bluuebunny/crossref_metadata_2025 huggingface dataset:
Filling in the Gaps: False Memories and Partisan Bias
Authors: Armaly Miles T. , Enders Adam M.
Published: May 2022

While cognitive psychologists have learned a great deal about people's propensity for constructing and acting on false memories, the connection between false memories and politics remains understudied. If partisan bias guides the adoption of beliefs and colors one's interpretation of new events and information, so too might it prove powerful enough to fabricate memories of political circumstances. Across two studies, we first distinguish false memories from false beliefs and expressive responses; false political memories appear to be genuine and subject to partisan bias. We also examine the political and psychological correlates of false memories. Nearly a third of respondents reported remembering a fabricated or factually altered political event, with many going so far as to convey the circumstances under which they “heard about” the event. False‐memory recall is correlated with the strength of partisan attachments, interest in politics, and participation, as well as narcissism, conspiratorial thinking, and cognitive ability.
Estimating Monthly Labour Force Figures During the COVID-19 Pandemic in the Netherlands
Authors: Brakel Jan , Souren Martijn , Krieg Sabine
Published: May 2022

Official monthly statistics about the Dutch labour force are based on the Dutch Labour Force Survey (LFS). The LFS is a continuously conducted survey that is designed as a rotating panel design. Data collection among selected households is based on a mixed-mode design that uses web interviewing, telephone interviewing and face-to-face interviewing. Monthly estimates about the labour force are obtained with a structural time series model. Due to the COVID-19 pandemic, face-to-face interviewing stopped. It was anticipated that this would have a systematic effect on the outcomes of the LFS and that the lockdown at the same time affected the real monthly labour force figures. The lockdown indeed marked a sharp turning point in the evolution of the series of the monthly labour force figures and strongly increased the volatility of these series. In this paper, it is explained how Statistics Netherlands produced monthly labour force figures during the COVID-19 pandemic. It is shown how the sudden change in the mode effects, because face-to-face interviewing stopped, were separated from real period-to-period changes in the labour force figures. It is also explained how the time series model is adapted to the increased volatility in the labour force figures.
Bayesian Nonparametric Modelling of Multiple Graphs with an Application to Ethnic Metabolic Differences
Authors: Molinari Marco , Cremaschi Andrea , De Iorio Maria , Chaturvedi Nishi , Hughes Alun D. , Tillin Therese
Published: May 2022

We propose a novel approach to the estimation of multiple Gaussian graphical models (GGMs) to analyse patterns of association among a set of metabolites, under different conditions. Our motivating application is the SABRE (Southall And Brent REvisited) study, a triethnic cohort study conducted in the United Kingdom. Through joint modelling of pattern of association corresponding to different ethnic groups, we are able to identify potential ethnic differences in metabolite levels and associations, with the aim of gaining a better understanding of different risk of cardiometabolic disorders across ethnicities. We model the relationship between a set of metabolites and a set of covariates through a sparse seemingly unrelated regressions model and we use GGMs to represent the conditional dependence structure among metabolites. We specify a dependent generalised Dirichlet process prior on the edge inclusion probabilities to borrow strength across groups and we adopt the horseshoe prior to identify important biomarkers. Inference is performed via Markov chain Monte Carlo.
Pedagogical values in teaching public theology: Resonances from an underground seminary
Authors: Day Katie
Published: May 2022

This article is a reflection on the teaching of public theology in two very different contexts: in a Protestant seminary in the US (1985–2019) and an underground seminary in Nazi Germany (1935–1937). The author analyzes her teaching career over years of change, both institutional and social, that challenged pedagogical methods to remain relevant and effective. Yet informing and shaping her pedagogy were five values that remained constant throughout: contextuality, democratic participation, collegiality, dialogue, and inclusion of diverse voices. These values resonated with another theological school in another time and place—the underground seminary at Finkenwalde in Germany, created by Dietrich Bonhoeffer in 1935. It trained students for the Confessing Church until it was shut down by the Gestapo in 1937. Moving into a future in which pedagogical methods are changing and instructors are retooling to learn new technologies and teaching skills, these core values remain as touchstones in shaping curriculum and the educational experience.
Evaluation of Heller's reaction and the urine dipstick method alone or in combination to detect proteinuria in sheep
Authors: Athanasiou Labrini V. , Katsoulos Panagiotis D. , Katsogiannou Eleni G. , Pazarakioti Aikaterini T. , Spanou Victoria M. , Tsokana Constantina N. , Apostolidis Kosmas N. , Tzivara Athanasia H. , Polizopoulou Zoe S.
Published: May 2022

Background

Urine dipstick and Heller's reaction are easy first‐line screening tests for the detection of proteinuria; however, the performance of these methods in alkaline ovine urine is largely unknown.

Objective

The aim of this study was to evaluate the diagnostic performance of Heller's reaction alone or in combination with dipstick for the detection of proteinuria in sheep, using the urine protein to creatinine ratio (UP/C) with two cut‐off values as the reference method.

Methods

Ninety‐eight urine samples were collected from sheep using the transient apnea method. Heller's reaction, the dipstick method, and the UP/C ratio were used to assess proteinuria. The results were statistically analyzed twice, based on two different UP/C cut‐off values of 0.2 and 0.5. Cohen's kappa value was used to determine the agreement between the UP/C ratios and Heller's reaction, the dipstick method, or the combination of methods. Sensitivity, specificity, and positive and negative likelihood ratios were calculated. ROC curves were also generated, and the areas under the curve (AUC) were evaluated to determine the optimal threshold for the numerical values of the two methods.

