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Methanol is a promising alternative fuel due to its wide availability of raw materials, mature production processes, and low production cost. However, because of the low cetane number, methanol must include a more reactive fuel to assist with combustion when used in compression ignition (CI) engines. In this study, based on the optical CI engine platform, methanol is injected into the intake port, and diesel is directly injected into the cylinder to achieve dual-fuel combustion. The effects of the methanol energy ratios and diesel split injection strategies on combustion are investigated. The results show that the premixed blue flame was mainly concentrated in the near wall region, whereas the yellow flame produced by diesel combustion tended to concentrate in the central region as the methanol energy ratio increased. When the methanol energy ratio exceeded 50%, the ignition delay was significantly prolonged, while the flame area was greatly reduced. Meanwhile, the peak values for the cylinder pressure and heat release rate decreased significantly, indicating a significant deterioration in combustion. At the earlier diesel pre-injection timing at −58°, the overall dual-fuel combustion at each main injection timing exhibited low-temperature premixed combustion characteristics, with a lower peak exothermic rate and flame brightness. At the later pre-injection timing at −33°, the spray flame at all main injection timings could be observed, with higher peak heat release rates and indications of thermal efficiency. Combustion at later main injection timings was characterized by diffusion combustion, and the main injection timing could effectively regulate the combustion process through phase adjustment. [ABSTRACT FROM AUTHOR]

A single-inductor, low-voltage, three-step self-starting boost converter is proposed for photovoltaic (PV) energy harvesting. In order to enhance energy transfer efficiency, a variable-step Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) scheme has been devised based on a novel pulse multiplication technique. Upon overcoming the speed and accuracy limitations, the maximum power point (MPP) of the PV model is accurately tracked. In the boost converter, the average inductor current is utilized to implement closed-loop control of the MPPT loop, enhancing the stability of the tracking process and enabling efficient energy transmission. Finally, the boost converter is implemented using a 0.18 μm CMOS process, which is capable of self-starting and maintaining stable operations at input voltages ranging from 90 mV to 300 mV, achieving a peak efficiency of 93%. [ABSTRACT FROM AUTHOR]

The construction industry plays a crucial role in achieving global carbon neutrality. The purpose of this study is to explore the application of photovoltaic curtain walls in building models and analyze their impact on carbon emissions in order to find the best adaptation method that combines economy and carbon reduction. Through a carbon emissions calculation and economic analysis of replacing photovoltaic curtain walls on a large public building in Zhenjiang, China, the results showed that after replacing glass curtain walls with photovoltaic curtain walls, the carbon emissions during the construction operation stage decreased by 30.74%, but the carbon emissions during the production and transportation stage of building materials increased by 10.48%. The carbon emissions throughout the entire life cycle of the building have been reduced by 20.99%. This indicates that photovoltaic curtain wall technology has the potential to reduce building carbon emissions. Further promoting the development of production technology and sales routes for photovoltaic curtain walls and accelerating the improvement of carbon trading systems can further improve the carbon emission reduction effect of buildings. This study provides practical reference for public buildings in similar areas and guidance for reducing carbon emissions in the future. [ABSTRACT FROM AUTHOR]

In recent years, China has been vigorously carrying out the construction and development of a sponge city. To prove that the material and energy consumption involved in the implementation of a sponge city is much less than that of the integrated urban drainage system (IUDS) in addition to saved energy and reduced carbon in the sponge city, it was important to calculate the corresponding carbon source and sink and analyze its key influence factors. The emission factor method was used to calculate carbon emissions. In view of this, based on the Intergovernmental Panel on Climate Change (IPCC) guidelines and life cycle assessment (LCA), this research established a systematic accounting method for carbon emissions from the IUDS and the sponge city, which focused on improving the calculation method of the carbon sink stage. A case study was conducted in Beijing, China, and the carbon emission reduction effect of the construction of the sponge city was discussed. The results showed that the carbon emission reduction potential (CRP) of sponge facilities in this project for 50 years was 612.45 tons of CO2 equivalent after the renovation. Compared with IUDS, sponge city construction had a positive effect on carbon emission reduction and reduced carbon emissions by 87.08% on average. For the IUDS and the sponge city, the stormwater pipe network had the largest contribution of carbon emission, and its material, transportation, pipeline laying, and maintenance of stormwater pipe networks had important influences. Morris global analysis method was used to analyze the sensitivity of LCA results and obtained that the influence degree of sensitivity factors on carbon emissions in the life cycle was in the order of annual rainfall > carbon sequestration rate of green space > high-density polyethylene (HDPE) > transport distance > fertilization and insecticide. This study can provide a positive contribution to the construction of a sponge city and planning the low-carbon development of the city in the future in China. [ABSTRACT FROM AUTHOR]

