A New Taraxastane‐Type Triterpene from Vitex trifolia var. simplicifolia

3‐Oxotaraxer‐14‐en‐30‐al ( 1 ), a new taraxastane‐type triterpene, together with 14 known compounds, taraxerone ( 2 ), 3‐epiursolic acid ( 3 ), 2α,3β‐dihydroxyurs‐12‐en‐28‐oic acid ( 4 ), lupeol ( 5 ), betulinic acid ( 6 ), casticin ( 7 ), artemetin ( 8 ), luteolin ( 9 ), 4‐hydroxybenzoic acid ( 10 ), docosanoic acid ( 11 ), tetracosanoic acid ( 12 ), cerotic acid ( 13 ), β‐sitosterol ( 14 ), and β‐daucosterol ( 15 ), was isolated from the leaves and twigs of Vitex trifolia var. simplicifolia . Compounds 2 – 6 were found for the first time in this plant. Their structures were established by spectroscopic analysis, including 2D‐NMR techniques. Cytotoxic activities of compounds 3 , and 5 – 10 were tested on the three cancer cell lines, PANC‐1, K562, and BxPC‐3. Results revealed that 7 exhibited cytotoxicity against PANC‐1, K562, and BxPC‐3, with IC₅₀ values of 4.67, 0.72, and 4.01 μg/ml, respectively, whereas 8 was inactive against these cancer cell lines. The structure? activity relationship of compound 7 and 8 indicated that the 3′‐OH group in polymethoxyflavonoids is essential for antitumor activity.     

Synthesis of New Azocompounds and Fused Pyrazolo[5,1‐c][1,2,4]triazines Using Heterocyclic Components

Diazotization of 3‐methyl‐4‐phenyl‐1H‐pyrazol‐5‐amine 1 in hydrochloric acid has been reported to afford the corresponding diazonium salt 2 . The latter underwent azocoupling with a variety of active methylene compounds (barbituric 3a and thiobarbituric 3b acid, 2‐hetarylpyrimidine‐4,6‐dione 6a , 6b , 4‐hydroxy‐6‐methylpyridin‐2(1H)‐one 10a , 4‐hydroxy‐6‐methyl‐2H‐pyran‐2‐one 10b , 4‐hydroxy‐1‐p‐tolyl‐1H‐pyrazole‐3‐carboxylic acid ethyl ester 14 , 1,3‐thiazolidine‐2,4‐dione 16a , 2‐thioxo‐1,3‐thiazolidin‐4‐one 16b ) to yield new pyrazolylazo derivatives. Fused pyrazolo[5,1‐c][1,2,4]triazines 5 , 9a , 9b , 12 , 13 were obtained by heterocyclization reactions. Copyright © 2013 HeteroCorporation     

Optimal Randomness for Stochastic Configuration Network (SCN) with Heavy-Tailed Distributions

Stochastic Configuration Network (SCN) has a powerful capability for regression and classification analysis. Traditionally, it is quite challenging to correctly determine an appropriate architecture for a neural network so that the trained model can achieve excellent performance for both learning and generalization. Compared with the known randomized learning algorithms for single hidden layer feed-forward neural networks, such as Randomized Radial Basis Function (RBF) Networks and Random Vector Functional-link (RVFL), the SCN randomly assigns the input weights and biases of the hidden nodes in a supervisory mechanism. Since the parameters in the hidden layers are randomly generated in uniform distribution, hypothetically, there is optimal randomness. Heavy-tailed distribution has shown optimal randomness in an unknown environment for finding some targets. Therefore, in this research, the authors used heavy-tailed distributions to randomly initialize weights and biases to see if the new SCN models can achieve better performance than the original SCN. Heavy-tailed distributions, such as Lévy distribution, Cauchy distribution, and Weibull distribution, have been used. Since some mixed distributions show heavy-tailed properties, the mixed Gaussian and Laplace distributions were also studied in this research work. Experimental results showed improved performance for SCN with heavy-tailed distributions. For the regression model, SCN-Lévy, SCN-Mixture, SCN-Cauchy, and SCN-Weibull used less hidden nodes to achieve similar performance with SCN. For the classification model, SCN-Mixture, SCN-Lévy, and SCN-Cauchy have higher test accuracy of 91.5%, 91.7% and 92.4%, respectively. Both are higher than the test accuracy of the original SCN.     

A Time-Symmetric Formulation of Quantum Entanglement

I numerically simulate and compare the entanglement of two quanta using the conventional formulation of quantum mechanics and a time-symmetric formulation that has no collapse postulate. The experimental predictions of the two formulations are identical, but the entanglement predictions are significantly different. The time-symmetric formulation reveals an experimentally testable discrepancy in the original quantum analysis of the Hanbury Brown–Twiss experiment, suggests solutions to some parts of the nonlocality and measurement problems, fixes known time asymmetries in the conventional formulation, and answers Bell’s question “How do you convert an ’and’ into an ’or’?”     

Spectral Properties of Effective Dynamics from Conditional Expectations

The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffusion processes, a general procedure to find effective equations is the conditioning approach. In this paper, we are interested in the spectrum of the generator of the resulting effective dynamics, and how it compares to the spectrum of the full generator. We prove a new relative error bound in terms of the eigenfunction approximation error for reversible systems. We also present numerical examples indicating that, if Kramers–Moyal (KM) type approximations are used to compute the spectrum of the reduced generator, it seems largely insensitive to the time window used for the KM estimators. We analyze the implications of these observations for systems driven by underdamped Langevin dynamics, and show how meaningful effective dynamics can be defined in this setting.     

