Improving information sharing in Chinese hospitals with electronic medical record: The resource-based view and social capital theory perspective

This research implicates that in large Chinese hospitals, in the individual level, EMR is able to make clinicians get access to more sources of information and knowledge to increase their working efficiency and make the right decision; in organisational level, EMR helps Chinese hospitals achieve effective cross-boundary information sharing and integration and promotes organisational learning and organisational memory in these hospitals

The Design of an Online Roommate Finding System for Property Management Portals—the Virtual Community Perspective

With the evolution and diffusion of the internet at the society level, various business sectors have been transformed and redesigned with the new technologies such as enterprise systems, social media, virtual communities, social commerce, and business intelligence. For example, most fortune 500 companies have installed ERP system by 1998 (Magal & Word, 2012), resulting in major manufacturing and traditional businesses to re-design their business processes. The travel industry has been disrupted by the online booking system such as booking.com and TripAdvisor.com (Mellinas, Martínez María-Dolores, & Bernal García, 2015). Many bookshops have been closed because of the operations of online booking stores such as Amazon (Pitt, Berthon, & Berthon, 1999). The emerging smart city research also implies that the transformation by the digital technology is at the national and city level into all sectors including transportation, energy, water etc (Paroutis, Bennett, & Heracleous, 2014). In the property management sector, various property management portals have been established to facilitate the estate agencies to manage properties and the customers to find suitable properties. The typical examples are zoopla.com and rightmove.com, both of which are specialized in one-stop property renting and selling in the United Kingdom. At the same time, there are also many small property management agencies who operate the independent property management platforms. The traditional property management portal normally consists of three key functions, property listing and management for agencies; property browsing and appointment booking for customers; and the property information integration including neighbourhood, billing, local tax etc. While the traditional property management system has satisfied the great needs for estate agencies and focus heavily on the information of the properties themselves, the customer experience has mainly ignored from the traditional design of the website. Practically, there is a need to bring the most recent knowledge of improving online shopping experience into the property management system design. This paper proposed a new business model for property management portals by designing an online roommate finding system with the virtual community theory. Specifically, the virtual community concept is used to design the online roommate system from the interpersonal relationship perspective. The proposed online roommate finding system is designed based on the interpersonal relationship framework (Li & Lee, 2013) and borrowed the concept and algorithm of the online recommendation system (Jiang, Shang, & Liu, 2010). Specifically, the following functions are implemented for the online roommate finding system so that a renting community emerges from the rental portal, the profile information of each tenant, the desired roommate features including personality, age, country, native language, etc, and the inside communication channels. The proposed online roommate finding system is going to be integrated into the existing online property management portal in UK. The action research method will be used to test the effectiveness of the online roommate finding system from 3 stages for 3 years, stage one is for the system testing, stage 2 is for community member recruitment, stage 3 is for operations of the system for profit generation. The current project is in the early phase of stage 1 and the requirements analysis is finished

STUDY ON THE EFFECT OF THREE KINDS OF FILTER AID ON THE DEHYDRATION PERFORMANCE OF MICROCYSTIS AERUGINOSA

In recent years, algae bloom phenomenon outbreaks frequently in large-scale water bodies during summer. At present, mechanical method is used to collect cyanobacteria and reduce volume. However, the characteristics of algae, namely high viscosity, small particle size and high moisture content, lead to poor efficiency of dehydration. In order to improve the dehydration efficiency of algae and achieve the purpose of volume reduction and dehydration, the dehydration performance of Microcystis aeruginosa was studied in this paper. Three filter aid agent, including Poly Aluminium Chloride (PAC), Montmorillonite and Diatomite were added to the algae solution to improve filterability of Microcystis aeruginosa. The results showed that all of three filter aid agent have positive effect on the algae filtration rate, specific resistance, compression index and dehydration efficiency. Compared with the other two filter aid agents, the filtration rate of Diatomite is relatively faster. Meanwhile dehydration performance is better as well. When the dosage of Diatomite was 10.0g/L, the filtration rate increased from 0.108 L/h to 0.504 L/h. In addition, the compression index was reduced from 0.710 to 0.594. The specific resistance was reduced from 7.62 × 1010 s2/g to 2.35 × 108 s2 /g while the water content was decreased from 86.5% to 66.4%

Conversion of high moisture biomass to hierarchical porous carbon via molten base carbonisation and activation for electrochemical double layer capacitor

