Exploring the Path of Shantytown Renewal Based on the Theory of Environment-behavior Studies: A Case Study of the Northwest Area of Saihantala in Baotou City

The application of environment-behavior studies plays an important role in studying the renewal of shantytowns.One of the most humane ways of renewal is designing and constructing the necessary urban spatial environment from the perspective of human daily behavior.Most of the shantytown renovation projects currently carried out in China are mainly focused on demolition and reconstruction,which not only incurs high costs but also damages the original social structure and economic model.During the process of shantytown renewal,it should improve the urban landscape,living environment,and life quality of residents,and ensure the daily life of shantytown residents without increasing their economic burden,and preserve the traces of urban development.In order to achieve this goal,it should explore the renewal strategies of shantytowns from the perspective of environment-behavior studies through behavior maps,on-site research,and literature review.Updating and design from a human perspective often achieve faster and better development;the renewal of shantytowns should be a bottom-up approach and start from a grassroots perspective,completing the renovation design through the composition of the population and behavioral patterns.

Research and Discussion on Flipped Classroom Combined with Case-Based Learning in Pharmacoeconomics Teaching

Objective:To explore the application effect of flipped classroom combined with case-based learning teaching methods in pharmacoeconomics teaching.Methods:The students majoring in clinical pharmacy in 2019 were selected as the study subjects,and the cost-effectiveness analysis of different dosage forms of Yinzhihuang in the treatment of neonatal jaundice was selected as the teaching case.The flipped classroom combined with case-based learning teaching method was used to carry out theoretical teaching to the students.After the course,questionnaires were distributed through the Sojump platform to evaluate the teaching effect.Results:The results of the questionnaire showed that 85.71%of the students believed that the flipped classroom combined with case-based learning teaching method was helpful in mobilizing the learning enthusiasm and initiative,and improving the comprehensive application ability of the knowledge of pharmacoeconomics.92.86%of the students think that it is conducive to the understanding and memorization of learning content,as well as the cultivation of teamwork,communication,etc.Conclusion:Flipped classroom combined with case-based learning teaching method can improve students’knowledge mastery,thinking skills,and practical application skills,as well as optimize and improve teachers’teaching levels.

Study on Case-Based Fixture Design

Fixture is an important manufacturing activity. A fixture design system based on case-based reasoning (CBR) is proposed in this paper. A new method of case representation on the basis of fixture function is presented, where the case representation is constituted of workpiece knowledge, processing feature knowledge, and fixture feature knowledge. Running the prototype system shows that the knowledge representation method, using cases, s a better way to transform and explain the design knowledge.

A New Method to Predict Erythrocyte Sedimentation Rate with Natural Geographical Factors and Location by Case-based Reasoning: A Case Study of China

Reference values of erythrocyte sedimentation rate(ESR)are the key to interpret ESR blood test in clinic.The common local reference ESR values are more accuracy in blood test that are established with natural geographical factors by using the multiple linear regression(MLR)model and the artificial neural network(ANN).These knowledge-based methods have limitations since the knowledge domains of ESR and natural geographical factors are limited.This paper presents a new cases-depended model to establish reference ESR values with natural geographical factors and location using case-based reasoning(CBR)since knowledge domain of ESR and geographical factors is weak.Overall 224 local normal ESR values of China that calculated from 13623 samples were obtained,and the corresponding natural geographical factors and location that include altitude,sunshine hours,relative humidity,temperature,precipitation,annual temperature range and annual average wind speed were obtained from the National Geomatics Center of China.CBR was used to predict the unseen local reference ESR values with cases.The average absolute deviation(AAD),mean square error(MSE),prediction accuracy(PA),and Pearson correlation coefficient(r)between the observed and estimated data of proposed model is 33.07%,9.02,66.93% and 0.78,which are better than those of ANN and MLR model.The results show that the proposed model provides higher prediction accuracy than those of the artificial neural network and multiple linear regression models.The predicted values are very close to the observed values.Model results show significant agreement of cases data.Consequently,the model is used to predict the unseen local reference ESR with natural geographical factors and location.In spatial,the highest ESR reference areas are distributed in the southern-western district of China that includes Sichuan,Chongqing,Guangxi and Guizhou provinces,and the reference ESR values are greater than 23 mm/60 min.The higher ESR reference values are distributed in the middle part and northern-eastern of China which include Hubei,Henan,Shaanxi,Shanxi,Jilin and Heilongjiang provinces,and the reference ESR values are greater than 18 mm/60min.The lowest ESR reference values are distributed in the northern-western of China that includes Tibet and Xinjiang,and the reference ESR values are lower than 5 mm/60min.

