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Jinli Duan1 1, Feng Jiao2 1College of Modern Management, Yango University, Fuzhou, People’s Republic of China; 2INTO Newcastle University, Newcastle University, Newcastle Upon Tyne, NE1 7RU, UKCorrespondence: Jinli Duan Tel +86 13950315322Email 78308776@qq.comPurpose: Several threatening infectious diseases, including influenza, Ebola, SARS, and COVID-19, have affected human society over the past decades. These disease outbreaks naturally inspire a demand for sustained and advanced safety and suppression measures. To protect public health and safety, further research developments on emergency analysis methods and approaches for effective emergency treatment generation are urgently needed to mitigate the severity of the pandemic and save lives.Methods: To address these issues, a novel case-based reasoning (CBR) system is proposed using three phases. In the first phase, the similarity between the current case and the historical cases is calculated under a variety of heterogeneous information. In the second phase, a filter approach based on grey clustering analysis is created to retrieve relevant cases. In the third phase, the cases retrieved are taken as initial host nests in a cuckoo search (CS) algorithm, and our system searches an optimal solution through iteration of this algorithm.Results: The proposed model is compared with a CBR method improved by particle swarm optimization (PSO) and a CBR method improved by a differential evolution algorithm (DE), to confirm the efficiency of our CS algorithm in adapting solutions for public health emergencies. The results show that the proposed model is better than the existing algorithms.Conclusion: The proposed model improves the speed of case retrieval using grey clustering and increases solution accuracy with CS algorithms. The present research can contribute to government, CDC, and infectious disease emergency management fields with regard to the implementation of fast and accurate public biohazard prevention and control measures based on a variety of heterogeneous information.Keywords: case-based reasoning, grey clustering, cuckoo search algorithm, public health emergencies

Background: Currently there are various issues that exist in the medical institutions in China as a result of the price-setting in DRGs, which include the fact that medical institutions tend to choose patients and that the payment standard for complex cases cannot reasonably compensate the cost.Objective: The main objective is to prevent adverse selection problems in the operations of a diagnosis-related groups (DRGs) system with the game pricing model for scientific and reasonable pricing.Methods: The study proposes an improved bargaining game model over three stages, with the government and patients forming an alliance. The first stage assumes the alliance is the price maker in the Stackelberg game to maximize social welfare. Medical institutions are a price taker and decide the level of quality of medical service to maximize their revenue. A Stackelberg equilibrium solution is obtained. The second stage assumes medical institutions dominate the Stackelberg game and set an optimal service quality for maximizing their revenues. The alliance as the price taker decides the price to maximize the social welfare. Another Stackelberg equilibrium solution is achieved. The final stage establishes a Rubinstein bargaining game model to combine the Stackelberg equilibrium solutions in the first and second stage. A new equilibrium between the alliance and medical institutions is established.Results: The results show that if the price elasticity of demand increases, the ratio of cost compensation on medical institutions will increase, and the equilibrium price will increase. The equilibrium price is associated with the coefficient of patients' quality preference. The absolute risk aversion coefficient of patients affects government compensation and total social welfare.Conclusion: In a DRGs system, considering the demand elasticity and the quality preference of patients, medical service pricing can prevent an adverse selection problem. In the future, we plan to generalize these models to DRGs pricing systems with the effects of competition of medical institutions. In addition, we suggest considering the differential compensation for general hospitals and community hospitals in a DRGs system, in order to promote the goal of hierarchical diagnosis and treatment.

The sharp increase of the aging population has raised the pressure on the current limited medical resources in China. To better allocate resources, a more accurate prediction on medical service demand is very urgently needed. This study aims to improve the prediction on medical services demand in China. To achieve this aim, the study combines Taylor Approximation into the Grey Markov Chain model, and develops a new model named Taylor-Markov Chain GM (1,1) (T-MCGM (1,1)). The new model has been tested by adopting the historical data, which includes the medical service on treatment of diabetes, heart disease, and cerebrovascular disease from 1997 to 2015 in China. The model provides a predication on medical service demand of these three types of disease up to 2022. The results reveal an enormous growth of urban medical service demand in the future. The findings provide practical implications for the Health Administrative Department to allocate medical resources, and help hospitals to manage investments on medical facilities.

Disease cost estimation is an important and challenging issue. It serves as the key factor of hospital cost and cost control. It has been a challenge to estimate the disease cost because of the complexity of the disease pathology, individual differences of treatment process, adverse drug reaction, and complications. Especially in some high risk and high noise diseases there is another challenge from small sample and poor data. Grey relational analysis is a kind of effective method to study small sample, and poor data. In this paper, an improved model based on grey relational analysis and case-based reasoning is proposed to estimate the disease cost. Firstly, the similarity on cost attributes is calculated through the grey relational analysis method. And then the optimal attribute weights is found with the cuckoo search algorithm and there are a few cases matching to the target case according to the similarity in the historical case database to estimate the cost of target case. At last the estimation accuracy using the improved model in experimental study of the cost estimation of simple appendicitis disease, cesarean section, and heart bypass surgery is compared with the three models respectively with Euclidean distance, Angle cosine, and Mahalanobis distance. The improved model is best on cost estimation precision, especially in small sample and disease with high risk and high noise.

