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This study proposed a framework using artificial neural networks (ANNs), the designed residual regression method, and probabilistic indexing, for drought sensitivity shift analysis, associated with future yield loss risk in Anthropocene. The temporal assessment of the drought index (standardized precipitation evapotranspiration index, SPEI) illustrated prevalent occurrence of mild to moderate drought with a fluctuating trend. Furthermore, the optimal ANN model, with R2 = 0.86 for training and 0.7 for testing, was used to project yield for future analysis. The projected spatial changes in drought sensitivity patterns suggest most of the area will experience an increased sensitivity to drought in the far future (2036–2050). The estimated probability loss under the different risk levels defined by the yield reduction rate was 6.2–55.5%. Furthermore, the spatial distribution of the designed risk index (IR) revealed the districts with the highest probability of vulnerability and showed a probable increase in future vulnerability. [ABSTRACT FROM AUTHOR]

In this paper, we put forth an analysis of sensitivity which aims to discern individual from merely statistical evidence. We argue that sensitivity is not to be understood as a factive concept, but as a purely epistemic one. Our resulting analysis of epistemic sensitivity gives rise to an account of legal proof on which a defendant is only found liable based on epistemically sensitive evidence. [ABSTRACT FROM AUTHOR]

Energy resources are decreasing in the world and the use of electrical machines is increasing. Motor design and development studies are carried out to reduce the losses and increase the efficiency of motors, which are widely used especially in industry. In this study, Line Start Synchronous Reluctance Motor (LS-SynRM) was designed by taking an induction motor, one of the most widely used motors in the industrial field, as a reference. With its rotor cage structure feature, it can be line-start without the need of a driver. The rotor has a lot of design variables due to slots and barriers. Sensitivity analysis was used to determine the effect of design variables on performance criteria such as power factor, efficiency and torque ripple. Subsequently, Multi-Objective Genetic Algorithm (MOGA) optimization was used to find the values of the design variables that bring the motor performance closer to the optimum result. The results of the reference induction motor, initial LS-SynRM, and the optimized LS-SynRM are compared. It has been taken care to preserve the synchronization feature of the LS-SynRM and the related results are given in the analyses. It is shown that the optimized motor is in IE4 efficiency class and operates with low torque ripple. [ABSTRACT FROM AUTHOR]

To explore the effect of material parameters on dynamic air permeability of parachute fabrics, the relative porosity model was obtained by considering the yarns stretching in length and shrinking in cross-section under the transient pressure differential. A parachute fabric dynamic air permeability model with fabric material parameters was established based on the Ergun equation. The results showed that the new model is more accurate and is applicable of higher pressure differential compared with other traditional methods. On this basis, the sensitivity analysis of the effect of the fabric structural parameters and mechanical parameters on dynamic air permeability was conducted. The results showed that: (1) the dynamic air permeability decreases with increasing fabric thickness and fabric Young's modulus, and increases with increasing fabric test area and fabric Poisson's ratio, and (2) the dynamic air permeability is more sensitive to the fabric thickness and is less sensitive to the fabric tested area, The dynamic air permeability is significantly affected by fabric Young's modulus, but slightly affected by fabric Poisson's ratio. [ABSTRACT FROM AUTHOR]

The time-dependent mechanism reliability and sensitivity analysis with imprecise probability distributions is investigated in this article. First, the interval model is employed to describe the uncertainty of the parameters of input variables due to the lack of data and knowledge. Next, the form of time-dependent failure probability and global reliability sensitivity (GRS) main effect index in the case of interval distribution parameters is analyzed. Then, the calculation methods of failure probability and GRS main effect index under the above circumstance are discussed. Finally, combined with the optimization algorithm, the Monte Carlo simulation (MCS) method and the method based on envelope function (MEVF) are proposed. By comparing with the MCS results, several numerical and engineering examples are analyzed to demonstrate the significance as well as the effectiveness of MEVF. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze and evaluate the sensitivity and non-linearity of graphene piezoresistive MEMS force sensor by optimizing its geometrical parameters. In this work, important factors affecting sensitivity and non-linearity were identified such as geometrical dimensions of microcantilever, modulus of elasticity of material, shape, placement, doping concentration, and dimensions of piezoresistors. Based on the selection of factors, Taguchi optimization method was employed for finding an optimal combination of microcantilever and piezoresistor dimensions. The optimized model of force sensor was designed with the aid of obtained dimensions of microcantilever and piezoresistors. For designing and simulation, COMSOL Multiphysics® 5.3a software is used. The major findings revealed that the designed sensor possess a high sensitivity of 3.93 mV/µN in an operating range from 0 to 106 µN with 0.0092% of non-linearity. An important feature of flexibility is introduced in the sensor by incorporating the novel combination of Polydimethylsiloxane (PDMS) as a flexible substrate and graphene as a flexible piezoresistor. The originality also lies in the area of the cumulative analysis of various input factors which are listed above altogether in one platform. [ABSTRACT FROM AUTHOR]

