bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of hypertension disease using Artificial Neural Network (ANN) backpropagation method case study in mitigating health risk: UPT Modopuro Mojokerto Health Center
Authors: Rochman Eka Mala Sari , Indriawati Nina , Suzanti Ika Oktavia , Setiawan Wahyudi , Husni  , Ma'arof Muhammad Izzat Nor , Rachmad Aeri
Published: November 2024

Hypertension is a disease caused by increased blood pressure above 140/90 mmHg and is often referred to as "the silent killer" because most sufferers do not realize that they have hypertension, and only realize when complications have occurred. Hypertension is one of the main causes of death worldwide which can be influenced by many factors. In UPT (Integrated Service Unit) PUSKESMAS (Community Health Center) Modopuro, Mojokerto Regency, hypertension is ranked among the top 10 diseases with the most patients. With a fairly high risk of death and an increase in the number of people with hypertension, it is often caused by delays in diagnosis, which must be carried out blood pressure checks by medical personnel at least 2 times with 1 week to establish a diagnosis of hypertension. If hypertension is not treated immediately, it can cause other health conditions such as kidney disease, heart disease, and stroke. Therefore, a system is needed that can be used for the classification of early detection of whether a person has hypertension or not. To overcome these problems, a system was created to classify hypertension using the Backpropagation method. Backpropagation is very effective in helping artificial neural networks learn from mistakes, allowing the system to make more accurate predictions over time. Dataset used in this study is the medical record data of UPT Puskesmas Modopuro patients with 1000 data. The results obtained the best model with a network structure of 7-5-1, learning rate 0.001, and Adam optimizer. With an accuracy of 93.50% and a loss value of 0.0697. While the precision, recall, and f1-score values are 94.00%, 93.00%, and 93.00%, respectively. With good accuracy performance, indicating that the backpropagation model can be applied in hypertension classification.
How Much is Character Education Correlated with Learning Outcomes of Islamic Religious Education Students in Indonesia: Meta-Analysis Study
Authors: Astuti Rahayu Fuji , Susanti Eka , Yusnaldi Eka , Budiman  , Arsyad Junaidi , Setyawan Agung
Published: November 2024

This study aims to conduct a statistical evaluation of the correlation between character education and Islamic Religious Education (PAI) learning outcomes among students in Indonesia, addressing the variations in findings from previous research. A meta-correlation analysis was employed, analyzing data from 36 independent studies derived from 24 primary sources published between 2019 and 2023. The data was processed using JASP software (version 0.16.4). The analysis yielded a combined effect size of 0.30 (p < 0.001) based on a random effects model, indicating a small but statistically significant effect. These results suggest that improvements in character education are positively associated with academic achievement in Islamic Religious Education. The findings underscore the importance of integrating character education into the curriculum to enhance students' learning outcomes in PAI.
Study of diet composition in sea cucumber intestines in Socah Waters, Bangkalan Regency
Authors: Putri Rizka Rahmana , Putri Fareza Nabila Dhea Fatma , Laksani Mertiara Ratih Terry , Juanda Shobikhuliatul Jannah
Published: November 2024

Sea cucumbers, which belong to the Phylum Echinodermata, possess significant potential for cultivation. However, these invertebrates require further investigation concerning various aspects of their cultivation, including their feeding habits and diet composition. Research on the dietary requirements of sea cucumbers aims to identify their primary and supplementary food sources, which can serve as references for the provision of natural feed in future sea cucumber farming efforts. Data collection was conducted through random sampling in the Socah Waters, Bangkalan Regency. Observations of the food type found in the intestines of sea cucumbers revealed the presence of plankton, sediment, and detritus. The plankton species identified in the intestines include Cyclotella kuatzingiana, Chaetoceros densus, and Thalassiosira fluviatilis. The diet composition varied among the three sea cucumber species studied: Paracaudina australis, Phyllophorus sp., and Colochirus quadrangularis. In Paracaudina australis, the food composition consists of Cyclotella kuatzingiana (55%), Thalassiosira fluviatilis (30%), sediment (10%), and detritus (5%). For Phyllophorus sp., the composition consists of sediment (70%), detritus (15%), Thalassiosira fluviatilis (10%), and Chaetoceros densus (5%). In Colochirus quadrangularis, the diet comprised Thalassiosira fluviatilis (55%), Cyclotella kuatzingiana (20%), sediment (15%), and detritus (10%).
Hydroponic NFT agricultural monitoring website: Temperature control based on PID
Authors: Wahyuni Sri , Rusydi Amin , Fuad Muhammad
Published: November 2024

