bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental realisations of the fractional Schrödinger equation in the temporal domain
Authors: Liu Shilong , Zhang Yingwen , Malomed Boris A. , Karimi Ebrahim 
Published: January 2023

AbstractThe fractional Schrödinger equation (FSE)—a natural extension of the standard Schrödinger equation—is the basis of fractional quantum mechanics. It can be obtained by replacing the kinetic-energy operator with a fractional derivative. Here, we report the experimental realisation of an optical FSE for femtosecond laser pulses in the temporal domain. Programmable holograms and the single-shot measurement technique are respectively used to emulate a Lévy waveguide and to reconstruct the amplitude and phase of the pulses. Varying the Lévy index of the FSE and the initial pulse, the temporal dynamics is observed in diverse forms, including solitary, splitting and merging pulses, double Airy modes, and “rain-like” multi-pulse patterns. Furthermore, the transmission of input pulses carrying a fractional phase exhibits a “fractional-phase protection” effect through a regular (non-fractional) material. The experimentally generated fractional time-domain pulses offer the potential for designing optical signal-processing schemes.
Transformer for one stop interpretable cell type annotation
Authors: Chen Jiawei , Xu Hao , Tao Wanyu , Chen Zhaoxiong , Zhao Yuxuan , Han Jing-Dong J. 
Published: January 2023

AbstractConsistent annotation transfer from reference dataset to query dataset is fundamental to the development and reproducibility of single-cell research. Compared with traditional annotation methods, deep learning based methods are faster and more automated. A series of useful single cell analysis tools based on autoencoder architecture have been developed but these struggle to strike a balance between depth and interpretability. Here, we present TOSICA, a multi-head self-attention deep learning model based on Transformer that enables interpretable cell type annotation using biologically understandable entities, such as pathways or regulons. We show that TOSICA achieves fast and accurate one-stop annotation and batch-insensitive integration while providing biologically interpretable insights for understanding cellular behavior during development and disease progressions. We demonstrate TOSICA’s advantages by applying it to scRNA-seq data of tumor-infiltrating immune cells, and CD14+ monocytes in COVID-19 to reveal rare cell types, heterogeneity and dynamic trajectories associated with disease progression and severity.
Mechanochemically accessing a challenging-to-synthesize depolymerizable polymer
Authors: Hsu Tze-Gang , Liu Shiqi , Guan Xin , Yoon Seiyoung , Zhou Junfeng , Chen Wei-Yuan , Gaire Sanjay , Seylar Joshua , Chen Hanlin , Wang Zeyu , Rivera Jared , Wu Leyao , Ziegler Christopher J. , McKenzie Ruel , Wang Junpeng 
Published: January 2023

AbstractPolymers with low ceiling temperatures (Tc) are highly desirable as they can depolymerize under mild conditions, but they typically suffer from demanding synthetic conditions and poor stability. We envision that this challenge can be addressed by developing high-Tcpolymers that can be converted into low-Tcpolymers on demand. Here, we demonstrate the mechanochemical generation of a low-Tcpolymer, poly(2,5-dihydrofuran) (PDHF), from an unsaturated polyether that contains cyclobutane-fused THF in each repeat unit. Upon mechanically induced cycloreversion of cyclobutane, each repeat unit generates three repeat units of PDHF. The resulting PDHF completely depolymerizes into 2,5-dihydrofuran in the presence of a ruthenium catalyst. The mechanochemical generation of the otherwise difficult-to-synthesize PDHF highlights the power of polymer mechanochemistry in accessing elusive structures. The concept of mechanochemically regulating theTcof polymers can be applied to develop next-generation sustainable plastics.
Machine learning-based classification of dual fluorescence signals reveals muscle stem cell fate transitions in response to regenerative niche factors
Authors: Togninalli Matteo , Ho Andrew T. V. , Madl Christopher M. , Holbrook Colin A. , Wang Yu Xin , Magnusson Klas E. G. , Kirillova Anna , Chang Andrew , Blau Helen M. 
Published: January 2023

