Mechanism of Diabatic Heating on Precipitation and the Track of a Tibetan Plateau Vortex over the Eastern Slope of the Tibetan Plateau

Existing studies contend that latent heating(LH)will replace sensible heating(SH)to become the dominant factor affecting the development of the Tibetan Plateau vortex(TPV)after it moves off the Tibetan Plateau(TP).However,in the process of the TPV moving off the TP requires that the airmass traverse the eastern slope of the Tibetan Plateau(ESTP)where the topography and diabatic heating(DH)conditions rapidly change.How LH gradually replaces SH to become the dominant factor in the development of the TPV over the ESTP is still not very clear.In this paper,an analysis of a typical case of a TPV with a long life history over the ESTP is performed by using multi-sourced meteorological data and model simulations.The results show that SH from the TP surface can change the TPV-associated precipitation distribution by temperature advection after the TPV moves off the TP.The LH can then directly promote the development of the TPV and has a certain guiding effect on the track of the TPV.The SH can control the active area of LH by changing the falling area of the TPV-associated precipitation,so it still plays a key role in the development and tracking of the TPV even though it has moved out of the main body of the TP.

Numerical Study of the Biomechanical Behavior of a 3D Printed Polymer Esophageal Stent in the Esophagus by BP Neural Network Algorithm

Esophageal disease is a common disorder of the digestive system that can severely affect the quality of life andprognosis of patients. Esophageal stenting is an effective treatment that has been widely used in clinical practice.However, esophageal stents of different types and parameters have varying adaptability and effectiveness forpatients, and they need to be individually selected according to the patient’s specific situation. The purposeof this study was to provide a reference for clinical doctors to choose suitable esophageal stents. We used 3Dprinting technology to fabricate esophageal stents with different ratios of thermoplastic polyurethane (TPU)/(Poly-ε-caprolactone) PCL polymer, and established an artificial neural network model that could predict the radial forceof esophageal stents based on the content of TPU, PCL and print parameter. We selected three optimal ratios formechanical performance tests and evaluated the biomechanical effects of different ratios of stents on esophagealimplantation, swallowing, and stent migration processes through finite element numerical simulation and in vitrosimulation tests. The results showed that different ratios of polymer stents had different mechanical properties,affecting the effectiveness of stent expansion treatment and the possibility of postoperative complications of stentimplantation.

The Performance Analysis for Distributed Collaborative Beamforming Transmission of Clustered Mobile Sensor Network

Sensor nodes cannot directly communicate with the distant unmanned aerial vehicle( UAV) for their low transmission power. Distributed collaborative beamforming from sensor nodes within a cluster is proposed to provide high speed data transmission to the distant UAV. The bit error ratio( BER) closed-form expression of distributed collaborative beamforming transmission with mobile sensor nodes has been derived. Furthermore,based on the theoretical BER analysis and the numerical results,we have analyzed the impacts of nodes 'mobility,number of sensor nodes,transmission power and the elevation angle of UAV on the BER performance of collaborative beamforming. And we come to the following conclusions: the mobility of sensor nodes largely decreases the BER performance; when the position deviation radius is large,incensement in power cannot improve BER anymore; the size of cluster should be bigger than 10 for the purpose of achieving good BER performance in Rayleigh fading channel.

Prediction model of interval grey number based on DGM(1,1)

In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example's program simulation,the validity and practicability of this novel model are verified.

Amniotic membrane covering promotes healing of cornea epithelium and improves visual acuity after debridement for fungal keratitis

AIM:To investigate the effect of amniotic membrane covering(AMC) on the healing of cornea epithelium and visual acuity for fungal keratitis after debridement.METHODS:Twenty fungal keratitis patients were divided into two groups randomly, the AMC group and the control group, ten patients each group. Both debridement of the infected cornea tissue and standard anti-fungus drugs treatments were given to every patients, monolayer amniotic membrane were sutured to the surface of the entire cornea and bulbar conjunctiva with 10-0 nylon suture for patients in the AMC group.The diameter of the ulcer was determined with slit lamp microscope and the depth of the infiltration was determined with anterior segment optical coherence tomography. Uncorrected visual acuity(UCVA) was tested before surgery and three month after healing of the epithelial layer. The healing time of the cornea epithelium, visual acuity(VA) was compared between the two groups using t- test.RESULTS:There was no statistical difference of the diameter of the ulcer, depth of the infiltration, height of the hypopyon and VA between the two groups beforesurgery(P >0.05). The average healing time of the AMC group was 6.89 ±2.98 d, which was statistically shorter than that of the control group(10.23±2.78d)(P <0.05).The average UCVA of the AMC group was 0.138 ±0.083,which was statistically better than that of the control group(0.053±0.068)(P <0.05).CONCLUSION:AMC surgery could promote healing of cornea epithelium after debridement for fungal keratitis and lead to better VA outcome.