This study aims to develop an automated control system for hydroponic growing media to optimize temperature and nutrient conditions tailored to various plant types. The control method proposed in this study uses the Proportional Integral Derivative (PID). PID control allows for precise adjustments in temperature and nutrient levels, enhancing plant growth. A web-based interface enables users to monitor and adjust the system settings according to their chosen plant type. The vegetables planted for the trial testing of this system are caisim, pok choy, spinach, lettuce, broccoli, and cauliflower, which can grow in lowlands and highlands. Users will also get a reminder of the estimated harvest of plants being planted through the monitoring website so that users do not have to bother calculating the length of the planting process. The system achieves a remarkable control accuracy of 99.9% in maintaining optimal conditions, although it struggles to cool water to the desired 25℃ during peak daytime temperatures. This is because the Peltier work is very dependent on the ambient temperature. Future research may explore alternative cooling methods or adjustments to the Peltier for a more efficient cooling process or continue to use the Peltier but think about a better heat exchange concept in both the heat exchanger water so that the hot water resulting from the cooling process using the Peltier does not settle in one container. It is expected to make it easier for someone to grow vegetables for food-oriented development (FOD) and urban farming.
Integrating Neuroeducation into Educational Management: A Breakthrough for Enhancing Elementary Education
Authors: Bendriyanti Rita Prima , Setyawan Agung , Kurniasih Nila , Citrawati Tyasmirani
Published: November 2024

This study aims to evaluate the effectiveness of neuroeducation implementation in elementary education and develop a teacher training model to enhance understanding and application. A quantitative approach with a survey and quasi-experimental design was employed across seven regions in Indonesia, involving 28 public elementary schools implementing the Kurikulum Merdeka. Data were collected through evaluation questionnaires and structured interviews completed by teachers following neuroeducation training. The results show a significant increase in teachers' understanding and application of neuroeducation principles, with the average understanding score rising from 2.7 before training to 4.5 after training. Structured interviews revealed that while teachers felt more confident in applying neuroeducation, they still required ongoing support. The discussion links these findings to Andragogy, Constructivism, and Lifelong Learning theories, highlighting that experience-based and continuous training effectively enhances teacher competence. The conclusion drawn from this research is that neuroeducation can be effectively implemented in elementary schools with appropriate training support, contributing to the improvement of elementary education quality in Indonesia.
Experimental Study of The Growth of Ammonium Bisulfate Ash Deposition at Different Wall Temperatures and Heat Transfer Characteristics
Authors: Yu Yongfei , Pan Weiguo
Published: November 2024

The deposition of ammonium bisulfate ash (ABS) is a common occurrence in the flue of a boiler in a power plant. This can result in a reduction in the efficiency of the selective catalytic reduction (SCR) process and the air preheater. To reduce the formation of ABS deposits in flue gas systems, extend the service life of SCR catalysts, and improve the efficiency of heat exchangers, online monitoring technology was employed to observe the formation of ABS deposits in a vertical one-dimensional furnace. The objective of this study is to investigate the formation of ABS deposits on heat transfer surfaces at varying temperatures and their impact on heat transfer characteristics. It was observed that the growth rate of ABS deposition decreased with the increase in wall temperature. At temperatures of 250°C, 300°C, and 350°C, the stable thickness of ABS deposition decreased to 4.09mm, 3.97mm, and 3.84mm, respectively. Moreover, the relative heat flux (RHF) also increases with the increase of wall temperature, from 0.68 at 250°C to 0.78 at 350°C. Consequently, an increase in the surface temperature of the heat transfer medium can effectively reduce the formation of ABS deposits and enhance the efficiency of heat transfer.
Research on Effect of Microplastics Removal through Combination of Coagulation and Sand Filtration
Authors: Zhao Meizi , Zhu Yanjing , Wang Rui
Published: November 2024

Microplastics (MPs) removal by coagulation and sand filter was investigated in a secondary wastewater treatment plant effluent matrix. The samples were collected and treated using three typical coagulants, i.e., ferric chloride (FeCl3), polyferric sulfate (PFS) and polyaluminum chloride (PAC). Results showed that all the three tested coagulants can effectively remove MPs with applicable dosages in tertiary treatment (10-50 mg/L). The highest removal rate obtained was 61% with 40 mg/L PFS, and PFS were slightly more efficient than PAC and FeCl3. After sand filtration, about 75.7% of MPs was removed. The combined PFS (40 mg/L) +sand filter process could remove 91% of MPs, 82% of suspended solids (SS) and 85% of total phosphorus (TP). The treatment cost of coagulant was about 0.0594 Yuan/t wastewater. Therefore, it is technologically and economically feasible to use coagulation and sand filter process to remove MPs from wastewater in tertiary treatment process in wastewater treatment plant.
Study on the Microplastics’ Effect on the Life History of Daphnia magna
Authors: Zhao Biying , Tian Wenjing
Published: November 2024

Microplastics (MPs), a type of new pollutant, have shown negative impacts on the aquatic environment. To understand how MPs impact zooplanktons, we studied the life history of Daphnia magna. D. magna those fed with fluorescent microspheres at two different concentrations (0.1mg/L and 1mg/L) and particle sizes respectively (0.1μm and 5μm). The results showed that MPs negatively affected the growth and reproduction of D. magna significantly. Specifically, the impact of higher concentration of 5μm microspheres > high concentration of 0.1μm microspheres > low concentration of 0.1μm microspheres > low concentration of 5μm microspheres. In addition, prolonged feeding time in large-particle-size microspheres (5μm) enhanced the ingestion of microspheres by D. magna, resulting in higher impact on life history. In conclusion, smallparticle-size microspheres (0.1μm) are more harmful at low concentrations. However, microplastic pollution shows impacts only on the life history (growth and reproduction), but not the survival rate of D. magna in our study.
Comprehensive Evaluation of LID Deployment on Mountain Sponge City: Evidence from Yuzhong, Chonging in China
Authors: Zhang Shouping , Xie Song , Liu Xinke , Li Xia , Sun Qingya , Gao Qian
Published: November 2024

