bluuebunny/crossref_metadata_2025_split huggingface dataset:
A revisit of the normalized eight-point algorithm and a self-supervised deep solution
Authors: Fan Bin , Dai Yuchao , Seo Yongduek , He Mingyi 
Published: February 2024

AbstractThe normalized eight-point algorithm has been widely viewed as the cornerstone in two-view geometry computation, where the seminal Hartley’s normalization has greatly improved the performance of the direct linear transformation algorithm. A natural question is, whether there are and how to find other normalization methods that can further improve the performance for each input sample. In this paper, we provide a novel perspective and propose two contributions to this fundamental problem: (1) we revisit the normalized eight-point algorithm and make a theoretical contribution by presenting the existence of different and better normalization algorithms; (2) we introduce a deep convolutional neural network with a self-supervised learning strategy for normalization. Given eight pairs of correspondences, our network directly predicts the normalization matrices, thus learning to normalize each input sample. Our learning-based normalization module can be integrated with both traditional (e.g., RANSAC) and deep learning frameworks (affording good interpretability) with minimal effort. Extensive experiments on both synthetic and real images demonstrate the effectiveness of our proposed approach.
Adaptive neural network anti-disturbance control of a cable-driven flexible-joint-based underwater vehicle manipulator system with dead-zone input nonlinearities via multiple neural observers
Authors: Wang Hongdu , Zhang Ning , Shah Umer Hameed , Li Ming , Hou Dongdong 
Published: February 2024

AbstractTo achieve the requirements of lightweight, low energy consumption, and low inertia of an underwater vehicle manipulator system, a cable-driven manipulator is installed on the underwater vehicle to form a cable-driven flexible-joint-based underwater vehicle manipulator system (CDFJ–UVMS). The CDFJ–UVMS is a complex nonlinear system subject to model uncertainties, complex marine environment disturbances, and actuator dead-zone nonlinearity. To design track controllers, the CDFJ–UVMS dynamics is divided into two parts: known and unknown. Subsequently, a radial basis function neural network is adopted to approximate the unknown nonlinearity. A neural network performance observer is constructed, whose estimation error is then used to design a novel neural disturbance observer (NDO) to estimate the total disturbance. Finally, an adaptive neural network control method is proposed for the CDFJ–UVMS based on the NDO, neural network compensator, and neural performance observer. The stability of the closed-loop system is analyzed using the Lyapunov method. The proposed control algorithm is applied to a CDFJ–UVMS with two cable-driven joints and compared with other control methods to show the effectiveness of the proposed control algorithm.
Multi-scale spatial features and temporal attention mechanisms: advancing the accuracy of ENSO prediction
Authors: Tao Shengen , Li Yanqiu , Gao Feng , Fan Hao , Dong Junyu , Gan Yanhai 
Published: February 2024

AbstractThe exponential progression in oceanic observational technology has fostered the accumulation of substantial time series data pivotal for predictions in ocean meteorology. Foremost among the phenomena observed is El Niño-Southern Oscillation (ENSO), a critical determinant in the interplay of global ocean atmosphere interactions, with its severe manifestations inducing extreme meteorological conditions. Therefore, precisely predicting ENSO events carries immense gravitas. Historically, predictions hinged primarily on dynamic models and statistical approaches; however, the intricate and multifaceted spatiotemporal dynamics of ENSO events have often impeded the accuracy of these traditional methodologies. A notable lacuna in contemporary research is the insufficient exploration of long-term dependencies within oceanic data and the suboptimal integration of spatial information derived from spatiotemporal data. To address these limitations, this study introduces a forward-thinking ENSO prediction framework synergizing multiscale spatial features with temporal attention mechanisms. This innovation facilitates a more profound exploration of temporal and spatial domains, enhancing the retention of extensive-period data while optimizing the use of spatial information. Preliminary analyses executed on the global ocean data assimilation system dataset attest to the superior efficacy of the proposed method, underscoring a substantial improvement over established methods including SA-convolutional long short-term memory, particularly in facilitating long-term predictions.The source code and datasets are provided. The code is available at https://github.com/tse1998/ENSO-prediction.
WaterPairs: a paired dataset for underwater image enhancement and underwater object detection
Authors: Chen Long , Dong Xirui , Xie Yunzhou , Wang Sen 
Published: February 2024

