Storage time affects the level and diagnostic efficacy of plasma biomarkers for neurodegenerative diseases

Several promising plasma biomarker proteins,such as amyloid-β(Aβ),tau,neurofilament light chain,and glial fibrillary acidic protein,are widely used for the diagnosis of neurodegenerative diseases.However,little is known about the long-term stability of these biomarker proteins in plasma samples stored at-80°C.We aimed to explore how storage time would affect the diagnostic accuracy of these biomarkers using a large cohort.Plasma samples from 229 cognitively unimpaired individuals,encompassing healthy controls and those experiencing subjective cognitive decline,as well as 99 patients with cognitive impairment,comprising those with mild cognitive impairment and dementia,were acquired from the Sino Longitudinal Study on Cognitive Decline project.These samples were stored at-80°C for up to 6 years before being used in this study.Our results showed that plasma levels of Aβ42,Aβ40,neurofilament light chain,and glial fibrillary acidic protein were not significantly correlated with sample storage time.However,the level of total tau showed a negative correlation with sample storage time.Notably,in individuals without cognitive impairment,plasma levels of total protein and tau phosphorylated protein threonine 181(p-tau181)also showed a negative correlation with sample storage time.This was not observed in individuals with cognitive impairment.Consequently,we speculate that the diagnostic accuracy of plasma p-tau181 and the p-tau181 to total tau ratio may be influenced by sample storage time.Therefore,caution is advised when using these plasma biomarkers for the identification of neurodegenerative diseases,such as Alzheimer's disease.Furthermore,in cohort studies,it is important to consider the impact of storage time on the overall results.

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.

Effect of aspect ratio of elliptical stirred vessel on mixing time and flow field characteristics in the absence of baffles

Elliptical tanks were used as an alternative to circular tanks in order to improve mixing efficiency and reduce mixing time in unbaffled stirred tanks(USTs). Five different aspect ratios of elliptical vessels were designed to compare their mixing time and flow field. Computational fluid dynamics(CFD) simulations were performed using the k–ε model to calculate the mixing time and simulate turbulent flow field features, such as streamline shape, velocity distribution, vortex core region distribution, and turbulent kinetic energy(TKE) transfer. Visualization was also carried out to track the tinctorial evolution of the liquid phase. Results reveal that elliptical stirred tanks can significantly improve mixing performance in USTs. Specifically, the mixing time at an aspect ratio of 2.00 is only 45.3% of the one of a circular stirred tank. Furthermore, the secondary flow is strengthened and the vortex core region increases with the increase of aspect ratio. The axial velocity is more sensitive to the aspect ratio than the circumferential and radial velocity. Additionally, the TKE transfer in elliptical vessels is altered. These findings suggest that elliptical vessels offer a promising alternative to circular vessels for enhancing mixing performance in USTs.

Electrothermal Model Based Remaining Charging Time Prediction of Lithium-Ion Batteries against Wide Temperature Range

Battery remaining charging time(RCT)prediction can facilitate charging management and alleviate mileage anxiety for electric vehicles(EVs).Also,it is of great significance to improve EV users’experience.However,the RCT for a lithiumion battery pack in EVs changes with temperature and other battery parameters.This study proposes an electrothermal model-based method to accurately predict battery RCT.Firstly,a characteristic battery cell is adopted to represent the battery pack,thus an equivalent circuit model(ECM)of the characteristic battery cell is established to describe the electrical behaviors of a battery pack.Secondly,an equivalent thermal model(ETM)of the battery pack is developed by considering the influence of ambient temperature,thermal management,and battery connectors in the battery pack to calculate the temperature which is then fed back to the ECM to realize electrothermal coupling.Finally,the RCT prediction method is proposed based on the electrothermal model and validated in the wide temperature range from-20℃to 45℃.The experimental results show that the prediction error of the RCT in the whole temperature range is less than 1.5%.

