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Traditional techniques for estimating the weight of clusters in a winery, generally consist of manually counting the variety of clusters per vine, and scaling by means of the entire variety of vines. This method can be arduous, and costly, and its accuracy depends on the scale of the sample. To overcome these problems, hybrid approaches of computer vision, deep learning (DL), and machine learning (ML) based vineyard yield prediction systems are proposed. Self-prepared datasets are used for comparative analysis of 2D and 3D yield prediction systems for vineyards. DL-based approach for segmentation operation on an RGB-D image dataset created with the D435I camera is used along with the ML-based weight prediction technique of grape clusters present in the single image using these datasets. A comparative analysis of the DL-based Keras regression model and various ML-based regression models for the weight prediction task is taken into account, and finally, a prediction model is proposed to estimate the yield of the entire vineyard. The analysis shows improved performance with the 3D vineyard yield prediction system compared to the 2D vineyard yield prediction system with grape cluster segmentation pixel accuracy up to 94.81% and yield prediction accuracy up to 99.58%. [ABSTRACT FROM AUTHOR]

The paper presents a comparison between three different techniques for simultaneously estimating the speed, position and rotor flux modulus of an induction motor, which is used in a sensorless vector control system. The comparison highlights the dynamic performances, as well as the stability of the obervers in the area of low speeds. Dynamic performances testing is done by simulation using the Matlab-Simulink program. [ABSTRACT FROM AUTHOR]

The paper presents a comparison between three different techniques for simultaneously estimating the speed, position and rotor flux modulus of an induction motor, which is used in a sensorless vector control system. The comparison highlights the dynamic performances, as well as the stability of the obervers in the area of low speeds. Dynamic performances testing is done by simulation using the Matlab-Simulink program. [ABSTRACT FROM AUTHOR]

We propose a multithreshold change plane regression model which naturally partitions the observed subjects into subgroups with different covariate effects. The underlying grouping variable is a linear function of observed covariates and thus multiple thresholds produce change planes in the covariate space. We contribute a novel two-stage estimation approach to determine the number of subgroups, the location of thresholds, and all other regression parameters. In the first stage we adopt a group selection principle to consistently identify the number of subgroups, while in the second stage change point locations and model parameter estimates are refined by a penalized induced smoothing technique. Our procedure allows sparse solutions for relatively moderate- or high-dimensional covariates. We further establish the asymptotic properties of our proposed estimators under appropriate technical conditions. We evaluate the performance of the proposed methods by simulation studies and provide illustrations using two medical data examples. Our proposal for subgroup identification may lead to an immediate application in personalized medicine. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the Observed Time Difference of Arrival (OTDOA) technique to simultaneously estimate the position of the different user equipments and the relative time difference between Node Bs in real UMTS networks. We concentrate on comparing two methods to solve the nonlinear system of equations, the well-known Gauss-Newton and the Levenberg-Marquardt algorithm. We show this latter method offers better results, providing faster convergence, higher accuracy and more robustness. Finally, a modification to the classical Levenberg-Marquardt algorithm is proposed in order to avoid divergences in that method. [ABSTRACT FROM AUTHOR]

In an attempt to extend the applicability of the W1 and W2 ab initio computational thermochemistry methods, we propose explicitly correlated versions thereof, denoted W1-F12 and W2-F12. In W2-F12, we can 'save' one cardinal number (viz., angular momentum) in the basis set sequences without loss in accuracy; in W1-F12, we can do so for first-row compounds but not for second-row compounds. At a root mean square deviation (RMSD) = 0.19 kcal/mol for the first-row molecules in the W4-11 benchmark dataset, W1-F12 is in fact superior to ordinary W1 theory. For the entire W4-11 set, W2-F12 yields a RMSD = 0.20 kcal/mol, comparable to 0.19 kcal/mol from ordinary W2 theory. The extended applicability ranges of W1-F12 and W2-F12 are not just due to the lower computational cost but also to greatly reduced memory and especially storage requirements. They are illustrated through applications to nucleic acids and to polyacenes (with up to four rings), for which the following revised gas-phase heats of formation are found: ΔfH298° = 19.6 (benzene), 34.94 (naphthalene), 53.9, (anthracene), 73.9 (naphthacene/tetracene), 54.9 (adenine), -16.3 (cytosine), 5.1 (guanine), -80.6 (thymine), and -71.6 (uracil) kcal/mol. Our theoretical values for the DNA/RNA bases largely confirm recent predictions based on much lower-level calculations. The W1-F12 theoretical values for benzene, naphthalene, and anthracene are in very good to reasonable agreement with experiment. However, both W1-F12 and other computational estimates show that the accepted experimental value for naphthacene cannot be reconciled with those for the lower acenes: we suggest that ΔfH298°[naphthacene(g)] = 74.25 ± 1 kcal/mol is a more realistic estimate. [ABSTRACT FROM AUTHOR]

Summary: Postmarket comparative effectiveness and safety analyses of therapeutic treatments typically involve large observational cohorts. We propose double robust machine learning estimation techniques for implantable medical device evaluations where there are more than two unordered treatments and patients are clustered in hospitals. This flexible approach also accommodates high‐dimensional covariates drawn from clinical databases. The Massachusetts Data Analysis Center percutaneous coronary intervention cohort is used to assess the composite outcome of 10 drug‐eluting stents among adults implanted with at least one drug‐eluting stent in Massachusetts. We find remarkable discrimination between stents. A simulation study designed to mimic this coronary intervention cohort is also presented and produced similar results. [ABSTRACT FROM AUTHOR]

We develop variable selection approaches for accelerated failure time models, consisting of a group of algorithms based on a synthesis of two widely used techniques in the area of variable selection for survival analysis-the Buckley-James method and the Dantzig selector. Two algorithms are based on proposed modified Buckley-James estimating methods that are designed for high-dimensional censored data. Another two algorithms are based on a two-stage weighted Dantzig selector method where weights are obtained from the two proposed synthesis-based algorithms. The methods are easy to understand and they perform estimation and variable selection simultaneously. Furthermore, they can deal with collinearity among the covariates. We conducted several simulation studies and one empirical analysis with a microarray dataset; these studies demonstrated satisfactory variable selection performance. In addition, the microarray data analysis shows the methods performing similarly to three other correlation-based greedy variable selection techniques in the literature-sure independence screening, tilted correlation screening (TCS), and partial correlation (PC) simple. This empirical study also found that the sure independence screening technique considerably improves the performance of most of the proposed methods. [ABSTRACT FROM AUTHOR]

