bluuebunny/crossref_metadata_2025_split huggingface dataset:
Results of research work Russian society of oncomammologists “The use of artificial intelligence for early detection of breast cancer”
Authors: Pavlova V. I. , Belaya Yu. A. , Vorontsov A. Yu. , Prishchepov A. A. , Knyazev S. M. , Mikhaylov A. A. , Kovaleva A. V. , Arevshatyan E. G. , Paltuev R. M. , Chernaya A. V. , Zakharova N. A. 
Published: August 2023

Breast cancer is the most common cancer in women and one of the leading causes of death from cancer in Russia and most countries of the world. In countries with mammographic screening, there is a decrease in mortality from breast cancer. Introduction of mammographic image evaluation platforms into radiologist practice based on the work of artificial intelligence it allows not only to increase the coverage of the female population, but also to reduce the cost of screening, but it also increases the sensitivity and specificity of mammography as a method of breast cancer screening.The article presents the results of a study on the evaluation of mammographic images in women who have passed a preventive study using an artificial intelligence program.Within the framework of this project, mammographic images were analyzed using the service for viewing medical images “Celsus” in 8030 patients. The study assessed the age groups of 40-49 years, 50-59 years, 60 years and older. The average age of patients with suspected breast cancer was 54.8 years. Breast cancer was detected in 13 women (1.2 %), while the highest percentage of breast cancer was detected in the group with mammographic density D.
Pengaruh Model Problem Based Learning (PBL) terhadap kemampuan berpikir kritis siswa
Authors: Hartono Inaisya Putri , Suharto Yusuf , Sahrina Alfi , Soekamto Hadi 
Published: August 2023

One of the essential skills in 21st-century learning is critical thinking skills. Critical thinking skills can be developed by using problem-based learning model. The low critical thinking ability of students is caused by teacher-centered learning. The problem-based learning (PBL) model is one way to enhance critical thinking skills. This research aims to investigate the effect of PBL model on the critical thinking skills of SMAN 1 Dander. Students of grades XI Sosial 1 were set as the experimental class and XI Social 2 were set as control class to perform a quasi-experimental approach with a pretest-posttest control group design. A total of 10 essay questions based of indicator of critical thinking skills were used as the research instrument. The results revealed that the gain score achieved by the experimental class was higher than the control class by 40.9 percent and 3.3 percent. Independent sample t-test data analysis technique was used in this research with a significance value of 0.00 less than 0.05 and the average value of experimental class was higher than the control class indicating that PBL model had an effect on students’ critical thinking skills, specifically on the topic of “Types and Natural Disaster Countermeasures”.
Salah satu keterampilan penting dalam pembelajaran abad 21 adalah kemampuan berpikir kritis. Rendahnya kemampuan berpikir kritis siswa disebabkan oleh pembelajaran yang masih berpusat kepada guru (teacher centered). Kemampuan berpikir kritis dapat dikembangkan dengan menggunakan model pembelajaran berbasis masalah. Tujuan penelitian ini adalah untuk mengetahui pengaruh model pembelajaran berbasis masalah terhadap kemampuan berpikir kritis siswa. Penelitian ini merupakan penelitian eksperimen semu dengan desain penelitian pretest-posttest control group design. Subjek penelitian ini adalah siswa SMAN 1 Dander kelas XI IPS 1 sebagai kelas eksperimen dan XI IPS 2 sebagai kelas kontrol. Instrumen yang digunakan berupa soal essay dengan jumlah 10 soal berdasarkan indikator kemampuan berpikir kritis. Berdasarkan hasil penelitian yang telah dilakukan, gain score kelas eksperimen lebih tinggi daripada kelas kontrol, yaitu 40,9 persen dan 3,3 persen. Teknik analisis data yang digunakan dalam penelitian adalah independent sample t-test dengan nilai signifikansi 0.00 kurang dari 0.05 dan nilai rata-rata kelas eksperimen lebih tinggi daripada kelas kontrol sehingga dalam hal ini model pembelajaran berbasis masalah berpengaruh terhadap kemampuan berpikir kritis siswa pada materi jenis dan penanggulangan bencana alam.
Factores asociados con la interrupción de la lactancia materna exclusiva: análisis transversal de una encuesta nacional peruana
Authors: Tapia-Sequeiros Gustavo , Velazco-Cañari Alexander Mauricio , Ramos-Calizaya Nayelly , Medina-Vicente Lucero Alejandra , Rodríguez-Flores Camila , Ventura-Ramirez Frank , Maquera-Afaray Julio 
Published: August 2023

