studied post mortem using laser-induced breakdown spectroscopy (LIBS) in order to evaluate lithium intercalation/deintercalation efficiencies and detect possible cell degradation processes. In comparison to unstructured electrodes, 3D electrodes could hereby always be identified as superior: unstructured thick film electrodes show a significant drop in capacity retention for high power operation and tend to form hot spots acting as starting point for cell failure. The upscaling process is flanked by a further improvement of electrode design. For this purpose very recently laser induced forward transfer (LIFT) is applied as printing technology to draw new concepts for sophisticated model electrode architectures with advanced electrochemical performances. Finally, the micro-/nano-scaled texturing of current collectors and separator material is discussed as further possible approaches for boosting the electrochemical performances of LIB pouch cells.

Medical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs. To facilitate the research and development of medical dialogue systems, we build large-scale medical dialogue datasets -- MedDialog, which contain 1) a Chinese dataset with 3.4 million conversations between patients and doctors, 11.3 million utterances, 660.2 million tokens, covering 172 specialties of diseases, and 2) an English dataset with 0.26 million conversations, 0.51 million utterances, 44.53 million tokens, covering 96 specialties of diseases. To our best knowledge, MedDialog is the largest medical dialogue dataset to date. We pretrain several dialogue generation models on the Chinese MedDialog dataset, including Transformer, GPT, BERT-GPT, and compare their performance. It is shown that models trained on MedDialog are able to generate clinically correct and doctor-like medical dialogues. We also study the transferability of models trained on MedDialog to low-resource medical dialogue generation tasks. It is shown that via transfer learning which finetunes the models pretrained on MedDialog, the performance on medical dialogue generation tasks with small datasets can be greatly improved, as shown in human evaluation and automatic evaluation. The datasets and code are available at https://github.com/UCSD-AI4H/Medical-Dialogue-System

The successful utilization of adsorption methods in the dye wastewater treatment had promoted us to develop inexpensive adsorbents from industrial and agricultural wastes. The work appraised the application potentiality of bamboo shoot skin (BSS) as an adsorbent. Batch adsorption of methylene blue (MB) was conducted to investigate the influence of the dosage of adsorbent, concentration of MB, time of adsorption, temperature, and initial pH value on the adsorption properties of BSS. Four frequently used adsorption kinetic models were utilized to fit the experimental results, and the pseudo-second-order kinetic model with big correlation coefficient could well describe the adsorption kinetics. The experimental equilibrium data were fitted by two frequently used adsorption isotherm models, and the Langmuir isotherm model described well. Its maximum adsorption capacity was 29.88 mg/g. The obtained thermodynamic parameters indicated that the adsorption process was spontaneous and exothermic in nature. In addition, the adsorption mechanism and comparison of BSS with other adsorbents were also discussed.

Starch is one of the most popular biodegradable polymers in nature, which is gaining increasing attention because of its abundant availability and low cost. However, starch film itself is very brittle and its barrier property is poor for many applications. Polyvinyl alcohol (PVA), a versatile polymer in paper industry, is used to improve the barrier property of starch film. In this study, painting paper with exceptional barrier properties against organic solvents is successfully prepared for art creation purpose by coating a thin layer of environmentally friendly starch/PVA film on its surface. The coated paper can resist the penetration of the ink from marker pens. Furthermore, the solvent resistance and mechanical flexibility of freestanding starch/PVA hybrid film were investigated in detail. It found that the excellent barrier properties of the coated painting paper against solvents are due to the superior solvent resistance and mechanical flexibility of starch/PVA hybrid film. Therefore, the biodegradable and cost-effective strategy in this study provides a promising approach to enhance the barrier property of painting paper against solvents, which can find potential applications in painting field.

The incoming water area of the Central Line Project of the South-to-North Water Diversion comprises the upper reaches of the Han River in China. Bacterioplankton are important members of river ecosystems. However, the mechanisms (deterministic or stochastic processes) regulating planktonic bacterial community structure in the upper Han River are not well understood. Herein, we documented the spatiotemporal patterns, assembly processes, and co-occurrence relationships of the planktonic bacterial communities in the Han River and its tributaries. Seasonal variations in bacterioplankton communities were clearly observed and were more obvious than spatial differences. The planktonic bacterial community showed a significant distance (dendritic distance) decay pattern during the two sampling periods, and the distance decay pattern was stronger in spring than in the other season. Network analysis showed that bacterial community networks displayed non-random co-occurrence patterns, and significant differences in the topological properties of empirical and random networks (average clustering coefficient, average path length, and average degree) were found. Compared to those of the tributaries, the network of the mainstem had the lowest modularity; this may be caused by the significant difference in biodiversity between the mainstem and the tributaries. Redundancy analysis revealed that pH exhibited significant effects on the planktonic bacterial community in both seasons. However, variation partitioning analysis showed that spatial factors (stochastic processes) contributed more to explaining community assembly than environmental factors during the two seasons. In addition, the neutral community model can also explain a large part of the community variation observed during the autumn and spring (R2 = 0.817 and 0.808, respectively). This study shows that seasonal variation in the bacterial community is greatly influenced by seasonal environmental variation. However, stochastic processes dominantly affect the structure of the bacterioplankton community within seasons. In order to effectively manage and protect microbial diversity, managers consider not only local species diversity, but also the effect of regional species dispersal.

