Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may...Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may be related to neuroinflammation, cellular immunity, apoptosis, and autophagy, the exact underlying molecular mechanisms are unclear. This review summarizes the current status of different types of remote ischemic conditioning methods in animal and clinical studies and analyzes their commonalities and differences in neuroprotective mechanisms and signaling pathways. Remote ischemic conditioning has emerged as a potential therapeutic approach for improving stroke-induced brain injury owing to its simplicity, non-invasiveness, safety, and patient tolerability. Different forms of remote ischemic conditioning exhibit distinct intervention patterns, timing, and application range. Mechanistically, remote ischemic conditioning can exert neuroprotective effects by activating the Notch1/phosphatidylinositol 3-kinase/Akt signaling pathway, improving cerebral perfusion, suppressing neuroinflammation, inhibiting cell apoptosis, activating autophagy, and promoting neural regeneration. While remote ischemic conditioning has shown potential in improving stroke outcomes, its full clinical translation has not yet been achieved.展开更多
Fine-grained sediments are widely distributed and constitute the most abundant component in sedi-mentary systems,thus the research on their genesis and distribution is of great significance.In recent years,fine-graine...Fine-grained sediments are widely distributed and constitute the most abundant component in sedi-mentary systems,thus the research on their genesis and distribution is of great significance.In recent years,fine-grained sediment gravity-flows(FGSGF)have been recognized as an important transportation and depositional mechanism for accumulating thick successions of fine-grained sediments.Through a comprehensive review and synthesis of global research on FGSGF deposition,the characteristics,depositional mechanisms,and distribution patterns of fine-grained sediment gravity-flow deposits(FGSGFD)are discussed,and future research prospects are clarified.In addition to the traditionally recognized low-density turbidity current and muddy debris flow,wave-enhanced gravity flow,low-density muddy hyperpycnal flow,and hypopycnal plumes can all form widely distributed FGSGFD.At the same time,the evolution of FGSGF during transportation can result in transitional and hybrid gravity-flow deposits.The combination of multiple triggering mechanisms promotes the widespread develop-ment of FGSGFD,without temporal and spatial limitations.Different types and concentrations of clay minerals,organic matters,and organo-clay complexes are the keys to controlling the flow transformation of FGSGF from low-concentration turbidity currents to high-concentration muddy debris flows.Further study is needed on the interaction mechanism of FGSGF caused by different initiations,the evolution of FGSGF with the effect of organic-inorganic synergy,and the controlling factors of the distribution pat-terns of FGSGFD.The study of FGSGFD can shed some new light on the formation of widely developed thin-bedded siltstones within shales.At the same time,these insights may broaden the exploration scope of shale oil and gas,which have important geological significances for unconventional shale oil and gas.展开更多
Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications.However,existing approaches often rely on manually zooming remote sensing images at diff...Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications.However,existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples.This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios.To address this limitation,we introduce the million-scale fine-grained geospatial scene classification dataset(MEET),which contains over 1.03 million zoom-free remote sensing scene samples,manually annotated into 80 fine-grained categories.In MEET,each scene sample follows a scene-in-scene layout,where the central scene serves as the reference,and auxiliary scenes provide crucial spatial context for fine-grained classification.Moreover,to tackle the emerging challenge of scene-in-scene classification,we present the context-aware transformer(CAT),a model specifically designed for this task,which adaptively fuses spatial context to accurately classify the scene samples.CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes.Based on MEET,we establish a comprehensive benchmark for fine-grained geospatial scene classification,evaluating CAT against 11 competitive baselines.The results demonstrate that CAT significantly outperforms these baselines,achieving a 1.88%higher balanced accuracy(BA)with the Swin-Large backbone,and a notable 7.87%improvement with the Swin-Huge backbone.Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping.The source code and dataset will be publicly available at https://jerrywyn.github.io/project/MEET.html.展开更多
Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimo...Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features.Given this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for JMASA.First,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect terms.Then,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature learning.Thereby,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and enhanced.Experiments on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
Based on recent advancements in shale oil exploration within the Ordos Basin,this study presents a comprehensive investigation of the paleoenvironment,lithofacies assemblages and distribution,depositional mechanisms,a...Based on recent advancements in shale oil exploration within the Ordos Basin,this study presents a comprehensive investigation of the paleoenvironment,lithofacies assemblages and distribution,depositional mechanisms,and reservoir characteristics of shale oil of fine-grained sediment deposition in continental freshwater lacustrine basins,with a focus on the Chang 7_(3) sub-member of Triassic Yanchang Formation.The research integrates a variety of exploration data,including field outcrops,drilling,logging,core samples,geochemical analyses,and flume simulation.The study indicates that:(1)The paleoenvironment of the Chang 7_(3) deposition is characterized by a warm and humid climate,frequent monsoon events,and a large water depth of freshwater lacustrine basin.The paleogeomorphology exhibits an asymmetrical pattern,with steep slopes in the southwest and gentle slopes in the northeast,which can be subdivided into microgeomorphological units,including depressions and ridges in lakebed,as well as ancient channels.(2)The Chang 7_(3) sub-member is characterized by a diverse array of fine-grained sediments,including very fine sandstone,siltstone,mudstone and tuff.These sediments are primarily distributed in thin interbedded and laminated arrangements vertically.The overall grain size of the sandstone predominantly falls below 62.5μm,with individual layer thicknesses of 0.05–0.64 m.The deposits contain intact plant fragments and display various sedimentary structure,such as wavy bedding,inverse-to-normal grading sequence,and climbing ripple bedding,which indicating a depositional origin associated with density flows.(3)Flume simulation experiments have successfully replicated the transport processes and sedimentary characteristics associated with density flows.The initial phase is characterized by a density-velocity differential,resulting in a thicker,coarser sediment layer at the flow front,while the upper layers are thinner and finer in grain size.During the mid-phase,sliding water effects cause the fluid front to rise and facilitate rapid forward transport.This process generates multiple“new fronts”,enabling the long-distance transport of fine-grained sandstones,such as siltstone and argillaceous siltstone,into the center of the lake basin.(4)A sedimentary model primarily controlled by hyperpynal flows was established for the southwestern part of the basin,highlighting that the frequent occurrence of flood events and the steep slope topography in this area are primary controlling factors for the development of hyperpynal flows.(5)Sandstone and mudstone in the Chang 7_(3) sub-member exhibit micro-and nano-scale pore-throat systems,shale oil is present in various lithologies,while the content of movable oil varies considerably,with sandstone exhibiting the highest content of movable oil.(6)The fine-grained sediment complexes formed by multiple episodes of sandstones and mudstones associated with density flow in the Chang 7_(3) formation exhibit characteristics of“overall oil-bearing with differential storage capacity”.The combination of mudstone with low total organic carbon content(TOC)and siltstone is identified as the most favorable exploration target at present.展开更多
