New design equations for assessment of load carrying capacity of castellated steel beams: a machine learning approach

This paper presents an innovative machine learning approach for the formulation of load carrying capacity of castellated steel beams (CSB). New design equations were developed to predict the load carrying capacity of CSB using linear genetic programming (LGP), and an integrated search algorithm of genetic programming and simulated annealing, called GSA. The load capacity was formulated in terms of the geometrical and mechanical properties of the castellated beams. An extensive trial study was carried out to select the most relevant input variables for the LGP and GSA models. A comprehensive database was gathered from the literature to develop the models. The generalization capabilities of the models were verified via several criteria. The sensitivity of the failure load of CSB to the influencing variables was examined and discussed. The employed machine learning systems were found to be effective methods for evaluating the failure load of CSB. The prediction performance of the optimal LGP model was found to be better than that of the GSA model.     

Interactions between serotypes of dengue highlight epidemiological impact of cross-immunity

Dengue, a mosquito-borne virus of humans, infects over 50 million people annually. Infection with any of the four dengue serotypes induces protective immunity to that serotype, but does not confer long-term protection against infection by other serotypes. The immunological interactions between serotypes are of central importance in understanding epidemiological dynamics and anticipating the impact of dengue vaccines. We analysed a 38-year time series with 12 197 serotyped dengue infections from a hospital in Bangkok, Thailand. Using novel mechanistic models to represent different hypothesized immune interactions between serotypes, we found strong evidence that infection with dengue provides substantial short-term cross-protection against other serotypes (approx. 1–3 years). This is the first quantitative evidence that short-term cross-protection exists since human experimental infection studies performed in the 1950s. These findings will impact strategies for designing dengue vaccine studies, future multi-strain modelling efforts, and our understanding of evolutionary pressures in multi-strain disease systems.     

Effect of filler material on local and global behaviour of buckling‐restrained braces

The nonlinear response of buildings has attracted a tremendous amount of attention in recent years. Braces, as lateral force‐resisting elements of a structure, are designed to not only react in the elastic region, but also to exhibit nonlinear response beyond the elastic limit. However, buckling in compression drastically degrades the performance of braces under earthquake loading. Buckling restrained braces (BRBs) have been evolved into very effective systems for severe seismic applications. They prevent buckling in compression through the encasing of core steel into a steel tube and confining infill concrete. The effect of infill material is investigated in this research through the use of experimental tests. Filler material may be concrete, grout or mortar, as well as granular material such as compacted aggregate. Moreover, lightweight concrete or lean concrete may be utilized as filler to reduce the overall structural weight. Furthermore, the need for unbonding material may not arise when sand and gravel mixture is used. Nevertheless, the strength of the aggregate should be such that no buckling or strength deterioration is observed. Parametric studies on BRB characteristics are carried out in this research. Results of cyclic loading tests are then provided for individual cases to characterize the effect of response parameters of BRB assemblages. Copyright © 2009 John Wiley & Sons, Ltd.     

Probabilistic models for robot-based object segmentation

This paper introduces a novel probabilistic method for robot based object segmentation. The method integrates knowledge of the robot’s motion to determine the shape and location of objects. This allows a robot with no prior knowledge of its workspace to isolate objects against their surroundings by moving them and observing their visual feedback. The main contribution of the paper is to improve upon current methods by allowing object segmentation in changing environments and moving backgrounds. The approach allows optimal values for the algorithm parameters to be estimated. Empirical studies against alternatives demonstrate clear improvements in both planar and three dimensional motion.     

Genetic-based modeling of uplift capacity of suction caissons

In this study, classical tree-based genetic programming (TGP) and its recent variants, namely linear genetic programming (LGP) and gene expression programming (GEP) are utilized to develop new prediction equations for the uplift capacity of suction caissons. The uplift capacity is formulated in terms of several inflecting variables. An experimental database obtained from the literature is employed to develop the models. Further, a conventional statistical analysis is performed to benchmark the proposed models. Sensitivity and parametric analyses are conducted to verify the results. TGP, LGP and GEP are found to be effective methods for evaluating the horizontal, vertical and inclined uplift capacity of suction caissons. The TGP, LGP and GEP models reach a prediction performance better than or comparable with the models found in the literature.     

Does Capacity Utilization Predict Inflation? A Wavelet Based Evidence from United States

Computational Economics - This paper aims to test a causal nexus between capacity utilization and inflation in the United States for the period from January 1969 to June 2017. Given the...     

