bluuebunny/crossref_metadata_2025 huggingface dataset:
An Ensemble Feature Selection Approach for Analysis and Modeling of Transcriptome Data in Alzheimer’s Disease
Authors: Paplomatas Petros , Krokidis Marios G. , Vlamos Panagiotis , Vrahatis Aristidis G.
Published: February 2023

Data-driven analysis and characterization of molecular phenotypes comprises an efficient way to decipher complex disease mechanisms. Using emerging next generation sequencing technologies, important disease-relevant outcomes are extracted, offering the potential for precision diagnosis and therapeutics in progressive disorders. Single-cell RNA sequencing (scRNA-seq) allows the inherent heterogeneity between individual cellular environments to be exploited and provides one of the most promising platforms for quantifying cell-to-cell gene expression variability. However, the high-dimensional nature of scRNA-seq data poses a significant challenge for downstream analysis, particularly in identifying genes that are dominant across cell populations. Feature selection is a crucial step in scRNA-seq data analysis, reducing the dimensionality of data and facilitating the identification of genes most relevant to the biological question. Herein, we present a need for an ensemble feature selection methodology for scRNA-seq data, specifically in the context of Alzheimer’s disease (AD). We combined various feature selection strategies to obtain the most dominant differentially expressed genes (DEGs) in an AD scRNA-seq dataset, providing a promising approach to identify potential transcriptome biomarkers through scRNA-seq data analysis, which can be applied to other diseases. We anticipate that feature selection techniques, such as our ensemble methodology, will dominate analysis options for transcriptome data, especially as datasets increase in volume and complexity, leading to more accurate classification and the generation of differentially significant features.
The Stationary Thermal Field in a Multilayer Elliptic Cylinder
Authors: Gołębiowski Jerzy , Zaręba Marek
Published: February 2023

An analytical–numerical method for determining the two-dimensional (2D) thermal field in a layer-inhomogeneous elliptic cylinder (elliptical roller) was developed in the article. A mathematical model was formulated in the form of a boundary problem for Poisson equations with an external boundary condition of the third kind (Hankel’s). The conditions of continuity of temperature and heat flux increment were assumed at the inner boundaries of material layers. The eigenfunctions of the boundary problem were determined analytically. Hankel’s condition was subjected to appropriate mathematical transformations. As a result, a system of algebraic equations with respect to the unknown coefficients of the eigenfunctions was obtained. The above-mentioned system of equations was solved numerically (iteratively). As an example of an application of the aforementioned method, an analysis of the thermal field in an elliptical electric wire was presented. The system consists of an aluminum core and two layers of insulation (PVC and rubber). In addition to the field distribution, the steady-state current rating was also determined. The thermal conductivities of PVC and rubber are very similar to each other. For this reason, apart from the real model, a test system was also considered. Significantly different values of thermal conductivity were assumed in individual layers of the test model. The temperature distributions were presented graphically. The graphs showed that the temperature drop is almost linear in the insulation of an electrical conductor. On the other hand, in the analogous area of the test model, a broken line was observed. It was also found that the elliptical layer boundaries are not isothermal. The results obtained by the method presented in this paper were verified numerically.
Improvement in Runtime Speed for Frequency Domain Soil–Structure Interaction Analysis Using a Coarray Parallel Processing Technique
Authors: Kim Jae-Min , Lim Jae-Sung , Lee Hyeok-Ju
Published: February 2023

In this paper, we propose a new algorithm for introducing Coarray Fortran (CAF) into a program that dynamically analyzes the frequency domain in soil–structure interactions. This was implemented in KIESSI-3D, which is frequency domain soil-structure interaction analysis computer code based on finite and infinite element techniques, and the performance of analysis speed based on the number of images (or coarrays) and cores per image was evaluated. For the performance evaluation, we used examples of full-scale nuclear power plant buildings with a shallow foundation model as well as a deep foundation model. In terms of analysis speed, the new KIESSI-3D improved the analysis speed by an average of 2.78 times for the shallow foundation problem and 2.69 times for the deep foundation problem, compared with the existing KIESSI-3D, because of the new algorithm and CAF. Further, as the number of cores and the internal memory size in the computer systems increased, the efficiency of also parallel processing increased.
Archaeoacoustics around the World: A Literature Review (2016–2022)
Authors: Navas-Reascos Gustavo , Alonso-Valerdi Luz M. , Ibarra-Zarate David I.
Published: February 2023

Acoustics has been integrated with archaeology to better understand the social and cultural context of past cultures. Specifically, public events such as rituals or ceremonies, where an appreciation of sound propagation was required to hold an event. Various acoustic techniques have been used to study archaeological sites, providing information about the building characteristics and organizational structures of ancient civilizations. This review aims to present recent advances in Archaeoacoustics worldwide over the last seven years (2016–2022). For this purpose, one hundred and five articles were identified and categorized into two topics: (1) Archaeoacoustics in places, and (2) Archaeoacoustics of musical instruments and pieces. In the first topic, three subtopics were identified: (1) measurement and characterization of places, (2) rock art, and (3) simulation, auralization, and virtualization. Regarding the first subtopic, it was identified that the standards for reverberation times in enclosures are generally applied in their development. In the second subtopic, it was determined that the places selected to make paintings were areas with long reverberation time. The last subtopic, simulation, auralization, and virtualization, is the area of most remarkable growth and innovation. Finally, this review opens the debate to seek standardization of a measurement method that allows comparing results from different investigations.
The Effect of the Texture of Two Energy Bars on the Oral Processing of Cyclists: An Exploratory Study
Authors: Jimenez-Perez Irene , Aladro-Gonzalvo Arian Ramón , Vera Morán Antonio , Camacho-García Andrés , Encarnación-Martínez Alberto , Pérez-Soriano Pedro
Published: February 2023

