Rate coefficients of the gas-phase reactions of Cl atoms with a series of fluorinated diketones(FDKs):CF_(3)C(O)CH_(2)C(O)CH_(3)(TFP),CF_(3)C(O)CH_(2)C(O)CH_(2)CH_(3)(TFH)and CF_(3)C(O)CH_(2)C(O)CH(CH_(3))2(TFMH),have...Rate coefficients of the gas-phase reactions of Cl atoms with a series of fluorinated diketones(FDKs):CF_(3)C(O)CH_(2)C(O)CH_(3)(TFP),CF_(3)C(O)CH_(2)C(O)CH_(2)CH_(3)(TFH)and CF_(3)C(O)CH_(2)C(O)CH(CH_(3))2(TFMH),have been measured at(298±2)K and under atmospheric pressure.The experiments were performed using the relative-rate method with a GC-FID detection system.From different determinations and references used,the following rate coefficients were obtained(in cm3/(molecule·sec)):k_(4)(TFP+Cl)=(1.75±0.21)×10^(−10),k_(5)(TFH+Cl)=(2.05±0.23)×10^(−10),k_(6)(TFMH+Cl)=(2.71±0.34)×10^(−10).Reactivity trends of FDKs were discussed and Free Energy Relationships analysis was developed.The expression lgkOH=1.68 lgkCl+5.71 was obtained for the reactivity of the studied FDKs together with similar unsaturated VOCs with Cl and OH radicals Additionally,acetic acid(CH_(3)C(O)OH)and trifluoroacetic acid(CF_(3)C(O)OH)were positively identified and quantified as degradation products using in situ FTIR spectroscopy.According to the identified products,atmospheric chemical mechanisms were proposed.The atmospheric implications of the studied reactions were assessed by the estimation of the tropospheric lifetimes of TFP,TFH,and TFMH concerning their reaction with Cl atoms to be 48,41,and 31 hours,respectively.The relatively short residence in the atmosphere of the fluorocarbons studied will have a local/regional impact with restricted transport.Global warming potential(GWP(20 yr))calculated for the studied fluoro diketones were 0.014,0.003 and 0.001 for TFP,TFH and TFMH,respectively with a negligible contribution to the greenhouse effect.展开更多
A super-radiant terahertz free-electron laser(THz-FEL)light source was developed for the first time in Thailand and Southeast Asia at the PBP-CMU Electron Linac Laboratory(PCELL)of Chiang Mai University.This radiation...A super-radiant terahertz free-electron laser(THz-FEL)light source was developed for the first time in Thailand and Southeast Asia at the PBP-CMU Electron Linac Laboratory(PCELL)of Chiang Mai University.This radiation source requires relatively ultrashort electron bunches to produce intense coherent THz pulses.Three electron bunch compression processes are utilized in the PCELL accelerator system comprising pre-bunch compression in an alpha magnet,velocity bunching in a radio-frequency(RF)linear accelerator(linac),and magnetic bunch compression in a 180°acromat system.Electron bunch compression in the magnetic compressor system poses considerable challenges,which are addressed through the use of three quadrupole doublets.The strengths of the quadrupole fields significantly influence the rotation of the beam line longitudinal phase space distribution along the bunch compressor.Start-to-end beam dynamics simulations using the ASTRA code were performed to optimize the electron beam properties for generating super-radiant THz-FEL radiation.The operational parameters considered in the simulations comprise the alpha magnet gradient,linac RF phase,and quadrupole field strengths.The optimization results show that 10-16MeV femtosecond electron bunches with a low energy spread(~0.2%),small normalized emittance(~15πmm·mrad),and high peak current(165-247A)can be produced by the PCELL accelerator system at the optimal parameters.A THz-FEL with sub-microjoule pulse energies can thus be obtained at the optimized electron beam parameters.The physical and conceptual design of the THz-FEL beamline were completed based on the beam dynamics simulation results.The construction and installation of this beamline are currently underway and expected to be completed by mid-2024.The commissioning of the beamline will then commence.展开更多
Man-made superheavy elements(SHE)are produced as energetic recoils in complete-fusion reactions and need to be thermalized in a gas-filled chamber for chemical studies.The ever-shorter half-lives and decreasing produc...Man-made superheavy elements(SHE)are produced as energetic recoils in complete-fusion reactions and need to be thermalized in a gas-filled chamber for chemical studies.The ever-shorter half-lives and decreasing production rates of the elements beyond Fl(atomic number Z=114)-the heaviest element chemically studied today-require the development of novel techniques for quantitative thermalization and fast extraction efficiency.The Universal high-density gas stopping Cell(UniCell),currently under construction,was proposed to achieve this.Within this work,we propose an Ion Transfer by Gas Flow(ITGF)device,which serves as a UniCell ejector to interface with a gas chromatography detector array for chemical studies.Detailed parameter optimizations,using gas dynamics and Monte Carlo ion-trajectory simulations,promise fast(within a few ms)and highly efficient(up to 100%)ion extraction across a wide mass range.These ions can then be transmitted quantitatively through the ITGF into the high-pressure environment needed for further chemical studies.展开更多
