bluuebunny/crossref_metadata_2025 huggingface dataset:
Personalised electric vehicle charging stop planning through online estimators
Authors: Shafipour Elnaz , Stein Sebastian , Ahipasaoglu Selin
Published: September 2024

In this paper, we address the problem of finding charging stops while travelling in electric vehicles (EVs) using artificial intelligence (AI). Choosing a charging station is challenging, because drivers have very heterogeneous preferences in terms of how they trade off the features of various alternatives (for example, regarding the time spent driving, charging costs, waiting times at charging stations, and the facilities provided at the charging stations). The key problem here is eliciting the diverse preferences of drivers, assuming that these preferences are typically not fully known a priori, and then planning stops based on each driver’s preferences. Our approach to solving this problem is to develop an intelligent personal agent that learns preferences gradually over multiple interactions. This study proposes a new technique that utilises a small-scale discrete choice experiment as a method of interacting with the driver in order to minimise the cognitive burden on the driver. Using this method, drivers are presented with a variety of routes with possible combinations of charging stops depending on the agent’s latest belief about their preferences. In subsequent iterations, the personal agent will continue to learn and refine its belief about the driver’s preferences, suggesting more personalised routes that are closer to the driver’s preferences. Based on real preference data from EV drivers, we evaluate our novel algorithm and show that, after only a few queries, our method quickly converges to the optimal routes for EV drivers [This paper is an extended version of an ECAI workshop short paper (Shafipour Yourdshahi et al., in: ECAI 2023 workshops, Kraków, Poland, 2023)].
Preparedness for practice, competency and skill development and learning in rural and remote clinical placements: A scoping review of the perspective and experience of health students
Authors: Hepburn Stevie-Jae , Fatema Syadani Riyad , Jones Rikki , Rice Kylie , Usher Kim , Williams Jen
Published: September 2024

When considering health professionals’ requirements and responsibilities, competence is a complex concept that extends beyond knowledge to encompass understanding, application, technical skills, problem-solving, and clinical judgment. Rural clinical placements provide a rich learning environment for students to improve their competencies, self-esteem, and preparedness for practice (PFP). This scoping review aimed to identify pre-registration health students’ perspectives on rural placement regarding competency and skill development, and enablers and barriers to learning. The methodology outlined by the Joanna Briggs Institute was followed. Out of 1186 records (366 duplicates), 821 were screened by title and abstract, 59 underwent full-text screening and 18 studies were included. Over half the studies included medicine students (n = 11). Reported competencies predominantly focused on self-assessed confidence regarding clinical skills. The reported barriers and enablers to learning highlighted the complexity of the placement experience and the importance of interpersonal factors, learner engagement and the supervisor’s role. The review identified a gap in the literature pertaining to student perspectives of competencies and skills not assessed or experienced as well as a lack of standardised measures for PFP. The identified enablers and barriers provide suggestions for rural placement design and emphasise the importance of the student learning experience. Future research could include multiple health disciplines and specific methodologies to identify health students’ perspectives regarding the development of competency, relatedness and autonomy, that is how to support health students to think, feel and act like health professionals.
Self-adjusted graph based semi-supervised embedded feature selection
Authors: Zhu Jianyong , Zheng Jiaying , Zhou Zhenchen , Ding Qiong , Nie Feiping
Published: September 2024

Graph-based semi-supervised feature selection has aroused continuous attention in processing high-dimensional data with most unlabeled and fewer data samples. Many graph-based models perform on a pre-defined graph, which is separated from the procedure of feature selection, making the model hard to select the discriminative features. To address this issue, we exploit a self-adjusted graph for semi-supervised embedded feature selection method (SAGFS), which learns an optimal sparse similarity graph to replace the pre-defined graph to alleviate the effect of data noise. SAGFS allows the learned graph itself to be adjusted according to the local geometric structure of the data and the procedure of selecting features to select the most representative features. Besides that, we introduce $$l_{2,p}$$

l

2
,
p

-norm to constrain the projection matrix for efficient feature selection. An efficient alternating optimization algorithm is presented, together with analyses on its convergence. Systematical experiments on several publicly datasets are performed to analyze the proposed model from several aspects, and demonstrate that our approaches outperform other comparison methods.
A novel ML-MCDM-based decision support system for evaluating autonomous vehicle integration scenarios in Geneva’s public transportation
Authors: Zakeri Shervin , Konstantas Dimitri , Sorooshian Shahryar , Chatterjee Prasenjit
Published: September 2024