Protective effect of apoptosis signal-regulating kinase1 inhibitor against mice liver injury

Objective:To explore the protective effect and its molecular mechanism of apoptosis signalregulating kinase 1(ASK1) inhibitor(GS-459679) on acetaminophen-induced liver injury in mice.Methods:The model of liver injury was established by administration of acetaminophen(APAP)(300 mg/kg,i.p.) on C57BL/6 mice.Forty-eight male C57BL/6 mice were randomly divided into four groups,consisting of control group,GS group(GS-459679,30 mg/kg,i.p.),APAPinduced group,and GS combined with APAP-induced group.For GS combined with APAPinduced group,mice were treated with GS 30 min prior to administration of APAP.After mice were euthanized at 6 h or 12 h.respectively,serum levels of alanine aminotransferase(ALT) and aspartate aminotransferase(AST) were analyzed,and mRNA levels of TNF- α,IL-6 and IL-1βwere tested.The activity of glutathione(GSH),oxidized GSH(GSSG) and malondialdehyde were quantified.In addition,ASK1,P-ASK1,JNK and P-JNK protein levels were tested in all groups.Results:The ASK1 and P-ASK1 levels were up-regulated in APAP-induced group.Compared to the control group,serum levels of ALT and AST.and mRNA levels of TNF- a,IL-6 and IL-1(3were increased in APAP-induced group.Meanwhile,the levels of MAD and GSSG.and the ratio of GSSG/GSH were higher and the JNK was activatedin APAP-induced group compared with that in control group.However,compared to APAP-induced group,GS combined with APAP-induced group displayed a decrease of protein expression levels of ASK 1,P-ASKI and P-JNK,a reduction of serum levels of ALT and AST,a decrease in TNF- a.IL-6 and IL-1(3 mRNA levels,and a low ration of GSSG/GSH.Conclusions:GS-459679 treatment effectively down-regulates ASK1 and P-ASK 1 expression.Addition of GS-459679 decreases the generation of liver metabolites and inflammatory factors,reduces oxidative stress reaction,inhibits JNK activation,and then protects the responsiveness to APAP-induced liver injury.

Aurora-A is a novel predictor of poor prognosis in patients with resected lung adenocarcinoma

Background: The Aurora-A(Aur-A) gene, a key regulator of mitosis, has been proved as an oncogene in a variety of cancers. The Aur-A overexpression has been proved correlated with aggressiveness of cancer cells. However, the frequency of Aur-A protein overexpression, as well as its association with clinicopathologic parameters and prognosis remain unclear in lung adenocarcinoma(ADC). This study tried to clarify the clinical significance of Aur-A in patients with resected lung ADC. Patients and methods: A total of 142 informative patients with surgically resected lung ADC and 20 normal lung tissues were enrolled. Western blot and immunohistochemistry(IHC) were utilized to assess protein expression of Aur-A.Result: The expression of Aur-A was elevated in most of tumor tissues compared with the adjacent tissues by western blot. The IHC results showed that Aur-A protein was over-expressed in 98 of 142(69.0%) tumor sections, while Aur-A was low-expressed in all normal lung sections. A positive correlation between Aur-A overexpression rate and ascending pathologic stages was observed(P<0.05). Kaplan-Meier analysis demonstrated that patients with Aur-A high expression had significantly inferior survival compared to those with Aur-A low expression. Both overall survival(OS) and disease-free survival(DFS) of positive overexpression patients were shorter than the negative group(P=0.036, P=0.041, respectively). Multivariate analysis confirmed that Aur-A expression, as an independent and significant factor for both DFS and OS, could predict a poor prognosis in patients with resected lung ADC(P=0.022, P=0.049, respectively).Conclusions: Aur-A was overexpressed in lung ADC and overexpression of Aur-A might be a novel predictor for poor prognosis and potential therapeutic target in lung ADC.