In the face of the unrelenting challenge posed by earthquakes-a natural hazard of unpredictable nature with a legacy of significant loss of life,destruction of infrastructure,and profound economic and social impacts-t...In the face of the unrelenting challenge posed by earthquakes-a natural hazard of unpredictable nature with a legacy of significant loss of life,destruction of infrastructure,and profound economic and social impacts-the scientific community has pursued advancements in earthquake early warning systems(EEWSs).These systems are vital for pre-emptive actions and decision-making that can save lives and safeguard critical infrastructure.This study proposes and validates a domain-informed deep learning-based EEWS called the hybrid earthquake early warning framework for estimating response spectra(HEWFERS),which represents a significant leap forward in the capabilities to predict ground shaking intensity in real-time,aligning with the United Nations’disaster risk reduction goals.HEWFERS ingeniously integrates a domain-informed variational autoencoder for physics-based latent variable(LV)extraction,a feed-forward neural network for on-site prediction,and Gaussian process regression for spatial prediction.Adopting explainable artificial intelligence-based Shapley explanations further elucidates the predictive mechanisms,ensuring stakeholder-informed decisions.By conducting an extensive analysis of the proposed framework under a large database of approximately 14000 recorded ground motions,this study offers insights into the potential of integrating machine learning with seismology to revolutionize earthquake preparedness and response,thus paving the way for a safer and more resilient future.展开更多
Kinetics of the gas-phase reactions of•OH radicals with a series of fluoroesters were studied for the first time at 298±3 K and atmospheric pressure.Relative rate coefficients were determined by in situ FTIR spec...Kinetics of the gas-phase reactions of•OH radicals with a series of fluoroesters were studied for the first time at 298±3 K and atmospheric pressure.Relative rate coefficients were determined by in situ FTIR spectroscopy in nitrogen and GC-FID in air to monitor the decay of reactants and references.The following coefficient values(in 10^(−12)cm^(3)/(molecule•sec))were obtained for ethyl fluoroacetate(EFA),ethyl 4,4,4-trifluorobutyrate(ETB),and butyl fluoroacetate(BFA),respectively:k_(1)(EFA+OH)=1.15±0.25 by FTIR and 1.34±0.23 by GC-FID;k_(2)(ETB+OH)=1.61±0.36 by FTIR and 2.02±0.30 by GC-FID;k_(3)(BFA+OH)=2.24±0.37 by FTIR.Reactivity trends were developed and correlated with the number of CH_(3)and F substituents in the fluoroester,and structure-activity relationships(SARs)calculations were performed.In addition,the tropospheric lifetimes of EFA,ETB,and BFA upon degradation by OH radicals were calculated to be 9,6,and 5 days,respectively,indicating that these fluorinated compounds could have a possible regional effect from the emission source.Relatively small photochemical ozone creation potentials of 9,7,and 19 were estimated for EFA,ETB,and BFA,respectively.The GlobalWarming Potentials(GWPs)for EFA,ETB,and BFA were calculated for different time horizons.For a 20-year time horizon,the GWPs were 1.393,0.063,and 0.062,respectively.In the case of a 100-year time horizon,the GWPs were 0.379,0.017,and 0.017,and for a 500-year time horizon,the GWPs were 0.108,0.005,and 0.005 for EFA,ETB,and BFA.展开更多
Plants and their interaction partners offer unparalleled views of evolutionary ecology.Nectar larceny,entailing nectar extraction without pollinating,is thought to be an example of a harmful,antagonistic behavior,but ...Plants and their interaction partners offer unparalleled views of evolutionary ecology.Nectar larceny,entailing nectar extraction without pollinating,is thought to be an example of a harmful,antagonistic behavior,but the precise consequences of floral larceny on plant reproductive success remain contentious.We conducted a comprehensive meta-analysis of 153 studies across 120 plant species,using 14 moderators to assess the effects of floral larceny on plant reproductive success and examine the key moderators.We found that floral larceny negatively impacts flower traits,pollinator visitation,pollen deposition,and fruit set,while having a neutral effect on critical female fitness indicators,such as seed set and seed quality,as well as on male fitness.By altering pollinator behavior,floral larceny may reduce geitonogamy,potentially enhancing genetic diversity.Additionally,factors such as pollinator type,plant mating system,and pollen limitation were identified as key moderators of these effects.Our analysis reveals an ultimately neutral effect of floral larceny on plant reproductive success,with potential benefits in certain contexts.These findings suggest that floral larceny plays a complex and multifaceted role within plant-pollinator interactions,facilitating the evolutionary stability and coexistence of floral larcenists and host plants.展开更多
The sulfur-fumigation process not only induces the chemical transformation of Lycium barbarum(Lb,a widely used traditional Chinese medicine)but also severely influences human health.Given the existing challenges like ...The sulfur-fumigation process not only induces the chemical transformation of Lycium barbarum(Lb,a widely used traditional Chinese medicine)but also severely influences human health.Given the existing challenges like the complex and time-consuming operation,as well as the high technical demands of the current detection methods for sulfur-fumed Lycium barbarum(SF-Lb),this paper employs a simple chemiresistor to carry out discrimination research between Lb and SF-Lb which have significant differences in volatolomics.The sensor is constructed by a conductive metal-organic framework(cMOF)thin film,Cu_(3)(HHTP)_(2),due to its abundant active sites,excellent electron transfer performance as well as the capacity to detect specific groups of volatile organic compounds(VOCs).Consequently,the response values of Cu_(3)(HHTP)_(2)-based sensor to 0.5 g SF-Lb(151.74%)are significantly higher than those to normal Lb(80.07%),identifying SF-Lb simply and rapidly with an accuracy of~100%.Our work investigates volatolomics of SF-Lb and establishes a new rapid discrimination method for sulfur-fumed traditional Chinese herbs.展开更多
