Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantita...Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.展开更多
When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ...When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.展开更多
The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initiall...The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.展开更多
Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to pred...Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.展开更多
Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development...Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.展开更多
Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this iss...Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.展开更多
Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of indivi...Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.展开更多
Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhance...Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.展开更多
Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive s...Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.展开更多
The M1/M2 phenotypic shift of microglia after spinal cord injury plays an important role in the regulation of neuroinflammation during the secondary injury phase of spinal cord injury.Regulation of shifting microglia ...The M1/M2 phenotypic shift of microglia after spinal cord injury plays an important role in the regulation of neuroinflammation during the secondary injury phase of spinal cord injury.Regulation of shifting microglia polarization from M1(neurotoxic and proinflammatory type)to M2(neuroprotective and anti-inflammatory type)after spinal cord injury appears to be crucial.Tryptanthrin possesses an anti-inflammatory biological function.However,its roles and the underlying molecular mechanisms in spinal cord injury remain unknown.In this study,we found that tryptanthrin inhibited microglia-derived inflammation by promoting polarization to the M2 phenotype in vitro.Tryptanthrin promoted M2 polarization through inactivating the cGAS/STING/NF-κB pathway.Additionally,we found that targeting the cGAS/STING/NF-κB pathway with tryptanthrin shifted microglia from the M1 to M2 phenotype after spinal cord injury,inhibited neuronal loss,and promoted tissue repair and functional recovery in a mouse model of spinal cord injury.Finally,using a conditional co-culture system,we found that microglia treated with tryptanthrin suppressed endoplasmic reticulum stress-related neuronal apoptosis.Taken together,these results suggest that by targeting the cGAS/STING/NF-κB axis,tryptanthrin attenuates microglia-derived neuroinflammation and promotes functional recovery after spinal cord injury through shifting microglia polarization to the M2 phenotype.展开更多
Schwann cell transplantation is considered one of the most promising cell-based therapy to repair injured spinal cord due to its unique growth-promoting and myelin-forming properties.A the Food and Drug Administration...Schwann cell transplantation is considered one of the most promising cell-based therapy to repair injured spinal cord due to its unique growth-promoting and myelin-forming properties.A the Food and Drug Administration-approved Phase I clinical trial has been conducted to evaluate the safety of transplanted human autologous Schwann cells to treat patients with spinal cord injury.A major challenge for Schwann cell transplantation is that grafted Schwann cells are confined within the lesion cavity,and they do not migrate into the host environment due to the inhibitory barrier formed by injury-induced glial scar,thus limiting axonal reentry into the host spinal cord.Here we introduce a combinatorial strategy by suppressing the inhibitory extracellular environment with injection of lentivirus-mediated transfection of chondroitinase ABC gene at the rostral and caudal borders of the lesion site and simultaneously leveraging the repair capacity of transplanted Schwann cells in adult rats following a mid-thoracic contusive spinal cord injury.We report that when the glial scar was degraded by chondroitinase ABC at the rostral and caudal lesion borders,Schwann cells migrated for considerable distances in both rostral and caudal directions.Such Schwann cell migration led to enhanced axonal regrowth,including the serotonergic and dopaminergic axons originating from supraspinal regions,and promoted recovery of locomotor and urinary bladder functions.Importantly,the Schwann cell survival and axonal regrowth persisted up to 6 months after the injury,even when treatment was delayed for 3 months to mimic chronic spinal cord injury.These findings collectively show promising evidence for a combinatorial strategy with chondroitinase ABC and Schwann cells in promoting remodeling and recovery of function following spinal cord injury.展开更多
Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in c...Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.展开更多
