bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep feature selection using local search embedded social ski-driver optimization algorithm for breast cancer detection in mammograms
Authors: Pramanik Payel , Mukhopadhyay Souradeep , Mirjalili Seyedali , Sarkar Ram 
Published: November 2022

AbstractBreast cancer has become a common malignancy in women. However, early detection and identification of this disease can save many lives. As computer-aided detection helps radiologists in detecting abnormalities efficiently, researchers across the world are striving to develop reliable models to deal with. One of the common approaches to identifying breast cancer is through breast mammograms. However, the identification of malignant breasts from mass lesions is a challenging research problem. In the current work, we propose a method for the classification of breast mass using mammograms which consists of two main stages. At first, we extract deep features from the input mammograms using the well-known VGG16 model while incorporating an attention mechanism into this model. Next, we apply a meta-heuristic called Social Ski-Driver (SSD) algorithm embedded with Adaptive Beta Hill Climbing based local search to obtain an optimal features subset. The optimal features subset is fed to the K-nearest neighbors (KNN) classifier for the classification. The proposed model is demonstrated to be very useful for identifying and differentiating malignant and healthy breasts successfully. For experimentation, we evaluate our model on the digital database for screening mammography (DDSM) database and achieve 96.07% accuracy using only 25% of features extracted by the attention-aided VGG16 model. The Python code of our research work is publicly available at: https://github.com/Ppayel/BreastLocalSearchSSD.
Ricci flow does not preserve positive sectional curvature in dimension four
Authors: Bettiol Renato G. , Krishnan Anusha M. 
Published: November 2022

AbstractWe find examples of cohomogeneity one metrics on$$S^4$$S4and$$\mathbb {C}P^2$$CP2with positive sectional curvature that lose this property when evolved via Ricci flow. These metrics are arbitrarily small perturbations of Grove–Ziller metrics with flat planes that become instantly negatively curved under Ricci flow.
The estimation of health state utility values in rare diseases: do the approaches in submissions for NICE technology appraisals reflect the existing literature? A scoping review
Authors: Meregaglia Michela , Nicod Elena , Drummond Michael 
Published: November 2022

Abstract
Background
Rare diseases negatively impact patients’ quality of life, but the estimation of health state utility values (HSUVs) in research studies and cost–utility models for health technology assessment is challenging.

Objectives
This study compared the methods for estimating the HSUVs included in manufacturers’ submissions of orphan drugs to the National Institute for Health and Care Excellence (NICE) with those of published studies addressing the same rare diseases to understand whether manufacturers fully exploited the existing literature in developing their economic models.

Methods
All NICE Technology Appraisal (TA) and Highly Specialized Technologies (HST) guidance documents of non-cancer European Medicines Agency (EMA) orphan medicinal products were reviewed and compared with any published primary studies, retrieved via PubMed until November 2020, and estimating HSUVs for the same conditions addressed in manufacturers’ submissions.

Results
We identified 22 NICE TA/HST appraisal reports addressing 19 different rare diseases. Sixteen reports presented original HSUVs estimated using EQ-5D or Health Utility Index (n = 12), direct methods (n = 2) or mapping (n = 2), while the other six included values obtained from the literature only. In parallel, we identified 111 published studies: 86.6% used preference-based measures (mainly EQ-5D, 60.7%), 12.5% direct techniques, and 2.7% mapping. The collection of values from non-patient populations (using ‘vignettes’) was more frequent in manufacturers’ submissions than in the literature (22.7% vs. 8.0%).

Conclusions
The agreement on methodological choices between manufacturers’ submissions and published literature was only partial. More efforts should be made by manufacturers to accurately reflect the academic literature and its methodological recommendations in orphan drugs submissions.
Utility of ultrasonography for predicting indications for tolvaptan in patients with autosomal dominant polycystic kidney disease
Authors: Iijima Hiroko , Tada Toshifumi , Hashimoto Mariko , Nishimura Takashi , Kiriki Masato , Higashiura Akiko , Iwasaki Aya , Honda Michino , Nagasawa Yasuyuki , Yamakado Koichiro 
Published: November 2022

Abstract
Purpose
Tolvaptan is the first approved treatment for autosomal dominant polycystic kidney disease (ADPKD) that targets a mechanism directly contributing to the development and growth of renal cysts. We investigated the ability of ultrasonography to predict total kidney volume (TKV) of 750 mL or more, which is an indication for tolvaptan therapy in patients with ADPKD.