The Chilean Pampean flat slab subduction segment is characterized by the nearly horizontal subduction of the Nazca Plate within the depth range of 100-120 km.Numerous seismic tomography studies have been conducted to ...The Chilean Pampean flat slab subduction segment is characterized by the nearly horizontal subduction of the Nazca Plate within the depth range of 100-120 km.Numerous seismic tomography studies have been conducted to investigate its velocity structure;however,they have used only seismic body wave data or surface wave data.As a result,the existing velocity models in the region may have relatively large uncertainties.In this study,we use body wave arrival times from earthquakes occurring in central Chile between 2014 and 2019,as well as Rayleigh wave phase velocity maps at periods of 5-80 s from ambient noise empirical Green’s functions in Chile.By jointly using body wave arrival times and surface wave dispersion data,we refine the VS model and improve earthquake locations in the central Chile subduction zone.Compared with previous velocity models,our velocity model better reveals an eastward-dipping high-velocity plate representing the subducting Nazca Plate,which is 40-50 km thick and is more consistent with the slab thickness estimated by receiver function imaging and thermal modeling.Overall,the intraslab seismicity distribution spatially correlates well with the slab high-velocity anomalies except along the subduction paths of the CopiapóRidge and Juan Fernández Ridge.Additionally,parallel low-velocity stripes are imaged beneath the subducting plate,which are likely associated with the accumulated melts.The joint inversion velocity model also resolves widespread low-velocity anomalies in the crust beneath the Central Volcanic Zone of the central Andes,likely representing crustal magma chambers for various volcanoes.展开更多
The early and precise identification of Alzheimer’s Disease(AD)continues to pose considerable clinical difficulty due to subtle structural alterations and overlapping symptoms across the disease phases.This study pre...The early and precise identification of Alzheimer’s Disease(AD)continues to pose considerable clinical difficulty due to subtle structural alterations and overlapping symptoms across the disease phases.This study presents a novel Deformable Attention Vision Transformer(DA-ViT)architecture that integrates deformable Multi-Head Self-Attention(MHSA)with a Multi-Layer Perceptron(MLP)block for efficient classification of Alzheimer’s disease(AD)using Magnetic resonance imaging(MRI)scans.In contrast to traditional vision transformers,our deformable MHSA module preferentially concentrates on spatially pertinent patches through learned offset predictions,markedly diminishing processing demands while improving localized feature representation.DA-ViT contains only 0.93 million parameters,making it exceptionally suitable for implementation in resource-limited settings.We evaluate the model using a class-imbalanced Alzheimer’s MRI dataset comprising 6400 images across four categories,achieving a test accuracy of 80.31%,a macro F1-score of 0.80,and an area under the receiver operating characteristic curve(AUC)of 1.00 for the Mild Demented category.Thorough ablation studies validate the ideal configuration of transformer depth,headcount,and embedding dimensions.Moreover,comparison research indicates that DA-ViT surpasses state-of-theart pre-trained Convolutional Neural Network(CNN)models in terms of accuracy and parameter efficiency.展开更多
BACKGROUND The decision to administer adjuvant chemotherapy to patients with local stage depends on specific high-risk features that are T4 tumor stage,presence of perineural invasion,lymphovascular invasion,poorly di...BACKGROUND The decision to administer adjuvant chemotherapy to patients with local stage depends on specific high-risk features that are T4 tumor stage,presence of perineural invasion,lymphovascular invasion,poorly differentiated tumor histology,inadequate lymph node sampling(fewer than 12 lymph nodes),and evidence of tumor perforation or obstruction.Tumor-stroma ratio,tumor infiltrating lymphocytes(TIL),Crohn-like reaction(CLR),desmoid reaction,poorly differentiated clusters(PDC)are new pathological markers that are being studied.AIM To examine the relationship between new pathological markers and defined high METHODS We evaluated 155 patients with the diagnosis stage I and II colorectal cancer between the years 2007 and 2021 who were treated at Trakya University Hospital,Department of Medical Oncology.We divided those with and without high-risk factors into two groups.We examined the relationship of new pathological markers with these groups and with pathological markers in risk factors.RESULTS There was no statistically significant correlation between presence of TIL,presence of PDC,presence of tumor budding,presence of CLR,presence of desmoid reaction and low and high-risk groups according to the degree of those with PDC(P=0.82,P=0.51,P=0.77,P=0.37,P=0.83,respectively).In addition,no statistically significant correlation was found between the tumor-stroma ratio and low and high risk groups(P=0.80).We found a statistically significant correlation between the presence of PDC and the presence of PDC grade 3 and T stage(P=0.001,P=0.001,respectively).It was determined that the presence of PDC and the frequency of grade 3 PDC increased with the advanced T stage.CONCLUSION No relationship was found between the presence of new pathological markers and high-low risk groups.When we examined the relationship between new and old pathological markers,only the frequency of detection of PDC and PDC grade 3 was found to be correlated with advanced T stage.展开更多
