bluuebunny/crossref_metadata_2025_split huggingface dataset:
Entanglement and energy transportation in central-spin quantum battery
Authors: Liu 刘 Fan 帆 , Yang 杨 Hui-Yu 慧宇 , Wang 王 Shuai-Li 帅立 , Wang 王 Jun-Zhong 俊钟 , Zhang 张 Kun 堃 , Wang 王 Xiao-Hui 晓辉 
Published: December 2024

Abstract
Quantum battery exploits the principle of quantum mechanics to transport and store energy. We study the energy transportation of the central-spin quantum battery, which is composed of N
b spins serving as the battery cells, and surrounded by N
c spins serving as the charger cells. We apply the invariant subspace method to solve the dynamics of the central-spin battery with a large number of spins. We establish a universal inverse relationship between the battery capacity and the battery–charger entanglement, which persists in any size of the battery and charger cells. Moreover, we find that when N
b = N
c, the central-spin battery has the optimal energy transportation, corresponding to the minimal battery–charger entanglement. Surprisingly, the central-spin battery has a uniform energy transportation behaviors in certain battery–charger scales. Our results reveal a nonmonotonic relationship between the battery–charger size and the energy transportation efficiency, which may provide more insights on designing other types of quantum batteries.
Optimizing the performance of an indirect Time of Flight (iToF) LiDAR by adjusting optical power and level of modulation frequency
Authors: Nikmah A , Ramadani R , Firdaus R A , Kartolo S , Rianaris A , Pratomo H , Hanto D , Hapiddin A 
Published: December 2024

Abstract
The LiDAR system should be optimally designed to recognize any object, regardless of its surface or reflectance. Several key factors influence the performance of LiDAR, such as laser wavelength, optical power, modulation frequency, detector, signal processing, and others. This work validates the distance measurement performance of the indirect time of flight (iToF) LiDAR system by adjusting optical power and level of modulation frequency. Two target materials—aluminum foil (AF) and high-impact polystyrene (HIPS)—were experimentally characterized by measuring each target from 1 m to 56 meters. The optical power is adjusted by applying a bias current of 60 mA and 100 mA from a laser driver. The level of modulation frequency varies from 500 mV, 1000 mV, and 1260 mV in a signal generator. The experiment’s results, achieved by combining optical power and level of modulation frequency, indicate that the proposed LiDAR system can effectively differentiate between two target materials and maintain high accuracy across various distances. High optical power and level of modulation frequency settings allow possibilities to improve the signal strength obtained by the receiver of the iToF LiDAR. Possibilities the higher signal strength is also obtained when the target has a higher reflectivity. Consequently, the LiDAR system can cover a maximum distance for a target AF and HIPS at 56 m and 31 m, respectively.
Evaluation of Zn-Mg alloys: Microstructural and mechanical properties under low sintering condition
Authors: Yunata E E , Widiatmoko P P , Fauzi A D 
Published: December 2024

Abstract
This study evaluates the microstructural and mechanical properties of Zn-Mg alloys sintered at a temperature of 325°C for two hours. Zn-Mg alloys with varying magnesium (Mg) contents of 5%, 10%, 15%, and 20% were synthesized, with CaCO3 added as a pore-generating agent to introduce controlled porosity. Scanning electron microscopy (SEM) revealed pore sizes ranging from 70 to 113 μm, particularly prominent in the 20% Mg sample, which also exhibited a rough surface morphology. The mechanical properties, assessed using Micro Vickers hardness testing, showed a progressive increase in hardness from 18.30 HV to 23.82 HV with increasing Mg content. X-ray diffraction (XRD) analysis confirmed the formation of MgZn2 and Mg2Zn11 phases, indicating significant phase development even at this low sintering temperature. The findings suggest that low-temperature sintering can effectively control the microstructural and mechanical properties of Zn-Mg alloys, offering insights that may contribute to their potential as biomaterials.
Effect of amorphous silica from rice husk on the structure and optical properties of PVA
Authors: Riyanto A , Machmudah S , Purwaningsih S Y , Pratapa S 
Published: December 2024

