bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diversity of volcanism and evidence of discrete eruption centres in the Miocene Andes of Central Chile
Authors: Leiva Camila , Browning John , Marquardt Carlos , Clunes Matias , Villarroel Matias , Espinosa Javier , Meyer Martin , Payacán Italo , Mpodozis Constantino 
Published: July 2023

Abstract

The geology of the Farellones region in the Andean Cordillera of central Chile, comprise a thick sequence of volcanic and volcaniclastic Miocene rocks. The occurrence of discrete eruption centres within this sequence, whilst suggested, has been difficult to stablish, as in the modern volcanic systems of the SVZ to the southeast of the study area. Here we report, for the first time a previously uncharacterized composite (Cerro Colorado Volcano) associated to a series of intercalated lava flows and pyroclastic deposits of basaltic to rhyolitic composition of Miocene age. Eruptive sequences reach 1.7 km in vertical section, yet the lateral continuity of units is interrupted by a major faults, and gravity collapse deposits. We document a series of large pyroclastic block and ash flows, which are overlain by rhyolitic pyroclastic density currents, ash fall and crystal, lithic and vitric tuffs, all making up more than 300 m of the sequence. A further 300 m thick unit of spherulite-bearing rhyolitic lavas represent the upper most section of the Cerro Colorado volcano. During the early stages of its construction magmas and hydrothermal fluids interacted to form a maar-diatreme system (Quebrada Lunes maar-diatreme). Much of the volcanic units are intruded by E-W and NW-SE striking andesitic and rhyolitic dikes One of the dikes exhibits internal pyroclastic textures evidence of shallow conduit fragmentation. This pyroclastic dike is further evidence of magma-fluid interaction and related explosivity. Similar pyroclastic breccias described elsewhere related to porphyry copper mineralization. Our results indicate that Miocene volcanism in the Andes of Central Chile is linked to discrete eruptive centres which can be identified and characterized through careful field mapping.
IoT-enabled Personalized English Learning in Colleges using Big Data Analysis and Decision Support System
Authors: Wu Li 
Published: July 2023

Abstract
In recent years, the achievements of technology, particularly in the Internet of Things (IoT) and computer technology, have hastened their incorporation into education. To create novel educational opportunities for improving the effects of teaching and learning on management decision-making. On the other hand, this study represents establishing a personalized, IoT-enabled environment for learning college English that employs big data analysis and a decision support system based on a data mining algorithm. Educational analytics generates useful learning outcomes by analyzing provided data, enhancing numerous personalized learning experiences in Chinese, French, and English. The study aims to improve college and university students' English learning experiences using IoT devices, classroom data collection, and data mining techniques. Big data analysis examines the collected data, yielding insightful results that improve real-time customization of English learning experiences. The recommended platform includes an intelligent decision-support system that uses the ARTXP algorithm data mining model based on time series data from English learning resources downloaded by college students to provide each user with personalized educational instructions. The building structure includes a specific information model based on student profiles and preferred learning methods. The site's database of learning resources is available in English knowledge points. The expectation-maximization (E.M.) strategy groups users with similar learning patterns, whereas the recommendation model selects and predicts learning outcomes for adjacent users. The approach employs time series data from English language learning resources and is built on the Cross-Industry Standard Process for Data Mining (CRISP-DM) paradigm. The platform's accuracy, precision, and stability are demonstrated in testing results, emphasizing its ability to significantly boost the efficacy of college English learning.
Deep Learning-Based Localization of Preoperative Parathyroid Glands in Secondary Hyperparathyroidism Using Dual-Modality Data from Unenhanced CT and Contrast-Enhanced CT
Authors: Yang Hao , Li Fuqiang , Zhang Yao , Wen Yijing , Wang Xiaomei 
Published: July 2023

