bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Iodine Doping on Electrical Characteristics of Solution-Processed Copper Oxide Thin-Film Transistors
Authors: Lee Hyeonju , Zhang Xue , Kim Bokyung , Bae Jin-Hyuk , Park Jaehoon
Published: October 2021

In order to implement oxide semiconductor-based complementary circuits, the improvement of the electrical properties of p-type oxide semiconductors and the performance of p-type oxide TFTs is certainly required. In this study, we report the effects of iodine doping on the structural and electrical characteristics of copper oxide (CuO) semiconductor films and the TFT performance. The CuO semiconductor films were fabricated using copper(II) acetate hydrate as a precursor to solution processing, and iodine doping was performed using vapor sublimated from solid iodine. Doped iodine penetrated the CuO film through grain boundaries, thereby inducing tensile stress in the film and increasing the film’s thickness. Iodine doping contributed to the improvement of the electrical properties of the solution-processed CuO semiconductor including increases in Hall mobility and hole-carrier concentration and a decrease in electrical resistivity. The CuO TFTs exhibited a conduction channel formation by holes, that is, p-type operation characteristics, and the TFT performance improved after iodine doping. Iodine doping was also found to be effective in reducing the counterclockwise hysteresis in the transfer characteristics of CuO TFTs. These results are explained by physicochemical reactions in which iodine replaces oxygen vacancies and oxygen atoms through the formation of iodide anions in CuO.
The Effect of Carbon Nanotubes on the Strength of Sand Seeped by Colloidal Silica in Triaxial Testing
Authors: Jin Weifeng , Tao Ying , Wang Xin , Gao Zheng
Published: October 2021

Colloidal silica can quickly seep through sand and then form silica gels to cement sand particles. To improve the strength of sand seeped by colloidal silica, carbon nanotubes were dispersed in the colloidal silica to form carbon-nanotube-reinforced sand-gel composites. Then triaxial tests were performed to explore how carbon nanotube content affects shear strength. The test results showed that: (1) with the increase of colloidal silica concentration, the shear strength significantly increased with the same carbon nanotube content (especially the low concentration of 10 wt. % colloidal silica, which showed almost no reinforcing effect with carbon nanotubes) while 40 wt. % colloidal silica plus 0.01 wt. % carbon nanotube caused the maximum increase of shear strength by up to 93.65%; (2) there was a concentration threshold of colloidal silica, above which the shear strength first increased to the peak value and then decreased with increasing carbon nanotube content (and we also established a formula to predict such phenomenon); and (3) SEM images showed that carbon nanotubes were connected as several ropes in the micro-cracks of the silica gel, resulting in greater macroscopic shear strength. Our new method of mixing carbon nanotubes and colloidal silica to seep through sand can contribute to sandy ground improvement.
Electrodeposition of Pb and PbO2 on Graphite Felt in Membraneless Flow-Through Reactor: A Method to Prepare Lightweight Electrode Grids for Lead-Acid Batteries
Authors: Ilginis Arminas , Žmuidzinavičienė Nerita , Griškonis Egidijus
Published: October 2021

One of the possible ways of mitigating the primary lead-acid battery downside—mass— is to replace the heavy lead grids that can add up to half of the total electrode’s mass. The grids can be exchanged for a lightweight, chemically inert, and conductive material such as graphite felt. To reduce carbon surface area, Pb/PbO2 can be electrochemically deposited on graphite felt. A flow-through reactor was applied to enhance penetration of adequate coverage of graphite felt fibers. Three types of electrolytes (acetate, nitrate, and methanesulfonate) and two additives (ligninsulfonate and Triton X-100) were tested. The prepared composite electrodes showed greater mechanical strength, up to 5 times lower electrical resistivity, and acted as Pb and PbO2 electrodes in sulfuric acid electrolytes.
Effect of Excess Atomic Volume on Crack Evolution in a Deformed Iron Single Crystal
Authors: Kryzhevich Dmitrij S. , Korchuganov Aleksandr V. , Zolnikov Konstantin P.
Published: October 2021

This paper presents a molecular dynamics study of how the localization and transfer of excess atomic volume by structural defects affects the evolution and self-healing of nanosized cracks in bcc iron single crystals under different mechanical loading conditions at room temperature. It is shown that deformation is initially accompanied by a local growth of the atomic volume at the crack tips. The crack growth behavior depends on whether the excess atomic volume can be transferred by structural defects from the crack tips to the free surface or other interfaces. If an edge crack is oriented with respect to the loading direction so that dislocations are not emitted from its tip or only twins are emitted, then the sample undergoes a brittle-ductile fracture. The transfer of the excess atomic volume by dislocations from the crack tips prevents the opening of edge cracks and is an effective healing mechanism for nanocracks in a mechanically loaded material.
Preliminary Study of the Influence of Supplementary Cementitious Materials on the Application of Electro Remediation Processes
Authors: Martinez Isabel , Castellote Marta
Published: October 2021

