bluuebunny/crossref_metadata_2025_split huggingface dataset:
Catchment-scale variability and driving factors of fine sediment deposition: insights from a coupled experimental and machine-learning-based modeling study
Authors: Grangeon Thomas , Gracianne Cécile , Favreau Yvonnick , Vandromme Rosalie , Dupeux Grégory , Cerdan Olivier , Rohmer Jérémy , Evrard Olivier , Salvador-Blanes Sébastien 
Published: April 2023

AbstractPurposeFine sediment deposition is an important component of the catchment sediment budget and affects river morphology, biology, and contaminant transfer. However, the driving factors of fine sediment deposition remain poorly understood at the catchment scale, limiting our ability to model this process.MethodsFine sediment deposition and river reach characteristics were collected over the entire river network of three medium-sized (200–2200 km2) temperate catchments, corresponding to 11,302 river reaches. This unique database was analyzed and used to develop and evaluate a random forest model. The model was used to predict sediment deposition and analyze its driving factors.ResultsFine sediment deposition displayed a high spatial variability and a weak but significant relationship with the Strahler order and river reach width (Pearson coefficient r =  −0.4 and 0.4, respectively), indicating the likely nonlinear influence of river reach characteristics. The random forest model predicted fine sediment deposition intensity with an accuracy of 81%, depending on the availability of training data. Bed substrate granularity, flow condition, reach depth and width, and the proportion of cropland and forest were the six most influential variables on fine sediment deposition intensity, suggesting the importance of both hillslope and within-river channel processes in controlling fine sediment deposition.ConclusionThis study presented and analyzed a unique dataset. It also demonstrated the potential of random forest approaches to predict fine sediment deposition at the catchment scale. The proposed approach is complementary to measurements and process-based models. It may be useful for improving the understanding of sediment connectivity in catchments, the design of future measurement campaigns, and help prioritize areas to implement mitigation strategies.
An audit of secondary prevention for peripheral arterial disease in primary care — scope for improved collaboration between vascular surgery and general practitioners
Authors: Foley Megan Power , Tubassam Muhammad , Walsh Stewart R. 
Published: April 2023

Abstract
Background
Symptomatic peripheral arterial disease (PAD) is a common cause for referral from primary care to vascular surgery. Best medical therapy (BMT), encompassing anti-platelets, statins, smoking cessation, blood pressure and glycaemic control, is a cornerstone of PAD management. However, these easily modifiable risk factors are often left unaddressed between referral and clinic review.

Methods
A prospective audit of electronic ‘Healthlink’ referrals by GPs to the vascular department for symptomatic PAD between July 2021 and June 2022 was performed. Referrals were individually reviewed for demographics, symptoms, medical history, smoking status and medications. An information leaflet on BMT was posted to all GP practices in the Soalta region as part of an educational intervention, with plans to re-audit after 6 months.

Results
One-hundred-and-seventy referrals were analysed. The median age was 68.5 years (range 33–94) and 69% (n = 117) were male. The typical vasculopath comorbidity profile was noted. Fifty-two percent (n = 88) were referred with claudication-type pain and 25% (n = 43) with critical limb ischaemia (CLI). Twenty-eight percent (n = 33) were active smokers and 31% (n = 36) had no smoking status documented. Regarding BMT, only 34.5% (n = 40) and 52% (n = 60) were on anti-platelets and statins, respectively. Suspected CLI was not significantly associated with BMT prescription at referral (p = 0.664). Only eleven referral letters mentioned risk factor optimisation.

