Shear resistance of longitudinally stiffened panels—Part 1: Tests and numerical analysis of imperfections

This paper deals with the results of four full-scale tests, numerical simulation of tests and initial geometric imperfection analysis for longitudinally stiffened panels in shear. The tests examine the influence of varying position and bending stiffness of one trapezoidal longitudinal stiffener on the panel shear resistance and its buckling behaviour. The stiffeners were designed such as to obtain both global and local buckling shapes. Numerical simulations (FEA), based on the test girder geometry, the measured initial geometric imperfections and elastic-plastic material characteristic from the tensile tests, demonstrate a very good agreement with the tests. The initial geometric imperfection study on different verified numerical models shows a limited sensitivity of the panel shear capacity to any kind of imperfection shape variation with amplitude at the allowable fabrication tolerances. Finally, the paper offers some ideas for modelling geometric imperfections with regard to the design or research demands.     

Organic Ligands Made Porous: Magnetic and Catalytic Properties of Transition Metals Coordinated to the Surfaces of Mesoporous Organosilica

Inorganic solids with porosity on the mesoscale possess a high internal surface area and a well‐accessible pore system. Therefore, it is a relevant task to equip the surfaces of such materials with a maximum density of various organic functional groups. Among these functions it is the capability of coordinating to metal species as a ligand that is of extraordinary importance in many areas, for example, in catalysis. This paper describes how prominent ligands containing donor functions such as carboxylic, thio, chelating, or amine groups can be obtained in the form of nanoporous organosilica materials. The coordination of metal centers such as Co^II, Mn^II, V^IV, or Pt^IV is studied in detail. The magnetic properties of the corresponding materials and some applications in catalysis are reported. A quantitative determination of the surface density of donor atoms by distance measurements using EPR spectroscopy is shown.     

Stability and transformation of products formed from dimeric dehydroascorbic acid at low pH

Dehydroascorbic acid dimer (DDHA) is the commercially available form of oxidised vitamin C. When DDHA enters an aqueous environment, it will interact with water, but the details of this process are not well defined. Hydration of DDHA was analyzed as a function of concentration, pH and temperature. Above pH 5 only hydrated dehydroascorbic acid monomer (DHA) and its degradation product 2,3-diketogulonic acid (DKG) were observed. At pH lower than 4 and in MilliQ water, relatively stable hydrated dimeric species were additionally detected. They are intermediates formed from DDHA and transformed into DKG, either directly or through DHA. A lower temperature of dissolution favours the formation of hydrated dimeric products, while the concentration of DDHA has no effect on their yield. All products were separated chromatographically and analyzed by three detectors: diode array, refractive index and electrospray ionisation mass spectrometry. The stability and transformations of products were studied in the mixture and in the isolated fractions. Two initially formed monohydrated products are transformed to a dihydrated product that is degraded to DHA and DKG. Once formed, the dihydrated product and one of the monohydrated products are sufficiently stable to be identified at neutral pH. All three hydrated products are interconvertible and can be also formed after dissolution of dried DHA.     

Modeling of nonlinear coil in a ferroresonant circuit

An adjustment of the standard method of converting measured RMS characteristics of the nonlinear coil into instantaneous characteristics has been suggested. A model of the nonlinear coil, obtained in this way, is used for predicting the prechaotic bifurcation points of a ferroresonant circuit. Slight improvements over the standard method are verified by the experimental results. The cause of the disagreement between the simulation and the measurement is identified.     

Seasonal variations in the concentrations of selected heavy metals and radionuclides in Sava River sediments upstream and downstream of NPP Krsko

In order to estimate the influence of a nuclear power plant and other industrial and agricultural anthropogenic sources on the quality of Sava River sediments, samples taken from seven locations (one upstream and six downstream of the Krsko NPP) were characterized. Seasonal variations in the sediment composition were determined on the basis of four samplings taken during the year 2004 (in February, May, October and December). Total concentrations of the elements Cr, Mn, Fe, Cu, Zn, Co and Pb in the sediment fractions less than 0.5 mm have been measured by source excited energy dispersive X-ray fluorescence (EDXRF), while ⁴⁰K, ¹³⁷Cs, ¹³¹I, ⁷Be, ²²⁸Th, Th(²²⁸Ra), U(²³⁴Th), ²²⁶Ra and ²¹⁰Pb were determined by gamma spectrometry. Mineralogical examinations of the samples were performed using the X-ray diffraction (XRD) method.     

