bluuebunny/crossref_metadata_2025 huggingface dataset:
Exact Relationship between Black Phosphorus Thickness and Behaviors of Field-Effect Transistors
Authors: Feng Liefeng , Liu Kaijin , Wang Miaoyu
Published: January 2023

As a two-dimensional (2D) semiconductor material with excellent optoelectronic properties, black phosphorus (BP) has attracted widespread attention. It was found that the energy band structure of BP crystal changes with its thickness if BP is thin. To explore the accurate effects of the BP thicknesses on devices, BP-FETs with different BP thickness (50 nm, 40 nm, 30 nm, 20 nm, and 6 nm) as the channel material were fabricated by mechanical exfoliation technique. The output characteristics and transfer characteristics of the BP-FETs were analyzed in detail. The source–drain current (Ids) of devices is directly related to the BP thickness. The larger the BP thickness, the larger the Ids obtained under the same gate voltage modulation, but the electric field modulation effect decreases. Especially, the correlation between Ids and BP thickness can be described by a semi-empirical formula, which predicts that only when the BP thickness is less than 21.7 nm, the band structure of BP will be significantly affected by the thickness. The mobility of the carrier increases with the increasing of the BP thickness; for BP thickness of 6 nm, 20 nm, 30 nm, 40 nm, and 50 nm, the mobility is about 52.5 cm2/Vs, 187.5 cm2/Vs, 214.4 cm2/Vs, 252.5 cm2/Vs, and 336.4 cm2/Vs. Finally, the 50 nm BP in FET was etched to 30 nm using plasma etching technology to further verify the above experimental results. It also confirmed that plasma etching methods tend to introduce structural damage and impurity elements, which in turn has an impact on the output characteristics of the device.
Normalized Weighting Schemes for Image Interpolation Algorithms
Authors: Rukundo Olivier
Published: January 2023

Image interpolation algorithms pervade many modern image processing and analysis applications. However, when their weighting schemes inefficiently generate very unrealistic estimates, they may negatively affect the performance of the end-user applications. Therefore, in this work, the author introduced four weighting schemes based on some geometric shapes for digital image interpolation operations. Moreover, the quantity used to express the extent of each shape’s weight was the normalized area, especially when the sums of areas exceeded a unit square size. The introduced four weighting schemes are based on the minimum side-based diameter (MD) of a regular tetragon, hypotenuse-based radius (HR), the virtual pixel length-based height for the area of the triangle (AT), and the virtual pixel length for hypotenuse-based radius for the area of the circle (AC). At the smaller scaling ratio, the image interpolation algorithm based on the HR scheme scored the highest at 66.6% among non-traditional image interpolation algorithms presented. However, at the higher scaling ratio, the AC scheme-based image interpolation algorithm scored the highest at 66.6% among non-traditional algorithms presented, and, here, its image interpolation quality was generally superior or comparable to the quality of images interpolated by both non-traditional and traditional algorithms.
Variable Multiple Interleaved Bi-Directional DC/DC Converter with Current Ripple Optimization
Authors: Duan Jiandong , Wang Shuai , Xu Yiming , Fan Shaogui , Zhao Ke , Sun Li
Published: January 2023

In order to reduce the current ripple and improve the power density of the system, the multiple structure design is generally adopted by the traditional bidirectional DC/DC converter. However, the fixed multiplicity design can’t make the DC/DC power converter always output the smallest current ripple under different duty ratios. Through this research, it is found that the current ripple is related to duty cycle and parallel multiplicity, and then a variable multiplicity bidirectional DC/DC power converter is proposed. Firstly, the relationship between the current ripple and parallel multiplicity and duty cycle is deduced, and the basic topology of variable multiplicity bidirectional DC/DC power converter is determined; Secondly, the average value model and AC small signal model of the system are established based on the topological structure, and then the state equation is obtained. Thirdly, the current compensation control method is designed based on the state equation. Finally, the experimental platform of variable multiplicity bidirectional DC/DC power converter is built.
Short-Term Power Prediction of Wind Turbine Applying Machine Learning and Digital Filter
Authors: Liu Shujun , Zhang Yaocong , Du Xiaoze , Xu Tong , Wu Jiangbo
Published: January 2023

As wind energy development increases, accurate wind energy forecasting helps to develop sensible power generation plans and ensure a balance between supply and demand. Machine-learning-based forecasting models possess exceptional predictive capabilities, and data manipulation prior to model training is also a key focus of this research. This study trained a deep Long Short-Term Memory (LSTM) neural network to learn the processing results of the Savitzky-Golay filter, which can avoid overfitting due to fluctuations and noise in measurements, improving the generalization performance. The optimum data frame length to match the second-order filter was determined by comparison. In a single-step prediction, the method reduced the root-mean-square error by 3.8% compared to the model trained directly with the measurements. The method also produced the smallest errors in all steps of the multi-step advance prediction. The proposed method ensures the accuracy of the forecasting and, on that basis, also improves the timeliness of the effective forecasts.
Monte Carlo Investigation of Gamma Radiation Shielding Features for Bi2O3/Epoxy Composites
Authors: Mahmoud Karem G. , Sayyed M. I. , Almuqrin Aljawhara H. , Arayro Jack , Maghrbi Yasser
Published: January 2023

