bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fully automated 18F-fluorination of N-succinimidyl-4-[18F]fluorobenzoate ([18F]SFB) for indirect labelling of nanobodies
Authors: Nagachinta Surasa , Novelli Paolo , Joyard Yoann , Maindron Nicolas , Riss Patrick , Dammicco Sylvestre 
Published: November 2022

AbstractN-succinimidyl-4-[18F]fluorobenzoate ([18F]SFB), a widely used labeling agent to introduce the 4-[18F]fluorobenzoyl-prosthetic group, is normally obtained in three consecutive steps from [18F]fluoride ion. Here, we describe an efficient one-step labeling procedure of [18F]SFB starting from a tin precursor. This method circumvents volatile radioactive side-products and simplifies automatization. [18F]SFB was obtained after HPLC purification in a yield of 42 + 4% and a radiochemical purity (RCP) > 99% (n = 6). In addition, we investigate the automation of the coupling of [18F]SFB to a nanobody (cAbBcII10, targeting β-lactamase enzyme) and purification by size exclusion chromatography (PD-10 desalting column) to remove unconjugated reagent. Production and use of [18F]SFB were implemented on a radiosynthesis unit (Neptis®). The fully automated radiosynthesis process including purification and formulation required 160 min of synthesis time. [18F]SFB-labeled nanobody was obtained in a yield of 21 + 2% (activity yield 12 + 1% non-decay corrected) and a radiochemical purity (RCP) of > 95% (n = 3). This approach simplifies [18F]SFB synthesis to one-step, enhances the yield in comparison to the previous report and enables the production of radiolabeled nanobody on the same synthesis module.
Evaluation modeling of highway collapse hazard based on rough set and support vector machine
Authors: He Hujun , Quan Guorong , Zhu Haolei , Li Wei , Xing Rui , Zhao Yichen 
Published: November 2022

AbstractThe prediction of possibility and risk classification of collapse is an important issue in the process of highway construction in mountain area. Based on the principle of rough set and support vector machine, a landslide hazard prediction model was established. First of all, according to field investigation, an evaluation index system and a sample set of evaluation index data were established, the rough set decision table was constructed by preprocessing the original data based on the function classification of standard evaluation index, and then, the influence indexes of the collapse activity were reduced by rough set theory, and the main 9 indexes affecting the collapse activity as the key discriminant factors of support vector machine model, namely slope shape of slope, aspect of slope, slope of slope, height of slope, exposed structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate and weathering degree of rock were extracted. Then, taking the data of 13 post earthquake collapses in Yingxiu-Wolong highway of Hanchuan County measured by the authors in the field as training samples, the optimal model parameters were analyzed and calculated. When the penalty parameter $$C$$
C
is 8 and the kernel parameter $$\sigma$$
σ
is 0.5, the correct rate of cross-validation is 100%, and the model is optimal. At last, 4 other landslide data were tested, the discriminant results of the test sample data were compared with the results obtained by uncertainty measure and distance discriminant analysis. The results show that the discriminant results of the test sample data by RS-SVM were consistent with the results obtained by uncertainty measure and distance discriminant analysis, the accurate rate is 100%. The collapse hazard analysis model based on rough set and support vector machine can reduce the computation while ensuring the accuracy of evaluation, and better solve the small sample and nonlinear problems, can provide certain a good idea for collapse hazard evaluation in the future.
Frequency of the winter temperature extremes over Siberia dominated by the Atlantic Meridional Overturning Circulation
Authors: Wang Huan , Zuo Zhiyan , Qiao Liang , Zhang Kaiwen , Sun Cheng , Xiao Dong , Lin Zouxing , Bu Lulei , Zhang Ruonan 
Published: November 2022

