Showing papers by "Louisiana State University published in 2022"
TL;DR: In this article, the spatial and temporal distribution characteristics of severe haze in China, analyzes the interaction between haze pollution and the influence of economy and energy structure on haze in 31 provinces of China, and provides references for the treatment of haze weather and the prevention and control of air pollution in China.
Abstract: In recent years, the occurrence and frequency of haze have constantly been increasing, bringing severe threats to people's daily lives. To this end, this paper discusses the spatial and temporal distribution characteristics of severe haze in China, analyzes the interaction between haze pollution and the influence of economy and energy structure on haze in 31 provinces of China. It provides references for the treatment of haze weather and the prevention and control of air pollution in China. This paper mainly adopts the spatial autocorrelation method. The data processed mainly includes API (Air Pollution Index) and meteorological station data. Combined with the statistical yearbook data, this paper conducts multi-aspect research and exploration. By using statistical methods to study the haze distribution in China, we found that the haze and PM2.5 concentrations were mainly distributed in Beijing-Tianjin-Hebei, Shandong Province, the northern northwest, southeastern Sichuan, and Chongqing. Haze distribution has obvious seasonality, more in winter and less in summer. There are also regional differences in the concentration distribution of urban pollutants. The concentration of SO2 and absorbable particles are relatively high in northern cities. In contrast, that of southern cities is relatively low and changes with seasonal changes.
69 citations
TL;DR: In this paper , the spatial and temporal distribution characteristics of severe haze in China, analyzes the interaction between haze pollution and the influence of economy and energy structure on haze in 31 provinces of China, and provides reference for the treatment and the prevention and control of air pollution in China.
Abstract: In recent years, the occurrence and frequency of haze have constantly been increasing, bringing severe threats to people's daily lives. To this end, this paper discusses the spatial and temporal distribution characteristics of severe haze in China, analyzes the interaction between haze pollution and the influence of economy and energy structure on haze in 31 provinces of China. It provides references for the treatment of haze weather and the prevention and control of air pollution in China. This paper mainly adopts the spatial autocorrelation method. The data processed mainly includes API (Air Pollution Index) and meteorological station data. Combined with the statistical yearbook data, this paper conducts multi-aspect research and exploration. By using statistical methods to study the haze distribution in China, we found that the haze and PM 2.5 concentrations were mainly distributed in Beijing-Tianjin-Hebei, Shandong Province, the northern northwest, southeastern Sichuan, and Chongqing. Haze distribution has obvious seasonality, more in winter and less in summer. There are also regional differences in the concentration distribution of urban pollutants. The concentration of SO 2 and absorbable particles are relatively high in northern cities. In contrast, that of southern cities is relatively low and changes with seasonal changes. • Focuses on the spatial and temporal distribution characteristics of severe haze in China based on pollution-related data from the Ministry of Environmental Protection. • Analyzes the interaction between haze and the economy and energy structure in 31 provinces of China, and provides reference for the treatment and the prevention and control of air pollution in China. • The haze were concentrated in Beijing-Tianjin-Hebei region, Shandong Province, the northern northwest region, southeastern Sichuan province, and Chongqing. • According to the spatial autocorrelation, haze distribution has obvious seasonality, more in winter and less in summer. • The concentration of SO 2 and absorbable particles is relatively high in northern cities, while that of southern cities is relatively low, and changes with seasonal changes
69 citations
TL;DR: In this article, the authors used the Gaussian pyramid to improve the simple ORB-oriented algorithm, which is more suitable for minimally invasive surgery endoscopic image mosaic through theoretical analysis and experimental verification.
64 citations
TL;DR: In this paper , the authors used the Gaussian pyramid to improve the simple ORB-oriented algorithm, which has invariability, good robustness in scale change and rotation change, high registration accuracy, and stitching speed is about 10 times that of SIFT.
61 citations
TL;DR: Wang et al. as discussed by the authors proposed a deep learning technology based on a Deep Belief-Back Propagation neural network to provide a decision-making basis for predicting and preventing smog polluted weather.
