Geochemical and Isotopic Techniques Constraints on the Origin,Evolution,and Residence Time of Low-enthalpy Geothermal Water in Western Wugongshan,SE China

Geothermal resources are increasingly gaining attention as a competitive,clean energy source to address the energy crisis and mitigate climate change.The Wugongshan area,situated in the southeast coast geothermal belt of China,is a typical geothermal anomaly and contains abundant medium-and low-temperature geothermal resources.This study employed hydrogeochemical and isotopic techniques to explore the cyclic evolution of geothermal water in the western Wugongshan region,encompassing the recharge origin,water-rock interaction mechanisms,and residence time.The results show that the geothermal water in the western region of Wugongshan is weakly alkaline,with low enthalpy and mineralization levels.The hydrochemistry of geothermal waters is dominated by Na-HCO_(3)and Na-SO_(4),while the hydrochemistry types of cold springs are all Na-HCO_(3).The hydrochemistry types of surface waters and rain waters are NaHCO_(3)or Ca-HCO_(3).The δD and δ^(18)O values reveal that the geothermal waters are recharged by atmospheric precipitation at an altitude between 550.0 and 1218.6 m.Molar ratios of maj or solutes and isotopic compositions of^(87)Sr/^(86)Sr underscore the significant role of silicate weathering,dissolution,and cation exchange in controlling geothermal water chemistry.Additionally,geothermal waters experienced varying degrees of mixing with cold water during their ascent.Theδ^(13)C values suggest that the primary sources of carbon in the geothermal waters were biogenic and organic.Theδ^(34)S value suggests that the sulfates in geothermal water originate from sulfide minerals in the surrounding rock.Age dating using 3H and^(14)C isotopes suggests that geothermal waters have a residence time exceeding 1 kaBP and undergo a long-distance cycling process.

Defining the association between the prolonged operative time and 90-day complications in patients undergoing radical cystectomy

Objective:Radical cystectomy is a complex lengthy procedure associated with postoperative morbidity.We aimed to assess the operative time(OT)in patients undergoing radical cystectomy and its impact on 90-day postoperative complications and readmission rates.Methods:The retrospective cohort study included 296 patients undergoing radical cystectomy and urinary diversion from May 2010 to December 2018 in our institution.The OT of 369 min was set as a cutoff value between short and long OT groups.The primary outcome was 90-day postoperative complication rates.Secondary outcomes were gastrointestinal recovery time,length of hospital stay,and 90-day readmission rates.Results:The overall incidence of 90-day postoperative complications was 79.7%where 43.2%representing low-grade complications according to the ClavieneDindo classification(Grade 1 and Grade 2),and 36.5%representing high-grade complications(Grade3).Gastrointestinal tract and infectious complications are the most common complications in our data set(45.9%and 45.6%,respectively).On multivariable analysis,prolonged OT was significantly associated with odds of high-grade complications(odds ratio 2.340,95%confidence interval 1.288e4.250,p=0.005).After propensity score-matched analysis,a higher incidence of major complications was identified in the long OT group 55(51.4%)compared to 35(32.7%)in the short OT group(p=0.006).A shorter gastrointestinal tract recovery time was noticed in the short OT group(p=0.009).Prolonged OT was associated with a higher 90-day readmission rate on univariate and multivariate analyses(p<0.001,p=0.001,respectively).

Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

Long-term time series forecasting stands as a crucial research domain within the realm of automated machine learning(AutoML).At present,forecasting,whether rooted in machine learning or statistical learning,typically relies on expert input and necessitates substantial manual involvement.This manual effort spans model development,feature engineering,hyper-parameter tuning,and the intricate construction of time series models.The complexity of these tasks renders complete automation unfeasible,as they inherently demand human intervention at multiple junctures.To surmount these challenges,this article proposes leveraging Long Short-Term Memory,which is the variant of Recurrent Neural Networks,harnessing memory cells and gating mechanisms to facilitate long-term time series prediction.However,forecasting accuracy by particular neural network and traditional models can degrade significantly,when addressing long-term time-series tasks.Therefore,our research demonstrates that this innovative approach outperforms the traditional Autoregressive Integrated Moving Average(ARIMA)method in forecasting long-term univariate time series.ARIMA is a high-quality and competitive model in time series prediction,and yet it requires significant preprocessing efforts.Using multiple accuracy metrics,we have evaluated both ARIMA and proposed method on the simulated time-series data and real data in both short and long term.Furthermore,our findings indicate its superiority over alternative network architectures,including Fully Connected Neural Networks,Convolutional Neural Networks,and Nonpooling Convolutional Neural Networks.Our AutoML approach enables non-professional to attain highly accurate and effective time series forecasting,and can be widely applied to various domains,particularly in business and finance.

