bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing deep learning to predict Alzheimer's disease and mild cognitive impairment with optical coherence tomography
Authors: Chua Jacqueline , Li Chi , Antochi Florina , Toma Eduard , Wong Damon , Tan Bingyao , Garhöfer Gerhard , Hilal Saima , Popa‐Cherecheanu Alina , Chen Christopher Li‐Hsian , Schmetterer Leopold 
Published: January 2025

AbstractINTRODUCTIONDiagnostic performance of optical coherence tomography (OCT) to detect Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains limited. We aimed to develop a deep‐learning algorithm using OCT to detect AD and MCI.METHODSWe performed a cross‐sectional study involving 228 Asian participants (173 cases/55 controls) for model development and testing on 68 Asian (52 cases/16 controls) and 85 White (39 cases/46 controls) participants. Features from OCT were used to develop an ensemble trilateral deep‐learning model.RESULTSThe trilateral model significantly outperformed single non‐deep learning models in Asian (area under the curve [AUC] = 0.91 vs. 0.71–0.72, p = 0.022‐0.032) and White (AUC = 0.84 vs. 0.58–0.75, p = 0.056‐ < 0.001) populations. However, its performance was comparable to that of the trilateral statistical model (AUCs similar, p > 0.05).DISCUSSIONBoth multimodal approaches, using deep learning or traditional statistical models, show promise for AD and MCI detection. The choice between these models may depend on computational resources, interpretability preferences, and clinical needs.Highlights
A deep‐learning algorithm was developed to detect Alzheimer's disease (AD) and mild cognitive impairment (MCI) using OCT images.
The combined model outperformed single OCT parameters in both Asian and White cohorts.
The study demonstrates the potential of OCT‐based deep‐learning algorithms for AD and MCI detection.
Association of a remote monitoring programme with all‐cause mortality and hospitalizations in patients with heart failure: National‐scale, real‐world evidence from a 3‐year propensity score analysis of the TELESAT‐HF study
Authors: Girerd Nicolas , Barbet Vanessa , Seronde Marie‐France , Benchimol Hélène , Jagu Annabelle , Tartière Jean‐Michel , Hanon Olivier , Picard François , Lafitte Stéphane , Lemaitre Magali , Pages Nicolas , Nisse‐Durgeat Sophie , Jourdain Patrick 
Published: January 2025

AbstractAimsTo examine the association of a remote monitoring programme (RMP) with all‐cause mortality and hospital admissions for heart failure (HF) within the French healthcare system.Methods and resultsA national‐scale, real‐world, propensity‐weighted cohort study was conducted using the SNDS French database from August 2018 to December 2022 (NCT06312501). Patients receiving standard of care (SoC) were compared with those receiving RMP (Satelia® Cardio, NP Medical). The Satelia® Cardio algorithm adjusted the monitoring frequency based on symptom and weight changes, and provided tailored web‐based patient education. The RMP included a digital interface for proficient patients and phone monitoring by nurses for those uncomfortable with digital technology. Data were sourced from over 300 healthcare centres across France. A propensity‐weighted Cox regression model was used, supplemented by sensitivity analyses across subgroups. In total, 5357 RMP patients and 13 525 SoC patients were included after weighting. Weighted/adjusted analyses showed lower all‐cause mortality for RMP patients (hazard ratio [HR] 0.64; 95% confidence interval [CI] 0.59–0.70; p < 0.0001), persisting across hospitalization and/or long‐term illness status subgroups (HR 0.52 to 0.75). RMP was neutrally associated with HF hospitalization rates (rate ratio [RR] 0.95; 95% CI 0.89–1.02) but linked to less time in hospital (−2.1%, p < 0.0001) and fewer emergency visits (RR 0.83; 95% CI 0.75–0.92; p = 0.001).ConclusionIn France, RMP with customized monitoring frequencies and educational strategies was associated with lower all‐cause mortality, emergency visits, and time spent in hospital in patients with HF which may enhance nationwide HF management.
Catalytic epoxidation of waste palm kernel oil using in situ performic acid formation
Authors: Jalil Mohd Jumain , Ibrahim Izni Mariah , Saputro Erwan Adi , Habri Hamzah Hafizuddin , Rasib Ismail Md , Rahman Siti Juwairiyah A. , Azmi Intan Suhada 
Published: January 2025

