bluuebunny/crossref_metadata_2025_split huggingface dataset:
Leveraging Data from the Genomes to Fields Initiative to
Investigate G×E in Maize in North America
Authors: Lopez-Cruz Marco , Aguate Fernando , Washburn Jacob , de Leon Natalia , Kaeppler Shawn , Lima Dayane Cristina , Tan Ruijuan , Thompson Addie , Bretonne Laurence de la , Campos Gustavo de los 
Published: May 2023

Abstract
Genotype-by-environment (GxE) interactions play a significant role in crop performance and stability. Investigating GxE requires extensive data where diverse genotypes are tested over multiple locations and years. Since 2014, the Genomes to Fields (G2F) initiative has collected phenotype and genotype data for more than 4,000 diverse hybrids tested in more than 130 year-locations combinations in the US and Canada. We curated this data set and expanded it by generating (using a crop model) environmental covariates for each of the trials conducted by the G2F initiative since 2014. The resulting data set includes DNA genotypes and environmental data linked to more than 70,000 phenotypic records of grain yield and flowering traits in North America. We used multivariate analyses to characterize the data set’s genetic and environmental structure, study the association of key environmental factors with grain yield and flowering traits, and provide benchmarks using state-of-the-art genomic prediction models. The workflows used to generate and analyze the data set are provided as open-source code. The data set that we introduce in this study can serve as a benchmark in agricultural modeling and prediction, and paves the way for countless GxE investigations in maize.
Ridge-twin boundaries as prolific dislocation sources in low stacking-fault energy metals and alloys
Authors: Fu Xiaoqian , Ding Jun , Ozsoy-Keskinbora Cigdem , Yang Guang , Chen Yujie , Fang Yan , Park Eun Soo , Zhang Ze , Ritchie Robert , Ma En , Yu Qian 
Published: May 2023

Abstract
Dislocation activities are crucial in facilitating plastic deformation, even in metals that are prone to deformation twinning. We have discovered a novel type of prolific dislocation sources, which reside on nano-sized ridges along the borders between different twin variants in low stacking-fault energy (SFE) materials. These sources act as dislocation generators that promote dislocation interaction and accumulation, spreading plastic strain and leading to robust strain hardening at the early stages of plastic deformation. Molecular dynamic simulations indicate that the formation of nano-sized ridge-twin structures is energetically favorable at the junctions between multiple twins, explaining why such structures are ubiquitous in low-SFE materials. Decreasing the SFE can significantly increase the population of ridge-twin boundaries, facilitating strain hardening to sustain the stability of plastic flow. These findings provide new insights into the origin of dislocation plasticity and the high early-stage strain hardening rate in low-SFE materials.
PTEN regulated PI3K-p110 and AKT isoform plasticity controls metastatic prostate cancer progression
Authors: Miller Karina , Degan Seamus , Wang Yanqing , Cohen Joseph , Ku Sheng-Yu , Goodrich David , Gelman Irwin 
Published: May 2023

Abstract
PTEN loss, one of the most frequent mutations in prostate cancer (PC), is presumed to drive disease progression through AKT activation. However, two transgenic PC models with Akt activation plus Rb loss exhibited different metastasis development: Pten/RbPE:−/− mice produced systemic metastatic adenocarcinomas with high AKT2 activation, whereas RbPE:−/− mice deficient for the Src-scaffolding protein, Akap12, induced high-grade prostatic intraepithelial neoplasias and indolent lymph node disseminations, correlating with upregulated phosphotyrosyl PI3K-p85α. Using PC cells isogenic for PTEN, we show that PTEN-deficiency correlated with dependence on both p110β and AKT2 for in vitro and in vivo parameters of metastatic growth or motility, and with downregulation of SMAD4, a known PC metastasis suppressor. In contrast, PTEN expression, which dampened these oncogenic behaviors, correlated with greater dependence on p110α plus AKT1. Our data suggest that metastatic PC aggressiveness is controlled by specific PI3K/AKT isoform combinations influenced by divergent Src activation or PTEN-loss pathways.
Multi-scale feature fusion object detection with bidirectional feature pyramid network and secondary candidate box refinement
Authors: Sun Yibo , Li Xue , Liu Chenlei , Xu Bixiao , Gong Jing , Sun Zhe 
Published: May 2023