ANTECEDENTES: La lactancia materna exclusiva, sin la incorporación de otros alimentos distintos a la leche humana, es suficiente para el crecimiento, desarrollo y fortalecimiento del sistema inmunológico del lactante en los primeros 6 meses de vida.
OBJETIVO: Identificar los factores asociados con la interrupción de la lactancia materna exclusiva mediante el análisis de una encuesta nacional levantada en el 2021.
MATERIALES Y MÉTODOS: Estudio transversal y analítico al que se incluyeron madres de lactantes igual y mayores de seis meses. La variable dependiente fue la interrupción de la lactancia materna exclusiva y las variables independientes las características sociodemográficas de la madre y del lactante. Se describieron las frecuencias absolutas y relativas, junto con un análisis bivariado y multivariado.
RESULTADOS: Se incluyeron 11,296 madres con hijos igual o mayores de seis meses. El 26.2% de las madres interrumpió la lactancia materna exclusiva. Los factores asociados fueron: nivel educativo superior (RPa: 1.55; IC95%: 1.06-2.27) y lactante hijo único (RPa: 1.10; IC95%: 1.01-1.20). Los factores protectores fueron: residir en la selva (RPa: 0.77; IC95%: 0.71-0.84), idioma nativo indígena (RPa: 0.82; IC95%: 0.75-0.91), capacitación en lactancia materna (RPa: 0.88; IC95%: 0.82-0.94) y lactante con seguro de salud (RPa: 0.91; IC95%: 0.84-0.97).
CONCLUSIÓN: La prevalencia de la interrupción de la lactancia materna exclusiva es baja. Las variables sociodemográficas asociadas fueron: nivel educativo secundario o superior de la madre, residir en la costa, índice de riqueza familiar medio o rico, no recibir capacitación referente a la lactancia materna, lactante hijo único y no tener seguro de salud.
Overview on the Polyphenol Avenanthramide in Oats (<em>Avena sativa</em> Linn.) as Regulators of PI3K Signaling in the Management of Neurodegenerative Diseases
Authors: Wankhede Nitu L , Kale Mayur B , Bawankule Ashwini K , Aglawe Manish M , Taksande Brijesh G , Trivedi Rashmi V , Umekar Milind J , Jamadagni Ankush , Walse Prathamesh , Koppula Sushruta , Kopalli Spandana Rajendra 
Published: August 2023

Avenanthramides (Avns) and its derivatives, a group of polyphenolic compounds found abundantly in Oats (Avena sativa Linn.) have emerged as a promising candidate for neuroprotection due to their immense anti-oxidant, anti-inflammatory, and anti-apoptotic properties. Neurodegenerative diseases (NDDs), characterized by progressive degeneration of neurons, present a significant global health burden with limited therapeutic options. The phosphoinositide 3-kinase (PI3K) signalling pathway plays a crucial role in cell survival, growth, and metabolism, making it an attractive target for therapeutic intervention. Dysregulation of PI3K signalling has been implicated in the pathogenesis of various NDDs including Alzheimer&#039;s and Parkinson&#039;s disease. Avns has been shown to modulate PI3K/AKT signalling, leading to increased neuronal survival, reduced oxidative stress, and improved cognitive function. This review explores the potential of Avns polyphenols, as modulators of the PI3K signalling pathway focusing on their beneficial effects against NDDs. Further, we outlined the need for clinical exploration to elucidate the specific mechanisms of Avns action on the PI3K/AKT pathway and its potential interactions with other signalling cascades involved in neurodegeneration. Based on the available literature using relevant keywords from Google Scholar, PubMed, Scopus, Science Direct, and Web of Science, our review emphasizes the potential of Avns as a therapeutic strategy for NDDs and warrants further investigation and clinical exploration.
Application of Volatile Solvent Treatment for Downhole Water Blockage and Organic Residue Removals – A Case Study
Authors: Asghar Shahab Azeem , Talha M Shehzad , Haque Inam , Khan M Nisar , Nawaz Ahmad , Asad Abdul , Saeed Muhammad Salman , Anwar Rameez , Yousaf Arif , Ahmad Syed Hamza 
Published: August 2023