Cohort study on the treatment of BRAF V600E mutant metastatic colorectal cancer with integrated Chinese and western medicine

BACKGROUND Patients with BRAF V600E mutant metastatic colorectal cancer(mCRC)have a low incidence rate,poor biological activity,suboptimal response to conventional treatments,and a poor prognosis.In the previous cohort study on mCRC conducted by our team,it was observed that integrated Chinese and Western medicine treatment could significantly prolong the overall survival(OS)of patients with colorectal cancer.Therefore,we further explored the survival benefits in the population with BRAF V600E mutant mCRC.AIM To evaluate the efficacy of integrated Chinese and Western medicine in the treatment of BRAF V600E mutant metastatic colorectal cancer.METHODS A cohort study was conducted on patients with BRAF V600E mutant metastatic colorectal cancer admitted to Xiyuan Hospital of China Academy of Chinese Medical Sciences and Traditional Chinese Medicine Hospital of Xinjiang Uygur Autonomous Region from January 2016 to December 2022.The patients were divided into two cohorts.RESULTS A total of 34 cases were included,with 23 in Chinese-Western medicine cohort(cohort A)and 11 in Western medicine cohort(cohort B).The median overall survival was 19.9 months in cohort A and 14.2 months in cohort B,with a statistically significant difference(P=0.038,hazard ratio=0.46).The 1-3-year survival rates were 95.65%(22/23),39.13%(9/23),and 26.09%(6/23)in cohort A,and 63.64%(7/11),18.18%(2/11),and 9.09%(1/11)in cohort B,respectively.Subgroup analysis showed statistically significant differences in median OS between the two cohorts in the right colon,liver metastasis,chemotherapy,and first-line treatment subgroups(P<0.05).CONCLUSION Integrated Chinese and Western medicine can prolong the survival and reduce the risk of death in patients with BRAF V600E mutant metastatic colorectal cancer,with more pronounced benefits observed in patients with right colon involvement,liver metastasis,combined chemotherapy,and first-line treatment.

IMPROVED AERODYNAMIC APPROXIMATION MODEL WITH CASE-BASED REASONING TECHNIQUE FOR MDO OF AIRCRAFT

To increase the efficiency of the multidisciplinary optimization of aircraft, an aerodynamic approximation model is improved. Based on the study of aerodynamic approximation model constructed by the scaling correction model, case-based reasoning technique is introduced to improve the approximation model for optimization. The aircraft case model is constructed by utilizing the plane parameters related to aerodynamic characteristics as attributes of cases, and the formula of case retrieving is improved. Finally, the aerodynamic approximation model for optimization is improved by reusing the correction factors of the most similar aircraft to the current one. The multidisciplinary optimization of a civil aircraft concept is carried out with the improved aerodynamic approximation model. The results demonstrate that the precision and the efficiency of the optimization can be improved by utilizing the improved aerodynamic approximation model with ease-based reasoning technique.

Comparative Studies on Tourist Satisfaction of World Heritage Sites——A Case Study of Huangshan Mountain,Lushan Mountain and Wuyi Mountain

Through the questionnaire survey and comparative studies on tourist satisfaction of tourism services among three world heritage sites,i.e.Huangshan Mountain,Lushan Mountain and Wuyi Mountain,this study pointed out the problems in tourism services of three scenic areas and then put forward relevant countermeasures for the management of scenic areas.