Abstract
As a task to locate and classify objects of interest in given images or videos, object detection is a core research direction of computer vision. It promotes intelligent monitoring, face recognition, and image segmentation development. However, deep learning-based object detection models still have a low detection accuracy for small-scale objects. In this paper, we propose a multi-scale feature fusion object detection with a bidirectional feature pyramid network and 1 secondary candidate box refinement, named MS-Faster R-CNN. The strategy, combined with the Feature Pyramid Network(FPN), uses two links to complete the feature fusion, making the semantics of the fused features richer and adapted to different scale objects. In the candidate box recommendation stage, we use the cascaded Region Proposal Network(RPN) and optimized Non-Maximum Sup-pression(NMS) so that the candidate box of the small-scale object would not be over-suppressed, which improves the recommendation efficiency of the candidate box. Finally, the Region of Interest(ROI) Align pooling technology based on the bilinear interpolation method is considered to avoid the loss of accuracy caused by quantization. Extensive experiments show that our scheme has better detection performance than other methods on datasets of Pascal VOC 2007, Pascal VOC 2012, and MS COCO.
ANGPTL4 accelerates carcinogenesis and angiogenesis in the tumor microenvironment by activating the JAK2/STAT3 pathway and interacting with ESM1
Authors: Li Yukun , Gao An-bo , Zeng Tian , Zhang Qun-feng , Ran Xiao-min , Tang Zheng-zi , Li Yan , Liu Jue , Zhang Ting , Shi Gang-qing , Zhou Wen-chao , Zou Wen-da , Liu Dan , Peng Juan , Zhang Juan , Li Hui , Zou Juan 
Published: May 2023

Abstract
Ovarian cancer (OC) is a malignant neoplasm that displays increased vascularization. Angiopoietin-like 4 (ANGPTL4) is a secreted glycoprotein that functions as a regulator of cell metabolism and angiogenesis and plays a critical role in tumorigenesis. However, the precise role of ANGPTL4 in the OC microenvironment, particularly its involvement in angiogenesis, has not been fully elucidated. Our study demonstrates a significant upregulation of ANGPTL4 in OC specimens and its strong association with unfavorable prognosis. RNA-seq analysis affirms that ANGPTL4 facilitates OC development by driving janus kinase 2- signal transducer and activator of transcription 3 (JAK2-STAT3) signaling pathway activation. The interaction between ANGPTL4 and endothelial cell-specific molecule 1 (ESM1) promotes ANGPTL4 binding to lipoprotein lipase (LPL), thereby resulting in reprogrammed lipid metabolism and the promotion of OC cell proliferation, migration, and invasion. In the OC microenvironment, ESM1 may interfere with the binding of ANGPTL4 to integrin and vascular-endothelial cadherin (VE-Cad), which leads to stabilization of vascular integrity and ultimately promotes angiogenesis. Collectively, our findings underscore that ANGPTL4 promotes OC development via JAK signaling and induces angiogenesis in the tumor microenvironment through its interaction with ESM1.
Automatic puncture path planning before percutaneous vertebroplasty based on image processing
Authors: Li Yue , Deng Yunjiao , Yan Jiangtao , Liang Shunpan , Hou Yulei , Zeng Daxing 
Published: May 2023

Abstract
Background Percutaneous vertebroplasty (PVP) has become the mainstream method for the treatment of osteoporotic vertebral compression fractures(OVCF). Generally, surgeons manually plan the puncture path by themselves. This is time-consuming and laborious, which increases the working pressure of surgeons. Image processing algorithm is used to automatically segment contour of vertebral body, and plan the puncture path before operation. In order to obtain the contours of vertebral body and skin, binarization and contour extraction algorithm were performed. The connecting algorithm we proposed was used to connect the discontinuous contour of vertebral foramen. We determined the centerline of vertebral body by inscribed circle center of the contours of vertebral body and vertebral foramen, located the narrowest part of vertebral pedicle based on rotating segment algorithm and calculated medical parameters. The experimental results show that the segmentation accuracy of algorithm is 95.92%, the average relative error of extracted parameters was no more than 4.18%. This method realizes automatic and accurate planning of puncture path before PVP, and it is of great significance to reduce the workload of surgeons, the number of intraoperative fluoroscopy and the harm of radiation to surgeons.
Hidden periodic states in gas hydrate systems lead to spontaneous gas release without external triggers
Authors: Burwicz-Galerne Ewa , Schmidt Christopher , Rüpke Lars , Gupta Shubhangi 
Published: May 2023