Industrial waste management constitutes a major challenge for sustainable development. This study aims to transform hardened cement waste stored in cement warehouses and in real estate construction sites into paving s...Industrial waste management constitutes a major challenge for sustainable development. This study aims to transform hardened cement waste stored in cement warehouses and in real estate construction sites into paving stones. This innovative solution will contribute to the protection of the environment and the reduction of inert industrial waste. To do this, paving stones based on hardened cement have been developed and characterized. The raw materials were subjected to physical and mechanical characterization tests. The hardened cement aggregates previously crushed with the 5/15 granular class were used as substitutes to replace the natural 5/15 aggregates in the hardened paving stones at contents ranging from 0 to 100%. The mechanical characterization results on the raw material showed that the hardened cement aggregate is made from lightweight aggregates. On the prepared mortar, in the fresh state, the Abrams cone slump test showed an increase in the quantity of waste water with the increase in the content of hardened cement aggregate. In the hardened state, physical (porosity, absorption and dry density) and mechanical (compression, splitting traction, 3-point bending traction and wear) characterization tests were carried out at periods of 7, 14 and 28 days of maturation in water on the cobblestones. These results show that the substitution of natural aggregates by hardened cement aggregates in increasingly large proportions leads to an improvement in compressive, flexural, splitting and wear resistance. In addition, the incorporation of hardened cement aggregate considerably slows down the mechanical degradation of the paving stones. They can, therefore, be used in road and interior or exterior floor coverings.展开更多
A 60-year-old female with post-concussion syndrome (PCS) presented with persistent cognitive deficits and functional limitations following a slip and fall. She underwent a multimodal therapeutic protocol including hyp...A 60-year-old female with post-concussion syndrome (PCS) presented with persistent cognitive deficits and functional limitations following a slip and fall. She underwent a multimodal therapeutic protocol including hyperbaric therapy (HBT), photobiomodulation (PBM), and molecular hydrogen (MH) therapy over 10 sessions. Pre- and post-treatment assessments demonstrated significant improvements in cognitive function and neurophysiological markers, as evidenced by WAVi EEG and Trail Making Test (TMT) results. This case highlights the potential of a non-invasive, multimodal therapeutic approach to address persistent post-concussion symptoms, an area with limited effective interventions. Findings suggest that integrating these therapies into standard rehabilitation protocols may enhance recovery trajectories, particularly for patients with persistent cognitive symptoms. This case report explores the clinical course, treatment efficacy, and the potential for combining these therapies in addressing complex neurological recovery.展开更多
Solid waste management in Freetown has been further complicated in the wake of rapid population growth and urbanization, resulting in considerable pressure to implement effective and sustainable solutions. This study ...Solid waste management in Freetown has been further complicated in the wake of rapid population growth and urbanization, resulting in considerable pressure to implement effective and sustainable solutions. This study fills the knowledge gap on the recycling infrastructure, solid waste collection processing, sorting and material recovery facilities specific to the Freetown waste management system. The aim of this study is to examine these components in terms of identifying inefficiencies and suggest sustainable practices to eliminate them. The study was guided by a mixed-method approach, which consisted of both quantitative and qualitative methods, and data collection was done through systematic random sampling. The sample of 384 respondents was collected, which includes stakeholders from a range of sectors. The outcome exhibited inefficient waste collection, a lack of formal recycling infrastructure, and suboptimal waste separation at house level, with 65.2% of respondents evidencing not separating their waste and 33% being without access to waste collection services that result in illegal dumping and environmental pollution. The analysis of the solid waste composition shows that a larger share of the waste generated in Freetown is composed of organic material (53% is being organic), which allows for composting programs to be initiated. This research establishes the inevitable requirement for infrastructure upgrading, mounting public awareness, and policy development. By taking into account these sectors, Freetown can become a more environment-friendly waste management system, which would mean a reduction in landfills and much-emphasized resource recovery.展开更多