To comprehensively assess the effects of different Low Impact Development (LID) measures on urban rainfall and water quality control, this study focuses on the Liberation Monument Street in Yuzhong District, Chongqing City, and establishes a coupled model for water quantity and water quality. The model calibration and validation are carried out by targeting the uncertain parameters in the model, using watershed characteristic factors as the objective function. Different LID scheme with varying deployment areas were proposed to explore the control effects of water quantity and water quality indicators. The comprehensive evaluation of various schemes, including water quantity, water quality, construction and operational costs, was conducted using the life cycle cost, the analytic hierarchy process, and the principal component analysis. The results show that combination of green roof 10.62 hm2, permeable pavement 45.15 hm2, and biological retention pool 1.14 hm2 is the best, with a total construction cost of 181.53 million RMB. Under different return periods, the optimal scheme varies, providing a reference for selecting the best LID combi-nation deployment scheme under different return periods.
The Nexus of UG-ESs in the Chinese Loess Plateau using CL-CA and Ecological Assessment Models
Authors: Liang Youjia , Su Zichong , Liu Lijun
Published: November 2024

Urban growth (UG) in the Chinese Loess Plateau has increased rapidly, impacting regional ecosystem services (ESs). Accurate evaluations of UG-ESs have become a challenge for the development of simulation models. To address long-term spatiotemporal dependencies in grid neighborhood interactions, this study enhances land-use simulation accuracy using a method combining machine learning algorithms and cellular automata (CL-CA) to model competitive relationship between urban growth and other land-use types during 2000-2050, and then, ESs supply was simulated with ecological assessment models under three landuse scenarios: business as usual, ecological priority, and economic priority. Key findings include: (1) Growth rates and land-use patterns are influenced by policies and natural environments, with an expected urban growth rate of 3%-6%, shifting from leapfrog to marginal growth post-2030; (2) Forests and grasslands primarily impact ESs; and (3) The EP scenario optimally balances sustainable urban development and ES enhancement.
Osteoporotische Indikatorfraktur: Die distale
Radiusfraktur
Authors: Oezel Lisa , Thelen Simon , Maus Uwe
Published: November 2024

Distale Radiusfrakturen stellen die häufigsten Frakturen des Menschen dar. Bei
älteren Patienten sind sie häufig, und die Inzidenz nimmt mit dem
demographischen Wandel der Bevölkerung weiter zu. Als Indikatorfraktur für
Osteoporose, kommt der distalen Radiusfraktur eine besondere Bedeutung zu. Neben
einer adäquaten Therapie der Fraktur, welche individuell an die
Frakturmorphologie und Patientenbedürfnisse angepasst werden sollte und operativ
oder konservativ erfolgen kann, ist zur Vermeidung weiterer
Osteoporose-assoziierter Frakturen die Einleitung einer Osteoporose- Therapie
und Diagnostik unabdingbar. Ziel der Behandlung ist es, eine schmerzfreie
Extremität mit guter Funktion wiederherzustellen und zu erhalten. Bei der
Entscheidung für einen chirurgischen Eingriff sollten die Knochenqualität und
die funktionelle Aktivität des Patienten besonders berücksichtigt werden. Wenn
eine chirurgische Intervention angebracht ist, wird in der Regel eine
winkelstabile palmare Plattenosteosynthese eingesetzt. Die chirurgische
Behandlung verbessert oftmals die Frakturstellung und damit die radiologischen
Parameter, führt jedoch nicht unbedingt zu besseren klinischen Ergebnissen.
Daher sollte sich bei der Behandlung distaler Radiusfrakturen des älteren
Menschen individuell und mit Sorgfalt für ein Behandlungsregime entschieden
werden.
Cranial Nerve Dysfunction in Patients with an Occipital Condyle Fracture: Underdiagnosis and Clinical Relevance
Authors: Thevis Madelon , Derks Jolanda , Jansen Thijs T.G. , Hosman Allard J.F. , Kunst Henricus P.M.
Published: November 2024

Objectives This study aims to fill in the knowledge gap about patients with occipital condyle fractures (OCFs) and cranial nerve dysfunction (CND) and give advice about when to test the cranial nerves (CNs) and what to do when CND is diagnosed.

Design A 14-year period observational, retrospective cohort study.

Setting Level-I trauma center study.

Participants All 119 surviving cases admitted with an OCF, whereof all 40 cases with either diagnosed CND (confirmed by clinical examination) or expected CND (reported observations high suspicious for CND) were selected for detailed data collection. Early death was the only exclusion criterion because of missing data and clinical irrelevance.

Main Outcome Measures One-third of all surviving OCF patients have CND (n = 40/119, 33.6%), where three-quarters had more than one CN affected with a median of three CNs. Of the cases with a concomitant lateral skull base fracture (n = 24/40, 60%), one in three cases (36%, n = 13/36) had facial nerve palsy and nearly two in three cases (61%, n = 22/36) had hearing loss.

