bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electronic nonequilibrium effect in ultrafast-laser-irradiated solids
Authors: Medvedev Nikita 
Published: December 2023

Abstract
This paper describes the effects of electronic nonequilibrium in a simulation of ultrafast laser irradiation of materials. The simulation scheme based on tight-binding molecular dynamics, in which the electronic populations are traced with a combined Monte Carlo and Boltzmann equation, enables the modeling of nonequilibrium, nonthermal, and nonadiabatic (electron-phonon coupling) effects simultaneously. The electron-electron thermalization is described within the relaxation-time approximation, which automatically restores various known limits such as instantaneous thermalization (the thermalization time

τ

e
−
e

→
0

) and Born-Oppenheimer (BO) approximation (

τ

e
−
e

→
∞

). The results of the simulation suggest that the non-equilibrium state of the electronic system slows down electron-phonon coupling with respect to the electronic equilibrium case in all studied materials: metals, semiconductors, and insulators. In semiconductors and insulators, it also alters the damage threshold of ultrafast nonthermal phase transitions induced by modification of the interatomic potential due to electronic excitation. It is demonstrated that the models that exclude electron-electron thermalization (using the assumption of

τ

e
−
e

→
∞
,

such as BO or Ehrenfest approximations) may produce qualitatively different results, and a reliable model should include all three effects: electronic nonequilibrium, nonadiabatic electron-ion coupling, and nonthermal evolution of interatomic potential.
Thermodynamic and dynamic contributions to the abrupt increased winter Arctic sea ice growth since 2008
Authors: Yi Daling Li , Fan Ke , He Shengping 
Published: December 2023

Abstract
The area of Arctic winter sea ice growth (WSIG) has expanded dramatically since winter 2008. Yet the thermodynamic and dynamic contributions to the abrupt increase in WSIG remain unclear. Here using an ice concentration budget, we characterized quantitatively the increasing WSIG and revealed the relative contributions of dynamics during 1985–2021. Ice dynamics related to ice convergence/divergence are compared in two representative regions. The northern Laptev Sea is a freezing-dominated ice growth region and is competitively driven by the ice convergence. While in northwest Beaufort Gyre (BG), the combined effects of freezing and ice divergence have both enhanced since 2008, and the dynamics contribute 84% to the significant WSIG intensification since 2008. Comparison of thermodynamic and dynamic contributions emphasized that the winter sea-ice expansion is influenced not only by winter freeze, but also by convergence/divergence relative to newly formed thinner and mobile ice. Furthermore, the amplified summer Beaufort High in the mid-2000s and its long-lasting memory of the wind-driven strengthened BG are partially attributed to the abrupt increased WSIG since 2008.
Overview of Axial Flux Permanent Magnet Generator for Small-Scale Industry
Authors: Mostaman Nur Afiqah , Sulaiman Erwan , Jenal Mahyuzie 
Published: December 2023

Abstract
A magnetic generator is not like a conventional generator that is produced by the coil. Consequently, this generator used the permanent magnetic field to produce magnetic flux energy. Although, most of the permanent magnet designs produce less aggressive copper winding. This paper provides an overview of axial flux permanent magnet generators for small-scale industries. First of all, the classification and a detailed overview of permanent magnet generators are presented first. The main characteristics of the generators together with their benefits and drawbacks are highlighted. Additionally, an overview of the most recent machine developments is also presented. The design of convenient permanent magnet generators that have been used to create small-scale generator varieties is then reviewed to conclude the most suitable design among axial flux which is the sandwiched construction.
Design Data Logger for PV Analyzer Based on Arduino
Authors: Effendi Asnal , Dewi Arfita Yuana , Antonov  
Published: December 2023

