bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Heat Treatment on Microstructure and Mechanical Properties of Titanium Alloy Fabricated by Laser–Arc Hybrid Additive Manufacturing
Authors: Chen Yuhang , Fu Juan , Zhou Lilong , Zhao Yong , Wang Feiyun , Chen Guoqiang , Qin Yonghui
Published: May 2024

The tailored thermal heat-treatment process for Ti-6Al-4V alloy manufactured by laser–arc hybrid additive manufacturing can achieve desired microstructures and excellent mechanical properties for components. The effects of different heat treatment regimens on the microstructure and mechanical properties of Ti-6Al-4V alloy manufactured by laser–arc hybrid additive manufacturing are investigated in this study. Utilizing optical microscopy and scanning electron microscopy, we analyze the variations in microstructure with changes in heat-treatment parameters and explore the reasons for the changes in mechanical properties under different solutions’ treatment temperatures and cooling rates. The microstructure of Ti-6Al-4V alloy fabricated via laser–arc hybrid additive manufacturing was primarily composed of Widmanstätten α plate structures and a small amount of acicular martensite α′ within columnar β grains that grew outward from the substrate along the deposition direction. Following solution treatment and aging heat treatment, the microstructure transitioned to a typical high-performance net basket structure with significantly reduced α plate thickness, leading to noticeable enhancements in sample ductility and toughness. Specifically, when the solution treatment and aging treatment regimen was set at 950 °C for 1 h, followed by air cooling, and then aging at 540 °C for 6 h with subsequent air cooling, the average grain size decreased by a factor of two compared to the as-deposited samples, while the impact toughness increased by 66.7%.
Microstructure and Properties of CoCrFeNiMnTix High-Entropy Alloy Coated by Laser Cladding
Authors: Ma Shibang , Zhang Congzheng , Li Liang , Yang Yinhai
Published: May 2024

In this study, laser cladding of CoCrFeNiMnTix (x is the proportion of the mass of a material, x = 0.0, 0.2, 0.4, 0.6, 0.8) high-entropy alloy (HEA) composite powder coating on 45 steel substrate was studied by using the method of preplaced powder. The phase composition, morphology, microhardness, corrosion resistance and wear properties of CoCrFeNiMnTix high entropy alloy were analyzed by XRD, SEM, microhardness tester, electrochemical workstation and reciprocating friction wear tester, respectively. The influences of Ti concentration on structure and properties of CoCrFeNiMn HEA laser cladding coating were discussed. The macromorphology of CoCrFeNiMnTix HEA coating layer becomes worse with the increase in Ti quantity. The coating layer is a face-centered cubic solid solution phase. The microstructure of the coating layer is dominated by dendrites and equiaxed crystals. The average microhardness of the coating layer grows with the increases in Ti content, and CoCrFeNiMnTi0.8 can reach 823 HV. The friction coefficient of the cladding coating gradually reduces and the wear resistance adds as Ti content rises; the friction coefficients of CoCrFeNiMnTi0.6 and CoCrFeNiMnTi0.8 cladding coating are similar, at 0.835 and 0.828, respectively. Adhesive and abrasive wear are the two basic types of cladding coating wear. In 3.5 wt.% NaCl solution, the corrosion potential of cladding coating increases with increases in Ti content, the corrosion potential of CoCrFeNiMnTi0.8 is about 244 mV higher than that of CoCrFeNiMnTi0, and the density of corrosion current drops to 3.41 × 10−6 A/cm2 from 7.17 × 10−5 A/cm2.
Evaluation of Edible Coatings from Components from Chlorella vulgaris and Comparison with Conventional Coatings
Authors: Mari Alexandra , Fafalis Charilaos , Krokida Magdalini
Published: May 2024

The present customer demand for ready-to-eat food items with higher nutritious value and longer shelf life necessitates creative solutions. An edible coating is a sustainable packaging solution that can prevent food deterioration and preserve food quality. Proteins, starch, and the addition of plasticizers are used to create edible coatings. The aim of this study was to develop coating solutions that can best preserve food using isolated starch and proteins from Chlorella vulgaris, and then compare them to coatings that comprise conventional ingredients like chitosan and starch. A number of criteria pertaining to the coatings’ mechanical, optical, thermal, and physical properties were tested. The alternative coatings performed just as well as the conventional ones, with the protein algal coating exhibiting the best thermal, optical, and physical qualities. The food product that needs to be coated can determine which coating is ideal. In conclusion, edible coatings derived from Chlorella vulgaris offer a sustainable solution to preserve ready-to-eat food items, showcasing comparable performance to conventional coatings.
Aluminium-Silicon Lightweight Thermal Management Alloys with Controlled Thermal Expansion
Authors: Lewis Peter , Tarrant Andrew , Frehn Andreas , Grensing Fritz , Nicholson James , Farrah Nick , Acreman Martyn
Published: May 2024