Mega-analysis, or the meta-analysis of individual data, enables pooling and comparing multiple studies to enhance estimation and power. A challenge in mega-analysis is estimating the distribution for clustered, potentially censored event times where the dependency structure can introduce bias if ignored. We propose a new proportional odds model with unknown, time-varying coefficients, and random effects. The model directly captures event dependencies, handles censoring using pseudo-values, and permits a simple estimation by transforming the model into an easily estimable additive logistic mixed effect model. Our method consistently estimates the distribution for clustered event times even under covariate-dependent censoring. Applied to three observational studies of Huntington's disease, our method provides, for the first time in the literature, evidence of similar conclusions about motor and cognitive impairments in all studies despite different recruitment criteria. [ABSTRACT FROM AUTHOR]

Summary: The present study aims to show the effectiveness of a methodological procedure to estimate the volumetric capacity of archaeological ceramic vessels and the net and gross weights of their probable contents. This method can be easily applied, independently of cultural or chronological contexts, and, alongside other historical and economic conclusions, might serve to verify the possible existence of typological and metrological standardizations of domestic or commercial containers. This study gives a detailed description of a simple methodological protocol which uses profile drawings to calculate the approximate volume of any vessel, thus enabling assessment of its conformity to ancient weight systems. This article will illustrate the strength of the method using a sample of Ramon T‐11213 amphorae made in the Bay of Cadiz during the fifth century BC, which, given its quantitative and qualitative strengths, proves to be an exemplary case study and a valid pilot. [ABSTRACT FROM AUTHOR]

This paper introduces a reliable strategy for the state of charge (SOC) and the state of health (SOH) estimation of healthy and aged Lithium polymer cells. Dynamics of the cell are modeled using some equivalent circuit models and parameters of each model are calculated by adaptive particle swarm optimization. The modeling process involves modeling and parametric uncertainties as well as measurement and instrumentation noise. They may degrade the performance of an optimal filter for SOC and SOH estimation. To alleviate effects of such uncertain factors, the smooth variable structure filter (SVSF) is implemented. The SVSF is a novel robust state estimation method that benefits from the robustness property of variable structure systems. The performance of the SVSF is compared with the extended Kalman filter (EKF) for real-time SOC estimation of a healthy and an aged Lithium polymer cell. The paper moreover presents a novel method for SOH estimation using the SVSF’s chattering signal and without the need for modeling the cell undergoes aging. Experiments show performance benefits of the SVSF for reliable SOC and SOH estimation of healthy and aged Lithium polymer cells. [ABSTRACT FROM AUTHOR]

To quantify polygenic effects, i.e. undetected genetic effects, in large-scale association studies, we propose a generalized estimating equation (GEE) based estimation framework. We develop a marginal model for single-variant association test statistics of complex diseases that generalizes existing approaches such as LD Score regression and that is applicable to population-based designs, to family-based designs or to arbitrary combinations of both. We extend the standard GEE approach so that the parameters of the proposed marginal model can be estimated based on working-correlation/linkage-disequilibrium (LD) matrices from external reference panels. Our method achieves substantial efficiency gains over standard approaches, while it is robust against misspecification of the LD structure, i.e. the LD structure of the reference panel can differ substantially from the true LD structure in the study population. In simulation studies and in applications to population-based and family-based studies, we illustrate the features of the proposed GEE framework. Our results suggest that our approach can be up to 100% more efficient than existing methodology. [ABSTRACT FROM AUTHOR]

Two main theories have been used to explain the arithmetic split effect: decision‐making process theory and strategy choice theory. Using the inequality paradigm, previous studies have confirmed that individuals tend to adopt a plausibility‐checking strategy and a whole‐calculation strategy to solve large and small split problems in complex addition arithmetic, respectively. This supports strategy choice theory, but it is unknown whether this theory also explains performance in solving different split problems in complex subtraction arithmetic. This study used small, intermediate and large split sizes, with each split condition being further divided into problems requiring and not requiring borrowing. The reaction times (RTs) for large and intermediate splits were significantly shorter than those for small splits, while accuracy was significantly higher for large and middle splits than for small splits, reflecting no speed–accuracy trade‐off. Further, RTs and accuracy differed significantly between the borrow and no‐borrow conditions only for small splits. This study indicates that strategy choice theory is suitable to explain the split effect in complex subtraction arithmetic. That is, individuals tend to choose the plausibility‐checking strategy or the whole‐calculation strategy according to the split size. [ABSTRACT FROM AUTHOR]

Functional neuroimaging has the spatial resolution to explain the neural basis of emotions. Activation likelihood estimation (ALE), as opposed to traditional qualitative meta-analysis, quantifies convergence of activation across studies within affective categories. Others have used ALE to investigate a broad range of emotions, but without the convenience of the BrainMap database. We used the BrainMap database and analysis resources to run separate meta-analyses on coordinates reported for anger, anxiety, disgust, fear, happiness, humor, and sadness. Resultant ALE maps were compared to determine areas of convergence between emotions, as well as to identify affect-specific networks. Five out of the seven emotions demonstrated consistent activation within the amygdala, whereas all emotions consistently activated the right inferior frontal gyrus, which has been implicated as an integration hub for affective and cognitive processes. These data provide the framework for models of affect-specific networks, as well as emotional processing hubs, which can be used for future studies of functional or effective connectivity. [ABSTRACT FROM AUTHOR]

The synthetic control methodology (Abadie and Gardeazabal, 2003, American Economic Review 93: 113-132; Abadie, Diamond, and Hainmueller, 2010, Journal of the American Statistical Association 105: 493-505) allows for a data-driven approach to small-sample comparative studies. synth runner automates the process of running multiple synthetic control estimations using synth. It conducts placebo estimates in space (estimations for the same treatment period but on all the control units). Inference (p-values) is provided by comparing the estimated main effect with the distribution of placebo effects. It also allows several units to receive treatment, possibly at different time periods. It allows automatic generation of the outcome predictors and diagnostics by splitting the pretreatment into training and validation portions. Additionally, it provides diagnostics to assess fit and generates visualizations of results. [ABSTRACT FROM AUTHOR]