In this paper,we propose hierarchical attention dual network(DNet)for fine-grained image classification.The DNet can randomly select pairs of inputs from the dataset and compare the differences between them through hi...In this paper,we propose hierarchical attention dual network(DNet)for fine-grained image classification.The DNet can randomly select pairs of inputs from the dataset and compare the differences between them through hierarchical attention feature learning,which are used simultaneously to remove noise and retain salient features.In the loss function,it considers the losses of difference in paired images according to the intra-variance and inter-variance.In addition,we also collect the disaster scene dataset from remote sensing images and apply the proposed method to disaster scene classification,which contains complex scenes and multiple types of disasters.Compared to other methods,experimental results show that the DNet with hierarchical attention is robust to different datasets and performs better.展开更多
Soil responds to cavity expansion is inherently rate-dependent,especially in the case of fine-grained soils.To better understand such rate effects,self-boring pressuremeter tests were conducted on Kunming peaty soil w...Soil responds to cavity expansion is inherently rate-dependent,especially in the case of fine-grained soils.To better understand such rate effects,self-boring pressuremeter tests were conducted on Kunming peaty soil within a strain rate range of 0.1%/min to 5.0%/min.The results showed a clear dependence of cavity pressure and excess pore pressure(EPP)on strain ratesdboth increased with higher rates for a given radial displacement.In light of the experimental results,three cases of cylindrical cavity expansion were investigated using the finite element method and analytical method,partially drained expansion in Modified Cam-Clay(MCC)soil,and undrained and partially drained expansion in elastoviscoplastic(EVP)soil.The EVP behavior was and modeled using the MCC model and the overstress viscoplastic theory.The results indicated that over the strain rate range of 0.0001%/min and 50%/min,the rate response of cavity pressure for the case of partially drained expansion in MCC soil(permeability coefficient ranging from 5×10^(-6) m/s to 2.5×10^(-11) m/s)is not obvious,while the EPP response during undrained expansion in EVP soil shows rate-independent.Only the partially drained solution for cavity expansion in EVP soil captured the rate-sensitive responses of both cavity pressure and EPP,confirmed by the pressuremeter tests on the Kunming peaty soil,Saint-Herblain clay,and Burswood clay.This suggests that the rate effect results from a combination of drainage-related and time-dependent soil behavior.Parametric studies further demonstrated that both viscous behavior and the overconsolidation ratio significantly influence cylindrical cavity expansion response,and the drainage conditions during expansion can be assessed using a nondimensional velocity.展开更多
Climate change is a global phenomenon that has profound impacts on ecological dynamics and biodiversity,shaping the interactions between species and their environment.To gain a deeper understanding of the mechanisms d...Climate change is a global phenomenon that has profound impacts on ecological dynamics and biodiversity,shaping the interactions between species and their environment.To gain a deeper understanding of the mechanisms driving climate change,phenological monitoring is essential.Traditional methods of defining phenological phases often rely on fixed thresholds.However,with the development of technology,deep learning-based classification models are now able to more accurately delineate phenological phases from images,enabling phenological monitoring.Despite the significant advancements these models have made in phenological monitoring,they still face challenges in fully capturing the complexity of biotic-environmental interactions,which can limit the fine-grained accuracy of phenological phase identification.To address this,we propose a novel deep learning model,RESformer,designed to monitor tree phenology at a fine-grained level using PhenoCam images.RESformer features a lightweight structure,making it suitable for deployment in resource-constrained environments.It incorporates a dual-branch routing mechanism that considers both global and local information,thereby improving the accuracy of phenological monitoring.To validate the effectiveness of RESformer,we conducted a case study involving 82,118 images taken over two years from four different locations in Wisconsin,focusing on the phenology of Acer.The images were classified into seven distinct phenological stages,with RESformer achieving an overall monitoring accuracy of 96.02%.Furthermore,we compared RESformer with a phenological monitoring approach based on the Green Chromatic Coordinate(GCC)index and ten popular classification models.The results showed that RESformer excelled in fine-grained monitoring,effectively capturing and identifying changes in phenological stages.This finding not only provides strong support for monitoring the phenology of Acer species but also offers valuable insights for understanding ecological trends and developing more effective ecosystem conservation and management strategies.展开更多
The spray-deposition was used to produce billets of Mg-4Al-1.5Zn-3Ca-1Nd(A alloy)and Mg-13Al-3Zn-3Ca-1Nd(B alloy),and evolution of deformation substructure and Mg_(x)Zn_(y)Ca_(z)metastable phase in fine-grained(3μm)M...The spray-deposition was used to produce billets of Mg-4Al-1.5Zn-3Ca-1Nd(A alloy)and Mg-13Al-3Zn-3Ca-1Nd(B alloy),and evolution of deformation substructure and Mg_(x)Zn_(y)Ca_(z)metastable phase in fine-grained(3μm)Mg alloys was investigated by scanning electron microscopy(SEM),transmission electron microscopy(TEM),X-ray diffraction(XRD),and electron backscattered diffraction(EBSD).It was found that different dislocation configurations were formed in A and B alloys.Redundant free dislocations(RFDs)and dislocation tangles were the ways to form deformation substructure in A alloy,no RFDs except dislocation tangles were found in B alloy.The interaction between nano-scale second phase particles(nano-scale C15 andβ-Mg_(17)(Al,Zn)_(12)phase)and different dislocation configurations had a significant effect on the deformation substructures formation.The mass transfer of Mg_(x)Zn_(y)Ca_(z)metastable phases and the stacking order of stacking faults were conducive to the Mg-Nd-Zn typed long period stacking ordered(LPSO)phases formation.Nano-scale C15 phases,Mg-Nd-Zn typed LPSO phases,c/a ratio,β-Mg_(17)(Al,Zn)_(12)phases were the key factors influencing the formation of textures.Different textures and grain boundary features(GB features)had a significant effect on k-value.The non-basal textures were the main factor affecting k-value in A alloy,while the high-angle grain boundary(HAGB)was the main factor affecting k-value in B alloy.展开更多
Bird monitoring and protection are essential for maintaining biodiversity,and fine-grained bird classification has become a key focus in this field.Audio-visual modalities provide critical cues for this task,but robus...Bird monitoring and protection are essential for maintaining biodiversity,and fine-grained bird classification has become a key focus in this field.Audio-visual modalities provide critical cues for this task,but robust feature extraction and efficient fusion remain major challenges.We introduce a multi-stage fine-grained audiovisual fusion network(MSFG-AVFNet) for fine-grained bird species classification,which addresses these challenges through two key components:(1) the audiovisual feature extraction module,which adopts a multi-stage finetuning strategy to provide high-quality unimodal features,laying a solid foundation for modality fusion;(2) the audiovisual feature fusion module,which combines a max pooling aggregation strategy with a novel audiovisual loss function to achieve effective and robust feature fusion.Experiments were conducted on the self-built AVB81and the publicly available SSW60 datasets,which contain data from 81 and 60 bird species,respectively.Comprehensive experiments demonstrate that our approach achieves notable performance gains,outperforming existing state-of-the-art methods.These results highlight its effectiveness in leveraging audiovisual modalities for fine-grained bird classification and its potential to support ecological monitoring and biodiversity research.展开更多
