bluuebunny/crossref_metadata_2025 huggingface dataset:
Protection of Environmental and Natural Values of Urban Areas against Investment Pressure: A Case Study of Romania and Poland
Authors: Legutko-Kobus Paulina , Nowak Maciej , Petrisor Alexandru-Ionut , Bărbulescu Dan , Craciun Cerasella , Gârjoabă Atena-Ioana
Published: January 2023

Although conservation and development are two facets of sustainability, they are often placed in contradictory positions. In this context, planning systems are able to respond to investment pressure, especially in countries with underdeveloped institutional solutions for this purpose, and are consequently characterized by a shifting relationship between spatial planning and environmental protection. Although these issues have been relatively well conceptualized, the literature still lacks more in-depth analyses of selected case studies. In order to fill the gap, this study aimed to identify potential ways to protect the environment and natural values in urban areas from investment pressures in countries with less developed planning systems, based on a comparative Polish-Romanian perspective. The method consisted of comparing the national legal frameworks for environmental protection and spatial development and analyzing in detail two case studies from each country. The findings indicate that national protection is required in both countries to ensure the effective protection of natural areas situated within city administrative limits that provide important ecosystem services. Moreover, the results reveal the need for more research on similar areas using multi-scale interdisciplinary approaches and reviewing planning theory with respect to its efficiency in protecting nature.
A Historical-Variationist Analysis of Subject Pronoun Expression in 19th and Early 20th Century Arizonan Spanish
Authors: Cerrón-Palomino Álvaro , Loza Sergio , Vana Rosti
Published: January 2023

This diachronic study is a variationist analysis of subject pronoun expression (SPE) in two key Spanish-language Arizonan newspapers, El Fronterizo (1878–1914) and El Tucsonense (1915–1957), following Tucson’s annexation to the United States through the Gadsden Purchase, a period of great social change during which the Spanish-speaking population in the city underwent a gradual process of anglicization. Since some research on SPE in Spanish in the United States suggests that English-Spanish bilingualism increases the use of overt subject personal pronouns (SPPs) because of their almost categorical use in English, this study’s main aim is to track the initial stages of such progression in a period when social bilingualism was steadily extending in Tucson. In this respect, our results show that the presence of overt SPPs does increase over time in the data analyzed; however, lower rates of overt SPPs in contemporary Tucson and Phoenix spoken Spanish raise the possibility that the percentage surge in the aforementioned period is rather due to the offline written nature of the newspapers, which, for instance, weakens the effect of online constraints, such as switch reference, ambiguous TAM endings, and non-reflexive verbs. Even so, regression analyses with the mixed-effects statistical software Rbrul reveal that the linguistic factor groups shaping SPE in the diachronic data are essentially the same ones found operating in contemporary varieties of Spanish.
Pause Length and Differences in Cognitive State Attribution in Native and Non-Native Speakers
Authors: Matzinger Theresa , Pleyer Michael , Żywiczyński Przemysław
Published: January 2023

Speech pauses between turns of conversations are crucial for assessing conversation partners’ cognitive states, such as their knowledge, confidence and willingness to grant requests; in general, speakers making longer pauses are regarded as less apt and willing. However, it is unclear if the interpretation of pause length is mediated by the accent of interactants, in particular native versus non-native accents. We hypothesized that native listeners are more tolerant towards long pauses made by non-native speakers than those made by native speakers. This is because, in non-native speakers, long pauses might be the result of prolonged cognitive processing when planning an answer in a non-native language rather than of a lack of knowledge, confidence or willingness. Our experiment, in which 100 native Polish-speaking raters rated native and non-native speakers of Polish on their knowledge, confidence and willingness, showed that this hypothesis was confirmed for perceived willingness only; non-native speakers were regarded as equally willing to grant requests, irrespective of their inter-turn pause durations, whereas native speakers making long pauses were regarded as less willing than those making short pauses. For knowledge and confidence, we did not find a mediating effect of accent; both native and non-native speakers were rated as less knowledgeable and confident when making long pauses. One possible reason for the difference between our findings on perceived willingness to grant requests versus perceived knowledge and confidence is that requests might be more socially engaging and more directly relevant for interpersonal cooperative interactions than knowledge that reflects on partners’ competence but not cooperativeness. Overall, our study shows that (non-)native accents can influence which cognitive states are signaled by different pause durations, which may have important implications for intercultural communication settings where topics are negotiated between native and non-native speakers.
A Simplified Method for Inverse Kinematics of a Flexible Panel Continuum Robot for Real-Time Shape Morphing
Authors: Wang Wenbin , Yu Xiangping , Zhao Yinjun , Li Long , Li Yuwen , Tian Yingzhong , Xi Fengfeng
Published: January 2023

Continuum robots are good candidates for shape morphing. However, due to the coupled problem between kinematics and statics, the inverse kinematics of continuum robots is highly nonlinear, posing a challenging problem for real-time applications. This paper presents a simplified approach to solving the inverse kinematics of a flexible panel continuum robot efficiently. Through an experiment, two approximate relationships are discovered. First, the arc length of the middle backbone can be estimated from the arc lengths of the two panels; second, the length difference between the two panels can be related to the tip angle of the end-effector. Based on these two discovered relationships, a simplified inverse kinematics method is proposed based on a constant curvature model. This method has been validated by the experimental data with high accuracy of less than 2% error, thereby demonstrating the effectiveness of the proposed method for real-time applications.
Classification of Wall Following Robot Movements Using Genetic Programming Symbolic Classifier
Authors: Anđelić Nikola , Baressi Šegota Sandi , Glučina Matko , Lorencin Ivan
Published: January 2023

