Role of intelligent/interactive qualitative and quantitative analysisthree-dimensional estimated model in donor-recipient size mismatch following deceased donor liver transplantation

BACKGROUND Donor-recipient size mismatch(DRSM)is considered a crucial factor for poor outcomes in liver transplantation(LT)because of complications,such as massive intraoperative blood loss(IBL)and early allograft dysfunction(EAD).Liver volumetry is performed routinely in living donor LT,but rarely in deceased donor LT(DDLT),which amplifies the adverse effects of DRSM in DDLT.Due to the various shortcomings of traditional manual liver volumetry and formula methods,a feasible model based on intelligent/interactive qualitative and quantitative analysis-three-dimensional(IQQA-3D)for estimating the degree of DRSM is needed.AIM To identify benefits of IQQA-3D liver volumetry in DDLT and establish an estimation model to guide perioperative management.METHODS We retrospectively determined the accuracy of IQQA-3D liver volumetry for standard total liver volume(TLV)(sTLV)and established an estimation TLV(eTLV)index(eTLVi)model.Receiver operating characteristic(ROC)curves were drawn to detect the optimal cut-off values for predicting massive IBL and EAD in DDLT using donor sTLV to recipient sTLV(called sTLVi).The factors influencing the occurrence of massive IBL and EAD were explored through logistic regression analysis.Finally,the eTLVi model was compared with the sTLVi model through the ROC curve for verification.RESULTS A total of 133 patients were included in the analysis.The Changzheng formula was accurate for calculating donor sTLV(P=0.083)but not for recipient sTLV(P=0.036).Recipient eTLV calculated using IQQA-3D highly matched with recipient sTLV(P=0.221).Alcoholic liver disease,gastrointestinal bleeding,and sTLVi>1.24 were independent risk factors for massive IBL,and drug-induced liver failure was an independent protective factor for massive IBL.Male donor-female recipient combination,model for end-stage liver disease score,sTLVi≤0.85,and sTLVi≥1.32 were independent risk factors for EAD,and viral hepatitis was an independent protective factor for EAD.The overall survival of patients in the 0.85<sTLVi<1.32 group was better compared to the sTLVi≤0.85 group and sTLVi≥1.32 group(P<0.001).There was no statistically significant difference in the area under the curve of the sTLVi model and IQQA-3D eTLVi model in the detection of massive IBL and EAD(all P>0.05).CONCLUSION IQQA-3D eTLVi model has high accuracy in predicting massive IBL and EAD in DDLT.We should follow the guidance of the IQQA-3D eTLVi model in perioperative management.

Consequences of Insufficient Selectivity in Quantitative and Qualitative Chemical Analysis

A problem in chemical analysis in connection with measurements of a substance normally occurring in a sample, or identification of a substance which should not exist in a sample, is insufficient selectivity. In this article, we analyze this problem and propose remedies. We use a real doping case to illustrate how chemical noise causes a serious selectivity problem, probably causing a false positive outcome.

Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa)

The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

Comprehensive Evaluation of Talent Training Model for Modern Rehabilitation Therapy Technology:A Case Study of School Y

The purpose of this study is to comprehensively evaluate the modern training model of rehabilitation therapy technology talents.Selecting the third-year students of the rehabilitation therapy technology program in School Y as the research subject,300 questionnaires were collected and the effective response rate was 92%.The strengths and weaknesses of the modern training model were analyzed through a mixed qualitative and quantitative research method.It was found that 68%of the students thought that the modern model had obvious advantages in practical teaching,but 42%of the students thought that it still needed to be improved in personalized teaching.This study provides an empirical basis and specific suggestions for optimizing the cultivation of rehabilitation therapy technology talents.

A Comparative Study on Proteomics between LNCap and DU145 Cells by Quantitative Detection and SELDI Analysis

The differences in intracellular and extracellular protein expressions between human prostate cancer lines LNCap and DU145 were examined, The proteins of the two cell lines were extracted and condensed by using protein extraction kits. And the intracellular and extracellular proteins were quantitatively detected on a micro-plate reader by using bicinchoninic acid （BCA） method. The proteins in cell culture fluid were qualitatively assayed by SELDI-TOF-MS, The results showed that the intracellular protein contents of LNCap cells were extremely higher than those of DU145 cells. After serum-free culture, both intracellular and extracellular protein contents of LNCap and DU145 were decreased to some extent. And the intracellular proteins were decreased by 5% in LNCap and by 36% in DU145 respectively, while the extracellular proteins were decreased by 89% in LNCap and 96% in DU145 respectively. SELDI assay revealed that there were 5 marker proteins in LNCap and 6 in DU145. Although both LNCap and DU145 cell lines originated from human prostate cancer, they had some differences in protein expression.

