bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engineering Spin Coherence in Core-Shell Diamond Nanocrystals
Authors: Maurer Peter , Zvi Uri , Candido Denis , Weiss Adam , Jones Aidan , Chen Lingjie , Golovina iryna , Yu Xiaofei , Wang Stella , Talapin Dmitri , Flatté Michael E. , Esser-Kahn Aaron 
Published: August 2023

Abstract
Diamond nanocrystals can harbor spin qubit sensors capable of probing the physical properties of biological systems with nanoscale spatial resolution. These diamond nanosensors can readily be delivered into intact cells and even living organisms. However, applications beyond current proof-of-principle experiments require a substantial increase in sensitivity, which is generally limited by surface-noise-induced spin dephasing and relaxation. In this work, we significantly reduce magnetic surface noise by engineering core-shell structures, which in combination with dynamical decoupling result in qubit coherence times (T2) ranging from 52μs to 87μs – a drastic improvement over the 1.1μs to 35μs seen in bare particles. This improvement in spin coherence, combined with an overall increase in particle fluorescence, corresponds to an up to two-order-of-magnitude reduction in integration time. Probing qubit dynamics at a single particle level, furthermore, reveals that the noise characteristics fundamentally change from a bath with spins that rearrange their spatial configuration during the course of an experiment to a more dilute static bath. The observed results shed light on the underlying mechanisms governing spin dephasing in diamond nanocrystals and offer an effective noise mitigation strategy based on engineered core-shell structures.
When one does not want, two fight less: low mobility and similar odors result in peaceful interspecific encounters in termites
Authors: Santana Daniela Lucio , Bacci Leandro , Cristaldo Paulo Fellipe , Araújo Ana P. Albano 
Published: August 2023

Abstract
The cohabitation in nests of eusocial insects may involve different strategies that allow the stable coexistence. Here, we investigated the role of mobility and whole body odors in interspecific encounters in termites. Specifically, we tested the hypothesis that aggressiveness is reduced in interspecific encounters when: i) one of the involved species has low mobility; and/or ii) non-nestmate individuals share similar whole body odor. Manipulative bioassays were conducted to evaluate the proportion of attacks between the host species (Constrictotermes sp.) and target individuals: inquiline (Inquinitermes microcerus) and non-inquiline species (Nasutitermes corniger). The treatments consisted of the manipulation of combinations between the mobility (immovable or free) and odor of the target species and variation in host castes (S: soldier, W: worker, or S + W: both castes). For odor manipulation, the body watery extract was used to treat the species with each other's odors. Host and treated target individuals were inserted into the arena to determine the time elapsed until the first attack. Hosts and inquilines exhibited low aggression towards each other. The host's attack on the inquiline varied only among castes, with greater aggressiveness in the presence of the host worker (W or S + W). The proportion of attacks by the host on non-inquilines, and vice versa, was greater when the non-inquiline was free and had its own odor, followed by a neutral odor, the odor of inquiline, or the host. Our results suggest that low mobility and acquisition of similar odors can reduce interspecific aggression. These results contribute to the understanding of the mechanisms involved in the interactions between termites and other eusocial species.
Quantitative Analysis of Individual Atoms in the Channels of Beryl
Authors: Knez Daniel , Gspan Christian , Šimić Nikola , Mitsche Stefan , Fitzek Harald , Gatterer Karl , Wiltsche Helmar , Kothleitner Gerald , Grogger Werner , Hofer Ferdinand 
Published: August 2023

