bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fairness in graph-based semi-supervised learning
Authors: Zhang Tao , Zhu Tianqing , Han Mengde , Chen Fengwen , Li Jing , Zhou Wanlei , Yu Philip S 
Published: October 2022

AbstractMachine learning is widely deployed in society, unleashing its power in a wide range of applications owing to the advent of big data. One emerging problem faced by machine learning is the discrimination from data, and such discrimination is reflected in the eventual decisions made by the algorithms. Recent study has proved that increasing the size of training (labeled) data will promote the fairness criteria with model performance being maintained. In this work, we aim to explore a more general case where quantities of unlabeled data are provided, indeed leading to a new form of learning paradigm, namely fair semi-supervised learning. Taking the popularity of graph-based approaches in semi-supervised learning, we study this problem both on conventional label propagation method and graph neural networks, where various fairness criteria can be flexibly integrated. Our developed algorithms are proved to be non-trivial extensions to the existing supervised models with fairness constraints. Extensive experiments on real-world datasets exhibit that our methods achieve a better trade-off between classification accuracy and fairness than the compared baselines.
A machine and deep learning analysis among SonarQube rules, product, and process metrics for fault prediction
Authors: Lomio Francesco , Moreschini Sergio , Lenarduzzi Valentina 
Published: October 2022

Abstract
Background
Developers spend more time fixing bugs refactoring the code to increase the maintainability than developing new features. Researchers investigated the code quality impact on fault-proneness, focusing on code smells and code metrics.

Objective
We aim at advancing fault-inducing commit prediction using different variables, such as SonarQube rules, product, process metrics, and adopting different techniques.

Method
We designed and conducted an empirical study among 29 Java projects analyzed with SonarQube and SZZ algorithm to identify fault-inducing and fault-fixing commits, computing different product and process metrics. Moreover, we investigated fault-proneness using different Machine and Deep Learning models.

Results
We analyzed 58,125 commits containing 33,865 faults and infected by more than 174 SonarQube rules violated 1.8M times, on which 48 software product and process metrics were calculated. Results clearly identified a set of features that provided a highly accurate fault prediction (more than 95% AUC). Regarding the performance of the classifiers, Deep Learning provided a higher accuracy compared with Machine Learning models.

Conclusion
Future works might investigate whether other static analysis tools, such as FindBugs or Checkstyle, can provide similar or different results. Moreover, researchers might consider the adoption of time series analysis and anomaly detection techniques.
Static test flakiness prediction: How Far Can We Go?
Authors: Pontillo Valeria , Palomba Fabio , Ferrucci Filomena 
Published: October 2022

AbstractTest flakiness is a phenomenon occurring when a test case is non-deterministic and exhibits both a passing and failing behavior when run against the same code. Over the last years, the problem has been closely investigated by researchers and practitioners, who all have shown its relevance in practice. The software engineering research community has been working toward defining approaches for detecting and addressing test flakiness. Despite being quite accurate, most of these approaches rely on expensive dynamic steps, e.g., the computation of code coverage information. Consequently, they might suffer from scalability issues that possibly preclude their practical use. This limitation has been recently targeted through machine learning solutions that could predict the flakiness of tests using various features, like source code vocabulary or a mixture of static and dynamic metrics computed on individual snapshots of the system. In this paper, we aim to perform a step forward and predict test flakiness only using static metrics. We propose a large-scale experiment on 70 Java projects coming from the iDFlakies and FlakeFlagger datasets. First, we statistically assess the differences between flaky and non-flaky tests in terms of 25 test and production code metrics and smells, analyzing both their individual and combined effects. Based on the results achieved, we experiment with a machine learning approach that predicts test flakiness solely based on static features, comparing it with two state-of-the-art approaches. The key results of the study show that the static approach has performance comparable to those of the baselines. In addition, we found that the characteristics of the production code might impact the performance of the flaky test prediction models.
The CUBES science case
Authors: Evans Chris , Cristiani Stefano , Opitom Cyrielle , Cescutti Gabriele , D’Odorico Valentina , Alcalá Juan Manuel , Alencar Silvia H. P. , Balashev Sergei , Barbuy Beatriz , Bastian Nate , Battino Umberto , Cambianica Pamela , Carini Roberta , Carter Brad , Cassisi Santi , Vaz Castilho Bruno , Christlieb Norbert , Cooke Ryan , Covino Stefano , Cremonese Gabriele , Cunha Katia , da Silva André R. , D’Elia Valerio , De Cia Annalisa , De Silva Gayandhi , Diaz Marcos , Di Marcantonio Paolo , Ernandes Heitor , Fitzsimmons Alan , Franchini Mariagrazia , Gänsicke Boris T. , Genoni Matteo , Giribaldi Riano E. , Grazian Andrea , Hansen Camilla Juul , La Forgia Fiorangela , Lazzarin Monica , Marcolino Wagner , Marconi Marcella , Migliorini Alessandra , Noterdaeme Pasquier , Pereira Claudio , Pilecki Bogumil , Quirrenbach Andreas , Randich Sofia , Rossi Silvia , Smiljanic Rodolfo , Snodgrass Colin , Stürmer Julian , Trost Andrea , Vanzella Eros , Ventura Paolo , Wright Duncan , Zafar Tayyaba 
Published: October 2022