Aim: In sick children who are unable to be weighed estimation of weight is often required, but the routinely used equations lack accuracy and precision. This study aimed to develop a novel equation (Children's European Estimator of Weight-CEEW) using measurements of mid-upper arm circumference (MUAC) and other predictors in multinational groups of sick children in Europe.Methods: Weight estimation equations were developed in 2086 children from the UK, Greece and the Netherlands, using a combination of demographics, MUAC and height measurements. The final CEEW equations were compared against the performance of the European Resuscitation Council (ERC), Advanced Paediatric Life Support (APLS) and the Cattermole equations.Results: Two final CEEW equations were developed, incorporating measurements of age, gender and MUAC, with (CEEW1) or without (CEEW2) the inclusion of height. Both equations presented very high coefficients of determination (R2>96.5%), minimal mean prediction error and narrower limits of agreement than the comparator equations. 88% (CEEW1) and 77% (CEEW2) of weight estimates fell within 15% of measured body weight. These figures compared with less than 57%, 57% and 37% for the ERC, APLS and Cattermole equations respectively.Conclusion: The CEEW equations performed substantially better than other routinely used equations for weight estimation. An electronic application for mobile use is presented. [ABSTRACT FROM AUTHOR]

Objective: This qualitative study aimed to investigate consumer opinions on the usefulness of portion size estimation aids (PSEA); consumer preferences in terms of format and context for use; and the level of detail of guidance considered necessary for the effective application of PSEA.Design: Six focus groups (three to eight participants per group) were conducted to elicit views on PSEA. The discussions were recorded, transcribed verbatim and analysed by two independent researchers using a template approach.Setting: The focus groups were conducted in 2013 by an experienced moderator in various sites across the island of Ireland (three in the Republic of Ireland and three in Northern Ireland) including local leisure, community and resource centres; the home environment; and a university meeting room.Participants: General population, males (n = 17) and females (n = 15) aged 18-64 years old. Participants were recruited from both urban and rural locations representing a range of socio-economic groups.Results: The majority of participants deemed the coloured portion pots and disposable plastic cup (household measures) to be useful particularly for the estimation of amorphous cereal products (e.g. breakfast cereals). Preferences were evident for "visual" PSEA (reference objects, household measures and food packaging) rather than 'quantities and measures' such as weighing in grams or ounces. Participants stated that PS education should be concise, consistent, from a reputable source, initiated at school age and communicated innovatively e.g. mobile app or TV advertisement. Guidance in relation to gender, age and activity level was favoured over a "one size fits all" approach.Conclusions: This study identified consumer preferences and acceptance of "visual" PSEA such as portion pots/cups to estimate appropriate PS of amorphous grain foods such as breakfast cereals, pasta and rice. Concise information from a reputable source in relation to gender, age and activity level should accompany PSEA. [ABSTRACT FROM AUTHOR]

Aim: When children's weight cannot be measured during medical emergencies, it must be estimated, as weight is required for many interventions. Age-based formulas are the oldest weight estimation systems in children, but have been shown to be very inaccurate in many studies. This aim of this study was to evaluate the accuracy of age- and length-based formulas and to see if a measure of body habitus could be used to improve the performance of these formulas.Methods: This was an analysis of data from a sample of 1085 children aged from 1 month to 16 years, collected from four Emergency Departments in Johannesburg, South Africa. Basic demographic and anthropometric data was collected and each child had a visual assessment of body habitus, quantified as a habitus score. Weight estimates from 20 existing age-based formulas and two length-based formulas were then compared against measured weight to determine their accuracy. Age- and length-based, habitus-modified models were developed and similarly evaluated. [ABSTRACT FROM AUTHOR]

Mixed mode data collection designs are increasingly being adopted with the hope that they may reduce selection errors in single mode survey designs. Yet possible reductions in selection errors achieved by mixing modes may be offset by a potential increase in total survey error due to extra measurement error being introduced by the additional mode(s). Few studies have investigated this empirically, however. In the present study, we compute the Mean Squared Error (MSE) for a range of estimates using data from a mode comparison experiment. We compare two mixed mode designs (a sequential web plus mail survey, and a combined concurrent and sequential CATI plus mail survey) with a single mode mail survey. The availability of auxiliary data on the sampling frame allows us to estimate several components of MSE (sampling variance, non-coverage, nonresponse and measurement bias) for a number of sociodemographic and target variables. Overall, MSEs are lowest for the single mode survey, and highest for the CATI plus mail design, though this pattern is not consistent across all estimates. Mixing modes generally reduces total bias, but the relative contribution to total survey error from different sources varies by design and by variable type. [ABSTRACT FROM AUTHOR]

The first step in subspace methods for identification of multivariable systems is the estimation of the order of the model to be identified. Model order estimation is especially difficult for ill-conditioned systems. In previous work we showed heuristically that appropriately designed experiments with rotated PRBS inputs greatly facilitate model order estimation, hence overall model accuracy. However, design of such experiments depends on the very system to be identified. To overcome that difficulty, in this paper we propose an adaptive design of experiments. The proposed approach follows rigorous justification of the need for rotated PRBS inputs, and is tested through computer simulations on two case studies involving a high-purity distillation column and a fluidized catalytic cracking unit. Comparisons of the approach to open- and closed-loop alternatives are presented, and suggestions for further development are made. [ABSTRACT FROM AUTHOR]

