Specific Modeling Research Articles

On Modeling Antennas Using MoM-Based Algorithms: Wire-Grid versus Surface Triangulation

This paper focuses on antenna modeling using wire-grid and surface triangulation as two of the most commonly used MoM-based approaches in this field. A comprehensive overview is provided for each of them, including their history, applications, and limitations. The mathematical background of these approaches is briefly presented. Two working algorithms were developed and described in detail, along with their implementations using acceleration techniques. The wire-grid-based algorithm enables modeling of arbitrary antenna solid structures using their equivalent grid of wires according to a specific modeling recommendation proposed in earlier work. On the other hand, the surface triangulation-based algorithm enables calculation of antenna characteristics using a novel excitation source model. Additionally, a new mesh generator based on the combined use of the considered algorithms is developed. These algorithms were used to estimate the characteristics of several antenna types with different levels of complexity. The algorithms computational complexities were also obtained. The results obtained using these algorithms were compared with those obtained using the finite difference time domain numerical method, as well as those calculated analytically and measured. The analysis and comparisons were performed on the example of a rectangle spiral, a spiral, rounded bow-tie planar antennas, biconical, and horn antennas. Furthermore, the validity of the proposed algorithms is verified using the Monte Carlo methodology.

Technology in World Civilization: A Thousand-Year History by Arnold Pacey and Francesca Bray

Reviewed by: Technology in World Civilization: A Thousand-Year History by Arnold Pacey and Francesca Bray Jennifer Karns Alexander (bio) Technology in World Civilization: A Thousand-Year History Revised and expanded edition. By Arnold Pacey and Francesca Bray. Cambridge, MA: MIT Press, 2021. Pp. 338. Arnold Pacey collaborates with Francesca Bray in a new edition of his classic survey, Technology in World Civilization (TWC). What a delight it is! A wealth of examples appears: cooking stoves with ceramic linings (Kenya), gas-engine dynamos (England), astrolabes with beautifully etched tympans (Marrakesh), a machine for reeling silk (China)—and these examples come just from the illustrations—alongside concise and satisfying technical descriptions: how block printing was done and early guns cast and the significance of semiconducting materials. The first edition offered a strong interpretive framework, which is slightly different and more precisely drawn in the new one. Less apparent is the interest in technology transfer that previously motivated Pacey; more developed is the concept of technological dialogue and frameworks of environmental constraint and industrial movements and/or revolutions (as plural processes that happened more than once). TWC gives us a "thousand-year history as a continuous, global process of dialogue or exchange" (p. xv) among and beyond China, West Asia, Africa, South America, the Islamic Mediterranean, India, and Europe, broadly considered. The book is a model of concrete discussion and historical specificity, with every technology tied to specific places, people, and times. We see important historical debates as scholars saw them: Karl Wittfogel and hydraulic civilizations; Christopher Freeman and waves of innovation; Tessa Morris-Suzuki and technology transfer as creative, not copying. Pacey and Bray move from the iron industry of Asia around the year 1000 to technological complexes of nomadic Mongol culture and different agricultural regions of China and the Middle East. Next come movement, trade and technologies of transport, and agroecology in the Americas. A three-way dialogue appears in mining in Zimbabwe under the Portuguese and in the crops the Portuguese had introduced: maize and peanuts from the Americas that endured long after [End Page 578] the Changamire drove the Portuguese off Zimbabwe's southern plateaus. Gunpowder empires illustrate Japan's experience with firearms, unification, and international withdrawal. Printing and books brought "new methods for handling technical information and formulating technical (and managerial) ideas" (p. 112), expressed in machine drawings and in factories and plantations, as in the novel organization of plantation sugar production on Madeira and strict divisions of labor that came to characterize later manufacturing. The new TWC is a book for our time, as we reassess our technological heritage in light of its effect on our planet's climate. About halfway through, TWC turns to the development of industry and patterns that endure. Language that in the previous edition suggested general approbation of industrial development has been excised: a "decisive advantage … [in] material production" gained by the West has become simply a "situation very different" (p. 128) from elsewhere. Pacey and Bray offer industrial movements rather than a singular industrial revolution: in Britain of "steam engines, iron, and coal" (p. 129) and changes in productive organization; in India of textiles and supporting chemical industries and in wooden ship building. Railway empires show the imperial ambitions of Europe and Japan. Scientific developments influenced and drew from technology: electricity and chemistry in France and Germany; nuclear research seemingly, and worryingly, all over the place. The inescapable dialogue of technology with health, food, and basic needs appears in discussions of public health and infant mortality, the green revolution in Asia, agroforestry in the Americas, and everyday cooking technologies in recent African history. The final chapter carries TWC into our current century, using the concept of waves of innovation—that is, innovations interacting and bunching together—to trace the continued significance of semiconductors and communications and the developing importance of photovoltaics and new batteries. TWC concludes with a discussion of environmental limits, climate change, and the need for a "radical switch to non-polluting energy sources" (p. 258) to power a twenty-first-century industrial revolution. This final chapter marks the most significant change from Pacey's first edition, which concluded with a chapter on "Survival Technology in the Twentieth...