Highlights • We tested patterns of multi-faceted beta diversity across mountain streams. • All three facets of beta diversities increase from the north slope to south slope. • Spatial variables were most important in structuring three facets of beta diversity. • Functional and phylogenetic beta diversity complement to taxonomic beta diversity. • Combining multi-faceted biodiversity is essential for management and conservation. There is a growing recognition that examining patterns of ecological communities and their underlying determinants is not only feasible based on taxonomic data, but also functional and phylogenetic approaches. This is because these additional facets can enhance the understanding of the relative contribution of multiple processes in shaping biodiversity. However, few studies have focused on multifaceted beta diversities in lotic macroinvertebrates, especially when considering driving factors operating at multiple spatial scales. Here, we examined the spatial patterns of multi-faceted (i.e., taxonomic, functional and phylogenetic) beta diversity and their components (i.e., turnover and nestedness) of macroinvertebrates in 50 sites in 10 streams situated in the north and south slope of the Qinling Mountains, the geographical dividing line of Northern and Southern China. We found that the streams draining the north slope showed significantly lower values of beta diversity based on all three facets than the streams draining the south slope. Such north-to-south increases of beta diversity were caused by the distinct climatic and local environmental conditions between the sides of the mountain range. Moreover, spatial variables generally played the most important role in structuring all facets and components of beta diversity, followed by local environmental and climatic variables, whereas catchment variables were less important. Despite the similar results of relative contribution of explanatory variables on each beta diversity facet, the details of community-environment relationships (e.g., important explanatory variables and explanatory power) were distinct among different diversity facets and their components. In conclusion, measuring functional and phylogenetic beta diversity provides complementary information to traditional taxonomic approach. Therefore, an integrative approach embracing multiple facets of diversity can better reveal the mechanisms shaping biodiversity, which is essential in assessing and valuing aquatic ecosystems for biodiversity management and conservation.

The Weihe River is the largest tributary of the typically sediment-laden Yellow River in China. Assuming that high sediment concentrations may increase the turbidity of water bodies, and therefore affect riverine ecosystem, in which the bacterioplankton are crucial components and serve as important indicators of environmental and ecological status through their structure and response to the environment change, it is essential to deep understanding the bacterioplankton structure and influencing factors in turbid and clear river ecosystems. Here, high-throughput sequencing was used to analyze the differences in bacterioplankton structure and major determinants in the typically turbid Weihe River and its clear tributaries from the northern foot of the Qinling Mountains from October to November 2017 and April to May 2018. The results demonstrated that bacterioplankton communities shared similar dominant subcommunities in the Weihe River mainstem and its tributaries, mainly consisting of Proteobacteria and Bacteroidetes phyla and Flavobacterium and Acinetobacter genera. The Faith phylogenetic diversity (PD) index was significantly higher in the turbid mainstem than in the tributaries and was related to turbidity (Turb). Variation partitioning analysis (VPA) showed that geographical distance exhibited notable influences on the community composition in the mainstem; however, the communities in the tributaries had a much stronger response to local environmental factors. Bacteria exhibited a significant distance-decay relationship in the mainstem, whereas geographical distance was not correlated with community dissimilarities in the tributaries. Chlorophyll a emerged as the major determinant of the bacterioplankton structure in the turbid Weihe River, indicating the importance of phytoplankton-bacterioplankton relationships in the turbid river system. These results provide important insights into future research on microbial ecology, environmental monitoring and classified management in diverse river systems.

