bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fracture Growth Through Microseismic Quiescent Zones: Indication of Stealth or Complex Fracturing?
Authors: Maxwell S. C. , Doss S. , Holman R. , Bryce B. 
Published: January 2025

Abstract
Often microseismicity levels tend to vary from one lithological unit to the next, with some layers being predominantly quiet and lack any microseismicity. Since shear activated deformation associated with microseismicity will depend on the geomechanical properties and natural fabric of the formation, the lack of microseisms in certain layers may or may not be indicative of a change in the hydraulic fracture geometry. In this work, microseismic observations are integrated with strain and other observations to investigate the microseismic response in relation to the underlying hydraulic fracture geometry for different rock types. The combined conclusions allow identification of two distinct types of response for aseismic layers. The first type are ‘stealth’ homogeneous layers that behave aseismically with the lack of natural fabric to host shear activated microseisms from consistent fracture growth. The second type are interbedded shaly layers where the lack of microseismicity is associated with fracture complexity that results in compartmentalized portions of the hydraulic fracture which may not effectively drain the reservoir. Examples are described of these types from integrated monitoring of hydraulic fracture growth in Uinta Basin, Utah and Midland Basin, Texas.
Incorporating Physical Observations into Analytical Models for Enhanced Well Performance Prediction in the Midland Basin
Authors: Block Adam , Cross Cameron , Bernet Carl , Kang Charles , Sufit Jessica , McClure Mark , Yotter Tim 
Published: January 2025

Abstract
This paper focuses on integrating physical observations and techniques into analytical models to improve well performance predictions in the Midland Basin. By incorporating physical and geological insights through feature engineering and hybrid modeling approaches, we aimed to enhance the accuracy and generalizability of various machine learning models. The study explored three key areas: the development of a physics-informed multivariate regression (MVR) model, the integration of a hybrid, fully-coupled reservoir and fracture simulator with machine learning, and the incorporation of dynamic production and pressure variables into a time-series multivariate regression (DMVR) model. The results demonstrate that combining physical principles with data-driven models can lead to improved understanding for well spacing, completion strategies, and reservoir management decisions.
A younger trend in acute myocardial infarction in China and a novel classification of clinical risk factors: “A single center retrospective study”
Authors: Hu Chunsong 
Published: January 2025

Abstract

There has been a significant increase in the number of acute myocardial infarction (AMI) in China. However, little is known about the age trend and comprehensive clinical risk factors (CRF). Here, data on the ages of AMI patients in China from 1990 to 2019 were collected and divided groups: 1990s, 1995s, 2000s, 2005s, 2010s, 2015s and 2020s. The mean minimum age for each group was approximately 55.0 (1990s), 46.4 (1995s), 48.2 (2000s), 55.0 (2005s), 47.1 (2010s), 43.9 (2015s), and 52.8 (2020s) years. The median minimum ages for each group were about 55.0, 58.0, 61.0, 62.0, 59.0, 61.0, and 59.0 years, respectively. Both the mean and median curves showed a trend towards younger for AMI. Additionally, a novel classification for CRF in AMI was developed. In conclusion, there is a younger trend in AMI due to unhealthy E(e)SEEDi lifestyle. The novel CRF classification is helpful in better prevention of AMI globally.
Behavioral Improvement Through In Vivo Base Editing in a Mouse Model of Snijders Blok-Campeau Syndrome
Authors: Yang Kan 
Published: January 2025

