bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tree species identification and health assessment of forest sample plots based on UAV hyperspectral remote sensing technology
Authors: Zeng Guanzhong , Xu Jiaqi , Zhang Wei , Wang Bin 
Published: October 2023

Abstract
National forest resource information is an important part of national basic information in many countries, sample plot survey is the main means to obtain this information. With the progress of science and technology and social development, the demand for cost saving and scientific and technological innovation has led to the wide application of UAV remote sensing in forest resource survey. This study introduced the practice of UAV hyperspectral remote sensing survey in Yicheng, Hubei Province, described in detail how to realize tree species identification and health assessment in forest sample plots by means of unmanned aerial vehicles. The results showed that the classification results of tree species identification method based on UAV hyperspectral remote sensing technology had high accuracy, and the results of the tree health assessment method used had certain reliability. This method greatly improved the safety of work in hazardous areas and reduced the cost.
Prefab-Net: Segmentation of prefabricated building from satellite imagery with deep neural network
Authors: Wang Minjie , Xiong Zhen , Zhang Leyong , Li Zhiqiang , Chen Ting , Wang Zhiyong , He Jianjun 
Published: October 2023

Abstract
The development of deep learning techniques such as convolutional neural networks (CNN) has injected new vitality into the study of semantic segmentation. Benefiting from the development of new technology, the automatic and intelligent work of remote sensing image segmentation has also entered a new stage. With the further improvement of China’s urbanization rate, urban construction is also developing rapidly. One of the most important tasks in land surveillance is to monitor buildings above ground using remote sensing images. Prefabricated building is the most common type of illegal building in developing area. At present, supervision mainly relies on the traditional human-centered method, which is time-consuming and low in efficiency. Whether the deep learning methods can benefit the prefabricated building segmentation has not yet been tested. By taking the realistic demand into account, this paper proposes a customized neural network structure, which combines multiple refined modules and improves the feature extraction, especially for the prefabricated building segmentation task. Through the comparison with the baseline algorithm, the specifically refined model for the prefabricated building has shown better results in our experimental area, which proves the feasibility and superiority in practical application.
Characterization of the Angat Ophiolite: New insights from bulk major and trace element geochemistry and petrographic analysis
Authors: Colocar R.D.A , De Leon H.R.R. , Pagbilao V.T.M. , Arpa M.C.B. , Queaño K.L. 
Published: October 2023

Abstract
The Angat Ophiolitic Complex, located north-northeast of Manila, Luzon is perhaps one of Luzon’s most fundamental suspect terranes. The definite age of the ophiolite is not well-established, with various authors having different claims. Encarnacion et al. (1993) conducted a U-Pb age dating for the Angat wherein the Angat Ophiolite was found to have an Early Middle Eocene age (48 Ma), close to the ZOC age - leading to the assumption that the two ophiolites are related and underlie most of Central Luzon. Hence, this paper aims to collect samples from the Eocene and Cretaceous Angat Ophiolite for petrographic and geochemical analyses, identify the relationship between the separated basalt units from the basalts in the main ophiolite body, and compare the geochemistry of the Eocene and Cretaceous units of the Angat Ophiolite with the other well-known ophiolites from the literature. Field investigations were conducted in five important localities wherein 15 samples were obtained. The results highlighted that the major mineral phases in the samples collected are plagioclase and augite, with some samples having hornblende and olivine. All samples appear to have undergone low-grade greenschist facies metamorphism, which may be attributed to hydrothermal alteration. Chloritization of pyroxene minerals is also evident, along with the hydrothermal alteration products of plagioclase and pyroxenes. The relationship between the EAO, MOC, and separated basalt patch in Marilaque Highway is identified. The Coto Block of the Zambales Ophiolite and the Angat Ophiolite may be related and formed over a mantle initially enriched by a subduction component.
Rare Earth Elements in Mud Volcanic Water of the North-Western Caucasus
Authors: Chelnokov G. A. , Lavrushin V.Y. , Kharitonova N.A. , Zheng Guodong , Aidarkozhina A. S. 
Published: October 2023

