bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Light Inside: A Reflection on an Art Program, Traumatised Women and Thriving during the 2020 Pandemic
Authors: Riggs Anne 
Published: November 2022

COVID-19 and the lockdown are not the worst things to have been imposed upon the people with whom I work. In fact, their lives marinated in childhood sexual trauma, abuse, neglect, family violence, severe mental ill health, and/or disability, have prepared them well for isolation, self-reliance, and uncertainty. Deep wells of resilience, coping skills and an outlook on life formed in the shadow of trauma has enabled these women to manage the impact of the virus much better than they or I expected at the start of the pandemic lockdown. However, that is not to say it has been all smooth sailing.
This study reflects on some of the inner and external resources that supported women through this. As users of this service receive National Disability Insurance Scheme (NDIS) funding, it is valuable to reflect upon how its continued active support of users assists them and helps minimise the multiple losses and effects of the lockdown and virus.
This is a case study of one small art service being provided to women in Melbourne, Australia. It explores how COVID-19 has impacted them, some of their losses, and their desires for the future post-lockdown. Its focus is on the threads that have woven a sense of community through this service and how women who have never met each other have provided practical and emotional support to each other to alleviate some of the adverse effects of the virus. It speaks to the artist's contributions, the NDIS, and the service provided in enabling those who could have expected to be overwhelmed and severely impacted by this situation, if not to flourish during this time, at least not sink into despair and depression.
Machine Learning Brings Vast Core-Analysis Legacy Data to Life
Authors: Carpenter Chris 
Published: November 2022

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31419, “Bringing Huge Core-Analysis Legacy Data to Life Using Machine Learning,” by Siti N.F. Zulkipli, SPE, Benard Ralphie, and Jamari M. Shah, SPE, Petronas, et al. The paper has not been peer reviewed. Copyright 2022 Offshore Technology Conference. Reproduced by permission.

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Among the sources of subsurface data, rock and fluid analyses stand out as the best means of directly measuring subsurface properties. The implication of modeling this data into an organized data store means better assessment of economic viability and producibility in frontier basins and the capability to identify bypassed pay in old wells that may not have rock material. The complete paper presents agile technologies that integrate data management, data-quality assessment, and predictive machine learning (ML) to maximize company asset value with legacy core data.

Introduction
The complete paper integrates data gathering, data filtering, the connecting of scattered data, and the building of useful knowledge models using legacy core data from various operating assets. This integration is achieved by a data quality check (QC) work flow and ML to improve the definition of reservoir rock properties that affect field development and asset management. ML and deep-learning capabilities have been implemented to predict critical reservoir properties based on qualified legacy data.
The work flow is aimed at bridging gaps in areas with limited core data coverage, reducing subsurface uncertainty and risk, and accelerating project delivery. In addition, data-prediction accuracy can be improved with ML applications as new data become available.

Phase I: Data Preparation and Verification
In this stage, more than 60,000 data points are gathered from 327 wells and grouped into different categories such as routine core analysis, special core analysis, geology, and rock mechanics. Leveraging on best practices in laboratory core analysis and subject-matter expert (SME) expertise, 88 QC rules are generated to delineate the data, identify outliers, and classify the data into good quality (labeled as 0), data requiring further QC (1), and rejected data (2). The generated QC rules target various rock properties such as porosity, permeability, capillary pressure, electrical properties, relative permeability, and rock mechanics. QC-rule implementation is an iterative process in which, after the initial screening, the rules are further optimized and enhanced to assist data classification based on practical experiences. These QC rules are needed because some observed data errors are related to data tabulation and incorrect naming.
A total of 1,826 relevant variables, generated by different vendors, was extracted during QC-rule creation. These variables had to be merged in the QC process, which reduced the number of variables to 240.
Assisted Cement Log Interpretation Using Machine Learning
Authors: Viggen Erlend Magnus , Singstad Bjørn-Jostein , Time Eirik , Mishra Siddharth , Berg Eirik 
Published: November 2022

