Seasonal variation of phytoplankton community assembly processes in Tibetan Plateau floodplain

Uncovering the mechanisms underlying phytoplankton community assembly remains a major challenge in freshwater ecology. The roles of environmental filtering and spatial processes in shaping phytoplankton metacommunity in Tibetan floodplain ecosystems under various hydrological conditions are still unclear. Here, multivariate statistics and a null model approach were used to compare the spatiotemporal patterns and assembly processes of phytoplankton communities in the river-oxbow lake system of Tibetan Plateau floodplain between non-flood and flood periods. The results showed that phytoplankton communities had significant seasonal and habitat variations, with the seasonal variations being more remarkable. Phytoplankton density, biomass, and alpha diversity were distinctly lower in the flood than non-flood period. The habitat differences (rivers vs. oxbow lakes) in phytoplankton community were less pronounced during the flood than non-flood period, most likely due to the increased hydrological connectivity. There was a significant distance-decay relationship only in lotic phytoplankton communities, and such relationship was stronger in the non-flood than flood period. Variation partitioning and PER-SIMPER analysis showed that the relative role of environmental filtering and spatial processes affecting phytoplankton assemblages varied across hydrological periods, with environmental filtering dominating in the non-flood period and spatial processes in the flood period. These results suggest that the flow regime plays a key role in balancing environmental and spatial factors in shaping phytoplankton communities. This study contributes to a deeper understanding of ecological phenomena in highland floodplains and provides a theoretical basis for floodplain ecosystem maintenance and ecological health management.Peer reviewe

O Serviço Social nas Autarquias e a sua Importância para o Desenvolvimento Social Local

Aprofundar o conhecimento do Serviço Social e reflectir sobre a prática profissional do Assistente Social e a criação de políticas sociais com vista ao desenvolvimento social local, nomeadamente, na Câmara Municipal da Batalha, constituíram o objectivo de estudo. A descentralização do Poder Central para o Poder Local, assente na proximidade ao cidadão, mantém-se em discussão na agenda política e ganha maior relevo na conjuntura actual, com a reforma do Poder Local. Contudo, até ao momento, as transferências no âmbito da Acção Social mantêm-se bastante genéricas e sem regulamentação. Por essa razão, o Poder Local intervém na área social sem que essas competências estejam delineadas pela tutela e muitas vezes sem o devido financiamento, deixando aos Executivos Municipais a decisão sobre a criação de políticas sociais. Neste sentido, com o intuito de assegurarem os interesses das suas populações, as Câmaras Municipais implementam medidas sociais de âmbito local, que se revelam mais ou menos intensas, consoante o importância que lhes é dada por cada Executivo, que define as áreas de intervenção prioritárias e quais os recursos disponíveis para investir no domínio social. O Serviço Social revela ser um importante recurso das autarquias na criação das políticas sociais locais, na medida em que o Assistente Social, ao conhecer o território e intervir mais próximo dos cidadãos, pode propor programas de desenvolvimento local, adequados aos interesses da população. No caso particular da Câmara Municipal da Batalha, reflectiu-se sobre a prática da Assistente Social e evocaram-se as políticas sociais por esta planeadas e desenvolvidas, revelando o seu contributo para o desenvolvimento social do concelho. Atestou-se, em género de conclusão, que, apesar do Assistente Social ter um papel cada vez mais preponderante na execução das políticas de desenvolvimento local, a sua prática profissional tem limitações por não ser capaz, por si só, de resolver problemas sociais de génese estrutural, influenciados pela conjuntura nacional e internacional

Use of MicroRNA Let-7 to Control the Replication Specificity of Oncolytic Adenovirus in Hepatocellular Carcinoma Cells