Modeling Linkages among Urban Agglomeration, Construction Industry, Non-Renewable Energy, and Zero-Carbon Future

On the one hand, the twin perspectives of the construction industry and urban agglomeration proliferate economic prosperity. However, on the other hand, construction activities and increased population density give rise to environmental challenges. This study is an initial attempt to explore links between the construction industry, urban agglomeration, non-renewable energy utilization, carbon dioxide emissions (CO2e), and economic output within a system of simultaneous equation modeling. This study develops modeling specifications to include the construction industry as a shifting factor and CO2e as a determinant of technical efficiency. A heterogeneous fully modified ordinary least squares (FMOLS) technique, capable of providing concrete empirical outcomes even in the presence of modern panel-data econometric issues, is utilized for the data of China’s 30 provincial/ city divisions during the 2003–2019 period. It has been revealed that: (i) the influence of urban agglomeration on the economic output was heterogeneous, with an adverse link for China’s western part, neutrality connection for the central part, and favorable for China’s eastern part; and (ii) shifting from China’s western to eastern parts, the expansion of the construction industry has a significant impact on economic output, and, hence, has been described as “the Economic Effects of Urban agglomeration” for the Chinese economy. The policies of this study have crucial lessons for global economies.

Social Jeopardy of Substance Use among Adolescents: A Review to Recognize the Common Risk and Protective Factors at the Global Level

Adolescence is a phase of life between childhood and adulthood marked by rapid biological, social and psychological changes. During this phase, individuals bear a more emotional and curious mind and may engage in risky behaviours. Decades of investigations have revealed that substance use usually begins in adolescence. The main essence of this paper is to carry out an elaborative review of earlier works to recognize familiar risks and protective factors for substance use among adolescents at the global level. Additional emphasis was given to identifying the various statistical modelling approaches, widely used in earlier studies, to promote research methodological issues for future research in this specific domain. Articles published from 1991 to 2021 on adolescent substance use were downloaded, and after carrying out a preliminary full-text review, 50 articles were selected keeping the priority of the aforementioned objectives. After an intensive review, risk factors were identified and clustered around five broad domains such as individual, parental, familial, peer and environmental factors. Protective factors were also categorized under the headings of five broad domains viz. individual, parental, familial, social and interventional. Specific statistical modelling techniques were identified to evaluate the relative risk of specific groups of adolescents being in the clutches of substance use. It is necessary to recognise the potential risk and protective factors and their combined effect on substance use among adolescents to prevent this menace from society. For a better understanding of research about the exact vulnerable age of onset of substance use during the adolescence period, both the orthogonally placed risk and protective factors necessarily need to be distinguished with an attempt to protect adolescents from the further abuse of substances, as recognised by parents and society. To prevent substance use, interventions such as regulating substance price & accessibility, school intervention programs, academic monitoring, social support, clear expectations between parents and child, addressing family trauma, awareness activities, healthy lifestyle habits, mental health support, family health counselling and substance abuse treatment should be implemented.