Summary
The Assisted Cement Log Interpretation Project has used machine learning (ML) to create a tool that interprets cement logs by predicting a predefined set of annular condition codes used in the cement log interpretation process.
The development of a cement log interpretation tool speeds up the log interpretation process and enables expert knowledge to be efficiently shared when training new professionals. By using high-quality and consistent training data sets, the project has trained a model that will support unbiased and consistent interpretations over time.
The tool consists of a training and a prediction tool integrated with cased-hole logging interpretation software. By containerizing the code using an “API First” design principle (API: application programming interface), the applicability of this add-on tool is broad. The ML model is trained using selected and engineered features from cement logs, and the tool predicts an annular condition code according to the cement classification system for each depth segment in the log. The interpreters can easily fetch a complete cement log interpretation prediction for the log and use that as a template for their final interpretation. The ML model can easily be retrained with new data sets to improve accuracy even further.
To improve cement log interpretation consistency in the industry, the code will be made available as open source.
HER2 expression in peritoneal dissemination of high-grade serous ovarian carcinoma: a comparative study of immunohistochemical reactivity using four HER2 antibodies
Authors: Yeo Min-Kyung , Kim Sup , Yoo Heon Jong , Suh Kwang-Sun , Kim Kyung-Hee 
Published: November 2022

Abstract
Objective: Most high-grade serous ovarian carcinomas (HGSOCs) involving the peritoneum are highly aggressive. Epidermal growth factor receptor 2 (HER2) is aberrantly activated and a therapeutic target in a variety of solid cancers. However, the role of HER2 in HGSOC is still controversial. The HER2 status of a tumor is based on cytoplasmic membrane staining of an intracellular domain (ICD)-specific HER2 antibody. In this study, we compared four anti-HER2 antibodies in an immunohistochemical study of HGSOC with peritoneal dissemination.
Methods: HER2 expression was assessed in peritoneal disseminated HGSOC specimens from 38 patients by immunohistochemistry using four different anti-HER2 antibodies [an ICD antibody (clone A0485), an extracellular domain (ECD) antibody (clone SP3), and two antibodies recognizing HER2 phosphorylated at tyrosine 877 or 1248 (pHER2Y877 and pHER2Y1248)]. HER2 gene amplification was accessed by chromogenic in situ hybridization (CISH).
Results: The antibodies showed HER2 positivity as follows: 31.6 % of cases (12/38) with A0485, 26.3 % (10/38) with SP3, 7.9 % (3/38) with pHER2Y877, and 21.1% (8/38) with pHER2Y1248. Fifteen of 38 (39.5 %) cases were positive with at least one of the four HER2 antibodies, and two cases tested positive with all four antibodies. Differences in the HER2 expression using the pHER2Y877 assay and the A0485 or SP3 assay were observed (p = 0.012 and p = 0.039, respectively). HER2 gene amplification was detected in 3/19 cases.
Conclusion: All four HER2 antibodies could be used for patient selection for anti-HER2 therapies. These findings raise the possibility of anti-HER2 therapeutic strategies for HGSOC with peritoneal dissemination.
Effect of cepharanthine on the stemness of lung squamous cell carcinoma Based on Network Pharmacology and Bioinformatics
Authors: Liu Bo , Deng Jian-xiong 
Published: November 2022

Abstract
Background. Lung squamous cell carcinoma (LUSC) has poor survival prognosis and few clinical treatment options. We urgently need to explore new therapeutic drugs in clinical practice. Cepharanthine (CEP), which has been shown to have anticancer effects in several tumors, but the mechanism of CEP in treating LUSC has not been reported.
Methods. SwissTargetPrediction, PharmMapper and GeneCards were used to identify targets of CEP and LUSC. Further topological analysis was used to obtain hub genes via Cytoscape. Molecular docking was carried out to verify the combination of CEP with hub targets. Based on bioinformatics, we first analyzed the expression and survival of hub targets in LUSC, and further analyzed the correlation between hub targets and cancer stemness, immune cell infiltration and tumor mutation burden (TMB).
Results. A total of 41 targets were identified. Further topological analysis identified 6 hub genes: AURKA, CCNA2, CCNE1, CDK1, CHEK1 and PLK1. Molecular docking analysis showed that CEP had stable binding to all these 6 target proteins. In-depth bioinformatics analysis of these 6 targets showed that high expression of these targets were positively correlated with cancer stemness index, and negatively correlated with tumor infiltrating immune cells. In immune subtype analysis, the expressions of these targets were significantly decreased in inflammatory tumors. In addition, we also found that the expressions of these targets were positively correlated with TMB.
Conclusion. Based on multidisciplinary analysis, we preliminarily identified potential targets of CEP for LUSC treatment and suggested that CEP may play a role in regulating LUSC stemness.
Grow Newtonian rigid inertia into parameter repetitiveness memory equivalent bio-inertia over the “super-simultaneousness” of quantum mechanics for growth turnover selection inheritance
Authors: Lai Yi Yu 
Published: November 2022