AbstractWe introduce the scientific motivations for the development of the Cassegrain U-Band Efficient Spectrograph (CUBES) that is now in construction for the Very Large Telescope. The assembled cases span a broad range of contemporary topics across Solar System, Galactic and extragalactic astronomy, where observations are limited by the performance of current ground-based spectrographs shortwards of 400 nm. A brief background to each case is presented and specific technical requirements on the instrument design that flow-down from each case are identified. These were used as inputs to the CUBES design, that will provide a factor of ten gain in efficiency for astronomical spectroscopy over 300-405 nm, at resolving powers of $$R~\sim$$

R

∼

24,000 and $$\sim$$
∼
7,000. We include performance estimates that demonstrate the ability of CUBES to observe sources that are up to three magnitudes fainter than currently possible at ground-ultraviolet wavelengths, and we place its predicted performance in the context of existing facillities.
Exploring the Links Between Parental Attachment Style, Child Temperament and Parent-Child Relationship Quality During Adolescence
Authors: Walsh Geraldine , Zadurian Natalie 
Published: October 2022

AbstractLinked with a myriad of developmental outcomes, the parent-child relationship serves an important function, and it is therefore important that determinants of this relationship are elucidated so that optimal outcomes can be promoted. This study investigated links between parental attachment style and child temperament in the prediction of parent-child relationship quality during early adolescence. One hundred parents of 12–15-year-olds completed an online survey. Findings indicated that when examining parent attachment style alone, attachment-related anxiety but not avoidance predicted parent-child relationship quality. When examining child temperament alone, negative affect and affiliation predicted parent-child relationship quality. When examining both parental attachment style and child temperament in the same model, child temperament was uniquely predictive of the parent-child relationship quality. No moderation effects were detected. More precise models and expanded measures of parental attachment style, child temperament and parent-child relationship quality are recommended to fully capture the transactional and dynamic nature of the parent-child relationship.
Composite Nanoarchitectonics of Magnetic Silicon Dioxide-Modified Chitosan for Doxorubicin Delivery and In Vitro Cytotoxicity Assay
Authors: Nassar Mostafa Y. , El-Salhy Hamed I. , El-Shiwiny W. H. , Abdelaziz Gamal , El-Shiekh R. 
Published: October 2022