It was to investigate the neuroprotective mechanism of tanshinone after cerebral infarction via the Kelch-like ECH-associated protein 1 (Keap1)-nuclear factor erythroid 2-related factor 2 (Nrf2)/antioxidant reaction element (ARE) signaling pathway. Forty specific pathogen-free (SPF) Sprague Dawley (SD) rats were selected, all of which were male, approximately seven weeks old, weighing 250 ± 25 g. They were randomly divided into a model group, a non-model operation group, a positive control group, and an experimental group with ten SD rats in each group. The model of cerebral infarction in rats was established by the wire occlusion method. The model group and non-model operation group (control group) were injected with normal saline daily, the negative control group was injected with Keap1 gene inhibitor daily, and the experimental group was injected with tanshinone IIA (10 mg·kg−1·d−1) daily. Animal behavior analysis was performed on the 7th day after the operation, and pathology and the neuroprotective effects of tanshinone IIA on cells were assessed, including cell proliferation, autophagy, oxidative damage, and mitochondrial membrane permeability. The neuroprotective mechanism based on the Keap1-Nrf2/ARE pathway was explored and analyzed. Compared with the model group, the number of Keap1 proteins in the experimental group and the control group was substantially reduced (P < 0.05), and the experimental group was substantially different from the model group (P < 0.01). The protein expression of Nrf2, HO-1, and NQO1 increased substantially (P < 0.05), and the experimental group was substantially different from the model group (P < 0.01). In summary, tanshinone IIA promoted the proliferation of nerve cells, inhibited the production of cellular reactive oxygen species, inhibited the change in mitochondrial membrane potential, and activated the Keap1-Nrf2/ARE signaling pathway. It also induced and regulated the upregulation of downstream NQO1, HO-1, etc. and protected cells from cerebral infarction. [ABSTRACT FROM AUTHOR]

Objective: This investigation aims to determine the antidepressant role of Xingpijieyu formula (XPJYF) mediated via gut microbiota (GM)–brain axis. Methods: We collected fecal microbiota from patients with depressive disorder (DD) and cultured microbiota in vitro. Some of microbiota were transplanted into germ‐free rats with the intragastric administration of XPJYF grain at the dose of 1.533 g/kg/day. The behaviors were studied by forced swimming test, open field test, sucrose preference test, and body weight. Products of hypothalamus–pituitary–adrenocortical (HPA) axis, neurotransmitter, and serum cytokines were investigated by enzyme linked immunosorbent assay. Glial fibrillary acidic protein (GFAP), a biomarker of astrocyte, was quantified using immunofluorescence. Microbiota culturing in vitro after XPJYF treatment was analyze by 16 s RNA sequencing technology. We used lipopolysaccharide (LPS) to mimic activated rat primary astrocyte in vitro. Brain‐derived neurotrophic factor (BDNF), cytokines, and oxidative stress factors were determined by western blotting, and glycometabolism in astrocyte was investigated by 2‐deoxy‐D‐glucose (2‐DG) uptake, adenosine triphosphate (ATP), and glucose‐1‐phosphate (G1P) kits. Results: Microbiota composition during 8 mg/ml of XPJYF (H12‐8) for 12 h showed the more consistency. Lactococcus is enriched in DD‐derived microbiota composition, and Biffdobacterium and Lactobacillus in H12‐8 group. GLUCOSE1PMETAB‐PWY and PWY‐7328 of which biofunctions were dominantly encoded by Biffdobacterium were the top two of altered pathways. XPJYF improved behaviors and repressed astrocyte activation in depression rats. XPJYF elevated 2‐DG uptake, ATP, glucose‐1‐phosphate, and brain‐derived neurotrophic factor (BDNF), and inhibited cytokines and oxidative stress in LPS‐induced astrocyte. Conclusion: XPJYF treatment targets inflammation, activation, and glycometabolim in astrocyte via gut microbiota modulation, thereby improve animal behaviors, HPA axis dysfunction, and neurotransmitter synthesis in depression rats. [ABSTRACT FROM AUTHOR]

Reactive powder concrete-filled steel tube (RPC-FST) is a critical supporting component of large-span, high-rise, and heavy-load structures. The collapse of RPC-FST may occur under explosive load. Therefore, investigation of the dynamic response is essential for understanding the mechanisms of collapse. In this article, the numerical simulation of reactive powder concrete (RPC) adopted the modified Holmquist–Johnson–Cook (HJC) model and the modified Karagozian and Case (K&C) model. The dynamic response of RPC-FST columns under explosive load is analyzed based on arbitrary Lagrange–Euler (ALE) method. The proposed model is verified by experimental results. Results show that the modified HJC model and modified K&C model can be applied to simulate the dynamic response of RPC-FST columns under explosive load. As compared with the modified HJC model, the modified K&C model has more accurate results. This phenomenon mainly accounts for the lack of ultimate strain of RPC (EFMIN). To analyze the reliability sensitivity of RPC-FST, an efficient probability analysis method is proposed based on the Kriging model and Monte Carlo simulation (MCS). The proposed method considers five nonlinear factors, including weight and distance of TNT, height and section diameter of RPC-FST, and steel tube thickness. Finally, the sensitivity of each factor is evaluated. Results show that TNT weight greatly influences the reliability of the RPC-FST, followed by TNT distance, RPC-FST height, RPC-FST section diameter, and steel tube thickness. In addition, the RPC-FST dynamic response analysis method based on the Kriging model and MCS can improve the calculation efficiency by more than 200 times compared with the ALE method. [ABSTRACT FROM AUTHOR]