Biomass-derived carbon for supercapacitors faces the challenge of achieving hierarchical porous carbon with graphitic structure and specific heteroatoms through a single-stage thermal process that minimises resource input. Herein, molten base carbonisation and activation is proposed. The process utilises the inherent moisture of Moso bamboo shoots, coupled with a low amount of KOH, to form potassium organic salts before drying. The resultant potassium salts promote in-situ activation during single-stage heating process, yielding hierarchical porous, large specific surface area, and partially graphitised carbon with heteroatoms (N, O). As an electrode material, this carbon exhibits a specific capacitance of 327F g−1 in 6 M KOH and 182F g−1 in 1 M TEABF4/AN, demonstrating excellent cycling stability over 10,000 cycles at 2 A/g. Overall, this study presents a straightforward process that avoids pre-drying of biomass, minimises base consumption, and employs single-stage heating to fabricate electrode carbon suitable for supercapacitors

A high throughput screening method for anti-cancer drug leads discovery from the herbal medicine

A high throughput anti-cancer drug leads screening method has been successfully established employing the cell line we reported in 2001. The method is based on the principle of fluorescence resonance energy transfer (FRET) and fluorescent protein variants of GFP. This cell-based method has advantages over the animal model screening and biochemistry-based screening. Compared to animal model screening, this cell-based method will save a lot of time and money in screening. At the same time, the cell-based screening method considers the cell context. The screening results will reflect interaction between compounds and cells or compounds and proteins in the cells compared to biochemistry-based screening. The YFP/CFP emission ratio (Y/C emission ratio) has been used to judge the screening result. The distinguished advantage of this cell-based screening method is that the Y/C emission ratio is only response to apoptotic cell death but not necrotic cell death. Thus, the method can distinguish apoptotic cell death from necrotic cell death. The compounds, which can significantly induce cell apoptosis, will be picked out from the compound library after screening. Optimization has been done for the screening procedure to enable it high throughput and low cost. In the process of optimization, it is found that medium only can be used as background. At the same time, the initial cell confluence and fluorescent plate reader parameters were also optimized. By now, a standard protocol has been established. Five anti-cancer drugs have been tested by this method. The screening results showed that the screening method is an excellent screening method. In addition, a new method to determine screening threshold has been developed based on the relation between Y/C emission ratio and cell viability. The screening threshold was set to 3 for our screening setup, which means that the compound that can induce Y/C emission decreases below the 3, will be considered as effective compound. Several small scale screening projects have been done. The screened compounds belong to two compound families: tanshinone compound family which were extracted from Salvia miltiorrhiza Bunge and podophyllotoxin compound family which were extracted from Podophyllum emodi Wall., which are all herbal extractions or their derivatives. In podophyllotoxin family, the deoxypodophyllotoxin (DP1) is the most potent anti-cancer compound. In tanshinone compound family, it is found that tanshinone IIA (TIIA) is the most potent compound on killing cancer cell. This result is consistent with reference. Although tanshinone IIA is potent in killing cancer cells, its solubility in water is not good. With chemical modification, a new compound called diacetyltanshinone IIA (ATA) was got. The solubility of ATA is improved compared to TIIA. The toxicity and mechanism studies were also carried out on ATA. In vitro toxicity assay results show that this compound has inhibition and killing effects on various cancer cell lines. And ATA anti-cancer effect is better than its parental compounds TIIA on some cancer cell lines. At the same time, the mechanism studies showed that ATA can induce cell apoptosis through mitochondrion-dependent pathway. The further investigation revealed that reactive oxygen species (ROS) generation and intracellular Ca2+ level decrease may play an important role in the process of ATA induced apoptosis. Establishment of methods and preliminary screening results demonstrates that our screening platform is a powerful and reliable tool for anti-cancer drug leads discovery. And ATA is a promising anti-cancer compound

An Ensemble Learning and RUL Prediction Method Based on Bearings Degradation Indicator Construction

The prediction of the remaining life of a bearing plays a vital role in reducing the accident-related maintenance costs of machinery and in improving the reliability of machinery and equipment. To predict bearing remaining useful life (RUL), the abilities of statistical characteristics to reflect the bearing degradation state differ, and the single prediction model has low generalization ability and a poor prediction effect. An ensemble robust prediction method is proposed here to predict bearing RUL based on the construction of a bearing degradation indicator set: the initial bearing degradation indicator subsets were constructed using the Fast Correlation-Based Filter with Approximate Markov Blankets (FCBF-AMB) and Maximal Information Coefficient (MIC) selection methods. Through the cross-operation of the obtained subsets, we obtained a set of robust degradation indicators. These selected degradation indicators were fed into the long short-term memory (LSTM) neural network prediction model enhanced by the AdaBoost algorithm. We found through calculation that the average prediction accuracy of the proposed method is 91.40%, 92.04%, and 93.25% at 2100, 2250, and 2400 rpm, respectively. Compared with other methods, the proposed method improves the prediction accuracy by 1.8% to 14.87% at most. Therefore, the method proposed in this paper is more accurate than the other methods in terms of RUL prediction