Abstract
Liquid blockage is a damage mechanism which occurs due to accumulation of immovable liquid phase near the wellbore area causing impairment of the relative permeability of the valuable hydrocarbons leading to significant reduction in production. The liquid block may be caused by the accumulation of condensates, water or immovable emulsions formed by interaction of incompatible fluids. These incompatible fluids may be introduced during the drilling operations or during the commingled production of fluids through single completion string. This damage may cause complete seizure of production in low pressure gas wells due to drastic reduction in the relative permeability of gas due to high mobility contrast. Similarly, the potential organic residue deposition in injection wells cause significant damage leading to abnormal injection pressures and rendering the operation expensive and uneconomical.
A well-known solution for treating liquid blocks is the usage of alcohol-based treatments that work by reducing the viscous forces of the blocking fluid, reducing the interfacial tension, solubilizing the blocking water, causing vaporization, and subsequently removing the fluid blockage. Similarly, the aromatic fluids-based mixture with mutual solvent has been used for treatment of organic residue depositions and emulsion removal. However, limited applications of these solutions in the Indus Basin require further work on the subject to establish the minimum confidence on the successful solution recipe and development of the best practices for such wells.
This paper demonstrates the practical application of utilization of these solutions for successful treatment of liquid blockage in 1st attempt, putting depleted gas well back at pre water block damage production level and significant improvement in injection pressures of another injector well saving multi folds cost of operation.
Further physical study about solution structures for nonlinear q-deformed Sinh-Gordon equation along with bifurcation and chaotic behaviors
Authors: Bai Leiqiang , Qi Jianming , Sun Yiqun 
Published: August 2023

Abstract
In this article, with the help of Matlab R2021a software, the exact solutions of the nonlinear q-deformed Sinh-Gordon equation are successfully examined by (G′/G2)-expansion method. The main novelty of this paper lies in fifive aspects: (1) To our best knowledge, the modifified(G′/G2)-expansion method was fifirstly applied in nonlinear q-deformed Sinh-Gordon equation (NQSGE). And thus get many new solutions that were not found previously literature[Ali et al., 2022; Raza et al., 2023]. (2) The effffects of wave obliqueness about NQSGE are fifirstly discussed in this paper which did not happen in previous papers[Ali & Abdel-Aty, 2022; Raza et al., 2022, 2023; Ali et al., 2022; Alrebdi et al., 2022]. (3) Phase portraits and bifurcation behaviors about NQSGE are also fifirstly investigated in Hamiltonian system that did not appear in previous literatures[Ali & Abdel-Aty, 2022; Raza et al., 2022, 2023; Ali et al., 2022; Alrebdi et al., 2022]. (4) Sensitive analysis to initial value and chaotic behavior are also fifirstly studied in NQSGE. This is also a work not done in other previous literatures[Ali & Abdel-Aty, 2022; Raza et al., 2022, 2023; Ali et al., 2022; Alrebdi et al., 2022]. (5) The modifified Riemann-Liouville, Beta, Conformable and M-truncated fractional derivatives are tested for accuracy in Fig. 18 (a) and (b). To our best knowledge, we seem fifirstly compare the relations and distinctions among difffferent fractional order derivatives in NQSGE model. The generalizations (1)-(5) indicated the wave propagation of solitions about NQSGE model is mastered by the changed fraction, changed wave obliqueness angle and other physical factors. The geometrical representations of the NQSGE provide the corporal information to explain the physically phenomenons.
Spin-orbital Jahn-Teller bipolarons
Authors: Franchini Cesare , Celiberti Lorenzo , Mosca Dario Fiore , Allodi Giuseppe , Pourovskii Leonid , Tassetti Anna , Forino Paola , Cong Rong , Garcia Erick , Tran Phuong , De Renzi Roberto , Woodward Patrick , Mitrovic Vesna , Sanna Samuele 
Published: August 2023