God Time = Planck Time: Finally Detected! And Its Relation to Hubble Time

Newton already mentioned indivisible time in Principia. In 1899, Max Planck derived a unique time period from three universal constants: G, c, and ħ, and today this is known as the Planck time. The Planck time is of the order of about 10−44 seconds while the best atomic clocks are down to 10−19 seconds. An approach has recently been outlined that puts an upper limit on the quantization of time to 10−33 seconds;this is, however, still far away from the Planck time. We demonstrate that the Planck time can easily be measured without any knowledge of any other physical constants. This is remarkable as this means we have demonstrated that the Planck time and therefore the Planck scale is real and detectable. It has taken more than 100 years to understand this. The reason for the breakthrough in Planck scale physics in recent years comes from understanding that G is a composite constant and that the true matter wavelength is the Compton wavelength rather than the de Broglie wavelength. When this is understood, the mysteries of the Planck scale can be uncovered. In this paper, we also demonstrate how to measure the number of Planck events in a gravitational mass without relying on any constants. This directly relates to a new and simple method for quantizing general relativity theory that we also will shortly discuss.

Attosecond ionization time delays in strong-field physics

Electronic processes within atoms and molecules reside on the timescale of attoseconds. Recent advances in the laserbased pump-probe interrogation techniques have made possible the temporal resolution of ultrafast electronic processes on the attosecond timescale, including photoionization and tunneling ionization. These interrogation techniques include the attosecond streak camera, the reconstruction of attosecond beating by interference of two-photon transitions, and the attoclock. While the former two are usually employed to study photoionization processes, the latter is typically used to investigate tunneling ionization. In this review, we briefly overview these timing techniques towards an attosecond temporal resolution of ionization processes in atoms and molecules under intense laser fields. In particular, we review the backpropagation method, which is a novel hybrid quantum-classical approach towards the full characterization of tunneling ionization dynamics. Continued advances in the interrogation techniques promise to pave the pathway towards the exploration of ever faster dynamical processes on an ever shorter timescale.

Improved Responses with Multitaper Spectral Analysis for Magnetotelluric Time Series Data Processing:Examples from Field Data

In order to attain good quality transfer function estimates from magnetotelluric field data(i.e.,smooth behavior and small uncertainties across all frequencies),we compare time series data processing with and without a multitaper approach for spectral estimation.There are several common ways to increase the reliability of the Fourier spectral estimation from experimental(noisy)data;for example to subdivide the experimental time series into segments,taper these segments(using single taper),perform the Fourier transform of the individual segments,and average the resulting spectra.

ESTIMATION OF AVERAGE DIFFERENTIAL ENTROPY FOR A STATIONARY ERGODIC SPACE-TIME RANDOM FIELD ON A BOUNDED AREA

In this paper,we mainly discuss a discrete estimation of the average differential entropy for a continuous time-stationary ergodic space-time random field.By estimating the probability value of a time-stationary random field in a small range,we give an entropy estimation and obtain the average entropy estimation formula in a certain bounded space region.It can be proven that the estimation of the average differential entropy converges to the theoretical value with a probability of 1.In addition,we also conducted numerical experiments for different parameters to verify the convergence result obtained in the theoretical proofs.

An analytical model to estimate the time delay to reach spontaneous ignition considering heat loss in oil reservoirs

During air injection into an oil reservoir,an oxidation reaction generates some heat to raise the reservoir temperature.When the reservoir temperature reaches an ignition temperature,spontaneous ignition occurs.There is a time delay from the injection to ignition.There are mixed results regarding the feasibility of spontaneous ignition in real-field projects and in laboratory experiments.No analytical model is available in the literature to estimate the oxidation time required to reach spontaneous ignition with heat loss.This paper discusses the feasibility of spontaneous ignition from theoretical points and experimental and field project observations.An analytical model considering heat loss is proposed.Analytical models with and without heat loss investigate the factors that affect spontaneous ignition.Based on the discussion and investigations,we find that it is more difficult for spontaneous ignition to occur in laboratory experiments than in oil reservoirs;spontaneous ignition is strongly affected by the initial reservoir temperature,oil activity,and heat loss;spontaneous ignition is only possible when the initial reservoir temperature is high,the oil oxidation rate is high,and the heat loss is low.