In cycling, a wide range of ergogenic foods with a variety of flavours, shapes, and textures are available. The timing of their consumption and their correct oral processing can influence the performance of athletes. Furthermore, the differences in the texture of energy bars could result in differences in the chewing required. Nonetheless, research in this area is still scarce. The aim of this study was to analyse how the consumption of two energy bars with different textures (viscous versus hard) influenced the variables of oral processing, pedalling intensity, and the perception of satisfaction among cyclists. Ten cyclists performed two 15 min sections on a cycle ergometer at a moderate intensity (120–130 W) and consumed one of the two energy bars at random in each of the sections. The results showed that a shorter chewing duration and a fewer number of chews were required to consume the softer bar (p < 0.05, ES > 0.7). However, no differences among the cyclists were observed in the intensity of pedalling or perception of satisfaction. Nevertheless, participants were able to distinguish between the two different textures while pedalling. In conclusion, the texture of energy bars altered the oral processing of cyclists but did not affect pedalling intensity or perception of satisfaction.
Hydrodynamics and Musculature Actuation of Fish during a Fast Start
Authors: Li Yuhan , Song Jialei , Yin Ling , Jin Bowen , Yin Bo , Zhong Yong
Published: February 2023

The fast start of fish is a rapid event that involves fast actuation in musculature and highly unsteady hydrodynamics. Fast-start capability is of great significance for fish to either hunt prey or escape from predators. In this study, we used a three-dimensional CFD model to study the hydrodynamics of a crucian carp during a C-type fast start. This study confirms the previous observations from both experiments and simulations that the jets are induced by the fast start for force generation, and the vortex rings generated in both the preparation and propulsion stages connect to each other. In addition, an obvious vortex ring generated by the head during the propulsion stage was observed, which potentially benefits the rotational motion during the fast start. According to the hydrodynamic information from CFD modeling, we established a model to analyze the internal torque, which represents the muscular actuation. The backward traveling speed of internal torque is 1.56 times the curvature speed, which confirms the existence of neuromechanical phase lag during the fast start of fish. This study potentially benefits the design of robot fish in terms of kinematics and driving mode.
Radial Point Interpolation-Based Error Recovery Estimates for Finite Element Solutions of Incompressible Elastic Problems
Authors: Kahla Nabil Ben , AlQadhi Saeed , Ahmed Mohd.
Published: February 2023

Error estimation and adaptive applications help to control the discretization errors in finite element analysis. The study implements the radial point interpolation (RPI)-based error-recovery approaches in finite element analysis. The displacement/pressure-based mixed approach is used in finite element formulation. The RPI approach considers the radial basis functions (RBF) and polynomials basis functions together to interpolate the finite element solutions, i.e., displacement over influence zones to recover the solution errors. The energy norm is used to represent global and local errors. The reliability and effectiveness of RPI-based error-recovery approaches are assessed by adaptive analysis of incompressibility elastic problems including the problem with singularity. The quadrilateral meshes are used for discretization of problem domains. For adaptive improvement of mesh, the square of error equally distributed technique is employed. The computational outcome for solution errors, i.e., error distribution and convergence rate, are obtained for RPI technique-based error-recovery approach employing different radial basis functions (multi quadratic, thin-plate splint), RBF shape parameters, different shapes of influence zones (circular, rectangular) and conventional patches. The error convergence in the original FEM solution, in FEM solution considering influence-zone-based RPI recovery with MQ RBF, conventional patch-based RPI recovery with MQ RBF and conventional patch LS-based error recovery are found as (0.97772, 2.03291, 1.97929 and 1.6740), respectively, for four-node quadrilateral discretization of problem, while for nine-node quadrilateral discretization, the error convergence is (1.99607, 3.53087, 4.26621 and 2.54955), respectively. The study concludes that the adaptive analysis, using error-recovery estimates-based RPI approach, provides results with excellent accuracy and reliability.
Improvement of Concrete Crack Segmentation Performance Using Stacking Ensemble Learning
Authors: Lee Taehee , Kim Jung-Ho , Lee Sung-Jin , Ryu Seung-Ki , Joo Bong-Chul
Published: February 2023