The presence of endogenous neural stem/progenitor cells in the adult mammalian brain suggests that the central nervous system can be repaired and regenerated after injury.However,whether it is possible to stimulate ne...The presence of endogenous neural stem/progenitor cells in the adult mammalian brain suggests that the central nervous system can be repaired and regenerated after injury.However,whether it is possible to stimulate neurogenesis and reconstruct cortical layers II to VI in non-neurogenic regions,such as the cortex,remains unknown.In this study,we implanted a hyaluronic acid collagen gel loaded with basic fibroblast growth factor into the motor cortex immediately following traumatic injury.Our findings reveal that this gel effectively stimulated the proliferation and migration of endogenous neural stem/progenitor cells,as well as their differentiation into mature and functionally integrated neurons.Importantly,these new neurons reconstructed the architecture of cortical layers II to VI,integrated into the existing neural circuitry,and ultimately led to improved brain function.These findings offer novel insight into potential clinical treatments for traumatic cerebral cortex injuries.展开更多
To investigate the performance of utilizing the shape memory effect of SMA(Shape Memory Alloy)wire to generate recovery stress,this paper performed single heating recovery stress tests and reciprocating heating-coolin...To investigate the performance of utilizing the shape memory effect of SMA(Shape Memory Alloy)wire to generate recovery stress,this paper performed single heating recovery stress tests and reciprocating heating-cooling recovery stress tests on SMA wire under varying initial strain conditions.The effects of various strains and different energized heating methods on the recovery stress of SMA wires were explored in the single heating tests.The SMA wire was strained from 2%to 8%initially,and two distinct heating approaches were employed:one using a large current interval for rapid heating and one using a small current interval for slower heating.The experimental outcomes reveal that during a single heating cycle,the temperature-recovery stress relationship of SMA wire exhibits three distinct stages:the martensite phase stage,the transition stage from martensite to austenite phase,and the austenite phase stage.Notably,the choice of heating method does not influence the maximum recovery stress value,and the correlation between initial strain and maximum recovery stress is predominantly linear.Moreover,conducting the reciprocating temperature rise and fall performance test is important to better simulate the scenario in practical engineering where multiple recovery stress in SMA wires for structural repair.In this test,two temperature cycling methods were studied:interval rise and fall,as well as direct rise and fall.In the case of utilizing the interval temperature rise and fall method,it was observed that the recovery stress associated with cooling was significantly higher than that corresponding to heating at the same temperature.Furthermore,the recovery stress was lower upon subsequent heating than that measured during the previous heating cycle.Based on the experimental results,a prediction model for the temperature-recovery stress relationship has been proposed to simplify numerical calculations.It is hoped that an approximate temperaturerecovery stress curve can be obtained from the parameters of the SMA wire.The calculated values derived from this model show good alignment with the measured values,indicating its reliability.展开更多
The mainstream silver recovery has problems such as resource waste,weak silver selectivity,and complicated operation.Here,self-propelled magnetic enhanced capture hydrogel(magnetic NbFeB/MXene/GO,MNMGH)was prepared by...The mainstream silver recovery has problems such as resource waste,weak silver selectivity,and complicated operation.Here,self-propelled magnetic enhanced capture hydrogel(magnetic NbFeB/MXene/GO,MNMGH)was prepared by self-crosslinking encapsulation method.MNMGH achieved high selectivity(K_(d)=23.31 mL/g)in the acidic range,and exhibited ultrahigh silver recovery capacity(1604.8 mg/g),which greatly improved by 66%with the assistance of in-situ magnetic field.The recovered silver crystals could be directly physically exfoliated,without acid/base additions.The selective sieving effect of adsorption,MNMGH preferentially adsorbed Ag(I),and then selectively reduced to Ag(0),realizing dual-selective recovery.The in-situ magnetic field enhanced selective adsorption by enhancing mass transfer,reactivity of oxygen-containing functional groups.Furthermore,density function theory simulations demonstrated that the in-situ magnetic field could lower the silver reduction reaction energy barrier to enhance the selective reduction.Three-drive synergy system(reduction drive,adsorption drive and magnetic drive)achieved ultrahigh silver recovery performance.This study pioneered an in-situ magnetic field assisted enhancement strategy for dual-selective(adsorption/reduction)recovery of precious metal silver,which provided new idea for low-carbon recovery of noble metal from industrial waste liquids.展开更多
