bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment and Prediction of Carbon Storage Based on Land Use/Land Cover Dynamics in the Gonghe Basin
Authors: Jia Hong , Yang Siqi , Liu Lianyou , Li Hang , Li Zeshi , Chen Yixin , Liu Jifu
Published: December 2024

Land use pattern is a dominant factor causing carbon storage changes in terrestrial ecosystems and is crucial for maintaining the stability of carbon storage. Understanding the impact of land use on carbon storage variations in drylands is of great significance for local ecological protection and the sustainable management of land resources. Based on the land use data of the Gonghe Basin from 1990 to 2020, the InVEST model was applied to analyze the spatiotemporal changes in carbon storage, and the PLUS model was used to predict the changes in carbon storage under three different development scenarios in 2030. The results are as follows: (1) From 1990 to 2020, the main land use types in the Gonghe Basin were grassland and unused land, with an overall increase in grassland and a marked decrease in unused land. (2) The spatial distribution of carbon storage was generally characterized by being low in the center and high at the edge, and grassland was the most important land use type with the highest carbon storage. Over the past 30 years, it has shown an increase followed by a decline, with an overall increase of 1.84%. (3) The carbon storage under the natural trend, urban development, and ecological protection scenarios will be 158.80 × 106 Mg, 158.66 × 106 Mg, and 159.83 × 106 Mg in 2030, respectively. The grassland and cropland areas were larger under the ecological protection scenario, which was more conducive to improving the carbon storage in this region. This study provides an effective reference for optimizing land use and achieving carbon neutrality (“dual carbon” goals) in drylands.
Progressive Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) from a Young Age Due to a Rare Genetic Disorder, Familial Partial Lipodystrophy: A Case Report and Review of the Literature
Authors: Vorona Elena , Sorkina Ekaterina , Trebicka Jonel
Published: December 2024

Steatotic liver disease is common in the general population and is associated with higher risk for cardiovascular diseases. Early diagnosis and appropriate therapy can prevent the development of irreversible end-stage liver fibrosis and reduce liver-related and cardiovascular mortality. It is important to recognise not only the common causes of metabolic dysfunction-associated steatotic liver disease, such as type 2 diabetes mellitus or morbid obesity, but also rare conditions, because their treatment is different from conventional therapy. Here, we report a female patient with familial partial lipodystrophy, in whom the diagnosis was not confirmed until several years after the initial manifestation, which delayed the start of pathogenetic therapy. After the initiation of leptin replacement therapy, a significant improvement in liver stiffness measurement was achieved within a few months. In addition, we summarise the current treatment options for diabetes and their influence on steatosis hepatis.
A Rate-Dependent Probabilistic Model of Hysteresis
Authors: Cross Rod , Grinfeld Michael , Lamba Harbir
Published: December 2024

Instead of modelling an economic agent by a hysteron, we suggest a fluid–mechanical notion of rate-dependent hysteretic agents based on the theory of Poisson counters. It leads to a simple representation of assemblies of such agents. We discuss the properties of the new version of hysteresis and its advantages over classical models of hysteresis in economics.
An Improved Constrained Multiobjective Optimization for Energy Multimodal Transport Among Clustering Islands
Authors: Yang Xu , Zhang Fuxing , Miao Honglei
Published: December 2024

Clustering islands located close to each other and sharing some common characteristics offer diverse and unique opportunities for tourism, trade, and research, and especially take a crucial part in the military. Remote from inland, islands have relatively limited resources, which makes them dependent on imported energy sources such as oil and gas or renewable energy. However, there are few studies about the energy security of clustering islands. To this end, this study proposes a novel energy optimization framework that aims to optimize the use of their different types of energy among clustering islands and improve the stability of the whole energy internet via a multilayer transportation network. The transportation network also enables islands to serve as emergency power sources for each other in some emergency situations. Specifically, we construct an assignment model that considers multimodal transport, multiobjective, and multiple constraints. To address this issue, we develop an unconstrained-individuals guiding constrained multiobjective optimization algorithm, named uiCMOA. Experimental results demonstrate the effectiveness of the transportation network and the efficiency of the proposed algorithm.
A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting
Authors: Liu Jing , He Qingling , Yue Zhikun , Pei Yulong
Published: December 2024