AbstractThe use of renewable resources in the epoxidation process can reduce the dependence on non‐renewable petroleum resources and contribute to a more environmentally friendly chemical industry. This study aims to investigate the epoxidation of waste palm kernel oil as a renewable feedstock. The synthesis of epoxidized waste palm kernel oil was conducted by reacting waste palm kernel oil, formic acid, and hydrogen peroxide in a one‐pot system. Currently, there is no reported literature on the simultaneous application of a catalyst for the epoxidation of waste palm kernel oil derived from industrial waste. The optimum process parameters were determined, including hydrogen peroxide to waste palm kernel oil molar ratio (1.5:1), formic acid to waste palm kernel oil molar ratio (0.5:1), and stirring speed (300 rpm). The optimum relative conversion to oxirane of epoxidized waste palm kernel oil was 88%. A mathematical model was developed using numerical integration based on the fourth‐order Runge–Kutta method as follows: = 0.894 mol·L−1·min−1, = 7.420 mol·L−1·min−1, and = 0.086 mol·L−1·min−1. Based on the findings of the kinetic study, the kinetic model was validated due to its minimal simulation error.
Nonlinear Signal‐Based Control for a Shake Table Supporting a Heavy Multi‐Storey Nonlinear Structure
Authors: Enokida Ryuta , Ikago Kohju , Kajiwara Koichi 
Published: January 2025

ABSTRACTShake table control is greatly affected by an interaction with a heavy specimen, especially when it has severe nonlinear characteristics. Hence, to this fundamental and challenging issue in the experimentation, this study proposes a solution using nonlinear signal‐based control (NSBC) and demonstrates its effectiveness in actual experiments. Moreover, an innovative controller design is presented in this paper: the bare condition referenced (BCR) approach relies on the bare table dynamics and the specimen's weight. It frees the design from the properties of the controlled system, in contrast to the orthodox approach, which uses the dynamics of a table supporting a specimen. Following numerical examinations including a stability analysis, experiments were carried out on NSBC with these approaches, with a table having a three‐storey structure that was 2.5 times heavier than the table and had nonlinear characteristics. An inversion‐based controller, using a feedforward controller only, did not perform well, even at small excitations, owing to the modelling gap and nonlinearity. NSBC, with the orthodox approach, accurately realised the expected acceleration on the table, despite the considerable interaction with the specimen and the nonlinearity of its collapse level. NSBC, with the BCR approach, performed as well or better than the orthodox approach, despite the obvious modelling gap and nonlinearity. NSBC with both approaches can solve the challenging control problem and has considerable potential for deployment in large experiments. Furthermore, the BCR approach is more advantageous than the orthodox approach, as it eliminates the need to identify the dynamics of the table supporting the specimen.
Study on Zonal Support Mechanism and the Surrounding Rock Control Technology of Rock Roadway Excavated by TBM in Coal Mine
Authors: Chen Zhao , Zhang Sheng , Lu Yiqiang , Yang Zhanbiao , Wang Longfei , He Fei 
Published: January 2025

ABSTRACTTunnel boring machine (TBM) has been increasingly used for excavating rock roadways in coal mines. However, the slower speed of support installation, compared to the cutterhead's fast rock‐breaking capability, limits the overall excavation speed of rock roadways. This study examines the construction of a gas drainage roadway in Shoushan No.1 coal mine using a double‐shield TBM. A mechanical model for TBM excavation was developed, considering the spatial effects of the excavation face. The study identified a zonal support mechanism for the surrounding rock in TBM excavation roadways, it also analyzed the effects of support reaction forces and virtual support forces on the surrounding rock of different zones. A zonal control technology for surrounding rock was proposed and successfully implemented in the field. The results indicate that the strain evolution of the surrounding rock behind the TBM excavation face displays distinct zonal features. Based on this, the study recommends timely support for critical areas of the roadway roof in rapidly deforming zones through localized active primary anchor bolting. In slower deforming zones, secondary active anchor bolting is recommended for the remaining parts of the roadway roof and the side supports. In stable zones, cables anchor bolting support are implemented. A phased control technology system for the zonal management of surrounding rock in TBM excavation roadway was developed, and optimal parameters were determined using numerical simulations. The phased and zonal control technology was successfully applied at Shoushan No. 1 coal mine, achieving a maximum excavation speed of 623 m per month. This study provides valuable insights into the application of rapid excavation technology by TBM under similar conditions.
Accurate Molar Mass Estimation of Polyolefin Blends Using High Temperature‐size Exclusion Chromatography With Triple Detection: Insight Into Molecular Level Mixing of Polypropylene With Various Application Grades of Polyethylene
Authors: Subbaiah Yogesha , AlAhmadi Ahmad Salem , Debasagoiti Mark , Nagarajan Balaji , Alhafs Rawan Jassem , Shanmugam Senthilkumar 
Published: January 2025