AbstractDue to its importance in marine engineering and aquatic robotics, underwater image enhancement works as a preprocessing step to improve the performance of high-level vision tasks such as underwater object detection and recognition. Although several studies exhibit that underwater image enhancement algorithms can boost the detection accuracy of detectors, no work has focused on studying the relationship between these two tasks. This is mainly because current underwater datasets lack either bounding box annotations or high-quality reference images, based on which detection accuracy or image quality assessment metrics are calculated. To examine how underwater image enhancement methods affect underwater object detection tasks, we provide a large-scale underwater object detection dataset with both bounding box annotations and high-quality reference images, namely, the WaterPairs dataset. The WaterPairs dataset offers a platform for researchers to comprehensively study the influence of underwater image enhancement algorithms on underwater object detection tasks. We will release our dataset at https://github.com/IanDragon/WaterPairs once this paper is accepted.
Validity of matched-field source localization in under-ice shallow water
Authors: Liu Chonglei , Zhang Yangfan , Yin Li , Huang Haining 
Published: February 2024

AbstractUnderwater source localization, such as matched-field processing (MFP), triangulation, and waveguide invariant, have been extensively investigated in temperate oceans. Seasonal or yearlong ice floes or ice cover exist in high-latitude sea regions and the polar ocean. In under-ice shallow water, sound interacts frequently with ice and sea bottom, which results in dramatic reflection, attenuation, and modal dispersion. The boundary effects generate more uncertainties in model-based source localization methods, for example, the MFP method. In this work, we develop the preliminary scheme of the under-ice MFP. The performances of the incoherent Bartlett and minimum variance algorithms are verified by real data collected by a 12-element Vertical line array with a space of 1 m for a source (650–750 Hz) at 2.7-km range and 5-m depth in the northern Yellow Sea in winter. The experimental findings demonstrate that the range error is within 2% and the depth error is within 10%. The error primarily originates from the uncertainty of sea bottom parameters.
Spatially Resolved Observations of Meteor Radio Afterglows With the OVRO‐LWA
Authors: Varghese S. S. , Dowell J. , Obenberger K. S. , Taylor G. B. , Anderson M. , Hallinan G. 
Published: February 2024

AbstractWe conducted an all‐sky imaging transient search with the Owens Valley Radio Observatory Long Wavelength Array (OVRO‐LWA) data collected during the Perseid meteor shower in 2018. The data collection during the meteor shower was motivated to conduct a search for intrinsic radio emission from meteors below 60 MHz known as the meteor radio afterglows (MRAs). The data collected were calibrated and imaged using the core array to obtain lower angular resolution images of the sky. These images were input to a pre‐existing LWA transient search pipeline to search for MRAs as well as cosmic radio transients. This search detected 5 MRAs and did not find any cosmic transients. We further conducted peeling of bright sources, near‐field correction, visibility differencing and higher angular resolution imaging using the full array for these 5 MRAs. These higher angular resolution images were used to study their plasma emission structures and monitor their evolution as a function of frequency and time. With higher angular resolution imaging, we resolved the radio emission size scales to less than 1 km physical size at 100 km heights. The spectral index mapping of one of the long duration event showed signs of diffusion of plasma within the meteor trails. The unpolarized emission from the resolved radio components suggest resonant transition radiation as the possible radiation mechanism of MRAs.
An Improved Stochastic Model for the Geodetic GNSS Receivers Under Ionospheric Scintillation at Low Latitudes
Authors: Luo Xiaomin , Lin Yingzong , Dai Xiaolei , Bian Shaofeng , Chen Dezhong 
Published: February 2024

