bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural stability, mechanical, and thermodynamic properties under pressure of B2-type CuM (M = Be, Al, and Zn) alloys: a DFT investigation
Authors: Zhang Leilei , Yang Baocheng , Huang Tengfei , Wang Shuaiwei , Wu Donghai , Wei Yaru , Chen Houyang 
Published: April 2024

Abstract
In this work, we systematically examined the structural stability, mechanical properties, and thermodynamic behavior of B2-type CuBe alloy, and compared the results with isostructural Cu-based alloys (CuAl and CuZn) by employing first-principles calculations in the pressure range of −22 to 100 GPa. This study revealed the stable existence of CuBe alloy at low-density expansion states (e.g. ∼ −20 GPa), indicating its superior structural stability compared to CuAl and CuZn. The pressure dependence of properties such as cell parameter a (a/a
0) and density ρ (ρ/ρ
0), elastic parameters (elastic constants C

ij
, bulk modulus B, shear modulus G, and Young's modulus E), deduced parameters (B/G ratio, Poisson's ratio ν, Vickers hardness, sound velocity, and Debye termperature ΘD), and thermodynamic parameters (free energy F, entropy S, and heat capacity C
v) were investigated. All CuM (M = Be, Al, and Zn) alloys had more difficulty undergoing uniaxial stress than shear stress. External pressure reduced the ductility of the CuBe alloy, while excess pressure (P > 50 GPa) resulted in increased ductility, which was similar to CuAl but different from CuZn. The hardness and ΘD values demonstrated consistent variation corresponding to the ductility changes. Thermodynamic parameters were minimally affected by pressure, and the stronger interactions led to greater F in the CuBe alloy. These findings offer confidence for the future design of ordered Cu-Be alloys with exceptional properties.
Extracting macroscopic quantities in crowd behaviour with deep learning
Authors: Zhou Shuaiqi , Shi Rongrong , Wang Lingxiao 
Published: April 2024

Abstract
Abnormal behaviours in crowded populations can pose significant threats to public safety, with the occurrence of such anomalies often corresponding to changes in macroscopic quantities of the complex system. Therefore, the automatic extraction and prediction of macroscopic quantities in pedestrian collective behaviour becomes significant. In this study, we generated pedestrian evacuation data through simulation, and calculated the average kinetic energy, entropy and order parameter of the system based on principles of statistical physics. These macroscopic quantities can characterize the changes in crowd behaviour patterns over time and can also assist in detecting abnormalities. Subsequently, we designed deep convolutional neural networks(CNNs) to estimate these macroscopic quantities directly from frame-by-frame image data. In the end, a convolutional auto-encoder(CAE) model is trained to learn the underlying physics unsupervisedly. Successful results indicate that deep learning methods can directly extract macroscopic information from crowd dynamics, aiding in analysing collective behaviour.
Conformal transformations and cosmological perturbations in New General Relativity
Authors: Golovnev Alexey , Semenova A.N. , Vandeev V.P. 
Published: April 2024

Abstract
We study conformal transformations in the most general parity-preserving models of the New
General Relativity type. Then we apply them to analysis of cosmological perturbations in the
(simplest) spatially flat cosmologies. Strong coupling issues around Minkowski spacetime are seen
for many special cases of these models. At the same time, the behaviour of the most general
three-parameter case seems to be very robust, presumably always with only the eight first-class
constraints coming from diffeomorphisms. Also the case of the so-called 1-parameter New GR doesn't
show any discontinuity between Minkowski and the cosmology, though without showing any deviations
from GR which would be observable at this level either.
Performance of Secure Door Access System Using Identification Numbers, Fingerprints, and Facial Recognition
Authors: Azhari  , Manullang R R , Yanti M , Hasibuan C D , Yudhistira E 
Published: April 2024