In human motion analysis predictive or functional methods are used to estimate the location of the hip joint centre (HJC). It has been shown that the Harrington regression equations (HRE) and geometric sphere fit (GSF) method are the most accurate predictive and functional methods, respectively. To date, the comparative reliability of both approaches has not been assessed. The aims of this study were to (1) compare the reliability of the HRE and the GSF methods, (2) analyse the impact of the number of thigh markers used in the GSF method on the reliability, (3) evaluate how alterations to the movements that comprise the functional trials impact HJC estimations using the GSF method, and (4) assess the influence of the initial guess in the GSF method on the HJC estimation. Fourteen healthy adults were tested on two occasions using a three-dimensional motion capturing system. Skin surface marker positions were acquired while participants performed quite stance, perturbed and non-perturbed functional trials, and walking trials. Results showed that the HRE were more reliable in locating the HJC than the GSF method. However, comparison of inter-session hip kinematics during gait did not show any significant difference between the approaches. Different initial guesses in the GSF method did not result in significant differences in the final HJC location. The GSF method was sensitive to the functional trial performance and therefore it is important to standardize the functional trial performance to ensure a repeatable estimate of the HJC when using the GSF method. [ABSTRACT FROM AUTHOR]

Feature selection methods are usually evaluated by wrapping specific classifiers and datasets in the evaluation process, resulting very often in unfair comparisons between methods. In this work, we develop a theoretical framework that allows obtaining the true feature ordering of two-dimensional sequential forward feature selection methods based on mutual information, which is independent of entropy or mutual information estimation methods, classifiers, or datasets, and leads to an undoubtful comparison of the methods. Moreover, the theoretical framework unveils problems intrinsic to some methods that are otherwise difficult to detect, namely inconsistencies in the construction of the objective function used to select the candidate features, due to various types of indeterminations and to the possibility of the entropy of continuous random variables taking null and negative values. [ABSTRACT FROM AUTHOR]

Multidimensional computerized adaptive testing ( MCAT) has received increasing attention over the past few years in educational measurement. Like all other formats of CAT, item replenishment is an essential part of MCAT for its item bank maintenance and management, which governs retiring overexposed or obsolete items over time and replacing them with new ones. Moreover, calibration precision of the new items will directly affect the estimation accuracy of examinees' ability vectors. In unidimensional CAT ( UCAT) and cognitive diagnostic CAT, online calibration techniques have been developed to effectively calibrate new items. However, there has been very little discussion of online calibration in MCAT in the literature. Thus, this paper proposes new online calibration methods for MCAT based upon some popular methods used in UCAT. Three representative methods, Method A, the 'one EM cycle' method and the 'multiple EM cycles' method, are generalized to MCAT. Three simulation studies were conducted to compare the three new methods by manipulating three factors (test length, item bank design, and level of correlation between coordinate dimensions). The results showed that all the new methods were able to recover the item parameters accurately, and the adaptive online calibration designs showed some improvements compared to the random design under most conditions. [ABSTRACT FROM AUTHOR]

In this paper, we study the physical layer security (PLS) of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS) scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC) technique and the selection combining (SC) technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP), closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS) scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI) estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to develop county-level estimates of poor health-related quality of life (HRQOL) among aged 65 years and older U.S. adults and to identify spatial clusters of poor HRQOL using a multilevel, poststratification approach.Methods: Multilevel, random-intercept models were fit to HRQOL data (two domains: physical health and mental health) from the 2011-2012 Behavioral Risk Factor Surveillance System. Using a poststratification, small area estimation approach, we generated county-level probabilities of having poor HRQOL for each domain in U.S. adults aged 65 and older, and validated our model-based estimates against state and county direct estimates.Results: County-level estimates of poor HRQOL in the United States ranged from 18.07% to 44.81% for physical health and 14.77% to 37.86% for mental health. Correlations between model-based and direct estimates were higher for physical than mental HRQOL. Counties located in the Arkansas, Kentucky, and Mississippi exhibited the worst physical HRQOL scores, but this pattern did not hold for mental HRQOL, which had the highest probability of mentally unhealthy days in Illinois, Indiana, and Vermont.Conclusions: Substantial geographic variation in physical and mental HRQOL scores exists among older U.S. adults. State and local policy makers should consider these local conditions in targeting interventions and policies to counties with high levels of poor HRQOL scores. [ABSTRACT FROM AUTHOR]

Importance: County-level patterns in mortality rates by cause have not been systematically described but are potentially useful for public health officials, clinicians, and researchers seeking to improve health and reduce geographic disparities.Objectives: To demonstrate the use of a novel method for county-level estimation and to estimate annual mortality rates by US county for 21 mutually exclusive causes of death from 1980 through 2014.Design, Setting, and Participants: Redistribution methods for garbage codes (implausible or insufficiently specific cause of death codes) and small area estimation methods (statistical methods for estimating rates in small subpopulations) were applied to death registration data from the National Vital Statistics System to estimate annual county-level mortality rates for 21 causes of death. These estimates were raked (scaled along multiple dimensions) to ensure consistency between causes and with existing national-level estimates. Geographic patterns in the age-standardized mortality rates in 2014 and in the change in the age-standardized mortality rates between 1980 and 2014 for the 10 highest-burden causes were determined.Exposure: County of residence.Main Outcomes and Measures: Cause-specific age-standardized mortality rates.Results: A total of 80 412 524 deaths were recorded from January 1, 1980, through December 31, 2014, in the United States. Of these, 19.4 million deaths were assigned garbage codes. Mortality rates were analyzed for 3110 counties or groups of counties. Large between-county disparities were evident for every cause, with the gap in age-standardized mortality rates between counties in the 90th and 10th percentiles varying from 14.0 deaths per 100 000 population (cirrhosis and chronic liver diseases) to 147.0 deaths per 100 000 population (cardiovascular diseases). Geographic regions with elevated mortality rates differed among causes: for example, cardiovascular disease mortality tended to be highest along the southern half of the Mississippi River, while mortality rates from self-harm and interpersonal violence were elevated in southwestern counties, and mortality rates from chronic respiratory disease were highest in counties in eastern Kentucky and western West Virginia. Counties also varied widely in terms of the change in cause-specific mortality rates between 1980 and 2014. For most causes (eg, neoplasms, neurological disorders, and self-harm and interpersonal violence), both increases and decreases in county-level mortality rates were observed.Conclusions and Relevance: In this analysis of US cause-specific county-level mortality rates from 1980 through 2014, there were large between-county differences for every cause of death, although geographic patterns varied substantially by cause of death. The approach to county-level analyses with small area models used in this study has the potential to provide novel insights into US disease-specific mortality time trends and their differences across geographic regions. [ABSTRACT FROM AUTHOR]