Restoring the balance of gut microbiota has emerged as a critical strategy in treating intestinal disorders,with probiotics playing a pivotal role in maintaining bacterial equilibrium.Surgical preparations,trauma,and ...Restoring the balance of gut microbiota has emerged as a critical strategy in treating intestinal disorders,with probiotics playing a pivotal role in maintaining bacterial equilibrium.Surgical preparations,trauma,and digestive tract reconstruction associated with intestinal surgeries often disrupt the intestinal flora,prompting interest in the potential role of probiotics in postoperative recovery.Lan et al conducted a prospective randomized study on 60 patients with acute appendicitis,revealing that postoperative administration of Bacillus licheniformis capsules facilitated early resolution of inflammation and restoration of gastrointestinal motility,offering a novel therapeutic avenue for accelerated postoperative recovery.This editorial delves into the effects of perioperative probiotic supplementation on physical and intestinal recovery following surgery.Within the framework of enhanced recovery after surgery,the exploration of new probiotic supplementation strategies to mitigate surgical complications and reshape gut microbiota is particularly intriguing.展开更多
BACKGROUND Appendicitis is a common acute abdominal pain disorder.Laparoscopic appendectomy,a commonly used modality,is associated with less trauma and faster recovery than traditional open appendectomy.However,postop...BACKGROUND Appendicitis is a common acute abdominal pain disorder.Laparoscopic appendectomy,a commonly used modality,is associated with less trauma and faster recovery than traditional open appendectomy.However,postoperative recovery remains an important issue that affects rehabilitation quality and surgical results.AIM To explore the effects of rapid rehabilitation and surgical nursing care on gastrointestinal function recovery and sleep quality among patients undergoing laparoscopic appendectomy.METHODS A total of 120 patients who underwent laparoscopic appendectomy at our hospital between January 2019 and March 2024 and for whom complete clinical data were available were selected.Patients were randomly assigned to two groups(n=60 each)using the random number table method.The control group received routine nursing care,while the experimental group received rapid rehabilitation surgical nursing care;all patients continued to receive nursing care until discharge.The recovery of gastrointestinal function,length of hospital stay,complications,Pittsburgh sleep quality index,and nursing satisfaction were compared between groups.RESULTS Following the implementation of effective nursing measures,the times to bowel sound recovery,first exhaust,first defecation,and first feeding were notably shorter in the study vs control group(P<0.05).Additionally,the duration of the first postoperative activity and the length of hospital stay were significantly shorter in the study vs control group(P<0.05).Furthermore,the study group exhibited better sleep quality than the control group(P<0.05).The postoperative complication rate was significantly lower and the nursing satisfaction rate significantly higher in the study vs control group(P<0.05).CONCLUSION Rapid rehabilitation surgical nursing interventions provided to patients after laparoscopic appendectomy can accelerate their postoperative recovery,reduce the occurrence of complications,and improve their sleep quality and nursing satisfaction.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52279107 and 52379106)the Qingdao Guoxin Jiaozhou Bay Second Submarine Tunnel Co.,Ltd.,the Academician and Expert Workstation of Yunnan Province(No.202205AF150015)the Science and Technology Innovation Project of YCIC Group Co.,Ltd.(No.YCIC-YF-2022-15)。
文摘Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.
文摘When employing penetration ammunition to strike multi-story buildings,the detection methods using acceleration sensors suffer from signal aliasing,while magnetic detection methods are susceptible to interference from ferromagnetic materials,thereby posing challenges in accurately determining the number of layers.To address this issue,this research proposes a layer counting method for penetration fuze that incorporates multi-source information fusion,utilizing both the temporal convolutional network(TCN)and the long short-term memory(LSTM)recurrent network.By leveraging the strengths of these two network structures,the method extracts temporal and high-dimensional features from the multi-source physical field during the penetration process,establishing a relationship between the multi-source physical field and the distance between the fuze and the target plate.A simulation model is developed to simulate the overload and magnetic field of a projectile penetrating multiple layers of target plates,capturing the multi-source physical field signals and their patterns during the penetration process.The analysis reveals that the proposed multi-source fusion layer counting method reduces errors by 60% and 50% compared to single overload layer counting and single magnetic anomaly signal layer counting,respectively.The model's predictive performance is evaluated under various operating conditions,including different ratios of added noise to random sample positions,penetration speeds,and spacing between target plates.The maximum errors in fuze penetration time predicted by the three modes are 0.08 ms,0.12 ms,and 0.16 ms,respectively,confirming the robustness of the proposed model.Moreover,the model's predictions indicate that the fitting degree for large interlayer spacings is superior to that for small interlayer spacings due to the influence of stress waves.