Supplementary cementitious materials (SCMs), based on pozzolanic materials, improve durability against corrosion and mechanical properties of concrete structures by decreasing their permeability. Even though the influence of SCMs on the chloride combination with the cement phases has been widely studied, its effects on electrokinetic remediation processes such as electrochemical chloride extraction (ECE) have not been clarified. For this reason, the influences of two SCMs, fly ash (FA) and blast-furnace slag, on the extraction of chloride through the concrete net pore have been studied in this paper to determine the viability of the application of electrochemical chloride treatments in these structural materials. Alternative electrochemical indicators to the ones included in the standards are also proposed to better determine the final point of the treatment. A cement replacement of 8% on both SCM (FA and slag) has been tested, and in addition to charge density, chloride content, and corrosion measurement at the end of the treatment (included in the standards), different electrical and electrochemical indicators such as electrical resistivity, EIS, or depolarized potentials are used to monitor the ECE. The influence of the treatment on disconnected steel has been also studied. In the case of slag mortar, no steel passivation was reached, while in the case of FA, the passivation of the steels connected to treatment was reached in the same way as in plain CEM I specimens. A degree of protection is also detected in the nonconnected steel, which means that substitution of 8% in FA does not affect treatment efficiency and can also partially protect the metallic elements embedded in the same electrolyte but not connected to the treatment.
Dehydrated at Different Conditions and Powdered Leek as a Concentrate of Biologically Active Substances: Antioxidant Activity and Phenolic Compound Profile
Authors: Biernacka Beata , Dziki Dariusz , Kozłowska Joanna , Kowalska Iwona , Soluch Agata
Published: October 2021

This study aimed to analyze the antioxidant activity, phenolic acid profile, color changes, and chemical composition of dried and powdered leek (Allium porrum). Leek was divided into white shaft (WH) and green shaft (GR) and subjected to drying by different methods—convection drying, vacuum drying, and freeze-drying (FD)—at a temperature of 60 °C. A sample freeze-dried at a temperature of 20 °C was used as control. Analyses of the dried leek samples revealed that GR contained a higher amount of ash, protein, fat, fiber, phenolic acids, and flavonoids, and exhibited higher antioxidant capacity compared to WH. The dominant phenolic acid in WH was p-cumaric acid followed by synapic and protocatechuic acids. GR had a several-fold higher content of phenolic acids than WH, with ferulic acid being dominant (about 85% of the total phenolic content). It was also observed that a higher drying temperature resulted in the degradation of phenolic compounds and reduced the antioxidant properties of leek shafts. Most importantly, FD under a temperature of 60 °C caused a similar degree of degradation of biologically active compounds as air drying. An increase in drying temperature was associated with a slight decrease in the lightness of GR, whereas in the case of WH no significant change in this parameter was observed.
Electrochemical Corrosion Behaviour of Different Grades of WC-Co, High-Cr White Cast Irons and Hadfield Steel in 1 M Sulphuric Acid
Authors: Potgieter Johannes H. , Whitefield David , Motsumi Vivian
Published: October 2021

Electrochemical polarisation tests were carried out on three grades of WC-Co cemented carbides to investigate the corrosive behaviour of the hardmetals and rank them as viable protective liners for chutes and skips in the mining industry. The cobalt binder content and WC particle size varied. The binder content ranged from 6–12 wt%, and the grain size of the WC particles ranged from 0.4–2.3 µm. The performance of the WC-Co hardmetal was compared to three different grades of high chromium white cast irons and Hadfield steel. The cast irons varied in both their chromium content and the morphology of the Cr-rich primary carbides. Potentiodynamic polarisation and linear polarization resistance scans were used to determine the corrosion current density and other electrochemical parameters. The microstructural characteristics of the samples were analysed using Scanning Electron Microscope(SEM) with Energy Dispersive Spectroscopy (EDS), and optical microscopy. The potentiodynamic scans revealed that, although the WC-Co alloys were found to have generally improved corrosion resistance, it was the high-Cr white cast iron (22 wt% Cr) that recorded the lowest corrosion current density and therefore displayed the best resistance against corrosive attack in 1 M H2SO4. The Hadfield steel exhibited the poorest resistance to corrosion and therefore, suffered the most degradation to its exposed surface.
Enhanced Defluoridation of Water Using Zirconium—Coated Pumice in Fixed-Bed Adsorption Columns
Authors: Geleta Wondwosen Sime , Alemayehu Esayas , Lennartz Bernd
Published: October 2021

Millions of people across the globe suffer from health issues related to high fluoride levels in drinking water. The purpose of this study was to test modified pumice as an adsorbent for the purification of fluoride-containing waters. The adsorption of fluoride onto zirconium-coated pumice (Zr–Pu) adsorbent was examined in fixed-bed adsorption columns. The coating of zirconium on the surface of VPum was revealed by X-ray diffractometer (XRD), Inductively coupled plasma-optical emission spectroscopy (ICP-EOS), and X-ray fluorescence (XRF) techniques. The degree of surface modification with the enhanced porosity of Zr–Pu was evident from the recorded scanning electron microscope (SEM) micrographs. The Brunauer-Emmett-Teller (BET) analysis confirmed the enhancement of the specific surface area of VPum after modification. The Fourier transform infrared (FTIR) examinations of VPum and Zr–Pu before and after adsorption did not reveal any significant spectrum changes. The pH drift method showed that VPum and Zr–Pu have positive charges at pHPZC lower than 7.3 and 6.5, respectively. Zr–Pu yielded a higher adsorption capacity of 225 mg/kg (2.05 times the adsorption capacity of VPum: 110 mg/kg), at pH = 2 and volumetric flow rate (QO) of 1.25 mL/min. Breakthrough time increases with decreasing pH and flow rate. The experimental adsorption data was well-matched by the Thomas and Adams-Bohart models with correlation coefficients (R2) of ≥ 0.980 (Zr–Pu) and ≥ 0.897 (VPum), confirming that both models are suitable tools to design fixed-bed column systems using volcanic rock materials. Overall, coating pumice with zirconium improved the defluoridation capacity of pumice; hence, a Zr–Pu-packed fixed-bed can be applied for defluoridation of excess fluoride from groundwater. However, additional investigations on, for instance, the influences of competing ions are advisable to draw explicit conclusions.
Cutting Forces during Inconel 718 Orthogonal Turn-Milling
Authors: Felusiak-Czyryca Agata , Madajewski Marek , Twardowski Paweł , Wiciak-Pikuła Martyna
Published: October 2021