Predicting Remaining Useful Life of Rolling Bearings Based on Reliable Degradation Indicator and Temporal Convolution Network with the Quantile Regression

High precision and multi information prediction results of bearing remaining useful life (RUL) can effectively describe the uncertainty of bearing health state and operation state. Aiming at the problem of feature efficient extraction and RUL prediction during rolling bearings operation degradation process, through data reduction and key features mining analysis, a new feature vector based on time-frequency domain joint feature is found to describe the bearings degradation process more comprehensively. In order to keep the effective information without increasing the scale of neural network, a joint feature compression calculation method based on redefined degradation indicator (DI) was proposed to determine the input data set. By combining the temporal convolution network with the quantile regression (TCNQR) algorithm, the probability density forecasting at any time is achieved based on kernel density estimation (KDE) for the conditional distribution of predicted values. The experimental results show that the proposed method can obtain the point prediction results with smaller errors. Compared with the existing quantile regression of long short-term memory network(LSTMQR), the proposed method can construct more accurate prediction interval and probability density curve, which can effectively quantify the uncertainty of bearing running state

Optimization of preventive maintenance schedule of subway train components based on a game model from the perspective of failure risk

With the sustainable development of urban transportation systems, the safety and economy of subway trains have become important criteria. However, in the process of formulating the operation and maintenance strategy of subway trains, there is always a conflict of interest between the operator, who aims to improve the operation reliability, and the maintainer, who aims to reduce the maintenance cost. To resolve this conflict, this paper proposes a preventive maintenance decision-making method for subway train components based on a game model. A failure-rate model based on the memory factor was developed and combined with the dynamic attenuation law of a subway train. The failure risk of subway train components was quantitatively evaluated, and a risk penalty cost model was established. Next, a maintenance cost model based on the maintenance reliability and economy was developed. Then, a non-cooperative dynamic game model with operators and maintainers as players was developed, and the balance was solved using the particle swarm optimization algorithm. Finally, the preventive maintenance of the bogie axle box of a subway train was examined for validation. The validation results indicated that the proposed method can balance the interests of the subway train operation and maintenance departments and improve the operation and maintenance decision-making in the field of sustainable cities

Individual Behavior Change under Smart City Environment—A Proposal of Smart Citizen Concept with Four Dimensions

This study proposed a new concept Smart Citizen under smart city environment that has not been noticed before. Smart city has introduced the opportunity for massive information acquisition, digitalization of many life activities, virtual social networking, and consequently, many work has been designed or shifted to be completed through self-service with digital devices such as desktop, laptop, mobile phones etc. Yet we know little about how the life process is being changed by this wave of new technology innovation. Most smart city research focused on either the technology infrastructure or the policy but neglect the most important element of the smart city, the person who lives in the city. This study aims to fill in this research gap by firstly proposing the concept of smart citizen defined in four dimensions of individual behavior, followed by several relevant research questions of each dimension respectively. The four dimensions are (1) slacktivism and knowledge bubble, (2) personal digitalization，(3) virtual social relationship, and (4) digital life process burden. We expect to arouse discussions on how an individual under smart city environment shall respond to these four challenging perspectives

The Emerging of Smart Citizen Concept under Smart City Environment

This study proposed a new concept Smart Citizen under smart city environment that has not been noticed before. Smart city has introduced opportunities for improved citizen wellbeing through digitalization of many activities of our life. The information acquisition, shopping, life style tracking, and social life are all shifting from offline to online, which also creates many burdens in our life. Yet we know little about how the life process is being changed by this wave of new technology innovation. Most smart city research focused either on the technology infrastructure or the policy but neglect the most important element of the smart city is the person who lives in the city. A clear definition and examination of the role of citizens under the smart city environment would help us better cope with the technology. This study proposed a new concept smart citizen with four dimensions, followed by several relevant research questions of each dimension respectively. The four dimensions are (1) slacktivism and knowledge bubble, (2) personal digitalization，(3) virtual social relationship, and (4) digital life process burden. We expect to arouse discussions on how an individual under smart city environment shall respond to these four challenging perspectives