基金supported by the National Key Research and Development Program of China(grant number 2019YFE0123600)。
文摘The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.
基金supported by the National Natural Science Foundation of China(41977215)。
文摘Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.
基金National Key Research and Development Program of China(No.2023YFB3907103).
文摘Effectively managing extensive,multi-source,and multi-level real-scene 3D models for responsive retrieval scheduling and rapid visualization in the Web environment is a significant challenge in the current development of real-scene 3D applications in China.In this paper,we address this challenge by reorganizing spatial and temporal information into a 3D geospatial grid.It introduces the Global 3D Geocoding System(G_(3)DGS),leveraging neighborhood similarity and uniqueness for efficient storage,retrieval,updating,and scheduling of these models.A combination of G_(3)DGS and non-relational databases is implemented,enhancing data storage scalability and flexibility.Additionally,a model detail management scheduling strategy(TLOD)based on G_(3)DGS and an importance factor T is designed.Compared with mainstream commercial and open-source platforms,this method significantly enhances the loadable capacity of massive multi-source real-scene 3D models in the Web environment by 33%,improves browsing efficiency by 48%,and accelerates invocation speed by 40%.
基金supported by the National Natural Science Foundation of China(61903305,62073267)the Fundamental Research Funds for the Central Universities(HXGJXM202214).
文摘Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.
基金supported by the National Key Research and Devel-opment Program of China (Grant No.2022YFC3005503)the National Natural Science Foundation of China (Grant Nos.52322907,52179141,U23B20149,U2340232)+1 种基金the Fundamental Research Funds for the Central Universities (Grant Nos.2042024kf1031,2042024kf0031)the Key Program of Science and Technology of Yunnan Province (Grant Nos.202202AF080004,202203AA080009).
文摘Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.
文摘Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.
文摘Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.
基金supported by the National Natural Science Foundation of China,Nos.82071387(to HT),81971172(to YW)the Natural Science Foundation of Zhejiang Province,China,No.LY22H090012(to HT)the Basic Research Project of Wenzhou City,China,No.Y20220923(to MZ)。
文摘The M1/M2 phenotypic shift of microglia after spinal cord injury plays an important role in the regulation of neuroinflammation during the secondary injury phase of spinal cord injury.Regulation of shifting microglia polarization from M1(neurotoxic and proinflammatory type)to M2(neuroprotective and anti-inflammatory type)after spinal cord injury appears to be crucial.Tryptanthrin possesses an anti-inflammatory biological function.However,its roles and the underlying molecular mechanisms in spinal cord injury remain unknown.In this study,we found that tryptanthrin inhibited microglia-derived inflammation by promoting polarization to the M2 phenotype in vitro.Tryptanthrin promoted M2 polarization through inactivating the cGAS/STING/NF-κB pathway.Additionally,we found that targeting the cGAS/STING/NF-κB pathway with tryptanthrin shifted microglia from the M1 to M2 phenotype after spinal cord injury,inhibited neuronal loss,and promoted tissue repair and functional recovery in a mouse model of spinal cord injury.Finally,using a conditional co-culture system,we found that microglia treated with tryptanthrin suppressed endoplasmic reticulum stress-related neuronal apoptosis.Taken together,these results suggest that by targeting the cGAS/STING/NF-κB axis,tryptanthrin attenuates microglia-derived neuroinflammation and promotes functional recovery after spinal cord injury through shifting microglia polarization to the M2 phenotype.