Abstract
The distribution and abundance of rare earth elements in mud volcanic waters of the North-Western Caucasus were studied. Waters are represented by two types: Na-Cl and Na-HCO3-Cl. All waters are characterized by high TDS (8.1-29.5 g/l), neutral to alkaline pH (7.2–8.9), reduced conditions (Eh from -280 to +92 mV), and methane as the main associated gas. It is established that concentrations of REE vary from 0.18 to 7.02 ppb. Based on REE content and pH mud volcanic waters were subdivided into three groups. In each group the concentration of ∑REE roughly increases as pH decreases. Due to geological conditions the highest concentrations of REE are observed in mud volcanoes located within the oldest Cretaceous sediments within the flexural-fault zones of the North-Western Caucasus and the Taman region. Mud volcanoes connected with the Maikop series (₽3-N1), have lower REE concentrations. For the first time the geochemical and geological data suggest different sources of matter for mud volcanoes of the studied area.
Forestry ecological security measurements and obstacle factor analysis in Yunnan
Authors: Wang Fuli , Fu Wei , Luo Mingcan 
Published: October 2023

Abstract
Forestry ecological security is not only a necessary condition for sustainable development of forestry economy, but also an important guarantee for protecting biodiversity and reducing carbon emissions. It plays a crucial role in achieving high-quality industrial development and ecological civilization construction goals. The ecological security of forestry in Yunnan was examined from 2011 to 2020 using the PSR model, entropy power technique, and barrier degree model. The results show that the forestry ecological safety composite index generally shows an improving trend, rising from 0.3495 in 2011 to 0.7290 in 2020. The index of forestry industry pressure subsystem and human response subsystem has an increasing trend, with an average annual increase of 22.36% and 34.05%, respectively. The index of forest ecological subsystem is on a decreasing trend. Urban sewage discharge intensity, forestry investment, per capita GDP, per capita water resources, per capita forest area, and per capita forest fire damage area were the main obstacle factors impacting forestry ecological security in Yunnan.
Linear scaling approach for optical excitations using maximally localized Wannier functions
Authors: Merkel Konrad , Ortmann Frank 
Published: October 2023

Abstract
We present a theoretical method for calculating optical absorption spectra based on maximally localized Wannier functions, which is suitable for large periodic systems. For this purpose, we calculate the exciton Hamiltonian, which determines the Bethe–Salpeter equation for the macroscopic polarization function and optical absorption characteristics. The Wannier functions are specific to each material and provide a minimal and therefore computationally convenient basis. Furthermore, their strong localization greatly improves the computational performance in two ways: first, the resulting Hamiltonian becomes very sparse and, second, the electron–hole interaction terms can be evaluated efficiently in real space, where large electron–hole distances are handled by a multipole expansion. For the calculation of optical spectra we employ the sparse exciton Hamiltonian in a time-domain approach, which scales linearly with system size. We demonstrate the method for bulk silicon—one of the most frequently studied benchmark systems—and envision calculating optical properties of systems with much larger and more complex unit cells, which are presently computationally prohibitive.
Design of a low stiffness magnetic support for the carbon fiber pipe under low-frequency vibration and impulse
Authors: Xu Zhenyuan , Zhang Yang , Ye Mingsong , Ma Wenjing , Luo Junpeng , Yang Kaike , Zhang Junwei , Wang Xi 
Published: October 2023

Abstract
Carbon fiber optical arms are highly sensitive to vibration disturb, and external vibrational excitation can significantly degrade the accuracy of the optical path. Firstly, this paper proposes a carbon fiber optical arm pipe magnetic support system for low-frequency and impulse vibrations. The overall stiffness of the magnetic support is reduced by the cooperation of mechanical springs with positive stiffness and magnetic springs with negative stiffness. Secondly, based on analytical calculations of magnetic forces and finite element simulations, a comprehensive dynamic model of the system is established and solved using the Runge–Kutta method. Finally, an experimental platform for the equipment is set up, and both frequency sweep response tests and impulse vibration response tests are conducted on the system. The results demonstrate that the proposed magnetic support with low stiffness effectively reduces the interference of low-frequency vibrations on the supported carbon fiber pipe.
Neuromorphic cytometry: implementation on cell counting and size estimation
Authors: Zhang Ziyao , Xu Zhangyu , McGuire Helen M , Essam Chip , Nicholson Andrew , Hamilton Tara J , Li Jiayin , Eshraghian Jason K , Yong Ken-Tye , Vigolo Daniele , Kavehei Omid 
Published: October 2023