Inconel 718 is a material often used in the aerospace and marine industries due to its properties and ability to work in harsh environments. However, its machining is difficult, and therefore methods are sought to facilitate this process. One of such methods is turn-milling. This paper presents the forces during orthogonal turn-milling of the Inconel 718 alloy. In this machining, both the side and the end edge are involved in the material removal, which causes the tool to be more loaded. The forces during turn-milling can be up to 50% higher than in the case of milling, which causes damage to the tool. Tool wear during machining has a significant impact on the values of the cutting force proportional coefficients. In the case of the tested material, it is important to take it into account when creating cutting force models.
Abrasive Wear of High-Carbon Low-Alloyed Austenite Steel: Microhardness, Microstructure and X-ray Characteristics of Worn Surface
Authors: Brykov Michail Nikolaevich , Akrytova Taisiia Oleksandrivna , Osipov Michail Jurievich , Petryshynets Ivan , Puchy Viktor , Efremenko Vasily Georgievich , Shimizu Kazumichi , Kunert Maik , Hesse Olaf
Published: October 2021

A high-carbon, high-silicon steel (1.21 wt% C, 2.56 wt% Mn, 1.59 wt% Si) was subjected to quenching from 900 and 1000 °C, resulting in microstructures containing 60 and 94% of retained austenite, respectively. Subsequent abrasive wear tests of quenched samples were performed using two-body abrasion and three-body abrasion testing machines. Investigations on worn surface and subsurface were carried out using SEM, XRD, and microhardness measurement. It was found that the highest microhardness of worn surface (about 1400 HV0.05) was achieved on samples quenched from 900 °C after three-body abrasion. Microhardness of samples after two-body abrasion was noticeably smaller. with a maximum of about 1200 HV0.05. This difference correlates with microstructure investigations along with XRD results. Three-body abrasion has produced a significantly deeper deformed layer; corresponding diffractograms show bigger values of the full width at half maximum parameter (FWHM) for both α and γ alone standing peaks. The obtained results are discussed in the light of possible differences in abrasive wear conditions and differing stability of retained austenite after quenching from different temperatures. It is shown that a structure of metastable austenite may be used as a detector for wear conditions, as the sensitivity of such austenite to phase transformation strongly depends on wear conditions, and even small changes in the latter lead to significant differences in the properties of the worn surface.
Kinematic Analysis and Parameter Measurement for Multi-Axis Laser Engraving Machine Tools
Authors: Yin Zhenshuo , Liu Qiang , Sun Pengpeng , Ding Ji
Published: October 2021

Multi-axis Laser Engraving Machine Tools (LEMT) are widely used in precision processing of parts with complex surface. The accuracy of kinematic model and parameter measurement are the key factors determining the processing quality of LEMT. In this paper, a kinematic model of multi-axis LEMT was established based on Homogeneous Transformation Matrix (HTM). Two types of unknown parameters, linkage parameters and positioning parameters, were measured in the presented model. Taking advantage of the characteristics of laser processing, this paper proposed a rapid measurement method of linkage parameters by combining the machine tool motion with the laser marking action. For positioning parameters, this study proposed a non-contact measurement method based on structured light scanner, which can obtain the translation values and the rotation values from the Workpiece Coordinate System (WCS) to the Basic Coordinate System (BCS) simultaneously. After the measurement of two kinds of parameters of a multi-axis LEMT was completed, the processing of a spatial curve was performed and the average contour error was controlled at 15.1 μm, which is sufficient to meet the project requirements.
Bearing Remaining Useful Life Prediction Based on a Scaled Health Indicator and a LSTM Model with Attention Mechanism
Authors: Gao Songhao , Xiong Xin , Zhou Yanfei , Zhang Jiashuo
Published: October 2021

Rotor systems are of considerable importance in most modern industrial machinery, and the evaluation of the working conditions and longevity of their core component—the rolling bearing—has gained considerable research interest. In this study, a scale-normalized bearing health indicator based on the improved phase space warping (PSW) and hidden Markov model regression was established. This indicator was then used as the input for the encoder–decoder LSTM neural network with an attention mechanism to predict the rolling bearing RUL. Experiments show that compared with traditional health indicators such as kurtosis and root mean square (RMS), this scale-normalized bearing health indicator directly indicates the actual damage degree of the bearing, thereby enabling the LSTM model to predict RUL of the bearing more accurately.
Spectral Properties of Clipping Noise
Authors: Frömming Alexander , Häring Lars , Czylwik Andreas
Published: October 2021