ABSTRACTIn this study, a commercially available polypropylene homopolymer (H‐PP) was blended with blow molding polyethylene (PE) grade via melt mixing using a compounding machine. The resulting blends were subjected to high‐temperature size exclusion chromatography (SEC) analysis, coupled with infrared‐5 (IR‐5), viscometer (VISCO), and multi‐angle laser light scattering (MALS) detectors. The molecular weight (MW) and MW distributions were investigated using SEC, and the exact blend compositions were evaluated using 13C nuclear magnetic resonance. The molecular‐level mixing of the PP/PE blend composition was assessed by comparing the theoretical and measured weight‐average MW (Mw) values obtained using different SEC detection modes. The measured average Mw values of different PP/PE blends obtained using VISCO and multi‐angle light‐scattering detection were found to be in close agreement with predicted blend ratios, compared to the conventional SEC technique (IR‐5), with percentage errors ranging from ‐4.53 to ‐5.99 and 1.57 to 7.65, respectively. The linear relationship between the melt flow rate (MFR) and Mw was studied to assess the molecular‐level mixing behavior of the prepared blends using different SEC detection modes. Furthermore, the SEC methodology was extended to other application grades of PE with varying MFRs to verify the blend mixing behavior with H‐PP, and the obtained results are discussed.
Molten Salt Corrosion Studies of Sanicro‐25 by Electrochemical Techniques at High Temperature
Authors: JagadeeswaraRao Ch. , M. Anantha Lakshmi , Suneesh P. V. , Ningshen S. 
Published: January 2025

ABSTRACTNickel and chromium‐based alloys are being considered structural materials for crucibles for electrorefining in pyrochemical reprocessing. LiCl–KCl molten salt is used as an electrolyte under an inert argon atmosphere. In the present work, the corrosion behavior of the Sanicro‐25 steel exposed to LiCl–KCl molten salt at 500°C with inert argon cover gas was explored using electrochemical methods like open circuit potential (OCP), linear polarization resistance, and electrochemical impedance spectroscopy (EIS). A change in the OCP of Sanicro‐25 towards the noble direction was observed. The linear polarization resistance, measured at various exposure intervals, decreased with the increase of molten salt exposure. The Nyquist plot consists of two semi‐circles with an incomplete semi‐circle at the lower frequency end, indicating the existence of three‐time constants and formation of intermittent oxide film. The oxide films formed over the surface are characterized by Raman analysis, X‐ray diffraction, X‐ray photoelectron spectroscopy, and scanning electron microscope coupled with elemental analysis. The formation of Fe3O4, Cr2O3, iron hydroxide, W‐oxides, and spinels are evidenced.
Log‐TF‐IDF and NETCONF‐Based Network Switch Anomaly Detection
Authors: Nam Sukhyun , Jeong Eui‐Dong , Hong James Won‐Ki 
Published: January 2025

ABSTRACTIn this study, we propose and evaluate a model that utilizes both log data and state data to detect abnormal conditions in network switches. Building upon our previous research and drawing inspiration from TF‐IDF used in natural language processing to measure word importance, we propose a statistical method, Log‐TF‐IDF, to quantify the rarity of each log pattern in the log data. Furthermore, based on this Log‐TF‐IDF, we introduce the AB Score, which quantifies how abnormal the current log pattern is. Our findings indicate that the AB Score is notably higher and more volatile in abnormal conditions. We confirm that anomaly detection is feasible through the AB Score, which has the advantage of being computationally efficient due to its statistical basis. We combined the metrics generated during the AB Score calculation with resource data collected with NETCONF and developed a machine‐learning model to detect abnormal conditions in network switches. We confirm that this model can detect abnormal conditions with an F1 score of 0.86 on our collected dataset, confirming its viability for detecting abnormal states in network equipment.
A New English Education Model Based on 6G and Sliced Network Virtual Reality Platform
Authors: Liu Xiaozheng 
Published: January 2025

