Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major...Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major topics of concern include“SI”(security intelligence),“D-DA”(data-driven analytics),“PE”(proven expertise),and“R-TD”(real-time defense)capabilities.“DRBTs”(dynamic response behavior types)include“incident response”,“endpoint management”,“threat intelligence”,“network security”,and“fraud protection”.The consumer demand for electricity as essential public access and service is indexed to population growth estimates.Consumer-driven economies continue to add electrical consumption to their grids even though improvements in lower-power consumption and higher design efficiencies are present in new electric-powered products.Dependence on the production of electrical energy has no peer replacement technology and creates a societal vulnerability to targeted public electrical grid interruptions.When access to,or production of,electrical power is interrupted,the result is a“Mass Effect”every consumer feels with equal distribution.Electric grid security falls directly into the levels of authorized,and unauthorized,access via the“IoT”(Internet of Things)concepts,and the“IoM2M”(Internet of Machine-to-Machine)integration.Electrical grid operations that include production and network management augment each other in order to support the demand for electricity every day either in peak or off-peak,thus cybersecurity plays a big role in the protection of such assets at our disposal.With help from AI(artificial intelligence)integrated into the IoT a resilient system can be built to protect the electric grid system nationwide and will be able to detect and preempt Smart Malware attacks.展开更多
Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries.Motivated by the major development strategies and needs of industrial intellectu...Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries.Motivated by the major development strategies and needs of industrial intellectualization in China,this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization,as well as their application to smart industrial engineering.First,this study describes a general methodology for the fusion of data analytics and optimization.Then,it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing.Finally,it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization.The framework uses data analytics to perceive and analyze industrial production and logistics processes.It also demonstrates the intelligent capability of planning,scheduling,operation optimization,and optimal control.Data analytics and system optimization technologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing,resources and materials,energy,and logistics systems,such as high energy consumption,high costs,low energy efficiency,low resource utilization,and serious environmental pollution.The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency。Therefore,industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.展开更多
Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a mul...Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multifield visualization problem, where the geo-space provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivariate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementation that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixed-window brushing and correlation-enhanced display. We conceived our system with a team of climate researchers, who already made a few important discoveries using it. This demonstrates our system＇s great potential to enable scientific discoveries, possibly also in other domains where data have a geospatial reference.展开更多
Many cities,countries and transport operators around the world are striving to design intelligent transport systems.These systems capture the value of multisource and multiform data related to the functionality and us...Many cities,countries and transport operators around the world are striving to design intelligent transport systems.These systems capture the value of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility,interests,economic activity and lifestyles.They aim to provide services that can enable transportation customers and managers to be better informed and make safer and more efficient use of infrastructure.In developing principles,guidelines,methods and tools to enable synergistic work between humans and computer-generated information,the science of visual analytics continues to expand our understanding of data through effective and interactive visual interfaces.In this paper,we describe an application of visual analytics related to the study of movement and transportation systems.This application documents the use of rapid,2D and 3D web visualisation and data analytics libraries and explores their potential added value to the analysis of big public transport performance data.A novel approach to displaying such data through a generalisable framework visualisation system is demonstrated.This framework recalls over a year’sworth of public transport performance data at a highly granular level in a fast,interactive browser-based environment.Greater Sydney,Australia forms a case study to highlight potential uses of the visualisation of such large,passively-collected data sets as an applied research scenario.In this paper,we argue that such highly visual systems can add data-driven rigour to service planning and longer-term transport decision-making.Furthermore,they enable the sharing of quality of service statistics with various stakeholders and citizens and can showcase improvements in services before and after policy decisions.The paper concludes by making recommendations on the value of this approach in embedding these or similar web-based systems in transport planning practice,performance management,optimisation and understanding of customer experience.展开更多
