bluuebunny/crossref_metadata_2025 huggingface dataset:
A Parametric Physics-Informed Deep Learning Method for Probabilistic Design of Thermal Protection Systems
Authors: Zhang Runlin , Xu Nuo , Zhang Kai , Wang Lei , Lu Gui
Published: May 2023

Precise and efficient calculations are necessary to accurately assess the effects of thermal protection system (TPS) uncertainties on aerospacecrafts. This paper presents a probabilistic design methodology for TPSs based on physics-informed neural networks (PINNs) with parametric uncertainty. A typical thermal coating system is used to investigate the impact of uncertainty on the thermal properties of insulation materials and to evaluate the resulting temperature distribution. A sensitivity analysis is conducted to identify the influence of the parameters on the thermal response. The results show that PINNs can produce quick and accurate predictions of the temperature of insulation materials. The accuracy of the PINN model is comparable to that of a response surface surrogate model. Still, the computational time required by the PINN model is only a fraction of the latter. Considering both computational efficiency and accuracy, the PINN model can be used as a high-precision surrogate model to guide the TPS design effectively.
State-of-the-Art of Concentrating Photovoltaic Thermal Technology
Authors: Resch Alois , Höller Robert
Published: May 2023

Concentrating photovoltaic thermal (CPVT) technology has the potential to support the industrial sector with renewable electricity and heat simultaneously. The implementation of spectral splitting emerges as a possible approach to significantly increase the conversion efficiency, and furthermore, to hurdle the fundamental discrepancy of CPVT systems, that the electrical and the thermal receiver part have opposing temperature requirements. This paper provides an introductive description of beam splitting methodology and presents an updated review of the latest developments in the specific sector of spectral splitting by selective absorption. Furthermore, a novel CPVT receiver design utilizing bendable PV cells and an innovative heat transfer fluid are explained in detail. Simulation results illustrate the possibilities of spectral splitting to raise the electrical conversion efficiency in CPVT receivers by up to 42.9%. Potential improvements in receiver designs are discussed for further enhancement of the technical capabilities and possible cost reduction of the implemented material.
Convergence of Energy Intensity of the Export of Goods by Rail Transport: Linkages with the Spatial Integration and Economic Condition of Countries
Authors: Szaruga Elżbieta , Załoga Elżbieta , Drewnowski Arkadiusz , Dąbrosz-Drewnowska Paulina
Published: May 2023

This article concerns the identification of connections between the energy intensity of rail transport and spatial integration (convergence processes in the EU and spatial proximity) and the economic situation of countries that are in international export–import trade relations. Three research questions are formulated in the article: (1) Does the improvement of the economic situation of the importing country reduce the energy intensity of the Polish export of goods by rail transport to the partner country? (2) Does EU integration contribute to reducing the energy intensity of the export of goods by rail transport? (3) Is there a positive spatial effect (convergence) of reducing the energy intensity of the export of goods by rail transport? This study concerned 14 geographical destinations (export destinations from Poland) during the years 2010–2020. A comprehensive study of convergence was used by building a spatial (club) and type β convergence model and using an unconventional method (panel stationarity analysis). It has been verified that there is a convergence in the energy intensity of goods exportation by rail transport in EU countries. The rate of spatial (club) convergence is 8.66% per year, while the period after which this convergence will be halfway between the initial state and the long-term equilibrium point is 8 years.
Direct Numerical Simulation of Thermal Turbulent Boundary Layer Flow over Multiple V-Shaped Ribs at Different Angles
Authors: Ji Feng , Ding Jing , Lu Jianfeng , Wang Weilong
Published: May 2023

Direct numerical simulations (DNSs) of spatially developing thermal turbulent boundary layers over angle-ribbed walls were performed. Four rib angles (γ=90°,60°,45° and 30°) were examined. It was found that the 45° ribs produced the highest drag coefficient, whereas the 30° ribs most improved the Stanton number. In comparison to the transverse rib case, streamwise velocity and dimensionless temperature in the V-shaped cases significantly increased in the near wall region and were attenuated by secondary flows further away from the ribs, which suggested a break of the outer-layer similarity in the scenario presented. The surprising improvement of heat transfer performance in the 30° rib case was mainly due to its large dispersive heat flux, while dispersive stress reached its peak value in the 45° case, emphasizing the dissimilarity in transporting momentum and heat by turbulence over a ribbed surface. Additionally, by calculating the global and local Reynolds analogy factors, we concluded that the enhancement in heat transfer efficiency was attributed to an increasing Reynolds analogy factor in the intermediate region as the rib angle decreased.
Improving the Accuracy of Digital Unbalanced Impedance Bridges
Authors: Kontorski Kamil , Rybski Ryszard , Kaczmarek Janusz
Published: May 2023

