Multiple factors influencing high-purity indium electrolytic refining

The effects of various contaminants in the electrolytic refinement of indium were investigated using a glow discharge mass spectrometer(GDMS).The effects of several factors such as the indium ion(In3+)concentration,the sodium chloride(NaCl)concentration,the current density,the gelatin concentration,the pH,and the electrode distance,were examined.Significant variations in impurity levels concerning gelatin concentration were observed.Both the gelatin and In3+concentration were moderately positively correlated with the Pb content.The Sb concentration was associated positively with the NaCl concentration,while the Ti concentration had an adverse correlation with the NaCl concentration.The Bi element content was positively linked to the electrode distance.As the current density increased,Cu,Pb,and Bi impurities initially rose and then eventually declined.Notably,a critical current density of 45 A·m^(-2) was identified in this behavior.

The investigation of multiple factors on elastic anisotropy of artificial shale based on the orthogonal experiment

Elastic anisotropy of shales is critical to accurate constraints for rock physical models,quantitative interpretation and hydraulic fracturing.However,the causes of elastic anisotropy of shales are very complicated,and the understanding of how multiple influence factors affect the elastic anisotropy of shales is still not clear.Hence,the orthogonal experiment,as an effective multiple factors experimental method,is adopted in this study to analyze the effect of multiple factors for shale elastic anisotropy.Three factors,clay content,organic matter(OM)content and compaction stress are selected as independent variables,the orthogonal test table L_(16)(4^(3))with four levels for each factor is adopted.According to the designed orthogonal table,sixteen artificial shales are constructed based on the cold-pressing method,and all the dry artificial shales are measured by the ultrasonic measurements.The influence of each factor on the elastic anisotropy and the sensitivity orders of three factors are obtained using the range analysis.The orders of sensitivity for selected factors follow the sequence clay content>compaction stress>OM content for velocity anisotropy parameters.The compaction mechanism of artificial shales is also discussed by the compaction factor,which are positively correlated with the velocity anisotropy parameters.The clay platelets orientation distribution function(ODF)of samples is evaluated by a theoretical model,the ODF coefficients are significantly affected by the clay content and compaction stress,and W200 are much more sensitive to these factors than W400.The results can provide a critical rock physics basis for quantitative interpretation and reservoir prediction of the low-maturity or maturity shale reservoir.

Effect of Intensive Therapy of Multiple Factors Intervention on Vascular Complications in Type 2 Diabetes

The effects of intensive versus regular therapy on incidence and progress of microalbuminuria in type 2 diabetes were compared. During a follow-up of 3 years, 96 cases of diabetes mellitus were randomized to intensive and regular therapy groups. HbA 1c goal was same in the two groups, but the goal of blood pressure (Bp) and lipid was more strict in the intensive therapy group than in the regular therapy group. There was statistically significant difference in the incidence and progression of vascular complications between the two groups. Logistic stepwise-regression analysis (odds ration, OR) showed that there was significant difference in the progression of nephropathy (OR 0.24, 95 % CI 0.12-0.76), retinopathy (OR 0.38, 95 % CI 0.16-0.88), peripheral neuropathy (OR 0.42, 95 % CI 0.22-0.86) and autonomic neuropathy (OR 0.29, 95 % CI 0.12-0.86) between the two groups (P<0.01). It was concluded that intensive blood glucose controlling could retard diabetic vascular complications. Intensive therapy of multiple factors interventions (controlling Bp, regulating blood lipid, improving microcirculation) could decrease various risk factors for diabetic vascular complications.

Study on Two-Tier EV Charging Station Recommendation Strategy under Multi-Factor Influence

This article aims to address the clustering effect caused by unorganized charging of electric vehicles by adopting a two-tier recommendation method.The electric vehicles(EVs)are classified into high-level alerts and general alerts based on their state of charge(SOC).EVs with high-level alerts have the most urgent charging needs,so the distance to charging stations is set as the highest priority for recommendations.For users with general alerts,a comprehensive EV charging station recommendation model is proposed,taking into account factors such as charging price,charging time,charging station preference,and distance to the charging station.Using real data from EV charging stations and ride-hailing vehicles in Xiamen City,Fujian Province,simulation analyses are conducted using Python for different periods of the day.The research results show that the stability of the multi-factor recommendation model in terms of service density variance,coverage rate,price cost,and distance cost outperform single-factor models.This indicates that our composite multi-factor recommendation model has significant practical value in resolving the clustering phenomenon caused by unorganized EV charging,optimizing the EV charging service system,and improving user satisfaction.