CASE-BASED PRODUCT CONFIGURATION AND REUSE IN MASS CUSTOMIZATION

The increasing complexity and size of configuration knowledge bases requres the provisionof advanced methods supporting the development of the actual configuration process and design reuse.A new framework to find a feasible and practical product configuration method is presented in masscustomization. The basic idea of the appoach is to integrate case-based reasoning (CBR) with a con-straint satisfaction problem(CSP). The similarity measure between a crisp and range is also given,which is common in case retrieves. Based on the configuration model, a product platform and customerneeds, case adaptation is carried out with the repair-based algorithm. Lastly, the methodology in theelevator configuration design domain is tested.

Endpoint temperature prediction of molten steel in RH using improved case-based reasoning

An improved case-based reasoning （CBR） method was proposed to predict the endpoint temperature of molten steel in Ruhrstahl Heraeus （RH） process. Firstly, production data were analyzed by multiple linear regressions and a pairwise comparison matrix in analytic hierarchy process （AHP） was determined by this linear regression＇s coefficient. The weights of various influencing factors were obtained by AHP. Secondly, the dividable principles of case base including ＂0-1＂ and ＂breakpoint＂ were proposed, and the case base was divided into several homogeneous parts. Finally, the improved CBR was compared with ordinary CBR, which is based on the even weight and the single base. The results show that the improved CBR has a higher hit rate for predicting the endpoint temperature of molten steel in RH.

Design System of the Two-step Gear Reducer on Case-based Reasoning

The design of the two-step gear reducer is a tedious and time-consuming process. For the purpose of improving the efficiency and intelligence of design process, case-based reasoning（CBR） technology was applied to the design of the two-step gear reducer. Firstly, the current design method for the two-step gear reducer was analyzed and the principle of CBR was described. Secondly, according to the characteristics of the reducer, three key technologies of CBR were studied and the corresponding methods were provided, which are as follows： （a） an object-oriented knowledge representation method, （b） a retrieval method combining the nearest neighbor with the induction indexing, and （c） a case adaptation algorithm combining the revision based on rule with artificial revision. Also, for the purpose of improving the credibility of case retrieval, a new method for determining the weights of characteristics and a similarity formula were presented, which is a combinatorial weighting method with the analytic hierarchy process（AHP） and roughness set theory. Lastly, according to the above analytic results, a design system of the two-step gear reducer on CBR was developed by VC＋＋, UG and Access 2003. A new method for the design of the two-step gear reducer is provided in this study. If the foregoing developed system is applied to design the two-step gear reducer, design efficiency is improved, which enables the designer to release from the tedious design process of the gear reducer so as to put more efforts on innovative design. The study result fully reflects the feasibility and validity of CBR technology in the process of the design of the mechanical parts.

CASE-BASED CONCEPTUAL DESIGN

The current method of case-based design (CBD) can be well practiced forconfiguration design in which design experience knowledge is involved. However, since the designcase is confined to a certain application domain, it is difficult for CBD to be applied toconceptual design process that develops concepts to meet design specifications. Firstly, a functionfactor description space is erected to provide an exhibition room for all functions of design cases.Next, the approach for identifying the space state of function factor in description space isproposed, including the determination of the similarities between function factors of design case.And then a general object-oriented representation for design case is presented by bringing the classof function and in-out flow into the current case representation. Finally, a living example forelectro-pet design that illustrates the implementation of the method for case-based conceptualdesign based on distributed design case repositories is described.

Pressure-flow studies in patients with benign prostatic hyperplasia:a study comparing suprapubic and transurethral methods

Aim： To compare the use of the suprapubic puncture method versus the transurethral method in pressure-flow studies in patients with benign prostatic hyperplasia. Methods： Twenty-three men with benign prostatic hyperplasia underwent both suprapubic and transurethral pressure-flow studies during a single session. Standard pressure-flow variables were recorded in all patients with both methods, enabling calculation of obstruction using commonly used grading systems, such as the urethral resistance algorithm, the Abrams-Griffith （AG） number and the Schaefer linear nomogram. Results： There were statistically significant differences between the methods in the mean values of maximum flow rate （P 〈 0.05）, detrusor pressure at the maximum flow （P 〈 0.01）, urethral resistance algorithm （P 〈 0.01）, AG number （P 〈 0.01） and maximum cystic capacity （P 〈 0.01）. Of the men in the study, 10 （43.5%） remained in the same Schaefer class with both methods and 18 （78.3%） in the same AG number area. Using the transurethral method, 12 （52.2%） men increased their Schaefer class by one and 1 （4.3%） by two. There were also differences between the suprapubic and transurethral methods using the AG number： 4 （17.4%） men moved from a classification of equivocal to obstructed and 1 （4.3%） from unobstructed to equivocal. Conclusion： The differences between the techniques for measuring intravesical pressure alter the grading of obstruction determined by several of the commonly used classifications. An 8 F transurethral catheter significantly increases the likelihood of a diagnosis of bladder outlet obstruction when compared with the suprapubic method.

