bluuebunny/crossref_metadata_2025 huggingface dataset:
The Dorset Rotulus
Authors: Bent Margaret , Hartt Jared C. , Lefferts Peter M.
Published: January 2023

The exciting discovery of new music from the Middle Ages sheds new light on knowledge of the medieval motet.
The Critical Life of Toni Morrison
Authors: Mayberry Susan Neal
Published: January 2023

The first book to trace the critical reception of the great African American woman writer, attending not only to her fiction but to her nonfiction and critical writings.
Transformative Waters in Late-Medieval Literature
Authors: Howes Hetta Elizabeth
Published: January 2023

A consideration of the metaphor of water in religious literature, especially in relation to women.
The Social World of the Abbey of Cava, c. 1020-1300
Authors: Loud Graham
Published: January 2023

A pioneering, comprehensive investigation into a major Italian monastery.
Chrétien's Equal: Raoul de Houdenc
Authors: de Houdenc Raoul
Published: January 2023

By his contemporaries, Raoul de Houdenc was 'mentioned in the same breath as Chrétien de Troyes as one of the masters of French poetry' (Keith Busby, The New Arthurian Encyclopaedia).
Pilot Programs and Postcolonial Pivots: Pioneering “DNA Fingerprinting” on Britain’s Borders
Authors: Bivins Roberta
Published: January 2023

Developed in Britain and the United States in the 1980s, genetic profiling has since become a global technology. Today, it is widely regarded as the evidentiary “gold standard” in individual and forensic identification. However, its origins as a technology of post-empire at Britain’s externalized borders in South Asia have remained unexamined. This article will argue that the first state-sanctioned use of “DNA fingerprints,” a pilot program exploring its value in disputed cases of family reunification migration from Bangladesh and Pakistan to Britain’s postcolonial cities, repays closer examination. National and transnational responses to the advent of genetic profiling as an identification technology demonstrate the interplay between imperial and postcolonial models and networks of power and truth production. At the same time, this experiment prefigured and conditioned the wider reception of DNA profiling in matters of kinship. Far from being a footnote, the use of genetic profiling by migrants determined to exercise their legal rights in the face of a hostile state also worked to naturalize genetic ties as the markers of “true” familial relationships.
Uhuru Sasa! Federal Futures and Liminal Sovereignty in Decolonizing East Africa
Authors: Donovan Kevin P.
Published: January 2023

Decolonization in East Africa was a regional affair that required the remaking of temporal orders. The staggered independence timelines of Tanganyika, Uganda, and Kenya caused considerable consternation due to transnational solidarities and visions for East African Federation. The interminable delays of Kenyan decolonization also threatened the linked economy of the region and diluted the sovereignty of neighboring states. At issue was “liminal sovereignty,” with polities and people languishing between normative legal orders. Against expectations about self-determination, East Africans found themselves in partial control of their collective endeavors. I analyze the tactics of temporal activism by Africans who aimed to undo British control over the pacing, sequencing, and synchronicity of decolonization. The indeterminate geography of decolonization was linked to uncertain temporalities of independence which threatened to subvert self-determination. In East Africa, federation was a style of claims-making and chronopolitics intended to orchestrate the distribution of rights, resources, and authority in a new layering of sovereignty between postcolonies.
m‐NLP Inference Models Using Simulation and Regression Techniques
Authors: Liu Guangdong , Marholm Sigvald , Eklund Anders J. , Clausen Lasse , Marchand Richard
Published: January 2023

