A Strategy and Model of Change for SMEs in the Hong Kong Manufacturing Industry

The re-establishment of the Hong Kong manufacturin g industry as a local pillar of economy is vital in the restructuring of the e conomy in Hong Kong. The SMEs should play a key role in such a process. It requi res major changes to take place in the operation of the enterprises in order to enhance their competitiveness and therefore the chance of success in the restruc turing process. It is suggested that the strategy of going for high value-added products and related services together with the practice of "focused factory" s hould be adopted by the SMEs in the industry. Effective change management by the top managers and owners in the SMEs is an underpinning element for the success. Basing upon the characteristics of the SMEs in the industry, a model of change is proposed. The roles that should be played by the top management and owners in the industry are suggested and discussed. It is believe that the proposal and s uggestions made would help the industry to effectively manage the changes that a re necessary for the industry to shape the competitiveness of the industry in th e world arena in future.

System Recovery-Aware Virus Propagation Model and Its Steady-State Analysis

Network structures and human behaviors are considered as two important factors in virus defense currently. However, due to ignorance of network security, normal users usually take simple activities, such as reinstalling computer system, or using the computer recovery system to clear virus. How system recovery influences virus spreading is not taken into consideration currently. In this paper, a new virus propagation model considering the system recovery is proposed first, and then in its steady-state analysis, the virus propagation steady time and steady states are deduced. Experiment results show that models considering system recovery can effectively restrain virus propagation. Furthermore, algorithm with system recovery in BA scale-free network is proposed. Simulation result turns out that target immunization strategy with system recovery works better than traditional ones in BA network.

Showcasing modeling strategies in the ESOL writing class： Blending rhetorical fluency with grammatical accuracy

This paper argues for an overt innovational shift in praxis, as well as classroom configuration in the ESOL writing class by calling for a move away from the current foci on process-based pedagogies for newcomer populations, to an explicit teaching of modeling strategies with concomitant practice opportunities provided in the ESOL writing class. It is argued that explicit, sequenced instruction in the domains of rhetorical structure as well as grammatical accuracy provide ESOL （English for Speakers of Other Languages） learners in the emerging stages of language learning with a more concrete grasp of meaning, structure and grammar in rhetorical construction. The modeling strategies proposed in the paper focus on a simultaneous building of rhetorical fluency and grammatical accuracy via spotlighted and sequenced strategies which afford learners practice in smaller chunks of composition including but not limited to thesis statement writing, varied paragraph organization, multiple modes of exposition, and grammatical complexity all in a bid to generate rhetorical depth and grammatical detail in writing. In short, both form and function need to be explicitly taught in the ESOL writing class with adequate opportunities provided for rhetorical practice. Using a meticulous blend of meaningful, authentic and purposeful tasks combined with one-on-one instruction which incorporates a variety of visual and rhetorical modeling strategies, emerging writers, it is argued a move from controlled to automatic writing fluency within a short time span. The pedagogy proposed in the current paper spotlights the specific learner, rather than the writing process and entails a move away from traditional, teacher-fronted classrooms to targeted, workshop-centered configurations which permit for one-on-one conferencing in the ESOL writing class. The visually rendered modeling strategies proposed in this paper argue for writing instruction for ESOL students which is learner responsive, relevant and practical.

Transfer Strategy for Power Output Estimation of Wind Farm at Planning Stage Based on a SVR Model

The conventional wind farm(WF)power generation modelling method highly relies on wind hindcast produced by record time-series data or numerical weather modelling.However,estimating production at future sites is challenging in the absence of local wind monitoring.To address this,a data-driven WF modelling and model transfer strategy is proposed in this work.It considers the challenge of how to transpose metered data from existing operational WFs to sites that might feature as a prospective site for a new WF.By modelling 14 WFs distributed across Scotland using a machine learning(ML)approach,this study proved it was possible to effectively model metered production at a site using modelled wind speed and direction.In addition,this study also found when the latitude difference between two WFs is less than 0.2 degrees and the distance is less than 5o km,two WFs in non-mountainous areas can share an ML model.The results of the shared ML model remain superior to the results of the given power curve from manufacturers,after adjusting the results by the ratio of the power curve in these two WFs.The WF model transfer strategy investigated in this work offered a novel approach to transposing WF production estimates to new sites and appeared to offer better value than simple power curves,which is of importance at the early planning stage for site selection,although it would likely not fully replace detailed micro-siting modelling which are well established in the industry.Index Terms-Machine learning,model transfer strategy,power curve,power output estimation,wind farm.