Abstract
Imaging flow cytometry (FC) is a powerful analytic tool that combines the principles of conventional FC with rich spatial information, allowing more profound insight into single-cell analysis. However, offering such high-resolution, full-frame feedback can restrain processing speed and has become a significant trade-off during development. In addition, the dynamic range (DR) offered by conventional photosensors can only capture limited fluorescence signals, which compromises the detection of high-velocity fluorescent objects. Neuromorphic photo-sensing focuses on the events of interest via individual-firing pixels to reduce data redundancy and latency. With its inherent high DR, this architecture has the potential to drastically elevate the performance in throughput and sensitivity to fluorescent targets. Herein, we presented an early demonstration of neuromorphic cytometry, demonstrating the feasibility of adopting an event-based resolution in describing spatiotemporal feedback on microscale objects and for the first time, including cytometric-like functions in object counting and size estimation to measure 8 µm, 15 µm microparticles and human monocytic cell line (THP-1). Our work has achieved highly consistent outputs with a widely adopted flow cytometer (CytoFLEX) in detecting microparticles. Moreover, the capacity of an event-based photosensor in registering fluorescent signals was evaluated by recording 6 µm Fluorescein isothiocyanate-marked particles in different lighting conditions, revealing superior performance compared to a standard photosensor. Although the current platform cannot deliver multiparametric measurements on cells, future endeavours will include further functionalities and increase the measurement parameters (granularity, cell condition, fluorescence analysis) to enrich cell interpretation.
Program for Integration and Rapid Analysis of Mass Isotopomer Distributions (PIRAMID)
Authors: Gomez Javier D , Wall Martha L , Rahim Mohsin , Kambhampati Shrikaar , Evans Bradley S , Allen Doug K , Antoniewicz Maciek R , Young Jamey D 
Published: October 2023

Abstract

Summary
The analysis of stable isotope labeling experiments requires accurate, efficient, and reproducible quantification of mass isotopomer distributions (MIDs), which is not a core feature of general-purpose metabolomics software tools that are optimized to quantify metabolite abundance. Here, we present PIRAMID (Program for Integration and Rapid Analysis of Mass Isotopomer Distributions), a MATLAB-based tool that addresses this need by offering a user-friendly, graphical user interface-driven program to automate the extraction of isotopic information from mass spectrometry (MS) datasets. This tool can simultaneously extract ion chromatograms for various metabolites from multiple data files in common vendor–agnostic file formats, locate chromatographic peaks based on a targeted list of characteristic ions and retention times, and integrate MIDs for each target ion. These MIDs can be corrected for natural isotopic background based on the user-defined molecular formula of each ion. PIRAMID offers support for datasets acquired from low- or high-resolution MS, and single (MS) or tandem (MS/MS) instruments. It also enables the analysis of single or dual labeling experiments using a variety of isotopes (i.e. 2H, 13C, 15N, 18O, 34S).

Data availability and implementation
MATLAB p-code files are freely available for non-commercial use and can be downloaded from https://mfa.vueinnovations.com/. Commercial licenses are also available. All the data presented in this publication are available under the “Help_menu” folder of the PIRAMID software.
TNF-α protects from exacerbated myocarditis and cardiac death by suppressing expansion of activated heart-reactive CD4+ T cells
Authors: Rolski Filip , Tkacz Karolina , Węglarczyk Kazimierz , Kwiatkowski Grzegorz , Pelczar Paweł , Jaźwa-Kusior Agnieszka , Bar Anna , Kuster Gabriela M , Chłopicki Stefan , Siedlar Maciej , Kania Gabriela , Błyszczuk Przemysław 
Published: October 2023

Abstract

Aims
Tumour necrosis factor α (TNF-α) represents a classical pro-inflammatory cytokine, and its increased levels positively correlate with the severity of many cardiovascular diseases. Surprisingly, some heart failure patients receiving high doses of anti-TNF-α antibodies showed serious health worsening. This work aimed to examine the role of TNF-α signalling on the development and progression of myocarditis and heart-specific autoimmunity.