Conclusions
Our first-cycle results identified significant scope for improvement in community-based risk factor modification for PAD referrals. We aim to continue supporting and educating our colleagues that effective medical management can start safely in primary care and further explore the barriers preventing this.
Uniform-in-phase-space data selection with iterative normalizing flows
Authors: Hassanaly Malik , Perry Bruce A. , Mueller Michael E. , Yellapantula Shashank 
Published: April 2023

Abstract
Improvements in computational and experimental capabilities are rapidly increasing the amount of scientific data that are routinely generated. In applications that are constrained by memory and computational intensity, excessively large datasets may hinder scientific discovery, making data reduction a critical component of data-driven methods. Datasets are growing in two directions: the number of data points and their dimensionality. Whereas dimension reduction typically aims at describing each data sample on lower-dimensional space, the focus here is on reducing the number of data points. A strategy is proposed to select data points such that they uniformly span the phase-space of the data. The algorithm proposed relies on estimating the probability map of the data and using it to construct an acceptance probability. An iterative method is used to accurately estimate the probability of the rare data points when only a small subset of the dataset is used to construct the probability map. Instead of binning the phase-space to estimate the probability map, its functional form is approximated with a normalizing flow. Therefore, the method naturally extends to high-dimensional datasets. The proposed framework is demonstrated as a viable pathway to enable data-efficient machine learning when abundant data are available.
Understanding L2-derived words in context: Is complete receptive morphological knowledge necessary?
Authors: Laufer Batia 
Published: April 2023

AbstractThe study investigates whether comprehension of derived words in text context requires a complete understanding of word parts. It explores comprehension of derived words as a function of learner proficiency and contextual clues. Ninety English-as-a-foreign-language learners at three proficiency levels participated in three successive tests representing three clues conditions, absence of clues, availability of syntactic clues, and availability of syntactic and semantic clues. They had to supply the meaning of 22 derived pseudowords constructed with nonword stems and 22 frequent affixes—for example, stacement, gummful. The meanings of the nonword stems were provided. Test scores were compared by 3 (proficiency level) × 3 (clue condition) analysis of variance with repeated measures. The results showed effects of both variables, proficiency and clues. The largest increase in comprehension scores occurred with the addition of syntactic clues. The results imply that derived forms of familiar base words can be understood even when learners’ receptive morphological knowledge is not complete.
Collision risk quantification for pairs of recorded aircraft trajectories
Authors: Kallinen Valtteri , Barry Steve , McFadyen Aaron 
Published: April 2023

AbstractComplex domestic airspace requires collision risk models and monitoring tools suitable for arbitrary aircraft trajectories. This paper presents a new mathematically based collision risk approach that extends the International Civil Aviation Organisation (ICAO) models to full aircraft encounters based on real trajectory data. A new continuous time intervention model is presented, along with a position uncertainty propagation model that better reflects aircraft behaviour and allows generalisation to all trajectories to eliminate degenerate cases. The proposed risk model is computationally efficient compared to the models it is based on and can be applied to large-scale trajectory data. The utility of the model is demonstrated through a series of case studies using real aircraft trajectories.
Enhanced Dependence of China's Vegetation Activity on Soil Moisture Under Drier Climate Conditions
Authors: Zhao Fubo , Wang Xi , Wu Yiping , Sivakumar Bellie , Liu Shuguang 
Published: April 2023

AbstractVegetation growth is known to be largely dependent on the availability of soil moisture (SM), yet the changes in response to climate change are still not clear. Here, we use the long‐term satellite‐observed normalized difference vegetation index (NDVI) and reanalysis SM to examine changes in the dependence of vegetation on SM across the vegetated lands of China during 1982–2015. The results show that the strength of the relationship between the interannual variability of the growing season NDVI and SM (partial correlation coefficient RSM‐NDVI) significantly increased in over 45% land fractions from 1982 to 2015. The strongest increasing trend occurred in the originally SM‐dependent areas, indicating an enhancing regime. The increase in RSM‐NDVI coincided with a decrease in precipitation and SM, highlighting the key role of drying in driving the increase in RSM‐NDVI. We also demonstrate that North China is a hotspot region which is more vulnerable to soil dryness. Our findings would be valuable for vegetation planning and management in China under future drying and intensified drought conditions.
TAX1BP1 contributes to deoxypodophyllotoxin-induced glioma cell parthanatos via inducing nuclear translocation of AIF by activation of mitochondrial respiratory chain complex I
Authors: Wang Xuan-zhong , Liang Shi-peng , Chen Xi , Wang Zhen-chuan , Li Chen , Feng Chun-sheng , Lu Shan , He Chuan , Wang Yu-bo , Chi Guang-fan , Ge Peng-fei 
Published: April 2023