This paper presents GM (1, N) models with linear cross effect and nonlinear cross effect, and discusses the difference of driving factors between these two types of models to solve the cross effects of GM (1, N) model. The model with a linear cross effect in this paper preserves the solution of whitenization in the GM (1, 1) model. While the model with nonlinear cross effect integrates the sequences of systemic features, driving factors, and the cross effect of these driving factors. While applying support vector machine (SVM) regression, it transfers the nonlinear relationship among these sequences to a linear relationship. To test the GM (1, N) model that is based on support vector machine (SVM) with nonlinear effect, the study applies it to forecast the total output of the pharmaceutical industry. The range of the data is selected from 2005&ndash, 2017, which the data from 2005&ndash, 2013 are used to fit into the model. The GM (1, N) model based on SVM with nonlinear cross effect achieves 0.6566 and 0.2956 in its fitted total of relative error and the forecast total of relative error, respectively. The new model presents a more accurate analysis on fitting and forecast precision than the classic GM (1, N) model and GM (1, N) with the linear cross effect model.

This paper introduces a versatile approach for surface modification of 621-terylene filtration fabric (FF) self-assembled by a dynamic layer-by-layer technique. The hexadecyl trimethyl ammonium bromide (HTAB) and cross-linked polyvinyl alcohol microspheres (PVA-MS) were alternatively deposited on support membrane under a pressure of 0.01 MPa to modify FF. Morphological changes and hydrophilicity of the modified FF were characterized in detail by scanning electron micrograph and water contact angle measurements. Results revealed that PVA-MS could be adsorbed mainly on the surface of FF and water contact angle decreased with the increase of HTAB/PVA-MS bilayer numbers indicating an enhanced hydrophilicity for the modified FF. Backwash experiments of the modified FF exhibited much higher stability of PVA-MS. Protein adsorption experiments were conducted to evaluate the antifouling property of the modified FF. Results indicated that protein adsorption of the membrane surface could be obviously improved by modification, which exhibited superior antifouling property of the modified FF.

This paper introduces a versatile approach for the modification of terylene microporous membrane by PVA-MS layer-by-layer self-assembling to improve its filterability. The preparation conditions including filtration time of the first HTAB layer, reaction time and bilayer number were investigated. The results suggested that suitable filtration time of the first HTAB layer was 8 min and the reaction time was 10 min with suitable HTAB/PVA-MS bilayer numbers. Membrane chemistry, morphological changes and hydrophilicity of the composite membrane were characterized in details by FTIR-ATR spectroscopy, scanning electron micrograph and water dynamic contact angle measurements. Results revealed that PVA-MS could be adsorbed mainly on the surface of the terylene microporous membrane and dynamic contact angle on the terylene microporous membrane surface decreased with the increase of bilayer numbers indicating an enhanced hydrophilicity for the modified terylene microporous membrane. Backwash experiments of composite membranes exhibited much higher stability of the HTAB/PVA-MS active layer. The permeation flux of activated sludge was measured to evaluate the anti-fouling property of composite membranes, and the results showed an enhancement of anti-fouling property of modified composite membranes.

Membranes suffer from operational problems due to fouling in water filtration. Fouling is caused by the build-up of chemicals, bioorganic materials, and biofilms at the membrane surface. The focus of this study was the fabrication and characterization of 4-vinyl pyridine grafted polyvinyl alcohol (PVA-g-4VP) and the modifi cation of nonwoven membrane (NWF) for the prevention of bacterial attachment. The graft copolymerization using Ce(IV) as an initiator was carried out in an aqueous solution. With keeping other conditions constant, the optimum conditions were shown as following: [Ce(IV)]=4 mmol/l, [4VP]=0.15 mol/l, reaction temperature=60°C, reaction time=240 min. NWF membranes were modified by coating of PVA-g-4VP with different graft concentrations, and quaternization of the pyridine groups with benzyl bromide. A significant surface enrichment of vinyl pyridine polymer side chains was observed by Fourier transform infrared-attenuated total refl ectance. The permeability of the membrane was reduced afte...

This article introduced an approach using cross-linked polyvinyl alcohol microspheres (PVA-MS) to form dynamic membrane on the surface of the industry filter cloth instead of the conventional MF/UF membrane to build a membrane bioreactor (MBR) for wastewater treatment. The performance of the dynamic MBR for treating synthetic domestic wastewater and membrane fouling were investigated. For treating synthetic domestic wastewater sequentially, the results of the batch tests showed that the effluent turbidity was less than 4 NTU and SS was zero at the most operation time. The average removal efficiency of CODCr and NH4+-N were 93.18 and 98.6%, respectively. Membrane fouling was mainly caused by sludge layer. The sludge cake and precoated dynamic membrane could be easily removed by brushing. The support membrane permeate flux was almost recovered fully and could be reused again. These results indicated that the precoated dynamic membrane could prevent pollutants and biomass intervening to the surface and inter...

The purpose of this work was to investigate the potential of the macroporous resin, H-103, in adsorbing sorbic acid. Study on adsorption thermodynamics and kinetics of sorbic acid by H-103 resin was carried out through static experiments. These adsorption processes of sorbic acid were indicative of exothermic process and physical adsorption. The adsorption of sorbic acid on H-103 resin fit well to Freundlich model .Temperature variations were used to evaluate enthalpy DeltaH, entropy DeltaS and Gibbs free energy DeltaG values. The negative valueof DeltaG showed the spontaneous nature of adsorption. In the temperature range from 303-333 K, DeltaH and DeltaS were negative, and the reaction was exothermic and reversible. Adsorption kinetics was found to follow first order reversible model expression.