One serious disadvantage of any multicarrier-modulation technique such as orthogonal frequency division multiplexing (OFDM) is its high peak-to-average-power ratio (PAPR) which might lead to signal clipping in several scenarios. To maximize the transmit data rate, it is important to take this non-linear distortion into account. The most common approach is based on the Bussgang theorem, which splits the distortion in a correlated part, represented by a linear damping factor, and uncorrelated additive noise. However, there are two aspects that are not correctly considered by the Bussgang theorem. Firstly, clipping noise shows a frequency-dependent power spectrum which depends on the clipping probability. Secondly, some of the clipping noise power is located outside of the transmission bandwidth, so that it does not influence the transmission quality. In this work, the Bussgang theorem is reviewed in detail and the exact power spectral density of the uncorrelated clipping noise is approximated to determine the signal-to-noise power ratio on every subcarrier separately. Although it is shown that the frequency dependence within the transmission bandwidth is relatively small, at least 36% of the uncorrelated noise power, depending on the clipping level, lays outside of the transmission band. Monte Carlo simulations validate that a simple expression for the power spectral density allows to calculate the symbol error probability of an OFDM transmission system that suffers from clipping. Furthermore, the newly found result can be used to optimize bit allocation tables in bit loading algorithms or to calculate the channel capacity.
Analysis of First-Year University Student Dropout through Machine Learning Models: A Comparison between Universities
Authors: Opazo Diego , Moreno Sebastián , Álvarez-Miranda Eduardo , Pereira Jordi
Published: October 2021

Student dropout, defined as the abandonment of a high education program before obtaining the degree without reincorporation, is a problem that affects every higher education institution in the world. This study uses machine learning models over two Chilean universities to predict first-year engineering student dropout over enrolled students, and to analyze the variables that affect the probability of dropout. The results show that instead of combining the datasets into a single dataset, it is better to apply a model per university. Moreover, among the eight machine learning models tested over the datasets, gradient-boosting decision trees reports the best model. Further analyses of the interpretative models show that a higher score in almost any entrance university test decreases the probability of dropout, the most important variable being the mathematical test. One exception is the language test, where a higher score increases the probability of dropout.
One Laptop per Child? Using Production Frontiers for Evaluating the Escuela2.0 Program in Spain
Authors: Feliciano Daniel , López-Torres Laura , Santín Daniel
Published: October 2021

Over the last few decades, public programs have driven the gradual adoption of information and communication technologies (ICTs) in education. The most ambitious project in Spain so far was Escuela 2.0, which provided students from the regions that opted into the program with laptops. The objective of this paper is to evaluate the impact of this program on school performance and productivity. To do this, we developed a new methodological approach based on combining causal inference techniques and the analysis of production frontiers. We calculated the differences in productivity and performance between treated and control schools using the base-group Camanho–Dyson Malmquist index and the base-group performance gap index. We estimate the impact of the program as the variation of these differences, following the essence of the difference-in-differences analysis. The main results are that Escuela 2.0 had a negative impact on performance and productivity.
Applications of the Fractional Calculus in Fuzzy Differential Subordinations and Superordinations
Authors: Lupaş Alina Alb
Published: October 2021

The fractional integral of confluent hypergeometric function is used in this paper for obtaining new applications using concepts from the theory of fuzzy differential subordination and superordination. The aim of the paper is to present new fuzzy differential subordinations and superordinations for which the fuzzy best dominant and fuzzy best subordinant are given, respectively. The original theorems proved in the paper generate interesting corollaries for particular choices of functions acting as fuzzy best dominant and fuzzy best subordinant. Another contribution contained in this paper is the nice sandwich-type theorem combining the results given in two theorems proved here using the two theories of fuzzy differential subordination and fuzzy differential superordination.
Marginalized Two-Part Joint Modeling of Longitudinal Semi-Continuous Responses and Survival Data: With Application to Medical Costs
Authors: Shahrokhabadi Mohadeseh Shojaei , Chen (Din) Ding-Geng , Mirkamali Sayed Jamal , Kazemnejad Anoshirvan , Zayeri Farid
Published: October 2021

Non-negative continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical costs data. It is thus critical to incorporate the potential dependence of survival status and longitudinal medical costs in joint modeling, where censorship is death-related. Despite the wide use of conventional two-part joint models (CTJMs) to capture zero-inflation, they are limited to conditional interpretations of the regression coefficients in the model’s continuous part. In this paper, we propose a marginalized two-part joint model (MTJM) to jointly analyze semi-continuous longitudinal costs data and survival data. We compare it to the conventional two-part joint model (CTJM) for handling marginal inferences about covariate effects on average costs. We conducted a series of simulation studies to evaluate the superior performance of the proposed MTJM over the CTJM. To illustrate the applicability of the MTJM, we applied the model to a set of real electronic health record (EHR) data recently collected in Iran. We found that the MTJM yielded a smaller standard error, root-mean-square error of estimates, and AIC value, with unbiased parameter estimates. With this MTJM, we identified a significant positive correlation between costs and survival, which was consistent with the simulation results.
A Study of Seven Asymmetric Kernels for the Estimation of Cumulative Distribution Functions
Authors: Lafaye de Micheaux Pierre , Ouimet Frédéric
Published: October 2021