AbstractParthanatos is a type of programmed cell death initiated by over-activated poly (ADP-ribose) polymerase 1 (PARP1). Nuclear translocation of apoptosis inducing factor (AIF) is a prominent feature of parthanatos. But it remains unclear how activated nuclear PARP1 induces mitochondrial AIF translocation into nuclei. Evidence has shown that deoxypodophyllotoxin (DPT) induces parthanatos in glioma cells via induction of excessive ROS. In this study we explored the downstream signal of activated PARP1 to induce nuclear translocation of AIF in DPT-triggered glioma cell parthanatos. We showed that treatment with DPT (450 nM) induced PARP1 over-activation and Tax1 binding protein 1 (TAX1BP1) distribution to mitochondria in human U87, U251 and U118 glioma cells. PARP1 activation promoted TAX1BP1 distribution to mitochondria by depleting nicotinamide adenine dinucleotide (NAD+). Knockdown of TAX1BP1 with siRNA not only inhibited TAX1BP1 accumulation in mitochondria, but also alleviated nuclear translocation of AIF and glioma cell death. We demonstrated that TAX1BP1 enhanced the activity of respiratory chain complex I not only by upregulating the expression of ND1, ND2, NDUFS2 and NDUFS4, but also promoting their assemblies into complex I. The activated respiratory complex I generated more superoxide to cause mitochondrial depolarization and nuclear translocation of AIF, while the increased mitochondrial superoxide reversely reinforced PARP1 activation by inducing ROS-dependent DNA double strand breaks. In mice bearing human U87 tumor xenograft, administration of DPT (10 mg· kg−1 ·d−1, i.p., for 8 days) markedly inhibited the tumor growth accompanied by NAD+ depletion, TAX1BP1 distribution to mitochondria, AIF distribution to nuclei as well as DNA DSBs and PARP1 activation in tumor tissues. Taken together, these data suggest that TAX1BP1 acts as a downstream signal of activated PARP1 to trigger nuclear translocation of AIF by activation of mitochondrial respiratory chain complex I.
Genotyping of Mycobacterium tuberculosis complex isolated from humans and animals in northeastern Iran
Authors: Ghazvini Kiarash , Khoshbakht Reza , Tadayon Keyvan , Mosavari Nader , BahramiTaghanaki Hamid Reza , Mohammadi Gholam Reza , Rashti Baf Mohammad , Nourian Kimiya , Samiei Amin , Ghavidel Mahdis 
Published: April 2023

AbstractThe objective of this study was to genotype Mycobacterium tuberculosis complex isolated from humans and cattle in northern Iran. Over the course of one year, a total of 120 human and 21 cattle isolates were tested using region of difference (RD)-based polymerase chain reaction (PCR) and mycobacterial interspersed repetitive unites-variable number tandem repeats (MIRU-VNTR). In M. tuberculosis, out of 120 isolates investigated, the most common genotype detected was NEW-1 (53.3%), followed by CAS/ Delhi (24.1%), Haarlem (5%), Beijing (4.16%), Uganda I (4.16%), S (3.3%), Ural (0.83%), TUR (0.83%), Uganda II (0.83%), Lam (0.83%) and Cameroon (0.83%). The HGDI rate was 0.9981 and the clustering rate was 10.83. Of the isolates, QUB26 had the highest allele diversity (h: 0.76), while the loci Mtub29 and MIRU24 had the lowest (h: 0). In M. Bovis, out of 123 collected tissue samples, 21 (17%) grew on culture media. The HGDI rate was 0.71 and clustering rate was 85.7%. The locus ETRC had the highest allele diversity (h: 0.45). The findings of this study suggest that there is high genetic diversity among M. tuberculosis isolates in Khorasan Razavi Province, which is consistent with similar results from other studies in other provinces in Iran and neighboring countries. This indicates that the prevalent genotypes in this study are spreading in the Middle East region. Furthermore, considering that M. Bovis isolates were identified in two clusters, it seems that all of them have a common origin and are circulating among the livestock farms in the province.
Prediction of an effective cervical ripenning in the induction of labour using vaginal dinoprostone
Authors: López Jiménez Nuria , García Sánchez Fiamma , Pailos Rafael Hernández , Rodrigo Álvaro Valentin , Pascual Pedreño Ana , Moreno Cid María , Hernández Martínez Antonio , Molina Alarcón Milagros 
Published: April 2023