With the ever-growing emphasis on global decarbonization and rapid increases in the power densities of electronics equipment in recent years, new methods and lightweight materials have been developed to manage heat load as well as interfacial stresses associated with coefficient of thermal expansion (CTE) mismatches between components. The Al–Si system provides an attractive combination of CTE performance and high thermal conductivity whilst being a very lightweight option. Such materials are of interest to industries where thermal management is a key design criterion, such as the aerospace, automotive, consumer electronics, defense, EV, and space sectors. This paper will describe the development and manufacture of a family of high-performance hypereutectic Al–Si alloys (AyontEX™) by a powder metallurgy method. These alloys are of particular interest for structural heat sink applications that require high reliability under thermal cycling (CTE of 17 μm/(m·°C)), as well as reflective optics and instrument assemblies that require good thermal and mechanical stability (CTE of 13 μm/(m·°C)). Critical performance relationships are presented, coupled with the microstructural, physical, and mechanical properties of these Al–Si alloys.
Impact of Zinc Oxide on the Structure and Surface Properties of Magnesium–Potassium Glass–Crystalline Glazes
Authors: Pasiut Katarzyna , Partyka Janusz , Kozień Dawid , Pańtak Piotr
Published: May 2024

The present work describes test results for glass crystal materials based on the SiO2-Al2O3-MgO-K2O system after 5, 10, 15, and 20 wt.% zinc oxide was added. The glazing analysis involved determining the effect of the additive on the characteristic temperatures and properties of the surface obtained, such as color, gloss, and roughness, as expressed by a Ra parameter. The obtained glazes were also analyzed for changes in phase composition (quantitative and qualitative XRD tests), changes in microstructure (based on images obtained with a scanning electron microscope), and structure (based on analyses and decomposition of spectra obtained using mid-infrared spectroscopy). As a result, the maximum addition of zinc oxide provided the best results.
Hierarchically Porous Carbon Cloth–Polyaniline (CC–PANI) Composite Supercapacitor Electrodes with Enhanced Stability
Authors: Stakhanova Svetlana V. , Krechetov Ilya S. , Shafigullina Kristina E. , Lepkova Tatiana L. , Berestov Valentine V. , Statnik Eugene S. , Zyryanova Zlatotsveta E. , Novikova Elena A. , Korsunsky Alexander M.
Published: May 2024

In this work, hierarchically porous composites were prepared in the form of activated carbon cloth (CC) Busofit T–1–055 filled with an electrically conductive polymer, polyaniline (PANI), for use as pseudocapacitive electrodes of electrochemical supercapacitors (SCs). CC fibers have high nanoporosity and specific surface area, so it was possible to deposit (via the chemical oxidative polymerization of aniline) a significant amount of PANI on them in the form of a thin layer mainly located on the inner surface of the pores. Such morphology of the composite made allowed the combining of the high capacitive characteristics of PANI with the reversibility of electrochemical processes, high columbic efficiency and cyclic stability rather typical for carbon materials of double-layer SCs. The highest capacitance of composite electrodes of about 4.54 F/cm2 with high cyclic stability (no more than 8% of capacity loss after 2000 charge–discharge cycles with a current density of 10 A/cm2) and columbic efficiency (up to 98%) was achieved in 3 M H2SO4 electrolyte solution when PANI was synthesized from an aniline hydrochloride solution with a concentration of 0.25 M. Trasatti analysis revealed that 27% of specific capacitance corresponded to pseudocapacitance, and 73% to the double-layer capacitance.
Structural and Optical Characterization of a New Tetra- and Hexa-Coordinated Cd-Based Hybrid Compound with White Light Emission
Authors: Sayer Imen , Msalmi Rawia , Mosconi Edoardo , Guesmi Ahlem , Houas Ammar , Ben Hamadi Naoufel , Naïli Houcine
Published: May 2024

The present paper deals with a new two-in-one zero-dimensional (0D) organic–inorganic hybrid compound namely (C6H10N2)4[CdBr6][CdBr4]2. This molecular crystal structure contains isolated CdBr4 tetrahedra and CdBr6 octahedra. The optical characterization by UV–Vis–NIR spectroscopy shows that the (C6H10N2)4[CdBr6][CdBr4]2 exhibits a large gap energy of 4.97 eV. Under UV excitation, this hybrid material shows a bright cold white light emission (WLE) at room temperature. The photoluminescence (PL) analysis suggests that the WLE originates from the organic molecules. Density of states (DOS) analysis using the density functional theory (DFT) demonstrates that the calculated HOMO(Br)→LUMO(organic) absorption transition (4.1 eV) does not have significant intensity, while, the transition involving the valence band (VB) and the second and third conduction bands (CB) around 5 eV are allowed, which is in good agreement with the experimental gap value. The interesting theoretical result is that the LUMO(organic)→HOMO(Br) emission is allowed, which confirms the important role of the organic molecule in the emission mechanism, in good agreement with the experimental PL analysis.
Unveiling University Groupings: A Clustering Analysis for Academic Rankings
Authors: Matlis George , Dimokas Nikos , Karvelis Petros
Published: May 2024