Signs of functional loss due to the deterioration of structures are primarily identified from cracks occurring on the surface of structures, and continuous monitoring of structural cracks is essential for socially important structures. Recently, many structural crack monitoring technologies have been developed with the development of deep-learning artificial intelligence (AI). In this study, stacking ensemble learning was applied to predict the structural cracks more precisely. A semantic segmentation model was primarily used for crack detection using a deep learning AI model. We studied the crack-detection performance by training UNet, DeepLabV3, DeepLabV3+, DANet, and FCN-8s. Owing to the unsuitable crack segmentation performance of the FCN-8s, stacking ensemble learning was conducted with the remaining four models. Individual models yielded an intersection over union (IoU) score ranging from approximately 0.4 to 0.6 for the test dataset. However, when the metamodel completed with stacking ensemble learning was used, the IoU score was 0.74, indicating a high-performance improvement. A total of 1235 test images was acquired with drones on the sea bridge, and the stacking ensemble model showed an IoU of 0.5 or higher for 64.4% of the images.
Scale Models to Verify the Effectiveness of the Methods to Reducing the Vertical Bending Vibration of the Railway Vehicles Carbody: Applications and Design Elements
Authors: Dumitriu Mădălina , Mazilu Traian , Apostol Ioana Izabela
Published: February 2023

The purpose of this paper is to present applications and design elements of scale models of the carbody of railway vehicles integrated in experimental laboratory systems to verify the effectiveness of the methods to reduce vertical bending vibration of the carbody. In the first part of the paper, some applications of such experimental systems are presented, which include different scale models of the railway vehicle carbody. In the second part of the paper, the structure and dimensioning elements of a new demonstrative experimental system, specially designed by the authors of the present paper for testing the functionality of an original method of reducing the vertical bending vibrations of the carbody of railway vehicles, are presented. This method is based on an innovative approach that involves the use of a passive system consisting of two bars rigidly mounted on the longitudinal beams of the carbody underframe, having the role of opposing the bending of the carbody. The main element of the demonstrative experimental system is the scale model of the vehicle carbody, reduced to a beam, on which the two bars, called anti-bending bars, are mounted. For the dimensioning of the experimental model of the carbody and the anti-bending bars, original methodologies are developed in which several conditions are involved. In the case of the dimensioning of the experimental model of the carbody, the conditions refer to the convenient adoption of the scaling factor of the dimensions of the real carbody from the perspective of the practical realization of the experimental model of the carbody, ensuring the buckling stability of the demonstrative experimental system, achieving natural frequency of the vertical bending of the real carbody and avoiding the interference of the bounce vibration with the vertical bending vibration of the demonstrative experimental model of the carbody. The dimensions of the anti-bending bars are established from the condition that the vertical bending frequency of the experimental model of the carbody is outside the range of sensitivity of the human body to vertical vibration. Additionally, the natural frequency of the vertical bending vibration of the anti-bending bars must be chosen to avoid interference with the vertical bending vibration of the experimental model of the carbody. The effectiveness of the anti-bending bars in reducing the vertical bending vibration of the experimental model of the carbody is investigated with the help of numerical simulation results developed based on an original theoretical model of the experimental model of the carbody with anti-bending bars.
Analysis of Foundation Pit Excavation Deformation and Parameter Influence of Pile-Anchor-Ribbed-Beam Support System
Authors: Yin Quan , Fu He-Lin
Published: February 2023

The support system is the most important part of foundation pit engineering, which mainly determines the safety of foundation pit engineering. Based on the characteristics of the foundation pit of Changsha international financial center, the original pile-anchor-beam (PAB) support system is improved into a new form of support system, the pile-anchor-ribbed-beam (PARB) support system. This study establishes a numerical simulation model to calculate the surface settlement and the deformation of the retaining structure caused by the excavation of the foundation pit by using the PAB and PARB support systems, respectively. Finally, this study analyzes the influence of pile anchorage depth, ribbed beam size and waist beam size on the support effect. The field monitoring data are in good agreement with the numerical simulation results, which verifies the validity and accuracy of the numerical calculation model. The support effect of the new PARB support system is 30% higher than that of the original PAB support system. The position of maximum surface settlement is about 0.5 times the excavation depth from the retaining structure, and the position of maximum lateral deformation of the pile is about 0.9 times the excavation depth from the pile top. The increase in pile embedded depth and ribbed beam size can significantly improve the support effect, while the change of waist beam size does not improve the support effect significantly.
Adoption of Blockchain Technology in Healthcare: Challenges, Solutions, and Comparisons
Authors: Singh Dilbag , Monga Suhasini , Tanwar Sudeep , Hong Wei-Chiang , Sharma Ravi , He Yi-Lin
Published: February 2023

Blockchain technology was bestowed through bitcoin; research has continuously stretched out its applications in different sectors, proving blockchain as a versatile technology expanded in non-financial use cases. In the healthcare industry, blockchain is relied upon to have critical effects. Although exploration here is generally new yet developing quickly, along these lines, researchers in computer science, healthcare information technology, and professionals are continually geared to stay up with research progress. The study presents an exhaustive study on blockchain as a technology in depth from all possible perspectives and its adoption in the healthcare sector. A mapping study has been conducted to search different scientific databases to identify the existing challenges in healthcare management systems and to analyze the existing blockchain-based healthcare applications. Though blockchain has inherent highlights, such as distributed ledger, encryption, consensus, and immutability, blockchain adoption in healthcare has challenges. This paper also provides insights into the research challenges in blockchain and proposes solution taxonomy through comparative analysis.
Evaluating Prediction Models for Airport Passenger Throughput Using a Hybrid Method
Authors: Chen Bin , Zhao Xing , Wu Jin
Published: February 2023