AbstractThe receiver tracking error stochastic (RTES) model can improve GNSS precise point positioning (PPP) performance under ionospheric scintillation. However, it relies on scintillation products derived from ionospheric scintillation monitoring receivers (ISMRs), which means the RTES model cannot be used for abundant geodetic GNSS receivers. In this study, we propose an improved RTES, referred to as Impr_RTES model, to mitigate scintillation effects on geodetic GNSS receivers at low latitudes, where severe scintillation frequently occurs. In the Impr_RTES model, the tracking error variances at the output of code delay locked loop are calculated by using the indexS4c, and these of phase locked loop are modeled by using the rate of total electron content index (ROTI) andS4c. BothS4cand ROTI can be derived from geodetic GNSS receivers. The performance of the Impr_RTES model is validated by using the data sets from ISMR and geodetic receivers, respectively. Using one month of GPS data collected at HNLW station installed with ISMR in Hainan of China from 1 to 28 February in 2023, statistical results indicate that the PPP solution based on Impr_RTES model can improve the positioning accuracy by approximately 22.6%, 23.8%, and 30.2% in the east, north, and up directions, respectively, over the elevation angle stochastic (EAS) model. Meanwhile, the positioning performance of Impr_RTES PPP is comparable to that of RTES PPP. For the GPS data from geodetic receivers, experimental results suggest that compared with EAS, the Impr_RTES model can obviously mitigate scintillation effects on PPP.
Genomic alterations in oral multiple primary cancers
Authors: Zhou Xuan , Cai Xinjia , Jing Fengyang , Li Xuefen , Zhang Jianyun , Zhang Heyu , Li Tiejun 
Published: February 2024

AbstractOral squamous cell carcinoma (OSCC) is the predominant type of oral cancer, while some patients may develop oral multiple primary cancers (MPCs) with unclear etiology. This study aimed to investigate the clinicopathological characteristics and genomic alterations of oral MPCs. Clinicopathological data from patients with oral single primary carcinoma (SPC, n = 202) and oral MPCs (n = 34) were collected and compared. Copy number alteration (CNA) analysis was conducted to identify chromosomal-instability differences among oral MPCs, recurrent OSCC cases, and OSCC patients with lymph node metastasis. Whole-exome sequencing was employed to identify potential unique gene mutations in oral MPCs patients. Additionally, CNA and phylogenetic tree analyses were used to gain preliminary insights into the molecular characteristics of different primary tumors within individual patients. Our findings revealed that, in contrast to oral SPC, females predominated the oral MPCs (70.59%), while smoking and alcohol use were not frequent in MPCs. Moreover, long-term survival outcomes were poorer in oral MPCs. From a CNA perspective, no significant differences were observed between oral MPCs patients and those with recurrence and lymph node metastasis. In addition to commonly mutated genes such as CASP8, TP53 and MUC16, in oral MPCs we also detected relatively rare mutations, such as HS3ST6 and RFPL4A. Furthermore, this study also demonstrated that most MPCs patients exhibited similarities in certain genomic regions within individuals, and distinct differences of the similarity degree were observed between synchronous and metachronous oral MPCs.
A novel saliva-based miRNA profile to diagnose and predict oral cancer
Authors: Balakittnen Jaikrishna , Ekanayake Weeramange Chameera , Wallace Daniel F. , Duijf Pascal H. G. , Cristino Alexandre S. , Hartel Gunter , Barrero Roberto A. , Taheri Touraj , Kenny Liz , Vasani Sarju , Batstone Martin , Breik Omar , Punyadeera Chamindie 
Published: February 2024

AbstractOral cancer (OC) is the most common form of head and neck cancer. Despite the high incidence and unfavourable patient outcomes, currently, there are no biomarkers for the early detection of OC. This study aims to discover, develop, and validate a novel saliva-based microRNA signature for early diagnosis and prediction of OC risk in oral potentially malignant disorders (OPMD). The Cancer Genome Atlas (TCGA) miRNA sequencing data and small RNA sequencing data of saliva samples were used to discover differentially expressed miRNAs. Identified miRNAs were validated in saliva samples of OC (n = 50), OPMD (n = 52), and controls (n = 60) using quantitative real-time PCR. Eight differentially expressed miRNAs (miR-7-5p, miR-10b-5p, miR-182-5p, miR-215-5p, miR-431-5p, miR-486-3p, miR-3614-5p, and miR-4707-3p) were identified in the discovery phase and were validated. The efficiency of our eight-miRNA signature to discriminate OC and controls was: area under curve (AUC): 0.954, sensitivity: 86%, specificity: 90%, positive predictive value (PPV): 87.8% and negative predictive value (NPV): 88.5% whereas between OC and OPMD was: AUC: 0.911, sensitivity: 90%, specificity: 82.7%, PPV: 74.2% and NPV: 89.6%. We have developed a risk probability score to predict the presence or risk of OC in OPMD patients. We established a salivary miRNA signature that can aid in diagnosing and predicting OC, revolutionising the management of patients with OPMD. Together, our results shed new light on the management of OC by salivary miRNAs to the clinical utility of using miRNAs derived from saliva samples.
Hydrodynamic function and spring constant calibration of FluidFM micropipette cantilevers
Authors: Bonyár Attila , Nagy Ágoston G. , Gunstheimer Hans , Fläschner Gotthold , Horvath Robert 
Published: February 2024

