bluuebunny/crossref_metadata_2025_split huggingface dataset:
MR-guided HDR prostate brachytherapy with teleoperated steerable needles
Authors: de Vries M. , Wijntjes M. , Sikorski J. , Moreira P. , van de Berg N. J. , van den Dobbelsteen J. J. , Misra S. 
Published: July 2023

AbstractConformity of tumour volumes and dose plans in prostate brachytherapy (BT) can be constrained by unwanted needle deflections, needle access restrictions and visualisation limitations. This work validates the feasibility of teleoperated robotic control of an active steerable needle using magnetic resonance (MR) for guidance. With this system, perturbations can be counteracted and critical structures can be circumvented to access currently inaccessible areas. The system comprises of (1) a novel steerable needle, (2) the minimally invasive robotics in an MR environment (MIRIAM) system, and (3) the daVinci Research Kit (dVRK). MR scans provide visual feedback to the operator controlling the dVRK. Needle steering is performed along curved trajectories to avoid the urethra towards targets (representing tumour tissue) in a prostate phantom with a targeting error of 1.2 ± 1.0 mm. This work shows the potential clinical applicability of active needle steering for prostate BT with a teleoperated robotic system in an MR environment.
Tool Condition Monitoring Methods Applicable in the Metalworking Process
Authors: Lara de Leon Melvin Alexis , Kolarik Jakub , Byrtus Radek , Koziorek Jiri , Zmij Petr , Martinek Radek 
Published: July 2023

AbstractThis article reviews and analyzes the approaches utilized for monitoring cutting tool conditions. The Research focuses on publications from 2012 to 2022 (10 years), in which Machine Learning and other statistical processes are used to determine the quality, condition, wear, and remaining useful life (RUL) of shearing tools. The paper quantifies the typical signals utilized by researchers and scientists (vibration of the cutting tool and workpiece, the tool cutting force, and the tool’s temperature, for example). These signals are sensitive to changes in the workpiece quality condition; therefore, they are used as a proxy of the tool degradation and the quality of the product. The selection of signals to analyze the workpiece quality and the tool wear level is still in development; however, the article shows the main signals used over the years and their correlation with the cutting tool condition. These signals can be taken directly from the cutting tool or the workpiece, the choice varies, and both have shown promising results. In parallel, the Research presents, analyzes, and quantifies some of the most utilized statistical techniques that serve as filters to cleanse the collected data before the prediction and classification phase. These methods and techniques also extract relevant and wear-sensitive information from the collected signals, easing the classifiers’ work by numerically changing alongside the tool wear and the product quality.
How Do Women “Shine?” Exploring Professional Women’s Perceptions of “Women’s Advancement” in Japan
Authors: Iida Aki 
Published: July 2023

AbstractThe Abe administration has introduced policies and legislation to increase women’s participation in the workforce, known as Abenomics, under the slogan “ society where all women shine.” The study investigates the perceptions of professional women in Japan regarding the “women’s advancement” policy and the prevailing gender dynamics in a society known for its severe gender inequality. To accomplish this, semi-structured interviews with 30 professional Japanese women were conducted. The findings show that women perceive many barriers to “shining.” For example, the law promoting women’s participation and advancement in the workplace only applies to some women working in large companies. The number of women liable to benefit is small, so the initiative may have the unintended consequence of fueling divisions among women, highlighting the challenge of promoting women’s activity horizontally and vertically. As Japan’s economy has been stagnant for the past 30 years, it is perhaps natural that the government would implement policies to increase and exploit women’s labor. However, women are likely to be overburdened and stressed unless men’s participation in the home is substantially increased at the same time. Women face the challenges of working regular hours, giving birth, raising children, doing housework, and caring for family members. For this reason, the government and companies need to implement more family-friendly policies, such as improving social welfare policies, expanding public daycare centers, and setting up in-house daycare centers. Only when these issues are resolved will women be able to “shine.”
Portrayal of autism in mainstream media – a scoping review about representation, stigmatisation and effects on consumers in non-fiction and fiction media
Authors: Mittmann Gloria , Schrank Beate , Steiner-Hofbauer Verena 
Published: July 2023