Three different samples were synthesized based on polyepoxide resin, a solidifying agent, and a Bi2O3 doping compound. The polyepoxide resin and solidifying agent were added in a 2:1 ratio by weight and the Bi2O3 compound was added in ratios of 0, 5, and 10 wt. %. The density of the synthesized composites was measured using an MH-300A densimeter with an uncertainty in measurement of 0.001 g/cm3. The measurements showed that the density of the fabricated composite varied from 1.103 g/cm3 to 1.20 g/cm3 when the reinforcing Bi2O3 compound was raised from 0 wt. % to 10 wt. %. Furthermore, the γ-ray shielding parameters were evaluated based on the simulated mean track length of γ-photons inside the synthesized composites using MCNP-5 code. The simulated results show an enhancement in the shielding parameter when increasing the Bi2O3 concentration, where the linear attenuation coefficient values increased from 0.101 cm−1 to 0.118 cm−1 as the Bi2O3 concentration increased from 0 to 10 wt. %. The increase in the LAC has a positive effect on the other shielding properties.
Dynamic Mixed Reality Assembly Guidance Using Optical Recognition Methods
Authors: Maffei Antonio , Dalle Mura Michela , Monetti Fabio Marco , Boffa Eleonora
Published: January 2023

Augmented (AR) and Mixed Reality (MR) technologies are enablers of the Industry 4.0 paradigm and are spreading at high speed in production. Main applications include design, training, and assembly guidance. The latter is a pressing concern, because assembly is the process that accounts for the biggest portion of total cost within production. Teaching and guiding operators to assemble with minimal effort and error rates is pivotal. This work presents the development of a comprehensive MR application for guiding novice operators in following simple assembly instructions. The app follows innovative programming logic and component tracking in a dynamic environment, providing an immersive experience that includes different guidance aids. The application was tested by experienced and novice users, data were drawn from the performed experiments, and a questionnaire was submitted to collect the users’ perception. Results indicate that the MR application was easy to follow and even gave confidence to inexperienced subjects. The guidance support was perceived as useful by the users, though at times invasive in the field of view. Further development effort is required to draw from this work a complete and usable architecture for MR application in assembly, but this research forms the basis to achieve better, more consistent instructions for assembly guidance based on component tracking.
Generic Patient-Centered Blockchain-Based EHR Management System
Authors: Haddad Alaa , Habaebi Mohamed Hadi , Suliman Fakher Eldin M. , Elsheikh Elfatih A. A. , Islam Md Rafiqul , Zabidi Suriza Ahmad
Published: January 2023

Accessing healthcare services by several stakeholders for diagnosis and treatment has become quite prevalent owing to the improvement in the industry and high levels of patient mobility. Due to the confidentiality and high sensitivity of electronic healthcare records (EHR), the majority of EHR data sharing is still conducted via fax or mail because of the lack of systematic infrastructure support for secure and reliable health data transfer, delaying the process of patient care. As a result, it is critically essential to provide a framework that allows for the efficient exchange and storage of large amounts of medical data in a secure setting. The objective of this research is to develop a Patient-Centered Blockchain-Based EHR Management (PCEHRM) system that allows patients to manage their healthcare records across multiple stakeholders and to facilitate patient privacy and control without the need for a centralized infrastructure by means of granting or revoking access or viewing one’s records. We used an Ethereum blockchain and IPFS (inter-planetary file system) to store records because of its advantage of being distributed and ensuring the immutability of records and allowing for the decentralized storage of medical metadata, such as medical reports. To achieve secure a distributed, and trustworthy access control policy, we proposed an Ethereum smart contract termed the patient-centric access control protocol. We demonstrate how the PCEHRM system design enables stakeholders such as patients, labs, researchers, etc., to obtain patient-centric data in a distributed and secure manner and integrate utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions. Finally, we tested the proposed framework in the Windows environment by compiling a smart contract prototype using Truffle and deploy on Ethereum using Web3. The proposed system was evaluated in terms of the projected medical data storage costs for the IPFS on blockchain, and the execution time for a different number of peers and document sizes. The findings of the study indicate that the proposed strategy is both efficient and practicable.
Assessment of Low-Reynolds Number k-ε Models in Prediction of a Transitional Flow with Coanda Effect
Authors: Nie Xin , Chen Zhihang , Zhu Zehui
Published: January 2023

Precise prediction of ventilation flow is essential to create a comfortable, economical, and healthy indoor environment. In the past three decades, the computational fluid dynamics (CFD) method has been used more often, and it is now one of the primary methods for studying building ventilation. The most common CFD method is RANS simulation because of the low cost of computational resources and good accuracy. This paper presents a numerical investigation of a transitional ventilation flow with the Coanda effect, which makes the initial free jet transform into a wall jet. Six low-Reynolds number k-ε models proposed by Abid (AB), Lam and Bremhorst (LB), Launder and Sharma (LS), Yang and Shih (YS), Abe Kondoh and Nagano (AKN), and Chang, Hsieh and Chen (CHC) are applied. The performance of the six models is evaluated by comparing the computational results with the PIV measurements of Van Hooff et al. The predictions revealed that the LS model has a good approximation of velocity profiles because of its two extra terms in k and ε equations, and the AB model is in good agreement with experimental results for predicting the Coanda effect. The LB model provides the worst agreement with experimental data on account of the wrong prediction of turbulent kinetic energy and dissipation rate.
Instantaneous Reactive Power Theory in the Geometric Algebra Framework
Authors: Salmerón Patricio , Flores-Garrido Juan L. , Gómez-Galán Juan A.
Published: January 2023