Understanding Differences in Event Attribution Results Arising from Modeling Strategy

While there is high confidence that human activities have increased the likelihood and severity of hot extreme events over many parts of the world,there is notable spread in quantitative estimates of anthropogenic influence even on a single event.To better understand the uncertainty of attribution results,here we compare different event attribution methods using the 2015 July-August record-breaking heat event in northwestern China as a case study.To address the anthropogenic influence on the likelihood of the extreme event,we employ attribution runs with two modeling strategies—atmosphere-only and coupled simulations—with different conditioning.In atmosphere-only attribution runs,given the observed sea surface boundary conditions and external forcings in 2015,it is estimated that anthropogenic forcing has increased the likelihood of hot extremes such as that observed in 2015 in the target region,by approximately 27 and 12 times in MIROC5 and HadGEM3-A-N216,respectively.In Coupled Model Intercomparison Project phase 5(CMIP5)fully coupled attribution runs,given the external forcing at the 1961-2015 level and regardless of sea surface boundary conditions,there is a 21-fold increase in the likelihood of similar heat events due to anthropogenic forcing.The differences in quantitative attribution results can arise from modeling strategies,which are tightly linked to different conditioning in attribution.Specifically,different ocean boundary conditions,external forcings,and air-sea coupling processes contribute to different attribution results between the two modeling strategies.Within each modeling strategy,model uncertainty affects quantitative attribution conclusions.The comparison of different attribution methods provides a better understanding of the uncertainty of attribution results,which is useful in synthesizing and interpreting attribution results.

Simulation of water and nitrogen dynamics as affected by drip fertigation strategies

The aim of drip fertigation is synchronising the application of water and nutrients with crop requirements, and maintaining the proper concentration and distribution of nutrient and water in the soil. The wetting patterns and nutrient distributions under drip fertigation have been proved to be closely related to the fertigation strategies. In order to find out the critical factors that affect the nutrient distribution under different drip fertigaiton strategies, a computer simulation model HYDRUS2D/3D was used to simulate the water and nitrate distribution for various fertigation strategies from a surface point source. Simulation results were compared with the observed ones from our previous studies. A 15° wedge-shaped plexiglass container was used in our experiment to represent one-twenty-fourth of the complete cylinder. The height of container is 40 cm, and the radius is 41 cm. The ammonium nitrate solution was added through a no. 7 needle connected to a Mariotte tube with a flexible hose. The soil water content, nitrate and ammonium concentrations were measured. The comparison of simulated and observed data demonstrated that the model performed reliably. The numerical analysis for various fertigation strategies from a surface point source showed that：（1） The total amount of irrigation water, the concentration of the fertilizer solution and the amount of pure water used to flush the pipeline after fertilizer solution application are the three critical factors influencing the distribution of water and fertilizer nitrogen in the soil.（2） The fresh water irrigation duration prior to fertigation has no obvious effect on nitrate distribution. The longer flushing time period after fertigation resulted in nitrate accumulation closer to the wetting front. From the point of avoiding the possibility of nitrate loss from the root zone, we recommended that the flushing time period should be as shorter as possible.（3） For a given amount of fertilizer, higher concentration of the fertilizer applied solution reduces the potential of nitrate leaching in drip irrigation system. While, lower concentration of the fertilizer solution resulted in an uniform distribution of nitrate band closer to the wetted front.