To address the issues of slow convergence and large errors in existing metaheuristic algorithms when optimizing neural network-based subway passenger flow prediction, we propose the following improvements. First, we replace the random initialization method of the population in the SSA with Circle mapping to enhance its diversity and quality. Second, we introduce a hybrid mechanism combining dimensional small-hole imaging backward learning and Cauchy mutation, which improves the diversity of the individual sparrow selection of optimal positions and helps overcome the algorithm’s tendency to become trapped in local optima and premature convergence. Finally, we enhance the individual sparrow position update process by integrating a cosine strategy with an inertia weight adjustment, which improves the algorithm’s global search ability, effectively balancing global search and local exploitation, and reducing the risk of local optima and insufficient convergence precision. Based on the analysis of the correlation between different types of subway station passenger flows and weather factors, the ISSA is used to optimize the hyperparameters of the CNN-LSTM model to construct a subway passenger flow prediction model based on ISSA-CNN-LSTM. Simulation experiments were conducted using card swipe data from Harbin Metro Line 1. The results show that the ISSA provides a more accurate optimization with the average values and standard deviations of the 12 benchmark test function simulations being closer to the optimal values. The ISSA-CNN-LSTM model outperforms the SSA-CNN-LSTM, PSO-ELMAN, GA-BP, CNN-LSTM, and LSTM models in terms of error evaluation metrics such as MAE, RMSE, and MAPE, with improvements ranging from 189.8% to 374.6%, 190.9% to 389.5%, and 3.3% to 6.7%, respectively. Moreover, the ISSA-CNN-LSTM model exhibits the smallest variation in prediction errors across different types of subway stations. The ISSA demonstrates superior parameter optimization accuracy and convergence speed compared to the SSA. The ISSA-CNN-LSTM model is suitable for the precise prediction of passenger flow at different types of subway stations, providing theoretical and data support for subway station passenger density and trend forecasting, passenger organization and management, risk emergency response, and the improvement of service quality and operational safety.
The Random Effect Transformation for Three Regularity Classes
Authors: Šiaulys Jonas , Lewkiewicz Sylwia , Leipus Remigijus
Published: December 2024

We continue the analysis of the influence of the random effect transformation on the regularity of distribution functions. The paper considers three regularity classes: heavy-tailed distributions, distributions with consistently varying tails, and exponential-like-tailed distributions. We apply the random effect transformation to the primary distribution functions from these classes and investigate whether the resulting distribution function remains in the same class. We find that the random effect transformation has the greatest impact on exponential-like-tailed distributions. We establish that any heavy-tailed distribution subjected to a random effect transformation remains heavy-tailed, and any distribution with a consistently varying tail remains with a consistently varying tail after the random effect transformation. Meanwhile, different cases are possible when an exponential-like-tailed class of distributions is subjected to a random effect transformation. Sometimes, depending on the structure of a random effect, the resulting distribution remains exponential-like-tailed, and sometimes that distribution regularly varies. All of the derived theoretical results are illustrated with several examples.
Two-Step Surgical Strategy for Parathyroid Carcinoma: A Single-Center Experience
Authors: Longo Filippo , Sarubbi Antonio , Palladino Claudia , Palermo Andrea , Naciu Anda Mihaela , Crescenzi Anna , Taffon Chiara , Tabacco Gaia , Frasca Luca , Crucitti Pierfilippo
Published: December 2024

Parathyroid carcinoma (PC) is a rare endocrine malignancy that poses significant diagnostic challenges due to its resemblance to benign conditions. This case series describes the clinical presentation, diagnosis, management, and short-term outcomes of four male patients (aged 54, 65, 73, and 74 years) with primary hyperparathyroidism and hypercalcemia. The preoperative diagnosis of PC remains challenging; suspicion should arise in cases of severe hypercalcemia, elevated parathyroid hormone levels, and the presence of a mass on imaging or during surgery. All patients underwent an initial localized parathyroidectomy, with PC confirmed postoperatively. Subsequently, they received ipsilateral hemithyroidectomy and prophylactic central lymph node dissection. Over a two-year follow-up period, all patients maintained normocalcemia without evidence of disease recurrence or metastasis. In conclusion, whether to perform a complete en bloc resection or a two-step surgical strategy remains a difficult decision in PC patients with intricate preoperative evaluations.
Laser Cladding Performance and Process Parameter Optimization for Fe90 Alloy
Authors: Cao Yang , Yuan Chenye , Zhang Yanchao , Ma Jun
Published: December 2024

Fe90 alloy has a high weld hardness, good toughness, and high oxidation resistance, and is often used as a cladding material to repair the surfaces of 42CrMo steel structures of large shearer picks. The influence of the laser cladding processing parameters on the microstructure, properties, and formation mechanism of Fe90 alloy layers on the surface of 42CrMo steel was studied. Simulations were conducted to investigate how these processing parameters affect the temperature field and internal stress of the cladding layer. A complex nonlinear relationship between variables and residual stresses in the laser cladding layers obtained by additive manufacturing was fitted. An optimization model for residual stress in the cladding layer was established and an improved genetic algorithm was used for optimization, which resulted in a 15.88% reduction in residual stress. The results show that optimizing the processing parameters increased the amount of Ni-Cr-Fe solid solution in the cladding layer, enhancing its strength and corrosion resistance. The amount of residual stresses rose with increases in laser power, but at higher powers, increasing the scanning speed and spot diameter reduced stresses. At lower powers, the amount of residual stresses initially increased and then decreased with the scanning speed, with more significant changes occurring with larger spot diameters. Analyzing temperature and residual stress changes allowed us to improve the cladding layer quality, providing a theoretical basis for laser cladding on 42CrMo.
Metagenomic Analysis Revealing the Impact of Water Contents on the Composition of Soil Microbial Communities and the Distribution of Major Ecological Functional Genes in Poyang Lake Wetland Soil
Authors: Long Yuxin , Zhang Xiaomei , Peng Xuan , Yang Huilin , Ni Haiyan , Zou Long , Long Zhong’er
Published: December 2024