Abstract
Layered door security systems are increasingly essential in enhancing safety and convenience for people in their daily lives. Features such as ID number technology, fingerprints, and facial recognition can be employed in the security system. This study aims to develop and validate a system that authenticates the user’s identity as they pass through a doorway. The sensors utilized include of PN 532 as an ID number detection sensor, FPM10A as a fingerprint detection sensor, and ESP32CAM as a facial image detection sensor. The system is structured hierarchically and linked to the Internet of Things (IoT) in order to enable remote monitoring through the utilization of the Blynk application. This gadget employs a servo motor for door access control and incorporates an RFID module in its use. This study employs an Atmega328 microcontroller for the purpose of data processing. The PN532 test yielded a sensitivity rate of 100% and successfully detected and read RFID data from E-KTP chips. The testing of the FPM10A sensor demonstrated a sensitivity level of 90%. In addition, the testing of ESP32CAM demonstrates a sensitivity rate of 85%. Based on the test findings, the overall system achieved a tool performance score of 91.6%, indicating that the system is functioning effectively.
Synthesis and Characterization of Graphitic Carbon Nanostructures from Cellulose Extraction of Durian Peel Waste
Authors: Marlina H A , Noer Z , Purwasasmita B S 
Published: April 2024

Abstract
The synthesis of graphitic carbon nanostructures from cellulose extraction of durian peel waste has been successfully carried out in this study. This study aim to produce the graphitic carbon nanostructures to give innovative solutions to the renewable energy storage challenge. Durian peel cellulose was synthesized into graphitic carbon nanostructures through catalytic graphitization method. 4.8 grams of durian peel cellulose was hydrocharred at 200°C for 4 hours, then impregnated using Fe(NO3).9H2O and ethanol for 90 minutes. The sample was then precipitated for 12 hours and dried at 60°C. The sample was pyrolysed at 900°C for 3 hours. Characterization was carried out using TEM and XRD. Characterization TEM showed the morphological characteristics of graphitic carbon nanostructures in the form of coils in uneven amounts with the avarage diameter size is 24.9134 nm. In addition, the XRD characterization results also strengthen the characteristic phase of graphitic carbon nanostructures at 2θ 26.5° and 44.7°, although nanoparticles from Fe catalysis are visible in the sample due to the absence of reflux.
Analysis of Subsurface Resistivity Distribution of the Kelud Volcano Using Magnetotelluric Method
Authors: Nurhasan Nurhasan , Pratama Andika , Naufal Muhammad Risyad , Zahra Iradati , Srigutomo Wahyu , Mustopa Enjang Jaenal , Fitriani Dini , Harja Asep , Ogawa Yasuo 
Published: April 2024

Abstract
Indonesia has the world’s most active volcanoes, with more than 30% of them lying within its borders. The Kelud volcano erupted in 2007, resulting in the development of a Lava Dome in the crater lake. This phenomena is known as effusive. The magnetotelluric approach is used in this study to predict the subsurface resistivity distribution in the Kelud volcano area. Data was obtained at 10 different locations around the Kelud volcano area. The subsurface structure of the Kelud Volcano can be identified based on resistivity values that show significant differences, according to the modelling results. According to the findings, the surface resistivity surrounding the Kelud volcano ranges from 1 to 100 ohm. The main structure of the hydrothermal system’s clay cap was discovered at a depth of 1000 m from the surface in the western part of the summit, with resistivity values ranging from 1-10.m. With a resistivity of more than 100 ohm.m., a high resistivity forming a conduit appears in the centre of the summit area. The subsurface structure values obtained indicate that these structures are volcanic.
Design of Automatic Cleaning System on Solar Panel Using IoT-based Wiper
Authors: Hamid Muhammadin , Simamora Micael Frans , Vania Maria Derani Ester , Cholillah Putri 
Published: April 2024