Results

Heller's reaction is more specific (96.67% and 96.00% when the cut‐off value is 0.2 and 0.5, respectively) than the dipstick method, while the dipstick method was more sensitive (91.18% and 91.30%, when the cut‐off value was 0.2 and 0.5, respectively) than Heller's reaction for the detection of proteinuria. Both tests were accurate when any grade >0 was considered positive.

Conclusions

Proteinuria can almost be excluded in ovine urine samples with negative Heller's reaction and dipstick test.
Reviewer Acknowledgements
Authors: Johnson Patricia
Published: May 2022

Studies in Media and Communication (SMC) would like to acknowledge the following reviewers for their assistance with peer review of manuscripts for this issue. Many authors, regardless of whether SMC publishes their work, appreciate the helpful feedback provided by the reviewers. Their comments and suggestions were of great help to the authors in improving the quality of their papers. Each of the reviewers listed below returned at least one review for this issue.Reviewers for Volume 10, Number 1 Amie Jones, University of Georgia, USAAndreas Veglis, Aristotle University of Thessaloniki, GreeceAyşe Aslı Sezgin, Çukurova University, TurkeyBernard Naledzani Rasila, University of Venda, South AfricaCamelia Cmeciu, Danubius University of Galati, RomaniaCarmen Pérez-Sabater, Universitat Politècnica de València, SpainChristof Demont-Heinrich, University of Denver, USAImed Ben Labidi, Doha Institute for Graduate Studies, USAJavier Serrano Puche, University of Navarra, SpainJianbo Hou, Xi'an International Studies University, ChinaKunle Olufemi Aramide, The Polytechnic Ibadan, NigeriaLambrini Papadopoulou, National and Kapodistrian University, GreeceLaura Cervi, Universitat Autonoma de Barcelona, SpainMaría José Serrano, Universidad de La Laguna, SpainMatthias Degen, Westphalian University of Applied Sciences, GermanyMunira Fayzulloeva, Tajik State University of Law, TajikistanNina Gunnarsson, Jönköping university, SwedenPhilemon Bantimaroudis, University of Cyprus, CyprusRefat Aljumily, Newcastle University, UKYi Luo, Montclair State University, USAYoung Joon Lim, University of Texas Rio Grande Valley, USA   Patricia JohnsonEditorial AssistantOn behalf of,The Editorial Board of Studies in Media and CommunicationRedfame Publishing9450 SW Gemini Dr. #99416Beaverton, OR 97008, USAURL: http://smc.redfame.com
Spin of Protons in NICA and PTR Storage Rings as an Axion Antenna
Authors: Nikolaev N. N.
Published: May 2022

A new approach to search for axions in the storage ring experiments, applicable at a short coherence time of the in-plane polarization as is the case for protons is discussed. The technique can readily be applied at any storage ring equipped with internal polarimeter for the radial polarization of the beam (COSY, NICA, PTR). A possibility of substantial broadening of the range of attainable axion masses in storage rings with the hybrid electric and magnetic bending is pointed out, the PTR proton storage ring being an example.
Tagging the Higgs boson decay to bottom quarks with colour-sensitive observables and the Lund jet plane
Authors: Cavallini Luca , Coccaro Andrea , Khosa Charanjit K. , Manco Giulia , Marzani Simone , Parodi Fabrizio , Rebuzzi Daniela , Rescia Alberto , Stagnitto Giovanni
Published: May 2022

We study the problem of distinguishing b-jets stemming from the decay of a colour singlet, such as the Higgs boson, from those originating from the abundant QCD background. In particular, as a case study, we focus on associate production of a vector boson and a Higgs boson decaying into a pair of b-jets, which has been recently observed at the LHC. We consider the combination of several theory-driven observables proposed in the literature, together with Lund jet plane images, in order to design an original Hbb tagger. The observables are combined by means of standard machine learning algorithms, which are trained on events obtained with fast detector simulation techniques. We find that the combination of high-level single-variable observables with the Lund jet plane provides an excellent discrimination performance. We also study the dependence of the tagger on the invariant mass of the decaying particles, in order to assess the extension to a generic Xbb tagger.
Time-varying graph representation learning via higher-order skip-gram with negative sampling
Authors: Piaggesi Simone , Panisson André
Published: May 2022

Representation learning models for graphs are a successful family of techniques that project nodes into feature spaces that can be exploited by other machine learning algorithms. Since many real-world networks are inherently dynamic, with interactions among nodes changing over time, these techniques can be defined both for static and for time-varying graphs. Here, we show how the skip-gram embedding approach can be generalized to perform implicit tensor factorization on different tensor representations of time-varying graphs. We show that higher-order skip-gram with negative sampling (HOSGNS) is able to disentangle the role of nodes and time, with a small fraction of the number of parameters needed by other approaches. We empirically evaluate our approach using time-resolved face-to-face proximity data, showing that the learned representations outperform state-of-the-art methods when used to solve downstream tasks such as network reconstruction. Good performance on predicting the outcome of dynamical processes such as disease spreading shows the potential of this method to estimate contagion risk, providing early risk awareness based on contact tracing data.
Influence of gamma radiation on magnetoelectric properties of extruded samples of solid solution Bi85Sb15〈Te〉 modified ZrO2
Authors: Tagiyev Mail Masim , Abdullayeva Ilaha Adil
Published: May 2022