Qualitative and quantitative analysis of four different polarity fractions from Huang-Lian-Jie-Du-Decoction by HPLC-DAD-ESI-MS/MS and their related neuroprotective effects

Huang-Lian-Jie-Du-Decoction （HLJDD） has been widely used for the treatment of Alzheimer＇s disease （AD） in clinic. However, the relationship between its chemical profile and neuroprotective bioactivity was not clearly clarified yet. In present study, the water extract of HLJDD and subsequent three polarity fractions divided by different reagents were investigated. A total of 17 chromatographic peaks were confirmed by comparison with standards and their UV, MS spectra. Among them, 11 major compounds were determined by HPLC-DAD method with good linear regression relationship （r2, 0.9994-0.9999）, precisions （inter-day precision RSD, 0.79%-1.07%; intra-day precision RSD, 1.59%-2.10%）, repeatability （RSD, 1.66%-3.67%）, stability （RSD, 1.26%-4.77%） and recovery （95.24%-105.41%, RSD, 0.29%-2.69%）. Furthermore, PC12 cells and primary neurons cells were used for the neuroprotective effective assessment of aforementioned four samples from HLJDD. 3＂he total aqueous extract and n-butanol extract of HLJDD presented more significant effects than the other two parts. According to their quality and quantity determination results, iridoids and alkaloids have a positive correlation with the neuroprotective effectiveness of HLJDD.

GRINDING OF DOUBLE DISC GRINDING MACHINE

The grinding of two parallel sides of a component is accomplished with theaccuracy and higher productivity by passing a blank through the truncated cone shape grinders, whichare turned angles. The machine is designated by the name of double disc grinding machine (DDGM).Usually, it is used in the mass production. The relationship between these angles, the accuracy,productivity, allowance and parameters of the machine and technology is explained in detail by math,such as vector analysis, transformation of 3D space coordinates, etc. Therefore, in the aspects ofqualitative and quantitative analyses, the grinding potential of DDGM is enormous increased andsuperior to conventional methods. Furthermore, the theoretical foundation of DDGM grinding designand technology is provided to improve, to expand and to create for future. The established machinedesign and practical experience of grinding technology will get great benefit by them.

THE BETAINES FROM CHINESE SEAWEEDS

Cation-exchange chromatography was selected to extract and separate betaines from marine algae. On the basis of the special chemical characteristics of the betaines and their analogues, Dragendorff’s reagent (KBiI 4) was used to test the existence of betaines and their analogues in marine algae. The total content of betaines from seven species was obtained by using the Reinkeate salt precipitation method. The results showed that the content of betaines in two species of Chlorophyta and two species of Rhodophyta were relatively high,and that the content of betaines in Enteromopha prolifera could even reach to 0.9%. The content in the three species of Phaeophyta was relatively low.

Preliminary study on qualitative and quantitative detection of norfloxacin based on terahertz spectroscopy

Norfloxacin is a kind of quinolone bactericide which is widely used in food industry,livestock feed and medicine area.At present,how to develop a rapid,convenient and accurate technique for qualitative and quantitative detection of norfloxacin is still a challenge.In this study,Terahertz Time-domain Spectroscopy technology(THz-TDS)was used to explore qualitative and quantitative analysis of norfloxacin.Forty-five norfloxacin samples with different levels were prepared.The pure norfloxacin powder was mixed with polyethylene(PE)powder together and made into tablets by tablet-making machine.The minimum detection concentration was 10%and the maximum detection concentration evaluated in the paper was 90%.Then,terahertz(THz)spectra of each sample were measured on K15 THz-TDS equipment.The multiple linear regressions and the partial least squares regression algorithms were used to establish a model to make quantitative analysis.From the results,two typical fingerprint peaks of norfloxacin in terahertz band were observed at 0.944 THz and 1.206 THz,and the correlation coefficient and the root mean square error of the established model reached 0.9908 and 0.0481,respectively,which showed that the model performed well for the prediction.This preliminary study indicates that THz spectroscopy has great potential for future screening applications to detect the presence of norfloxacin residues in food,livestock feed and medicine industries.