Abstract: Smog pollution is becoming a significant problem for people worldwide, becoming an essential threat to the global environment. Many studies on haze already exist, which still need to continue in-depth research to better deal with haze problems. Due to its unique geographical environment, Sichuan has become one of the areas with severe smog pollution. Therefore, the research and prediction of smog pollution in Sichuan has become an urgent need. This paper proposes a deep learning technology based on a Deep Belief-Back Propagation neural network. It makes in-depth prediction research by using the air pollution data of PM2.5, PM10, O 3 , CO NO 2, and SO 2 in Sichuan smog to provide a decision-making basis for predicting and preventing smog polluted weather. According to the prediction results of the model, the concentrations of PM2.5 and PM10 in Chengdu were predicted. The analysis shows that the larger the number of hidden layers in the belief network, the higher the prediction accuracy. Under the same network, the prediction accuracy of PM2.5 is significantly higher than that of PM10. Compared with the traditional Back Propagation neural network, the prediction effect of the Deep Belief-Back Propagation neural network is better. • Based on the air pollution data of PM2.5, PM10, O3, Co, NO2 and SO2 in Sichuan smog, this paper makes an prediction research for predicting and preventing smog polluted weather. • Aiming at the problem of PM2.5 and PM10 concentration prediction, this paper constructs a prediction model based on Deep Belief -Back Propagation neural network. • The results show that the prediction effect of Deep Belief - BP neural network is better than BP neural network, and can quickly extract the concentration characteristics in the first 24 times.
47 citations
TL;DR: In this article, a grounded theory approach is used to investigate the "lived experiences" of inside salespeople at the intersection with social media in sales, and a framework depicting: inside sales strategic social media use → inside salesperson-customer digital engagement →Inside sales performance is presented.
28 citations
TL;DR: The LSTM model trained with the combination of surface-riser-downhole comprehensive detection technologies performs the best in reducing both the prediction error and detection time delay, which could be used to quantitatively evaluate the downhole gas kick risk in the more accurate, faster, more stable, more reliable, and cost-effective manner.
28 citations
TL;DR: In this article, the authors used spatial econometric and threshold effect models to study the effects of foreign direct investment (FDI) in China's energy conservation and emissions reduction.
Abstract: This paper uses spatial econometric and the threshold effect models to study the effects of foreign direct investment (FDI) in China’s energy conservation and emissions reduction. We use provincial...
27 citations
TL;DR: In this article, a methodology that applies pattern recognition methods to guide Bayesian model updating (BMU) and supervise the identification of structural damage is proposed, where the transfer learning technique realized by domain adaptation is used to bridge the gap between the biased numerical model and the real structure and to guide the model updating process.
23 citations
TL;DR: In this paper , the authors investigated the efficiency of psychrotrophic cellulose-degrading fungal strains (PCDFSs) and EDBs combined with humic acid (HA) on estrone (E1) and 17β-estradiol (E2) degradation.
22 citations
TL;DR: In this article , a set of DNA probes targeting a specific segment of the nucleocapsid phosphoprotein (N) gene of SARS-CoV-2 with high binding efficiency was developed.
University of British Columbia1, European Gravitational Observatory2, The University of Texas Rio Grande Valley3, University of Wisconsin–Milwaukee4, California Institute of Technology5, International Centre for Theoretical Sciences6, University of Arizona7, Cardiff University8, Haverford College9, University of Birmingham10, INFN Sezione di Padova11, University of Hamburg12, Laboratoire des Matériaux Avancés13, Université libre de Bruxelles14, Swinburne University of Technology15, Northwestern University16, University of Texas at Austin17, Brera Astronomical Observatory18, University of the Balearic Islands19, Laser Interferometer Gravitational Wave Observatory20, IFAE21, McGill University22, Astroparticle and Cosmology Laboratory23, The Chinese University of Hong Kong24, University of Western Australia25, Paris Diderot University26, University of Florida27, INFN Sezione di Pisa28, Southern University and A&M College29, National Institute for Space Research30, Utrecht University31, Pennsylvania State University32, KEK33, University of Cambridge34, National Institute for Subatomic Physics35, Rochester Institute of Technology36, Observatoire de la Côte d’Azur37, INFN Sezione di Roma I38, University of Tokyo39, University of Glasgow40, Raja Ramanna Centre for Advanced Technology41, INFN Sezione di Roma II42, Louisiana State University43, INFN Sezione di Napoli44, Massachusetts Institute of Technology45, National Central University46
TL;DR: In this paper , the frequency and frequency time-derivative of the gravitational wave signals from 18 pulsars in data from LIGO and Virgo's third observing run (O3) was investigated.