Composite polymer electrolytes(CPEs)offer a promising solution for all-solid-state lithium-metal batteries(ASSLMBs).However,conventional nanofillers with Lewis-acid-base surfaces make limited contribution to improving...Composite polymer electrolytes(CPEs)offer a promising solution for all-solid-state lithium-metal batteries(ASSLMBs).However,conventional nanofillers with Lewis-acid-base surfaces make limited contribution to improving the overall performance of CPEs due to their difficulty in achieving robust electrochemical and mechanical interfaces simultaneously.Here,by regulating the surface charge characteristics of halloysite nanotube(HNT),we propose a concept of lithium-ion dynamic interface(Li^(+)-DI)engineering in nano-charged CPE(NCCPE).Results show that the surface charge characteristics of HNTs fundamentally change the Li^(+)-DI,and thereof the mechanical and ion-conduction behaviors of the NCCPEs.Particularly,the HNTs with positively charged surface(HNTs+)lead to a higher Li^(+)transference number(0.86)than that of HNTs-(0.73),but a lower toughness(102.13 MJ m^(-3)for HNTs+and 159.69 MJ m^(-3)for HNTs-).Meanwhile,a strong interface compatibilization effect by Li^(+)is observed for especially the HNTs+-involved Li^(+)-DI,which improves the toughness by 2000%compared with the control.Moreover,HNTs+are more effective to weaken the Li^(+)-solvation strength and facilitate the formation of Li F-rich solid-electrolyte interphase of Li metal compared to HNTs-.The resultant Li|NCCPE|LiFePO4cell delivers a capacity of 144.9 m Ah g^(-1)after 400 cycles at 0.5 C and a capacity retention of 78.6%.This study provides deep insights into understanding the roles of surface charges of nanofillers in regulating the mechanical and electrochemical interfaces in ASSLMBs.展开更多
MXene-based smart contact lenses demonstrate a cutting-edge advancement in wearable ophthalmic technology,combining real-time biosensing,therapeutic capabilities,and user comfort in a single platform.These devices tak...MXene-based smart contact lenses demonstrate a cutting-edge advancement in wearable ophthalmic technology,combining real-time biosensing,therapeutic capabilities,and user comfort in a single platform.These devices take the advantage of the exceptional electrical conductivity,mechanical flexibility,and biocompatibility of two-dimensional MXenes to enable noninvasive,tear-based monitoring of key physiological markers such as intraocular pressure and glucose levels.Recent developments focus on the integration of transparent MXene films into the conventional lens materials,allowing multifunctional performance including photothermal therapy,antimicrobial and anti-inflammation protection,and dehydration resistance.These innovations offer promising strategies for ocular disease management and eye protection.In addition to their multifunctionality,improvements in MXene synthesis and device engineering have enhanced the stability,transparency,and wearability of these lenses.Despite these advances,challenges remain in long-term biostability,scalable production,and integration with wireless communication systems.This review summarizes the current progress,key challenges,and future directions of MXene-based smart contact lenses,highlighting their transformative potential in next-generation digital healthcare and ophthalmic care.展开更多
The mechanisms underlying the pathophysiology of ischemic stroke are complex and multifactorial and include excitotoxicity,oxidative stress,inflammatory responses,and blood–brain barrier disruption.While vascular rec...The mechanisms underlying the pathophysiology of ischemic stroke are complex and multifactorial and include excitotoxicity,oxidative stress,inflammatory responses,and blood–brain barrier disruption.While vascular recanalization treatments such as thrombolysis and mechanical thrombectomy have achieved some success,reperfusion injury remains a significant contributor to the exacerbation of brain injury.This emphasizes the need for developing neuroprotective strategies to mitigate this type of injury.The purpose of this review was to examine the application of nanotechnology in the treatment of ischemic stroke,covering research progress in nanoparticlebased drug delivery,targeted therapy,and antioxidant and anti-inflammatory applications.Nanobased drug delivery systems offer several advantages compared to traditional therapies,including enhanced blood–brain barrier penetration,prolonged drug circulation time,improved drug stability,and targeted delivery.For example,inorganic nanoparticles,such as those based on CeO_(2),have been widely studied for their strong antioxidant capabilities.Biomimetic nanoparticles,such as those coated with cell membranes,have garnered significant attention owing to their excellent biocompatibility and targeting abilities.Nanoparticles can be used to deliver a wide range of neuroprotective agents,such as antioxidants(e.g.,edaravone),anti-inflammatory drugs(e.g.,curcumin),and neurotrophic factors.Nanotechnology significantly enhances the efficacy of these drugs while minimizing adverse reactions.Although nanotechnology has demonstrated great potential in animal studies,its clinical application still faces several challenges,including the long-term safety of nanoparticles,the feasibility of large-scale production,quality control,and the ability to predict therapeutic effects in humans.In summary,nanotechnology holds significant promise for the treatment of ischemic stroke.Future research should focus on further exploring the mechanisms of action of nanoparticles,developing multifunctional nanoparticles,and validating their safety and efficacy through rigorous clinical trials.Moreover,interdisciplinary collaboration is essential for advancing the use of nanotechnology in stroke treatment.展开更多
