具有时滞和旅途过程中有传染的两斑块SIS模型的全局动力学

本文建立了一个具有时滞的SI S模型,研究了旅途过程中疾病的传染.得到了基本再生数.通过线性化方法和比较原理,证明了当基本再生数小于1时无病平衡点是全局渐近稳定的,疾病绝灭.当基本再生数大于1时,系统存在唯一的全局吸引的地方病平衡点,且疾病持续生存.数值模拟验证了扩散率对疾病传播的影响.分析了基本再生数对扩散率的依赖性.     

The impact of acceleration/deceleration on travel-time models in class-based automated S/R systems

The travel time models of Automated Storage and Retrieval systems (AS/RS) machines under randomized storage proposed by Chang et al. (IIE Transactions, 27(1), 108–111, 1995), which consider the speed profiles in real-world applications, are extended in this paper. In the present study, travel time models are proposed that consider various travel speeds with known acceleration and deceleration rates. Compact forms of expected travel times under the class-based storage assignment and full-turnover-based storage assignment have been determined. The results show that both the proposed exponential travel time model and the adjusted exponential model perform satisfactorily and could be useful tools for designing an AS/RS in real-world applications.     

Role of high-dose exposure in transmission hot zones as a driver of SARS-CoV-2 dynamics

Epidemiological data about SARS-CoV-2 spread indicate that the virus is not transmitted uniformly in the population. The transmission tends to be more effective in select settings that involve exposure to relatively high viral dose, such as in crowded indoor settings, assisted living facilities, prisons or food processing plants. To explore the effect on infection dynamics, we describe a new mathematical model where transmission can occur (i) in the community at large, characterized by low-dose exposure and mostly mild disease, and (ii) in so-called transmission hot zones, characterized by high-dose exposure that can be associated with more severe disease. The model yields different types of epidemiological dynamics, depending on the relative importance of hot zone and community transmission. Interesting dynamics occur if the rate of virus release/deposition from severely infected people is larger than that of mildly infected individuals. Under this assumption, we find that successful infection spread can hinge upon high-dose hot zone transmission, yet the majority of infections are predicted to occur in the community at large with mild disease. In this regime, residual hot zone transmission can account for continued virus spread during community lockdowns, and the suppression of hot zones after community interventions are relaxed can cause a prolonged lack of infection resurgence following the reopening of society. This gives rise to the notion that targeted interventions specifically reducing virus transmission in the hot zones have the potential to suppress overall infection spread, including in the community at large. Epidemiological trends in the USA and Europe are interpreted in light of this model.     

Transmission and control of an emerging influenza pandemic in a small-world airline network

The avian influenza virus H5N1 and the 2009 swine flu H1N1 are potentially serious pandemic threats to human health, and air travel readily facilitates the spread of infectious diseases. However, past studies have not yet incorporated the effects of air travel on the transmission of influenza in the construction of mathematical epidemic models. Therefore, this paper focused on the human-to-human transmission of influenza, and investigated the effects of air travel activities on an influenza pandemic in a small-world network. These activities of air travel include passengers’ consolidation, conveyance and distribution in airports and flights. Dynamic transmission models were developed to assess the expected burdens of the pandemic, with and without control measures. This study also investigated how the small-world properties of an air transportation network facilitate the spread of influenza around the globe. The results show that, as soon as the influenza is spread to the top 50 global airports, the transmission is greatly accelerated. Under the constraint of limited resources, a strategy that first applies control measures to the top 50 airports after day 13 and then soon afterwards to all other airports may result in remarkable containment effectiveness. As the infectiousness of the disease increases, it will expand the scale of the pandemic, and move the start time of the pandemic ahead.     

A discrete-time Bayesian network reliability modeling and analysis framework

Dependability tools are becoming an indispensable tool for modeling and analyzing (critical) systems. However the growing complexity of such systems calls for increasing sophistication of these tools. Dependability tools need to not only capture the complex dynamic behavior of the system components, but they must be also easy to use, intuitive, and computationally efficient. In general, current tools have a number of shortcomings including lack of modeling power, incapacity to efficiently handle general component failure distributions, and ineffectiveness in solving large models that exhibit complex dependencies between their components. We propose a novel reliability modeling and analysis framework based on the Bayesian network (BN) formalism. The overall approach is to investigate timed Bayesian networks and to find a suitable reliability framework for dynamic systems. We have applied our methodology to two example systems and preliminary results are promising. We have defined a discrete-time BN reliability formalism and demonstrated its capabilities from a modeling and analysis point of view. This research shows that a BN based reliability formalism is a powerful potential solution to modeling and analyzing various kinds of system components behaviors and interactions. Moreover, being based on the BN formalism, the framework is easy to use and intuitive for non-experts, and provides a basis for more advanced and useful analyses such as system diagnosis.     