A case-based method of selecting covariates for digital soil mapping

Selecting a proper set of covariates is one of the most important factors that influence the accuracy of digital soil mapping(DSM).The statistical or machine learning methods for selecting DSM covariates are not available for those situations with limited samples.To solve the problem,this paper proposed a case-based method which could formalize the covariate selection knowledge contained in practical DSM applications.The proposed method trained Random Forest(RF)classifiers with DSM cases extracted from the practical DSM applications and then used the trained classifiers to determine whether each one potential covariate should be used in a new DSM application.In this study,we took topographic covariates as examples of covariates and extracted 191 DSM cases from 56 peer-reviewed journal articles to evaluate the performance of the proposed case-based method by Leave-One-Out cross validation.Compared with a novices’commonly-used way of selecting DSM covariates,the proposed case-based method improved more than 30%accuracy according to three quantitative evaluation indices(i.e.,recall,precision,and F1-score).The proposed method could be also applied to selecting the proper set of covariates for other similar geographical modeling domains,such as landslide susceptibility mapping,and species distribution modeling.

Case-Based Reasoning for Slope Stability Evaluation and Its Application

Slope is a non-linear and uncertain kinetic system affected by many factors. In view of the incompleteness and uncertainty of the information of slope stability evaluation, a new method of slop stability evaluation by using case-based reasoning is presented. Considering the sensitivity of attribute weights to the environment, the algorithm of attribute weights is set up on the basis of the concept of changeable weights. Calculating the similarity between target case of the slope and base case, the stability of target case is evaluated. It is shown from examples that the method is simple, visual, practical, and convenient for use.

Case-Based Reasoning(CBR) Model for Ultra-Fast Cooling in Plate Mill

New generation thermo-mechanical control process（TMCP） based on ultra-fast cooling is being widely adopted in plate mill to product high-performance steel material at low cost. Ultra-fast cooling system is complex because of optimizing the temperature control error generated by heat transfer mathematical model and process parameters. In order to simplify the system and improve the temperature control precision in ultra-fast cooling process, several existing models of case-based reasoning（CBR） model are reviewed. Combining with ultra-fast cooling process, a developed R5 CBR model is proposed, which mainly improves the case representation, similarity relation and retrieval module. Certainty factor is defined in semantics memory unit of plate case which provides not only internal data reliability but also product performance reliability. Similarity relation is improved by defined power index similarity membership function. Retrieval process is simplified and retrieval efficiency is improved apparently by windmill retrieval algorithm. The proposed CBR model is used for predicting the case of cooling strategy and its capability is superior to traditional process model. In order to perform comprehensive investigations on ultra-fast cooling process, different steel plates are considered for the experiment. The validation experiment and industrial production of proposed CBR model are carried out, which demonstrated that finish cooling temperature（FCT） error is controlled within±25℃ and quality rate of product is more than 97%. The proposed CBR model can simplify ultra-fast cooling system and give quality performance for steel product.

Case-based retrieval approach for machining fixture design utilizingontology

In order to develop an intelligent case-based reasoning （CBR） system to reuse fixture de- sign knowledge, ontology technology was integrated in CBR system by semantic annotation of fixture design case. Domain ontology of fixture design was constructed; concepts and relations were de- fined and represented. The 2-level similarity evaluation approach of domain ontology was presented. The concept similarity of cases was calculated as the first grade case retrieval. Numerical measure- ment was the second grade case retrieval, which adopted various methods to calculate different types of attribute values. The problem of similarity measurement of fixture design case was resolved. Pro- totype system based on the proposed method was illustrated and the retrieval approach was proved to be efficient.