Current inference techniques for processing multi‐needle Langmuir probe (m‐NLP) data are often based on adaptations of the Orbital Motion‐Limited (OML) theory which relies on several simplifying assumptions. Some of these assumptions, however, are typically not well satisfied in actual experimental conditions, thus leading to uncontrolled uncertainties in inferred plasma parameters. In order to remedy this difficulty, three‐dimensional kinetic particle in cell simulations are used to construct a synthetic data set, which is used to compare and assess different m‐NLP inference techniques. Using a synthetic data set, regression‐based models capable of inferring electron density and satellite potentials from 4‐tuples of currents collected with fixed‐bias needle probes similar to those on the NorSat‐1 satellite, are trained and validated. The regression techniques presented show promising results for plasma density inferences with RMS relative errors less than 20%, and satellite potential inferences with RMS errors less than 0.2 V for potentials ranging from −6 to −1 V. The new inference approaches presented are applied to NorSat‐1 data, and compared with existing state‐of‐the‐art inference techniques.
Global Simulations of Multi‐Frequency HF Signal Absorption for Direct Observation of Middle Atmosphere Temperature and Composition
Authors: Mahmoudian Alireza , Kosch Michael J. , Baghaei Reza Mohammadi
Published: January 2023

This paper presents the first numerical study on a new concept for the direct measurement of D‐region absorption in the high‐frequency (HF) band. Numerical simulations based on the Appleton‐Hartree and Garrett equations of refractive index are presented. Electron temperature as a result of HF radio pumping of the ionosphere is included in the calculations using proper numerical formulation. Both O‐ and X‐mode radio wave polarizations are taken into consideration. A global map of HF absorption in the northern hemisphere is calculated. Detailed calculations of HF radio wave absorption as it propagates through the lower atmosphere are presented. The effect of several parameters on the amount of absorption is calculated. The best frequencies to be used for the purpose of this study are discussed. A machine learning model is developed and the capability of the model in estimation of D and E‐region constituents includes N2, O, O2, as well as T and Ne is examined. Such a technique can also lead to global mapping of HF absorption and improve OTHR (over‐the‐horizon‐radar) performance.
Bulk Transfer Coefficients Estimated From Eddy‐Covariance Measurements Over Lakes and Reservoirs
Authors: Guseva S. , Armani F. , Desai A. R. , Dias N. L. , Friborg T. , Iwata H. , Jansen J. , Lükő G. , Mammarella I. , Repina I. , Rutgersson A. , Sachs T. , Scholz K. , Spank U. , Stepanenko V. , Torma P. , Vesala T. , Lorke A.
Published: January 2023

The drag coefficient, Stanton number and Dalton number are of particular importance for estimating the surface turbulent fluxes of momentum, heat and water vapor using bulk parameterization. Although these bulk transfer coefficients have been extensively studied over the past several decades in marine and large‐lake environments, there are no studies analyzing their variability for smaller lakes. Here, we evaluated these coefficients through directly measured surface fluxes using the eddy‐covariance technique over more than 30 lakes and reservoirs of different sizes and depths. Our analysis showed that the transfer coefficients (adjusted to neutral atmospheric stability) were generally within the range reported in previous studies for large lakes and oceans. All transfer coefficients exhibit a substantial increase at low wind speeds (<3 m s−1), which was found to be associated with the presence of gusts and capillary waves (except Dalton number). Stanton number was found to be on average a factor of 1.3 higher than Dalton number, likely affecting the Bowen ratio method. At high wind speeds, the transfer coefficients remained relatively constant at values of 1.6·10−3, 1.4·10−3, 1.0·10−3, respectively. We found that the variability of the transfer coefficients among the lakes could be associated with lake surface area. In flux parameterizations at lake surfaces, it is recommended to consider variations in the drag coefficient and Stanton number due to wind gustiness and capillary wave roughness while Dalton number could be considered as constant at all wind speeds.
Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System
Authors: Wang Jingjing , Shi Yurong , Luo Bingxian , Liu Siqing , Kong Linggao , Ma Jijie , Li Wenya , Tang Binbin , Zhang Aibing , Li Lei , Shi Liqin , Zhong Qiuzhen , Chen Yanhong
Published: January 2023