In this paper, we complement a study recently conducted in a paper of H.A. Mombeni, B. Masouri and M.R. Akhoond by introducing five new asymmetric kernel c.d.f. estimators on the half-line [0,∞), namely the Gamma, inverse Gamma, LogNormal, inverse Gaussian and reciprocal inverse Gaussian kernel c.d.f. estimators. For these five new estimators, we prove the asymptotic normality and we find asymptotic expressions for the following quantities: bias, variance, mean squared error and mean integrated squared error. A numerical study then compares the performance of the five new c.d.f. estimators against traditional methods and the Birnbaum–Saunders and Weibull kernel c.d.f. estimators from Mombeni, Masouri and Akhoond. By using the same experimental design, we show that the LogNormal and Birnbaum–Saunders kernel c.d.f. estimators perform the best overall, while the other asymmetric kernel estimators are sometimes better but always at least competitive against the boundary kernel method from C. Tenreiro.
A Chemical Analysis of Hybrid Economic Systems—Tokens and Money
Authors: Pardi Anabele-Linda , Paolucci Mario
Published: October 2021

With the influence of digital technology in our daily lives continuously growing, we investigate methods with the purpose of assessing the stability, sustainability, and design of systems of token economies that include tokens and conventional currencies. Based on a chemical approach, we model markets with a minimum number of variables and compare the transaction rates, stability, and token design properties at different levels of tokenisation. The kinetic study reveals that in certain conditions, if the price of a product contains both conventional money and tokens, one can treat this combination as one composite currency. The dynamic behaviour of the analysed systems is proven to be dynamically stable for the chosen models. Moreover, by applying the supply and demand law to recalculate the prices of products, the necessity of previous knowledge of certain token attributes—token divisibility and token–money exchange rates—emerges. The chemical framework, along with the analytic methods that we propose, is flexible enough to be adjusted to a variety of conditions and offer valuable information about economic systems.
A Binary Machine Learning Cuckoo Search Algorithm Improved by a Local Search Operator for the Set-Union Knapsack Problem
Authors: García José , Lemus-Romani José , Altimiras Francisco , Crawford Broderick , Soto Ricardo , Becerra-Rozas Marcelo , Moraga Paola , Becerra Alex Paz , Fritz Alvaro Peña , Rubio Jose-Miguel , Astorga Gino
Published: October 2021

Optimization techniques, specially metaheuristics, are constantly refined in order to decrease execution times, increase the quality of solutions, and address larger target cases. Hybridizing techniques are one of these strategies that are particularly noteworthy due to the breadth of applications. In this article, a hybrid algorithm is proposed that integrates the k-means algorithm to generate a binary version of the cuckoo search technique, and this is strengthened by a local search operator. The binary cuckoo search algorithm is applied to the NP-hard Set-Union Knapsack Problem. This problem has recently attracted great attention from the operational research community due to the breadth of its applications and the difficulty it presents in solving medium and large instances. Numerical experiments were conducted to gain insight into the contribution of the final results of the k-means technique and the local search operator. Furthermore, a comparison to state-of-the-art algorithms is made. The results demonstrate that the hybrid algorithm consistently produces superior results in the majority of the analyzed medium instances, and its performance is competitive, but degrades in large instances.
The Impact of Electronic Money on Monetary Policy: Based on DSGE Model Simulations
Authors: Luo Sumei , Zhou Guangyou , Zhou Jinpeng
Published: October 2021

Starting with the interactive relationship between electronic money and household consumption stimuli, this paper deeply analyzes the changes in the behavior of each monetary subject under the impact of electronic money, and establishes a DSGE model based on the three economic sectors of family, commercial bank and central bank under the New Keynesian framework. On this basis, the impact of electronic money on savings, loans, output and the interest rate, and its impact on monetary policy, are described by numerical simulation. The simulation results show that: (1) electronic money has asymmetric effects on savings and loans, but an irrational deviation on households; (2) the influence of electronic money on the interest rate has a reverse effect, and the “inverse adjustment” of the interest rate increases the management difficulty of the micro subject to a certain extent, and affects the effectiveness of monetary policy; (3) the regulatory effect of price monetary policy is better than that of quantitative monetary policy, and electronic money has the effect of its risk restraining impact. Finally, based on the analysis, this paper gives policy recommendations.
Solvability and Stability of the Inverse Problem for the Quadratic Differential Pencil
Authors: Bondarenko Natalia P. , Gaidel Andrey V.
Published: October 2021

The inverse spectral problem for the second-order differential pencil with quadratic dependence on the spectral parameter is studied. We obtain sufficient conditions for the global solvability of the inverse problem, prove its local solvability and stability. The problem is considered in the general case of complex-valued pencil coefficients and arbitrary eigenvalue multiplicities. Studying local solvability and stability, we take the possible splitting of multiple eigenvalues under a small perturbation of the spectrum into account. Our approach is constructive. It is based on the reduction of the non-linear inverse problem to a linear equation in the Banach space of infinite sequences. The theoretical results are illustrated by numerical examples.
BVPs Codes for Solving Optimal Control Problems
Authors: Mazzia Francesca , Settanni Giuseppina
Published: October 2021