Abstract
Combining amorphous silica (SiO2) particles into polyvinyl alcohol (PVA) results in a composite with unique optical characteristics. This study investigates the effects of SiO2 particles derived from rice husks on PVA’s structure and optical properties. Samples were prepared by blending PVA with SiO2 particles and casting the mixture into composite sheets. FTIR analysis exposed a reduction in hydroxyl groups (−OH) as the SiO2 content increased, designating stronger interactions among the −OH group and the particles through hydrogen bonds. XRD analysis showed increased molecular disorder and amorphousness with higher SiO2 concentrations. These structural changes altered optical properties, increasing the absorption spectrum as SiO2 concentration rose. The direct transition band gap reduced from 5.42 to 5.13 eV, and the indirect transition band gap dropped from 4.65 to 3.52 eV for pure PVA and the composite with 10% SiO2 content, respectively. Urbach energy enlarged from 0.52 to 1.41 eV, and the refractive index rose from 1.93 to 1.98.
Comparative analysis of material properties and applications of dried, fresh, and extracted longan leaves with Kopyor varieties
Authors: Paramita O , Ansori M , Putri S N , Mayangsari E D 
Published: December 2024

Abstract
This study aims to analyze the properties of dried leaves, fresh leaves, and essential extracts to determine the best ways to utilize these leaves in various applications. It also seeks to identify the flavonoid content and test the antioxidant activity of extracts from kopyor longan leaves from Semarang Regency. The tested leaves include fresh leaves, extracts, and dried leaves. The research involves extraction, flavonoid content, and antioxidant activity testing using 2,2-diphenyl-1-picrylhydrazyl (DPPH), FRAP, and ABTS methods. The kopyor longan leaf extract has the highest flavonoid content compared to fresh and dried leaf powder. The fresh leaf extract shows the highest antioxidant activity among the three samples, with the lowest IC50 (24.767 ppm). In antioxidant testing using the FRAP method, the dried leaf extract demonstrates higher antioxidant capacity than the fresh leaf extract and is more consistent than fresh leaves. The fresh leaf extract, tested with the ABTS method, shows a very high and consistent antioxidant capacity. In contrast, the dried leaf extract shows the highest and most consistent antioxidant capacity among the three samples. The kopyor longan leaf extract can be used to direct practical applications in the health and nutraceutical industries, focusing on the material’s most influential and consistent form.
Portable and inexpensive electrochemical impedance spectroscopy system for characterization of saline solution impedance
Authors: Rahmawati E , Santoso D R , Noor J A E , Dharmawan H A 
Published: December 2024

Abstract
The developed portable and inexpensive EIS instruments can measure impedance spectra from 0.01 Hz to 100 kHz. The instruments include a programmable current source from 1 μA to 300 μA for adjusting the range of impedance of the sample, which is possibly from 10 Ω to 1 kΩ, gain phase detector-based data acquisition, and microcontroller-PC-based software for controlling, collecting, and real-time plotting data in Bode and Nyquist diagram. The EIS system was validated by measuring dummy components’ impedance, resulting in less than 2% error. The system can measure the sample’s impedance and investigate the electrode-sample interface’s double-layer phenomenon with the available frequency range. This phenomenon is experienced in every impedance measurement and can affect the interpretation of the measurement spectrum. Furthermore, the instrument is applied to characterize the impedance of two different saline solutions (KCl and MgCl2) and the double-layer phenomena between electrode-electrolytes.
Implementation of Ethno-STEM based inquiry learning model assisted by LKPD to train creative thinking skills learners in the Merdeka curriculum learning
Authors: Anggreini  , Abdurrahman  , Kharisma D C 
Published: December 2024