Combining the upstream solar wind observations measured by Mars Atmosphere and Volatile Evolution (MAVEN), Advanced Composition Explorer(ACE) and Deep Space Climate Observatory (DSCOVR) from October 2014 to April 2021, we investigate the statistical properties of the background solar wind at Mars and Earth. By applying an operational solar wind prediction system (Wang et al., 2018, https://doi.org/10.1051/swsc/2018025) in Space Weather Prediction Center (SEPC), we simulate the solar wind conditions and carry out a comparative analysis with observations to study our model performance. We find that our model is able to simulate the solar wind conditions upstream of Earth and Mars, corresponding to the different heliocentric distances and different levels of solar activity. Furthermore, we apply an event‐based evaluation by analyzing the high speed enhancements (HSEs), and find that the hit rate of HSEs is 70.38% and 66.37% for Earth and Mars, respectively. By predicting the HSEs at Earth (Mars), our model reaches a Mean Absolute Error (MAE) of 83.93 km/s (65.91 km/s) and 22.98 hr (21.65 hr) for maximum speed and arrival time prediction error, respectively. We also conduct a three‐month case study, from November 2020 to January 2021, analyzing solar wind conditions upstream of Earth, Mars, and measured by Tianwen‐1 (China's first Mars mission), for which our model is capable to predict the upstream solar wind conditions up to Mars.
A gain-of-function TPC2 variant R210C increases affinity to PI(3,5)P2 and causes lysosome acidification and hypopigmentation
Authors: Wang Qiaochu , Wang Zengge , Wang Yizhen , Qi Zhan , Bai Dayong , Wang Chentong , Chen Yuanying , Xu Wenjian , Zhu Xili , Jeon Jaepyo , Xiong Jian , Hao Chanjuan , Zhu Michael Xi , Wei Aihua , Li Wei
Published: January 2023

Albinism is a group of inherited disorders mainly affecting skin, hair and eyes. Here we identify a de novo point mutation, p.R210C, in the TPCN2 gene which encodes Two Pore Channel 2 (TPC2) from a patient with albinism. TPC2 is an endolysosome and melanosome localized non-selective cation channel involved in regulating pigment production. Through inside-out recording of plasma membrane targeted TPC2 and direct recording of enlarged endolysosomal vacuoles, we reveal that the R210C mutant displays constitutive channel activation and markedly increased affinity to PI(3,5)P2. Mice harboring the homologous mutation, R194C, also exhibit hypopigmentation in the fur and skin, as well as less pigment and melanosomes in the retina in a dominant inheritance manner. Moreover, mouse embryonic fibroblasts carrying the R194C mutation show enlarged endolysosomes, enhanced lysosomal Ca2+ release and hyper-acidification. Our data suggest that R210C is a pathogenic gain-of-function TPC2 variant that underlies an unusual dominant type of albinism.
An optofluidic platform for interrogating chemosensory behavior and brainwide neural representation in larval zebrafish
Authors: Sy Samuel K. H. , Chan Danny C. W. , Chan Roy C. H. , Lyu Jing , Li Zhongqi , Wong Kenneth K. Y. , Choi Chung Hang Jonathan , Mok Vincent C. T. , Lai Hei-Ming , Randlett Owen , Hu Yu , Ko Ho
Published: January 2023

Studying chemosensory processing desires precise chemical cue presentation, behavioral response monitoring, and large-scale neuronal activity recording. Here we present Fish-on-Chips, a set of optofluidic tools for highly-controlled chemical delivery while simultaneously imaging behavioral outputs and whole-brain neuronal activities at cellular resolution in larval zebrafish. These include a fluidics-based swimming arena and an integrated microfluidics-light sheet fluorescence microscopy (µfluidics-LSFM) system, both of which utilize laminar fluid flows to achieve spatiotemporally precise chemical cue presentation. To demonstrate the strengths of the platform, we used the navigation arena to reveal binasal input-dependent behavioral strategies that larval zebrafish adopt to evade cadaverine, a death-associated odor. The µfluidics-LSFM system enables sequential presentation of odor stimuli to individual or both nasal cavities separated by only ~100 µm. This allowed us to uncover brainwide neural representations of cadaverine sensing and binasal input summation in the vertebrate model. Fish-on-Chips is readily generalizable and will empower the investigation of neural coding in the chemical senses.
Near-infrared-featured broadband CO2 reduction with water to hydrocarbons by surface plasmon
Authors: Hu Canyu , Chen Xing , Low Jingxiang , Yang Yaw-Wen , Li Hao , Wu Di , Chen Shuangming , Jin Jianbo , Li He , Ju Huanxin , Wang Chia-Hsin , Lu Zhou , Long Ran , Song Li , Xiong Yujie
Published: January 2023