Optimal control problems arise in many applications and need suitable numerical methods to obtain a solution. The indirect methods are an interesting class of methods based on the Pontryagin’s minimum principle that generates Hamiltonian Boundary Value Problems (BVPs). In this paper, we review some general-purpose codes for the solution of BVPs and we show their efficiency in solving some challenging optimal control problems.
A Fast Fixed-Point Algorithm for Convex Minimization Problems and Its Application in Image Restoration Problems
Authors: Thongpaen Panadda , Wattanataweekul Rattanakorn
Published: October 2021

In this paper, we introduce a new iterative method using an inertial technique for approximating a common fixed point of an infinite family of nonexpansive mappings in a Hilbert space. The proposed method’s weak convergence theorem was established under some suitable conditions. Furthermore, we applied our main results to solve convex minimization problems and image restoration problems.
A Self-Learning Based Preference Model for Portfolio Optimization
Authors: Hu Shicheng , Li Danping , Jia Junmin , Liu Yang
Published: October 2021

An investment in a portfolio can not only guarantee returns but can also effectively control risk factors. Portfolio optimization is a multi-objective optimization problem. In order to better assist a decision maker to obtain his/her preferred investment solution, an interactive multi-criterion decision making system (MV-IMCDM) is designed for the Mean-Variance (MV) model of the portfolio optimization problem. Considering the flexibility requirement of a preference model that provides a guiding role in MV-IMCDM, a self-learning based preference model DT-PM (decision tree-preference model) is constructed. Compared with the present function based preference model, the DT-PM fully considers a decision maker’s bounded rationality. It does not require an assumption that the decision maker’s preference structure and preference change are known a priori and can be automatically generated and completely updated by learning from the decision maker’s preference feedback. Experimental results of a comparison show that, in the case that the decision maker’s preference structure and preference change are unknown a priori, the performances of guidance and fitness of the DT-PM are remarkably superior to function based preference models; in the case that the decision maker’s preference structure is known a priori, the performances of guidance and fitness of the DT-PM is approximated to the predefined function based model. It can be concluded that the DT-PM can agree with the preference ambiguity and the variability of a decision maker with bounded rationality and be applied more widely in a real decision system.
Chemical Constituents of the Deep-Sea-Derived Penicillium solitum
Authors: He Zhi-Hui , Wu Jia , Xu Lin , Hu Man-Yi , Xie Ming-Ming , Hao You-Jia , Li Shu-Jin , Shao Zong-Ze , Yang Xian-Wen
Published: October 2021

A systematic chemical investigation of the deep-sea-derived fungus Penicillium solitum MCCC 3A00215 resulted in the isolation of one novel polyketide (1), two new alkaloids (2 and 3), and 22 known (4–25) compounds. The structures of the new compounds were established mainly on the basis of exhaustive analysis of 1D and 2D NMR data. Viridicatol (13) displayed moderate anti-tumor activities against PANC-1, Hela, and A549 cells with IC50 values of around 20 μM. Moreover, 13 displayed potent in vitro anti-food allergic activity with an IC50 value of 13 μM, compared to that of 92 μM for the positive control, loratadine, while indole-3-acetic acid methyl ester (9) and penicopeptide A (10) showed moderate effects (IC50 = 50 and 58 μM, respectively).
Prognostic Factors for Post-Recurrence Survival in Stage II and III Colorectal Carcinoma Patients
Authors: Nikolic Neda , Radosavljevic Davorin , Gavrilovic Dusica , Nikolic Vladimir , Stanic Nemanja , Spasic Jelena , Cacev Tamara , Castellvi-Bel Sergi , Cavic Milena , Jankovic Goran
Published: October 2021

Background and objectives: This study aimed to evaluate prognostic factors for post-recurrence survival in local and locally advanced colorectal cancer patients. Materials and Methods: A total of 273 patients with stage III and high-risk stage II colorectal cancer were prospectively enrolled. All patients underwent operative treatment of the primary tumor and adjuvant fluorouracil-based chemotherapy. Results: Over the three-year period (2008–2010), a cohort of 273 patients with stage III and high-risk stage II colorectal cancer had been screened. During follow up, 105 (38.5%) patients had disease recurrence. Survival rates 1-, 3- and 5-year after recurrence were 53.9, 18.2 and 6.5%, respectively, and the median post-recurrence survival time was 13 months. Survival analysis showed that age at diagnosis (p < 0.01), gender (p < 0.05), elevated postoperative Ca19-9 (p < 0.01), tumor histology (adenocarcinoma vs. mucinous vs. signet ring tumors, p < 0.01) and tumor stage (II vs. III, p < 0.05) had a significant influence on post-recurrence survival. Recurrence interval and metastatic site were not related to survival following recurrence. Multivariate analysis showed that older age (HR 2.43), mucinous tumors (HR 1.51) and tumors expressing Ca19-9 at baseline (HR 3.51) were independently associated with survival following recurrence. Conclusions: Baseline patient and tumor characteristics largely predicted patient outcomes after disease recurrence. Recurrence intervals in local and locally advanced colorectal cancer were not found to be prognostic factors for post-recurrence survival. Older age, male gender, stage III and mucinous histology were poor prognostic factors after the disease had recurred. Stage II patients had remarkable post-recurrence survival compared to stage III patients.
Patients’ Perception of Recovery after Dental Implant Placement
Authors: Kahn Adrian , Masri Daya , Shalev Tamir , Meir Haya , Sebaoun Alon , Chaushu Liat
Published: October 2021