AbstractWidespread observed and projected increases in warm extremes, along with decreases in cold extremes, have been confirmed as being consistent with global and regional warming. Here we disclosed that the decadal variation in the frequency of the surface air temperature (SAT) extremes over Siberia in winter was primarily dominated by the Atlantic Meridional Overturning Circulation (AMOC) rather than anthropogenic forcing. The stronger AMOC induced more warm and cold extremes through increasing the variance of winter SAT over Siberia while the direct effect of external forcings, especially anthropogenic greenhouse gases, had little impact on the summation of warm and cold extremes due to equivalent effects on the increases in warm extremes and decreases in cold extremes. The possible mechanism can be deduced that the stronger AMOC stimulated the propagation of the wave train originated in the North Atlantic Ocean, across mid- to high latitudes, thereby increasing the variabilities in the circulations over the Ural blocking region and Siberia, which are critical to the SAT extremes there.
Identification of novel prognostic and predictive biomarkers in salivary duct carcinoma via comprehensive molecular profiling
Authors: Kohsaka Shinji , Tada Yuichiro , Ando Mizuo , Nakaguro Masato , Shirai Yukina , Ueno Toshihide , Kojima Shinya , Hirai Hideaki , Saigusa Natsuki , Kano Satoshi , Tsukahara Kiyoaki , Togashi Takafumi , Ozawa Hiroyuki , Kondo Takahito , Okami Kenji , Takahashi Hideaki , Kawakita Daisuke , Fushimi Chihiro , Suzuki Takayoshi , Shimizu Akira , Okamoto Isaku , Okada Takuro , Sato Yuichiro , Imanishi Yorihisa , Watanabe Yoshihiro , Sakai Akihiro , Ebisumoto Koji , Sato Yukiko , Urano Makoto , Honma Yoshitaka , Yamazaki Keisuke , Ueki Yushi , Hanazawa Toyoyuki , Saito Yuki , Shimura Tomotaka , Nagao Toshitaka , Mano Hiroyuki 
Published: November 2022

AbstractMolecular targets and predictive biomarkers for prognosis in salivary duct carcinoma (SDC) have not been fully identified. We conducted comprehensive molecular profiling to discover novel biomarkers for SDC. A total of 67 SDC samples were examined with DNA sequencing of 464 genes and transcriptome analysis in combination with the clinicopathological characteristics of the individuals. Prognostic biomarkers associated with response to combined androgen blockade (CAB) treatment were explored using mRNA expression data from 27 cases. Oncogenic mutations in receptor tyrosine kinase (RTK) genes or genes in the MAPK pathway were identified in 55 cases (82.1%). Alterations in the phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway were identified in 38 cases (56.7%). Interestingly, patient prognosis could be predicted using mRNA expression profiles, but not genetic mutation profiles. The risk score generated from the expression data of a four-gene set that includes the ADAMTS1, DSC1, RNF39, and IGLL5 genes was a significant prognostic marker for overall survival in the cohort (HR = 5.99, 95% confidence interval (CI) = 2.73–13.1, p = 7.8 × 10−6). Another risk score constructed from the expression of CD3E and LDB3 was a strong prognostic marker for progression-free survival for CAB treatment (p = 0.03). Mutations in RTK genes, MAPK pathway genes, and PI3K/AKT pathway genes likely represent key mutations in SDC tumorigenesis. The gene expression profiles identified in this study may be useful for stratifying patients who are good candidates for CAB treatment and may benefit from additional systemic therapies.
Improved winter data coverage of the Southern Ocean CO2 sink from extrapolation of summertime observations
Authors: Mackay Neill , Watson Andrew J. , Suntharalingam Parvada , Chen Zhaohui , Landschützer Peter 
Published: November 2022

AbstractThe Southern Ocean is an important sink of anthropogenic CO2, but it is among the least well-observed ocean basins, and consequentially substantial uncertainties in the CO2 flux reconstruction exist. A recent attempt to address historically sparse wintertime sampling produced ‘pseudo’ wintertime observations of surface pCO2 using subsurface summertime observations south of the Antarctic Polar Front. Here, we present an estimate of the Southern Ocean CO2 sink that combines a machine learning-based mapping method with an updated set of pseudo observations that increases regional wintertime data coverage by 68% compared with the historical dataset. Our results confirm the suggestion that improved winter coverage has a modest impact on the reconstruction, slightly strengthening the uptake trend in the 2000s. After also adjusting for surface boundary layer temperature effects, we find a 2004-2018 mean sink of −0.16 ± 0.07 PgC yr−1 south of the Polar Front and −1.27 ± 0.23 PgC yr−1 south of 35°S, consistent with independent estimates from atmospheric data.
The Severity-Calibrated Aphasia Naming Test
Authors: Walker Grant M. , Fridriksson Julius , Hillis Argye E. , den Ouden Dirk B. , Bonilha Leonardo , Hickok Gregory 
Published: November 2022