The navigation of mobile robots throughout the surrounding environment without collisions is one of the mandatory behaviors in the field of mobile robotics. The movement of the robot through its surrounding environment is achieved using sensors and a control system. The application of artificial intelligence could potentially predict the possible movement of a mobile robot if a robot encounters potential obstacles. The data used in this paper is obtained from a wall-following robot that navigates through the room following the wall in a clockwise direction with the use of 24 ultrasound sensors. The idea of this paper is to apply genetic programming symbolic classifier (GPSC) with random hyperparameter search and 5-fold cross-validation to investigate if these methods could classify the movement in the correct category (move forward, slight right turn, sharp right turn, and slight left turn) with high accuracy. Since the original dataset is imbalanced, oversampling methods (ADASYN, SMOTE, and BorderlineSMOTE) were applied to achieve the balance between class samples. These over-sampled dataset variations were used to train the GPSC algorithm with a random hyperparameter search and 5-fold cross-validation. The mean and standard deviation of accuracy (ACC), the area under the receiver operating characteristic (AUC), precision, recall, and F1−score values were used to measure the classification performance of the obtained symbolic expressions. The investigation showed that the best symbolic expressions were obtained on a dataset balanced with the BorderlineSMOTE method with ACC¯±SD(ACC), AUC¯macro±SD(AUC), Precision¯macro±SD(Precision), Recall¯macro±SD(Recall), and F1−score¯macro±SD(F1−score) equal to 0.975×1.81×10−3, 0.997±6.37×10−4, 0.975±1.82×10−3, 0.976±1.59×10−3, and 0.9785±1.74×10−3, respectively. The final test was to use the set of best symbolic expressions and apply them to the original dataset. In this case the ACC¯±SD(ACC), AUC¯±SD(AUC), Precision¯±SD(Precision), Recall¯±SD(Recall), and F1−score¯±SD(F1−Score) are equal to 0.956±0.05, 0.9536±0.057, 0.9507±0.0275, 0.9809±0.01, 0.9698±0.00725, respectively. The results of the investigation showed that this simple, non-linearly separable classification task could be solved using the GPSC algorithm with high accuracy.
Efficient Associate Rules Mining Based on Topology for Items of Transactional Data
Authors: Li Bo , Pei Zheng , Zhang Chao , Hao Fei
Published: January 2023

A challenge in association rules’ mining is effectively reducing the time and space complexity in association rules mining with predefined minimum support and confidence thresholds from huge transaction databases. In this paper, we propose an efficient method based on the topology space of the itemset for mining associate rules from transaction databases. To do so, we deduce a binary relation on itemset, and construct a topology space of itemset based on the binary relation and the quotient lattice of the topology according to transactions of itemsets. Furthermore, we prove that all closed itemsets are included in the quotient lattice of the topology, and generators or minimal generators of every closed itemset can be easily obtained from an element of the quotient lattice. Formally, the topology on itemset represents more general associative relationship among items of transaction databases, the quotient lattice of the topology displays the hierarchical structures on all itemsets, and provide us a method to approximate any template of the itemset. Accordingly, we provide efficient algorithms to generate Min-Max association rules or reduce generalized association rules based on the lower approximation and the upper approximation of a template, respectively. The experiment results demonstrate that the proposed method is an alternative and efficient method to generate or reduce association rules from transaction databases.
Object-Aware 3D Scene Reconstruction from Single 2D Images of Indoor Scenes
Authors: Wen Mingyun , Cho Kyungeun
Published: January 2023

Recent studies have shown that deep learning achieves excellent performance in reconstructing 3D scenes from multiview images or videos. However, these reconstructions do not provide the identities of objects, and object identification is necessary for a scene to be functional in virtual reality or interactive applications. The objects in a scene reconstructed as one mesh are treated as a single object, rather than individual entities that can be interacted with or manipulated. Reconstructing an object-aware 3D scene from a single 2D image is challenging because the image conversion process from a 3D scene to a 2D image is irreversible, and the projection from 3D to 2D reduces a dimension. To alleviate the effects of dimension reduction, we proposed a module to generate depth features that can aid the 3D pose estimation of objects. Additionally, we developed a novel approach to mesh reconstruction that combines two decoders that estimate 3D shapes with different shape representations. By leveraging the principles of multitask learning, our approach demonstrated superior performance in generating complete meshes compared to methods relying solely on implicit representation-based mesh reconstruction networks (e.g., local deep implicit functions), as well as producing more accurate shapes compared to previous approaches for mesh reconstruction from single images (e.g., topology modification networks). The proposed method was evaluated on real-world datasets. The results showed that it could effectively improve the object-aware 3D scene reconstruction performance over existing methods.
Traveling Wave Solutions for Complex Space-Time Fractional Kundu-Eckhaus Equation
Authors: Alabedalhadi Mohammed , Shqair Mohammed , Al-Omari Shrideh , Al-Smadi Mohammed
Published: January 2023