This article presents an automatic digital unbalanced impedance bridge for comparing two-port impedances: R-R, R-C and C-C. The bridge consists of a two-channel digital source of voltage sinusoidal waveforms supplying the bridge arms and a three-channel precise digitizer, by means of which the complex ratio of the source output voltages and the relative bridge unbalanced voltage are determined. The hardware implementation of the bridge is based on a relatively inexpensive universal data acquisition (DAQ) card by National Instruments, USB-6281, which contains, among others, a multi-channel 18-bit analog-to-digital converter (ADC) and two 16-bit digital-to-analog converters (DAC). Thanks to the new approach to the bridge operation algorithm, consisting in the use of the interpolation method in the comparison process, the influence of the accuracy of the measurement of the bridge unbalanced voltage and some bridge parasitic admittances on the uncertainty of the impedance comparison were minimized. This simplifies the measurement procedure and shortens its execution time. The obtained results confirmed that a relatively simple digital unbalanced bridge can compare impedance standards with an uncertainty of less than 10−5. By reducing the requirements regarding the uncertainty of the measurement, and thus its execution time, the presented bridge supplemented with impedance sensors can be used in many areas of industry.
Preliminary Results of Heat Transfer and Pressure Drop Measurements on Al2O3/H2O Nanofluids through a Lattice Channel
Authors: Corasaniti Sandra , Potenza Michele , Petracci Ivano
Published: May 2023

A nanofluid is composed of a base fluid with a suspension of nanoparticles that improve the base fluid’s thermophysical properties. In this work, the authors have conducted experimental tests on an alumina-based nanofluid (Al2O3/H2O) moving inside a 3D-printed lattice channel. The unit cell’s lattice shape can be considered a double X or a double pyramidal truss with a common vertex. The test channel is 80 mm long and has a cross-sectional area, without an internal lattice with that has the dimensions H × W, with H = 5 mm and W = 15 mm. A nanofluid and a lattice duct can represent a good compound technique for enhancing heat transfer. The channel is heated by an electrical resistance wound onto its outer surface. The heat transfer rate absorbed by the nanofluid, the convective heat transfer coefficients, and the pressure drops are evaluated. The experimental tests are carried out at various volumetric contents of nanoparticles (φ = 1.00%, φ = 1.50% and φ = 2.05%) and at various volumetric flow rates (from 0.2 L/min to 2 L/min). The preliminary results show that in the range between 0.5 L/min ÷ 2.0 L/min, the values of convective heat transfer coefficients are greater than those of pure water (φ = 0) for all concentrations of Al2O3; thus, the nanofluid absorbed a higher thermal power than the water, with an average increase of 6%, 9%, and 14% for 1.00%, 1.50% and 2.05% volume concentrations, respectively. The pressure drops are not very different from those of water; therefore, the use of nanofluids also increased the cooling efficiency of the system.
Reputation of Electric Vehicles in the Environment of Carbon Reduction and Accelerated Digitization
Authors: Pollák František , Markovič Peter , Majdúchová Helena
Published: May 2023

The accelerated digitization of the third decade of the twenty-first century poses a challenge both for science and for practice. The study presents partial results of continuous research on online reputation management of entities operating in the environment of low-carbon economy. The aim of the study is the application of a standardized methodology for calculating the Total level of Online Reputation (TOR) to determine the market position of selected Electric Vehicles (EVs) compared to the market position of conventional Vehicles with Internal Combustion Engines (ICEVs) in the online environment. The research sample consists of the ten best-selling Vehicles and the ten best-selling Electric Vehicles in the world by sales in the year 2021. Based on the measurement results and the subsequent analysis of the context, it can be concluded that the EV market shows the parameters of a developing market not only from the point of view of sales but also in terms of the overall level of Online Reputation as such. At the same time, it is possible to point out a high geographical specificity and significant disproportionality of the EV market compared to ICEVs. From the overall market perspective, the future of cars in the EV category is still unclear, as building trust in low-carbon products is limited by historical tradition. The main representatives of the EV industry thus represent the first forays of the onset of the low-carbon era in individual transport. The description of the issue will require the monitoring of status indicators over time. The results of the presented study can thus serve as a baseline and methodological framework for further research of the adoption of low-carbon policies in common practice.
Predication of Ocean Wave Height for Ocean Wave Energy Conversion System
Authors: Cui Yingjie , Zhang Fei , Chen Zhongxian
Published: May 2023

Ocean wave height is one of the critical factors to decide the efficiency of the ocean wave energy conversion system. Usually, only when the resonate occurs between the ocean wave height (ocean wave speed in the vertical direction) and ocean wave energy conversion system, can the conversion efficiency from ocean wave energy into electric energy be maximized. Therefore, this paper proposes two predication methods to predict the future ocean wave height in 1.5–2.5 s. Firstly, the data fitting of real ocean wave height is achieved by the polynomial method, which is beneficial to the predication of ocean wave height. Secondly, the models of the moving average (MA) predication method and auto regressive (AR) predication method are presented by the time series analysis process. Lastly, after the predication of ocean wave height by the MA method and AR method, and compared with the data fitting result of real ocean wave height, it can be found that the AR method is more accurate for the predication of ocean wave height. In addition, the predication results also indicated that the error between the predication value and true value in the future 2.5 s is considered acceptable, which provides enough time to optimize the operation process of the ocean wave energy conversion system by a suitable control method.
Realistic μPMU Data Generation for Different Real-Time Events in an Unbalanced Distribution Network
Authors: Medattil Ibrahim Abdul Haleem , Sharma Madhu , Subramaniam Rajkumar Vetrivel
Published: May 2023