Effects of Serum Concentration, Synchronization Time and Confluence on the Cell-Cycle Synchronization Efficiency of Goat Fibroblasts

This study aims to evaluate the effect of serum concentration, synchronization time, and confluence degree on the synchronisation efficiency of goat fibroblast cycle. The results indicated that there was no difference in the percentage of nucleated fibroblasts in the G0/G1 stage between serum concentrations of 0.3% and 0.4% (83.89% and 82.69%, respectively, P > 0.05) as well as between serum concentrations of 0.2% and 0.5% (76.95% and 75.46%, respectively, P > 0.05). The percentage of nucleated fibroblasts in the G0/G1 stage was highest at the concentration of 0.3% and lowest in the control group (83.89% vs. 62.67%, P 0.05). The beneficial effect of high confluence was confirmed by the large percentage of nucleated fibroblasts at the G0/G1 stage. The 60% confluency was significantly lower than the 80% and 100% confluency (73.44%, 86.63%, and 87.17%, respectively, P < 0.05). The results indicate that the goat fibroblast cycle synchronization is the most effective at the serum concentration of 0.3%, 72 hours of synchronization and 100% confluency.

The Emergence of Time from Quantum Information Dynamics

This paper presents a novel framework for understanding time as an emergent phenomenon arising from quantum information dynamics. We propose that the flow of time and its directional arrow are intrinsically linked to the growth of quantum complexity and the evolution of entanglement entropy in physical systems. By integrating principles from quantum mechanics, information theory, and holography, we develop a comprehensive theory that explains how time can emerge from timeless quantum processes. Our approach unifies concepts from quantum mechanics, general relativity, and thermodynamics, providing new perspectives on longstanding puzzles such as the black hole information paradox and the arrow of time. We derive modified Friedmann equations that incorporate quantum information measures, offering novel insights into cosmic evolution and the nature of dark energy. The paper presents a series of experimental proposals to test key aspects of this theory, ranging from quantum simulations to cosmological observations. Our framework suggests a deeply information-theoretic view of the universe, challenging our understanding of the nature of reality and opening new avenues for technological applications in quantum computing and sensing. This work contributes to the ongoing quest for a unified theory of quantum gravity and information, potentially with far-reaching implications for our understanding of space, time, and the fundamental structure of the cosmos.

Seasonal Characteristics of Forecasting Uncertainties in Surface PM_(2.5)Concentration Associated with Forecast Lead Time over the Beijing-Tianjin-Hebei Region

Forecasting uncertainties among meteorological fields have long been recognized as the main limitation on the accuracy and predictability of air quality forecasts.However,the particular impact of meteorological forecasting uncertainties on air quality forecasts specific to different seasons is still not well known.In this study,a series of forecasts with different forecast lead times for January,April,July,and October of 2018 are conducted over the Beijing-Tianjin-Hebei(BTH)region and the impacts of meteorological forecasting uncertainties on surface PM_(2.5)concentration forecasts with each lead time are investigated.With increased lead time,the forecasted PM_(2.5)concentrations significantly change and demonstrate obvious seasonal variations.In general,the forecasting uncertainties in monthly mean surface PM_(2.5)concentrations in the BTH region due to lead time are the largest(80%)in spring,followed by autumn(~50%),summer(~40%),and winter(20%).In winter,the forecasting uncertainties in total surface PM_(2.5)mass due to lead time are mainly due to the uncertainties in PBL heights and hence the PBL mixing of anthropogenic primary particles.In spring,the forecasting uncertainties are mainly from the impacts of lead time on lower-tropospheric northwesterly winds,thereby further enhancing the condensation production of anthropogenic secondary particles by the long-range transport of natural dust.In summer,the forecasting uncertainties result mainly from the decrease in dry and wet deposition rates,which are associated with the reduction of near-surface wind speed and precipitation rate.In autumn,the forecasting uncertainties arise mainly from the change in the transport of remote natural dust and anthropogenic particles,which is associated with changes in the large-scale circulation.