Methods and results
Mice with genetic deletion of TNF-α (Tnf+/− and Tnf−/−) and littermate controls (Tnf+/+) were used to study myocarditis in the inducible and the transgenic T cell receptor (TCRM) models. Tnf+/− and Tnf−/− mice immunized with α-myosin heavy chain peptide (αMyHC) showed reduced myocarditis incidence, but the susceptible animals developed extensive inflammation in the heart. In the TCRM model, defective TNF-α production was associated with increased mortality at a young age due to cardiomyopathy and cardiac fibrosis. We could confirm that TNF-α as well as the secretome of antigen-activated heart-reactive effector CD4+ T (Teff) cells effectively activated the adhesive properties of cardiac microvascular endothelial cells (cMVECs). Our data suggested that TNF-α produced by endothelial in addition to Teff cells promoted leucocyte adhesion to activated cMVECs. Analysis of CD4+ T lymphocytes from both models of myocarditis showed a strongly increased fraction of Teff cells in hearts, spleens, and in the blood of Tnf+/− and Tnf−/− mice. Indeed, antigen-activated Tnf−/− Teff cells showed prolonged long-term survival and TNF-α cytokine-induced cell death of heart-reactive Teff.

Conclusion
TNF-α signalling promotes myocarditis development by activating cardiac endothelial cells. However, in the case of established disease, TNF-α protects from exacerbating cardiac inflammation by inducing activation-induced cell death of heart-reactive Teff. These data might explain the lack of success of standard anti-TNF-α therapy in heart failure patients and open perspectives for T cell–targeted approaches.
T5-like phage BF23 evades host-mediated DNA restriction and methylation
Authors: Skutel Mikhail , Andriianov Aleksandr , Zavialova Maria , Kirsanova Maria , Shodunke Oluwasefunmi , Zorin Evgenii , Golovshchinskii Aleksandr , Severinov Konstantin , Isaev Artem 
Published: October 2023

Abstract
Bacteriophage BF23 is a close relative of phage T5, a prototypical Tequintavirus that infects Escherichia coli. BF23 was isolated in the middle of the XXth century and was extensively studied as a model object. Like T5, BF23 carries long ∼9.7 kb terminal repeats, injects its genome into infected cell in a two-stage process, and carries multiple specific nicks in its double-stranded genomic DNA. The two phages rely on different host secondary receptors—FhuA (T5) and BtuB (BF23). Only short fragments of the BF23 genome, including the region encoding receptor interacting proteins, have been determined. Here, we report the full genomic sequence of BF23 and describe the protein content of its virion. T5-like phages represent a unique group that resist restriction by most nuclease-based host immunity systems. We show that BF23, like other Tequintavirus phages, resist Types I/II/III restriction–modification host immunity systems if their recognition sites are located outside the terminal repeats. We also demonstrate that the BF23 avoids host-mediated methylation. We propose that inhibition of methylation is a common feature of Tequintavirus and Epseptimavirus genera phages, that is not, however, associated with their antirestriction activity.
Long-Read–Based Genome Assembly Reveals Numerous Endogenous Viral Elements in the Green Algal Bacterivore Cymbomonas tetramitiformis
Authors: Gyaltshen Yangtsho , Rozenberg Andrey , Paasch Amber , Burns John A , Warring Sally , Larson Raegan T , Maurer-Alcalá Xyrus X , Dacks Joel , Narechania Apurva , Kim Eunsoo 
Published: October 2023

Abstract
The marine tetraflagellate Cymbomonas tetramitiformis has drawn attention as an early diverging green alga that uses a phago-mixotrophic mode of nutrition (i.e., the ability to derive nourishment from both photosynthesis and bacterial prey). The Cymbomonas nuclear genome was sequenced previously, but due to the exclusive use of short-read (Illumina) data, the assembly suffered from missing a large proportion of the genome's repeat regions. For this study, we generated Oxford Nanopore long-read and additional short-read Illumina data and performed a hybrid assembly that significantly improved the total assembly size and contiguity. Numerous endogenous viral elements were identified in the repeat regions of the new assembly. These include the complete genome of a giant Algavirales virus along with many genomes of integrated Polinton-like viruses (PLVs) from two groups: Gezel-like PLVs and a novel group of prasinophyte-specific PLVs. The integrated ∼400 kb genome of the giant Algavirales virus is the first account of the association of the uncultured viral family AG_03 with green algae. The complete PLV genomes from C. tetramitiformis ranged between 15 and 25 kb in length and showed a diverse gene content. In addition, heliorhodopsin gene-containing repeat elements of putative mirusvirus origin were identified. These results illustrate past (and possibly ongoing) multiple alga–virus interactions that accompanied the genome evolution of C. tetramitiformis.
Cross-sectional Association Between Plasma Biomarkers and Multimorbidity Patterns in Older Adults
Authors: Vázquez-Fernández Aitana , Lana Alberto , Struijk Ellen A , Vega-Cabello Verónica , Cárdenas-Valladolid Juan , Salinero-Fort Miguel Ángel , Rodríguez-Artalejo Fernando , Lopez-Garcia Esther , Caballero Francisco Félix 
Published: October 2023