Abstract: Isolated neutron stars that are asymmetric with respect to their spin axis are possible sources of detectable continuous gravitational waves. This paper presents a fully-coherent search for such signals from eighteen pulsars in data from LIGO and Virgo's third observing run (O3). For known pulsars, efficient and sensitive matched-filter searches can be carried out if one assumes the gravitational radiation is phase-locked to the electromagnetic emission. In the search presented here, we relax this assumption and allow the frequency and frequency time-derivative of the gravitational waves to vary in a small range around those inferred from electromagnetic observations. We find no evidence for continuous gravitational waves, and set upper limits on the strain amplitude for each target. These limits are more constraining for seven of the targets than the spin-down limit defined by ascribing all rotational energy loss to gravitational radiation. In an additional search we look in O3 data for long-duration (hours-months) transient gravitational waves in the aftermath of pulsar glitches for six targets with a total of nine glitches. We report two marginal outliers from this search, but find no clear evidence for such emission either. The resulting duration-dependent strain upper limits do not surpass indirect energy constraints for any of these targets.
TL;DR: In this article, exosomes from adipose-derived stem cells (ASCs) were characterized with nanoparticle tracking analysis, transmission electron microscopy, and immunoblotting analysis for exosomal markers.
TL;DR: In this article, a Gamma-based stochastic resistance degradation model is developed by incorporating the spatial degradation into a non-stationary degradation process, and based on the hazard-function-based reliability analysis method, a novel reliability assessment approach of aging structures is proposed.
TL;DR: In this article , the authors determine speed limits on the informational measures, namely the von Neumann entropy, maximal information, and coherence of quantum systems evolving under dynamical processes, to determine the fundamental limitations on the evolution time required by the quantum systems for the changes in their informational measures.
Abstract: The quantum speed limit indicates the maximal evolution speed of the quantum system. In this work, we determine speed limits on the informational measures, namely the von Neumann entropy, maximal information, and coherence of quantum systems evolving under dynamical processes. These speed limits ascertain the fundamental limitations on the evolution time required by the quantum systems for the changes in their informational measures. Erasing of quantum information to reset the memory for future use is crucial for quantum computing devices. We use the speed limit on the maximal information to obtain the minimum time required to erase the information of quantum systems via some quantum processes of interest.
TL;DR: In this article , a review summarizes studies and analogizes metal-organic frameworks (MOFs) as Hg 2+ ions removing materials from the water, and the role of functional sites for detecting heavy metal ions, removal potential, principle, and MOFs properties are discussed significantly.
TL;DR: In this article , a Stackelberg game model is employed while the government is considered as the leader and the manufacturer as the follower, and the results of the model are compared with the centralized one indicating that the centralized model will result in a better solution for both the manufacturer and the government.
TL;DR: In this article , a controlled phytotron glasshouse study was done to investigate the effects of short-term low or high temperature stress on grain yield and the proportions of starch and protein in two wheat cultivars Ningmai 13 and Zhenmai 12.
TL;DR: In this paper, the robustness of convolutional neural networks (CNNs) for text classification on out-of-distribution (OOD) datasets resulting from the natural evolution of clinical text in pathology reports was investigated.
TL;DR: In this article , the authors simulated climate impacts of US-Russia and India-Pakistan nuclear wars in an Earth System Model, here, they report on the ocean impacts, characterized by shallower pycnoclines, thermoclines and nutriclines, ventilated deep water masses, and thicker Arctic sea ice.
Abstract: Nuclear war would produce dire global consequences for humans and our environment. We simulated climate impacts of US-Russia and India-Pakistan nuclear wars in an Earth System Model, here, we report on the ocean impacts. Like volcanic eruptions and large forest fires, firestorms from nuclear war would transport light-blocking aerosols to the stratosphere, resulting in global cooling. The ocean responds over two timescales: a rapid cooling event and a long recovery, indicating a hysteresis response of the ocean to global cooling. Surface cooling drives sea ice expansion, enhanced meridional overturning, and intensified ocean vertical mixing that is expanded, deeper, and longer lasting. Phytoplankton production and community structure are highly modified by perturbations to light, temperature, and nutrients, resulting in initial decimation of production, especially at high latitudes. A new physical and biogeochemical ocean state results, characterized by shallower pycnoclines, thermoclines, and nutriclines, ventilated deep water masses, and thicker Arctic sea ice. Persistent changes in nutrient limitation drive a shift in phytoplankton community structure, resulting in increased diatom populations, which in turn increase iron scavenging and iron limitation, especially at high latitudes. In the largest US-Russia scenario (150 Tg), ocean recovery is likely on the order of decades at the surface and hundreds of years at depth, while changes to Arctic sea-ice will likely last thousands of years, effectively a “Nuclear Little Ice Age.” Marine ecosystems would be highly disrupted by both the initial perturbation and in the new ocean state, resulting in long-term, global impacts to ecosystem services such as fisheries.