Monitoring, protection, and control processes are becoming more complex as distributed energy resources (DERs) penetrate distribution networks (DNs). This is due to the inherent nature of power DNs and the bi-directional flow of current from various sources to the loads. To improve the system’s situational awareness, the grid dynamics of the entire DER integration processes must be carefully monitored using synchronized high-resolution real-time measurement data from physical devices installed in the DN. μPMUs have been introduced into the DN to help with this. In comparison to traditional measurement devices, μPMUs can measure voltage, current, and their phasors, in addition to frequency and rate of frequency change (ROCOF). In this study, an approach to generating realistic event data for a real utility DN utilizing strategically installed μPMUs is proposed. The method employs an IEEE 34 test feeder with 12 μPMUs installed in strategic locations to generate real-time events-based realistic μPMU data for various situational awareness applications in an unbalanced DN. The node voltages and line currents were used to analyze the various no-fault and fault events. The author generated the data as part of his PhD research project, utilizing his real-time utility grid operation experience to be used for various situational awareness and fault location studies in a real unbalanced DN. The DN was modeled in DIgSILENT PowerFactory (DP) software. The generated realistic μPMU data can be utilized for developing data-driven algorithms for different event-detection, classification and section-identification research works.
The Development of Renewable Energy in Mineral Resource Clusters—The Case of the Siberian Federal District
Authors: Zhironkin Sergey , Abu-Abed Fares , Dotsenko Elena
Published: May 2023

This article presents a study of the specific features and development factors of renewable energy in macro-regions that combine extractive and industrial clusters with rural, sparsely populated areas. While in some countries—leaders in energy transition (the EU, China)—the growth of investments in solar, wind, and hydropower production is taking place systematically within the framework of an increasing number of national and international strategies and programs, in the Russian Federation there is a lack of renewable generation capacity. Particular difficulties are experienced in regions that, on the one hand, have a developed fuel and raw material complex and, therefore, fuel generation (which makes a significant contribution to global greenhouse gas emissions), and, on the other hand, many rural, sparsely populated areas that are in need of new distributed generation. The aim of the study is to analyze the factors of transition to renewable energy in mineral-resource regions, such as the Siberian Federal District (Siberia), as well as to identify measures to enhance their effectivity. The article shows the place of Siberia in the national energy system and considers the factors related to its energy transition in detail, e.g., the saturation with main powerlines, the control of air pollution caused by fuel energy facilities, its provision with fuel resources, investments in renewable energy, and ways of improving the health and well-being of the local population. Attention is drawn to the challenges and obstacles related to the development of renewable energy in the Siberian Federal District, associated, on the one hand, with Russia’s lagging behind other countries in the dynamics of energy transition, and on the other hand, with external and internal technological and investment restrictions.
Impact of the Operation of Distribution Systems on the Resilience Assessment of Transmission Systems under Ice Disasters
Authors: Wang Zhiwei , Ma Xiao , Gao Song , Wang Changjiang , Li Shuguang
Published: May 2023

Ice disasters, such as ice storms, can cause serious damage to power systems. To understand ice disasters’ influences on power systems, this paper introduces a resilience evaluation frame for transmission and distribution systems during ice disasters. First, we built a vulnerability model for transmission and distribution systems under ice disaster weather. Then, we established an optimal load power shedding model for transmission and distribution systems. After this, according to the vulnerability model and the optimal power load power shedding model, we generated the fault scenario set of a system in the influence of an ice disaster. According to the curve of system resilience, we propose two resilience evaluation indices of transmission and distribution systems under ice disaster weather. Finally, we verified the efficacy and rationalization of the established resilience evaluation framework with an example in which a transmission and distribution system is coupled with a six-bus transmission system and two distribution systems. This study highlights the necessity of resilience assessment of transmission and distribution systems during ice disasters.
Stock Price Forecasting of IBEX35 Companies in the Petroleum, Electricity, and Gas Industries
Authors: Todorov Ivan Borisov , Sánchez Lasheras Fernando
Published: May 2023

In recent years, time series forecasting has become an essential tool for stock market analysts to make informed decisions regarding stock prices. The present research makes use of various exponential smoothing forecasting methods. These include exponential smoothing with multiplicative errors and additive trend (MAN), exponential smoothing with multiplicative errors (MNN), and simple exponential smoothing with additive errors (ANN) for the forecasting of the stock prices of six different companies in the petroleum, electricity, and gas industries that are listed in the IBEX35 index. The database employed for this research contained the IBEX35 index values and stock closing prices from 3 January 2000 to 30 December 2022. The models trained with this data were employed in order to forecast the index value and the closing prices of the stocks under study from 2 January 2023 to 24 March 2023. The results obtained confirmed that although none of the proposed models outperformed the rest for all the companies, it is possible to calculate forecasting models able to predict a 95% confidence interval about real stock closing values and where the index will be in the following three months.
MOF-801/Graphene Adsorbent Material for Greenhouse Climate Control System—Numerical Investigation
Authors: Aziz Andrew N. , Al-Dadah Raya , Mahmoud Saad , Ismail Mohamed A. , Almesfer Mohammed K. , El-Kady Marwa F. , Shokry Hassan
Published: May 2023