Aim: The investigation aims to evaluate the potential effect of Shugan Granule (SGKL) on the gut, brain, and behaviors in rats exposed to chronic restraint stress (CRS). Methods: The fecal microbiota and metabolite changes were studied in rats exposed to CRS and treated with SGKL (0.1 mg/kg/day). Depressive behaviors of these rats were determined through an open‐field experiment, forced swimming test, sucrose preference, and weighing. Moreover, LPS‐stimulated microglia and CRS‐stimulated rats were treated with SGKL to investigate the regulation between SGKL and the PI3K/Akt/pathway, which is inhibited by LY294002, a PI3K inhibitor. Results: (i) SGKL improved the altered behaviors in CRS‐stimulated rats; (ii) SGKL ameliorated the CRS‐induced neuronal degeneration and tangled nerve fiber and also contributed to the recovery of intestinal barrier injury in these rats; (iii) SGKL inhibited the hippocampus elevations of TNF‐α, IL‐1β, and IL‐6 in response to CRS modeling; (iv) based on the principal coordinates analysis (PCoA), SGKL altered α‐diversity indices and shifted β‐diversity in CRS‐stimulated rats; (v) at the genus level, SGKL decreased the CRS‐enhanced abundance of Bacteroides; (vi) Butyricimonas and Candidatus Arthromitus were enriched in SGKL‐treated rats; (vii) altered gut microbiota and metabolites were correlated with behaviors, inflammation, and PI3K/Akt/mTOR pathway; (viii) SGKL increased the LPS‐decreased phosphorylation of the PI3K/Akt/mTOR pathway in microglia and inhibited the LPS‐induced microglial activation; (ix) PI3K/Akt/mTOR pathway inactivation reversed the SGKL effects in CRS rats. Conclusion: SGKL targets the PI3K/Akt/mTOR pathway by altering gut microbiota and metabolites, which ameliorates altered behavior and inflammation in the hippocampus. [ABSTRACT FROM AUTHOR]

Plants interact to the seasonality of their environments, and changes in plant phenology have long been regarded as sensitive indicators of climatic change. Plant phenology modeling has been shown to be the simplest and most useful tool to assess phenol-climate shifts. Temperature, solar radiation, and water availability are assumed to be the key factors that control plant phenology. Statistical, mechanistic, and theoretical approaches have often been used for the parameterization of plant phenology models. The statistical approaches correlate the timing of phenological events to environmental factors or heat unit accumulations. The approaches have the simplified calculation procedures, correct phenological mechanism assumptions, but limited applications and predictive abilities. The mechanistic approaches describe plant phenology with the known or assumed 'cause-effect relationships' between biological processes and key driving variables. The mechanistic approaches have the improved parameter processes, realistic assumptions, broad applications, and effective predictions. The theoretical approaches assume cost-benefit tradeoff strategies in trees. These methods are capable of capturing and quantifying the potential impacts and consequences of global climate change and human activity. However, certain limitations still exist related to our understanding of phenological mechanisms in relation to (1) interactions between plants and their specific climates, (2) the integration of both field observational and remote sensing data with plant phenology models across taxa and ecosystem type, (3) amplitude clarification of scale-related sensitivity to global climate change, and (4) improvements in parameterization processes and the overall reduction of modeling uncertainties to forecast impacts of future climate change on plant phenological dynamics. To improve our capacity in the prediction of the amplitude of plant phenological responses with regard to both structural and functional sensitivity to future global climate change, it is important to refine modeling methodologies by applying long-term and large-scale observational data. It is equally important to consider other less used but critical factors (such as heredity, pests, and anthropogenic drivers), apply advanced model parameterization and data assimilation techniques, incorporate process-based plant phenology models as a dynamic component into global vegetation dynamic models, and test plant phenology models against long-term ground observations and high-resolution satellite data across different spatial and temporal scales. Key words: plant phenology, climate change, NDVI, ecological forecasting, process-based model. Les plantes interagissent avec la saisonnalite de leur environnement et on a longtemps considere les changements de la phenologie comme indicateurs du changement climatique. On a montre que la modelisation de la phenologie des plantes constitue le moyen le plus simple et le plus utile pour evaluer les glissements pheno-climatiques. On assume que la temperature, la radiation solaire et la disponibilite de l'eau constituent des facteurs determinants controlant la phenologie des plantes. On a egalement souvent utilise des approches statistiques, mecanistes et theoriques pour parametrer les modeles de phenologie vegetale. Les approches statistiques font la correlation entre l'incidence des evenements phenologiques, les facteurs environnementaux ou les accumulations d'unites thermiques. Ces approches statistiques ont l'avantage d'utiliser des methodes de calcul simplifiees et de corriger les mecanismes phenologiques assumes mais ont des capacites d'application et de prediction limitees. Les approches mecanistes decrivent la phenologie des plantes avec les relations de causes a effets connues ou presumees impliquant les processus biologiques et des variables determinantes. Les approches mecanistes ont l'avantage d'ameliorer le parametrage des processus, d'etablir des postulats realistes et de fournir des applications et des predictions valables. L'approche theorique se base sur des strategies cout benefice dans l'arbre. Ces methodes peuvent integrer et quantifier les impacts potentiels et les consequences du changement climatique global et de l'activite humaine. Cependant, il existe toujours certaines limitations reliees a notre comprehension des mecanismes phenologiques en relation avec (1) les interactions entre les plantes et les climats specifiques, (2) l'integration a la fois des donnees de terrain et de teledetection avec les modeles phenologiques vegetaux a travers les taxons et les types d'ecosystemes, (3) la clarification de l'amplitude et de la sensibilite reliees a l'echelle du changement climatique global et (4) l'amelioration des processus de parametrisation et la reduction generale des incertitudes de la modelisation pour predire les impacts du changement climatique futur sur la dynamique phenologique des plantes. Pour ameliorer notre capacite a predire l'amplitude des reactions phenologique des plantes en relation avec la sensibilite a la fois structurale et fonctionnelle du futur changement climatique, il faut raffiner les methodologies de modelisation en appliquant des donnees a long terme et a grande echelle. Il faut egalement considerer des facteurs moins utilises mais critiques (comme l'heredite, les pestes et les determinants anthropiques), appliquer la parametrisation de modeles avances et des techniques d'assimilation des donnees, incorporer des modeles de phenologie vegetale bases sur des processus comme composante dynamique des modeles globaux dynamiques de la vegetation et tester les modeles de phenologie vegetale contre des observations a long terme ainsi que les donnees satellites a haute resolution sur differentes echelles spatiales et temporelles. [Traduit par la Redaction] Mots-cles: phenologie vegetale, changement climatique, NDVI, previsions ecologiques, modele base sur des processus., 1. Introduction Phenology is the scientific study of periodic plant and animal life cycle events (such as flowering, breeding, and migration) and how these are influenced by seasonal and interannual [...]

