bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short Pulse Grid and Subthreshold Micropulse Laser (the Sandwich Grid) Plus Intravitreal Ranibizumab for the Treatment of Diabetic Macular Edema
Authors: Peroni Renato , Cardillo José Augusto , Memória Rafael , Pinto Tomás de Oliveira Castro Teixeira , Albieri Lucélia , Scott Ingrid U. , Jorge Rodrigo 
Published: August 2024

Abstract

Objective: To investigate the effects of two laser treatment procedures combined, short pulse grid laser (SP) and subthreshold micropulse laser (MP) (the sandwich grid [SWG] technique), plus intravitreal ranibizumab (IVR) on central subfield thickness (CSFT), best-corrected visual acuity (BCVA) and macular sensitivity in patients with diabetic macular edema (DME).
Methods: Forty-five eyes (of 33 patients) with center-involving DME were treated with the SWG laser technique plus IVR and followed for 12 months. Laser treatment was performed at baseline: SP laser spots were placed in a grid pattern the macular area (500 μm from the fovea) according to the extension of DME; subsequently, MP laser was delivered up to the edge of the fovea. MP laser re-treatment sessions could be performed every 3 months if DME was present and CSFT was ≥ 300 μm on SD-OCT. IVR injection was performed at baseline and repeated monthly if CSFT > 300μm. Preoperatively and monthly, ophthalmological examination was performed including measurements of BCVA, CSFT, and macular sensitivity.
Results: One-year follow-up data is available for 37 eyes of 27 patients. Mean ± SE CSFT (µm) was 509.36 ± 25.14 and 325.76 ± 15.34 at baseline and 12 months, respectively. A significant reduction in mean CSFT was observed at all study visits compared to baseline (p<0.001). Mean ± SE BCVA (logMAR) was 0.62 ± 0.04 and 0.45 ± 0.04 at baseline and 12 months, respectively. A significant improvement in mean BCVA was observed at all study visits compared to baseline (p<0.001). Mean ± SE macular sensitivity (dB) was 17.85 ± 0.80 and improved to 19.05 ± 0.59 after one year of follow-up (p=0.006). The mean number of IVR injections was 8.29 ± 0.63. The mean number of MP laser procedures including the initial SWG laser session was 3.67 ± 0.22. No ocular or systemic adverse effects were observed.
Conclusion: The SWG laser technique plus IVR was associated with significant improvement in macular edema, BCVA, and macular sensitivity in patients with center-involving DME.
Discrete Element Modeling of the Drag Force on a Rigid Body Swimming in a Granular Media
Authors: Guo Hong , Fu Jiangtao , Jiang Hong , Xu Qian , Tao Mingjiang 
Published: August 2024

Abstract

Owing to the difficulties in the accurate calculation of the shear zone area, determining drag force (FD)applied on a rigid body swimming in a granular bed is more complicated compared with that on the semi-immersed flat plate. In this study, we simplified the shear zone, made three assumptions to describe the “wedge,” and introduced the inertial number in the dynamic friction coefficient. The results showed that the boundary conditions have little effect on the overall FD and it increases with the increase in the swimming velocity and immersion depth and decreases as the particle diameter increases. Furthermore, we modified the Coulomb passive-earth pressure model, which is based on various functions, including swimming velocity and immersion depth, to effectively predict FD. Thus, the modified model could successfully predict the respective FD on rigid bodies at different swimming velocities and immersion depths.
Peripheral membrane protein endophilin B1 probes, perturbs and permeabilizes lipid bilayers
Authors: Sundborger-Lunna Anna , Thorlacius Arni , Rulev Maksim , Sundberg Oscar 
Published: August 2024

