bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structural characterization and macromolecular structure construction of non-caking coal in Chicheng Mine
Authors: Jia Jinzhang , Yang Qiang , Liu Baogang , Wang Dongming 
Published: October 2023

AbstractGiven that coal is not a homogeneous substance, it is of great significance to identify and quantify the structural characteristics thereof for comprehensive analysis. In this paper, the non-caking coal in Chicheng Coal Mine was selected as the research object. The C, H, O, N, and S contents in the coal samples were obtained by proximate/ultimate analysis experiments. The structural characteristics of aromatic, aliphatic hydrocarbons, and oxygen-containing functional groups in the experimental coal samples were obtained by Fourier transform infrared spectroscopy (FT-IR) experiments. X-ray photoelectron spectroscopy (XPS) experiments were performed to obtain the occurrence state of N and S elements in coal samples. Nuclear magnetic resonance (13C NMR) experiments provided the carbon skeleton structural information of the coal samples. The macromolecular structure model of non-caking coal in the Chicheng Coal Mine was established on this basis. The molecular formula of non-caking coal in Chicheng Coal Mine was determined to be C207H181O32N3S.The13C NMR-predicted spectrum of the model showed good consistency with the 13C NMR-experimental spectrum obtained from the experiments, providing researchers with reference to the construction ideas and methods of molecular structure models of different coal samples.
Prevalence and prognosis of genetically proven familial hypercholesterolemia in subjects with coronary artery disease and reduced ejection fraction
Authors: Lee Wen-Jane , Chuang Han-Ni , Hsiao Tzu-Hung , Lee Wen-Lieng , Wu Jen-Pey , Sheu Wayne H.-H. , Liang Kae-Woei 
Published: October 2023

AbstractFew studies have genetically screened variants related to familial hypercholesterolemia (FH) and investigated their survival impact in patients with coronary artery disease (CAD) and reduced left ventricular ejection fraction (EF). Patients with CAD and reduced EF (< 40%) were enrolled. Their genomic DNAs were sequenced for FH-related genes. All-cause and cardiovascular mortality data served as the major outcome. A total of 256 subjects were analyzed and 12 subjects (4.7%) carried FH-related genetic variants. After a median follow-up period of 44 months, 119 of the study subjects died. Cox survival analysis showed that carrying the FH genetic variant did not have a significant impact on the survival of CAD with reduced EF. However, higher estimated glomerular filtration rate (eGFR), better EF and beta blocker use were protective for a lower all-cause mortality. Further larger studies are needed to evaluate the impact of carrying the FH-related genetic variant on survival of CAD with reduced EF.
Bayesian learning from multi-way EEG feedback for robot navigation and target identification
Authors: Wirth Christopher , Toth Jake , Arvaneh Mahnaz 
Published: October 2023

AbstractMany brain-computer interfaces require a high mental workload. Recent research has shown that this could be greatly alleviated through machine learning, inferring user intentions via reactive brain responses. These signals are generated spontaneously while users merely observe assistive robots performing tasks. Using reactive brain signals, existing studies have addressed robot navigation tasks with a very limited number of potential target locations. Moreover, they use only binary, error-vs-correct classification of robot actions, leaving more detailed information unutilised. In this study a virtual robot had to navigate towards, and identify, target locations in both small and large grids, wherein any location could be the target. For the first time, we apply a system utilising detailed EEG information: 4-way classification of movements is performed, including specific information regarding when the target is reached. Additionally, we classify whether targets are correctly identified. Our proposed Bayesian strategy infers the most likely target location from the brain’s responses. The experimental results show that our novel use of detailed information facilitates a more efficient and robust system than the state-of-the-art. Furthermore, unlike state-of-the-art approaches, we show scalability of our proposed approach: By tuning parameters appropriately, our strategy correctly identifies 98% of targets, even in large search spaces.
Polyethylene glycol-grafted graphene oxide nanosheets in tailoring the structure and reverse osmosis performance of thin film composite membrane
Authors: Sanei Zahra , Ghanbari Taranom , Sharif Alireza 
Published: October 2023

