Discussion on the application prospect of the transient electromagnetic method based on the dual launcher and mine advanced detection

The dual transmitter implements the equivalent anti-magnetic flux transient electromagnetic method, which can effectively reduce the scope of the transient electromagnetic detection blind area. However, this method is rarely reported in the detection of pipelines in urban geophysical exploration and the application of coal mines. Based on this, this paper realizes the equivalent anti-magnetic flux transient electromagnetic method based on the dual launcher. The suppression effect of this method on the blind area is analyzed by physical simulation. And the detection experiment of underground pipelines is carried out outdoors. The results show that the dual launcher can significantly reduce the turn-off time, thereby effectively reducing the impact of the blind area on the detection results, and the pipeline detection results verify the device’s effectiveness. Finally, based on the ground experimental results, the application prospect of mine advanced detection is discussed. Compared with other detection fields, the formation of blind areas is mainly caused by the equipment. If the dual launcher can be used to reduce the blind area, the accuracy of advanced detection can be improved more effectively. The above research results are of great significance for improving the detection accuracy of the underground transient electromagnetic method.

非常规储层微纳米孔隙介质中流体相态研究进展

非常规油气储层具有岩石骨架颗粒小、比表面积大、微纳米孔隙发育的特点,流体与孔隙介质间存在着诸多复杂的界面效应问题,影响微纳米孔隙介质中流体的相态变化规律。对于受限域流体,经典油气相态理论方法忽略分子间相互作用及界面效应的影响,预测微纳米孔隙介质中流体相变特征存在偏差。为了更全面地揭示油气在受限空间中的相态特征及其微观作用机理,总结当前微纳米孔隙介质中流体相态研究技术现状,详细阐述微观实验测试、相态理论模型和分子模拟3种主流技术方法,指出3种技术各自的优缺点,并对未来流体相态研究技术提出展望。分析认为:微观实验测试方法可通过研究流体热力学参数的变化来确定流体相变点,由于实验误差、人为误差等原因,需与理论计算相结合;相态理论模型方法可通过改进临界参数场、考虑流体与孔壁界面作用、考虑相间毛管压力修正相平衡判据方程等方法建立纳米孔隙空间相态理论模型,但是由于没有综合考虑界面效应带来的影响且缺乏有力的实验数据支撑,难以推广应用;分子模拟方法能在分子尺度上揭示流体分子的相行为,但现有研究主要围绕小分子展开,并且与流体发生相变时的临界参数结合得较少。后续研究应以多界面效应耦合影响的微纳米孔隙介质中油气流体相变特征为研究对象,以微观实验、理论模型和分子模拟为技术手段,为描述微纳米孔隙介质中流体相态提供合理的实验测试手段和可靠的理论计算模型。

页岩矿物不同润湿性表征与吸附微观机理

无机矿物作为页岩气吸附的重要载体,其表面性质对甲烷吸附能力有着重要影响,而润湿性作为固体重要表面性质之一,对矿物气体吸附能力的影响不可忽视.文章以蒙脱石和石英作为研究对象,通过对矿物表面甲基化(-CH_(3))和羟基化(-OH)处理来改变其润湿性,以探究无机矿物表面润湿性对甲烷吸附能力的影响.采用分子动力学方法研究矿物体系的润湿性,用接触角对润湿性进行定量表征,并构建纳米狭缝,结合巨正则蒙特卡罗方法模拟润湿性改变前后,CH4在矿物中的吸附变化.研究结果表明,水滴在羟基化矿物表面迅速破裂并铺展在矿物表面,而在甲基化表面铺展程度较小,普遍呈半球形.羟基化蒙脱石和石英表面的润湿接触角分别为12.7°和26.5°,均小于其甲基化表面接触角62.5°和85.7°.甲基化矿物甲烷吸附量均高于其羟基化,气体几乎大都以吸附状态位于孔隙壁面,随着矿物亲水性的减弱,其对甲烷吸附能力增强.

