283 research outputs found
Global pattern and mechanism of terrestrial evapotranspiration change indicated by weather stations
Accurate estimation of global terrestrial evapotranspiration (ET) is
essential to understanding changes in the water cycle, which are expected to
intensify in the context of climate change. Current global ET products are
derived from physics-based, yet empirical, models, water balance methods, or
upscaling from sparse in situ observations. However, these products contain
substantial limitations such as the coarse resolution due to the coarse climate
reanalysis forcing data, the assumptions on the parameterization of the
process, the sparsity of the observations, and the lack of global accuracy
validation. Using estimates of ET based on the global weather station network
and machine learning, we show that global ET ranged from 493 to 522 mm yr-1 and
increased at the rate of 0.60 mm yr-2 from 2003 to 2019. Between the two
periods of 2003-2010 and 2011-2019, 61.7% of stations showed an increase in ET.
At the large river basin scale, the reliability of the produced ET in this
study is comparable to gridded ET data and even higher in regions where weather
stations are relatively dense and more representative. Correlation analysis and
causal network analysis showed that the main drivers of ET long-term changes
are changes in air temperature, radiation, vegetation conditions, and vapor
pressure deficit. There is great variability in the causal mechanisms of ET
change across vegetation cover and across seasons. This study highlights the
promise of using weather stations to complement global ET and water cycle
studies at the station scale
A pair of new BAC and BIBAC vectors that facilitate BAC/BIBAC library construction and intact large genomic DNA insert exchange
<p>Abstract</p> <p>Background</p> <p>Large-insert BAC and BIBAC libraries are important tools for structural and functional genomics studies of eukaryotic genomes. To facilitate the construction of BAC and BIBAC libraries and the transfer of complete large BAC inserts into BIBAC vectors, which is desired in positional cloning, we developed a pair of new BAC and BIBAC vectors.</p> <p>Results</p> <p>The new BAC vector pIndigoBAC536-S and the new BIBAC vector BIBAC-S have the following features: 1) both contain two 18-bp non-palindromic I-<it>Sce</it>I sites in an inverted orientation at positions that flank an identical DNA fragment containing the <it>lac</it>Z selection marker and the cloning site. Large DNA inserts can be excised from the vectors as single fragments by cutting with I-<it>Sce</it>I, allowing the inserts to be easily sized. More importantly, because the two vectors contain different antibiotic resistance genes for transformant selection and produce the same non-complementary 3' protruding ATAA ends by I-<it>Sce</it>I that suppress self- and inter-ligations, the exchange of intact large genomic DNA inserts between the BAC and BIBAC vectors is straightforward; 2) both were constructed as high-copy composite vectors. Reliable linearized and dephosphorylated original low-copy pIndigoBAC536-S and BIBAC-S vectors that are ready for library construction can be prepared from the high-copy composite vectors pHZAUBAC1 and pHZAUBIBAC1, respectively, without the need for additional preparation steps or special reagents, thus simplifying the construction of BAC and BIBAC libraries. BIBAC clones constructed with the new BIBAC-S vector are stable in both <it>E. coli </it>and <it>Agrobacterium</it>. The vectors can be accessed through our website <url>http://GResource.hzau.edu.cn</url>.</p> <p>Conclusions</p> <p>The two new vectors and their respective high-copy composite vectors can largely facilitate the construction and characterization of BAC and BIBAC libraries. The transfer of complete large genomic DNA inserts from one vector to the other is made straightforward.</p
Nanoporous Oxides and Nanoporous Composites
Nanoporous oxides, such as cupric oxide (CuO), nickelous oxide (NiO), titanium dioxide (TiO2), cobaltosic oxide (Co3O4), and cerium oxide (CeO2), and noble-metal-based nanoporous composites, such as silver (Ag) ligaments loaded with CeO2, TiO2, zirconium dioxide (ZrO2) or NiO and palladium (Pd) ligaments loaded with TiO2 or ZrO2, are described in the chapter. Oxide-based nanoporous composites, such as Au loaded on CuO and CeO2 or platinum (Pt) loaded on TiO2, are also summarized. The structures, microstructures, and microstructure parameters of these materials are reviewed. The performance of the noble-based nanoporous composites is presented, including the catalytic oxidation of methanol and ethanol. Environmental protection applications, such as catalytic oxidation of carbon monoxide (CO) for the oxide-based nanoporous composites, have also been developed. Applications of rare earth elements in nanoporous materials are also reviewed
A Robust Integrated Multi-Strategy Bus Control System via Deep Reinforcement Learning
An efficient urban bus control system has the potential to significantly
reduce travel delays and streamline the allocation of transportation resources,
thereby offering enhanced and user-friendly transit services to passengers.