In this paper, a new approach for instantaneous reactive power analysis in the geometric algebra (GA) environment is presented. The different formulations of the instantaneous reactive power theory (IRPT) proposed, to date, have been developed in three-phase systems. There, an instantaneous power variable, and two/three reactive power variables, all handled independently, were introduced. Thanks to GA, it is possible to carry out a global treatment where an instantaneous power multivector is defined. Thus, in the same multidimensional entity all the power variables are included. From the instantaneous power multivector, the instantaneous power current and the instantaneous reactive current are determined. It should be noted that in this mathematical framework there is no limitation on the number of phases, and the extension of the IRPT to the analysis of multi-phase systems appears in a natural manner. In this study, a systematic approach with the most relevant definitions and theorems corresponding to the proposed methodology has been established. Two practical cases of five-phase and three-phase systems have been included to apply the new established formulation.
Questioning the NFT “Revolution” within the Art Ecosystem
Authors: Radermecker Anne-Sophie V. , Ginsburgh Victor
Published: January 2023

Three years after the sensational debut of non-fungible tokens (NFTs) on the art scene, it seems timely to reflect on their presumed revolutionary attributes. The speculative fascination at the beginning has gradually given way to mixed outcomes, with hardly predictable future directions. However, once recontextualized in the art ecosystem and its value chain, one may question the ability of NFT technology to lead to radical changes. Our main argument is that although they offer perspectives that are worth considering regarding contracts, authors’ rights management, and provenance, blockchain-based technologies do not substantially modify the typical characteristics of the art world. Based on recent press articles and academic publications, we comment on the effects of this technology on producers (artists’ creative process and career development), intermediaries (art market gatekeepers), and consumers (quest for authenticity, collecting habits, and museum intervention in the art market). Our main conclusions suggest that NFTs perpetuate oversupply and job precarity in cyberenvironments and reinforce existing purchasing behaviors driven by the quest for authenticity and conspicuous consumption. Our goal is to mitigate some statements found in the literature and the press, especially regarding the democratization of the art market, and to help art market stakeholders approach this technology most objectively.
Animal Imagery in Eastern Han Tomb Reliefs from Shanbei 陝北
Authors: Wallace Leslie V.
Published: January 2023

Wild and fantastical animals climb, fly, scamper, and prance across pictorial stone carvings decorating Eastern Han tomb doors in northern Shaanxi. Alongside dragons and other mythical animals, bears felicitously dance, tigers grin opening their mouths to roar, and other wild animals frolic in swirling cloudscapes. While the same animals can be found in Eastern Han tomb reliefs and mortuary art in other regions, their frequency, emphasis on plasticity and movement, and combination with the yunqi 雲氣 motif are unique to the region. Originating in a hybrid style of art that was created during the Mid-Western Han Dynasty (206 BCE–9 CE), their significance was dependent not so much on any individual creature but on their display as an assemblage of shared forms, behaviors, and habitats. This paper explores how Eastern Han patrons and artists in Shanbei reinvigorated such imagery. It argues that on tomb doors through the region, these same wild and fantastical animals have become a key element of compositions meant to pacify the potentially dangerous realms that awaited the deceased in their postmortem ascension to Heaven (tian 天).
Scale-Dependent Verification of the OU MAP Convection Allowing Ensemble Initialized with Multi-Scale and Large-Scale Perturbations during the 2019 NOAA Hazardous Weather Testbed Spring Forecasting Experiment
Authors: Johnson Aaron , Han Fan , Wang Yongming , Wang Xuguang
Published: January 2023

Given the large range of resolvable space and time scales in large-domain convection-allowing for ensemble forecasts, there is a need to better understand optimal initial-condition perturbation strategies to sample the forecast uncertainty across these space and time scales. This study investigates two initial-condition perturbation strategies for CONUS-domain ensemble forecasts that extend into the two-day forecast lead time using traditional and object-based verification methods. Initial conditions are perturbed either by downscaling perturbations from a coarser resolution ensemble (i.e., LARGE) or by adopting the analysis perturbations from a convective-scale, EnKF system (i.e., MULTI). It was found that MULTI had more ensemble spread than LARGE across all scales initially, while LARGE’s perturbation energy surpassed that of MULTI after 3 h and continued to maintain a surplus over MULTI for the rest of the 36h forecast period. Impacts on forecast bias were mixed, depending on the forecast lead time and forecast threshold. However, MULTI was found to be significantly more skillful than LARGE at early forecast hours for the meso-gamma and meso-beta scales (1–9h), which is a result of a larger and better-sampled ensemble spread at these scales. Despite having a smaller ensemble spread, MULTI was also significantly more skillful than LARGE on the meso-alpha scale during the 20–24h period due to a better spread-skill relation. MULTI’s performance on the meso-alpha scale was slightly worse than LARGE’s performance during the 6–12h period, as LARGE’s ensemble spread surpassed that of MULTI. The advantages of each method for different forecast aspects suggest that the optimal perturbation strategy may require a combination of both the MULTI and LARGE techniques for perturbing initial conditions in a large-domain, convection-allowing ensemble.
An Overview of the Automated and On-Line Systems to Assess the Oxidative Potential of Particulate Matter
Authors: Carlino Alessandro , Romano Maria Pia , Lionetto Maria Giulia , Contini Daniele , Guascito Maria Rachele
Published: January 2023