Reactive power concrete (RPC) possesses high compressive strength, toughness, and durability, and it is increasingly being used in important buildings. The column is an important load-bearing member of a building, and its failure under blast loading results in building collapse. Based on these attributes, the dynamic response and the degree of damage to the RPC column are critical in assessing building performance. Due to the lack of methods, the progress of the study is relatively slow. In order to solve these issues, the dynamic response of the RPC column is studied based on the equivalent single-degree-of-freedom method and P-I curve in this paper. During the model validation phase, the deformation of the RPC column predicted using the ESDOF approach correlates well with the explosion simulation and test results. The P-I curves of the typical RPC column were also determined, and some data were analyzed to evaluate the influence of different key parameters, such as slenderness ratio, cross-sectional dimension, and axial compression ratio. The results show that the RPC column is susceptible to shear, bending, and bending-shear failure in the impulse load region, quasi-static load region, and dynamic load region, respectively. The cross-sectional dimension and slenderness ratio exhibit the greatest influence on P-I curves among the five parameters. With the increasing cross-sectional dimension and slenderness ratio, the overpressure asymptote of bending response increases by 4.2 times and decreases by about 57.3%. Furthermore, combined with the P-I curve features, it is found that reasonably increasing the cross-sectional dimensions and RPC strength could simultaneously improve the comprehensive anti-blast performance of RPC columns. This study was carried out to obtain the effect of the five parameters mentioned above on the degree of damage under different blast loading, which can provide a valuable reference for the dynamic response of RPC columns. [ABSTRACT FROM AUTHOR]

Canopy interception loss is an important hydrological process that affects rainfall redistribution, nutrient cycling, and soil and water conservation in forest ecosystems. However, the manner in which interception loss is affected in forests that are in restoration stages dominated by different tree species has not been fully understood. In this study, interception loss, throughfall, and stemflow were measured consecutively for 2 years (May 2017 through April 2019) in three secondary forests in subtropical China: a coniferous and broadleaved mixed forest (Pinus massoniana, Lithocarpus glaber, PM) in early restoration stage, a deciduous broadleaved forest (Choerospondias axillaris, CA) in middle restoration stage, and an evergreen broadleaved forest (L. glaber–Cyclobalanopsis glauca, LG) in late restoration stage. For a given amount of rainfall, the relative interception loss in the CA was significantly lower than that in the evergreen forests in summer, spring, or winter. The amount of interception loss during light rain, moderate rain, or heavy storms was also significantly lower in CA as compared to that in evergreen forests, owing to the lesser leaf area and phenology of deciduous tree species as well as a higher leaf area index (LAI) and stand density in PM and LG. Meanwhile, the highest relative interception loss, interception loss amount, canopy storage capacity, canopy cover fraction, and mean evaporation rate was observed in the climax forest (LG), which has a higher LAI and stand density. Further, the revised Gash's analytical model (RGAM) and the sparse Rutter models were successfully applied to simulate interception loss in these forests, with the RGAM performing better as compared to the sparse Rutter model. The results of the field measurements and model simulations depict that the climax community at the late restoration stage can effectively reduce the amount of rainwater reaching the soil surface, thus weakening the effect of flood peaks. [ABSTRACT FROM AUTHOR]