Fine-grained aircraft target detection in remote sensing holds significant research valueand practical applications,particularly in military defense and precision strikes.Given the complex-ity of remote sensing images...Fine-grained aircraft target detection in remote sensing holds significant research valueand practical applications,particularly in military defense and precision strikes.Given the complex-ity of remote sensing images,where targets are often small and similar within categories,detectingthese fine-grained targets is challenging.To address this,we constructed a fine-grained dataset ofremotely sensed airplanes;for the problems of remote sensing fine-grained targets with obvious head-to-tail distributions and large variations in target sizes,we proposed the DWDet fine-grained tar-get detection and recognition algorithm.First,for the problem of unbalanced category distribution,we adopt an adaptive sampling strategy.In addition,we construct a deformable convolutional blockand improve the decoupling head structure to improve the detection effect of the model ondeformed targets.Then,we design a localization loss function,which is used to improve the model’slocalization ability for targets of different scales.The experimental results show that our algorithmimproves the overall accuracy of the model by 4.1%compared to the baseline model,and improvesthe detection accuracy of small targets by 12.2%.The ablation and comparison experiments alsoprove the effectiveness of our algorithm.展开更多
Fine-grained Image Recognition(FGIR)task is dedicated to distinguishing similar sub-categories that belong to the same super-category,such as bird species and car types.In order to highlight visual differences,existin...Fine-grained Image Recognition(FGIR)task is dedicated to distinguishing similar sub-categories that belong to the same super-category,such as bird species and car types.In order to highlight visual differences,existing FGIR works often follow two steps:discriminative sub-region localization and local feature representation.However,these works pay less attention on global context information.They neglect a fact that the subtle visual difference in challenging scenarios can be highlighted through exploiting the spatial relationship among different subregions from a global view point.Therefore,in this paper,we consider both global and local information for FGIR,and propose a collaborative teacher-student strategy to reinforce and unity the two types of information.Our framework is implemented mainly by convolutional neural network,referred to Teacher-Student Based Attention Convolutional Neural Network(T-S-ACNN).For fine-grained local information,we choose the classic Multi-Attention Network(MA-Net)as our baseline,and propose a type of boundary constraint to further reduce background noises in the local attention maps.In this way,the discriminative sub-regions tend to appear in the area occupied by fine-grained objects,leading to more accurate sub-region localization.For fine-grained global information,we design a graph convolution based Global Attention Network(GA-Net),which can combine extracted local attention maps from MA-Net with non-local techniques to explore spatial relationship among subregions.At last,we develop a collaborative teacher-student strategy to adaptively determine the attended roles and optimization modes,so as to enhance the cooperative reinforcement of MA-Net and GA-Net.Extensive experiments on CUB-200-2011,Stanford Cars and FGVC Aircraft datasets illustrate the promising performance of our framework.展开更多
Coralline soils,specialized materials found extensively in the South China Sea,are playing an increasingly vital role in engineering projects.However,like most terrigenous soils,fine-grained coral soil is prone to shr...Coralline soils,specialized materials found extensively in the South China Sea,are playing an increasingly vital role in engineering projects.However,like most terrigenous soils,fine-grained coral soil is prone to shrinkage and cracking,which can significantly affect its engineering properties and ultimately jeopardize engineering safety.This paper presents a desiccation cracking test of fine-grained coral soil,with a particular focus on the thickness effect.The study involved measuring the water content and recording the evolution of desiccation cracking.Advanced image processing technology is employed to analyze the variations in crack parameters,clod parameters,fractal dimensions,frequency distributions,and desiccation cracking propagation velocities of fine-grained coral soil.Furthermore,the dynamic evolution of desiccation cracking under the influence of layer thickness is analyzed.A comprehensive crack evolution model is proposed,encompassing both top-down and bottom-up crack propagation,as well as internal tensile cracking.This work introduces novel metrics for the propagation velocity of the total crack area,the characteristic propagation velocities of desiccation cracks,and the acceleration of crack propagation.Through data fitting,theoretical formulas for soil water evaporation,propagation velocities of desiccation cracks,and crack propagation acceleration are derived,laying a foundation for future soil cracking theories.展开更多
Cardiac arrest(CA)is a major global public health challenge,and its high morbidity and low survival rate pose severe tests for emergency and critical care.Although modern CPR techniques significantly improve the immed...Cardiac arrest(CA)is a major global public health challenge,and its high morbidity and low survival rate pose severe tests for emergency and critical care.Although modern CPR techniques significantly improve the immediate resuscitation success rate in CA patients,poor outcomes such as neurological impairment still significantly increase the long-term care burden and reduce the quality of survival.In recent years,the application of remote ischemic conditioning(RIC)has attracted much attention in the field of cardiac arrest through its unique myocardial-nerve dual protection mechanism against the heart.This paper summarizes the conceptual connotation,physiological mechanism,operation method,and its application progress in CA and explores the potential of this technology in the field of CA care in order to provide reference for the research and application of RIC in the field of emergency care.展开更多
LDACs(liquid desiccant air-conditioners)with heat pump can perform cooling dehumidification or heating humidification,and have high energy-saving and sterilization performance.Therefore,they are installed in hospitals...LDACs(liquid desiccant air-conditioners)with heat pump can perform cooling dehumidification or heating humidification,and have high energy-saving and sterilization performance.Therefore,they are installed in hospitals,nursing homes,and food factories,where humidity control is required.However,LiCl(lithium chloride),a conventional humidity control liquid,is highly corrosive to metals,requiring the use of highly corrosion-resistant materials for the pipes and the heat exchangers.These lead to the problem that the manufacturing cost of the air conditioner increases.Therefore,we developed an inexpensive and compact LDAC by adopting a novel IL(ionic liquid)that does not corrode the metals commonly used in air conditioners.In this study,we evaluated the metal solubilities and sterilizing properties of the IL.Based on the physical properties of the IL,the humidity control module was improved for the purpose of downsizing and cost reduction of the unit.Moreover,we conducted a performance evaluation of the LDAC in the environmental test room under the condition in which temperature and humidity change rapidly in short period of time to simulate the condition of sudden showers of rain in summer.Test results showed that processed air was supplied at very stable level.展开更多