Drivers of the decrease of patent similarities from 1976 to 2021.

The citation network of patents citing prior art arises from the legal obligation of patent applicants to properly disclose their invention. One way to study the relationship between current patents and their antecedents is by analyzing the similarity between the textual elements of patents. Many patent similarity indicators have shown a constant decrease since the mid-70s. Although several explanations have been proposed, more comprehensive analyses of this phenomenon have been rare. In this paper, we use a computationally efficient measure of patent similarity scores that leverages state-of-the-art Natural Language Processing tools, to investigate potential drivers of this apparent similarity decrease. This is achieved by modeling patent similarity scores by means of generalized additive models. We found that non-linear modeling specifications are able to distinguish between distinct, temporally varying drivers of the patent similarity levels that explain more variation in the data (R2 ∼ 18%) compared to previous methods. Moreover, the model reveals an underlying trend in similarity scores that is fundamentally different from the one presented previously.

Experimental and numerical studies of screwed connections with hot-rolled steel plate and cold-formed steel sheet

This paper presents a test and numerical program on screwed connections of cold-formed steel (CFS) sheets and hot-rolled steel (HRS) plates. The shear strength, load–deformation relationship, and failure mode of the specimens were obtained. The test results were compared with the results predicted by the North American Specification (AISI S 100–16), European Standard (EN1993-1–3), and finite element (FE) models. The influence of the fastener diameter and thickness of the CFS sheet and HRS plate on the specimens was discussed. In addition, a new method of calculating the bearing capacity of the connections with thicker plates was proposed. The results showed that bearing failure, shear failure, and combined bearing/shear failure were observed in the specimens. The nominal strengths predicted by AISI S 100 and EN 1993–1–3 for specimens are generally conservative. The numerical models can predict the failure modes and load–deformation relationships of the specimens with good agreement. In addition, the proposed method for the bearing capacity has better accuracy when the connections have thicker HRS plates.

State of broker–dealer leverage and the transmission of monetary policy

AbstractThis paper investigates how responses of US macroeconomic activities to monetary policy shocks depend on the state of broker–dealer leverage. The analysis makes use of leverage data to create an indicator series that distinguishes above and below-trend leverage states for the economy which is then integrated into switching econometric models. Using state-dependent local projection methods, we find that during the below-trend leverage state, monetary policy affects the economy in a traditional fashion. However, during the above-trend leverage state, expansionary monetary policy is problematic for stimulating the economy. Additionally, during the above-trend leverage state, we find that a policy rate cut raises counterparty risks in financial markets, which in part accounts for the weaker effectiveness of the monetary policy. These findings are robust to several alternative modeling specifications and suggest that monetary policy authorities should monitor the leverage cycle when determining their policy stance on macroeconomic stability.

An Overview of Selected Material Properties in Finite Element Modeling of the Human Femur

Specific finite detail modeling of the human body gives a capable primary enhancement to the prediction of damage risk through automobile impact. Currently, car crash protection countermeasure improvement is based on an aggregate of testing with installed anthropomorphic test devices (i.e., ATD or dummy) and a mixture of multibody (dummy) and finite element detail (vehicle) modeling. If an incredibly easy finite element detail version can be advanced to capture extra statistics beyond the abilities of the multi-body structures, it might allow advanced countermeasure improvement through a more targeted prediction of overall performance. Numerous research has been done on finite element analysis of broken femurs. However, there are two missing pieces of information: 1- choosing the right material properties, and 2- designing a precise model including the inner structure of the bone. In this research, most of the chosen material properties for femur bone will be discussed and evaluated.

