Comparison of a linear and a non-linear model for using sensory–motor,cognitive, personality,and demographic data to predict driving ability in healthy older adults

This study compared the ability of binary logistic regression (BLR) and non-linear causal resource analysis (NCRA) to utilize a range of cognitive, sensory–motor, personality and demographic measures to predict driving ability in a sample of cognitively healthy older drivers.Participants were sixty drivers aged 70 and above (mean = 76.7 years, 50% men) with no diagnosed neurological disorder. Test data was used to build classification models for a Pass or Fail score on an on-road driving assessment. The generalizability of the models was estimated using leave-one-out cross-validation.Sixteen participants (27%) received an on-road Fail score. Area under the ROC curve values were .76 for BLR and .88 for NCRA (no significant difference, z = 1.488, p = .137). The ROC curve was used to select three different cut-points for each model and to compare classification. At the cut-point corresponding to the maximum average of sensitivity and specificity, the BLR model had a sensitivity of 68.8% and specificity of 75.0% while NCRA had a sensitivity of 75.0% and specificity of 95.5%. However, leave-one-out cross-validation reduced sensitivity in both models and particularly reduced specificity for NCRA.Neither model is accurate enough to be relied on solely for determination of driving ability. The lowered accuracy of the models following leave-one-out cross-validation highlights the importance of investigating models beyond classification alone in order to determine a model's ability to generalize to new cases.     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

Why do organizations not learn from incidents? Bottlenecks,causes and conditions for a failure to effectively learn

If organizations would be able to learn more effectively from incidents that occurred in the past, future incidents and consequential injury or damage can be prevented. To improve learning from incidents, this study aimed to identify limiting factors, i.e. the causes of the failure to effectively learn. In seven organizations focus groups were held to discuss factors that according to employees contributed to the failure to learn. By use of a model of the learning from incidents process, the steps, where difficulties for learning arose, became visible, and the causes for these difficulties could be studied.     

Performance model’s development: a novel approach encompassing ontology-based data access and visual analytics

Scientometrics - The quantitative evaluation of research is currently carried out by means of indicators calculated on data extracted and integrated by analysts who elaborate them by creating...     

Strategies to synthesise copper oxide nanoparticles and their bio applications – a review

Researchers have identified copper oxide nanoparticles (CuO-NPs) as a key of interest because of their unique shape- and size-dependent bio-medical properties. Researchers have discovered and invented a variety of methods for the synthesis of CuO-NPs under physical, chemical and biological approach. In this review paper, we give an overview of the preparation of CuO-NPs through various methods and also their applications in the bio-medical field. The main aim of this paper is to keep up to date with the myriad ongoing methods of NPs’ synthesis and also examine their applications, especially in the field of medicine.     

Queuing network analysis for a mixed voice and data communication network with end‐to‐end window flow control policy

Abstract

A Mixed Voice and Data Communication Network (MVDNET) with end‐to‐end (ETE) window flow control policy is modeled by a closed multichain queuing network. Using an approximate solution of the Mean Value Analysis (MVA) algorithm, the computational complexity of analysing a large‐scale MVDNET and various commodities is dramatically reduced by several orders of magnitude over that required by traditional product‐form solution. We consider the problems concerned with the choice of window size, the effect of voice interruption, the number of voice‐grade (VG) channels per internode link and the selection of appropriate packet length. It is shown that the analytic results are very close to the simulation ones using GPSS language, and that the extensive MVA algorithm is a practical and valuable tool for solving the MVDNET analytical model with ETE window flow control policy.     

Measurements of Vapor Pressures from 280 to 369 K and (p, ρ, T) Properties from 340 to 400 K at Pressures to 200 MPa for Propane

Measurements of (p, ρ, T) properties for compressed liquid propane have been obtained by means of a metal-bellows variable volumometer at temperatures from 340 to 400 K at pressures up to 200 MPa. The volume- fraction purity of the propane sample was 0.9999. The expanded uncertainties (k = 2) of temperature, pressure, and density measurements have been estimated to be less than 3 mK; 1.5 kPa ( MPa), 0.06% (7 MPa MPa), 0.1% (50 MPa MPa) , and 0.2% (p>150 MPa); and 0.11%, respectively. Four (p, ρ, T) measurements at the same temperatures and pressures as literature values have been conducted for comparisons. In addition, vapor pressures were measured at temperatures from 280 to 369 K. Furthermore, comparisons of available equations of state with the present measurements are reported.Paper presented at the 17th European Conference on Thermophysical Properties, September 5–8, 2005, Bratislava, Slovak Republic.     