Highly selective therapy for hepatocellular carcinoma (HCC) remains an unmet medical need. In present study, we found that the tumor suppressor microRNA, let-7 was significantly downregulated in a proportion of primary HCC tissues (12 of 33, 36.4%) and HCC cell lines. In line with this finding, we have engineered a chimeric Ad5/11 fiber oncolytic adenovirus, SG7011let7T, by introducing eight copies of let-7 target sites (let7T) into the 3′ untranslated region of E1A, a key gene associated with adenoviral replication. The results showed that the E1A expression (both RNA and protein levels) of the SG7011let7T was tightly regulated according to the endogenous expression level of the let-7. As contrasted with the wild-type adenovirus and the control virus, the replication of SG7011let7T was distinctly inhibited in normal liver cells lines (i.e. L-02 and WRL-68) expressing high level of let-7 (>300 folds), whereas was almost not impaired in HCC cells (i.e. Hep3B and PLC/PRF/5) with low level of let-7. Consequently, the cytotoxicity of SG7011let7T to normal liver cells was successfully decreased while was almost not attenuated in HCC cells in vitro. The antitumor ability of SG7011let7T in vivo was maintained in mice with Hep3B xenograft tumor, whereas was greatly decreased against the SMMC-7721 xenograft tumor expressing a high level of let-7 similar with L-02 when compared to the wild-type adenovirus. These results suggested that SG7011let7T may be a promising anticancer agent or vector to mediate the expression of therapeutic gene, broadly applicable in the treatment for HCC and other cancers where the let-7 gene is downregulated

Climate change impacts on solar power generation and its spatial variability in Europe based on CMIP6

Solar photovoltaics (PV) plays an essential role in decarbonizing the European energy system. However, climate change affects surface solar radiation and will therefore directly influence future PV power generation. We use scenarios from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for a mitigation (SSP1-2.6) and a fossil-fuel-dependent (SSP5-8.5) pathway in order to quantify climate risk for solar PV in Europe as simulated by the Global Solar Energy Estimator (GSEE). We find that PV potential increases by around 5 % in the mitigation scenario, suggesting a positive feedback loop between climate change mitigation and PV potential. While increased clear-sky radiation and reduced cloud cover go hand in hand in SSP1-2.6, the effect of a decrease in clear-sky radiation is outweighed by a decrease in cloud cover in SSP5-8.5, resulting in an increase in all-sky radiation. Moreover, we find that the seasonal cycle of PV generation changes in most places, as generation grows more strongly in winter than in summer (SSP1-2.6) or increases in summer and declines in winter (SSP5-8.5). We further analyze climate change impacts on the spatial variability of PV power generation. Similar to the effects anticipated for wind energy, we report an increase in the spatial correlations of daily PV production with large inter-model agreement yet relatively small amplitude, implying that PV power balancing between different regions in continental Europe will become more difficult in the future. Thus, based on the most recent climate simulations, this research supports the notion that climate change will only marginally impact renewable energy potential, while changes in the spatiotemporal generation structure are to be expected and should be included in power system design.ISSN:2190-4987ISSN:2190-497

Solar Radiation Nowcasting Using a Markov Chain Multi-Model Approach

International audienceSolar energy has found increasing applications in recent years, and the demand will continue to grow as society redirects to a more renewable development path. However, the required high-frequency solar irradiance data are not yet readily available everywhere. There have been endeavors to improve its forecasting in order to facilitate grid integration, such as with photovoltaic power planning. The objective of this study is to develop a hybrid approach to improve the accuracy of solar nowcasting with a lead time of up to one hour. The proposed method utilizes irradiance data from the Copernicus Atmospheric Monitoring Service for four European cities with various cloud conditions. The approach effectively improves the prediction accuracy in all four cities. In the prediction of global horizontal irradiance for Berlin, the reduction in the mean daily error amounts to 2.5 Wh m−2 over the period of a month, and the relative monthly improvement reaches nearly 5% compared with the traditional persistence method. Accuracy improvements can also be observed in the other three cities. Furthermore, since the required model inputs of the proposed approach are solar radiation data, which can be conveniently obtained from CAMS, this approach possesses the potential for upscaling at a regional level in response to the needs of the pan-EU energy transition

Multi-Model- and Soft-Transition-Based Height Soft Sensor for an Air Cushion Furnace