In this work, the class of nonlinear complex fractional Kundu-Eckhaus equation is presented with a novel truncated M-fractional derivative. This model is significant and notable in quantum mechanics with good-natured physical characteristics. The motivation for this paper is to construct new solitary and kink wave solutions for the governing equation using the ansatz method. A complex-fractional transformation is applied to convert the fractional Kundu-Eckhaus equation into an ordinary differential equations system. The equilibria of the corresponding dynamical system will be presented to show the existence of traveling wave solutions for the governing model. A novel kink and solitary wave solutions of the governing model are realized by means of the proposed method. In order to gain insight into the underlying dynamics of the obtained solutions, some graphical representations are drawn. For more illustration, several numerical applications are given and analyzed graphically to demonstrate the ability and reliability of the method in dealing with various fractional engineering and physical problems.
Buckling of Coated Functionally Graded Spherical Nanoshells Rested on Orthotropic Elastic Medium
Authors: Abdelhaffez Gamal S. , Daikh Ahmed Amine , Saleem Hussein A. , Eltaher Mohamed A.
Published: January 2023

Coated functionally graded materials (FGMs) are used in several industrial structures such as turbine blades, cutting tools, and aircraft engines. Given the need for analytical and numerical analysis of these complex structures, a mathematical model of tricoated FG structures is presented for the first time in this paper. The objective of this work was to analyze analytically the buckling problem of unidirectional (1D), bidirectional (2D), and tridirectional (3D) coated FG spherical nanoshells resting on an orthotropic elastic foundation subjected to biaxial loads. Based on the generalized field of displacement, a 2D higher-order shear deformation theory was proposed by reducing the number of displacement variables from five to four variables for specific geometry cases. The nonlocal strain gradient theory was employed to capture the size-dependent and microstructure effects. The equilibrium equations were performed by applying the principle of the virtual work, and the obtained differential equations were solved by applying the Galerkin technique to cover all possible boundary conditions. The proposed elastic foundation was defined based on three parameters: one spring constant and two shear parameters referring to the orthotropy directions. A detailed parametric analysis was carried out to highlight the impact of various schemes of coated FGMs, gradient material distribution, length scale parameter (nonlocal), material scale parameter (gradient), geometry of the nanoshell, and variation in the orthotropic elastic foundation on the critical buckling loads.
A Many-Objective Evolutionary Algorithm Based on Indicator and Decomposition
Authors: Xia Yizhang , Huang Jianzun , Li Xijun , Liu Yuan , Zheng Jinhua , Zou Juan
Published: January 2023

In the field of many-objective evolutionary optimization algorithms (MaOEAs), how to maintain the balance between convergence and diversity has been a significant research problem. With the increase of the number of objectives, the number of mutually nondominated solutions increases rapidly, and multi-objective evolutionary optimization algorithms, based on Pareto-dominated relations, become invalid because of the loss of selection pressure in environmental selection. In order to solve this problem, indicator-based many-objective evolutionary algorithms have been proposed; however, they are not good enough at maintaining diversity. Decomposition-based methods have achieved promising performance in keeping diversity. In this paper, we propose a MaOEA based on indicator and decomposition (IDEA) to keep the convergence and diversity simultaneously. Moreover, decomposition-based algorithms do not work well on irregular PFs. To tackle this problem, this paper develops a reference-points adjustment method based on the learning population. Experimental studies of several well-known benchmark problems show that IDEA is very effective compared to ten state-of-the-art many-objective algorithms.
Optimal Selection of Stock Portfolios Using Multi-Criteria Decision-Making Methods
Authors: Jing Dongmei , Imeni Mohsen , Edalatpanah Seyyed Ahmad , Alburaikan Alhanouf , Khalifa Hamiden Abd El-Wahed
Published: January 2023

In the past, investors used their own or others’ experiences to achieve their goals. With the development of financial management, investors’ choices became more scientific. They could select the optimal choice by using different models and combining the results with their experiences. In portfolio optimization, the main issue is the optimal selection of the assets and securities that can be provided with a certain amount of capital. In the present study, the problem of optimization, i.e., maximizing stock portfolio returns and minimizing risk, has been studied. Therefore, this study discussed comprehensive modeling for the optimal selection of stock portfolios using multi-criteria decision-making methods in companies listed on the Tehran Stock Exchange. A sample of 79 companies listed on the Tehran Stock Exchange was used to conduct this research. After simulating the data and programming them with MATLAB software, the cumulative data analysis model was performed, and 24 companies were selected. This research data were collected from the financial statements of companies listed on the Tehran Stock Exchange in 2020. The primary purpose of this study was a comprehensive modeling for the optimal selection of stock portfolios using multi-criteria decision-making methods in companies listed on the Tehran Stock Exchange. The index in the Tehran Stock Exchange can be used to provide a comprehensive and optimal model for the stock portfolio; different multi-index decision-making methods (TOPSIS method), the taxonomy method (Taxonomy), ARAS method, VIKOR method, The COPRAS method and the WASPAS method can all identify the optimal stock portfolio and the best stock portfolio for the highest return.
Observer-Based PID Control Protocol of Positive Multi-Agent Systems
Authors: Yang Xiaogang , Huang Mengxing , Wu Yuanyuan , Feng Siling
Published: January 2023