Abstract
Designing a data logger for an Arduino-based PV analyzer. The goal is to analyze the energy yield of PV. The sensors used are current and voltage sensors integrated into the data logger board to measure parameters that affect the efficiency value of the PV array. Analyzers help measure and record output parameters of PV systems such as current, voltage, and power. The device also can store parameter data such as Temperature affecting PV performance. The advantage of using data loggers is that data can be collected automatically over some time. Additionally, the data can be displayed in the form of V-I and P-V diagrams for analytical purposes. This sequential design can be used for PV systems that provide many components with a specific power. Test-bench results were recorded at a maximum output of 20,016W. This type of data logger can be used as a portable recorder for measuring PV performance in different areas.
The Influence of Nanofluid Characteristics on the Thermal Performance of Photovoltaic Thermal System
Authors: Umam Mukhamad Faeshol , Hasanuzzaman Md , Rahim Nasrudin Abd 
Published: December 2023

Abstract
Optimal solar energy utilization can be achieved with a Photovoltaic Thermal (PVT) system, which simultaneously produces electricity and heat. PVT generally uses water as heat transfer fluid to cool the PV cells while transporting heat for other purposes. However, water has low thermal conductivity and capacity as a heat transfer fluid. Nanofluid, which is popular in heat exchanger applications, has also been researched and tested for use in improving the performance of PVT systems. The superior thermal conductivity of nanofluid could produce a PVT system efficiency of up to 89.75%. However, nanofluid applications in the PVT system still face challenges, especially in their preparation and properties. This study determines the properties of nanofluids that could improve the electrical and thermal performance of PVT systems. The authors found that preparation procedures for manufacturing nanofluids were essential for researchers to consider before applying nanofluids. Also, some disadvantages of nanofluids are still an obstacle in their application, especially economic issues and adverse environmental effects.
Thermal behaviour of Paraffin-MWCNT stabilized by Sodium dodecylbenzene sulphonate nano-enhanced phase change material for energy storage applications
Authors: Bhutto Yasir Ali , Pandey A. K. , Saidur R. , Laghari Imtiaz Ali , Buddhi D. , Tyagi V.V. 
Published: December 2023

Abstract
The Phase change materials (PCMs) possess the great potential to store renewable and sustainable thermal energy that can mitigate the issue of energy to a great extent. However, the low thermal conductivity hinders the extensive use of PCM in various applications. To alleviate this deficiency, the PCMs are often incorporated with highly conductive nanoparticles. The carbon-based nanoparticles are highly regarded to be a promising option because of their elevated thermal conductivity like Multiwall carbon-nanotube (MWCNT). However, these highly conductive nanoparticles sometimes exhibit the issue of non-uniform dispersion with PCM. In this paper, we report the use of surface-modified MWCNT by using stabilized Sodium dodecylbenzene sulphonate surfactant (SDBS) with Paraffin wax (PW) RT47 at wt% 0.1 and 0.3 of MWCNT. The sample is created by using two-step method. Further, for characterization; chemical composition by Fourier transform infrared spectroscopy (FTIR), thermal conductivity by thermal property analyzer (TEMPOs) and for thermal stability, thermal gravimetric analyzer (TGA) is used. The results showed a significant enhancement in the thermal conductivity of composite PCM, the inclusion of 0.1 and 0.3 wt% of surface-modified MWCNT increased the thermal conductivity up to 51.29% and 76.5% respectively. The FT-IR confirms that the components are physically mixed in NePCM composite, no chemical reaction appeared as no displacement of characteristic peaks or a new peaks appeared. TGA results showed the prepared nano-enhanced phase change material (NePCM) is stable. Thus, surface modification of MWCNT by using SDBS for PW can be the effective method to boost the overall performance of NePCM without losing its basic characteristics. Therefore, based on results, it can be concluded that the surface modified Paraffin/MWCNT NePCM is well suited for applications like energy storage, photovoltaic thermal system, and battery thermal management. PCM showed enhanced thermo-physical properties. Therefore, it might be the candidate for energy storage and other thermal practical applications in future.
Series Motor Four Quadrants DC Chopper For DC Drive Electric Vehicle Driving Cycle Test
Authors: Hazrimy Fathul , Arof Saharul , Mawby Philip , Arof Hamzah , Noorsal Emilia 
Published: December 2023