In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive streng...In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive strength.In this study,505 groups of data were collected,and a new database of compressive strength of PFGC was constructed.In order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative analysis.The five machine learning models all showed good compressive strength prediction performance on PFGC.Among them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,respectively.While R2,MSE,RMSE and MAE of random forest model(RF)are 0.97,5.17,2.27 and 1.38,respectively.The two models have high prediction accuracy and outstanding generalization ability.In order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 variables.These 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide dosage.Curing temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PFGC than ordinary Portland cement concrete.The importance of curing conditions of PFGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.展开更多
We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresp...We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresponding extended ab initio data set,we construct interpolation formulas covering the range from low-density,high-temperature to high-density,low-temperature plasmas.Our conductivity model repro-duces the well-known limits of the Spitzer and Ziman theory.We compare with available experimental data andfind very good agreement.The new conductivity model can be applied,for example,in dynamo simulations for magneticfield generation in gas giant planets,brown dwarfs,and stellar envelopes.展开更多
Stroke is classified as ischemic or hemorrhagic,and there are few effective treatments for either type.Immunologic mechanisms play a critical role in secondary brain injury following a stroke,which manifests as cytoki...Stroke is classified as ischemic or hemorrhagic,and there are few effective treatments for either type.Immunologic mechanisms play a critical role in secondary brain injury following a stroke,which manifests as cytokine release,blood–brain barrier disruption,neuronal cell death,and ultimately behavioral impairment.Suppressing the inflammatory response has been shown to mitigate this cascade of events in experimental stroke models.However,in clinical trials of anti-inflammatory agents,longterm immunosuppression has not demonstrated significant clinical benefits for patients.This may be attributable to the dichotomous roles of inflammation in both tissue injury and repair,as well as the complex pathophysiologic inflammatory processes in stroke.Inhibiting acute harmful inflammatory responses or inducing a phenotypic shift from a pro-inflammatory to an anti-inflammatory state at specific time points after a stroke are alternative and promising therapeutic strategies.Identifying agents that can modulate inflammation requires a detailed understanding of the inflammatory processes of stroke.Furthermore,epigenetic reprogramming plays a crucial role in modulating post-stroke inflammation and can potentially be exploited for stroke management.In this review,we summarize current findings on the epigenetic regulation of the inflammatory response in stroke,focusing on key signaling pathways including nuclear factor-kappa B,Janus kinase/signal transducer and activator of transcription,and mitogen-activated protein kinase as well as inflammasome activation.We also discuss promising molecular targets for stroke treatment.The evidence to date indicates that therapeutic targeting of the epigenetic regulation of inflammation can shift the balance from inflammation-induced tissue injury to repair following stroke,leading to improved post-stroke outcomes.展开更多
In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal s...In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).展开更多
As the world shift towards sustainable energy solutions,solid oxide fuel cells(SOFCs)using non-carbon fuels like ammonia and hydrogen emerge as promising pathways to produce clean energy and enhance conversion efficie...As the world shift towards sustainable energy solutions,solid oxide fuel cells(SOFCs)using non-carbon fuels like ammonia and hydrogen emerge as promising pathways to produce clean energy and enhance conversion efficiency.However,current implementations encounter challenges such as nitriding effects from direct ammonia injection to the stack,overestimated benefits of anode off-gas(AOG)recirculation,and a sole focus on electrical efficiency that overlooks the thermal advantages of SOFCs.This study addresses these gaps through a comprehensive multi-objective optimization of SOFC systems fueled by ammonia and hydrogen,assessing their efficiency,fuel utilization,and heat exergy.The research translates material phenomena into mathematical constraints and quantifies the effects of control variables through systematic parameter variation.Results indicate that ammonia-fueled SOFC systems slightly outperform hydrogen,achieving an electrical efficiency of about 65% compared to 62% for hydrogen systems,although hydrogen demonstrates superior fuel utilization and exergy efficiency.Optimal AOG recirculation and NH3cracking fraction that do not compromise stack lifetime and stay in the safe operating zone of nitriding are identified.It also challenges the assumptions that a higher AOG recirculation can benefit performance,suggesting that more extensive AOG recirculation might not always enhance it.Soft sensors are provided to predict system’s performance and enable proactive adjustments to facilitate industrial applications where some parameters,such as high-temperature stack’s pressure drop,are costly or difficult to measure.This study significantly advances the practical deployment of SOFC technologies,enhancing their feasibility for sustainable energy development.展开更多
