bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved bounds of Mitrinović–Adamović-type inequalities by using two-parameter functions
Authors: Qian Guiping , Chen Xiao-Diao 
Published: February 2023

AbstractThis paper provides improved bounds of inequalities of Mitrinović–Adamović type by using two-parameter functions. It achieves a much better approximation effect than those bounds of prevailing methods. A new method based on the Páde interpolation is used to prove the new bounds, which can also be applied for proving the results of prevailing methods and their much more generalized results.
A microservice regression testing selection approach based on belief propagation
Authors: Chen Li-zhe , Wu Ji , Yang Hai-yan , Zhang Kui 
Published: February 2023

AbstractRegression testing is required to assure the quality of each iteration of microservice systems. Test case selection is one of main techniques to optimize regression testing. Existing techniques mainly involve artifacts acquisition, processing and maintenance, thus hard to apply in microservice regression testing since it is difficult to obtain and process required artifacts from multiple development teams, which is normal in cases of microservice systems. This paper proposes a novel approach, namely MRTS-BP, which takes API gateway logs instead of artifacts as inputs. By mining service dependencies from API gateway logs, MRTS-BP analyzes service change impacts based on a propagation calculation, and selects test cases affected by changes based on impact degree values. To evaluate the effectiveness of MRTS-BP, empirical studies based on four real deployed systems are presented. Retest-all strategy and a regression testing selection approach based on control flow graphs called RTS-CFG are compared with MRTS-BP. The results show that, MRTS-BP can significantly reduce both the number of test cases and overall time cost while maintaining the fault detection capability of selected test suite, and that MRTS-BP can save more time cost than RTS-CFG with the similar safety and precision.
Exploring student teachers’ perceptions of assessment ethics across university-based teacher education programs in Iran
Authors: Darabi Bazvand Ali 
Published: February 2023

AbstractIt is acknowledged that assessment ethics is an integral part of teacher education. Unlike sizable published research on students' perceptions of assessment in higher education, very little is reported on student teachers' perceptions of assessment ethics across university-based teacher education programs. This study aimed to explore Teaching English as a Foreign Language (TEFL) student teachers’ perceptions of assessment ethics in the classroom. Qualitative (phone interview) data from 15 TEFL teacher candidates were collected and analyzed using thematic content analysis. Based on the informants' responses, three overarching issues in assessment ethics emerged and are namely related to (a) assessment development (i.e., content underrepresentation, one-dimensional assessment, surprise items), (b) assessment administration(i.e., time, noise, and inconsistency in educators' behaviors), and (c) assessment scoring and communication (i.e., lack of transparency in feedback provision' 'misalignment of grading practice,' and 'breaching confidentiality in grade communication'). Furthermore, it was revealed that assessment is, for a great part, teacher-initiated and summative-oriented. In light of these findings, this study can inform professional development programs on assessment in teacher education.
An approach to application-layer DoS detection
Authors: Kemp Cliff , Calvert Chad , Khoshgoftaar Taghi M. , Leevy Joffrey L. 
Published: February 2023

AbstractWith the massive resources and strategies accessible to attackers, countering Denial of Service (DoS) attacks is getting increasingly difficult. One of these techniques is application-layer DoS. Due to these challenges, network security has become increasingly more challenging to ensure. Hypertext Transfer Protocol (HTTP), Domain Name Service (DNS), Simple Mail Transfer Protocol (SMTP), and other application protocols have had increased attacks over the past several years. It is common for application-layer attacks to concentrate on these protocols because attackers can exploit some weaknesses. Flood and “low and slow” attacks are examples of application-layer attacks. They target weaknesses in HTTP, the most extensively used application-layer protocol on the Internet. Our experiment proposes a generalized detection approach to identify features for application-layer DoS attacks that is not specific to a single slow DoS attack. We combine four application-layer DoS attack datasets: Slow Read, HTTP POST, Slowloris, and Apache Range Header. We perform a feature-scaling technique that applies a normalization filter to the combined dataset. We perform a feature extraction technique, Principal Component Analysis (PCA), on the combined dataset to reduce dimensionality. We examine ways to enhance machine learning techniques for detecting slow application-layer DoS attacks that employ these methodologies. The machine learners effectively identify multiple slow DoS attacks, according to our findings. The experiment shows that classifiers are good predictors when combined with our selected Netflow characteristics and feature selection techniques.
Preoperative subcategorization based on magnetic resonance imaging in intrahepatic cholangiocarcinoma
Authors: Xiao Yuyao , Zhou Changwu , Ni Xiaoyan , Huang Peng , Wu Fei , Yang Chun , Zeng Mengsu 
Published: February 2023