Modeling Historical and Future Forest Fires in South Korea: The FLAM Optimization Approach

Climate change-induced heat waves increase the global risk of forest fires, intensifying biomass burning and accelerating climate change in a vicious cycle. This presents a challenge to the response system in heavily forested South Korea, increasing the risk of more frequent and large-scale fire outbreaks. This study aims to optimize IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM)—a processed-based model integrating biophysical and human impacts—to South Korea for projecting the pattern and scale of future forest fires. The developments performed in this study include: (1) the optimization of probability algorithms in FLAM based on the national GIS data downscaled to 1 km2 with additional factors introduced for national specific modeling; (2) the improvement of soil moisture computation by adjusting the Fine Fuel Moisture Code (FFMC) to represent vegetation feedbacks by fitting soil moisture to daily remote sensing data; and (3) projection of future forest fire frequency and burned area. Our results show that optimization has considerably improved the modeling of seasonal patterns of forest fire frequency. Pearson’s correlation coefficient between monthly predictions and observations from national statistics over 2016–2022 was improved from 0.171 in the non-optimized to 0.893 in the optimized FLAM. These findings imply that FLAM’s main algorithms for interpreting biophysical and human impacts on forest fire at a global scale are only applicable to South Korea after the optimization of all modules, and climate change is the main driver of the recent increases in forest fires. Projections for forest fire were produced for four periods until 2100 based on the forest management plan, which included three management scenarios (current, ideal, and overprotection). Ideal management led to a reduction of 60–70% of both fire frequency and burned area compared to the overprotection scenario. This study should be followed by research for developing adaptation strategies corresponding to the projected risks of future forest fires.

Using Pop-GUIDE to Assess the Applicability of MCnest for Relative Risk of Pesticides to Hummingbirds

Hummingbirds are charismatic fauna that provide important pollination services, including in the continental US, where 15 species regularly breed. Compared to other birds in North America, hummingbirds (family Trochilidae) have a unique exposure route to pesticides because they forage on nectar. Therefore, hummingbirds may be exposed to systemic pesticides borne in nectar. They also may be particularly vulnerable to pesticide exposure due to their small size and extreme metabolic demands. We review relevant factors including hummingbird life history, nectar residue uptake, and avian bioenergetic considerations with the goal of clearly identifying and articulating the specific modeling challenges that must be overcome to develop and/or adapt existing modeling approaches. To help evaluate these factors, we developed a dataset for ruby-throated hummingbirds (Archilochus colubris) and other avian species potentially exposed to pesticides. We used the systemic neonicotinoid pesticide imidacloprid as an illustration and compared results to five other common current use pesticides. We use the structure of Pop-GUIDE to provide a conceptual modeling framework for implementation of MCnest and to compile parameter values and relevant algorithms to predict the effects of pesticide exposure on avian pollinators. Conservative screening assessments suggest the potential for adverse effects from imidacloprid, as do more refined assessments, though many important limitations and uncertainties remain. Our review found many areas in which current USEPA avian models must be improved in order to conduct a full higher-tier risk assessment for avian pollinators exposed to neonicotinoid insecticides, including addition of models suitable for soil and seed treatments within the MCnest environment, ability to include empirical residue data in both nectar and invertebrates rather than relying on existing nomograms, expansion of MCnest to a full annual cycle, and increased representation of spatial heterogeneity. Although this work focuses on hummingbirds, the methods and recommendations may apply more widely to other vertebrate pollinators.

Combining generalized modeling and specific modeling in the analysis of ecological networks.

The complexity of real food webs involves uncertainty in data and in underlying ecological processes, and modeling approaches deal with these challenges differently. Generalized modeling provides a linear stability analysis without narrow specification of all processes, and conventional dynamical systems models approximate functional forms to discuss trajectories in phase space. This study compares results and ecological interpretations from both methods in four-species ecological networks at steady state. We find that a specific (dynamical systems) model only provides a subset of stability data from the generalized model, which spans many plausible dynamic scenarios, allowing for conflicting results. Nevertheless, both approaches reveal that fixed points become stable when nutrient flows to predators are fettered and even more when the basal growth rate approaches a maximum. The specific model identifies a distinct ecosystem response to bottom-up forcing, the enrichment of lower trophic levels. Enrichment stabilizes a fixed point when basal species are in a resource-deprived environment but destabilizes it if resources become more abundant. The generalized model provides less specific information since infinitely many paths of enrichment are hypothetical. Nevertheless, generalized modeling of ecological systems is a powerful technique that enables a meta analysis of these uncertain complex systems.