Imitating the natural photosynthesis to synthesize hydrocarbon fuels represents a viable strategy for solar-to-chemical energy conversion, where utilizing low-energy photons, especially near-infrared photons, has been the ultimate yet challenging aim to further improving conversion efficiency. Plasmonic metals have proven their ability in absorbing low-energy photons, however, it remains an obstacle in effectively coupling this energy into reactant molecules. Here we report the broadband plasmon-induced CO2 reduction reaction with water, which achieves a CH4 production rate of 0.55 mmol g−1 h−1 with 100% selectivity to hydrocarbon products under 400 mW cm−2 full-spectrum light illumination and an apparent quantum efficiency of 0.38% at 800 nm illumination. We find that the enhanced local electric field plays an irreplaceable role in efficient multiphoton absorption and selective energy transfer for such an excellent light-driven catalytic performance. This work paves the way to the technique for low-energy photon utilization.
Experimental realisations of the fractional Schrödinger equation in the temporal domain
Authors: Liu Shilong , Zhang Yingwen , Malomed Boris A. , Karimi Ebrahim
Published: January 2023

The 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

Consistent 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

Polymers 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

The 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

A 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

Dealing 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

Plant 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

The 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

Chronic 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

Material-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

Low 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

The 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

Podocytes 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

Seed 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.
Hydrological characteristics of different organic materials mulches
Authors: Zhang Pengfei , Xiao Menglin , Zhang Zhaorui , Dai Yanyan , Liu Geng , Senge Masateru
Published: January 2023

The study aims to find the properties of three organic mulch varieties and their effects on soil moisture and crop growth. Three organic mulches: newspaper, grass, and bran were selected as the research objects, and were analyzed through double-ring infiltration and water loss tests so that water permeability and water-holding capacity of the three mulching materials could be figured out. The results showed the descending order of the three mulching treatments and non-treatment by the infiltration rate of the soil: newspaper > bare ground > grass > bran. In terms of the water-holding capacity, the three organic mulches can be ranked from high to low as newspaper, grass, and bran; by the cumulative water loss as newspaper, grass, and bran; and by water-retention capacity as bran, grass, and newspaper, respectively. By conducting regression analysis, it is found that the water-holding capacity of the mulches is related to water immersion time and the amount of water absorbed and that there is a significant logarithmic relationship between the amount of water loss and water losing time. The fitting results of the three mulches are good. Besides, a power-function relationship exists between water absorption rate and immersion time, and between water loss rate and water loss time. The water infiltration of the soil under the newspaper mulching treatment is the best, as the newspaper can help to improve soil moisture and weaken surface runoff under flood irrigation and heavy rain. Bran possesses the strongest capacity for water retention, which is beneficial to soil moisture retention in areas where sprinkler irrigation, drip irrigation, and light to moderate rain prevail. The research results can provide a basis for improving the moisture-utilization efficiency in farmlands by using organic mulches.
Inhibition of c-Jun in AgRP neurons increases stress-induced anxiety and colitis susceptibility
Authors: Jiao Fuxin , Hu Xiaoming , Yin Hanrui , Yuan Feixiang , Zhou Ziheng , Wu Wei , Chen Shanghai , Liu Zhanju , Guo Feifan
Published: January 2023