Abstract
The detection of single atoms with atomic resolution is a major challenge, in particular for technologically highly relevant nanoporous materials. Their nano-sized pores provide a large surface area and can also confine individual atoms and molecules, enabling the fine-tuning of catalytic performance or molecular transport properties. Previous studies employing aberration-corrected scanning transmission electron microscopy (STEM) have been limited to visualizing guest components within the pores without providing quantitative information. In this study, utilizing natural beryl (Be3Al2Si6O18) as a model system, we present a quantitative analysis of atomic occupancy within its channels. Through high-angle annular dark-field (HAADF) imaging, we clearly demonstrate the presence of Cs atoms within the channels. Furthermore, employing statistical analysis of atomic column intensities and comparison with a series of multislice simulations, we successfully determine the three-dimensional positions of individual Cs atoms within the channels. Thereby, we also reveal that the Cs atoms are non-uniformly distributed within the channels. By extracting the necessary information from a single high-resolution micrograph, we minimize the adverse effects of beam damage, making this methodology a promising approach for the analysis of diverse porous materials.
“Indigenous Spots”: Microscopic Imaging and Spectroscopic Analysis of Galvanic Halos Associated with Metal Inclusions in the Paper of Mid-19th Century Salted Paper Prints by William Henry Fox Talbot
Authors: Hardman-Peavy Colette , Wiggins Marcie B. , Hark Richard R. , Bezur Anikó , Messier Paul , Melita Lucia Noor , Risdonne Valentina , Burgio Lucia 
Published: August 2023

Abstract
Metallic inclusions in the paper substrate of historic salted paper prints are responsible for the formation of light-colored or white image regions immediately surrounding the particle, which are especially noticeable in areas of high image density. These low-density regions or “halos” often appear around a dark central spot. Our work shows this formation is connected with the electrochemical reaction of the metallic inclusion with the silver salt solution applied during the preparation of sensitized photographic paper, suggesting that these blemishes found in early prints can be termed “galvanic halos.” Early photographers were aware of the flaws caused by metal impurities and attempted to purchase the best quality paper to mitigate the problem. An ongoing study of prints in William Henry Fox Talbot’s The Pencil of Naturerevealed numerous examples of galvanic halos, prompting an initiative to document and characterize the phenomenon, and an investigation into formation mechanisms. Talbot’s seminal publication was the first commercially produced photographically illustrated book, containing 24 hand-printed photographs. This paper documents observations related to the forty galvanic halos identified and analyzed in the course of this study using X-ray fluorescence (XRF) and Raman spectroscopy, microscopic imaging, and the preparation of simulacra using historic methods. Elemental analysis, including the use of scanning micro- X-ray fluorescence spectroscopy (scanning XRF) has shown that copper, brass, and lead particles all cause the formation of halos.
Application of vacuum and convective drying processes for the valorization of Pisco grape pomace to enhance the retention of its bioactive compounds
Authors: Quispe Issis , Poblete Jacqueline , Aranda Mario , Vega-Gálvez Antonio 
Published: August 2023

Abstract
Purpose Pisco grape pomace is a waste product from the pisco industry, and their research is minimal compared to other wastes. However, in recent years, with the growing interest in reducing the environmental impact and converting these residues into novel by-products, the research, and their evaluation in each stage can contribute significantly to ensuring their recovery. This study evaluated the kinetics of vacuum and convective drying from grape pomace at different temperatures and the influence on the retention of polyphenolic compounds and antioxidant activity, as scalable alternatives for agro-industry.
Methods Liquid chromatography and spectrophotometry were used for polyphenols profile characterization and antioxidant activity evaluated.
Results The best drying grape pomace process was vacuum drying at 60 °C with a short drying time (210 min), and diffusivity values were higher (6.64 x 10-10 m2s-1) than those obtained by other drying conditions. The model that best fits the experimental data was the Midilli Kucuk model. Vacuum drying at 60 °C obtained the highest content of polyphenols and flavonoids, and significant antioxidant capacity was obtained. The gallic acid, 4-hydroxybenzoic acid, catechin, epicatechin and rutin were found in grape pomace.
Conclusions To preserve the bioactive compounds in pisco grape pomace and reduce energy costs, vacuum drying at 60 °C is an attractive alternative to revalue this waste, maintain the bio-compounds, and reduce drying times. The results of this study will contribute to the careful and efficient use of this residue, which in the future can have commercial value due to the biological properties of its bioactive compounds present.
Impact of Medical Technologies may be Predicted Using Constructed Graph Bibliometrics
Authors: Jiang Lawrence , Raza Ashir , Ariss Abdel-Badih , Chen David , Danaher-Garcia Nicole , Lee Jarone , He Shuhan 
Published: August 2023