Purpose:
We present a 20-item naming test, the Severity-Calibrated Aphasia Naming Test (SCANT), that can serve as a proxy measure for an aphasia severity scale that is derived from a thorough test battery of connected speech production, single-word production, speech repetition, and auditory verbal comprehension.

Method:
We use lasso regression and cross-validation to identify an optimal subset from a set of 174 pictures to be named for prediction of aphasia severity, based on data from 200 participants with left-hemisphere stroke who were quasirandomly selected to represent the full impairment scale. Data from 20 healthy controls (i.e., participant caretakers/spouses) were also analyzed. We examine interrater reliability, test–retest reliability, sensitivity and specificity to the presence of aphasia, sensitivity to therapy gains, and external validity (i.e., correlation with aphasia severity measures) for the SCANT.

Results:
The SCANT has extremely high interrater reliability, and it is sensitive and specific to the presence of aphasia. We demonstrate the superiority of predictions based on the SCANT over those based on the full set of naming items. We estimate a 15% reduction in power when using the SCANT score versus the full test battery's aphasia severity score as an outcome measure; for example, to maintain the same power to detect a significant group average change in aphasia severity, a study with 25 participants using the full test battery to measure treatment effectiveness would require 30 participants if the SCANT were to be used as the testing instrument instead.

Conclusion:
We provide a linear model to convert SCANT scores to aphasia severity scores, and we identify a change score cutoff of four SCANT items to obtain a high degree of confidence based on test–retest SCANT data and the modeled relation between SCANT and aphasia severity scores.

Supplemental Material:

https://doi.org/10.23641/asha.21476871
Autism in the Kingdom of Saudi Arabia: Current Situation and Future Perspectives for Services and Research
Authors: Al-Dakroury Wael A. , Alnemary Fahad M. , Alnemary Faisal 
Published: November 2022

Purpose:
Autism spectrum disorder (ASD) services and research have evolved over the past decades to mitigate the negative effects of this lifelong condition on those who live with it and the society. The purpose of this article is to shed light on the current state of ASD services and research in the Kingdom of Saudi Arabia (KSA) and discuss future directions to enhance services and research in relation to accessibility and optimizing the journey of care for individuals with ASD.

Conclusions:
Background information is provided about the KSA and its role in the region as a major country to lead the advancement of ASD services, regulations, awareness, and research. ASD in KSA is gaining more attention and recognition at all levels, which will ultimately lead to larger opportunities to provide a high-quality service at the levels of diagnosis and intervention.
Retracted: Performance optimization of unstructured E‐commerce log data for activity and pattern evaluation using web analytics
Authors: Shukla Shubham , Mishra Pawan , Sinha Anurag , Garg Namit , Pandey Saroj Kumar , Raja Linesh , Kumar Ankit , Chetri Manoj 
Published: November 2022

AbstractThe above article from IET Communications, published online on 4 November 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Interim Editor‐in‐Chief, Jian Ren, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal's peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.
Exploiting spatio‐temporal knowledge for video action recognition
Authors: Zhang Huigang , Wang Liuan , Sun Jun 
Published: November 2022