A tunnel type sediment excluder is a preventive fluidic device constructed on the bed of the river in front of head regulator to mitigate the sediment in the off-taking canal. The water approaching the head regulator is separated into two parts by the roof slab of the tunnels. The top part having relatively clearer water enters into the offtake canal, while the bottom layer which carries most of sediment flows through the tunnels and is discharged from the undersluices to downstream side. Very crude methods for design of sediment excluder are in vogue to date which are based on past experiences and physical model study. So, a rational approach of machine learning methods; multivariate adaptive regression splines (MARS), group method of data handling (GMDH) and M5P has been utilized for estimating the removal efficiency of sediment excluder (E). These machine learning methods have also been compared with the conventional models given by earlier researchers. Sensitivity study indicated that extraction ratio (R) was the most influencing parameter, which is followed by size of silt (S). Parametric study further suggests that with increase of R, E is getting enhanced. [ABSTRACT FROM AUTHOR]

This paper introduces a sub-leasing type of round-trip carsharing to enhance its efficiency for both customers and companies. This innovative type of carsharing provides new temporary stations and allows customers to access both vehicles in the company's stations and vehicles already reserved but parked and unused in other locations. The evaluation is performed using simulation with available demand datasets. Results show that the proposed model significantly increases the acceptance rate of the reservations, enhances the availability and accessibility of the company's vehicles, and reduces the needed fleet size. Hence, it provides many benefits for both companies and customers. Sensitivity analyses quantify the expected improvement by assuming a higher acceptable walking distance for customers and by increasing the flexibility of the customers' reservation time. [ABSTRACT FROM AUTHOR]

To explore the effect of structure parameters on the air permeability of parachute fabric, the parachute fabric was treated as a porous medium. A nonlinear model of the viscosity and the inertia coefficient of the parachute fabric was established based on the Ergun formula, and an an alytical model of the fabric permeability with the fabric structure parameters was established considering the air permeability of fabric with the standard differential pressure. The results, which were compared with the two-point reverse estimation method showed that the new model is more accurate and has a wider applicable dynamic pressure range. Based on this, a sensitivity analysis of the effect of the fabric structure parameters on the air permeability of parachute fabric was conducted. The results showed that (1) the air permeability of fabric decreases with the increasing fabric planar weight and increases with the increasing fiber density and fabric thickness, and (2) the fabric planar weight has a greater influence on the air permeability of the fabric when the fabric structure parameter is less than the standard structure parameter. The thickness of the fabric has a significant effect on the air permeability of fabrics when the fabric structure parameter is greater than the standard structure parameter. [ABSTRACT FROM AUTHOR]

Dynamic modulus ( | E ∗ |) of asphalt can be estimated using predictive models to avoid the time-taking and costly laboratory-based measurements. Several predictive models such as the Witczak model have been widely used by many researchers for the prediction of the | E ∗ |. Previously developed models have been widely reported to either overpredict or underpredict the values of | E ∗ |. In this study, to overcome the issues related to the previously developed models, a random forests algorithm was used to develop predictive models of the | E ∗ | using a comprehensive dataset. The performance of the developed models was compared with that of the Witczak model using an independent dataset. The results show that random forests algorithm can be successfully used to develop a model for the estimation of the | E ∗ | with better performance than of the Witczak model. The R2 values of the developed model in this study and the Witczak model were obtained as 0.9462 and 0.7371, respectively. Through a logarithmic transformation, the R2 value increased from 0.9462 to 0.9634. A sensitivity analysis was also performed to find the most significant factors that affect the | E ∗ |. The variables defined for test temperature and loading frequency were found to have the most effective impact on the prediction of | E ∗ |. [ABSTRACT FROM AUTHOR]

It has been argued that an advantage of the safety account over the sensitivity account is that the safety account preserves epistemic closure, while the sensitivity account implies epistemic closure failure. However, the argument fails to take the method-relativity of the modal conditions on knowledge, viz., sensitivity and safety, into account. In this paper, I argue that the sensitivity account and the safety account are on a par with respect to epistemic closure once the method-relativity of the modal conditions is taken into account. Therefore, epistemic closure is no longer an arbiter in the debate. [ABSTRACT FROM AUTHOR]

Chloride ingress and carbonation are the main factors leading to corrosion initiation of reinforced concrete structures. Lifetime assessment and maintenance optimisation of these deteriorating structures has been based for several practical applications on analytical predictive models. The literature review shows that there are numerous analytical models of chloride ingress and carbonation. It was also found that comprehensive lifetime assessment requires that the selected models be able to propagate uncertainties in a correct manner. Thus, this article proposes a methodology for probabilistic sensitivity analysis of analytical models for chloride ingress and carbonation. Given that different parameter notations were found for each model, a homogenisation of notations and generic forms are first proposed. The sensitivity analysis is based on the following indicators: elasticity coefficient, Pearson coefficient, bias of the mean and standard deviation of the response of the model. The results highlighted which parameters are influential for each model by considering three concrete types. Overall results indicated a higher effect of the non-linearity of the models on the sensitivity indicators. It was also found that the level of influence of each parameter depends also on the concrete type and the duration of the exposure to chlorides or carbon dioxide. [ABSTRACT FROM AUTHOR]