Recent years have seen a significant increase in the scientific literature related to various methods for analyzing oxidative potential (OP) of atmospheric particulate matter (PM). The presence of several types of PM, differing chemical and physical properties, released by both anthropogenic and natural sources, leads to numerous health issues in living organisms and represents an attractive target for air quality monitoring. Therefore, several studies have focused on developing rapid and self-operative tests, employing different target molecules to assess OP of atmospheric aerosols as well as unique approaches to overcome some of the most common laboratory-related issues in this kind of analysis. This work provides an overview of online and automated systems, as well as a broad picture of the state-of-art of the various devices and methods developed on this topic over the last two decades. Moreover, representative studies on this subject will be discussed, analyzing the advantages and drawbacks of the developed automated techniques.
Investigating the Impact of Weather Conditions on Urban Heat Island Development in the Subtropical City of Hong Kong
Authors: Zheng Yingsheng , Li Wenjie , Fang Can , Feng Biyin , Zhong Qiru , Zhang Dongxu
Published: January 2023

Subtropical monsoon climates, high-density and heterogeneous urban built environments, as well as coastal–mountainous geographical environments influence the development of urban heat island (UHI) effects in Hong Kong. For better weather control of in situ observations and spatial analysis of UHI effects, it is necessary to quantitatively understand the influence of weather conditions on UHI development in Hong Kong and establish weather-based UHI estimation models. Meteorological records of four urban stations, one rural reference station, and one wind reference station at an hourly interval during the period of 2002–2012 were collected from Hong Kong observatory. A frequency analysis of the mean values of multiple meteorological elements and UHI parameters in urban stations was conducted to examine the prevailing and critical weather conditions, as well as the associated UHI conditions in Hong Kong. Multiple Linear Regression (MLR) was used to estimate the daily maximum UHI intensity (UHImax) based on a set of meteorological elements including cloud amount, wind speed, wind direction, relative humidity, and air temperature, as well as a UHI parameter of the daily maximum UHI intensity of the previous day (UHIpre-max). The results showed that MLR-based models can explain 33% and 56% variations of the UHImax in the summer and the whole year, respectively. The relative importance of each meteorological element on UHI development differed in the summer and annual periods, and the UHImax tended to be intensified under high temperature conditions in the summer.
Scots Pines (Pinus sylvestris) as Sources of Biological Ice-Nucleating Macromolecules (INMs)
Authors: Seifried Teresa M. , Reyzek Florian , Bieber Paul , Grothe Hinrich
Published: January 2023

Scots pine (Pinus sylvestris) is the most widespread pine species in the world. It grows in the largest forest system in the northern hemisphere and, together with birch trees, occupies a major part of the boreal forests. Recently, birch trees have been discovered as important emission sources of terrestrial ice-nucleating macromolecules (INMs) coming from pollen, bark, leaves, petioles, branches, and stem surfaces. It is known that pine pollen nucleate ice; however, the potential of other tree parts releasing INMs and contributing to the emission of ice-active aerosols is unknown. Here, we investigated the distribution of INMs in, on, and around Scots pines (Pinus sylvestris) in a laboratory and field study. We collected bark, branch wood, and needle samples from six pine trees in an urban park in Vienna, Austria. The concentration of INMs from aqueous extracts of milled (powder extracts) and intact surfaces (surface extracts) were determined. In addition, we collected rainwater rinsed off from three pines during a rainfall event and analyzed its INM content. All investigated samples contained INMs with freezing onset temperatures ranging from −16 °C to −29 °C. The number concentration of INMs in powder extracts at −25 °C (nINMs−25 °C) ranged from 105 to 109 per mg dry weight. Surface extracts showed concentrations from 105 to 108 INMs per cm2 of extracted surface, with needle samples exhibiting the lowest concentrations. In the rain samples, we found 106 and 107 INMs per cm2 of rain-collector area at −25 °C, with freezing onset temperatures similar to those observed in powder and surface extracts. With our data, we estimate that one square meter of pine stand can release about 4.1 × 109 to 4.6 × 1012 INMs active at −25 °C and higher, revealing pine forests as an extensive reservoir of INMs. Since pines are evergreen and release INMs not only from pollen grains, pines and the boreal forest in general need to be considered as a dominant source of INMs in high latitude and high-altitude locations, where other species are rare and other ice nuclei transported over long distances are diluted. Finally, we propose pine trees as an INM emission source which can trigger immersion freezing events in cloud droplets at moderate supercooled temperatures and therefore may have a significant impact on altering mixed phase clouds.
Time-Series Prediction of Intense Wind Shear Using Machine Learning Algorithms: A Case Study of Hong Kong International Airport
Authors: Khattak Afaq , Chan Pak-Wai , Chen Feng , Peng Haorong
Published: January 2023