Abstract

Bin/Amphiphysin/Rvs (BAR) domain containing proteins are cytosolic, peripheral membrane proteins that regulate the curvature of membranes in eukaryotic cells. BAR protein endophilin B1 plays a key role in multiple cellular processes critical for oncogenesis, including autophagy and apoptosis. Amphipathic regions in endophilin B1 drive membrane association and tubulation through membrane scaffolding. Our understanding of exactly how BAR proteins like endophilin B1 promote highly diverse intracellular membrane remodeling events in the cell is severely limited due to lack of high-resolution structural information. Here we present the highest resolution cryo-EM structure of a BAR protein to date and the first structures of a BAR protein bound to nanodiscs. Using neural networks, we can effectively sort particle species of different stoichiometries, revealing the tremendous flexibility of post-membrane binding, pre-polymer BAR dimer organization and membrane deformation. We also show that endophilin B1 efficiently permeabilizes negatively charged liposomes that contain mitochondria-specific lipid cardiolipin and propose a new model for Bax-mediated cell death.
Population Genetic Structure of Phaedranassa Cinerea Ravenna (Amaryllidaceae) and Conservation Implications
Authors: Buenaño María Belén , Ulloa Carmen Ulloa , Francisco-Ortega Javier , Meerow Alan W. , Oleas Nora H. 
Published: August 2024

Abstract

Background
Andean orogeny has shaped the endemism of plant species in montane forests, creating a mosaic of habitats in small and isolated areas. Understanding these endemic species' genetic diversity patterns is crucial for their conservation. Phaedranassa cinerea (Amaryllidaceae), a species restricted to the western Andes of Ecuador, is listed as “vulnerable” according to the IUCN criteria. This study aimed to analyze the genetic structure of P. cinerea to propose conservation measures.
Results
Using 13 microsatellites and a Bayesian approach, we analyzed the genetic differentiation of P. cinerea, evidence of bottlenecks, and possible diversification scenarios. Our results indicate that the genetic diversity of P. cinerea is greater than that of congeneric species. The Bayesian analysis identified two genetic groups, with no evidence of isolation by distance. Populations in the northwest of the Ecuadorean Andes have less allele richness compared to those in the southwest. Additionally, the species exhibits excess homozygosity and evidence of bottlenecks. Our Bayesian analysis suggests that the differentiation between populations was not older than 5000 years and was as recent as 600 years ago for some of the populations. Based on the geographic distribution of the known populations, the species should be listed as endangered instead of vulnerable to extinction.
Conclusions
The findings suggest that conservation efforts should focus on securing genetic exchange between populations to preserve the genetic diversity of P. cinerea.
A Load Forecasting Method of New Power System Based on Personalized Federated Learning
Authors: Shen Yang , Li Zewen , Deng Fangming , Gao Bo 
Published: August 2024

Abstract

The emerging distributed generation technology in new power systems encounters the challenges of unstable efficiency and high accuracy of prediction models. The generalization ability of prediction models is hindered by variations in users’ behavioral characteristics. Furthermore, inability to share power data across regions poses substantial impediments to generation arrangement and power dispatch. This paper proposes a load forecasting technology based on federated learning (FL), which can avoid uploading or sharing the users’ data to protect data privacy. A multi-task module was added to traditional FL to improve user accuracy (UA) rather than global model accuracy, where the client trains a separate personalized model by keeping the local Layer-Normalization (LN) private. Moreover, in order to fast model convergence, the local LSTM prediction algorithm was added with the Grey Wolf optimization (GWO) algorithm and the attention mechanism. The experimental results show that the overall model training time of the improved LSTM algorithm is shortened by 26%. The Mean absolute percentage error (MAPE) of the proposed multi-task FL is 9.79% lower than traditional FL, and the MAPE of clients with small data volume and large feature deviation is reduced by 18.07% at most.
Research on Optimal Selection of Runoff Prediction Models Based on Coupled Machine Learning Methods
Authors: Wei Xing , CHEN Mengen , ZHOU Yulin , ZOU Jianhua , Ran Libo , SHI Ruibo 
Published: August 2024

