bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of quality indicators for vulvar cancer in gynaecological cancer centres certified by the German Cancer Society (DKG)
Authors: Stuebs Frederik A. , Beckmann Matthias W. , Dannecker Christian , Follmann Markus , Nothacker Monika , Schnürch Hans-Georg , Woelber Linn , Wesselmann Simone 
Published: May 2024

Abstract
Purpose
In 2018, the first guideline-based quality indicators (QI) for vulvar cancer were implemented in the data-sheets of certified gynaecological cancer centres. The certification process includes guideline-based QIs as a fundamental component. These indicators are specifically designed to evaluate the level of care provided within the centres. This article aims to give an overview of the developing process of guideline based-QIs for women with vulvar cancer and presents the QIs results from the certified gynaecological cancer centres.

Methods
The QIs were derived in a standardized multiple step process during the update of the 2015 S2k guideline “Diagnosis, Therapy, and Follow-Up Care of Vulvar Cancer and its Precursors” (registry-number: no. 015/059) and are based on strong recommendations.

Results
In total, there are eight guideline-based QIs for vulvar cancer. Four QIs are part of the certification process. In the treatment year 2021, 2.466 cases of vulvar cancer were treated in 177 centres. The target values in the centres for pathology reports on tumour resection and lymphadenectomy as well as sentinel lymph nodes have increased since the beginning of the certification process and have been above 90% over the past three treatment years (2019–2021).

Discussion
QIs based on strong guideline recommendations, play a crucial role in measuring and allowing to quantify essential aspects of patient care. By utilizing QIs, centres are able to identify areas for process optimization and draw informed conclusions. Over the years the quality of treatment of vulvar cancer patients measured by the QIs was improved. The certification system is continuously reviewed to enhance patient care even further by using the outcomes from QIs revaluation.
Frequency curves of high and low flows in intermittent river basins for hydrological analysis and hydraulic design
Authors: Sarigil Gokhan , Cavus Yonca , Aksoy Hafzullah , Eris Ebru 
Published: May 2024

AbstractUpper and lower percentiles of Flow Duration Curves (FDCs) of daily streamflow data were investigated to develop frequency curves. Upper percentiles with exceedance probability of 1, 5 and 10% (Q1, Q5, Q10) were used for high flows, and lower percentiles with non-exceedance probability of 10, 5 and 1% (Q90, Q95, Q99) for low flows. Median value (Q50) was covered to represent the average conditions of streamflow. A mixed frequency analysis based on the total probability theorem taking zero values into account was applied for the lower percentiles of FDC. Case studies were performed for three intermittent Streamflow Gauging Stations (SGSs) from Kucuk Menderes River Basin in western Turkey. An overall assessment of results shows that the best-fit probability distribution function does not change from one SGS to another considerably for low flows while each SGS has its own probability distribution function for high flows. Upper and lower percentiles, and median value were calculated at various return periods by using the identified probability distribution functions. The calculated values were plotted in the form of frequency curves of high flow percentiles and low flow percentiles. The frequency curves have a practically significant potential use in hydrological analysis, water resources management and hydraulic design under high and low flow conditions. They are yet open to further development for regionalization and their applicability can be extended to ungauged sites in river basins.
Evaluating the performance of metaheuristic-tuned weight agnostic neural networks for crop yield prediction
Authors: Jovanovic Luka , Zivkovic Miodrag , Bacanin Nebojsa , Dobrojevic Milos , Simic Vladimir , Sadasivuni Kishor Kumar , Tirkolaee Erfan Babaee 
Published: May 2024

AbstractThis study explores crop yield forecasting through weight agnostic neural networks (WANN) optimized by a modified metaheuristic. WANNs offer the potential for lighter networks with shared weights, utilizing a two-layer cooperative framework to optimize network architecture and shared weights. The proposed metaheuristic is tested on real-world crop datasets and benchmarked against state-of-the-art algorithms using standard regression metrics. While not claiming WANN as the definitive solution, the model demonstrates significant potential in crop forecasting with lightweight architectures. The optimized WANN models achieve a mean absolute error (MAE) of 0.017698 and an R-squared ($$R^2$$