Machine learning algorithms are applied to predict intense wind shear from the Doppler LiDAR data located at the Hong Kong International Airport. Forecasting intense wind shear in the vicinity of airport runways is vital in order to make intelligent management and timely flight operation decisions. To predict the time series of intense wind shear, Bayesian optimized machine learning models such as adaptive boosting, light gradient boosting machine, categorical boosting, extreme gradient boosting, random forest, and natural gradient boosting are developed in this study. The time-series prediction describes a model that predicts future values based on past values. Based on the testing set, the Bayesian optimized-Extreme Gradient Boosting (XGBoost) model outperformed the other models in terms of mean absolute error (1.764), mean squared error (5.611), root mean squared error (2.368), and R-Square (0.859). Afterwards, the XGBoost model is interpreted using the SHapley Additive exPlanations (SHAP) method. The XGBoost-based importance and SHAP method reveal that the month of the year and the encounter location of the most intense wind shear were the most influential features. August is more likely to have a high number of intense wind-shear events. The majority of the intense wind-shear events occurred on the runway and within one nautical mile of the departure end of the runway.
Is Technical Analysis Profitable on Renewable Energy Stocks? Evidence from Trend-Reinforcing, Mean-Reverting and Hybrid Fractal Trading Systems
Authors: Nor Safwan Mohd , Zawawi Nur Haiza Muhammad , Wickremasinghe Guneratne , Halim Zairihan Abdul
Published: January 2023

Demand for power sources is gradually shifting from ozone-depleting-substances towards renewable and sustainable energy resources. The growth prospects of the renewable energy industry coupled with improved cost efficiency means that renewable energy companies offer potential returns for traders in stock markets. Nonetheless, there have been no studies investigating technical trading rules in renewable energy stocks by amalgamating fractal geometry with technical indicators that focus on different market phases. In this paper, we explore the profitability of technical analysis using a portfolio of 20 component stocks from the NASDAQ OMX Renewable Energy Generation Index using fractal dimension together with trend-reinforcing and mean-reverting (contrarian) indicators. Using daily prices for the period 1 July 2012 to 30 June 2022, we apply several tests to measure trading performance and risk-return dynamics of each form of technical trading system—both in isolation and simultaneously. Overall, trend (contrarian) trading system outperforms (underperforms) the naïve buy-and-hold policy on a risk-adjusted basis, while the outcome is further enhanced (reduced) by the fractal-reinforced strategy. Simultaneous use of both trend-reinforcing and mean-reverting indicators strengthened by fractal geometry generates the best risk-return trade-off, significantly outperforming the benchmark. Our findings suggest that renewable energy stock prices do not fully capture historical price patterns, allowing traders to earn significant profits from the weak form market inefficiency.
On Semi-Continuous and Clisquish Functions in Generalized Topological Spaces
Authors: Aponte Elvis , Subramanian Vadakasi , Macías Jhixon , Krishnan Muthumari
Published: January 2023

In this paper, we will focus on three types of functions in a generalized topological space, namely; lower and upper semi-continuous functions, and cliquish functions. We give some results for nowhere dense sets and for second category sets. Further, we discuss the nature of cliquish functions in generalized metric spaces and provide the characterization theorem for cliquish functions in terms of nowhere dense sets.
On Λ-Fractional Derivative and Human Neural Network
Authors: Karaoulanis D. , Lazopoulos A. K. , Lazopoulou N. , Lazopoulos K.
Published: January 2023

Fractional derivatives can express anomalous diffusion in brain tissue. Various brain diseases such as Alzheimer’s disease, multiple sclerosis, and Parkinson’s disease are attributed to the accumulation of proteins in axons. Discrete swellings along the axons cause other neuro diseases. To model the propagation of voltage in axons with all those causes, a fractional cable geometry has been adopted. Although a fractional cable model has already been presented, the non-existence of fractional differential geometry based on the well-known fractional derivatives raises questions. These minute parts of the human neural system are modeled as cables that function with a non-uniform cross-section in the fractional realm based upon the Λ-fractional derivative (Λ-FD). That derivative is considered the unique fractional derivative generating differential geometry. Examples are presented so that fruitful conclusions can be made. The present work is going to help medical and bioengineering scientists in controlling various brain diseases.
Fixed Point Theorems via Orthogonal Convex Contraction in Orthogonal ♭-Metric Spaces and Applications
Authors: Nallaselli Gunasekaran , Baazeem Amani S. , Gnanaprakasam Arul Joseph , Mani Gunaseelan , Javed Khalil , Ameer Eskandar , Mlaiki Nabil
Published: January 2023

In this paper, we introduce the concept of orthogonal convex structure contraction mapping and prove some fixed point theorems on orthogonal ♭-metric spaces. We adopt an example to highlight the utility of our main result. Finally, we apply our result to examine the existence and uniqueness of the solution for the spring-mass system via an integral equation with a numerical example.
An Integrated Intuitionistic Fuzzy Closeness Coefficient-Based OCRA Method for Sustainable Urban Transportation Options Selection
Authors: Mishra Arunodaya Raj , Rani Pratibha , Cavallaro Fausto , Hezam Ibrahim M. , Lakshmi Jyoti
Published: January 2023