Aging Mongolian pine plantations face high risks of drought-induced growth decline:evidence from both individual tree and forest stand measurements

Discerning vulnerability differences among different aged trees to drought-driven growth decline or to mortality is critical to implement age-specific countermeasures for forest management in water-limited areas.An important species for afforestation in dry environments of northern China,Mongolian pine(Pinus sylvestris var.mongolica Litv.)has recently exhibited growth decline and dieback on many sites,particularly pronounced in old-growth plantations.However,changes in response to drought stress by this species with age as well as the underlying mechanisms are poorly understood.In this study,tree-ring data and remotely sensed vegetation data were combined to investigate variations in growth at individual tree and stand scales for young(9-13 years)and aging(35-52 years)plantations of Mongolian pine in a water-limited area of northern China.A recent decline in tree-ring width in the older plantation also had lower values in satellited-derived normalized difference vegetation indices and normalized difference water indices relative to the younger plantations.In addition,all measured growth-related metrics were strongly correlated with the self-calibrating Palmer drought severity index during the growing season in the older plantation.Sensitivity of growth to drought of the older plantation might be attributed to more severe hydraulic limitations,as reflected by their lower sapwood-and leaf-specific hydraulic conductivities.Our study presents a comprehensive view on changes of growth with age by integrating multiple methods and provides an explanation from the perspective of plant hydraulics for growth decline with age.The results indicate that old-growth Mongolian pine plantations in water-limited environments may face increased growth declines under the context of climate warming and drying.

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

Spatiotemporal variations of parameters of internal solitary waves in the northern South China Sea

The dynamic parameters for internal solitary waves(ISWs)derived from the extended Korteweg-de Vries(eKdV)equation play an important role in the understanding and prediction of ISWs.The spatiotemporal variations of the dynamic parameters of the ISWs in the northern South China Sea(SCS)were studied based on the reanalysis of long-term temperature and salinity datasets.The results for spectrum analysis show that there are definite geographical differences for the periodic variation of the parameters:in shallow water,all parameters vary with a wave period of one year,while in deep water wave components of the parameters at other frequencies exist.Using wavelet analysis,the wavelet power spectral densities in deep water exhibited an inter-annual variation pattern.For example,the wave component of the dispersion coefficient with a wave period of about half a year reached its power peak once every two years.Based on previous work,this inter-annual variation pattern was deduced to be caused by dynamic processes.In further work on the regulatory mechanisms,empirical orthogonal function(EOF)decomposition was performed.It was found that the modes of the dispersion coefficient have different geographical distributions,explaining the reason why the wave components in different frequencies appeared in different locations.The numerical simulation results confirm that the variations in the parameters of the ISWs derived from the eKdV equation could affect the waveforms significantly because of changes in the polarity of the ISWs.Therefore,the periodic variations of the dynamic parameters are related to the geographical location because of dynamic processes operating.

Crosstalk among Oxidative Stress,Autophagy,and Apoptosis in the Protective Effects of Ginsenoside Rb1 on Brain Microvascular Endothelial Cells:A Mixed Computational and Experimental Study

Objective Brain microvascular endothelial cells (BMECs) were found to shift from their usually inactive state to an active state in ischemic stroke (IS) and cause neuronal damage. Ginsenoside Rb1 (GRb1),a component derived from medicinal plants,is known for its pharmacological benefits in IS,but its protective effects on BMECs have yet to be explored. This study aimed to investigate the potential protective effects of GRb1 on BMECs. Methods An in vitro oxygen-glucose deprivation/reperfusion (OGD/R) model was established to mimic ischemia-reperfusion (I/R) injury. Bulk RNA-sequencing data were analyzed by using the Human Autophagy Database and various bioinformatic tools,including gene set enrichment analysis (GSEA),Gene Ontology (GO) classification and enrichment analysis,Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis,protein-protein interaction network analysis,and molecular docking. Experimental validation was also performed to ensure the reliability of our findings. Results Rb1 had a protective effect on BMECs subjected to OGD/R injury. Specifically,GRb1 was found to modulate the interplay between oxidative stress,apoptosis,and autophagy in BMECs. Key targets such as sequestosome 1 (SQSTM1/p62),autophagy related 5 (ATG5),and hypoxia-inducible factor 1-alpha (HIF-1α) were identified,highlighting their potential roles in mediating the protective effects of GRb1 against IS-induced damage. Conclusion GRbl protects BMECs against OGD/R injury by influencing oxidative stress,apoptosis,and autophagy. The identification of SQSTM1/p62,ATG5,and HIF-1α as promising targets further supports the potential of GRb1 as a therapeutic agent for IS,providing a foundation for future research into its mechanisms and applications in IS treatment.