AbstractThe proper regulation of muscle stem cell (MuSC) fate by cues from the niche is essential for regeneration of skeletal muscle. How pro-regenerative niche factors control the dynamics of MuSC fate decisions remains unknown due to limitations of population-level endpoint assays. To address this knowledge gap, we developed a dual fluorescence imaging time lapse (Dual-FLIT) microscopy approach that leverages machine learning classification strategies to track single cell fate decisions with high temporal resolution. Using two fluorescent reporters that read out maintenance of stemness and myogenic commitment, we constructed detailed lineage trees for individual MuSCs and their progeny, classifying each division event as symmetric self-renewing, asymmetric, or symmetric committed. Our analysis reveals that treatment with the lipid metabolite, prostaglandin E2 (PGE2), accelerates the rate of MuSC proliferation over time, while biasing division events toward symmetric self-renewal. In contrast, the IL6 family member, Oncostatin M (OSM), decreases the proliferation rate after the first generation, while blocking myogenic commitment. These insights into the dynamics of MuSC regulation by niche cues were uniquely enabled by our Dual-FLIT approach. We anticipate that similar binary live cell readouts derived from Dual-FLIT will markedly expand our understanding of how niche factors control tissue regeneration in real time.
Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies
Authors: Carrea Laura , Crétaux Jean-François , Liu Xiaohan , Wu Yuhao , Calmettes Beatriz , Duguay Claude R. , Merchant Christopher J. , Selmes Nick , Simis Stefan G. H. , Warren Mark , Yesou Hervé , Müller Dagmar , Jiang Dalin , Embury Owen , Bergé-Nguyen Muriel , Albergel Clément 
Published: January 2023

AbstractA consistent dataset of lake surface water temperature, ice cover, water-leaving reflectance, water level and extent is presented. The collection constitutes the Lakes Essential Climate Variable (ECV) for inland waters. The data span combined satellite observations from 1992 to 2020 inclusive and quantifies over 2000 relatively large lakes, which represent a small fraction of the number of lakes worldwide but a significant fraction of global freshwater surface. Visible and near-infrared optical imagery, thermal imagery and microwave radar data from satellites have been exploited. All observations are provided in a common grid at 1/120° latitude-longitude resolution, jointly in daily files. The data/algorithms have been validated against in situ measurements where possible. Consistency analysis between the variables has guided the development of the joint dataset. It is the most complete collection of consistent satellite observations of the Lakes ECV currently available. Lakes are of significant interest to scientific disciplines such as hydrology, limnology, climatology, biogeochemistry and geodesy. They are a vital resource for freshwater supply, and key sentinels for global environmental change.
An approach to $$(\mu ,\nu ,\omega )$$-single-valued neutrosophic submodules
Authors: Hameed Muhammad Shazib , Ahmad Zaheer , Ali Shahbaz , Kamran Muhammad , Lula Babole Alphonse-Roger 
Published: January 2023

AbstractDealing with erroneous, unexpected, susceptible, flawed, vulnerable, and intricate information is simplified with the use of a single-valued neutrosophic set (svns). This is because of the fact that these types of information are more sensitive to error. This is due to the fact that these particular kinds of information are more prone to error. The ideas of fuzzy sets and intuitionistic fuzzy sets have both undergone further development as a direct result of the development of this new theory. In svns, indeterminacy is quantified in a way that is both obvious and unambiguous, and truth membership, indeterminacy membership, and falsity membership are all completely independent of one another. In algebraic analysis, certain binary operations can be thought of as interacting with algebraic modules. These modules are intricate and ubiquitous structures. There are many different applications for modules to be used in. Modules find use in an extremely wide variety of different kinds of businesses and market segments. We investigate the idea of$$(\mu ,\nu ,\omega )$$(μ,ν,ω)-svns and relate it to$$(\mu ,\nu ,\omega )$$(μ,ν,ω)-single-valued neutrosophic module and$$(\mu ,\nu ,\omega )$$(μ,ν,ω)-single-valued neutrosophic submodule, respectively. The goals of this research are to comprehend the algebraic structures of a$$(\mu ,\nu ,\omega )$$(μ,ν,ω)-single-valued neutrosophic submodule of a classical module and enhance the legitimacy of this technique by discussing numerous essential aspects. Both of these goals will be accomplished through the course of this study. The strategies that we have developed in this manuscript are more generalizable than those that have been utilized in the past. These strategies include fuzzy sets, intuitionistic fuzzy sets, and neutrosophic sets.
Characterization and phylogenetic analysis of the complete mitochondrial genome sequence of Photinia serratifolia
Authors: Wang Ying , Chen Shengjia , Chen Jiajun , Chen Chaojie , Lin Xiaojian , Peng He , Zhao Qian , Wang Xingya 
Published: January 2023

