A fracture model of reinforced concrete

Analyzed in this work is the failure mechanism of unidirectionally reinforced concrete under general stress state. The fracture process is described analytically by establishing the relation between loading and damage that involves the constitutive parameters of the reinforced concrete. Taken into account are the stiffnesses of mortar and reinforcement, bond strength of interface and mortar fracture toughness. An estimate on the ultimate strength is made with results given to the shear strength of a concrete slab.     

Electrospray-assisted laser desorption/ionization and tandem mass spectrometry of peptides and proteins

We have constructed an electrospray-assisted laser desorption/ionization (ELDI) source which utilizes a nitrogen laser pulse to desorb intact molecules from matrix-containing sample solution droplets, followed by electrospray ionization (ESI) post-ionization. The ELDI source is coupled to a quadrupole ion trap mass spectrometer and allows sampling under ambient conditions. Preliminary data showed that ELDI produces ESI-like multiply charged peptides and proteins up to 29 kDa carbonic anhydrase and 66 kDa bovine albumin from single-protein solutions, as well as from complex digest mixtures. The generated multiply charged polypeptides enable efficient tandem mass spectrometric (MS/MS)-based peptide sequencing. ELDI-MS/MS of protein digests and small intact proteins was performed both by collisionally activated dissociation (CAD) and by nozzle-skimmer dissociation (NSD). ELDI-MS/MS may be a useful tool for protein sequencing analysis and top-down proteomics study, and may complement matrix-assisted laser desorption/ionization (MALDI)-based measurements.     

Nanostructured MoS2 Nanorose/Graphene Nanoplatelet Hybrids for Electrocatalysis

Tailoring and enhancing electrocatalytic activity is of the utmost importance from the viewpoints of sustainable energy and sensing. MoS₂ and graphene show great promise for the electrocatalysis of many reactions. Given that both graphene and MoS₂ are highly anisotropic in nature, with edge planes that are several orders of magnitude more catalytically active than basal planes, a new hybrid material with maximized edge‐plane density to provide efficient electron transfer, high catalytic activity, and conductive cores was engineered. The hybrid material consists of radial MoS₂ nanosheets with a high density of edge planes and unsaturated active sulfur atoms as well as interspersed with conductive graphene nanoplatelets. This hybrid material exhibits excellent activity for the hydrogen evolution reaction and the detection of DNA nucleobases. Such a nanoengineered, nanostructured hybrid material may play a major role in future electrocatalytic devices.     

Multi-objective simulation-based evolutionary algorithm for an aircraft spare parts allocation problem

Simulation optimization has received considerable attention from both simulation researchers and practitioners. In this study, we develop a solution framework which integrates multi-objective evolutionary algorithm (MOEA) with multi-objective computing budget allocation (MOCBA) method for the multi-objective simulation optimization problem. We apply it on a multi-objective aircraft spare parts allocation problem to find a set of non-dominated solutions. The problem has three features: huge search space, multi-objective, and high variability. To address these difficulties, the solution framework employs simulation to estimate the performance, MOEA to search for the more promising designs, and MOCBA algorithm to identify the non-dominated designs and efficiently allocate the simulation budget. Some computational experiments are carried out to test the effectiveness and performance of the proposed solution framework.     

Texture analysis of bone marrow in knee MRI for classification of subjects with bone marrow lesion — Data from the Osteoarthritis Initiative

Visualization of bone marrow lesion (BML) can improve the diagnosis of many bone disorders that are associated with it. A quantitative approach in detecting BML could increase the accuracy and efficiency of diagnosing those bone disorders. In this paper, we investigated the feasibility of using magnetic resonance imaging (MRI)-based texture to (a) identify slices and (b) classify subjects with and without BML. A total of 58 subjects were studied; 29 of them were affected by BML. The ages of subjects ranged from 45 to 74 years with a mean age of 59. Texture parameters were calculated for the weight-bearing region of distal femur. The parameters were then analyzed using Mann–Whitney U test and individual feature selection methods to identify potentially discriminantive parameters. Forward feature selection was applied to select features subset for classification. Classification results from eight classifiers were studied. Results show that 98 of the 147 parameters studied are statistically significantly different between the normal and affected marrows: parameters based on co-occurrence matrix are ranked highest in their separability. The classification of subjects achieved an area under the receiver operating characteristic curve (AUC) of 0.914, and the classification of slices achieved an AUC of 0.780. The results show that MRI-texture-based classification can effectively classify subjects/slices with and without BML.