bluuebunny/crossref_metadata_2025_split huggingface dataset:
Compressed Sensing Channel Estimation Algorithm Combined with Wavelet Denoising
Authors: Kong Chuiyuan , Wang Hao , Chang Junming 
Published: November 2023

Abstract
In wireless multipath channels, there is sparsity, in which traditional channel estimation algorithms do not take advantage of and ignore the impact of noise. An effective estimation algorithm combining compressed sensing and wavelet de-noising is proposed. Before channel estimation, the pilot signal received by the receiver is de-noised by the wavelet de-noising method to obtain the de-noised measurement vector, and then the original signal is recovered by the compressed sensing technology for sparse channel estimation. This algorithm breaks away from the limitation of traditional algorithms that require predictive sparsity to achieve sparsity adaptive signal reconstruction. Through simulation analysis, it has been proven that the fusion wavelet denoising algorithm can improve the estimation performance, reduce estimation errors, and be more suitable for sparse channel estimation by denoising the signal during channel estimation.
Improved Faster R-CNN Traffic Sign Detection Algorithm Based on Transformer
Authors: Tian Chengjun , Liu Zhe , Liu Haobo , Yan Yu , Zhang Jintong 
Published: November 2023

Abstract
In view of the fact that traffic sign detection is becoming more and more important in assisted driving, but there are situations where the target is small, occluded and the background is complex, this paper proposes a Transformer-based improved Faster R-CNN algorithm for traffic sign detection. The algorithm in this paper uses the Transformer network based on the shift window as the backbone. The multi-level feature map is fused across layers through the cascade fusion module to obtain the fusion feature map. Moreover, the model’s feature extraction ability is improved. The detection head module eliminates rounding through RoI Align quantization error. Based on experiments in the TT100K dataset, it can be known that the mAP and detection speed of the algorithm in this paper has been improved. The effectiveness of the improved model in this paper is proven and it is applicable to real scenarios.
Application and evaluation of CNN-LSTM classification regression based multi-source precipitation data fusion model in water resources research in Qinghai Province
Authors: You Shaojie , Zhang Xiaodan , Quan Chen , Wang Hongyu , Zhao Tong , Liu Chang , Du Huali 
Published: November 2023

Abstract
Qinghai Province is located in the Qinghai-Tibet Plateau region, with complex and diverse topography and sparse precipitation stations, which makes it difficult to obtain reliable precipitation data. This study proposes a classification and regression model based on a deep learning algorithm, which combines a convolutional neural network (CNN) and a long short-term memory neural network (LSTM), with the CNN extracting the spatial features of multi-source data, the LSTM capturing their temporal dependencies. The regression results are used to determine whether rainfall is occurring and to further calibrate the non-rainfall component of the precipitation forecast results. ERA5, IMERG, CHIRPS and DEM were selected as feature data and rain gauge data as label data. The findings indicate that the proposed CNN-LSTM classification regression model (CLCR) is superior to other models (CNN, CNN-LSTM, LSTM). The Kling-Gupta efficiency (KGE) of the data fused using CLCR was 0.66, which was significantly better than that of the raw rainfall data (0.53, -0.36, 0.34) and other models (0.58, 0.65, 0.63). CLCR also showed more performance in daily precipitation detection than other models and raw precipitation data, with Critical Success Index (CSI), Probability of Detection (POD), and False Alarm Ratio (FAR) 0.61, 0.25 and 0.76 respectively. This study generated a high-precision daily rainfall dataset with a precision of 0.01° resolution for 2013-2017 in Qinghai Province, which provides reliable data support for hydrological studies in Qinghai Province.
Differential evolutionary algorithm based on principal component analysis for the satellite bandwidth resource scheduling problem
Authors: Wang Zihan , Wang Dan , Zhang Anqi , Yang Liping 
Published: November 2023