Mechanical properties of small structures built by selective laser melting 316 L stainless steel – a phenomenological approach to improve component design

Experimental investigations are conducted to quantify the influence of specimen thickness and orientation on the mechanical properties of selective laser melted stainless steel 316 L. The results indicate that the mechanical strength and ductility increase with increasing specimen thickness until a saturation value is reached from a specimen thickness of about 2 mm. Specimen orientation dependency is pronounced for thin specimens (<1.5 mm), whereas only small deviations in strength are observed for thicker specimens with orientations of 30°, 45° and 90° to build direction. The mechanical properties of the specimen orientation of 0° to build direction shows great deviation to the other orientations and the smallest overall strength. A reliable design of selective laser melted components should account for specimen thickness and orientation, e. g. by a correction factor. Furthermore, it is recommended to avoid loads vertical (90°) and parallel (0°) to build direction to guarantee higher ductility and strength.     

Multistage accurate mass spectrometry: a "basket in a basket" approach for structure elucidation and its application to a compound from combinatorial synthesis

A "basket in a basket" method based on a multistage accurate mass spectrometric (MAMS) technique was developed and demonstrated by obtaining a unique elemental composition of a compound (with a molecular weight of 517) from combinatorial synthesis. The accurate masses for the parent and the fragment ions were obtained with up to five stages of MAMS using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This approach requires only input of elements used in the synthetic processes and some constraints about unusual light elements, such as fluorine, while the compositions of the parent ions and their fragments are obtained for structure elucidation. Conversely, accuracy of better than 0.02 ppm (assuming elements C, H, N, O, S, and F are involved) would be required in order to define a unique composition for the same mass using a direct accurate mass measurement because the number of possible elemental compositions increases sharply as the mass increases. Similarly, due to the uncertainty in determining elemental compositions of fragments and complexity of possible internal fragmentation, tandem mass spectrometry may not provide enough information for structure elucidation of unknown compounds, especially of the organic molecules in the mass range of 300-1000 Da, typically encountered in combinatorial lead generation. The application of MAMS to combinatorial drug discovery is particularly advantageous since the built-in chemical information from the synthesis can be used as constraints. The implementation of a nanoelectrospray ionization technique makes this approach practical for characterization of small quantities of compounds typically available from lead generation processes.     

The relation between speed environment,age and injury outcome for bicyclists struck by a motorized vehicle – a comparison with pedestrians

This study analyzes (a) the relation between injury severities, the age of the bicyclist and the speed environment at accident locations (mean travel speed of the traffic flow involved in the accident) where a bicyclist was struck by a motorized vehicle and (b) how these relations differ from those for struck pedestrians. Accident data from Sweden for the years 2004–2008 was used to identify accident locations to analyze the relations between speed environment, age and injury outcome. Seventy-seven accident sites were used for field measurements and further analysis. The results show that both speed environment and age have considerable correlation with injury severity. There was a statistically significant relation between injury severity and the speed environment, and large proportion of the serious bicycle accidents occur at locations with speeds below 30 km/h. Also, the risk of serious injuries or fatalities seems to increase after the age of 45. To our knowledge this is the first study that uses the mean travel speed in this manner for analyzing injury severity of struck bicyclists.     

From waste to value – a system dynamics model for strategic decision-making in closed-loop supply chains

Although the field of closed-loop supply chain management has attracted a lot of attention in recent years and the management of reverse logistics processes has become a major field of supply chain management, there is still a lack of research conducting analyses using a comprehensive approach that takes the complexity of problems of reverse logistics processes into account. Hence, the purpose of this paper is to develop a model that allows an original equipment manufacturer in the electronics industry to test different value recovery strategies for business-to-business products in a closed-loop supply chain setting. For this purpose system dynamics is used because this approach enables one to capture the high complexity of reverse logistics processes and is suitable, contrary to traditional optimisation approaches, for analysing the dynamic behaviour of closed-loop supply chains comprehensively. The simulation analysis identifies leverage points for the improvement of decisions concerning reverse logistics. In particular, the simulation runs conducted highlight the high complexity and connectivity inherited with various value recovery processes. The paper contributes to a better understanding of supply chain dynamics, the impact of product backflow, and reverse logistics.     

CARI – a heuristic approach to machine-part cell formation using correlation analysis and relevance index

Machine-part cell formation is the process of identifying part families and the appropriate machine cell for each part family. Grouping efficacy (GE), the widely used measure for assessing the goodness of the machine-part cells depends on identification of correct part families and the appropriate machine cell for each part family. In this paper, a heuristic based on correlation analysis and relevance index is proposed for the formation of machine-part cells. Computational performance of the proposed heuristic on a set of group technology data-set available in the literature is also presented. GE of the solutions produced by the proposed heuristic is equal to the best efficacy reported in the literature for 63% of the test instances and improved the GE for 6% of the total test instances.     