Each year,accidents involving ships result in significant loss of life,environmental pollution and economic losses.The promotion of navigation safety through risk reduction requires methods to assess the spatial distr...Each year,accidents involving ships result in significant loss of life,environmental pollution and economic losses.The promotion of navigation safety through risk reduction requires methods to assess the spatial distribution of the relative likelihood of occurrence.Yet,such methods necessitate the integration of large volumes of heterogenous datasets which are not well suited to traditional data structures.This paper proposes the use of the Discrete Global Grid System(DGGS)as an efficient and advantageous structure to integrate vessel traffic,metocean,bathymetric,infrastructure and other relevant maritime datasets to predict the occurrence of ship groundings.Massive and heterogenous datasets are well suited for machine learning algorithms and this paper develops a spatial maritime risk model based on a DGGS utilising such an approach.A Random Forest algorithm is developed to predict the frequency and spatial distribution of groundings while achieving an R2 of 0.55 and a mean squared error of 0.002.The resulting risk maps are useful for decision-makers in planning the allocation of mitigation measures,targeted to regions with the highest risk.Further work is identified to expand the applications and insights which could be achieved through establishing a DGGS as a global maritime spatial data structure.展开更多
In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry problem.Recent demonstrations and applications in several fi...In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry problem.Recent demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial importance.This study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each other.The immense achievement of deep learning has resulted in a growing use of its much architecture to enhance efficiency.This review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of data.The following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics statistically.In this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further investigation.The information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.展开更多
The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activit...The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activity, sedentary habits, sleep patterns) within the 24-h cycle of daily life. Wearables are applied in research, clinical practice, and as lifestyle devices;most obvious, they promise to be a key element for increasing human physical activity, one of the biggest health challenges nowadays.展开更多
Rechargeable zinc(Zn)-ion batteries(RZIBs) with hydrogel electrolytes(HEs) have gained significant attention in the last decade owing to their high safety, low cost, sufficient material abundance, and superb environme...Rechargeable zinc(Zn)-ion batteries(RZIBs) with hydrogel electrolytes(HEs) have gained significant attention in the last decade owing to their high safety, low cost, sufficient material abundance, and superb environmental friendliness, which is extremely important for wearable energy storage applications. Given that HEs play a critical role in building flexible RZIBs, it is urgent to summarize the recent advances in this field and elucidate the design principles of HEs for practical applications. This review systematically presents the development history, recent advances in the material fundamentals, functional designs, challenges, and prospects of the HEs-based RZIBs. Firstly, the fundamentals, species, and flexible mechanisms of HEs are discussed, along with their compatibility with Zn anodes and various cathodes. Then, the functional designs of hydrogel electrolytes in harsh conditions are comprehensively discussed, including high/low/wide-temperature windows, mechanical deformations(e.g., bending, twisting, and straining), and damages(e.g., cutting, burning, and soaking). Finally, the remaining challenges and future perspectives for advancing HEs-based RZIBs are outlined.展开更多
We report here arsenic speciation in 1643 freshwater fish samples,representing 14 common fish species from 53 waterbodies in Alberta,Canada.Arsenic species were extracted from fish muscle tissue.Arsenic species in the...We report here arsenic speciation in 1643 freshwater fish samples,representing 14 common fish species from 53 waterbodies in Alberta,Canada.Arsenic species were extracted from fish muscle tissue.Arsenic species in the extracts were separated using anion-exchange high-performance liquid chromatography(HPLC)and quantified using inductively coupled plasma mass spectrometry(ICPMS).The total arsenic concentrations in fish ranged from 2.8 to 1200μg/kg(in wet weight of sample)(mean 71±101μg/kg),which are all below the 2000μg/kg(wet weight)maximum allowable total arsenic in fish,recommended by the Ontario Ministry of the Environment.In 99.7%,or 1638 of all 1643 freshwater fish samples analyzed,arsenobetaine(AsB)was detectable,with concentrations higher than the method detection limit of 0.25μg/kg(wet weight).Dimethylarsinic acid(DMA)was detectable(concentration>0.25μg/kg)in 92.1%,or 