Abstract
Background
Accurate preoperative localization of parathyroid glands (PGs) is crucial in patients with secondary hyperparathyroidism (sHPT) who are scheduled for parathyroidectomy (PTx) surgery. Nonetheless, despite its importance, this remains a challenging task. The existing medical imaging techniques used for preoperative PG localization have varying levels of sensitivity and accessibility. This study aims to construct a deep-learning model based on a multimodal framework for identifying PGs drawing on a dual-modality dataset consisting of plain CT and enhanced CT, we validate the model’s sensitivity in clinical performance.
Methods
A retrospective study was conducted using a dataset of 94 CT images from 47 patients. For each patient there is a plain CT and an enhanced CT scanned image. The data were randomly partitioned into a training set (38 cases, 76 CT images) and a test sets (9 cases, 18 CT images). A U-Net model was trained on the training set then validated on the test set. In our analysis, the sensitivity of recognizing PGs with imaging information of various modalities was compared between the developed model and clinical physicians. An error analysis and an inter-modal imaging complementarity analysis were performed to provide references for subsequent model enhancement and application.
Results
The identification of parathyroid glands (PGs) using dual-modality CT has shown a diagnostic sensitivity of 94.44%. This result is significantly higher than those obtained by clinicians using ultrasound (61.11%, P = 0.0013) and CT (72.22%, P = 0.0238). Additionally, the sensitivity achieved by dual-modality CT is comparable to that of Tc-MIBI SPECT/CT (86.11%, P = 0.429). We also found that combining the predictions from this model with other imaging modalities could further improve the detection rate of PGs.
Conclusions
To the best of our knowledge, this study is the first to use artificial intelligence techniques with CT bimodal data for preoperative localization of parathyroid glands. The findings of the study suggest that using a deep learning model with plain and enhanced CT data can improve the ability to identify parathyroid glands prior to thyroidectomy or parathyroidectomy.
Human influence on late Holocene fire history in a mixed-conifer forest, Sierra National Forest, California
Authors: Klimaszewski-Patterson Anna , Dingemans Theodore , Morgan Christopher T. , Mensing Scott A. 
Published: July 2023

Abstract
Understanding pre-1850s fire history and its effect on forest structure can provide insights useful for fire managers in developing plans to moderate fire hazards in the face of forecasted climate change. While climate clearly plays a substantial role in California wildfires, traditional use of fire by Indigenous people also affected fire history and forest structure in the Sierra Nevada. Disentangling the effects of human versus climatically-induced fire on Sierran forests from paleoecological records has historically proved challenging, but here we use pollen-based forest structure reconstructions and comparative paleoclimatic-vegetation response modeling to identify periods of human impact over the last 1300 years at Markwood Meadow, Sierra National Forest. We find strong evidence for anthropogenic fires at Markwood Meadow ca. 1550–1750, contemporaneous with archaeological evidence for fundamental shifts in Indigenous lifeways. When we compare our findings to five other paleoecological sites in the central and southern Sierra Nevada, we find evidence for contemporaneous anthropogenic effects on forest structure across a broad swath of cismontane central California. This is significant because it implies that late 19th and early 20th century forest structure – the structure that land managers most often seek to emulate – was in part the result anthropogenic fire and precolonial resource management. We consequently suggest that modern management strategies consider (1) further incorporating traditional ecological knowledge fire practices in consultation with local tribal groups, and (2) using pollen-based reconstructions to track how forest composition compares to pre-1850 conditions rather than the novel forest states encountered in the late 20th and early 21st centuries. These strategies could help mitigate the effects of forecast climate change and associated megafires on forests and on socio-ecological systems in a more comprehensive manner.
Deep learning-based method for reducing the number of transmitting coils in logging while drilling tool
Authors: Liu Qiwei , Kong Fanmin , Chen Xiaolong , liu yong , Li Kang 
Published: July 2023

Abstract
Electromagnetic wave logging while drilling (LWD) technology is an important tool for evaluation of formation oil and gas content. It generally adopts multi-transmitter-receiver coil system structure and the symmetrical coil system arrangement with equal transmitter-receiver spacing can obtain the measurement results with borehole compensation, thus reducing the influence of environmental factors on formation resistivity parameters. At present, the space of the drill collar to hold the coil system is limited and the power supply of the LWD instrument is limited. However, under the premise that the drilling quality remains unchanged, reducing the number of transmitting coils is beneficial to shorten the length of the LWD tool and reduce the power consumption. This paper focuses on reasonable inversion of logging data through deep learning technology, which is combined with Levenberg-Marquardt (LM) algorithm, modular and fast construction of deep neural network (DNN) model. Under the condition of reducing outermost transmitting coil, the measurement results with borehole compensation are realized by inversion, thereby we can shorten the instrument length to reduce drilling tool sticking risk and reduce the LWD instrument structure complexity, high power and other problems. At the same time, the accuracy of inversion is tested. The results show that the DNN method can achieve high-precision inversion, and the average error is reduced by about 50% compared with the traditional algorithm such as linear regression.
Identification of genes associated with the biosynthesis of fatty acid in safflower seeds based on genetic markers and transcriptome analysis
Authors: Fan Kangjun , Qin Yonghua , Hu Xueli , Xu Jindong , Ye Qingzhi , Zhang Chengyang , Ding Yangyang , Li Gang , Chen Yan , Liu Jiao , Wang Peiqi , Hu Zunhong , Yan Xingchu , Xiong Hairong , Liu Hong , Qin Rui 
Published: July 2023