Abstract
Scientific research is propelled by allocation of funding to different research projects based in part on the predicted scientific impact of the work. Data-driven algorithms can inform decision-making of funding by identifying likely high-impact studies using bibliometrics. Compared to standardized citation-based metrics alone, we utilize a machine learning pipeline that analyzes high-dimensional relationships among a range of bibliometric features to improve the accuracy of predicting high-impact research. Random forest classification models were trained using 28 bibliometric features calculated from a dataset of 1,485,958 publications in medicine to retrospectively predict whether a publication would become high-impact. For each random forest model, the balanced accuracy score was above 0.95 and the area under the receiver operating characteristic curve was above 0.99. The high performance of high impact research prediction using our proposed models show that machine learning technologies are promising algorithms that can support funding decision-making for medical research.
Optimizing Indoor Air Quality: CFD Simulation and Novel Air Cleaning Methods for Effective Aerosol Particles Inhibition in Public Spaces
Authors: Geng Chaolong , Zhu Xuyanran , Chen Ning 
Published: August 2023

Abstract
There is no sufficient supply of clean outdoor air to remove viruses quickly in the modern ventilation systems in most buildings, posing a significant health risk. To address this issue, this study utilizes computational fluid dynamics (CFD) simulations to investigate the effectiveness and speed of a locally uniform downward flow field in inhibiting the propagation of aerosol particles. The results indicate that such a flow field is particularly effective in areas with human movement as it facilitates the prompt settling of aerosol particles and significantly reduces their dispersion. By implementing this flow field, the risk of infection from the new coronavirus can be mitigated without increasing energy consumption, especially in high-turnover public spaces like supermarkets. Furthermore, we propose a novel air cleaning device that incorporates shelves and optimize its design using the PSO-SVR algorithm. This optimization achieves an optimal air distribution pattern that mimics the “air rain” effect. These findings offer valuable insights and practical applications for the prevention and control of respiratory diseases, particularly in post-epidemic scenarios.
Predictive Modelling of Thermal Conductivity in Single-Material Nanofluids: A Novel Approach
Authors: Onyiriuka Ekene 
Published: August 2023

Abstract
Background
This research introduces a novel approach for modelling single-material nanofluids, considering the constituents and characteristics of the fluids under investigation. The primary focus of this study was to develop models for predicting the thermal conductivity of nanofluids using a range of machine learning algorithms, including ensembles, trees, neural networks, linear regression, Gaussian process regressors, and support vector machines.
The main body of the abstract
To identify the most relevant features for accurate thermal conductivity prediction, the study compared the performance of established feature selection algorithms, such as minimum redundancy, maximum relevance, Ftest, and RReliefF, with a newly proposed feature selection algorithm. The novel algorithm eliminated features lacking direct implications for fluid thermal conductivity. The selected features encompassed temperature as a thermal property of the fluid itself, multiphase features such as volume fraction and particle size, and material features including nanoparticle material and base fluid material, which could be fixed based on any two intensive properties. Statistical methods were employed to select the features accordingly.
Results
The results demonstrated that the novel feature selection algorithm outperformed the established approaches in predicting the thermal conductivity of nanofluids. The models were evaluated using 5-fold cross-validation, and the best model based on the proposed feature selection algorithm exhibited a root mean squared error of validation of 1.83 and an R-squared value of 0.94. The model achieved a root mean squared error of 1.46 for the test set and an R-squared value of 0.97.
Conclusions
The developed predictive model holds practical significance by enabling nanofluids' numerical study and optimisation before their creation. This model facilitates the customisation of conventional fluids to attain desired fluid properties, particularly emphasising thermal properties. Additionally, the model permits the exploration of numerous nanofluid variations based on permutations of their features. Consequently, this research contributes valuable insights to the design and optimisation of nanofluid systems, advancing our understanding and application of thermal conductivity in nanofluids.
Bulk and Single-Cell Transcriptome Analysis Reveal Shared Key Genes and Patterns of Immune Dysregulation in Sepsis and Systemic Lupus Erythematosus
Authors: Wen Xuehuan , Bai Songjie , Zhang Kai , Li Shumin , Li Jiahui , Yang Jie , Yu Qing , Cao Lanxin , Cai Zhijian , Zhang Gensheng 
Published: August 2023