Multiple Risk Factor Clustering and Risk of Hypertension in the Mongolian Ethnic Population of China

Objective To evaluate whether the clustering of risk factors, both environmental and genetic, increases the risk of essential hypertension （EH） and the accumulation of risk factors influences the blood pressure level in normotensives. Methods On the basis of a prevalence survey, 501 subjects of Mongolian ethnicity （243 hypertensives and 258 normotensives） who were not related to each other were selected to conduct a case-control study. All subjects were interviewed with questionnaires and their blood specimens were collected. Renin gene insertion/deletion （I/D） polymorphism, a new genetic marker, was genotyped with PCR and polyacrylamide gel electrophoresis. Results Overweight, alcohol consumption, and renin gene I/D polymorphism were significant risk factors of EH （P〈0.05）. The odds ratios （OR） for the number of risk factors were 2.39 （95%CI： 0.98-6.74） for one risk factor, 5.03 （95%CI： 2.06-14.18） for two, and 6.09 （95%CI： 1.85-22.38） for three respectively after adjusting for age and sex. In normotensives, age- and sex-adjusted mean blood pressures increased with more accumulation of risk factors. However, there were no significant differences among the different blood pressure levels according to the number of risk factors （P〉0.05）. Conclusion Overweight, alcohol consumption, and renin gene I/D polymorphism are risk factors of EH in the Mongolian ethnic population of China. The accumulation of the risk factors causes a sharp increase of the risk of EH.

Erectile dysfunction: on the efficacy of a phosphodiesterase inhibitor in patients with multiple risk factors

1 Introduction With the 1998 introduction of sildenafil (Viagra), the first available oral phosphodiesterase inhibitor, there

A Collaboration Network Model with Multiple Evolving Factors

To describe the empirical data of collaboration networks, several evolving mechanisms have been proposed, which usually introduce different dynamics factors controlling the network growth. These models can reasonably reproduce the empirical degree distributions for a number of we11-studied real-world collaboration networks. On the basis of the previous studies, in this work we propose a collaboration network model in which the network growth is simultaneously controlled by three factors, including partial preferential attachment, partial random attachment and network growth speed. By using a rate equation method, we obtain an analytical formula for the act degree distribution. We discuss the dependence of the act degree distribution on these different dynamics factors. By fitting to the empirical data of two typical collaboration networks, we can extract the respective contributions of these dynamics factors to the evolution of each networks.

Dominant early heading without yield drag in a sister-line BC breeding progeny DEH_229 is controlled by multiple genetic factors with maineffect loci

Dominant early heading(DEH)in rice(Oryza sativa L.)is of interest in both breeding and genetics.The genetic mechanisms underlying DEH have remained largely unclear.We have developed a near-isogenic DEH line without yield drag named DEH_229 by sister-line backcross(BC)breeding with MH63,a restorer,as the genetic background.We conducted a pilot genetic investigation under both short-day(SD)and long-day(LD)conditions.The DEH line harbored only 1.06%variation in the genome sequence relative to MH63.The variants were distributed throughout the genome.Using QTL mapping by sequencing(QTL-seq)on an F_(2) population derived from a cross of MH63×DEH_229,57 loci were detected under the SD condition.Joint mapping employing a genome-wide association study with accessions from the 3000 rice genome sequencing project(3K-RG),reduced the number of QTL by 43.9%.Using Rice Functional Genomics&Breeding(RFGB)database,the number of SNP cluster regions within the QTL regions reduced by 27.3%.Further comparison of the genome variation between DEH_229 and MH63 in addition to gene annotation information revealed a new DEH allele of DTH3 with multiple variable sites as a possible major factor underlying the early-heading phenotype of DEH_229.An InDel marker,ZMEH_1,was designed based on the variation between DEH_229 and MH63 within this region.It accounted for 86.0%of heading date variation under both SD and LD conditions in 109 randomly chosen progeny derived from extreme lines of the MH63×DEH_229 population.This study reveals the genetic complexity of DEH in the near-isogenic line and may provide useful material and marker information for plant molecular breeding.