GmAP1d regulates flowering time under long-day photoperiods in soybean

Flowering time is important for adaptation of soybean(Glycine max)to different environments.Here,we conducted a genome-wide association study of flowering time using a panel of 1490 cultivated soybean accessions.We identified three strong signals at the qFT02-2 locus(Chr02:12037319–12238569),which were associated with flowering time in three environments:Gongzhuling,Mengcheng,and Nanchang.By analyzing linkage disequilibrium,gene expression patterns,gene annotation,and the diversity of variants,we identified an AP1 homolog as the candidate gene for the qFT02-2 locus,which we named GmAP1d.Only one nonsynonymous polymorphism existed among 1490 soybean accessions at position Chr02:12087053.Accessions carrying the Chr02:12087053-T allele flowered significantly earlier than those carrying the Chr02:12087053-A allele.Thus,we developed a cleaved amplified polymorphic sequence(CAPS)marker for the SNP at Chr02:12087053,which is suitable for marker-assisted breeding of flowering time.Knockout of GmAP1d in the‘Williams 82’background by gene editing promoted flowering under long-day conditions,confirming that GmAP1d is the causal gene for qFT02-2.An analysis of the region surrounding GmAP1d revealed that GmAP1d was artificially selected during the genetic improvement of soybean.Through stepwise selection,the proportion of modern cultivars carrying the Chr02:12087053-T allele has increased,and this allele has become nearly fixed(95%)in northern China.These findings provide a theoretical basis for better understanding the molecular regulatory mechanism of flowering time in soybean and a target gene that can be used for breeding modern soybean cultivars adapted to different latitudes.

A step to the decentralized real-time timekeeping network

The composite time scale(CTS) provides an accurate and stable time-frequency reference for modern science and technology. Conventional CTS always features a centralized network topology, which means that the CTS is accompanied by a local master clock. This largely restricts the stability and reliability of the CTS. We simulate the restriction and analyze the influence of the master clock on the CTS. It proves that the CTS's long-term stability is also positively related to that of the master clock, until the region dominated by the frequency drift of the H-maser(averaging time longer than ~10~5s).Aiming at this restriction, a real-time clock network is utilized. Based on the network, a real-time CTS referenced by a stable remote master clock is achieved. The experiment comparing two real-time CTSs referenced by a local and a remote master clock respectively reveals that under open-loop steering, the stability of the CTS is improved by referencing to a remote and more stable master clock instead of a local and less stable master clock. In this way, with the help of the proposed scheme, the CTS can be referenced to the most stable master clock within the network in real time, no matter whether it is local or remote, making democratic polycentric timekeeping possible.

Fudan multi-purpose active target time projection chamber(fMeta-TPC)for photonuclear reaction experiments

Active target time projection chambers are state-of-the-art tools in the field of low-energy nuclear physics and are particularly suitable for experiments using low-intensity radioactive ion beams or gamma rays.The Fudan multi-purpose active target time projection chamber(fMeta-TPC)with 2048 channels was developed to studyα-clustering nuclei.This study focused on the photonuclear reaction with a laser Compton scattering gamma source,particularly for the decay of the highly excitedαcluster state.The design of fMeta-TPC is described in this paper.A comprehensive evaluation of its offline performance was conducted using an ultraviolet laser and ^(241)Amαsource.The results showed that the intrinsic angular resolution of the detector was within 0.30°,and the detector had an energy resolution of 6.85%for 3.0 MeVαparticles.The gain uniformity of the detector was approximately 10%(RMS/Mean),as tested by the ^(55)Fe X-ray source.

Intelligent responsive self-assembled micro-nanocapsules:Used to delay gel gelation time

In the application of polymer gels to profile control and water shutoff,the gelation time will directly determine whether the gel can"go further"in the formation,but the most of the methods for delaying gel gelation time are complicated or have low responsiveness.There is an urgent need for an effective method for delaying gel gelation time with intelligent response.Inspired by the slow-release effect of drug capsules,this paper uses the self-assembly effect of gas-phase hydrophobic SiO_(2) in aqueous solution as a capsule to prepare an intelligent responsive self-assembled micro-nanocapsules.The capsule slowly releases the cross-linking agent under the stimulation of external conditions such as temperature and pH value,thus delaying gel gelation time.When the pH value is 2 and the concentration of gas-phase hydrophobic SiO_(2) particles is 10%,the gelation time of the capsule gel system at 30,60,90,and 120℃is12.5,13.2,15.2,and 21.1 times longer than that of the gel system without containing capsule,respectively.Compared with other methods,the yield stress of the gel without containing capsules was 78 Pa,and the yield stress after the addition of capsules was 322 Pa.The intelligent responsive self-assembled micronanocapsules prepared by gas-phase hydrophobic silica nanoparticles can not only delay the gel gelation time,but also increase the gel strength.The slow release of cross-linking agent from capsule provides an effective method for prolongating the gelation time of polymer gels.

