Prediction of Chameleonic Efficiency

Chameleonic properties, i. e., the capacity of a molecule to hide polarity in non-polar environments and expose it in water, help achieving sufficient permeability and solubility for drug molecules with high MW. We present models of experimental measures of polarity for a set of 24 FDA approved drugs (MW 405-1113) and one PROTAC (MW 1034). Conformational ensembles in aqueous and non-polar environments were generated using molecular dynamics. A linear regression model that predicts chromatographic apparent polarity (EPSA) with a mean unsigned error of 10 Ų was derived based on separate terms for donor, acceptor, and total molecular SASA. A good correlation (R²=0.92) with an experimental measure of hydrogen bond donor potential, Δlog P_oct-tol, was found for the mean hydrogen bond donor SASA of the conformational ensemble scaled with Abraham's A hydrogen bond acidity. Two quantitative measures of chameleonic behaviour, the chameleonic efficiency indices, are introduced. We envision that the methods presented herein will be useful to triage designed molecules and prioritize those with the best chance of achieving acceptable permeability and solubility.     

Formation process of zirconia nanotubes and porous structures and model of oxygen bubble growth

Preparation and growth mechanism of anodization of Ti and Al has been widely concerned for two decades, but the research on anodic ZrO₂ is relatively lacking. In this paper, anodic TiO₂ and ZrO₂ nanotubes were prepared in glycerol electrolyte containing 0.35 M NH₄F and 4 vol% H₂O under different anodizing voltages. We had successfully prepared the anodic ZrO₂ nanotubes (AZNTs) with a complete top and a “bulb” at the bottom under 60 V, and with the increase of the applied anodizing voltage, the “bulb” cavity also increased. However, under the same anodizing conditions, the surface of anodic TiO₂ nanotubes (ATNTs) is a cluster of nano-tip morphology, and the bottom of the ATNTs is a conventional hemisphere shape. In addition, both AZNTs and porous anodic zirconia (PAZ) were found to coexist in the anodic ZrO₂ layer prepared at 60 V. Here, we used the oxygen bubble model and ionic current and electronic current theories to analyze the reason of the special morphology. It is confirmed that the porous anodic oxides are actually evolved from nanotubes. In other words, the structure is essentially the same.     

Influence of pulse-jet cleaning pressure on performance of compact dust collector with pleated filter operated in clean-on-time mode

To operate a bag filter continuously, pulse-jet cleaning of dust particles from the filter medium is commonly required, and the pulse-jet pressure significantly affects the filter performance. In this study, the accumulation structure of residual dust particles inside and on the surface of a filter medium at different pulse-jet pressures was investigated by constructing a simple model, and the influence of the dust structure on the filter performance was clarified. Using a simple model, we determined the effective ratio of filtration area β, which represents the ratio of the filterable area to the total filtration area, the true resistance coefficient due to the primary dust layer ζ_p’ thinly deposited on the filter surface, and the true resistance coefficient inside the filter media itself ζ_f’_. The effective ratio of filtration area β decreased with operation time for all pulse-jet pressures; however, it maintained a high value when the pulse-jet pressure was high. The validity of β analyzed by the model was verified using two different methods, and the results showed good agreement, indicating that the model is effective in identifying real conditions. The true resistance coefficient due to the primary dust layer ζ_p’ decreased as the pulse-jet pressure increased; however, the true resistance coefficient inside the filter media itself ζ_f’ was the highest at 0.5 MPa. In addition, the dust collection efficiency was different at each pulse-jet pressure, which was considered to be caused by the difference in the dust particle accumulation structure.     

Salt-assisted solution combustion synthesis of NiFe2O4: Effect of salt type

The effects of three types of salt including NaF, KCl, and NaCl on the properties of NiFe₂O₄ nanoparticles using salt-assisted solution combustion synthesis (SSCS) have been investigated. The synthesized powders were evaluated by SEM, TEM, FTIR, XRD, and VSM analysis. Also, the specific surface area (SSA), as well as size distribution and volume of the porosities of NiFe₂O₄ powders were determined by the BET apparatus. The visual observations showed that the intensity and time of combustion synthesis of nanoparticles have been severely influenced by the type of salt. The highest crystallinity was observed in the synthesized powder using NaCl. The SSA has also been correlated completely to the type of salt. The quantities of SSA was achieved about 91.62, 64.88, and 47.22 m²g^-1 for the powders synthesized by KCl, NaCl, and NaF respectively. Although the magnetic hysteresis loops showed the soft ferromagnetic behavior of the NiFe₂O₄ nanoparticles in all conditions, KCl salt could produce the particles with the least coercivity and remanent magnetization. Based on the present study, the salt type is a key parameter in the SSCS process for the preparation of spinel ferrites. Thermodynamic evaluation also showed that the melting point and heat capacity are important parameters for the proper selection of the salt.     