A novel two-degree-of-freedom spherical ultrasonic motor using three travelling-wave type annular stators

In order to promote the tolerance and controllability of the multi-degree-of-freedom(M-DOF) ultrasonic motor, a novel two-degree-of-freedom(2-DOF) spherical ultrasonic motor using three traveling-wave type annular stators was put forward. Firstly,the structure and working principle of this motor were introduced, especially a spiral spring as the preload applied component was designed for adaptive adjustment. Then, the friction drive model of 2-DOF spherical motor was built up from spatial geometric relation between three annular stators and the spherical rotor which was used to analyze the mechanical characteristics of the motor.The optimal control strategy for minimum norm solution of three stators' angular velocity was proposed, using Moore-Penrose generalized inverse matrix. Finally, a 2-DOF prototype was fabricated and tested, which ran stably and controllably. The maximum no-load velocity and stall torque are 92 r/min and 90 m N·m, respectively. The 2-DOF spherical ultrasonic motor has compact structure, easy assembly, good performance and stable operation.

Recent development of transient electronics

Transient electronics are an emerging class of electronics with the unique characteristic to completely dissolve within a programmed period of time. Since no harmful byproducts are released, these electronics can be used in the human body as a diagnostic tool, for instance, or they can be used as environmentally friendly alternatives to existing electronics which disintegrate when exposed to water. Thus, the most crucial aspect of transient electronics is their ability to disintegrate in a practical manner and a review of the literature on this topic is essential for understanding the current capabilities of transient electronics and areas of future research. In the past, only partial dissolution of transient electronics was possible, however, total dissolution has been achieved with a recent discovery that silicon nanomembrane undergoes hydrolysis. The use of single- and multi-layered structures has also been explored as a way to extend the lifetime of the electronics. Analytical models have been developed to study the dissolution of various functional materials as well as the devices constructed from this set of functional materials and these models prove to be useful in the design of the transient electronics.

Urban Heat Island： Dynamic Simulation, Assessment and Measuring Mitigation in Cities of Extreme Dry Weather

Increasing urbanization in the cities of northern Mexico reflects a general trend to increased temperatures, so it is likely that heat waves amplify the frequency and intensity in urban centers, mainly located in arid and semiarid as Mexicali city with extremely arid climate, very hot in summer and cold and rainy in winter. Mexicali, Baja California, Mexico is located at N32°38＇ and W115°20＇. The urban area is expanded over 14,890 hectares, with a population rise the 689,775. In the last four decades has experienced an accelerated industrial growth and mismatched land uses, for example： most of the industrial parks were established before the 1980 in what was the outskirts of the city, but nowadays practically are inside of the urban area contributing to the increase the urban temperature. The heat islands profile shows that are intensified in industrial areas as well as trade and services. The preliminary scenarios of climate change for Mexicali indicate that for the decade of 2080 the temperature will increase between 4.2℃ and 4.4℃. This paper addresses in a simulation context, an industrial and commercial city sector and their ability to implement urban heat island mitigation strategies. The simulation of this process requires several spatial analysis tools and specific knowledge about the processes that increase urban temperatures. In this work, only land use, land cover and buildings are considered. The proposed method takes into account the actual spatial organization to analyze trends for the proposed growth areas.

Hydrodynamic modeling strategy for dense to dilute gas-solid fluidized beds

When investigating the hydrodynamic behavior of gas–solid flow systems, there are several options for the drag function, viscosity model, and other parameters. The low accuracy obtained with a random trial and error modeling strategy has led researchers to develop new drag models that are fine-tuned for their specific studies. However, besides the drag functions, an appropriate viscosity model together with radial distribution function have a great impact on the hydrodynamic modeling of fluidized beds. In this study, a detailed validation and verification task is conducted using three different experimental datasets to derive a modeling strategy for predicting hydrodynamic behavior in dense to dilute flow regimes of various fluidized beds. For this purpose, the steady-state Reynolds-averaged Navier–Stokes equations are solved in a finite volume scheme using the twoPhaseEulerFoam solver in the OpenFOAM 2.1.1 software. A comparative study of different drag and viscosity models enables an optimal modeling strategy to be determined for the accurate prediction of the bed pressure drop, bed expansion ratio, time-averaged solid hold-up, and bed height in various dense and dilute flow regimes. Our results show that the modeling strategy prescribed in this study is widely applicable for identifying the hydrodynamic characteristics of various gas–solid fluidized beds with different operating conditions.