1514 of the 1643 freshwater fish samples.Inorganic arsenate(iAs^(Ⅴ))was detectable(>0.25μg/kg)in 1119 fish(i.e.,68.1% of 1643 samples).Monomethylarsonic acid(MMA)was detectable(>0.25μg/kg)in 418 fish(25.4%of 1643 samples).The concentrations of arsenic species in the 1643 fish samples varied by as much as three orders of magnitude,ranging from below the method detection limit of 0.25μg/kg to the maximum concentrations of 380μg/kg for AsB,150μg/kg for DMA,70μg/kg for iAs^(Ⅴ),and 51μg/kg for MMA.AsB made up 46.1%±26.2% of total arsenic species.Arsenic speciation patterns varied between lake whitefish,northern pike,and walleye,the three most common types of fish analyzed.The relative proportion of DMA in northern pike was larger than in lake whitefish and walleye,and conversely,the relative proportion of iAs^(Ⅴ) was lower in northern pike.Seven unknown arsenic species were detected,and their chromatographic retention time did not match with those of available arsenic standards.At least one unknown arsenic species was detected in 33.4%,or 549 of 1643 freshwater fish samples.The concentrations of unknown arsenic species were as high as 61μg/kg.Future research is necessary to identify unknown arsenic species and to determine contributing factors to the observed arsenic species patterns and concentrations.展开更多
In cold regions,slope rocks are inevitably impacted by freeze-thaw,dry-wet cycles and their alternating actions,leading to strength weakening and pore degradation.In this study,the mechanical and microstructural prope...In cold regions,slope rocks are inevitably impacted by freeze-thaw,dry-wet cycles and their alternating actions,leading to strength weakening and pore degradation.In this study,the mechanical and microstructural properties of schist subjected to four conditions were investigated:freeze-thaw cycles in air(FTA),freeze-thaw cycles in water(FTW),dry-wet cycles(DW),and dry-wet-freeze-thaw cycles(DWFT).Uniaxial compressive strength(UCS),water absorption,ultrasonication,low-field nuclear magnetic resonance,and scanning electron microscopy analyses were conducted.The integrity attenuation characteristics of the longitudinal wave velocity,UCS,and elastic modulus were analyzed.The results showed that liquid water emerged as a critical factor in reducing the brittleness of schist.The attenuation function model accurately described the peak stress and static elastic modulus of schist in various media(R2>0.97).Different media affected the schist deterioration and half-life,with the FTW-immersed samples having a half-life of 28 cycles.Furthermore,the longitudinal wave velocity decreased as the number of cycles increased,with the FTW showing the most significant reduction and having the shortest half-life of 208 cycles.Moreover,the damage variables of compressive strength and elastic modulus increased with the number of cycles.After 40 cycles,the schist exposed to FTW exhibited the highest damage variables and saturated water content.展开更多
We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of ...We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of propane over propylene and thus highly inverse selective separation of propane/propylene mixture.The inverse propane-selective performance of Zn‑tfbdc‑dabco for the propane/propylene separation was validated by single-component gas adsorption isotherms,isosteric enthalpy of adsorption calculations,ideal adsorbed solution theory calculations,along with the breakthrough experiment.The customized fluorinated networks served as a propane-trap to form more interactions with the exposed hydrogen atoms of propane,as unveiled by the simulation studies at the molecular level.With the advantage of inverse propane-selective adsorption behavior,high adsorption capacity,good cycling stability,and low isosteric enthalpy of adsorption,Zn‑tfbdc‑dabco can be a promising candidate adsorbent for the challenging propane/propylene separation to realize one-step purification of the target propylene substance.展开更多
文摘Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major topics of concern include“SI”(security intelligence),“D-DA”(data-driven analytics),“PE”(proven expertise),and“R-TD”(real-time defense)capabilities.“DRBTs”(dynamic response behavior types)include“incident response”,“endpoint management”,“threat intelligence”,“network security”,and“fraud protection”.The consumer demand for electricity as essential public access and service is indexed to population growth estimates.Consumer-driven economies continue to add electrical consumption to their grids even though improvements in lower-power consumption and higher design efficiencies are present in new electric-powered products.Dependence on the production of electrical energy has no peer replacement technology and creates a societal vulnerability to targeted public electrical grid interruptions.When access to,or production of,electrical power is interrupted,the result is a“Mass Effect”every consumer feels with equal distribution.Electric grid security falls directly into the levels of authorized,and unauthorized,access via the“IoT”(Internet of Things)concepts,and the“IoM2M”(Internet of Machine-to-Machine)integration.Electrical grid operations that include production and network management augment each other in order to support the demand for electricity every day either in peak or off-peak,thus cybersecurity plays a big role in the protection of such assets at our disposal.With help from AI(artificial intelligence)integrated into the IoT a resilient system can be built to protect the electric grid system nationwide and will be able to detect and preempt Smart Malware attacks.