Poyang Lake is the largest freshwater lake in China, which boasts unique hydrological conditions and rich biodiversity. In this study, metagenomics technology was used to sequence the microbial genome of soil samples S1 (sedimentary), S2 (semi-submerged), and S3 (arid) with different water content from the Poyang Lake wetland; the results indicate that the three samples have different physicochemical characteristics and their microbial community structure and functional gene distribution are also different, resulting in separate ecological functions. The abundance of typical ANME archaea Candidatus Menthanoperedens and the high abundance of mcrA in S1 mutually demonstrate prominent roles in the methane anaerobic oxidation pathway during the methane cycle. In S2, the advantageous bacterial genus Nitrospira with ammonia oxidation function is validated by a large number of nitrification functional genes (amoA, hao, nxrA), manifesting in that it plays a monumental role in nitrification in the nitrogen cycle. In S3, the dominant bacterial genus Nocardioides confirms a multitude of antibiotic resistance genes, indicating their crucial role in resistance and their emphatic research value for microbial resistance issues. The results above have preliminarily proved the role of soil microbial communities as indicators predicting wetland ecological functions, which will help to better develop plans for restoring ecological balance and addressing climate change.
Impact of Biochar Addition on Biofloc Nitrifying Bacteria and Inorganic Nitrogen Dynamics in an Intensive Aquaculture System of Shrimp
Authors: Xu Wujie , Zhang Demin , Su Haochang , Xu Yu , Hu Xiaojuan , Wen Guoliang , Cao Yucheng
Published: December 2024

In this study, an eight-week culture trial of Penaeus vannamei juveniles was conducted in commercial intensive systems to compare the impacts of biochar and molasses addition on biofloc nitrifying bacteria and inorganic nitrogen dynamics under limited water exchange conditions. During the trial, the biofloc concentration (in terms of VSS and TSS), quantities of total bacteria (TB) and total Vibrio (TV), and ratio of TV/TB in the culture water were lower in the biochar group compared to the molasses group. Metagenomic sequencing analysis revealed that the bacterial community composition of bioflocs showed higher α-diversity and complexity in the biochar group compared to the molasses group. Moreover, the abundance of nitrifying bacterial genera and functional genes in bioflocs was higher in the biochar group compared to the molasses group. Inorganic nitrogen dynamics showed that NH4+-N and NO2−-N were better controlled in the biochar group compared to the molasses group, as reflected by lower peaks of NH4+-N and NO2−-N and higher NO3−-N concentrations. Excellent production performance of shrimp was achieved, which in turn proved the reliable effect of biochar addition on the mediation of inorganic nitrogen transformation through nitrifying bacteria. These results showed that biochar addition could promote biofloc nitrifying bacteria and nitrification to more effectively control harmful nitrogen for shrimp efficient production. This study provides a practical example for the biochar application in biofloc-based systems for intensive aquaculture.
Planted Citrus Regulates the Community and Networks of phoD-Harboring Bacteria to Drive Phosphorus Availability Between Karst and Non-Karst Soils
Authors: Yu Xuan , Feng Lulu , Huang Yuan , Liang Yueming , Pan Fujing , Zhang Wei , Zhao Yuan , Xiao Yuexin
Published: December 2024

The phosphorus (P) availability in soils is influenced by microbes, particularly those containing the gene responsible for phosphate solubilization. The present study investigated the community structure, diversity, and co-occurrence networks of phoD-harboring bacteria in karst and non-karst citrus orchard soils across a planting duration gradient, natural forests, and abandoned land, as well as the soil total P (TP) and available P (AP) contents and enzyme activities. The soil AP contents were lower in the karst regions than in the non-karst regions, while the soil organic carbon (C; SOC), exchangeable calcium, and microbial biomass nitrogen (N) contents; alkaline phosphatase (ALP) and β-Glucuronidase activities; and pH had the opposite trends. In addition, the soil AP and SOC contents and the ALP and acid phosphatase (ACP) activities in the karst regions decreased with an increase in the planting years, whereas the AP, TP, and microbial biomass P contents and ACP activities in the non-karst regions increased. The diversity indices and network complexity of phoD-harboring bacteria were higher in the karst regions than in the non-karst regions, with marked community differences between different planting years in the non-karst regions. The soil AP was significantly and positively correlated with the rare genera Pelagicola, Methylobacter, Streptomyces, and Micromonospora in the karst regions and Roseivivax, Collimonas, Methylobacterium, Ralstonia, and Phyllobacterium in the non-karst regions. Structural Equation Modeling showed that citrus cultivation altered the soil pH, SOC, and total N, and, in turn, the phoD-harboring bacterial community structure and diversity, which led to changes in the ALP activity and P availability. Thus, the rare genera of the phoD-harboring bacteria, influenced by the pH and SOC, highly regulated the availability of P in the karst and non-karst citrus orchard soils.
Clinical and In Vitro Safety of Heyndrickxia coagulans AO 1167B: A Double-Blind, Placebo-Controlled Trial
Authors: García Gissel , Soto Josanne , Díaz Antonio , Barreto Jesús , Soto Carmen , Pérez Ana Beatriz , Boffill Suselys , Gutiérrez Ángela , Cano Raúl de Jesús
Published: December 2024