Hydrogen-bonded organic framework modified separator for simultaneously enhancing the safety and electrochemical performance of Ni-rich lithium-ion battery

Nickel-rich layered oxide cathode(LiNi_(x)Co_(y)Mn_(1−x−y)O_(2),x>0.5,NCM)shows substantial potential for applications in longer-range electrical vehicles.However,the rapid capacity decay and serious safety concerns impede its practical viability.This work provides a hydrogen-bonded organic framework(HOF)modification strategy to simultaneously improve the electrochemical performance,thermal stability and incombustibility of separator.Melamine cyanurate(MCA),as a low-cost and reliable flame-retardant HOF,was implemented in the separator modification layer,which can prevent the battery short circuit even at a high temperature.In addition,the supermolecule properties of MCA provide unique physical and chemical microenvironment for regulating ion-transport behavior in electrolyte.The MCA coating layer enabled the nickel-rich layered oxide cathode with a high-capacity retention of 90.3%after 300 cycles at 1.0 C.Collectively,the usage of MCA in lithium-ion batteries(LIBs)affords a simple,low-cost and efficient strategy to improve the security and service life of nickel-rich layered cathodes.

Cholesterol-induced deformation of the gramicidin A channel inhibiting potassium ion binding and transport

Gramicidin A(gA)is a kind of antibiotic peptide produced by bacillus brevis and it can dimerize across lipid bilayers to form a monovalent cation channel.In this work,we investigate the impact of cholesterol in the lipid bilayer on the binding of potassium ions with the gA channel and the transport of the ions across the channel.The results indicate that cholesterol can significantly influence the conformational stability of the gA channel and cause the channel deformation which inhibits the potassium ion binding with the channel and transport across the channel.The work provides some molecular insights into understanding of influence of lipids on the activity of gA channel in both model membranes and plasma membranes of intact cells.

L_(1)-Smooth SVM with Distributed Adaptive Proximal Stochastic Gradient Descent with Momentum for Fast Brain Tumor Detection

Brain tumors come in various types,each with distinct characteristics and treatment approaches,making manual detection a time-consuming and potentially ambiguous process.Brain tumor detection is a valuable tool for gaining a deeper understanding of tumors and improving treatment outcomes.Machine learning models have become key players in automating brain tumor detection.Gradient descent methods are the mainstream algorithms for solving machine learning models.In this paper,we propose a novel distributed proximal stochastic gradient descent approach to solve the L_(1)-Smooth Support Vector Machine(SVM)classifier for brain tumor detection.Firstly,the smooth hinge loss is introduced to be used as the loss function of SVM.It avoids the issue of nondifferentiability at the zero point encountered by the traditional hinge loss function during gradient descent optimization.Secondly,the L_(1) regularization method is employed to sparsify features and enhance the robustness of the model.Finally,adaptive proximal stochastic gradient descent(PGD)with momentum,and distributed adaptive PGDwithmomentum(DPGD)are proposed and applied to the L_(1)-Smooth SVM.Distributed computing is crucial in large-scale data analysis,with its value manifested in extending algorithms to distributed clusters,thus enabling more efficient processing ofmassive amounts of data.The DPGD algorithm leverages Spark,enabling full utilization of the computer’s multi-core resources.Due to its sparsity induced by L_(1) regularization on parameters,it exhibits significantly accelerated convergence speed.From the perspective of loss reduction,DPGD converges faster than PGD.The experimental results show that adaptive PGD withmomentumand its variants have achieved cutting-edge accuracy and efficiency in brain tumor detection.Frompre-trained models,both the PGD andDPGD outperform other models,boasting an accuracy of 95.21%.