Abstract
The lack of optimal learning innovation based on science, technology, and local wisdom that adapts to the characteristics of students has resulted in the Merdeka Curriculum being poorly implemented. Therefore, the specific target of this research is to produce ethno-STEM-based inquiry-based LKPD and see the effectiveness of ethno-STEM-based inquiry models on students’ creative thinking skills on the material of rigid body equilibrium. The research method combines hybrid design type III with mixed method sequential explanatory design. The sample of this research is SMAN 4 Metro. Based on the results of the LKPD validation, the average score was 85.5%, which is a very valid category for media and design validation, and 79.7%, which is a valid category for material and construct validation. The practicality test result obtained an average teacher perception test of 86.25% with an efficient category. The effectiveness test results obtained an average N-gain of 0.54 with a moderate category. Based on the study’s results, it can be concluded that applying the ethno-STEM-based inquiry model assisted by LKPD on the equilibrium material of firm bodies can train students’ creative thinking skills towards implementing the Merdeka Curriculum.
Profile analysis of students’ creative thinking ability in physics learning based on problem-based essay question instruments
Authors: Dwikoranto  , Admoko S , Dzulkiflih  , Setiani R , Khansa I H , Putra D A , Widiasih  
Published: December 2024

Abstract
This research aims to describe the profile of students’ creative thinking abilities using problem-solving-based creative thinking ability assessment instruments. Creative thinking skills tend to train students to come up with ideas and express themselves in the learning process. The instrument for targeting student profiles is in the form of an essay referring to the creative thinking indicators of fluency, elaboration, originality and flexibility. Using quantitative descriptive to analyze student profiles. The data collection technique uses a creative thinking ability test. The results of the implementation of the instrument showed that the level of creative thinking ability or student profile was obtained, and it was known that students’ abilities were categorized in each creative thinking indicator; the highest and lowest scores were respectively described in the specified aspects of creativity. The results of the analysis of students’ creative thinking abilities on renewable energy material were 68.0% in the creative category, 32.0% quite creative, and the average obtained for each indicator was 52.0%. Based on the data and analysis, it can be concluded that creative thinking abilities show the creative category and are creative enough so that physics learning is needed, which can further foster and increase student creativity.
Development of multimedia oriented to local wisdom to improve students’ understanding of physics concepts
Authors: Saputra O , Satriawan M , Anggaryani M , Habibbulloh M , Kholiq A 
Published: December 2024

Abstract
This research aims to develop learning media oriented to local wisdom and to find out how students respond to the media that has been developed. This research model uses the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) design. The sample for this research was 22 prospective teacher students at one of the universities in East Java province, Indonesia. The research results show that n-gain has increased by 0.71 (in the high category), and most students think the media developed is very useful for understanding phenomena in everyday life.
The collapse of students’ conceptions when solving physics problems
Authors: Widodo W , Mahdiannur M A , Suryanti  
Published: December 2024

Abstract
This study aimed to reveal whether students’ conceptions on the anchor concept can change along with the level of the physics problem to be solved. This descriptive research involves 58 prospective science teachers on Electrical Circuit material. Concept understanding was measured using a test instrument with the Three Tier-Test (TTT) method. While problem solving skills are measured using problem solving test instruments referring to the Multiple Misconception Revealing Test (MMRT). Data were analyzed by descriptive analysis. The results showed that students’ conceptions on the anchor concept can change when solving problems. Students who have correct conceptions (scientific conceptions) on the concept understanding test, do not always use their correct conceptions when solving problems. This finding indicates that even students with adequate conceptions try to switch to alternative concepts that are considered appropriate to the level of problem analysis so that the problem can be solved. And when they fail to choose the appropriate concept to solve the problem, there is a collapse of conception that leads to misconceptions when working on problem-solving problems. As an implication, physics educators must develop ways for students to defend their correct concepts when solving challenging physics problems.
Injectable, cryopreservable mesenchymal stromal cell-loaded microbeads for pro-angiogenic therapy: in vitro proof-of-concept
Authors: Touani Francesco K , Hamouda Inès , Noiseux Nicolas , Hoesli Corinne , Der Sarkissian Shant , Lerouge Sophie 
Published: December 2024