By high calibre of the fundamental nature of electric power, both of our economic and personal interests, a system is expected to supply as electrical energy as possible with the highest degree of quality and reliability. This research work aimed to evaluate the reliability measures of a hydroelectric power station. The results of this study are deliberate to provide the improved criteria for upcoming proposals, and serves as a basis for generation expansion planning of hydroelectric power stations. This paper presents a Markov-process based mathematical model for a hydroelectric power plant. The important reliability measures have been derived and discussed with the help of failure and repair rates through the analysis. This research gives a clear view of how the hydropower plants are modelled by defining the states under the failure and repair rates. [ABSTRACT FROM PUBLISHER]

We formulate the MFG limit for N interacting agents with a common noise as a single quasi-linear deterministic infinite-dimensional partial differential second order backward equation. We prove that any (regular enough) solution provides an -Nash-equilibrium profile for the initial N-player game. We use the method of stochastic characteristics to provide the link with the basic models of MFG with a major player. We develop two auxiliary theories of independent interest: sensitivity and regularity analysis for McKean-Vlasov SPDEs and the -convergence rate for the propagation of chaos property of interacting diffusions. [ABSTRACT FROM AUTHOR]

We investigate first the sensitivity of the continuous Lyapunov tensor equation where A is positively stable. On one hand, this leads to a Frobenius norm bound on the sensitivity. Comparing the result with the 2013 Shi Wei Ling Frobenius norm bound shows that our result is more general and the bound is less conservative for the continuous Lyapunov tensor equation. On the other hand, the investigation provides an spectral norm bound on the sensitivity, which is closely related to linear system . Proceeding as in the derivation of results above, we also present the sensitivity analysis of the discrete Lyapunov tensor equation [ABSTRACT FROM AUTHOR]

Tolerance analysis of mechanical components and assemblies is a key element in the industry for improving product quality and reducing overall cost. This paper is an attempt to propose a methodology to formulate and compute the kinematic assembly variations with respect to the critical dimensions (joint clearances) by calculating the homogeneous matrix of loops with considering the transforming and rotation matrix, the tolerance sensitivities, the geometrical responses to assembly variations, and the tolerance sensitivity of mechanism for clearance in the joints in different motion phases. The analysis is performed by the systematic methodology which is extended for kinematic sensitivity and positional error analysis with published results. [ABSTRACT FROM AUTHOR]

Several dynamic rollover test procedures have been developed over the years; however, the repeatability of test results is often questioned. Also, there can be sensitivity of test and simulation results to small variations in the initial conditions. The objective of this study is to evaluate the response variation of three different crash dummy finite element (FE) models (two versions of a 50th percentile male Hybrid III (HIII) and a Test Device for Human Occupant Restraint (THOR) dummy) in a simulation of a controlled rollover test, using a late model vehicle FE model. A baseline model was established with each dummy, and then a global sensitivity analysis was performed for each dummy varying vehicle design and crash parameters. The simplified HIII dummy model was very sensitive to small variations in the initial conditions of the test. Both the THOR and detailed HIII models gave very consistent results presenting similar trends in the sensitivity analysis. [ABSTRACT FROM AUTHOR]

There is an increasing requirement in higher education (HE) worldwide to deliver excellence. Benchmarking is widely used for this purpose, but methodological approaches to the creation of benchmark metrics vary greatly. Approaches require selection of factors for inclusion and subsequent calculation of benchmarks for comparison. We describe an approach using machine learning to select input factors based on their value to predict completion rates of nursing courses. Data from over 36,000 students, from nine institutions over three years were included and weighted averages provided a dynamic baseline for year on year and within year comparisons between institutions. Anonymised outcomes highlight the variation in benchmarked performances between institutions and we demonstrate the value of accompanying sensitivity analyses. Our methods are appropriate worldwide, for many forms of data and at multiple scales of enquiry. We discuss our results in the context of HE management, highlighting the value of scrutinising benchmark calculations. [ABSTRACT FROM AUTHOR]

4,4ˊ-diamino-3,3ˊ-azoxy furazan (DAAF) is an insensitive high explosive. DAAF has safety characteristics (impact, friction) similar to triaminotrinitrobenzene and shock sensitivity similar to HMX. The present article describes the thermal analysis and sensitivity study of DAAF with RDX and 2,4,6-trinitrotoluene (TNT). DAAF has been evaluated as a possible replacement for RDX in TNT-based, aluminized as well as nonaluminized melt cast formulation. DAAF-based melt cast formulations were characterized for their sensitivity to mechanical stimuli, bomb calorimetric analysis, and thermal decomposition behavior. The thermal analysis reveals the compatibility of DAAF with benchmark explosives like RDX and TNT in explosive formulations. The composition DT (DAAF + TNT) and DTA (DAAF + TNT+ Al) is more friction and impact insensitive as compared to RT (RDX + TNT) and RTA (RDX + TNT+ Al) compositions. The bomb calorimetric values of DT composition as well as DTA composition are higher than RT and RTA compositions. The result shows that DAAF can be effectively used as a RDX replacement in melt cast explosive formulations. DT-based aluminized composition showed more thermal stability than RT- and RTA-based control compositions, which clearly revealed the usefulness of DAAF for enhanced blast effect. [ABSTRACT FROM AUTHOR]