Abstract
The most common need for electric car is to be able to carry a maximum load of 850-1300 kg. The expected maximum speed of the electric vehicle (EC) is about at 110-120 km/h and the acceleration is for 60Km/h in less than 10 seconds. To determine whether the DC Drive EV performance is up to a standard requirement for the end user’s such as maximum speed, cruising speed, acceleration, deceleration, stability, safety, etc., an EV’s full design must go through some sort of testing. This study examined the use of a series motor and a four-quadrant DC chopper (FQDC) for typical driving cycle tests like the New European Driving Cycle to test these special requirements of a DC drive electric automobile (NEDC). Using Matlab/Simulink software and vehicle dynamics equations, a simulation model of the DC Drive EV is created in order to examine and investigate the performance under the NEDC test applied to the FQDC in order to make sure that it complies with the NEDC requirements. From the test findings, it can be inferred that the FQDC is capable of meeting all NEDC standards.
Stratification and Radiation of Heat in Hybrid Gold-Graphene/Ethylene Glycol Nanofluid Flows Past a Leaning Cylinder
Authors: Ghani S N A , Noor N F M 
Published: December 2023

Abstract
Hybrid gold-graphene/ethylene-glycol (EG) nanofluid past a permeable leaning cylinder is devoted in the current investigation under the effect of thermal radiation and stratification. The governing partial differential equations are reformulated into nonlinear ordinary differential equations by implementing similarity terms. A shooting approach is elected to reformulate the equations into a boundary value problem which is determined by applying a bvp4c code in MATLAB. The effects of selected parameters regarding the recent model on dimensionless velocity and temperature disseminations, reduced skin friction coefficient and reduced Nusselt number are analyzed and presented in graphs and tables. It is perceived that by rising the value of the thermal stratification and radiation parameter, the reduced Nusselt number for the preferred mono and hybrid nanofluids will be declined. The reduced Nusselt number is reported to be the highest value when considering hybrid gold (ϕ

s1=0.02)-graphene (ϕ

s2 = 0.04)/EG nanofluid.
Performance Simulation of PVT System Using TRNSYS for Varying Mass Flow Rates
Authors: Sekhar Y Raja , Rao V Tirupati , Amal Krishna T S , Gurusree S , Lal Hitesh 
Published: December 2023

Abstract
Solar collector hybrids called photovoltaic thermal (PVT) collectors use solar energy to produce both electrical and thermal energy. System simulations are widely used as a first stage before testing in real-world applications to discover the best solutions and new applications for PVT collectors. Therefore, the construction of well-validated PVT collector models is a vital effort at this time. In this paper, the authors validated the experimental data with the simulation results obtained from TRNSYS software under similar conditions. The analysis was carried out with water as the working fluid, and at different mass flow rates for PVT collectors for varying operating conditions during the day. The authors compared outlet water temperature values from the PVT collector obtained through experiments and simulation. The minimum and maximum deviation of estimated outlet water temperature from the simulation is -3% to 8% respectively for different mass flow rates.
Performance Analysis of a Switched-Mode Flyback DC-DC Converter with Influence of Non-Ideal Switching Devices
Authors: Kamar Shazlin Shafiqah Shamsul , Azmi Syahrul Ashikin , Isa Zainuddin Mat 
Published: December 2023

Abstract
This paper approach for the performance analysis of a dc-dc flyback converter for low power application. Modelling is done with parasitic components for non-ideal flyback converter. Ac and dc input characteristic of the flyback converter are analysed and investigated by PSIM simulations and calculations. The influence of parasitic effects in converter components on input characteristic is studied in continuous conduction mode (CCM). The results of the calculation based on analytical formula and averaged models are in a good accordance with PSIM simulations and calculation. The goal of this project is to compare an ideal and non-ideal condition in order to see the effect on the efficiency and ability of the converter to control the output voltage. The converter is expected to be operated in continuous conduction mode at all time and focus application is low power application that less than 100W.
Casting light on the tribological properties of paraffin-based HDPE enriched with graphene nano-additives: an experimental investigation
Authors: Nabhan Ahmed , Fouly Ahmed , Albahkali Thamer , Shar Muhammad Ali , Abdo Hany S , Taha Mohamed 
Published: December 2023