Characteristics of gut microbiota in anastomotic leakage patients in cold zones post-colorectal cancer surgery: A high-throughput sequencing and propensity-score matching study

Objective:The study aimed to explore the association between gut microbiota and anastomotic leakage(AL)after surgery in colorectal cancer(CRC)patients from a frigid zone,based on high-throughput sequencing.Methods:A total of 98 CRC patients admitted to the Second Affiliated Hospital of Harbin Medical University from July 2018 to February 2019,who met the inclusion criteria,were included.Among these,10 patients were diagnosed as AL.After propensity-score matching of baseline characteristics,10 patients from the anastomotic leakage group(AG)and 10 patients from the normal group(NG)were finally included in this study.Fecal samples were collected,and total DNA was extracted for high-throughput sequencing and bioinformatic analysis.Results:Alpha diversity analysis showed no significant difference between the two groups,while beta diversity analysis revealed significant differences in principal components.Differential microbiota were classified as Proteobacteria at the phylum level(P=0.021).At the genus level,the abundances of Streptococcus(P=0.045),Citrobacter(P=0.008)and Klebsiella(P=0.002)were significantly different between the two groups.LEfSe analysis indicated that these genera contributed most to the differences between the groups.Conclusion:The characteristics of the gut microbiota in the AG and NG were significantly different,and these differences might be associated with AL in CRC patients from frigid zones.

体育强国背景下的线上线下融合式教学设计与实践

体育强国国家战略的实现需要兼具体育专项技能、自主学习、信息素养等综合素质人才的支持,普通高等体育院校肩负着培养体育人才的重要使命。《计算机应用基础》作为普通高等体育院校开设的计算机公共基础课程,是术科学生掌握信息技术应用能力、发展信息素养的重要课程。文章采用行动研究法和问卷调查法,以北京体育大学开设的《计算机应用基础》课程为例,在“立德树人”的教育根本任务引领下,以发展自主学习能力和信息素养为目标,基于学生发展需要的具有体育特色的实践任务为驱动,以多元化学习资源为基础,从课前自主学习、课中演示释疑、实践应用、课后巩固拓展四个环节进行《计算机应用基础》线上线下融合式教学设计与实践。通过问卷调查和实践教学数据分析,线上线下融合式教学设计能有效提升运动训练和体育教育专业学生信息素养,对学生自主学习能力的培养有积极影响。

Engineering HOF‑Based Mixed‑Matrix Membranes for Efficient CO_(2) Separation

Hydrogen-bonded organic frameworks(HOFs)have emerged as a new class of crystalline porous materials,and their application in membrane technology needs to be explored.Herein,for the first time,we demonstrated the utilization of HOF-based mixed-matrix membrane for CO_(2) separation.HOF-21,a unique metallo-hydrogen-bonded organic framework material,was designed and processed into nanofillers via amine modulator,uniformly dispersing with Pebax polymer.Featured with the mix-bonded framework,HOF-21 possessed moderate pore size of 0.35 nm and displayed excellent stability under humid feed gas.The chemical functions of multiple binding sites and continuous hydrogen-bonded network jointly facilitated the mass transport of CO_(2).The resulting HOF-21 mixed-matrix membrane exhibited a permeability above 750 Barrer,a selectivity of~40 for CO_(2)/CH_(4) and~60 for CO_(2)/N_(2),surpassing the 2008 Robeson upper bound.This work enlarges the family of mixed-matrix membranes and lays the foundation for HOF membrane development.