Abstract
Inversion energy is defined as parameter-against-gravity-internal-fluctuation, the non-simultaneousness in correlated internal fluctuations is quantizing time. Modified Newtonian Three Laws are, first: cosx = sinx = ; second: + ; third: Wavelength = L, frequency = n . Bio-systems are topological spaces that can process input objects into inversion energy for entropy-control by repetitiveness memory, the capability of equivalent procured inversion energy with memorized trigonometric repetitiveness by quantizing time is bio-inertia. Evolution grows the trigonometric folding equivalent capacity of a topological space. Schrödinger equation has only quantized energy but hasn’t quantized time thus inducing quantum collapse. We then define in vivo conditions to grow over the “super-simultaneousness” of conventional quantum to reverse collapse for lifespan. Originating from the quantum scale difference between Planck regions and surface tension regions, bio quantum duality grows in vivo cross folded-surface tension region flow. Life relies on trigonometric negentropy procured from elastic entropy generation ground states and physically inherit by bio quantum growthturnover selection.
Multi-UAVs cooperative coverage search for non-convex region without prior information
Authors: Li Minghan , Xia Xuewen 
Published: November 2022

Abstract
An Unmanned Aerial Vehicle (UAV) is considered as a suitable equipment in coverage search missions due to its small size, high maneuverability, low cost and portability. However, due to the non convexity of reality coverage tasks, the complexity is further increased, a single UAV can not effectively perform the task due to its shortcomings in endurance. Therefore, using a group of UAVs in coverage search missions has become a research hotspot in recent years. In this paper, a Multi-UAVs cooperative coverage algorithm for non-convex region call CSANCR is proposed to deal with non-convex tasks. The strategy adopts the path planning algorithm based on differential evolution algorithm for prior planning, the information interaction between UAVs is carried out through the network, and a Distributed Model Predictive Control (DMPC) is used for cooperative control and path optimization among UAVs. A dynamic reward function is designed to evaluate the quality of the solution according to the change of UAV state.The experimental results show that the strategy can achieve high coverage and low energy consumption index under the constraints of collision avoidance.
PACS: 0000, 1111 2000 MSC: 0000, 1111
Rockfall Feature Investigation and Kinematic Simulation Based on Nap-of-the-Object Photogrammetry and GIS Spatial Modeling
Authors: li xude , Liu Fuzhen , Zhao Li , Deng Na , Chen Long , pan Jingshen , Tang Guoqiang 
Published: November 2022

Abstract
Chaya County, as one of the important towns in the "Three Rivers Region" in southeastern Tibet, is the key target for future expansion and development. Disaster risk investigation and research are the primary task of county expansion and development. UAVs have been widely used in disaster surveys by virtue of their ability to rapidly acquire rich and diverse geospatial data. However, due to the comprehensive influence of terrain environment, GPS positioning accuracy, and image acquisition and processing methods, the positioning accuracy and resolution acquired from the 3D model and DSM data are difficult to guarantee its reliability. In this case, when interpreting rock mass characteristics, there will be limitations such as inaccurate extraction of joint and fissure information, inability to reflect rock mass surface roughness, and even incapacity to identify fine joints. Meanwhile, the resolution of terrain data will also affect the reliability of the simulation results of rockfall motion characteristics. Therefore, a new image acquisition method and modeling idea are summarized in this paper, and obtains a real-world 3D model with a positioning accuracy of less than 5 cm and DSM data with sub-centimeter resolution for a slope in the study area by this way. According to these data, a rock mass characteristic survey was completed, and a 3D numerical simulation of the potential rockfall movement characteristics was performed in GIS. At present, there are three potential rockfall areas in the study area, with a volume of about 2690m³. Affected by factors such as freeze-thaw erosion, differential weathering, faults, and unfavorable structural plane combinations, rockfall disasters may continue to occur in the future. The simulation results show that after the high-level rockfall occurs, the movement trajectory presents a diversion phenomenon, and the side of the township road is more threatened than the side of the G349 National Highway. The results of this paper have important reference value for disaster prevention and mitigation for the expansion of Chaya County, and can also provide important basic data for the research on fault activity, landform formation and evolution in Changdu and surrounding areas.
Majorana corner states on the dice lattice
Authors: Mohanta Narayan , Soni Rahul , Okamoto Satoshi , Dagotto Elbio 
Published: November 2022