This paper proposes the observer-based proportional-integral-derivative control of positive multi-agent systems. First, a positive observer is constructed for the considered multi-agent systems in terms of a matrix decomposition approach. Then, a novel proportional-integral-derivative protocol framework is proposed based on an improved observer. By using copositive Lyapunov function, the positivity and consensus of the multi-agent systems are achieved. The corresponding observer and control protocol gain matrices are designed in terms of linear programming. Moreover, the proposed design is developed for heterogeneous positive multi-agent systems. The main contributions of this paper include the following: (i) A positive observer is constructed to estimate the states of positive multi-agent systems; (ii) A novel observer-based proportional-integral-derivative protocol is designed to handle the consensus problem of positive multi-agent systems; and (iii) The presented conditions are solvable in terms of linear programming and the gain matrices can be constructed based on a matrix decomposition technology. Finally, two illustrative examples are provided to verify the effectiveness of the design.
A Dynamical Model with Time Delay for Risk Contagion
Authors: Aliano Mauro , Cananà Lucianna , Cestari Greta , Ragni Stefania
Published: January 2023

The explanation of risk contagion among economic players—not only in financial crises—and how they spread across the world has fascinated scholars and scientists in the last few decades. Inspired by the literature dealing with the analogy between financial systems and ecosystems, we model risk contagion by revisiting the mathematical approach of epidemiological models for infectious disease spread in a new paradigm. We propose a time delay differential system describing risk diffusion among companies inside an economic sector by means of a SIR dynamics. Contagion is modelled in terms of credit and financial risks with low and high levels. A complete theoretical analysis of the problem is carried out: well-posedness and solution positivity are proven. The existence of a risk-free steady state together with an endemic equilibrium is verified. Global asymptotic stability is investigated for both equilibria by the classical Lyapunov functional theory. The model is tested on a case study of some companies operating in the food economic sector in a specific Italian region. The analysis allows for understanding the crucial role of both incubation time and financial immunity period in the asymptotic behaviour of any solution in terms of endemic permanence of risk rather than its disappearance.
High Resolution Spatio-Temporal Model for Room-Level Airborne Pandemic Spread
Authors: Lazebnik Teddy , Alexi Ariel
Published: January 2023

Airborne pandemics have caused millions of deaths worldwide, large-scale economic losses, and catastrophic sociological shifts in human history. Researchers have developed multiple mathematical models and computational frameworks to investigate and predict pandemic spread on various levels and scales such as countries, cities, large social events, and even buildings. However, attempts of modeling airborne pandemic dynamics on the smallest scale, a single room, have been mostly neglected. As time indoors increases due to global urbanization processes, more infections occur in shared rooms. In this study, a high-resolution spatio-temporal epidemiological model with airflow dynamics to evaluate airborne pandemic spread is proposed. The model is implemented, using Python, with high-resolution 3D data obtained from a light detection and ranging (LiDAR) device and computing model based on the Computational Fluid Dynamics (CFD) model for the airflow and the Susceptible–Exposed–Infected (SEI) model for the epidemiological dynamics. The pandemic spread is evaluated in four types of rooms, showing significant differences even for a short exposure duration. We show that the room’s topology and individual distribution in the room define the ability of air ventilation to reduce pandemic spread throughout breathing zone infection.
Influence of Aortic Valve Leaflet Material Model on Hemodynamic Features in Healthy and Pathological States
Authors: Pil Nikita , Kuchumov Alex G. , Kadyraliev Bakytbek , Arutunyan Vagram
Published: January 2023

Long-term fiber tissue remodeling and the progressive thickening of the aortic valve leaflets called calcific aortic stenosis lead to cardiac blood outflow obstruction. This disease is the most prevalent heart valve pathology in developed countries. Surgeons can perform aortic valve replacement through traditional open-heart surgery involving a cut (incision) in the chest or use minimally invasive methods such as transcatheter aortic valve implantation (TAVI). These types of surgery have numerous advantages and limitations. Recently, the Ozaki operation for aortic valve replacement using tissue from the autologous pericardium has been proposed. Despite being a promising technique for aortic valve pathology treatment, there is a lack of long-term results and optimal selection of leaflet sizing. Numerical fluid simulations can help surgeons predict operation outcomes for each patient. Nevertheless, the description of the material model for leaflet mechanics leaves an open question. Furthermore, selecting the most suitable model to describe the different conditions of the aortic valve is difficult. We performed a numerical analysis of aortic valve leaflet material models to describe the hemodynamics in normal, pathological, and Ozaki cases. We also reveal wall shear stress, von Mises stress, and displacement distributions. Based on the parameters mentioned above, we found that the Ozaki case model behaved similarly to the mathematical model describing the normal case. Numerical simulations also provide information on the mechanisms of aortic valve work in different states of the heart cycle.
A Surgical Challenge Generated by Colonic Malakoplakia in Disguise as a Locally Advanced Colonic Malignancy—A Case Report
Authors: Șerban Cristina , Toma Alexandra , Voicu Dragoș Cristian , Popazu Constantin , Firescu Dorel , Țocu George , Mihailov Raul , Rebegea Laura
Published: January 2023