Abstract
Background
Safflower (Carthamus tinctorius L.) is an oilseed crop with substantial medicinal and economic value. However, the methods for constructing safflower core germplasm resources are limited, and the molecular mechanisms of lipid biosynthesis in safflower seeds are not well understood.
Results
In this study, 11 oil-related quantitative traits and 50 pairs of InDel markers were used to assess the diversity of a collection of 605 safflower germplasms. The original safflower germplasm exhibited rich phenotypic diversity, with high variation for most of the phenotypic traits under investigation. Similarly, high genetic diversity was evaluated in the original germplasm, in which the mean Shannon’s information index (I), observed heterozygosity (H0), and expected heterozygosity (He) were 0.553, 0.182, and 0.374, respectively. Four subgroups with strong genetic structures were identified and a core germplasm of 214 cultivars was constructed, which is well represented in the original germplasm. Meanwhile, differential expression analysis of the transcriptomes of high and low linoleic acid safflower varieties at two stages of seed development identified a total of 47 genes associated with lipid biosynthesis. High expression of gene KAS II and SAD gene enhanced the synthesis and accumulation of oleic acid, while FAD genes like FAD2 (Chr8G0104100), FAD3, FAD7 and FAD8 promoted the consumption of oleic acid conversion. The coordinated regulation of these multiple genes ensures the high accumulation of oleic acid in safflower seed oil.
Conclusions
The above results provide a guide for further studies to elucidate the molecular basis of oil accumulation in safflower seeds, contributing to the breeding of safflower seed for oil use.
Correlation between Vitamin D Level and the Development of Idiopathic Scoliosis in Pediatric Population: Early Detection
Authors: Alghadier Mshari , Basalem Nourah , Elnaggar Ragab K , Sallam Sallam Ali , Abbas Amany Mohammed Ebrahim , Zaid Ibrahim Ismail Abu 
Published: July 2023

Abstract
Background
Adolescent idiopathic scoliosis (AIS) is the most common spinal deformity with unclear etiology. Vitamin D deficiency may contribute to the etiology of AIS through its impacts on bone metabolism. The aim of this study is to examine the correlation between vitamin D level and the development of idiopathic scoliosis in pediatric patient.
Methods
This study involved 130 patients diagnosed with idiopathic scoliosis aged 7 to 18 years at a physiotherapy and rehabilitation center, Qena, Egypt, between May 2021 and October 2022. Patients’ clinical and demographic data were extracted from the medical record including age, gender, height, weight, serum vitamin D level, and Cobb angle. Scoliosis was identified when Cobb angle equal to and greater than 10 degrees.
Results
Patients’ mean age was 13.1 ± 2.75 years, mean level of vitamin D in the sample was 10.3 ng/ml ± 4.76, mean weight of 47.4 kg ± 9.63. In the patient group, the mean value of the Cobb angle was 16.8 degrees 5.79 with a 95% CI between 15.8 and 17.8. Vitamin D level was positively correlated with age (p < 0.001, r = 0.45), Cobb angle (p = 0.18, r = 0.11), and weight (p < .001, r = 0.51),
Conclusion
In conclusion, we found that vitamin D deficiency may contribute to the pathogenesis of AIS by affecting the metabolism of calcium and phosphorus in human bone. As a result, we recommended testing vitamin D levels in those with AIS. there is a positive correlation between vitamin D levels and Cobb's angle. Vitamin D deficiency/insufficiency should be examined in patients having AIS.
A digital footprint in enhancing agricultural practices with improved production using machine learning
Authors: C Pabitha , S Benila , A Suresh 
Published: July 2023