ABSTRACTThe information society has led to a shift in traditional English education methods, with the evolution of technology, particularly internet and communication network technologies, reshaping the teaching landscape. This facilitated innovative instructional approaches and enhanced the learning experience. This research introduces a novel virtual learn net architecture (VLNA) within the 6G network layers, which processes the performance of the virtual reality‐based English education system (VR‐EES) model to provide a seamless, personalized learning experience for online learners. This architecture is structured into several layers: The user equipment (UE) layer connects VR headsets to the network with ultrareliable, low‐latency links; the radio access network (RAN) layer, employing massive MIMO and beam forming, enhances connection speed, capacity, and coverage. Edge computing handles latency‐sensitive tasks like speech recognition and adaptive content delivery, reducing the load on the core network. The core network layer (CLN) manages network slices for specific learning tasks such as real‐time interaction, high‐definition multimedia, and computation‐intensive processes, with control plane and user plane separation (CUPS) optimizing network management and security through end‐to‐end encryption. Software‐defined networking (SDN) and network function virtualization (NFV) provide centralized, dynamic control, allowing real‐time resource allocation based on demand. Cloud‐edge integration supports Artificial intelligence (AI)‐driven adaptive learning, optimizing educational content delivery based on individual progress. The study results demonstrate that stimulation of VLNA achieved significant improvements in latency reduction, bandwidth utilization, throughput, packet loss rate, jitter, user engagement, learning efficiency, and user satisfaction. The integration of edge computing and network slicing led to a significant reduction in latency, while the enhanced throughput enabled seamless VR experiences. In this study, latency reduction, bandwidth utilization, and user satisfaction emerge as the most significant factors, with user satisfaction standing out as the top performer due to its substantial impact on enhancing the overall learning experience. The packet loss rate is maintained to a certain level, ensuring reliable data transmission. The VR‐EES model's experimental results also enhanced visual learning, multimedia quality, user pleasure, learning effectiveness, and user engagement.
Maleinized Vegetable Oil: A Green Approach for Sustainable Polyamide Composites
Authors: Gaddam Sashivinay Kumar , Boddu Venkateswar Rao , Boga Karteek , Bhatt Himanshu Kumar , Das Paramita , Pinjari Sharad Dnyanu , Qi Xiaoning , Gaddam R. R. , Arukula Ravi 
Published: January 2025

ABSTRACTOver the past two decades, the rising demand for sustainable materials has sparked significant interest in developing plant‐based or bio‐based polymers. This study explores an innovative approach to synthesizing eco‐friendly polyamide‐graphene composites using maleinized cottonseed oil (MACSO) as a sustainable precursor. The composites were produced through a room‐temperature catalyst‐free ring opening of MACSO with 4,4′‐Diaminodiphenylmethane (DDM) and graphenamine, followed by high‐temperature curing. The impact of graphenamine content on the composites' structural, thermo‐mechanical, surface, and anticorrosion properties was thoroughly examined. Notably, the composite containing 3 wt% graphenamine demonstrated superior thermal stability, glass transition temperature (Tg), mechanical toughness, and corrosion resistance. This research represents a unique example of using anhydride‐grafted vegetable oil for amide bond formation in the final polymer, highlighting an economically viable approach to sustainable polyamide synthesis. Furthermore, using MACSO as a bio‐based modifier aligns with the principles of green chemistry, offering a sustainable alternative to traditional petrochemical‐based additives.
Enhancement of Dynamic Mechanical and Physicochemical Characteristics of PolyAAm:PVA‐Grafted mFlax‐Reinforced Polyester Composite
Authors: Saini Divyansh , Saksham  , Sharma Himani , Dolui Susmriti , Bedi Raman , Kaith Balbir Singh 
Published: January 2025