Abstract

Snijders Blok-Campeau Syndrome (SNIBCPS) is a rare neurodevelopmental disorder caused by mutations in the CHD3 gene. Here, we report a de novo single-nucleotide variant (c.C3073T, p.R1025W) in CHD3 identified in a child with SNIBCPS, which leads to accelerated degradation of the CHD3 protein. Using a Chd3R1025W/+ knock-in mouse model, we observed impaired vocalization, cognition, and autism-like behaviors. To address these deficits, we developed an improved TadA-embedded adenine base editor (TeABE) and delivered into the mouse brain via Adeno-associated virus (AAV). Base editing in vivo significantly restored CHD3 protein levels in the mouse brain and ameliorated various behavioral abnormalities. Furthermore, we validated the AAV-mediated delivery efficacy of TeABE in nonhuman primate, highlighting its translational potential. These findings establish in vivo base editing as a promising therapeutic strategy for SNIBCPS and pave the way for clinical applications targeting brain disorders.
Regenerative agriculture amplifies productivity and profitability while negating greenhouse gas emissions
Authors: Harrison Matthew , Muleke Albert , Christie-Whitehead Karen , Cain Michelle , Burgess Paul , Wiltshire Katy , Liu Ke , Pexas Georgios 
Published: January 2025

Abstract

The broad philosophy comprising regenerative agriculture can be deconstructed into several underpinning components, including adaptive multi-paddock grazing (AMP), improved biodiversity, silvopasture, and minimal use of cultivation and synthetic fertilisers. Here, we use sheep farms positioned across a rainfall gradient to examine how pasture species diversity, antecedent SOC and AMP influence soil organic carbon (SOC) accrual, greenhouse gas (GHG) emissions, pasture production and enterprise profit. Compared with light grazing intensities for long durations, high-intensity short-duration cell grazing with long spelling periods (AMP) amplified pasture productivity, improving SOC accrual and GHG abatement, increasing profit per animal and hectare. Renovation of pastures with high-yielding, low-emissions ecotypes enhanced pasture production and carbon removals, albeit to a lesser extent than that realised from AMP. Adaptive grazing management, where animals were moved in response to pasture residual, evoked the greatest SOC accrual and GHG abatement, but also increased supplementary feed costs. Low stocking rates with longer spelling periods between grazing events were the most profitable, highlighting the need for agile, proactive grazing management adapted in line with seasonal conditions. We conclude that (1) whole farm stocking rate and seasonal rainfall quantum have greater influence on pasture production, SOC, GHG and profit compared with species diversity and grazing management, (2) individual pasture species – rather than species diversity – have greater bearing on sward production, (3) notwithstanding carbon removals via improved SOC, CH4 from enteric fermentation dominates farm GHG profiles, and (4), AMP can catalyse SOC accrual and sward production compared with lighter stocking conducted for longer durations, but only when whole farm stocking rate is harmonised with long-term sustainable carrying capacity, with the latter being a function of plant-available water capacity and drought frequency.
SFPQ Directs Histone H3.3 Deposition to R-Loops in DNA Repeats to Protect Genome Stability
Authors: Schoeftner Stefan , Ferrando Alessandro , Gambelli Alice , Broccia Pamela Veneziano , Zappone Annie , Napolitano Luisa , Canarutto Giulia , Giaquinto Michele , Petti Eleonora , Framarini Alessandro , Onesti Silvia , Piazza Silvano , Benetti Roberta 
Published: January 2025

Abstract

R-loops are three-stranded nucleic acid structures that contain an RNA:DNA hybrid duplex and an unpaired single stranded DNA loop. Unscheduled or persistent R-loops drive genome instability by creating conflicts with transcription and replication. Up to 75% of the human genome comprises repetitive DNA elements that can engage in R-loop formation. We demonstrate that the RNA binding protein SFPQ suppresses R-loop mediated replication stress and DNA damage at repeat elements such as telomeres, (peri)-centromeres, LINE-1 and SINE elements. SFPQ shows in-vitro R-loop binding activity, binds to chromatin containing R-loops and recruits the histone H3.3 specific chaperon DAXX to maintain a correct nucleosome template that antagonizes R-loop formation. Loss of SFPQ results in DAXX delocalization from repeat elements, reduction of histone H3.3 incorporation, replication stress mediated genome instability and the formation of cytoplasmatic DNA species, which activate innate immunity pathways via the cGAS/STING pathway resulting improved sarcoma patient survival.
Experimental and Numerical Study on the Bearing Capacity of Tapered Piles in Sand Under Compressive Load
Authors: mohammadizadeh moein , mohammadizadeh mohsen 
Published: January 2025