Abstract
This paper focuses on the research of the communication satellite bandwidth resource scheduling problem. Satellite resource scheduling refers to adjusting the order of task execution within a certain scheduling time to complete as many satellite tasks as possible while satisfying bandwidth and time constraints. Traditional algorithms cannot meet the time requirements in the process of satellite communication resource scheduling. Therefore, this paper proposes a differential evolution algorithm based on principal component analysis (PCA) and combines it with the Lowest Horizontal Line Algorithm (LHLA) to solve this problem. The method was validated on two datasets at 20 dimensions and 40 dimensions, and compared with other traditional DE algorithms. The experimental results showed that the method obtained better solutions.
Capsule Endoscopy Image Deblurring Method Based on Multi-scale Recurrent Network
Authors: Yang Shiyu , Guo Tai , Zhan Ruoya 
Published: November 2023

Abstract
During the process of acquiring capsule endoscope images, image motion blur may result from errors made by the operating physician. A multi-scale recurrent attention network is proposed to address the issue of motion blur in collected images. Considering the issue of over-exposure during image acquisition in capsule endoscopy, which can adversely affect network generation results, an image preprocessing module has been incorporated into the network to eliminate highlights caused by over-exposure in input images. To enhance network sampling efficiency, the encoder is equipped with a Convolutional Block Attention Module (CBAM) to extract fuzzy features more effectively. Additionally, depthwise separable convolution is employed to reduce parameter count. Since the structure of images obtained through capsule endoscopy is relatively simple and stable, we have opted for the mean square error as our loss function due to its heightened sensitivity to data errors. The experimental results demonstrate that the proposed network achieves a Peak Signal-to-Noise Ratio (PSNR) of 31.096 and a Structural Similarity Index Measure (SSIM) of 0.925, indicating a significant improvement over DeblurGAN-v2 and Pix2pix.
A Y-Shaped Tilting Wing UAV for Vertical Take-off and Landing Cargo
Authors: Shen Xinmin , Zhu Xiaoqing 
Published: November 2023

Abstract
To address the growing demand for express cargo transportation within and between cities, this study presents a conceptual design of a Y-shaped tilting wing unmanned aerial vehicle (UAV) capable of vertical take-off and landing (VTOL). The design aims to overcome the limitations of existing UAV designs and combine the advantages of multi-rotor and fixed-wing aircraft. By incorporating fixed-wing features, the UAV offers an extended battery life and range, making it an ideal choice for urban express cargo transportation. Firstly, a master geometry model of the UAV is established. Subsequently, dynamic simulations are conducted to evaluate the UAV’s performance under different trajectories. The analysis of the research results verifies that the UAV can successfully complete its flight missions along predetermined paths.
Lightweight Transformer with Transposed-attention for Hyperspectral Unmixing
Authors: Mo Ye , Sun Haixin , Meng Fanlei 
Published: November 2023

Abstract
Hyperspectral unmixing primarily involves accurately estimating the end members and abundances from mixed pixels in hyperspectral images. In our task, we design a transposed-attention mechanism in the lightweight Transformer to capture the effective information between channels to provide better performance and faster computing speed. We compare the proposed model with those of the CyCU, FCLS, and DHTN methods. The quantitative and qualitative results indicate that our method outperforms the quality of endmember spectral and abundance maps and has a competitive advantage in calculation speed.
Dynamic Object Tracking Based on Triplet Relationship Guided Sampling Consensus Algorithm
Authors: Zhou Jiaxing , Yao Youxin , Chen Xiang , Guo Hanlin , Huang Qixuan 
Published: November 2023

Abstract
Compared with the traditional methods based on the prediction of moving object trajectory, the method based on image registration has the advantage of not relying on the object motion equation to track the object. However, in the case of a large number of outliers, the image matching method has the defects of inadequate filtering of outliers or erroneous filtering of incomers due to the limitations of spatial constraints of feature matching pairs, which will make the tracking of flying objects inaccurate or impossible. During the flight, the object may be in a similar background and the image shooting angle is different, which makes the object imaging angle change, resulting in a large number of outlier interference. Because of the above situation, this paper adopted an improved TRESAC algorithm based on RANSAC, which used a feature matching method based on a triplet relationship to effectively filter outliers and then adopted an initial data subset selection strategy to increase its robustness. Experimental results show that the TRESAC algorithm can filter outliers quickly and accurately, and the object is still tracked effectively under the condition of similar background and pose change.
The spatial and temporal evolution of surface temperature in the main urban area of Hangzhou from 1990 to 2020 based on GEE
Authors: Liu Han 
Published: November 2023