R
2

) score of 0.886555, indicating promising forecasting performance. Statistical analysis and Simulator for Autonomy and Generality Evaluation (SAGE) validate the improvement significance and feature importance of the proposed approach.
Design of a fully integrated sensor system of a plain bearing
Authors: Paeßens Janek , Kratz Karl-Heinz , Gemmeke Tobias , Kauth Kevin , Baszenski Thao , Lehmann Benjamin , Jacobs Georg 
Published: May 2024

AbstractRecent years revealed a notable trend for rolling bearings to be increasingly replaced by plain bearings for particular applications. A prominent example is the planetary stage in wind turbine gearboxes. The advantages of plain bearings are higher realizable power density due to smaller installation space compared to rolling bearings as well as the possibility of wear-free operation under ideal operational conditions. In real applications, however, plain bearings are subject to wear, for example due to start-stop processes, which lead to mixed friction conditions. Since the wear of plain bearings strongly depends on the operational conditions, monitoring is essential to detect inadmissible operating conditions. To avoid extra installation space and to achieve a minimal influence on the surrounding system, this work aims to integrate an energy-autarkic sensor system into the bearing volume to monitor the operational status of the plain bearing. To achieve autarky, the resulting data must be transmitted wirelessly and the external power supply must be eliminated. In this work, the software and hardware architecture of a sensor-integrating plain bearing prototype for monitoring the minimum oil gap height and the displacement angle of the shaft based on in-situ temperature measurements is presented. Furthermore, energy harvesting and energy saving measures are implemented and evaluated which intend to enable completely autarkic operation of the sensor integrating machine element in the future. A prototype of the sensor system is in turn used in-the-field to investigate required sampling rates and the spatial resolution of the temperature measurements.
A linear time algorithm for linearizing quadratic and higher-order shortest path problems
Authors: Çela Eranda , Klinz Bettina , Lendl Stefan , Woeginger Gerhard J. , Wulf Lasse 
Published: May 2024

Abstract
An instance of the NP-hard Quadratic Shortest Path Problem (QSPP) is called linearizable iff it is equivalent to an instance of the classic Shortest Path Problem (SPP) on the same input digraph. The linearization problem for the QSPP (LinQSPP) decides whether a given QSPP instance is linearizable and determines the corresponding SPP instance in the positive case. We provide a novel linear time algorithm for the LinQSPP on acyclic digraphs which runs considerably faster than the previously best algorithm. The algorithm is based on a new insight revealing that the linearizability of the QSPP for acyclic digraphs can be seen as a local property. Our approach extends to the more general higher-order shortest path problem.
The relationship between imaging features, therapeutic response, and overall survival in pediatric diffuse intrinsic pontine glioma
Authors: Yu Xiaojun , Lai Mingyao , Li Juan , Wang Lichao , Ye Kunlin , Zhang Dong , Hu Qingjun , Li Shaoqun , Hu Xinpeng , Wang Qiong , Ma Mengjie , Xiao Zeyu , Zhou Jiangfen , Shi Changzheng , Luo Liangping , Cai Linbo 
Published: May 2024