The electrical and thermal properties of extruded samples of Bi[Formula: see text]Sb[Formula: see text] [Formula: see text] modified with ZrO2 were investigated depending on the dose of gamma radiation in the temperature range [Formula: see text] K and magnetic field strength (H) [Formula: see text] A/m. It was found that an increase in the mobility in the irradiated modified Bi[Formula: see text]Sb[Formula: see text] [Formula: see text] is associated with the radiation introduction of acceptor (negatively charged) centers, which at low doses are generated mainly in the regions of the efficiency of impurity scattering of charge carriers and partially neutralized centers and, accordingly, to a certain increase in the mobility. In the extruded modified samples of the Bi[Formula: see text]Sb[Formula: see text] solid solution, irradiation with gamma quanta results not only in the generation of radiation defects (RDs) (centers), but also accompanied by their rearrangement. This causes a change in the spectrum of localized states and the electron scattering process, which leads to corresponding changes in the presented electrical and thermal parameters.
A novel link prediction method integrated link attributes for directed graph
Authors: Wang Guishen , Li Hao , Pu Jiajia , Wu Junlin , Wang Hongmei
Published: May 2022

Link prediction is an important topic in the complex networks which aims to mine the missed or unobserved links and find the possible connected links in the network according to the known network structure. In this paper, we proposed a novel link prediction method for the directed graph which considers link semantic. The experimental results on the wiki vote network show that our link prediction method integrating link attributes achieved better results than the other compared methods.
A possible trial beyond the conventional random phase approximation for the su(2)-Lipkin model including the case of nonclosed shell system
Authors: Tsue Yasuhiko , Providência Constança , da Providência João , Yamamura Masatoshi
Published: May 2022

Concerning the [Formula: see text]-Lipkin model, the calculation of the excitation energy to the first excited state gives rise to the following fact: The two results based on the exact treatment and the conventional random phase approximation (RPA) are in unexpected disagreement. In order to remove this discrepancy, the conventional RPA is renewed. With the aim of this renewal, the terms, which cannot be dealt with in the conventional one, are estimated. The basic framework of this new form is not reorganized from that of the conventional one. In addition, the [Formula: see text]-Lipkin model itself is also modified so as to be applicable to the case with nonclosed shell system. To this modification, one more [Formula: see text]-algebra, which has been already proposed by the present authors, is applied. Through the use of this algebra, the [Formula: see text]-Lipkin model is applicable to the case with any total fermion number permitted in the model.
DOES REAL ACUPUNCTURE PRODUCE THE SAME EFFECT AS PLACEBO ACUPUNCTURE ON SENSORY PERCEPTION? A RANDOMIZED CONTROLLED CLINICAL TRIAL
Authors: Maciel Leonardo Y. S. , Neto Mauricio L. P. , Leite Paula Michele S. , Mendonça Andreza C. R. , Santana Mylena Maria S. , Araujo Carla Carolina A. , Souza Jersica H. S. , Santana Érika Thatyana N. , DeSantana Josimari M.
Published: May 2022

Background: Acupuncture treatment has become increasingly popular in the Western due to its therapeutic effects and low cost. However, some studies suggest that both real and sham acupuncture have effects.

Objectives: Our study aimed to evaluate the effect of real and placebo acupuncture in cutaneous and deep sensitivity threshold.

Methods: Three different types of placebo acupunctures were compared with real acupuncture, four groups at the St25 point (abdominal) and four at the Bl52 point (lumbar region), totaling eight groups. 185 subjects were recruited and randomized, ratings of cutaneous sensitivity threshold (von Frey filaments) and pressure pain threshold (algometer) occurred before and after the application.

Results: The cutaneous sensitivity threshold showed no significant difference in the intragroup analysis and also compared between groups. The pressure pain threshold showed a significant decrease in values in the Real group Bl52 (p = 0.044) and insertion and removal Bl52 (p = 0.037) for intra-group analysis and comparison between groups, there was a significant reduction in Real groups St25 and insertion and withdrawal in Bl52 point compared to Park Sham Bl52 and Real Bl52, respectively (p < 0.05).

Conclusion: Cutaneous sensitivity threshold did not change after applying acupuncture or placebo, but these techniques influence the pressure pain threshold.
Contemporary Potentials and Challenges of Digital Logistics and Supply Chain Management
Authors: Tsipoulanidis Alexander , Nanos Ioannis
Published: May 2022

As the recent COVID-19 pandemic crisis has shown, global supply chains and value adding networks are vulnerable to changes on the economic, business, technological, and social environment. Therefore, there is a need of facilitating and transforming supply chains in a more efficient, resilient, and sustainable way. The aim of this paper is to analyze the importance and the impact of digital technologies to the transformation of supply chain management, through an examination of potential use cases and implementation strategies and under a methodological framework related to the supply chain operations reference (SCOR) model, which is connected to the principles of lean thinking.
Attitude Towards Using Fintech Services: Digital Immigrants Versus Digital Natives
Authors: Koroleva Ekaterina
Published: May 2022