AbstractTo develop a predictive model for successful cervical ripening in women that undergo induction of labour by means of a vaginal prostaglandin slow-release delivery system (Propess®). Prospective observational study on 204 women that required induction of labour between February 2019 and May 2020 at “La Mancha Centro” hospital in Alcázar de San Juan, Spain. The main variable studied was effective cervical ripening (Bishop score > 6). Using multivariate analysis and binary logistic regression, we created three initial predictive models (model A: Bishop Score + Ultrasound cervical length + clinical variables (estimated fetal weight, premature rupture of membranes and body mass index)); model B: Ultrasound cervical lenght + clinical variables; and model C: Bishop score + clinical variables) to predict effective cervical ripening. All three predictive models obtained (A, B and C) presented good predictive capabilities, with an area under the ROC curve ≥ 0.76. Predictive model C, composed of the variables: gestational age (OR 1.55, 95% CI 1.18–2.03, p = 0.002), premature rupture of membranes (OR 3.21 95% CI 1.34–7.70, p = 0.09) body mass index (OR 0.93, 95% CI 0.87–0.98, p = 0.012), estimated fetal weight (OR 0.99, 95% CI 0.99–1.00, p = 0.068) and Bishop score (OR 1.49 95% CI 1.18–1.81, p = 0.001), is presented as the model of choice with an area under the ROC curve of 0.76 (95% CI 0.70–0.83, p < 0.001). A predictive model composed of the variables: gestational age, premature rupture of membranes, body mass index, estimated fetal weight and Bishop score upon admission presents good capabilities in predicting successful cervical ripening following administration of prostaglandins. This tool could be useful in making clinical decisions with regard to induction of labour.
Fully distributed event‐triggered consensus control for linear multiagent systems under DoS attacks
Authors: Du Shengli , Sheng Hong , Sun Hao‐Yuan 
Published: April 2023

AbstractThis article investigates the event‐triggered consensus problem of general linear multiagent systems with denial‐of‐service (DoS) attacks. A distributed event‐triggered mechanism is presented to alleviate the limited communication resources, the designed mechanism is fully distributed owing to the introduction of some adaptive parameters. Moreover, since the DoS attacks have been considered in the event‐triggered rule design, a switching strategy for the adaptive parameters is adopted. A switching Lyapunov function is used to strictly demonstrate that secure consensus can be reached effectively under the proposed control mechanism. The quantitative relationship between the frequency of the DoS attacks and the consensus is also presented. Moreover, the Zeno behaviour can be excluded for the studied close‐looped systems. Finally, a numerical simulation example is given to demonstrate the validity of the designed control law.
A robust beamforming for MIMO radar against virtual array steering vector mismatch
Authors: Gao Yongchan , Jing Pucheng , Liao Guisheng , Zuo Lei 
Published: April 2023

AbstractThis letter considers the problem of beamforming in multiple‐input multiple‐output (MIMO) radar. The mismatch phenomenon of MIMO radar virtual array steering vector is addressed, which can better describe the mismatch characteristics of not only one‐way transmitting or receiving path but also the whole transmit‐receive path for a collocated MIMO radar. Then, a new robust beamforming method for MIMO radar against virtual array steering vector mismatch is proposed. The object function of this robust MIMO radar beamformer is constructed from an infinite norm of the output data, which is solved by linear programming. The performance of the proposed beamformer is verified by simulation results. Numerical results illustrate that proposed beamformer exhibits good performance improvement in virtual array steering vector mismatch compared to conventional methods.
Activity‐related multifractal properties of Wi‐Fi signals
Authors: Bjelica Milan , Slavković Nikola 
Published: April 2023