基金This work is supported by the Major International Joint Research Project of the National Natural Science Foundation of China(Grant No.71520107004)the Major Program of National Natural Science Foundation of China(Grant No.71790614)+1 种基金the Fund for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.71621061)and the 111 Project(Grant No.B16009).
文摘Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries.Motivated by the major development strategies and needs of industrial intellectualization in China,this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization,as well as their application to smart industrial engineering.First,this study describes a general methodology for the fusion of data analytics and optimization.Then,it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing.Finally,it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization.The framework uses data analytics to perceive and analyze industrial production and logistics processes.It also demonstrates the intelligent capability of planning,scheduling,operation optimization,and optimal control.Data analytics and system optimization technologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing,resources and materials,energy,and logistics systems,such as high energy consumption,high costs,low energy efficiency,low resource utilization,and serious environmental pollution.The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency。Therefore,industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.
基金Partial support for this research was provided by the US National Science Foundation (Nos. 1050477, 0959979, and 1117132)by a Brookhaven National Lab LDRD grant+2 种基金by the US Department of Energy (DOE) Office of Basic Energy Sciences, Division of Chemical Sciences, GeosciencesBiosciences and by the IT Consilience Creative Project through the Ministry of Knowledge Economy, Republic of Korea national scientific user facility sponsored by the DOE's OBER at Pacific Northwest National Laboratory (PNNL)PNNL is operated by the US DOE by Battelle Memorial Institute under contract No.DE-AC06-76RL0 1830
文摘Climate research produces a wealth of multivariate data. These data often have a geospatial reference and so it is of interest to show them within their geospatial context. One can consider this configuration as a multifield visualization problem, where the geo-space provides the expanse of the field. However, there is a limit on the amount of multivariate information that can be fit within a certain spatial location, and the use of linked multivariate information displays has previously been devised to bridge this gap. In this paper we focus on the interactions in the geographical display, present an implementation that uses Google Earth, and demonstrate it within a tightly linked parallel coordinates display. Several other visual representations, such as pie and bar charts are integrated into the Google Earth display and can be interactively manipulated. Further, we also demonstrate new brushing and visualization techniques for parallel coordinates, such as fixed-window brushing and correlation-enhanced display. We conceived our system with a team of climate researchers, who already made a few important discoveries using it. This demonstrates our system＇s great potential to enable scientific discoveries, possibly also in other domains where data have a geospatial reference.
文摘Many cities,countries and transport operators around the world are striving to design intelligent transport systems.These systems capture the value of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility,interests,economic activity and lifestyles.They aim to provide services that can enable transportation customers and managers to be better informed and make safer and more efficient use of infrastructure.In developing principles,guidelines,methods and tools to enable synergistic work between humans and computer-generated information,the science of visual analytics continues to expand our understanding of data through effective and interactive visual interfaces.In this paper,we describe an application of visual analytics related to the study of movement and transportation systems.This application documents the use of rapid,2D and 3D web visualisation and data analytics libraries and explores their potential added value to the analysis of big public transport performance data.A novel approach to displaying such data through a generalisable framework visualisation system is demonstrated.This framework recalls over a year’sworth of public transport performance data at a highly granular level in a fast,interactive browser-based environment.Greater Sydney,Australia forms a case study to highlight potential uses of the visualisation of such large,passively-collected data sets as an applied research scenario.In this paper,we argue that such highly visual systems can add data-driven rigour to service planning and longer-term transport decision-making.Furthermore,they enable the sharing of quality of service statistics with various stakeholders and citizens and can showcase improvements in services before and after policy decisions.The paper concludes by making recommendations on the value of this approach in embedding these or similar web-based systems in transport planning practice,performance management,optimisation and understanding of customer experience.