Results The facial nerve was the most commonly diagnosed CND. Solitary OCF cases often had lower CND (n = 11/14). Fifty-eight percent of all CND cases with follow-up data (n = 19/33)—corresponding to one in six of all surviving OCF cases—had chronic CND sequelae.

Conclusions Multiple and chronic CND is common in patients with an OCF. All CNs should be tested in those patients as soon as clinically possible, and testing should be repeated after 3 to 7 days and before discharge. Patients with CND should be counseled about their prognosis and be potentially referred to (e.g.) a speech and language therapist, ophthalmologist, neurologist, or otorhinolaryngologist for early treatment options.
Contribution of supercritical states of 3He quasiparticles to the thermodynamics of superfluid solutions
Authors: Antsygina T. N. , Slyusarev V. A. , Strzhemechnyi M. A.
Published: November 2024

Within the framework of a modified Lee model the paper discusses the energy spectrum of 3He excitations in superfluid 4He in the range of momenta close to the critical point at which the 3He excitation decays into a roton and a low-momentum excitation. The thermodynamic potential is reconstructed taking account of the contribution from supercritical states.
Low-temperature collective Greens’s function and longitudinal susceptibility of an anisotropic Heisenberg ferromagnet
Authors: Rudoi Yu. G.
Published: November 2024

The longitudinal dynamic susceptibiltiy of an “easy axis” anisotropic Heisenberg ferromagnet is studied in the presence of a variable, spatially nonuniform external magnetic field. Linearized quantum equations of motion for the Fourier transforms of the longitudinal components of the spin operators are used to construct a dynamic random phase approximation at low temperatures. The dispersion equation is analyzed and it is shown that there are no long-wavelength excitations of the “zero magnon” type for either a spin model or for a broad class of quasibosons (including the models of Oguchi and Dyson).
Predicting terrain-induced wind turbulence for smokejumper parachute operations
Authors: Wagenbrenner Natalie , Atwood Loren , Forthofer Jason , Grenfell Isaac
Published: November 2024

Background Terrain-induced turbulence is dangerous for smokejumpers parachuting into complex terrain and results in numerous serious accidents annually. Aims We quantify wind modelling system WindNinja’s ability to reproduce terrain-induced effects on the mean wind speed and turbulence in complex terrain. We assess WindNinja’s suitability for use in identifying safe jump spots during smokejumper operations in complex terrain. Methods We evaluate the model’s ability to reproduce mean wind speed, mean wind direction and turbulence kinetic energy (TKE) measured by sonic anemometers and lidar scanners over a ridge–valley–ridge system collected under near-neutral atmospheric conditions during the Perdigão field campaign. We conduct a WindNinja simulation to examine the wind and turbulence conditions during the 2021 Eicks Fire smokejumper accident. Key results WindNinja can reproduce both mean wind speed and turbulence characteristics induced by the terrain. WindNinja revealed critical turbulence information that could have been useful to smokejumpers during the Eicks Fire jumping operation. Conclusions WindNinja’s ability to reproduce key features in the mean wind speed and turbulence fields induced by the terrain make it suitable for use as an aid in identifying safe jump spots in complex terrain. Implications Findings from this work will reduce parachute accidents and increase the safety of aerial firefighter operations.
Cultural tightness and resilience against environmental shocks in nonindustrial societies
Authors: Tverskoi Denis , Ember Carol R. , Gelfand Michele J. , Jones Eric C. , Skoggard Ian , Toutée Louise , Gavrilets Sergey
Published: November 2024

With climate change intensifying, building resilience against climate-related shocks is now a global imperative. Historically, many societies have faced natural hazards, with some adapting through specific social and cultural practices. Understanding these responses is key to developing modern sustainability strategies. Here, we address this issue by developing a mathematical model explicitly accounting for various environmental shock dimensions, cooperative activities common in nonindustrial societies, and decision-making based on material factors as well as personal values and social norms. Our results suggest that cultural looseness can be vital for effectively responding to mild, slow-onset shocks, leading to moderate cooperation and minimal cultural change. Conversely, coping with severe shocks requires an intermediate level of cultural tightness, fostering significant cultural transformation and high cooperation. While tight societies struggle with new shocks, they may handle regular, severe, fast-onset shocks better than do loose societies. Our research enhances understanding of environmental impacts on cooperation, cultural tightness, and social resilience, and highlights cultural adaptations useful in addressing current environmental challenges like global warming, floods, tornadoes, and soil degradation.
Race and affect in Gustave de Beaumont’s Marie, ou L’esclavage aux Etats‑Unis
Authors: Dobie Madeleine
Published: November 2024

Gustave de Beaumont’s novel Marie, ou l’esclavage (1835), a companion piece to
Alexis de Tocqueville’s Democracy In America (1835, 1840)
(Beaumont accompanied Tocqueville on his travels through the United States), belongs to a small group of early
nineteenth-century francophone fictions in which the question of slavery is deflected onto the examination of race.
Romantic psychology and epistemology shape Beaumont’s exploration of race as a site of emotional intensity that has no
fixed referent. This treatment of race as an emotional forcefield rather than as the cause of an emotional effect,
anticipates the work of theorists of affect and social emotionality such as Sara Ahmed. While Beaumont strives to
demystify race, thereby exposing the absurdity of racial prejudice, by centering whiteness as an aesthetic value and
metaphor for purity, the novel in the end illustrates its tenacious hold.
Orientalism, slavery and emotion
Authors: Moussa Sarga
Published: November 2024