TL;DR: In this article , a cold shock protein (csp) gene was upregulated for maintaining stable growth in Arthrobacter sp. C2 responding to vanillin and cold stress, and the recombinant strain C2 was constructed by simultaneously deleting the xylC gene encoding benzaldehyde dehydrase and overexpressing the pchF gene encoding vanillyl alcohol oxidase.
TL;DR: In this article , the authors examined how motor skills might explain autistic individuals' low adaptive behavior scores and which individual components of IQ (i.e., verbal comprehension and perceptual reasoning) and motor skills (e.g., manual dexterity, aiming and catching, and balance) may drive this effect.
Abstract: It is well-documented that intelligence quotient (IQ) is a poor predictor of adaptive behavior scores in autism, with autistic children having lower adaptive behavior scores than would be predicted based on their IQ scores. Differences in motor skills may explain the variability in their adaptive behavior scores. The current study examined how motor skills might explain autistic individuals' low adaptive behavior scores and which individual components of IQ (i.e., verbal comprehension and perceptual reasoning) and motor skills (i.e., manual dexterity, aiming and catching, and balance) may drive this effect. We examined the associations between IQ, motor skills, calibrated severity, and adaptive behavior scores in 45 autistic children and adolescents. Using a t-test, we found a significant difference (p <0.001) between full-scale IQ and adaptive behavior scores, indicating that our participants' adaptive behavior scores were lower than would be expected given their full-scale IQ. Using a linear regression, we investigated whether motor skills predicted adaptive behavior in autistic children and adolescents and found that motor skills scores were associated with adaptive behavior scores (p = 0.022). To further investigate these associations, we used another linear regression to examine how individual components of IQ and motor skills predicted adaptive behavior scores in autistic children and adolescents. Our results indicated that manual dexterity scores were associated with adaptive behavior scores (p = 0.036). These findings clearly illustrate the need for further understanding of autistic individuals' difficulties with adaptive behavior and the potential role of motor skill difficulties that may underlie these difficulties. LAY SUMMARY: Autistic children have lower adaptive behavior scores (e.g., daily living skills, social skills, communication) than intelligence scores (e.g., verbal and perceptual skills) along with difficulties with motor skills. Motor skills may explain the gap between adaptive behavior and intelligence. We found motor skills were associated with adaptive behavior in autistic children and adolescents. In particular, hand coordination was associated with adaptive behavior. We need to better understand how autistic individuals' motor skills impact their adaptive behavior to provide effective supports.
TL;DR: In this paper, a stochastic approach is used to evaluate the benefits which may arise from the use of structural health monitoring systems on the support structures of offshore wind, and the relevant failure modes acknowledged for the common monopile-type turbine were selected based on real events, and evaluation of the critical regions of these structures was performed making use of results from the literature.
TL;DR: In this paper, the authors studied the rheology and annular flow of a smart lost circulation material (LCM) at 160°C, using a high-temperature flow loop.
01 Jan 2022-Journal of Materials Chemistry C. Materials for Optical, Magnetic and Electronic Devices
TL;DR: In this article , the authors discuss the fabrication, optimization and applications of liquid crystal microcapsules in detail, and the current challenges and potential development directions are also introduced briefly, as well as the current development directions.
Abstract: In this review, we discuss the fabrication, optimization and applications of liquid crystal microcapsules in detail. The current challenges and potential development directions are also introduced briefly.
TL;DR: In this article , an anisotropic elasto-plastic-damage model was developed for quasi-brittle materials within the thermodynamics framework, which is characterized by second-order damage tensors that are different under tensile and compressive loadings.
TL;DR: In this article , electrical trigeminal nerve stimulation (TNS) has been shown to enhance cerebral circulation at multiple levels, lessen the impact of cerebral ischemia, and ameliorate the consequences of delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage.