Numerical solution of second‐order,two‐point boundary value problems using continuous genetic algorithms

Second‐order, two‐point boundary‐value problems are encountered in many engineering applications including the study of beam deflections, heat flow, and various dynamic systems. Two classical numerical techniques are widely used in the engineering community for the solution of such problems; the shooting method and finite difference method. These methods are suited for linear problems. However, when solving the non‐linear problems, these methods require some major modifications that include the use of some root‐finding technique. Furthermore, they require the use of other basic numerical techniques in order to obtain the solution. In this paper, the author introduces a novel method based on continuous genetic algorithms for numerically approximating a solution to this problem. The new method has the following characteristics; first, it does not require any modification while switching from the linear to the non‐linear case; as a result, it is of versatile nature. Second, this approach does not resort to more advanced mathematical tools and is thus easily accepted in the engineering application field. Third, the proposed methodology has an implicit parallel nature which points to its implementation on parallel machines. However, being a variant of the finite difference scheme with truncation error of the order O(h²), the method provides solutions with moderate accuracy. Numerical examples presented in the paper illustrate the applicability and generality of the proposed method. Copyright © 2004 John Wiley & Sons, Ltd.     

Industrial statistics: The challenges and the research

ABSTRACT

Industrial problems have stimulated an enormous amount of valuable statistical research, from the t-test to advanced statistical tools for quality. Industry continues to generate challenging problems for statistical design, modeling, and analysis. Useful articles are published in our journals, often stimulated by industrial applications. Nonetheless, there is concern that research in industrial statistics is falling well short of its potential for providing interesting problems, that some of the most exciting problems are not getting space in our journals, and that few statisticians working in industry are publishing research. This article endeavors to map out the current state of research in industrial statistics, to describe major issues that need to be addressed, and to discuss whether the research is on target to meet those challenges.     

Privacy Data Management Mechanism Based on Blockchain and Federated Learning

Due to the extensive use of various intelligent terminals and the popularity of network social tools, a large amount of data in the field of medical emerged. How to manage these massive data safely and reliably has become an important challenge for the medical network community. This paper proposes a data management framework of medical network community based on Consortium Blockchain (CB) and Federated learning (FL), which realizes the data security sharing between medical institutions and research institutions. Under this framework, the data security sharing mechanism of medical network community based on smart contract and the data privacy protection mechanism based on FL and alliance chain are designed to ensure the security of data and the privacy of important data in medical network community, respectively. An intelligent contract system based on Keyed-Homomorphic Public Key (KH-PKE) Encryption scheme is designed, so that medical data can be saved in the CB in the form of ciphertext, and the automatic sharing of data is realized. Zero knowledge mechanism is used to ensure the correctness of shared data. Moreover, the zero-knowledge mechanism introduces the dynamic group signature mechanism of chosen ciphertext attack (CCA) anonymity, which makes the scheme more efficient in computing and communication cost. In the end of this paper, the performance of the scheme is analyzed from both asymptotic and practical aspects. Through experimental comparative analysis, the scheme proposed in this paper is more effective and feasible.     

Using Theory to Inform Capacity‐Building: Bootstrapping Communities of Practice in Computer Science Education Research

In this paper, we describe our efforts in the deliberate creation of a community of practice of researchers in computer science education (CSEd). We understand community of practice in the sense in which Wenger describes it, whereby the community is characterized by mutual engagement in a joint enterprise that gives rise to a shared repertoire of knowledge, artefacts, and practices. We first identify CSEd as a research field in which no shared paradigm exists, and then we describe the Bootstrapping project, its metaphor, structure, rationale, and delivery, as designed to create a community of practice of CSEd researchers. Features of other projects are also outlined that have similar aims of capacity building in disciplinary‐specific pedagogic enquiry. A theoretically derived framework for evaluating the success of endeavours of this type is then presented, and we report the results from an empirical study. We conclude with four open questions for our project and others like it: Where is the locus of a community of practice? Who are the core members? Do capacity‐building models transfer to other disciplines? Can our theoretically motivated measures of success apply to other projects of the same nature?     