The time and frequency system of the Tianma 65 m radio telescope

A time and frequency system is a critical component of Very Long Baseline Interferometry(VLBI)stations,providing stable and reliable standards that directly impact data processing quality.At the Tianma 65 m radio telescope(TMRT),this system has been meticulously designed to ensure long-term reliability and high performance.It incorporates high-performance hydrogen atomic clocks,high-precision time standards,automatic signal switching,and robust system software.This comprehensive approach has enabled the system to achieve long-term reliable operation,successfully supporting both major national engineering tasks and daily scientific observations.The effectiveness of the system is evidenced by its consistent delivery of the precision and stability required for radio astronomy.This article provides an in-depth exploration of the design and operation of the time and frequency system at the Tianma 65 m telescope,examining various aspects of its architecture,implementation,and performance.By sharing these insights,we aim to contribute knowledge that could benefit similar systems at other VLBI stations,greatly advancing radio astronomy infrastructure.

Intrinsic Spin Angular Momentum of Electron Relation to the Discrete Indivisible Quantum of Time Kshana or Moment

The frequency of any periodic event can be defined in terms of units of Time. Planck constructed a unit of time called the Plank time from other physical constants. Vyasa defined a natural unit of time, kshana, or moment based on the motion of a fundamental particle. It is the time taken by an elementary particle, to change its direction from east to north. According to Vyasa, kshana is discrete, exceedingly small, indivisible, and is a constant time quantum. When the intrinsic spin angular momentum of an electron was related to the angular momentum of a simple thin circular plate, spherical shell, and solid sphere model of an electron, we found that the value of kshana in seconds was equal to ten to a power of minus twenty-one second. The disc model for the spinning electron provides an accurate value of the number of kshanas per second as determined previously and compared with other spinning models of electrons. These results indicate that the disk-like model of spinning electrons is the correct model for electrons. Vyasa’s definition of kshana opens the possibility of a new foundation for the theory of physical time, and perspectives in theoretical and philosophical research.

Prediction of three-dimensional ocean temperature in the South China Sea based on time series gridded data and a dynamic spatiotemporal graph neural network

Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Deep Learning for Financial Time Series Prediction:A State-of-the-Art Review of Standalone and HybridModels

Financial time series prediction,whether for classification or regression,has been a heated research topic over the last decade.While traditional machine learning algorithms have experienced mediocre results,deep learning has largely contributed to the elevation of the prediction performance.Currently,the most up-to-date review of advanced machine learning techniques for financial time series prediction is still lacking,making it challenging for finance domain experts and relevant practitioners to determine which model potentially performs better,what techniques and components are involved,and how themodel can be designed and implemented.This review article provides an overview of techniques,components and frameworks for financial time series prediction,with an emphasis on state-of-the-art deep learning models in the literature from2015 to 2023,including standalonemodels like convolutional neural networks(CNN)that are capable of extracting spatial dependencies within data,and long short-term memory(LSTM)that is designed for handling temporal dependencies;and hybrid models integrating CNN,LSTM,attention mechanism(AM)and other techniques.For illustration and comparison purposes,models proposed in recent studies are mapped to relevant elements of a generalized framework comprised of input,output,feature extraction,prediction,and related processes.Among the state-of-the-artmodels,hybrid models like CNNLSTMand CNN-LSTM-AM in general have been reported superior in performance to stand-alone models like the CNN-only model.Some remaining challenges have been discussed,including non-friendliness for finance domain experts,delayed prediction,domain knowledge negligence,lack of standards,and inability of real-time and highfrequency predictions.The principal contributions of this paper are to provide a one-stop guide for both academia and industry to review,compare and summarize technologies and recent advances in this area,to facilitate smooth and informed implementation,and to highlight future research directions.