AbstractIn wireless local area networks (WLANs) compliant with the IEEE 802.11n standard, channel state information (CSI) is known to embed information about the surrounding environment, including the positions and movements of people. So far, this information has been inferred by exploiting certain temporal and spectral features of the related WLAN signals. In this letter, their multifractal, i.e. structural properties are examined by means of detrended fluctuation analysis. Preliminary results support the claims that (a) CSI traces exhibit multifractal properties and (b) these are influenced by human presence and activity/posture within the room.
Power disturbance waveform analysis and proactive application in power systems
Authors: Xiao Xianyong , Zhou Yi , Zhang Wenhai , Wang Yang , Zheng Zixuan , Hu Wenxi 
Published: April 2023

AbstractPower disturbances, defined as the waveform distortion of a power system under normal or abnormal conditions, contain considerable system and equipment state information. Obtaining equipment and system state information from power disturbance is very important to ensure the safety of power grids. To adapt to the development of power electronics, informatisation and digitisation of power systems, several applications with waveform‐recording devices have obtained large amounts of disturbance waveform data, laying an important foundation for the analysis and application of power disturbance waveform data. First, typical disturbance waveform monitoring devices and a disturbance trigger detection algorithm are introduced. Then, disturbances are classified as switching, fault, or abnormal operations, according to the cause. The characteristics of various typical disturbance waveform data were analysed by combining the simulation and measured data. This paper summarises the application analysis of power disturbance waveform data at both the system and equipment levels. Finally, the construction scheme of a power disturbance waveform data monitoring and analysis platform for two different application scenarios was proposed for commutation failure monitoring and medium‐voltage distribution network fault warning. The research conducted here is expected to support the construction of a power disturbance waveform analysis platform.
Adversarial discriminative domain adaptation for modulation classification based on Ulam stability
Authors: Ren Wenjuan , Chen Qian , Yang Zhanpeng 
Published: April 2023

AbstractDomain adaptation modulation classification aims to improve the cross‐domain robustness of modulation classification, with the basic idea of mitigating the domain shift between the label‐rich source domain and label‐poor target domain in the latent common feature subspace. Due to the complex and heterogeneous wireless propagation conditions, how to construct the optimal latent common feature subspace is a hard problem. In this letter, the authors introduce Ulam stability to character the boundary of the latent common feature space. These theorems can provide guidance for cross‐domain feature extraction and eliminate the domain shift. Based on the proposed stable theorems, the authors define the Ulam loss and present a new method named Adversarial Discriminative Domain Adaptation with Ulam stability (U‐ADDA). Experiments on public datasets prove the effectiveness and generality of the method.
Chromosome instability‐associated prognostic signature and cluster investigation for cutaneous melanoma cases
Authors: Liu Ning , Liu Guangjing , Ma Qian , Li Xiaobing 
Published: April 2023

AbstractChromosomal instability (CIN) is closely associated to the early detection of several clinical tumours. In this study, the authors first established a novel prognostic model of melanoma using the hub genes of CIN, based on the datasets of The cancer genome atlas‐skin cutaneous melanoma (TCGA‐SKCM) and GSE65904 cohorts. Based on the risk scores of our model, the disease‐specific survival (DSS) prognosis was worse in the high‐risk group. Combining risk score, stage, age, ulceration, and clark factors, a Nomogram was generated to predict 1, 3, 5‐year survival rates, which indicated a good clinical validity. Our finding also showed a correlation between high/low risk and tumour infiltration levels of ‘activated CD8 T cells’ and ‘effector memory CD8 T cells’. Moreover, the authors first performed a CIN‐based tumour clustering analysis using TCGA‐SKCM cases, and identified two melanoma clusters, which exhibit the distinct DSS prognosis and the tumour‐infiltrating levels of CD8 T cells. Taken together, a promising CIN‐related prognostic signature and clustering for melanoma cases were first established in our study.