As information technologies continue to evolve, the gap between those who were born before (digital immigrants) and after (digital natives) the technology revolution continues to widen. Building on the technology acceptance model, we examine the determinants and influences on attitudes towards using FinTech services and analyze differences in attitudes between the two categories of consumers. The results show the relevance of digital literacy, financial literacy, perceived ease of use and the personal habits of consumers in prompting a positive attitude towards the use of FinTech services. Digital natives have stronger personal habits oriented towards information systems; they rate their own levels of digital literacy higher and also perceive ease of use in FinTech. Digital immigrants rate their levels of financial literacy higher. The research highlights the relevance of improving the financial literacy of digital natives and the digital literacy of digital immigrants. Moreover, it is important to investigate further measures that would increase the perceived ease of use of FinTech by digital immigrants.
Statistically Convergent Difference Sequences of Complex Uncertain Variables
Authors: Saha Sangeeta , Tripathy Binod Chandra
Published: May 2022

The main aim of this paper is to introduce several forms of statistical convergence of difference sequences of complex uncertain variables: [Formula: see text]-statistically convergence almost surely, [Formula: see text]-statistically convergence in measure, [Formula: see text]-statistically convergence in mean and [Formula: see text]-statistically convergence uniformly almost surely. Furthermore, we have established the inter-relationship between all the proposed concepts and give necessary examples when the relationship fails to develop. Lastly, we have provided a diagram to represent the overall idea of this paper.
One-Step Fabrication of Flower-Like ZnWO4/BiOBr Nanospheres with Enhanced Photocatalytic Degradation Efficiency
Authors: Zhao Hong-Jian , Yu Zhe , Wu Ren-Jang , Mu Jing-Xia , Ma Fu
Published: May 2022

Flower-like zinc tungstate/bismuth bromate (ZnWO4/BiOBr) nanospheres were synthesized by a one-step hydrothermal method. The photocatalytic activity of the ZnWO4/BiOBr heterojunction was evaluated by the photocatalytic degradation of 30[Formula: see text]mg/L of rhodamine B (RhB). It was found that 10% of ZnWO4/BiOBr had the best degradation ability toward RhB. The degradation rate of RhB reached 97.7% (5 times and 358 times those of BiOBr and ZnWO4, respectively) after light-emitting diode (LED) visible light irradiation for 30[Formula: see text]min. The ZnWO4/BiOBr heterojunction had excellent photocatalytic activity because of its higher specific surface area and enhanced spectral response range. Moreover, the ZnWO4/BiOBr heterojunction improved the charge separation efficiency and promoted the generation of more holes, [Formula: see text] O[Formula: see text] and [Formula: see text] OH radicals under light irradiation; thus, improving the degradation efficiency. Finally, a possible photocatalytic degradation mechanism was proposed. This study provides a good reference for the preparation of bismuth-based composite photocatalysts for the degradation and purification of organic pollutants.
Chaos in a nonautonomous model for the impact of media on disease outbreak
Authors: Medda Rakesh , Tiwari Pankaj Kumar , Pal Samares
Published: May 2022

Social media initiatives educate the public about the tools and strategies necessary to defend themselves from emerging diseases. The effect of media advertisements in combating an infectious disease is explored in the present investigation. The numerical results show that the system destabilizes when the growth rate of media advertisements goes above a certain value. For lower ranges of the rate of distribution of awareness through social media platforms, our system showcases stable endemic state. But as the rate of disseminating awareness surpasses a critical value, the system undergoes a Hopf bifurcation and limit cycle oscillations appear. However, the persistent oscillations are killed out and the system returns to a stable endemic state as the rate of distribution of awareness exceeds another threshold value. Extremely large values of the awareness distribution through media advertisements eradicate the disease from the entire community. Model parameters with significant impacts on the disease prevalence and eradication are identified through sensitivity analysis. We extend our model to encapsulate the seasonal variation in the rate of media advertisements. Sufficient conditions have been derived for which the nonautonomous system exhibits globally attractive positive periodic solution. The nonautonomous system is shown to produce chaotic dynamics under the circumstances of the corresponding autonomous system that exhibits limit cycle oscillations. Overall, our findings deduce that media advertisements play a critical role in raising public awareness and ultimately resulting in the eradication of the disease from the society.
Operator level limit of the circular Jacobi β-ensemble
Authors: Li Yun , Valkó Benedek
Published: May 2022

We prove an operator level limit for the circular Jacobi [Formula: see text]-ensemble. As a result, we characterize the counting function of the limit point process via coupled systems of stochastic differential equations. We also show that the normalized characteristic polynomials converge to a random analytic function, which we characterize via the joint distribution of its Taylor coefficients at zero and as the solution of a stochastic differential equation system. We also provide analogous results for the real orthogonal [Formula: see text]-ensemble.
Cointegration Tests Using Instrumental Variables
Authors: Lee Junsoo , Yucel Ali
Published: May 2022