Effect of slake durability on time dependent swelling behavior of red-bed siltstone in Sichuan Basin

The swelling behavior of red-bed rocks is a significant factor in the abnormal uplift of subgrades for high-speed railways constructed on the red stratum in the Sichuan Basin,China.The prime objective of this paper is to investigate the impact of mineralogical composition,moisture content,and overburden load on the time-dependent unconfined and oedometric swelling behavior of red-bed siltstone in the context of differences in the slake durability.Twenty samples were prepared for the swelling test,with eleven used for the unconfined swelling and slake index tests and nine for the oedometric swelling test.The temporal dependency of swelling is characterized by the viscosity coefficient of water absorption in a proposed swelling model.Results indicate that the swelling deformation of red-bed rocks is due to a combination of hydration swelling within the rock matrix and crack expansion caused by air breakage.In the unconfined swelling test,the final axial swelling strain of red-bed rocks decreases linearly with increasing slake index,while the viscosity coefficient increases exponentially with the slake index.In the oedometric swelling test,red-bed rocks with lower slake durability show greater sensitivity to lateral constraint and overburden load compared to those with higher slake durability.

Laboratory evaluation of toxicity of selected insecticides against egg and larval stages of cotton pink bollworm, Pectinophora gossypiella (Saunders) (Lepidoptera: Gelechiidae)

Background The cryptic nature of pink bollworm Pectinophora gossypiella(Saunders)larvae enables its reduced vul-nerability to insecticidal control.Further,the development of resistance against Bacillus thuringiensis(Bt)toxins posed a serious threat to transgenic cotton cultivation.This necessitated determining the critical timing of spray applications on the control effectiveness.This study assessed the influence of egg age(freshly laid vs.three-day-old)and the loca-tion of larvae(directly exposed to the insecticide residues on the boll rind vs.burrowed inside the bolls)on insecticide control efficacy.Results The results revealed a significant decrease in the ovicidal activity of tested insecticides with an increase in the age of eggs from one day old to three days old(paired t-test,P<0.05).The larvae directly exposed to the insec-ticide residues on the boll rind were more susceptible(>80%mortality)than the larvae exposed after they had bur-rowed inside the bolls(<49%mortality).The inhibitory effects of tested insecticides on developmental biology were more pronounced in the experiment on pre-larval release insecticide treatment compared with insecticide treatment given post-larval release and entry inside the bolls.Conclusion Egg age influences the insecticide susceptibility,as does the larval location,directly exposed vs bur-rowed inside the bolls.Older eggs and the larvae that had burrowed inside the green bolls of cotton were relatively less susceptible to the insecticide treatments.The toxic effects of insecticides on egg and larval stages were primar-ily ephemeral.These findings are significant for devising a comprehensive strategy for pink bollworm management on a sustainable basis.

Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series

In the context of rapid digitization in industrial environments,how effective are advanced unsupervised learning models,particularly hybrid autoencoder models,at detecting anomalies in industrial control system(ICS)datasets?This study is crucial because it addresses the challenge of identifying rare and complex anomalous patterns in the vast amounts of time series data generated by Internet of Things(IoT)devices,which can significantly improve the reliability and safety of these systems.In this paper,we propose a hybrid autoencoder model,called ConvBiLSTMAE,which combines convolutional neural network(CNN)and bidirectional long short-term memory(BiLSTM)to more effectively train complex temporal data patterns in anomaly detection.On the hardware-in-the-loopbased extended industrial control system dataset,the ConvBiLSTM-AE model demonstrated remarkable anomaly detection performance,achieving F1 scores of 0.78 and 0.41 for the first and second datasets,respectively.The results suggest that hybrid autoencoder models are not only viable,but potentially superior alternatives for unsupervised anomaly detection in complex industrial systems,offering a promising approach to improving their reliability and safety.

A Novel Method for Linear Systems of Fractional Ordinary Differential Equations with Applications to Time-Fractional PDEs

This paper presents an efficient numerical technique for solving multi-term linear systems of fractional ordinary differential equations(FODEs)which have been widely used in modeling various phenomena in engineering and science.An approximate solution of the system is sought in the formof the finite series over the Müntz polynomials.By using the collocation procedure in the time interval,one gets the linear algebraic system for the coefficient of the expansion which can be easily solved numerically by a standard procedure.This technique also serves as the basis for solving the time-fractional partial differential equations(PDEs).The modified radial basis functions are used for spatial approximation of the solution.The collocation in the solution domain transforms the equation into a system of fractional ordinary differential equations similar to the one mentioned above.Several examples have verified the performance of the proposed novel technique with high accuracy and efficiency.

