Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

Formalization of Ring Theory in PVS

This paper presents a PVS development of relevant results of the theory of rings. The PVS theory includes complete proofs of the three classical isomorphism theorems for rings, and characterizations of principal, prime and maximal ideals. Algebraic concepts and properties are specified and formalized as generally as possible allowing in this manner their application to other algebraic structures. The development provides the required elements to formalize important algebraic theorems. In particular, the paper presents the formalization of the general algebraic-theoretical version of the Chinese remainder theorem (CRT) for the theory of rings, as given in abstract algebra textbooks, proved as a consequence of the first isomorphism theorem. Also, the PVS theory includes a formalization of the number-theoretical version of CRT for the structure of integers, which is the version of CRT found in formalizations. CRT for integers is obtained as a consequence of the general version of CRT for the theory of rings.

     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

Multicellular Tumor Spheroids (MCTS) as a 3D In Vitro Evaluation Tool of Nanoparticles

Multicellular tumor spheroid models (MCTS) are often coined as 3D in vitro models that can mimic the microenvironment of tissues. MCTS have gained increasing interest in the nano‐biotechnology field as they can provide easily accessible information on the performance of nanoparticles without using animal models. Considering that many countries have put restrictions on animals testing, which will only tighten in the future as seen by the recent developments in the Netherlands, 3D models will become an even more valuable tool. Here, an overview on MCTS is provided, focusing on their use in cancer research as most nanoparticles are tested in MCTS for treatment of primary tumors. Thereafter, various types of nanoparticles—from self‐assembled block copolymers to inorganic nanoparticles, are discussed. A range of physicochemical parameters including the size, shape, surface chemistry, ligands attachment, stability, and stiffness are found to influence nanoparticles in MCTS. Some of these studies are complemented by animal studies confirming that lessons from MCTS can in part predict the behaviour in vivo. In summary, MCTS are suitable models to gain additional information on nanoparticles. While not being able to replace in vivo studies, they can bridge the gap between traditional 2D in vitro studies and in vivo models.     

Microwave dielectric properties of ultra-low loss Li2MgTi0.7(Mg1/3Nb2/3)0.3O4 ceramics sintered at low temperature by LiF addition

In this work, ultra-low loss Li₂MgTi_0.7(Mg_1/3Nb_2/3)_0.3O₄ ceramics were successfully prepared via the conventional solid-state method. X-ray photoelectron spectroscopy (XPS), thermally stimulated depolarization current (TSDC) and bond energy were used to determine the distinction between intrinsic and extrinsic dielectric loss in (Mg_1/3Nb_2/3)⁴⁺ ions substituted ceramics. The addition of (Mg_1/3Nb_2/3)⁴⁺ ions enhances the bond energy in unit cell without changing the crystal structure of Li₂MgTiO₄, which results in high Q·f value as an intrinsic factor. The extrinsic factors such as porosity and grain size influence the dielectric loss at lower sintering temperature, while the oxygen vacancies play dominant role when the ceramics densified at 1400?°C. The Li₂MgTi_0.7(Mg_1/3Nb_2/3)_0.3O₄ ceramics sintered at 1400?°C can achieve an excellent combination of microwave dielectric properties: ε_r =?16.19, Q·f?=?160,000?GHz and τ_f =??3.14?ppm/°C. In addition, a certain amount of LiF can effectively lower the sintering temperature of the matrix, and the Li₂MgTi_0.7(Mg_1/3Nb_2/3)_0.3O₄-3?wt% LiF ceramics sintered at 1100?°C possess balanced properties with ε_r?=?16.32, Q·f?=?145,384?GHz and τ_f =??16.33?ppm/°C.