Photothermal‐boosted polaron transport in Fe_(2)O_(3)photoanodes for efficient photoelectrochemical water splitting

Introduction of the photothermal effect into transition-metal oxide photoanodes has been proven to be an effective method to improve the photoelectrochemical(PEC)water-splitting performance.However,the precise role of the photothermal effect on the PEC performance of photoanodes is still not well understood.Herein,spinel-structured ZnFe_(2)O_(4)nanoparticles are deposited on the surface of hematite(Fe_(2)O_(3)),and the ZnFe_(2)O_(4)/Fe_(2)O_(3)photoanode achieves a high photocurrent density of 3.17 mA cm^(-2)at 1.23 V versus a reversible hydrogen electrode(VRHE)due to the photothermal effect of ZnFe_(2)O_(4).Considering that the hopping of electron small polarons induced by oxygen vacancies is thermally activated,we clarify that the main reason for the enhanced PEC performance via the photothermal effect is the promoted mobility of electron small polarons that are bound to positively charged oxygen vacancies.Under the synergistic effect of oxygen vacancies and the photothermal effect,the electron conductivity and PEC performance are significantly improved,which provide fundamental insights into the impact of the photothermal effect on the PEC performance of small polaron-type semiconductor photoanodes.

Significant wave height forecasts integrating ensemble empirical mode decomposition with sequence-to-sequence model

As wave height is an important parameter in marine climate measurement,its accurate prediction is crucial in ocean engineering.It also plays an important role in marine disaster early warning and ship design,etc.However,challenges in the large demand for computing resources and the improvement of accuracy are currently encountered.To resolve the above mentioned problems,sequence-to-sequence deep learning model(Seq-to-Seq)is applied to intelligently explore the internal law between the continuous wave height data output by the model,so as to realize fast and accurate predictions on wave height data.Simultaneously,ensemble empirical mode decomposition(EEMD)is adopted to reduce the non-stationarity of wave height data and solve the problem of modal aliasing caused by empirical mode decomposition(EMD),and then improves the prediction accuracy.A significant wave height forecast method integrating EEMD with the Seq-to-Seq model(EEMD-Seq-to-Seq)is proposed in this paper,and the prediction models under different time spans are established.Compared with the long short-term memory model,the novel method demonstrates increased continuity for long-term prediction and reduces prediction errors.The experiments of wave height prediction on four buoys show that the EEMD-Seq-to-Seq algorithm effectively improves the prediction accuracy in short-term(3-h,6-h,12-h and 24-h forecast horizon)and long-term(48-h and 72-h forecast horizon)predictions.

Electromagnetic interference assessment of a train-network-pipeline coupling system based on a harmonic transmission model

The harmonics and resonance of traction power supply systems(TPSSs)aggravate the electromagnetic interference(EMI)to adjacent metallic pipelines(MPs),which has aroused widespread concern.In this paper,an evaluation method on pipeline interference voltage under harmonic induction is presented.The results show that the Carson integral formula is more accurate in calculating the mutual impedance at higher frequencies.Then,an integrated train-network-pipeline model is established to estimate the influences of harmonic distortion and resonance on an MP.It is revealed that the higher the harmonic cur-rent distortion rate of the traction load,the larger the interference voltage on an MP.Particularly,the interference voltage is amplified up to 7 times when the TPSS resonates,which is worthy of attention.In addition,the parameters that affect the variation and sensitivity of the interference voltage are studied,namely,the pipeline coating material,locomotive position,and soil resistivity,indicating that soil resistivity and 3PE(3-layer polyethylene)anticorrosive coating are more sensitive to harmonic induction.Field test results show that the harmonic distortion can make the interference voltage more serious,and the protective measures are optimized.