AbstractMainstream media is a common source of information on mental health, and its portrayal of mental disorders can influence public perceptions and stigmatisation. Recently, autism has received increased attention in mainstream media. This scoping review aims to contribute to the existing literature on the portrayal of autism and its stigmatising effect by mapping the characteristics and range of records that describe the representation of autism in mainstream media with a focus on non-fiction media (newspapers and social media) and fiction media (movies & TV, and literature). We extracted 31 articles from PubMed and PsychInfo, as well as conducting secondary searches, covering articles published between 2010 and 2022, with a time frame of media from 1988 to 2022. Most of the articles focused on newspapers and movies & TV. Our findings suggest that while the portrayal of autism in media varies, stigmatisation is most prominent in newspapers and movies & TV, often with a negative tone and stereotypical portrayal such as savantism. One possible reason for this could be the lack of representation of experts by experience in these media outlets. In contrast, our review found that literature often has a more diverse and positive representation, and social media tends to have a more supportive tone. Our recommendation is that autistic individuals should be included in the content creation process. Furthermore, future research should focus on newer forms of media, particularly social media, where self-representation is more common, and investigate how this affects the portrayal and stigmatisation of autism.
Effects of exercise on cancer-related cognitive impairment in breast cancer survivors: a scoping review
Authors: Jesús Orellana-Jaén , Luis Carrasco-Páez , Matilde Mora-Fernández 
Published: July 2023

Abstract
Background
Cancer-related cognitive impairment (CRCI) is one of the major long-term concerns reported by breast cancer survivors after overcoming the disease. The present study undertakes a scoping review of relevant research publications to explore the effect of increasing physical activity (PA) levels or the use of exercise (EX)-based programs on CRCI in female breast cancer survivors; who have completed neo/adjuvant chemotherapy treatment and are awaiting or receiving hormonal therapy.

Methods
An electronic search of Pubmed, Embase, Scopus, WOS, and Cochrane databases has been conducted to identify published literature from January 2000 to December 2021.

Results
Of 1129 articles, twenty met the inclusion criteria. The majority of the included observational studies (90%) reported cross-sectional design; meanwhile, 72% of experimental research reported randomized controlled trials (RCTs) or randomized crossover trials. 15 neuropsychological batteries and tests, and 5 self-reported validated questionnaires were employed. Only 27% of the included articles used a combination of the previously mentioned methods. The recorder of moderate–vigorous PA (MVPA), defined as more than 3 METs, or represented as average daily minutes spent (≥ 1952 counts/min) was the most analyzed variable in cross-sectional studies, and EX programs based on aerobic training (AT) were the most proposed by RCTs.

Conclusions
The exploratory approach of this review demonstrates modest but increasingly promising evidence regarding exercise’s potential to improve brain health among breast cancer survivors although these findings highlight the importance of addressing methodological heterogeneity in the same direction with the view of using exercise within the clinic area.
Machine economies
Authors: Hartwich Eduard , Rieger Alexander , Sedlmeir Johannes , Jurek Dominik , Fridgen Gilbert 
Published: July 2023

AbstractThis fundamentals article discusses efficient machine economies in which non-human agents can autonomously exchange information and value. We first identify criteria for achieving Pareto efficiency in such economies by drawing on the Coase Theorem. We then translate these economic criteria to technical requirements before developing a framework that characterizes four types of machine economies. We discuss real-life examples for each type to highlight key challenges in achieving Pareto efficiency. In particular, we highlight that machine economies with human involvement in economic interactions and governance face significant challenges regarding perfect information, rationality, and transaction costs. Machine economies without human involvement, in turn, promise a high degree of Pareto efficiency, but there are still many open questions, particularly regarding machine-enforced governance. We conclude with opportunities for future research on the interactions and governance in machine economies.
Multimodal learning of clinically accessible tests to aid diagnosis of neurodegenerative disorders: a scoping review
Authors: Huang Guan , Li Renjie , Bai Quan , Alty Jane 
Published: July 2023

AbstractWith ageing populations around the world, there is a rapid rise in the number of people with Alzheimer’s disease (AD) and Parkinson’s disease (PD), the two most common types of neurodegenerative disorders. There is an urgent need to find new ways of aiding early diagnosis of these conditions. Multimodal learning of clinically accessible data is a relatively new approach that holds great potential to support early precise diagnosis. This scoping review follows the PRSIMA guidelines and we analysed 46 papers, comprising 11,750 participants, 3569 with AD, 978 with PD, and 2482 healthy controls; the recency of this topic was highlighted by nearly all papers being published in the last 5 years. It highlights the effectiveness of combining different types of data, such as brain scans, cognitive scores, speech and language, gait, hand and eye movements, and genetic assessments for the early detection of AD and PD. The review also outlines the AI methods and the model used in each study, which includes feature extraction, feature selection, feature fusion, and using multi-source discriminative features for classification. The review identifies knowledge gaps around the need to validate findings and address limitations such as small sample sizes. Applying multimodal learning of clinically accessible tests holds strong potential to aid the development of low-cost, reliable, and non-invasive methods for early detection of AD and PD.
Early detection of paediatric and adolescent obsessive–compulsive, separation anxiety and attention deficit hyperactivity disorder using machine learning algorithms
Authors: Haque Umme Marzia , Kabir Enamul , Khanam Rasheda 
Published: July 2023

Abstract
Purpose
Mental health issues of young minds are at the threshold of all development and possibilities. Obsessive–compulsive disorder (OCD), separation anxiety disorder (SAD), and attention deficit hyperactivity disorder (ADHD) are three of the most common mental illness affecting children and adolescents. Several studies have been conducted on approaches for recognising OCD, SAD and ADHD, but their accuracy is inadequate due to limited features and participants. Therefore, the purpose of this study is to investigate the approach using machine learning (ML) algorithms with 1474 features from Australia's nationally representative mental health survey of children and adolescents.