AbstractWe aimed to evaluate the relationship between imaging features, therapeutic responses (comparative cross-product and volumetric measurements), and overall survival (OS) in pediatric diffuse intrinsic pontine glioma (DIPG). A total of 134 patients (≤ 18 years) diagnosed with DIPG were included. Univariate and multivariate analyses were performed to evaluate correlations of clinical and imaging features and therapeutic responses with OS. The correlation between cross-product (CP) and volume thresholds in partial response (PR) was evaluated by linear regression. The log-rank test was used to compare OS patients with discordant therapeutic response classifications and those with concordant classifications. In univariate analysis, characteristics related to worse OS included lower Karnofsky, larger extrapontine extension, ring-enhancement, necrosis, non-PR, and increased ring enhancement post-radiotherapy. In the multivariate analysis, Karnofsky, necrosis, extrapontine extension, and therapeutic response can predict OS. A 25% CP reduction (PR) correlated with a 32% volume reduction (R2 = 0.888). Eight patients had discordant therapeutic response classifications according to CP (25%) and volume (32%). This eight patients’ median survival time was 13.0 months, significantly higher than that in the non-PR group (8.9 months), in which responses were consistently classified as non-PR based on CP (25%) and volume (32%). We identified correlations between imaging features, therapeutic responses, and OS; this information is crucial for future clinical trials. Tumor volume may represent the DIPG growth pattern more accurately than CP measurement and can be used to evaluate therapeutic response.
Learning search algorithm: framework and comprehensive performance for solving optimization problems
Authors: Qu Chiwen , Peng Xiaoning , Zeng Qilan 
Published: May 2024

AbstractIn this study, the Learning Search Algorithm (LSA) is introduced as an innovative optimization algorithm that draws inspiration from swarm intelligence principles and mimics the social learning behavior observed in humans. The LSA algorithm optimizes the search process by integrating historical experience and real-time social information, enabling it to effectively navigate complex problem spaces. By doing so, it enhances its global development capability and provides efficient solutions to challenging optimization tasks. Additionally, the algorithm improves the collective learning capacity by incorporating teaching and active learning behaviors within the population, leading to improved local development capabilities. Furthermore, a dynamic adaptive control factor is utilized to regulate the algorithm’s global exploration and local development abilities. The proposed algorithm is rigorously evaluated using 40 benchmark test functions from IEEE CEC 2014 and CEC 2020, and compared against nine established evolutionary algorithms as well as 11 recently improved algorithms. The experimental results demonstrate the superiority of the LSA algorithm, as it achieves the top rank in the Friedman rank-sum test, highlighting its power and competitiveness. Moreover, the LSA algorithm is successfully applied to solve six real-world engineering problems and 15 UCI datasets of feature selection problems, showcasing its significant advantages and potential for practical applications in engineering problems and feature selection problems.
Balancing the cardinality of clusters with a distance constraint: a fast algorithm
Authors: Calvete Herminia I. , Galé Carmen , Iranzo José A. 
Published: May 2024

AbstractLogistics companies partition the customers they serve into delivery zones as a tactical decision and manage the customers assigned to each zone as a cluster for the purpose of routing, workload allocation, etc. Frequently, this partition is made in accordance with customers’ geographical location, which can result in very unbalanced clusters in terms of the number of customers they include. In addition, in the day-to-day operations, not necessarily all customers need to be served every day so, even if the clusters originally created are balanced, daily needs may lead to unbalanced clusters. Given an a priori assignment of customers to clusters, improving the balance between clusters in advance of workload management is therefore a key issue. This paper addresses the problem of balancing clusters, when there is a distance constraint that prevents reassigning customers to clusters far away from their original pre-assignment. This problem is formulated as a lexicographic biobjective optimization model. The highest priority objective function minimizes the variance of the number of customers in the clusters. The second ranked objective function minimizes the total distance resulting from all reassignments. A fast and effective heuristic algorithm is developed, based on exploring customer reassignments, either by comparing clusters two by two or by extending the search to allow for sequential customer swaps among clusters. Both the quality of the solution and the computational time required encourage the use of this algorithm by logistics companies to balance clusters in real scenarios.
Investigation of Sidewall and Reynolds Number Effects in a Ribbed Square Duct
Authors: Santese Tiziano , Martinez-Sanchis Daniel , Sternin Andrej , Manfletti Chiara 
Published: May 2024