COVID-19 Detection Based on 6-Layered Explainable Customized Convolutional Neural Network

This paper presents a 6-layer customized convolutional neural network model(6L-CNN)to rapidly screen out patients with COVID-19 infection in chest CT images.This model can effectively detect whether the target CT image contains images of pneumonia lesions.In this method,6L-CNN was trained as a binary classifier using the dataset containing CT images of the lung with and without pneumonia as a sample.The results show that the model improves the accuracy of screening out COVID-19 patients.Compared to othermethods,the performance is better.In addition,the method can be extended to other similar clinical conditions.

Source analysis of dissolved heavy metals in the Shaying River Basin,China

Over the years,the Shaying River Basin has experienced frequent instances of river pollution.The presence of numerous critical pollutant discharge enterprises and sewage-treatment plants in the vicinity of the Shaying River has transformed it a major tributary with relatively serious pollution challenge within the upper reaches of Huaihe River Basin.To study the sources of manganese(Mn),chromium(Cr),nickel(Ni),arsenic(As),cadmium(Cd)and lead(Pb)in Shaying River water,123 sets of surface water samples were collected from 41 sampling points across the entire basin during three distinct phases from 2019 to 2020,encompassing normal water period,dry season and wet season.The primary origins of heavy metals in river water were determined by analyzing the heavy metal contents in urban sewage wastewater,industrial sewage wastewater,groundwater,mine water,and the heavy metal contributions from agricultural non-point source pollution.The analytical findings reveal that Mn primarily originates from shallow groundwater used for agricultural irrigation,While Cr mainly is primarily sourced from urban sewage treatment plant effluents,coal washing wastewater,tannery wastewater,and industrial discharge related to metal processing and manufacturing.Ni is mainly contributed by urban sewage treatment plant effluents and industrial wastewater streams associated with machinery manufacturing and metal processing.Cd primarily linked to industrial wastewater,particularly from machinery manufacturing and metal processing facilities,while Pb is predominantly associated with urban sewage treatment plant effluents and wastewater generated in Pb processing and recycling wastewater.These research provides a crucial foundation for addressing the prevention and control of dissolved heavy metals at their sources in the Shaying River.

The fabrication of hydroxyapatite mineralized hydrogels for bone tissue engineering

Bone is a complex but orderly mineralized tissue with hydroxyapatite(HA)as the inorganic phase and collagen as the organic phase.Inspired by natural bone tissues,HA-mineralized hydrogels have been widely designed and used in bone tissue engineering.HA is majorly utilized for the treatment of bone defects because of its excellent osteoconduction and bone inductivity.Hydrogel is a three-dimensional hydrophilic network structure with similar properties to the extracellular matrix(ECM).The combination of HA and hydrogels produces a new hybrid material that could effectively promote osteointegration and accelerate the healing of bone defects.In this review,the structure and growth of bone and the common strategies used to prepare HA were briefly introduced.Importantly,we discussed the fabrication of HA mineralized hydrogels from simple blending to in situ mineralization.We hope this review can provide a reference for the development of bone repair hydrogels.

The effects of overexpressing UDP-Glycosyltransferases genes on the plant response to abiotic stress:a meta-analysis

Uridine diphosphate(UDP)-Glycosyltransferases(UGT)play essential roles in modifying secondary metabolites during the plant life cycle and are also involved in the response to abiotic stresses.However,the plant UGT family is vast and the available data describing their role in abiotic stress responses is varied and intricate,so that their potential roles are often obscured.To address this,a meta-analysis was conducted to assess the effects of overexpression of UGT on various plant physiological indicators under abiotic stress.Out of the 15 plant characteristics examined in UGT overexpressing plants,10 showed an increase of over 30%,while two plant characteristics decreased by more than 30%,while only three indices were significantly affected under non-stressed conditions.Notably,UGT had a significant and positive effect in salt-stressed plants.This study sheds light on the complex role of UGT in abiotic stress and can provide valuable guidance for future research on UGT functions and their genetic manipulation in crop breeding programs for improved abiotic stress tolerances.