AbstractFluidic force microscopy (FluidFM) fuses the force sensitivity of atomic force microscopy with the manipulation capabilities of microfluidics by using microfabricated cantilevers with embedded fluidic channels. This innovation initiated new research and development directions in biology, biophysics, and material science. To acquire reliable and reproducible data, the calibration of the force sensor is crucial. Importantly, the hollow FluidFM cantilevers contain a row of parallel pillars inside a rectangular beam. The precise spring constant calibration of the internally structured cantilever is far from trivial, and existing methods generally assume simplifications that are not applicable to these special types of cantilevers. In addition, the Sader method, which is currently implemented by the FluidFM community, relies on the precise measurement of the quality factor, which renders the calibration of the spring constant sensitive to noise. In this study, the hydrodynamic function of these special types of hollow cantilevers was experimentally determined with different instruments. Based on the hydrodynamic function, a novel spring constant calibration method was adapted, which relied only on the two resonance frequencies of the cantilever, measured in air and in a liquid. Based on these results, our proposed method can be successfully used for the reliable, noise-free calibration of hollow FluidFM cantilevers.
Insights and implications of sexual dimorphism in osteoporosis
Authors: Zhang Yuan-Yuan , Xie Na , Sun Xiao-Dong , Nice Edouard C. , Liou Yih-Cherng , Huang Canhua , Zhu Huili , Shen Zhisen 
Published: February 2024

AbstractOsteoporosis, a metabolic bone disease characterized by low bone mineral density and deterioration of bone microarchitecture, has led to a high risk of fatal osteoporotic fractures worldwide. Accumulating evidence has revealed that sexual dimorphism is a notable feature of osteoporosis, with sex-specific differences in epidemiology and pathogenesis. Specifically, females are more susceptible than males to osteoporosis, while males are more prone to disability or death from the disease. To date, sex chromosome abnormalities and steroid hormones have been proven to contribute greatly to sexual dimorphism in osteoporosis by regulating the functions of bone cells. Understanding the sex-specific differences in osteoporosis and its related complications is essential for improving treatment strategies tailored to women and men. This literature review focuses on the mechanisms underlying sexual dimorphism in osteoporosis, mainly in a population of aging patients, chronic glucocorticoid administration, and diabetes. Moreover, we highlight the implications of sexual dimorphism for developing therapeutics and preventive strategies and screening approaches tailored to women and men. Additionally, the challenges in translating bench research to bedside treatments and future directions to overcome these obstacles will be discussed.
Dispersion curve engineering for automated topology design of a unit cell in spoof surface plasmon polaritons
Authors: Mirhadi Salma , Javidi Zahra , Komjani Nader 
Published: February 2024

AbstractIn this paper, an automatic design method is proposed for unit cell in spoof surface plasmon polaritons (SSPP) with an almost arbitrary dispersion curve. In this method, the pixel configuration is considered for the unit cell and, by using the binary particle swarm optimization method, the proper topology of the unit cell is explored so as to reach the target dispersion curve. Unlike the traditional method of controlling the dispersion curve, which is performed based on changing the geometric parameters of the predetermined unit cell, in this method, there is no need to know the shape of the unit cell, and the dispersion curve of the modes of SSPP unit cell can be controlled independently with more freedom. Two unit cell samples are designed in order to show the efficiency of the procedure. In the first sample, the dispersion curve is designed to have the lowest asymptotic frequency; in the second sample, the dispersion curve of the second mode is controlled independently from the first mode and is changed arbitrarily. SSPP transmission lines which are related to the unit cells of the two samples are designed, and it is demonstrated that measurement and simulation results are greatly in line with each other.
Unveiling the microbial communities and metabolic pathways of Keem, a traditional starter culture, through whole-genome sequencing
Authors: Rana Babita , Chandola Renu , Sanwal Pankaj , Joshi Gopal Krishna 
Published: February 2024