The oriental travel narratives of the first half of the nineteenth century played an important
role in debates about slavery. An episode in the slave market of Constantinople that appeared in Alphonse de
Lamartine’s Voyage en Orient (1835) created a model followed by later writers. But while Lamartine, a
committed abolitionist, tried to stir up feelings of pity by describing the sale of a black woman and her child, in
Marcellus, Nerval and Pückler-Muskau, similar descriptions evoked different reactions, ranging from the condemnation
of Islamic polygamy to the acceptance of slavery as an ‘oriental fatality.’ Nerval, for his part, reserved pity for
the fate of white slaves. Oriental travel narratives as such represent a kind of emotional barometer that gauges both
the progress of abolitionist discourse and resistance to it.
Affection amidst domination in a post-slavery society
Authors: Cottias Myriam
Published: November 2024

This article considers the relationship between compensation and intimacy, focusing on the
relationship between the colonist Pierre Dessalles, who owned a plantation in the French colony of Martinique in the
mid-nineteenth century, i.e. the period of the abolition of slavery, and Nicaise, one of his slaves. It shows slavery
to be a relation of property and domination that did not, however, foreclose the possibility of emotional ties ranging
from fear, anger and disgust to love. Readings of the diary of this planter — an exceptional document for its time —
show how intimacy and “emotion” in all senses of the word — feelings but also, in French, something closer to
“stirring” or “revolt” — both shape and are shaped by the political situation in which they develop.
Differential impacts of ribosomal protein haploinsufficiency on mitochondrial function
Authors: Surya Agustian , Bolton Blythe Marie , Rothe Reed , Mejia-Trujillo Raquel , Leonita Amanda , Zhao Qiuxia , Arya Alia , Liu Yue , Rangan Rekha , Gorusu Yasash , Nguyen Pamela , Cenik Can , Sarinay Cenik Elif
Published: November 2024

The interplay between ribosomal protein (RP) composition and mitochondrial function is essential for energy homeostasis. Balanced RP production optimizes protein synthesis while minimizing energy costs, but its impact on mitochondrial functionality remains unclear. Here, we investigated haploinsufficiency for RP genes (rps-10, rpl-5, rpl-33, and rps-23) in Caenorhabditis elegans and corresponding reductions in human lymphoblast cells. Significant mitochondrial morphological differences, upregulation of glutathione transferases, and SKN-1–dependent oxidative stress resistance were observed across mutants. Loss of a Datasingle rps-10 copy reduced mitochondrial activity, energy levels, and oxygen consumption, mirrored by similar reductions in mitochondrial activity and energy levels in lymphoblast cells with 50% lower RPS10 transcripts. Both systems exhibited altered translation efficiency (TE) of mitochondrial electron transport chain components, suggesting a conserved mechanism to adjust mitochondrial protein synthesis under ribosomal stress. Finally, mitochondrial membrane and cytosolic RPs showed significant RNA and TE covariation in lymphoblastoid cells, highlighting the interplay between protein synthesis machinery and mitochondrial energy production.
Optimizing solar cell models: a multi-objective parameter estimation algorithm for improved photovoltaic system performance
Authors: Singla Manish Kumar , Aljaidi Mohammad , Gupta Jyoti , Safaraliev Murodbek , Kumar Ramesh , Ali Ziad M , Alsharif Mohammed H , Kim Mun-Kyeom
Published: November 2024

Accurate models of solar cells are required to improve the performance of solar photovoltaic (PV) systems. Due to a lack of precise parameters in the manufacturer’s datasheet, the solar cell model is often inaccurate. Estimating the parameters needed improperly makes it impossible to build up a reliable solar PV cell model. This paper proposes an algorithm for estimating cell parameters by multi-objective optimization to solve this issue. Several optimizers attempted to address the suboptimal results of optimization due to local minima and premature convergence. This work aims to evaluate the effectiveness of the proposed algorithm with those other popular algorithms to understand its reliability. The efficiency of this algorithm is proven using empirical results and statistical figures. It has important features, including simplicity and high accuracy, which imply that the algorithm is better suited to estimating solar PV models when compared with other algorithms. This algorithm is robust as it is computationally efficient and easy to use, which makes this method applicable for solving a wide variety of problems related to solar energy.
Structural, electronic, vibrational, optical and thermoelectric properties of 1T-Na2O monolayer via MD and DFT study
Authors: Rueshwin S Chellaiya Thomas , Eithiraj R D
Published: November 2024