Transportation systems play a key role in urban development by providing access for people to markets and education, employment, health care, recreation, and other key services. However, uncontrolled urban population and fast growth of vehicle mobility inevitably lead to unsustainable urban transportation systems in terms of economic, technical, social, and geographical aspects of sustainability. Thus, there is a need to select suitable sustainable urban transportation (SUT) alternatives, which can contributed to the technological advancement of a city and changes in societal necessities, mitigating the climate change impact from transport and transforming living habits, in the context of high urban population growth. Therefore, this paper aims to introduce an integrated multi-attribute decision analysis (MADA) framework for assessing and ranking the sustainable urban transportation (SUT) options under an intuitionistic fuzzy sets (IFSs) context. In this regard, firstly IF-distance measures and their properties are developed to obtain the criteria weight. Second, an IF-relative closeness coefficient-based model is presented to find the criteria weights. Third, the operational competitiveness rating (OCRA) model is introduced with the IF-score function-RS-based decision experts’ weighing model and the relative closeness coefficient-based criteria weight determination model under the IFSs environment. To exemplify the utility and effectiveness of the developed IF-relative closeness coefficient-based OCRA methodology, a case study ranking the different SUT bus options is presented from an intuitionistic fuzzy perspective. A comparison with different models is made to prove the superiority and solidity of the obtained outcome. Moreover, the comparative analysis outperforms the other extant MADA models, as it can provide more sound outcomes than others, and thus it is more suitable and efficient to elucidate uncertain information in handling practical MADA problems. In this study, we analyze and determine the most suitable and sustainable SUT by considering the economic, technical, environmental, and social dimensions of sustainability and also make a significant contribution to the current scientific knowledge by providing a novel decision support system from an uncertainty perspective.
Identification of Potential Hub Genes Related to Aflatoxin B1, Liver Fibrosis and Hepatocellular Carcinoma via Integrated Bioinformatics Analysis
Authors: Hamdy Hayam , Yang Yi , Cheng Cheng , Liu Qizhan
Published: January 2023

The molecular mechanism of the hepatotoxicant aflatoxin B1 to induce liver fibrosis and hepatocellular carcinoma (HCC) remains unclear, to offer fresh perspectives on the molecular mechanisms underlying the onset and progression of AFB1-Fibrosis-HCC, which may offer novel targets for the detection and therapy of HCC caused by AFB1. In this study, expression profiles of AFB1, liver fibrosis and liver cancer-related datasets were downloaded from the Gene Expression Omnibus (GEO), and differentially expressed genes (DEGs) were identified by the GEO2R tool. The STRING database, CytoHubba, and Cytoscape software were used to create the protein-protein interaction and hub genes of the combined genes, and the ssGSEA score for inflammatory cells related gene sets, the signaling pathway, and immunotherapy were identified using R software and the GSEA database. The findings revealed that AFB1-associated liver fibrosis and HCC combined genes were linked to cell process disruptions, the BUB1B and RRM2 genes were identified as hub genes, and the BUB1B gene was significantly increased in JAK-STAT signaling gene sets pathways as well as having an immunotherapy-related impact. In conclusion, BUB1B and RRM2 were identified as potential biomarkers for AFB1-induced fibrosis and HCC progression.
Inventory of the Seaweeds and Seagrasses of the Hawaiian Islands
Authors: Sherwood Alison R. , Guiry Michael D.
Published: January 2023

This updated list is composed of a total of 661 records, which includes 71 brown algae, 450 red algae, 137 green algae, and three seagrasses, with an overall rate of endemism of 13.2%. Almost half (46.7%) of the Hawaiian records presented here are represented by at least one DNA sequence, while 16.3% are confirmed through a DNA sequence match to a topotype, and 6.7% are confirmed through a DNA sequence match to a type specimen. The data are presented in the context of the natural history of the Hawaiian Islands, which is heavily influenced by the volcanic hotspot origin of the archipelago in the middle of the Pacific Ocean, as well as the important cultural role of seaweeds and other marine plants in Hawai‘i, and the current threats to marine ecosystems, which include the introduction and proliferation of a number of invasive marine macroalgae.
The Course of Mechanical Stress: Types, Perception, and Plant Response
Authors: Kouhen Mohamed , Dimitrova Anastazija , Scippa Gabriella Stefania , Trupiano Dalila
Published: January 2023