Abstract
Polarons and spin-orbit (SO) coupling are distinct quantum effects that play a critical role in charge transport and spin-orbitronics. Polarons originate from strong electron-phonon interaction and are ubiquitous in polarizable materials featuring electron localization, in particular 3d transition metal oxides (TMOs). On the other hand, the relativistic coupling between the spin and orbital angular momentum is notable in lattices with heavy atoms and develops in 5d TMOs, where electrons are spatially delocalized. Here we combine ab initio calculations and magnetic measurements to show that these two seemingly mutually exclusive interactions are entangled in the electron-doped SO-coupled Mott insulator Ba2Na1-xCaxOsO6 (0 < x < 1), unveiling the formation of spin-orbital bipolarons. Polaron charge trapping, favoured by the Jahn-Teller lattice activity, converts the Os 5d1 spin-orbital Jeff=3/2 levels, characteristic of the parent compound Ba2NaOsO6 (BNOO), into a bipolaron 5d2 Jeff=2 manifold, leading to the coexistence of different J-effective states in a single-phase material. The gradual increase of bipolarons with increasing doping creates robust in-gap states that prevents the transition to a metal phase even at ultrahigh doping, thus preserving the Mott gap across the entire doping range from 5d1 BNOO to 5d2 Ba2CaOsO6 (BCOO).
Landscape of molecular crosstalk between SARS-CoV-2 infection and cardiovascular diseases: emphasis on mitochondrial dysfunction and immune-inflammation
Authors: Dai Shiyu , Cao Ting , Shen Han , Zong Xuejing , Gu Wenyu , Li Hanghang , Wei Lei , Huang Haoyue , Yu Yunsheng , Chen Yihuan , Ye Wenxue , Hua Fei , Fan Hongyou , Shen Zhenya 
Published: August 2023

Abstract
Background: SARS-CoV-2, the pathogen of COVID-19, is a worldwide threat to human health and causes a long-term burden on the cardiovascular system. Individuals with pre-existing cardiovascular diseases are at higher risk for SARS-CoV-2 infection and tend to have a worse prognosis. However, the relevance and pathogenic mechanisms between COVID-19 and cardiovascular diseases are not yet completely comprehended.
Methods: Common differentially expressed genes (DEGs) were obtained in datasets of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) infected with SARS-CoV-2 and myocardial tissues from heart failure patients. Further GO and KEGG pathway analysis, protein–protein interaction (PPI) network construction, hub genes identification, immune microenvironment analysis, and drug candidate predication were performed. Then, an isoproterenol-stimulated myocardial hypertrophy cell model and a transverse aortic constriction-induced mouse heart failure model were employed to validate the expression of hub genes.
Results: A total of 315 up-regulated and 78 down-regulated common DEGs were identified. Functional enrichment analysis revealed mitochondrial metabolic disorders and extensive immune inflammation as the most prominent shared features of COVID19 and cardiovascular diseases. Then, 11 hub DEGs, as well as hub immune-related and mitochondria-related DEGs, were screened. Additionally, nine potential therapeutic agents for COVID-19-related cardiovascular diseases were proposed. Furthermore, the expression patterns of most of the hub genes related to cardiovascular diseases in the validation dataset along with cellular and mouse myocardial damage models, were consistent with the findings of bioinformatics analysis.
Conclusions: The study unveiled the molecular networks and signaling pathways connecting COVID-19 and cardiovascular diseases, which may provide novel targets for intervention of COVID-19-related cardiovascular diseases.
BBB Dysfunction Defines the Aging Myeloid Landscape Favoring Immune Evasion for Glioma and Alzheimer's Disease
Authors: Gargini Ricardo , Segura-Collar Berta , Mondejar-Ruescas Lucia , Garranzo-Asensio María , Mata-Martinez Pablo , Garcia-Escudero Ramón , Hernández-Laín Aurelio , Sepúlveda Juan , Nuñez Ángel Pérez , Avila Jesus , Sánchez-Gómez Pilar 
Published: August 2023

Abstract
The blood-brain barrier (BBB) defines the physiological function of the brain, and it is disrupted in multiple neuropathological diseases. Although vascular abnormalities and BBB leakage characterize the progression of gliomas and occurs in the early stages of Alzheimer's disease (AD), it is unclear their correlation with the neurodegeneration observed in the brain parenchyma. Here, molecular analysis of the brain’s ecosystem showed that gene expression signatures linked to BBB dysfunction and neuronal synapses correlate directly and inversely, respectively, with the progression of AD and gliomas. Using human samples, patient´s-derived xenografts and mice with orthotopically implanted glioma cells, we observed that neuronal loss is linked to BBB breakdown in mesenchymal tumors. This involves the extravasation of monocyte-derived macrophages, specifically those with a suppressive phenotype, in tandem with a surge of inflammatory cytokines. Moreover, our data demonstrate that vascular normalization can revert the neuronal loss and the aggressiveness in those gliomas. Overall, we propose that BBB dysfunction is a common process associated with aging that drives chronic inflammation, which is governed by TREM2+/TIM3+ suppressor myeloid cells. These results could help us to apply therapies to the progression of central nervous system pathologies that are associated with the aging process, with the hallmarks of toxic neuroinflammation and myeloid dysfunction.
Dynamic Resectorization to Improve Utility of Healthcare Systems
Authors: Teymourifar Aydin , Trindade Maria A. M. 
Published: August 2023