Abstract
Lattice geometry continues providing exotic new topological phases in condensed matter physics. Exciting recent examples are the higher-order topological phases, manifesting via localized lower-dimensional boundary states. Moreover, flat electronic bands with a non-trivial topology arise in various lattices and can hold a finite superfluid density, bounded by the Chern number $C$. Here we provide a general route to analyze the topological properties of flat bands in the superconducting state. We argue that the topological superconductivity induced in a flat band with $C=n$ is of order $n$ and the associated boundary Majorana states have a complex structure when $n>1$. As example, we show that an attractive interaction in the dice lattice, that exhibits flat bands with $C=2$, gives rise to second-order topological superconductivity with mixed singlet-triplet pairing. The second-order nature of the topological superconducting phase is revealed by the zero-energy Majorana bound states at the lattice corners. These findings suggest that flat bands with a finite Chern number provide feasible platforms for inducing topological superconductivity of various orders.
WITHDRAWN: Investigation of Seasonal Metal Pollution in Karacaören II Dam Lake Sediment Samples by X-ray Fluorescence Technique
Authors: Apaydın G. , Koksal O. K. , Cengiz E. , Şirin M. , Baltaş H. , Tıraşoğlu E. 
Published: November 2022

Abstract
Sediment samples collected from twelve different notes of the Karacaören II Dam Lake were analysed for seasonal metal pollution in this study. Energy dispersive X-ray fluorescence spectrometry was used to measure the amount of metal in soil samples. Metal concentrations found in the sediments were used to generate the geoaccumulation index and enrichment factor expressions. The results were compared seasonally to values at the local, state, and international levels. Copper, zinc, lead, arsenic, nickel, chromium, and mercury element content ratios (in ppm) measured in sediments in all seasons were determined to be 42–96, 53–78, 11–14, 4–7, 233–244, and 611–711, respectively. The elemental content of the sediments and their contamination levels are also discussed.
A novel HOXD13 mutation causes synpolydactyly and promotes osteoclast differentiation by regulating pSMAD5/p65/c-Fos/RANK axis
Authors: Zhang Lishan , Fang Ziqi , Cheng Guangdong , He Mengting , Lin Yanliang 
Published: November 2022

Abstract
The mutations of HoxD13 gene have been involved in synpolydactyly (SPD), and the polyalanine extension mutation of HoxD13 gene could lead to SPD in mice. In this study, a novel missense mutation of HoxD13 (NM_000523: exon2: c.G917T: p.R306L) was identified in a Chinese family with SPD. The mice carrying the corresponding HoxD13 mutation were generated. The results showed that the homozygous mutation of HoxD13 also caused SPD, but heterozygous mutation did not affect limbs development, which was different from that of SPD patients. With the increasing generation, the mice with homozygous HoxD13 mutation presented more severe syndactyly. Western blotting showed that this mutation did not affect HOXD13 expression, suggesting that this mutation did not result in haploinsufficiency. Further analysis demonstrated that this homozygous HoxD13 mutation promoted osteoclast differentiation and bone loss, and enhanced the expression of osteoclast-related genes RANK, c-Fos, and p65. Meanwhile, this homozygous HoxD13 mutation elevated the level of phosphorylated SMAD5 (pSMAD5). Co-immunoprecipitation verified that this mutation attenuated the interaction between pSMAD5 and HOXD13, suggesting that this mutation released more pSMAD5. Inhibition of pSMAD5 reduced the expression of RANK, c-Fos and p65 despite in the mutation group. In addition, inhibition of pSMAD5 repressed the osteoclast differentiation. ChIP assay confirmed that p65 and c-Fos could bind to the promoter of RANK. These results suggested that this novel HoxD13 mutation promoted osteoclast differentiation by regulating smad5/p65/c-Fos/RANK axis, which might provide a new insight into SPD development.
Differential Associations between Trauma Types and Borderline Personality Disorder from the Perspective of Emotion Dysregulation
Authors: Yuan Yan , Lee Hyunji , Newhill Christina , Eack Shaun , Fusco Rachel , Scott Lori 
Published: November 2022