Abstract

Deep foundations are widely recognized as one of the most effective methods for transferring surface loads to subsurface soil layers. While cylindrical piles are the conventional choice for deep foundations, tapered piles offer significant advantages in load transfer and material efficiency. This study investigates 12 types of tapered piles with varying characteristics in the loose and dense soils under static loading conditions in both loose and dense sands through laboratory experiments. The behavior of tapered piles is also modeled numerically using finite difference analysis, and the numerical results are validated against the experimental data. Additionally, a parametric analysis is conducted to evaluate the influence of design variables such as taper angle, pile length and sand relative density on the load-settlement behavior. The comparative analysis between tapered and cylindrical piles identifies an optimal taper angle for homogeneous sands, revealing that the bearing capacity decreases by 2.86 degrees with an increase in pile angle. Moreover, increasing the relative density of the soil results in a 2- to 3-fold improvement in the bearing capacity of the piles.
Spatial distribution of light-melanosome interaction dependent on irradiation fluence and spot size for short-pulsed laser skin treatment: A phantom study
Authors: Takeda Gakuto , Shimojo Yu , Ozawa Toshiyuki , Nishimura Takahiro 
Published: January 2025

Abstract

Purpose: Short-pulsed lasers provide safe and efficacious treatment of pigmented lesions by setting irradiation parameters based on immediate whitening resulting from vacuolization. However, visual observation of this phenomenon as an irradiation endpoint is subjective and makes it difficult to assess the depth to which the light response is induced inside the skin. To quantitatively understand the dependence of the light response on irradiation parameters, this study analyzes the spatial distribution of light-melanosome interaction based on the fluence distribution in an optical phantom.
Methods: Nanosecond laser irradiation was applied to an optical phantom with a uniform distribution of melanosomes with varying irradiation fluence and spot size. The observed spatial distribution of the light-melanosome response was compared with the fluence distribution in the phantom calculated from numerical simulations.
Results: The resulting relationship between irradiation parameters and optical response showed that cavitation increased rapidly at an in-phantom fluence of 1.37 J/cm$^2$ and reached a saturated state at the threshold fluence for melanosome disruption. Additionally, increasing the spot size promoted cavitation at greater depths as well as increasing irradiation fluence, highlighting the need to consider both irradiation fluence and spot size for treatment depth control.
Conclusion: The experimental results suggest the potential for quantitative control of optical responses in laser treatment of pigmented lesions. Further validation by experiments on samples with spatial distribution of cutaneous melanosomes is required.
Endometrial preparation protocols did not impact outcomes after frozen-thaw embryo transfer for chronic endometritis treatment
Authors: Shi Xiao , Zhang Shuyi 
Published: January 2025

Abstract

Background
Intended to investigate the potential effects of endometrial preparation procedures on the results of subsequent frozen embryo transfer (FET) cycles in infertile women with chronic endometritis (CE) following a single course of antibiotic therapy.
Methods
From July 2020 to December 2023, 773 infertile patients participated in a retrospective research. CD138 was immunostained in endometrial tissues taken during the proliferative phase. CE was suggested by the presence of CD138-positive cells in the stromal cells. Oral antibiotics were administered to every patient with a CE diagnosis. After CE was cured, patients had frozen embryo transfers and endometrial preparation. This study compared the impact of different endometrial preparation techniques on pregnancy outcomes.
Results
Hormone replacement treatment (HRT), ovulation induction, natural cycle, and gonadotrophin-releasing hormone agonist-HRT (GnRH agonist-HRT) regimens did not significantly alter the outcome of pregnancy in patients with CE. Compared to other groups, the ovulation induction cycle group had a higher clinical pregnancy rate and embryo implantation rate. However, the miscarriage rate is lower compared to other populations. Patients with treated CE who received HRT, GnRH agonist-HRT, ovulation induction cycle, and natural cycle did not differ substantially (P > 0.05).
Conclusion
Patients with cured CE did not see any change in pregnancy outcomes as a result of endometrial preparation procedures.
The duration of intensive vegetable cultivation regulates the fates of accumulated nitrate under reductive soil disinfestation
Authors: Zhang Huimin , Wang Jing , Fallah Nyumah , Uwiragiye Yves , Qian Yinfei , Yi Cheng , zhang Maoheng , Cai Zucong , Müller Christoph 
Published: January 2025