Greenhouses with efficient controlled environment offer a promising solution for food security against the impacts of increasing global temperatures and growing water scarcity. However, current technologies used to achieve this controlled environment consume a significant amount of energy, which impacts on operational costs and CO2 emissions. Using advanced metal organic framework materials (MOFs) with superior water adsorption characteristics, this work investigates the development of a new technology for a greenhouse-controlled environment. The system consists of MOF coated heat exchanger, air to air heat exchanger, and evaporative cooler. A three-dimensional computational fluid dynamics (CFD) model was developed using COMSOL software and experimentally validated for the MOF-801/Graphene coated heat exchanger (DCHE) to determine the best cycle time and power input. It was found that using desorption time of 16 min and power input of 1.26 W, the maximum water removal rate was obtained from MOF-801/Graphene of 274.4 g/kgMOF/W.hr. In addition, an overall mathematical model for the greenhouse climate control was developed and used to investigate the effects of air humidity and velocity on the input air conditions to the greenhouse. Results showed that with high relative humidity levels of 90% in the greenhouse can be conditioned to reach the required relative humidity of 50%.
The Role of Hydrochar in Promoting Methane Production from Anaerobic Digestion with Different Inocula
Authors: Sun Jieyi , Zhang Shicheng , Luo Gang
Published: May 2023

Carbon materials, including hydrochar, can promote methane production from anaerobic digestion, and many previous studies have investigated the mechanism by analyzing changes in the microbial community. Based on the fact that the major functional microorganisms have varied in different studies, in order to investigate the effect of inocula on the final microbial composition and to compare the promotion effects of hydrochar on different microorganisms, this study introduced inocula from three distinct sources to anaerobic sequential batch reactors and analyzed the microbial community using 16S rRNA gene sequencing. Hydrochar showed significant promotion effects for all three of the inocula, by increasing microbial activity at high acid concentrations and/or by reducing butyrate accumulation. The dominant microorganisms in all reactors were Clostridium and Methanosarcina, and hydrochar increased the proportion of acetoclastic methanogens. The bacteria which were promoted by hydrochar (e.g., Aminicenantales, Anaerolineaceae and SBR1031 in anaerobic granular sludge and sludge digestate, as well as Lachnospiraceae in food waste digestate) only accounted for around 10%. The bacteria found to be involved in DIET in earlier studies were lacking in this study. It was speculated that hydrochar acted as an electron intermediate and supported microbial aggregation, while the possibility that hydrochar promoted DIET cannot be ruled out.
The Effect of Solid-State Fermentation on the Nutritive Value of Rapeseed Cakes and Performance of Broiler Chickens
Authors: Zaworska-Zakrzewska Anita , Kasprowicz-Potocka Małgorzata , Kierończyk Bartosz , Józefiak Damian
Published: May 2023

This study aimed to assess the applicability of eleven different products of solid-state fermentation of rapeseed cakes with commercial enzyme additives. Ground rapeseed cakes were mixed with water (1:2) and the enzymatic preparation (0.1%) according to the different variants and fermented at 25 °C for 24 h under anaerobic conditions. For fermentation, different enzymes were used: (1) α-amylase, (2) endo 1,4-β-xylanase, (3) endo-1,3(4)β-glucanase, (4) endo 1,4-β-xylanase, endo-1,3(4)β-glucanase, (5) α-amylase, endo-1,3(4)β-glucanase, (6) 6-phytase, (7) RONOZYME HiPhos 6-phytase, (8) liquid exogenous-6-phytase; and mixed combinations: (9) endo 1,4-β-xylanase, endo-1,3(4)β-glucanase, liquid exogenous-6-phytase, (10) α-amylase, endo-1,3(4)β-glucanase, liquid exogenous-6-phytase, and (11) α-amylase, endo 1,4-β-xylanase, endo-1,3(4)β-glucanase, liquid exogenous-6-phytase. After fermentation, the crude protein content in the products was similar, but the true protein content was significantly higher than in nonfermented rapeseed cakes (p < 0.05). Fermentation significantly reduced (p < 0.05) the levels of phytate phosphorous, raffinose family oligosaccharides, and glucosinolates in the products. In the next step, the most advantageous fermentation product obtained using liquid exogenous-6-phytase was selected in terms of nutritional value, produced on the technical scale, and incorporated into the diets for broilers. Six diets containing 12, 17, or 22% raw or fermented rapeseed cakes, respectively, were prepared. Up to 22% fermented rapeseed cakes did not adversely affect broiler production rates. Replacing raw rapeseed cakes with fermented products improved body weight gain in the grower phase, lowered feed intake in the finisher phase, and lowered the feed conversion ratio in all periods. A level of 22% of naturally fermented rapeseed cakes with liquid exogenous-6-phytase in the diet of broilers could be recommended.
Future Internet Architectures on an Emerging Scale—A Systematic Review
Authors: Mohammed Sarfaraz Ahmed , Ralescu Anca L.
Published: May 2023