Mechanical stimuli, together with the corresponding plant perception mechanisms and the finely tuned thigmomorphogenetic response, has been of scientific and practical interest since the mid-17th century. As an emerging field, there are many challenges in the research of mechanical stress. Indeed, studies on different plant species (annual/perennial) and plant organs (stem/root) using different approaches (field, wet lab, and in silico/computational) have delivered insufficient findings that frequently impede the practical application of the acquired knowledge. Accordingly, the current work distils existing mechanical stress knowledge by bringing in side-by-side the research conducted on both stem and roots. First, the various types of mechanical stress encountered by plants are defined. Second, plant perception mechanisms are outlined. Finally, the different strategies employed by the plant stem and roots to counteract the perceived mechanical stresses are summarized, depicting the corresponding morphological, phytohormonal, and molecular characteristics. The comprehensive literature on both perennial (woody) and annual plants was reviewed, considering the potential benefits and drawbacks of the two plant types, which allowed us to highlight current gaps in knowledge as areas of interest for future research.
Effectiveness of Respiratory Muscles Training by Voluntary Isocapnic Hyperpnea Versus Inspiratory Threshold Loading on Intercostales and Vastus Lateralis Muscles Deoxygenation Induced by Exercise in Physically Active Adults
Authors: Espinosa-Ramírez Maximiliano , Riquelme Santiago , Araya Felipe , Rodríguez Guido , Figueroa-Martínez Fernanda , Gabrielli Luigi , Viscor Ginés , Reid W. Darlene , Contreras-Briceño Felipe
Published: January 2023

Respiratory muscle training (RMT) improves physical performance, although it is still debated whether this effect depends on the type of training. The purpose of this study was to compare the effects of two different types of RMT, i.e., voluntary isocapnic hyperpnea (VIH) and inspiratory threshold loading (ITL), on the deoxygenation of intercostal (ΔSmO2-m. intercostales) and vastus lateralis (ΔSmO2-m. vastus lateralis) muscles during exercise. Twenty-four participants performed eight weeks of RMT by: (i) VIH (3 days·week−1 for 12 min at 60% maximal voluntary ventilation) or (ii) ITL (5 sets·week−1 of 30 breaths·minute−1 at 60% maximal inspiratory pressure). Cardiopulmonary exercise testing (CPET) included ΔSmO2 (the change from baseline to end of test) of intercostal and vastus lateralis muscles. After RMT, both groups showed decreased ΔSmO2-m. intercostales (VIH = 12.8 ± 14.6%, p = 0.04 (effect size, ES = 0.59), and ITL = 8.4 ± 9.8%, p = 0.04 (ES = 0.48)), without a coincident change of ∆SmO2-m. vastus lateralis. ITL training induced higher V˙O2-peak absolute values than VIH (mean Δ post–pre, ITL = 229 ± 254 mL·min−1 [95% CI 67–391] vs. VIH, 39 ± 153 mL·min−1 [95% CI −58–136.0], p = 0.01). In conclusion, both RMT improved the balance between supply and oxygen consumption levels of m. intercostales during CPET, with ITL also inducing an increase of aerobic capacity.
Does Exercise-Induced Hypoalgesia Depend on Exercise Duration?
Authors: Tomschi Fabian , Kieckbusch Luisa , Zachow Julius , Hilberg Thomas
Published: January 2023

Acute physical activity is assumed to lead to exercise-induced hypoalgesia (EIH). Yet, little research has been conducted dealing with the influence of exercise duration on EIH. The aim of this study was to investigate the effects of three different exercise durations using the same intensity compared to a control session on EIH. A total of 36 participants conducted three different exercise sessions on a bicycle ergometer for 30, 45, and 60 min, respectively, in addition to a passive control session. The intensity was set to 75% of the individual’s VO2max. Pre and post exercise, pain sensitivity was measured employing pressure pain thresholds (PPT) at the elbow, knee, and ankle joints, as well as the sternum and forehead. In addition, the conditioned pain modulation (CPM) response was conducted pre and post exercise. The results reveal that the exercises neither led to any changes in PPT measured at any landmark nor induced any CPM response effects. These results do not confirm the hypoalgesic effects usually observed after exercise. The reasons explaining these results remain rather elusive but might be explained by the low intensities chosen leading to a milder release of pain inhibiting substances, the landmarks employed for PPT measurements, or potential non-responsiveness of participants.
The Role of Platelets in Hypoglycemia-Induced Cardiovascular Disease: A Review of the Literature
Authors: Ali Ahmed Ali Gebril , Niinuma Sara Anjum , Moin Abu Saleh Md , Atkin Stephen L. , Butler Alexandra E.
Published: January 2023

Cardiovascular diseases (CVDs) are the leading cause of death globally as well as the leading cause of mortality and morbidity in type 2 diabetes (T2D) patients. Results from large interventional studies have suggested hyperglycemia and poor glycemic control to be largely responsible for the development of CVDs. However, the association between hypoglycemia and cardiovascular events is also a key pathophysiological factor in the development of CVDs. Hypoglycemia is especially prevalent in T2D patients treated with oral sulfonylurea agents or exogenous insulin, increasing the susceptibility of this population to cardiovascular events. The adverse cardiovascular risk of hypoglycemia can persist even after the blood glucose levels have been normalized. Hypoglycemia may lead to vascular disease through mechanisms such as enhanced coagulation, oxidative stress, vascular inflammation, endothelial dysfunction, and platelet activation. In the following review, we summarize the evidence for the role of hypoglycemia in platelet activation and the subsequent effects this may have on the development of CVD. In addition, we review current evidence for the effectiveness of therapies in reducing the risk of CVDs.
Critical Roles of METTL3 in Translation Regulation of Cancer
Authors: Meng Wangyang , Xiao Han , Mei Peiyuan , Chen Jiaping , Wang Yangwei , Zhao Rong , Liao Yongde
Published: January 2023