Background and Objectives: The success rates of surgical dental implant insertions are high. However, knowledge of patients’ recovery is still lacking. “Health-related quality of life” (HRQOL) questionnaires are gaining popularity in all fields of medicine. The present survey assessed the perception of recovery after the surgical placement of dental implants. Materials and Methods: Forty individuals (26 women and 14 men; mean age, 55 ± 12 years) filled a questionnaire evaluating patients’ perception of recovery for 7 consecutive days post-surgery. Confounding factors included age, gender, oral habits, smoking, bruxism, bone quality (tactile evaluation) and quantity, implant location, number of implants, implant type, length and diameter, one-stage vs. two-stage, and the need for bone grafting. Results: The most serious difficulties were found in swelling, which became minimal after 5 days, followed by eating everyday food, ability to enjoy everyday food, maximal pain and average pain (3 days); analgesics consumption (2.5 days); limitations in daily routine, mouth opening, and speech (2 days); swallowing and sleep (1.5 days); and, within 1 day, all other measures attained minimal levels. Gender, and implant location (anterior vs. posterior) were significant predictor variables exerting their different characteristic delayed recoveries. Conclusions: (1) Patients should expect, in general, recovery within 4 days after dental implant placement; (2) women will experience a delayed recovery, (3) implants placed in the intercanine area will result in postoperative eating difficulties for nearly one week, and (4) the number of implants placed during the same appointment has no effect on post treatment recovery.
Comparison and Performance Validation of Calculated and Established Anaerobic Lactate Thresholds in Running
Authors: Ji Sanghyeon , Sommer Aldo , Bloch Wilhelm , Wahl Patrick
Published: October 2021

Background and Objectives: This study aimed to compare the calculated running velocity at the anaerobic lactate threshold (cLTAn), determined by a mathematical model for metabolic simulation, with two established threshold concepts (onset of blood lactate accumulation (OBLA; 4 mmol∙L−1) and modified maximal deviation method (mDmax)). Additionally, all threshold concepts were correlated with performance in different endurance running events. Materials and Methods: Ten sub-elite runners performed a 30 s sprint test on a cycle ergometer adjusted to an isokinetic mode set to a cadence of 120 rpm to determine maximal lactate production rate (VLamax), and a graded exercise test on a treadmill to determine maximal oxygen uptake (VO2max). Running velocities at OBLA, mDmax, and cLTAn were then compared with each other, and further correlated with running performance over various distances (3000 m, 5000 m, and 10,000 m). Results: The mean difference in cLTAn was −0.13 ± 0.43 m∙s−1 and −0.32 ± 0.39 m∙s−1 compared to mDmax (p = 0.49) and OBLA (p < 0.01), respectively. cLTAn indicated moderate to good concordance with the established threshold concepts (mDmax: ICC = 0.87, OBLA: ICC = 0.74). In comparison with other threshold concepts, cLTAn exhibited comparable correlations with the assessed running performances (cLTAn: r = 0.61–0.76, mDmax: r = 0.69–0.79, OBLA: r = 0.56–0.69). Conclusion: Our data show that cLTAn can be applied for determining endurance performance during running. Due to the consideration of individual physiological profiles, cLTAn offers a physiologically justified approach to assess an athlete’s endurance performance.
Common Pitfalls in Ewing Sarcoma and Desmoplastic Small Round Cell Tumor Diagnosis Seen in a Study of 115 Cases
Authors: Trikalinos Nikolaos A. , Chrisinger John S. A. , Van Tine Brian A.
Published: October 2021

Ewing sarcoma (ES), “Ewing-like sarcoma” (ELS) and desmoplastic small round cell tumors (DSRCT) can masquerade as other tumor types, particularly neuroendocrine neoplasms and receive inappropriate treatment. We retrieved 115 cases of ES, ELS and DSRCT seen over 17 years in a tertiary center. An initial misdiagnosis or incomplete diagnosis occurred in 6/93 (6.4%) of ES/ELS and 5/22 (22.7%) of DSRCT cases. The most frequent misdiagnosis was small cell neuroendocrine carcinoma. While any misdiagnosis or incomplete classification is almost certainly multifactorial, the most common identified reason for erroneous/incomplete initial reporting was expression of neuroendocrine markers. Other contributing factors included keratin expression, older patient age and apparently unusual tumor location. Most patients treated with a non-sarcoma chemotherapy regimen expired, while those who received a sarcoma-related regimen were alive as of last evaluation. Increased awareness of this diagnostic pitfall is needed in evaluating cases of round cell malignancies.
High Entropy Materials: Challenges and Prospects
Authors: Liaw Peter K. , Li Weidong
Published: October 2021

Entropy is an important concept in thermodynamics, measuring the disorder in a system or, more precisely, the number of possible microscopic configurations of individual atoms or molecules of a system, i.e., microstates [...]
Microstructure Design and Its Effect on Mechanical Properties in Gamma Titanium Aluminides
Authors: Liu Xuqi , Lin Qia , Zhang Wenjing , Horne Constance Van , Cha Limei
Published: October 2021