Abstract
Background: Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by autoantibody production and multi-organ dysfunction. SLE patients are at an elevated risk of sepsis due to immune dysregulation. Sepsis is a life-threatening condition resulting from dysregulated responses to infection and is the leading cause of ICU admission and death in SLE patients. However, the common mechanism of immune dysregulation shared between these two diseases still remains unclear.
Methods: Sepsis and SLE datasets were harvested from the Gene Expression Omnibus and Single Cell Portal database. Differential expression and weighted gene co-expression network analysis (WGCNA) were used to identify essential hub genes crucial to sepsis and SLE. The least absolute shrinkage and selection operator (LASSO) regression was used to establish a diagnostic model for SLE, and a receiver operating characteristic (ROC) curve was performed to assess the diagnostic efficiency of the model for SLE and individual genes for sepsis. Single-cell RNA sequencing data of PBMCs from patients with sepsis or SLE were analyzed to evaluate the proportion of different immune cell types. The expression profiles of hub genes in sepsis and SLE patients were further investigated, and similar pathway changes were explored by Gene Set Enrichment Analysis and Gene Ontology (GO) enrichment analysis.
Results: We identified 49 co-upregulated and 44 co-downregulated genes between sepsis and SLE datasets. GO analyses of these differentially expressed genes (DEGs) showed that they mainly affected the defence response to the bacteria and immune response. Combined DEGs and WGCNA analysis, we identified 11 hub genes: ANKRD22, RSPH9, DHRS9, AIM2, CCNA1, CEACAM1, FBXO6, TNFAIP6, FCGR1A, PLSCR1, and FCGR1BP. LASSO regression analysis and ROC curve highlighted TNFAIP6 and PLSCR1 as key genes with strong diagnostic values for sepsis and SLE. Single-cell RNA analysis showed an elevated proportion of CD14+ monocytes in sepsis and SLE patients, and hub gene expression was significantly increased in this group. Meanwhile, CD14+ monocytes in these two diseases shared some common transcriptional changes.
Conclusion:
TNFAIP6 and PLSCR1 are essential genes with strong diagnostic values for sepsis and SLE. In addition, the proportion of CD14+ monocytes within PBMCs of sepsis and SLE patients increased, with indications of some shared transcriptional changes.
Vascular insufficiency in normal tension glaucoma: A prospective cohort study
Authors: Kasaki Itsuo 
Published: August 2023

Abstract
Glaucoma is a disease that causes axonal loss of the optic nerve, resulting in scotomas in the visual field. Glaucoma is also the major cause of blindness. Hayreh identifies the long posterior ciliary artery,short posterior ciliary artery and centripetal branch in his "Study of the blood supply of the optic nerve head". Lee et al found delayed perfusion of adjacent parapapillary choroidal perfusion in the prelaminar region in indocyanine green angiography of primary open angle glaucoma. In the present study, we found Vascular insufficiency of centripetal branches In other words, the adjacent parapapillary choroidal perfusion of Lee et al corresponds to the centripetal branch of Hayreh. In fact, the running of the adjacent papillary choroidal circulation of Lee et al was centripetal in figures. Furthermore, in a prospective cohort study, we found that as vascular insufficiency developed, the dark spots also expanded correspondingly, suggesting a causal relationship between VI and scotoma
Biochemical Outcome in Metastatic Prostate Cancer Patients Following Prostate-Directed Radiotherapy
Authors: Ayoub Heba Maged , Zamzam Maha Lotfy , Elsayed Fifi Mostafa , Hassanin Ihab Mohammed , Elsemary Eman Essam 
Published: August 2023