Abstract
The impressive mechanical properties and robust resistance to wear recorded by nano-polymeric composites have positioned them as a viable alternative in many applications. When it comes to frictional materials, high-density polyethylene (HDPE) emerges as one of the best candidate materials that can be used. However, it tribological properties need more enhancement to suite with wide variety of applications. The objective of the current study is to identify the optimal loading ratio using a comprise of paraffin oil and nano-graphene with varying loading compositions. Different experiments were carried out to assess the modulus of elasticity, hardness, and strength. Additionally, the friction coefficient and wear resistance of the proposed nanocomposite have been estimated. Surfaces topographies were analyzed to recognize the wear mechanism. The results pointed that samples containing 5% paraffin oil and 0.5 wt% have relatively better mechanical and tribological behavior compared to further compositions; where, a 38% decrease in wear and a 34% reduction in COF compared to other composite samples.
From trash to treasure: crafting electrochemical supercapacitors with recycled waste materials
Authors: Padha Bhavya , Verma Sonali , Ahmed Aamir , Chavhan Madhav P , Mahajan Prerna , Arya Sandeep 
Published: December 2023

Abstract
Over the past few decades, there has been a massive increase in research focused on the global need for renewable energy sources. Numerous studies and reports in the literature have been conducted on technologies like wind and solar energy. However, partly due to expense and the difficulty of providing service during off-peak hours, these technologies have not been widely used all over the world. Over the past several decades, research on energy storage systems has increased to make such systems more competitive and advanced. This envisions formulating an energy storage system with cost-efficient power storage during off-peak hours for later distribution. A supercapacitor (SC) is an example of energy storage and delivery technology that accumulates and transfers energy rapidly, providing a considerable amount of current for a short time. SC technology research and development have proliferated during the last ten years. In particular, this review highlights the advancements made in SCs to provide solutions to problems associated with solid waste management (SWM) and energy usage. It begins with the introduction to SCs, wastes, SWM, waste hierarchy, and essential waste products that can be utilized to fabricate the electrodes of SCs. A brief discussion is made regarding recycling and concern for environmental pollution. Prominent recycling techniques and materials have been overviewed, followed by the performance of such waste products-derived SC electrodes. The summary concludes with the authors’ views and discusses the future scope and unstated challenges.
Bursting dynamics in a spiking neuron with a memristive voltage-gated channel
Authors: Wu Jiaming , Wang Kang , Schneegans Olivier , Stoliar Pablo , Rozenberg Marcelo 
Published: December 2023

Abstract
We introduce a voltage-gated conductance model for an artificial neuron that exhibits tonic, fast, and two types of intrinsic burst spiking. The spike generation is achieved with a single voltage-gated channel that exploits the conductance commutation properties of a two-terminal memristive device. Our circuit implementation is of unprecedented simplicity, using just four electronic components, all conventional, cheap and out-of-the-shelf. Our bursting neuron is a two-compartment model, similar to the Pinsky–Rinzel model. We obtain the full phase diagram and discuss the origin of the different regions. We find that the spike traces of the model bare striking similarity to experimental biological neuronal recordings. Our work may open a new way to investigate neural pathologies, such as epilepsy and Parkinson’s disease, from the study of the phase diagram and the transitions between spiking states of physical neuron models.
Carbon storage in the built environment: a review
Authors: Bjånesøy Stavroula , Kinnunen Antti , Einarsdóttir Hulda , Heinonen Jukka 
Published: December 2023