Equivalency and unbiasedness of grey prediction models

In order to deeply research the structure discrepancy and modeling mechanism among different grey prediction models, the equivalence and unbiasedness of grey prediction models are analyzed and verified. The results show that all the grey prediction models that are strictly derived from x(0)(k) +az(1)(k) = b have the identical model structure and simulation precision. Moreover, the unbiased simulation for the homogeneous exponential sequence can be accomplished. However, the models derived from dx(1)/dt + ax(1)= b are only close to those derived from x(0)(k) + az(1)(k) = b provided that |a| has to satisfy|a| < 0.1; neither could the unbiased simulation for the homogeneous exponential sequence be achieved. The above conclusions are proved and verified through some theorems and examples.

Single-nucleus transcriptomic profiling of multiple organs in a rhesus macaque model of SARS-CoV-2 infection

Infection with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) causes diverse clinical manifestations and tissue injuries in multiple organs.However, cellular and molecular understanding of SARS-CoV-2 infection-associated pathology and immune defense features in different organs remains incomplete. Here, we profiled approximately 77 000single-nucleus transcriptomes of the lung, liver,kidney, and cerebral cortex in rhesus macaques(Macaca mulatta) infected with SARS-CoV-2 and healthy controls. Integrated analysis of the multiorgan dataset suggested that the liver harbored the strongest global transcriptional alterations. We observed prominent impairment in lung epithelial cells, especially in AT2 and ciliated cells, and evident signs of fibrosis in fibroblasts. These lung injury characteristics are similar to those reported in patients with coronavirus disease 2019(COVID-19).Furthermore, we found suppressed MHC class I/II molecular activity in the lung, inflammatory response in the liver, and activation of the kynurenine pathway,which induced the development of an immunosuppressive microenvironment. Analysis of the kidney dataset highlighted tropism of tubule cells to SARS-CoV-2, and we found membranous nephropathy(an autoimmune disease) caused by podocyte dysregulation. In addition, we identified the pathological states of astrocytes and oligodendrocytes in the cerebral cortex, providing molecular insights into COVID-19-related neurological implications. Overall, our multi-organ single-nucleus transcriptomic survey of SARS-CoV-2-infected rhesus macaques broadens our understanding of disease features and antiviral immune defects caused by SARS-CoV-2 infection,which may facilitate the development of therapeutic interventions for COVID-19.

Noninvasive Blood Glucose Monitoring System Based on Distributed Multi-Sensors Information Fusion of Multi-Wavelength NIR

In this research, a near infrared multi-wavelength noninvasive blood glucose monitoring system with distributed laser multi-sensors is applied to monitor human blood glucose concentration. In order to improve the monitoring accuracy, a multi-sensors information fusion model based on Back Propagation Artificial Neural Network is proposed. The Root- Mean-Square Error of Prediction for noninvasive blood glucose measurement is 0.088mmol/L, and the correlation coefficient is 0.94. The noninvasive blood glucose monitoring system based on distributed multi-sensors information fusion of multi-wavelength NIR is proved to be of great efficient. And the new proposed idea of measurement based on distri- buted multi-sensors, shows better prediction accuracy.

Optimal Planning of IDR-integrated Electricity-heat Systems Considering Techno-economic and Carbon Emission Issues

This study presents an optimal electricity-heat system(EHS)planning framework to promote the accommodation of wind power while considering technical,economic and environmental criteria.To this end,integrated demand response(IDR)is introduced as a flexibility resource to complement the inherent fluctuation of renewable energy sources and modeled by using price elasticity theory.Both the timing transferring and energy substitution potentials are considered in the proposed IDR program.Incorporating the effect of IDR into the EHS planning model,a two-stage stochastic programming model can be devised,in which the optimal EHS configuration design and associated operation control techniques are found simultaneously to minimize the system’s total economic and carbon-emission costs over the planning horizon.The multi-scale uncertainties arising from both long-term demand growth and operation-level variability of renewables/load demands are captured collectively by using a scenario-based method.The suggested planning approach is illustrated using a real EHS test case and the results show that it is effective in practical applications.

Quantifying Contribution of DER-Integrated EV Parking Lots to Reliability of Power Distribution Systems

In the future smart cities,parking lots(PLs)can accommodate hundreds of electric vehicles(EVs)at the same time.This trend creates an opportunity for PLs to serve as a potential flexibility resource,considering growing penetration of EVs and integration of distributed energy resources DER(such as photovoltaic and energy storages).Given this background,this paper proposes a comprehensive evaluation framework to investigate the potential role of DER-integrated PLs(DPL)with the capability of vehicle-to-grid(V2G)in improving the reliability of the distribution network.For this aim,first,an overview for the distribution system with DPLs is provided.Then,a generic model for the available generation capacity(AGC)of DPLs with consideration of EV scheduling strategy is developed.On the above basis,an iterative-based algorithm leveraging sequential Monte Carlo simulation is presented to quantify the contribution of DPLs to the reliability of the system.In order to verify the effectiveness of the proposed method,a series of numerical studies are carried out.The simulation results show that the integration of DPLs with the V2G capability could help to improve the reliability performance of distribution grid to a great extent and reduce the adverse impact incurred by EV accommodation,if utilized properly.