Effects of Standing Time during Pretreatment on the Nitrite Concentration Detected by Spectrophotometric Method

Food safety problems caused by excessive nitrite addition have been frequently reported and the detection of nitrite in food is particularly important. The standing time during the pretreatment of primary sample has a great influence on the concentration of nitrite tested by spectrophotometric method. In this context, three kinds of food samples are prepared, including canned mustard, canned fish and home-made pickled water. A series of standing times are placed during the sample pretreatments and the corresponding nitrite contents in these samples are detected by spectrophotometric method based on N-ethylenediamine dihydrochloride. This study aims to find out a reasonable standing time during the pretreatment of food sample, providing influence factor for precise detection of nitrite.

Research on the Damping Mechanism of Time-Delay Coupled Negative Stiffness Dynamic Absorber in Nonlinear Vibration Damping System

A study was conducted on the effect of time delay and structural parameters on the vibration reduction of a time delayed coupled negative stiffness dynamic absorber in nonlinear vibration reduction systems. Taking dynamic absorbers with different structural and control parameters as examples, the effects of third-order nonlinear coefficients, time-delay control parameters, and negative stiffness coefficients on reducing the replication of the main system were discussed. The nonlinear dynamic absorber has a very good vibration reduction effect at the resonance point of the main system and a nearby area, and when 1 increases to a certain level, the stable region of the system continues to increase. The amplitude curve of the main system of a nonlinear dynamic absorber will generate Hop bifurcation and saddle node bifurcation in the region far from the resonance point, resulting in almost periodic motion and jumping phenomena in the system. For nonlinear dynamic absorbers with determined structural parameters, time-delay feedback control can be adopted to control the amplitude of the main system. For different negative stiffness coefficients, there exists a minimum damping point for the amplitude of the main system under the determined system structural parameters and time-delay feedback control parameters.

Dependence of Lower Molding Temperature Limit and Molding Time on Molding Mechanism in Dental Thermoforming

Effectiveness and safety of a sports mouthguard depend on its thickness and material, and the thermoforming process affects these. The purpose of this study was to clarify the effects of differences in molding mechanisms on the lower molding temperature limit and molding time in dental thermoforming. Ethylene vinyl acetate resin mouthguard sheet and two thermoforming machines;vacuum blower molding machine and vacuum ejector/pressure molding machine were used. The molding pressures for suction molding were −0.018 MPa for vacuum blower molding and −0.090 MPa for vacuum ejector molding, and for pressure molding was set to 0.090 MPa or 0.450 MPa. Based on the manufacturer’s standard molding temperature of 95˚C, the molding temperature was lowered in 2.5˚C increments to determine the lower molding temperature limit at which no molding defects occurred. In order to investigate the difference in molding time depending on the molding mechanism, the duration of molding pressure was adjusted in each molding machine, and the molding time required to obtain a sample without molding defects was measured. The molding time of each molding machine were compared using one-way analysis of variance. The lower molding temperature limit was 90.0˚C for the vacuum blower machine, 77.5˚C for the vacuum ejector machine, 77.5˚C for the pressure molding machine at 0.090 MPa, and 67.5˚C for the pressure molding machine at 0.45 MPa. The lower molding temperature limit was higher for lower absolute values of molding pressure. The molding time was shorter for pressure molding than for suction molding. Significant differences were observed between all conditions except between the pressure molding machine at 0.090 MPa and 0.45 MPa (P < 0.01). A comparison of the differences in lower molding temperature limit and molding time due to molding mechanisms in dental thermoforming revealed that the lower molding temperature limit depends on the molding pressure and that the molding time is longer for suction molding than for pressure molding.

Linking Perceived Risk of Public Health Emergency to Psychological Distress among Chinese College Students: The Chain Mediation Role of Balanced Time Perspective and Negative Coping Styles