Abstract
Agriculture shows an important role in the enlargement of an economy. The proposed system explores how utilizing digital footprints might help improve agricultural practices and production. Agricultural data is increasingly available in digital form because of the development of modern technology and the spread of connected devices. These data can be utilized to produce digital footprints that document the whole lifecycle of agricultural production, from planting to harvesting. Farmers may then decide when to sow, water, fertilize, and harvest their crops by using machine learning algorithms trained on these digital footprints to spot patterns and forecast results. The study examines various machine learning methods that can be used to examine digital footprints and shows the advantages of doing so, including higher yields, better resource management, and lower costs. The timing of crop planting, fertilization, and harvest has long been determined by the agriculture sector using conventional techniques and experience. However, with the expansion of agricultural data available, there is now a chance to use machine learning algorithms to recognize trends and forecast outcomes based on this data. This study explores the potential of machine learning methods, particularly Random Forest optimization, to improve agricultural practices and boost output. The study uses Random Forest optimization, a potent machine learning method that can examine massive datasets, to forecast crop yield based on many variables like weather patterns, soil quality, and fertilizer application. The study's findings show how well the Random Forest optimization technique predicts crop productivity with an accuracy of 99.97%. By giving farmers useful information about forecasting crop yields, they may increase their overall productivity by using their resources wisely. The report also emphasizes the necessity of additional study and funding for the creation of machine learning algorithms that are specifically customized to the peculiarities of the agricultural sector, as well as the significance of data quality and privacy in the collecting and analysis of agricultural data. A combination of hardware and software tools, including data collection sensors, data processing equipment, graphics processing units (GPUs), cloud computing services, and mobile applications, will be needed for the hardware implementation of increasing agricultural practices in production using machine learning with Random Forest optimization techniques.
Ezetimibe suppresses the migration and invasion of triple-negative breast cancer cells by targeting TGFβ2 and EMT
Authors: He Qinyu , Ma Ding , Kong konglingkai , Shi Weiwei , Jiang Chunping , Wu Junhua , Xin Qilei 
Published: July 2023

Abstract
In recent years, the important role of cholesterol in tumor metastasis has been revealed. Ezetimibe is the only selective cholesterol uptake inhibitor currently on the market. Here, we aimed to explore the effect of ezetimibe on breast cancer metastasis. The effects of ezetimibe on breast cancer cell migration, invasion, and EMT were examined by wound healing assay, invasion assay, and western blotting assay. After ezetimibe treatment of breast cancer cells, differentially expressed genes were investigated by transcriptome sequencing and validated by western blotting assay and qRT-PCR. Breast cancer cells overexpressing TGFβ2 were constructed, and the effect of TGFβ2 on the migration and invasion of ezetimibe-treated breast cancer cells was examined by wound healing and invasion assays. The study showed that ezetimibe inhibited the migration, invasion, and EMT of breast cancer cells and significantly suppressed the expression of TGFβ2 in breast cancer cells. Enhanced TGFβ2 expression reversed the inhibitory effect of ezetimibe on the migration and invasion of breast cancer cells. This study demonstrates that ezetimibe is a potential drug for the treatment of breast cancer metastasis.
The cultural safety of reports of research on primary healthcare use by Indigenous Peoples: a systematic review
Authors: Hiyare Amandi , Sinka Victoria , Grande Eleonora Dal , Kerr Marianne , Kim Siah , Mallitt Kylie-Ann , Dickson Michelle , Jauré Allison , Wilson Rhonda , Craig Jonathan C , Stephens Jacqueline H 
Published: July 2023

Abstract

Introduction
The use of primary healthcare is associated with better chronic disease outcomes for Indigenous Peoples. Community-driven and owned health research data in understanding PHC use enablers provide opportunities to enhance PHC use within communities. Therefore, may reduce chronic disease burden.
Methods
Medline, CINAHL and Embase were all systematically searched from 1st January 2002 to 4th April 2023. Papers were included if they were original studies, published in English and included data (quantitative, qualitative and/or mixed methods) on primary healthcare use for chronic disease (chronic kidney disease, cardiovascular disease and/or diabetes mellitus) by Indigenous Peoples from Western colonial countries. Study screening and data extraction were undertaken independently by two authors, at least one of whom was Indigenous. The baseline characteristics of the papers were analyzed using descriptive statistics. Aspects of cultural safety of the research papers were assessed using two quality appraisal tools: the CONSIDER tool and the CREATE tool (subset analysis). This systematic review was conducted in accordance with the Assessing the Methodological Quality of Systematic Reviews (AMSTAR) tool.
Results
We identified 35 papers from Australia, New Zealand, Canada, and the United States. Most papers were quantitative (n = 21) and included data on 42438 people. Cultural safety across the included papers varied significantly with gaps in adequate reporting of research partnerships, provision of clear collective consent from participants and Indigenous research governance throughout the research process, particularly in dissemination. The majority of the papers (94%, 33/35) stated that research aims emerged from communities or empirical evidence. We also found that 71.4% (25/35) papers also reported of using strengths-based approaches by considering the impacts of colonization on reduced primary healthcare access.
Conclusion
Research on Indigenous PHC use must be changed to privilege Indigenous voices throughout the research process including dissemination, provide further engagement opportunities for the community and include sufficient detail on partnership agreements between Indigenous and non-Indigenous researchers.