The evaluation and ranking of educational institutions are of paramount importance to a wide range of stakeholders, including students, faculty members, funding organizations, and the institutions themselves. Traditional ranking systems, such as those provided by QS, ARWU, and THE, have offered valuable insights into university performance by employing a variety of indicators to reflect institutional excellence across research, teaching, international outlook, and more. However, these linear rankings may not fully capture the multifaceted nature of university performance. This study introduces a novel clustering analysis that complements existing rankings by grouping universities with similar characteristics, providing a multidimensional perspective on global higher education landscapes. Utilizing a range of clustering algorithms—K-Means, GMM, Agglomerative, and Fuzzy C-Means—and incorporating both traditional and unique indicators, our approach seeks to highlight the commonalities and shared strengths within clusters of universities. This analysis does not aim to supplant existing ranking systems but to augment them by offering stakeholders an alternative lens through which to view and assess university performance. By focusing on group similarities rather than ordinal positions, our method encourages a more nuanced understanding of institutional excellence and facilitates peer learning among universities with similar profiles. While acknowledging the limitations inherent in any methodological approach, including the selection of indicators and clustering algorithms, this study underscores the value of complementary analyses in enriching our understanding of higher educational institutions’ performance.
Efficient Quantum Private Comparison Based on GHZ States
Authors: Hou Min , Wu Yue , Zhang Shibin
Published: May 2024

Quantum private comparison (QPC) is a fundamental cryptographic protocol that allows two parties to compare the equality of their private inputs without revealing any information about those inputs to each other. In recent years, QPC protocols utilizing various quantum resources have been proposed. However, these QPC protocols have lower utilization of quantum resources and qubit efficiency. To address this issue, we propose an efficient QPC protocol based on GHZ states, which leverages the unique properties of GHZ states and rotation operations to achieve secure and efficient private comparison. The secret information is encoded in the rotation angles of rotation operations performed on the received quantum sequence transmitted along the circular mode. This results in the multiplexing of quantum resources and enhances the utilization of quantum resources. Our protocol does not require quantum key distribution (QKD) for sharing a secret key to ensure the security of the inputs, resulting in no consumption of quantum resources for key sharing. One GHZ state can be compared to three bits of classical information in each comparison, leading to qubit efficiency reaching 100%. Compared with the existing QPC protocol, our protocol does not require quantum resources for sharing a secret key. It also demonstrates enhanced performance in qubit efficiency and the utilization of quantum resources.
Towards Multi-Objective Object Push-Grasp Policy Based on Maximum Entropy Deep Reinforcement Learning under Sparse Rewards
Authors: Zhang Tengteng , Mo Hongwei
Published: May 2024

In unstructured environments, robots need to deal with a wide variety of objects with diverse shapes, and often, the instances of these objects are unknown. Traditional methods rely on training with large-scale labeled data, but in environments with continuous and high-dimensional state spaces, the data become sparse, leading to weak generalization ability of the trained models when transferred to real-world applications. To address this challenge, we present an innovative maximum entropy Deep Q-Network (ME-DQN), which leverages an attention mechanism. The framework solves complex and sparse reward tasks through probabilistic reasoning while eliminating the trouble of adjusting hyper-parameters. This approach aims to merge the robust feature extraction capabilities of Fully Convolutional Networks (FCNs) with the efficient feature selection of the attention mechanism across diverse task scenarios. By integrating an advantage function with the reasoning and decision-making of deep reinforcement learning, ME-DQN propels the frontier of robotic grasping and expands the boundaries of intelligent perception and grasping decision-making in unstructured environments. Our simulations demonstrate a remarkable grasping success rate of 91.6%, while maintaining excellent generalization performance in the real world.
The SU(3)C × SU(3)L × U(1)X (331) Model: Addressing the Fermion Families Problem within Horizontal Anomalies Cancellation
Authors: Corianò Claudio , Melle Dario
Published: May 2024

One of the most important and unanswered problems in particle physics is the origin of the three generations of quarks and leptons. The Standard Model does not provide any hint regarding its sequential charge assignments, which remain a fundamental mystery of Nature. One possible solution of the puzzle is to look for charge assignments, in a given gauge theory, that are inter-generational, by employing the cancellation of the gravitational and gauge anomalies horizontally. The 331 model, based on an SU(3)C×SU(3)L×U(1)X does this in an economical way and defines a possible extension of the Standard Model, where the number of families has necessarily to be three. We review the model in Pisano, Pleitez, and Frampton’s formulation, which predicts the existence of bileptons. Another characteristics of the model is to unify the SU(3)C×SU(2)L×U(1)X into the 331 symmetry at a scale that is in the TeV range. Expressions of the scalar mass eigenstates and of the renormalization group equations of the model are also presented.
Analyzing the Impact of Public Capital on Private Capital Productivity in a Panel of African Nations
Authors: Ezzahid Elhadj , Rafik Hamid
Published: May 2024