Abstract

Purpose
Reductive soil disinfestation (RSD) can remove over-accumulated nitrate (NO3−-N) from topsoil in intensive vegetable fields via elevating NO3−-N consumption processes. The duration of intensive vegetable cultivation may affect the relative importance of these consuming processes of NO3−-N during RSD treatment by altering topsoil properties. However, it remains elusive how the duration of intensive vegetable cultivation affects the fates of topsoil NO3−-N during RSD treatment.
Methods
Here, a soil column experiment labeled with K15NO3 was conducted to investigate the effects of different cultivation ages (5, 10, 20 and 30 years) of intensive vegetables on the fates of topsoil NO3−-N under RSD treatment.
Results
The results showed that more than 91.8% of the added 15NO3−-N in topsoil was removed by RSD treatment, regardless of cultivation years. There was a trade-off between denitrification and NO3−-N leaching into the subsoil, both of which together accounted for 85.5–97.1% of the added 15NO3−-N, regardless of cultivation years. The proportion of gaseous 15N loss via denitrification to added 15NO3−-N (Pdenitrification) initially increased from 5 to 10 years of cultivation, and then decreased with further cultivation ages, but the trend was reversed for the proportion of leaching of 15NO3−-N into the subsoil to added 15NO3−-N (Pleaching). The structural equation model revealed that the initial soil carbon/nitrogen ratio had an indirect positive effect on Pdenitrification by driving the initial nirK abundance under RSD treatment.
Conclusion
Overall, our results highlight the critical role of using RSD in removing accumulated NO3−-N from the topsoil with its fates of a trade-off between Pdenitrification and Pleaching as ages of intensive vegetable cultivation.
Effective Estrogen Receptor Status Classification in BreastCancer Using a Single TMA Image and HGCN-CNN Ensemble
Authors: Kousha Atefeh Azin , Zhang Jingxin 
Published: January 2025

Abstract

Introduction: This study proposes a Computer-Aided Diagnosis (CAD) method to determine Estrogen Receptor Status (ERS) in breast cancer patients using Hematoxylin and Eosin (H&E)-stained tissue microarray (TMA) images. It is the first to explore the contributions of graph-based analysis for this task and their integration with conventional Convolutional Neural Network (CNN)-based approaches.
Methods: A graph model of H&E-stained images is proposed, representing intercellular spatial dependencies as graph edges. We explore the significance of intercellular spatial relationship properties derived from cellular morphology and graph topology, which have been unexplored in previous studies. Additionally, this work combines the results of the proposed graph classifier with those of well-established Convolutional Neural Network(CNN) classifiers to optimize accuracy.
Results: The proposed Hybrid Graph Convolutional Network (HGCN) achieves 14%,25%, and 39% higher specificity compared to the popular pre-trained CNN classifiers VGG16, DenseNet121, and ResNet50, respectively. Whereas, HGCN demonstrates lower sensitivity than these CNN classifiers. By combining the strengths of both approaches in a novel HGCN-CNN ensemble, a well-balanced trade-off between sensitivity and specificity is achieved, resulting in the highest Area Under the Receiver Operating CharacteristicCurve (AUC-ROC) of 87% among all the classifiers. The ensemble outperforms individual CNN classifiers in accuracy, AUC-ROC, and specificity while also exceeding the HGCN classifier in accuracy, AUC-ROC, and sensitivity. These results are obtained from a training dataset of 1,000 H&E-stained TMA images and a test dataset of 554 TMA images.
Conclusions: The results demonstrate that the graph-based approach offers significantly higher specificity compared to popular pre-trained CNN classifiers, while the CNN classifiers excel in sensitivity. The proposed HGCN-CNN ensemble effectively leverages the complementary strengths of both classifier types, enhancing overall binary classification performance in terms of AUC-ROC and accuracy compared to all individual classifiers.
Low-lethality strategies: Impacts on Panonychus citri transgenerational fitness and Neoseiulus californicus effectiveness
Authors: QAYYOUM MUHAMMAD ASIF , Zi-Wei Song , Dun-Song Li , Saeed Khan Bilal , Tain-Ci Yi 
Published: January 2025