Methods
A total of 46 patients with ADPKD were evaluated. The most statistically appropriate measurement based on ultrasonography for predicting TKV determined by computed tomography (CT) was assessed.

Results
TKV determined by CT was 796.8 (508.8–1,560.3) mL. The median length, anteroposterior distance, and mediolateral distance determined using ultrasonography were 15.7 cm, 7.6 cm, and 7.6 cm in the left kidney, and 13.4 cm, 6.9 cm, and 7.2 cm in the right kidney, respectively. Multivariate regression analysis showed that total kidney length (left and right) [variance inflation factor (VIF), 9.349] and total mediolateral distance (left and right) (VIF, 3.988) were independently associated with TKV. The correlation (r) between the logarithm of TKV determined by CT and total mediolateral distance determined using ultrasonography was 0.915 (p < 0.001). The linear regression equation was log (total kidney volume) = 1.833 + 0.075 × total mediolateral distance (left and right) based on ultrasonography. The area under the receiver operating characteristic curve for total mediolateral distance determined using ultrasonography to predict TKV of 750 mL or more was 0.989. Using the total mediolateral distance cut-off value of 14.2 cm, the sensitivity and specificity were 96.0% and 100.0%, respectively.

Conclusion
Total mediolateral distance determined using ultrasonography can predict TKV in patients with ADPKD.
Predicting the Sustained Implementation of an Evidence-Based Parenting Program: A Structural Equation Modelling Approach
Authors: Ma Tianyi , Tellegen Cassandra L. , McWilliam Jenna , Sanders Matthew R. 
Published: November 2022

Abstract
Purpose
Sustained implementation is required for evidence-based parenting programs to promote children and their families’ wellbeing at the societal level. Previous literature has examined the role of a range of different factors in enhancing sustainability. However, the inter-relationship between, and the relative importance of different factors remain largely unknown. The overall aim of this study is to identify predictors of sustained program use, the relative importance of factors, and potential mediation pathways.

Methods
We surveyed 1202 practitioners who were trained in at least one variant of the Triple P-Positive Parenting Program, at least one and half years before data collection. The present data were linked with data collected during professional training. We first examined the independent effect of each factor on sustained program use, then, developed and evaluated a structural equation model of sustained program use.

Results
The structural equation model explained a considerable amount of variance in sustained program use, with seven positive predictors and one negative predictor identified. Organisational support was identified as a key facilitator, which was not only positively linked with other facilitators but also had an independent positive effect. Perceived usefulness of the program was the most important practitioner-level facilitator, which might be contributed by both research-based evidence and practice-based evidence. Practitioners’ self-regulation in program delivery impacted sustained use by influencing other factors such as perceived usefulness of the program.

Conclusion
The findings provided insight into factors influencing the sustainability of evidence-based parenting programs which could be used to inform future implementation practice.
Changes in breast cancer treatment during the COVID-19 pandemic: a Dutch population-based study
Authors: Eijkelboom Anouk H. , de Munck Linda , Menke-van der Houven van Oordt C. Willemien , Broeders Mireille J. M. , van den Bongard Desiree H. J. G. , Strobbe Luc J. A. , Mureau Marc A. M. , Lobbes Marc B. I. , Westenend Pieter J. , Koppert Linetta B. , Jager Agnes , Siemerink Ester J. M. , Wesseling Jelle , Verkooijen Helena M. , Vrancken Peeters Marie-Jeanne T. F. D. , Smidt Marjolein L. , Tjan-Heijnen Vivianne C. G. , Siesling Sabine ,   The NABON-COVID-19 Consortium,   The COVID and Cancer Care-NL Consortium, van Hoeve J. C. , Merkx M. A. W. , de Wit N. J. , Dingemans I. , Nagtegaal I. D. 
Published: November 2022

Abstract
Purpose
We aimed to compare (1) treatments and time intervals between treatments of breast cancer patients diagnosed during and before the COVID-19 pandemic, and (2) the number of treatments started during and before the pandemic.