Mosquito-larvicidal efficacy of gold nanoparticles synthesized from the seaweed,Turbinaria ornata (Turner) J.Agardh 1848

Malaria is considered a dreadful mosquito-borne infectious disease of human beings caused and spread by biting of the female mosquito Anopheles stephensi infected with a parasitic protozoan Plasmodium falciparum. Continuous application of chemicals/synthetic insecticides for vector control causes various problems such as resistant mechanism of mosquito, toxicity to nontarget aquatic organisms and disturbance to the microbial community of the soil. Currently, green synthesized nanoparticles are being employed in various biological processes including insect and pest control. The present investigation focused on the mosquito-larvicidal property of Turbinaria ornata-mediated gold nanoparticles (To-AuNPs) and its boiled aqueous extract (To-AE) against the malarial vector A. stephensi. The recorded lethal concentration (LC₅₀ and LC₉₀) values (µg/ml) of To-AE and To-AuNPs against fourth instar larvae of A. stephensi were 37.77 and 159.55 and 12.79 and 78.70, respectively. The To-AuNPs were characterized through UV-visible spectroscopy, Fourier transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), energy dispersive x-ray spectroscopy (EDX), zeta potential and dynamic light scattering (DLS) method. The presently synthesized gold nanoparticles through the single-step, eco-friendly method is a potentially effective mosquitocidal agent.     

Predicting the frequency of median barrier crashes on Pennsylvania interstate highways

Median barrier warrant criteria were developed in the 1970s and generally remain unchanged today. Vehicle travel, including both traffic volumes and operating speeds, have increased over this same time period. Encroachments into the median, and subsequent collisions with vehicles traveling in the opposite travel lanes, result in high severity crashes. Median barrier is typically used to prevent cross-median crashes; median barrier selection is based on median width and traffic volumes. Quantifiable information regarding the effects of median barrier installation and its placement on crash frequency is limited. This paper investigates median barrier crash frequency on Pennsylvania Interstate highways, including separate models for the Turnpike and all other Interstate-designated highways. Negative binomial regression models were used to develop predictive crash frequency tools. Traffic volume, horizontal alignment, interchange ramp presence, and median barrier offset distance from the travel lanes were used to estimate median barrier crash frequency. The analytical methodology developed in this research can be used, in concert with other prediction models, to assess the consequences of median barrier placement decisions.     

Analytical and Numerical Solution of the Stress Field and the Dynamic Stress Intensity Factors in a Cracked Plate under Sinusoidal Loading

A cracked plate subjected to a sinusoidal loading perpendicular to its plane is considered, and the analytical solution of the dynamic vibration behavior of a plate, which allowed the determination of the stress field near the crack tip, is developed. A mixed mode of loading near the crack tip has been established and described with dynamic stress intensity factors K _I (z,t) and K _II (z,t) associated with modes I and II crack openings, respectively. To validate the analytical results, a finite element analysis (FEA) of a 1 × 1 m square plate with a thickness of 1 cm, having a middle crack of 10 cm in length, is made. The results have shown significant agreement between analytical and FEA findings.     

Analysis and simulation of an Adefovir anti‐hepatitis B virus infection therapy immune model with alanine aminotransferase

Hepatitis B virus (HBV) infection models and anti‐HBV infection therapy models have been set up to understand and explain clinical phenomena. Many of these models have been proposed based on Zeuzem et al. and Nowak et al.''s basic virus infection model (BVIM). Some references have pointed out that the basic infection reproductive number of the BVIM is biologically questionable and gave the modified models with standard mass action incidences. This study describes one anti‐HBV therapy immune model with alanine aminotransferase (ALT) based on standard mass action incidences. There are two basic infection reproductive numbers R ₀ and R ₁ in the model. It is proved that if R ₀ < 1 and R ₁ < 1, the disease free equilibrium is locally and globally asymptotically stable, respectively. For the endemic equilibrium, simulation shows that if R ₁ > 1, it may be also globally asymptotically stable. Simulations based on clinical data of HBV DNA and ALT can explain some clinical phenomena. Simulations of the correlation between liver cells, HBV DNA, cytotoxic T lymphocytes and ALT are also given.Inspec keywords: blood, cellular biophysics, diseases, DNA, enzymes, liver, microorganisms, molecular biophysics, patient treatmentOther keywords: Adefovir antihepatitis B virus infection therapy immune model analysis, Adefovir antihepatitis B virus infection therapy immune model simulation, alanine aminotransferase, clinical phenomena, basic infection reproductive number, standard mass action incidences, disease free equilibrium, asymptotic stability, endemic equilibrium, HBV DNA, ALT, liver cells, cytotoxic T lymphocytes     