Thermoelectric air conditioning systems based on the Peltier effect had two modes:heating and cooling.In this work,the proposed design provides continuous improvement in COP from the first minute of operation.In cooli...Thermoelectric air conditioning systems based on the Peltier effect had two modes:heating and cooling.In this work,the proposed design provides continuous improvement in COP from the first minute of operation.In cooling mode,the coefficient of performance(COP)was 1.176 due to the techniques used in this device,and it increased to 1.24 in the last minute of operation.Concerning the steady-state scenario,from the first minute,the Qc was larger than the W for the entire duration of the operation.The output temperature reaches 18.97℃ ,and the temperature on the cold side reaches 4.96℃ in the fifteen minutes of operation.The cooling mood was checked in Iraq/Baghdad in October with a temperature of 31℃ .Furthermore,the heating mode was checked in December with a temperature of 22℃ .Due to the size of the component on the cold side being small compared with the size of the component on the heat side,it reached a steady state in 13 min.This means the COP in heating mode reached 1.01 in 14 min.Furthermore,due to the presence of a thermal insulator made inside the device to separate the cold side and the hot side,the difference in temperature causes a noticeable little ascent.This is why the COP increased because it kept the degree differences low.Performance enhancements were achieved by optimizing the behavior of thermoelectric materials.The device contains 3 Peltier elements,a water-cooled system with one Peltier,a heat sink,and a fan.The design of the dehumidification system addresses the humidity issue commonly associated with thermoelectric air conditioners.In this context,the results indicate that the humidity rates had decreased and the cooling rate had increased with these innovative techniques,and thus,excellent performance can be achieved even if the Seebeck coefficient is not at its highest based on the condition of providing the Peltier elements’reliability and optimal thermal performance for various applications requiring both cooling and heating functions.The insulation plays a critical role in maintaining the efficiency of the system,reducing energy consumption,and ensuring long-term functionality.The proposed system is valuable for devices or environments that demand precise and dual thermal control with minimal energy wastage.展开更多
The energy consumption of a Split air conditioning unit(ACU)inside a building is extremely large,and efforts to decrease this issue are ongoing.The current work aims to experimentally investigate the thermal performan...The energy consumption of a Split air conditioning unit(ACU)inside a building is extremely large,and efforts to decrease this issue are ongoing.The current work aims to experimentally investigate the thermal performance of ACU using an external cooling-water loop for pre-cooling the condenser to improve the efficiency and to reduce energy consumption by reducing refrigerant temperature before entering the condenser,thereby reducing the coefficient of performance.The experiments are performed on ACU with and without using an external cooling-water loop under different climate conditions.By using the experimental data,the systems’performances for both cases are evaluated based on the energy,exergy,and pressure drop analysis.Effects of several parameters,e.g.,ambient temperature,inlet water temperature,and water volume flow rate,on the energy and exergy performances of ACU systems are presented for the purpose of comparison.The outcomes display that the use of an external cooling water loop system has a significant impact on the system performance as compared to conventional ACU.The results display that the addition of an external cooling-water loop leads to a reduction in the compressor power consumption and to an increase in the coefficient of performance(COP)as compared to a normal ACU.The maximum reduction in compressor power consumption is obtained equal 37%at T_(w)=15℃and 11 L/min,whereas the maximum enhancement in COP is obtained equal 21.5%at T_(w)=30℃,11 L/min,and T_(amb)=45℃.The modified model shows an increase in exergy efficiency with the maximum enhancement of about 17%at T_(w)=30℃and 15.8 L/min.The use of an external cooling water loop leads to a reduction in the irreversibility process of the compressor,evaporator and expansion valve and to an increase in the condenser losses.The outcomes show that the pressure drop is reduced by using a cooling water loop as compared to a normal ACU,where the reduction becomes more evident with a reduction in water volume flow rate and inlet temperature.Finally,the present study reveals that the use of an external cooling water loop system leads to an improvement in the performance of ACUs.展开更多
As an indispensable part of modern buildings,centralized central air conditioning systems play an important role in maintaining the comfort and air quality of the indoor environment.However,with the increasing energy ...As an indispensable part of modern buildings,centralized central air conditioning systems play an important role in maintaining the comfort and air quality of the indoor environment.However,with the increasing energy consumption,how to improve the energy efficiency ratio of air conditioning systems and reduce energy consumption has become an important issue in research and practice.The purpose of this paper is to discuss the impact of humidity control strategies on energy saving in centralized central air conditioning systems,with a view to providing a theoretical basis and practical guidance for realizing building energy efficiency.展开更多
In the background of reform of higher education in the new era,how to organically integrate innovation and entrepreneurship education with curriculum ideology and politics has become a key proposition for deepening th...In the background of reform of higher education in the new era,how to organically integrate innovation and entrepreneurship education with curriculum ideology and politics has become a key proposition for deepening the reform of education and teaching.As an important branch in the field of engineering,the refrigeration and air conditioning major not only undertakes the professional mission of cultivating technical talents in the industry,but also shoulders the era responsibility of implementing the fundamental task of cultivating morality and talents.Combining with the characteristics of the refrigeration and air conditioning major,this paper systematically analyzes the internal logic and practical significance of the integration of innovation and entrepreneurship education and curriculum ideology and politics,and explores its implementation paths in aspects such as the excavation of curriculum content,the innovation of teaching methods,the construction of practical platforms and the optimization of evaluation systems.It aims to provide practical reference and theoretical support for promoting the collaborative education of professional education and ideological and political education.展开更多
基金supported partly by the National Natural Science Foundation of China,No.82071332the Chongqing Natural Science Foundation Joint Fund for Innovation and Development,No.CSTB2023NSCQ-LZX0041 (both to ZG)。
文摘Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may be related to neuroinflammation, cellular immunity, apoptosis, and autophagy, the exact underlying molecular mechanisms are unclear. This review summarizes the current status of different types of remote ischemic conditioning methods in animal and clinical studies and analyzes their commonalities and differences in neuroprotective mechanisms and signaling pathways. Remote ischemic conditioning has emerged as a potential therapeutic approach for improving stroke-induced brain injury owing to its simplicity, non-invasiveness, safety, and patient tolerability. Different forms of remote ischemic conditioning exhibit distinct intervention patterns, timing, and application range. Mechanistically, remote ischemic conditioning can exert neuroprotective effects by activating the Notch1/phosphatidylinositol 3-kinase/Akt signaling pathway, improving cerebral perfusion, suppressing neuroinflammation, inhibiting cell apoptosis, activating autophagy, and promoting neural regeneration. While remote ischemic conditioning has shown potential in improving stroke outcomes, its full clinical translation has not yet been achieved.