Intermetallic gamma titanium aluminides display attractive engineering properties at high temperatures of up to 750 °C. To date, they have been used in low-pressure turbine blades and turbocharger rotors in advanced aircraft and automotive engines. This review summarizes the fundamental information of the Ti–Al system. After providing the development of γ TiAl alloys, typical phases, microstructures and their characteristics in TiAl alloys, the paper focuses on the effects of alloying elements on the phase boundary shifting, stabilizing effects and strengthening mechanism. The relationships between chemical additions, microstructure evolution and mechanical properties of the alloy are discussed. In parallel, the processing technologies and the common heat treatment methods are described in detail, both of which are applied to optimize the mechanical properties via adjusting microstructures. On this basis, the effects from chemical composition, processing technologies and heat treatments on microstructure, which controls the mechanical properties, can be obtained. It has a certain guiding significance for tailoring the microstructures to gain desired mechanical properties.
Characterization of AlSi10Mg-CP-Ti Metal/Metal Composite Materials Produced by Electro-Sinter-Forging
Authors: Gobber Federico Simone , Fracchia Elisa , Fais Alessandro , Peter Ildiko , Grande Marco Actis
Published: October 2021

Metal–metal composites represent a particular class of materials showing innovative mechanical and electrical properties. Conventionally, such materials are produced by severely plastically deforming two ductile phases via rolling or extruding, swaging, and wire drawing. This study presents the feasibility of producing metal–metal composites via a capacitive discharge-assisted sintering process named electro-sinter-forging. Two different metal–metal composites with CP-Ti/AlSi10Mg ratios (20/80 and 80/20 vol.%) are evaluated, and the effects of the starting compositions on the microstructural and compositional properties of the materials are presented. Bi-phasic metal–metal composites constituted by isolated α-Ti and AlSi10Mg domains with a microhardness of 113 ± 13 HV0.025 for the Ti20-AlSi and 244 ± 35 HV0.025 for the Ti80-AlSi are produced. The effect of the applied current is crucial to obtain high theoretical density, but too high currents may result in Ti dissolution in the Ti80-AlSi composite. Massive phase transformations due to the formation of AlTiSi-based intermetallic compounds are observed through thermal analysis and confirmed by morphological and compositional observation. Finally, a possible explanation for the mechanisms regulating densification is proposed accounting for current and pressure synergistic effects.
The Role of Citrate Transporter INDY in Metabolism and Stem Cell Homeostasis
Authors: Kannan Kavitha , Rogina Blanka
Published: October 2021

I’m Not Dead Yet (Indy) is a fly gene that encodes a homologue of mammalian SLC13A5 plasma membrane citrate transporter. Reducing expression of Indy gene in flies, and its homologues in worms, extends longevity. Indy reduction in flies, worms, mice and rats affects metabolism by regulating the levels of cytoplasmic citrate, inducing a state similar to calorie restriction. Changes include lower lipid levels, increased insulin sensitivity, increased mitochondrial biogenesis, and prevention of weight gain, among others. The INDY protein is predominantly expressed in fly metabolic tissues: the midgut, fat body and oenocytes. Changes in fly midgut metabolism associated with reduced Indy gene activity lead to preserved mitochondrial function and reduced production of reactive oxygen species. All these changes lead to preserved intestinal stem cell homeostasis, which has a key role in maintaining intestinal epithelium function and enhancing fly healthspan and lifespan. Indy gene expression levels change in response to caloric content of the diet, inflammation and aging, suggesting that INDY regulates metabolic adaptation to nutrition or energetic requirements by controlling citrate levels.
Abiotic and Biotic Damage of Microalgae Generate Different Volatile Organic Compounds (VOCs) for Early Diagnosis of Algal Cultures for Biofuel Production
Authors: Reese Kristen L. , Fisher Carolyn L. , Lane Pamela D. , Jaryenneh James D. , Jones A. Daniel , Frank Matthias , Lane Todd W.
Published: October 2021

Open microalgal ponds used in industrial biomass production are susceptible to a number of biotic and abiotic environmental stressors (e.g., grazers, pathogens, pH, temperature, etc.) resulting in pond crashes with high economic costs. Identification of signature chemicals to aid in rapid, non-invasive, and accurate identification of the stressors would facilitate targeted and effective treatment to save the algal crop from a catastrophic crash. Specifically, we were interested in identifying volatile organic compounds (VOCs) that can be used to as an early diagnostic for algal crop damage. Cultures of Microchloropsis gaditana were subjected to two forms of algal crop damage: (1) active grazing by the marine rotifer, Brachionus plicatilis, or (2) repeated freeze–thaw cycles. VOCs emitted above the headspace of these algal cultures were collected using fieldable solid phase microextraction (SPME) fibers. An untargeted analysis and identification of VOCs was conducted using gas chromatography-mass spectrometry (GC-MS). Diagnostic VOCs unique to each algal crop damage mechanism were identified. Active rotifer grazing of M. gaditana was characterized by the appearance of carotenoid degradation products, including β-cyclocitral and various alkenes. Freeze–thaw algae produced a different set of VOCs, including palmitoleic acid. Both rotifer grazing and freeze–thawed algae produced β-ionone as a VOC, possibly suggesting a common stress-induced cellular mechanism. Importantly, these identified VOCs were all absent from healthy algal cultures of M. gaditana. Early detection of biotic or abiotic environmental stressors will facilitate early diagnosis and application of targeted treatments to prevent algal pond crashes. Thus, our work further supports the use of VOCs for monitoring the health of algal ponds to ultimately enhance algal crop yields for production of biofuel.