基金supported in part by NIH R01 NS100531,R01 NS103481NIH R21NS130241(to LD)+3 种基金Merit Review Award I01 BX002356,I01 BX003705 from the U.S.Department of Veterans AffairsIndiana Spinal Cord and Brain Injury Research Foundation(No.19919)Mari Hulman George Endowment Funds(to XMX)Indiana Spinal Cord&Brain Injury Research Fund from ISDH(to NKL and LD)。
文摘Schwann cell transplantation is considered one of the most promising cell-based therapy to repair injured spinal cord due to its unique growth-promoting and myelin-forming properties.A the Food and Drug Administration-approved Phase I clinical trial has been conducted to evaluate the safety of transplanted human autologous Schwann cells to treat patients with spinal cord injury.A major challenge for Schwann cell transplantation is that grafted Schwann cells are confined within the lesion cavity,and they do not migrate into the host environment due to the inhibitory barrier formed by injury-induced glial scar,thus limiting axonal reentry into the host spinal cord.Here we introduce a combinatorial strategy by suppressing the inhibitory extracellular environment with injection of lentivirus-mediated transfection of chondroitinase ABC gene at the rostral and caudal borders of the lesion site and simultaneously leveraging the repair capacity of transplanted Schwann cells in adult rats following a mid-thoracic contusive spinal cord injury.We report that when the glial scar was degraded by chondroitinase ABC at the rostral and caudal lesion borders,Schwann cells migrated for considerable distances in both rostral and caudal directions.Such Schwann cell migration led to enhanced axonal regrowth,including the serotonergic and dopaminergic axons originating from supraspinal regions,and promoted recovery of locomotor and urinary bladder functions.Importantly,the Schwann cell survival and axonal regrowth persisted up to 6 months after the injury,even when treatment was delayed for 3 months to mimic chronic spinal cord injury.These findings collectively show promising evidence for a combinatorial strategy with chondroitinase ABC and Schwann cells in promoting remodeling and recovery of function following spinal cord injury.
基金supported by the National Key R&D Program of China [grant number 2023YFF0805202]the National Natural Science Foun-dation of China [grant number 42175045]the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDB42000000]。
文摘Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.
文摘Industrial waste management constitutes a major challenge for sustainable development. This study aims to transform hardened cement waste stored in cement warehouses and in real estate construction sites into paving stones. This innovative solution will contribute to the protection of the environment and the reduction of inert industrial waste. To do this, paving stones based on hardened cement have been developed and characterized. The raw materials were subjected to physical and mechanical characterization tests. The hardened cement aggregates previously crushed with the 5/15 granular class were used as substitutes to replace the natural 5/15 aggregates in the hardened paving stones at contents ranging from 0 to 100%. The mechanical characterization results on the raw material showed that the hardened cement aggregate is made from lightweight aggregates. On the prepared mortar, in the fresh state, the Abrams cone slump test showed an increase in the quantity of waste water with the increase in the content of hardened cement aggregate. In the hardened state, physical (porosity, absorption and dry density) and mechanical (compression, splitting traction, 3-point bending traction and wear) characterization tests were carried out at periods of 7, 14 and 28 days of maturation in water on the cobblestones. These results show that the substitution of natural aggregates by hardened cement aggregates in increasingly large proportions leads to an improvement in compressive, flexural, splitting and wear resistance. In addition, the incorporation of hardened cement aggregate considerably slows down the mechanical degradation of the paving stones. They can, therefore, be used in road and interior or exterior floor coverings.
文摘A 60-year-old female with post-concussion syndrome (PCS) presented with persistent cognitive deficits and functional limitations following a slip and fall. She underwent a multimodal therapeutic protocol including hyperbaric therapy (HBT), photobiomodulation (PBM), and molecular hydrogen (MH) therapy over 10 sessions. Pre- and post-treatment assessments demonstrated significant improvements in cognitive function and neurophysiological markers, as evidenced by WAVi EEG and Trail Making Test (TMT) results. This case highlights the potential of a non-invasive, multimodal therapeutic approach to address persistent post-concussion symptoms, an area with limited effective interventions. Findings suggest that integrating these therapies into standard rehabilitation protocols may enhance recovery trajectories, particularly for patients with persistent cognitive symptoms. This case report explores the clinical course, treatment efficacy, and the potential for combining these therapies in addressing complex neurological recovery.