AbstractDeveloping drug delivery carriers for highly selective, controlled, and sustained release of the anti-cancer drugs is one of the crucial issues in the cancer strive. We herein report the synthesis of Fe3O4 (M) and SiO2 (S) nanoparticles and their nanocomposites with chitosan (CS) for high loading efficiency and subsequent release potentiality of Doxorubicin (DOX) anticancer drug. The as-synthesized nanostructures were characterized using Fourier transform infrared (FT-IR), X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), high-resolution transmission electron microscopy (HR-TEM), and thermal analysis techniques. The average crystallite sizes of the as-prepared M, S, CS/M, CS/S, and CS/M/S nanostructures were found to be 5, 15, 70, 22, and 29 nm, respectively. The loading and cumulative release of Doxorubicin for the produced nanostructures were examined, and the results exhibited loading efficacy of 71%, 95%, 96%, 79%, 17%, and 42% for M, S, CS, CS/M, CS/S, and CS/M/S nanostructures, respectively. The Doxorubicin releasing results revealed a promising cumulative release percentages at pH 4.2 and pH 5 compared with those at pH 7.4. At pH 4.2, the cumulative release percentages for DOX-M, DOX-S, DOX-CS, DOX/M, and DOX/CS/M/S were 94%, 96%, 92%, 95%, and 98%, respectively. While the corresponding percentages at pH 5 were 97%, 90%, 46%, 43%, and 70%. The percentage for DOX-CS/S was 60% at pH 5, though. The in-vitro cytotoxicity of M-DOX, CS-DOX, and M/CS-DOX was explored against two human cancer cell lines (MCF-7 and Hep-G2) using SRB (Sulforhodamine B) assay. The DOX-loaded M/CS exhibited the highest cytotoxicity and its IC50 values were 2.65 and 2.25 μg/mL against Hep-G2 and MCF-7 cell lines, respectively, compared to the corresponding values of 5.1 and 4.5 μg/mL for free DOX. The results indicated that M/CS nanocomposite is a good candidate as drug delivery nano-carrier for the Doxorubicin anti-cancer drug.
The temporal clustering of storm surge, wave height, and high sea level exceedances around the UK coastline
Authors: Jenkins Luke J. , Haigh Ivan D. , Camus Paula , Pender Douglas , Sansom Jenny , Lamb Rob , Kassem Hachem 
Published: October 2022

AbstractThe temporal clustering of storms presents consecutive storm surge and wave hazards that can lead to amplified flood and erosional damages; thus, clustering is important for coastal stakeholders to consider. We analyse the prevalence of storm clustering around the UK coastline by examining the temporal and spatial characteristics of storm surge, wave height, and high still sea level exceedances at the 1 in 1- and 5-year return levels. First, at the interannual timescale, we show that there are periods of high/low exceedance counts on national and regional scales. Elevated annual counts of exceedances with smaller magnitudes can occur without a respective signal of higher-magnitude exceedances. Secondly, at the intra-annual timescale, we show that high proportions of exceedances are clustering over short timescales. Storm surge, wave height and still sea level exceedances occurring < 50 days after the prior exceedance at a given site account for between ~ 35–44% and ~ 15–22% of all exceedances at the 1 in 1- and 5-year return levels, respectively. Still sea levels have the highest proportion of exceedances clustered in quick succession, with ~ 25% of 1 in 1-year exceedances occurring < 2 days after the previous at the same site. Spatially, for UK storm surges and still sea levels, the North Sea has the lowest proportion of clustering, whereas the North Atlantic and Bristol Channel have the highest. For English wave records, the highest proportions of clustering are found in the North Sea for exceedances of a lower magnitude and the English Channel for exceedances of a higher magnitude. These findings illuminate the prevalence of the clustering of coastal hazards around the UK—helping coastal stakeholders evaluate the threat of surges, waves, and sea levels clustering over short periods.
Soil chemistry and fungal communities are associated with dieback in an Endangered Australian shrub
Authors: Andres Samantha E. , Emery Nathan J. , Rymer Paul D. , Powell Jeff R. 
Published: October 2022

Abstract
Background and aims
Field surveys across known populations of the Endangered Persoonia hirsuta (Proteaceae) in 2019 suggested the soil environment may be associated with dieback in this species. To explore how characteristics of the soil environment (e.g., pathogens, nutrients, soil microbes) relate to dieback, a soil bioassay (Experiment 1) was conducted using field soils from two dieback effected P. hirsuta populations. Additionally, a nitrogen addition experiment (Experiment 2) was conducted to explore how the addition of soil nitrogen impacts dieback.

Methods
The field soils were baited for pathogens, and soil physiochemical and microbial community characteristics were assessed and related to dieback among plants in the field and nursery-grown plants inoculated with the same field soils. Roots from inoculated plants were harvested to confirm the presence of soil pathogens and root-associated endophytes. Using these isolates, a dual culture antagonism assay was performed to examine competition among these microbes and identify candidate pathogens or pathogen antagonists.