Recognition of suspicious behavior using case-based reasoning

A novel method case-based reasoning was proposed for suspicious behavior recognition. The method is composed of three departs: human behavior decomposition, human behavior case representation and case-based reasoning. The new approach was proposed to decompose behavior into sub-behaviors that are easier to recognize using a saliency-based visual attention model. New representation of behavior was introduced, in which the sub-behavior and the associated time characteristic of sub-behavior were used to represent behavior case. In the process of case-based reasoning, apart from considering the similarity of basic sub-behaviors,order factor was proposed to measure the similarity of a time order among the sub-behaviors and span factor was used to measure the similarity of duration time of each sub-behavior, which makes the similarity calculations more rational and comprehensive.Experimental results show the effectiveness of the proposed method in comparison with other related works and can run in real-time for the recognition of suspicious behaviors.

Mineral Prospectivity Mapping Method Integrating Multi-Sources Geology Spatial Data Sets and Case-Based Reasoning

Extracting and synthesizing information from existing and massive amounts of geology spatial data sets is of great scientific significance and has considerable value in its applications. To make mineral exploration less expensive, more efficient, and more accurate, it is important to move beyond traditional concepts and establish a rapid, efficient, and intelligent method of predicting the existence and location of minerals. This paper describes a case-based reasoning (CBR) method for mineral prospectivity mapping that takes spatial features of geology data into account and offers an intelligent approach. This method include a metallogenic case representation that combines spatial and attribute features, metallogenic case-based storage organization, and a metallogenic case similarity retrieval model. The experiments were performed in the eastern Kunlun Mountains, China using CBR and weights-of-evidence (WOE), respectively. The results show that the prediction accuracy of the CBR is higher than that of the WOE.

Coffee consumption and risk of type 2 diabetes mellitus in Asians:A meta-epidemiological study of population-based cohort studies

BACKGROUND Previous systematic reviews have consistently reported that coffee consumption has a preventive effect on the occurrence of type 2 diabetes mellitus(T2DM).However,further evaluations between coffee consumption and the risk of T2DM in Asian populations are needed.AIM To conduct a meta-epidemiological study on systematic reviews evaluating the association between coffee consumption and the risk of T2DM in Asian people.METHODS The selection criterion was defined as a population-based prospective cohort study evaluating the association between coffee consumption and the risk of T2DM in Asian populations,reporting the adjusted relative risk(RR)and its 95%confidence interval(CI)for potential confounders.A fixed-effect model metaanalysis was applied to calculate the summary RR and its 95%CI in less than 50%of the I2 value indicating the level of heterogeneity.A two-stage fixed-effects doseresponse meta-analysis(DRMA)was performed to calculate the risk per unit dose(a cup per day).RESULTS A total of seven studies were selected in this meta-epidemiological study.The risk of T2DM in Asian populations was significantly reduced in the highest to the lowest dose group(summary RR=0.73,95%CI:0.66-0.82;I2 value=0.0%).The DRMA showed that drinking one cup of coffee per day reduced the risk of T2DM in Asian populations by 8%(RR=0.92,95%CI:0.90-0.95).CONCLUSION These findings support the conclusion that coffee consumption has a protective effect on the occurrence of T2DM in Asian men and women.

Temperature Prediction of Aluminum Alloy Work-Pieces in Aging Furnaces Based on Improved Case-Based Reasoning

The temperature of aluminum alloy work-pieces in the aging furnace directly affects the quality of aluminum alloy products. Since the temperature of aluminum alloy work-pieces cannot be measured directly, a temperature prediction model based on improved case-based reasoning (CBR) method is established to realize the online measurement of the work-pieces temperature. More specifically, the model is constructed by an advanced case-based reasoning method in which a state transition algorithm (STA) is firstly used to optimize the weights of feature attributes. In other words, STA is utilized to find the suitable attribute weights of the CBR model that can improve the accuracy of the case retrieval process. Finally, the CBR model based on STA (STCBR) was applied to predict the temperature of aluminum alloy work-pieces in the aging furnace. The results of the experiments indicated that the developed model can realize high-accuracy prediction of work-pieces temperature and it has good application prospects in the industrial field.