AbstractThis paper presents a comprehensive three-dimensional Direct Numerical Simulation (DNS) investigation of flow characteristics over a roughened wall in a duct, exploring bulk Reynolds number variations from 4400 to 13,200 and considering the influence of side walls. Notably, a significant increase in friction factor highlights heightened resistance to flow due to surface roughness, emphasizing the importance of considering surface conditions in engineering applications. The study reveals three recirculation zones in the streamwise direction, indicating intricate separation phenomena caused by the interaction between the ribbed wall and the flow. Furthermore, the presence of sidewalls creates two major vortices perpendicular to the flow direction, highlighting the complexity of the vortical structures in this configuration, crucial for predicting flow behavior and optimizing system performance. The study demonstrates that the influence of the Reynolds number on these vortices is not well-scalable with respect to outer units, in contrast with respect to smooth ducts. Investigating side-wall effects, increased turbulent production rate, and non-equilibrium turbulence along the side walls highlight the sensitivity of turbulent stresses to Reynolds number and side-wall proximity. In conclusion, the paper provides novel insights into the interplay between Reynolds numbers, roughened surfaces, and boundary conditions in turbulent flows, laying a foundation for a deeper understanding of the flow in duct with high roughness.
Curcumin’s effects on growth indices, histological scores, blood metabolites, redox state, immunity, and antioxidant-related genes of red tilapia (Oreochromis sp.)
Authors: Eissa El-Sayed Hemdan , Awlya Ohaad F. , Abusudah Wafaa F. , Qadhi Alaa H. , Abd El-Aziz Yasmin M. , Rinthong Prasob-orn , Abdelnour Sameh A. , Munir Mohammad Bodrul , Eissa Moaheda E. H. , Sakr Salah El-Sayed 
Published: May 2024

AbstractCurcumin, a polyphenol, targets multiple signaling molecules and shows activity at the cellular level, supporting its various health benefits. Thereafter, the present study examines the effects of different doses of dietary curcumin on growth indices, feed efficiency, serum metabolites, redox (oxidation) status, immunity, histological assessment, and antioxidant-related genes in red tilapia (Oreochromis sp, Oreochromis aureus x O. mossambicus). A total of 1200 red tilapia with an average weight of 19.1±0.03 g were distributed in 12 cement ponds (3×3.5×1m). Each treatment was assigned three pounds (n=100 replicates). For 60 days, fish were fed baseline diets containing 0, 0.4, 0.6, and 0.8 g of curcumin/kg of diet. The treated fish showed increased body weight and SGR (specific growth rate) compared to the T0 group (P<0.05). Curcumin in the diet significantly improved weight gain, percentages, and FCR (feed conversion ratio), with a dose-dependent effect (P < 0.05). Curcumin supplementation showed no influence on feed intake, fish mortality, or survival rate (P >0.05). The curcumin-treated fish groups improved tissue structure in hepatocytes, pancreatic lumens, hepatic blood sinusoids, and intestine tissue layers, particularly the mucosal layer. The T0.8 group had reduced liver enzymes (AST and ALT) and greater total protein and albumin levels (P<0.05). The T0.6 and T0.8 groups showed significantly lower MDA levels than the other groups (P < 0.05). Curcumin groups demonstrated significantly higher antioxidant indices (CAT, GPx, and SOD) compared to the basal diet (P<0.05). Curcumin administration resulted in significant improvements in IgM and lysosome levels (P<0.05). All supplemented groups had considerably (P<0.05) higher levels of SOD, CAT, and GPx mRNA than the control group. Consequently, administering 0.6–0.8 g/kg of curcumin to red tilapia (Oreochromis sp.) diets may improve the fish’s growth, health, tissue composition, and antioxidant response.
A hybrid model for post-earthquake performance assessments in challenging contexts
Authors: Kijewski-Correa Tracy , Canales Eric , Hamburger Rachel , Lochhead Meredith , Mbabazi Angelique , Presuma Lamarre 
Published: May 2024