This research contributes to the ongoing discourse concerning the efficiency of public capital and its influence on the productivity of private capital and total factor productivity within African economies. Employing the standard production approach, we include public capital as a distinct input to assess its specific impact on output growth and the enhancement of total factor productivity. We argue that public capital, predominantly manifesting through infrastructure, constitutes an indispensable element for fostering growth. Fundamental to the productivity of private capital is its reliance on a sufficient stock of public infrastructure for operational efficiency. Our empirical analysis reveals that public capital exhibits a substantive long-term influence on output growth and the productivity of private capital. However, in the short term, the discernible impact of public capital is less pronounced. Moreover, while public capital emerges as a noticeable factor in output growth, its influence on total factor productivity remains relatively subdued.
Neurodiversity Positively Predicts Perceived Extraneous Load in Online Learning: A Quantitative Research Study
Authors: Le Cunff Anne-Laure , Giampietro Vincent , Dommett Eleanor
Published: May 2024

Working memory impairments are common in neurodevelopmental conditions, potentially impacting how neurodivergent students experience cognitive load during learning. We conducted a survey with 231 participants focused on students with attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and dyslexia. Parametric tests and a regression analysis were used to investigate the relationship between neurodiversity and perceived cognitive load in online learning. Neurodivergent students reported significantly higher extraneous cognitive load (ECL) in online learning compared to their neurotypical peers. However, no significant differences in perceived intrinsic and germane cognitive load were found between the two groups. Neurodiversity, and specifically ADHD, positively predicted perceived ECL in online learning. This study provides novel insights into the association between neurodiversity and cognitive load in online learning, suggesting a need for targeted support to help neurodivergent students reduce ECL in online learning environments and highlighting the importance of promoting inclusive educational practices that meet the needs of all students.
Digital and Physical Interactive Learning Environments: Early Childhood Mathematics Teachers’ Beliefs about Technology through Reflective Writing
Authors: Alsaeed Maha Saad , Aladil Mona Khalifah
Published: May 2024

In early mathematics education, the beliefs of the teacher are essential for facilitating the integration of technology into teaching mathematics. This study explores the influence of physical and digital interactive learning environments on the development of early childhood teachers’ beliefs about integrating technology into early mathematics classrooms. To understand the development of teachers’ beliefs, a half-year, content-based professional development program that incorporates interactive digital and physical environments was designed for this research on early childhood mathematics teachers (N = 58). We administered a questionnaire to measure teachers’ beliefs regarding employing an interactive technological environment in mathematics classrooms before and after engaging in an intervention program. In addition, a reflective writing strategy was implemented with the participants (N = 10) to understand the development of their beliefs about technology via an evaluation of their levels of reflection. In general, the research findings indicate that an interactive learning environment supports an improvement in teachers’ beliefs about technology. Furthermore, positive qualitative findings were drawn from the reflective writing essays of early childhood teachers. The qualitative findings indicate that an interactive environment enables teachers to be conscious of selecting effective math-specific technologies that facilitate children’s exploration and discovery of mathematics concepts.
Gender and STEM Education: An Analysis of Interest and Experience Outcomes for Black Girls within a Summer Engineering Program
Authors: Fletcher Trina , Hooper Kerrie , Alfonso Danay Fernandez , Alharbi Ahlam
Published: May 2024

An effective way to increase the participation of historically excluded students in engineering education is through informal programming that covers science, technology, engineering, and mathematics (STEM). This study is part of a broader investigation conducted by Fletcher aimed at evaluating the programs offered by the National Society of Black Engineers (NSBE) as part of the Summer Engineering Experience for Kids (SEEK) program at different sites. The study collected pre- and post-assessment data from 1235 girls across twelve sites to determine if there were significant differences in interest- and experience-related outcomes at single-gender and coeducation sites. The study found that the two single-gender sites out of the twelve sites had statistically significant differences in participant responses in favor of single-gender sites, with one site showing a significant association with overall enjoyment of the program. The study used social cognitive theory (SCT) and intersectionality to guide the research and found that the site type had a significant association with the results. These findings suggest the need for further exploration of the impact of site type within informal education programs, especially those targeting historically excluded populations in STEM.
Facilitators of and Barriers to Inclusive Education in the Arab Community of Israel: The Parents’ Perspective
Authors: Jorban Mohamad , Cachón-Zagalaz Javier , Mecías-Calvo Marcos , Navarro-Patón Rubén
Published: May 2024

A positive and collaborative partnership between parents and schools is required to improve the education of children with special educational needs. Therefore, the present study aimed to explore the educational context in the Arab community in Israel based on the perceptions and beliefs of parents of children with special educational needs about their children’s education in relation to schools. Twenty parents of children with different special educational needs were interviewed to understand their thoughts and beliefs about special education in the Arab community in Israel. Six core categories emerged from the analysis of the interviews [i.e., (a) parenting, (b) learning at home, (c) communicating, (d) volunteering, (e) inclusion of parents in decision-making related to their children, and (f) teachers’ attitudes towards children from the perspective of parents], which were perceived as axes with high potential to improve special education in this community and guarantee an optimal education for children with special needs. The role of the school as a tool to assist parents is highlighted, with the aim of empowering them and encouraging their active participation in school processes with a clear educational policy that clarifies the demands of the school system for parents and vice versa. Finally, we conclude by highlighting the importance of teachers in a child’s life, emphasizing the potential benefits of cooperation and collaboration between teachers, students, and parents.
Practices Promoting the Inclusion of Adult Students with Disabilities in the Classroom: A Case of a Technical Vocational Education and Training College in Kazakhstan
Authors: Assanbayev Arman , Makoelle Tsediso Michael
Published: May 2024