In this paper, a diode-pumped CW Kerr lens mode-locked Nd:YVO4laser is demonstrated in the megahertz (MHz) oscillations mode-locked regime for the first time. Considered the beam mode size in the laser crystal and the Kerr lens sensitivity, an effective laser system with a symmetrical z-shaped cavity is strictly designed by the ABCD matrix and experimentally researched. The laser system can be self-starting without the need of any additional components. When an incident pump power is of 8 W, the maximum output power is 1.65 W, with a slope efficiency of 23.8%. The mode-locked repetition rate and pulse width are 530 MHz and 15.1 ps, respectively. [ABSTRACT FROM PUBLISHER]

Sensitivity analysis is important in understanding the relationship between sunshine duration (SD) and reference evapotranspiration (ETref). This study was developed in the Lancang-Mekong River Basin using a non-dimensional relative sensitivity coefficient (SN) relating ETrefto SD. The SNfor January and July for each station were calculated. The results indicate that (a) the SD and SNchange in similar ways, where January and July are selected as two representative time slices; (b) the spatial distributions of the long-term averaged SNfor January and July are the reverse of each other; (c) the most abrupt changes in climate occur in the 1980s and the middle region is sensitive to climate change; and (d) periodicities of 2–4 and 14–16 years are detected in the basin generally. The significant increase of inter-decadal filter variance indicates changes in the long-term memory of the local climate system.EDITOR Z.W. KundzewiczASSOCIATE EDITOR not assigned [ABSTRACT FROM AUTHOR]

During diagnostic accuracy studies, hypotheses are often tested on more than one accuracy measure. One common example is to make inferences both on the area under the receiver operating characteristic curve (AUC) and on the sensitivity and specificity at a particular operating point. This represents a unique multiple testing situation as the AUC is a function of the sensitivity and specificity. Through a large simulation study, we showed that a naïve approach of testing all three accuracy measures at a 0.05-level greatly elevates the family-wise Type I error rate (i.e., up to 10%). When a gatekeeping approach to controlling the FWER was appropriate (family 1: AUC, family 2: sensitivity and specificity), adjustment in the second family was necessary to control the FWER across all scenarios. When a nonhierarchical approach was appropriate, the methods of Xie (2012) offered increased power over Holm's step-down procedure, but required assumptions about the correlation among the test statistics. In our simulations, the correlation between the test statistics of the AUC and sensitivity and between the test statistics of the AUC and specificity ranged from 0.3 to 0.6, while there was no correlation between the test statistics of the sensitivity and specificity. [ABSTRACT FROM AUTHOR]

The accuracy of French medico-administrative data concerning amyotrophic lateral sclerosis (ALS) is to date unknown. We aimed to assess the validity of hospital discharge data (HDD) and health insurance data (HID) related to ALS. A retrospective population-based study was performed. The French register of ALS in Limousin (FRALim) was used as gold standard (2000–2013 period). All patients discharged from the regional hospitals with a ‘G12.2’ code in their HDD (according to the International Classification of Disease-10th version) or having a G12 HID code were considered. In the study period, the register included a total of 322 incident ALS patients. Among 451 subjects identified through HDD, 290 were true incident ALS cases, corresponding to 90.1% (95% CI 86.3–93.1) sensitivity and 64.3% (95% CI 59.7–68.7) positive predictive value (PPV). A total of 184 subjects were identified through HID, 142 of which were true ALS cases. This corresponded to 44.1% (95% CI 38.6–49.7) sensitivity and 75.5% (95% CI 68.7–81.5) PPV. The combination of both HDD and HID led to 93.8% (95% CI 90.6–96.2) sensitivity and 60.8% (95% CI 56.3–65.1) PPV. This study shows that French HDD and HID, even if combined, are not per se suitable for accurate and exhaustive direct identification of ALS cases. [ABSTRACT FROM AUTHOR]

A study has been undertaken to acquire conductivity data using the EM39 low-induction-number conductivity tool. Measurements were taken in three holes in the Sudbury, Ontario, area: at Victoria in the south-west part of the Sudbury structure; at Levack, in the north range; and at the Lady Violet deposit near Copper Cliff. These data were compared with preexisting data acquired using four other tools and measurements taken on core extracted from the holes. The four tools are the DGI galvanic downhole resistivity tool, the IFG downhole conductivity tool, and the handheld KT-10 and GDD meters. The comparison shows that each tool has a finite range of sensitivity. The resistivity tool used by DGI Geoscience is sensitive to conductivities primarily in the range 0.01 to 100 mS/m; the EM39 tool is sensitive to conductivities in the range of ~30 mS/m to 3000 mS/m and the IFG tool to conductivities greater than 30 mS/m. In the sub-ranges where the ranges of two instruments overlap, one might expect a good correlation between the measurements derived from the two tools. However, this is not always the case, as the instruments can have a different volume of sensitivity: theEM39has a coil separation of 50 cm and will see material greater than 20 cm away from the hole; whereas the IFG conductivity tool seems to have a smaller spatial scale of sensitivity due to its 10 cm coil size. The handheld instruments used to log the conductivity of the core are sensitive to more conductive material (greater than ~1 S/m). The scale of the sensors of these handheld instruments is a few cm, so they are focussing on a very local estimate. The spatial characteristics of the handheld instruments are similar to the IFG tool, so there is a reasonable linear correlation between the conductivities derived from these three different instruments. However, the slopes are not unity; for example, the GDD instrument gives values three times greater than the KT-10. When selecting tools for measuring the resistivity and conductivity, ensure that the values that you expect to measure fall within the range of sensitivity of the instrument and that the features sought are comparable in size to the volume of sensitivity. [ABSTRACT FROM AUTHOR]