In the presented paper, a simple and feasible method for estimation of stage-discharge relationship in natural rivers using the concept of discharge estimation based on single point velocity measurement is introduced. Two innovative techniques have been implemented in rating curve estimation. First, discharge at a certain stage can be estimated by velocity measurement at an arbitrary point in the flow cross section. Then a relationship between the parameters obtained by the single point measurement technique and discharge ratios at different stages is presented. For this purpose, a relationship based on dimensional analysis through minimization of the differences between the calculated and analytical discharges at two different stages is established. For the verification, the results of the proposed relationship are compared with the observed stage-discharge data taken from the Severn River in UK, the Cuenca and Tomebamba rivers in Ecuador. The results have shown the high accuracy of the proposed method in such a way that the maximum relative errors for the Severn, Cuenca and Tomebamba rivers are less than 3%, 6% and 3%, respectively. In estimation of stage-discharge relationship, if the referenced stage is taken from higher stages, maximum error will be reduced to much smaller values. [ABSTRACT FROM AUTHOR]

The application of the Quality by Design principles is one of the key issues of the recent pharmaceutical developments. In the past decade a lot of knowledge was collected about the practical realization of the concept, but there are still a lot of unanswered questions. The key requirement of the concept is the mathematical description of the effect of the critical factors and their interactions on the critical quality attributes (CQAs) of the product. The process design space (PDS) is usually determined by the use of design of experiment (DoE) based response surface methodologies (RSM), but inaccuracies in the applied polynomial models often resulted in the over/underestimation of the real trends and changes making the calculations uncertain, especially in the edge regions of the PDS. The completion of RSM with artificial neural network (ANN) based models is therefore a commonly used method to reduce the uncertainties. Nevertheless, since the different researches are focusing on the use of a given DoE, there is lack of comparative studies on different experimental layouts. Therefore, the aim of present study was to investigate the effect of the different DoE layouts (2 level full factorial, Central Composite, Box–Behnken, 3 level fractional and 3 level full factorial design) on the model predictability and to compare model sensitivities according to the organization of the experimental data set. It was revealed that the size of the design space could differ more than 40% calculated with different polynomial models, which was associated with a considerable shift in its position when higher level layouts were applied. The shift was more considerable when the calculation was based on RSM. The model predictability was also better with ANN based models. Nevertheless, both modelling methods exhibit considerable sensitivity to the organization of the experimental data set, and the use of design layouts is recommended, where the extreme values factors are more represented. [ABSTRACT FROM AUTHOR]

Estimating and verifying soil unit weight determined on the basis of SCPTu tests. The unit weight, as a basic physical feature of soil, is an elementary quantity, and knowledge of this parameter is necessary in each geotechnical and geo-engineering task. Estimation of this quantity can be made with both laboratory and field techniques. The paper comprises a multi-scale evaluation of unit weight of cohesive soil, based on several measurements made in nearby locations using the SCPTu static probe. The procedures used were based on the two classifications and two solutions from literature. The results were referenced to the actual values of unit weight determined with a direct procedure from undisturbed samples. The resulting solutions were the basis for proposing a new formula to determine the soil unit weight from SCPTu measurements, as well as comparative analysis using exemplary values taken from the national Polish standard. [ABSTRACT FROM AUTHOR]

The main objective of this study is to investigate the use of the landfill gas as potential energy and electricity obtained from the municipal solid waste (domestic, industrial, medical waste, and sewage sludge) stored regularly in the Harmandali solid waste landfill area, within the boundaries of the contiguous area of Izmir. The most important factor in making a decision about energy potential in the landfill is the amount of methane in the landfill gas. There are several approaches that have been used to determine the amount of the landfill gas. In this study, three different methods and one approach in the literature were used for this purpose. The methods used are the Multi-Phase, the LandGEM, and the IPCC 2006. The results of the landfill gas obtained using the three methods, namely the Multi-Phase, the LandGEM (k= 0.35,k= 0.1, andk= 0.05), and the IPCC 2006, were as follows, respectively: 291897215, 792073359, 769734749, 681685027, and 491752247 m3. It may be concluded that the Harmandali Landfill has high landfill gas potential based on the measurements and mathematical methods used in the Harmandali landfill. [ABSTRACT FROM AUTHOR]

The present study reports the characteristics of the bottom-side profile thickness (B0) and shape (B1) parameters from ionosonde and IRI-2012 model over the Brazilian sector. The ionosonde data from an equatorial station Fortaleza and a low latitude station Cachoera Paulista during a two year period from 2010 to 2011 are considered in this study. Simultaneous comparison is made on the performance of three different options ‘Gul-1987’, ‘Bil-2000’ and the ‘ABT-2009’ for bottom-side profile estimation in the latest available IRI-2012. The diurnal and seasonal characteristics of the B0 and B1 from ionosonde measurements are studied and compared with those from the IRI-2012 model using the three different options. It is seen that the Gul-1987 method shows better predictions of the observed B0 at the equatorial and low latitudes values when compared with the other options. The latest option ‘ABT-2009’ has shown improved predictions in the estimation of B1 compared with those from the other methods particularly during the night-time hours. A comparison on the seasonal characteristics of the day maximum values of B0 between observations and the three different options in IRI-2012 reveals that the Gul-1987 method shows better predictions of the seasonal variations in B0 while ABT-2009 method shows better predictions of seasonal variations in B1. Further, an insight into the percentage of deviations in the estimation of B0 and B1 reveals that the models overestimate the B0 during night-time and underestimate the B0 (at equator) during day-time while they underestimate the B1 during night-time hours at both locations. Also, the variations in the bottom-side total electron content are studied using the three different methods in the IRI-2012 model and compared with those derived from the ionosonde observations. [ABSTRACT FROM AUTHOR]

We introduce very simple non-parametric methods that overcome key limitations of the existing literature on both the joint and marginal density estimation. In doing so, we do not assume any form of the marginal distribution or joint distribution a priori. Furthermore, our method circumvents the bandwidth selection problems. We compare our method to the kernel density method. [ABSTRACT FROM AUTHOR]

Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended moving average (MFDMA) algorithm have been established as two important methods to estimate the multifractal spectrum of the one-dimensional random fractal signal. They have been generalized to deal with two-dimensional and higher-dimensional fractal signals. This paper gives a brief introduction of the two-dimensional multifractal detrended fluctuation analysis (2D-MFDFA) and two-dimensional multifractal detrended moving average (2D-MFDMA) algorithm, and a detailed description of the application of the two-dimensional fractal signal processing by using the two methods. By applying the 2D-MFDFA and 2D-MFDMA to the series generated from the two-dimensional multiplicative cascading process, we systematically do the comparative analysis to get the advantages, disadvantages and the applicabilities of the two algorithms for the first time from six aspects such as the similarities and differences of the algorithm models, the statistical accuracy, the sensitivities of the sample size, the selection of scaling range, the choice of the q -orders and the calculation amount. The results provide a valuable reference on how to choose the algorithm from 2D-MFDFA and 2D-MFDMA, and how to make the schemes of the parameter settings of the two algorithms when dealing with specific signals in practical applications. [ABSTRACT FROM AUTHOR]

This paper proposes the nonnegative adaptive lasso method for variable selection both in the classical fixed p setting (OLS initial estimator) and the ultra-high dimensional setting (root-n-consistent initial estimator). This method is an extension of the adaptive lasso with nonnegative constraint on the coefficients. It is shown to have asymptotic unbiasedness, asymptotic normality and variable selection consistency and its mean squared error decays fast too. Comparing with other procedures, nonnegative adaptive lasso satisfies oracle properties and can select the true variables under fewer assumptions. To get the solution of the nonnegative adaptive lasso, we extend the multiplicative approach for computing. This algorithm is valid for the general framework where the number of regression parameters p is allowed to very large. Simulations are performed to illustrate above results. The constrained index tracking problem in the stock market without short sales is studied in the empirical part. A two-stage method, nonnegative adaptive lasso + nonnegative LS, is applied in the financial modeling. The tracking results indicate that nonnegative adaptive lasso and the two-stage method can both get small tracking error and is successful in assets selection. [ABSTRACT FROM AUTHOR]

Introduction: Generally range of motion (ROM) in total hip arthroplasty (THA) is intraoperatively assessed by eye. Can we assume that visual estimation of ROM is reliable?Methods: 60 patients underwent cementless THA in a subgroup analysis of a clinical prospective trial using a minimally invasive anterolateral approach in lateral decubitus position. Four experienced surgeons intraoperatively estimated ROM visually by assessment of the femur relative to the alignment of the patient's pelvis. These estimations were compared with computer navigation measurements.Results: We found a mean difference between navigation measurements and intraoperative estimations by eye of -5.6° (±10.9°; -17° to 30°) for flexion, respectively, -0.4° (±10.7°; -24° to 30°) for extension, 8.7° (±9.0°; -10° to 34°) for abduction, 5.9° (±18.3°; -58° to 68°) for external rotation and -5.8° (±12.1°; -38° to 22°) for internal rotation. Multivariate analysis showed no association between the visual accuracy of estimation of ROM and patient characteristics, such as BMI, sex, grade of osteoarthritis and treatment side except for a significant correlation of visual accuracy of estimation of extension and the level of professional experience. Otherwise, the level of professional experience had no impact on the accuracy of estimation of ROM by eye.Conclusions: Even the experienced surgeon's intraoperative estimation of ROM by eye is not reliable and differs up to 30° compared to objective measurements in minimally invasive THA. For accurate intraoperative assessment of ROM, the use of technical devices is recommended.Trial Registration: DRKS00000739. [ABSTRACT FROM AUTHOR]

Objective: To effectively practice evidence-based medicine, surgeons need to understand and be able to communicate health-relevant numerical information. We present the first study examining risk literacy in surgeons by assessing numeracy and surgical risk comprehension. Our study also investigated whether visual aids improve risk comprehension in surgeons with limited numeracy.Methods: Participants were 292 surgeons from 60 countries who completed an instrument measuring numeracy and evaluated the results of a randomized controlled trial including post-surgical side-effects. Half of the surgeons received this information in numbers. The other half received the information represented visually. Accuracy of risk estimation, reading latency, and estimate latency (i.e., deliberation) were assessed.Results: Some surgeons have low numeracy and could not correctly interpret surgical risks without additional support. Visual aids made risks transparent and eliminated differences in risk understanding between more and less numerate surgeons, increasing the amount of time that less numerate surgeons spent deliberating about risks.Conclusions: Visual aids can be an efficient and inexpensive means of improving risk comprehension and clinical judgement in surgeons with low numerical and statistical skills.Practice Implications: Programs designed to help professionals represent and communicate health-relevant numerical information in simple transparent graphs may unobtrusively promote informed decision making. [ABSTRACT FROM AUTHOR]

As the demand for eco-friendly food—produced without pesticides and environmentally harmful chemicals—increases, the need to develop genetically modified (GM) organisms that are more resistant to parasites and other environmental crop threats may increase. Because of this, products labeled both “eco-friendly” and “genetically modified” could become commonly available on the market. In this paper, we explore—in a Swedish and a UK sample—the consequences of combining eco-labeling and GM-labeling to judgments of taste, health consequences and willingness to pay for raisins. Participants tasted and evaluated four categories of raisins (eco-labeled and GM-labeled; eco-labeled; GM-labeled; and neither eco-labeled nor GM-labeled). The results suggest that there is a cost associated with adding a GM-label to an eco-labeled product: The GM-label removes the psychological benefits of the eco-label. This negative effect of the GM-label was larger among Swedish participants in comparison with UK participants, because the magnitude of the positive effect of the eco-label was larger in the Swedish sample and, hence, the negative effects of the GM-label became more pronounced (especially for health estimates). The roles of individual differences in attitudes, environmental concern and socially desirable responding in relation to the label effects are discussed. [ABSTRACT FROM AUTHOR]