基金supported by National Natural Science Foundation of China(Grant Nos.42072126,42372139)the Natural Science Foundation of Sichuan Province(Grant Nos.2022NSFSC0990).
文摘Fine-grained sediments are widely distributed and constitute the most abundant component in sedi-mentary systems,thus the research on their genesis and distribution is of great significance.In recent years,fine-grained sediment gravity-flows(FGSGF)have been recognized as an important transportation and depositional mechanism for accumulating thick successions of fine-grained sediments.Through a comprehensive review and synthesis of global research on FGSGF deposition,the characteristics,depositional mechanisms,and distribution patterns of fine-grained sediment gravity-flow deposits(FGSGFD)are discussed,and future research prospects are clarified.In addition to the traditionally recognized low-density turbidity current and muddy debris flow,wave-enhanced gravity flow,low-density muddy hyperpycnal flow,and hypopycnal plumes can all form widely distributed FGSGFD.At the same time,the evolution of FGSGF during transportation can result in transitional and hybrid gravity-flow deposits.The combination of multiple triggering mechanisms promotes the widespread develop-ment of FGSGFD,without temporal and spatial limitations.Different types and concentrations of clay minerals,organic matters,and organo-clay complexes are the keys to controlling the flow transformation of FGSGF from low-concentration turbidity currents to high-concentration muddy debris flows.Further study is needed on the interaction mechanism of FGSGF caused by different initiations,the evolution of FGSGF with the effect of organic-inorganic synergy,and the controlling factors of the distribution pat-terns of FGSGFD.The study of FGSGFD can shed some new light on the formation of widely developed thin-bedded siltstones within shales.At the same time,these insights may broaden the exploration scope of shale oil and gas,which have important geological significances for unconventional shale oil and gas.
基金supported by the National Natural Science Foundation of China(42030102,42371321).
文摘Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications.However,existing approaches often rely on manually zooming remote sensing images at different scales to create typical scene samples.This approach fails to adequately support the fixed-resolution image interpretation requirements in real-world scenarios.To address this limitation,we introduce the million-scale fine-grained geospatial scene classification dataset(MEET),which contains over 1.03 million zoom-free remote sensing scene samples,manually annotated into 80 fine-grained categories.In MEET,each scene sample follows a scene-in-scene layout,where the central scene serves as the reference,and auxiliary scenes provide crucial spatial context for fine-grained classification.Moreover,to tackle the emerging challenge of scene-in-scene classification,we present the context-aware transformer(CAT),a model specifically designed for this task,which adaptively fuses spatial context to accurately classify the scene samples.CAT adaptively fuses spatial context to accurately classify the scene samples by learning attentional features that capture the relationships between the center and auxiliary scenes.Based on MEET,we establish a comprehensive benchmark for fine-grained geospatial scene classification,evaluating CAT against 11 competitive baselines.The results demonstrate that CAT significantly outperforms these baselines,achieving a 1.88%higher balanced accuracy(BA)with the Swin-Large backbone,and a notable 7.87%improvement with the Swin-Huge backbone.Further experiments validate the effectiveness of each module in CAT and show the practical applicability of CAT in the urban functional zone mapping.The source code and dataset will be publicly available at https://jerrywyn.github.io/project/MEET.html.
基金supported by the Science and Technology Project of Henan Province(No.222102210081).
文摘Joint Multimodal Aspect-based Sentiment Analysis(JMASA)is a significant task in the research of multimodal fine-grained sentiment analysis,which combines two subtasks:Multimodal Aspect Term Extraction(MATE)and Multimodal Aspect-oriented Sentiment Classification(MASC).Currently,most existing models for JMASA only perform text and image feature encoding from a basic level,but often neglect the in-depth analysis of unimodal intrinsic features,which may lead to the low accuracy of aspect term extraction and the poor ability of sentiment prediction due to the insufficient learning of intra-modal features.Given this problem,we propose a Text-Image Feature Fine-grained Learning(TIFFL)model for JMASA.First,we construct an enhanced adjacency matrix of word dependencies and adopt graph convolutional network to learn the syntactic structure features for text,which addresses the context interference problem of identifying different aspect terms.Then,the adjective-noun pairs extracted from image are introduced to enable the semantic representation of visual features more intuitive,which addresses the ambiguous semantic extraction problem during image feature learning.Thereby,the model performance of aspect term extraction and sentiment polarity prediction can be further optimized and enhanced.Experiments on two Twitter benchmark datasets demonstrate that TIFFL achieves competitive results for JMASA,MATE and MASC,thus validating the effectiveness of our proposed methods.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金Supported by the CNPC Major Science and Technology Project(2021DJ1806).