An optimization model for conductivity of hydraulic fracture networks in the Longmaxi shale,Sichuan basin,Southwest China

Shale gas is an important unconventional resource.The economic recovery of shale gas is only possible when a fracture network with sufficient conductivity is created by hydraulic fracturing,that,if effectively propped,connects fracturing fractures and natural fractures.Focusing on the Longmaxi shale in the Sichuan Basin,Southwest China,we built an optimization model for conductivity of multi-grade fractures based on equivalent seepage theory.We then experimentally analyzed the conductivity of self-propped and sand-propped fractures,and optimized the propping patterns of multi-grade hydraulic fractures in shale gas reservoirs.We concluded that the propping effectiveness of fracture networks could be improved by using low concentrations of small-sized sands and by focusing on creating a large number of self-propped fractures.By applying this understanding to the optimization of fracturing designs for the Longmaxi shale,we successfully created networks of well-propped fractures.

Day-ahead Network-constrained Unit Commitment Considering Distributional Robustness and Intraday Discreteness:A Sparse Solution Approach

Quick-start generation units are critical devices and flexible resources to ensure a high penetration level of renewable energy in power systems.By considering the wind uncertainty and both binary and continuous decisions of quickstart generation units within the intraday dispatch,we develop a Wasserstein-metric-based distributionally robust optimization model for the day-ahead network-constrained unit commitment(NCUC)problem with mixed-integer recourse.We propose two feasible frameworks for solving the optimization problem.One approximates the continuous support of random wind power with a finite number of events,and the other leverages the extremal distributions instead.Both solution frameworks rely on the classic nested column-and-constraint generation(C&CG)method.It is shown that due to the sparsity of L_(1)-norm Wasserstein metric,the continuous support of wind power generation could be represented by a discrete one with a small number of events,and the rendered extremal distributions are sparse as well.With this reduction,the distributionally robust NCUC model with complicated mixed-integer recourse problems can be efficiently handled by both solution frameworks.Numerical studies are carried out,demonstrating that the model considering quick-start generation units ensures unit commitment(UC)schedules to be more robust and cost-effective,and the distributionally robust optimization method captures the wind uncertainty well in terms of out-of-sample tests.

DFPC-SLAM:A Dynamic Feature Point Constraints-Based SLAM Using Stereo Vision for Dynamic Environment

Visual SLAM methods usually presuppose that the scene is static, so the SLAM algorithm formobile robots in dynamic scenes often results in a signicant decrease in accuracy due to thein°uence of dynamic objects. In this paper, feature points are divided into dynamic and staticfrom semantic information and multi-view geometry information, and then static region featurepoints are added to the pose-optimization, and static scene maps are established for dynamicscenes. Finally, experiments are conducted in dynamic scenes using the KITTI dataset, and theresults show that the proposed algorithm has higher accuracy in highly dynamic scenes comparedto the visual SLAM baseline.

A Nonlinear Grey Bernoulli Model with Conformable Fractional-Order Accumulation and Its Application to the Gross Regional Product in the Cheng-Yu Area

This study considers a nonlinear grey Bernoulli forecasting model with conformable fractionalorder accumulation,abbreviated as CFNGBM(1,1,λ),to study the gross regional product in the ChengYu area.The new model contains three nonlinear parameters,the power exponentγ,the conformable fractional-orderαand the background valueλ,which increase the adjustability and flexibility of the CFNGBM(1,1,λ)model.Nonlinear parameters are determined by the moth flame optimization algorithm,which minimizes the mean absolute prediction percentage error.The CFNGBM(1,1,λ)model is applied to the gross regional product of 16 cities in the Cheng-Yu area,which are Chongqing,Chengdu,Mianyang,Leshan,Zigong,Deyang,Meishan,Luzhou,Suining,Neijiang,Nanchong,Guang’an,Yibin,Ya’an,Dazhou and Ziyang.With data from 2013 to 2021,several grey models are established and results show that the new model has higher accuracy in most cases.