The floating height of the strip in an air cushion furnace is a key parameter for the quality and efficiency of production. However, the high temperature and high pressure of the working environment prevents the floating height from being directly measured. Furthermore, the strip has multiple floating states in the whole operation process. It is thus difficult to employ a single model to accurately describe the floating height in different states. This paper presents a multi-model soft sensor to estimate the height based on state identification and the soft transition. First, floating states were divided using a partition method that combined adaptive k-nearest neighbors and principal component analysis theories. Based on the identified results, a hybrid model for the stable state, involving a double-random forest model for the vibration state and a soft-transition model, was created to predict the strip floating height. In the hybrid model for the stable state, a mechanistic model combined thick jet theory and the equilibrium equation of force to cope with the lower floating height. In addition, a novel soft-transition model based on data gravitation that further reflects the intrinsic process characteristic was developed for the transition state. The effectiveness of the proposed approach was validated using a self-developed air cushion furnace experimental platform. This study has important value for the process prediction and control of air cushion furnaces

The corps’ growth with different water-saving irrigation conditions in new reclamation areas along the coast of Jiangsu

This study performed a quantitative evaluation of the impact of the corps’ growth with different water-saving irrigation conditions in new reclamation areas along the coast of Jiangsu. In this work, the yield and the amount of irrigation water of corps’ (watermelon, green pepper, and rice) with different water-saving irrigation modes were investigated. The results indicate that the drip-irrigation and micro-spray irrigation can observably reduce the amount of irrigation-water. With respect to normal irrigation, the rate of water-saving is 39.2%. At the same time, there’s been some improvement in the yield of corps. Water-saving irrigation can been accepted as an important means for alleviating the shortage of fresh water resources in the new reclamation

Biological and biocompatible characteristics of fullerenols nanomaterials for tissue engineering

. Fullerenes, as hydrophobic molecules, are limited in biomedical function due to their very low solubility. But taking C60(OH)x as an example, the properties of fullerenols were analyzed. It was found that fullerenols had good stability, water solubility, good biocompatibility and low cytotoxicity by adding a hydroxyl group to carbon atoms. In the biomedical field, it has been found that fullerene C60 can be used as a powerful free radical scavenger, with antioxidant activity, with antibacterial and inhibitory effects on cancer cells. Fullerenols inherit the good properties of fullerenes, and are better used in cancer treatment, including loading drug therapy and directly as an anticancer drug. In addition, fullerenols are also used in the repair of myocardial injury, the treatment of myocardial infarction and neuroprotection. With the development of tissue engineering technology, the preparation of nerve scaffolds which can improve ischemia, hypoxia and oxidative stress after nerve injury has become a research hotspot. The electron absorption and reduction characteristics of fullerenols in biomedical research bring new ideas for the treatment of oxidative stress in the repair of peripheral nerve defects. It seems that the research on fullerenols loaded neural scaffold has great prospects

A Novel Waveform Decomposition and Spectral Extraction Method for 101-Channel Hyperspectral LiDAR

The 101-channel full-waveform hyperspectral LiDAR (FWHSL) is able to simultaneously obtain geometric and spectral information of the target, and it is widely applied in 3D point cloud terrain generation and classification, vegetation detection, automatic driving, and other fields. Currently, most waveform data processing methods are mainly aimed at single or several wavelengths. Hidden components are revealed mainly through optimization algorithms and comparisons of neighbor distance in different wavelengths. The same target may be misjudged as different ones when dealing with 101 channels. However, using the gain decomposition method with dozens of wavelengths will change the spectral intensity and affect the classification. In this paper, for hundred-channel FWHSL data, we propose a method that can detect and re-decompose the channels with outliers by checking neighbor distances and selecting specific wavelengths to compose a characteristic spectrum by performing PCA and clustering on the decomposition results for object identification. The experimental results show that compared with the conventional single channel waveform decomposition method, the average accuracy is increased by 20.1%, the average relative error of adjacent target distance is reduced from 0.1253 to 0.0037, and the degree of distance dispersion is reduced by 95.36%. The extracted spectrum can effectively characterize and distinguish the target and contains commonly used wavelengths that make up the vegetation index (e.g., 670 nm, 784 nm, etc.)