Inversion of Seabed Geotechnical Properties in the Arctic Chukchi Deep Sea Basin Based on Time Domain Adaptive Search Matching Algorithm

The chirp sub-bottom profiler,for its high resolution,easy accessibility and cost-effectiveness,has been widely used in acoustic detection.In this paper,the acoustic impedance and grain size compositions were obtained based on the chirp sub-bottom profiler data collected in the Chukchi Plateau area during the 11th Arctic Expedition of China.The time-domain adaptive search matching algorithm was used and validated on our established theoretical model.The misfit between the inversion result and the theoretical model is less than 0.067%.The grain size was calculated according to the empirical relationship between the acoustic impedance and the grain size of the sediment.The average acoustic impedance of sub-seafloor strata is 2.5026×10^(6) kg(s m^(2))^(-1)and the average grain size(θvalue)of the seafloor surface sediment is 7.1498,indicating the predominant occurrence of very fine silt sediment in the study area.Comparison of the inversion results and the laboratory measurements of nearby borehole samples shows that they are in general agreement.

Quasi-anti-parity–time-symmetric single-resonator micro-optical gyroscope with Kerr nonlinearity

Parity–time(PT) and quasi-anti-parity–time(quasi-APT) symmetric optical gyroscopes have been proposed recently which enhance Sagnac frequency splitting. However, the operation of gyroscopes at the exceptional point(EP) is challenging due to strict fabrication requirements and experimental uncertainties. We propose a new quasi-APT-symmetric micro-optical gyroscope which can be operated at the EP by easily shifting the Kerr nonlinearity. A single resonator is used as the core sensitive component of the quasi-APT-symmetric optical gyroscope to reduce the size, overcome the strict structural requirements and detect small rotation rates. Moreover, the proposed scheme also has an easy readout method for the frequency splitting. As a result, the device achieves a frequency splitting 10~5 times higher than that of a classical resonant optical gyroscope with the Earth's rotation. This proposal paves the way for a new and valuable method for the engineering of micro-optical gyroscopes.

Quality-adjusted time without symptoms or toxicity analysis of haploidentical-related donor vs.identical sibling donor hematopoietic stem cell transplantation in acute myeloid leukemia

Objective:We aimed to compare the quality-adjusted time without symptoms or toxicity(Q-TWiST)in acute myeloid leukemia(AML)patients who received haploidentical-related donor(HID)and identical sibling donor(ISD)hematopoietic stem cell transplantation(HSCT).Methods:Five clinical health states were defined:toxicity(TOX),acute graft-versus-host disease(GVHD),chronic GVHD(cGVHD),time without symptoms and toxicity(TWiST)and relapse(REL).The equation used in this study was as follows:Q-TWiST=UTOX×TOX+UTWiST×TWiST+UREL×REL+UaGVHD×aGVHD+UcGVHD×cGVHD.Results:A total of 239 AML patients were enrolled.We established a mathematical model,i.e.,Q-TWiST HID HSCT>Q-TWiST ISD HSCT,to explore the range of utility coefficients satisfying the inequality.Based on the raw data,the utility coefficient is equivalent to the following inequality:10.57067UTOX-46.27733UREL+105.9374+3.388078UaGVHD-210.8198UcGVHD>0.The model showed that when UTOX,UREL,and UaGVHD were within the range of 0-1,as well as when UcGVHD was within the range of 0-0.569,the inequality Q-TWiST HID HSCT>Q-TWiST ISD HSCT was valid.According to the results of the ChiCTR1800016972 study,the median coefficients of TOX,acute GVHD(aGVHD),and cGVHD were 0.56(0.41-0.76),0.56(0.47-0.72),and 0.54(0.37-0.79),respectively.We selected a series of specific examples of the coefficients,i.e.,UTOX=0.5,UREL=0.05,UaGVHD-0.5,and UcGVHD-0.5.The Q-TWiST values of ISD and HID HSCT were 896 and 900 d,respectively(P=0.470).Conclusions:We first observed that Q-TWiST was comparable between AML patients receiving HID HSCT and those receiving ISD HSCT.

Vehicle routing optimization algorithm based on time windows and dynamic demand

To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.