AbstractPlant mitochondrial genomes (mitogenomes) are a valuable source of genetic information for a better understanding of phylogenetic relationships. However, no mitogenome of any species in the genus of Photinia has been reported. In this study, using NGS sequencing, we reported the mitogenome assembly and annotation of Photinia serratifolia, which is 473,579 bp in length, contains 38 protein-coding genes, 23 tRNAs, and 6 rRNAs, with 61 genes have no introns. The rps2 and rps11 genes are missing in the P. serratifolia mitogenome. Although there are more editing sites (488) in the P. serratifolia mitogenome than in most angiosperms, fewer editing types were found in the P. serratifolia mitogenome, showing a clear bias in RNA-editing. Phylogenetic analysis based on the mitogenomes of P. serratifolia and 8 other taxa of the Rosaceae family reflected the exact evolutionary and taxonomic status of P. serratifolia. However, Ka/Ks analysis revealed that 72.69% of the protein-coding genes in the P. serratifolia mitogenome had undergone negative selections, reflecting the importance of those genes in the P. serratifolia mitogenome. Collectively, these results will provide valuable information for the evolution of P. serratifolia and provide insight into the evolutionary relationships within Photinia and the Rosaceae family.
Optimization of the mechanical properties of polyester/coconut shell ash (CSA) composite for light-weight engineering applications
Authors: Daramola O. O. , Akinwande A. A. , Adediran A. A. , Balogun O. A. , Olajide J. L. , Adedoyin K. J. , Adewuyi B. O. , Jen T. C. 
Published: January 2023

AbstractThe mechanical properties of coconut shell ash (CSA) reinforced polyester composite have been optimized. Various test specimens were developed by dispersing 10, 20, 30 and 40 wt.%, of CSA in unsaturated polyester resin in decreasing particle sizes of 40, 30, and 20 µm in an open mould using hand lay-up technique. Tensile, flexural, and impact strengths, as well as tensile and flexural moduli and Shore D hardness of all test samples were determined. The results showed that 10–20 wt.% CSA increased tensile, flexural, impact strengths and flexural modulus for all particle sizes, but 30–40 wt. % CSA engendered depreciation in corresponding performance. For all particle sizes, 10–40 wt. percent CSA resulted in an increase in tensile strength, whereas 10–40 wt. percent resulted into a linear increase in Shore D hardness. Further observation portrayed that in each case, the finest CSA (20 µm) have the optimum result. Statistical analysis carried out on experimental outcomes confirmed the experimental variables (particle proportion and sizes) to be significant. From the surface plot, the strength responses revealed more dependence on the individual variables than their interactions. Regression models developed for individual responses are termed statistically fit in representing the experimental data.
A multi-task convolutional neural network for classification and segmentation of chronic venous disorders
Authors: Oliveira Bruno , Torres Helena R. , Morais Pedro , Veloso Fernando , Baptista António L. , Fonseca Jaime C. , Vilaça João L. 
Published: January 2023