Phase-only nulling with low sidelobe level is a problem of interest in array synthesis which is a tedious problem without an analytical solution. In this communication, a novel framework for the phase-only nulling based on radial basis function neural network (RBFNN) is proposed to predict the phase adjustment for the array pattern nulling with sidelobe control. In the process of network training, the parameters of the RBFNN are optimized simultaneously based on the self-adaptive differential evolution (SADE) algorithm, which aims to improve the approximation ability and reduce the complexity of the network. Simulation results of the optimized RBFNN models show compact network structure and form the array pattern under desired performance with good generalization capability. [ABSTRACT FROM AUTHOR]

The safety and cost of structures composed of concrete-filled steel tube (CFST) frame-steel plate shear walls (SPSWs) with two-side connections are governed by the seismic performance. The response modification factor R and displacement amplification factor Cd are important seismic performance factors. In this paper, nonlinear seismic responses of 10-story, 15-story, and 20-story CFST frame-SPSWs (CFST-SPSWs) are studied. A nonlinear finite element model which includes both material and geometric nonlinearities is developed using the finite element software OpenSees for this study. The accuracy of model was validated by comparing with experimental results. Nonlinear seismic analysis shows that CFST-SPSWs, in high seismic region, behave in a stable and ductile manner. Also, R and Cd of CFST-SPSWs were evaluated for the structure models using incremental dynamic analysis (IDA), and the average values of 3.17 and 3.05 are recommended, respectively. The recommended R value is greater than the value (2.8) in the "Chinese Code for seismic design of buildings" for composite structures, indicating the code is conservative. The structural periods provided by current code are generally lower than the periods calculated by finite element analysis. Research results show that R and Cd increase with increasing story number, span number, and structural period. Ductility reduction factor Rμ increases with increasing span number and decreasing story number. Overstrength factor Rs increases with increasing story number and decreasing span number. [ABSTRACT FROM AUTHOR]

Influenza A virus (IAV), a highly infectious respiratory pathogen, remains a major threat to global public health. Numerous long non-coding RNAs (lncRNAs) have been shown to be implicated in various cellular processes. Here, we identified a new lncRNA termed RIG-I-dependent IAV-upregulated noncoding RNA (RDUR), which was induced by infections with IAV and several other viruses. Both in vitro and in vivo studies revealed that robust expression of host RDUR induced by IAV was dependent on the RIG-I/NF-κB pathway. Overexpression of RDUR suppressed IAV replication and downregulation of RDUR promoted the virus replication. Deficiency of mouse RDUR increased virus production in lungs, body weight loss, acute organ damage and consequently reduced survival rates of mice, in response to IAV infection. RDUR impaired the viral replication by upregulating the expression of several vital antiviral molecules including interferons (IFNs) and interferon-stimulated genes (ISGs). Further study showed that RDUR interacted with ILF2 and ILF3 that were required for the efficient expression of some ISGs such as IFITM3 and MX1. On the other hand, we found that while NF-κB positively regulated the expression of RDUR, increased expression of RDUR, in turn, inactivated NF-κB through a negative feedback mechanism to suppress excessive inflammatory response to viral infection. Together, the results demonstrate that RDUR is an important lncRNA acting as a critical regulator of innate immunity against the viral infection. [ABSTRACT FROM AUTHOR]

Influenza A virus (IAV) infection regulates the expression of numerous host genes. However, the precise mechanism underlying implication of these genes in IAV pathogenesis remains largely unknown. Here, we employed isobaric tags for relative and absolute quantification (iTRAQ) to identify host proteins regulated by IAV infection. iTRAQ analysis of mouse lungs infected or uninfected with IAV showed a total of 167 differentially upregulated proteins in response to the viral infection. Interestingly, we observed that p27Kip1, a potent cyclin‐dependent kinase inhibitor, was markedly induced by IAV both at mRNA and protein levels through in vitro and in vivo studies. Furthermore, it was shown that innate immune signalling positively regulated p27Kip1 expression in response to IAV infection. Ectopic expression of p27Kip1 in A549 cells dramatically inhibited IAV replication, whereas, p27Kip1 knockdown significantly enhanced the virus replication. in vivo experiments demonstrated that p27Kip1 knockout (KO) mice were more susceptible to IAV than wild‐type (WT) mice: exhibiting higher viral load in lung tissue, faster body‐weight loss, reduced survival rate and more severe organ damage. Moreover, we found that p27Kip1 overexpression facilitated the degradation of viral NS1 protein, caused a dramatic STAT1 activation and promoted the expression of IFN‐β and several critical antiviral interferon‐stimulated genes (ISGs). Increased p27Kip1 expression also restricted infections of several other viruses. Conversely, IAV‐infected p27Kip1 KO mice exhibited a sharp increase in NS1 protein accumulation, reduced level of STAT1 activation and decreased expression of IFN‐β and the ISGs in the lung compared to WT animals. These findings reveal a key role of p27Kip1 in enhancing antiviral innate immunity. [ABSTRACT FROM AUTHOR]