Abstract
Background
The role of cytoreductive local radiotherapy (RT) in metastatic prostate cancer has recently been established. This study aimed to evaluate the biochemical outcome of local RT in metastatic prostate cancer.
Methods
This randomized controlled phase III study was conducted at the Clinical Oncology Department, Suez Canal University Hospital. Eligible participants were de-novo or metachronous metastatic prostate cancer patients with Eastern Cooperative Oncology Group performance status of 0–2. Participants were randomized to receive either cytoreductive prostate-directed RT in addition to standard care or standard care alone. The conventional radiation schedule of 70 Gy/35 fractions or the hypofractionated schedule of 55 Gy/20 fractions were delivered. The primary endpoint was biochemical progression-free survival (BPFS), and secondary endpoints included clinical response, and overall survival (OS). Survival and post-hoc analyses were performed using Cox regression and the Kaplan-Meier method with the log-rank test.
Results
Between November 23, 2020, and November 21, 2022, 70 patients were enrolled in this study. Of them, 34 patients were assigned to the prostate radiotherapy group, and 29 patients were assigned to the control group. At a median follow-up of 12 months, the median BPFS has not been reached for the prostate radiotherapy group compared to 4.067 months for the control group (HR: 0.147, p < 0.001). Subgroup analysis showed that the median BPFS was statistically significantly correlated with low-volume (95% CI, 0.004 to 0.262, p = 0·001) and hormonal-sensitive metastatic disease (95% CI, 0.010 to 0.192, p < 0·001). The median OS was 16.33 months for the prostate-radiotherapy group compared to 11.33 months for the control group (HR: 0.313, p = 0.003).
Conclusion
Prostate-directed RT improved BPFS and OS in metastatic prostate cancer patients, particularly in those with low volume and hormonal-sensitive disease.
Trial Registration:
This trial is registered on (27/4/2023) with pactr.samrc.ac.za, PACTR202305854600529, URL: https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=25510
Boron decreased cadmium accumulation in water spinach by enhancing cadmium chelation of covalently bound pectin in the root cell wall
Authors: Huang Ying-Ying , Shen Chuang , Wang Xue-Song , Fu Hui-Ling , Huang Bai-Fei , Li Yi , Wen Hui , Wang Yun-Fan , Zhou Wen-Jing , Xin Junliang 
Published: August 2023

Abstract
Cadmium (Cd) contamination and boron (B) deficiency are two major challenges associated with the farmland soils in Southern China. Therefore, this study was undertaken to examine the impacts of B supply on Cd accumulation in water spinach (Ipomoea aquatica) by using cultivar (T308) with high Cd concentration. The study further investigated the physiological mechanism behind the changes in Cd accumulation due to B supply. The findings revealed that B supply substantially reduced the Cd concentration in the leaves of water spinach by 41.20% and 37.16% under the Cd stress of 10 µM and 25 µM, respectively. Subcellular distribution of Cd showed that the Cd content as well as its proportion in root cell wall (RCW) increased significantly after B supply. Fourier transform infrared spectroscopy showed a significant enrichment of negative charged groups (such as -OH, -COOH, and -NH2) in the RCW after B supply. Overall, B supply also enhanced covalently bound pectin (CSP) content as well as the Cd content linked with CSP under Cd stress. These observations revealed that B regulated the Cd chelation in RCW, thereby reducing the amassment of Cd in water spinach.