AbstractIntroducing hydrophilic polymers such as polyethylene glycol (PEG) within the polyamide (PA) layer of thin film composite (TFC) membranes helps achieve high water desalination performance. Here, PEGs of different molecular weights (X: 1500, 6000, 16,000 g/mol) are effectively introduced into the PA layer of TFC membranes utilizing PEG-grafted graphene oxide (GOPX) nanosheets and their effects on the physicochemical properties and reverse osmosis (RO) performance of the thin film nanocomposite (TFN) membranes are investigated. Among the TFNs prepared the GOP16000/TFN exhibits the best performance with 68% improvement in water flux and almost constant salt rejection compared to those of the bare TFC. The influence of PEG molecular weight on the RO performance of the membranes is interpreted by different surface and bulk hydrophilicity as well as thickness and surface roughness of PA layers of GOPX/TFNs. Furthermore, TFNs with thinner and smoother PA layers and thus higher water flux are obtained by dispersing GOPXs in the aqueous phase of the PA interfacial polymerization reaction than by dispersing them in the organic phase of the reaction. Finally, the high antifouling potential of TFNs containing PEG-grafted GOs is demonstrated.
Microwave bone fracture diagnosis using deep neural network
Authors: Beyraghi Sina , Ghorbani Fardin , Shabanpour Javad , Lajevardi Mir Emad , Nayyeri Vahid , Chen Pai-Yen , Ramahi Omar M. 
Published: October 2023

AbstractThis paper studies the feasibility of a deep neural network (DNN) approach for bone fracture diagnosis based on the non-invasive propagation of radio frequency waves. In contrast to previous “semi-automated” techniques, where X-ray images were used as the network input, in this work, we use S-parameters profiles for DNN training to avoid labeling and data collection problems. Our designed network can simultaneously classify different complex fracture types (normal, transverse, oblique, and comminuted) and estimate the length of the cracks. The proposed system can be used as a portable device in ambulances, retirement houses, and low-income settings for fast preliminary diagnosis in emergency locations when expert radiologists are not available. Using accurate modeling of the human body as well as changing tissue diameters to emulate various anatomical regions, we have created our datasets. Our numerical results show that our design DNN is successfully trained without overfitting. Finally, for the validation of the numerical results, different sets of experiments have been done on the sheep femur bones covered by the liquid phantom. Experimental results demonstrate that fracture types can be correctly classified without using potentially harmful and ionizing X-rays.
Evaluation of growth adaptation of Cinnamomum camphora seedlings in ionic rare earth tailings environment
Authors: Zhang H. , Liu C. , Lu X. , Xia G. 
Published: October 2023

AbstractThe root system is an important organ for nutrient uptake and biomass accumulation in plants, while biomass allocation directly affects essential oils content, which plays an essential role in plant growth and development and resistance to adverse environmental conditions. This study was undertaken to investigate the differences and correlation of biomass allocation, root traits and essential oil content (EOC), as well as the adaptations of camphor tree with different chemical types to the ionic rare earth tailing sand habitats. Data from 1-year old cutting seedlings of C. camphora showed that the biomass of C. camphora cuttings was mainly distributed in root system, with the ratio of root biomass 49.9–72.13% and the ratio of root to canopy 1.00–2.64. The total biomass was significantly positively correlated with root length (RL), root surface area (RSA) and dry weight of fine roots (diameter ≤ 2 mm) (P < 0.05). Root biomass and leaf biomass were negatively and positively with specific root length (SRL) and specific root surface area (SRSA), respectively. Leaf biomass presented a positive effect on EOC (P < 0.05), with the correlation coefficient of 0.808. The suitability sort of these camphor trees was as follows: C. camphora β-linalool, C. camphora α-linaloolII, C. camphora α-linaloolI being better adapted to the ionic rare earth tailings substrate, C. camphora citral being the next, and C. porrectum β-linalool and C. camphora borneol being the least adaptive. EOC played a positive role in the adaptation of C. camphora (R2 = 0.6099, P < 0.05). Therefore camphor tree with linalool type is the appropriate choice in the ecological restoration of ionic rare earth tailings. The study could provide scientific recommendations for the ecological restoration of ionic rare earth tailings area combined with industrial development.
Ultrasound-based radiomics combined with immune status to predict sentinel lymph node metastasis in primary breast cancer
Authors: Zhao Miaomiao , Zheng Yan , Chu Jian , Liu Zhenhua , Dong Fenglin 
Published: October 2023