Future Internet is a general term that is used to refer to the study of new Internet architectures that emphasize the advancements that are paving the way for the next generation of internet. Today’s internet has become more complicated and arduous to manage due to its increased traffic. This traffic is a result of the transfer of 247 billion emails, the management of more than a billion websites and 735 active top-level domains, the viewing of at least one billion YouTube videos per day (which is the source of main traffic), and the uploading of more than 2.5 billion photos to Facebook every year. The internet was never anticipated to provide quality of service (QoS) support, but one can have a best effort service that provides support for video streams and downloaded media applications. Therefore, the future architecture of the internet becomes crucial. Furthermore, the internet as a service has witnessed many evolving conflicts among its stakeholders, leading to extensive research. This article presents a systematic review of the internet’s evolution and discusses the ongoing research efforts towards new internet architectures, as well as the challenges that are faced in increasing the network’s performance and quality. Moreover, as part of these anticipated future developments, this article draws attention to the Metaverse, which combines the emerging areas of augmented reality, virtual reality, mixed reality, and extended reality, and is considered to be the next frontier for the future internet. This article examines the key role of the blockchain in organizing and advancing the applications and services within the Metaverse. It also discusses the potential benefits and challenges of future internet research. Finally, the article outlines certain directions for future internet research, particularly in the context of utilizing blockchains in the Metaverse.
NDN-BDA: A Blockchain-Based Decentralized Data Authentication Mechanism for Vehicular Named Data Networking
Authors: Benmoussa Ahmed , Kerrache Chaker Abdelaziz , Calafate Carlos T. , Lagraa Nasreddine
Published: May 2023

Named Data Networking (NDN) is an implementation of Information-Centric Networking (ICN) that has emerged as a promising candidate for the Future Internet Architecture (FIA). In contrast to traditional networking protocols, NDN’s focus is on content, rather than the source of the content. NDN enables name-based routing and location-independent data retrieval, which gives NDN the ability to support the highly dynamic nature of mobile networks. Among other important features, NDN integrates security mechanisms and prioritizes protecting content over communication channels through cryptographic signatures. However, the data verification process that NDN employs may cause significant delays, especially in mobile networks and vehicular networks. This aspect makes it unsuitable for time-critical and sensitive applications such as the sharing of safety messages. Therefore, in this work, we propose NDN-BDA, a blockchain-based decentralized mechanism that provides a faster and more efficient data authenticity mechanism for NDN-based vehicular networks.
Benchmarking Change Detector Algorithms from Different Concept Drift Perspectives
Authors: Sakurai Guilherme Yukio , Lopes Jessica Fernandes , Zarpelão Bruno Bogaz , Barbon Junior Sylvio
Published: May 2023

The stream mining paradigm has become increasingly popular due to the vast number of algorithms and methodologies it provides to address the current challenges of Internet of Things (IoT) and modern machine learning systems. Change detection algorithms, which focus on identifying drifts in the data distribution during the operation of a machine learning solution, are a crucial aspect of this paradigm. However, selecting the best change detection method for different types of concept drift can be challenging. This work aimed to provide a benchmark for four drift detection algorithms (EDDM, DDM, HDDMW, and HDDMA) for abrupt, gradual, and incremental drift types. To shed light on the capacity and possible trade-offs involved in selecting a concept drift algorithm, we compare their detection capability, detection time, and detection delay. The experiments were carried out using synthetic datasets, where various attributes, such as stream size, the amount of drifts, and drift duration can be controlled and manipulated on our generator of synthetic stream. Our results show that HDDMW provides the best trade-off among all performance indicators, demonstrating superior consistency in detecting abrupt drifts, but has suboptimal time consumption and a limited ability to detect incremental drifts. However, it outperforms other algorithms in detection delay for both abrupt and gradual drifts with an efficient detection performance and detection time performance.
A Distributed Sensor System Based on Cloud-Edge-End Network for Industrial Internet of Things
Authors: Wang  Mian , Xu Cong’an , Lin Yun , Lu Zhiyi , Sun Jinlong , Gui Guan
Published: May 2023