Separation of 47Sc produced from natCa(n, γ) reaction for potential medical applications by a synthesized raspberry-like structure of metal-organic framework material

This work aimed for the synthesis of a novel metal organic framework through a facile and gamma-irradiation process to be applied for the separation of scandium-47 as theranostic radioisotope from the irradiated calcium target. Polyacrylonitrile-cupric oxide nanocomposite structure (as metal organic framework) was successfully synthesized and characterized. The optimized conditions (such as monomer concentration, weight of cupric oxide nanoparticles and gamma-dose) for the synthesis of polyacrylonitrile-cupric oxide were identified. The newly synthesized resin was used to study the separation of micro amounts of scandium-47 from gram amounts of the irradiated calcium carbonate by batch equilibration and column studies. Preliminary study demonstrated that the Kd values of scandium(III) ions are little higher than that of calcium(II) ions. The elution yield of scandium-47(III) was found to be 61±2 %. Future work will be done to improve this yield for nuclear medicine applications.     

Binary Bees Algorithm – bioinspiration from the foraging mechanism of honeybees to optimize a multiobjective multidimensional assignment problem

The simultaneous mission assignment and home allocation for hospital service robots studied is a Multidimensional Assignment Problem (MAP) with multiobjectives and multiconstraints. A population-based metaheuristic, the Binary Bees Algorithm (BBA), is proposed to optimize this NP-hard problem. Inspired by the foraging mechanism of honeybees, the BBA's most important feature is an explicit functional partitioning between global search and local search for exploration and exploitation, respectively. Its key parts consist of adaptive global search, three-step elitism selection (constraint handling, non-dominated solutions selection, and diversity preservation), and elites-centred local search within a Hamming neighbourhood. Two comparative experiments were conducted to investigate its single objective optimization, optimization effectiveness (indexed by the S-metric and C-metric) and optimization efficiency (indexed by computational burden and CPU time) in detail. The BBA outperformed its competitors in almost all the quantitative indices. Hence, the above overall scheme, and particularly the searching history-adapted global search strategy was validated.     

Molar Heat Capacity Cv, Vapor Pressure, and (p, ρ, T) Measurements from 92 to 350 K at Pressures to 35 MPa and a New Equation of State for Chlorotrifluoromethane (R13)

Measurements of the molar heat capacity at constant volume C _v for chlorotrifluoromethane (R13) were conducted using an adiabatic method. Temperatures ranged from 95 to 338 K, and pressures were as high as 35 MPa. Measurements of vapor pressure were made using a static technique from 250 to 302 K. Measurements of (p, , T) properties were conducted using an isochoric method; comprehensive measurements were conducted at 15 densities which varied from dilute vapor to highly compressed liquid, at temperatures from 92 to 350 K. The R13 samples were obtained from the same sample bottle whose mole fraction purity was measured at 0.9995. A test equation of state including ancillary equations was derived using the new vapor pressures and (p, , T) data in addition to similar published data. The equation of state is a modified Benedict–Webb–Rubin type with 32 adjustable coefficients. Acceptable agreement of C _v predictions with measurements was found. Published C _v(, T) data suitable for direct comparison with this study do not exist. The uncertainty of the C _v values is estimated to be less than 2.0% for vapor and 0.5% for liquid. The uncertainty of the vapor pressures is 1 kPa, and that of the density measurements is 0.1%.     

Coronavirus mapping in scientific publications: When science advances rapidly and collectively,is access to this knowledge open to society?

Scientometrics - The COVID-19 pandemic is creating a global health emergency. Mapping this health emergency in scientific publications demands multiple approaches to obtain a picture as complete as...     

A systems-integration approach to the optimization of macroscopic water desalination and distribution networks: a general framework applied to Qatar’s water resources

The objective of this article is to introduce an optimization-based approach for the integrated design and operation of macroscopic water networks. A structural representation approach is developed to embed all potential configurations of interest. This representation accounts for water resources, desalination plants, water users, wastewater treatment facilities, and storage. Water recycle/reuse is enhanced via the use of treated water. Water utilization is improved by minimizing the losses of discharged water resulting from the linkage of power plants and thermal desalination plants and the lack of integration between water production and consumption. Excess water is saved in storage systems or injected in aquifers for strategic (long-term) storage. The developed approach also accounts for the economic values of water uses and storage and for the cost of water production and allocation. An optimization formulation is developed and solved to determine the optimal operation of the infrastructure. The solution also determines the optimal monthly allocation and storage of water resources. A case study is solved for managing the water resources in the State of Qatar while accounting for desalination, distribution, and storage. The solution indicates that storage in tanks reaches its maximum capacity in less than a month while storage in aquifers continues throughout the year as a strategic step towards water security. The solution also illustrates the need to treat wastewater in addition to using desalination of seawater. The output water streams with different qualities are assigned to proper destinations.