(1) Background: Heyndrickxia coagulans, a lactic acid-producing bacterium, displays characteristics of both Lactobacillus and Bacillus genera. Clinical evidence suggests its potential health benefits. This study evaluated the safety of H. coagulans AO1167B as a candidate probiotic supplement. (2) Methods: Strain identification was confirmed through morphological, cultural, and genomic analyses, including 16S RNA and whole genome sequencing to assess antimicrobial resistance and virulence factors. Phenotypic tests, such as disk diffusion for antimicrobial resistance, and safety assays for cytotoxicity and hemolytic activity, were conducted. In a phase I, double-blind, placebo-controlled clinical trial, healthy adults were randomized into H. coagulans AO1167B and placebo groups for 60 days. Daily capsule consumption was monitored through clinical and hematological evaluations, adverse event tracking, and health surveys. (3) Results: The genome of H. coagulans AO1167B revealed no concerning features. Disk diffusion tests showed no antimicrobial resistance. The strain exhibited no cytotoxic or hemolytic activity, indicating in vitro safety. No significant differences in clinical or hematological parameters were observed between groups. The most common adverse event, gas, diminished over time. (4) Conclusions: H. coagulans AO1167B demonstrates a suitable safety profile, genetic stability, and probiotic potential for gastrointestinal health, justifying further clinical research.
Investigation on the Coordination Bonding Nature of Actinide-Doped Endohedral Borospherenes An@B400/+/− (An = U, Np, Pu, Am, Cm)
Authors: Zhao Xiao-Ni , Wei Zhi-Hong , Li Si-Dian
Published: December 2024

Endohedral metallo-borospherenes M@B40 have received considerable attention since the discovery of B40 in 2014. However, the coordination bonding nature of most of actinide-doped endohedral An@B40 still remains in dispute or unexplored. Extensive and systematic first-principles theory calculations performed herein unveil the ground states of triplet U@B40 (1, C2v, 3A2), quartet U@B40− (2, C2v, 4B1), quintet Np@B40+ (3, C2v, 5A1), sextet Np@B40 (4, C2, 6A), septet Pu@B40 (5, C2v, 7A2), octet Am@B40 (6, C2v, 8A2), and octet Cm@B40+ (7, C2v, 8A2) at the coupled-cluster with triple excitations CCSD(T) level. Detailed principal interacting spin orbital (PISO) and adaptive natural density partitioning (AdNDP) analyses reveal their coordination bonding patterns and show that, with the numbers of unpaired α-electrons in parallel spins varying from nα = 2, 3, 4, 5, 6, 7, to 7 in these complexes, the percentage contribution of the An 5f-involved PISO pairs to overall coordination bonding interactions decreases monotonously from 41% to 1%, and the contribution of An 6d-involved PISO pairs increases monotonously from 47% to 72%, while the marginal contribution of An 7s-involved PISO pairs remains basically unchanged (4~7%). The IR, Raman, and photoelectron spectra of the most concerned species are computationally simulated to facilitate their characterizations in future experiments.
A Liquid Metal Balloon for the Exfoliation of an Ultrathin and Uniform Gallium Oxide Layer
Authors: Zhexembekova Anar , Lim Seongyeop , Lee Cheongha , Kim Yun-Tae , Lee Chang Young
Published: December 2024

We report the exfoliation of ultrathin gallium oxide (Ga2O3) films from liquid metal balloons, formed by injecting air into droplets of eutectic gallium–indium alloy (eGaIn). These Ga2O3 films enable the selective adsorption of carbon nanotubes (CNTs) dispersed in water, resulting in the formation of a dense, percolating CNT network on their surface. The self-assembled CNT network on Ga2O3 provides a versatile platform for device fabrication. As an example application, we fabricated a chemiresistive gas sensor for detecting simulants of chemical warfare agents (CWAs), including diisopropyl methylphosphonate (DIMP), dimethyl methylphosphonate (DMMP), and triethyl phosphate (TEP). The sensor exhibited reversible responses, high sensitivity, and low limits of detection (13 ppb for DIMP, 28 ppb for DMMP, and 53 ppb for TEP). These findings highlight the potential of Ga2O3 films derived from liquid metal balloons for integrating CNTs into functional electronic devices.
Mapping Thrombosis Serum Markers by 1H-NMR Allied with Machine Learning Tools
Authors: Martins Lucas G. , Manzini Bruna M. , Montalvão Silmara , Honorato Millene A. , Colella Marina P. , Hayakawa Gabriela G. Y. , de Paula Erich V. , Orsi Fernanda A. , Braga Erik S. , Avramović Nataša , Omage Folurunsho Bright , Tasic Ljubica , Annichino-Bizzacchi Joyce M.
Published: December 2024

Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). 1H-NMR-based metabonomics data of the serum samples of patients with arterial or venous thromboembolism (VTE) without APS (n = 32), thrombotic primary APS patients (APS, n = 32), and healthy controls (HCs) (n = 32) were investigated. Unique metabolic profiles between VTE and HCs, APS and HCs, and between VTE and triple-positive APS groups were indicative of the significant alterations in the metabolic pathways of glycolysis, the TCA cycle, lipid metabolism, and branched-chain amino acid (BCAA) metabolism, and pointed to the complex pathogenesis mechanisms of APS and VTE. Histidine, 3-hydroxybutyrate, and threonine were shown to be the top three metabolites with the most substantial impact on model predictions, suggesting that these metabolites play a pivotal role in distinguishing among APS, VTE, and HCs. These metabolites might be potential biomarkers to differentiate APS and VTE patients.
The Impact of Laser Irradiation on Thin ZrN Films Deposited by Pulsed DC Magnetron Sputtering
Authors: Nazneen Ameena , Lei Penghui , Yun Di
Published: December 2024