Abstract
In this study, remote sensing (RS), geographic information system (GIS), Google Earth Engine (GEE), and mathematical analysis methods are applied to study the evolution and development trend of land surface temperature in Hangzhou. The GEE platform used in this study, which can fit remote sensing images of multiple regions under different spatial and temporal conditions, has the advantages of wide range and timeliness, and enables the study area to cover the entire Hangzhou city. The purpose of this study is to study the evolution of surface temperature in Hangzhou from 1990 to 2020 using a combination of remote sensing inversion and GIS spatial analysis, and to combine a variety of geostatistical analysis methods to specifically study the trend of surface temperature change and urban heat island development in Hangzhou in order to improve the local people’s life and local environment.
Study on Remote Sensing Image Coverage Frequency Based on Spatial Grid
Authors: Huang Shusong , Zeng Yong , Chen Weirong , Qi Wenping , Zhang Wenhui 
Published: November 2023

Abstract
The coverage frequency analysis of remote sensing images is helpful to analyse the data acquisition capability of satellites or the vigorous users’ demand. In the current research, thermal values are mostly calculated using an individual point or surface target. In this paper, an index RSICF is proposed, which is calculated based on two shapes, image vectors, and spatial grid, to measure the frequency of remote sensing image coverage. The study uses GF-1 satellite image vectors to calculate RSICF around China to verify its availability. The result shows RSICF can reflect the distribution of historical image frequency respectively and can be introduced by creating a heatmap of remote sensing image coverage.
CDMnet: Cloud Detection in Remote Sensing Images Based on CNN
Authors: Shi Jia , Wang Chunyu 
Published: November 2023

Abstract
The main objective of cloud detection is to accurately distinguish between clouds and areas that are not clouds to extract accurate surface information. To achieve an accurate distinction between cloud and non-cloud regions, we propose a novel method called Cloud Detection Method Net (CDMnet). The method employs a lightweight network backbone, compared to traditional classical algorithms like SVM, to effectively reduce computational costs while maintaining accuracy. Additionally, we utilize hole convolutions with varying dilation rates to extract cloud features in parallel. We also employ SAM spatial attention multiple times to fine-tune cloud position positioning and obtain more accurate cloud masks. From the experimental results, it can be concluded that our method is more efficient than other traditional methods.
Electric field in the RF cavity with large beam duct for high current beam acceleration
Authors: Sako T. , Ishi Y. , Uesugi T. , Kuriyama Y. , Mori Y. , Tsumori K. , Ando A. , Yonemura Y. 
Published: November 2023

Abstract
A acceleration scheme using a bunch of single-cell cavities
as the first-stage acceleration of ion beams. The single-cell cavity
has been shown the possibility of accelerating high-current beams of
1 A or more. As an elemental test before we started a cavity
fabrication, we compared simulations of the electric field
distribution with experiments utilizing the existing cavity.
Effects of a spherical slip cavity filled with micropolar fluid on a spherical micropolar droplet
Authors: Salem Ahmed G 
Published: November 2023