Stability behavior of the Lanxi ancient flood control levee after reinforcement with upside-down hanging wells and grouting curtain

The stability of the ancient flood control levees is mainly influenced by water level fluctuations, groundwater concentration and rainfalls. This paper takes the Lanxi ancient levee as a research object to study the evolution laws of its seepage, displacement and stability before and after reinforcement with the upside-down hanging wells and grouting curtain through numerical simulation methods combined with experiments and observations. The study results indicate that the filled soil is less affected by water level fluctuations and groundwater concentration after reinforcement. A high groundwater level is detrimental to the levee's long-term stability, and the drainage issues need to be fully considered. The deformation of the reinforced levee is effectively controlled since the fill deformation is mainly borne by the upside-down hanging wells. The safety factors of the levee before reinforcement vary significantly with the water level. The minimum value of the safety factors is 0.886 during the water level decreasing period, indicating a very high risk of the instability. While it reached 1.478 after reinforcement, the stability of the ancient levee is improved by a large margin.

Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Chlorine-anion doping induced multi-factor optimization in perovskites for boosting intrinsic oxygen evolution

The oxygen evolution reaction(OER) plays a crucial role in many electrochemical energy technologies,and creating multiple beneficial factors for OER catalysis is desirable for achieving high catalytic efficiency.Here,we highlight a new halogen-chlorine(Cl)-anion doping strategy to boost the OER activity of perovskite oxides.As a proof-of-concept,proper Cl doping at the oxygen site of LaFeO3(LFO) perovskite can induce multiple favorable characteristics for catalyzing the OER,including rich oxygen vacancies,increased electrical conductivity and enhanced Fe-O covalency.Benefiting from these factors,the LaFeO2.9-δCl0.1(LFOCl) perovskite displays significant intrinsic activity enhancement by a factor of around three relative to its parent LFO.This work uncovers the effect of Cl-anion doping in perovskites on promoting OER performance and paves a new way to design highly efficient electrocatalysts.

Management of extramedullary plasmacytoma: Role of radiotherapy and prognostic factor analysis in 55 patients

Objective： To investigate potential prognostic factors affecting patient outcomes and to evaluate the optimal methods and effects of radiotherapy（RT） in the management of extramedullary plasmacytoma（EMP）.Methods： Data from 55 patients with EMP between November 1999 and August 2015 were collected. The median age was 51（range, 22–77） years. The median tumor size was 3.5（range, 1.0–15.0） cm. The median applied dose was 50.0（range, 30.0–70.0） Gy. Thirty-nine patients（70.9%） presented with disease in the head or neck region. Twelve patients received RT alone, 9 received surgery（S） alone, 3 received chemotherapy（CT） alone, and 3 patients did not receive any treatment. Combination therapies were applied in 28 patients.Results：The median follow-up duration was 56 months.The 5-year local recurrence-free survival（LRFS）,multiple myeloma-free survival（MMFS）,progression-free survival（PFS）and overall survival（OS）rates were 79.8%,78.6%,65.2% and 76.0%,respectively.Univariate analysis revealed that RT was a favourable factor for all examined endpoints.Furthermore,head and neck EMPs were associated with superior LRFS,MMFS and PFS.Tumor size〈4 cm was associated with superior MMFS,PFS and OS;serum M protein negativity was associated with superior MMFS and PFS;age≥50 years and local recurrence were associated with poor MMFS.The dose≥45 Gy group exhibited superior 5-year LRFS,MMFS and PFS rates（94.7%,94.4%,90.0%,respectively）,while the corresponding values for the dose〈45 Gy group were 62.5%（P=0.008）,53.3%（P=0.036）and 41.7%（P〈0.001）.Conclusions：Involved-site RT of at least 45 Gy should be considered for EMP.Furthermore,patients with head and neck EMP,tumor size〈4 cm,age〈50 years and serum M protein negativity had better outcomes.