Transition metal nitrides have extensive applications, including magnetic storage devices, hardware resistance coatings, and low-temperature fuel cells. This study investigated the structural, electrical, and mechanical properties of thin zirconium nitride (ZrN) films by examining the effects of laser irradiation times. Thin ZrN films were deposited on glass substrates using pulsed DC magnetron sputtering and irradiated with a diode laser for 6 and 10 min. Characterization was performed using X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HRTEM), nanoindentation, and four-point probe techniques. Extended laser irradiation times resulted in increased numbers of peaks on XRD analysis, indicating enhanced crystalline behavior of thin ZrN film. SEM analysis revealed surface voids, while HRTEM showed nanostructured ZrN with uniform plane orientation. The electrical properties of the thin ZrN film improved with extended laser irradiation, as demonstrated by a reduction in sheet resistance from 0.43 × 109 Ω to 0.04 × 109 Ω. Additionally, nanoindentation tests revealed an increase in hardness, rising from 8.91 GPa to 9.36 GPa.
Folic Acid-Targeted Mixed Pluronic Micelles for Delivery of Triptolide
Authors: Yin Meizhen , Zhang Xinying , Zhang Tongguang , Bao Zhiqiang , He Zhihui
Published: December 2024

The present study aimed to explore an ideal delivery system for triptolide (TPL) by utilizing the thin-film hydration method to prepare drug-loaded, folate-modified mixed pluronic micelles (FA–F-127/F-68–TPL). Scanning electron microscopy and atomic force microscopy showed that the drug-loaded micelles had a spherical shape with a small particle size, with an average of 30.7 nm. Cell viability experiments showed that FA–F-127/F-68–TPL significantly reduced HepG2 cell viability, exhibiting strong cytotoxicity. Its cytotoxicity was markedly enhanced compared with bare TPL. Nile red (Nr) was used as a model drug to prepare FA–F-127/F-68–Nr to further validate its tumor-targeting and cellular uptake capability. After coincubation with HepG2 cells, a multifunctional microplate reader showed that intracellular fluorescence intensity significantly increased, indicating that FA–F-127/F-68–Nr could more effectively enter the cells. A nude mouse model of subcutaneous hepatocellular carcinoma was constructed. Following tail vein injection of FA–F-127/F-68–Nr, the fluorescence imaging system showed that FA–F127/F-68–Nr could significantly target tumor tissue, and even if entering the small-sized tumor was challenging, it could be excreted through urine. Nude mice with subcutaneous hepatocellular carcinoma were treated with tail vein injections of FA–F-127/F-68–TPL (45 µg/kg) every other day for 21 days. The results showed that the growth of the transplanted tumors was significantly slowed, with no significant difference compared with bare TPL. In summary, the FA–F-127/F-68–TPL exhibits the advantages of low cost, excellent biological properties, active/passive targeting capabilities, notable cytotoxicity against liver cancer cells, and significant inhibition of transplanted hepatocellular carcinoma growth. Significantly, the FA–F-127/F-68–TPL, despite challenges in targeting tumors with an insignificant EPR effect, can be efficiently excreted via the kidneys, thereby preventing the release of the drug during prolonged circulation and potential damage to normal tissues. Therefore, FA–F-127/F-68–TPL represents a promising antitumor drug delivery system.
BetaSigmaSlurryFoam: An Open Source Code for the Numerical Simulation of Pseudo-Homogeneous Slurry Flow in Pipes
Authors: Yang Qi , Messa Gianandrea Vittorio
Published: December 2024

In this study, we present, test, and make available to the scientific community the betaSigmaSlurryFoam solver, which is a two-phase model based on the Eulerian-Eulerian approach for the simulation of turbulent slurry transport in piping systems. Specifically, betaSigmaSlurryFoam is a fully open source implementation, within the OpenFOAM platform, of the existing β-σ two-fluid model, developed over a decade by researchers at Politecnico di Milano, which, as certified by scientific publications, proved an effective way to simulate the pipe flow of fine particle slurries in the pseudo-homogeneous regime. In this paper, we first provide the mathematical and coding details of betaSigmaSlurryFoam. Afterwards, we verify the new solver by comparison with the earlier β-σ two-fluid model for the case of slurry transport in a horizontal pipe, demonstrating not only that the two solutions are very close to each other, but also that the effects of the two calibration coefficients β and σ are the same for the two implementations. Finally, we apply betaSigmaSlurryFoam to the more complex case of slurry transport in a horizontal pipe elbow, which has never been subject to investigation using the earlier β-σ two-fluid model. We prove that the solution of betaSigmaSlurryFoam is physically consistent, and, after assessing the impact of β and σ through an extensive sensitivity analysis, we show that reasonably good agreement could be achieved against experimental data reported in the literature even for slightly different particle sizes than those considered in our previous research. The sharing of betaSigmaSlurryFoam as open source code promotes its further development by fostering collaboration between research groups worldwide.
Application of Time-Weighted PageRank Method with Citation Intensity for Assessing the Recent Publication Productivity and Partners Selection in R&D Collaboration
Authors: Biloshchytskyi Andrii , Kuchanskyi Oleksandr , Mukhatayev Aidos , Andrashko Yurii , Toxanov Sapar , Faizullin Adil , Kassenov Khanat
Published: December 2024