Oxidative coupling of methane (OCM) is one of the most promising approaches to produce ethylene and ethane (C_(2)-hydrocarbons) in the post-oil era.The MnO_(x)-Na_(2)WO_(4)/SiO_(2) system shows promising OCM performan...Oxidative coupling of methane (OCM) is one of the most promising approaches to produce ethylene and ethane (C_(2)-hydrocarbons) in the post-oil era.The MnO_(x)-Na_(2)WO_(4)/SiO_(2) system shows promising OCM performance,which can be further enhanced by cofed steam.However,the positive effect of steam on C_(2)-hydrocarbons selectivity practically disappears above 800℃.In the present study,we demonstrate that the use of SiC as a support for MnO_(x)-Na_(2)WO_(4) is beneficial for achieving high selectivity up to 850℃.Our sophisticated kinetic tests using feeds without and with steam revealed that the steam-mediated improvement in selectivity to C_(2)-hydrocarbons is due to the inhibition of the direct CH_(4) oxidation to carbon oxides because of the different enhancing effects of steam on the rates of CH_(4) conversion to C_(2)H_(6) and CO/CO_(2).Other descriptors of the selectivity improvement are MnO_(x) dispersion and the catalyst specific surface area.The knowledge gained herein may be useful for optimizing OCM performance through catalyst design and reactor operation.展开更多
文摘Rate coefficients of the gas-phase reactions of Cl atoms with a series of fluorinated diketones(FDKs):CF_(3)C(O)CH_(2)C(O)CH_(3)(TFP),CF_(3)C(O)CH_(2)C(O)CH_(2)CH_(3)(TFH)and CF_(3)C(O)CH_(2)C(O)CH(CH_(3))2(TFMH),have been measured at(298±2)K and under atmospheric pressure.The experiments were performed using the relative-rate method with a GC-FID detection system.From different determinations and references used,the following rate coefficients were obtained(in cm3/(molecule·sec)):k_(4)(TFP+Cl)=(1.75±0.21)×10^(−10),k_(5)(TFH+Cl)=(2.05±0.23)×10^(−10),k_(6)(TFMH+Cl)=(2.71±0.34)×10^(−10).Reactivity trends of FDKs were discussed and Free Energy Relationships analysis was developed.The expression lgkOH=1.68 lgkCl+5.71 was obtained for the reactivity of the studied FDKs together with similar unsaturated VOCs with Cl and OH radicals Additionally,acetic acid(CH_(3)C(O)OH)and trifluoroacetic acid(CF_(3)C(O)OH)were positively identified and quantified as degradation products using in situ FTIR spectroscopy.According to the identified products,atmospheric chemical mechanisms were proposed.The atmospheric implications of the studied reactions were assessed by the estimation of the tropospheric lifetimes of TFP,TFH,and TFMH concerning their reaction with Cl atoms to be 48,41,and 31 hours,respectively.The relatively short residence in the atmosphere of the fluorocarbons studied will have a local/regional impact with restricted transport.Global warming potential(GWP(20 yr))calculated for the studied fluoro diketones were 0.014,0.003 and 0.001 for TFP,TFH and TFMH,respectively with a negligible contribution to the greenhouse effect.
基金support from the NSRF via the Program Management Unit for Human Resources&Institutional Development,Research,and Innovation(No.B05F650022),as well as from Chiang Mai University.
文摘A super-radiant terahertz free-electron laser(THz-FEL)light source was developed for the first time in Thailand and Southeast Asia at the PBP-CMU Electron Linac Laboratory(PCELL)of Chiang Mai University.This radiation source requires relatively ultrashort electron bunches to produce intense coherent THz pulses.Three electron bunch compression processes are utilized in the PCELL accelerator system comprising pre-bunch compression in an alpha magnet,velocity bunching in a radio-frequency(RF)linear accelerator(linac),and magnetic bunch compression in a 180°acromat system.Electron bunch compression in the magnetic compressor system poses considerable challenges,which are addressed through the use of three quadrupole doublets.The strengths of the quadrupole fields significantly influence the rotation of the beam line longitudinal phase space distribution along the bunch compressor.Start-to-end beam dynamics simulations using the ASTRA code were performed to optimize the electron beam properties for generating super-radiant THz-FEL radiation.The operational parameters considered in the simulations comprise the alpha magnet gradient,linac RF phase,and quadrupole field strengths.The optimization results show that 10-16MeV femtosecond electron bunches with a low energy spread(~0.2%),small normalized emittance(~15πmm·mrad),and high peak current(165-247A)can be produced by the PCELL accelerator system at the optimal parameters.A THz-FEL with sub-microjoule pulse energies can thus be obtained at the optimized electron beam parameters.The physical and conceptual design of the THz-FEL beamline were completed based on the beam dynamics simulation results.The construction and installation of this beamline are currently underway and expected to be completed by mid-2024.The commissioning of the beamline will then commence.
基金This work was supported by the German BMBF (No.05P21UMFN2)
文摘Man-made superheavy elements(SHE)are produced as energetic recoils in complete-fusion reactions and need to be thermalized in a gas-filled chamber for chemical studies.The ever-shorter half-lives and decreasing production rates of the elements beyond Fl(atomic number Z=114)-the heaviest element chemically studied today-require the development of novel techniques for quantitative thermalization and fast extraction efficiency.The Universal high-density gas stopping Cell(UniCell),currently under construction,was proposed to achieve this.Within this work,we propose an Ion Transfer by Gas Flow(ITGF)device,which serves as a UniCell ejector to interface with a gas chromatography detector array for chemical studies.Detailed parameter optimizations,using gas dynamics and Monte Carlo ion-trajectory simulations,promise fast(within a few ms)and highly efficient(up to 100%)ion extraction across a wide mass range.These ions can then be transmitted quantitatively through the ITGF into the high-pressure environment needed for further chemical studies.
基金the financial support from the Chilean National Research and Development Agency(Agencia Nacional de Investigación y Desarrollo,ANID)through Fondo Nacional de Desarrollo Científico y Tecnológico(FONDECYT)Regular 1240503Fondo de Valorización de la Investigación(FOVI)230030 projectsthe financial support from the ANID through FONDECYT Reg-ular 1240501.