Colonic malakoplakia is an uncommon granulomatous development of cells resulting from the impaired capacity of the mononuclear cells to eliminate the phagocytosed bacteria, and in rare cases it can also affect the gastrointestinal tract. We report the case of a 78-year-old female patient that was admitted to hospital by The Emergency Department with the diagnosis of bowel obstruction, confirmed by the clinical and paraclinical investigations. We decided to surgically manage the case for suspicious symptomatic colonic neoplasm. The histological examination of the surgical specimens revealed colonic malakoplakia, characterized by the presence of the aggregated granular histiocytes and Michaelis-Gutmann bodies. Through this paper, we want to raise awareness for Malakoplakia, which remains an extremely rare disease that may affect multiple organs, and because it does not present specific symptoms or clinical manifestations, the final diagnosis remains the histopathological study. The clinical conduct should be decided after taking into consideration all the aspects of this pathology along with the benefits and risks for the patient.
Numerical Simulation of the Donor-Assisted Stir Material for Friction Stir Welding of Aluminum Alloys and Carbon Steel
Authors: Maniscalco Joseph , Elmustafa Abdelmageed A. , Bhukya Srinivasa , Wu Zhenhua
Published: January 2023

In this research effort, we explore the use of a donor material to help heat workpieces without wearing the tool or adding more heat than necessary to the system. The donor material would typically be a small piece (or pieces) of material, presumably of lower strength than the workpiece but with a comparable melting point. The donor, a sandwich material, is positioned between the tool head and the material to be welded, where the tool initially plunges and heats up in the same manner as the parent material that is intended for welding. The donor material heats up subsequent to tool penetration due to friction and as a result heats up the material beneath it. This preheating technique softens the harder parent material, which helps to minimize tool wear and produce better weld performance. The goal is to investigate the use of the donor material as a preheating technique that minimizes wear and tear on the tool head without negatively impacting the structural properties of the weld. To demonstrate the donor material concept, a combination of Cu-Al, Cu-1045 Carbon steel (CS), and Al-1045 CS sets of donor and parent materials were used in the simulation, in addition to control samples Al-Al and CS-CS. We simulated two thicknesses of donor material 25 and 50% of the parent material thickness, respectively. The simulation suggests that the donor material concept generates phenomenal results by reducing the temperature and axial forces for the friction stir welding of aluminum AA6061 and carbon steel 1045. It also assists downstream during welding, resulting from frictional mechanical work which is converted into stored heat.
Proteotyping of Campylobacter jejuni by MALDI-TOF MS and Strain Solution Version 2 Software
Authors: Ojima-Kato Teruyo , Nagai Satomi , Fujita Akane , Sakata Junko , Tamura Hiroto
Published: January 2023

Identification of microorganisms by MALDI-TOF MS has become a popular method in the past 20 years. Strain Solution ver. 2 software appended with MALDI-TOF MS enables accurate discrimination of serotypes and strains beyond the genus and species level by creating a theoretical mass-based database. In this study, we constructed a theoretical mass database with the validated biomarkers to proteotype Campylobacter jejuni. Using 10 strains belonging to Campylobacter spp. available from culture collections and 41 Campylobacter jejuni strains isolated from humans and foods, the ribosomal protein subunits L36, L32, S14, L24, L23, L7/L12, and S11 could be selected as the effective biomarkers for the proteotyping of C. jejuni at MALDI-TOF MS. An accurate database of their theoretical mass-based values was constructed by matching these gene DNA sequences and the observed mass peaks. We attempted to automatically classify 41 strains isolated from nature using this database and Strain Solution ver. 2 software, and 38 strains (93%) were correctly classified into the intended group based on the theoretical mass-based values. Thus, the seven biomarkers found in this study and Strain Solution ver. 2 are promising for the proteotyping of C. jejuni by MALDI-TOF MS.
Binary Diffusion Coefficients for Short Chain Alcohols in Supercritical Carbon Dioxide—Experimental and Predictive Correlations
Authors: Santos Cecília I. A. V. , Ribeiro Ana C. F. , Shevtsova Valentina
Published: January 2023

Experimental binary diffusion coefficients for short-chain alcohols in supercritical carbon dioxide were measured using the Taylor dispersion technique in a temperature range of 306.15 K to 331.15 K and along the 10.5 MPa isobar. The obtained diffusion coefficients were in the order of 10−8 m2 s−1. The dependence of D on temperature and solvent density was examined together with the influence of molecular size. Some classic correlation models based on the hydrodynamic and free volume theory were used to estimate the diffusion coefficients in supercritical carbon dioxide. Predicted values were generally overestimated in comparison with experimental ones and correlations were shown to be valid only in high-density regions.
Synthesis Routes on Electrochemical Behavior of Co-Free Layered LiNi0.5Mn0.5O2 Cathode for Li-Ion Batteries
Authors: Tsai Shu-Yi , Fung Kuan-Zong
Published: January 2023