Abstract
Background
Appropriate preoperative identification of iCCA subtype is essential for personalized management, so the aim of this study is to investigate the role of MR imaging features in preoperatively differentiating the iCCA subtype.

Methods
Ninety-three patients with mass-forming intrahepatic cholangiocarcinoma (iCCA, 63 small duct type and 30 large duct type) were retrospectively enrolled according to the latest 5th WHO classification (mean age, males vs. females: 60.66 ± 10.53 vs. 61.88 ± 12.82, 50 men). Significant imaging features for differentiating large duct iCCA and small duct iCCA were identified using univariate and multivariate logistic regression analyses, and a regression-based predictive model was then generated. Furthermore, diagnostic performance parameters of single significant imaging features and the predictive model were obtained, and corresponding receiver operating characteristic (ROC) curves were subsequently presented.

Results
The univariate analysis showed that tumor in vein, arterial phase hypoenhancement, intrahepatic duct dilatation, lack of targetoid restriction and lack of targetoid appearance in T2 were predictors of large duct type iCCA. Arterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction were independent predictors for large duct type iCCA in multivariate analysis. The regression-based predictive model has achieved the best preoperative prediction performance in iCCA subcategorization so far. The area under the ROC curve of the regression-based predictive model was up to 0.91 (95% CI: 0.85, 0.98), and it was significantly higher than every single significant imaging feature.

Conclusions
Arterial phase hypoenhancement, intrahepatic duct dilatation and lack of targetoid restriction could be considered reliable MR imaging indicators of large duct type iCCA. MR imaging features can facilitate noninvasive prediction of iCCA subtype with satisfactory predictive performance.
Development and evaluation of a facile mesh-to-surface tool for customised wheelchair cushions
Authors: Nace Susan , Tiernan John , Ní Annaidh Aisling , Holland Donal 
Published: February 2023

Abstract
Background
Custom orthoses are becoming more commonly prescribed for upper and lower limbs. They require some form of shape-capture of the body parts they will be in contact with, which generates an STL file that designers prepare for manufacturing. For larger devices such as custom-contoured wheelchair cushions, the STL created during shape-capture can contain hundreds of thousands of tessellations, making them difficult to alter and prepare for manufacturing using mesh-editing software. This study covers the development and testing of a mesh-to-surface workflow in a parametric computer-aided design software using its visual programming language such that STL files of custom wheelchair cushions can be efficiently converted into a parametric single surface.

Methods
A volunteer in the clinical space with expertise in computer-aided design aided was interviewed to understand and document the current workflow for creating a single surface from an STL file of a custom wheelchair cushion. To understand the user needs of typical clinical workers with little computer-aided design experience, potential end-users of the process were tasked with completing the workflow and providing feedback during the experience. This feedback was used to automate part of the computer-aided design process using a visual programming tool, creating a new semi-automated workflow for mesh-to-surface translation. Both the original and semi-automated process were then evaluated by nine volunteers with varying levels of computer-aided design experience.

Results
The semi-automated process showed a 37% reduction in the total number of steps required to convert an STL model to a parametric surface. Regardless of previous computer-aided design experience, volunteers completed the semi-automated workflow 31% faster on average than the manual workflow.