Kazakhstan’s government has launched many policy reforms to enhance the well-being of its underrepresented citizens and develop human capital by providing education to all. Therefore, the government has adopted a policy on inclusive education and recognised the rights to education of all learners, including those with disabilities, based on equal opportunity, without any discrimination. This aims to facilitate equal access to lifelong education opportunities, including in Technical Vocational Education Training Institutes (TVETIs). Thus, inclusive education in TVET settings and lifelong learning, especially for adults with special needs, has become an educational priority in Kazakhstan. Therefore, this collaborative action research study intended to explore classroom practices promoting the inclusion of adult students with disabilities at Kazakhstani Technical Vocational Education and Training Institutions (TVETIs). Qualitative data were collected through reflective journals, student focus-group interviews, documentary analysis, and reflective meetings of the professional learning group of selected teachers and students during the four stages of collaborative action research (CAR). Data were analysed through group interpretative meetings by the research team and inductive thematic content analysis by the researcher. Among the findings is that the educative process in TVETIs does not sufficiently provide reasonable inclusive support for adult students with disabilities. As a result, a comprehensive review of inclusive practices in these institutions was critical. This paper discusses some practices that could promote inclusion in TVET classrooms.
ChatGPT-Generated and Student-Written Historical Narratives: A Comparative Analysis
Authors: Kindenberg Björn
Published: May 2024

This study investigates alternative approaches for demonstrating historical understanding in elementary school history education, motivated by challenges to educational institutions posed by increased ChatGPT-related plagiarism. Focused on secondary education, an area with scant research, this study, through sociocultural and linguistic methods of analysis, contrasted human-generated historical narratives with those produced by ChatGPT. It was found that ChatGPT’s narratives, while stylistically superior, lacked emotional depth, highlighting a key differentiation from human storytelling. However, despite this differentiation, ChatGPT otherwise effectively mimicked typical discourse patterns of historical storytelling, suggesting that narrative-based writing assignments do not significantly reduce the likelihood of ChatGPT-assisted plagiarism. The study concludes by suggesting that rather than focusing on mitigating plagiarism, educational approaches to ChatGPT should seek to channel its potential for historical narratives into assistance with task design, delivery of content, and coaching student writing.
An Improved Genetic Method for Satellite Selection in Multi-Global Navigation Satellite System Positioning for Mobile Robots
Authors: Li Xiang , Qiu Shidong , Jiang Jinmao , Qi Jun , Huang Jie , Teng Yunlong
Published: May 2024

Mobile robots have been widely engaged in many fields. To obtain the precise and consistent localization of mobile robots, the Global Navigation Satellite System (GNSS) is often employed. With the continuous development and modernization of GNSS, more tracked satellites can be used for multi-GNSS positioning calculation, which can improve the positioning performance and enhance accuracy. However, it also increases computational complexity. Therefore, a satellite selection method, which selects a subset from all visible satellites, is necessary. In multi-GNSS positioning, the geometric dilution of precision (GDOP) is an essential metric for satellite selection. However, the traditional traversal method requires a large amount of solution resources. In this paper, we proposed an improved genetic algorithm for satellite selection. By defining the maturity factor (MF) to guide the crossover and mutation operators, the search performance is guaranteed while reducing unnecessary crossover and mutation operations, thus reducing the search time. By adopting the previous epoch optimal individual inheritance strategy, the satellite selection results of subsequent epochs under continuous epochs have been improved. The experimental results verify the effectiveness of the proposed method.
Enriching Language Models with Graph-Based Context Information to Better Understand Textual Data
Authors: Roethel Albert , Ganzha Maria , Wróblewska Anna
Published: May 2024

A considerable number of texts encountered daily are somehow connected. For example, Wikipedia articles refer to other articles via hyperlinks, or scientific papers relate to others via citations or (co)authors; tweets relate via users that follow each other or reshare content. Hence, a graph-like structure can represent existing connections and be seen as capturing the “context” of the texts. The question thus arises of whether extracting and integrating such context information into a language model might help facilitate a better-automated understanding of the text. In this study, we experimentally demonstrate that incorporating graph-based contextualization into the BERT model enhances its performance on an example of a classification task. Specifically, in the Pubmed dataset, we observed a reduction in balanced mean error from 8.51% to 7.96%, while increasing the number of parameters just by 1.6%.
LoRa Radio Frequency Fingerprinting with Residual of Variational Mode Decomposition and Hybrid Machine-Learning/Deep-Learning Optimization
Authors: Baldini Gianmarco , Bonavitacola Fausto
Published: May 2024