Density Functional Theory (DFT) was implemented to determine the physical properties of the 1T-Na2O monolayer with the aid of WIEN2k software. To determine the electronic property exchange correlation such as GGA and hybrid functionals were implemented. The electronic property studies unveiled the 1T-Na2O monolayer as a direct bandgap semiconductor that has band gap values of 1.68 eV and 2.75 eV with GGA and hybrid correlation functionals. The dynamical stability of the 1T-Na2O monolayer was established by harnessing Phonon dispersion analysis, while the thermal stability was established by harnessing the Ab-initio Molecular Dynamics (AIMD). The optical properties investigation revealed that the 1T-Na2O monolayer shows an excellent absorption coefficient in the UV region and has a potential application in optoelectronic applications. The 1T-Na2O monolayer shows promise for waste heat recovery systems due to its thermoelectric properties, with a figure of merit of 0.82 at 400 K. The effective masses of electrons and holes (charge carriers) are determined. The relative ratio was estimated to determine the recombination rate of charge carriers and was found to be limited.
Coport: a new public code for polarized radiative transfer in a covariant framework
Authors: Huang Jiewei , Zheng Liheng , Guo Minyong , Chen Bin
Published: November 2024

General relativistic radiative transfer calculations are essential for comparing theoretical models of black hole accretion flows and jets with observational data. In this work, we introduce Coport,[The public version of Coport is available at the following URL: https://github.com/JieweiHuang/Coport.] a novel public code specifically designed for covariant polarized ray-tracing radiative transfer computations in any spacetime. Written in Julia, Coport includes an interface for visualizing numerical results obtained from HARM, a publicly available implementation of the general relativistic magnetohydrodynamics code. We validate the precision of our code by comparing its outputs with the results from a variety of established methodologies. This includes the verification against analytical solutions, the validation through thin-disk assessments, and the evaluation via thick-disk analyses. Notably, our code employs a methodology that eliminates the need for separating the computations of spacetime propagation and plasma propagation. Instead, it directly solves the coupled, covariant, polarized radiative transfer equation in curved spacetime, seamlessly integrating the effects of gravity with plasma influences. This approach sets our code apart from the existing alternatives and enhances its accuracy and efficiency.
Fast likelihood-free inference in the LSS Stage IV era
Authors: Franco-Abellán Guillermo , Cañas-Herrera Guadalupe , Martinelli Matteo , Savchenko Oleg , Sciotti Davide , Weniger Christoph
Published: November 2024

Forthcoming large-scale structure (LSS) Stage IV surveys will provide us with unprecedented data to probe the nature of dark matter and dark energy. However, analysing these data with conventional Markov Chain Monte Carlo (MCMC) methods will be challenging, due to the increase in the number of nuisance parameters and the presence of intractable likelihoods. In light of this, we present the first application of Marginal Neural Ratio Estimation (MNRE) (a recent approach in simulation-based inference) to LSS photometric probes: weak lensing, galaxy clustering and the cross-correlation power spectra. In order to analyse the hundreds of spectra simultaneously, we find that a pre-compression of data using principal component analysis, as well as parameter-specific data summaries lead to highly accurate results. Using expected Stage IV experimental noise, we are able to recover the posterior distribution for the cosmological parameters with a speedup factor of ∼ 10-60 compared to classical MCMC methods. To illustrate that the performance of MNRE is not impeded when posteriors are significantly non-Gaussian, we test a scenario of two-body decaying dark matter, finding that Stage IV surveys can improve current bounds on the model by up to one order of magnitude. This result supports that MNRE is a powerful framework to constrain the standard cosmological model and its extensions with next-generation LSS surveys.
Timing Calibration of the Follow-up X-Ray Telescope On Board the Einstein Probe Satellite
Authors: Zhao Xiaofan , Cui Weiwei , Wang Hao , Zhang Yifan , Zhao Zijian , Hou Dongjie , Zhu Yuxuan , Wang Yusa , Xu Jingjing , Luo Laidan , Han Dawei , Yang Yanji , Wang Juan , Ma Jia , Yang Xiongtao , Huo Jia , Li Wei , Zhang Ziliang , Geng Haoyang , Chen Yong
Published: November 2024

The Follow-up X-ray Telescope (FXT) is one of the main scientific instruments on board the Einstein Probe astronomical satellite, which was launched in 2024 January. FXT consists of two Wolter I type nested telescopes (FXT-A and FXT-B) with a focal length of 1600 mm. The focal plane detector employs a PNCCD with 384 × 384 pixels. The timing mode of FXT serves as the primary operating mode for fast X-ray timing observations. To evaluate and validate the timing performance of FXT prior to launch, a comprehensive timing calibration was performed at the 100 m X-ray test facility. By simulating various periodic Crab-like profiles using the Grid Controlled X-ray Tube (GCXT) in conjunction with a pulsar simulation module, it was verified that the relative time accuracy of FXT exceeds 5 × 10−9. Furthermore, employing GCXT with a voltage pulse generation module enabled the determination of the time resolutions for FXT-A and FXT-B, recorded as 45.6 ± 2.7 μs and 47.1 ± 2.8 μs, respectively. An absolute timing calibration for FXT-B was carried out using the GCXT and a time interval analyzer, revealing a measured time delay of 3.9 ± 2.1 μs for FXT-B.
Three-dimensional Reverse Time Migration for Detecting Tree Trunk Defects Using Ground Penetrating Radar
Authors: Liu Y , Feng D , Wang X
Published: November 2024