This paper proposes a hybrid evaluation method to assess the prediction models for airport passenger throughput (APT). By analyzing two hundred three airports in China, five types of models are evaluated to study the applicability to different airports with various airport passenger throughput and developing conditions. The models were fitted using the historical data before 2014 and were verified by using the data from 2015–2019. The evaluating results show that the models employed for evaluating perform well in general except that there are insufficient historical data for modelling, or the APT of the airports changes abruptly owing to expansion, relocation or other kinds of external forces such as earthquakes. The more the APT of an airport is, the more suitable the models are for the airport. Particularly, there is no direct relation between the complexity and the predicting accuracy of the models. If the parameters of the models are properly set, time series models, causal models, market share methods and analogy-based methods can be utilized to predict the APT of 88% of studied airports effectively.
Underground Garage Patrol Based on Road Marking Recognition by Keras and Tensorflow
Authors: Gan Jianwen , Zhang Longqing , Chen Hongming , Bai Liping , Zhang Xinwei , Yang Lei , Zhang Yanghong
Published: February 2023

The purpose of this study was to design an unmanned patrol service in combination with artificial intelligence technology to solve the problem of underground vehicle patrol. This design used the Raspberry Pi development board, L298N driver chip, Raspberry Pi camera, and other major hardware equipment to transform the remote control car. This design used Python as the programming language. By writing Python code, the car could be driven under the control of the computer keyboard and the camera was turned on for data collection. The Keras neural network library was used to quickly build a neural network model, the collected data was used to train the model, and the model was finally generated. The model was placed in the TensorFlow system for processing, and the car could travel in a preset track for unmanned driving.
Q1Synth: A Quantum Computer Musical Instrument
Authors: Miranda Eduardo Reck , Thomas Peter , Itaboraí Paulo Vitor
Published: February 2023

This paper introduces Q1Synth, an unprecedented musical instrument that produces sounds from (a) quantum state vectors representing the properties of a qubit, and (b) its measurements. The instrument is presented on a computer screen (or mobile device, such as a tablet or smartphone) as a Bloch sphere, which is a visual representation of a qubit. The performer plays the instrument by rotating this sphere using a mouse. Alternatively, a gesture controller can be used, e.g., a VR glove. While the sphere is rotated, a continuously changing sound is produced. The instrument has a ‘measure key’. When the performer activates this key, the instrument generates a program (also known as a quantum circuit) to create the current state vector. Then, it sends the program to a quantum computer over the cloud for processing, that is, measuring, in quantum computing terminology. The computer subsequently returns the measurement, which is also rendered into sound. Currently, Q1Synth uses three different techniques to make sounds: frequency modulation (FM), subtractive synthesis, and granular synthesis. The paper explains how Q1Synth works and details its implementation. A setup developed for a musical performance, Spinnings, with three networked Q1Synth instruments is also reported. Q1Synth and Spinnings are examples of how creative practices can open the doors to new application pathways for quantum computing technology. Additionally, they illustrate how such emerging technology is leading to new approaches to musical instrument design and musical creativity.
Design and Development of Technical Solution for NFC-Based Self-Management Therapy in Actual Oncology Treatment
Authors: Bedriova Nicole , Smetana Milan , Gombarska Daniela
Published: February 2023

The purpose of the study was to design, develop, and implement an e-oncology: a technical solution based on self-management supportive treatment using a mobile communication device utilizing NFC technology. The goal was to optimize the process of treating oncology patients and make it more efficient. The idea of the designed system was to create a complex multifunctional mobile application that would help in their treatment and subsequently make the work of the medical staff easier. Direct attention was paid to the design and implementation of the NFC module itself, including the development and debugging of the mobile application, which was created for devices with the Android operating system. The developed system was successfully tested at a clinical- and radiation-oncology workplace for 60 days before implementation. In total, two oncology clinics and 100 patients were included in the testing process. Based on the relevant feedback, it can be concluded that the proposed system significantly shortened the waiting times for patients in the process of their oncology treatment and brought significant benefits in terms of more efficient use of the time of doctors, nurses, and especially patients.
Failure Strength of Automotive Steering Knuckle Made of Metal Matrix Composite
Authors: Reza Kashyzadeh Kazem
Published: February 2023

This article presents the static performance of composite steering knuckle due to drive on an equivalent road, including different types of roughness and maneuvers. To achieve this purpose, the driving of a full-vehicle model was simulated using the multi-body dynamics (MBD) method, and the imposed loads on connection points of the steering knuckle to different components of the suspension system were extracted considering various maneuvers. Next, CATIA software was used to prepare a smooth model of the steering knuckle by employing coordinate measuring machine (CMM) data. Stress analysis was performed under the maximum value of the loading history in finite element (FE) software. Eventually, the safety factor was calculated based on some well-known criteria for static failure of the composite materials. Moreover, the optimum value of tungsten carbide as a reinforcing substance in aluminum composite was estimated to increase failure strength. The results show that an increase in tungsten carbide leads to an increase in the strength of the steering knuckle under purely axial loads (normal stress criterion) and also that an increase in this substance leads to a decrease in the strength of the part under shear loads (shear stress criterion). Therefore, based on the nature of the loads (i.e., multi-axial non-proportional random amplitude loading conditions) applied to the automotive steering knuckle due to actual conditions, this metal matrix composite (aluminum matrix and tungsten carbide as reinforcement) is not practical.
Design Considerations for a Distributed Low-Cost Air Quality Sensing System for Urban Environments in Low-Resource Settings
Authors: Bainomugisha Engineer , Ssematimba Joel , Okure Deo
Published: February 2023