Abstract
Gas hydrates are one of the largest marine carbon reservoirs on Earth. The conventional understanding of hydrate dynamics assumes that the system converges to a steady-state over geological time-scales, achieving fixed concentrations of gas hydrate and free gas phase. However, using a high-fidelity numerical model and consistently resolving phase states across multiple fluid-fluid and fluid-solid phase boundaries, we have identified well-defined periodic states embedded within hydrate system dynamics. These states lead to cyclic formation and dissolution of massive hydrate layers that is self-sustaining even in the absence of external triggers. This previously unresolved characteristic could manifest as spontaneous gas discharge and pressure release in, supposedly, unperturbed systems. Our findings challenge the foundational principle that the gas hydrate systems have unique steady-state solutions. Instead, existence of periodic states introduces an irreducible uncertainty in gas hydrate dynamics which puts significant error bars on previous hydrate estimates.
A Deep Learning Framework for Multi-Cancer Detection in Medical Imaging
Authors: Desale Ketan , Asole Prasanna , Bhosale Girish , Bhos Sanket , Ambhore Ankush 
Published: May 2023

Abstract
Cancer is the second leading cause of death worldwide, and finding the disease at an early stage significantly increases the chances that treatment will be successful. The conventional methods of diagnosing cancer, such as biopsies and imaging, can be invasive, time-consuming, and costly. In the field of cancer detection, deep learning algorithms have recently demonstrated a great deal of promise. In this research paper, we have applied one of the most discussed deep learning method Convolutional Neural Network (CNN) with three different architectures which are currently making an important place in this field. We have worked with DenseNet201, VGG16, and MobileNetV3 for the detection of multiple forms of cancer that is based on deep learning. This research made use of a dataset that contained images and data from patients who had been diagnosed with various types of cancer, including Acute lymphoblastic Leukemia, Brain Cancer, Breast Cancer, Cervical Cancer, Kidney Cancer, Lung and Colon Cancer, Lymphoma, Oral Cancer. The findings point to the potential of deep learning algorithms in the early detection of multiple types of cancer. If successful, this would result in better patient outcomes and lower overall healthcare costs.
Extreme Weather Events and the Performance of Critical Utility Infrastructures: A Case Study of Hurricane Harvey
Authors: Rafi Shahnawaz , Meng Sisi , Santos Joost , Mozumder Pallab 
Published: May 2023

Abstract
Extreme weather events have considerable economic and social ramifications by disrupting public utility services, such as power outages, disconnecting phone service, and transportation interruptions. This study seeks to understand the performance and resilience of critical infrastructure systems in Houston, Texas, using Hurricane Harvey (2017) as a case study. We surveyed five hundred residents of the Houston Metropolitan Statistical Area after Hurricane Harvey's landfall. Our initial data analysis concentrated on the number of homes that reported interruptions in electricity, water, phone/cellphone, Internet, public transportation, places of employment, and grocery stores. We also estimate the duration of each type of disruption. Around 69% of the respondents reported electricity disruption, while half (49%) had no water supply for up to six days. Two-thirds of the surveyed households did not have internet access, and 47% had their phone services disconnected. Finally, around 70% of the respondents could not commute to their workplace, while 71% could not buy groceries for their families. We incorporated the household survey responses into the Dynamic Inoperability Input-Output Model (DIIM) to estimate inoperability and economic losses in multiple linked sectors. The total economic loss was estimated to be over $6 billion, and workforce disruption is the major challenge that policymakers must consider for improving resilience. Understanding the resilience of each sector and the inherent interdependencies across the sectors can provide helpful input to policymakers for disaster risk management, notably preparedness and recovery planning for future events.
JEL Classification: Q50, Q54. R11, R12, R15
Deep sea treasures - insights from museum archives shed light on coral microbial diversity and functioning within deepest ocean ecosystems
Authors: Ricci Francesco , Leggat William , Pasella Marisa , Bridge Tom , Horowitz Jeremy , Girguis Peter , Ainsworth Tracy 
Published: May 2023