AbstractAction recognition has been a popular area of computer vision research in recent years. The goal of this task is to recognise human actions in video frames. Most existing methods often depend on the visual features and their relationships inside the videos. The extracted features only represent the visual information of the current video itself and cannot represent the general knowledge of particular actions beyond the video. Thus, there are some deviations in these features, and the recognition performance still requires improvement. In this sudy, we present a novel spatio‐temporal knowledge module (STKM) to endow the current methods with commonsense knowledge. To this end, we first collect hybrid external knowledge from universal fields, which contains both visual and semantic information. Then graph convolution networks (GCN) are used to represent and aggregate this knowledge. The GCNs involve (i) a spatial graph to capture spatial relations and (ii) a temporal graph to capture serial occurrence relations among actions. By integrating knowledge and visual features, we can get better recognition results. Experiments on AVA, UCF101‐24 and JHMDB datasets show the robustness and generalisation ability of STKM. The results report a new state‐of‐the‐art 32.0 mAP on AVA v2.1. On UCF101‐24 and JHMDB datasets, our method also improves by 1.5 AP and 2.6 AP, respectively, over the baseline method.
Focusing dynamic single‐channel synthetic aperture radar video with optical flow‐informed reconstruction
Authors: Watson F. M. 
Published: November 2022

AbstractThe motion of targets is well known to result in their defocusing and displacement in SAR imagery, but detection of motion and re‐focusing of targets under generic conditions remains an ongoing interest. One class of methods involves forming images of sub‐apertures in which motion defocusing will be reduced. In this paper, dynamic tomographic image formation methods utilising an optical flow constraint is used to form a video of SAR sub‐aperture images. These retain fine resolution of the full aperture, focusing along‐track motion.
High‐precision simulation technology for enhanced Loran signal simulators based on Lagrange farrow structure filter
Authors: Ma Hongyu , Yuan Yanning , Li Zheng , Liu Jiangfan , Pu Yurong , Du Yongxing , Xi Xiaoli 
Published: November 2022

AbstractIn this study, a real‐time high accuracy signal simulation technique for an enhanced Loran (eLoran) signal simulator is proposed, which can be used to verify the performance of the eLoran receiver. The proposed method is based on a maximumly flat design of the low‐pass filter, and high simulation accuracy can be obtained in the low‐frequency band. The simulator structure is based on the variable fractional delay Farrow structure, which can regenerate eLoran signals with high‐precision time of arrival (TOA) in real‐time based on discrete samples on a hardware platform. By comparison of existing methods and the true TOA data validation, the proposed method has high performance for low‐frequency narrow‐band eLoran signals and the proposed technology can apply to arbitrary TOA real‐time simulations.
Evaluation and calibration of low‐cost off‐the‐shelf particulate matter sensors using machine learning techniques
Authors: Ghamari Mohammad , Kamangir Hamid , Arezoo Keyvan , Alipour Khalil 
Published: November 2022

AbstractThe use of inexpensive, lightweight, and portable particulate matter (PM) sensors is increasingly becoming popular in air quality monitoring applications. As an example, these low‐cost sensors can be used in surface or underground coal mines for monitoring of inhalable dust, and monitoring of inhalable particles in real‐time can be beneficial as it can possibly assist in preventing coal mine related respiratory diseases such as black lung disease. However, commercially available PM sensors are not inherently calibrated, and as a result, they have vague and unclear measurement accuracy. Therefore, they must initially be evaluated and compared with standardised instruments to be ready to be deployed in the fields. In this study, three different types of inexpensive, light‐scattering‐based widely available PM sensors (Shinyei PPD42NS, Sharp GP2Y1010AU0F, and Laser SEN0177) are evaluated and calibrated with reference instruments. PM sensors are compared with reference instruments in a controlled environment. The calibration is done by means of different machine learning techniques. The results demonstrate that the calibrated response obtained by fusion of sensors has a higher accuracy in comparison to the calibrated response of each individual sensor.
A prototype of a microlensed hyperspectral imager for solar observations
Authors: van Noort M. , Bischoff J. , Kramer A. , Solanki S. K. , Kiselman D. 
Published: November 2022