With rapid urbanization, hazardous environmental exposures such as air, noise, plastic, soil and water pollution have emerged as a major threat to urban health. Recent studies show that 9 out of 10 people worldwide breathe contaminated air contributing to over 7 million premature deaths annually. Internet of Things (IoT) and Artificial Intelligence (AI)-based environmental sensing and modelling systems have potential for contributing low-cost and effective solutions by providing timely data and insights to inform mitigation and management actions. While low and middleincome countries are among those most affected by environmental health risks, the appropriateness and deployment of IoT and AI systems in low-resource settings is least understood. Motivated by this knowledge gap, this paper presents a design space for a custom environmental sensing and management system designed and developed to fill the data gaps in low-resource urban settings with a particular focus on African cities. The paper presents the AirQo system, which is the first instance of the design space requirements. The AirQo system includes: (1) autonomous AirQo sensors designed and customised to be deployed in resource constrained environments (2) a distributed sensor network that includes over 120 static and mobile nodes for air quality sensing (3) AirQo network manager tool for tracking and management of installation and maintenance of nodes, (4) AirQo platform that provides calibration, data access and analytics tools to support usage among policy makers and citizens. Case studies from African cities that are using the data and insights for education, awareness and policy are presented. The paper provides a template for designing and deploying a technology-driven solution for cities in low resource settings.
Modeling and Assessment of PM10 and Atmospheric Metal Pollution in Kayseri Province, Turkey
Authors: Kunt Fatma , Ayturan Zeynep Cansu , Yümün Feray , Karagönen İlknur , Semerci Mümin , Akgün Mehmet
Published: February 2023

Air pollution has numerous detrimental consequences for human health, visibility, climate, materials, plant health, and animal health. A portion of air pollution consists of metals, which are emitted into the environment via the combustion of fossil fuels, industrial activities, and the incineration of metal-containing products. In this work, the particulate matter and particle-related metal pollution from various sources, in the Turkish province of Kayseri, were determined. AERMOD modeling was also used to examine the distribution of PM10 around the Kayseri Organized Industrial Zone (OIZ). Particulate matter (PM10) samples were collected using MCZ dust collecting devices at six monitoring locations mainly affected by residential heating (Hürriyet, Talas, and Kocasinan), industry (OIZ), and traffic (Tramway and Cumhuriyet) during the autumn/winter months and at three monitoring locations mainly affected by residential heating (Kocasinan), industry (OIZ), and traffic (Tramvay) during the spring months. ICP-MS analysis was used to assess the concentrations of the heavy metals (Pb, As, Cd, and Ni) in samples collected over 6 different time periods of 16 days each. During the autumn/winter months, the concentrations of Pb near roadways were found to exceed the Air Quality Assessment and Management Regulation of Turkey (AQAMR) limit value. During all the sampling periods, the Ni and Cd concentrations were below the AQAMR limit values. At the points associated with winter heating, the concentrations exceeded the AQAMR limit value, which may result from coal combustion.
Advanced Climate Simulation and Observation
Authors: Hu Zengyun , Tang Xuguang , Xin Qinchuan
Published: February 2023

Global climate changes, particularly extreme weather events, can directly or indirectly affect freshwater availability and food production, and cause disease outbreaks, floods and droughts [...]
Effects of Nutrient Addition on Pedicularis kansuensis Invasion of Alpine Grassland
Authors: Li Haining , Gong Yanming , Fang Fei , Li Kaihui , Liu Yanyan
Published: February 2023

In order to study the changes in invasive plant population characteristics under different nutrient addition treatments, this study used the native invasive species Pedicularis kansuensis, which is spreading in the Bayabulak alpine grassland, as the research object and conducted two consecutive years of field studies in which nutrients were added to plots. Changes in the P. kansuensis population’s invasive characteristics were monitored in 2020 and 2021 in four different nutrient-addition treatments, namely no-nutrients (control), low-nitrogen, high-nitrogen, and phosphorus treatments. The result showed that (1) nutrient addition had significant effects on P. kansuensis height and root/shoot ratio (p < 0.05); the time effect had significant effects on P. kansuensis height, coverage, abundance, aboveground biomass, and belowground biomass (p < 0.01), and the interaction between nutrient addition and time had a significant effect on P. kansuensis height (p < 0.01). (2) Nitrogen addition effectively inhibited the growth and the development of P. kansuensis, especially under high-nitrogen conditions in the second growing season, where the effect of height (2.50 cm), coverage (0.13%), richness (3 strains), aboveground biomass (0.21 g m−2), and belowground biomass (0.03 g m−2) was significant, with the P. kansuensis population almost disappearing by the end of the trial. (3) Phosphorus addition had no significant effect on the P. kansuensis population’s invasive characteristics. These results indicate that higher nitrogen addition could effectively slow the invasion of the P. kansuensis population, and the findings of this study could provide certain baseline data and scientific guidance for the effective control of the P. kansuensis invasion of the Bayabulak alpine grassland in the future as well as identify certain theoretical bases for the effect of nutrient addition on invasive plants overall.
Differential Description of Multiple Ionization of Uracil by 3.5 MeV/u C6+ Impact
Authors: Cariatore N. D. , Bachi N. , Otranto S.
Published: February 2023