Abstract
With a rapidly decreasing carbon budget, the urgency of deep greenhouse gas reductions becomes increasingly necessary. This accentuates the need for the emerging paradigm shift, transforming the built environment from a major source of CO2 emissions to a carbon sink. Biogenic carbon sequestration and storage (CSS) has the potential to play a pivotal role as it offers multiple pathways for cities to improve their carbon sink capacity. There are various methods used to quantify the carbon storage potential of the built environment, and there is a lack of consensus on how biogenic carbon should be treated. This review aims to elucidate the ways in which scientific literature has considered carbon storage in the built environment by drawing a picture of the existing mechanism for CSS in the urban built environment with the focus on the existing mechanism of biogenic CSS materials. Limitations and challenges of using biogenic CSS materials are identified to point out future research directions. In addition, barriers hindering wider utilization of CSS in the built environment are discussed.
Estimating protection afforded by prior infection in preventing reinfection: applying the test-negative study design
Authors: Ayoub Houssein H , Tomy Milan , Chemaitelly Hiam , Altarawneh Heba N , Coyle Peter , Tang Patrick , Hasan Mohammad R , Al Kanaani Zaina , Al Kuwari Einas , Butt Adeel A , Jeremijenko Andrew , Kaleeckal Anvar Hassan , Latif Ali Nizar , Shaik Riyazuddin Mohammad , Nasrallah Gheyath K , Benslimane Fatiha M , Al Khatib Hebah A , Yassine Hadi M , Al Kuwari Mohamed G , Al Romaihi Hamad Eid , Abdul-Rahim Hanan F , Al-Thani Mohamed H , Al Khal Abdullatif , Bertollini Roberto , Abu-Raddad Laith J 
Published: December 2023

Abstract
The COVID-19 pandemic has highlighted the need to use infection testing databases to rapidly estimate effectiveness of prior infection in preventing reinfection ($P{E}_S$) by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Mathematical modeling was used to demonstrate a theoretical foundation for applicability of the test-negative, case–control study design to derive $P{E}_S$. Apart from the very early phase of an epidemic, the difference between the test-negative estimate for $P{E}_S$ and true value of $P{E}_S$ was minimal and became negligible as the epidemic progressed. The test-negative design provided robust estimation of $P{E}_S$ and its waning. Assuming that only 25% of prior infections are documented, misclassification of prior infection status underestimated $P{E}_S$, but the underestimate was considerable only when &gt; 50% of the population was ever infected. Misclassification of latent infection, misclassification of current active infection, and scale-up of vaccination all resulted in negligible bias in estimated $P{E}_S$. The test-negative design was applied to national-level testing data in Qatar to estimate $P{E}_S$ for SARS-CoV-2. $P{E}_S$ against SARS-CoV-2 Alpha and Beta variants was estimated at 97.0% (95% CI, 93.6-98.6) and 85.5% (95% CI, 82.4-88.1), respectively. These estimates were validated using a cohort study design. The test-negative design offers a feasible, robust method to estimate protection from prior infection in preventing reinfection.
DeepWalk-aware graph attention networks with CNN for circRNA–drug sensitivity association identification
Authors: Li Guanghui , Li Youjun , Liang Cheng , Luo Jiawei 
Published: December 2023

Abstract
Circular RNAs (circRNAs) are a class of noncoding RNA molecules that are widely found in cells. Recent studies have revealed the significant role played by circRNAs in human health and disease treatment. Several restrictions are encountered because forecasting prospective circRNAs and medication sensitivity connections through biological research is not only time-consuming and expensive but also incredibly ineffective. Consequently, the development of a novel computational method that enhances both the efficiency and accuracy of predicting the associations between circRNAs and drug sensitivities is urgently needed. Here, we present DGATCCDA, a computational method based on deep learning, for circRNA–drug sensitivity association identification. In DGATCCDA, we first construct multimodal networks from the original feature information of circRNAs and drugs. After that, we adopt DeepWalk-aware graph attention networks to sufficiently extract feature information from the multimodal networks to obtain the embedding representation of nodes. Specifically, we combine DeepWalk and graph attention network to form DeepWalk-aware graph attention networks, which can effectively capture the global and local information of graph structures. The features extracted from the multimodal networks are fused by layer attention, and eventually, the inner product approach is used to construct the association matrix of circRNAs and drugs for prediction. The ultimate experimental results obtained under 5-fold cross-validation settings show that the average area under the receiver operating characteristic curve value of DGATCCDA reaches 91.18%, which is better than those of the five current state-of-the-art calculation methods. We further guide a case study, and the excellent obtained results also show that DGATCCDA is an effective computational method for exploring latent circRNA–drug sensitivity associations.