The Industrial Internet of Things (IIoT) refers to the application of the IoT in the industrial field. The development of fifth-generation (5G) communication technology has accelerated the world’s entry into the era of the industrial revolution and has also promoted the overall optimization of the IIoT. In the IIoT environment, challenges such as complex operating conditions and diverse data transmission have become increasingly prominent. Therefore, studying how to collect and process a large amount of real-time data from various devices in a timely, efficient, and reasonable manner is a significant problem. To address these issues, we propose a three-level networking model based on distributed sensor self-networking and cloud server platforms for networking. This model can collect monitoring data for a variety of industrial scenarios that require data collection. It enables the processing and storage of key information in a timely manner, reduces data transmission and storage costs, and improves data transmission reliability and efficiency. Additionally, we have designed a feature fusion network to further enhance the amount of feature information and improve the accuracy of industrial data recognition. The system also includes data preprocessing and data visualization capabilities. Finally, we discuss how to further preprocess and visualize the collected dataset and provide a specific algorithm analysis process using a large manipulator dataset as an example.
System Performance Analysis of Sensor Networks for RF Energy Harvesting and Information Transmission
Authors: Lei Kuncheng , Zhang Zhenrong
Published: May 2023

This paper investigates the problem of RF energy harvesting in wireless sensor networks, with the aim of finding a suitable communication protocol by comparing the performance of the system under different protocols. The network is made up of two parts: first, at the beginning of each timeslot, the sensor nodes harvest energy from the base station (BS) and then send packets to the BS using the harvested energy. For the energy-harvesting part of the wireless sensor network, we consider two methods: point-to-point and multi-point-to-point energy harvesting. For each method, we use two independent control protocols, namely head harvesting energy of each timeslot (HHT) and head harvesting energy of dedicated timeslot (HDT). Additionally, for complex channel states, we derive the cumulative distribution function (CDF) of packet transmission time using selective combining (SC) and maximum ratio combining (MRC) techniques. Analytical expressions for system reliability and packet timeout probability are obtained. At the same time, we also utilize the Monte Carlo simulation method to simulate our system and have analyzed both the numerical and simulation solutions. Results show that the performance of the HHT protocol is better than that of the HDT protocol, and the MRC technology outperforms the SC technology for the HHT protocol in terms of the energy-harvesting efficiency coefficient, sensor positions, transmit signal-to-noise ratio (SNR), and length of energy harvesting time.
Evaluating Traffic Operation Conditions during Wildfire Evacuation Using Connected Vehicles Data
Authors: Ahmad Salman , Ali Asad , Ahmed Hafiz Usman , Huang Ying , Lu Pan
Published: May 2023

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over the world, particularly in the Western United States. Communities in wildland–urban interface (WUI) areas are at the greatest risk of fire. Such fires cause mass evacuations and can result in traffic congestion, endangering the lives of both citizens and first responders. While existing wildfire evacuation research focuses on social science surveys and fire spread modeling, they lack data on traffic operations during such incidents. Additionally, traditional traffic data collection methods are unable to gather large sets of data on historical wildfire events. However, the recent availability of connected vehicle (CV) data containing lane-level precision historical vehicle movement data has enabled researchers to assess traffic operational performance at the region and timeframe of interest. To address this gap, this study utilized a CV dataset to analyze traffic operations during a short-notice evacuation event caused by a wildfire, demonstrating that the CV dataset is an effective tool for accurately assessing traffic delays and overall traffic operation conditions during the selected fire incident. The findings also showed that the selected CV dataset provides high temporal coverage and similar travel time estimates as compared to an alternate method of travel time estimation. The study thus emphasized the importance of utilizing advanced technologies, such as CV data, to develop effective evacuation strategies and improve emergency management.
Dynamics of Age-Structure Smoking Models with Government Intervention Coverage under Fractal-Fractional Order Derivatives
Authors: Addai Emmanuel , Adeniji Adejimi , Peter Olumuyiwa J. , Agbaje Janet O. , Oshinubi Kayode
Published: May 2023

The rising tide of smoking-related diseases has irreparably damaged the health of both young and old people, according to the World Health Organization. This study explores the dynamics of the age-structure smoking model under fractal-fractional (F-F) derivatives with government intervention coverage. We present a new fractal-fractional model for two-age structure smokers in the Caputo–Fabrizio framework to emphasize the potential of this operator. For the existence-uniqueness criterion of the given model, successive iterative sequences are defined with limit points that are the solutions of our proposed age-structure smoking model. We also use the functional technique to demonstrate the proposed model stability under the Ulam–Hyers condition. The two age-structure smoking models are numerically characterized using the Newton polynomial. We observe that in Groups 1 and 2, a change in the fractal-fractional orders has a direct effect on the dynamics of the smoking epidemic. Moreover, testing the inherent effectiveness of government interventions shows a considerable impact on potential, occasional, and temporary smokers when the fractal-fractional order is 0.95. It is the view that this study will contribute to the applicability of the schemes, the rich dynamics of the fractal, and the fractional perspective of future predictions.
Investigation of the Second-Order Hankel Determinant for Sakaguchi-Type Functions Involving the Symmetric Cardioid-Shaped Domain
Authors: Ullah Khalil , Arif Muhammad , Aldawish Ibtisam Mohammed , El-Deeb Sheza M.
Published: May 2023