Methods
Women were selected from the Netherlands Cancer Registry. For aim one, odds ratios (OR) and 95% confidence intervals (95%CI) were calculated to compare the treatment of women diagnosed within four periods of 2020: pre-COVID (weeks 1–8), transition (weeks 9–12), lockdown (weeks 13–17), and care restart (weeks 18–26), with data from 2018/2019 as reference. Wilcoxon rank-sums test was used to compare treatment intervals, using a two-sided p-value < 0.05. For aim two, number of treatments started per week in 2020 was compared with 2018/2019.

Results
We selected 34,097 women for aim one. Compared to 2018/2019, neo-adjuvant chemotherapy was less likely for stage I (OR 0.24, 95%CI 0.11–0.53), stage II (OR 0.63, 95%CI 0.47–0.86), and hormone receptor+/HER2− tumors (OR 0.55, 95%CI 0.41–0.75) diagnosed during transition. Time between diagnosis and first treatment decreased for patients diagnosed during lockdown with a stage I (p < 0.01), II (p < 0.01) or III tumor (p = 0.01). We selected 30,002 women for aim two. The number of neo-adjuvant endocrine therapies and surgeries starting in week 14, 2020, increased by 339% and 18%, respectively. The number of adjuvant chemotherapies decreased by 42% in week 15 and increased by 44% in week 22.

Conclusion
The pandemic and subsequently altered treatment recommendations affected multiple aspects of the breast cancer treatment strategy and the number of treatments started per week.
Influence of rewetting on N2O emissions in three different fen types
Authors: Berendt Jacqueline , Jurasinski Gerald , Wrage-Mönnig Nicole 
Published: November 2022

AbstractIn recent years, many peatlands in Europe have been rewetted for nature conservation and global warming mitigation. However, the effects on emissions of the greenhouse gas nitrous oxide (N2O) have been found to be highly variable and driving factors are poorly understood. Therefore, we measured N2O fluxes every two weeks over three years on pairs of sites (one drained, one rewetted) of three important peatland types in North-Eastern Germany, namely, percolation fen, alder forest and coastal fen. Additionally, every three months, sources of N2O were determined using a stable isotope mapping approach. Overall, fluxes were under the very dry conditions of the study years usually small with large temporal and spatial variations. Ammonium concentrations consistently and significantly correlated positively with N2O fluxes for all sites. Cumulative fluxes were often not significantly different from zero and apart from the rewetted alder forest, which was always a source of N2O, sites showed varying cumulative emission behavior (insignificant, source, potentially sink in one case) among years. Precipitation was positively correlated with cumulative fluxes on all drained sites and the rewetted alder forest. Isotope mapping indicated that N2O was always produced by more than one process simultaneously, with the estimated contribution of denitrification varying between 20 and 80%. N2O reduction played a potentially large role, with 5 to 50% of total emissions, showing large variations among sites and over time. Overall, neither the effect of rewetting, water level nor seasonality was clearly reflected in the fluxes or sources. Emissions were concentrated in hotspots and hot moments. A better understanding of the driving factors of N2O production and reduction in (rewetted) fens is essential and stable isotope methods including measurements of 15N and 18O as well as site preferences can help foster the necessary comprehension of the underlying mechanisms.
Leveraging siamese networks for one-shot intrusion detection model
Authors: Hindy Hanan , Tachtatzis Christos , Atkinson Robert , Brosset David , Bures Miroslav , Andonovic Ivan , Michie Craig , Bellekens Xavier 
Published: November 2022