Abstract

Runoff fluctuations under the influence of climate change and human activities present a significant challenge and valuable application in constructing high-accuracy runoff prediction models. This study aims to address this challenge by taking the Wanzhou station in the Three Gorges Reservoir area as a case study to optimize various prediction models. The study first selects artificial neural network (ANN) and support vector machine (SVM) as the base models. Then, it evaluates and selects from three time-series decomposition methods: Time-Varying Filter-based Empirical Mode Decomposition (TVF-EMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and Variational Mode Decomposition (VMD). Subsequently, these decomposition methods are coupled with optimization algorithms, including Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA), and Sparrow Search Algorithm (SSA), to construct various hybrid prediction models. The results indicate that: (1) Among the single prediction models, the Long Short-Term Memory (LSTM) model outperforms the Backpropagation Neural Network (BP) and SVM in terms of prediction accuracy; (2) The hybrid models show superior accuracy compared to the individual models, with the VMD-LSTM model outperforming the CEEMDAN-LSTM and TVF-EMD-LSTM models; (3) Among the coupled machine learning prediction models, the VMD-SSA-LSTM model achieves the highest accuracy. Employing a "decomposition-reconstruction" strategy combined with robust optimization algorithms enhances the performance of machine learning prediction models, thereby significantly improving the runoff prediction capabilities in watershed hydrological models.
Preparation of copolymers based on aniline and 2[2-chloro-1-methylbut-2-en-1-yl]aniline and their application for the removal of methyl orange from aqueous solutions
Authors: Usmanova Gulsum S. , Latypova Lyaysan R. , Yusupova Alfia R. , Mustafin Akhat G. 
Published: August 2024

Abstract

In this work, new copolymers P1-P9 were synthesized by oxidative copolymerization of aniline and 2-[2-chloro-1-methylbut-2-en-1-yl]aniline in HCl solution. The resulting copolymers were characterized with nitrogen adsorption-desorption isotherms, particle size. The equilibrium, kinetics, isotherms and thermodynamics of adsorption of methyl orange azo dye from aqueous solutions on P1-P9 copolymers have been studied. The influence of physicochemical variables (dosage, contact time, pH, dye concentration, temperature, ionic strength of the solution) on the specific adsorption of dye was determined. It is shown that P1-P4 copolymers are able to remove dye from aqueous solutions in a wide range of concentrations with efficiency up to 99.27%. The adsorption of methyl orange follows the Langmuir model (correlation coefficient is 0.9852-0.9990), which corresponds to monolayer adsorption on a homogeneous surface. The kinetics of dye adsorption is described by a pseudo-second-order equation, which is characteristic of chemisorption. Thermodynamic parameters of adsorption have been determined, allowing us to conclude that dye adsorption is a spontaneous endothermic process. It is shown that P1-P4 exhibit good adsorption capacity up to 110 mg/g. These copolymers retain high efficiency in five repeated adsorption-desorption cycles. The developed materials are considered to be suitable as cheap regenerated sorbents for anionic pollutants in wastewater.
Novel Insights into the Relationship Between Glucose-Lowering Drugs and Nonalcoholic Fatty Liver Disease and liver function: a Mendelian Randomization Study
Authors: Lei Gang , Dai Chibing 
Published: August 2024

Abstract

Objectives
The potential risk of nonalcoholic fatty liver disease (NAFLD) and liver toxicity attributed to glucose-lowering medications is uncertain. The objective of this study was to explore the causal relationship between these factors through the implementation of a Mendelian randomization (MR) analysis.
Methods
Two-sample MR, summary-data-based MR (SMR), and colocalization analysis were utilized to investigate the association between ten drug reduce glucose targets (PPARG, DPP4, GLP1R, INSR, SLC5A2, ABCC8, KCNJ11, ETFDH, GPD2, and PRKAB1) to reduce NAFLD and liver function tests (LFTs) levels, including aspartate aminotransferase (AST), gamma glutamyl transferase (GGT), alkaline phosphatase (ALP), alanine aminotransferase (ALT), and bilirubin.
Results
DPP4 is closely associated with GGT and ALT. PPARG is significantly associated with NAFLD and correlated with various liver enzymes GGT, AST, ALT, ALP, total bilirubin, and direct bilirubin. PRKAB1 is linked to total and direct bilirubin levels, while SLC5A2 is associated with total and direct bilirubin levels, ALP levels, and NAFLD risk. Limited evidence suggests that genetic variants in PRKAB1, GLP1R, INSR, GPD2, DPP4, and ABCC8/KCNJ11 are correlated with GGT, ALT, bilirubin, and NAFLD levels. Additional validation through SMR and colocalization analysis further confirmed the causal effects of these findings.
Conclusions
Specific glucose-lowering medications have been associated with an elevated risk of NAFLD and abnormal LFTs results, potentially offering innovative strategies for the management of NAFLD and LFTs abnormalities.
Ultrafast Polymerase Chain Reaction on MEMS Microheater
Authors: Cheng Xing , Liu Hongjun , Liu Yu , Liu Rongyue , Chen Rifei , Li Weihao , Chen Zijun , KIM Ji Tae , Chen Zhongren 
Published: August 2024