ABSTRACTThe present study explores the copolymerization of mercerized Flax (mFlax) using a combination of acrylamide (AAm) and polyvinyl alcohol (PVA) as a binary vinyl monomeric mixture (AAm:PVA). Polyester‐based composites reinforced with different Flax samples, i.e., raw, mercerized, and grafted Flax with a 5% loading concentration, were fabricated, and their mechanical properties were analyzed using dynamic mechanical analysis (DMA). The samples were characterized using various analytical techniques. Grafting of AAm:PVA onto mFlax enhanced its chemical and moisture resistance, reducing weight loss by blocking vulnerable sites with binary vinyl monomeric live chains. This conversion rendered the Flax less susceptible to solvents. The DMA results revealed an elevation in the loss modulus and Tan δ values for the (AAm:PVA)‐grafted mFlax‐reinforced polyester composite, while a reduction in the value of storage modulus was observed.
Denture base poly(methyl methacrylate) reinforced with SrTiO3/Y2O3: Structural, morphological and mechanical analysis
Authors: Elhmali Houda Taher , Radojevic Vesna , Stajcic Aleksandar , Petrovic Milos , Stojanovic Dusica B. , Vlahovic Branislav , Stajcic Ivana 
Published: January 2025

AbstractThis study presented the use of SrTiO3/Y2O3 nanoparticles for the reinforcement of dental poly(methyl methacrylate) (PMMA) to enhance its mechanical properties important for everyday use of denture base materials. The average crystallite size of prepared nanoparticles was 19.9 nm. The influence of 0.5, 1.0, and 1.5 wt% SrTiO3/Y2O3 loading on absorbed impact energy, microhardness and tensile properties was investigated. Scanning electron microscopy of the composite fracture surface revealed multiple toughening mechanisms, with agglomerates directly included in the crack pinning, indicating improvement in mechanical performance. Dynamic mechanical analysis proved that agglomerates improved the elastic behavior of PMMA and confirmed the absence of a residual monomer. After the incorporation of SrTiO3/Y2O3, the mechanical properties of composites showed a high increase compared to neat PMMA. The optimal concentration of nanoparticles was 1 wt%, for which the microhardness, modulus of elasticity, and absorbed impact energy were higher by 218.4%, 65.8% and 135.6%, respectively. With such a high increase, this research showed that SrTiO3/Y2O3 represents an efficient filler which use does not have to be limited to dental materials.Highlights
SrTiO3/Y2O3 hybrid nanoparticles were prepared.
PMMA‐SrTiO3/Y2O3 composite showed increase in impact resistance up to 135.4%.
Elastic behavior of PMMA was improved.
With 1 wt% of SrTiO3/Y2O3, microhardness increased by 218.4%.
Synthesis of Poly(Itaconate)s With High Monomer Conversion Applying Emulsion Polymerization
Authors: Fischer von Mollard S. Charlotte , Ueberschaar Nico , Schreiber Martin , Kamphuis Frank , Zechel Stefan , Hager Martin D. 
Published: January 2025

ABSTRACTItaconic acid and its derivatives can be obtained from renewable feedstocks. However, there are only very limited applications of polymers containing itaconic acid so far. One limitation of the application of this polymer is that commonly utilized polymerization techniques lead to very low conversions of the corresponding monomers. Consequently, itaconic acid and its derivatives are generally considered difficult or poorly polymerizable monomers. The current study presents the improvement of the polymerization by applying an emulsion polymerization of itaconic acid esters, leading to very high monomer conversions with a residual monomer content of less than 1%.
Robust Second‐Order Backstepping Design of Integrated Guidance and Control Based on a Fully Actuated System Approach
Authors: Wang Wei , Chen Shiwei , Fan Junfang , Zhang Hongyan 
Published: January 2025

ABSTRACTThis article investigates the angle constraint issue in the integrated guidance and control (IGC) design. By using the high‐order fully actuated system (HOFAS) approach, a non‐linear robust controller is presented under the framework of the second‐order backstepping method. First, the IGC model is represented as a complete second‐order non‐linear system without any linearization assumption, where the modeling error, unmodeled non‐linearity, and external disturbance are unknown uncertainties. Combined with the dynamic model, the non‐linear system is transformed into a pseudo‐feedback system. An IGC model with fully actuated features is established, consisting of the guidance, dynamics, and attitude subsystems. Then, under the framework of the backstepping method, the non‐linear controller of each subsystem is designed based on the HOFAS approach and robust control law, and a tracking differentiator based on inverse hyperbolic sine function is used to obtain the precise differential signal of the virtual control command. The controller parameter matrix is solved according to the desired closed‐loop poles, while the closed‐loop system is transformed into a steady linear system with desired performance. The subsystem state convergence is proven by Lyapunov theory, and the stability of the whole system is analyzed. Finally, the simulation results of terminal angle constraint verify the effectiveness of the proposed robust IGC design.