Abstract
Multimorbidity is the simultaneous presence of 2 or more chronic conditions. Metabolomics could identify biomarkers potentially related to multimorbidity. We aimed to identify groups of biomarkers and their association with different multimorbidity patterns. Cross-sectional analyses were conducted within the Seniors-ENRICA-2 cohort in Spain, with information from 700 individuals aged ≥65 years. Biological samples were analyzed using high-throughput proton nuclear magnetic resonance metabolomics. Biomarker groups were identified with exploratory factor analysis, and multimorbidity was classified into 3 types: cardiometabolic, neuropsychiatric, and musculoskeletal. Logistic regression was used to estimate the association between biomarker groups and multimorbidity patterns, after adjusting for potential confounders including sociodemographics, lifestyle, and body mass index. Three factors were identified: the “lipid metabolism” mainly reflected biomarkers related to lipid metabolism, such as very-low-density lipoprotein and low-density lipoprotein cholesterol; the “high-density lipoprotein cholesterol” mainly included high-density lipoprotein cholesterol subclasses and other lipids not included in the first factor; and the “amino acid/glycolysis/ketogenesis,” composed of some amino acids, glycolysis-related metabolites, and ketone bodies. Higher scores in the “lipid metabolism” factor were associated with a higher likelihood of cardiometabolic multimorbidity, odds ratio for tertile 3 versus tertile 1 was 1.79 (95% confidence interval: 1.17–2.76). The “high-density lipoprotein cholesterol” factor was associated with lower odds of cardiometabolic multimorbidity [0.51 (0.32–0.82)], and the “amino acid/glycolysis/ketogenesis” factor was associated with more frequent cardiometabolic multimorbidity [1.85 (1.18–2.90)].
Different metabolomic biomarkers are associated with different multimorbidity patterns; therefore, multiple biomarker measurements are needed for a complete picture of the molecular mechanisms of multimorbidity.
Time Use and Well-Being in Family and Other Unpaid Caregivers of Older Adults
Authors: Baik Sol , Lehning Amanda J , Sacco Paul 
Published: October 2023

Abstract

Objectives
Caregivers report limited freedom to engage with others, participate in physical activities, pursue leisure activities, and sleep. Few studies have focused on caregivers’ time use across different activities, particularly how different patterns of time use are associated with well-being. This study aimed to (a) identify time-use profiles of family caregivers of older adults and (b) examine associations between identified time-use profiles and caregiver well-being.

Methods
We analyzed data from 1,640 family caregivers of community-dwelling older adults from Round 7 (2017) of the National Study of Caregiving and the National Health and Aging Trends Study. Latent profile analysis was used to estimate time-use profiles based on 4 indicators (i.e., regenerative time, discretionary time, eldercare-related committed time, non-eldercare committed time). We conducted regressions to examine the relationship between the latent profiles and well-being outcomes.

Results
Three profiles of caregivers emerged based on time-use patterns. The Overloaded profile (20%) spent the greatest time in non-eldercare committed activities, such as household activities and paid work. The Flexible profile (49%) spent the most amount of time in social activities and physical activities, and the least amount of non-eldercare committed time compared to the other 2 caregiver types. Lastly, the Occupied profile (31%) allocated time relatively evenly in all activities. When comparing well-being outcomes, caregivers in the Flexible profile had lower levels of anxiety than the Occupied profile.

Discussion
The profiles acknowledge the diverse experiences of caregivers, underscoring the significance of granting them greater latitude in balancing eldercare responsibilities and personal life for enhanced well-being.