Radio Frequency Fingerprinting (RFF) refers to the technique for identifying and classifying wireless devices on the basis of their physical characteristics, which appear in the digital signal transmitted in space. Small differences in the radio frequency front-end of the wireless devices are generated across the same wireless device model during the implementation and manufacturing process. These differences create small variations in the transmitted signal, even if the wireless device is still compliant with the wireless standard. By using data analysis and machine-learning algorithms, it is possible to classify different electronic devices on the basis of these variations. This technique has been well proven in the literature, but research is continuing to improve the classification performance, robustness to noise, and computing efficiency. Recently, Deep Learning (DL) has been applied to RFF with considerable success. In particular, the combination of time-frequency representations and Convolutional Neural Networks (CNN) has been particularly effective, but this comes at a great computational cost because of the size of the time-frequency representation and the computing time of CNN. This problem is particularly challenging for wireless standards, where the data to be analyzed is extensive (e.g., long preambles) as in the case of the LoRa (Long Range) wireless standard. This paper proposes a novel approach where two pre-processing steps are adopted to (1) improve the classification performance and (2) to decrease the computing time. The steps are based on the application of Variational Mode Decomposition (VMD) where (in opposition to the known literature) the residual of the VMD application is used instead of the extracted modes. The concept is to remove the modes, which are common among the LoRa devices, and keep with the residuals the unique intrinsic features, which are related to the fingerprints. Then, the spectrogram is applied to the residual component. Even after this step, the computing complexity of applying CNN to the spectrogram is high. This paper proposes a novel step where only segments of the spectrogram are used as input to CNN. The segments are selected using a machine-learning approach applied to the features extracted from the spectrogram using the Local Binary Pattern (LBP). The approach is applied to a recent LoRa radio frequency fingerprinting public data set, where it is shown to significantly outperform the baseline approach based on the full use of the spectrogram of the original signal in terms of both classification performance and computing complexity.
Benedict–Webb–Rubin–Starling Equation of State + Hydrate Thermodynamic Theories: An Enhanced Prediction Method for CO2 Solubility and CO2 Hydrate Phase Equilibrium in Pure Water/NaCl Aqueous Solution System
Authors: You Changyu , Chen Zhaoyang , Li Xiaosen , Zhao Qi , Feng Yun , Wang Chuan
Published: May 2024

Accurately predicting the phase behavior and physical properties of carbon dioxide (CO2) in pure water/NaCl mixtures is crucial for the design and implementation of carbon capture, utilization, and storage (CCUS) technology. However, the prediction task is complicated by CO2 liquefaction, CO2 hydrate formation, multicomponent and multiphase coexistence, etc. In this study, an improved method that combines Benedict–Webb–Rubin–Starling equation of state (BWRS EOS) + hydrate thermodynamic theories was proposed to predict CO2 solubility and phase equilibrium conditions for a mixed system across various temperature and pressure conditions. By modifying the interaction coefficients in BWRS EOS and the Van der Waals–Platteeuw model, this new method is applicable to complex systems containing two liquid phases and a CO2 hydrate phase, and its high prediction accuracy was verified through a comparative evaluation with a large number of reported experimental data. Furthermore, based on the calculation results, the characteristics of CO2 solubility and the variation of phase equilibrium conditions of the mixture system were discussed. These findings highlight the influence of hydrates and NaCl on CO2 solubility characteristics and clearly demonstrate the hindrance of NaCl to the formation of CO2 hydrates. This study provides valuable insights and fundamental data for designing and implementing CCUS technology that contribute to addressing global climate change and environmental challenges.
Laboratory Study of Liquid Nitrogen Cryo-Fracturing as an Environmentally Friendly Approach for Coalbed Methane (CBM) Reservoirs
Authors: Longinos Sotirios Nik. , Serik Alina , Bayramov Emil , Junussov Medet , Begaliyev Dastan , Hazlett Randy
Published: May 2024

This study evaluated two distinct cryo-fracturing techniques using liquid nitrogen (LN2). The evaluation included tests for peak compression strength, acoustic emission, and energy absorption. The experiments compared single-exposure freezing time (FT) and multiple-exposure freezing–thawing cycle (FTC) processes on dried specimens. The outcomes indicated that FTC experiments demonstrated lower uniaxial compression stress (UCS) values compared to FT experiments because, during the thawing phase, the ice inside the pores reverts to liquid as the temperature rises. The difference between average baseline experiments versus FT180 and FTC6 indicated a reduction in stress of 14.5% and 38.5%, respectively. The standard error of our experiments ranged from 0.58% for FT60 to 5.35% for FTC6. The damage factor follows a downward trend in both FT and FTC experiments as the time of LN2 treatment augments. The amount of energy that can be absorbed in elastic or plastic deformation before failure is less for FTC specimens with the same total LN2 exposure time. Samples undergoing the freezing time process demonstrate a greater and denser quantity of acoustic emissions in comparison to freezing–thawing cycle processes, suggesting a positive correlation with uniaxial compressive strength outcomes. The large network of fractures formed by the FTC and PFTC techniques indicated that they have the greatest potential as stimulation approaches. The engineering results were improved by adding the geological context, which is essential to apply these findings to coals that have comparable origins.
Deterministic Mathematical Model of Energy Demand of Single-Family Building with Different Parameters and Orientation of Windows in Climatic Conditions of Poland
Authors: Jezierski Walery , Święcicki Adam , Werner-Juszczuk Anna Justyna
Published: May 2024