Aberrant translation, a characteristic feature of cancer, is regulated by the complex and sophisticated RNA binding proteins (RBPs) in the canonical translation machinery. N6-methyladenosine (m6A) modifications are the most abundant internal modifications in mRNAs mediated by methyltransferase-like 3 (METTL3). METTL3 is commonly aberrantly expressed in different tumors and affects the mRNA translation of many oncogenes or dysregulated tumor suppressor genes in a variety of ways. In this review, we discuss the critical roles of METTL3 in translation regulation and how METTL3 and m6A reader proteins in collaboration with RBPs within the canonical translation machinery promote aberrant translation in tumorigenesis, providing an overview of recent efforts aiming to ‘translate’ these results to the clinic.
Metabolic Pathway Analysis: Advantages and Pitfalls for the Functional Interpretation of Metabolomics and Lipidomics Data
Authors: Tsouka Sofia , Masoodi Mojgan
Published: January 2023

Over the past decades, pathway analysis has become one of the most commonly used approaches for the functional interpretation of metabolomics data. Although the approach is widely used, it is not well standardized and the impact of different methodologies on the functional outcome is not well understood. Using four publicly available datasets, we investigated two main aspects of topological pathway analysis, namely the consideration of non-human native enzymatic reactions (e.g., from microbiota) and the interconnectivity of individual pathways. The exclusion of non-human native reactions led to detached and poorly represented reaction networks and to loss of information. The consideration of connectivity between pathways led to better emphasis of certain central metabolites in the network; however, it occasionally overemphasized the hub compounds. We proposed and examined a penalization scheme to diminish the effect of such compounds in the pathway evaluation. In order to compare and assess the results between different methodologies, we also performed over-representation analysis of the same datasets. We believe that our findings will raise awareness on both the capabilities and shortcomings of the currently used pathway analysis practices in metabolomics. Additionally, it will provide insights on various methodologies and strategies that should be considered for the analysis and interpretation of metabolomics data.
Bioactive PEEK: Surface Enrichment of Vitronectin-Derived Adhesive Peptides
Authors: Cassari Leonardo , Zamuner Annj , Messina Grazia M. L. , Marsotto Martina , Chen Hongyi , Gonnella Giovanni , Coward Trevor , Battocchio Chiara , Huang Jie , Iucci Giovanna , Marletta Giovanni , Di Silvio Lucy , Dettin Monica
Published: January 2023

Polyetheretherketone (PEEK) is a thermoplastic polymer that has been recently employed for bone tissue engineering as a result of its biocompatibility and mechanical properties being comparable to human bone. PEEK, however, is a bio-inert material and, when implanted, does not interact with the host tissues, resulting in poor integration. In this work, the surfaces of 3D-printed PEEK disks were functionalized with: (i) an adhesive peptide reproducing [351–359] h-Vitronectin sequence (HVP) and (ii) HVP retro-inverted dimer (D2HVP), that combines the bioactivity of the native sequence (HVP) with the stability toward proteolytic degradation. Both sequences were designed to be anchored to the polymer surface through specific covalent bonds via oxime chemistry. All functionalized PEEK samples were characterized by Water Contact Angle (WCA) measurements, Atomic Force Microscopy (AFM), and X-ray Photoelectron Spectroscopy (XPS) to confirm the peptide enrichment. The biological results showed that both peptides were able to increase cell proliferation at 3 and 21 days. D2HVP functionalized PEEK resulted in an enhanced proliferation across all time points investigated with higher calcium deposition and more elongated cell morphology.
Study of the Rv1417 and Rv2617c Membrane Proteins and Their Interactions with Nicotine Derivatives as Potential Inhibitors of Erp Virulence-Associated Factor in Mycobacterium tuberculosis: An In Silico Approach
Authors: Aguilar-Pineda Jorge Alberto , Febres-Molina Camilo , Cordova-Barrios Cinthia C. , Campos-Olazával Lizbeth M. , Del-Carpio-Martinez Bruno A. , Ayqui-Cueva Flor , Gamero-Begazo Pamela L. , Gómez Badhin
Published: January 2023

The increasing emergence of Mycobacterium tuberculosis (Mtb) strains resistant to traditional anti-tuberculosis drugs has alarmed health services worldwide. The search for new therapeutic targets and effective drugs that counteract the virulence and multiplication of Mtb represents a challenge for the scientific community. Several studies have considered the erp gene a possible therapeutic target in the last two decades, since its disruption negatively impacts Mtb multiplication. This gene encodes the exported repetitive protein (Erp), which is located in the cell wall of Mtb. In vitro studies have shown that the Erp protein interacts with two putative membrane proteins, Rv1417 and Rv2617c, and the impairment of their interactions can decrease Mtb replication. In this study, we present five nicotine analogs that can inhibit the formation of heterodimers and trimers between these proteins. Through DFT calculations, molecular dynamics, docking, and other advanced in silico techniques, we have analyzed the molecular complexes, and show the effect these compounds have on protein interactions. The results show that four of these analogs can be possible candidates to counteract the pathogenicity of Mtb. This study aims to combine research on the Erp protein as a therapeutic target in the search for new drugs that serve to create new therapies against tuberculosis disease.