AbstractThe use of supervised Machine Learning (ML) to enhance Intrusion Detection Systems (IDS) has been the subject of significant research. Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to retrain the model for every unseen cyber-attack class. However, retraining the models in-situ renders the network susceptible to attacks owing to the time-window required to acquire a sufficient volume of data. Although anomaly detection systems provide a coarse-grained defence against unseen attacks, these approaches are significantly less accurate and suffer from high false-positive rates. Here, a complementary approach referred to as “One-Shot Learning”, whereby a limited number of examples of a new attack-class is used to identify a new attack-class (out of many) is detailed. The model grants a new cyber-attack classification opportunity for classes that were not seen during training without retraining. A Siamese Network is trained to differentiate between classes based on pairs similarities, rather than features, allowing to identify new and previously unseen attacks. The performance of a pre-trained model to classify new attack-classes based only on one example is evaluated using three mainstream IDS datasets; CICIDS2017, NSL-KDD, and KDD Cup’99. The results confirm the adaptability of the model in classifying unseen attacks and the trade-off between performance and the need for distinctive class representations.
The Effectiveness of Positive Psychology Interventions for Promoting Well-being of Adults Experiencing Depression Compared to Other Active Psychological Treatments: A Systematic Review and Meta-analysis
Authors: Lim Wei Loong , Tierney Stephanie 
Published: November 2022

AbstractThis systematic review assesses if positive psychology interventions (PPI) are more effective than other active psychological interventions for increasing the well-being of depressed adults. A review of randomised trials that compared PPI to other active interventions was conducted. A systematic search was undertaken using PsycInfo, PubMed, EMBASE, Web of Science, Scopus, CINAHL, two trial registries, and a manual search. The outcomes were happiness and depression. Ten studies, totalling 1341 participants, were included in the review. The small effect sizes for depression (Hedge’s g = 0.15) and happiness (Hedge’s g = 0.20) favoured PPI but were not significant, indicating no difference between PPI and other active interventions for the outcomes. Heterogeneity was high mainly due to differences in trial implementation. Risks of bias ranged from moderate to high. The results should be interpreted with caution because of the small number of included studies, high heterogeneity, and presence of bias.Protocol Registration Number PROSPERO CRD42019152513.
Solvothermal treatment of MgF2 coating solutions: a comparative study
Authors: Steenhusen Sönke , Löbmann Peer 
Published: November 2022

AbstractMgF2 coating solutions were prepared by the fluorolytic processing of Mg(OEt)2 and MgCl2. Parts of these sols are solvothermally treated in an autoclave at 160 °C. The two respective precursors were used to prepare porous λ/4 antireflective films by dip-coating on soda-lime and borosilicate glass substrates. UV–Vis spectroscopy and X-Ray diffraction (XRD) were applied to characterize the films as a function of annealing temperature. Samples treated at 500 °C underwent testing of abrasion resistance and water solubility.
rDSA : an intelligent tool for data science assignments
Authors: Vittorini Pierpaolo , Galassi Alessandra 
Published: November 2022

AbstractTools supporting the teaching and learning of programming may help professors in correcting assignments and students in receiving immediate feedback, thus improving the solution before the final submission. This paper describes the rDSA tool, which was designed, developed, and evaluated to support students in completing assignments concerning (i) the execution of statistical analyses in the R language and (ii) commenting on the results in natural language. The paper focuses on the feedback provided by the tool to students and how it was designed/evaluated/improved over the years. The paper also presents the results of two studies that indicate the advantages of using the tool in terms of engagement and learning outcomes. To conclude, we provide a discussion on the characteristics of the tool, its use in similar courses, and the scope for future work.
Estimating the trace of matrix functions with application to complex networks
Authors: Fuentes Rafael Díaz , Donatelli Marco , Fenu Caterina , Mantica Giorgio 
Published: November 2022

