bluuebunny/crossref_metadata_2025_split huggingface dataset:
XRF online analyzer for measurements of P2O5 content in phosphate slurry
Authors: Ben Amar Ismail , Thomas Andrew , Bachmann Claus , Hafnaoui Anass , Griguer Hafid , Miled Amine , Messaddeq Younès 
Published: October 2023

AbstractOnline X-ray Fluorescence (XRF) setup was constructed and optimized for analysing the P2O5 content in phosphate slurry (PS). Serval samples were analysed using two configurations of the setup, one with low and vertical flow and another with high and horizontal flow. The mean absolute error achieved through the first configuration was 0.87% and 0.38% using the second configuration. Reference samples were analyzed using the two configurations to construct the calibration curves. The curves cover a concentration range of P2O5 from 13.50 to 18.50% when considering the horizontal flow configuration, and a range of 14.00–15.60% when considering the vertical flow setup. An experimental study was conducted in order to optimize the measurement parameters for the online measurement of P2O5 in the phosphate slurry using the horizontal flow setup. A good signal-to-noise ratio (SNR) of $$P\left(K\alpha \right)$$

P

K
α

was attained using an excitation energy of 20 kV or 25 kV, an excitation current of 600 µA, a distance of 18 mm between the sample and the detector, a measurement time of 60 s per spectrum and the use of an Aluminum filter between the X-ray tube and the measurement window. Online X-ray fluorescence analysis of P entails some challenges due to the low characteristic energy of P, the phosphate slurry matrix and the online analysis mode. However, the outcomes of this study indicate that XRF is a promising technology to meet the requirement for digitalization of chemical analysis of phosphate products.
Renal impairment as a risk factor for trifluridine/tipiracil-induced adverse events in metastatic colorectal cancer patients from the REGOTAS study
Authors: Shiroyama Mamiko , Fukuoka Shota , Masuishi Toshiki , Takashima Atsuo , Kumekawa Yosuke , Kajiwara Takeshi , Yamazaki Kentaro , Shimada Yasuhiro , Esaki Taito , Makiyama Akitaka , Moriwaki Toshikazu 
Published: October 2023

AbstractRenal impairment may be associated with an increased risk of hematologic events (AEs) in patients undergoing treatment with trifluridine/tipiracil (FTD/TPI). This study aimed to investigate the specific types of AEs linked to renal impairment in patients with metastatic colorectal cancer (mCRC) receiving FTD/TPI, using real-world data. Among the patients included in the REGOTAS study (a retrospective study of FTD/TPI versus regorafenib), those treated with FTD/TPI were evaluated. Creatinine clearance values of < 30, 30–60, 60–90, and > 90 mL/min were defined as severe, moderate, mild renal impairment, and normal renal function, respectively. Renal impairment was analyzed as a risk factor for grade 3 or higher AEs using a logistic regression model. Overall survival (OS) and progression-free survival (PFS) based on renal impairment were evaluated. A total of 309 patients were included in the analysis, with 124, 130, and 55 patients divided into the normal, mild, and moderate-to-severe groups, respectively. The risk of grade 3 or higher neutropenia was significantly higher in the moderate-to-severe group (odds ratio 3.47; 95% confidence interval 1.45–8.30; P = 0.005), but there was no significant increase in the risk of non-hematologic AEs in any of the groups. The OS and PFS of patients in the mild and moderate-to-severe groups were comparable to those in the normal group. Patients with mCRC and moderate/severe renal impairment receiving FTD/TPI therapy may develop severe neutropenia; however, FTD/TPI remains a viable treatment option due to its clinical benefit.
Binding affinity predictions with hybrid quantum-classical convolutional neural networks
Authors: Domingo L. , Djukic M. , Johnson C. , Borondo F. 
Published: October 2023

AbstractCentral in drug design is the identification of biomolecules that uniquely and robustly bind to a target protein, while minimizing their interactions with others. Accordingly, precise binding affinity prediction, enabling the accurate selection of suitable candidates from an extensive pool of potential compounds, can greatly reduce the expenses associated to practical experimental protocols. In this respect, recent advances revealed that deep learning methods show superior performance compared to other traditional computational methods, especially with the advent of large datasets. These methods, however, are complex and very time-intensive, thus representing an important clear bottleneck for their development and practical application. In this context, the emerging realm of quantum machine learning holds promise for enhancing numerous classical machine learning algorithms. In this work, we take one step forward and present a hybrid quantum-classical convolutional neural network, which is able to reduce by 20% the complexity of the classical counterpart while still maintaining optimal performance in the predictions. Additionally, this results in a significant cost and time savings of up to 40% in the training stage, which means a substantial speed-up of the drug design process.
The disulfidptosis-related signature predicts prognosis and immune features in glioma patients
Authors: Wang Xiong , Yang Jijun , Yang Fengjie , Mu Ketao 
Published: October 2023