Conclusions
The creation of a semi-automated process for creating a single parametric surface of a custom wheelchair cushion from an STL mesh makes mesh-to-surface conversion more efficient and more user-friendly to all, regardless of computer-aided design experience levels. The steps followed in this study may guide others in the development of their own mesh-to-surface tools in the wheelchair sector, as well as those creating other large custom prosthetic devices.
IFN-γ-STAT1-mediated CD8+ T-cell-neural stem cell cross talk controls astrogliogenesis after spinal cord injury
Authors: Wang Jingyu , Xu Lintao , Peng Deqing , Zhu Yongjian , Gu Zhaowen , Yao Ying , Li Heyangzi , Cao Xi , Fu Chun-yan , Zheng Mingzhi , Song Xinghui , Ding Yueming , Shen Yueliang , Zhong Jinjie , Chen Ying-ying , Hu Jue , Wang Lin-lin 
Published: February 2023

Abstract
Background
Spinal cord injury (SCI) causes nearly all patients to suffer from protracted disabilities. An emerging therapeutic strategy involving the recruitment of endogenous neural stem cells (NSCs) has been developed. However, endogenous NSCs in the adult spinal cord differentiate into mostly astrocytes after traumatic injury, forming glial scars, which is a major cause of regeneration failure in SCI. Thus, understanding which factors drive the activation and differentiation of endogenous NSCs after SCI is critical for developing therapeutic drugs.

Methods
The infiltration, state, and location of CD8+ T cells in spinal cord after traumatic injury were analyzed by flow cytometry and immunofluorescence (IF) staining. The Basso Mouse Scale (BMS) scores and rotarod testing were used for motor behavioral analysis. NSCs were co-cultured with CD8+ T cells. EdU assay was used to detect proliferative cells. Western blotting was used to analyze the expression levels of STAT1, p-STAT1, and p27. ChIP-seq and ChIP-qRT-PCR analyses were used to detect the downstream of STAT1. Nestin-CreERT2::Ai9 transgenic mice were used to genetic lineage tracing of Nestin+ NSCs after SCI in vivo.

Results
A prolonged increase of activated CD8+ T cells occurs in the injured spinal cords. The behavioral analysis demonstrated that the administration of an anti-CD8 antibody promotes the recovery of locomotor function. Then, we discovered that CD8+ T cells suppressed the proliferation of NSCs and promoted the differentiation of NSCs into astrocytes by the IFN-γ-STAT1 pathway in vitro. ChIP-seq and ChIP-qRT-PCR analysis revealed that STAT1 could directly bind to the promoters of astrocyte marker genes GFAP and Aldh1l1. Genetic lineage tracing of Nestin+ NSCs demonstrated that most NSCs differentiated into astrocytes following SCI. Depleting CD8+ T cells reduced the differentiation of NSCs into astrocytes and instead promoted the differentiation of NSCs into oligodendrocytes.

Conclusion
In conclusion, CD8+ T cells suppressed the proliferation of NSCs and promoted the differentiation of NSCs into astrocytes by the IFN-γ-STAT1-GFAP/Aldhl1l axis. Our study identifies INF-γ as a critical mediator of CD8+ T-cell-NSC cross talk and a potential node for therapeutic intervention in SCI.
The Triple-S framework: ensuring scalable, sustainable, and serviceable practices in educational technology
Authors: Moro Christian , Mills Kathy A. , Phelps Charlotte , Birt James 
Published: February 2023