Survival of Virus Particles in Water Droplets: Hydrophobic Forces and Landauer’s Principle

Many small biological objects, such as viruses, survive in a water environment and cannot remain active in dry air without condensation of water vapor. From a physical point of view, these objects belong to the mesoscale, where small thermal fluctuations with the characteristic kinetic energy of k_BT (where k_B is the Boltzmann’s constant and T is the absolute temperature) play a significant role. The self-assembly of viruses, including protein folding and the formation of a protein capsid and lipid bilayer membrane, is controlled by hydrophobic forces (i.e., the repulsing forces between hydrophobic particles and regions of molecules) in a water environment. Hydrophobic forces are entropic, and they are driven by a system’s tendency to attain the maximum disordered state. On the other hand, in information systems, entropic forces are responsible for erasing information, if the energy barrier between two states of a switch is on the order of k_BT, which is referred to as Landauer’s principle. We treated hydrophobic interactions responsible for the self-assembly of viruses as an information-processing mechanism. We further showed a similarity of these submicron-scale processes with the self-assembly in colloidal crystals, droplet clusters, and liquid marbles.     

Performance of Portfolios Based on the Expected Utility-Entropy Fund Rating Approach

Yang and Qiu proposed and reframed an expected utility–entropy (EU-E) based decision model. Later on, a similar numerical representation for a risky choice was axiomatically developed by Luce et al. under the condition of segregation. Recently, we established a fund rating approach based on the EU-E decision model and Morningstar ratings. In this paper, we apply the approach to US mutual funds and construct portfolios using the best rating funds. Furthermore, we evaluate the performance of the fund ratings based on the EU-E decision model against Morningstar ratings by examining the performance of the three models in portfolio selection. The conclusions show that portfolios constructed using the ratings based on the EU-E models with moderate tradeoff coefficients perform better than those constructed using Morningstar. The conclusion is robust to different rebalancing intervals.     

The Intensity of Heat Exchange between Rock and Flowing Gas in Terms of Gas-Geodynamic Phenomena

Gas-induced geodynamic phenomena can occur during underground mining operations if the porous structure of the rock is filled with gas at high pressure. In such cases, the original compact rock structure disintegrates into grains of small dimensions, which are then transported along the mine working space. Such geodynamic events, particularly outbursts of gas and rock, pose a danger both to the life of miners and to the functioning of the mine infrastructure. These incidents are rare in copper ore mining, but they have recently begun to occur, and have not yet been fully investigated. To ensure the safety of mining operations, it is necessary to determine parameters of the rock–gas system for which the energy of the gas will be smaller than the work required to disintegrate and transport the rock. Such a comparison is referred to as an energy balance and serves as a starting point for all engineering analyses. During mining operations, the equilibrium of the rock–gas system is disturbed, and the rapid destruction of the rock is initiated together with sudden decompression of the gas contained in its porous structure. The disintegrated rock is then transported along the mine working space in a stream of released gas. Estimation of the energy of the gas requires investigation of the type of thermodynamic transformation involved in the process. In this case, adiabatic transformation would mean that the gas, cooled in the course of decompression, remains at a temperature significantly lower than that of the surrounding rocks throughout the process. However, if we assume that the transformation is isothermal, then the cooled gas will heat up to the original temperature of the rock in a very short time (<1 s). Because the quantity of energy in the case of isothermal transformation is almost three times as high as in the adiabatic case, obtaining the correct energy balance for gas-induced geodynamic phenomena requires detailed analysis of this question. For this purpose, a unique experimental study was carried out to determine the time required for heat exchange in conditions of very rapid flows of gas around rock grains of different sizes. Numerical simulations reproducing the experiments were also designed. The results of the experiment and the simulation were in good agreement, indicating a very fast rate of heat exchange. Taking account of the parameters of the experiment, the thermodynamic transformation may be considered to be close to isothermal.     

Reducing Cognitive Effort in Scoring Negotiation Space Using the Fuzzy Clustering Model

Negotiation scoring systems are fundamental tools used in negotiation support to facilitate parties searching for negotiation agreement and analyzing its efficiency and fairness. Such a scoring system is obtained in prenegotiation by implementing selected multiple criteria decision-aiding methods to elicit the negotiator’s preferences precisely and ensure that the support is reliable. However, the methods classically used in the preference elicitation require much cognitive effort from the negotiators, and hence, do not prevent them from using heuristics and making simple errors that result in inaccurate scoring systems. This paper aims to develop an alternative tool that allows scoring the negotiation offers by implementing a sorting approach and the reference set of limiting profiles defined individually by the negotiators in the form of complete packages. These limiting profiles are evaluated holistically and verbally by the negotiator. Then the fuzzy decision model is built that uses the notion of increasing the preference granularity by introducing a series of limiting sub-profiles for corresponding sub-categories of offers. This process is performed automatically by the support algorithm and does not require any additional preferential information from the negotiator. A new method of generating reference fuzzy scores to allow a detailed assignment of any negotiation offer from feasible negotiation space to clusters and sub-clusters is proposed. Finally, the efficient frontier and Nash’s fair division are used to identify the recommended packages for negotiation in the bargaining phase. This new approach allows negotiators to obtain economically efficient, fair, balanced, and reciprocated agreements while minimizing information needs and effort.