This paper proposes new cointegration tests based on instrumental variable (IV) estimation. An important property of our tests is that the asymptotic distribution remains standard normal (or Chi-square) regardless of the number of regressors, differing deterministic terms, structural dummies, and inclusion of stationary covariates. Thus, our IV cointegration tests have the operational advantage that they do not depend on nuisance parameters. As such, we can incorporate stationary covariates into a model to enhance power without affecting the asymptotic distribution of the test. This is important because it alleviates the need to tabulate the critical values for every possible case or to bootstrap the critical values.
A Holistic Approach for Role Inference and Action Anticipation in Human Teams
Authors: Dong Junyi , Huo Qingze , Ferrari Silvia
Published: May 2022

The ability to anticipate human actions is critical to many cyber-physical systems, such as robots and autonomous vehicles. Computer vision and sensing algorithms to date have focused on extracting and predicting visual features that are explicit in the scene, such as color, appearance, actions, positions, and velocities, using video and physical measurements, such as object depth and motion. Human actions, however, are intrinsically influenced and motivated by many implicit factors such as context, human roles and interactions, past experience, and inner goals or intentions. For example, in a sport team, the team strategy, player role, and dynamic circumstances driven by the behavior of the opponents, all influence the actions of each player. This article proposes a holistic framework for incorporating visual features, as well as hidden information, such as social roles, and domain knowledge. The approach, relying on a novel dynamic Markov random field (DMRF) model, infers the instantaneous team strategy and, subsequently, the players’ roles that are temporally evolving throughout the game. The results from the DMRF inference stage are then integrated with instantaneous visual features, such as individual actions and position, in order to perform holistic action anticipation using a multi-layer perceptron (MLP). The approach is demonstrated on the team sport of volleyball, by first training the DMRF and MLP offline with past videos, and, then, by applying them to new volleyball videos online. These results show that the method is able to infer the players’ roles with an average accuracy of 86.99%, and anticipate future actions over a sequence of up to 46 frames with an average accuracy of 80.50%. Additionally, the method predicts the onset and duration of each action achieving a mean relative error of 14.57% and 15.67%, respectively.
i
-QER: An Intelligent Approach Towards Quantum Error Reduction
Authors: Basu Saikat , Saha Amit , Chakrabarti Amlan , Sur-Kolay Susmita
Published: May 2022

Quantum computing has become a promising computing approach because of its capability to solve certain problems, exponentially faster than classical computers. A
n
-qubit quantum system is capable of providing 2

n

computational space to a quantum algorithm. However, quantum computers are prone to errors. Quantum circuits that can reliably run on today’s Noisy Intermediate-Scale Quantum (NISQ) devices are not only limited by their qubit counts but also by their noisy gate operations. In this article, we have introduced
i
-QER, a scalable machine learning-based approach to evaluate errors in a quantum circuit and reduce these without using any additional quantum resources. The
i
-QER predicts possible errors in a given quantum circuit using supervised learning models. If the predicted error is above a pre-specified threshold, it cuts the large quantum circuit into two smaller sub-circuits using an error-influenced fragmentation strategy for the first time to the best of our knowledge. The proposed fragmentation process is iterated until the predicted error reaches below the threshold for each sub-circuit. The sub-circuits are then executed on a quantum device. Classical reconstruction of the outputs obtained from the sub-circuits can generate the output of the complete circuit. Thus,
i
-QER also provides classical control over a scalable hybrid computing approach, which is a combination of quantum and classical computers. The
i
-QER tool is available at
https://github.com/SaikatBasu90/i-QER
.
MIMORPH
Authors: Lacruz Jesus O. , Ruiz Rafael
Published: May 2022

With the rapid increase in performance and complexity of wireless networks, it has become challenging to build experimentation platforms that can meet such performance requirements but at the same time are comparatively easy to use and flexible. The lack of suitable platforms inspired us to build MIMORPH, a single experimentation platform that supports massive MIMO sub-6 GHz systems, ultra-high bandwidth Millimeter Wave (mmWave) MIMO, as well as mixed sub-6 GHz and mmWave configurations. It can be operated in a closed-loop manner and is intended for WLAN, 5G-NR and future 6G research. MIMORPH is built on top of standard components, such as a state-of-the-art RFSoC FPGA system and its implementation is made freely available to the research community.
Effect of FNS Incorporation on the Properties of Ternary Blended Cement Containing Blast Furnace Slag and Fly Ash
Authors: Kim Min Jae , Park Eon Sang , Hwang Woong Ik , Cho Won Jung
Published: May 2022

This study aims to assess the properties of ternary blended concrete in terms of mechanical performance and resistance to chemical attack. Specimens consisted of concrete and paste having a water to binder ratio of 0.45 made with ordinary Portland cement, pozzolanic materials, and ferronickel slag. Results on compressive strength at l80 days of curing showed that ternary blended concrete with ferronickel slag was 8% to 18% higher than for OPC. For splitting tensile strength and flexural strength, however, there was no such trend. Durability was examined in terms of resistance to rapid chloride penetration, carbonation, and sulfate attack. Ternary mix showed always-higher resistance against chloride penetration and sulfate attack while being more susceptible to carbonation due to the lower pH of the cement matrix. In addition, all ternary mixes exhibited lower heat of hydration compared to OPC and binary mixes with pozzolanic materials showed the lowest heat evaporation. Furthermore, from the results of XRD analysis, identical hydration products were found irrespective to the binder, while a significant change was observed on the portlandite peak. Overall, results showed that the incorporation of ferronickel slag affected positively the properties of concrete.
PEGylated Magnetite/Hydroxyapatite: A Green Nanocomposite for T2-Weighted MRI and Curcumin Carrying
Authors: Gharehaghaji Nahideh , Divband Baharak
Published: May 2022