Men who have sex with men are increasingly recognised as one of the most vulnerable HIV risk groups in Kenya. Sex between men is highly stigmatised in Kenya, and efforts to provide sexual health services to men who have sex with men require a deeper understanding of their lived experiences; this includes how such men in Kenya construct their sexual identities and how these constructions affect sexual decision-making. Adult self-identified men who have sex with men (n= 26) in Malindi, Kenya, participated in individual interviews to examine sociocultural processes influencing sexual identity construction and decision-making. Four key themes were identified: (1) tensions between perceptions of ‘homosexuality’ versus being ‘African’, (2) gender-stereotyped beliefs about sexual positioning, (3) socioeconomic status and limitations to personal agency and (4) objectification and commodification of non-normative sexualities. Findings from this analysis emphasise the need to conceive of same-sex sexuality and HIV risk as context-dependent social phenomena. Multiple sociocultural axes were found to converge and shape sexual identity and sexual decision-making among this population. These axes and their interactive effects should be considered in the design of future interventions and other public health programmes for men who have sex with men in this region. [ABSTRACT FROM PUBLISHER]

The conventional SUR model has a strong assumption of normally distributed residuals which might not be realistic. What this paper suggests is to take an advantage from Copulas approach in order to relax this normality assumption. Therefore, we introduce the Copulabased SUR model as an alternative to the conventional SUR model. The performance and accuracy of the proposed model are evaluated through the simulation study. We then apply the Copula-based SUR model to the real data set of Thai rubber and compare the estimation result with the result obtained f rom the conventional SUR model. The results of this paper could support our suggestion that the Copulas can be used appropriately to relax the assumption of normality of residuals in the conventional SUR model. [ABSTRACT FROM AUTHOR]

Soil fertility and organic carbon (C) stock estimations are crucial to soil management, especially that of degraded soils, for productive agricultural use and in soil C sequestration studies. Currently, estimations based on generalized soil mass (hectare furrow basis) or bulk density are used which may be suitable for normal agricultural soils, but not for degraded soils. In this study, soil organic C, available nitrogen (N), available phosphorus (P2O5) and available potassium (K2O), and their stocks were estimated using three methods: (i) generalized soil mass (GSM, 2 million kg ha-1 furrow soil), (ii) bulk-density-based soil mass (BDSM) and (iii) the proportion of fine earth volume (FEV) method, for soils sampled from physically degraded lands in the eastern dry zone of Karnataka State in India. Comparative analyses using these methods revealed that the soil organic C, N, P2O and K2O stocks determined by using BDSM were higher than those determined by the GSM method. The soil organic C values were the lowest in the FEV method. The GSM method overestimated soil organic C, N, P2O and K2O by 9.3-72.1, 9.5-72.3, 7.1-66.6 and 9.2-72.3%, respectively, compared to FEV-based estimations for physically degraded soils. The differences among the three methods of estimation were lower in soils with low gravel content and increased with an increase in gravel volume. There was overestimation of soil organic C and soil fertility with GSM and BDSM methods. A reassessment of methods of estimation was, therefore, attempted to provide fair estimates for land development projects in degraded lands. [ABSTRACT FROM AUTHOR]

We estimated the dynamic cell metabolic activity and the distribution of the pH value and oxygen concentration in tissue samples cultured in vitro by using real-time sensor records and a numerical simulation of the underlying reaction-diffusion processes. As an experimental tissue model, we used chicken spleen slices. A finite element method model representing the biochemical processes and including the relevant sensor data was set up. By fitting the calculated results to the measured data, we derived the spatiotemporal values of the pH value, the oxygen concentration and the absolute metabolic activity (extracellular acidification and oxygen uptake rate) of the samples. Notably, the location of the samples in relation to the sensors has a great influence on the detectable metabolic rates. The long-term vitality of the tissue samples strongly depends on their size. We further discuss the benefits and limitations of the model. [ABSTRACT FROM AUTHOR]

Impact by windborne debris can cause severe and wide spread damage to building facades and other exposed installations. There is no clear guidance on how to estimate the amount of force generated by the impact of windborne debris when design codes of practices only provide estimates of the wind pressure. The model presented in this paper enables the value of the peak contact force generated by the impact of a piece of debris to be predicted. Results of calculations employing the derived relationships have been verified by comparison with experimental results across a wide range of impact scenarios. Once the impact action has been quantified the predicted impact force can be applied to the target in a quasi-static manner for predicting damage. [ABSTRACT FROM AUTHOR]

Accurate estimates of spatio-temporal resolved near-surface air temperature ( T a ) are crucial for environmental epidemiological studies. However, values of T a are conventionally obtained from weather stations, which have limited spatial coverage. Satellite surface temperature ( T s ) measurements offer the possibility of local exposure estimates across large domains. The Southeastern United States has different climatic conditions, more small water bodies and wetlands, and greater humidity in contrast to other regions, which add to the challenge of modeling air temperature. In this study, we incorporated satellite T s to estimate high resolution (1 km×1 km) daily T a across the southeastern USA for 2000–2014. We calibrated T s – T a measurements using mixed linear models, land use, and separate slopes for each day. A high out-of-sample cross-validated R 2 of 0.952 indicated excellent model performance. When satellite T s were unavailable, linear regression on nearby monitors and spatio-temporal smoothing was used to estimate T a . The daily T a estimations were compared to the NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) model. A good agreement with an R 2 of 0.969 and a mean squared prediction error (RMSPE) of 1.376 °C was achieved. Our results demonstrate that T a can be reliably predicted using this T s -based prediction model, even in a large geographical area with topography and weather patterns varying considerably. [ABSTRACT FROM AUTHOR]

An estimate of stature can be used by a forensic anthropologist with the preliminary identification of an unknown individual when human skeletal remains are recovered. Fordisc is a computer application that can be used to estimate stature; like many other methods it requires the user to assign an unknown individual to a specific group defined by sex, race/ancestry, and century of birth before an equation is applied. The assumption is that a group-specific equation controls for group differences and should provide the best results most often. In this paper we assess the utility and benefits of using group-specific equations to estimate stature using Fordisc. Using the maximum length of the humerus and the maximum length of the femur from individuals with documented stature, we address the question: Do sex-, race/ancestry- and century-specific stature equations provide the best results when estimating stature? The data for our sample of 19th Century White males (n=28) were entered into Fordisc and stature was estimated using 22 different equation options for a total of 616 trials: 19th and 20th Century Black males, 19th and 20th Century Black females, 19th and 20th Century White females, 19th and 20th Century White males, 19th and 20th Century any, and 20th Century Hispanic males. The equations were assessed for utility in any one case (how many times the estimated range bracketed the documented stature) and in aggregate using 1-way ANOVA and other approaches. This group-specific equation that should have provided the best results was outperformed by several other equations for both the femur and humerus. These results suggest that group-specific equations do not provide better results for estimating stature while at the same time are more difficult to apply because an unknown must be allocated to a given group before stature can be estimated. [ABSTRACT FROM AUTHOR]