AbstractIn the past few years, the axillary lymph node dissection technique has been steadily replaced by sentinel lymph node biopsy for treating and diagnosing breast cancer, thereby minimizing the complications and sequelae of the patients. Nevertheless, sentinel lymph node biopsy still presents limitations, such as high operation requirements, prolonged surgical duration, and adverse reactions to tracer agents. This study developed a novel non-invasive method to predict sentinel lymph node metastasis in breast cancer by analyzing the ultrasound imaging characteristics of the primary tumor, combined with the analysis of peripheral blood T-cell subsets that reflect the immune status of the body. The radiomic features analyzed in this study were extracted from preoperative ultrasound images of 199 solitary breast cancer patients, who were undergoing surgery and were pathologically diagnosed at the Yancheng First People's Hospital. All cases were randomly categorized in a 4:1 ratio to the training (n = 159) and validation (n = 40) cohorts. The extracted radiomics features were subjected to dimensional reduction with the help of the least absolute shrinkage and selection operator technique, resulting in the inclusion of 19 radiomics features. Four classifiers, including naïve Bayesian, logistic regression, classification decision tree, and support vector machine, were utilized to model the radiomics features, conventional ultrasound features, and peripheral blood T cell subsets in the training dataset, and validated using the validation dataset. The best-performing model was chosen for constructing the combined model. The radiomics model constructed using the logistic regression showed the best performance, with the training and validation cohorts showing areas under the curve (AUCs) of 0.77 and 0.68, respectively. The conventional ultrasound and peripheral blood T cell models constructed using the classification decision tree showed the best performance, wherein the training cohort presented AUCs of 0.71 and 0.81, respectively, while the validation cohort presented AUCs of 0.68 and 0.69, respectively. The combined model constructed by logistic regression showed AUCs of 0.91 and 0.79 in the training and validation datasets, respectively. The resulting combined model can be considered a simple, non-invasive method with strong reproducibility and clinical significance. Thus, it can be utilized to predict sentinel lymph node metastasis in breast cancer. Furthermore, the combined model can be effectively used to guide clinical decisions related to the selection of surgical procedures in breast surgery.
A memory-improving dipeptide, Tyr-Pro, can reach the mouse brain after oral administration
Authors: Cheng Lihong , Tanaka Mitsuru , Yoshino Atsuko , Nagasato Yuki , Takata Fuyuko , Dohgu Shinya , Matsui Toshiro 
Published: October 2023

AbstractThe transport and accumulation of orally administered functional food-derived peptides in the brain was not fully explored. Thus, in the present study, we aimed to provide critical evidence regarding brain accumulation of a memory-improving soy dipeptide, Tyr-Pro, following oral administration. Stable isotope-labeled Tyr-Pro (Tyr-[13C5,15N]Pro) was orally administered to male ICR mice at 10 or 100 mg/kg. Surprisingly, the intact labeled Tyr-Pro exhibited maximal plasma and brain levels 15 min after administration (plasma: area under the curve [AUC0–120 min], 1331 ± 267 pmol·min/mL-plasma; brain: AUC0–120 min of 0.34 ± 0.11 pmol·min/mg-dry brain, at 10 mg/kg). In addition, we detected labeled Tyr-Pro in the brain parenchyma, indicating a validated blood–brain-barrier (BBB) transportability. Moreover, we confirmed the preferable accumulation of Tyr-Pro in the hypothalamus, hippocampus, and cortex with > 0.02 pmol/mg-tissue. In conclusion, we provided the first evidence that orally administered Tyr-Pro at 10 mg/kg directly entered the blood circulation with an absorption ratio of 0.15%, of which 2.5% of Tyr-Pro was transported from the plasma to the mouse brain parenchyma.
Nemonoxacin achieved a better symptomatic improvement and a prolonged interval to next exacerbation than moxifloxacin for outpatients with acute exacerbations of chronic obstructive pulmonary disease
Authors: Meng Weiwei , Zeng Huihui , Zhao Zhiqi , Xiong Ruoyan , Chen Yan , Li Zhuo 
Published: October 2023