AbstractGlioma is the most common primary malignant tumor in the central nervous system. Disulfidptosis is a recently identified programmed cell death in tumor cells overexpressing SLC7A11 under glucose starvation. Clinical prognostic significance of disulfidptosis has been reported in several tumors, and in this study, we explored the correlation of disulfidptosis with clinical prognosis, immune cell infiltration, and immunotherapy response in glioma. A total of 1592 glioma patients were included in this study, including 691 glioma patients from The Cancer Genomic Atlas (TCGA), 300 patients with from the Chinese Glioma Genomic Atlas (CGGA) array, 325 patients from CGGA sequencing, and 276 patients from Gene Expression Omnibus (GEO) GSE16011. R software (V4.2.2) and several R packages were applied to develop the risk score model and correlation calculation and visualization. Three disulfidptosis-related genes, LRPPRC, RPN1, and GYS1, were screened out and applied to establish the risk score model. Low-risk patients exhibit favorable prognosis, and the disulfidptosis-related signature significantly correlated with clinicopathological properties, molecular subtypes, and immunosuppressive microenvironment of glioma patients. We developed a disulfidptosis-related risk model to predict the prognosis and immune features in glioma patients, and this risk model may be applied as an independent prognostic factor for glioma.
Optimizing the precision of laser speckle contrast imaging
Authors: González Olmos Alberto , Zilpelwar Sharvari , Sunil Smrithi , Boas David A. , Postnov Dmitry D. 
Published: October 2023

AbstractLaser speckle contrast imaging (LSCI) is a rapidly developing technology broadly applied for the full-field characterization of tissue perfusion. Over the recent years, significant advancements have been made in interpreting LSCI measurements and improving the technique’s accuracy. On the other hand, the method’s precision has yet to be studied in detail, despite being as important as accuracy for many biomedical applications. Here we combine simulation, theory and animal experiments to systematically evaluate and re-analyze the role of key factors defining LSCI precision—speckle-to-pixel size ratio, polarisation, exposure time and camera-related noise. We show that contrary to the established assumptions, smaller speckle size and shorter exposure time can improve the precision, while the camera choice is less critical and does not affect the signal-to-noise ratio significantly.
Inflammatory cell death, PANoptosis, screen identifies host factors in coronavirus innate immune response as therapeutic targets
Authors: Malireddi R. K. Subbarao , Bynigeri Ratnakar R. , Mall Raghvendra , Connelly Jon P. , Pruett-Miller Shondra M. , Kanneganti Thirumala-Devi 
Published: October 2023

AbstractThe COVID-19 pandemic, caused by the β-coronavirus (β-CoV) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to cause significant global morbidity and mortality. While vaccines have reduced the overall number of severe infections, there remains an incomplete understanding of viral entry and innate immune activation, which can drive pathology. Innate immune responses characterized by positive feedback between cell death and cytokine release can amplify the inflammatory cytokine storm during β-CoV–mediated infection to drive pathology. Therefore, there remains an unmet need to understand innate immune processes in response to β-CoV infections to identify therapeutic strategies. To address this gap, here we used an MHV model and developed a whole genome CRISPR-Cas9 screening approach to elucidate host molecules required for β-CoV infection and inflammatory cell death, PANoptosis, in macrophages, a sentinel innate immune cell. Our screen was validated through the identification of the known MHV receptor Ceacam1 as the top hit, and its deletion significantly reduced viral replication due to loss of viral entry, resulting in a downstream reduction in MHV-induced cell death. Moreover, this screen identified several other host factors required for MHV infection-induced macrophage cell death. Overall, these findings demonstrate the feasibility and power of using genome-wide PANoptosis screens in macrophage cell lines to accelerate the discovery of key host factors in innate immune processes and suggest new targets for therapeutic development to prevent β-CoV-induced pathology.
Theoretical and experimental characterization of non-Markovian anti-parity-time systems
Authors: Wilkey Andrew , Suelzer Joseph , Joglekar Yogesh N. , Vemuri Gautam 
Published: October 2023