Results
Dieback among plants in the field and Experiment 1 was associated with soil physiochemical properties (nitrogen and potassium), and soil microbes were identified as significant indicators of healthy and dieback-affected plants. Plants in Experiment 2 exhibited greater dieback when treated with elevated nitrogen. Additionally, post-harvest culturing identified fungi and other soil pathogens, some of which exhibited antagonistic behavior.

Conclusion
This study identified candidate fungi and soil physiochemical properties associated with observed dieback and dieback resistance in an Endangered shrub and provides groundwork for further exploring what drives dieback and how it can be managed to promote the conservation of wild populations.
Different measures of international faculty and their impacts on global rankings
Authors: Shin Jung Cheol , Lee Soo Jeung 
Published: October 2022

AbstractThis study analyzed how the ranking status has changed at various higher education system levels by applying different definitions of international faculty. Among the four measures (birthplace, current citizenship, and the country of bachelor and doctoral education), this study found that international faculty measured by the country of doctoral studies produced significantly different international outlook scores and thus ranking status from that based on birthplace or citizenship. Specifically, major English-speaking systems such as the UK, Canada, and Australia hire a large number of faculty who are foreign citizens while non-English speaking systems (Italy, Portugal, China, Korea, and Brazil) hire more local academics who have earned their doctoral degree abroad. This suggests that these non-English speaking countries are systematically under-rated in their international outlook scores by the adoption of the birthplace-based or citizenship-based international faculty measures. As an alternative, this study proposes to update the international faculty measure using a combination of citizenship of employment and doctoral training to minimize this systemic bias.
Occurrence and Risk Assessment of Antibiotic Residues in Sewage Sludge of Two Nigerian Hospital Wastewater Treatment Plants
Authors: Ajibola Akinranti S. , Zwiener Christian 
Published: October 2022

AbstractAntibiotic residues in sewage sludge can present detrimental environmental effects due to sewage sludge application onto soils for agricultural purposes. Reports on the occurrence of antibiotics in sewage sludge and risk assessment due to the application of sewage sludge onto soils are still limited in Africa. The occurrence of fourteen antibiotic residues in sewage sludge from two Nigerian hospital wastewater treatment plants was investigated. For the first time, the potential environmental risk of target antibiotics associated with the use of sewage sludge for application onto soils in Nigeria was assessed. Risk assessment was carried out using both terrestrial and aquatic toxicity data. All target antibiotics were detected in at least one sludge sample. Ciprofloxacin and ofloxacin (fluoroquinolones) had the highest concentrations, up to 674 ng g−1 dry weight for ciprofloxacin. All ten antibiotics evaluated for terrestrial ecological risk in sludge-amended soils presented low risk. Only three out of thirteen antibiotics assessed for aquatic ecological risk in sludge-amended soils posed medium risk, while the remaining antibiotics presented low risk. Antibiotic mixtures presented low risk in sludge-amended soils. A more holistic evaluation of the potential risks due to a mixture of a wider scope of chemicals in Nigerian sewage sludge is recommended prior to application onto soils as fertilizers for agricultural purposes.
Physiological and mental health changes in cancer patients during the COVID-19 state of emergency
Authors: Gutiérrez-Santamaría Borja , Castañeda-Babarro Arkaitz , Arietaleanizbeaskoa Maria Soledad , Mendizabal-Gallastegui Nere , Grandes Gonzalo , Coca Aitor 
Published: October 2022

Abstract
Backgrounds
Due to the COVID-19 pandemic that we are currently facing, many governments across the world have declared a state of emergency and even confinements. This stressful situation, in addition to prolonged stays at home, may imply a radical change in lifestyle behavior and physical activity (PA). The aim of this study is to evaluate the physiological and psychological effects in cancer patients who changed their PA habits during the COVID-19 state of emergency in Spain.

Methods
Thirty-three participants were evaluated pre- and post-state of emergency. A series of questionnaires was used to assess cancer-specific quality of life.

Results
The most relevant results revealed significantly lower walking time (p < 0.001) and sitting time (p = 0.014). Upper and lower body strength also decreased significantly (p = 0.009 and 0.012, respectively) and oxygen consumption (VO2 peak) (p = 0.023). None of the parameters analysed showed significant differences for psychological aspects (QLQ-C-30 and SF-36) and body composition.