In this work, a theoretical analysis of the impact of the multiple ionization of uracil by 3.5 MeV/u C6+ is developed in the framework of a classical trajectory Monte Carlo method, as recently introduced for multi-electronic targets. The electron emission contribution arising from the multiple electron ionization is explicitly determined and the emission geometries and the reaction regions for double and triple ionization are explicitly identified. The present results suggest that double ionization is mainly characterized by the emission of slow electrons with a relative angle of 80∘–120∘. For triple ionization, on the other hand, the emission seems to occur with the three electrons holding similar interelectronic angles.
A New Advanced Class of Convex Functions with Related Results
Authors: Khan Muhammad Adil , Adnan  , Saeed Tareq , Nwaeze Eze R.
Published: February 2023

It is the purpose of this paper to propose a novel class of convex functions associated with strong η-convexity. A relationship between the newly defined function and an earlier generalized class of convex functions is hereby established. To point out the importance of the new class of functions, some examples are presented. Additionally, the famous Hermite–Hadamard inequality is derived for this generalized family of convex functions. Furthermore, some inequalities and results for strong η-convex function are also derived. We anticipate that this new class of convex functions will open the research door to more investigations in this direction.
Use of Fumaric Acid to Inhibit Malolactic Fermentation in Bottled Rioja Wines: Effect in pH and Volatile Acidity Control
Authors: Morata Antonio , Adell Elena , López Carmen , Palomero Felipe , Suárez Elena , Pedrero Silvia , Bañuelos María Antonia , González Carmen
Published: February 2023

Fumaric acid (FH2) is an additive allowed by the Codex Alimentarius and the International Organization of Vine and Wine (OIV) that can be used for wine acidification but also to inhibit malolactic fermentation (MLF). FH2 has a positive effect in the reduction in SO2 doses by controlling LAB and other bacteria and by preserving molecular SO2 due to pH effect. This article reports the use of FH2 at 600 mg/L in wines produced with 3 varieties of Vitis vinifera L. grapes (Tempranillo, Garnacha and Viura) made in vintages 2018, 2020 and 2021. Wines treated with 600 mg/L of FH2 were more stable in the long term and showed lower pH by the preservation of malic acid due to both the absence of MLF (which reduced the pH in 0.1–0.2 units compared with controls) and the effect of FH2 acidification (what produced and additional reduction of 0.05–0.1 pH units). The wines treated with FH2 also remained with very low volatile acidity contents close to 0.2 mg/L or lower. These results corroborate that FH2 can be used to successfully control malolactic fermentation in all still wine types (red, white, and rose) from either of the studied varieties.
Cell–Biomaterial Interactions
Authors: Deplaigne Vincent , Rochefort Gael Y.
Published: February 2023

In animals, the extracellular matrix (ECM) forms a three-dimensional network occupying the intercellular spaces (interstitial matrix) or serving as physical and biochemical support for cells and tissues (basement membrane) [...]
Water Hardness Improves the Antioxidant Response of Zinc-Exposed Goldfish (Carassius auratus)
Authors: Choi Cheol Young , Kim Min Ju , Song Jin Ah , Kho Kang Hee
Published: February 2023

Zinc (Zn), a heavy metal, is an essential element in fish; however, exposure to high concentrations causes oxidative stress. Water hardness reduces oxidative stress reactions caused by heavy metals. To confirm the effect of water hardness on oxidative stress caused by Zn, goldfish were exposed to various Zn concentrations (1.0, 2.0, and 5.0 mg/L) and water hardness (soft (S), hard (H), and very hard (V)). The activity of superoxide dismutase (SOD) and catalase (CAT) in plasma increased with 1.0, 2.0, and 5.0 mg/L of Zn, and decreased with H and V water hardness. The levels of H2O2 and lipid peroxide (LPO) increased with Zn above 1.0 mg/L and decreased with H and V of water hardness. Caspase-9 mRNA expression in the liver increased after 7 and 14 days of Zn exposure and decreased with H and V water hardness. It was confirmed that DNA damage was less dependent on H and V water hardness. Based on the results of this study, at least 1.0 mg/L Zn causes oxidative stress in goldfish, and a high level of apoptosis occurs when exposed for more than 7 days. It appears that the oxidative stress generated by Zn can be alleviated by water hardness of at least 270 mg/L CaCO3. This study provides information on the relationship between the antioxidant response caused by heavy metals and water hardness in fish.
Morphogenic Effect of Exogenous Glucocorticoid Hormones in the Girardia tigrina Planarian (Turbellaria, Tricladida)
Authors: Ermakov Artem , Kudykina Natalia , Bykova Arina , Tkacheva Ulyana
Published: February 2023