Determining the sharp bounds for coefficient-related problems that appear in the Taylor–Maclaurin series of univalent functions is one of the most difficult aspects of studying geometric function theory. The purpose of this article is to establish the sharp bounds for a variety of problems, such as the first three initial coefficient problems, the Zalcman inequalities, the Fekete–Szegö type results, and the second-order Hankel determinant for families of Sakaguchi-type functions related to the cardioid-shaped domain. Further, we study the logarithmic coefficients for both of these classes.
RETRACTED: Fractional Model of Electron–Phonon Interaction
Authors: Kulish Vladimir , Aslfattahi Navid , Schmirler Michal
Published: May 2023

Based on the derivation of the equation of state for systems with a fractional power spectrum, the relationship between the van der Waals constant and the fractional derivative order has been established. The fractional model of electron–phonon interaction has received additional consideration, which may be pertinent when interpreting the experimental results. This model is valuable for describing superconductivity at high temperatures because it predicts relatively large values for the electron–phonon interaction constant.
Multifunctional Finishing of Cotton Fabric with Curcumin Derivatives Coatings Obtained by Sol–Gel Method
Authors: Raduly Florentina Monica , Rădițoiu Valentin , Rădițoiu Alina , Frone Adriana Nicoleta , Nicolae Cristian Andi , Răut Iuliana , Constantin Mariana , Grapin Maria
Published: May 2023

Textile materials with fluorescent, repellent, or antimicrobial properties are increasingly used in common applications. Obtaining multi-functional coatings is of wide interest, especially for applications related to signaling or to the medical field. In order to increase the performance (color properties, fluorescence lifetime, self-cleaning or antimicrobial properties) of textile materials with special uses, a series of research was carried out regarding the modification of surfaces with nanosols. In this study, coatings with multiple properties were obtained by depositing nanosols on cotton fabrics generated through sol–gel reactions. These multifunctional coatings are hybrid materials in which the host matrix is generated using tetraethylorthosilicate (TEOS) and network modifying organosilanes:dimethoxydimethylsilane (DMDMS) or dimethoxydiphenylsilane (DMDPS) in a 1:1 mass ratio. Two curcumin derivatives were embedded in siloxane matrices, a yellow one (CY) that is identical to bis-demethoxycurcumin (one of the natural constituents in turmeric) and a red dye (CR) that has a N,N-dimethylamino group grafted in position 4 of the dicinnamoylmethane skeleton of curcumin. The nanocomposites obtained by embedding curcumin derivatives in siloxane matrices were deposited on cotton fabric and studied in relation to the dye and the type of host matrix. Fabrics coated with such systems provide a hydrophobic surface, have fluorescent and antimicrobial properties, change color depending on the pH, and therefore can be used in various fields where textiles provide signaling properties, self-cleaning, or antibacterial protection. The coated fabrics maintained their good multifunctional properties even after several washing cycles.
A Novel Bio-Adhesive Mesh System for Medical Implant Applications: In Vivo Assessment in a Rabbit Model
Authors: Harman Melinda , Champaigne Kevin , Cobb William , Lu Xinyue , Chawla Varun , Wei Liying , Luzinov Igor , Mefford O. Thompson , Nagatomi Jiro
Published: May 2023

Injectable surgical sealants and adhesives, such as biologically derived fibrin gels and synthetic hydrogels, are widely used in medical products. While such products adequately adhere to blood proteins and tissue amines, they have poor adhesion with polymer biomaterials used in medical implants. To address these shortcomings, we developed a novel bio-adhesive mesh system utilizing the combined application of two patented technologies: a bifunctional poloxamine hydrogel adhesive and a surface modification technique that provides a poly-glycidyl methacrylate (PGMA) layer grafted with human serum albumin (HSA) to form a highly adhesive protein surface on polymer biomaterials. Our initial in vitro tests confirmed significantly improved adhesive strength for PGMA/HSA grafted polypropylene mesh fixed with the hydrogel adhesive compared to unmodified mesh. Toward the development of our bio-adhesive mesh system for abdominal hernia repair, we evaluated its surgical utility and in vivo performance in a rabbit model with retromuscular repair mimicking the totally extra-peritoneal surgical technique used in humans. We assessed mesh slippage/contraction using gross assessment and imaging, mesh fixation using tensile mechanical testing, and biocompatibility using histology. Compared to polypropylene mesh fixed with fibrin sealant, our bio-adhesive mesh system exhibited superior fixation without the gross bunching or distortion that was observed in the majority (80%) of the fibrin-fixed polypropylene mesh. This was evidenced by tissue integration within the bio-adhesive mesh pores after 42 days of implantation and adhesive strength sufficient to withstand the physiological forces expected in hernia repair applications. These results support the combined use of PGMA/HSA grafted polypropylene and bifunctional poloxamine hydrogel adhesive for medical implant applications.
Lagging Strand Initiation Processes in DNA Replication of Eukaryotes—Strings of Highly Coordinated Reactions Governed by Multiprotein Complexes
Authors: Nasheuer Heinz Peter , Onwubiko Nichodemus O.
Published: May 2023