AbstractOpen systems with anti-parity-time ($${{{{{{{\mathcal{APT}}}}}}}}$$
APT
) or $${{{{{{{\mathcal{PT}}}}}}}}$$
PT
symmetry exhibit a rich phenomenology absent in their Hermitian counterparts. To date all model systems and their diverse realizations across classical and quantum platforms have been local in time, i.e., Markovian. Here we propose a non-Markovian system with anti-$${{{{{{{\mathcal{PT}}}}}}}}$$
PT
-symmetry where a single time-delay encodes the retention of memory, and experimentally demonstrate its consequences with two time-delay coupled semiconductor lasers. A transcendental characteristic equation with infinitely many eigenvalue pairs sets our model apart. We show that a sequence of amplifying-to-decaying dominant mode transitions is induced by the time delay in our minimal model. The signatures of these transitions quantitatively match results obtained from four, coupled, nonlinear rate equations for laser dynamics, and are experimentally observed as constant-width sideband oscillations in the laser intensity profiles. Our work introduces a paradigmatic non-Hermitian system with memory, paves the way for its realization in classical systems, and may apply to time-delayed feedback-control for quantum systems.
Bayesian weighting of climate models based on climate sensitivity
Authors: Massoud Elias C. , Lee Hugo K. , Terando Adam , Wehner Michael 
Published: October 2023

AbstractUsing climate model ensembles containing members that exhibit very high climate sensitivities to increasing CO2concentrations can result in biased projections. Various methods have been proposed to ameliorate this ‘hot model’ problem, such as model emulators or model culling. Here, we utilize Bayesian Model Averaging as a framework to address this problem without resorting to outright rejection of models from the ensemble. Taking advantage of multiple lines of evidence used to construct the best estimate of the earth’s climate sensitivity, the Bayesian Model Averaging framework produces an unbiased posterior probability distribution of model weights. The updated multi-model ensemble projects end-of-century global mean surface temperature increases of 2 oC for a low emissions scenario (SSP1-2.6) and 5 oC for a high emissions scenario (SSP5-8.5). These estimates are lower than those produced using a simple multi-model mean for the CMIP6 ensemble. The results are also similar to results from a model culling approach, but retain some weight on low-probability models, allowing for consideration of the possibility that the true value could lie at the extremes of the assessed distribution. Our results showcase Bayesian Model Averaging as a path forward to project future climate change that is commensurate with the available scientific evidence.
Quantifying the Occupational Voice Use of Teachers
Authors: Eastman Sarah E. , Ghasemzadeh Hamzeh , Van Stan Jarrad , Hillman Robert E. , Mehta Daryush D. 
Published: October 2023

Purpose:
The teaching profession is a high–voice use occupation at elevated risk for developing voice disorders. Continued research on teachers' vocal demands is necessary to advocate for and establish vocal health programs. This study quantified ambulatory vocal dose measures for teachers during both on- and off-work periods, comparing their occupational voice use to that in other studies that have reported percent phonation ranging from 17% to 30%.

Method:
Participants included 26 full-time, female school teachers between 23 and 55 years of age across multiple grades and subjects, including individuals with and without a voice disorder. Ambulatory voice data were collected from weeklong voice monitoring that recorded phonatory activity through anterior neck-surface vibration. Three vocal dose measures—time, cycle, and distance doses—were computed for each participant for three time periods: on-work weekdays, off-work weekdays, and off-work weekend days.

Results:
The teachers' average percent phonation was 16.2% on-work weekdays, 8.4% off-work weekdays, and 8.0% off-work weekend days. No statistically significant differences for vocal dose measures were found between off-work weekdays and weekend days. Overall, all vocal dose measures were approximately 2 times higher during work relative to off-work time periods.

Conclusions:
This study provides values for vocal dose measures for school teachers using ambulatory voice-monitoring technology. The vocal demands of this particular teacher sample and voice activity detection algorithm are potential factors contributing to percent phonation values on the lower end of the range reported in the literature. Future work is needed to continue to understand occupational voice use and its associated risks related to voice health, with the ultimate goal of preventing and managing voice disorders in individuals engaged in high-risk occupations.
Protection method of traction power supply system for low and medium speed Maglev traffic based on fault traveling wave features
Authors: Yan Ningning , Wang Jian , Li Qingmin 
Published: October 2023

AbstractLow and medium speed magnetic levitation traffic with short power supply distance and complex grounding network structure, prone to power supply rail grounding faults. However, the existing fault location methods do not accurately locate the fault point, making it difficult for the protective device to act to cut off the fault. To address the above problems, this paper builds a dynamic simulation model of the low and medium speed magnetic levitation power supply rails to study the distribution characteristics of the fault traveling waves after a ground fault occurs in the power supply rails, and analyses the generation mechanism of the traveling wave spectrum through formula calculation. First, the difference in current between the positive and negative bus bars is analyzed to determine whether a ground fault has occurred. Second, the direction of the current difference between stations is compared to locate the faulty section. Finally, the fault distance is calculated from the frequency difference of the fault voltage at the double‐ended station. Through simulation, the method is validated to be unaffected by fault location, fault transition resistance, noise interference, and is applicable to short circuit faults caused by lightning strikes, and the ranging error always remains within 20 m. The method has strong robustness, can effectively solve the problem of protection misoperation and accurately locate the fault point. It is suitable for low and medium speed magnetic levitation transportation power supply rail ground fault.
Coronal bright point statistics
Authors: Kraus I. , Bourdin Ph.-A. , Zender J. , Bergmann M. , Hanslmeier A. 
Published: October 2023