Numerical study on the wave pattern characteristic of air layer in cavity and the effects of multiple influence factors

Air-layer drag reduction (ALDR) technology for ship energy saving is getting more and more attention in recent years because of the outstanding drag reduction effect. In order to promote practical application, it is necessary to fully understand the two phase flow characteristics of the air layer. Recent experimental studies have shown that the surface of the air layer presents wave pattern, which has an important influence on its damage risk. However, it is difficult to measure the wave pattern quantificationally due to the interference of equipment. The main goal of the present paper is to investigate the wave pattern characteristic of air layer in cavity using numerical simulation method. On this basis, the effect of flow and geometric influence factors are discussed to understand the key control conditions. A computational fluid dynamics (CFD) numerical method based on Reynolds averaged Navier-Stokes (RANS) equations and volume of fluid (VOF) interface capturing method is established, and has been successfully applied in the simulation of air layer wave pattern. Both 2-D and 3-D simulations are carried out, aiming at analyzing air-water interface flow and vortex flow directly. Based on the simulation results, several important conclusions about the mechanism of air layer wave pattern can be obtained. Firstly, it is found to be an inherent characteristic that the wave height of the upstream air layer is higher than that of the downstream. The extremely high wave peak is easy to contact with the flat plate, leading to the breakup of air layer and a “central blank area” phenomenon. With the help of flow analysis, it is found that this characteristic is mainly caused by the strong counterclockwise vortex behind the bow wedge block. Secondly, the air layer stability is reduced with the increase of water flow velocity by affecting the wave height. There is a saturation point of air flow rate to reach maximum thickness of air layer. Thirdly, cavity configuration has obvious influence on air layer stability by influencing vortex flow field. The increase of cavity depth and width can aggravate the unsteady and nonlinear characteristics of air layer. Finally, comprehensive design criteria are concluded from the view of geometrical configuration and flow conditions. A cavity with the moderate depth and width can avoid the upstream damage of air layer. Longitudinal position of air nozzles should be set within the low pressure zone behind the wedge block for stable air layer formation.

A Behavioral Authentication Method for Mobile Based on Browsing Behaviors

The passwords for unlocking the mobile devices are relatively simple,easier to be stolen,which causes serious potential security problems.An important research direction of identity authentication is to establish user behavior models to authenticate users.In this paper,a mobile terminal APP browsing behavioral authentication system architecture which synthesizes multiple factors is designed.This architecture is suitable for users using the mobile terminal APP in the daily life.The architecture includes data acquisition,data processing,feature extraction,and sub model training.We can use this architecture for continuous authentication when the user uses APP at the mobile terminal.

Planning Method of Ecological Embedded Industrial Parks

Exploration of the gentle slopes of low mountains and hills has already become a new topic in the development of urban land resources in hilly areas. For the high ecological sensitivity, tremendous cost of urban construction, as well as complicate utilization technology, planning and design of gentle slopes of low mountains and hills are faced with serious challenges. This paper took the planning of Yidu High-tech Industrial Park for example, to explore the design concepts and rational methods of planning "ecological embedded" industrial parks in hilly areas.

Multiple Fading Factors Kalman Filter for SINS Static Alignment Application

To solve the problem that the standard Kalman filter cannot give the optimal solution when the system model and stochastic information are unknown accurately, single fading factor Kalman filter is suitable for simple systems. But for complex systems with multi-variable, it may not be sufficient to use single fading factor as a multiplier for the covariance matrices. In this paper, a new multiple fading factors Kalman filtering algorithm is presented. By calculating the unbiased estimate of the innovation sequence covariance using fenestration, the fading factor matrix is obtained. Adjusting the covariance matrix of prediction error Pk｜k-1 using fading factor matrix, the algorithm provides different rates of fading for different filter channels. The proposed algorithm is applied to strapdown inertial navigation system （SINS） initial alignment, and simulation and experimental results demonstrate that, the alignment accuracy can be upgraded dramatically when the actual system noise characteristics are different from the pre-set values. The new algorithm is less sensitive to uncertainty noise and has better estimation effect of the parameters. Therefore, it is of significant value in practical applications.

Online Identification of Power Battery Parameters for Electric Vehicles Using a Decoupling Multiple Forgetting Factors Recursive Least Squares Method

Li-ion batteries are widely used in electric vehicles(EVs).However,the accuracy of online SOC estimation is still challenging due to the time-varying parameters in batteries.This paper proposes a decoupling multiple forgetting factors recursive least squares method(DMFFRLS)for EV battery parameter identification.The errors caused by the different parameters are separated and each parameter is tracked independently taking into account the different physical characteristics of the battery parameters.The Thevenin equivalent circuit model(ECM)is employed considering the complexity of battery management system(BMS)on the basis of comparative analysis of several common battery ECMs.In addition,decoupling multiple forgetting factors are used to update the covariance due to different degrees of error of each parameter in the identification process.Numerous experiments are employed to verify the proposed DMFFRLS method.The parameters for commonly used LiFePO4(LFP),Li(NiCoMn)O2(NCM)battery cells and battery packs are identified based on the proposed DMFFRLS method and three conventional methods.The experimental results show that the error of the DMFFRLS method is less than 15 mV,which is significantly lower than the conventional methods.The proposed DMFFRLS shows good performance for parameter identification on different kind of batteries,and provides a basis for state of charge(SOC)estimation and BMS design of EVs.