Carbon (C) flux between forest ecosystems and the atmosphere is an important ecosystem C cycling component. Modeling C flux plays a critical role in assessing both C cycles and budgets. This study aimed to determine important non-redundant input variables to quantify C flux and to develop a new application of a genetic neural network (GNN) model that accurately simulates C flux. Four input variables (atmospheric CO2 concentration, air temperature, photosynthetically active radiation (PAR), and relative humidity) were fixed, whereas three additional input variables (wind speed, soil temperature, and rainfall) were randomly combined to compile eight combinations of input variables (CIV 1–CIV 8). C flux and meteorological data were collected over a four-year period between January 2008 and December 2011 at the Huitong National Research Station of Forest Ecosystem. Results showed that CIV 8 (grouping atmospheric CO2 concentration, air temperature, PAR, relative humidity, wind speed, and soil temperature) performed best, yielding a correlation coefficient (R2) of 0.87, outlier of 0.79%, and a root mean squares of errors (RMSE) of 0.11. C flux data during summer generally provided the best performance with R2 ranging from 0.74 to 0.82, volumetric fitting (Ivf) ranging from 1.00 to 1.02, and outliers ranging from 1.20% to 1.40%. Spring data performance ranked second and winter last. When combining seasonal data to reflect the entire year, R2 ranged from 0.77 to 0.83, Ivf ranged from 0.92 to 0.97, outliers ranged from 1.40% to 1.78%, and RMSE ranged from 0.10 to 0.11, indicating that the GNN model is capable in capturing C flux dynamics while successfully simulating and predicting C flux in a Cunninghamia lanceolata plantation in subtropical China. [ABSTRACT FROM AUTHOR]

Antenna array synthesis based on the back propagation neural network is proposed in this Letter. The synthesis process is divided into three steps: pre‐processing, training, and post‐processing. In the pre‐processing, the interference directions and desired signal direction are coded so as to synthesise an arbitrary number of interferences. The back propagation neural network is unified to emulate the convex array synthesis model. To verify the performance of the network, the nine‐element and 11‐element linear array synthesis based on the neural network is realised and tested. Synthesis results show that the proposed method gives accurate approximation and have the good generalisation ability. [ABSTRACT FROM AUTHOR]

Long noncoding RNAs (lncRNAs) are involved in a diversity of biological processes. It is known that differential expression of thousands of lncRNAs occurs in host during influenza A virus (IAV) infection. However, only few of them have been well characterized. Here, we identified a lncRNA, named as interferon (IFN)-stimulated lncRNA (ISR), which can be significantly upregulated in response to IAV infection in a mouse model. A sequence alignment revealed that lncRNA ISR is present in mice and human beings, and indeed, we found that it was expressed in several human and mouse cell lines and tissues. Silencing lncRNA ISR in A549 cells resulted in a significant increase in IAV replication, whereas ectopic expression of lncRNA ISR reduced the viral replication. Interestingly, interferon-β (IFN-β) treatment was able to induce lncRNA ISR expression, and induction of lncRNA ISR by viral infection was nearly abolished in host deficient of IFNAR1, a type I IFN receptor. Furthermore, the level of IAV-induced lncRNA ISR expression was decreased either in retinoic acid-inducible gene I (RIG-I) knockout A549 cells and mice or by nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) inhibitor treatment. Together, these data elucidate that lncRNA ISR is regulated by RIG-I-dependent signaling that governs IFN-β production during IAV infection, and has an inhibitory capacity in viral replication. [ABSTRACT FROM AUTHOR]

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is the most commonly grown afforestation species in subtropical China. It is essential that we understand the response of radial tree growth to climate factors, yet most experiments have been conducted based on total annual growth and not on monthly dynamics, which alone can detail the influence of climatic factors. In this study, we aimed to: (i) construct a monthly growth model and compare the growth rate of different social statuses of trees, and (ii) determine the response of radial increments of different social statuses to climate factors. The radial growth was monitored monthly during four years using manual band dendrometers (MBD). The data were fitted using the Gompertz function. Within-stand differences in the social status of Chinese firs resulted in growing period and growth rate length variations. The radial growth began in March, and suppressed trees—especially groups of AS1 and BS1 (suppressed trees of classes I in sites A and B)—stopped in September, whereas dominant and intermediate trees were delayed and stopped in November. The periodic monthly increment curve showed double peaks, and the maximum growth rate occurred in April and August. The peak values were affected by social status, which showed that dominant trees had the greatest radial growth rates. S-shaped Gompertz meant that monthly increment models were successfully fitted to our data, which explained more than 98% of the variation in increment data and passed the uncertainty test. Temperature and precipitation had a significant influence on radial growth, and the correlation between radial growth and air temperature was the highest. Our results also revealed that temperatures explain the double-peak features of Chinese fir. The limiting factors of radial growth changed with the seasons and were mainly affected by temperature and precipitation, which should be considered in predicting the response of tree growth to climate change. [ABSTRACT FROM AUTHOR]