Abstract

Ultrafast polymerase chain reaction (PCR) is crucial for the rapid detection of pathogens, particularly in medical emergencies and public health scenarios. Conventional PCR systems, however, require extended processing times due to the inherent mass transfer rates of ~ 10 µL scale liquids. This study aims to achieve ultrafast nucleic acid amplification using a MEMS microheater to significantly reduce reaction volumes from a typical 10 µL PCR system to 3 nL, resulting in a total duration of 304 seconds for 38 thermal cycling. Temperature mapping and calibrations were conducted using infrared microscopy, and COMSOL simulations were employed to analyze thermal behavior and fluid dynamics within the droplets. The droplets were heated at a rate of 254°C/s and cooled at a rate of 122°C/s through natural thermal balance. The calibrated microheater exhibited high-temperature stability with a variation of ± 0.1°C, and efficient PCR amplification of HBV DNA and Coronavirus RNA samples were demonstrated, with Ct values significantly lower than those obtained using commercial equipment. As well, successful reverse transcription and PCR amplification of RNA samples were achieved. However, due to the limitations of the commercial reagents under such a short cycling duration, the amplification efficiency was undermined, being calculated at 88%. This technology offers a viable solution for rapid pathogen detection and holds potential for widespread applications in medical diagnostics and public health, particularly during pandemic outbreaks.
Emotion Recognition in Closed-Cabin Environment: An exploratory Study Using Millimeter-Wave Radar and Respiration Signal
Authors: Wang Hanyu , Chen Dengkai , Gu Sen , Zhou Yao , Sun Yiwei , Sun Jianhua , Huang Yuexin , Zhang Xian , Fan Hao 
Published: August 2024

Abstract

In the field of psychology and cognition within closed cabins, noncontact vital sign detection holds significant potential as it can enhance the user experience by utilizing objective measurements to assess emotions, making the process more sustainable and easier to deploy. To evaluate the capability of noncontact methods for emotion recognition in closed spaces, such as submarines, this study proposes an emotion recognition method that employs a millimeter-wave radar to capture respiration signals and uses a machine-learning framework for emotion classification. Respiration signals were collected while the participants watched videos designed to elicit different emotions. An automatic sparse encoder was used to extract features from respiration signals, and two support vector machines were employed for emotion classification. The proposed method was experimentally validated using the FaceReader software, which is based on audiovisual signals, and achieved an emotion classification accuracy of 68.21%, indicating the feasibility and effectiveness of using respiration signals to recognize and assess the emotional states of individuals in closed cabins.
The Role of Helical and Non-Helical Drives on the evolution of Self-Consistent Dynamos
Authors: BISWAS SHISHIR , Ganesh Rajaraman 
Published: August 2024

Abstract

In the self-consistent dynamo limit, the magnetic feedback on the velocity field is sufficiently strong to induce a change in the topology of the magnetic field. Consequently, the magnetic energy reaches a state of non-linear saturation. Here, we investigate the role played by helical and non-helical drives in the triggering and the eventual saturation of a self-consistent dynamo. Evidence of small-scale dynamo (SSD) activity is found for both helical and non-helical forcing, driven at the largest possible scale. Based on the spectrum analysis, we find that the evolution of kinetic energy follows Kolmogorov’s k-5/3 law while that of magnetic energy follows Kazantsev’s k3/2 scaling. Also, we have verified that the aforementioned scalings remain valid for various magnetic Prandtl numbers (Pm ). Statistical analysis is found to support our numerical finds.
Simulation Research on the Clinical Path of Non -Small Cell Lung Cancer Surgery Based on Time Petri Net
Authors: Da CHEN , Haitao SONG , Jun SONG , ZHONG Hui , Chuangchuang XU , Junli GAO 
Published: August 2024