This is the fifth article of a series on fundamental concepts in biostatistics and research. In this article, the author reviews the fundamental concepts in diagnostic testing, prior probability and predictive value, and how they relate to the concept of high-value care. The topics are discussed in common language with a minimum of jargon and mathematics. Emphasis is given to conceptual understanding. A companion article preceding this one focused on sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Due to advance technology, rapidly emergent complexity of networks and perseverance on network quality, reliability, and maintainability are progressively significant issues, and hence, the job of reliability analysts is becoming more challenging. A network’s optimum design is required for maintaining the reliability of a sophisticated network at a high level. Reliability of tree topology plays a key role in the measurement of quality of a network and in the performance of a network. Large-scale distributed networks are subject to frequent interruptions due to resource contention and failure. Failure of any component or subsystem affects the performance of the network. This research work has two significant goals: to design a mathematical model of a tree network using the Markov process and supplementary variable technique, and to determine the reliability characteristics such as availability, reliability, and mean time to failure (MTTF). The authors also seek the sensitivity analysis for reliability measures along with the precise values of the input parameters which is very helpful and necessary for attaining a highly reliable network. [ABSTRACT FROM AUTHOR]

This article provides an introduction to a decomposition-based method for the optimization of product families with predefined platforms. To improve the efficiency of the system coordinator, a new sensitivity-based coordination method (SCM) is proposed. The key idea in SCM is that the system level coordinates share variables by using sensitivity information to make trade-offs between the product subsystems. The coordinated shared variables are determined by minimizing the performance deviation with respect to the optimal design of subproblems and constraint violation incurred by sharing. Each subproblem has a significant degree of independence and can be solved in a simultaneous way. The numerical performance of SCM is investigated, and the results suggest that the new approach is robust and leads to a substantial reduction in computational effort compared with the analytical target cascading method. Then, the proposed methodology is applied to the structural optimization of a family of automotive body side-frames. [ABSTRACT FROM AUTHOR]

In this paper, we consider a class of nonlinear fractional order control system with delay in state variable. Existence and uniqueness of solution are shown by using method of steps. The sensitivity of the state and control with respect to the parameters of the system is shown. Finally, analytical results are substantiated by numerical examples. [ABSTRACT FROM AUTHOR]

Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms. [ABSTRACT FROM AUTHOR]

We apply the Ricardian approach to analyse the economic impact of climate change on agriculture using the 2007 World Bank Tajikistan Living Standards Survey. The study analyses data of 2557 farm households in 166 villages across the 10 agro-ecological country zones. In general, the results indicated that increasing temperature and precipitation will both be damaging to Tajikistan agriculture and consequently to the net revenue (NR) of farmers in the medium and long term. Regressing NR on climate parameters, household and soil variables showed that these variables have a significant impact on the farmers' NR per hectare. We examined the impact of the current climate on farmers' NR per hectare, and how that is affected by future climate scenarios: one +2.9°C warming and one 4.6°C warming scenarios. Although the analysis did not incorporate variables such as the carbon fertilization effect, the role of technology or the change in prices in the future, significant information for policy-making can be extracted. Tajikistan has very diverse regions in terms of geography, population density and socio-economic situation; our results will help policy-makers to anticipate the adaptation effort needed in different locations of the country. [ABSTRACT FROM AUTHOR]

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We examine a pore in an energetic material whose collapse following the passage of a strong genesis shock wave, the subsequent ignition of reactive gases within it produced by pyrolysis at the pore boundary, and the emission of shock waves as a consequence of this ignition, can lead to a detonation. The interest in such a problem arises from the interest in knowing the sensitivity and therefore the safe-handling protocol of energetic materials. We follow the initial pore collapse, before melting occurs, using rational analytical strategies, but to describe the later stages, with full coupling between the physics in the condensate and those in the pore cavity, we describe a numerical strategy. The results provide a description of the power deposition into the energetic material and lead to a power deposition model for the macro-scale, one that encompasses a number of pores. For suitable parameter choices, shock waves generated by the pores interact to form a detonation upstream of the genesis shock. [ABSTRACT FROM PUBLISHER]

The weighted kappa coefficient of a binary diagnostic test (BDT) is a measure of performance of a BDT, and is a function of the sensitivity and the specificity of the diagnostic test, of the disease prevalence and the weighting index. Weighting index represents the relative loss between the false positives and the false negatives. In this study, we propose a new measure of performance of a BDT: the average kappa coefficient. This parameter is the average function of the weighted kappa coefficients and does not depend on the weighting index. We have studied three asymptotic confidence intervals (CIs) for the average kappa coefficient, Wald, logit and bias-corrected bootstrap, and we carried out some simulation experiments to study the asymptotic coverage of each of the three CIs. We have written a program in R, called ‘akcbdt’, to estimate the average kappa coefficient of a BDT. This program is available as supplementary material. The results were applied to two examples. [ABSTRACT FROM AUTHOR]