We have studied the effect of two glucocorticoid hormones: hydrocortisone and its synthetic analogue methylprednisolone on the regeneration activity of head and tail blastema of the Girardia tigrina planarian. The regeneration activity was studied in head and tail blastema formed after resection by means of lifetime computer morphometry and immunohistochemical labeling of neoblasts. The search for orthologous proteins—glucocorticoid receptors (hydrocortisone) was performed using the SmedGD database of the Schmidtea mediterranea planarian. The results indicate that both hormones influence the recovery rate of the regenerating head and tail blastema. The worms with regenerating tail blastema have less sensitivity to the hormones’ treatment compared to the ones with regenerating head blastema. Hydrocortisone at a high concentration (10−3 M) suppressed the regeneration rate, while stimulating it at lower concentrations (10−4–10−6 M). The same concentrations of methylprednisolone inhibited the regeneration of head blastema, but did not affect the tail blastema regeneration. The two hormones acted differently: while hydrocortisone stimulated the proliferation of neoblasts in the periwound region, methylprednisolone reduced the mitotic activity, mainly on the tail zone furthest from the wound surface. We suggest that exogenous glucocorticoids can influence endogenous mechanisms of hormone-dependent regeneration.
Reactive Oxygen Species and NRF2 Signaling, Friends or Foes in Cancer?
Authors: Wang Ruolei , Liang Lirong , Matsumoto Misaki , Iwata Kazumi , Umemura Atsushi , He Feng
Published: February 2023

The imbalance between reactive oxygen species (ROS) production and clearance causes oxidative stress and ROS, which play a central role in regulating cell and tissue physiology and pathology. Contingent upon concentration, ROS influence cancer development in contradictory ways, either stimulating cancer survival and growth or causing cell death. Cells developed evolutionarily conserved programs to sense and adapt redox the fluctuations to regulate ROS as either signaling molecules or toxic insults. The transcription factor nuclear factor erythroid 2-related factor 2 (NRF2)-KEAP1 system is the master regulator of cellular redox and metabolic homeostasis. NRF2 has Janus-like roles in carcinogenesis and cancer development. Short-term NRF2 activation suppresses tissue injury, inflammation, and cancer initiation. However, cancer cells often exhibit constitutive NRF2 activation due to genetic mutations or oncogenic signaling, conferring advantages for cancer cells’ survival and growth. Emerging evidence suggests that NRF2 hyperactivation, as an adaptive cancer phenotype under stressful tumor environments, regulates all hallmarks of cancer. In this review, we summarized the source of ROS, regulation of ROS signaling, and cellular sensors for ROS and oxygen (O2), we reviewed recent progress on the regulation of ROS generation and NRF2 signaling with a focus on the new functions of NRF2 in cancer development that reach beyond what we originally envisioned, including regulation of cancer metabolism, autophagy, macropinocytosis, unfolded protein response, proteostasis, and circadian rhythm, which, together with anti-oxidant and drug detoxification enzymes, contributes to cancer development, metastasis, and anticancer therapy resistance.
Molecular Targets in Salivary Gland Cancers: A Comprehensive Genomic Analysis of 118 Mucoepidermoid Carcinoma Tumors
Authors: Bou Zerdan Maroun , Kumar Prashanth Ashok , Zaccarini Daniel , Ross Jeffrey , Huang Richard , Sivapiragasam Abirami
Published: February 2023

Introduction: Salivary gland carcinomas (SGC) are histologically diverse cancers and next-generation sequencing (NGS) to identify key molecular targets is an important aspect in the management of advanced cases. Methods: DNA was extracted from paraffin embedded tissues of advanced SGC and comprehensive genomic profiling (CGP) was carried out to evaluate for base substitutions, short insertions, deletions, copy number changes, gene fusions and rearrangements. Tumor mutation burden (TMB) was calculated on approximately 1.25 Mb. Some 324 genes in the FoundationOne CDX panel were analyzed. Results: Mucoepidermoid carcinoma (MECa) mutations were assessed. CDKN2A and CDKN2B GA were common in mucoepidermoid carcinoma (MECa) (52.5 and 30.5%). PIK3CA was also common in MECa (16.9%). ERBB2 amplification/short variants (amp/SV) were found in MECa (5.9/0%). HRAS GA was common in MECa (14.4%) as well. Other targets, including BAP1, PTEN, and KRAS, were noted but had a low incidence. In terms of immunotherapy (IO)-predictive markers, TMB > 10 was more common in MECa (16.9%). PDL1 high was also seen in MECa (4.20%). Conclusion: SGC are rare tumors with no FDA-approved treatment options. This large dataset reveals many opportunities for IO and targeted therapy contributing to the continuously increased precision in the selection of treatment for these patients.
Parkinsonism Is Associated with Altered SMA-Basal Ganglia Structural and Functional Connectivity in Frontotemporal Degeneration
Authors: Piervincenzi Claudia , Suppa Antonio , Petsas Nikolaos , Fabbrini Andrea , Trebbastoni Alessandro , Asci Francesco , Giannì Costanza , Berardelli Alfredo , Pantano Patrizia
Published: February 2023