Co-free layered LiNi0.5Mn0.5O2 has received considerable attention due to high theoretical capacity (280 mAh g−1) and low cost comparable than LiCoO2. The ability of nickel to be oxidized (Ni2+/Ni3+/Ni4+) acts as electrochemical active and has a low activation energy barrier, while the stability of Mn4+ provides a stable host structure. However, selection of appropriate preparation method and condition are critical to providing an ideal layered structure of LiNi0.5Mn0.5O2 with good electrochemical performance. In this study, Layered LiNi0.5Mn0.5O2 has been synthesized by sol-gel and solid-state routes. According to the XRD, the sol-gel method provides a pure phase, and solid-state process only minimize the secondary phases to certain limit. The Ni2+/Mn4+ content in the sol-gel process was higher than in the solid-state reaction, which may be due to the chemical composition homogeneity of the sol-gel samples. Regarding the electrochemical behavior, sol-gel process is better than solid-state reaction. The discharge capacity is 145 mAh/g and 91 mAh/g for the sol-gel process and solid-state reaction samples, respectively.
Active Self-Assembly of Ladder-Shaped DNA Carrier for Drug Delivery
Authors: Liu Yuan , Wang Jiaxin , Sun Lijun , Wang Bin , Zhang Qiang , Zhang Xiaokang , Cao Ben
Published: January 2023

With the advent of nanotechnology, DNA molecules have been transformed from solely genetic information carriers to multifunctional materials, showing a tremendous potential for drug delivery and disease diagnosis. In drug delivery systems, DNA is used as a building material to construct drug carriers through a variety of DNA self-assembly methods, which can integrate multiple functions to complete in vivo and in situ tasks. In this study, ladder-shaped drug carriers are developed for drug delivery on the basis of a DNA nanoladder. We first demonstrate the overall structure of the nanoladder, in which a nick is added into each rung of the nanoladder to endow the nanoladder with the ability to incorporate a drug loading site. The structure is designed to counteract the decrement of stability caused by the nick and investigated in different conditions to gain insight into the properties of the nicked DNA nanoladders. As a proof of concept, we fix the biotin in every other nick as a loading site and assemble the protein (streptavidin) on the loading site to demonstrate the feasibility of the drug-carrying function. The protein can be fixed stably and can be extended to different biological and chemical drugs by altering the drug loading site. We believe this design approach will be a novel addition to the toolbox of DNA nanotechnology, and it will be useful for versatile applications such as in bioimaging, biosensing, and targeted therapy.
Chemometric Approach Based on Explainable AI for Rapid Assessment of Macronutrients in Different Organic Fertilizers Using Fusion Spectra
Authors: Guindo Mahamed Lamine , Kabir Muhammad Hilal , Chen Rongqin , Huang Jing , Liu Fei , Li Xiaolong , Fang Hui
Published: January 2023

Wet chemical methods are usually employed in the analysis of macronutrients such as Potassium (K) and Phosphorus (P) and followed by traditional sensor techniques, including inductively coupled plasma optical emission spectrometry (ICP OES), flame atomic absorption spectrometry (FAAS), graphite furnace atomic absorption spectrometry (GF AAS), and inductively coupled plasma mass spectrometry (ICP-MS). Although these procedures have been established for many years, they are costly, time-consuming, and challenging to follow. This study studied the combination of laser-induced breakdown spectroscopy (LIBS) and visible and near-infrared spectroscopy (Vis-NIR) for the quick detection of PK in different varieties of organic fertilizers. Explainable AI (XAI) through Shapley additive explanation values computation (Shap values) was used to extract the valuable features of both sensors. The characteristic variables from different spectroscopic devices were combined to form the spectra fusion. Then, PK was determined using Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), and Extremely Randomized Trees (Extratrees) models. The computation of the coefficient of determination (R2), root mean squared error (RMSE), and residual prediction deviation (RPD) showed that FUSION was more efficient in detecting P (R2p = 0.9946, RMSEp = 0.0649% and RPD = 13.26) and K (R2p = 0.9976, RMSEp = 0.0508% and RPD = 20.28) than single-sensor detection. The outcomes indicated that the features extracted by XAI and the data fusion of LIBS and Vis-NIR could improve the prediction of PK in different varieties of organic fertilizers.
Sinomenine Hydrochloride Can Ameliorate Benign Prostatic Hyperplasia by Lowering the 5α-Reductase 2 Level and Regulating the Balance between the Proliferation and Apoptosis of Cells
Authors: Fan Mao-Si , Xia Yue-Fei , Ye Rui-Han , Sun Ze-Rui , Wang Ming-Yue , An Meng-Fei , Zhang Shao-Shi , Zhang Li-Juan , Zhao Yun-Li , Xiang Ze-Min , Sheng Jun
Published: January 2023