Methods
Based on the internal cross-validation (CV) score of the Tree-based Pipeline Optimization Tool (TPOTClassifier), the dataset has been examined using three of the most optimal algorithms, including Random Forest (RF), Decision Tree (DT), and Gaussian Naïve Bayes (GaussianNB).

Results
GaussianNB performs well in classifying OCD with 91% accuracy, 76% precision, and 96% specificity as well as in detecting SAD with 79% accuracy, 62% precision, 91% specificity. RF outperformed all other methods in identifying ADHD with 91% accuracy, 94% precision, and 99% specificity.

Conclusion
Using Streamlit and Python a web application was developed based on the findings of the analysis. The application will assist parents/guardians and school officials in detecting mental illnesses early in their children and adolescents using signs and symptoms to start the treatment at the earliest convenience.
On the sensitivity analysis of the DEM oedometer experiment
Authors: Jahn Momme , Meywerk Martin 
Published: July 2023

AbstractThe discrete element method (DEM) is frequently used to investigate the behaviour of granular media (Bravo in Simulation of soil and tillage-tool interaction by the discrete element method, 2013; Tijskens et al. in J Sound Vib 266:493–514, 2003; Langston et al. in Chem Eng Sci 50:967–987, 1995; Kohring et al. in Comput Methods Appl Mech Eng 124:273–281, 1995; Stahl et al. in Granul Matter 13:417–428, 2011). The parameter calibration is a challenging task due to the large number of input parameters and the computational effort. Sometimes, this is performed with a trial-and-error approach as mentioned in Roessler et al. (Powder Technol 343:803–812, 2019), Rackl and Hanley (Powder Technol 307:73–83, 2017) based on laboratory tests, e.g. the pile experiment, the oedometer experiment and the shear test. To achieve a more suitable calibration, a better model understanding is necessary in which the influence of the DEM parameters is analysed. Consequently, the calibration can be focused on specific parameters, which have a significant influence on thef model response. If parameters with a negligibly small influence exist, the number of calibration parameters can be reduced. On this basis, it is possible to decide whether the laboratory test is suitable for the calibration of specific parameters or not. This is demonstrated with a sensitivity analysis based on Sobol’ indices for the oedometer laboratory test. In order to reduce the computational effort, the sensitivity analysis is performed with different metamodels of the oedometer simulation. The metamodels are fitted and validated with two separate sampling point sets. It is shown that the Young’s modulus for the investigated input space is the most significant parameter. This knowledge can be used to only focus the calibration on this significant parameter which enables an easier calibration and makes clear that for calibrating of other parameters this laboratory test is inappropriate. An algorithm of a force-driven plate is developed and shown which prevents non-physical states in which the interaction force between the particles and the loadplate exceeds the applied force.
An overview of surface forces and the DLVO theory
Authors: Agmo Hernández Víctor 
Published: July 2023

AbstractThis lecture text focuses on surface forces and interactions in a liquid medium, with particular emphasis on the surface-surface interactions described by the DLVO theory, i.e., van der Waals attraction and electric double-layer repulsion. The text begins by describing the fundamental forces of nature, their connection to intermolecular interactions, and how the latter result in measurable forces between surfaces and macroscopical objects. A step-by-step reasoning on how DLVO forces arise is then presented, accompanied by a simplified description of the mathematical derivations of the main equations within the framework of the theory. The connection between the DLVO theory and the prediction of the stability of colloidal systems is presented. Examples on how the colloidal stability can be controlled or tuned are presented. The shortcomings of the original DLVO theory are discussed, and recent extended models dealing with these issues are briefly described. The text closes with a general overview of some of the most relevant non-DLVO interaction.
Alkali fusion of bauxite refining residue (red mud-RM) to produce low carbon cements
Authors: Pavia S. , Goodhue R. , Alelweet O. 
Published: July 2023