The submitted paper proposes the possible use of integrated semi-quantitative risk assessment of groundwater resources. There are risks resulting from both natural and anthropogenic hazard sources. Activation of these types of hazard sources can cause damage to, or destruction of, particular hydrogeological structures and technological equipment of selected groundwater resources suitable for the emergency drinking water supply of the population. The process of risk assessment is based on the described register of hazards, including semi-quantitative assessment of the frequency with which the assessed sources of hazards are activated, the register of sensitivity together with the semi-quantitative sensitivity assessment of selected threatened elements of the assessed water resource and the determination of their criticality. The semi-quantitative risk assessment should become one of the important criteria for classifying groundwater resources which have been proposed for emergency water supply. The classification carried out on the basis of the above-mentioned principle can contribute to faster selection and effective use of groundwater resources, as well as to the enhancement of emergency and crisis planning systems when the public system is either damaged or destroyed. [ABSTRACT FROM PUBLISHER]

Higher dimensional surfaces are used to examine the diagnostic performance of multiclass classification systems. These surfaces are extensions of the ROC curve and are known as ROC surfaces or manifolds. Manifolds may be constructed from either the correct classifications or from the misclassifications of the diagnostic system. Comparisons of the usefulness of each of these ROC manifolds with respect to the performance of the diagnostic system are made with emphasis on inferences from volume under the surface and optimal operating points (thresholds) of the system. Recommendations for when to use each type of ROC manifold and performance measure are discussed. [ABSTRACT FROM AUTHOR]

Simulation of chemically reacting flows using detailed chemistry introduces a large number of chemistry model parameters. While not all significantly affect the target outcomes of a simulation, the parameters that do are not always knowna priori. In order to improve simulations for specified target outcomes, termed quantities of interest (QoIs), the sensitivity of these QoIs to the model parameters are needed. However, evaluating the sensitivities is computationally expensive, especially for complex fuels that may involve many parameters. For these simulations, the forward sensitivity method requires the solution of an additional number of governing equations proportional to the number of parameters. Here, an adjoint sensitivity approach is formulated where the computational cost scales as the number of QoIs and not the number of parameters. Specifically, adjoint equations are derived for laminar, incompressible, variable density reacting flow and applied to hydrogen flame simulations. From the solution of the corresponding adjoint equations, sensitivity of the QoIs to chemistry model parameters is calculated. The one-dimensional simulation results show that the adjoint sensitivity results closely match those of forward sensitivity methods, thus providing validation of the adjoint method. The two-dimensional simulation results indicate the most sensitive parameters for two QoIs, flame tip temperature and NOx emission. For these tests, the adjoint method reduces computational expense compared to forward sensitivity methods by a factor proportional to the number of QoIs over the number of parameters, here 2/172. Such savings can be more drastic for cases that involve complex fuels, such as combustion of jet fuel, requiring thousands of chemistry model parameters. Further, this sensitivity information can be used in development of experiments by pointing out which are the critical chemistry model parameters. [ABSTRACT FROM PUBLISHER]

The explicit expressions for the condition numbers and the first-order perturbation bounds for both factorsRandSof the SR decomposition are presented by using theoperator. The new first-order bounds are sharper than those previous results given by Bhatia and Chang. Besides, we also give the rigorous perturbation bounds for these two factors. The first-order terms of the rigorous bounds are the same as the first-order perturbation bounds given by Bhatia. [ABSTRACT FROM AUTHOR]

The direct rainfall method (DRM) for flood modelling involves the application of rainfall to all cells in a 2D model, and runoff is routed within the hydraulic model. Advantages of this approach include the facilitation of cross catchment flows, a high definition of flow behaviour in catchments, and the approach can replace the requirement for hydrological models within the 2D model domain. Complications can occur when applying the DRM which can lead to unrealistic flow responses and large model errors. Issues are generally associated with model losses, run-times, gridscale effects and very shallow flow. The DRM was used to develop a flood model in the Serpentine area on the sandy Swan Coastal Plain in southwest Western Australia (approximately 20 km south of Perth). The project demonstrates the suitability of the DRM for design flood simulations and floodplain mapping. Due to the problems associated with the approach, a series of checks and quality assurance procedures are recommended if DRM flood modelling is undertaken. This paper explores the pros and cons of the DRM through the processes of model construction, a comprehensive model calibration, validation and sensitivity analysis, and a series of checks including mass balances, and comparison to traditional modelling techniques. [ABSTRACT FROM AUTHOR]