Modeling language for the function-oriented development of mechatronic systems with motego

As mechatronic products gain in popularity, methods for mastering the complexity of these systems in development become increasingly relevant, such as model-based systems engineering (MBSE). Main pillars of MBSE are method, language and tool. A method specifies procedures in product development. The application of the method is supported by a language and tool as the language specifies a system of symbols with which development artifacts can be represented in a software environment (i.e. tool). Currently, various MBSE methods exist, such as motego. Motego specifies a framework for the function-oriented seamless development of mechatronic systems from requirements to the physical realization down to mechanical and electrical contacts and the description of these via parameters and models. Central element in MBSE is the system model, which connects all relevant development artefacts. The system model is created with a language in a software environment such as Cameo Systems Modeler. In MBSE, the graphical systems modeling language SysML is widely established. The language elements in SysML are very abstract and numerous. As a result, the language is difficult to apply. However, its reasonable applicability is an essential prerequisite for the introduction of the motego methods in industrial practice. This results in the following research need: A specific modeling language for the motego method is needed that supports its reasonable application. Therefore, in this paper a modeling language is presented whose language elements are specifically adapted to the motego method. With the help of this domain specific language, the user is guided through method-compliant modeling.

A corrected p-y curve model for large-diameter pile foundation of offshore wind turbine

With the development of pile-soil interaction theory, at present the sand p-y model of API specification is adopted to the analysis and calculation of large diameter piles under horizontal static load, but the results of the ultimate soil resistance at different depths is underestimated and the initial foundation reaction modulus is overestimated, thus the calculation results are obtained with large errors. For this problem, a finite element numerical model of pile-soil interaction is established in this study, and the calculation models under horizontal static load with different pile diameters and soil depth are analyzed and the data regression is carried out. A correction coefficient is introduced to consider the size effect of large diameter pile, and the variation law of influence index of different factors is discussed. Finally, a corrected sand p-y curve model for single pile foundation with large diameter more than 2 m is proposed. Compared with the results of model test and field test, the calculation results of ultimate soil resistance and initial foundation reaction modulus from the corrected model is more in accord with the actual situation.

Modeling of drilling water supply wells with airlift reverse flush agent circulation

Purpose. Determination of the influence of mining and geological conditions of drilling hydrogeological wells with backwash on the technological parameters of the airlift method of cleaning it from drilled rock and the properties of the ascending flow of aerated washing liquids. Methodology. The tasks were solved by a complex research method, including analysis and generalization of literary and patent sources, analytical, experimental studies, using computer and mathematical modeling methods. Findings. An algorithm for the functioning of the airlift circulation method during rotary drilling with backwash has been developed. The algorithm takes into account: hydrostatic and hydrodynamic pressures, and the effect on them of the rate of drilling of the well; the effect of the sludge content in the upstream. The effective values of the airflow rate, the density of the water-air mixture and the velocity of its upward flow are established. A method for estimating the effective values of technological parameters and their changes in the upward flow of the mixture is proposed. A model has been developed that allows analyzing the dependences of the air flow rate, the density of the mixture and the rate of its ascent on the parameters of the well being drilled. The model is applied to typical drilling conditions of a large-diameter water intake well at the Samskoye groundwater deposit on the Mangystau peninsula. Originality. A mathematical algorithm has been developed for the functioning of the airlift backwash method when drilling large-diameter water intake wells. The method is based on the analysis of the pressure balance in the descending and ascending flows of the washing agent. For the case of backwash, a formula for estimating the content of sludge in it was obtained. A method has been developed for determining the average effective density of the mixture in terms of the height of the well, as well as the air content in it. Based on the average effective values, a method is proposed for estimating changes in the density of the mixture, its flow rate and velocity along the upward flow. Practical value. The proposed algorithm is the basis of a computer model that allows you to determine the dependences of the values of the density of the mixture, the content of air and sludge in it and the rate of ascent, from the depth of the well, the depth of the mixer descent, the speed of deepening, the specified velocity of the upward fluid flow, as well as the diameters of the well and drill pipes. Specific modeling results have been obtained in relation to the Samskoye groundwater deposit of the Mangystau peninsula.