疾病治疗及药物制备用酶的研究进展

生物技术的发展及对疾病机理的深入研究,使酶逐步应用于疾病治疗。与此同时,以酶作为催化剂制备非天然有机化合物具有反应条件温和、催化效率高、特异性高、选择性强、副反应少等优点。因而,酶也在药物制造方面展现了巨大潜力。此外,基因工程、酶化学修饰和固定化技术的应用进一步改善了酶的功能。基于此,文中结合本课题组的相关研究,综述了近年来酶作为药物用于疾病治疗及作为催化剂用于药物制造的研究进展,并对其存在的问题提出了相应的解决办法,最后对酶在医药领域的应用前景进行了展望。

Scutellarin inhibits caspase-11 activation and pyroptosis in macrophages via regulating PKA signaling

Inflammatory caspase-11 senses and is activated by intracellular lipopolysaccharide(LPS)leading to pyroptosis that has critical role in defensing against bacterial infection,whereas its excess activation under pathogenic circumstances may cause various inflammatory diseases.However,there are few known drugs that can control caspase-11 activation.We report here that scutellarin,a flavonoid from Erigeron breviscapus,acted as an inhibitor for caspase-11 activation in macrophages.Scutellarin dosedependently inhibited intracellular LPS-induced release of caspase-11 p26(indicative of caspase-11 activation)and generation of N-terminal fragment of gasdermin D(GSDMD-NT),leading to reduced pyroptosis.It also suppressed the activation of non-canonical nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3(NLRP3)inflammasome as evidenced by reduced apoptosisassociated speck-like protein containing a CARD(ASC)speck formation and decreased interleukin-1 beta(IL-1 b)and caspase-1 p10 secretion,whereas the NLRP3-specific inhibitor MCC950 only inhibited IL-1 b and caspase-1 p10 release and ASC speck formation but not pyroptosis.Scutellarin also suppressed LPS-induced caspase-11 activation and pyroptosis in RAW 264.7 cells lacking ASC expression.Moreover,scutellarin treatment increased Ser/Thr phosphorylation of caspase-11 at protein kinase A(PKA)-specific sites,and its inhibitory action on caspase-11 activation was largely abrogated by PKAinhibitor H89 or by adenylyl cyclase inhibitor MDL12330 A.Collectively,our data indicate that scutellarin inhibited caspase-11 activation and pyroptosis in macrophages at least partly via regulating the PKA signaling pathway.

Alterations in cecal microbiota of Jinhua piglets fostered by a Yorkshire sow

Gut microbiota play important roles in host health and diseases.Several factors,in particular antibiotics,affect the gut microbiota of pigs.Cross-fostering has been applied as a regular practice to equalize litter size,reduce pre-weaning mortality and increase body weight.However,the effect of cross-fostering on cecal microbiota is unclear.In this study,we fostered three Jinhua pigs to a Yorkshire sow.The fostered Jinhua piglets grew significantly faster than their biological siblings.To explore whether the cecal microbiota of piglets will alter during fostering,we characterized the cecal microbiota of allpiglets by examining the V3 hypervariable region of 16S rDNA.We observed altered cecal microbiota in these piglets using the Illumina HiSeq 2000 platform,and this was accompanied with an increase in growth rate after fostering.The relative abundance of Bacteroidetes in the fostered Jinhua piglets was decreased compared with their biological siblings,although still higher in comparison with their new littermates.Beta-diversity analysis also showed that the cecal microbiota of the adopted Jinhua piglets differed from their biological siblings with a shift toward their step-siblings.Our data show that cecal microbiota of piglets were altered after cross-fostering while the growth rate increased.

Construction of MoS2 field effect transistor sensor array for the detection of bladder cancer biomarkers

Bladder cancer is one of the commonest malignant tumors of urinary system with high recurrence. However, currently developed bladder cancer urine diagnosis methods are hindered by the low detection sensitivity and accuracy. Herein, a molybdenum disulfide(MoS2) nanosheets-based field effect transistor(FET) sensor array was constructed for simultaneous detection of multiple bladder cancer biomarkers in human urine. With the excellent electronic property of MoS2 and the high specific identification capability of recognition molecules, the proposed biosensor array could simultaneously detect nuclear matrix protein 22(NMP22) and cytokeratin 8(CK8) with a wide linear range of 10-6–10-1 pg mL-1 and an ultra-low detection limit of 0.027 and 0.019 aM, respectively. Furthermore, this highly sensitive and specific MoS2 FET sensor array could be used to identify bladder cancer biomarkers from human urine samples. This designed high-performance biosensor array shows great potential in the future diagnosis of bladder cancer.