AbstractEducational institutions are increasingly investing into digital delivery, acquiring new devices, and employing novel software and services. The rising costs associated with maintenance, in combination with increasing redundancy of older technologies, presents multiple challenges. While lesson content itself may not have changed, the educational landscape constantly evolves, where tertiary institutions are incorporating new modes of content delivery, hybrid-style learning, and interactive technologies. Investments into digital expansions must be taken with caution, particularly prior to the procurement of technology, with a need for the proposed interventions’ scalability, sustainability, and serviceability to be considered. This article presents the Triple-S framework for educators, administrators, and educational institutions, and outlines examples of its application within curricula. The paper synthesises research evidence to provide the foundation underlying the key principles of the Triple-S framework, presenting a useful model to use when evaluating digital interventions. Utilising the framework for decisions regarding the acquisition of educational technology, devices, software, applications, and online resources can assist in the assurance of viable and appropriate investments.
Graphical Abstract
Efficient removal of safranin from aqueous solution using a new type of metalated highly self-doped polyaniline nanocomposite
Authors: Hassan Hammed H. A. M. , Fattah Marwa Abdel 
Published: February 2023

AbstractWe report the chemical synthesis of poly(aniline-co-aniline-2,5-disulfonic acid)) and its composite containing L-hexuronic acid and metallic Ag/SiO2 nanoparticles as a new thermally stable anionic polyelectrolyte for removing safranin dye. The composite was characterized by IR, UV, cyclic voltammetry, SEM, TEM, TGA, DSC, EDXS and elemental analyses. Microscopic images exhibited intensified spherical particles dispersed over almost the entire surface. The XRD exhibited peaks of the partially crystalline material at many 2θ values, and their interatomic spacing and sizes were calculated. The cyclic voltammograms exhibited characteristic redox peaks relative to the quinoid ring transition states. The uptake rates up to 82.5% adsorption were completed within 75 min and the equilibrium time was 45 min. The isotherm of dye adsorption interprets the interaction with the adsorbent and explain the relationship between the dye removal capacity and the initial dye concentration. In the current, the Langmuir isotherm model was the optimum to interpret both the dye/copolymer and the dye/composite interactions. The uptake of safranin by copolymer/SiO2@Ag nanocomposite was well defined by pseudo second order model with rate constant K2 = 0.03 g− 1 mg− 1 min− 1 for 19 mg safranin. A comparison of safranin adsorption efficiency of the synthesized material with other reported material in the same domain suggested that the present composite has a higher adsorption rate and capacity. The ongoing research is devoted to improving the removal percentage of the dye by using 1,3,5-triazine based sulfonated polyaniline/Ag@ SiO2 nanocomposite.
Evaluating fireline effectiveness across large wildfire events in north-central Washington State
Authors: Lemons Rebecca E. , Prichard Susan J. , Kerns Becky K. 
Published: February 2023

AbstractBackgroundWildfires are increasing in incidence, size, and severity in the USA along with associated firefighting costs. Evaluation of firefighting containment and mop-up activities are crucial to reduce costs and to inform safe and effective wildfire response. As geospatial technologies advance, fireline effectiveness metrics have continued to be updated and improved. However, to develop standard analysis protocols and performance evaluations, there is a need to understand how widely metrics vary within and across fire events and are dependent on the different sources and accuracy of geospatial datasets, including firelines, fire perimeters, and severity layers. To ascertain the usefulness and limitations of four fireline effectiveness metrics, we evaluated several metrics including ratios of fireline engaged, held, and burned over. We performed a sensitivity analysis across 13 recent wildfires in north-central Washington State.ResultsOur study found that fire perimeter source and fireline buffer width had the largest impact on quantified fireline effectiveness metrics. Misclassification of firelines produced dramatic erroneous results which artificially increased the effectiveness and decreased suppression effort. High-severity fires were shown to be less effective across all fireline types and required higher suppression than most low- and moderate-severity fires.ConclusionOur results suggest that the fireline effectiveness methodology we tested was robust but could benefit from further refinement with the additional step of visual inspection for fireline misclassifications and database errors. Users should also consider evaluating a range of buffer widths prior to calculating fireline metrics to allow for some minor discrepancies between firelines and fire perimeters. Importantly, our results showed that for high-severity burns firelines were less efficient, and the placement of firelines should be carefully considered to more efficiently allocate firefighting resources and new dozer lines within high-severity landscapes, such as dense mixed conifer forests.
Automatic Classification of Tumor Response From Radiology Reports With Rule-Based Natural Language Processing Integrated Into the Clinical Oncology Workflow
Authors: Laurent Gery , Craynest Franck , Thobois Maxime , Hajjaji Nawale 
Published: February 2023