文摘Solid waste management in Freetown has been further complicated in the wake of rapid population growth and urbanization, resulting in considerable pressure to implement effective and sustainable solutions. This study fills the knowledge gap on the recycling infrastructure, solid waste collection processing, sorting and material recovery facilities specific to the Freetown waste management system. The aim of this study is to examine these components in terms of identifying inefficiencies and suggest sustainable practices to eliminate them. The study was guided by a mixed-method approach, which consisted of both quantitative and qualitative methods, and data collection was done through systematic random sampling. The sample of 384 respondents was collected, which includes stakeholders from a range of sectors. The outcome exhibited inefficient waste collection, a lack of formal recycling infrastructure, and suboptimal waste separation at house level, with 65.2% of respondents evidencing not separating their waste and 33% being without access to waste collection services that result in illegal dumping and environmental pollution. The analysis of the solid waste composition shows that a larger share of the waste generated in Freetown is composed of organic material (53% is being organic), which allows for composting programs to be initiated. This research establishes the inevitable requirement for infrastructure upgrading, mounting public awareness, and policy development. By taking into account these sectors, Freetown can become a more environment-friendly waste management system, which would mean a reduction in landfills and much-emphasized resource recovery.
基金supported by the National Natural Science Foundation of China,Nos.82272171(to ZY),82271403(to XL),81941011(to XL),31971279(to ZY),31730030(to XL)the Natural Science Foundation of Beijing,No.7222004(to HD).
文摘The presence of endogenous neural stem/progenitor cells in the adult mammalian brain suggests that the central nervous system can be repaired and regenerated after injury.However,whether it is possible to stimulate neurogenesis and reconstruct cortical layers II to VI in non-neurogenic regions,such as the cortex,remains unknown.In this study,we implanted a hyaluronic acid collagen gel loaded with basic fibroblast growth factor into the motor cortex immediately following traumatic injury.Our findings reveal that this gel effectively stimulated the proliferation and migration of endogenous neural stem/progenitor cells,as well as their differentiation into mature and functionally integrated neurons.Importantly,these new neurons reconstructed the architecture of cortical layers II to VI,integrated into the existing neural circuitry,and ultimately led to improved brain function.These findings offer novel insight into potential clinical treatments for traumatic cerebral cortex injuries.
基金financially supported by National Natural Science Foundation of China(Project No.51878156).
文摘To investigate the performance of utilizing the shape memory effect of SMA(Shape Memory Alloy)wire to generate recovery stress,this paper performed single heating recovery stress tests and reciprocating heating-cooling recovery stress tests on SMA wire under varying initial strain conditions.The effects of various strains and different energized heating methods on the recovery stress of SMA wires were explored in the single heating tests.The SMA wire was strained from 2%to 8%initially,and two distinct heating approaches were employed:one using a large current interval for rapid heating and one using a small current interval for slower heating.The experimental outcomes reveal that during a single heating cycle,the temperature-recovery stress relationship of SMA wire exhibits three distinct stages:the martensite phase stage,the transition stage from martensite to austenite phase,and the austenite phase stage.Notably,the choice of heating method does not influence the maximum recovery stress value,and the correlation between initial strain and maximum recovery stress is predominantly linear.Moreover,conducting the reciprocating temperature rise and fall performance test is important to better simulate the scenario in practical engineering where multiple recovery stress in SMA wires for structural repair.In this test,two temperature cycling methods were studied:interval rise and fall,as well as direct rise and fall.In the case of utilizing the interval temperature rise and fall method,it was observed that the recovery stress associated with cooling was significantly higher than that corresponding to heating at the same temperature.Furthermore,the recovery stress was lower upon subsequent heating than that measured during the previous heating cycle.Based on the experimental results,a prediction model for the temperature-recovery stress relationship has been proposed to simplify numerical calculations.It is hoped that an approximate temperaturerecovery stress curve can be obtained from the parameters of the SMA wire.The calculated values derived from this model show good alignment with the measured values,indicating its reliability.