High-surface-area mesoporous silica-yttria-zirconia ceramic materials prepared by coprecipitation method ― the role of silicon

A high surface area is one of desired properties for yttria-zirconia (Y₂O₃–ZrO₂) ceramic materials given their catalytic applications. The objective of this study is to develop high-surface-area Y₂O₃–ZrO₂ materials by silicon (Si) modification and investigate the role of Si. Si-modified yttrium-zirconium hydroxides were prepared via a one-step precipitation process and calcined at 800 or 950 °C to form Si-modified Y₂O₃–ZrO₂ (denoted as SiO₂–Y₂O₃–ZrO₂) materials containing 0-20 wt% Si as SiO₂. These hydroxides or materials were characterized by ²⁹Si NMR, XPS, TG-DSC, XRD, UV Raman, TEM, and N₂ physisorption measurements. Si species uniformly distributed in the hydroxides tended to be enriched on the material surface at high temperatures. These Si species dominated by the silicates blocked the migration of Y and Zr atoms, which resisted the crystallite growth of Y₂O₃–ZrO₂ components and reduced their crystallite size. Therefore, the SiO₂–Y₂O₃–ZrO₂ possessed a surface area of 59-112 m²/g after calcination at 950 °C for 9 h, which was significantly higher than that of the Y₂O₃–ZrO₂ (23 m²/g). This study may stimulate ideas for developing high-surface-area crystalline ceramic materials calcined at high temperatures.     

Crowding as an Agronomic Factor Determining the Development of Plants and the Productivity of Linseed (Linum usitatissimum L.)

ABSTRACT

Nine sowing densities of linseed were compared in a two-year experiment. Self-regulation of the density of a linseed stand resulted in a differentiated branching of the plants. The number of capsules on a linseed shoot, as well as seeds in the capsule, and the number of seeds from the shoot were highly varied from year to year, and there is even a stronger differentiation in the weight of 1000 seeds. Linear relationships were noted between the mass of seeds from the linseed plant and the number of capsules. The yield of linseed was affected by both factors. An increasing sowing rate reduced the seed yield from the shoot and the plant. At lower seeding rates, the lateral shoots contributed in the seeds yield of the plant to a higher degree compared to the main ones.     

Categorical observers for metamerism

A method is proposed to generate categorical colour observer functions (individual colour matching functions) for any field size based on the CIE 2006 system of physiological observer functions. The method combines proposed categorical observer techniques of Sarkar et al with a physiologically-based individual observer model of Asano et al and a clustering technique to produce the optimal set of categorical observers. The number of required categorical observers varies depending on an application with as many as 50 required to predict individual observers' matches when a laser projector is viewed. However, 10 categorical observers are sufficient to represent colour-normal populations for personalized colour imaging. The proposed and recommended categorical observers represent a robust and inclusive technique to examine and quantify observer metamerism in any application of colorimetry.     

Classification of the cardiotocogram data for anticipation of fetal risks using machine learning techniques

The aim of the research is evaluating the classification performances of eight different machine-learning methods on the antepartum cardiotocography (CTG) data. The classification is necessary to predict newborn health, especially for the critical cases. Cardiotocography is used for assisting the obstetricians’ to obtain detailed information during the pregnancy as a technique of measuring fetal well-being, essentially in pregnant women having potential complications. The obstetricians describe CTG shortly as a continuous electronic record of the baby's heart rate took from the mother's abdomen. The acquired information is necessary to visualize unhealthiness of the embryo and gives an opportunity for early intervention prior to happening a permanent impairment to the embryo. The aim of the machine learning methods is by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals to classify as pathological or normal. The dataset contains 1831 instances with 21 attributes, examined by applying the methods. In the paper, the highest accuracy displayed as 99.2%.     

Exactly satisfying initial conditions neural network models for numerical treatment of first Painlevé equation

In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models.