PURPOSE Imaging reports in oncology provide critical information about the disease evolution that should be timely shared to tailor the clinical decision making and care coordination of patients with advanced cancer. However, tumor response stays unstructured in free-text and underexploited. Natural language processing (NLP) methods can help provide this critical information into the electronic health records (EHR) in real time to assist health care workers. METHODS A rule-based algorithm was developed using SAS tools to automatically extract and categorize tumor response within progression or no progression categories. 2,970 magnetic resonance imaging, computed tomography scan, and positron emission tomography French reports were extracted from the EHR of a large comprehensive cancer center to build a 2,637-document training set and a 603-document validation set. The model was also tested on 189 imaging reports from 46 different radiology centers. A tumor dashboard was created in the EHR using the Timeline tool of the vis.js javascript library. RESULTS An NLP methodology was applied to create an ontology of radiographic terms defining tumor response, mapping text to five main concepts, and application decision rules on the basis of clinical practice RECIST guidelines. The model achieved an overall accuracy of 0.88 (ranging from 0.87 to 0.94), with similar performance on both progression and no progression classification. The overall accuracy was 0.82 on reports from different radiology centers. Data were visualized and organized in a dynamic tumor response timeline. This tool was deployed successfully at our institution both retrospectively and prospectively as part of an automatic pipeline to screen reports and classify tumor response in real time for all metastatic patients. CONCLUSION Our approach provides an NLP-based framework to structure and classify tumor response from the EHR and integrate tumor response classification into the clinical oncology workflow.
Addressing the Gap in Research Methodologies Education in Pediatric Oncology in the Eastern Mediterranean Region
Authors: Saab Raya , Santana Victor , Obeid Anas , Devidas Meenakshi , Belgaumi Asim , Bhakta Nickhill , Naidu Paula , Saha Vaskar , Sultan Iyad , Arora Ramandeep Singh , Mukoka Lilly , Jeha Sima 
Published: February 2023

PURPOSE Formal training in clinical research methodologies is limited in limited-resource countries. Through collaboration among high- and middle-resource settings and in response to an identified need verbalized by regional pediatric oncology practitioners, Pediatric Oncology East & Mediterranean Group and St Jude Global developed a workshop focused on capacity building in research skills. Here, we describe its structure, implementation, and early results. METHODS Leveraging virtual capabilities, the format included lectures and small group breakout exercise sessions, for 3 hours per day on 2 consecutive days per week for 2 consecutive weeks. Topics included basics of study design, introduction to health care statistics, research ethics, data registries, and scientific writing. Applicants were required to submit an abstract for a potential research project. Each breakout group selected one abstract for further development and presented the final version in a groupwide session. The participants' experience was evaluated through an online survey. RESULTS Attendance included 29 registrants from 12 countries and six disciplines. Each breakout group was assigned a themed category: cohort studies, clinical trials, or registries. Critical feedback from the breakout sessions helped strengthen the selected projects, which included a retrospective study, a prospective observational study, a prospective interventional study, and a registry proposal. After the workshop, participants were invited to further develop their original abstracts, and three proposals received additional mentoring, one of which was a multi-institutional prospective study that was subsequently submitted through the Pediatric Oncology East & Mediterranean Group network for implementation. The postworkshop survey revealed an overall highly positive experience, and feedback provided potential themes for future workshops. CONCLUSION This workshop demonstrated the potential for collaborative network partnerships in targeting research training gaps in pediatric oncology. Lessons learned will be applied to future workshops to strengthen research in limited-resource settings.