文摘Based on recent advancements in shale oil exploration within the Ordos Basin,this study presents a comprehensive investigation of the paleoenvironment,lithofacies assemblages and distribution,depositional mechanisms,and reservoir characteristics of shale oil of fine-grained sediment deposition in continental freshwater lacustrine basins,with a focus on the Chang 7_(3) sub-member of Triassic Yanchang Formation.The research integrates a variety of exploration data,including field outcrops,drilling,logging,core samples,geochemical analyses,and flume simulation.The study indicates that:(1)The paleoenvironment of the Chang 7_(3) deposition is characterized by a warm and humid climate,frequent monsoon events,and a large water depth of freshwater lacustrine basin.The paleogeomorphology exhibits an asymmetrical pattern,with steep slopes in the southwest and gentle slopes in the northeast,which can be subdivided into microgeomorphological units,including depressions and ridges in lakebed,as well as ancient channels.(2)The Chang 7_(3) sub-member is characterized by a diverse array of fine-grained sediments,including very fine sandstone,siltstone,mudstone and tuff.These sediments are primarily distributed in thin interbedded and laminated arrangements vertically.The overall grain size of the sandstone predominantly falls below 62.5μm,with individual layer thicknesses of 0.05–0.64 m.The deposits contain intact plant fragments and display various sedimentary structure,such as wavy bedding,inverse-to-normal grading sequence,and climbing ripple bedding,which indicating a depositional origin associated with density flows.(3)Flume simulation experiments have successfully replicated the transport processes and sedimentary characteristics associated with density flows.The initial phase is characterized by a density-velocity differential,resulting in a thicker,coarser sediment layer at the flow front,while the upper layers are thinner and finer in grain size.During the mid-phase,sliding water effects cause the fluid front to rise and facilitate rapid forward transport.This process generates multiple“new fronts”,enabling the long-distance transport of fine-grained sandstones,such as siltstone and argillaceous siltstone,into the center of the lake basin.(4)A sedimentary model primarily controlled by hyperpynal flows was established for the southwestern part of the basin,highlighting that the frequent occurrence of flood events and the steep slope topography in this area are primary controlling factors for the development of hyperpynal flows.(5)Sandstone and mudstone in the Chang 7_(3) sub-member exhibit micro-and nano-scale pore-throat systems,shale oil is present in various lithologies,while the content of movable oil varies considerably,with sandstone exhibiting the highest content of movable oil.(6)The fine-grained sediment complexes formed by multiple episodes of sandstones and mudstones associated with density flow in the Chang 7_(3) formation exhibit characteristics of“overall oil-bearing with differential storage capacity”.The combination of mudstone with low total organic carbon content(TOC)and siltstone is identified as the most favorable exploration target at present.
基金Supported by the National Natural Science Foundation of China(61601176)。
文摘In this paper,we propose hierarchical attention dual network(DNet)for fine-grained image classification.The DNet can randomly select pairs of inputs from the dataset and compare the differences between them through hierarchical attention feature learning,which are used simultaneously to remove noise and retain salient features.In the loss function,it considers the losses of difference in paired images according to the intra-variance and inter-variance.In addition,we also collect the disaster scene dataset from remote sensing images and apply the proposed method to disaster scene classification,which contains complex scenes and multiple types of disasters.Compared to other methods,experimental results show that the DNet with hierarchical attention is robust to different datasets and performs better.
基金The financial support of the National Natural Science Foundation of China(Grant Nos.41972293,42272337)the Science Fund for Distinguished Young Scholars of Hubei Province(Grant No.2023AFA078)are gratefully acknowledged.
文摘Soil responds to cavity expansion is inherently rate-dependent,especially in the case of fine-grained soils.To better understand such rate effects,self-boring pressuremeter tests were conducted on Kunming peaty soil within a strain rate range of 0.1%/min to 5.0%/min.The results showed a clear dependence of cavity pressure and excess pore pressure(EPP)on strain ratesdboth increased with higher rates for a given radial displacement.In light of the experimental results,three cases of cylindrical cavity expansion were investigated using the finite element method and analytical method,partially drained expansion in Modified Cam-Clay(MCC)soil,and undrained and partially drained expansion in elastoviscoplastic(EVP)soil.The EVP behavior was and modeled using the MCC model and the overstress viscoplastic theory.The results indicated that over the strain rate range of 0.0001%/min and 50%/min,the rate response of cavity pressure for the case of partially drained expansion in MCC soil(permeability coefficient ranging from 5×10^(-6) m/s to 2.5×10^(-11) m/s)is not obvious,while the EPP response during undrained expansion in EVP soil shows rate-independent.Only the partially drained solution for cavity expansion in EVP soil captured the rate-sensitive responses of both cavity pressure and EPP,confirmed by the pressuremeter tests on the Kunming peaty soil,Saint-Herblain clay,and Burswood clay.This suggests that the rate effect results from a combination of drainage-related and time-dependent soil behavior.Parametric studies further demonstrated that both viscous behavior and the overconsolidation ratio significantly influence cylindrical cavity expansion response,and the drainage conditions during expansion can be assessed using a nondimensional velocity.
基金supported by the National Natural Science Foundation of China(32171777)the Natural Science Foundation of Heilongjiang for Distinguished Young Scientists(JQ2023F002)the Fundamental Research Funds for Central Universities(2572023CT16).
文摘Climate change is a global phenomenon that has profound impacts on ecological dynamics and biodiversity,shaping the interactions between species and their environment.To gain a deeper understanding of the mechanisms driving climate change,phenological monitoring is essential.Traditional methods of defining phenological phases often rely on fixed thresholds.However,with the development of technology,deep learning-based classification models are now able to more accurately delineate phenological phases from images,enabling phenological monitoring.Despite the significant advancements these models have made in phenological monitoring,they still face challenges in fully capturing the complexity of biotic-environmental interactions,which can limit the fine-grained accuracy of phenological phase identification.To address this,we propose a novel deep learning model,RESformer,designed to monitor tree phenology at a fine-grained level using PhenoCam images.RESformer features a lightweight structure,making it suitable for deployment in resource-constrained environments.It incorporates a dual-branch routing mechanism that considers both global and local information,thereby improving the accuracy of phenological monitoring.To validate the effectiveness of RESformer,we conducted a case study involving 82,118 images taken over two years from four different locations in Wisconsin,focusing on the phenology of Acer.The images were classified into seven distinct phenological stages,with RESformer achieving an overall monitoring accuracy of 96.02%.Furthermore,we compared RESformer with a phenological monitoring approach based on the Green Chromatic Coordinate(GCC)index and ten popular classification models.The results showed that RESformer excelled in fine-grained monitoring,effectively capturing and identifying changes in phenological stages.This finding not only provides strong support for monitoring the phenology of Acer species but also offers valuable insights for understanding ecological trends and developing more effective ecosystem conservation and management strategies.