基金the financial support from the National Natural Science Foundation of China(52203123 and 52473248)State Key Laboratory of Polymer Materials Engineering(sklpme2024-2-04)+1 种基金the Fundamental Research Funds for the Central Universitiessponsored by the Double First-Class Construction Funds of Sichuan University。
文摘Composite polymer electrolytes(CPEs)offer a promising solution for all-solid-state lithium-metal batteries(ASSLMBs).However,conventional nanofillers with Lewis-acid-base surfaces make limited contribution to improving the overall performance of CPEs due to their difficulty in achieving robust electrochemical and mechanical interfaces simultaneously.Here,by regulating the surface charge characteristics of halloysite nanotube(HNT),we propose a concept of lithium-ion dynamic interface(Li^(+)-DI)engineering in nano-charged CPE(NCCPE).Results show that the surface charge characteristics of HNTs fundamentally change the Li^(+)-DI,and thereof the mechanical and ion-conduction behaviors of the NCCPEs.Particularly,the HNTs with positively charged surface(HNTs+)lead to a higher Li^(+)transference number(0.86)than that of HNTs-(0.73),but a lower toughness(102.13 MJ m^(-3)for HNTs+and 159.69 MJ m^(-3)for HNTs-).Meanwhile,a strong interface compatibilization effect by Li^(+)is observed for especially the HNTs+-involved Li^(+)-DI,which improves the toughness by 2000%compared with the control.Moreover,HNTs+are more effective to weaken the Li^(+)-solvation strength and facilitate the formation of Li F-rich solid-electrolyte interphase of Li metal compared to HNTs-.The resultant Li|NCCPE|LiFePO4cell delivers a capacity of 144.9 m Ah g^(-1)after 400 cycles at 0.5 C and a capacity retention of 78.6%.This study provides deep insights into understanding the roles of surface charges of nanofillers in regulating the mechanical and electrochemical interfaces in ASSLMBs.
文摘MXene-based smart contact lenses demonstrate a cutting-edge advancement in wearable ophthalmic technology,combining real-time biosensing,therapeutic capabilities,and user comfort in a single platform.These devices take the advantage of the exceptional electrical conductivity,mechanical flexibility,and biocompatibility of two-dimensional MXenes to enable noninvasive,tear-based monitoring of key physiological markers such as intraocular pressure and glucose levels.Recent developments focus on the integration of transparent MXene films into the conventional lens materials,allowing multifunctional performance including photothermal therapy,antimicrobial and anti-inflammation protection,and dehydration resistance.These innovations offer promising strategies for ocular disease management and eye protection.In addition to their multifunctionality,improvements in MXene synthesis and device engineering have enhanced the stability,transparency,and wearability of these lenses.Despite these advances,challenges remain in long-term biostability,scalable production,and integration with wireless communication systems.This review summarizes the current progress,key challenges,and future directions of MXene-based smart contact lenses,highlighting their transformative potential in next-generation digital healthcare and ophthalmic care.
基金supported by the National Natural Science Foundation of China,Nos.82301093(to QC)and 22334004(to HY)the Fuzhou University Fund for Testing Precious Equipment,No.2025T038(to QC)。
文摘The mechanisms underlying the pathophysiology of ischemic stroke are complex and multifactorial and include excitotoxicity,oxidative stress,inflammatory responses,and blood–brain barrier disruption.While vascular recanalization treatments such as thrombolysis and mechanical thrombectomy have achieved some success,reperfusion injury remains a significant contributor to the exacerbation of brain injury.This emphasizes the need for developing neuroprotective strategies to mitigate this type of injury.The purpose of this review was to examine the application of nanotechnology in the treatment of ischemic stroke,covering research progress in nanoparticlebased drug delivery,targeted therapy,and antioxidant and anti-inflammatory applications.Nanobased drug delivery systems offer several advantages compared to traditional therapies,including enhanced blood–brain barrier penetration,prolonged drug circulation time,improved drug stability,and targeted delivery.For example,inorganic nanoparticles,such as those based on CeO_(2),have been widely studied for their strong antioxidant capabilities.Biomimetic nanoparticles,such as those coated with cell membranes,have garnered significant attention owing to their excellent biocompatibility and targeting abilities.Nanoparticles can be used to deliver a wide range of neuroprotective agents,such as antioxidants(e.g.,edaravone),anti-inflammatory drugs(e.g.,curcumin),and neurotrophic factors.Nanotechnology significantly enhances the efficacy of these drugs while minimizing adverse reactions.Although nanotechnology has demonstrated great potential in animal studies,its clinical application still faces several challenges,including the long-term safety of nanoparticles,the feasibility of large-scale production,quality control,and the ability to predict therapeutic effects in humans.In summary,nanotechnology holds significant promise for the treatment of ischemic stroke.Future research should focus on further exploring the mechanisms of action of nanoparticles,developing multifunctional nanoparticles,and validating their safety and efficacy through rigorous clinical trials.Moreover,interdisciplinary collaboration is essential for advancing the use of nanotechnology in stroke treatment.