Background: Patients with frontotemporal degeneration (FTD) often manifest parkinsonism, which likely results from cortical and subcortical degeneration of brain structures involved in motor control. We used a multimodal magnetic resonance imaging (MRI) approach to investigate possible structural and/or functional alterations in FTD patients with and without parkinsonism (Park+ and Park−). Methods: Thirty FTD patients (12 Park+, 18 Park−) and 30 healthy controls were enrolled and underwent 3T MRI scanning. MRI analyses included: (1) surface-based morphometry; (2) basal ganglia and thalamic volumetry; (3) diffusion-based probabilistic tractography of fiber tracts connecting the supplementary motor area (SMA) and primary motor cortex (M1) to the putamen, globus pallidus, and thalamus; and (4) resting-state functional connectivity (RSFC) between the aforementioned regions. Results: Patients in Park+ and Park− groups showed comparable patterns of cortical thinning in frontotemporal regions and reduced thalamic volume with respect to controls. Only Park+ patients showed reduced putaminal volume and reduced fractional anisotropy of the fibers connecting the SMA to the globus pallidus, putamen, and thalamus, with respect to controls. Park+ patients also showed decreased RSFC between the SMA and putamen with respect to both Park− patients and controls. Conclusions: The present findings support the hypothesis that FTD patients with parkinsonism are characterized by neurodegenerative processes in specific corticobasal ganglia-thalamocortical motor loops.
Multiplexing AAV Serotype-Specific Neutralizing Antibodies in Preclinical Animal Models and Humans
Authors: Kuoch Hisae , Krotova Karina , Graham Melanie L. , Brantly Mark L. , Aslanidi George
Published: February 2023

The accurate assessment of AAV-specific pre-existing humoral immunity due to natural viral infection is critical for the efficient use of clinical gene therapy. The method described in the present study applies equivalent infection conditions to each AAV serotype (AAV1, AAV2, AAV3, AAV5, AAV6, AAV7, AAV8, AAV9, AAV10, and AAVAnc80L65). In the current study, we validated the assay by assessing AAV-neutralizing antibody titers in a limited cohort of random human donors and well-established preclinical large animal models, including dogs and non-human primates (NHPs). We achieved a rapid and accurate evaluation of neutralizing titers for each individual subject that can be used for clinical enrollment based on specific AAV serotypes and individualized selection of the most suitable AAV serotype for each specific patient.
Hypertrophic, Dilated, and Arrhythmogenic Cardiomyopathy: Where Are We?
Authors: El Hadi Hamza , Freund Anne , Desch Steffen , Thiele Holger , Majunke Nicolas
Published: February 2023

Cardiomyopathies are a heterogeneous group of structural, mechanical, and electrical heart muscle disorders which often correlate with life-threatening arrhythmias and progressive heart failure accounting for significant cardiovascular morbidity and mortality. Currently, cardiomyopathies still represent a leading reason for heart transplantation worldwide. The last years have brought remarkable advances in the field of cardiomyopathies especially in terms of understanding the molecular basis as well as the diagnostic evaluation and management. Although most cardiomyopathy treatments had long focused on symptom management, much of the current research efforts aim to identify and act on the disease-driving mechanisms. Regarding risk assessment and primary prevention of sudden cardiac death, additional data are still pending in order to pave the way for a more refined and early patient selection for defibrillator implantation. This review summarizes the current knowledge of hypertrophic, dilated and arrhythmogenic cardiomyopathy with a particular emphasis on their pathophysiology, clinical features, and diagnostic approach. Furthermore, the relevant ongoing studies investigating novel management approaches and main gaps in knowledge are highlighted.
Prognostic Associations of Concomitant Antibiotic Use in Patients with Advanced NSCLC Treated with Atezolizumab: Sensitivity Analysis of a Pooled Investigation of Five Randomised Control Trials
Authors: Manning-Bennett Arkady T , Cervesi Julie , Bandinelli Pierre-Alain , Sorich Michael J , Hopkins Ashley M
Published: February 2023

Background: Immune checkpoint inhibitors (ICIs) have been a significant milestone for the treatment of advanced non-small cell lung cancer (NSCLC). However, the efficacy of ICIs can vary substantially between patients, with disparities in treatment outcomes being potentially driving by changes in the microbiome. Antibiotics can cause dysbiosis and are hypothesised to impact the efficacy of ICIs Methods: Data were pooled from five randomised clinical control trials, IMpower130, IMpower131, IMpower150, OAK, and POPLAR, assessing atezolizumab in advanced NSCLC. Cox proportional hazard models were used to determine whether antibiotic use within 6-weeks before and after randomisation was associated with progression-free survival (PFS) and overall survival (OS) outcomes, with data further stratified by programmed death ligand-1 (PD-L1) status. Results: Antibiotic use was significantly associated with worsened PFS (hazard ratio (HR) = 1.19 [1.08–1.30], p ≤ 0.001) and OS (HR = 1.27 [1.13–1.42], p ≤ 0.001) in patients treated with atezolizumab and those not treated with atezolizumab (PFS, HR = 1.21 [1.08–1.36] p < 0.001, OS, HR = 1.33 [1.16–1.51] p < 0.001). These associations were relatively consistent in both PD-L1 positive and PD-L1 negative. Conclusions: Antibiotic use within a ±6-week window was significantly associated with worse PFS and OS.