Unsteady RANS and detached eddy simulation of the multiphase flow in a co-current spray drying

A detached eddy simulation(DES) and a k-ε-based Reynolds-averaged Navier–Stokes(RANS) calculation on the co-current spray drying chamber is presented. The DES used here is based on the Spalart–Allmaras(SA) turbulence model, whereas the standard k-ε(SKE) was considered here for comparison purposes. Predictions of the mean axial velocity, temperature and humidity profile have been evaluated and compared with experimental measurements. The effects of the turbulence model on the predictions of the mean axial velocity, temperature and the humidity profile are most noticeable in the(highly anisotropic) spraying region. The findings suggest that DES provide a more accurate prediction(with error less than 5%) of the flow field in a spray drying chamber compared with RANS-based k-ε models. The DES simulation also confirmed the presence of anisotropic turbulent flow in the spray dryer from the analysis of the velocity component fluctuations and turbulent structure as illustrated by the Q-criterion.

Dynamic optimal strategy for monitoring disease recurrence

Surveillance to detect cancer recurrence is an important part of care for cancer survivors.In this paper we discuss the design of optimal strategies for early detection of disease recurrence based on each patient's distinct biomarker trajectory and periodically updated risk estimated in the setting of a prospective cohort study.We adopt a latent class joint model which considers a longitudinal biomarker process and an event process jointly,to address heterogeneity of patients and disease,to discover distinct biomarker trajectory patterns,to classify patients into different risk groups,and to predict the risk of disease recurrence.The model is used to develop a monitoring strategy that dynamically modifies the monitoring intervals according to patients' current risk derived from periodically updated biomarker measurements and other indicators of disease spread.The optimal biomarker assessment time is derived using a utility function.We develop an algorithm to apply the proposed strategy to monitoring of new patients after initial treatment.We illustrate the models and the derivation of the optimal strategy using simulated data from monitoring prostate cancer recurrence over a 5-year period.

Dangerous Driving Behavior Recognition and Prevention Using an Autoregressive Time-Series Model

Time headway is an important index used in characterizing dangerous driving behaviors. This research focuses on the decreasing tendency of time headway and investigates its association with crash occurrence. An autoregressive（AR） time-series model is improved and adopted to describe the dynamic variations of average daily time headway. Based on the model, a simple approach for dangerous driving behavior recognition is proposed with the aim of significantly decreasing headway. The effectivity of the proposed approach is validated by means of empirical data collected from a medium-sized city in northern China. Finally, a practical early-warning strategy focused on both the remaining life and low headway is proposed to remind drivers to pay attention to their driving behaviors and the possible occurrence of crash-related risks.

Research and development in drug innovation: reflections from the 2013 bioeconomy conference in China, lessons learned and future perspectives

The enormous progress biotechnology,bioinformatics and nanotechnology made in recent years provides opportunities and scientific framework for development of biomedicine and constitutes a paradigm shift in pharmaceutical R&D and drug innovation.By analyzing the data and related information at R&D level over the past decades,developmental tendency and R&D patterns were summarized.We found that a growing number of biologics in the pipeline of pharma companies with successful products already in the market though,small molecular entities have primarily dominated drug innovation.Additionally,small/medium size companies will continue to play a key role in the development of small molecule drugs and biologics in a multi-channel integrated process.More importantly,modern and effective R&D strategies in biomedicine development to predict and evaluate efficacy and/or safety of 21st century therapeutics are urgently needed.To face new challenges,developmental strategies were proposed,in terms of molecular targeted medicine,generic drugs,new drug delivery system and protein-based drugs.Under the current circumstances,interdisciplinary cooperation mode and policy related to drug innovation in China were deeply discussed as well.

Variable-fidelity optimization with design space reduction

Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity （LF） model provides physics-based approximation of the high-fidelity （HF） model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.