Location is crucial when it comes to reducing the energy demand of buildings. Deterministic mathematical models of the energy demand of a single-family building were developed for the cities of Wrocław and Suwałki, representing the mild and severe climatic conditions of Poland, respectively, and compared with energy demand for Białystok, representing medium conditions. Models include the windows area, heat transfer coefficient, solar radiation transmittance of glazing, and orientation of windows. For medium conditions (Białystok), the energy demand is 18.3% higher than for mild conditions (Wrocław) and 7.3% lower than for severe climate conditions (Suwałki). Location does not influence the nature of the effect of the factors on energy demand, which increases with an increase in heat transfer coefficient and a decrease in window area, glazing solar radiation transmittance, and orientation change from north to south. The large impact of solar gains was proved. The optimisation procedure was performed and mathematical descriptions of recommended parameters were created to ensure the equivalent energy efficiency of windows for each orientation and location. For Bialystok, north-facing windows can have an area 1.32 times larger and south-facing windows 1.48 times smaller than east-facing windows to ensure a building’s energy demand remains constant.
From Retrofitting to Renewables: Navigating Energy Transition Pathways for European Residential Space Heating
Authors: Salim Steven S. , Luxembourg Stefan L. , Dalla Longa Francesco , van der Zwaan Bob
Published: May 2024

Transformative actions are crucial across all sectors emitting greenhouse gases. Nonetheless, energy transition research to date displays a notable imbalance, with a larger emphasis on the supply side than on the demand side. The present study addresses this inequity by focusing on residential sector space heating demand, a frequently overlooked energy service that currently contributes substantially to global greenhouse gas emissions. Our primary objective is to pinpoint effective climate policies and space heating strategies that align with the EU’s ambitious targets for emission reduction. We employ the recently developed TIMES-Europe model to conduct a comprehensive analysis of the residential sector’s policy frameworks, technological advancements, and associated costs. This analysis aims to determine the measures necessary to meet ambitious climate objectives within the European context. To achieve this, we formulate four distinct scenarios, each representing varying levels of ambition and collaboration among EU member states, thereby providing insight into the pathways toward achieving these targets. By implementing current intended EU policies on the renovation of dwellings, we project a substantial reduction of at most 850 PJ, or, i.e., a 19% decrease, in yearly energy demand for space heating between 2020 and 2050. In contrast, if the recent pace of dwelling renovation within the EU were to continue, space heating energy savings from renovation would only amount to less than 400 PJ/yr (i.e., a 9% reduction) in the same period. In our more ambitious climate scenarios, phasing out fossil fuels leads to widespread electrification of the European residential sector, and by 2050, electricity from heat pumps and electric boilers accounts for over 68% of the total residential sector space heating demand. The outcomes of our study underline the importance of implementing the currently planned EU policies. We also demonstrate the necessity for collaboration among EU member states in order to attain the common European climate targets under the most effective resource allocation.
Impact of Convection Regime on Temperature Distribution in Food Distribution Storage Box
Authors: Beaumont Fabien , Murer Sébastien , Bogard Fabien , Polidori Guillaume
Published: May 2024

This study aims to optimize the thermodynamic performance of a cold storage distribution box through the integration of a ventilation system. To achieve this goal, a prototype constructed from expanded polystyrene is developed, incorporating an active ventilation system to ensure cold temperature uniformity. Thermocouples are integrated into the device to monitor the temporal temperature evolution with and without ventilation. Concurrently, a 2D thermo-aerodynamic investigation is conducted using computational fluid dynamics (CFD). The numerical modeling of the thermodynamic behavior of the cold source employs polynomial laws as input data for the computational code (UDF functions). A comparison between experimental and numerical results reveals the computational code’s accurate prediction of the temporal temperature evolution in the cold storage distribution box, particularly under forced convection conditions. The findings indicate that in the absence of ventilation, thermal exchanges primarily occur through air conduction, whereas with ventilation, exchanges are facilitated by convection. Overall, forced convection induced by the inclusion of a ventilation device enhances thermal transfers and the thermodynamic performance of the cold storage distribution box. Furthermore, air mixing limits thermal stratification, thereby facilitating temperature homogenization.
Transcriptomic Analysis of Green Leaf Plants and White–Green Leaf Mutants in Haworthia cooperi var. pilifera
Authors: Li Peiling , Ren Maofei , Chen Juanjuan , Yue Jianhua , Liu Songhu , Zhu Qingsong , Wang Zhiyong
Published: May 2024