Abstract
Background: Borderline Personality Disorder (BPD) is characterized by pervasive instability in a range of areas including interpersonal relationships, self-image, and affect. Extant studies have consistently identified significant correlations between childhood trauma and BPD. While exploring this trauma-BPD link, a number of cross-sectional studies commonly emphasize the role of emotion dysregulation (ED). A better understanding of the association between trauma and BPD is essential in formulating early, effective intervention approaches, and in addressing varied adverse impacts.
Methods: We analyzed a subset of data collected for a larger community-based longitudinal study. Given that our current focus on trauma and ED, only those participants who completed the baseline assessment measures of trauma and ED (N=144) were included for the primary analyses. We conducted stepwise multivariate linear models to examine the differential relationships between BPD features, ED, and specific traumas. A path analysis with latent factors using the structural equation modeling (SEM) method was performed to test the indirect effect from trauma to BPD features via ED.
Results: Linear regression models revealed that emotional abuse (relative to other trauma types) was significantly associated with high BPD features. The SEM, by constructing direct and indirect effects simultaneously, showed that (1) ED partially mediated the path from trauma to BPD features; and (2) trauma played a complex role in which the direct effect remained significant even after accounting for the indirect effect through ED.
Conclusions: Our results highlight a most consistent association between emotional abuse and trauma, indicating its unique role in understanding BPD features in the context of childhood adversity. Further, shame-related negative appraisal and ED were found critical when examining the association between trauma and BPD, possibly providing promising treatment targets for future practices.
Transforming growth factor β (TGF-β) pathway in immunopathogenesis of multiple sclerosis (MS); molecular approaches
Authors: Esmaeilzadeh Abdolreza , Mohammadi Vahid , Elahi Reza 
Published: November 2022

Abstract
Multiple sclerosis (MS) is an acute demyelinating disease with an autoimmune nature, followed by gradual neurodegeneration and enervating scar formation. Dysregulated immune response is an important dilemma contributing to the pathogenesis of MS. The role of chemokines and cytokines, such as transforming growth factor-β (TGF-β), have been recently highlighted regarding their altered expressions in MS. TGF-β has three isoforms, TGF-β1, TGF-β2, and TGF-β3, that are structurally similar; however, they can show different functions. All three isoforms are known to induce immune tolerance by modifying Foxp3+ regulatory T cells. Nevertheless, there are controversial reports concerning the role of TGF-β1 and 2 in the progression of scar formation in MS, while these proteins are also known to improve oligodendrocyte differentiation and have shown neuroprotective behavior, two cellular processes that suppress the pathogenesis of MS. TGF-β3 shares the same properties but is less likely to contribute to scar formation and its direct role in MS remains elusive. To develop novel neuroimmunological treatment strategies for MS, the optimal strategy could be the one that causes immune suppression, induces neurogenesis, stimulates remyelination, and prevents excessive scar formation. Therefore, regarding its immunological properties, TGF-β could be an appropriate candidate for this; however, contradictory results of previous studies have questioned its role and therapeutic potential in MS. In this review article, we provide an overview of the immunopathogenesis of MS, the role of TGF-β in this process, related clinical and animal studies, and the treatment potential of TGF-β in MS by emphasizing the role of different TGF-β isoforms.