AbstractThis paper creates hydraulic binders using waste and a low energy input. Cements are produced with a bauxite refining residue (red mud-RM), blended with limestone and lime, and fused at temperatures from 600 to 1200 °C. The Saudi RM investigated has significant Al and Si but low Ca. Therefore, lime (CaO) and limestone (CaCO3) are used, as a source of calcium, to harvest cementing hydrates.When calcining RM alone, reactive aluminium phases begin to form at c.300 °C. However, at c.900 °C, they turn into crystalline corundum (Al2O3), a more stable and less reactive phase. It is hoped that the Ca provided by the lime/limestone will react with the Al in the RM during fusion, to form reactive silicates and aluminates rather than inert corundum. Both types of fusion produced calcium silicates and aluminates with cementing properties. However, lime fusion required higher temperature. Limestone fusion produces cementing phases at lower temperature than lime fusion, due to the lower decomposition temperature of CaCO3 when compared to CaO. High temperature is required to break down CaO (melting point = 2572 °C), whereas CaCO3 decomposes at 600 °C and disappears at 850 °C. Despite the top alkali fusion temperature being much lower than the CaO melting point, the results demonstrate that calcium was released from the lime and entered reactions forming calcium silicates and aluminates. This is probably due to the high alkali content of the RM acting as a flux and lowering the decomposition temperature of the CaO.
Complexity theory as an exploratory paradigm: can scientific inquiry effectively measure individual’s challenging behaviour in a non-linear way
Authors: Tomas Krista 
Published: July 2023

AbstractTheoretical constructs to explore neurocognitive management of challenging behaviour in young people are inherently fraught with the difficulty of what exactly is to be measured that is acceptably benchmarked against standard mechanistic scientific inquiry. Indeed, this identifies the potential for a new scientific paradigm to be developed that explains the links between complex brain systems and functions, the development of the mind and adolescent challenging behaviour. The imperative lies in overcoming the strictly linear nature of some of the current scientific inquiry methods embracing instead, tools that can measure the non-linear, unexpected and emergent features of change. These changes are elicited through the interaction of the brain and human environments, sometimes manifesting in chaotic and challenging behaviour. The objective of this article is to explore the subtleties of complexity theory, to determine an essential lead to a non-linear way of measuring challenging behaviour in adolescents. The brain is a complex system and CT provides, here, the framework for understanding the dynamic and often non-linear neural activity that shifts in response to changes in an individual’s environment. I pose the question; Exploring CT as an underpinning theoretical framework, is it demonstrated that there are methods of measuring the non-linearity of an individual’s challenging behaviour, in a way that meets the expectations of sound scientific inquiry? The method used is an exploratory review and is addressed in two parts. The first is how to explain challenging behaviour in a neuro-informed state of complexity and the second is whether it is possible to use Complexity Theory as an exploratory framework for determining the non-linear characteristics of challenging behaviour. The article concludes with suggestions that Complexity Theory is an evolving theoretical construct primed to advance a more in-depth understanding of the non-linearity of challenging behaviour. As such, Complexity Theory has the potential for exploring a new paradigm of scientific inquiry.
WeiTsing: a new face of Ca2+-permeable channels in plant immunity
Authors: Wang Feng-Zhu , Li Jian-Feng 
Published: July 2023

AbstractPlants employ pattern- and effector-triggered immunity (PTI and ETI) to synergistically defend invading pathogens and insect herbivores. Both PTI and ETI can induce cytosolic Ca2+ spikes, despite in different spatiotemporal patterns, to activate downstream Ca2+-dependent immune signaling cascades. While multiple families of Ca2+-permeable channels at the plasma membrane have been uncovered, the counterparts responsible for Ca2+ release from intracellular stores remain poorly understood. In a groundbreaking paper published recently by Cell, the authors reported that WeiTsing, an Arabidopsis endoplasmic reticulum (ER)-resident protein that was specifically expressed in the pericycle upon Plasmodiophora brassicae (Pb) infection, could form resistosome-like Ca2+-conducting channel and protect the stele of Brassica crops from Pb colonization. As the channel activity of WeiTsing was indispensable for its immune function, the findings highlight a previously underappreciated role of Ca2+ release from intracellular repertoire in promoting plant disease resistance.
Statistical Quality Control: Acceptance Sampling Plans in the Light of Fuzzy Mathematics
Authors: Bhattacharyya Surajit 
Published: July 2023

AbstractStatistical quality control is a productivity enhancing and regulatory technique with three factors––Management, Methods and Mathematics. More precisely, if we want to properly design a self-regulating system for quality, we have to look to the field of cybernetics for design information. Quality improvement management aims to decrease variability, which leads to decrease the costs, the production time, the number of defects, scrap, rework,––and increase the customer satisfaction. Many problems in these scientific investigations generate non-precise data incorporating non-statistical uncertainty. A non-precise observation of a qualitative variable can be described by a special type of membership function defined on the set of all real numbers called a fuzzy number. In this paper, I have thoroughly discussed Acceptance sampling plans (Single, Double, Chain and Sequential) by attributes with the help of fuzzy parameters (mainly by fuzzy Poisson distribution and hypotheses testing). Finally many examples have been used and at last the paper ends with a comparative study.