Conclusion
Lower physical activity leads to negative physiological adaptation, particularly affecting cardiovascular and strength levels. While it is important to maintain the general population’s amount and intensity of exercise, this particularly vulnerable group’s physical capacity is vital to their health and well-being.
Bifurcation matching for consistent cerebral vessel labeling in CTA of stroke patients
Authors: Rist Leonhard , Taubmann Oliver , Thamm Florian , Ditt Hendrik , Sühling Michael , Maier Andreas 
Published: October 2022

Abstract
Purpose
Vessel labeling is a prerequisite for comparing cerebral vasculature across patients, e.g., for straightened vessel examination or for localization. Extracting vessels from computed tomography angiography scans may come with a trade-off in segmentation accuracy. Vessels might be neglected or artificially created, increasing the difficulty of labeling. Related work mainly focuses on magnetic resonance angiography without stroke and uses trainable approaches requiring costly labels.

Methods
We present a robust method to identify major arteries and bifurcations in cerebrovascular models generated from existing segmentations. To localize bifurcations of the Circle of Willis, candidate paths for the adjacent vessels of interest are identified using registered landmarks. From those paths, the optimal ones are extracted by recursively maximizing an objective function for all adjacent vessels starting from a bifurcation to avoid erroneous paths and compensate for stroke.

Results
In 100 CTA stroke data sets for evaluation, 6 bifurcation locations are placed correctly in 85% of cases; 92.5% when allowing a margin of 5 mm. On average, 14 vessels of interest are found in 90% of the cases and traced correctly end-to-end in 73.5%. The baseline achieves similar detection rates but only 35.5% of the arteries are traced in full.

Conclusion
Formulating the vessel labeling process as a maximization task for bifurcation matching can vastly improve accurate vessel tracing. The proposed algorithm only uses simple features and does not require expensive training data.
BRAF Inhibitor Resistance in Melanoma: Mechanisms and Alternative Therapeutic Strategies
Authors: Zhong Jingqin , Yan Wangjun , Wang Chunmeng , Liu Wanlin , Lin Xinyi , Zou Zijian , Sun Wei , Chen Yong 
Published: October 2022

Opinion statementMelanoma is caused by a variety of somatic mutations, and among these mutations, BRAF mutation occurs most frequently and has routinely been evaluated as a critical diagnostic biomarker in clinical practice. The introduction of targeted agents for BRAF-mutant melanoma has significantly improved overall survival in a large proportion of patients. However, there is BRAF inhibitor resistance in most patients, and its mechanisms are complicated and need further clarification. Additionally, treatment approaches to overcome resistance have evolved rapidly, shifting from monotherapy to multimodality treatment, which has dramatically improved patient outcomes in clinical trials and practice. This review highlights the mechanisms of BRAF inhibitor resistance in melanoma and discusses the current state of its therapeutic approaches that can be further explored in clinical practice.
Promise and Challenges of Checkpoint Inhibitor Therapy for Progressive Multifocal Leukoencephalopathy in HIV
Authors: Corey Sydney , Smith Bryan R. , Cortese Irene C. M. 
Published: October 2022

Abstract
Purpose of Review
Progressive multifocal leukoencephalopathy (PML) is a severe opportunistic infection that remains an important cause of morbidity and mortality in people living with HIV (PLWH). Immune checkpoint molecules are negative regulators of the immune response that have been targeted as a strategy to bolster anti-viral immunity in PML, with varied outcomes reported. While initiation and optimization of antiretroviral therapy remains the standard of care in HIV-related PML, the specific opportunities and risks for checkpoint blockade in these cases should be explored.

Recent Findings
As of April 15, 2022, only 5 of the 53 total published cases of PML treated with checkpoint blockade had underlying HIV infection; four of these had a favorable outcome. The risk of promoting immune reconstitution inflammatory syndrome is a major concern and underscores the importance of patient selection and monitoring.

Summary
Checkpoint blockade warrants further exploration as a potentially promising option for treatment escalation in HIV-related PML.