Qualitative and quantitative analysis of atmospheric methanol using a continuous-wave terahertz spectrometer

We present a specific-window method to subtract the interference of water vapor on terahertz frequency-domain spectroscopy（THz-FDS） at ambient temperature and pressure. A continuous-wave spectrometer based on photomixing was utilized to obtain THz-FDS of methanol vapor in the range of 50–1200 GHz. The distinctly spaced absorption features in the neighborhood of atmospheric windows of transparency were selected to perform linear fitting versus the calculated absorption cross section and obtain the concentration of methanol. Furthermore, the gradually decreased methanol vapor was quantified to demonstrate the reliability of the method.

Compared Insights on Machine-Learning Anomaly Detection for Process Control Feature

Anomaly detection is becoming increasingly significant in industrial cyber security,and different machine-learning algorithms have been generally acknowledged as various effective intrusion detection engines to successfully identify cyber attacks.However,different machine-learning algorithms may exhibit their own detection effects even if they analyze the same feature samples.As a sequence,after developing one feature generation approach,the most effective and applicable detection engines should be desperately selected by comparing distinct properties of each machine-learning algorithm.Based on process control features generated by directed function transition diagrams,this paper introduces five different machine-learning algorithms as alternative detection engines to discuss their matching abilities.Furthermore,this paper not only describes some qualitative properties to compare their advantages and disadvantages,but also gives an in-depth and meticulous research on their detection accuracies and consuming time.In the verified experiments,two attack models and four different attack intensities are defined to facilitate all quantitative comparisons,and the impacts of detection accuracy caused by the feature parameter are also comparatively analyzed.All experimental results can clearly explain that SVM(Support Vector Machine)and WNN(Wavelet Neural Network)are suggested as two applicable detection engines under differing cases.

Limiting stand density and basal area projection models for even-aged Tecomella undulata plantations in a hot arid region of India

This paper presents equations for estimating limiting stand density for Z undulata plantations grown in hot desert areas of Raj asthan State in India. Five different stand level basal area projection models, belonging to the path invariant algebraic difference form of a non-linear growth function, were also tested and compared. These models can be used to predict future basal area as a function of stand variables like dominant height and stem number per hectare and are necessary for reviewing different silvicultural treatment options. Data from 22 sample plots were used for modelling. An all possible growth intervals data structure was used. Both, qualitative and quantitative criteria were used to compare alternative models. The Akaike＇s information criteria differ- ence statistic was used to analyze the predictive ability of the models. Results show that the model proposed by Hui and Gadow performed best and hence this model is recommended for use in predicting basal area development in 12 undulata plantations in the study area. The data used were not from thinned stands, and hence the models may be less accurate when used for predictions when natural mortality is very significant.

Managerial Ethics-A Tool for Social Crises

Social progress is constantly influenced by corruption and clientelism. One of the major causes is slow activityfrom experts on theoretical and practical management. In their decisions, they are not sufficiently ready to react todynamism of innovations in technical disciplines and current theory and practice in management. Contemporaryphilosophy of management is based on maximising quantity, expecting to deal with quality in due course.Management is focused on quantitative values and disregards the significance of the unity between quantity andquality. This leads to lack of transparency within management and uncertain efficiency of the decision-makingprocess. Disintegration affects the cooperation between individual production and administration branches. Theacademic world sees ethics more as a theoretical discipline connected with social sciences. Many companies,however, have begun to realise the need for innovation as part of successful long-term enterprising and creatingethical relationships inside and outside the company. Corruption scandals and increasing economic crime show thatit is counterproductive to advance business environment without adhering to moral and ethical principles.

Methodological Approaches to Study Internet Financial Communication

The aim of this paper is to show how qualitative and quantitative approaches can be complementary to study internet financial communication in a thesis by papers and how grounded theory （GT） can be the link among the different papers of the thesis. The study context of our thesis was the unregulated markets of New York Stock Exchange （NYSE） Euronext Brussels and the problematic rose from this context： What is the voluntary effort of communication when there is no obligation of internet financial communication？ Four papers tried to answer this central question and other following research questions. To answer those research questions, several methodological approaches were used： content analysis of websites and scoring, linear regression, paired sample, and interviews. At the end of our thesis by papers, we discovered that GT was the general methodological travel among the papers： Every article had for vocation to try to answer the questions raised by the previous article.