Background:With public health emergencies(PHE)worldwide increasing,the perceived risk of PHE has been one of the critical factors influencing college students’psychological distress.However,the mechanisms by which the perceived risk of PHE affects college students’psychological distress are not clear.The study’s purpose was to investigate the mediation roles of deviation from a balanced time perspective(DBTP)and negative coping styles between the perceived risk of PHE and psychological distress.Methods:A convenience sampling method was used to survey 1054 Chinese college students with self-reporting.Data was collected using the Public Risk Perception Scale(PRPS),the Zimbardo Time Perspective Inventory(ZTPI),the Simplified Coping Style Questionnaire(SCSQ),the PHE Anxiety Scale,and the Chinese version of the Patient Health Questionnaire(PHQ).The associations between the perceived risk of PHE,DBTP,negative coping styles,and psychological distress were clarified using the correlation analysis.Additionally,the mediating roles of DBTP and negative coping styles between the perceived risk of PHE and psychological distress were investigated using a structural equation model.Results:The findings revealed low to moderate correlations between the variables studied.Students’perceived risk of PHE was a positive predictor of their psychological distress(b=0.219,p<0.01).DBTP and negative coping styles played chain mediation roles between them with the effect being 0.009 and a 95%Boot CI of[0.003,0.023].This chain mediation model had an excellent fit index(χ^(2)/df=4.732,CFI=0.973,TLI=0.930,RMSEA=0.048,SRMR=0.047).Conclusion:These findings showed how the perceived risk of PHE affected college students’psychological distress.Specifically,these results suggested that improving students’mental ability to switch effectively among different time perspectives depending on task features and situational considerations and reducing their negative coping styles might be effective ways to promote their mental health.

Effects of the Ice Bath Time after Heat Shock and the Incubation Time on the Efficiency of Chemical Transformation Method

[Objective] The aim of the research was to study the effect of the ice bath time after heat shock and the incubation time on the transformation efficacy,and to establish a simple and quick transformation method.[Method]Competent cells were prepared with two buffer solutions;with the ice bath time after heat shock and the recovery time as the variables,the relationship between these two factors and transformation efficacy was studied.[Result]The transformation efficacy was the best when the ice bath time was 2 min and the recovery time was 30 or 40 min;when the ice bath time and the recovery time was 0 min,a certain amount of transformants still could be obtained.[Conclusion]The ice bath time after heat shock and the recovery time had certain impact on transformation efficacy,but they were not the decisive factors.Therefore,in the general transformation experiment,these two steps could be omitted.

Research on measuring time constant of NANMAC thermocouple

The theory for measuring the time constant of thermocouple was introduced, and the method for measuring the time constant of NANMAC thermocouple by using dynamic calibration system of transient surface temperature sensor was proposed. In this system, static and dynamic calibrations were conducted for infrared detectors and thermocouples, and then both temperature-time curves were obtained. Since the frequency response of infrared detector is superior to that of calibrat- ed thermocouple, the values measured by infrared detectors are taken as true values. Through dividing the values measured with thermocouples by those with infrared detectors, a normalized curve was obtained, based on which the time constant of thermocouple was measured. With this method, the experiments were carried out with NANMAC thermocouple to obtain its time constant. The results show that the method for measuring the time constant is feasible and the dynamic calibration of thermocouples can be achieved at microsecond and millisecond level. This research has a certain reference value for research and application of NANMAC thermocouple temperature sensor.

Diurnal activity rhythms and time budgets of captive Qinling golden takin(Budorcas taxicolor bedfordi) in the Qinling Mountains,Shaanxi,China

In July 2006, the diurnal activity rhythms of 13 heads of captive Qinling golden takin were observed in Shaanxi Provincial Centre for the Breeding and Conservation of Rare Wildlife （SPCBCRW） at daylight （from 9：00 am to 4：00 pm in July）. The behavioral ethnogram was identified through observation at the sampling site, with the behaviors of golden takin recorded at 5 min interval using instantaneous scannable sampling method. The results indicated that the resting of golden takin took an important part in the daylight activities. Meanwhile, drinking and urinating and defecating were 1.92 and 0.54 and 0.92 times per head per day. Ambient temperature had a strong effect on the diurnal activity rhythms of golden takin. The diurnal activity rhymes were affected by ages of the animals effectively, which was expressed through differentiation of the time budgets. Moreover, different individuals in the same population showed some non-synchronously activity rhythms.