However, bus operation efficiency can be impacted by bus bunching. This problem
is notably exacerbated when the bus system operates along a signalized corridor
with unpredictable travel demand. To mitigate this challenge, we introduce a
multi-strategy fusion approach for the longitudinal control of connected and
automated buses. The approach is driven by a physics-informed deep
reinforcement learning (DRL) algorithm and takes into account a variety of
traffic conditions along urban signalized corridors. Taking advantage of
connected and autonomous vehicle (CAV) technology, the proposed approach can
leverage real-time information regarding bus operating conditions and road
traffic environment. By integrating the aforementioned information into the
DRL-based bus control framework, our designed physics-informed DRL state fusion
approach and reward function efficiently embed prior physics and leverage the
merits of equilibrium and consensus concepts from control theory. This
integration enables the framework to learn and adapt multiple control
strategies to effectively manage complex traffic conditions and fluctuating
passenger demands. Three control variables, i.e., dwell time at stops, speed
between stations, and signal priority, are formulated to minimize travel
duration and ensure bus stability with the aim of avoiding bus bunching. We
present simulation results to validate the effectiveness of the proposed
approach, underlining its superior performance when subjected to sensitivity
analysis, specifically considering factors such as traffic volume, desired
speed, and traffic signal conditions
Adjusting Effects of Baicalin for Nuclear Factor-κB and Tumor Necrosis Factor-α on Rats With Caerulein-Induced Acute Pancreatitis
Forty Wistar rats were divided into 5 groups, including the control group, the acute pancreatitis group (AP group, induced by intraperitoneal injections of caerulein), and the AP group treated with baicalin, the AP group treated with LPS, and the AP group treated with LPS and baicalin. Pathological damage of pancreatic tissue was scored with hematoxylin and eosin (HE) staining. The mRNA expression of TNF-α was measured with semiquantitative RT-PCR, and activation of NF-κB was detected with flow cytometry assay. It was shown in the results that the expression of TNF-α mRNA, activation of NF-κB, and pathological score of AP group were all obviously higher than those of control group (P < .01). In AP group treated with LPS, further rise of these values were observed (P < .01). In the AP group treated with baicalin, activation of NF-κB decreased (P < .05), and expression of TNF-α mRNA also obviously decreased (P < .01), while pancreatic pathological damage was alleviated at the same time (P < .01); similar results were observed in AP group treated with LPS and baicalin (P < .01), which indicated that baicalin might be applied to inhibit NF-κB activating and TNF-α expressing so as to treat AP
Transient impulses enhancement based on adaptive multi-scale improved differential filter and its application in rotating machines fault diagnosis
Fault feature extraction for rolling element bearing diagnosis based on a multi-stage noise reduction method
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
Jointly processing information from multiple sensors is crucial to achieving
accurate and robust perception for reliable autonomous driving systems.
However, current 3D perception research follows a modality-specific paradigm,
leading to additional computation overheads and inefficient collaboration
between different sensor data. In this paper, we present an efficient
multi-modal backbone for outdoor 3D perception named UniTR, which processes a
variety of modalities with unified modeling and shared parameters. Unlike
previous works, UniTR introduces a modality-agnostic transformer encoder to
handle these view-discrepant sensor data for parallel modal-wise representation
learning and automatic cross-modal interaction without additional fusion steps.
More importantly, to make full use of these complementary sensor types, we
present a novel multi-modal integration strategy by both considering
semantic-abundant 2D perspective and geometry-aware 3D sparse neighborhood
relations. UniTR is also a fundamentally task-agnostic backbone that naturally
supports different 3D perception tasks. It sets a new state-of-the-art
performance on the nuScenes benchmark, achieving +1.1 NDS higher for 3D object
detection and +12.0 higher mIoU for BEV map segmentation with lower inference
latency. Code will be available at https://github.com/Haiyang-W/UniTR .Comment: Accepted by ICCV202
Mitochondrial Dysfunction Triggers Synaptic Deficits via Activation of p38 MAP Kinase Signaling in Differentiated Alzheimer’s Disease Trans-Mitochondrial Cybrid Cells
Loss of synapse and synaptic dysfunction contribute importantly to cognitive impairment in Alzheimer’s disease (AD). Mitochondrial dysfunction and oxidative stress are early pathological features in AD-affected brain. However, the effect of AD mitochondria on synaptogenesis remains to be determined. Using human transmitochondrial “cybrid” (cytoplasmic hybrid) neuronal cells whose mitochondria were transferred from platelets of patients with sporadic AD or age-matched non-AD subjects with relatively normal cognition, we provide the first evidence of mitochondrial dysfunction compromises synaptic development and formation of synapse in AD cybrid cells in response to chemical-induced neuronal differentiation. Compared to non-AD control cybrids, AD cybrid cells showed synaptic loss which was evidenced by a significant reduction in expression of two synaptic marker proteins: synaptophysin (presynaptic marker) and postsynaptic density protein-95, and neuronal proteins (MAP-2 and NeuN) upon neuronal differentiation. In parallel, AD-mediated synaptic deficits correlate to mitochondrial dysfunction and oxidative stress as well as activation of p38 MAP kinase. Notably, inhibition of p38 MAP kinase by pharmacological specific p38 inhibitor significantly increased synaptic density, improved mitochondrial function, and reduced oxidative stress. These results suggest that activation of p38 MAP kinase signaling pathway contributes to AD-mediated impairment in neurogenesis, possibly by inhibiting the neuronal differentiation. Our results provide new insight into the crosstalk of dysfunctional AD mitochondria to synaptic formation and maturation via activation of p38 MAP kinase. Therefore, blockade of p38 MAP kinase signal transduction could be a potential therapeutic strategy for AD by alleviating loss of synapses
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