Due to environmental degradation and external intrusions, trees may develop various defects that diminish their stability and survival rates, leading to significant losses. Ground penetrating radar (GPR), characterized by its rapid and non-destructive advantages, has been regarded as a potentially effective method for assessing tree health conditions. However, existing GPR-based tree imaging techniques are predominantly two-dimensional (2D), making it difficult to diagnose three-dimensional (3D) structural features of defects. Therefore, this paper introduces, for the first time, 3D reverse time migration (RTM) into trunk defect detection. Compared to 2D RTM, 3D RTM can simultaneously back-propagate in-line and cross-line signals, accurately locate reflection waves, and focus diffracted waves, reconstructing the true interfaces and defect positions within the tree trunk. Experimental results on irregular trunk models containing a cavity demonstrate the feasibility of 3D RTM in trunk defect detection, providing specific and comprehensive guidance for formulating tree protection and restoration measures.
Preliminary results of the interior features inferred from radargrams, Ulanhada Volcano, Inner Mongolia, China
Authors: Dai S , Su Y , Ding C Y , Xue X P , Li C , Zhu X Y
Published: November 2024

The Ulanhada Volcano Group is located in Inner Mongolia, China. It is an important Quaternary volcanic geological relic with different types of volcanic cones, craters, lava platforms, and other structures. Ground penetrating radar (GPR) can play an important role in volcanic exploration. We used pulse EKKO radar combined with 100MHz and 250MHz antennas to detect the No.1 Redhill volcanic. The results indicate that there are significant differences in reflection characteristics in radargrams of different frequencies, which can be used to analyze the material composition, eruption period, and stratigraphic coverage relationship of volcanic eruptions. At the same time, an accurate analysis of the region will also be used as an evaluation basis for the field scientific verification experiments of China’s Asteroid Core Scan Radar (ACSR) and Lunar Penetrating Radar (LPR).
Construction of electric dyadic Green’s functions in free space based on elliptic cylindrical coordinate system
Authors: Luo Xiangdong
Published: November 2024

A set of vector wave functions is defined in the elliptic cylindrical coordinate system. These vector wave functions can not only describe the propagation characteristics of electromagnetic waves in the elliptic cylindrical coordinate system but also meet the requirements of the electromagnetic field equation. By studying the orthogonality of these vector wave functions, the free space magnetic dyadic Green function is derived by the Ohm-Rayleigh method. The free space electric dyadic Green function is derived from the magnetic dyadic Green function. The special electromagnetic field boundary value problem is transformed into a Green function problem by the electric dyadic Green function. The distribution of the electromagnetic field on the boundary can be obtained by solving the Green function, and then the characteristics of the electromagnetic field can be analyzed. The core of this method is to transform the electromagnetic field problem into a Green function problem, thus simplifying the solving process. This method enriches the electromagnetic field theory and provides a new way to solve the practical electromagnetic field problem.
Utilizing BIC for the intelligent selection of functional data with principal components
Authors: Yu Zhixuan , Chai Xiaolong
Published: November 2024

Functional Principal Component Analysis (FPCA) is a technique for dimension reduction of functional data. Considering the impact of different data ownership, the paper innovatively proposes a weighted B-spline basis function and provides a continuous curve fitting function. Then, smoothing processing is carried out through the basis function expansion method and the maximum penalized likelihood function method. Subsequently, the process of selecting the number of principal components based on the BIC criterion is elaborated. Parameter estimation is realized through the newly proposed BIC-FPCA optimization algorithm. In the empirical analysis section, the paper uses student performance data randomly generated by Python to demonstrate the application of FPCA in data reconstruction. The results show that although the reconstructed data is smoother, there is still room for improvement in the selection of principal components. Finally, the paper summarizes the research findings, suggesting that the BIC criterion be combined with the cumulative variance contribution rate to improve the method of principal component selection, and the algorithm be optimized to reduce computational load. With these improvements, the application effect of FPCA in functional data analysis can be further enhanced.
Space environment simulation and analyses for the DAMPE mission
Authors: Chang Liang , Jiang Hu
Published: November 2024

DAMPE was sent into space orbit for nearly nine years. Since its expected lifespan is only three years, DAMPE has surpassed its expected lifespan by almost six years. Due to its long stay in orbit, some of its components have met with such puzzles as the capabilities of the equipment are partially degrading. The effects of the space environment are responsible for some of its degradation. So, the knowledge of the space environment in the coming year is vital for DAMPE operation. We focus on the following factors: 1) electrons and protons trapped in Earth’s radiation belts; 2) solar proton effect; 3) cosmic ray effect; 4) atom oxygen distribution. Based on the powerful analytic software SPENVIS, some typical effects of space environments are simulated and analyzed respectively, providing supportive constraints when the task team of DAMPE decides when to lengthen the lifespan, or when to start the reentry to Earth’s atmosphere.
Research and application of heteroskedasticity diagnostic method of matrix factor modeling
Authors: Jin Qiaotong , Ma Weijun
Published: November 2024

Matrix-type time series data are widely used in the fields of finance, medical environment, etc. Matrix factor models can effectively downscale such data and reveal their underlying structures. Based on the popular matrix factor model, this paper proposes a diagnostic method for its heteroskedasticity and verifies the effectiveness of the method through numerical simulation. Finally, this paper applies the method to Fama-French portfolio data and finds heteroskedasticity, so that a matrix factor model based on heteroskedasticity can be considered for analyzing this data, thus improving the robustness of the analysis results.
Analysis of light pollution risk assessment level
Authors: Zhai Kunzhi , Zhao Jiahao , Shu Yujie , Zhang Yanyan , Tu Xiaoguang , Lu Jian
Published: November 2024