Immunological heterogeneity informs estimation of the durability of vaccine protection

Deciphering the properties of vaccines against an emerging pathogen is essential for optimizing immunization strategies. Early after vaccine roll-out, however, uncertainties about vaccine immunity raise the question of how much time is needed to estimate these properties, particularly the durability of vaccine protection. Here we designed a simulation study, based on a generic transmission model of vaccination, to simulate the impact of a breadth of vaccines with different mean (range: 10 months–2 years) and variability (coefficient of variation range: 50–100%) of the duration of protection. Focusing on the dynamics of SARS-CoV-2 in the year after start of mass immunization in Germany as a case study, we then assessed how confidently the duration of protection could be estimated under a range of epidemiological scenarios. We found that lower mean and higher heterogeneity facilitated estimation of the duration of vaccine protection. Across the vaccines tested, rapid waning and high heterogeneity permitted complete identification of the duration of protection; by contrast, slow waning and low heterogeneity allowed only estimation of the fraction of vaccinees with rapid loss of immunity. These findings suggest that limited epidemiological data can inform the duration of vaccine immunity. More generally, they highlight the need to carefully consider immunological heterogeneity when designing transmission models to evaluate vaccines.     

Enhancement of piezoelectric vibration energy harvesting with auxetic boosters

This paper proposes a new concept to enhance the efficiency of the vibration energy harvesting via an intermediate booster. The boosters have auxetic structures and exert extra stretching strain in two perpendicular directions. The concept is tested on a conventional cantilever beam under the base excitation. The problem consists of a cantilever beam subjected to a body load at low frequencies. An auxetic substrate is bonded to the beam with a thin epoxy layer, and the piezoelectric (PZT) element is attached on top of it. Two different auxetic structures are investigated in this study. It is shown that employing these kinds of boosters can remarkably enhance the performance of the energy harvesting system. The harvesting efficiency is numerically evaluated in different load amplitudes and frequencies. A parametric study is then carried out, and effects of different geometrical design parameters of the auxetic boosters on the performance of the energy harvesting system are investigated. Comparing with the case in which the PZT is straightly attached to the cantilever, it is shown that adding such intermediate boosters at low-frequency range can increase the extracted power by factors of 3.9 and 7.0 for the two proposed geometries.     

Compact Chip-Resistor Loaded Active Integrated Patch Antenna for ISM Band Applications

As technology is moving towards miniature structures, demand for designing efficient compact antennas is increasing simultaneously. So it would be valuable to improve the features of small antennas, such as bandwidth and gain. A compact chip-resistor loaded microstrip antenna at 2.48 GHz frequency for industrial scientific and medical (ISM) band, with dimensions of 10 × 10 mm² is presented in this paper. With a novel geometry design, antenna is promoted to an active integrated antenna (AIA) on a two-layer printed circuit board (PCB), which contains passive antenna and active circuitry with a common ground plane. A monolithic amplifier is used to have an improvement around 10 dB in antenna gain. The impedance bandwidth has been increased during chip-resistor loading and adding active circuitry processes. For chip-resistor loaded antenna, that is 5.7 and 9.48% in simulation and measurement respectively. Moreover, the active integrated antenna has the measured impedance bandwidth of 58.7%. Since the low gain and narrow bandwidth of compact microstrip antennas might be a challenge for their operation, by compensating these drawbacks, proposed antenna would become more practical for special medical diagnostic applications, where doctors need stronger signals for monitoring.

     

Dynamic flexibility metrics for capability and capacity

In production environments, such as Flexible Manufacturing Systems (FMSs), the schedule can be disturbed by the occurrence of unplanned events. Machines stop for major failures, maintenance, tool changes due to wear, or tool reassignments. The rescheduling process, however, can be costly. In this study, a dynamic measure of flexibility which helps to determine an appropriate time for rescheduling an FMS has been defined and investigated. Flexibility is defined as a function of Capability and Capacity. Accordingly, two metrics have been developed to monitor the capability and capacity efficiency of each machine in the system for responding to the dynamic system status. The value of each metric falls between 0 and 1 at all times. Higher values in the capability metric mean better machine selection and part distribution strategies among the machines. Higher values for the capacity metric mean higher machine utilization in the production plan. Based on the interaction between the metrics and their respective behavior in the system, four states have been identified and characterized. Simulations of various scenarios can be used to demonstrate the use of these metrics for monitoring FMS operations and determining appropriate times for rescheduling and tool reassignment.