AbstractChronic Venous Disorders (CVD) of the lower limbs are one of the most prevalent medical conditions, affecting 35% of adults in Europe and North America. Due to the exponential growth of the aging population and the worsening of CVD with age, it is expected that the healthcare costs and the resources needed for the treatment of CVD will increase in the coming years. The early diagnosis of CVD is fundamental in treatment planning, while the monitoring of its treatment is fundamental to assess a patient’s condition and quantify the evolution of CVD. However, correct diagnosis relies on a qualitative approach through visual recognition of the various venous disorders, being time-consuming and highly dependent on the physician’s expertise. In this paper, we propose a novel automatic strategy for the joint segmentation and classification of CVDs. The strategy relies on a multi-task deep learning network, denominated VENet, that simultaneously solves segmentation and classification tasks, exploiting the information of both tasks to increase learning efficiency, ultimately improving their performance. The proposed method was compared against state-of-the-art strategies in a dataset of 1376 CVD images. Experiments showed that the VENet achieved a classification performance of 96.4%, 96.4%, and 97.2% for accuracy, precision, and recall, respectively, and a segmentation performance of 75.4%, 76.7.0%, 76.7% for the Dice coefficient, precision, and recall, respectively. The joint formulation increased the robustness of both tasks when compared to the conventional classification or segmentation strategies, proving its added value, mainly for the segmentation of small lesions.
Spectral X-ray dark-field signal characterization from dual-energy projection phase-stepping data with a Talbot-Lau interferometer
Authors: Taphorn Kirsten , Kaster Lennard , Sellerer Thorsten , Hötger Alexander , Herzen Julia 
Published: January 2023

AbstractMaterial-selective analysis of spectral X-ray imaging data requires prior knowledge of the energy dependence of the observed signal. Contrary to conventional X-ray imaging, where the material-specific attenuation coefficient is usually precisely known, the linear diffusion coefficient of the X-ray dark-field contrast does not only depend on the material and its microstructure, but also on the setup geometry and is difficult to access. Here, we present an optimization approach to retrieve the energy dependence of the X-ray dark-field signal quantitatively on the example of closed-cell foams from projection data without the need for additional hardware to a standard grating-based X-ray dark-field imaging setup. A model for the visibility is used to determine the linear diffusion coefficient with a least-squares optimization. The comparison of the results to spectrometer measurements of the linear diffusion coefficient suggests the proposed method to provide a good estimate for the energydependent dark-field signal.
Job satisfaction has differential associations with delay discounting and risk-taking
Authors: de Ruijter Markus J. T. , Dahlén Amelia D. , Rukh Gull , Schiöth Helgi B. 
Published: January 2023

AbstractLow job satisfaction has been associated with both negative health and negative organizational outcomes. Knowledge on which factors influence job satisfaction remains limited. This study assesses the associations between job satisfaction and three personality traits related to cognitive- and inhibitory control: delay discounting, risk-taking and sensation seeking (DRS-traits). Delay discounting and sensation seeking were inferred using self-reported behavioral data and health measurements for 80,676 participants in the UK Biobank. Multiple linear regression analysis produced beta coefficients and confidence intervals for each DRS-trait and job satisfaction. Analyses were adjusted for age, socioeconomic status and sleep quality. A combination of the three DRS-traits (CDRS) was assessed as well. Delay discounting and risk-taking were associated with, respectively, lower and higher job satisfaction in both sexes. Sensation seeking had no significant association with job satisfaction for either sex. The combined score, CDRS, was only negatively associated with job satisfaction in females but not in males. We discuss that the negative association between delay discounting and job satisfaction may be due to career related delay discounting effects, but also highlight that low job satisfaction itself may also lead to increased delay discounting. Additionally, we discuss why increased risk-taking behavior may have a positive effect on job satisfaction.
Lactate dehydrogenase is associated with flow-mediated dilation in hypertensive patients
Authors: Cai Xiaoqi , Wang Tingjun , Xie Liangdi 
Published: January 2023