Haworthia cooperi var. pilifera is a succulent plant with ornamental value. The white–green leaf mutant (wl) showed a significant difference in leaf color from the wild-type plant (WT). In this study, we integrated the transcriptomes of wl and WT plants to screen differentially expressed genes related to leaf color variation. The results of transcriptome analysis showed that 84,163 unigenes were obtained after de novo assembly and the NR database annotated the largest number of unigenes, which accounted for 57.13%, followed by NT (43.02%), GO (39.84%), Swiss-Prot (39.25%), KEGG (36.06%), and COG (24.88%). Our finding showed that 2586 genes were differentially expressed in the two samples, including 1996 down-regulated genes and 590 up-regulated genes. GO analysis predicted that these differentially expressed genes (DEGs) participate in 12 cellular components, 20 biological processes, and 13 molecular function terms and KEGG analysis showed that metabolic pathways, plant–pathogen interaction, glycerophospholipid metabolism, endocytosis, plant hormone signal transduction, and ether lipid metabolism were enriched among all identified pathways. Through functional enrichment analysis of DEGs, we found that they were involved in chloroplast division and the biosynthesis of plant pigments, including chlorophyll, carotenoids, anthocyanin, and transcription factor families, which might be related to the formation mechanism of leaf color. Taken together, these results present insights into the difference in gene expression characteristics in leaves between WT and wl mutants and provide a new insight for breeding colorful leaf phenotypes in succulent plants.
Normal Ovarian Function in Subfertile Mouse with Amhr2-Cre-Driven Ablation of Insr and Igf1r
Authors: Douglas Jenna C. , Sekulovski Nikola , Arreola Madison R. , Oh Yeongseok , Hayashi Kanako , MacLean James A.
Published: May 2024

Insulin receptor signaling promotes cell differentiation, proliferation, and growth which are essential for oocyte maturation, embryo implantation, endometrial decidualization, and placentation. The dysregulation of insulin signaling in women with metabolic syndromes including diabetes exhibits poor pregnancy outcomes that are poorly understood. We utilized the Cre/LoxP system to target the tissue-specific conditional ablation of insulin receptor (Insr) and insulin-like growth factor-1 receptor (Igf1r) using an anti-Mullerian hormone receptor 2 (Amhr2) Cre-driver which is active in ovarian granulosa and uterine stromal cells. Our long-term goal is to examine insulin-dependent molecular mechanisms that underlie diabetic pregnancy complications, and our conditional knockout models allow for such investigation without confounding effects of ligand identity, source and cross-reactivity, or global metabolic status within dams. Puberty occurred with normal timing in all conditional knockout models. Estrous cycles progressed normally in Insrd/d females but were briefly stalled in diestrus in Igf1rd/d and double receptor (DKO) mice. The expression of vital ovulatory genes (Lhcgr, Pgr, Ptgs2) was not significantly different in 12 h post-hCG superovulated ovaries in knockout mice. Antral follicles exhibited an elevated apoptosis of granulosa cells in Igf1rd/d and DKO mice. However, the distribution of ovarian follicle subtypes and subsequent ovulations was normal in all insulin receptor mutants compared to littermate controls. While ovulation was normal, all knockout lines were subfertile suggesting that the loss of insulin receptor signaling in the uterine stroma elicits implantation and decidualization defects responsible for subfertility in Amhr2-Cre-derived insulin receptor mutants.
Can Hemorrhagic Stroke Genetics Help Forensic Diagnosis in Pediatric Age (<5 Years Old)?
Authors: Treves Biancamaria , Sonnini Elena , La Russa Raffaele , Del Duca Fabio , Ghamlouch Alessandro , De Matteis Alessandra , Trignano Claudia , Marchal Juan Antonio , Carrillo Esmeralda , Napoletano Gabriele , Maiese Aniello
Published: May 2024

When stroke occurs in pediatric age, it might be mistakenly interpreted as non-accidental head injury (NAHI). In these situations, a multidisciplinary approach is fundamental, including a thorough personal and familial history, along with accurate physical examination and additional investigations. Especially when the clinical picture is uncertain, it is important to remember that certain genetic conditions can cause bleeding inside the brain, which may resemble NAHI. Pediatric strokes occurring around the time of birth can also be an initial sign of undiagnosed genetic disorders. Hence, it is crucial to conduct a thorough evaluation, including genetic testing, when there is a suspicion of NAHI but the symptoms are unclear. In these cases, a characteristic set of symptoms is often observed. This study aims to summarize some of the genetic causes of hemorrhagic stroke in the pediatric population, thus mimicking non-accidental head injury, considering elements that can be useful in characterizing pathologies. A systematic review of genetic disorders that may cause ICH in children was carried out according to the Preferred Reporting Item for Systematic Review (PRISMA) standards. We selected 10 articles regarding the main genetic diseases in stroke; we additionally selected 11 papers concerning patients with pediatric stroke and genetic diseases, or studies outlining the characteristics of stroke in these patients. The disorders we identified were Moyamoya disease (MMD), COL4A1, COL4A2 pathogenic variant, Ehlers–Danlos syndrome (E-D), neurofibromatosis type 1 (Nf1), sickle cell disease (SCD), cerebral cavernous malformations (CCM), hereditary hemorrhagic telangiectasia (HHT) and Marfan syndrome. In conclusion, this paper provides a comprehensive overview of the genetic disorders that could be tested in children when there is a suspicion of NAHI but an unclear picture.