AbstractDisasters provide an invaluable opportunity to evaluate contemporary design standards and construction practices; these evaluations have historically relied upon experts, which inherently limited the speed, scope and coverage of post-disaster reconnaissance. However, hybrid assessments that localize data collection and engage remote expertise offer a promising alternative, particularly in challenging contexts. This paper describes a multi-phase hybrid assessment conducting rapid assessments with wide coverage followed by detailed assessments of specific building subclasses following the 2021 M7.2 earthquake in Haiti, where security issues limited international participation. The rapid assessment classified and assigned global damage ratings to over 12,500 buildings using over 40 non-expert local data collectors to feed imagery to dozens of remote engineers. A detailed assessment protocol then conducted component-level evaluations of over 200 homes employing enhanced vernacular construction, identified via machine learning from nearly 40,000 acquired images. A second mobile application guided local data collectors through a systematic forensic documentation of 30 of these homes, providing remote engineers with essential implementation details. In total, this hybrid assessment underscored that performance in the 2021 earthquake fundamentally depended upon the type and consistency of the bracing scheme. The developed assessment tools and mobile apps have been shared as a demonstration of how a hybrid approach can be used for rapid and detailed assessments following major earthquakes in challenging contexts. More importantly, the open datasets generated continue to inform efforts to promote greater use of enhanced vernacular architecture as a multi-hazard resilient typology that can deliver life-safety in low-income countries.
Using biophysical modelling and marine connectivity to assess the risk of natural dispersal of non-indigenous species to comply with the Ballast Water Management Convention
Authors: Hansen Flemming Thorbjørn , Pastor Ane , Christensen Asbjørn , Stuer-Lauridsen Frank 
Published: May 2024

AbstractThe introduction of Marine Non-Indigenous Species (NIS) poses a significant threat to global marine biodiversity and ecosystems. To mitigate this risk, the Ballast Water Management Convention (BWMC) was adopted by the UN International Maritime Organisation (IMO), setting strict criteria for discharges of ballast water. However, the BWMC permits exemptions for shipping routes operating within a geographical area, known as a Same-Risk-Area (SRA). An SRA can be established in areas where a risk assessment (RA) can conclude that the spread of NIS via ballast water is low relative to the predicted natural dispersal. Despite the BWMC's requirement for RAs to be based on modelling of the natural dispersal of NIS, no standard procedures have been established. This paper presents a methodology utilizing biophysical modelling and marine connectivity analyses to conduct SRA RA and delineation. Focusing on the Kattegat and Øresund connecting the North Sea and Baltic Sea, we examine two SRA candidates spanning Danish and Swedish waters. We provide an example on how to conduct an RA including an RA summary, and addressing findings, challenges, and prospects. Our study aims to advance the development and adoption of consistent, transparent, and scientifically robust SRA assessments for effective ballast water management.
Limitations of the international approach to anti-corruption: a systematic review of South Africa’s compelling case of failing anti-corruption
Authors: Labik Amanquandor Thomas Duke 
Published: May 2024

AbstractIn the Global South, anti-corruption initiatives continue to fail despite varying commitments to the international anti-corruption agenda. Concurrently, as this study demonstrates, researchers investigating this paradox appear confined within orthodox explanations for failing anti-corruption efforts. Through a systematic review of 58 studies, this paper demonstrates that South Africa’s anti-corruption corpora from 1995 to 2022 fall to this critique. By employing socio-legal theoretical perspectives, the paper elucidates how and why the orthodoxy dominates the corpora and subsequently suggests a more nuanced understanding of the country’s ongoing failure to combat corruption. For example, the paper argues that the intricacies of South Africa’s corruption challenge the perspective that anti-corruption measures fail simply due to widespread rule-breaking. Through the prism of legal pluralism, this paper demonstrates that adherence to rules is indeed prevalent in South Africa, albeit often not aligned with formal state anti-corruption legislation and regulations. Finally, the paper posits innovative approaches to enhance and broaden our comprehension of why anti-corruption efforts fail, especially in the Global South.