Reliability Optimization in the Islanded Mode of Microgrid

A microgrid is a combination of distributed energy resources and controllable loads. The main objective of this research is to optimize energy flow within a microgrid with regards to reliability in grid connected mode. A microgrid with combined heat and power, natural gas generator, diesel generator, solar energy, wind energy, and battery energy storage along with a critical load is considered in this research. An event oriented analytical method called FTA （fault trees analysis） is implemented for reliability optimization using PTC Windchill Solutions software in a microgrid. The reliability of each component in each energy source of the microgrid is calculated using FTA. The reliability of the critical load is evaluated. The quantitative and qualitative results of FTA are evaluated in order to interpret the results of fault tree. The sensitivity and uncertainty of the fault tree results for critical load is deduced by calculating the importance measures such as risk achievement worth, risk reduction worth, criticality importance and Fussel-Vesely importance. Finally from the results the components that are sensitive and at high risk are deduced.

Insights into pH-dependent transformation of gibberellic acid in aqueous solution:Transformation pathway,mechanism and toxicity estimation

Gibberellic acid(GA_(3))is widely used in agriculture and maybe transfer with groundwater flow,which is an endocrine disruptor,but few studies have focused on the transformation pathway and toxicity assessment of GA_(3)and its products.Here,GA_(3)and its transformation products in aqueous solution were identified and quantified by liquid chromatography mass spectrometry hybrid ion trap time-of-flight(LCMS-IT-TOF)and high-performance liquid chromatography(HPLC),respectively.The results showed that the half-life of GA_(3)transformation in ultrapure water was 16.1–24.6 days at p H=2.0–8.0,with the lowest half-life occurring at p H=8.0 and highest half-life occurring at p H=3.3.Isomerized gibberellic acid(Iso-GA_(3))and gibberellenic acid(GEA)were the main transformation products with a little hydroxy gibberellic acid(OH-GA_(3)).In North China groundwater,the mass balance of GA_(3)and its products was 76.2%,including Iso-GA_(3)(58%),GEA(7.9%),GA_(3)(7.3%)and OH-GA_(3)(3%)after reaching transformation equilibrium.Using Gaussian 09 for chemical computation,it was found that the transformation mechanism of GA_(3)was dependent upon the bond energy and the stereochemical feature of its molecular structure.GA_(3)always isomerized from theγ-lactone ring due to the lowest bond energy between the oxygen terminus of theγ-lactone ring and A ring.While GA_(3)and its transformation products all had developmental toxicity,the predicated LC 50(96 hr)and LD 50 of the main products of GA_(3)were much lower than those of GA_(3),indicating GA_(3)would be transformed into higher toxicity derivatives in water environments,posing a significant health risk to humans and the environment.

Post-evaluation of a water pollution control plan： methodology and case study

China has developed more than 20 water pollution control plans for river basins （RBWPs） since 1996. However, the implementation has generally lagged. This paper proposes a three-step, post-evaluation methodology to analyze the implementation result of a RBWP and its influential factors. First, a multi-attribute evaluation method based on an index system is established to score the enforcement results of a RBWP. Indicators measure how well a RBWP has achieved its objectives, which include water quality compliance, pollution load control, project construction, financial inputs, and related management requirements. Second, an interpretive structural model is used to detect the significant factors that affect RBWP implementation. This model can effectively analyze the cause-effect chain and hierarchical relationship among variables. Five groups of factors were identified, namely, plan preparation, water resource endowment, policy, institution, and management. Both qualitative and quantitative methods are employed in the third step to evaluate the extent to which these factors have influenced the execution result of a RBWP, including pre-post contrast, scenario analysis, and correlation analysis. This research then post-evaluated the implementation of the Huai River Basin water pollution control plans （H-RBWPs） over a period of 10 years as a case study. Results showed that the implementation of the H-RBWPs was unsatisfactory during 2001–2005, although it improved during 2006–2010. The poor execution of these plans was partially caused by the underestimation of regional economic development in combination with ineffective industrial structure adjustment policies. Therefore, this case study demonstrates the feasibility and flexibility of the proposed post-evaluation methodology.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

Influence of temperature and turbidity on water COD detection by UV absorption spectroscopy

Ultraviolet(UV) absorption spectroscopy is used to detect the concentration of water chemical oxygen demand(COD). The UV absorption spectra of COD solutions are analyzed qualitatively and quantitatively. The partial least square(PLS) algorithm is used to model COD solution and the modeling results are compared. The influence of environmental temperature and turbidity is analyzed. These results show that the influence of temperature on the predicted value can be ignored. However, the change of turbidity can affect the detection results of UV spectra, and the COD detection error can be effectively compensated by establishing the single-element regression model.