Abstract
This study discusses a regional healthcare system including several hospitals with different characteristics. We define a utility function for the system based on the sectorization concept to form a balance between hospitals in terms of important outputs such as waiting times and demands. Since the determined system is dynamic, the balance state is lost over time; consequently, resectorization is done over time. We simulate the system utilizing the data of a case study. We characterize multiple periods and calculate the utility of the system's current state. We design resectorization scenarios based on boosting the capacity and quality of hospitals. Numerical results demonstrate that substantial improvement of utility with resectorization is achievable.
Predicting phenotypes of elderly from resting state fMRI
Authors: Verovnik Barbara , Hajduk Stefan , Hulle Marc Van 
Published: August 2023

Abstract
Machine learning techniques are increasingly embraced in neuroimaging studies of healthy and diseased human brains. They have been used successfully in predicting phenotypes, or even clinical outcomes, and in turning functional connectome metrics into phenotype biomarkers of both healthy individuals and patients. In this study, we used functional connectivity characteristics based on resting state functional magnetic resonance imaging data to accurately classify healthy elderly in terms of their phenotype status. Additionally, as the functional connections that contribute to the classification can be identified, we can draw inferences about the network that is predictive of the investigated phenotypes. Our proposed pipeline for phenotype classification can be expanded to other phenotypes (cognitive, psychological, clinical) and possibly be used to shed light on the modifiable risk and protective factors in normative and pathological brain aging.
DSFFNet: Tire Defect Detection Based on Deep and Shallow Feature Fusion
Authors: Wu Hao , Wang Yunfeng , Zhou Yi , Liu Xiyu , Zhai Xiaodi , Sun Kuizhi , Zheng Zhouzhou , Tian Chengliang , Li Tao , Jia Wenguang , Zhao Haixia , Zhang Yan 
Published: August 2023

Abstract

Recently, object detection based on deep learning has made great progress in the field of defect detection. Due to its complex texture background and varied defect features, existing defect detection methods based on object detection are face great challenges for the detection of tire internal defects. In this paper, a tire defect detection model based on deep and shallow feature fusion is proposed. Firstly, a multi-head feature extraction module is proposed, which extract abundant effective information from multiple dimensions. Secondly, a spatial semantic fusion upsampling module is proposed to alleviate the problem of information loss in the upsampling process. Finally, a novel prediction head is designed to expand the receptive field by compressing the size of the feature map to improve the detection accuracy of large defects. Experimental results show that the mAP of the proposed method achieves 94.03% on the tire internal defect dataset, the average detection time is 36.74ms, which can meet the needs of industrial online detection.
Adversarial system of one-pixel attack for hyperspectral image classification
Authors: Peng Xiaoxu , Zhou Dong , Sun Guanghui , Hu Yuhui 
Published: August 2023

Abstract
The introduction of deep learning arouses great success in hyperspectral image (HSI) classification. However, there is a growing concern about adversarial attacks on deep models, which can significantly impact the performance of HSI classification through imperceptible perturbations. In this paper, we first introduce a semi-black-box attack method to hyperspectral domain, one-pixel attack, which fools the HSI classifier by modifying only one pixel with high intensity. It is verified on standard datasets and a well-known HSI classification model, HybridSN. An adversarial system based on one-pixel attack (OPAS) is then proposed by integrating adversarial training into model training. The system not only improves the robustness of the classification model but also enhances the model’s ability to defend against other adversarial attacks. Experimental results demonstrate show that OPAS can achieve nearly 100% defense effectiveness against some basic adversarial attacks. Additionally, an HSI adversarial map is created to visualize one-pixel attack. Through it can be observed the characteristic that one-pixel attack can attack classification boundaries, and this property is further verified in hyperspectral field.