Abstract
Condition of the solar panel surface covered by dust and other particles can obstruct the absorption of sunlight, requiring maintenance and monitoring of the panel’s condition. The objective of this research is to facilitate human tasks in cleaning solar panels with an automatic cleaning device in the presence of dust and dirt. The methodology in this study begins with planning and designing to facilitate the construction phase of the tool. Data collection involves using a batch system or repeated data collection. Constructed tool yields an electric voltage on the clean surface of the solar panel more than in the dirty condition, with a voltage difference of 9.57 volts under a light intensity of <1000. The mechanism of this tool involves a single-channel relay module driving the cleaning motor (dust remover) and functioning as a sliding wheel. Dust sensors and RTC module are used in the reading process, and a servo motor moves the cleaner. The results of this process have been integrated with the IoT, allowing real-time monitoring of the solar panel surface condition using an Android device. It is expected that this research will assist the community in reducing costs and improving the efficiency of energy usage.
Photostimulated Nernst effect in two-dimensional compositional semiconductor superlattices under the influence of confined phonons
Authors: Thu Huong Nguyen , Thi Dien Tang , Quang Bau Nguyen , Khuong Duy Tran , Dinh Nam Nguyen , Thanh Hue Dao 
Published: April 2024

Abstract
The photostimulated Nernst effect in compositional semiconductor superlattices under the influence of a confined acoustic phonon is studied by using the quantum kinetic equation. The case of the confined electron-confined acoustic phonon scattering process is examined in detail. The obtained analytical results reveal that the Nernst coefficient (NC) depends on the external field such as magnetic field B, the frequency Ω, and the amplitude E
0 of the electromagnetic wave in a complicated way but also like a function of the temperature of the system and the period of the superlattice. It also depends on the quantum number m-describing the confined acoustic phonon. The theoretical results are depicted and discussed for GaAs/AlxGa
1

−
xAs compositional semiconductors superlattices. The results indicate that the Shubnikov-De hass oscillations have appeared. The confined phonons make the magnitude of the Nernst coefficient higher and more obvious than the case of a bulk phonon. In addition, the magneto-photon resonance condition is also proved. Besides, the Nernst coefficient decreases significantly as the temperature increases. The oscillations Nernst coefficient in a magnetic field are consistent with the previous experimental.
Adsorption behavior of formaldehyde gas on two-dimensional semiconductor monolayers MS2 (M=W, Mo)
Authors: Theu Luong Thi , Huy Tran Quang , Nhan Tran Thi , Bac T. Phung Viet , An Dinh Van 
Published: April 2024

Abstract
Detecting methanal molecule, an indoor air pollutant and potential carcinogen, is crucial for safeguarding human health, ensuring occupational safety, and maintaining environmental quality. In this study, density functional theory calculations have been performed to explore the adsorption behavior of formaldehyde (methanal) gas on the surface of two-dimensional semiconductor monolayers MS2 (M=W, Mo). Using the Computational DFT-based Nanoscope tool, we compute binding energies and determine configurations at global minimum energy of molecule adsorbed monolayer MS2. Five nonlocal van der Waals functionals; revPBE-vdW, optPBE-vdW, vdW-DF2, optB88-vdW, and optB86b-vdW are used to compute the adsorption energy profiles. The calculated results show that: (i) the optPBE-vdW functional products the largest adsorption energy magnitude, (ii) Methanal molecule exhibits physical adsorption on both MoS2 and WS2 materials (iii) Adsorption of methanal molecules may enhance the electrical conductivity of MoS2 and WS2 upon the electron donation to molecule by substrates. The adsorption energy magnitude, bandgap reduction, and charge transfer of the methanal-MoS2 adsorption system are respectively 1.04, 1.27, and 1.47 times larger than those of the methanal-WS2 adsorption system, while the diffusion barrier energy is 0.25 times smaller. These characteristic adsorption parameters imply that methanal exhibits higher sensitivity to the MoS2 substrate. This study also provides an in-depth discussion regarding the interaction between methanal and the MS2 substrate, focusing on aspects of relaxed geometrical structures, potential energy surface, adsorption energy, response length, recovery time, work function, charge transfer, density of states, and energy band structure.
Facile synthesis of co-axially electrospun Co-C nanofibers and their ferromagnetic behavior
Authors: Sethy Pujashree Priyadarshini , Sundaray Bibekananda 
Published: April 2024