We develop a widely applicable metric to determine the level of light pollution risk at a site. In general, the appropriate comprehensive evaluation model entropy weight method is used to evaluate and further quantify the risk level of light pollution. We find some factors related to the level of light pollution to solve the data selection and list typical regions for data statistics, classify and pretreatment the obtained data, and then comprehensively analyze the data of influencing factors by entropy weight method to obtain a comprehensive evaluation value. The higher the value is, the higher the risk level of light pollution is. After obtaining the results, it is returned to the original data, taking the pollution risk level as the independent variable, observing the trend of the factors affecting the risk level of light pollution with the change of the degree of light pollution risk level, and analyzing the trend of the curve and find out certain rules. Combined with this law and the actual situation, the light pollution factors are analyzed logically. The direction of light pollution prevention and control can be determined according to the analysis results.
Light culling based on the limitations of human visual perception
Authors: Chen Huiwen , Chen Chunyi
Published: November 2024

We propose a method to remove virtual point light sources (VPLs) in the scene to reduce the time overhead of lighting calculation for shading points in non-visually sensitive areas. We quantify the degree of light stimulation to the human eye and use it to calculate the lighting contribution of VPLs in the scene to visually sensitive areas. Based on this contribution, we remove VPLs that contribute less to visually sensitive areas to improve rendering speed. Experimental results show that the FLIP evaluation index difference between this method and FLC [1] is only 0.00077, while the average number of frames is 1.15 times that of the method in FLC. This proves that this paper can effectively improve rendering speed.
Numerical simulation of high moisture well based on DPM model
Authors: Li Feifei , Liu Chengting , Wei Hongfei , Wang Luna
Published: November 2024

In view of the deposition of high water-cut sand grains in horizontal shaft, this study uses the DPM module in Fluent to track the sand movement trajectory, and the realizable k-e model analyzes the key influence of sand size and sedimentation velocity under the influence of gravity, Saffman lift and friction resistance. CFD simulation results show that the deposition rate of sand grains in the bore and the rate increases with the particle diameter. The results of this study provide a clear direction for the deposition of sand particles in the high water content period and point out that the velocity, viscosity, and particle diameter of the fluid in the shaft can be used as an effective method to eliminate the deposition of sand particles in the high water content period.
Multi-task-based detection and prediction of epileptic EEGs
Authors: Li Bing , Guo Yu , Ni Shuo
Published: November 2024

Epilepsy is a common neurological disorder. Electroencephalography (EEG) is a common method of diagnosing epilepsy. However, it requires long-term supervision by clinical experts to provide alerts. In this paper, we propose a multi-task based epilepsy detection and prediction network (LFMA-Net) for epilepsy detection and prediction, which consists of a lightweight spatiotemporal attention network (LSTAF-Net), a multiscale spatiotemporal attention network (LSTAM-Net), and an AITM. Both LSTAF-Net and LSTAM-Net introduce a spatial spatiotemporal attention module (STAM) and a Lightweight Residual Module (LRM) for feature extraction. Then the 2-second interictal and preictal time intervals were classified using the Shallow and Deep Feature Fusion (SDF) module and the Multiscale Spatio-Temporal Model (MSTM), respectively. Finally, the CHB-MIT dataset was used to test how well the method worked. It made predictions that were 99.25% accurate, 99.34% sensitive, and 99.11% specific. The results show that the multitask-based method suggested in this paper can successfully use EEG data for finding and predicting epilepsy. It can also be used as a model for finding and predicting seizures in the real world.
H∞ state estimation for discrete neural networks with random sensor delays under variance constraints
Authors: Du Yanbiao , Chen Cai , Gao Yan
Published: November 2024

This paper primarily investigates the H
∞ state estimation (SE) problem for discrete time-varying uncertain neural networks (NNs) with random occurring sensor delays (ROSDs) under variance constraints. The paper models ROSDs using a random variable that adheres to a Bernoulli distribution with a known probability. The primary purpose is to design a state estimator for time-varying NNs experiencing ROSDs, which proposes sufficient criteria for bounded error variance(EV) and H
∞ performance constraints. This paper introduces a new H
∞ SE algorithm for time-varying NNs with ROSDs, without the need for the augmentation method. In the end, the feasibility and effectiveness are validated through numerical simulation.
Adaptive finite-time command filtered position control for DP ship in level ice
Authors: Liu Caiyun , Shao Chunrui , Chen Xinghua , Liu Qian , Zheng Zhenming
Published: November 2024

This work suggests an adaptive limited-time command filtering control method for moving ships around in the Arctic. It does a good job of solving the thruster dynamics problem while taking into account uneven ice loads, model errors, and unknown changes in the environment. In the DP system, the neural network system is used to get close to the unclear function. A finite-time control law is meant to get the ship to the point and course that the captain wants by using estimates. Lyapunov analysis showed that the closed-loop system as a whole is stable, which means that all signals are still limited in time. Number-based simulations have shown that the suggested control strategy works.