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In response to the current problems of high startup wind speed, complex design schemes, and inability to accurately measure the average wind speed of the entire section of the roadway using wind speed sensors, based on the principle of ultrasonic opposed wind measurement, a mine opposed wind speed and direction sensor with STM32 as the core is designed. The overall structure of the sensor, the design of the transmitting and receiving circuit, the filtering algorithm, and the software process are introduced. This sensor has changed the wind measurement method from point to surface, using a single ARM core and measuring the wind speed at the centerline of the roadway through long-distance (5-12 m) ultrasonic wind measurement technology. This wind speed represents the average wind speed of the entire roadway. It greatly improves the accuracy and real-time performance of roadway wind speed measurement. A test prototype is developed based on the design scheme, and the test results in a circular wind tunnel show that the measured values of the sensor has good consistency with the standard wind speed values in the range of 0.1-15 m/s, with a measurement error of less than 0.1 m/s. It can meet the precision requirements of intelligent mines for roadway wind speed measurement.

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]

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]

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 [...]