Abstract
In this work, a two-fluid phase flow problem involving an axisymmetrical quasi-steady motion of a spherical micropolar droplet translating at a concentric point in a second non-mixable micropolar fluid within a spherical impermeable cavity with a slip surface is analysed under low Reynolds numbers. The two fluid phases that have a microstructure (micropolar fluid) are the case that is being focused on. The Stokes equations are solved inside and outside the droplet for the velocity fields. In addition, based on the concentric position, general solutions in terms of spherical coordinates are obtained. In this case, tangential couple stress and continuity of microrotation are used. For different cases, the normalised drag forces acting on the droplet are represented via graphs for different values of relative viscosity, droplet-to-cavity radii ratio, and the parameter that connects the tangential couple stress with microrotation. The normalised drag force is found to be a monotonically increasing function of the drop-to-cavity radii ratio. It is found that when the droplet-to-cavity radii ratio approaches zero, there is a very strong interaction between the droplet and the cavity. When comparing a solid sphere to a gas bubble, the normalised drag force is larger. Additionally, the results showed that permitting spin and slip at the cavity’s interior surface improved the wall correction factor influencing the droplet. The present study is important in the fields of natural, industrial, and biomedical processes such as raindrop formation, liquid–liquid extraction, suspension rheology, sedimentation, coagulation, and the motion of blood cells in an artery or vein.
Validated frailty measures using electronic primary care records: a review of diagnostic test accuracy
Authors: Brack Carmen , Kynn Mary , Murchie Peter , Makin Stephen 
Published: November 2023

Abstract

Introduction
Identification of people who have or are at risk of frailty enables targeted interventions, and the use of tools that screen for frailty using electronic records (which we term as validated electronic frailty measures (VEFMs)) within primary care is incentivised by NHS England. We carried out a systematic review to establish the sensitivity and specificity of available primary care VEFMs when compared to a reference standard in-person assessment.

Methods
Medline, Pubmed, CENTRAL, CINHAL and Embase searches identified studies comparing a primary care VEFM with in-person assessment. Studies were quality assessed using Quality Assessment of Diagnostic Accuracy Studies revised tool. Sensitivity and specificity values were extracted or were calculated and pooled using StatsDirect.

Results
There were 2,245 titles screened, with 10 studies included. These described three different index tests: electronic frailty index (eFI), claims-based frailty index (cFI) and polypharmacy. Frailty Phenotype was the reference standard in each study. One study of 60 patients examined the eFI, reporting a sensitivity of 0.84 (95% CI = 0.55, 0.98) and a specificity of 0.78 (0.64, 0.89). Two studies of 7,679 patients examined cFI, with a pooled sensitivity of 0.48 (95% CI = 0.23, 0.74) and a specificity of 0.80 (0.53, 0.98). Seven studies of 34,328 patients examined a polypharmacy as a screening tool (defined as more than or equal to five medications) with a pooled sensitivity of 0.61 (95% CI = 0.50, 0.72) and a specificity of 0.66 (0.58, 0.73).

Conclusions
eFI is the best-performing VEFM; however, based on our analysis of an average UK GP practice, it would return a high number of false-positive results. In conclusion, existing electronic frailty tools may not be appropriate for primary care-based population screening.
Contemporary Trends in Antiseptic Pocket Rinse in Primary Breast Implant Surgery
Authors: Leow Sean Kwang Howe , Knight Robert John William 
Published: November 2023

Abstract

Background
Broad evidence supports the use of antiseptic pocket rinse in breast implant surgery to minimize the risk of capsular contracture or other complications. However, there is limited consensus or standardization of antiseptic rinse in practice.

Objectives
In this preliminary study, we sought to determine contemporary trends in antiseptic rinse use in primary breast implant surgery based on Australian Breast Device Registry (ABDR) data, and whether these trends align with the suggestions of the 14-point plan. This further served as a feasibility study for subsequent comparison of antiseptic rinse effects on clinical outcomes.

Methods
Institutional ethics approval was obtained and national ABDR data for primary breast implant surgery from 2015 to 2020 were analyzed for the use and type of antiseptic rinse. The surgeon-reported data were homogenized with regard to terminology and categorized by major trends, and the literature was reviewed.

Results
We analyzed data for 37,143 patients, totaling 73,935 primary implants. Antiseptic rinse included povidone-iodine (PVP-I) in 35,859 (48.5%), no antiseptic use in 24,216 (32.8%), other concentrations of PVP-I in 4200 (5.7%), and Betadine triple antibiotic in 1831 implants (2.5%). Multiple other antiseptic permutations were noted in 7004 implants (9.5%).