Abstract
We describe a simple co-axial electrospinning approach followed by a carbonisation process to create cobalt-carbon (Co-C) nanofibers that are then thoroughly analysed using various techniques. X-ray diffraction measurements showed the creation of pure crystalline cobalt with face-centered cubic (fcc) structure, and average crystallite size was determined using the Debye–Scherrer formula. The average crystallite size has been calculated to be in the range of 10 − 15 nm. According to the Raman investigation, all Co-C nanofibers have an amorphous carbon structure with little graphitic behaviour. Field emission scanning electron microscopy was used to determine the shape and average diameter of electrospun nanofibers. The field-dependent magnetic characterisation demonstrated a satisfactory ferromagnetic behaviour with maximum saturation magnetisation values of 10, 10.2, and 11.2 emu/g for Co12.5-C sample at 300, 100, and 5 K, respectively. Compared to bulk cobalt, the produced Co-C nanofibers have a high coercivity value. With average crystallite size, the coercivity varies. Again, magnetisation versus temperature measurements have supported the existence of ferromagnetism because there is no evidence of blocking temperature or any transitional behaviour below 300 K. As a result, applications for microwave absorption, catalysis, and several magnetic recording devices can benefit from the coupling of ferromagnetic properties with carbon nanofiber materials.
Investigation of a potential upstream harmonization based on image appearance matching to improve radiomics features robustness: a phantom study
Authors: Scapicchio Camilla , Imbriani Manuela , Lizzi Francesca , Quattrocchi Mariagrazia , Retico Alessandra , Saponaro Sara , Tenerani Maria Irene , Tofani Alessandro , Zafaranchi Arman , Fantacci Maria Evelina 
Published: April 2024

Abstract

Objective. Radiomics is a promising valuable analysis tool consisting in extracting quantitative information from medical images. However, the extracted radiomics features are too sensitive to variations in used image acquisition and reconstruction parameters. This limited robustness hinders the generalizable validity of radiomics-assisted models. Our aim is to investigate a possible harmonization strategy based on matching image quality to improve feature robustness. Approach. We acquired CT scans of a phantom with two scanners across different dose levels and percentages of Iterative Reconstruction algorithms. The detectability index was used as a comprehensive task-based image quality metric. A statistical analysis based on the Intraclass Correlation Coefficient was performed to determine if matching image quality/appearance could enhance the robustness of radiomics features extracted from the phantom images. Additionally, an Artificial Neural Network was trained on these features to automatically classify the scanner used for image acquisition. Main results. We found that the ICC of the features across protocols providing a similar detectability index improves with respect to the ICC of the features across protocols providing a different detectability index. This improvement was particularly noticeable in features relevant for distinguishing between scanners. Significance. This preliminary study demonstrates that a harmonization based on image quality/appearance matching could improve radiomics features robustness and heterogeneous protocols can be used to obtain a similar image appearance in terms of the detectability index. Thus protocols with a lower dose level could be selected to reduce the amount of radiation dose delivered to the patient and simultaneously obtain a more robust quantitative analysis.
The relative roles of energy and water intensity in the economic growth of the United States, 1950–2015
Authors: Lobo José , Ruddell Benjamin L 
Published: April 2024

Abstract
Water and energy are indispensable inputs to the modern economy and are of primary concern for the sustainability of the global economy. Continually growing use of water and energy cannot be sustained in the pursuit of greater wealth and prosperity, given planetary boundaries and other limitations on these resources. Water is a main input to the production of energy, and vice versa, and to some extent the two are substitutes. An economy’s energy intensity and water intensity measure the efficiency with which energy and water, respectively, are used in the generation of wealth. How far has an advanced economy like that of the US gone in decoupling energy and water use from economic growth? To answer this question, we decompose the growth of GDP per capita into improvement in energy and water intensity and the change in the per capita use of these two crucial inputs, using data for the US from 1950 to 2015. We find that water and energy use efficiency improvements are responsible for much more growth in per capita GDP than increases in water and energy inputs, and that water use can be decoupled more significantly from increasing wealth than the use of energy. The results have important implications for the future of energy and material consumption by the global economy.
A review of imaging methods for detection of photoluminescence in field-installed photovoltaic modules
Authors: Vuković M , Wiig M S , dos Reis Benatto G A , Olsen E , Burud I 
Published: April 2024