基金supported by The National Natural Science Foundation of China(52170087,22276137).
文摘The mainstream silver recovery has problems such as resource waste,weak silver selectivity,and complicated operation.Here,self-propelled magnetic enhanced capture hydrogel(magnetic NbFeB/MXene/GO,MNMGH)was prepared by self-crosslinking encapsulation method.MNMGH achieved high selectivity(K_(d)=23.31 mL/g)in the acidic range,and exhibited ultrahigh silver recovery capacity(1604.8 mg/g),which greatly improved by 66%with the assistance of in-situ magnetic field.The recovered silver crystals could be directly physically exfoliated,without acid/base additions.The selective sieving effect of adsorption,MNMGH preferentially adsorbed Ag(I),and then selectively reduced to Ag(0),realizing dual-selective recovery.The in-situ magnetic field enhanced selective adsorption by enhancing mass transfer,reactivity of oxygen-containing functional groups.Furthermore,density function theory simulations demonstrated that the in-situ magnetic field could lower the silver reduction reaction energy barrier to enhance the selective reduction.Three-drive synergy system(reduction drive,adsorption drive and magnetic drive)achieved ultrahigh silver recovery performance.This study pioneered an in-situ magnetic field assisted enhancement strategy for dual-selective(adsorption/reduction)recovery of precious metal silver,which provided new idea for low-carbon recovery of noble metal from industrial waste liquids.
文摘Restoring the balance of gut microbiota has emerged as a critical strategy in treating intestinal disorders,with probiotics playing a pivotal role in maintaining bacterial equilibrium.Surgical preparations,trauma,and digestive tract reconstruction associated with intestinal surgeries often disrupt the intestinal flora,prompting interest in the potential role of probiotics in postoperative recovery.Lan et al conducted a prospective randomized study on 60 patients with acute appendicitis,revealing that postoperative administration of Bacillus licheniformis capsules facilitated early resolution of inflammation and restoration of gastrointestinal motility,offering a novel therapeutic avenue for accelerated postoperative recovery.This editorial delves into the effects of perioperative probiotic supplementation on physical and intestinal recovery following surgery.Within the framework of enhanced recovery after surgery,the exploration of new probiotic supplementation strategies to mitigate surgical complications and reshape gut microbiota is particularly intriguing.
文摘BACKGROUND Appendicitis is a common acute abdominal pain disorder.Laparoscopic appendectomy,a commonly used modality,is associated with less trauma and faster recovery than traditional open appendectomy.However,postoperative recovery remains an important issue that affects rehabilitation quality and surgical results.AIM To explore the effects of rapid rehabilitation and surgical nursing care on gastrointestinal function recovery and sleep quality among patients undergoing laparoscopic appendectomy.METHODS A total of 120 patients who underwent laparoscopic appendectomy at our hospital between January 2019 and March 2024 and for whom complete clinical data were available were selected.Patients were randomly assigned to two groups(n=60 each)using the random number table method.The control group received routine nursing care,while the experimental group received rapid rehabilitation surgical nursing care;all patients continued to receive nursing care until discharge.The recovery of gastrointestinal function,length of hospital stay,complications,Pittsburgh sleep quality index,and nursing satisfaction were compared between groups.RESULTS Following the implementation of effective nursing measures,the times to bowel sound recovery,first exhaust,first defecation,and first feeding were notably shorter in the study vs control group(P<0.05).Additionally,the duration of the first postoperative activity and the length of hospital stay were significantly shorter in the study vs control group(P<0.05).Furthermore,the study group exhibited better sleep quality than the control group(P<0.05).The postoperative complication rate was significantly lower and the nursing satisfaction rate significantly higher in the study vs control group(P<0.05).CONCLUSION Rapid rehabilitation surgical nursing interventions provided to patients after laparoscopic appendectomy can accelerate their postoperative recovery,reduce the occurrence of complications,and improve their sleep quality and nursing satisfaction.