Psychiatric disorders, such as anxiety, are associated with inflammatory bowel disease (IBD), however, the neural mechanisms regulating this comorbidity are unknown. Here, we show that hypothalamic agouti-related protein (AgRP) neuronal activity is suppressed under chronic restraint stress (CRS), a condition known to increase anxiety and colitis susceptibility. Consistently, chemogenic activation or inhibition of AgRP neurons reverses or mimics CRS-induced increase of anxiety-like behaviors and colitis susceptibility, respectively. Furthermore, CRS inhibits AgRP neuronal activity by suppressing the expression of c-Jun. Moreover, overexpression of c-Jun in these neurons protects against the CRS-induced effects, and knockdown of c-Jun in AgRP neurons (c-Jun∆AgRP) promotes anxiety and colitis susceptibility. Finally, the levels of secreted protein thrombospondin 1 (THBS1) are negatively associated with increased anxiety and colitis, and supplementing recombinant THBS1 rescues colitis susceptibility in c-Jun∆AgRP mice. Taken together, these results reveal critical roles of hypothalamic AgRP neuron-derived c-Jun in orchestrating stress-induced anxiety and colitis susceptibility.
Microsphere-supported gold nanoparticles for SERS detection of malachite green
Authors: Hinds David T. , Belhout Samir A. , Colavita Paula E. , Ward Andrew D. , Quinn Susan J.
Published: January 2023

The high surface area of porous carbon microspheres is exploited to prepare surface-enhanced Raman scattering (SERS) gold substrates and sensitive detection of malachite green is observed for optically trapped individual composite particles.
Recent progress in organic-based radiative cooling materials: fabrication methods and thermal management properties
Authors: Li Xin , Ding Zhenmin , Kong Linghao , Fan Xueying , Li Yao , Zhao Jiupeng , Pan Lei , Wiersma Diederik S. , Pattelli Lorenzo , Xu Hongbo
Published: January 2023

A comprehensive review about the state-of-the-art polymer-based radiative coolers, and our insights are outlined to advance their commercial progress.
Mechanistic study of nickel-catalyzed intramolecular [4 + 2] cycloaddition of cyclobutanone with allene: origin of selectivity and ligand effect
Authors: Li Jinxia , Luo Jinbo , Tong Wenyan , Tang Dingyi , Zhang Jin , Zhang Zhi-Han , Qu Shuanglin
Published: January 2023

The transition metal catalyzed cycloaddition reaction is one of the most powerful tools for the construction of carbon- and heterocycles. DFT studies are performed to investigate the mechanism of the Ni-catalyzed intramolecular [4 + 2] cycloaddition.
Direction‐of‐arrival estimation based on difference‐sum co‐array of a special coprime array
Authors: Ye Kun , Cai Yongbin , Hong Shaohua , Sun Haixin
Published: January 2023

Coprime array can provide high degrees of freedom by using difference–sum co‐array under the same physical sensors, and can estimate the source under uncertain conditions. A special coprime array structure is proposed in this paper. Its difference–sum co‐array can improve the degrees of freedom. Finally, the proposed array structure estimation is used for direction‐of‐arrival. Simulation results and analysis show that the proposed array structure can effectively improve the accuracy of direction‐of‐arrival estimation. Under the same signal‐to‐noise ratio and snapshot number, it has lower root mean square error and higher estimation accuracy than other methods.
HE‐DETR‐DC5 method to rapidly detect objects on passive THz images in human safety inspection
Authors: Cheng Lu , Zhang Wenrui , Li Chao , Ji Yicai , Liu Xiaojun , Fang Guangyou
Published: January 2023