This paper reports on a bilateral comparison of millimeter-wave attenuation in WR-15 waveguide band between the National Metrology Institute of Japan (NMIJ) and the National Metrology Centre, A∗STAR (NMC). Different types of attenuation measurement systems were independently developed at both laboratories. The systems are based on a stabilized single-channel intermediate frequency (IF) substitution method at NMIJ, and a dual-channel audio frequency substitution method at NMC. A comparison was carried out at 50 GHz and 54 GHz using a programmable step attenuator fitted with precision coaxial to waveguide adaptors as a traveling standard. Good agreement of the measurement results between both laboratories was verified in the attenuation range up to 60 dB. [ABSTRACT FROM AUTHOR]

Because of its importance in number theory and singularity theory, the problem of finding a polynomial sharp upper estimate of the number of positive integral points in an n -dimensional ( n ≥ 3 ) polyhedron has received attention by a lot of mathematicians. The first named author proposed the Number Theoretic Conjecture for the upper estimate. The previous results on the Number Theoretic Conjecture in low dimension cases ( n < 7 ) are proved by using the sharp GLY conjecture which is true only for low dimensional case. Thus the proof cannot be generalized to high dimension. In this paper, we offer a uniform approach to prove the Number Theoretic Conjecture for all dimensions by simply using the induction method and the Yau–Zhang [19] estimates (see Lemmas 2.3–2.5 ). As a result, the Number Theoretic Conjecture is proven for n = 7 . An important estimate for all dimensions is also obtained ( Propositions 3.1 and 3.2 ) which will be useful to prove the general case of the Number Theoretic Conjecture. As an application, we give a sharper estimate of the Dickman–De Bruijn function ψ ( x , y ) for 5 ≤ y < 19 , compared with the result obtained by Ennola. [ABSTRACT FROM AUTHOR]

Estimating statistics of model outputs with the Monte Carlo method often requires a large number of model evaluations. This leads to long runtimes if the model is expensive to evaluate. Importance sampling is one approach that can lead to a reduction in the number of model evaluations. Importance sampling uses a biasing distribution to sample the model more efficiently, but generating such a biasing distribution can be difficult and usually also requires model evaluations. A different strategy to speed up Monte Carlo sampling is to replace the computationally expensive high-fidelity model with a computationally cheap surrogate model; however, because the surrogate model outputs are only approximations of the high-fidelity model outputs, the estimate obtained using a surrogate model is in general biased with respect to the estimate obtained using the high-fidelity model. We introduce a multifidelity importance sampling (MFIS) method, which combines evaluations of both the high-fidelity and a surrogate model. It uses a surrogate model to facilitate the construction of the biasing distribution, but relies on a small number of evaluations of the high-fidelity model to derive an unbiased estimate of the statistics of interest. We prove that the MFIS estimate is unbiased even in the absence of accuracy guarantees on the surrogate model itself. The MFIS method can be used with any type of surrogate model, such as projection-based reduced-order models and data-fit models. Furthermore, the MFIS method is applicable to black-box models, i.e., where only inputs and the corresponding outputs of the high-fidelity and the surrogate model are available but not the details of the models themselves. We demonstrate on nonlinear and time-dependent problems that our MFIS method achieves speedups of up to several orders of magnitude compared to Monte Carlo with importance sampling that uses the high-fidelity model only. [ABSTRACT FROM AUTHOR]

The subject of the study were dogs divided into two groups according to body weight: up to 10 kg and from 10 kg to 30 kg. The aim of the study was to determine the dynamics of the post-mortem decrease in rectal and kidney temperature. The temperature was measured on both sites at the same time using a thermometer connected to a computer, under constant environmental conditions of the necropsy room. In these animals, a higher temperature in the kidneys persisted for the duration of the study. Comparative analysis between mean differences in kidney and rectal temperature in small and large dogs showed the greatest temperature amplitude in the group of small dogs, both for the kidney and the rectum. The greatest decrease in temperature, 1.2°C, was noted for the kidney in small dogs between 4 and 6 hours after death. Analysis of the dynamics of the decrease in kidney and rectal temperature for both weight groups combined, and the difference in temperature between the kidney and the rectum in the time intervals analysed showed that in the first two hours the difference between kidney and rectal temperature did not exceed 0.5°C. Two hours after death the difference in temperature between the two measurement sites was about 0.5°C after which time dropped below 0.5ºC. [ABSTRACT FROM AUTHOR]

SuperParent-One-Dependence Estimators (SPODEs) represent a family of semi-naive Bayesian classifiers which relax the attribute independence assumption of Naive Bayes (NB) to allow each attribute to depend on a common single attribute (superparent). SPODEs can effectively handle data with attribute dependency but still inherent NB׳s key advantages such as computational efficiency and robustness for high dimensional data. In reality, determining an optimal superparent for SPODEs is difficult. One common approach is to use weighted combinations of multiple SPODEs, each having a different superparent with a properly assigned weight value ( i.e ., a weight value is assigned to each attribute). In this paper, we propose a self-adaptive SPODEs, namely SODE, which uses immunity theory in artificial immune systems to automatically and self-adaptively select the weight for each single SPODE. SODE does not need to know the importance of individual SPODE nor the relevance among SPODEs, and can flexibly and efficiently search optimal weight values for each SPODE during the learning process. Extensive experiments and comparisons on 56 benchmark data sets, and validations on image and text classification, demonstrate that SODE outperforms state-of-the-art weighted SPODE algorithms and is suitable for a wide range of learning tasks. Results also confirm that SODE provides an appropriate balance between runtime efficiency and accuracy. [ABSTRACT FROM AUTHOR]