Background. The design of new magnetic resonance imaging (MRI) contrast media with chemotherapy drug-carrying capacity has an important role in diagnostic and therapeutic purposes. This study aimed to synthesize a polyethylene glycol (PEG)-coated magnetite/hydroxyapatite nanocomposite as an MRI contrast agent investigate its curcumin loading/release properties and consider the cytotoxicity effect of the curcumin-loaded nanocomposite on different cell lines. Materials and Methods. PEGylated magnetite/hydroxyapatite (PMHA) nanocomposite was synthesized and characterized using X-ray diffraction, Fourier transform infrared spectroscopy, transmission electron microscopy, vibrating sample magnetometry, and energy dispersive X-ray analysis. MTT assay was performed to consider the A549, MCF-7, and MRC-5 cells toxicity of the PMHA and the curcumin-loaded nanocomposite. The r2 relaxivity of the nanocomposite was determined by an MRI device. The curcumin loading and its release from the nanocomposite at pH of 7.4 and 5.5 were investigated. Results. The spherical nanocomposite showed an average size of 20 nm and a superparamagnetic property. PMHA nanocomposite was highly cytocompatible, while the curcumin-loaded nanocomposite showed significant cytotoxicity for A549 and a much higher toxic effect on MCF-7 cancer cells. The r2 relaxivity was measured as 120 mM−1S−1. The curcumin loading capacity of PMHA was 1.9 mg/g, and the curcumin release profile showed a pH-dependent sustained release of the anti-cancer drug that was higher for pH of 5.5. Conclusion. The high r2 relaxivity of PMHA nanocomposite and sustained release of curcumin from the loaded one at the pH of tumor environment suggest that the nanocomposite is a potential candidate for T2-weighted MRI and cancer treatment.
Improving the Efficiency of Cutting Tools through Application of Filtered Cathodic Vacuum Arc Deposition Coating Techniques: A Review
Authors: Benti Hailu Gemechu , Woldeyohannes Abraham Debebe , Yigezu Belete Sirahbizu
Published: May 2022

The challenge of enhancing cutting tool life has been dealt with by many research studies. However, this challenge seems endless with growing technological advancement which brings about incremental improvement in tool life. The objective of this review paper is focused at assessing filtered cathodic vacuum arc deposition techniques applied on cutting tools and their effect on tool efficiency. The paper particularly picks filtered cathodic vacuum arc deposition (FCVAD) among other well-identified methods of coating like the Chemical Vapor Deposition (CVD) and Physical Vapor Deposition (PVD). Filtered Cathodic Vacuum Arc Deposition is the state of art in the coating technology finding wide application in the electronics industry and medical industry in addition to the machining industry, which is the concern of this review paper. This review is made in order to summarize and present the various techniques of FCVAD coatings and their applications, as investigated by various researches in the area.
Production of Biodiesel from Mixed Castor Seed and Microalgae Oils: Optimization of the Production and Fuel Quality Assessment
Authors: Beyene Dejene , Abdulkadir Mohammedsani , Befekadu Adisu
Published: May 2022

The diminishing reserves and environmental consequences of the fossil fuel-based petrodiesel necessitate the exploration of an alternative fuel with better quality and minimum environmental impacts. The study explores the optimization of biodiesel production from nonfood and locally available mixed feedstocks as an effective and a sustainable approach to solve the insufficiency and high costs of single oil feedstock. The selection of suitable oil feedstocks and optimization of process variables are the prime issues for cost-effective industrial scale production of biodiesel from mixed feedstocks toward the industrial scale production of biodiesel. The objective of this study was to optimize process variables for the alkaline transesterification of mixed castor seed and microalgae oils to optimize the yield of biodiesel. Oils were extracted from dried microalgae (Chlorella vulgaris) biomass and castor seed kernel using methanol. The oils were purified, characterized, mixed in a 1 : 1 ratio, and converted to biodiesel. The transesterification experiments designed according to the central composite design (CCD) were used to optimize the yield of biodiesel through the response surface methodology (RSM). Experimental results were analyzed by response surface regression to produce a model for predicting biodiesel yield. Model significance, fitness, the effect of significant variables, and interactions between the variables on the yield of biodiesel were studied through the analysis of variance (ANOVA). The optimization of transesterification process variables revealed that the catalyst concentration of 1.23% (w/w), ethanol to mixed oil ratio of 5.94 : 1 (v/v), and reaction temperature of 51.0°C were the optimum conditions to achieve an optimum biodiesel yield of 92.88%. Validation experiments conducted under the optimum conditions resulted in the biodiesel yield of 92.36%, which is very close to the model predicted value. Various standard methods were used to characterize the biodiesel produced under optimum conditions, and it was found compatible with ASTM 751 and EN14214 biodiesel standards.
System Evaluation and Management of College Students’ Physical Exercise Behavior Stages Integrating Bayesian Association Rules Data Mining Algorithm
Authors: Shi Juan
Published: May 2022