Long noncoding RNAs (lncRNAs) are single‐stranded RNA molecules longer than 200 nt that regulate many cellular processes. MicroRNA 155 host gene (MIR155HG) encodes the microRNA (miR)‐155 that regulates various signalling pathways of innate and adaptive immune responses against viral infections. MIR155HG also encodes a lncRNA that we call lncRNA‐155. Here, we observed that expression of lncRNA‐155 was markedly upregulated during influenza A virus (IAV) infection both in vitro (several cell lines) and in vivo (mouse model). Interestingly, robust expression of lncRNA‐155 was also induced by infections with several other viruses. Disruption of lncRNA‐155 expression in A549 cells diminished the antiviral innate immunity against IAV. Furthermore, knockout of lncRNA‐155 in mice significantly increased IAV replication and virulence in the animals. In contrast, overexpression of lncRNA‐155 in human cells suppressed IAV replication, suggesting that lncRNA‐155 is involved in host antiviral innate immunity induced by IAV infection. Moreover, we found that lncRNA‐155 had a profound effect on expression of protein tyrosine phosphatase 1B (PTP1B) during the infection with IAV. Inhibition of PTP1B by lncRNA‐155 resulted in higher production of interferon‐beta (IFN‐β) and several critical interferon‐stimulated genes (ISGs). Together, these observations reveal that MIR155HG derived lncRNA‐155 can be induced by IAV, which modulates host innate immunity during the virus infection via regulation of PTP1B‐mediated interferon response. [ABSTRACT FROM AUTHOR]

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is an important native tree species that is widely distributed in subtropical areas of southern China and cultivated for wood extraction. However, information on water use by Chinese fir plantations is still scarce. In this study, we performed species-specific parameter calibrations for the original Granier equation for sap flow density (SFD) estimates. Stand transpiration (Es) was related to environmental inputs, such as rainfall, air temperature (Ta), vapor pressure deficit (VPD), photosynthetically-active radiation (PAR), air relative humidity (RH), and potential evapotranspiration (PET) in order to examine how environmental factors affect the Es of Chinese fir plantations. According to our results, Granier’s original parameters set underestimated C. lanceolataSFD by up to 54% compared to our species-specific calibrated parameters set. A strong positive correlation was found between SFD, diameter at breast height (DBH), and tree height among trees populations. The total Es in 2015 was 522.1 mm, with obvious seasonal dynamics and an average of 1.4 mm·day−1. Daily and monthly Es were positively correlated with VPD, PAR, Ta, and PET. A negative relationship between Es and RH was detected only at a daily timescale. Our findings indicate that the original Granier equation requires a parameter calibration when it is applied to species-specific thermal dissipation probe (TDP) estimates, and our findings can also provide novel insights on the water use of Chinese fir in major wood production areas in Southern China. [ABSTRACT FROM AUTHOR]

[Display omitted] • A spatially explicit planning model was developed to adjust forest age structure. • Smart management could improve stand volume and carbon stocks. • Social preferences had less effects on stand quality after forest structure adjustment. • Forest management was more sensitive to carbon prices than timber prices. Forest farms are the main body of forest management at the landscape-scale in China, and have long sought ways to jointly maximize timber production and other ecosystem services. Carbon sequestration is of particular interest because China has established the goal of becoming carbon neutral by 2060. However, optimizing the balance between timber production and carbon sequestration is a challenge due to a lack of methods that account for the spatial arrangement of forest management activities within a landscape. This study developed a multi-objective planning model for forest management approaches to promote natural forest regeneration, adjusting the stand age structure of plantation forests to an even distribution across a landscape, and quantified the effects of social preferences and market prices on optimal management. The results show that depending on the dominant ecosystem services provided by the forests, forest management could promote an increased timber volume and stand carbon stock that is sustainable in the long-term. Social preferences have a relatively small influence on optimal management plans after forests are restructured to a normal forest age class distribution. In addition, forest management dynamics are more sensitive to carbon prices than timber prices. Hence, the spatial allocation of different management practices and forest restructuring, rather than protecting forests or managing them less intensively, is more effective for improving forest carbon stocks. More importantly, an urgent need also exists to increase the carbon price to guide and strengthen the attention of forest managers to forest carbon sequestration, with the goal of achieving a win–win strategy. [ABSTRACT FROM AUTHOR]