Conclusions
The majority (56.7%) of Australian practitioners utilize previously described antiseptic pocket irrigation solutions that align with the 14-point plan. A third (32.8%), however, do not record any antiseptic pocket irrigation. These findings will permit a subsequent (ongoing) study of outcomes comparing PVP-I pocket rinse to no antiseptic pocket rinse, which will likely constitute the largest study of its kind.
ChromaX: a fast and scalable breeding program simulator
Authors: Younis Omar G , Turchetta Matteo , Ariza Suarez Daniel , Yates Steven , Studer Bruno , Athanasiadis Ioannis N , Krause Andreas , Buhmann Joachim M , Corinzia Luca 
Published: November 2023

Abstract

Summary
ChromaX is a Python library that enables the simulation of genetic recombination, genomic estimated breeding value calculations, and selection processes. By utilizing GPU processing, it can perform these simulations up to two orders of magnitude faster than existing tools with standard hardware. This offers breeders and scientists new opportunities to simulate genetic gain and optimize breeding schemes.

Availability and implementation
The documentation is available at https://chromax.readthedocs.io. The code is available at https://github.com/kora-labs/chromax.
Fine-scale phylogeography of the Japanese Genji firefly
Authors: Suzuki Tomoya , Hiraishi Naoki , Ohba Shin-ya 
Published: November 2023

Abstract
The Japanese Archipelago consists of four major islands and numerous small islands. The Goto Islands are located near Kyushu, a major island in the Japanese Archipelago. We have previously reported that the population of the Japanese Genji firefly, Nipponoluciola cruciata, inhabiting the Goto Islands displays a unique flashing pattern that is used for pre-mating communication between males and females, indicating the possibility of genetic isolation of the Goto Islands population from neighbouring N. cruciata populations. In this study, we aimed to elucidate the gene flow between the Goto Islands N. cruciata population and its neighbouring island populations by molecular phylogenetic analyses based on the mitochondrial DNA regions of cytochrome c oxidase subunit II and ND5, also coupled to genome-wide analysis of nuclear DNA single nucleotide polymorphisms. Our results suggested that the Goto Islands N. cruciata population is genetically isolated from other populations of this species. Nuclear DNA-based population analyses indicated gene flow between the populations inhabiting the Kyushu and Iki Islands, situated at a distance approximately equal to that between the Goto and Kyushu Islands. Therefore, the genetic isolation of the Goto Islands N. cruciata population is largely affected by flashing pattern behaviour, underlining an ongoing speciation process.
Reducing re-excision rates in breast conserving surgery with Margin Probe: systematic review
Authors: Rossou Chara , Alampritis Georgios , Patel Bijendra 
Published: November 2023

Abstract

Introduction
Different intraoperative techniques with varying levels of evidence are available to decrease positive surgical margins during breast conserving surgery. The aim of this review is to assess the effectiveness of the MarginProbe® device as an intraoperative adjunct tool in reducing positive surgical margins, and subsequently exploring the effect on patient re-excision rates.

Methodology
A systematic review of the available medical literature was conducted from 2007 to March 2022. A literature search of Cochrane, PubMed and Embase by two independent reviewers reviwers was performed to identify eligible articles looking at the primary outcome of percentage reduction in patient re-excision rates using MarginProbe®. Secondary outcomes analysed were comparison of tissue volume removed, absolute and relative reduction in re-excision rate, cosmetic outcome, as well as MarginProbe® sensitivity and specificity.

Results
A total of 12 full text articles were identified. An independent samples t-test using a total of 2680 patients found a 54.68 per cent reduction in re-excision rate with the use of MarginProbe®, which was statistically significant with a large effect size (P &lt; 0.001; d = 1.826). Secondary outcomes showed a relatively higher sensitivity of the MarginProbe® device, at the expense of decreased specificity, and no significant impact on cosmesis and volume of breast tissue excised.

Conclusion
MarginProbe® is an effective intraoperative adjunct in breast-conservation surgery that reduces patient re-excision rates, with no adverse effects relating to breast cosmesis or increase in volume of excised tissue.