In their influential reviews, Hanahan and Weinberg coined the term ‘Hallmarks of Cancer’ and described genome instability as a property of cells enabling cancer development. Accurate DNA replication of genomes is central to diminishing genome instability. Here, the understanding of the initiation of DNA synthesis in origins of DNA replication to start leading strand synthesis and the initiation of Okazaki fragment on the lagging strand are crucial to control genome instability. Recent findings have provided new insights into the mechanism of the remodelling of the prime initiation enzyme, DNA polymerase α-primase (Pol-prim), during primer synthesis, how the enzyme complex achieves lagging strand synthesis, and how it is linked to replication forks to achieve optimal initiation of Okazaki fragments. Moreover, the central roles of RNA primer synthesis by Pol-prim in multiple genome stability pathways such as replication fork restart and protection of DNA against degradation by exonucleases during double-strand break repair are discussed.
Metformin Resistance Is Associated with Expression of Inflammatory and Invasive Genes in A549 Lung Cancer Cells
Authors: Seo Dong Soo , Joo Sungmin , Baek Seungwoo , Kang Jaehyeon , Kwon Taeg Kyu , Jang Younghoon
Published: May 2023

Metformin, the most commonly used drug for type 2 diabetes, has recently been shown to have beneficial effects in patients with cancer. Despite growing evidence that metformin can inhibit tumor cell proliferation, invasion, and metastasis, studies on drug resistance and its side effects are lacking. Here, we aimed to establish metformin-resistant A549 human lung cancer cells (A549-R) to determine the side effects of metformin resistance. Toward this, we established A549-R by way of prolonged treatment with metformin and examined the changes in gene expression, cell migration, cell cycle, and mitochondrial fragmentation. Metformin resistance is associated with increased G1-phase cell cycle arrest and impaired mitochondrial fragmentation in A549 cells. We demonstrated that metformin resistance highly increased the expression of proinflammatory and invasive genes, including BMP5, CXCL3, VCAM1, and POSTN, using RNA-seq analysis. A549-R exhibited increased cell migration and focal adhesion formation, suggesting that metformin resistance may potentially lead to metastasis during anti-cancer therapy with metformin. Taken together, our findings indicate that metformin resistance may lead to invasion in lung cancer cells.
Exploring the Diet-Gut Microbiota-Epigenetics Crosstalk Relevant to Neonatal Diabetes
Authors: Alsharairi Naser A.
Published: May 2023

Neonatal diabetes (NDM) is a rare monogenic disorder that presents as hyperglycemia during the first six months of life. The link between early-life gut microbiota dysbiosis and susceptibility to NDM remains uncertain. Experimental studies have demonstrated that gestational diabetes mellitus (GDM) could develop into meconium/gut microbiota dysbiosis in newborns, and thus, it is thought to be a mediator in the pathogenesis of NDM. Epigenetic modifications have been considered as potential mechanisms by which the gut microbiota and susceptibility genes interact with the neonatal immune system. Several epigenome-wide association studies have revealed that GDM is associated with neonatal cord blood and/or placental DNA methylation alterations. However, the mechanisms linking diet in GDM with gut microbiota alterations, which may in turn induce the expression of genes linked to NDM, are yet to be unraveled. Therefore, the focus of this review is to highlight the impacts of diet, gut microbiota, and epigenetic crosstalk on altered gene expression in NDM.
Metabarcoding of Antarctic Lichens from Areas with Different Deglaciation Times Reveals a High Diversity of Lichen-Associated Communities
Authors: Beck Andreas , Casanova-Katny Angélica , Gerasimova Julia
Published: May 2023

Lichens have developed numerous adaptations to optimise their survival under harsh abiotic stress, colonise different substrates, and reach substantial population sizes and high coverage in ice-free Antarctic areas, benefiting from a symbiotic lifestyle. As lichen thalli represent consortia with an unknown number of participants, it is important to know about the accessory organisms and their relationships with various environmental conditions. To this end, we analysed lichen-associated communities from Himantormia lugubris, Placopsis antarctica, P. contortuplicata, and Ramalina terebrata, collected from soils with differing deglaciation times, using a metabarcoding approach. In general, many more Ascomycete taxa are associated with the investigated lichens compared to Basidiomycota. Given our sampling, a consistently higher number of lichen-associated eukaryotes are estimated to be present in areas with deglaciation times of longer than 5000 years compared to more recently deglaciated areas. Thus far, members of Dothideomycetes, Leotiomycetes, and Arthoniomycetes have been restricted to the Placopsis specimens from areas with deglaciation times longer than 5000 years. Striking differences between the associated organisms of R. terebrata and H. lugubris have also been discovered. Thus, a species-specific basidiomycete, Tremella, was revealed for R. terebrata, as was a member of Capnodiales for H. lugubris. Our study provides further understanding of the complex terricolous lichen-associated mycobiome using the metabarcoding approach. It also illustrates the necessity to extend our knowledge of complex lichen symbiosis and further improve the coverage of microbial eukaryotes in DNA barcode libraries, including more extended sampling.