This article considers the problem of assessing the recent publication productivity of scientists based on PageRank class methods and proposes to use these assessments to solve the problem of selecting scientific partners for R&D projects. The methods of PageRank, Time-Weighted PageRank, and the Time-Weighted PageRank method with Citation Intensity (TWPR-CI) were used as a basis for calculating the publication productivity of individual subjects or scientists. For verification, we used the Citation Network Dataset (Ver. 14) of more than 5 million STEM publications with 36 million citations. The dataset is based on data from ACM, DBLP, and Microsoft Academic Graph databases. Only those individual subjects who published at least two articles after 2000, with at least one of these articles cited at least once before 2023 year, were analyzed. Thus, the number of individual subjects was reduced to 1,042,122, and the number of scientific publications was reduced to 2,422,326. For each of the methods, a range of estimates of productivity is indicated, which are obtained as a result and possible options for making decisions on the selection of potential individual subjects as performers of R&D projects. One of the key advantages of the TWPR-CI method is that it gives priority to those researchers who have recently published and been cited frequently in their respective research areas. This ensures that the best potential R&D project executors are selected, which should minimize the impact of subjective factors on this choice. We believe that the proposed concept for selecting potential R&D project partners could help to reduce the risks associated with these projects and facilitate the involvement of the most suitable specialists in the relevant area of knowledge.
The Universal and the Particular in Christian Political Life: Secular and Sacred Reflections on Christian Nationalism
Authors: Innes David C.
Published: December 2024

Being human in a world that is both physical and metaphysical confronts us with legitimate though competing obligations that pull us between particular and universal goods. This is superlatively true for Christians, as they live consciously and conscientiously in two kingdoms, one earthy and the other heavenly, serving a divine king and, under him, also an earthly one. The kingdom of God directs our sights to the universal relationship in Christ while leaving us separately embodied in particular families and communities—the one does not supplant these others—which both require and merit devotion and self-sacrifice. This tension between love of one’s own and the uniquely Christian universal love can be seen in the currently employed and contentiously scrutinized term Christian nationalism. Though seemingly an oxymoron, it recognizes and makes sense of the necessary coincidence of our inescapable particularity with our participation in and dependence on larger realities.
Design and Evaluation of Augmented Reality-Enhanced Robotic System for Epidural Interventions
Authors: Sayadi Amir , Cecere Renzo , Barralet Jake , Feldman Liane S. , Hooshiar Amir
Published: December 2024

The epidural injection is a medical intervention to inject therapeutics directly into the vicinity of the spinal cord for pain management. Because of its proximity to the spinal cord, imprecise insertion of the needle may result in irreversible damage to the nerves or spinal cord. This study explores enhancing procedural accuracy by integrating a telerobotic system and augmented reality (AR) assistance. Tele-kinesthesia is achieved using a leader–follower integrated system, and stable force feedback is provided using a novel impedance-matching force rendering approach. In this domain, augmented reality employs a magnetic-tracker-based approach for real-time 3D model projection onto the patient’s body, aiming to augment the physician’s visual field and improve needle insertion accuracy. Preliminary results indicate that our AR-enhanced robotic system may reduce the cognitive load and improve the accuracy of ENI, highlighting the promise of AR technologies in complex medical procedures. However, further studies with larger sample sizes and more diverse clinical settings must comprehensively validate these findings. This work lays the groundwork for future research into integrating AR into medical robotics, potentially transforming clinical practices by enhancing procedural safety and efficiency.
A 6.7 μW Low-Noise, Compact PLL with an Input MEMS-Based Reference Oscillator Featuring a High-Resolution Dead/Blind Zone-Free PFD
Authors: Kira Ahmed , Elsayed Mohannad Y. , Allidina Karim , Chodavarapu Vamsy P. , El-Gamal Mourad N.
Published: December 2024

This article reports a 110.2 MHz ultra-low-power phase-locked loop (PLL) for MEMS timing/frequency reference oscillator applications. It utilizes a 6.89 MHz MEMS-based oscillator as an input reference. An ultra-low-power, high-resolution phase-frequency detector (PFD) is utilized to achieve low-noise performance. Eliminating the reset feedback path used in conventional PFDs leads to dead/blind zone-free phase characteristics, which are crucial for low-noise applications within a wide operating frequency range. The PFD operates up to 2.5 GHz and achieves a linear resolution of 100 ps input time difference (Δtin), without the need for any additional calibration circuits. The linearity of the proposed PFD is tested over a phase difference corresponding to aa Δtin ranging from 100 ps to 50 ns. At a 1 V supply voltage, it shows an error of <±1.6% with a resolution of 100 ps and a frequency-normalized power consumption (Pn) of 0.106 pW/Hz. The PLL is designed and fabricated using a TSMC 65 nm CMOS process instrument and interfaced with the MEMS-based oscillator. The system reports phase noises of −106.21 dBc/Hz and −135.36 dBc/Hz at 1 kHz and 1 MHz offsets, respectively. It consumes 6.709 μW at a 1 V supply and occupies an active CMOS area of 0.1095 mm2.
Selective Detection of Formaldehyde and Nitrogen Dioxide Using Innovative Modeling of SnO2 Surface Response to Pulsed Temperature Profile
Authors: Bialic Emilie , Leblet Jimmy , Sendi Aymen , Gersberg Paul , Maupoux Axel , Lassabe Nicolas , Menini Philippe
Published: December 2024