Abstract
Deep sea benthic habitats are low productivity ecosystems that host an abundance of organisms within the Cnidaria phyla. The technical limitations and the high cost of deep sea surveys have made exploring deep sea environments and the biology of the organisms that inhabit them challenging. In spite of the widespread recognition of Cnidaria's environmental importance in these ecosystems, the microbial assemblage and its role in coral functioning have only been studied for a few deep water corals. Here we explored the prokaryotic diversity of deep sea corals by recovering nucleic acids from museum archive specimens. Firstly, we amplified and sequenced the V1-V3 regions of the 16S rRNA gene of specimens held in museum archival storage and utilised these to shed light on the microbial diversity associated with seven families of corals collected from depth in the Coral Sea (depth range 1,309 to 2,959 metres) and Southern Ocean (depth range 1,401 to 2,071 metres) benthic habitats. Most surprisingly, Cyanobacteria were consistently associated with six out of seven coral families from both sampling locations, suggesting that these bacteria are potentially ubiquitous members of the microbiome within these cold water and deep sea organisms. Consistent with previous studies, we show that the bacterial phyla Proteobacteria, Verrucomicrobia, Planctomycetes and Acidobacteriota dominate the microbial community of corals in the deep sea. We also explored the genomes of the genus Mycoplasma, which we identified as associated with specimens of three deep sea coral families, finding evidence that these bacteria may aid the host immune system. Importantly our results show that museum specimens retain components of host microbiome that can provide new insights into the diversity of deep sea coral microbiomes (and potentially other organisms), as well as the diversity of microbes writ large in deep sea ecosystems.
To sleep perchance to dream - not; Nyctophobia from COVID-19 induced hyposmia
Authors: Kalita Shweta , Birwatkar Drushti , Cosme Rosario , Mehdiratta Nikita , Hirsch Alan Richard 
Published: May 2023

Abstract
Objective:
Increase awareness of the correlation between nyctophobia and hyposmia in individuals with COVID-19.
Background:
Fear of sleep (nyctophobia) has been attributed to various conditions ranging from benign nocturnal panic attacks and Morvan's syndrome. Positional dependent hyposmia as an origin of nyctophobia has not heretofore been described.
Case presentation:
This 52-year-old woman presented with sudden onset of loss of smell and taste with COVID-19, which returned to 85% of normal. However, her symptoms worsened when she would lie down to 30% of normal but would improve with standing, moving, and sitting. Requiring her to stand for hours before her sense of smell would return led to her nyctophobia that forced her to move around all the time.
Conclusions:
Nyctophobia, a fear of positional dependent loss of smell, highlights the importance of smell to a narcissistic perception of self. This can be understood that the olfactory lobe is anatomically part of the limbic system. Deposition of memory engrams is facilitated as manifest with olfactory evoked nostalgia seen in 84% of the general population. The importance of smell is thus intrinsic to an individual's well-being, and the threat of loss of such sensation with a change in position with sleep was the precipitating event leading to nyctophobia in this subject. Assessing for fear of loss of smell in those with nyctophobia, especially with past COVID-19 infection, allows for an increased understanding of etiology and indicates potential treatment approaches.
Spatial Genetic Structure and Seed Quality of a Southernmost Abies nephrolepis Population
Authors: Kim Sunjeong , Lee Hye-Jin , Kim Yang-Gil , Kang Kyu-Suk 
Published: May 2023

Abstract

Abies nephrolepis(Trautv. ex Maxim.) Maxim. has its southernmost populations in South Korea and they are expected to decline under climate change. To establish a strategic conservation plan, this study aimed to investigate the spatial genetic structure and seed characteristics of A. nephrolepis. We used nine microsatellite markers on 165 individuals of A. nephrolepis and sampled seeds in a southernmost population at Mt. Hambaeksan, South Korea. We observed a high level of heterozygosity, and a simulation study found that sampling 20 individuals was enough to secure sufficient genetic diversity on average. Spatial autocorrelation analysis revealed that individuals had a positive genetic relationship until 30 m. Bayesian clustering models, STRUCTURE and GENELAND, failed to achieve a consensus in the optimal number of population (K), estimating K=1 and K=2, respectively. Principal coordinate analysis supported the absence of genetic substructure within a population. There was a large variance in seed production among mother trees. On average, seeds of A. nephrolepis from Mt. Hambaeksan had a purity of 70.4% and germination percentage of 32.2%. We found that seed weight was the most effective indicator of seed quality. Mother trees at higher altitudes had poorer purity which is threatening to A. nephrolepis considering the upslope retreat of subalpine species under climate change. Our results provide insights into the interactions among spatial processes, genetic structure, and seed quality within a population of A. nephrolepis.
A Study Of I.Q Levels In Children With Autism Spectrum Disorder In Syria And The Importance Of Categorization By These Levels In Rehabilitation Centers
Authors: Al-Assaf Abd Al-Munem , Al-Bany Maher 
Published: May 2023