Hollow-fibre system model of tuberculosis reproducibility and performance specifications for best practice in drug and combination therapy development.

The hollow-fibre system model of tuberculosis (HFS-TB) has been endorsed by regulators; however, application of HFS-TB requires a thorough understanding of intra- and inter-team variability, statistical power and quality controls. Three teams evaluated regimens matching those in the Rapid Evaluation of Moxifloxacin in Tuberculosis (REMoxTB) study, plus two high-dose rifampicin/pyrazinamide/moxifloxacin regimens, administered daily for up to 28 or 56 days against Mycobacterium tuberculosis (Mtb) under log-phase growth, intracellular growth or semidormant growth under acidic conditions. Target inoculum and pharmacokinetic parameters were pre-specified, and the accuracy and bias at achieving these calculated using percent coefficient of variation (%CV) at each sampling point and two-way analysis of variance (ANOVA). A total of 10 530 individual drug concentrations, and 1026 individual cfu counts were measured. The accuracy in achieving intended inoculum was >98%, and >88% for pharmacokinetic exposures. The 95% CI for the bias crossed zero in all cases. ANOVA revealed that the team effect accounted for <1% of variation in log10 cfu/mL at each timepoint. The %CV in kill slopes for each regimen and different Mtb metabolic populations was 5.10% (95% CI: 3.36%-6.85%). All REMoxTB arms exhibited nearly identical kill slopes whereas high dose regimens were 33% faster. Sample size analysis revealed that at least three replicate HFS-TB units are needed to identify >20% difference in slope, with a power of >99%. HFS-TB is a highly tractable tool for choosing combination regimens with little variability between teams, and between replicates.

On the global dynamics of path-following control of automated passenger vehicles

The nonlinear dynamics of the path-following control of passenger cars is analyzed in this paper. The effect of specific modeling aspects, such as tire deformation, steering dynamics, feedback delay and controller saturation, is considered. Possible equilibrium points and singularities in the state space are uncovered and analyzed for different vehicle model and controller designs. The equilibrium of stable path following is then analyzed in greater detail: The domains of stabilizing control gains are presented in stability charts and the basin of attraction of the equilibrium along the stable domain is approximated with the help of numerical continuation. Unsafe zones of control gains are highlighted, where the stable equilibrium is surrounded by low-amplitude unstable limit cycles. Finally, it is shown how specific modifications of the control law can remove unwanted equilibrium points and increase the basin of attraction of stable path following, resulting in safer and more reliable control of the vehicle.

How to approach machine learning-based prediction of drug/compound–target interactions