基金This work is partly funded by the University of Southampton’s Marine and Maritime Institute(SMMI)and the European Research Council under the European Union’s Horizon 2020 research and innovation program(grant agreement number:723526:SEDNA).
文摘Each year,accidents involving ships result in significant loss of life,environmental pollution and economic losses.The promotion of navigation safety through risk reduction requires methods to assess the spatial distribution of the relative likelihood of occurrence.Yet,such methods necessitate the integration of large volumes of heterogenous datasets which are not well suited to traditional data structures.This paper proposes the use of the Discrete Global Grid System(DGGS)as an efficient and advantageous structure to integrate vessel traffic,metocean,bathymetric,infrastructure and other relevant maritime datasets to predict the occurrence of ship groundings.Massive and heterogenous datasets are well suited for machine learning algorithms and this paper develops a spatial maritime risk model based on a DGGS utilising such an approach.A Random Forest algorithm is developed to predict the frequency and spatial distribution of groundings while achieving an R2 of 0.55 and a mean squared error of 0.002.The resulting risk maps are useful for decision-makers in planning the allocation of mitigation measures,targeted to regions with the highest risk.Further work is identified to expand the applications and insights which could be achieved through establishing a DGGS as a global maritime spatial data structure.
文摘In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry problem.Recent demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial importance.This study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each other.The immense achievement of deep learning has resulted in a growing use of its much architecture to enhance efficiency.This review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of data.The following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics statistically.In this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further investigation.The information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.
基金funded in part by the German Research Foundation(Grant reference:496846758).
文摘The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activity, sedentary habits, sleep patterns) within the 24-h cycle of daily life. Wearables are applied in research, clinical practice, and as lifestyle devices;most obvious, they promise to be a key element for increasing human physical activity, one of the biggest health challenges nowadays.
基金supported by the National Natural Science Foundation of China (22379038)Science Research Project of Hebei Education Department (JZX2024015)+4 种基金Shijiazhuang Science and Technology Plan Project (241791357A)Central Guidance for Local Science and Technology Development Funds Project (246Z4408G)Excellent Youth Research Innovation Team of Hebei University (QNTD202410)High-level Talents Research Start-Up Project of Hebei University (521100224223)Hebei Province Innovation Capability Enhancement Plan Project (22567620H)。
文摘Rechargeable zinc(Zn)-ion batteries(RZIBs) with hydrogel electrolytes(HEs) have gained significant attention in the last decade owing to their high safety, low cost, sufficient material abundance, and superb environmental friendliness, which is extremely important for wearable energy storage applications. Given that HEs play a critical role in building flexible RZIBs, it is urgent to summarize the recent advances in this field and elucidate the design principles of HEs for practical applications. This review systematically presents the development history, recent advances in the material fundamentals, functional designs, challenges, and prospects of the HEs-based RZIBs. Firstly, the fundamentals, species, and flexible mechanisms of HEs are discussed, along with their compatibility with Zn anodes and various cathodes. Then, the functional designs of hydrogel electrolytes in harsh conditions are comprehensively discussed, including high/low/wide-temperature windows, mechanical deformations(e.g., bending, twisting, and straining), and damages(e.g., cutting, burning, and soaking). Finally, the remaining challenges and future perspectives for advancing HEs-based RZIBs are outlined.
基金supported by Alberta Health,Alberta Innovates,the Canada Research Chairs program,the Canadian Institutes of Health Research,and the Natural Sciences and Engineering Research Council of Canada.