As worldwide counterterrorism operations grow, screening people for concealed objects in public places utilizing Terahertz security technology is becoming increasingly critical. In this letter, a passive THz Human security image Intelligent detection method (HE‐DETR‐DC5) is proposed that combines histogram equalization (HE) processing and DEtection TRansformer (DETR). The proposed method first performs histogram equalization on passive THz images to improve image contrast. In addition, the cavity convolution is added to the ResNet‐50 backbone network to enhance the model's attention to the concealed object in the passive THz image and improve the accuracy. The corresponding model is called DETR‐DC5. The experimental results show that the average precision mAP of the proposed method can achieve 99.9%. At the same time, compared to other image enhancement methods, the histogram equalization method used in this letter has better performance and higher detection accuracy. The detection speed of the proposed method is about 0.5 FPS, which can meet the demand for real‐time detection. Therefore, the proposed model can efficiently and automatically detect hidden objects in passive THz human security images.
Waveguide integration of a >4.7‐THz quantum‐cascade laser
Authors: Nuttall Eleanor , Han Yingjun , Pardo Diego , Kondawar Sanchit S. , Brewster Nick , Salih Mohammed , Li Lianhe , Horbury Michael D. , Davies A. Giles , Linfield Edmund H. , Wang Hui , Dean Paul , Ellison Brian N. , Valavanis Alexander
Published: January 2023

Waveguide integration of terahertz quantum cascade lasers (THz QCLs) is demonstrated at frequencies above 4.7 THz. A precision micromachining technique, followed by diamond‐turning and electroless‐plating has been used to manufacture hollow rectangular waveguides with integrated diagonal feedhorns. It is shown that surface roughness at the level is achieved, enabling outcoupling of radiation in the 4.75–5.05 THz band, with a divergence angle of along the plane of the QCLs substrate.
Local power consumption method of distributed photovoltaic generation in rural distribution network based on blockchain
Authors: Zhang Tao , Yang Jianhua , Jin Kaiyuan , Jing Tianjun
Published: January 2023

With the increasing penetration of distributed photovoltaic generation (DPVG) in the rural distribution network, some problems such as abandoning solar energy and increasing voltage fluctuation have become more and more prominent. In order to promote local or nearby power consumption of the photovoltaic (PV) generation in the distribution network, the profit strategy is given with an optimal electricity price based on blockchain technology (BCT) by considering the topology, the load fluctuation of the distribution network and the reputation value of agricultural park consumers. The electricity price in the blockchain (BC) transaction is used as an intermediate variable to establish the revenue model for the PV generation, the agricultural park consumers and the distribution network. The power trading mechanism of the PV generation is constructed in the decentralized management agency of the BC. The maximum overall comprehensive income of the PV generation and the park consumers is used as the objective function, and the Stackelberg game theory is applied to prove the existence of the optimal game strategy in the transaction. The local power consumption method of the PV generation is simulated with the optimal electricity price in the IEEE 33‐node distribution network. The problem of abandoning solar energy is effectively relieved within an appropriate voltage limitation, and the comprehensive benefit of the PV generation and the park consumers is raised in the distribution network.
Research on modelling of landscape architecture layout planning based on multi‐sensor data fusion
Authors: Wen Pingfang , Xu Hongwu
Published: January 2023

In order to improve the rationality of landscape architecture layout planning and reduce the energy consumption in the process of data fusion, a landscape architecture layout planning modelling method based on multi‐sensor data fusion is proposed in this study. Firstly, the spatial layer of landscape plants is divided, and the quantitative index value of landscape architecture is calculated by Simpson diversity index. Secondly, the weight of plant index is determined by analytic hierarchy process, and the error of garden image is analysed by unsupervised classification of garden image based on multi‐sensor data fusion. Then, the garden image is classified according to the existing template, and the training samples of each category of garden are extracted. Finally, the modelling of landscape architecture layout planning is constructed, and the optimal planning method of landscape architecture layout based on maximum likelihood method is proposed. The experimental results show that this method can effectively reduce the energy consumption in the data fusion process, reduce the probability of damaged nodes becoming cluster heads, improve the stability of landscape forest layout planning method, match the plants according to the plant species, and improve the rationality of landscape architecture layout planning.