Abstract

Background Clinical pathways are increasingly adopted to control costs and enhance quality management, becoming a standardized approach in treatment. This study aims to develop a hospital-specific clinical pathway for non-small cell lung cancer surgery, based on national standards and actual treatment practices, and evaluate its service efficiency through simulation. Methods We analyzed 94 electronic medical records of non-small cell lung cancer surgeries conducted from May 2020 to November 2022. The need for a localized clinical pathway was assessed by statistically analyzing delays in recorded treatment processes. A time Petri Net model was subsequently developed for this pathway, and simulations were conducted to determine the impact on hospital length of stay post-implementation. Results The existing treatment processes at the hospital generally conformed to national clinical pathway standards. The analysis of the Petri Net model confirmed its validity and effectiveness. Simulation results indicated that the average hospital stay is reduced to 8.20 days from a baseline of 7.76 days, achieving a total time reduction of approximately 10.28 hours, with reductions in individual diagnostic and treatment processes ranging from 0.15 to 5.04 hours. Conclusion The implementation of a tailored clinical pathway for non-small cell lung cancer surgery significantly improved service efficiency by aligning with national standards. This allows the hospital to better integrate and optimize medical resources, enhancing the overall quality of clinical pathway management.
A straightforward method for disaccharide characterization by a simplified version of time domain nuclear magnetic resonance
Authors: Sultana Afroza , Asghari Ali , Khalloufi Seddik 
Published: August 2024

Abstract

The necessity of identifying and quantifying sugars in food processing is endless for maintaining food quality attributes such as color, taste, and texture, monitoring regulatory compliance, labeling packages, and maintaining authenticity. Despite available analytical methods for characterizing sugar molecules, the limitations of conventional methods drive researchers to seek more convenient alternatives. This study aimed to characterize common disaccharides such as saccharose, lactose, maltose, and trehalose using a simplified version of time domain nuclear magnetic resonance (TD-NMR), facilitating a quick, cost-effective, and user-friendly approach. In the transverse relaxometry, secondary peak(s) were observed for all the disaccharides with a main peak. Although they have similar molecular formulas and weights, lactose exhibited the longest relaxation time for the secondary peak, followed by trehalose, saccharose, and maltose. This behavior was assumed due to the interaction of sugar molecules with water. The increasing concentration of disaccharide in the solution displayed the leftward shifting of peaks. Maltose showed two secondary peaks, which were not observed in other sugar samples. This TD-NMR showed potential to distinguish disaccharides from unknown powders and solutions by analyzing either the relaxation time of the secondary peak or the ratio of the secondary to the total peak. Moreover, quantification is possible from the standard curves of relaxation time and the combined surface area of the main and secondary peaks with the corresponding sugar concentration. However, it shows challenges in discrimination between α- and β-isomers.
Characterizing Shadowing and Fading in Emerging Wireless Communication Systems via the Shadowed Beaulieu-Xie Model
Authors: Olutayo Adebola , Holzman Jonathan F. , Chaaban Anas 
Published: August 2024

Abstract

The drive for wireless communications at higher frequencies has led to growing interest for systems in the millimetre-wave and terahertz bands. However, the performance of such systems has been greatly hampered to date by shadowing and fading, leaving emerging sixth-generation and land mobile satellite systems awaiting solutions. As such, we analyze and characterize the effects of shadowing and fading seen in these systems. We do so by introducing the second-order statistics of the shadowed Beaulieu-Xie model, and then apply the probability density and characteristic function methods to acquire expressions and results for the level crossing rate and average fade duration in these emerging systems. We then fit our modeled results to measured data obtained by the Communication Research Centre in Ottawa, Canada, in collaboration with the National Aeronautics and Space Administration of the United States of America. Our shadowed Beaulieu-Xie model shows an excellent fit to the strong shadowing and fading in the measured data, suggesting that the model has great potential in characterizing emerging communication environments and systems.