The form of association rules is simple, and it is efficient and convenient to apply. However, because association rules cannot express the connection between different rules, in some more complex application fields, when it is necessary to comprehensively consider the impact of multiple factors on the results, the application of rules is more difficult. In the process of reasoning about the node state, the influence of various factors (parent nodes) can be comprehensively considered. This paper proposes a Bayesian network-based association rule representation method. After mining the association rules from the data, through structural learning and conditional probability table learning, the original rules are finally used as Bayesian nets. This effectively expands the application of association rules. The experimental results show that after using MapReduce parallelization, the improved algorithm can not only process larger-scale data sets, but also save a lot of running time. The correlation between physical exercise behavior evaluation management, dimensional exercise motivation, exercise method, and college students’ school adaptability reached a significance of 0.001, and the correlation between dimension exercise time and college students’ school adaptability reached a significance of 0.05. The correlation between physical exercise behavior evaluation management and school adaptability in terms of interpersonal relationship adaptation, learning adaptation, campus adaptation, career adaptation, emotional adaptation, self-adjustment, and satisfaction reached significant levels.
[Retracted] Nestin Regulates Keap1‐Nrf2‐HO‐1‐Mediated Antioxidant Responses during Stress and Malignant Hematopoiesis
Authors: Lu Chunjuan , Wei Jin
Published: May 2022

Objective. To investigate the role of nestin in regulating Keap1‐nuclear factor erythroid‐2‐related factor 2 (Nrf2)‐heme oxygenase‐1‐(HO‐1‐) mediated antioxidant responses in stress and malignant hematopoiesis. Methods. The mRNA of peripheral blood mononuclear cells was extracted from 20 leukemia patients and 20 healthy people who were hospitalized in the Hematology Department of our hospital from September 2020 to December 2021, and the mRNA levels of nestin, Keap1, Nrf2, and HO‐1 were detected by real‐time‐ (RT‐) PCR. Results. Compared with healthy controls, the mRNA of nestin, Keap1, Nrf2, and HO‐1 in peripheral blood mononuclear cells of leukemia patients was significantly upregulated. Conclusion. The occurrence and development of leukemia are closely related to nestin regulating Keap1‐Nrf2‐Ho‐1 signal pathway. Research Significance. This study determined the effect of nestin on the biological behavior of leukemia cells and its possible mechanism and confirmed that nestin may be a marker of tumor and tumor blood vessels.
Exploration of the Effect of Icariin on Nude Mice with Lung Cancer Bone Metastasis via the OPG/RANKL/RANK System
Authors: Ruilian Zhao , Ying Gao , Hongmei Shen , Lihua Guo
Published: May 2022

Epimedium is a traditional Chinese medicine that is most commonly prescribed by practitioners of Chinese medicine for the clinical treatment of malignant tumor bone metastasis. The main component of Epimedium is icariin (ICA). Studies have shown that ICA inhibits bone resorption of osteoclasts through the OPG/RANKL/RANK signaling pathway. Osteoclasts are the only cells in the body that have a bone-destroying capability. The OPG/RANKL/RANK system consists of cytokines that play major roles in osteoclast formation. Therefore, our study selected the OPG/RANKL/RANK system as the research target to investigate the effect of ICA on nude mice with lung cancer bone metastasis. We established the model of bone metastasis in nude mice, intervened the model with icariin and zoledronic acid, and detected the levels of OPG and RANKL by ELISA and western blot. The results showed that ICA had a significant inhibitory effect on bone metastases in nude mice. ICA achieved its antibone metastasis effect in nude mice with lung cancer via inhibiting RANKL expression and simultaneously increasing OPG expression. ICA not only alleviated osteolytic bone destruction caused by bone metastases, but it also reduced weight loss in tumor-bearing nude mice at the late stage of the experiment. The role of ICA in preventing bone metastasis of lung cancer merits further investigation.
Volumetric Analysis of the Jaws in Skeletal Class I and III Patients with Different Facial Divergence Using CBCT Imaging
Authors: Alhawasli Rama Yasser , Ajaj Mowaffak A , Hajeer Mohammad Younis , Al-Zahabi Assil Mohammad Raef , Mahaini Luai
Published: May 2022

Aim. The main objective was to evaluate any possible maxillary or mandibular volumetric difference between hyperdivergent skeletal Class III (CIII), normodivergent skeletal CIII, hypodivergent skeletal CIII, and normodivergent skeletal Class I (CI) patients using cone-beam computed tomography (CBCT) images. Also, the secondary objective was to investigate any possible correlation between CBCT-derived lateral cephalometric variables and the mandibular and maxillary volumes (MdV and MxV, respectively). Materials and Methods. 80 CBCT images of patients between 18 and 32 years of age were taken with one CBCT imaging device (Scanora 3D®, Soredex, Tuusula, Finland). The sample consisted of four groups: 20 hypodivergent skeletal CIII (11 males and 9 females), 20 normodivergent skeletal CIII (7 males and 13 females), 20 hyperdivergent skeletal CIII (8 males and 12 females), and 20 normodivergent skeletal CI (5 males and 15 females). The volumes of both jaws and the ratio of MxV/MdV were obtained using Mimics™ 19 software (Materialise, NV, Belgium), and 2D variables were obtained from CBCT-derived lateral cephalogram using AudaxCeph™ software (Orthodontic software suite, Ljubljana, Slovenia). One-way ANOVA test and Kruskal–Wallis analysis were employed to detect any possible significant difference between the volumetric variables, whereas Pearson’s and Spearman’s correlation coefficients were calculated to detect any possible relationship between the 2D variables and the volumetric measurements. Results. There were no statistically significant differences in the maxillary volume or maxillary/mandibular ratio between the four groups (