基金financial support by the National Natural Science Foundation of China(No.51364032)the Inner Mongolia Natural Science Foundation(No.2022MS05028)。
文摘The spray-deposition was used to produce billets of Mg-4Al-1.5Zn-3Ca-1Nd(A alloy)and Mg-13Al-3Zn-3Ca-1Nd(B alloy),and evolution of deformation substructure and Mg_(x)Zn_(y)Ca_(z)metastable phase in fine-grained(3μm)Mg alloys was investigated by scanning electron microscopy(SEM),transmission electron microscopy(TEM),X-ray diffraction(XRD),and electron backscattered diffraction(EBSD).It was found that different dislocation configurations were formed in A and B alloys.Redundant free dislocations(RFDs)and dislocation tangles were the ways to form deformation substructure in A alloy,no RFDs except dislocation tangles were found in B alloy.The interaction between nano-scale second phase particles(nano-scale C15 andβ-Mg_(17)(Al,Zn)_(12)phase)and different dislocation configurations had a significant effect on the deformation substructures formation.The mass transfer of Mg_(x)Zn_(y)Ca_(z)metastable phases and the stacking order of stacking faults were conducive to the Mg-Nd-Zn typed long period stacking ordered(LPSO)phases formation.Nano-scale C15 phases,Mg-Nd-Zn typed LPSO phases,c/a ratio,β-Mg_(17)(Al,Zn)_(12)phases were the key factors influencing the formation of textures.Different textures and grain boundary features(GB features)had a significant effect on k-value.The non-basal textures were the main factor affecting k-value in A alloy,while the high-angle grain boundary(HAGB)was the main factor affecting k-value in B alloy.
基金supported by the Beijing Natural Science Foundation(No.5252014)the Open Fund of The Key Laboratory of Urban Ecological Environment Simulation and Protection,Ministry of Ecology and Environment of the People's Republic of China (No.UEESP-202502)the National Natural Science Foundation of China (No.62303063&32371874)。
文摘Bird monitoring and protection are essential for maintaining biodiversity,and fine-grained bird classification has become a key focus in this field.Audio-visual modalities provide critical cues for this task,but robust feature extraction and efficient fusion remain major challenges.We introduce a multi-stage fine-grained audiovisual fusion network(MSFG-AVFNet) for fine-grained bird species classification,which addresses these challenges through two key components:(1) the audiovisual feature extraction module,which adopts a multi-stage finetuning strategy to provide high-quality unimodal features,laying a solid foundation for modality fusion;(2) the audiovisual feature fusion module,which combines a max pooling aggregation strategy with a novel audiovisual loss function to achieve effective and robust feature fusion.Experiments were conducted on the self-built AVB81and the publicly available SSW60 datasets,which contain data from 81 and 60 bird species,respectively.Comprehensive experiments demonstrate that our approach achieves notable performance gains,outperforming existing state-of-the-art methods.These results highlight its effectiveness in leveraging audiovisual modalities for fine-grained bird classification and its potential to support ecological monitoring and biodiversity research.
基金supported by National Natural Science Foundation of China(No.62471034)Hebei Natural Science Foundation(No.F2023105001).
文摘Fine-grained aircraft target detection in remote sensing holds significant research valueand practical applications,particularly in military defense and precision strikes.Given the complex-ity of remote sensing images,where targets are often small and similar within categories,detectingthese fine-grained targets is challenging.To address this,we constructed a fine-grained dataset ofremotely sensed airplanes;for the problems of remote sensing fine-grained targets with obvious head-to-tail distributions and large variations in target sizes,we proposed the DWDet fine-grained tar-get detection and recognition algorithm.First,for the problem of unbalanced category distribution,we adopt an adaptive sampling strategy.In addition,we construct a deformable convolutional blockand improve the decoupling head structure to improve the detection effect of the model ondeformed targets.Then,we design a localization loss function,which is used to improve the model’slocalization ability for targets of different scales.The experimental results show that our algorithmimproves the overall accuracy of the model by 4.1%compared to the baseline model,and improvesthe detection accuracy of small targets by 12.2%.The ablation and comparison experiments alsoprove the effectiveness of our algorithm.
基金supported by the National Natural Science Foundation of China,China (Grants No.62171232)the Priority Academic Program Development of Jiangsu Higher Education Institutions,China。
文摘Fine-grained Image Recognition(FGIR)task is dedicated to distinguishing similar sub-categories that belong to the same super-category,such as bird species and car types.In order to highlight visual differences,existing FGIR works often follow two steps:discriminative sub-region localization and local feature representation.However,these works pay less attention on global context information.They neglect a fact that the subtle visual difference in challenging scenarios can be highlighted through exploiting the spatial relationship among different subregions from a global view point.Therefore,in this paper,we consider both global and local information for FGIR,and propose a collaborative teacher-student strategy to reinforce and unity the two types of information.Our framework is implemented mainly by convolutional neural network,referred to Teacher-Student Based Attention Convolutional Neural Network(T-S-ACNN).For fine-grained local information,we choose the classic Multi-Attention Network(MA-Net)as our baseline,and propose a type of boundary constraint to further reduce background noises in the local attention maps.In this way,the discriminative sub-regions tend to appear in the area occupied by fine-grained objects,leading to more accurate sub-region localization.For fine-grained global information,we design a graph convolution based Global Attention Network(GA-Net),which can combine extracted local attention maps from MA-Net with non-local techniques to explore spatial relationship among subregions.At last,we develop a collaborative teacher-student strategy to adaptively determine the attended roles and optimization modes,so as to enhance the cooperative reinforcement of MA-Net and GA-Net.Extensive experiments on CUB-200-2011,Stanford Cars and FGVC Aircraft datasets illustrate the promising performance of our framework.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2022CDJQY-012)the Innovation Group Science Foundation of the Natural Science Foundation of Chongqing,China(Grant No.cstc2020jcyj-cxttX0003).
文摘Coralline soils,specialized materials found extensively in the South China Sea,are playing an increasingly vital role in engineering projects.However,like most terrigenous soils,fine-grained coral soil is prone to shrinkage and cracking,which can significantly affect its engineering properties and ultimately jeopardize engineering safety.This paper presents a desiccation cracking test of fine-grained coral soil,with a particular focus on the thickness effect.The study involved measuring the water content and recording the evolution of desiccation cracking.Advanced image processing technology is employed to analyze the variations in crack parameters,clod parameters,fractal dimensions,frequency distributions,and desiccation cracking propagation velocities of fine-grained coral soil.Furthermore,the dynamic evolution of desiccation cracking under the influence of layer thickness is analyzed.A comprehensive crack evolution model is proposed,encompassing both top-down and bottom-up crack propagation,as well as internal tensile cracking.This work introduces novel metrics for the propagation velocity of the total crack area,the characteristic propagation velocities of desiccation cracks,and the acceleration of crack propagation.Through data fitting,theoretical formulas for soil water evaporation,propagation velocities of desiccation cracks,and crack propagation acceleration are derived,laying a foundation for future soil cracking theories.