The classification accuracy of remotely sensed data and its sensitivity to classification algorithms have a critical importance for the geospatial community, as classified images provide the base layers for many applications and models. Support Vector Machines (SVMs), a non-parametric statistical learning method that has recently been used in numerous applications in image processing. The SVMs need user-defined parameters and each parameter has different impact on kernels hence the classification accuracy of SVMs is based upon the choice of the parameters and kernels. The objective of this study is to investigate the sensitivity of SVM architecture including internal parameters and kernel types on landuse classification accuracy of RapidEye imagery for the study area in Turkey. Four types of kernels (linear, polynomial, radial basis function, and sigmoid) were used for the SVM classification. A total of 63 different models were developed and implemented for sensitivity analysis of SVM architecture. The traditional Maximum Likelihood Classification (MLC) method was also performed for comparison. The classification accuracies of the best model for each kernel type and MLC are 85.63%, 83.94%, 83.94%, 83.82% and 81.64% for polynomial, linear, radial basis function, sigmoid kernels and MLC, respectively. The results suggest that the choice of model parameters and kernel types play an important role on SVMs classification accuracy. Best model of polynomial kernel outperformed all SVMs models and gave the highest classification accuracy of 85.63% with RapidEye imagery. [ABSTRACT FROM AUTHOR]

Patient-specific finite element models of the implanted proximal femur can be built from pre-operative computed tomography scans and post-operative X-rays. However, estimating three-dimensional positioning from two-dimensional radiographs introduces uncertainty in the implant position. Further, accurately measuring the thin cement mantle and the degree of cement–bone interdigitation from imaging data is challenging. To quantify the effect of these uncertainties in stem position and cement thickness, a sensitivity study was performed. A design-of-experiment study was implemented, simulating both gait and stair ascent. Cement mantle stresses and bone–implant interface strains were monitored. The results show that small variations in alignment affect the implant biomechanics, especially around the most proximal and most distal ends of the stem. The results suggest that implant position is more influential than cement thickness. Rotation around the medial–lateral axis is the dominant factor in the proximal zones and stem translations are the dominant factors around the distal tip. [ABSTRACT FROM AUTHOR]

The Jamaican tourism industry is very climate sensitive, and, like most Caribbean islands, Jamaica's main tourism product is coastal, centered on "sun, sea and sand". The island is susceptible to many risks posed by climate change, including sea level rise and extreme events, with resultant impacts such as beach erosion, flooding, saline intrusion into aquifers and general coastal degradation. This paper evaluates the relative vulnerability of beach versus non-beach tourism in Jamaica, using 43 pre-determined literature-linked indicators. These comprise bio-geophysical, social, technological, economical, technological and institutional factors. Four case areas are assessed using multi-criteria decision analysis to derive vulnerability scores for each area. The study finds that non-beach tourism operations should not be automatically perceived as less vulnerable than beach-based operations. Sustainable adaptation options are complex and numerous, and overall beach tourism businesses have better insurance, emergency savings, disaster plans and backup power facilities, among others. They also have the advantage of being in business longer than the inland resorts, a firmer business structure and an extensive marketing budget. In the long term, better adaptation and planning by inland businesses could change this balance. [ABSTRACT FROM AUTHOR]

There is a lack of early biomarkers of intervertebral disc (IVD) degeneration. Thus, the authors developed the analysis of magnetic resonance signal intensity distribution (AMRSID) method to analyse the 3D distribution of the T2-weighted MR signal intensity within the IVD usingnormalised histograms, weighted centres and volume ratios.The objective was to assess the sensitivity of the AMRSID method to the segmentation process and data normalisation. Repetition of the semi-automatic segmentation by the same operator did not influence the quality of the contour or our new MR distribution parameters whereas the skills of the operator influenced only the MR distribution parameters, and the instructions given prior to the segmentation influenced both the quality of the contour and the MR distribution parameters. Bone normalisation produces an index that jointly highlights IVD and bone health, whereas cerebrospinal fluid normalisation only suppresses the effect of the acquisition gain. This robust AMRSID method has the potential to improve the diagnostic with earlier biomarkers and the prognosis of evolution. [ABSTRACT FROM AUTHOR]

A new fluorescent derivative (1) containing coumarin exhibits Fe(III)-selective strong yellow-green fluorescence in ethanol. This compound could be used as an “off-on” chemosensor and allow the detection of Fe3+by monitoring changes in absorption and fluorescence spectra. Upon addition of Fe3+, an overall emission change of 125-fold was observed. High selectivity and sensitivity were observed over other metal ions, mainly due to the spirolactam ring-opening power of Fe3+. The detection limit was as low as 5.6?ppb. Photo-induced electron transfer, coupled with intramolecular charge transfer are proposed to account for the observed spectral response. [ABSTRACT FROM PUBLISHER]

Oxalylhydrazinium nitrate (OHN) and dinitrate (OHDN) were synthesized by protonation of oxalyldihydrazide with nitric acid. The synthesis is extremely cost effective (∼$40/kg at the lab scale) and can be carried out in large scales and very good yields. OHN and OHDN were intensively characterized by low-temperature X-ray diffraction (XRD), nuclear magnetic resonance (NMR) and vibrational spectroscopy. These new organic nitrate salts could be used as powerful ingredients in energetic formulations due to their low sensitivities (measured by Bundesanstalt für Materialforschung und Pröfung methods). Their thermal stability was investigated by differential scanning calorimetry (DSC) measurements. Further thermal studies of OHN showed compatibility with TNT (2,4,6-trinitrotoluene), DNAN (2,4-dinitroanisole), and RDX (1,3,5-trinitro-1,3,5-triazinane). The theoretical detonation and propulsion parameters of OHN and OHDN were calculated with the EXPLO5.5 code and compared to well-known insensitive explosives. The aquatic toxicity of OHN was determined by the luminescent bacteria inhibition test, yielding a much lower toxicity than RDX. [ABSTRACT FROM AUTHOR]