Abstract
Despite their recognized potential for ischemic tissue repair, the clinical use of human mesenchymal stromal cells (hMSC) is limited by the poor viability of cells after injection and the variability of their paracrine function. In this study, we show how the choice of biomaterial scaffolds and the addition of cell preconditioning treatment can address these limitations and establish a proof-of-concept for cryopreservable hMSC-loaded microbeads. Injectable microbeads in chitosan, chitosan–gelatin, and alginate were produced using stirred emulsification to obtain a similar volume moment mean diameter (D[4,3] ∼ 500 µm). Cell viability was determined through live/dead assays, and vascular endothelial growth factor (VEGF) release was measured by ELISA. Proangiogenic function was studied by measuring the wound closure velocity of human umbilical vein endothelial cells (HUVEC) co-cultured with MSC-loaded microbeads. The effect of freeze–thawing on microbeads morphology, porosity, injectability and encapsulated MSC was also studied. hMSC-loaded chitosan-based microbeads were found to release 11-fold more VEGF than alginate microbeads (p < 0.0001) and chitosan–gelatin was chosen for further studies because it presented the best cell viability. Preconditioning with celastrol significantly enhanced the viability (1.12-fold) and VEGF release (1.40-fold) of MSC-loaded in chitosan–gelatin microbeads, as well as their proangiogenic paracrine function (1.2-fold; p < 0.05). In addition, preconditioning significantly enhanced the viability of hMSC after 1 and 3 d in low-serum medium after cryopreservation (p < 0.05). Cryopreserved hMSC-loaded microbeads maintained their mechanical properties, were easily injectable through a 23G needle, and kept their paracrine function, enhancing the proliferation and migration of scratched HUVEC. This study shows the advantage of chitosan as a scaffold material and concludes that chitosan–gelatin microbeads with celastrol-preconditioned cells form a promising off-the-shelf, cryopreservable allogenic MSC product. In vivo testing is required to confirm their potential in treating ischemic diseases or other clinical applications.
Transforming education: Navigating the human-AI ecosystem in psychological training and beyond
Authors: Lushyn P V , Sukhenko Y V 
Published: December 2024

Abstract
This article explores the dynamic impact of artificial intelligence (AI) on education, with a focus on its integration into the field of psychology. The study analyzes the dichotomous nature of AI in educational settings, highlighting both its potential for innovation and the challenges it presents, particularly in terms of academic integrity and the quality of training. Utilizing the concept of self-organization of systems, the article examines AI as a transformative factor in education, necessitating a new order of collective interaction among educational participants. Empirical research is presented, comparing the content, structure, and style of texts generated by AI (specifically Claude 2.1 and ChatGPT 4) and psychology students. This comparison establishes criteria for differentiating between “human” and “artificial” texts, underscoring the unique aspects of human creativity and critical thinking that AI currently cannot replicate. The study also reveals the evolving role of educators as facilitators within a hybrid ecosystem of human and AI participants. The article proposes future research directions, including the exploration of collaborative interactions between individuals and AI and the development of accelerated learning methodologies within the human-AI ecosystem. It emphasizes the necessity of balancing the strengths of human creativity with AI’s computational efficiency, aiming to enhance student motivation and expand cognitive capabilities in educational settings. Furthermore, the article discusses the emergence of new professional roles such as AI user facilitators, and AI facilitators, highlighting the growing complexity of human-AI interactions. These roles are crucial for effective and ethical utilization of AI in education, especially in psychology. The article presents AI as a catalyst for significant paradigm shifts in education and professional training, particularly in socionomic fields. It advocates for a synergistic approach to education, where AI complements human abilities, leading to enriched learning experiences and the development of a more adaptive, personalized, and efficient educational landscape.
Artificial intelligence, the labor market, and education for sustainable development: the points of intersection
Authors: Osadcha K P , Shumeiko N V 
Published: December 2024