Robust cubature Kalman filter method for the nonlinear alignment of SINS

Nonlinear initial alignment is a significant research topic for strapdown inertial navigation system(SINS).Cubature Kalman filter(CKF)is a popular tool for nonlinear initial alignment.Standard CKF assumes that the statics of the observation noise are pre-given before the filtering process.Therefore,any unpredicted outliers in observation noise will decrease the stability of the filter.In view of this problem,improved CKF method with robustness is proposed.Multiple fading factors are introduced to rescale the observation noise covariance.Then the update stage of the filter can be autonomously tuned,and if there are outliers exist in the observations,the update should be less weighted.Under the Gaussian assumption of KF,the Mahalanobis distance of the innovation vector is supposed to be Chi-square distributed.Therefore a judging index based on Chi-square test is designed to detect the noise outliers,determining whether the fading tune are required.The proposed method is applied in the nonlinear alignment of SINS,and vehicle experiment proves the effective of the proposed method.

Hydrocarbon accumulation principles in troughs within faulted depressions and their significance in exploration

Previously,troughs in continental faulted depressions were usually considered as a zone of hydrocarbon generation and expulsion rather than a zone for hydrocarbon accumulation.If they were confirmed to be the source kitchen,the possibility that they could constitute potential plays would be overlooked in the subsequent exploration program.Based on the hydrocarbon exploration practice of the Jizhong Depression and the Erlian Basin in the past several years,this paper discusses a new understanding that reservoir distribution is controlled by multiple factors and lithological accumulations are more likely to form in trough areas.It further documents the three main factors controlling the formation of large lithological hydrocarbon accumulations in trough areas.The paper also discusses the new concept that structural and lithological accumulations not only co-exist but also complement each other.We propose that fan-delta fronts on inverted steep slopes in troughs,delta fronts and sublacustrine fans on gentle slopes,channel sands along toes of fault scarps are favorable locations for discovery of new oil accumulations.The application of this concept has led to the discovery of several hundreds of million tonnes of oil in place in trough areas in the Jizhong Depression and the Erlian Basin.

A Novel Hybrid Intelligent Prediction Model for Valley Deformation: A Case Study in Xiluodu Reservoir Region, China

The narrowing deformation of reservoir valley during the initial operation period threatens the long-term safety of the dam,and an accurate prediction of valley deformation(VD)remains a challenging part of risk mitigation.In order to enhance the accuracy of VD prediction,a novel hybrid model combining Ensemble empirical mode decomposition based interval threshold denoising(EEMD-ITD),Differential evolutions—Shuffled frog leaping algorithm(DE-SFLA)and Least squares support vector machine(LSSVM)is proposed.The non-stationary VD series is firstly decomposed into several stationary subseries by EEMD;then,ITD is applied for redundant information denoising on special sub-series,and the denoised deformation is divided into the trend and periodic deformation components.Meanwhile,several relevant triggering factors affecting the VD are considered,from which the input features are extracted by Grey relational analysis(GRA).After that,DE-SFLA-LSSVM is separately performed to predict the trend and periodic deformation with the optimal inputs.Ultimately,the two individual forecast components are reconstructed to obtain the final predicted values.Two VD series monitored in Xiluodu reservoir region are utilized to verify the proposed model.The results demonstrate that:(1)Compared with Discrete wavelet transform(DWT),better denoising performance can be achieved by EEMD-ITD;(2)Using GRA to screen the optimal input features can effectively quantify the deformation response relationship to the triggering factors,and reduce the model complexity;(3)The proposed hybrid model in this study displays superior performance on some compared models(e.g.,LSSVM,Backward Propagation neural network(BPNN),and DE-SFLA-BPNN)in terms of forecast accuracy.