A combined rh‐adaptive scheme based on domain subdivision. Formulation and linear examples

An adaptive scheme is proposed in which the domain is split into two subdomains. One subdomain consists of regions where the discretization is refined with an h‐adaptive approach, whereas in the other subdomain node relocation or r‐adaptivity is used. Through this subdivision the advantageous properties of both remeshing strategies (accuracy and low computer costs, respectively) can be exploited in greater depth. The subdivision of the domain is based on the formulation of a desired element size, which renders the approach suitable for coupling with various error assessment tools. Two‐dimensional linear examples where the analytical solution is known illustrate the approach. It is shown that the combined rh‐adaptive approach is superior to its components r‐ and h‐adaptivity, in that higher accuracies can be obtained compared to a purely r‐adaptive approach, while the computational costs are lower than that of a purely h‐adaptive approach. As such, a more flexible formulation of adaptive strategies is given, in which the relative importance of attaining a pre‐set accuracy and speeding‐up the computational process can be set by the user. Copyright © 2001 John Wiley & Sons, Ltd.     

Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges

The complexity of the systemic inflammatory response and the lack of a treatment breakthrough in the treatment of pathogenic infection demand that advanced tools be brought to bear in the treatment of severe sepsis and trauma. Systems medicine, the translational science counterpart to basic science''s systems biology, is the interface at which these tools may be constructed. Rapid initial strides in improving sepsis treatment are possible through the use of phenomenological modelling and optimization tools for process understanding and device design. Higher impact, and more generalizable, treatment designs are based on mechanistic understanding developed through the use of physiologically based models, characterization of population variability, and the use of control-theoretic systems engineering concepts. In this review we introduce acute inflammation and sepsis as an example of just one area that is currently underserved by the systems medicine community, and, therefore, an area in which contributions of all types can be made.     

Performing Changes in Product Development: A Framework with Keys for Industrial Application

Industrial product development requires continuous improvements in work procedures as a result of constantly changing demands. Support tools have proven to be an oft chosen way to meet new demands; however, few research efforts have been made in how to implement new tools. This article is a contribution to knowledge on carrying out the implementation of support tools. The basis consists of four field studies performed during 1994–1999, containing 78 qualitative research interviews and focusing on the implementation and use of different support tools. A re-analysis has been performed of selected interviews from the field studies, in total 30 interviews. This resulted in recommendations for an implementation framework, consisting of an Implementation Cycle, Organizational Change Field and Managerial Consistence, and five implementation keys: Goal setting, Kowledge Development, Anchoring at All Levels, Suitable Resources and Focus on the Individual.     

Hemodialysis for an unusual occurrence of leptospirosis in a nonendemic region

Leptospirosis, an endemic zoonotic disease caused by Leptospira, is frequently seen in tropical regions and areas with low socioeconomic status. The disease can present a range of symptoms from mild to fatal, with potential involvement of multiple organs. This case report describes the treatment and clinical course of a 44-year-old male patient infected with Leptospira semeranga patoc 1 and presenting with jaundice and renal failure. The patient was residing in the Syrian Refugee Camp in the arid city of Sanliurfa. This case serves as an example of a nonendemic occurrence of leptospirosis, and a brief overview of relevant literature on the subject is also provided.     

News in brief and features in New Scientist magazine and the biomedical research papers that they cite,August 2008 to July 2009

New Scientist is a British weekly magazine that is half-way between a newspaper and a scientific journal. It has many news items, and also longer feature articles, both of which cite biomedical research papers, and thus serve to make them better known to the public and to the scientific community, mainly in the UK but about half overseas. An analysis of these research papers shows (in relation to their presence in the biomedical research literature) a strong bias towards the UK, and also one to the USA, Scandinavia and Ireland. There is a reasonable spread of subject areas, although neuroscience is favoured, and coverage of many journals—not just the leading weeklies. Most of the feature articles (but not the news items) in New Scientist include comments by other researchers, who can put the new results in context. Their opinions appear to be more discriminating than those of commentators on research in the mass media, who usually enthuse over the results while counselling patience before a cure for the disease is widely available.