Abstract: Delayed cerebral ischemia (DCI) is the most consequential secondary insult after aneurysmal subarachnoid hemorrhage (SAH). It is a multifactorial process caused by a combination of large artery vasospasm and microcirculatory dysregulation. Despite numerous efforts, no effective therapeutic strategies are available to prevent DCI. The trigeminal nerve richly innervates cerebral blood vessels and releases a host of vasoactive agents upon stimulation. As such, electrical trigeminal nerve stimulation (TNS) has the capability of enhancing cerebral circulation.To determine whether TNS can restore impaired cerebral macrocirculation and microcirculation in an experimental rat model of SAH.The animals were randomly assigned to sham-operated, SAH-control, and SAH-TNS groups. SAH was induced by endovascular perforation on Day 0, followed by KCl-induced cortical spreading depolarization on day 1, and sample collection on day 2. TNS was delivered on day 1. Multiple end points were assessed including cerebral vasospasm, microvascular spasm, microthrombosis, calcitonin gene-related peptide and intercellular adhesion molecule-1 concentrations, degree of cerebral ischemia and apoptosis, and neurobehavioral outcomes.SAH resulted in significant vasoconstriction in both major cerebral vessels and cortical pial arterioles. Compared with the SAH-control group, TNS increased lumen diameters of the internal carotid artery, middle cerebral artery, and anterior cerebral artery, and decreased pial arteriolar wall thickness. Additionally, TNS increased cerebrospinal fluid calcitonin gene-related peptide levels, and decreased cortical intercellular adhesion molecule-1 expression, parenchymal microthrombi formation, ischemia-induced hypoxic injury, cellular apoptosis, and neurobehavioral deficits.Our results suggest that TNS can enhance cerebral circulation at multiple levels, lessen the impact of cerebral ischemia, and ameliorate the consequences of DCI after SAH.
TL;DR: In this article, the authors compared ROT, patch-burn grazing, and before and after treatment implementation to assess their effects on grassland-associated bird species and found that ROT had more influence on the relative abundance of birds than Patch-Burn Grazing.
TL;DR: This work proposes a novel scale-aware network and then develops a new fusion scheme that derives high-consistency response maps and high-precision descriptions in pixel-level correspondences based on the intuition that keypoints need to be extracted and described on an appropriate scale.
TL;DR: In this article , the capacity of DMT, the monoamine oxidase inhibitor (MAOI) harmaline, and "pharmahuasca" (DMT + harmaline) to reduce reactive oxygen species (ROS) production and inflammatory gene expression and to modulate neuroplasticity-related gene expression in the model.
Abstract: Post-traumatic stress disorder (PTSD) is associated with cognitive deficits, oxidative stress, and inflammation. Animal models have recapitulated features of PTSD, but no comparative RNA sequencing analysis of differentially expressed genes (DEGs) in the brain between PTSD and animal models of traumatic stress has been carried out. We compared DEGs from the prefrontal cortex (PFC) of an established stress model to DEGs from the dorsolateral PFC (dlPFC) of humans. We observed a significant enrichment of rat DEGs in human PTSD and identified 20 overlapping DEGs, of which 17 (85%) are directionally concordant. N,N-dimethyltryptamine (DMT) is a known indirect antioxidant, anti-inflammatory, and neuroprotective compound with antidepressant and plasticity-facilitating effects. We tested the capacity of DMT, the monoamine oxidase inhibitor (MAOI) harmaline, and "pharmahuasca" (DMT + harmaline) to reduce reactive oxygen species (ROS) production and inflammatory gene expression and to modulate neuroplasticity-related gene expression in the model. We administered DMT (2 mg/kg IP), harmaline (1.5 mg/kg IP), pharmahuasca, or vehicle every other day for 5 days, following a 30 day stress regiment. We measured ROS production in the PFC and hippocampus (HC) by electron paramagnetic resonance spectroscopy and sequenced total mRNA in the PFC. We also performed in vitro assays to measure the affinity and efficacy of DMT and harmaline at 5HT2AR compared to 5-HT. DMT and pharmahuasca reduced ROS production in the PFC and HC, while harmaline had mixed effects. Treatments normalized 9, 12, and 14 overlapping DEGs, and pathway analysis implicated that genes were involved in ROS production, inflammation, growth factor signaling, neurotransmission, and neuroplasticity.