Novel insights into electrical transport mechanism in ionic‐polaronic glasses

Transformation of electrical transport from ionic to polaronic in glasses, which are a potential class of new cathode materials, has been investigated in four series containing WO₃/MoO₃ and Li⁺/Na⁺ ions, namely: xWO₃–(30?0.5x)Li₂O–(30?0.5x)ZnO–40P₂O₅, xWO₃–(30?0.5x)Na₂O–(30.5x)ZnO–40P₂O₅, xMoO₃–(30?0.5x)Li₂O–(30?0.5x)ZnO–40P₂O₅, and xMoO₃–(30?0.5x)Na₂O–(30?0.5x)ZnO–40P₂O₅, 0 ≤ x ≤ 60, (mol%). This study reports a detailed analysis of the role of structural modifications and its implications on the origin of electrical transport in these mixed ionic‐polaron glasses. Raman spectra show the clustering of WO₆ units by the formation of W–O–W bonds in glasses with high WO₃ content while the coexistence of MoO₄ and MoO₆ units is evidenced in glasses containing MoO₃ with no clustering of MoO₆ octahedra. Consequently, DC conductivity of tungstate glasses with either Li⁺ or Na⁺ exhibits a transition from ionic to polaronic showing a minimum at about 20‐30 mol% of WO₃ as a result of ion‐polaron interactions followed by a sharp increase for six orders of magnitude as WO₃ content increases. The formation of WO₆ clusters involved in W‐O‐W linkages for tungsten glasses plays a key role in significant increase in DC conductivity. On the other hand, DC conductivity is almost constant for glasses containing MoO₃ suggesting an independent ionic and polaronic transport pathways for glasses containing 10‐50 mol% of MoO₃.     

Mobile-robot pose estimation and environment mapping using an extended Kalman filter

In this paper an extended Kalman filter (EKF) is used in the simultaneous localisation and mapping (SLAM) of a four-wheeled mobile robot in an indoor environment. The robot’s pose and environment map are estimated from incremental encoders and from laser-range-finder (LRF) sensor readings. The map of the environment consists of line segments, which are estimated from the LRF’s scans. A good state convergence of the EKF is obtained using the proposed methods for the input- and output-noise covariance matrices’ estimation. The output-noise covariance matrix, consisting of the observed-line-features’ covariances, is estimated from the LRF’s measurements using the least-squares method. The experimental results from the localisation and SLAM experiments in the indoor environment show the applicability of the proposed approach. The main paper contribution is the improvement of the SLAM algorithm convergence due to the noise covariance matrices’ estimation.     

Machine learning tuning by diversity oriented firefly metaheuristics for Industry 4.0

The progress of Industrial Revolution 4.0 has been supported by recent advances in several domains, and one of the main contributors is the Internet of Things. Smart factories and healthcare have both benefited in terms of leveraged quality of service and productivity rate. However, there is always a trade-off and some of the largest concerns include security, intrusion, and failure detection, due to high dependence on the Internet of Things devices. To overcome these and other challenges, artificial intelligence, especially machine learning algorithms, are employed for fault prediction, intrusion detection, computer-aided diagnostics, and so forth. However, efficiency of machine learning models heavily depend on feature selection, predetermined values of hyper-parameters and training to deliver a desired result. This paper proposes a swarm intelligence-based approach to tune the machine learning models. A novel version of the firefly algorithm, that overcomes known deficiencies of original method by employing diversification-based mechanism, has been proposed and applied to both feature selection and hyper-parameter optimization of two machine learning models—XGBoost and extreme learning machine. The proposed approach has been tested on four real-world Industry 4.0 data sets, namely distributed transformer monitoring, elderly fall prediction, BoT-IoT, and UNSW-NB 15. Achieved results have been compared to the results of eight other cutting-edge metaheuristics, that have been implemented and tested under the same conditions. The experimental outcomes strongly indicate that the proposed approach significantly outperformed all other competitor metaheuristics in terms of convergence speed and results' quality measured with standard metrics—accuracy, precision, recall, and f1-score.     

Circulating Tumor Cells in Colorectal Cancer: Detection Systems and Clinical Utility

Colorectal cancer (CRC) is the third most common cancer worldwide. The high mortality from CRC is mainly related to metastasis affecting distant organs and their function. Dissemination of tumor cells from the primary tumor and hematogeneous spread are considered crucial in the formation of tumor metastases. The analysis of circulating tumor cells (CTCs) and CTC clusters in the blood can be used for the early detection of invasive cancer. Moreover, CTCs have a prognostic significance in the monitoring of a malignant disease or the response to chemotherapy. This work presents an overview of the research conducted on CTCs with the aim of finding suitable detection systems and assessing the possibility of clinical applications in patients with CRC.