文摘Cardiac arrest(CA)is a major global public health challenge,and its high morbidity and low survival rate pose severe tests for emergency and critical care.Although modern CPR techniques significantly improve the immediate resuscitation success rate in CA patients,poor outcomes such as neurological impairment still significantly increase the long-term care burden and reduce the quality of survival.In recent years,the application of remote ischemic conditioning(RIC)has attracted much attention in the field of cardiac arrest through its unique myocardial-nerve dual protection mechanism against the heart.This paper summarizes the conceptual connotation,physiological mechanism,operation method,and its application progress in CA and explores the potential of this technology in the field of CA care in order to provide reference for the research and application of RIC in the field of emergency care.
文摘LDACs(liquid desiccant air-conditioners)with heat pump can perform cooling dehumidification or heating humidification,and have high energy-saving and sterilization performance.Therefore,they are installed in hospitals,nursing homes,and food factories,where humidity control is required.However,LiCl(lithium chloride),a conventional humidity control liquid,is highly corrosive to metals,requiring the use of highly corrosion-resistant materials for the pipes and the heat exchangers.These lead to the problem that the manufacturing cost of the air conditioner increases.Therefore,we developed an inexpensive and compact LDAC by adopting a novel IL(ionic liquid)that does not corrode the metals commonly used in air conditioners.In this study,we evaluated the metal solubilities and sterilizing properties of the IL.Based on the physical properties of the IL,the humidity control module was improved for the purpose of downsizing and cost reduction of the unit.Moreover,we conducted a performance evaluation of the LDAC in the environmental test room under the condition in which temperature and humidity change rapidly in short period of time to simulate the condition of sudden showers of rain in summer.Test results showed that processed air was supplied at very stable level.
文摘Thermoelectric air conditioning systems based on the Peltier effect had two modes:heating and cooling.In this work,the proposed design provides continuous improvement in COP from the first minute of operation.In cooling mode,the coefficient of performance(COP)was 1.176 due to the techniques used in this device,and it increased to 1.24 in the last minute of operation.Concerning the steady-state scenario,from the first minute,the Qc was larger than the W for the entire duration of the operation.The output temperature reaches 18.97℃ ,and the temperature on the cold side reaches 4.96℃ in the fifteen minutes of operation.The cooling mood was checked in Iraq/Baghdad in October with a temperature of 31℃ .Furthermore,the heating mode was checked in December with a temperature of 22℃ .Due to the size of the component on the cold side being small compared with the size of the component on the heat side,it reached a steady state in 13 min.This means the COP in heating mode reached 1.01 in 14 min.Furthermore,due to the presence of a thermal insulator made inside the device to separate the cold side and the hot side,the difference in temperature causes a noticeable little ascent.This is why the COP increased because it kept the degree differences low.Performance enhancements were achieved by optimizing the behavior of thermoelectric materials.The device contains 3 Peltier elements,a water-cooled system with one Peltier,a heat sink,and a fan.The design of the dehumidification system addresses the humidity issue commonly associated with thermoelectric air conditioners.In this context,the results indicate that the humidity rates had decreased and the cooling rate had increased with these innovative techniques,and thus,excellent performance can be achieved even if the Seebeck coefficient is not at its highest based on the condition of providing the Peltier elements’reliability and optimal thermal performance for various applications requiring both cooling and heating functions.The insulation plays a critical role in maintaining the efficiency of the system,reducing energy consumption,and ensuring long-term functionality.The proposed system is valuable for devices or environments that demand precise and dual thermal control with minimal energy wastage.
文摘The energy consumption of a Split air conditioning unit(ACU)inside a building is extremely large,and efforts to decrease this issue are ongoing.The current work aims to experimentally investigate the thermal performance of ACU using an external cooling-water loop for pre-cooling the condenser to improve the efficiency and to reduce energy consumption by reducing refrigerant temperature before entering the condenser,thereby reducing the coefficient of performance.The experiments are performed on ACU with and without using an external cooling-water loop under different climate conditions.By using the experimental data,the systems’performances for both cases are evaluated based on the energy,exergy,and pressure drop analysis.Effects of several parameters,e.g.,ambient temperature,inlet water temperature,and water volume flow rate,on the energy and exergy performances of ACU systems are presented for the purpose of comparison.The outcomes display that the use of an external cooling water loop system has a significant impact on the system performance as compared to conventional ACU.The results display that the addition of an external cooling-water loop leads to a reduction in the compressor power consumption and to an increase in the coefficient of performance(COP)as compared to a normal ACU.The maximum reduction in compressor power consumption is obtained equal 37%at T_(w)=15℃and 11 L/min,whereas the maximum enhancement in COP is obtained equal 21.5%at T_(w)=30℃,11 L/min,and T_(amb)=45℃.The modified model shows an increase in exergy efficiency with the maximum enhancement of about 17%at T_(w)=30℃and 15.8 L/min.The use of an external cooling water loop leads to a reduction in the irreversibility process of the compressor,evaporator and expansion valve and to an increase in the condenser losses.The outcomes show that the pressure drop is reduced by using a cooling water loop as compared to a normal ACU,where the reduction becomes more evident with a reduction in water volume flow rate and inlet temperature.Finally,the present study reveals that the use of an external cooling water loop system leads to an improvement in the performance of ACUs.
文摘As an indispensable part of modern buildings,centralized central air conditioning systems play an important role in maintaining the comfort and air quality of the indoor environment.However,with the increasing energy consumption,how to improve the energy efficiency ratio of air conditioning systems and reduce energy consumption has become an important issue in research and practice.The purpose of this paper is to discuss the impact of humidity control strategies on energy saving in centralized central air conditioning systems,with a view to providing a theoretical basis and practical guidance for realizing building energy efficiency.
基金Undergraduate Teaching Research and Reform Project of the University of Shanghai for Science and Technology(Project No.:JGXM202526)。
文摘In the background of reform of higher education in the new era,how to organically integrate innovation and entrepreneurship education with curriculum ideology and politics has become a key proposition for deepening the reform of education and teaching.As an important branch in the field of engineering,the refrigeration and air conditioning major not only undertakes the professional mission of cultivating technical talents in the industry,but also shoulders the era responsibility of implementing the fundamental task of cultivating morality and talents.Combining with the characteristics of the refrigeration and air conditioning major,this paper systematically analyzes the internal logic and practical significance of the integration of innovation and entrepreneurship education and curriculum ideology and politics,and explores its implementation paths in aspects such as the excavation of curriculum content,the innovation of teaching methods,the construction of practical platforms and the optimization of evaluation systems.It aims to provide practical reference and theoretical support for promoting the collaborative education of professional education and ideological and political education.