Benign prostatic hyperplasia (BPH) is a chronic disease that affects the quality of life of older males. Sinomenine hydrochloride (SIN) is the major bioactive alkaloid isolated from the roots of the traditional Chinese medicinal plant Sinomenium acutum Rehderett Wilson. We wondered if the SIN administration exerted a regulatory effect on BPH and its potential mechanism of action. Mice with testosterone propionate-induced BPH subjected to bilateral orchiectomy were employed for in vivo experiments. A human BPH cell line (BPH-1) was employed for in vitro experiments. SIN administration inhibited the proliferation of BPH-1 cells (p < 0.05) by regulating the expression of androgen-related proteins (steroid 5-alpha reductase 2 (SRD5A2), androgen receptors, prostate-specific antigen), apoptosis-related proteins (B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax)) and proliferation-related proteins (proliferating cell nuclear antigen (PCNA), mammalian target of rapamycin, inducible nitric oxide synthase) in vitro. SIN administration decreased the prostate-gland weight coefficient (p < 0.05) and improved the histological status of mice suffering from BPH. The regulatory effects of SIN administration on SRD5A2, an apoptosis-related protein (Bcl-2), and proliferation-related proteins (PCNA, matrix metalloproteinase-2) were consistent with in vitro data. SIN exerted a therapeutic effect against BPH probably related to lowering the SRD5A2 level and regulating the balance between the proliferation and apoptosis of cells. Our results provide an important theoretical basis for the development of plant medicines for BPH therapy.
Green Synthesis of Silver Nanoparticles Using Salvia verticillata and Filipendula ulmaria Extracts: Optimization of Synthesis, Biological Activities, and Catalytic Properties
Authors: Mihailović Vladimir , Srećković Nikola , Nedić Zoran P. , Dimitrijević Silvana , Matić Miloš , Obradović Ana , Selaković Dragica , Rosić Gvozden , Katanić Stanković Jelena S.
Published: January 2023

The study’s objective was to obtain silver nanoparticles (SVAgNP and FUAgNP) using aqueous extracts of Salvia verticillata and Filipendula ulmaria. The optimal conditions for nanoparticle synthesis were determined and obtained; nanoparticles were then characterized using UV-Vis, Fourier-transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), Dynamic Light Scattering (DLS), Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM/EDS). SVAgNP and FUAgNP possessed a crystalline structure with 48.42% and 60.41% silver weight, respectively. The highest percentage of nanoparticles in the solution had a diameter between 40 and 70 nm. In DPPH˙ and ABTS˙+ methods, FUAgNP (IC50 15.82 and 59.85 µg/mL, respectively) demonstrated a higher antioxidant capacity than SVAgNP (IC50 73.47 and 79.49 µg/mL, respectively). Obtained nanoparticles also showed pronounced antibacterial activity (MIC ˂ 39.1 µg/mL for most of the tested bacteria), as well as high biocompatibility with the human fibroblast cell line MRC-5 and significant cytotoxicity on some cancer cell lines, especially on the human colon cancer HCT-116 cells (IC50 31.50 and 66.51 µg/mL for SVAgNP and FUAgNP, respectively). The nanoparticles demonstrated high catalytic effectiveness in degrading Congo red dye with NaBH4. The results showed a rapid and low-cost methodology for the synthesis of AgNPs using S. verticillata and F. ulmaria with promising biological potential.
Enhanced Performance of Flexible Organic Photovoltaics Based on MoS2 Micro-Nano Array
Authors: Peng Cuiyun , Ling Zhitian , Qu Minghao , Cao Chenhui , Chen Guo , Shi Wei , Wei Bin
Published: January 2023

In this work, we investigated the influence of MoS2 functioning as an electron transport layer (ETL) on the inverted flexible organic photovoltaics (FOPVs). Three ETLs, including MoS2, lithium quinolate (Liq), and a MoS2/Liq bilayer, were evaporated onto ITO-integrated polyethylene terephthalate substrates (PET-ITO), and the properties of transmittance, water contact angle, and reflectivity of the films were analyzed. The results revealed that MoS2 was helpful to improve the lipophilicity of the surface of the ETL, which was conducive to the deposition of the active layer. In addition, the reflectivity of MoS2 to the light ranging from 400 to 600 nm was the largest among the pristine PET-ITO substrate and the PET-ITO coated with three ETLs, which promoted the efficient use of the light. The efficiency of the FOPV with MoS2/Liq ETL was 73% higher than that of the pristine device. This was attributed to the nearly two-fold amplification of the MoS2 array to the light field, which promoted the FOPV to absorb more light. Moreover, the efficiency of the FOPV with MoS2 was maintained under different illumination angles and bending angles. The results demonstrate the promising applications of MoS2 in the fabrication of FOPVs.
The Expanded Vermiculite Was Quickly Prepared by the Catalytic Action of Manganese Dioxide on Hydrogen Peroxide and Its Adsorption Properties to Cd
Authors: Chen Yunzhu , Sun Hongjuan , Peng Tongjiang , Gao Tongxi , Ding Wenjin , Hui Tao , Jiang Lei
Published: January 2023