文摘In the face of the unrelenting challenge posed by earthquakes-a natural hazard of unpredictable nature with a legacy of significant loss of life,destruction of infrastructure,and profound economic and social impacts-the scientific community has pursued advancements in earthquake early warning systems(EEWSs).These systems are vital for pre-emptive actions and decision-making that can save lives and safeguard critical infrastructure.This study proposes and validates a domain-informed deep learning-based EEWS called the hybrid earthquake early warning framework for estimating response spectra(HEWFERS),which represents a significant leap forward in the capabilities to predict ground shaking intensity in real-time,aligning with the United Nations’disaster risk reduction goals.HEWFERS ingeniously integrates a domain-informed variational autoencoder for physics-based latent variable(LV)extraction,a feed-forward neural network for on-site prediction,and Gaussian process regression for spatial prediction.Adopting explainable artificial intelligence-based Shapley explanations further elucidates the predictive mechanisms,ensuring stakeholder-informed decisions.By conducting an extensive analysis of the proposed framework under a large database of approximately 14000 recorded ground motions,this study offers insights into the potential of integrating machine learning with seismology to revolutionize earthquake preparedness and response,thus paving the way for a safer and more resilient future.
文摘Kinetics of the gas-phase reactions of•OH radicals with a series of fluoroesters were studied for the first time at 298±3 K and atmospheric pressure.Relative rate coefficients were determined by in situ FTIR spectroscopy in nitrogen and GC-FID in air to monitor the decay of reactants and references.The following coefficient values(in 10^(−12)cm^(3)/(molecule•sec))were obtained for ethyl fluoroacetate(EFA),ethyl 4,4,4-trifluorobutyrate(ETB),and butyl fluoroacetate(BFA),respectively:k_(1)(EFA+OH)=1.15±0.25 by FTIR and 1.34±0.23 by GC-FID;k_(2)(ETB+OH)=1.61±0.36 by FTIR and 2.02±0.30 by GC-FID;k_(3)(BFA+OH)=2.24±0.37 by FTIR.Reactivity trends were developed and correlated with the number of CH_(3)and F substituents in the fluoroester,and structure-activity relationships(SARs)calculations were performed.In addition,the tropospheric lifetimes of EFA,ETB,and BFA upon degradation by OH radicals were calculated to be 9,6,and 5 days,respectively,indicating that these fluorinated compounds could have a possible regional effect from the emission source.Relatively small photochemical ozone creation potentials of 9,7,and 19 were estimated for EFA,ETB,and BFA,respectively.The GlobalWarming Potentials(GWPs)for EFA,ETB,and BFA were calculated for different time horizons.For a 20-year time horizon,the GWPs were 1.393,0.063,and 0.062,respectively.In the case of a 100-year time horizon,the GWPs were 0.379,0.017,and 0.017,and for a 500-year time horizon,the GWPs were 0.108,0.005,and 0.005 for EFA,ETB,and BFA.
基金support by the National Natural Science Foundation of China(32170241,32160054,and 32470241)supported by the Chinese Academy of Science's PIFI Fellowship Initiative(2024PVC0046).
文摘Plants and their interaction partners offer unparalleled views of evolutionary ecology.Nectar larceny,entailing nectar extraction without pollinating,is thought to be an example of a harmful,antagonistic behavior,but the precise consequences of floral larceny on plant reproductive success remain contentious.We conducted a comprehensive meta-analysis of 153 studies across 120 plant species,using 14 moderators to assess the effects of floral larceny on plant reproductive success and examine the key moderators.We found that floral larceny negatively impacts flower traits,pollinator visitation,pollen deposition,and fruit set,while having a neutral effect on critical female fitness indicators,such as seed set and seed quality,as well as on male fitness.By altering pollinator behavior,floral larceny may reduce geitonogamy,potentially enhancing genetic diversity.Additionally,factors such as pollinator type,plant mating system,and pollen limitation were identified as key moderators of these effects.Our analysis reveals an ultimately neutral effect of floral larceny on plant reproductive success,with potential benefits in certain contexts.These findings suggest that floral larceny plays a complex and multifaceted role within plant-pollinator interactions,facilitating the evolutionary stability and coexistence of floral larcenists and host plants.
基金supported by the National Natural Science Foundation of China(Nos.22205121,22494633,22401281)CAS President's International Fellowship for Visiting Scientists(No.2024VBC0002)+2 种基金the research fund of State Key Laboratory of Mesoscience and Engineering(Nos.MESO-23-A07,MESO-23-T02,MESO-24-A01)First-class Discipline Construction Project(Chemistry)in Higher Education Institutions of Ningxia(Ningxia Normal University)Engineering Research Center of Liupanshan(No.HGZD22-27).
文摘The sulfur-fumigation process not only induces the chemical transformation of Lycium barbarum(Lb,a widely used traditional Chinese medicine)but also severely influences human health.Given the existing challenges like the complex and time-consuming operation,as well as the high technical demands of the current detection methods for sulfur-fumed Lycium barbarum(SF-Lb),this paper employs a simple chemiresistor to carry out discrimination research between Lb and SF-Lb which have significant differences in volatolomics.The sensor is constructed by a conductive metal-organic framework(cMOF)thin film,Cu_(3)(HHTP)_(2),due to its abundant active sites,excellent electron transfer performance as well as the capacity to detect specific groups of volatile organic compounds(VOCs).Consequently,the response values of Cu_(3)(HHTP)_(2)-based sensor to 0.5 g SF-Lb(151.74%)are significantly higher than those to normal Lb(80.07%),identifying SF-Lb simply and rapidly with an accuracy of~100%.Our work investigates volatolomics of SF-Lb and establishes a new rapid discrimination method for sulfur-fumed traditional Chinese herbs.
基金funded by the National Natural Science Foundation of China under Grant 42230101the National Agency for Research and Development of Chile(ANID)by Projects AFB180004 and AFB220002the ANID Programa de Cooperación Internacional(PCI)Grant PII-180003.