The need for odor measurement and pollution source identification in various sectors (aeronautic, automobile, healthcare…) has increased in the last decade. Multisensor modules, such as electronic noses, seem to be a promising and inexpensive alternative to traditional sensors that were only sensitive to one gas at a time. However, the selectivity, the non-repetitiveness of their manufacture, and their drift remain major obstacles to the use of electronic noses. In this first work, we show how the mathematical modeling of the sensor response can be used to find new selectivity characteristics, different from those classically used in the literature. We identified new specific characteristics that have no physical meaning that can be used to find criteria for the presence of formaldehyde and nitrogen dioxyde alone or in a mixture. We discuss the limitations of the methodology presented and suggest avenues for improvement, with more precise modeling techniques involving symbolic regression.
Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management
Authors: Cruz Castañeda William Alberto , Bertemes Filho Pedro
Published: December 2024

One of the health challenges in the 21st century is to rethink approaches to non-communicable disease prevention. A solution is a smart city that implements technology to make health smarter, enables healthcare access, and contributes to all residents’ overall well-being. Thus, this paper proposes an architecture to deliver smart health. The architecture is anchored in the Internet of Things and edge computing, and it is driven by artificial intelligence to establish three foundational layers in smart care. Experimental results in a case study on glucose prediction noninvasively show that the architecture senses and acquires data that capture relevant characteristics. The study also establishes a baseline of twelve regression algorithms to assess the non-invasive glucose prediction performance regarding the mean squared error, root mean squared error, and r-squared score, and the catboost regressor outperforms the other models with 218.91 and 782.30 in MSE, 14.80 and 27.97 in RMSE, and 0.81 and 0.31 in R2, respectively, on training and test sets. Future research works involve extending the performance of the algorithms with new datasets, creating and optimizing embedded AI models, deploying edge-IoT with embedded AI for wearable devices, implementing an autonomous AI cloud engine, and implementing federated learning to deliver scalable smart health in a smart city context.
Age of Information Analysis for Multi-Priority Queue and Non-Orthoganal Multiple Access (NOMA)-Enabled Cellular Vehicle-to-Everything in Internet of Vehicles
Authors: Zhang Zheng , Wu Qiong , Fan Pingyi , Fan Qiang
Published: December 2024

With the development of Internet of Vehicles (IoV) technology, the need for real-time data processing and communication in vehicles is increasing. Traditional request-based methods face challenges in terms of latency and bandwidth limitations. Mode 4 in cellular vehicle-to-everything (C-V2X), also known as autonomous resource selection, aims to address latency and overhead issues by dynamically selecting communication resources based on real-time conditions. However, semi-persistent scheduling (SPS), which relies on distributed sensing, may lead to a high number of collisions due to the lack of centralized coordination in resource allocation. On the other hand, non-orthogonal multiple access (NOMA) can alleviate the problem of reduced packet reception probability due to collisions. Age of Information (AoI) includes the time a message spends in both local waiting and transmission processes and thus is a comprehensive metric for reliability and latency performance. To address these issues, in C-V2X, the waiting process can be extended to the queuing process, influenced by packet generation rate and resource reservation interval (RRI), while the transmission process is mainly affected by transmission delay and success rate. In fact, a smaller selection window (SW) limits the number of available resources for vehicles, resulting in higher collisions when the number of vehicles is increasing rapidly. SW is generally equal to RRI, which not only affects the AoI part in the queuing process but also the AoI part in the transmission process. Therefore, this paper proposes an AoI estimation method based on multi-priority data type queues and considers the influence of NOMA on the AoI generated in both processes in C-V2X system under different RRI conditions. Our experiments show that using multiple priority queues can reduce the AoI of urgent messages in the queue, thereby providing better service about the urgent message in the whole vehicular network. Additionally, applying NOMA can further reduce the AoI of the messages received by the vehicle.
Machine Learning Techniques for Sensor-Based Human Activity Recognition with Data Heterogeneity—A Review
Authors: Ye Xiaozhou , Sakurai Kouichi , Nair Nirmal-Kumar C. , Wang Kevin I-Kai
Published: December 2024

Sensor-based Human Activity Recognition (HAR) is crucial in ubiquitous computing, analyzing behaviors through multi-dimensional observations. Despite research progress, HAR confronts challenges, particularly in data distribution assumptions. Most studies assume uniform data distributions across datasets, contrasting with the varied nature of practical sensor data in human activities. Addressing data heterogeneity issues can improve performance, reduce computational costs, and aid in developing personalized, adaptive models with fewer annotated data. This review investigates how machine learning addresses data heterogeneity in HAR by categorizing data heterogeneity types, applying corresponding suitable machine learning methods, summarizing available datasets, and discussing future challenges.
Development of Test Cases for Automated Vehicle Driving Safety Assessment Using Driving Trajectories
Authors: Ko Woori , Shim Minkyu , Park Sangmin , Lee Soomok , Yun Ilsoo
Published: December 2024