Abstract
This scientific paper is devoted to clarifying the relationship between artificial intelligence (AI), the modern labor market, and Education for sustainable development. Within this study, the authors concentrate their efforts on the following directions: (1) exploring the existing educational approaches and techniques, the knowledge of which helps minimize the possible negative consequences associated with the implementation of AI into the labor market; (2) analyzing Ukrainian and Slovak students’ points of views, that were obtained by surveying, on AI technologies and their potential effects on the labor market; (3) providing substantiation regarding the need of using the pedagogical strategies, particularly, (a-b) the implementation of AI-related technologies in the professional cycle disciplines, (c) assigning tasks that require AI technologies to exploit, (d) exploiting AI technologies as the source of improving the information infrastructure in HEIs. While formulating these pedagogical strategies, the authors comprised possible consequences (a negative effect of AI on the labor market, risks of applying AI in all spheres of human activity, a negative attitude of students toward AI) of AI application and the planned results. The authors considered the five dimensions of sustainability (technical, social, environmental, user, and economic) and presented them in the format of the Sustainability Awareness Diagram (SAD). The visualization of the effects that may result from the use of pedagogical strategies for Education for Sustainable Features is suggested. Each planned result is put in the SAD, assuming their influence (immediate, enabling, structural) on Sustainable Features. In overall, the proposed strategies aim to reduce the potential negative impacts of AI on the functioning of the labor market and instill a positive attitude toward AI technologies in university youth. The findings comprise the multifaceted and dynamic relationships between AI, the modern labor market, and Education for sustainable development. Results also reveal that AI technologies significantly impact the labor market by influencing job roles and skill requirements. Correspondingly, Education for sustainable development is vital in preparing young people to be aware of the evolving demands of the labor market impacted by AI, promoting skills that align with both technological improvements and sustainable practices.
Prospects for using composite preparations based on silica nanosols
Authors: Aksylenko M D , Sheludko Y V , Tkachenko T V , Haidai O O , Yevdokymenko V O 
Published: December 2024

Abstract
Composite preparations were created for foliar feeding of winter wheat using obtained silica nanosols and lignin fugate after coals carbonization. Both laboratory and vegetative studies have confirmed the effectiveness of created preparations for foliar treatments of Cubus winter wheat (T riticum aestivum L.). When applied, the preparations enhanced the moisture-holding capacity of leaves, photosynthetic processes of the leaf apparatus, and biosynthesis of organic matter, compared to the control group. Additionally, the studied compositions increased the content of endogenous antioxidants, such as carotenoids in plants, and reliably contributed to the reduction of peroxidation processes in cell membrane lipids. Their use could increase the drought resistance of wheat plants.
Tool for management and planning of the fuel and energy complex taking into account the production potential of coal-mining enterprises
Authors: Pochepov V M , Mamaikin O R , Sheka I V , Krukovskyi O P , Lapko V V , Ashcheulova O M 
Published: December 2024

Abstract
The article presents a toolkit of manage balanced functioning of the fuel and energy complex with the aim of improving the system of state support for coal mines and harmonizing the interests of the enterprise, national interests, and interests of product consumers. To solve the problem, a comprehensive approach was used, which includes the assessment of the investment attractiveness of the enterprise, the determination of the production potential, and the determination of the possibility of transition to the break-even mode. The process of planning ways of saving the industrial potential of coal-producing regions can be considered as a reflection of a multidimensional space (initial and design values) into a one-dimensional (the amount of investment funds). The reduced task to the selection of the smallest number of factors that would most adequately reflect the internal potential of mine in terms of economic added value – as a result of the interaction factors of economic activity of coal mine. The scientific novelty lies in the fact that the formed matrix model of the commercial coal products balance is aimed at avoiding an imbalance in the sectoral coal market and significantly reducing unjustified costs both on the part of the state and on the part of mining enterprises due to the optimization of planned and forecast indicators. The practical significance lies in conducting an actual assessment of coal enterprises state of Ukraine and determining break-even limits, which made it possible to formulate recommendations for attracting volumes of financial resources.