AbstractNemonoxacin is a novel non-fluorinated quinolone with strong antibacterial efficacy, but data of its effect on acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is rare. This study was conducted to compare the efficacy of oral nemonoxacin with moxifloxacin in AECOPD outpatients. In this retrospective observational study, a total of 101 AECOPD outpatients initially treated with nemonoxacin or moxifloxacin from July 2021 to March 2022 were enrolled. We collected COPD assessment test (CAT), Transition Dyspnea Indices (TDI) scores, and exacerbations information during 24 weeks follow-up from the electronic medical records. Kaplan–Meier curve was used to analyze the time to the next moderate/severe exacerbation. Compared to the moxifloxacin group, changes in CAT scores and TDI scores were significantly higher in the nemonoxacin group, and the nemonoxacin group also had a greater probability to reach the minimal clinically important difference of CAT (71.40% vs. 97.80%, p < 0.01) and TDI (40.50% vs. 60.00%, p < 0.05) at week 4. Despite no significant difference in the incidence of exacerbations between two groups, patients treated with nemonoxacin had a significantly prolonged time to next moderate/severe exacerbation than those with moxifloxacin (p < 0.05). Nemonoxacin achieved a better symptomatic improvement and a prolonged interval to next moderate/severe exacerbation for AECOPD outpatients.
Silicon mitigates K deficiency in maize by modifying C, N, and P stoichiometry and nutritional efficiency
Authors: Costa Milton Garcia , de Mello Prado Renato , dos Santos Sarah Marcilene Machado , de Souza Antônia Erica Santos , de Souza Júnior Jonas Pereira 
Published: October 2023

AbstractPotassium (K) deficiency in maize plants damages the nutritional functions of K. However, few studies have investigated the influence of K on C:N:P stoichiometry, the nutritional efficiency of these nutrients, and whether the mitigating effect of Si in plants under stress could act on these nutritional mechanisms involved with C, N, and P to mitigate K deficiency. Therefore, this study aimed to evaluate the impact of K deficiency in the absence and presence of Si on N and P uptake, C:N:P stoichiometric homeostasis, nutritional efficiency, photosynthetic rate, and dry matter production of maize plants. The experiment was conducted under controlled conditions using a 2 × 2 factorial scheme comprising two K concentrations: potassium deficiency (7.82 mg L−1) and potassium sufficiency (234.59 mg L−1). These concentrations were combined with the absence (0.0 mg L−1) and presence of Si (56.17 mg L−1), arranged in randomized blocks with five replicates. Potassium deficiency decreased stoichiometric ratios (C:N and C:P) and the plant’s C, N, and P accumulation. Furthermore, it decreased the use efficiency of these nutrients, net photosynthesis, and biomass of maize plants. The results showed that Si supply stood out in K-deficient maize plants by increasing the C, N, and P accumulation. Moreover, it decreased stoichiometric ratios (C:N, C:P, N:P, C:Si, N:Si, and P:Si) and increased the efficiencies of uptake, translocation, and use of nutrients, net photosynthesis, and dry matter production of maize plants. Therefore, the low nutritional efficiency of C, N, and P caused by K deficiency in maize plants can be alleviated with the supply of 56.17 mg L−1 of Si in the nutrient solution. It changes C:N:P stoichiometry and favors the use efficiency of these nutrients, which enhances the photosynthesis and sustainability of maize.
Genome-wide identification and comprehensive analysis of WRKY transcription factor family in safflower during drought stress
Authors: Song Xianming , Hou Xianfei , Zeng Youling , Jia Donghai , Li Qiang , Gu Yuanguo , Miao Haocui 
Published: October 2023

AbstractThe WRKY family is an important family of transcription factors in plant development and stress response. Currently, there are few reports on the WRKY gene family in safflower (Carthamus tinctorius L.). In this study, a total of 82 CtWRKY genes were identified from the safflower genome and could be classified into 3 major groups and 5 subgroups based on their structural and phylogenetic characteristics. The results of gene structure, conserved domain and motif analyses indicated that CtWRKYs within the same subfamily maintained a consistent exon/intron organization and composition. Chromosomal localization and gene duplication analysis results showed that CtWRKYs were randomly localized on 12 chromosomes and that fragment duplication and purification selection may have played an important role in the evolution of the WRKY gene family in safflower. Promoter cis-acting element analysis revealed that the CtWRKYs contain many abiotic stress response elements and hormone response elements. Transcriptome data and qRT-PCR analyses revealed that the expression of CtWRKYs showed tissue specificity and a strong response to drought stress. Notably, the expression level of the CtWRKY55 gene rapidly increased more than eightfold under drought treatment and rehydration, indicating that it may be a key gene in response to drought stress. These results provide useful insights for investigating the regulatory function of the CtWRKY gene in safflower growth and development, as well as identifying key genes for future molecular breeding programmes.
Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning
Authors: Zhang Jiawei , Li Jiachong , Tan Qing-Shou , Bu Jintao , Yuan Wenfei , Wang Bin , Ding Geyi , Ding Wenqiang , Chen Liang , Yan Leilei , Su Shilei , Xiong Taiping , Zhou Fei , Feng Mang 
Published: October 2023