Abstract

Background:
The study explores the use of botanical pesticides as an environmentally friendly alternative to synthetic methods for controlling citrus red mites and biological pests, comparing their sublethal effects on Panonychus citri (Acari: Tetranychidae) and Neoseiulus californicus (Acari: Phytoseiidae).
Results:
The study showed that lowlethal (LC30) exposure to oils significantly reduced the fecundity rate of the F0 and F1 generations of P. citri, similar to synthetic chemicals. VO (Soybean oil) and ES (EnSpray) were more effective in reducing developmental stages and population life parameters. All population life parameters were significantly reduced in all treatments compared to the control. VO accelerated population growth over time. Chemical combinations had synergistic effects against F2 generations, except for VO: ES and ES: ABA (Abamectin). The next generation population of VO and ES were better perfume compared to SYP (SYP-9625) and ABA in terms of attractiveness, prey consumption, and fecundity rate. The greenhouse study revealed that N. californicus displays repellent behavior towards treated plantations, increasing with predatory mite density, with synthetic chemicals having a significant sublethal effect.
Conclusion:
The study found that synthetic chemicals, such as ABA and SYP, caused faster adult mortality and higher lethality in Panonychus citri and Neoseiulus californicus. These chemicals also significantly reduced fecundity, adult longevity, and egg hatchability in the parental generation, with SYP being the most effective. The above results showed that exposure to oils significantly reduced the fertility rate of P. citri, similar to synthetic chemicals. VO and ES decreased developmental stages in the F1 generation, accelerated population expansion in the F2 generation, and increased prey consumption toward VO and ES of N. californicus. The study emphasizes the need for balancing efficacy and environmental safety in acaricide development and application.
STFNIoT:Lightweight IoT Intrusion Detection Based on Explainable Analysis Using Spatiotemporal Fusion Networks
Authors: Chen Hanlin , Liu Huan , Yang Wenjun 
Published: January 2025

Abstract

With the widespread popularity of IoT applications, IoT devices are increasingly becoming targets of cyber attacks. Existing intrusion detection systems usually face computing resource limitations and accuracy challenges when facing complex, high-dimensional attack traffic data. Therefore, this paper proposes a lightweight IoT intrusion detection framework STFNIoT based on interpretable analysis of spatiotemporal fusion networks, which combines principal component analysis (PCA) and deep learning models to address the above problems. PCA performs data dimensionality reduction to reduce feature redundancy while retaining key information. Subsequently, a spatiotemporal fusion network(STFN) is used for feature learning. STFN contains two key components: a convolutional neural network (CNN) for extracting spatial features and a bidirectional long short-term memory network (BiLSTM) for capturing time-dependent features, thereby efficiently learning the spatiotemporal relationship between IoT devices. In addition, the framework integrates the SHAP interpretability analysis algorithm, which can intuitively reveal the decision-making process of the model and enhance the transparency and reliability of the system. Experimental results show that STFNIoT achieves 100%, 97.70% and 97.15% accuracy in the binary, hexaclass and multiclass tasks of the Edge-IIoTset dataset, respectively, significantly improving the detection performance compared with existing methods. In addition, the modular design of the framework effectively reduces the computational overhead and is suitable for resource-constrained IoT environments. This study provides an efficient and explainable IoT intrusion detection method.