AbstractThe level of lactate dehydrogenase (LDH) has been proved to be positively associated with albuminuria, which represents glomerular endothelial damage in hypertension (HTN). In this study, the relationship between LDH and endothelial function evaluated by flow-mediated dilation (FMD) was investigated in hypertensives. 1507 subjects (aged 61.2 ± 12.5 years) were enrolled. All hypertensives (n = 1216) were subdivided into 3 groups: LDH1 (lowest tertile of LDH, n = 399), LDH2 (mediate tertile of LDH, n = 409) and LDH3 (highest tertile of LDH, n = 408). Meanwhile, 291 normotensives served as controls. FMD of right anterior tibial artery was assessed by high-resolution color Doppler ultrasound. The level of LDH in hypertensives was significantly higher than normotensives (p < 0.001). Whereas, FMD was obviously more blunted in hypertensives (p < 0.001). There was an increasing trend of FMD < 8% from control, LDH1, LDH2 to LDH3 group (χ2 = 36.751, p < 0.001). Stepwise multiple liner regression analysis demonstrated an independent correlation between LDH and FMD in hypertensives (β =  − 0.145, p < 0.05). After stratified analysis, the relevance persisted in the male, young and middle-aged, hypertensives with grade 2 HTN, duration of HTN < 3 years, metabolic syndrome and those without statin therapy. In conclusion, the level of LDH was inversely correlated with FMD among hypertensives. Those hypertensives with increased LDH need to be scanned for target organ damage, such as microalbuminuria and endothelial dysfunction, and more frequent following up are also recommended.
β-Aminoisobutyric acid (L-BAIBA) is a novel regulator of mitochondrial biogenesis and respiratory function in human podocytes
Authors: Audzeyenka Irena , Szrejder Maria , Rogacka Dorota , Angielski Stefan , Saleem Moin A. , Piwkowska Agnieszka 
Published: January 2023

AbstractPodocytes constitute an external layer of the glomerular filtration barrier, injury to which is a hallmark of renal disease. Mitochondrial dysfunction often accompanies podocyte damage and is associated with an increase in oxidative stress and apoptosis. β-Aminoisobutyric acid (BAIBA) belongs to natural β-amino acids and is known to exert anti-inflammatory and antioxidant effects. BAIBA has been reported to be involved in regulating mitochondrial dynamics, but unknown is whether BAIBA influences podocyte bioenergetics. The present study showed that human podocytes express the BAIBA receptor, Mas-related G protein-coupled receptor type D (MRGPRD), which is sensitive to BAIBA stimulation. The treatment of podocytes with L-BAIBA significantly increased their respiratory parameters, such as basal and maximal respiration, adenosine triphosphate (ATP) production, and spare respiratory capacity. We also found that L-BAIBA altered mitochondrial quantity, size, and shape, promoting organelle elongation and branching. L-BAIBA significantly upregulated peroxisome proliferator activated receptor γ coactivator-1α (PGC-1α) and transcription factor A mitochondrial (TFAM), indicating an increase in mitochondrial biogenesis. Our results demonstrate a novel regulatory mechanism of mitochondrial dynamics in podocytes, which may be important for maintaining their functions in the renal filtration barrier and prompting further investigations of preventing or ameliorating mitochondrial damage in podocytes in pathological states.
QTL mapping for seed density per silique in Brassica napus
Authors: Zhu Jifeng , Lei Lei , Wang Weirong , Jiang Jianxia , Zhou Xirong 
Published: January 2023

AbstractSeed density per silique (SDPS) and valid silique length (VSL) are two important yield-influencing traits in rapeseed. SDPS has a direct or indirect effect on rapeseed yield through its effect on seed per silique. In this study, a quantitative trait locus (QTL) for SDPS was detected on chromosome A09 using the QTL-seq approach and confirmed via linkage analysis in the mapping population obtained from 4263 × 3001 cross. Furthermore, one major QTL for SDPS (qSD.A9-1) was mapped to a 401.8 kb genomic interval between SSR markers Nys9A190 and Nys9A531. In the same genomic region, a QTL (qSL.A9) linked to VSL was also detected. The phenotypic variation of qSD.A9-1 and qSL.A9 was 53.1% and 47.6%, respectively. Results of the additive and dominant effects demonstrated that the expression of genes controlling SDPS and VSL were derived from a different parent in this population. Subsequently, we identified 56 genes that included 45 specific genes with exonic (splicing) variants. Further analysis identified specific genes containing mutations that may be related to seed density as well as silique length. These genes could be used for further studies to understand the details of these traits of rapeseed.