Context. When spectropolarimetric data are recorded at high spatial, spectral, and temporal resolution, the quality of the data is generally limited by the signal-to-noise ratio.Aims. We present a prototype of an integral field spectrograph for solar observations. This prototype overcomes the limitations of traditional solar instrumentation and captures the spectral information for all points in a given field of view without scanning, in order to optimize the efficiency and to minimize spectral and spatial crosstalk.Methods. The prototype was executed as a plug-in for the TRIPPEL spectrograph at the Swedish 1-meter Solar Telescope (SST) and uses an array of microlenses to shrink each image element, so that dark space is created in between. The light is then dispersed in this space, allowing for the independent detection of each spatio-spectral image element on a 2D detector.Results. The prototype was built and installed at the SST, yielding several good-quality data sets. These data sets were used to determine the imaging performance and efficiency of the prototype.Conclusions. Although the instrument required high-accuracy optics, the transparency of the prototype was found to be about 25%, and the straylight properties were found to be typical for spectrographic instruments.
Radial velocity survey for planets around young stars (RVSPY)
Authors: Zakhozhay Olga V. , Launhardt Ralf , Trifonov Trifon , Kürster Martin , Reffert Sabine , Henning Thomas , Brahm Rafael , Vinés José I. , Marleau Gabriel-Dominique , Patel Jayshil A. 
Published: November 2022

Aims. We aim to detect planetary companions to young stars with debris disks via the radial velocity method.
Methods. We observed HD 114082 during April 2018–August 2022 as one of the targets of our RVSPY program (Radial Velocity Survey for Planets around Young stars). We use the FEROS spectrograph, mounted to the MPG/ESO 2.2 m telescope in Chile, to obtain high signal-to-noise spectra and time series of precise radial velocities (RVs). Additionally, we analyze archival HARPS spectra and TESS photometric data. We use the CERES, CERES++ and SERVAL pipelines to derive RVs and activity indicators and ExoStriker for the independent and combined analysis of the RVs and TESS photometry.
Results. We report the discovery of a warm super-Jovian companion around HD 114082 based on a 109.8±0.4 day signal in the combined RV data from FEROS and HARPS, and on one transit event in the TESS photometry. The best-fit model indicates a 8.0±1.0 MJup companion with a radius of 1.00±0.03 RJup in an orbit with a semi-major axis of 0.51±0.01 au and an eccentricity of 0.4±0.04. The companions orbit is in agreement with the known near edge-on debris disk located at ∼28 au. HD 114082 b is possibly the youngest (15±6 Myr), and one of only three young (< 100 Myr) giant planetary companions for which both their mass and radius have been determined observationally. It is probably the first properly model-constraining giant planet that allows distinguishing between hot and cold-start models. It is significantly more compatible with the cold-start model.
Experimental and Numerical Analysis of Leakage Characteristics of Proportional Directional Valve
Authors: Ledvoň Marian , Hružík Lumír , Bureček Adam , Dýrr Filip 
Published: November 2022

This article deals with the experimental and numerical analysis of the leakage characteristics of the proportional directional valve. These characteristics describe the flow through the directional valve in the region of the center position of the spool valve. The element under investigation is a three-position four-way directional valve with zero overlap and feedback from the valve spool position. The actual valve spool position is sensed by an inductive position sensor and processed by integrated electronics. By means of an offset on the integrated electronics, it is also possible to set the center position of the valve spool. By moving the valve spool, the size and direction of the working fluid flow in both directions can be controlled. Internal leakage occurs due to axial and radial clearances between the spool and the sleeve. The magnitude of the axial clearances that occur at the control edges is investigated. The blocked-line pressure sensitivity curve, leakage flow curve and center flow curve are determined by experimental measurements. Depending on the experimental measurement, the correction of the center position of the valve spool is then made using offset. The flow through the control edges at the center position of the valve spool was simulated using Ansys Fluent software. Subsequently, the geometry of the flow simulation model is adjusted. The adjustment is made to take into account manufacturing tolerances. Finally, the simulated dependencies including the effect of manufacturing tolerances are compared with the measured and analytically determined characteristics.
Research background: Spool valve description, mathematical equations, flow analysis through valve, radial and axial clearance.
Purpose of the article: Effect of axial clearance on leakage characteristic.
Methods: Experimental measurements, numerical simulation.
Findings & Value added: Determining the range of the center flow curve as a function of manufacturing tolerances