AbstractThe approximation of trace(f(Ω)), wherefis a function of a symmetric matrix Ω, can be challenging when Ω is exceedingly large. In such a case even the partial Lanczos decomposition of Ω is computationally demanding and the stochastic method investigated by Bai et al. (J. Comput. Appl. Math.74:71–89, 1996) is preferred. Moreover, in the last years, a partial global Lanczos method has been shown to reduce CPU time with respect to partial Lanczos decomposition. In this paper we review these techniques, treating them under the unifying theory of measure theory and Gaussian integration. This allows generalizing the stochastic approach, proposing a block version that collects a set of random vectors in a rectangular matrix, in a similar fashion to the partial global Lanczos method. We show that the results of this technique converge quickly to the same approximation provided by Bai et al. (J. Comput. Appl. Math.74:71–89, 1996), while the block approach can leverage the same computational advantages as the partial global Lanczos. Numerical results for the computation of the Von Neumann entropy of complex networks prove the robustness and efficiency of the proposed block stochastic method.
Empathic Flow: Dutch Humanist Chaplains’ Experiences with Professional Empathy and Its Challenges
Authors: van Dijke Jolanda , Duyndam Joachim , van Nistelrooij Inge , Bos Pien 
Published: November 2022

AbstractEmpathy is considered a key component of chaplaincy care, but little is known about the daily practice of empathy and the empathy barriers that chaplains encounter. This study investigates the factors that encourage or discourage empathy and provides insight into what chaplains actually do to achieve empathy and to overcome empathy challenges. Semistructured interviews were used to collect data from twenty humanist chaplains in the Netherlands. A grounded theory approach was applied to analyze the data. The core concept of empathic flow emerged from the analysis. This refers to the stream of empathic experiences that arises within the relational, dynamic exchange between chaplain and client. Based on the analysis, three types of empathic flow were distinguished: (1) uncomplicated empathy, which flows smoothly and easily; (2) challenged empathy, which fluctuates between flow and temporal stagnation or disruption; and (3) failed empathy, in which the flow of empathy is blocked. Professional empathy emerged as a second core category from the interview data. This refers to those chaplains’ activities that aim to establish or enhance empathic flow, particularly in the face of challenges. Professional empathy relies on several underlying key components: critical self-reflection, self-care, professional standards, and the chaplain’s humanistic worldview and values. The qualitative analysis yielded 10 themes of professional empathy. Our findings suggest that empathy is a rich and complex practice to which both chaplain and client contribute. As professional caregivers, chaplains consider themselves ultimately responsible for establishing empathy and overcoming challenges.
Vulnerable Capacity. Notes on a Quiet Legal Revolution
Authors: Bernardini Maria Giulia 
Published: November 2022

AbstractThevulnerability turnhas contributed to the concept of vulnerability becoming an established part of the legal lexicon. By adopting a legal-philosophical perspective, this paper will explore what might be considered the most interesting theoretical outcome of the vulnerability paradigm: the concept of universal legal capacity, enshrined in Article 12 of theConvention on the Rights of Persons with Disabilities. The reasoning will focus on two main areas. First, the theoretical background of this reflection will be clarified, by investigating the main arguments of the current debate on vulnerability. Such a reflection will provide the necessary background to explore the relationship between autonomy and vulnerability. The second part of this paper specifically aims to analyse the content and legal implications of Article 12 CRPD. The exegesis of Article 12 will attempt to show that said Article is theoretically founded on the paradigm of vulnerability. Following that, a ‘reality test’ will give the opportunity to discuss some of the main positions that are present in the existing literature on the topic, with particular attention to the relationship between support and substitution. The expressionvulnerable capacityhas been used in order to emphasise the complex analysis required to adequately address the issue of capacity from a theoretical perspective. It will be argued that legal capacity can be considered vulnerable because it characterises a (universally) vulnerable subject.
Demonstrations as actions
Authors: Ciecierski Tadeusz , Makowski Piotr Tomasz 
Published: November 2022

AbstractThis paper presents a dual intention model (DIM) of demonstrations as actions to show the agentive nature of demonstrations. According to the DIM, demonstrations are complex actions that contain as components at least three elements: an abductive intention, a deictic intention, and a basic ostensive act of indication. This paper unpacks these three components and discusses their roles from the viewpoint of the philosophy of action and the philosophy of language. It also shows how the DIM applies in selected practical examples and explains the merits of the model in the context of other views on demonstrations and demonstratives.