Context. The corona of the Sun is the part of the solar atmosphere with temperatures of over one million Kelvin, which needs to be heated internally in order to exist. This heating mechanism remains a mystery; we see large magnetically active regions in the photosphere lead to strong extreme UV (EUV) emission in the corona. On much smaller scales (on the order of tens of Mm), there are bipolar and multipolar regions that can be associated with evenly sized coronal bright points (CBPs).
Aims. Our aim was to study the properties of CBPs in a statistical sense and to use continuous data from the SDO spacecraft, which makes it possible to track CBPs over their whole lifetime. Furthermore, we tested various rotation-speed profiles for CBPs in order to find out if the lower corona is co-rotating with the photosphere. Then we compiled a database with about 346 CBPs together with information of their sizes, shapes, appearance and disappearance, and their visibility in the EUV channels of the AIA instrument. We want to verify our methods with similar previous studies.
Methods. We used the high-cadence data of the largest continuous SDO observation interval in 2015 to employ an automated tracking algorithm for CBPs. Some of the information (e.g., the total lifetime, the characteristic shape, and the magnetic polarities below the CBPs) still requires human interaction.
Results. In this work we present statistics on fundamental properties of CBPs along with some comparison tables that relate, for example, the CBP lifetime with their shape. CBPs that are visible in all AIA channels simultaneously seem to be brighter in total and also have a stronger heating, and hence a higher total radiation flux. We compared the EUV emission visibility in different AIA channels with the CBP’s shape and lifetime. From the tracking algorithm we confirm a strict co-rotation of the CBPs with the photospheric differential rotation.
Conclusions. The tracked CBPs have a typical lifetime of about 1–6 h, while the hottest and brightest ones seem to exist for significantly longer time, up to 24 h. Furthermore, the merging of two CBPs seems not to have an influence on the overall size of the persisting CBP. Finally, fainter and cooler CBPs tend to have only weaker magnetic polarities, which clearly supports a coronal bright point heating mechanism based on magnetic energy dissipation.
Synthesis of (–)-Virginiae Butanolide A (VB-A)
Authors: Nubbemeyer Udo , Donges Jonas , Frank Andrea , Schollmeyer Dieter 
Published: October 2023

AbstractThe 2-(1′-hydroxyalkyl) paraconyl alcohols (–)-VB-A and (–)-SCB-5 are known as highly active signaling molecules within antibiotics production in Streptomyces sp. These γ-butyrolactone type compounds are epimeric at the 1′-OH-group. A direct synthesis of (–)-VB-A from (–)-SCB-5 that uses a late-stage inversion of the 1′-hydroxy group is not favored because of side reactions of the carbinol in β-position to the lactone C=O function. Therefore, an orthogonally protected 1,4-diol incorporating the central syn/anti 1′,2,3-stereotriad as described within the (–)-SCB-5 synthesis was used as an advanced intermediate to generate (–)-VB-A, too. A combination of protecting group operations and a 1′-OH group inversion via oxidation and diastereoselective reduction delivered the anti/anti 1′,2,3-stereotriad. Final transformations related to that as described for (–)-SCB-5 enabled completion of the (–)-VB-A-synthesis.
Job satisfaction and self-efficacy of in-service early childhood teachers in the post-COVID-19 pandemic era
Authors: Zhou Yan-Fang , Nanakida Atsushi 
Published: October 2023

AbstractAlthough the global COVID-19 pandemic has drawn public attention to the ecology of teachers’ work, little is known about how external and internal factors interact and affect early childhood teachers’ job satisfaction and self-efficacy. The purpose of this study is to examine how the external ecology of kindergartens and individual personality traits affect the job satisfaction and self-efficacy of in-service early childhood teachers in the post-COVID-19 pandemic era through a self-reporting questionnaire distributed among 237 kindergarten teachers in online and offline learning community groups. It was found that the job satisfaction of early childhood teachers was a significant predictor of self-efficacy and played a partially mediating role between personality traits and self-efficacy. Furthermore, personality traits are considered significant predictors of job satisfaction and self-efficacy in Chinese early childhood teachers, and it was noted that these teachers were the least satisfied in terms of pay and promotion. With these findings, this study contributes to the job satisfaction and self-efficacy literature by validating their causal associations in the field of early childhood teachers. Our findings also provide guidelines for practitioners and policymakers in promoting early childhood teacher credentialing and external social support to enhance job satisfaction and self-efficacy. The unique value of this study lies in the clarification of how the work environment and ecology of early childhood teachers in the post-COVID-19 pandemic era influenced self-efficacy and of personality traits being the underlying attributions that led to this result.