AbstractTraditional alcoholic beverages have played a significant role in the cultural, social, and culinary fabric of societies worldwide for centuries. Studying the microbial community structure and their metabolic potential in such beverages is necessary to define product quality, safety, and consistency, as well as to explore associated biotechnological applications. In the present investigation, Illumina-based (MiSeq system) whole-genome shotgun sequencing was utilized to characterize the microbial diversity and conduct predictive gene function analysis of keem, a starter culture employed by the Jaunsari tribal community in India for producing various traditional alcoholic beverages. A total of 8,665,213 sequences, with an average base length of 151 bps, were analyzed using MG-RAST. The analysis revealed the dominance of bacteria (95.81%), followed by eukaryotes (4.11%), archaea (0.05%), and viruses (0.03%). At the phylum level, Actinobacteria (81.18%) was the most abundant, followed by Firmicutes (10.56%), Proteobacteria (4.00%), and Ascomycota (3.02%). The most predominant genera were Saccharopolyspora (36.31%), followed by Brevibacterium (15.49%), Streptomyces (9.52%), Staphylococcus (8.75%), Bacillus (4.59%), and Brachybacterium (3.42%). At the species level, the bacterial, fungal, and viral populations of the keem sample could be categorized into 3347, 57, and 106 species, respectively. Various functional attributes to the sequenced data were assigned using Cluster of Orthologous Groups (COG), Non-supervised Orthologous Groups (NOG), subsystem, and KEGG Orthology (KO) annotations. The most prevalent metabolic pathways included carbohydrate, lipid, and amino acid metabolism, as well as the biosynthesis of glycans, secondary metabolites, and xenobiotic biodegradation. Given the rich microbial diversity and its associated metabolic potential, investigating the transition of keem from a traditional starter culture to an industrial one presents a compelling avenue for future research.
Comparison activity of pure and chromium-doped nickel oxide nanoparticles for the selective removal of dyes from water
Authors: Athab Zahraa H. , Halbus Ahmed F. , Mohammed Sura Bahaa , Atiyah Abbas J. , Ismael Hussein Idrees , Saddam Nahlah Salman , Baqir Sadiq J. , Alesary Hasan F. , Algburi Sameer , Al-Ansari Nadhir 
Published: February 2024

AbstractThe current study involves a synthesis of a composite of nickel oxide nanoparticles (NiONPs) with a chromium dopant to yield (Cr/NiONPs). Synthesis of nickel oxide was performed by the co-precipitation method. The synthesis of the composite was conducted by the impregnation method. FTIR, EDX, SEM, and XRD were used to characterize the synthesized materials. The synthesised materials’ point zero charges (PZC) were performed using the potentiometric titration method. The obtained results show that the PZC for neat nickel oxide was around 5, and it was around 8 for Cr/NiONPs. The adsorption action of the prepared materials was examined by applying them to remove Reactive Red 2 (RR2) and Crystal Violate (CV) dyes from solutions. The outcomes demonstrated that Cr/NiONPs were stronger in the removal of dyes than NiONPs. Cr/NiONPs achieved 99.9% removal of dyes after 1 h. Adsorption isotherms involving Freundlich and Langmuir adsorption isotherms were also conducted, and the outcomes indicated that the most accurate representation of the adsorption data was offered by Langmuir adsorption isotherms. Additionally, it was discovered that the adsorption characteristics of the NiONPs and Cr/NiONPs correspond well with the pseudo-second-order kinetic model. Each of the NiONPs and Cr/NiONPs was reused five times, and the results display that the effectiveness of the removal of RR2 dye slightly declined with the increase in reuse cycles; it lost only 5% of its original efficiency after the 5 cycles. Generally, Cr/NiONPs showed better reusability than NiONPs under the same conditions.