p
=
0.081

and 0.432, respectively). There was a significant difference in MdV between CIII hypodivergent (higher mean) and CIII hyperdivergent (

p
=
0.039

). There were some correlations between the MdV and 2D variables in the four studied groups especially in the posterior facial height (S-Go) and the facial depth (N-Go). There were some weaker correlations between the MxV and some 2D variables in the CIII hypodivergent and hyperdivergent groups. Conclusions. The mandibular volume of the Class III hypodivergent patient was significantly greater than that of the Class III hyperdivergent patients. Correlations between the maxillary or mandibular volumes were found with some of the 2D variables. The volume of both jaws increased when the maxillofacial complex moved toward a horizontal growth pattern.
Vibration Characteristic Analysis of a Coupling System for Compound Biaxial and Inter-Shaft Bearings
Authors: Li Kun , Ding Hongchang , Cao Guohua , Hou Han
Published: May 2022

In order to analyse the system spatial vibration of compound biaxial and inter-shaft bearings during unbalanced excitation, the theory of rotor dynamics and bearing contact deformation are combined to establish a coupling system model of compound biaxial and inter-shaft bearings. Considering the moment of inertia, gyro effect, and structural damping, a one-dimensional beam model is used to perform the MATLAB numerical calculation of the coupling system to obtain the modal characteristics of the system, and based on the ANSYS simulation analysis of the three-dimensional model, a modal test is used to obtain the system modal shape and test frequency response function to verify the rationality of the coupling system model. Based on the Runge-Kutta iterative method and Hamilton’s principle, the nonlinear amplitude-frequency response of the system is calculated while taking into account the influence of the compound biaxial eccentricity, as well as the stiffness and radial clearance of the inter-shaft bearing. The results show that the changes in the eccentricity of the compound biaxial and the structural parameters of the inter-shaft bearing cause the unbalanced excitation of the system, additional external load changes, and different coupled vibrations between the composite compound biaxial and inter-shaft bearings. Therefore, it is reasonable to match the structural parameters of the coupling system and improve the dynamic performance to avoid system resonance.
Consensus of Multi‐Agent Systems with Switching Disconnected Topologies via Elementary‐Unit‐Based Dwell Time Approach
Authors: Sun Jian , Guo Chen , Shan Qihe , Wu Yanming
Published: May 2022

In this study, a leader‐following consensus problem is investigated for a class of multi‐agent systems with switching disconnected topologies. Different from the existing results on switching disconnected topologies, the multi‐agent systems considered in this study are unstable. In this situation, the disconnected agents can disperse over some periods even if there exists control protocol on them. To break through this challenge, we draw lessons from which an appropriate switching law can stabilize the switching unstable systems and propose a novel approach called elementary‐unit‐based dwell time (EUBDT) approach. Based on this approach, each switching interval is considered to consist of a certain number of elementary time segments. Then, by analyzing the local variation of the error states within each elementary time segment, the stabilization properties of switching behaviors are derived to compensate the divergence within the switching intervals. Based on this, the sufficient conditions for the leader‐following consensus can be obtained by using a novel kind of piecewise time‐varying Lyapunov functions (PTVLFs). Moreover, a time‐scheduled controller is designed for such system. Finally, a numerical simulation is given to illustrate the theoretical approach.
The Analysis of Fractional‐Order System Delay Differential Equations Using a Numerical Method
Authors: Sunthrayuth Pongsakorn , Dutt Hina M. , Ghani Fazal , Arefin Mohammad Asif
Published: May 2022

To solve fractional delay differential equation systems, the Laguerre Wavelets Method (LWM) is presented and coupled with the steps method in this article. Caputo fractional derivative is used in the proposed technique. The results show that the current procedure is accurate and reliable. Different nonlinear systems have been solved, and the results have been compared to the exact solution and different methods. Furthermore, it is clear from the figures that the LWM error converges quickly when compared to other approaches. When compared with the exact solution to other approaches, it is clear that LWM is more accurate and gets closer to the exact solution faster. Moreover, on the basis of the novelty and scientific importance, the present method can be extended to solve other nonlinear fractional‐order delay differential equations.
Bonding Performance of CFRP-Steel Interface after Continuous High Temperature
Authors: Gao Tian-Bao , Ma Peng-Xiang , Zhao Guo-Min , Zhang Zhu-Hui , Yao Xiao-Yao
Published: May 2022

The bonded shear performance of CFRP-reinforced steel structures following continuous high-temperature natural cooling was investigated experimentally, and 30 CFRP-steel specimens were subjected to single-shear tensile testing. In analyzing the shear stress-displacement relationship in each working condition, the equation for the coupling effect of the heating temperature and duration on the ultimate shear stress was proposed. The results show that the ultimate shear stress at the CFRP-steel interface tends to decrease with the increase of heating temperature, and the ultimate shear stress at the heating temperature of 300°C is 32.37% of that at 25°C. The high-temperature duration has an obvious influence on the bonding performance of the CFRP-steel interface, and the CFRP-steel specimens fail when the heating temperature is 300°C and lasts for 120 min.