文摘We report here arsenic speciation in 1643 freshwater fish samples,representing 14 common fish species from 53 waterbodies in Alberta,Canada.Arsenic species were extracted from fish muscle tissue.Arsenic species in the extracts were separated using anion-exchange high-performance liquid chromatography(HPLC)and quantified using inductively coupled plasma mass spectrometry(ICPMS).The total arsenic concentrations in fish ranged from 2.8 to 1200μg/kg(in wet weight of sample)(mean 71±101μg/kg),which are all below the 2000μg/kg(wet weight)maximum allowable total arsenic in fish,recommended by the Ontario Ministry of the Environment.In 99.7%,or 1638 of all 1643 freshwater fish samples analyzed,arsenobetaine(AsB)was detectable,with concentrations higher than the method detection limit of 0.25μg/kg(wet weight).Dimethylarsinic acid(DMA)was detectable(concentration>0.25μg/kg)in 92.1%,or 1514 of the 1643 freshwater fish samples.Inorganic arsenate(iAs^(Ⅴ))was detectable(>0.25μg/kg)in 1119 fish(i.e.,68.1% of 1643 samples).Monomethylarsonic acid(MMA)was detectable(>0.25μg/kg)in 418 fish(25.4%of 1643 samples).The concentrations of arsenic species in the 1643 fish samples varied by as much as three orders of magnitude,ranging from below the method detection limit of 0.25μg/kg to the maximum concentrations of 380μg/kg for AsB,150μg/kg for DMA,70μg/kg for iAs^(Ⅴ),and 51μg/kg for MMA.AsB made up 46.1%±26.2% of total arsenic species.Arsenic speciation patterns varied between lake whitefish,northern pike,and walleye,the three most common types of fish analyzed.The relative proportion of DMA in northern pike was larger than in lake whitefish and walleye,and conversely,the relative proportion of iAs^(Ⅴ) was lower in northern pike.Seven unknown arsenic species were detected,and their chromatographic retention time did not match with those of available arsenic standards.At least one unknown arsenic species was detected in 33.4%,or 549 of 1643 freshwater fish samples.The concentrations of unknown arsenic species were as high as 61μg/kg.Future research is necessary to identify unknown arsenic species and to determine contributing factors to the observed arsenic species patterns and concentrations.
基金supported by the National Natural Science Foundation of China(Nos.42171108 and 42101136)Sichuan Science and Technology Program(Nos.2024NSFSC2007 and2025YFHZ0273)Natural Science Starting Project of SWPU(No.2024QHZ029)。
文摘In cold regions,slope rocks are inevitably impacted by freeze-thaw,dry-wet cycles and their alternating actions,leading to strength weakening and pore degradation.In this study,the mechanical and microstructural properties of schist subjected to four conditions were investigated:freeze-thaw cycles in air(FTA),freeze-thaw cycles in water(FTW),dry-wet cycles(DW),and dry-wet-freeze-thaw cycles(DWFT).Uniaxial compressive strength(UCS),water absorption,ultrasonication,low-field nuclear magnetic resonance,and scanning electron microscopy analyses were conducted.The integrity attenuation characteristics of the longitudinal wave velocity,UCS,and elastic modulus were analyzed.The results showed that liquid water emerged as a critical factor in reducing the brittleness of schist.The attenuation function model accurately described the peak stress and static elastic modulus of schist in various media(R2>0.97).Different media affected the schist deterioration and half-life,with the FTW-immersed samples having a half-life of 28 cycles.Furthermore,the longitudinal wave velocity decreased as the number of cycles increased,with the FTW showing the most significant reduction and having the shortest half-life of 208 cycles.Moreover,the damage variables of compressive strength and elastic modulus increased with the number of cycles.After 40 cycles,the schist exposed to FTW exhibited the highest damage variables and saturated water content.
文摘We report a robust pillar-layered metal-organic framework,Zn‑tfbdc‑dabco(tfbdc:tetrafluoroterephthal-ate,dabco:1,4-diazabicyclo[2.2.2]octane),featuring the fluorinated pore environment,for the preferential binding of propane over propylene and thus highly inverse selective separation of propane/propylene mixture.The inverse propane-selective performance of Zn‑tfbdc‑dabco for the propane/propylene separation was validated by single-component gas adsorption isotherms,isosteric enthalpy of adsorption calculations,ideal adsorbed solution theory calculations,along with the breakthrough experiment.The customized fluorinated networks served as a propane-trap to form more interactions with the exposed hydrogen atoms of propane,as unveiled by the simulation studies at the molecular level.With the advantage of inverse propane-selective adsorption behavior,high adsorption capacity,good cycling stability,and low isosteric enthalpy of adsorption,Zn‑tfbdc‑dabco can be a promising candidate adsorbent for the challenging propane/propylene separation to realize one-step purification of the target propylene substance.