Graphical abstract, Highlights • The conductive TOCFs network is achieved by an electrostatic self-assembly process. • The paper sensor shows high sensitivity, excellent linearity, and long-time stability. • The paper sensor exhibits superior bending and folding durability. • The sensor shows good responses to human breath, fingertip humidity, and air humidity., Humidity sensors have been widely used for humidity monitoring in industrial fields. However, the application of conventional sensors is limited due to the structural rigidity, high cost, and time-consuming integration process. Owing to the good hydrophilicity, biodegradability, and low cost of cellulose, the sensors built on cellulose bulk materials are considered a feasible method to overcome these drawbacks while providing reasonable performance. Herein, we design a flexible paper-based humidity sensor based on conductive 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose fibers/carbon nanotubes (TOCFs/CNTs) conformal fibers network. The CNTs are dispersed by cationic cetyl trimethyl ammonium bromide (CTAB), which introduces positive charges on the CNTs surface. The conductive fibers are achieved by an electrostatic self-assembly process that positively charged CNTs are adsorbed to the surface of negatively charged TOCFs. The vast number of hydrophilic hydroxyl groups on the surface of TOCFs provide more water molecules adsorption sites and facilitate the electron transfer from water molecules to CNTs, endowing the sensor with an excellent humidity responsive property. Besides, the swelling of the TOCFs greatly damages the conductive CNTs network and further promotes the humidity sensitive performance of the sensor. Benefiting from the unique structure, the obtained sensor exhibits a maximum response value of 87.0% (ΔI/I0, and the response limit is 100%), outstanding linearity (R2 = 0.995) between 11 to 95% relative humidity (RH), superior bending (with a curvature of 2.1 cm−1) and folding (up to 50 times) durability, and good long-time stability (more than 3 months). Finally, as a proof of concept, the sensor demonstrates an excellent responsive property to human breath, fingertip humidity, and the change of air humidity, indicating a great potential towards practical applications.

This paper assesses the value of multi-scale near-surface (0∼5 cm) soil moisture observations to improve state-only or state-parameter estimation based on the ensemble Kalman filter (EnKF). To the best of our knowledge, studies on assimilating multi-scale soil moisture data into a distributed hydrological model with a series of detailed vertical soil moisture profiles are rare. Our analysis factors include spatial measurement scales, soil spatial heterogeneity, multi-scale data with contrasting information and systematic measurement errors. Results show that coarse-scale soil moisture data are also very useful for identifying finer-scale parameters and states given biased initial parameter fields, but it becomes increasingly difficult to recover the finer-scale spatial heterogeneity of soil property as the observation grids become coarser. In state-only estimation, near-surface soil moisture data result in improvement for shallow soil moisture profiles and degradation for deeper soil moisture profiles, with stronger influences from finer-scale data. With the decrease of background spatial heterogeneity of soil property, the value of coarse-scale data increases notably. Soil moisture data at two scales with contrasting information are found to be both useful. By updating spatially correlated soil hydraulic parameters, deviated observations still contain considerably useful information for finer-scale state-parameter estimation. Eventually, by presenting a difference information assimilation method based on EnKF we successfully extract useful information from soil moisture data containing systematic measurement errors. The current study can be extended to consider more complex atmosphere input and topography, etc.

In the past few decades, different data assimilation methods have been proposed to estimate soil parameters. It is not clear whether a straightforward sampling approach is sufficient or whether a linear filter or even an advanced nonlinear filter is needed to interpret the potential information carried by different data types (e.g., pressure head and water content data from multiple depths, easily available surface soil moisture data, and groundwater level data). In this study, three classical data assimilation methods, i.e., the ensemble Kalman filter (EnKF), the ensemble randomized maximum likelihood filter (EnRML), and the Markov chain Monte Carlo (MCMC), were investigated numerically in terms of the utility to cope with three different types of observations. Results show that, compared with the EnKF approach, EnRML is a superior method to extract the parameter information from observations. The MCMC approach performs well in homogeneous soil but not in heterogeneous soil. Regardless of the data assimilation methods and the soil heterogeneity, point-scale soil water pressure head data are the most valuable in terms of soil parameter estimation, followed by groundwater level data, which require a nonlinear filter to interpret. A smaller observation error for groundwater level data leads to obviously improved parameter estimates by using EnRML with a slight improvement by using EnKF. The stable performance of the EnKF method relies more heavily on a relatively large number of ensembles than the EnRML method, whereas only a few ensemble members are needed for EnRML in a homogeneous soil column.

Xi'an is an ancient historical and cultural city. In the process of building a national central city and an international metropolis with historical and cultural characteristics, it needs not only strong economic and technological support, but also the construction of its urban cultural atmosphere as an important image of Xi'an. Cultural atmosphere is the spiritual style of traditional culture, ideological character and behavior habit of a city. With the development of world culture and the change of people's life style, cultural atmosphere has become the key element of a city. The emphasis of creating the cultural atmosphere of urban public space in Xian Zhanba Ecological Zone is to mold the cultural theme of urban public space in accordance with the characteristics and attributes of different regions, aiming at the objects of urban public art, urban furniture and environmental art, and to use the cultural style of artistic design and the systematic design method of classification to embody it. The ecological characteristics of the Chan Ba ecological zone are "ecological, international and modern". Through systematic transformation and construction, the public space, public environment, public facilities and other software and hardware environment in the overall image of the Chenba Eco-Zone will be gradually upgraded, the cultural construction will be strengthened, the cultural image will be enhanced, the cultural soft power will be strengthened, and the cultural influence and external popularity of the Chenba Eco-Zone will be expanded, and the city will be promoted. Comprehensive and harmonious development.