This paper describes a recently developed new family of miniature surface resonators, used for electron spin resonance spectroscopy and imaging. The first part of the paper provides a detailed description of the operational principles of the surface resonators. It also includes sensitivity analysis for a variety of configurations with inner dimensions ranging from 150 μm down to 2 μm, operating at the Ku, Q, and W frequency bands. Most of the data presented here is based on theoretical predictions; however, some of it is accompanied by experiential results for verification. The second part of the paper describes a new type of double-surface microresonator and its production method. This new configuration enables an efficient coupling of the microwave energy from millimetre-sized microstrip lines to micron structures even at relatively low frequencies. The resonator is analysed both theoretically and experimentally – exhibiting ultra-high spin sensitivity. The conclusion of the two parts of the paper is that micron-scale surface microresonators may achieve spin sensitivity of a few thousands of spins in one second of acquisition time for special samples, such as phosphorous-doped28Si, at cryogenic temperatures. However, further miniaturization below 1–2 microns does not seem to be beneficial, sensitivity-wise. In addition to their high spin sensitivity, these resonators have a huge conversion factor, reaching in some cases to more than 500–1000 G of microwave magnetic field with input power of 1 W. Some possible applications of these unique capabilities are also described herein. [ABSTRACT FROM PUBLISHER]

In this paper, three numerical algorithms for the identification of wheel–rail contact forces based on measured wheel disc strains on an instrumented railway wheelset are discussed and compared. The three algorithms include one approach resting on static calibration, one that is applying a Kalman filter and the third is exploiting an inverse identification scheme. To demonstrate and evaluate the alternative methods, two load cases including periodic excitation by sinusoidal wheel–rail irregularities and transient excitation by an insulated rail joint are considered. Based on a previously presented vehicle–track interaction model in the time domain, load scenarios are defined by taking the calculated vertical wheel–rail contact forces as the reference force to be re-identified by the proposed algorithms. The reference contact forces are applied on a finite element model of the wheel to generate synthetic observation data, that is, radial strains at the positions of the strain gauges, serving as input to the identification procedures. It is concluded that the inverse identification scheme leads to superior accuracy at higher computational cost. If on-line implementation and evaluation is required, the Kalman filter generates better accuracy than the static calibration approach. [ABSTRACT FROM PUBLISHER]

Although it is desirable for a transistor model to be as accurate as possible, the extraction of model parameters from fabricated transistors is a time-consuming and often costly process. An investigation of the sensitivity of low-noise amplifier (LNA) performance characteristics to individual parameters of the physics-based standard HBT model HICUM/L2 was, therefore, done to gain a preliminary insight into the most important parameters for transistors used in actual circuits. This can potentially allow less strenuous accuracy requirements on some parameters which would ease the extraction process. Both a narrow- and wideband LNA configuration were investigated. It was found that the series resistance parameters have a large impact on LNA gain,S11and noise figure performance in both cases. Since the narrow-band LNA relied heavily on the transistor characteristics to provide a proper matching, it was also very sensitive to changes in the parameters used in modelling the high-frequency current gain and depletion capacitances of the transistor. [ABSTRACT FROM AUTHOR]

Experimental variables in continuous flow hydride generation inductively coupled plasma-optical emission spectrometry (CF-HG-ICP-OES) were optimized for determination of bismuth. Concentrations of NaBH4, HCl, and NaOH, flow rates of NaBH4, sample solution, waste and carrier argon, radio frequency power, lengths of reaction, and stripping coils were optimized to obtain lower detection limits. Under optimum conditions, the detection limit was calculated as 0.16 ng mL−1, and the calibration plot was linear between 1.0–50.0 ng mL−1. An improvement in detection limit of 5.75 times by CF-HG-ICP-OES was reached vs. ICP-OES. Relative standard deviation (RSD) for ten replicate measurements of 10.0 ng mL−1 Bi was calculated as 3.9%. Effect of possible interferic ions on Bi signal was evaluated. Accuracy of method was verified by using a standard reference material, SRM 1643e. Results found for Bi were in satisfactory agreement with certified values. The proposed method was then employed to determine trace concentration of Bi in milk samples. Bi amounts in samples were found in the range from lower than the quantitation limit to 14.5 ng mL−1, whereas Bi concentrations were lower than the detection limit in three samples. [ABSTRACT FROM AUTHOR]

The main structures of the gas absorption cell, including small graded-index lens type, Bragg fiber type, photonic crystal type, etc., are compared in this article. Also, different principles of the gas absorption cell were discussed in detail in order to improve the sensitivity of the optical gas sensor. The study showed that the structure of gas cells plays a key role in the improvement of the sensitivity of optical gas sensors. The end of the article discusses the future direction of the development of the gas cell. [ABSTRACT FROM PUBLISHER]