Abstract
Background and Aim: The aim of this study is to compare the mental-motor development and the improvement levels in two samples of children with Autism Spectrum Disorder (ASD) from two rehabilitation centers from Damascus, Syria. The first sample consists of children from Center A who underwent the Stanford-Binet I.Q evaluation test in their diagnostic assessment and have been categorized by it and by the severity of their symptoms into different classes. And the second sample, the Center B children. Center B does not give I.Q evaluation tests to its children and does not categorize them by symptom severity and puts children of varying I.Q and symptom levels in shared classes.
The comparison will be done in five fields: The Linguistic Field; The Social Field; The Field of Functional Play; The Field of Academic and Pre-Academic Skills, and The Behavioral Field.
Methods: The study sample consisted of 60 children with ASD which have been divided into two groups: 30 children from Center A and 30 children from Center B.
The age limit of the sample was set between 3-14 years. Type of study: Cross-Section. The time period was set between the dates
1/1/2022 to 1/1/2023 in which to evaluate the progression and improvement in these children.
Results:
- There is a real noticeable improvement that is statistically-significant in The Linguistic Field among the children of Sample A over the children of Sample B within the same timeframe.
- The study found no real statistically-significant improvement difference in The Social Field between the children of Sample A and Sample B within the same timeframe.
- The study found no real statistically-significant improvement difference in The Field of Functional Play between the children of Sample A and Sample B within the same timeframe.
- There is a real noticeable improvement that is statistically-significant in The Field of Academic and Pre-Academic Skills among the children of Sample A over the children of Sample B within the same timeframe.
- There is a real noticeable improvement that is statistically-significant in The Behavioral Field among the children of Sample A over the children of Sample B within the same timeframe.
- There is a real statistically-significant relationship between ASD symptom improvement and the categorization of children into different classes by I.Q level and symptom severity at the time of their diagnosis, and which has encompassed three fields; The Linguistic Field, The Field of Academic and Pre-Academic Skills, and The Behavioral Field.
Observed winter Barents Kara Sea ice variations induce prominent sub-decadal variability and a multi-decadal trend in the Warm Arctic Cold Eurasia pattern
Authors: Ghosh Rohit , Manzini Elisa , Gao Yongqi , Gastineau Guillaume , Cherchi Annalisa , Frankignoul Claude , Liang Yu-Chiao , Kwon Young-Oh , Suo Lingling , Tyrlis Evangelos , Mecking Jennifer V. , Tian Tian , Zhang Ying , Matei Daniela 
Published: May 2023

Abstract

The observed winter Barents-Kara Sea ice concentration (BKS SIC) has shown a close association with the second empirical orthogonal function (EOF) mode of Eurasian winter surface air temperature (SAT) variability, known as Warm Arctic Cold Eurasia (WACE) pattern. However, the potential role of BKS SIC on this WACE pattern of variability and on its long-term trend remains elusive. Here, we show that from 1979 to 2022, the winter BKS SIC and WACE association is most prominent and statistically significant for the variability at the sub-decadal time scale for 5 to 6 years. We also show the critical role of the multi-decadal trend in the principal component of the WACE mode of variability for explaining the overall Eurasian winter temperature trend over the same period. Furthermore, a large multi-model ensemble of atmosphere-only experiments from 1979 to 2014, with and without the observed Arctic SIC forcing, suggests that the BKS SIC variations induce this observed sub-decadal variability and the multi-decadal trend in the WACE. Additionally, we analyse the model simulated first or the leading EOF mode of Eurasian winter SAT variability, which in observations, closely relates to the Arctic Oscillation (AO). We find a weaker association of this mode to AO and a statistically significant positive trend in our ensemble simulation, opposite to that found in observation. This contrasting nature reflects excessive hemispheric warming in the models, partly contributed by the modelled Arctic Sea ice loss.