The structure and activity of vermiculite can be maintained by expanding vermiculite (Vrm) with hydrogen peroxide. However, it is time-consuming. In past studies, little attention has been paid to the catalytic properties of manganese dioxide on hydrogen peroxide to improve the swelling efficiency of vermiculite. In this experiment, this catalytic effect was utilized to swell Vrm in a short time. The samples were then used to adsorb Cd from the solution. Through a series of characterization tests. The results showed that the exothermic rate was 1960.42–2089.164 J/min and the total exothermic heat was 39,208.4–41,783.28 J when expanding 10 gVrm, which could have a good expansion effect. The expansion was completed in about 40 min. Compared with Vrm, the adsorption of Cd is enhanced by about 30%. It is consistent with the proposed secondary kinetic adsorption model. This study provides a new perspective and theoretical guidance for improving the efficiency of Vrm stripping by hydrogen peroxide. A kind of expanded Vrm with better Cd adsorption efficiency was also prepared.
Efficient Elimination of Viruses from Garlic Using a Combination of Shoot Meristem Culture, Thermotherapy, and Chemical Treatment
Authors: Benke Ashwini Prashant , Krishna Ram , Khandagale Kiran , Gawande Suresh , Shelke Poonam , Dukare Somnath , Dhumal Sweta , Singh Major , Mahajan Vijay
Published: January 2023

Garlic (Allium sativum L.) is a clonally propagated bulbous crop and can be infected by several viruses under field conditions. A virus complex reduces garlic yield and deteriorates the quality of the produce. In the present study, we aimed to eliminate Onion yellow dwarf virus (OYDV), Garlic common latent virus (GCLV), Shallot latent virus (SLV), and Allexiviruses from the infected crop using combination of meristem culture, thermotherapy, and chemotherapy. In this study, seven different treatments, namely shoot meristem culture, thermotherapy direct culture, chemotherapy direct culture, chemotherapy + meristem culture, thermotherapy + meristem culture, thermotherapy + chemotherapy direct culture, and thermotherapy + chemotherapy + meristem culture (TCMC), were used. Multiplex polymerase chain reaction (PCR) was employed to detect virus elimination, which revealed the percentage of virus-free plants was between 65 and 100%, 55 and 100%, and 13 and 100% in the case of GCLV, SLV, and OYDV, respectively. The in vitro regeneration efficiency was between 66.06 and 98.98%. However, the elimination of Allexiviruses could not be achieved. TCMC was the most effective treatment for eliminating GCLV, SLV, and OYDV from garlic, with 66.06% plant regeneration efficiency. The viral titre of the Allexivirus under all the treatments was monitored using real-time PCR, and the lowest viral load was observed in the TCMC treatment. The present study is the first to report the complete removal of GCLV, SLV, and OYDV from Indian red garlic with the application of thermotherapy coupled with chemotherapy and shoot meristem culture.
Impact of Different Attitudes toward Face-to-Face and Online Classes on Learning Outcomes in Japan
Authors: Aoe Mai , Esaki Seiji , Ikejiri Masahiro , Ito Takuya , Nagai Katsuhito , Hatsuda Yasutoshi , Hirokawa Yoshimi , Yasuhara Tomohisa , Kenzaka Takehiko , Nishinaka Toru
Published: January 2023

During the coronavirus disease 2019 (COVID-19) pandemic, online-based learning has become mainstream in many countries, and its learning outcomes have been evaluated. However, various studies have shown that online-based learning needs to be optimized in the future, and the number of reports for this purpose is currently not sufficient. The purpose in this study was to determine the relationship between academic performance and attitudes toward face-to-face and remote formats among Japanese pharmacy students enrolled in a course designed for knowledge acquisition. A combination of face-to-face and remote formats was used in a practice course for sixth-year pharmacy students, designed to improve academic performance through knowledge acquisition. To evaluate learning outcomes, we used a questionnaire that was administered to the course participants and the results of examinations conducted before and after the course. Online-oriented and face-to-face-oriented groups differed in their attitudes toward the ease of asking questions of faculty and communicating with the faculty members and classmates in each format. In a knowledge acquisition course for Japanese pharmacy students, the study revealed that the same academic outcomes were achieved, regardless of the students’ own perceptions of their aptitude for face-to-face or remote learning style.
Turing’s Biological Philosophy: Morphogenesis, Mechanisms and Organicism
Authors: Greif Hajo , Kubiak Adam , Stacewicz Paweł
Published: January 2023

Alan M. Turing’s last published work and some posthumously published manuscripts were dedicated to the development of his theory of organic pattern formation. In “The Chemical Basis of Morphogenesis” (1952), he provided an elaborated mathematical formulation of the theory of the origins of biological form that had been first proposed by Sir D’Arcy Wendworth Thompson in On Growth and Form (1917/1942). While arguably his most mathematically detailed and his systematically most ambitious effort, Turing’s morphogenetical writings also form the most thematically self-contained and least philosophically explored part of his work. We dedicate our inquiry to the reasons and the implications of Turing’s choice of biological topic and viewpoint. We will probe for possible factors in Turing’s choice that go beyond availability and acquaintance with On Growth and Form. On these grounds, we will explore how and to what extent his theory of morphogenesis actually ties in with his concept of mechanistic computation. Notably, Thompson’s pioneering work in biological ‘structuralism’ was organicist in outlook and explicitly critical of the Darwinian approaches that were popular with Turing’s cyberneticist contemporaries—and partly used by Turing himself in his proto-connectionist models of learning. Resolving this apparent dichotomy, we demonstrate how Turing’s quest for mechanistic explanations of how organisation emerges in nature leaves room for a non-mechanist view of nature.