AbstractExploring optimized processes of thermodynamics at microscale is vital to exploitation of quantum advantages relevant to microscopic machines and quantum information processing. Here, we experimentally execute a reinforcement learning strategy, using a single trapped 40Ca+ ion, for engineering quantum state evolution out of thermal equilibrium. We consider a qubit system coupled to classical and quantum baths, respectively, the former of which is achieved by switching on the spontaneous emission relevant to the qubit and the latter of which is made based on a Jaynes-Cummings model involving the qubit and the vibrational degree of freedom of the ion. Our optimized operations make use of the external control on the qubit, designed by the reinforcement learning approach. In comparison to the conventional situation of free evolution subject to the same Hamiltonian of interest, our experimental implementation presents the evolution of the states with higher fidelity while with less consumption of entropy production and work, highlighting the potential of reinforcement learning in accomplishment of optimized nonequilibrium thermodynamic processes at atomic level.
Competition between magnetic interactions and structural instabilities leading to itinerant frustration in the triangular lattice antiferromagnet LiCrSe2
Authors: Nocerino Elisabetta , Kobayashi Shintaro , Witteveen Catherine , Forslund Ola K. , Matsubara Nami , Tang Chiu , Matsukawa Takeshi , Hoshikawa Akinori , Koda Akihiro , Yoshimura Kazuyoshi , Umegaki Izumi , Sassa Yasmine , von Rohr Fabian O. , Pomjakushin Vladimir , Brewer Jess H. , Sugiyama Jun , Månsson Martin 
Published: October 2023

AbstractLiCrSe2 constitutes a recent valuable addition to the ensemble of two-dimensional triangular lattice antiferromagnets. In this work, we present a comprehensive study of the low temperature nuclear and magnetic structure established in this material. Being subject to a strong magnetoelastic coupling, LiCrSe2 was found to undergo a first order structural transition from a trigonal crystal system ($$P\bar{3}m1$$
P

3

¯

m
1
) to a monoclinic one (C2/m) at Ts = 30 K. Such restructuring of the lattice is accompanied by a magnetic transition at TN = 30 K. Refinement of the magnetic structure with neutron diffraction data and complementary muon spin rotation analysis reveal the presence of a complex incommensurate magnetic structure with a up-up-down-down arrangement of the chromium moments with ferromagnetic double chains coupled antiferromagnetically. The spin axial vector is also modulated both in direction and modulus, resulting in a spin density wave-like order with periodic suppression of the chromium moment along the chains. This behavior is believed to appear as a result of strong competition between direct exchange antiferromagnetic and superexchange ferromagnetic couplings established between both nearest neighbor and next nearest neighbor Cr3+ ions. We finally conjecture that the resulting magnetic order is stabilized via subtle vacancy/charge order within the lithium layers, potentially causing a mix of two co-existing magnetic phases within the sample.
Supernormal enrichment of cadmium in sphalerite via coupled dissolution-reprecipitation process
Authors: Duan Hongyu , Wang Changming , Hu Rong , Zhu Jiaxuan , Deng Jun 
Published: October 2023

AbstractSupernormal enrichment of cadmium in sphalerite is frequently observed in some sedimentary-hosted zinc-lead deposits, although related fluid process remains unconstrained. At the Jinding Mississippi Valley-type deposit, a considerable portion of cadmium has been remobilized from early sphalerite through coupled dissolution-reprecipitation reaction to form high-grade ores. Here we report natural occurrence of various sulfide nanoparticles and related textures in sphalerite that help document this process. A nanoscale study by transmission electron microscopy provides a rare glimpse of phase transition of cadmium from lattice-bond impurity, composition anomaly along planar defects, aggregates of hexagonal cadmium sulfide nanoparticles, to crystalline greenockite inclusions. Such a process may be mediated by oxidative dissolution on early-formed cadmiferous sphalerite during injection of cadmium-rich oxidative acidic fluids. This study provides an alternative mechanism versus exclusively solid-state diffusion for dispersed elements’ redistribution in hydrothermal ore deposits. It also sheds light on artificial synthesis of II-VI semiconductor nanomaterials by similar methods.