Abstract
Contactless detection with a camera of radiation emitted from silicon solar cells resulting from band-to-band recombination after charge carrier excitation with an illumination source, i.e. photoluminescence (PL) imaging, has shown a great potential in the laboratory setting. In the recent years, the first approaches to PL imaging in the outdoor setting have been conducted on silicon modules with the Sun, a LED module and laser as excitation sources. The reason for these attempts has been that fault detection in photovoltaic (PV) modules using imaging can be more efficient and accurate than fault detection using electrical parameters. Developments in fault detection and localization are necessary because accurate monitoring of solar plants is expected to be one of the critical tasks facing the energy industry, when one considers that PV energy conversion will be the largest installed power capacity by 2027 and that the utility-scale solar PV electricity generation will be the least costly option for new electricity generation in many of the world’s countries. The present study sums up the different methods for outdoor PL imaging and emphasizes their differences regarding filtering of the reflected excitation light from the PL signal. The different types of PL images obtained from each method and the image processing algorithms are described. Finally, the interpretation of the different types of PL images is addressed.
Additive manufacturing of micropatterned functional surfaces: a review
Authors: Chivate Aditya , Zhou Chi 
Published: April 2024

Abstract
Over the course of millions of years, nature has evolved to ensure survival and presents us with a myriad of functional surfaces and structures that can boast high efficiency, multifunctionality, and sustainability. What makes these surfaces particularly practical and effective is the intricate micropatterning that enables selective interactions with microstructures. Most of these structures have been realized in the laboratory environment using numerous fabrication techniques by tailoring specific surface properties. Of the available manufacturing methods, additive manufacturing (AM) has created opportunities for fabricating these structures as the complex architectures of the naturally occurring microstructures far exceed the traditional ways. This paper presents a concise overview of the fundamentals of such patterned microstructured surfaces, their fabrication techniques, and diverse applications. A comprehensive evaluation of micro fabrication methods is conducted, delving into their respective strengths and limitations. Greater emphasis is placed on AM processes like inkjet printing and micro digital light projection printing due to the intrinsic advantages of these processes to additively fabricate high resolution structures with high fidelity and precision. The paper explores the various advancements in these processes in relation to their use in microfabrication and also presents the recent trends in applications like the fabrication of microlens arrays, microneedles, and tissue scaffolds.
An algorithm for multi-armed bandit based on variance change sensitivity
Authors: Zhu Canxin , Yang Jingmin , Zhang Wenjie , Zheng Yifeng 
Published: April 2024

Abstract
The Multi-Arm Bandit problem is becoming increasingly popular as it enables real-world sequential decision making across application domains, including clinical trials, recommender systems, and online decision making. The Multi-Arm Bandit problem is a classical problem of exploration and exploitation dilemma in reinforcement learning and it needs to decide on the optimal strategy based on the reward situation of each rocker arm. However, the existing Multi-Arm Bandit algorithms have many shortcomings, such as blind exploration, weak generalization ability and endless exploration. Aiming at the shortcomings of the existing Multi-Armed Bandit algorithms, this paper proposes a Multi-Armed Bandit algorithm based on variance change sensitivity. The algorithm takes the variance change of reward as a clue, and adjusts the exploration probability by the average variance change of all actions, and selects the action with the largest variance change when exploring. At the same time, in order to reduce the waste of action selection times and maximize the cumulative reward, A parameter

N

c
o
n

was introduced to record the number of consecutive selections of the same action. The exploration stops when

N

c
o
n

reaches a certain value. Experiments show that the exploration algorithm can obtain higher reward value and lower regret value in the end.