文摘The Chilean Pampean flat slab subduction segment is characterized by the nearly horizontal subduction of the Nazca Plate within the depth range of 100-120 km.Numerous seismic tomography studies have been conducted to investigate its velocity structure;however,they have used only seismic body wave data or surface wave data.As a result,the existing velocity models in the region may have relatively large uncertainties.In this study,we use body wave arrival times from earthquakes occurring in central Chile between 2014 and 2019,as well as Rayleigh wave phase velocity maps at periods of 5-80 s from ambient noise empirical Green’s functions in Chile.By jointly using body wave arrival times and surface wave dispersion data,we refine the VS model and improve earthquake locations in the central Chile subduction zone.Compared with previous velocity models,our velocity model better reveals an eastward-dipping high-velocity plate representing the subducting Nazca Plate,which is 40-50 km thick and is more consistent with the slab thickness estimated by receiver function imaging and thermal modeling.Overall,the intraslab seismicity distribution spatially correlates well with the slab high-velocity anomalies except along the subduction paths of the CopiapóRidge and Juan Fernández Ridge.Additionally,parallel low-velocity stripes are imaged beneath the subducting plate,which are likely associated with the accumulated melts.The joint inversion velocity model also resolves widespread low-velocity anomalies in the crust beneath the Central Volcanic Zone of the central Andes,likely representing crustal magma chambers for various volcanoes.
基金Prince Sattambin Abdulaziz University for funding this research work through the project number(PSAU/2025/R/1446).
文摘The early and precise identification of Alzheimer’s Disease(AD)continues to pose considerable clinical difficulty due to subtle structural alterations and overlapping symptoms across the disease phases.This study presents a novel Deformable Attention Vision Transformer(DA-ViT)architecture that integrates deformable Multi-Head Self-Attention(MHSA)with a Multi-Layer Perceptron(MLP)block for efficient classification of Alzheimer’s disease(AD)using Magnetic resonance imaging(MRI)scans.In contrast to traditional vision transformers,our deformable MHSA module preferentially concentrates on spatially pertinent patches through learned offset predictions,markedly diminishing processing demands while improving localized feature representation.DA-ViT contains only 0.93 million parameters,making it exceptionally suitable for implementation in resource-limited settings.We evaluate the model using a class-imbalanced Alzheimer’s MRI dataset comprising 6400 images across four categories,achieving a test accuracy of 80.31%,a macro F1-score of 0.80,and an area under the receiver operating characteristic curve(AUC)of 1.00 for the Mild Demented category.Thorough ablation studies validate the ideal configuration of transformer depth,headcount,and embedding dimensions.Moreover,comparison research indicates that DA-ViT surpasses state-of-theart pre-trained Convolutional Neural Network(CNN)models in terms of accuracy and parameter efficiency.
文摘BACKGROUND The decision to administer adjuvant chemotherapy to patients with local stage depends on specific high-risk features that are T4 tumor stage,presence of perineural invasion,lymphovascular invasion,poorly differentiated tumor histology,inadequate lymph node sampling(fewer than 12 lymph nodes),and evidence of tumor perforation or obstruction.Tumor-stroma ratio,tumor infiltrating lymphocytes(TIL),Crohn-like reaction(CLR),desmoid reaction,poorly differentiated clusters(PDC)are new pathological markers that are being studied.AIM To examine the relationship between new pathological markers and defined high METHODS We evaluated 155 patients with the diagnosis stage I and II colorectal cancer between the years 2007 and 2021 who were treated at Trakya University Hospital,Department of Medical Oncology.We divided those with and without high-risk factors into two groups.We examined the relationship of new pathological markers with these groups and with pathological markers in risk factors.RESULTS There was no statistically significant correlation between presence of TIL,presence of PDC,presence of tumor budding,presence of CLR,presence of desmoid reaction and low and high-risk groups according to the degree of those with PDC(P=0.82,P=0.51,P=0.77,P=0.37,P=0.83,respectively).In addition,no statistically significant correlation was found between the tumor-stroma ratio and low and high risk groups(P=0.80).We found a statistically significant correlation between the presence of PDC and the presence of PDC grade 3 and T stage(P=0.001,P=0.001,respectively).It was determined that the presence of PDC and the frequency of grade 3 PDC increased with the advanced T stage.CONCLUSION No relationship was found between the presence of new pathological markers and high-low risk groups.When we examined the relationship between new and old pathological markers,only the frequency of detection of PDC and PDC grade 3 was found to be correlated with advanced T stage.
基金Funded by the Natural Science Foundation of China(No.52109168)。
文摘In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive strength.In this study,505 groups of data were collected,and a new database of compressive strength of PFGC was constructed.In order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative analysis.The five machine learning models all showed good compressive strength prediction performance on PFGC.Among them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,respectively.While R2,MSE,RMSE and MAE of random forest model(RF)are 0.97,5.17,2.27 and 1.38,respectively.The two models have high prediction accuracy and outstanding generalization ability.In order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 variables.These 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide dosage.Curing temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PFGC than ordinary Portland cement concrete.The importance of curing conditions of PFGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.
基金supported by the Priority Program SPP 1992 of the German Science Foundation(DFG)The Diversity of Exoplanets under project number 362460292.
