Acid Rock Drainage Remediation and Element Removal Using a Peat-Humic Agent with Subsequent Thermal Treatment of the Metal–Organic Residue

A novel, alternative method for acid rock drainage (ARD) remediation and metal recovery has been developed that uses a peat-humic agent (PHA) created by mechanical, chemical, and thermobaric treatment of peat from the Krugloe deposit (Novosibirsk region, Russia). The PHA effectively neutralised moderately acidic ARD and removed potential pollutants (e.g. Fe, Al, Zn, Cu, Pb, Cd, Ni, Co, and Hg), forming metal–organic residues. The organic matter can be removed completely from the metal–organic residues by heating them at 450–500 °C. After this treatment, the metal concentrate residues generally contained aggregates (20–350 μm in size), mainly composed of metal oxides and sulphates. Thermal decomposition of the organic matter in the PHA and metal–organic residues is an exothermic process with significant calorific value (9–15 kJ/g).     

Discovery of an Allosteric Ligand Binding Site in SMYD3 Lysine Methyltransferase

SMYD3 is a multifunctional epigenetic enzyme with lysine methyltransferase activity and various interaction partners. It is implicated in the pathophysiology of cancers but with an unclear mechanism. To discover tool compounds for clarifying its biochemistry and potential as a therapeutic target, a set of drug-like compounds was screened in a biosensor-based competition assay. Diperodon was identified as an allosteric ligand; its R and S enantiomers were isolated, and their affinities to SMYD3 were determined (K_D=42 and 84 μM, respectively). Co-crystallization revealed that both enantiomers bind to a previously unidentified allosteric site in the C-terminal protein binding domain, consistent with its weak inhibitory effect. No competition between diperodon and HSP90 (a known SMYD3 interaction partner) was observed although SMYD3–HSP90 binding was confirmed (K_D=13 μM). Diperodon clearly represents a novel starting point for the design of tool compounds interacting with a druggable allosteric site, suitable for the exploration of noncatalytic SMYD3 functions and therapeutics with new mechanisms of action.     

Self-assembled silver nanoislands formed on glass surface via out-diffusion for multiple usages in SERS applications

We demonstrate that silver nanoisland film self-assembled on the surface of silver-containing glass in the course of thermal processing in hydrogen is capable to detect 10⁻⁷ M concentration of rhodamine 6G in water using surface enhanced Raman spectroscopy (SERS) technique. The film can be multiply restored on the same glass substrate via annealing of the glass in hydrogen. We showed that the film can be self-assembled after as much as ten circles of the substrate cleaning followed by annealing. The proposed technique of the silver nanoisland film formation enables multiple usage of the same glass substrate in SERS experiments.     

Low-Frequency Magnetic Response in the Pseudogap Phase of Cuprate Perovskites

We calculate the magnetic susceptibility in the pseudogap phase of cuprates using the two-dimensional t-J model and the Mori projection operator technique. In this phase, the Fermi arcs lead to a quasi-elastic incommensurate magnetic response for low temperatures. The theory accounts for the reorientation of the susceptibility maxima from the axial to the diagonal direction occurring at small hole concentrations in La_2?x Sr _x CuO₄. A small cusp of the hole dispersion near the Fermi level, which is connected with the spin-polaron band, affords the growth of the maxima with decreasing frequency. As in the superconducting phase, the susceptibility maxima have an hourglass dispersion. The assumption of the phase separation into regions of superconducting and pseudogap phases in underdoped cuprates explains the lack of the superconducting gap in their susceptibility. The observed rapid change of widths of the susceptibility maxima with frequency is related to the contribution of the pseudogap phase. This contribution may also explain the strengthening of the quasi-elastic response by modest magnetic fields and by small impurity concentrations.     

Assessment of utility energy storage options for increased renewable energy penetration

Renewable energy technologies are expected to take the leading role in the forthcoming energy generation portfolio in order to achieve sustainable energy generation. The major constraints for increasing penetration of renewable energy sources is their availability and intermittency, which can be addressed through energy storage when available and energy use when needed. This work reviews the energy storage technologies and gives an up to date comparative summary of the performance parameters of the major energy storage options. The parameters compared here include efficiency, energy capacity, energy density, run time, capital investment costs, response time, lifetime in years and cycles, self discharge and maturity of each energy storage option. The choice of storage system will depend on individual requirements, and may even incorporate more than one energy storage system to increase the energy storage capacity and improve energy security.     

Universal probability-free prediction

We construct universal prediction systems in the spirit of Popper’s falsifiability and Kolmogorov complexity and randomness. These prediction systems do not depend on any statistical assumptions (but under the IID assumption they dominate, to within the usual accuracy, conformal prediction). Our constructions give rise to a theory of algorithmic complexity and randomness of time containing analogues of several notions and results of the classical theory of Kolmogorov complexity and randomness.     

Particle Swarm Optimization and Pure Adaptive Search in Finish Goods’ Inventory Management

Abstract

Inventory management deals with a tradeoff between the benefits of keeping stocks of goods that allows fulfillment of the customer’s demand, and the cost of carrying inventory. Inventory control techniques are very important components and the most organizations can substantially reduce their costs associated with the flow of materials. This paper presents new inventory management model based on particle swarm optimization and pure adaptive search global optimization algorithm in production-inventory system. The proposed model is focusing on planned level of demand for finished goods, production and raw materials cost, production capacity as the norm, change of the production cost and inventory capital cost, all of which are typical factors in automobile manufacture industry. The model determines different factors such as the minimizing inventory quantity, minimizing inventory value, and minimizing production cost based on demand for production items. The model is tested with original real-world dataset obtained from the automotive company Lear from US and its factory in Novi Sad, Serbia.     

Monodisperse Metal Nanoparticle Catalysts: Synthesis, Characterizations, and Molecular Studies Under Reaction Conditions

We aim to develop novel catalysts that exhibit high activity, selectivity and stability under real catalytic conditions. In the recent decades, the fast development of nanoscience and nanotechnology has allowed synthesis of nanoparticles with well-defined size, shape and composition using colloidal methods. Utilization of mesoporous oxide supports effectively prevents the nanoparticles from aggregating at high temperatures and high pressures. Nanoparticles of less than 2?nm sizes were found to show unique activity and selectivity during reactions, which was due to the special surface electronic structure and atomic arrangements that are present at small particle surfaces. While oxide support materials are employed to stabilize metal nanoparticles under working conditions, the supports are also known to strongly interact with the metals through encapsulation, adsorbate spillover, and charge transfer. These factors change the catalytic performance of the metal catalysts as well as the conductivity of oxides. The employment of new in situ techniques, mainly high-pressure scanning tunneling microscopy (HPSTM) and ambient-pressure X-ray photoelectron spectroscopy (APXPS) allows the determination of the surface structure and chemical states under reaction conditions. HPSTM has identified the importance of both adsorbate mobility to catalytic turnovers and the metal substrate reconstruction driven by gaseous reactants such as CO and O₂. APXPS is able to monitor both reacting species at catalyst surfaces and the oxidation state of the catalyst while it is being exposed to gases. The surface composition of bimetallic nanoparticles depends on whether the catalysts are under oxidizing or reducing conditions, which is further correlated with the catalysis by the bimetallic catalytic systems. The product selectivity in multipath reactions correlates with the size and shape of monodisperse metal nanoparticle catalysts in structure sensitive reactions.