For consumers to have confidence in the safety of automated vehicles (AVs), AVs must be assessed using systematically developed scenarios to verify driving safety and reliability. In particular, verification using scenarios has been widely performed for the assessment and certification of AVs. This study aims to develop test cases based on driving trajectories to assess the driving safety of AVs. To achieve this, concrete scenarios were systematically developed from functional and logical scenarios. Drone video data analysis was conducted to extract representative lane-change trajectories for AVs on expressway ramp sections. Subsequently, the test cases were selected from concrete scenarios through simulations using time-to-steer (TTS). Finally, the effectiveness of utilizing trajectories for scenario-based driving safety assessments was verified. Furthermore, it is expected that this approach can be applied to other driving patterns by providing a detailed procedure for the test case developed in this study.
Structured Representation of Pre-Defined Information Backflow in Standards and Directives
Authors: Layer Max , Luttmer Janosch , Nagarajah Arun , Stelzer Ralph
Published: December 2024

This publication examines the representation of information within test specifications and formulas defined in standards and directives. This information often pre-defines not only the tests and requirements to be conducted but also the information backflow within the execution. These results are crucial for the effective management of knowledge throughout the product development process as well as for the creation and maintenance of digital representations of a physical product or plant. However, the accessibility of this information is frequently hindered by its extensive and heterogenous definition across a multitude of standards, directives, and other technical regulations. Furthermore, the pre-defined information is typically documented and processed manually on a recurring basis. Given this challenge, the following article presents a holistic two-part approach for pre-defining the information backflow of subsequent physical instances. Initially, an analysis of multiple test specifications in standards and directives is conducted, resulting in the development of a generic data model to represent this Pre-defined Information Backflow (PdIB). The second step builds on the first and defines an optimized representation for machine readability and executability for the future design of standards and directives. The two parts are brought together and validated using representative examples, thereby demonstrating the practical applicability and effectiveness of the proposed approach. This enhances the accessibility and usability of information in test specifications and formulas, thereby establishing a foundation for enhancing the efficiency of knowledge work in product development and the creation of digital representations of products and plants.
Integration Analysis of Transcriptome Sequencing and Whole-Genome Resequencing Reveal Wool Quality-Associated Key Genes in Zhexi Angora Rabbits
Authors: Zhao Bohao , Yu Yongqi , Sun Shaoning , Cai Jiawei , Bao Zhiyuan , Chen Yang , Wu Xinsheng
Published: December 2024

Wool quality is a crucial economic trait in Angora rabbits, closely linked to hair follicle (HF) growth and development. Therefore, understanding the molecular mechanisms of key genes regulating HF growth and wool fiber formation is essential. In the study, fine- and coarse-wool groups were identified based on HF morphological characteristics of Zhexi Angora rabbits. According to the results, the diameters of fine and coarse fibers, and the percentage of coarse fibers, were significantly lower in the fine-wool group than in the coarse-wool group. Additionally, the HF density was higher in the fine-wool group than in the coarse-wool group, and the diameters of both primary hair follicles and second hair follicles were finer in this fine-wool group. Moreover, RNA sequencing (RNA-seq) and whole-genome resequencing (WGRS) were performed to identify key candidate genes and potential genetic variations between fine- and coarse-wool groups. RNA-seq analysis revealed 182 differentially expressed genes (DEGs), with 138 upregulated and 44 downregulated genes in the fine-wool group. The WGRS analysis identified numerous genetic variants including 15,705 InDels and 83,055 SNPs between the two groups. Additionally, the joint analysis of RNA-seq and WGRS showed enrichment of the Wnt, JAK-STAT, and TGF-β signaling pathways. The key overlapping candidate genes such as DKK4, FRZB, CSNK1A1, TLR2, STAT4, and BMP6 were identified as potential crucial regulators of wool growth. In summary, this study provides valuable theoretical insights into wool quality and offers the potential for improving the molecular breeding of Angora rabbits.
Empowering User-Centric Selection of Electric Vehicles Charging Stations: A Hybrid Approach Using the Best–Worst Method and Grey Relational Analysis
Authors: Saleh Haitham
Published: December 2024

The increasing adoption of electric vehicles offers a way to combat the harmful impacts of climate change and to improve city living standards. Yet limited access to and lack of consistency among electric vehicle charging stations present obstacles for electric vehicle owners. This study advocates for an approach that positions the preferences of electric vehicle drivers first when choosing an electric vehicle charging station. By considering relevant factors to electric vehicle drivers and treating the problem as a grey system where certain information is known while other aspects are unknown, this research aims to empower users to make decisions aligned with their needs. The best–worst method is employed to assign preferences allowing electric vehicle users to make informed choices based on their priorities. The grey relational analysis method is utilized to rank electric vehicle charging stations based on user preferences. The best–worst method-grey relational analysis approach, as shown by examples, efficiently assists electric vehicle users in choosing the optimal electric vehicle charging station. This study acknowledges and incorporates the often-overlooked perspectives of electric vehicle drivers into a user-centric solution in existing research models. The gained insights carry significance for managing transportation and energy systems and designing user-friendly applications pertaining to electric vehicle charging station selection.