• Mean concentration and annual output fluxes of DOC were the highest in the deciduous broadleaved forest. • Mean concentration of TDN tended to increase but annual TDN output fluxes decreased with forest restoration. • DOC cycle in the deciduous broadleaved forest was relatively open whereas TDN cycle turned to be closed as forest restored. In the restoration of subtropical forests, the hydrological fluxes of dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) have not been fully investigated in different stages dominated by different tree species. The concentrations of DOC and TDN in rainfall, throughfall, stemflow, and surface runoff were measured for two years in each of the three forests at different restoration stages: early coniferous forest (Pinus massoniana - Lithocarpus glaber), intermediate deciduous broadleaved forest (Choerospondias axillaris), and late evergreen broadleaved forest (L. glaber - Cyclobalanopsis glauca). Input and output fluxes as well as leaching and migration coefficients of DOC and TDN were calculated to examine the nutrient cycling status in the processes of forest restoration. In stemflow, DOC concentrations in the evergreen broadleaved forest differed significantly from those in the coniferous and deciduous broadleaved forests, whereas TDN concentrations differed significantly between the coniferous forest and other two forests. In throughfall, DOC and TDN concentrations were not significantly different among the three forests. The amount of DOC leached was primarily influenced by rainfall and was significantly related to fluxes in throughfall, with the highest value in the deciduous broadleaved forest (57.78 kg C ha−1). However, the amount of TDN leached was affected by rainfall and the absorption of vegetation and was not significantly related to fluxes in throughfall, except for the deciduous broadleaved forest. The highest value of TDN leached was in the coniferous forest (11.90 kg N ha−1). Mean TDN concentration in surface runoff tended to increase but annual TDN output fluxes decreased with forest restoration. However, both mean concentration and annual output fluxes of DOC in surface runoff were the highest in the deciduous broadleaved forest at the intermediate restoration stage. The concentrations were closely related to surface runoff, decomposition rate of litterfall, and soil organic matter content. The annual output fluxes of DOC and TDN in surface runoff were less than 30% of the input in throughfall, indicating nutrient accumulation in subtropical secondary forests. [ABSTRACT FROM AUTHOR]

Although studies have reported the modification effect of air pollutants on heat-related health risk, little is known on the modification effect among various particulate matter with different particle size on mortality. We aimed to investigate whether the associations of hot temperatures with daily mortality were modified by different air pollutant levels in Shandong Province, China. Daily data of air pollutants, meteorological factors, and mortality of 1,822 subdistricts in Shandong province from 2013 to 2018 were collected. We used a time-stratified case-crossover model with an interaction term between the cross-basis term for ambient temperature and the linear function of particulate matter ≤1 µm (PM1), PM2.5, nitrogen dioxide (NO2), and ozone to obtain heat-mortality associations during the hot season. Results showed that the cumulative odds ratio of extreme heat on mortality over 0 to 10 days was 3.66 (95% CI: 3.10-4.31). The mortality risk during hot seasons was stronger at high air pollutant levels. The modification effect of particulate matters on heat-related mortality decreased by its aerodynamic diameter. Females and older adults over 75 years were more vulnerable to the modification effect of air pollutants, and significant differences were detected in the association between temperatures and mortality stratified by PM1 and PM2.5. Higher heat-related mortality risks were observed at high NO2 levels, especially for cardiorespiratory disease. The findings suggest that more consideration should be given to the combined effect of very fine particles and NO2 with ambient heat when developing healthcare strategies, and women and older adults should be given priority in health-related settings.

Introduction: Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China., Methods: In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model., Results: The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively., Discussion: The increment of smaller PMs' modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhao, Chu, Xu, Cao, Schikowski, Geng, Chen, Bai, Hu, Xia, Ma, Liu, Lu, Guo and Zhao.)

Objective: Adolescents are at a special stage of physical and mental development, which is a susceptible period for mental disorders. Since the outbreak of coronavirus pneumonia in December 2019, long term stress may have negative effects on the mental health of the adolescents. In the context of the coronavirus disease 2019 (COVID-19), the study was designed to investigate the mental and psychological health of adolescents in China and its possible related factors., Methods: A cross-sectional study design was adopted using a structured questionnaire which were distributed through the Internet to measure depression, anxiety, life events and stress related factors. Descriptive statistics and multiple regression analyses were conducted to process the data., Results: The final sample comprised 795 adolescents. The total detection rate of depression was 76.48% and the total detection rate of anxiety was 33.08%. ANOVA showed that there were significant differences in depression scores in terms of gender, anxiety scores, history of mental disorders, COVID-19 knowledge reserve, family and social contradictions (p<0.05). And there were significant differences in anxiety scores in terms of gender, depression scores, mental health knowledge reserves, family and social contradictions (p<0.05). Multiple regression analysis showed that anxiety score, health status and COVID-19 knowledge reserve were positively associated with depression score (p<0.01), and history of psychosocial disorders was negatively associated with depression score (p<0.05); depression score, family and social contradictions were significantly positively correlated with anxiety score (p<0.01), and history of mental disorders was significantly negatively correlated with SDS score (p<0.01)., Conclusion: During the outbreak of COVID-19, adolescent students with better understanding of the pandemic, more complete knowledge of mental health, and better family and social relationship had less impact on their mental health. Therefore, to ensure a sound social support system, elaborate health instruction, and family communication and mutual understanding are conducive to alleviating the psychological stress caused by the epidemic, and it is positive for adolescent students to maintain a good mental health.