The identification of drug/compound–target interactions (DTIs) constitutes the basis of drug discovery, for which computational predictive approaches have been developed. As a relatively new data-driven paradigm, proteochemometric (PCM) modeling utilizes both protein and compound properties as a pair at the input level and processes them via statistical/machine learning. The representation of input samples (i.e., proteins and their ligands) in the form of quantitative feature vectors is crucial for the extraction of interaction-related properties during the artificial learning and subsequent prediction of DTIs. Lately, the representation learning approach, in which input samples are automatically featurized via training and applying a machine/deep learning model, has been utilized in biomedical sciences. In this study, we performed a comprehensive investigation of different computational approaches/techniques for protein featurization (including both conventional approaches and the novel learned embeddings), data preparation and exploration, machine learning-based modeling, and performance evaluation with the aim of achieving better data representations and more successful learning in DTI prediction. For this, we first constructed realistic and challenging benchmark datasets on small, medium, and large scales to be used as reliable gold standards for specific DTI modeling tasks. We developed and applied a network analysis-based splitting strategy to divide datasets into structurally different training and test folds. Using these datasets together with various featurization methods, we trained and tested DTI prediction models and evaluated their performance from different angles. Our main findings can be summarized under 3 items: (i) random splitting of datasets into train and test folds leads to near-complete data memorization and produce highly over-optimistic results, as a result, should be avoided, (ii) learned protein sequence embeddings work well in DTI prediction and offer high potential, despite interaction-related properties (e.g., structures) of proteins are unused during their self-supervised model training, and (iii) during the learning process, PCM models tend to rely heavily on compound features while partially ignoring protein features, primarily due to the inherent bias in DTI data, indicating the requirement for new and unbiased datasets. We hope this study will aid researchers in designing robust and high-performing data-driven DTI prediction systems that have real-world translational value in drug discovery.

Computer-Aided Formalization of Internal Consistent Product Family Models

The product line approach enables the rapid building of software products by reusing core assets. How to manage the commonality and variability of product family is the core problem of product line engineering. The feature modeling approach is one of the main approaches to solve this problem. However, this approach does not define the internal functions of features. Some researchers use formal descriptions to define the function of features, but they do not consider the connection between feature specification and feature model. These product family modeling approaches result in product family models that suffer from inconsistent descriptions, which are difficult to resolve manually. To this end, this paper proposes a computer-aided approach to construct an internally consistent product family model. The method performs an inconsistency check during the formalization of each feature in the given initial feature model, pushing the evolution of the feature model and feature specification. The creation and evolution of feature models are achieved through a template-based feature modeling approach. The method is implemented by means of templates, each of which contains two parts of knowledge: the elements required for a class of feature model, and a way to convert the given elements into a formal description. An inconsistency check is achieved through a rule-based detection approach. Each rule contains two parts: a class of conditions that the feature model and the feature specification satisfy, and the actions to resolve inconsistencies once the conditions are satisfied. We have developed a tool. The tool guides the user to build an internally consistent product family model that contains the feature model and feature specifications. Experiments have shown that our approach can provide effective automation support for the process of formal product family modeling.

What drives risk-taking incentives embedded in bank executive compensation? Some international evidence

This paper analyzes the country determinants of risk-taking incentives embedded in bank executive compensation using hand-collected international panel data on 135 publicly-traded banks in 26 countries. We exploit time-series changes in investor protection within a country and confirm that stronger protection leads to a higher vega. Moreover, the positive effect on vega is higher in countries where stronger bank competition and more extensive safety nets increase bank shareholders' risk-taking incentives. Our analysis controls for changes in bank regulation, systemic banking crises, and government bailouts. The results are robust to alternative specification models, alternative proxies for country determinants, and remain when we apply a more traditional cross-sectional analysis.

Contamination Landscapes: Spatio-Temporal Record and Analysis of Pathogens in Clinical Settings.

Nosocomial outbreaks require quick epidemiological clarification of possible chains of infection, since the pathogen usually has a head start that has to be caught up. Identification of people and areas at risk is crucial for efficient confinement. This paper describes a concept which can be applied to healthcare settings. The application skips the time-consuming and imperfect reconstruction of direct and indirect contacts. Indoor mobility of people and devices are instead measured precisely, and the mobility history is used to construct a spatio-temporal 'landscape of infection'. This landscape allows for the calculation of a modelled 'contamination landscape' (CL) adding location-based prolongation of infectivity. In that way, the risk per person can be derived in case of an outbreak. The CL concept is extremely flexible and can be adapted to various pathogen-specific settings. The combination of advanced measurements and specific modelling results in an instant list of possible recipients who need to be examined directly. The modelled, pathogen-specific parameters can be adjusted to get as close as possible to the results of mass screenings.