文摘We calculate the electrical and thermal conductivity of hydrogen for a wide range of densities and temperatures by using molecular dynamics simulations informed by density functional theory.On the basis of the corresponding extended ab initio data set,we construct interpolation formulas covering the range from low-density,high-temperature to high-density,low-temperature plasmas.Our conductivity model repro-duces the well-known limits of the Spitzer and Ziman theory.We compare with available experimental data andfind very good agreement.The new conductivity model can be applied,for example,in dynamo simulations for magneticfield generation in gas giant planets,brown dwarfs,and stellar envelopes.
基金supported by the National Natural Science Foundation of China,Nos.32070735(to QL),82371321(to QL),82171270(to ZL)Public Service Platform for Artificial Intelligence Screening and Auxiliary Diagnosis for the Medical and Health Industry,Ministry of Industry and Information Technology of the People's Republic of China,No.2020-0103-3-1(to ZL)+2 种基金the Natural Science Foundation of Beijing,No.Z200016(to ZL)Beijing Talents Project,No.2018000021223ZK03(to ZL)Beijing Municipal Committee of Science and Technology,No.Z201100005620010(to ZL)。
文摘Stroke is classified as ischemic or hemorrhagic,and there are few effective treatments for either type.Immunologic mechanisms play a critical role in secondary brain injury following a stroke,which manifests as cytokine release,blood–brain barrier disruption,neuronal cell death,and ultimately behavioral impairment.Suppressing the inflammatory response has been shown to mitigate this cascade of events in experimental stroke models.However,in clinical trials of anti-inflammatory agents,longterm immunosuppression has not demonstrated significant clinical benefits for patients.This may be attributable to the dichotomous roles of inflammation in both tissue injury and repair,as well as the complex pathophysiologic inflammatory processes in stroke.Inhibiting acute harmful inflammatory responses or inducing a phenotypic shift from a pro-inflammatory to an anti-inflammatory state at specific time points after a stroke are alternative and promising therapeutic strategies.Identifying agents that can modulate inflammation requires a detailed understanding of the inflammatory processes of stroke.Furthermore,epigenetic reprogramming plays a crucial role in modulating post-stroke inflammation and can potentially be exploited for stroke management.In this review,we summarize current findings on the epigenetic regulation of the inflammatory response in stroke,focusing on key signaling pathways including nuclear factor-kappa B,Janus kinase/signal transducer and activator of transcription,and mitogen-activated protein kinase as well as inflammasome activation.We also discuss promising molecular targets for stroke treatment.The evidence to date indicates that therapeutic targeting of the epigenetic regulation of inflammation can shift the balance from inflammation-induced tissue injury to repair following stroke,leading to improved post-stroke outcomes.
文摘In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).
基金supported by National Key Research and Development Program of China(2024YFE0207200)financial support from the project AMON。
文摘As the world shift towards sustainable energy solutions,solid oxide fuel cells(SOFCs)using non-carbon fuels like ammonia and hydrogen emerge as promising pathways to produce clean energy and enhance conversion efficiency.However,current implementations encounter challenges such as nitriding effects from direct ammonia injection to the stack,overestimated benefits of anode off-gas(AOG)recirculation,and a sole focus on electrical efficiency that overlooks the thermal advantages of SOFCs.This study addresses these gaps through a comprehensive multi-objective optimization of SOFC systems fueled by ammonia and hydrogen,assessing their efficiency,fuel utilization,and heat exergy.The research translates material phenomena into mathematical constraints and quantifies the effects of control variables through systematic parameter variation.Results indicate that ammonia-fueled SOFC systems slightly outperform hydrogen,achieving an electrical efficiency of about 65% compared to 62% for hydrogen systems,although hydrogen demonstrates superior fuel utilization and exergy efficiency.Optimal AOG recirculation and NH3cracking fraction that do not compromise stack lifetime and stay in the safe operating zone of nitriding are identified.It also challenges the assumptions that a higher AOG recirculation can benefit performance,suggesting that more extensive AOG recirculation might not always enhance it.Soft sensors are provided to predict system’s performance and enable proactive adjustments to facilitate industrial applications where some parameters,such as high-temperature stack’s pressure drop,are costly or difficult to measure.This study significantly advances the practical deployment of SOFC technologies,enhancing their feasibility for sustainable energy development.
基金supported by the National Key Research and Development Program (Nos.2020YFA0210903)the National Natural Science Foundation of China (Grant Nos.22225807,21961132026,22021004)DFG within joint Sino-German project (KO 2261/11-1)。
文摘Oxidative coupling of methane (OCM) is one of the most promising approaches to produce ethylene and ethane (C_(2)-hydrocarbons) in the post-oil era.The MnO_(x)-Na_(2)WO_(4)/SiO_(2) system shows promising OCM performance,which can be further enhanced by cofed steam.However,the positive effect of steam on C_(2)-hydrocarbons selectivity practically disappears above 800℃.In the present study,we demonstrate that the use of SiC as a support for MnO_(x)-Na_(2)WO_(4) is beneficial for achieving high selectivity up to 850℃.Our sophisticated kinetic tests using feeds without and with steam revealed that the steam-mediated improvement in selectivity to C_(2)-hydrocarbons is due to the inhibition of the direct CH_(4) oxidation to carbon oxides because of the different enhancing effects of steam on the rates of CH_(4) conversion to C_(2)H_(6) and CO/CO_(2).Other descriptors of the selectivity improvement are MnO_(x) dispersion and the catalyst specific surface area.The knowledge gained herein may be useful for optimizing OCM performance through catalyst design and reactor operation.