This paper proposes a novel decision-support system (DSS) to assist decision-makers in the ULTIMO project with integrating Autonomous Vehicles (AVs) in Geneva, Switzerland. Specifically, it aids in selecting the best scenario for incorporating AVs into Geneva’s public transportation system. The proposed DSS is architected on a combined integrated framework that includes a machine learning (ML) algorithm, random forest (RF) algorithm, and three novel multi-criteria decision-making (MCDM) algorithms: (1) Modified E-ARWEN (ME-ARWEN) for selecting the best scenario with high sensitivity; (2) Compromiser—Positive, Neutral, Negative (Compromiser-PNN) for extracting weights from stakeholders, considering their preferences and potential conflicts; and (3) Collective Weight Processor (CWP) for deriving weights from expert opinions. Besides the main objective, this article also aims to: (1) Address the gap in practical DSS software within AV-related studies by providing Python codes of the DSS; (2) Develop a highly sensitive and comprehensive MCDM framework to address the project’s needs; and (3) Employ Artificial Intelligence within the DSS to optimize outputs. By the application of the proposed DSS, four scenarios were evaluated: (1) Full integration of AVs; (2) Partial integration; (3) Pilot project in limited areas; and (4) Delayed integration. The analysis identified partial integration as the best scenario for integrating AVs. Furthermore, comprehensive analyses conducted to validate the DSS outputs demonstrated the reliability of the results.
Bandgap adjustment of a sandwich-like acoustic metamaterial plate with a frequency-displacement feedback control method
Authors: Liu Jianing , Li Jinqiang , Wu Ying
Published: September 2024

Several types of acoustic metamaterials composed of resonant units have been developed to achieve low-frequency bandgaps. In most of these structures, bandgaps are determined by their geometric configurations and material properties. This paper presents a frequency-displacement feedback control method for vibration suppression in a sandwich-like acoustic metamaterial plate. The band structure is theoretically derived using the Hamilton principle and validated by comparing the theoretical calculation results with the finite element simulation results. In this method, the feedback voltage is related to the displacement of a resonator and the excitation frequency. By applying a feedback voltage on the piezoelectric fiber-reinforced composite (PFRC) layers attached to a cantilever-mass resonator, the natural frequency of the resonator can be adjusted. It ensures that the bandgap moves in a frequency-dependent manner to keep the excitation frequency within the bandgap. Based on this frequency-displacement feedback control strategy, the bandgap of the metamaterial plate can be effectively adjusted, and the vibration of the metamaterial plate can be significantly suppressed.
Bridging the reality gap in drone swarm development through mixed reality
Authors: Sende Micha , Raffelsberger Christian , Bettstetter Christian
Published: September 2024

Swarm algorithms promise to solve certain problems in large multi-robot systems. The evaluation of large swarms is however challenging as simulations alone often lack some properties of real systems whereas real-world experiments are costly and complex. We present a mixed reality (MR) system that connects simulated and physical robots though a 5G network, facilitating MR experiments to evaluate communication-based swarm algorithms. The effectiveness of the system is demonstrated through extensive experiments with unmanned aerial vehicles. Measurements show that the communication requirements of swarm coordination are well met by 5G but the computing power of the simulation server can be a bottleneck. However, even when the simulation slows down, communication and coordination take place in real time. In conclusion, 5G-enabled MR experiments are a feasible tool for bridging the reality gap in the development and evaluation of robot swarms.
Effect of Ga-Promoted on Ni/Zr + Al2O3 Catalysts for Enhanced CO2 Reforming and Process Optimization
Authors: Al-Fatesh Ahmed S. , Chava Ramakrishna , Alwan Saba M. , Ibrahim Ahmed A. , Fakeeha Anis H. , Abu-Dahrieh Jehad K. , Yagoub Elnour Ahmed , Abasaeed Ahmed E. , Al-Othman Othman , Appari Srinivas
Published: September 2024

In this study, zirconia-modified alumina support (S) was used to investigate Ga-promoted Ni catalysts for dry reforming of methane (DRM). The catalysts (Ni + (0–3) wt% Ga/S) were prepared using the wet impregnation method and calcined at 700 °C for 3 h. The inclusion of Ga enhanced the surface area, basicity, and metal-support interaction of the Ni-Ga/S catalysts. Smaller Ni particles containing Ga were seen in the TEM. The most active and stable catalyst was Ni + 2.0 Ga/S, having a conversion of 35% CO2 and 28% CH4 at 600 °C and displaying less (17%) carbon deposition. Furthermore, the DRM process was optimized by a mathematical model. The model determined the optimal conditions as follows: temperature (800 °C), gas flow rate (GHSV—30,000 ml h−1gcat−1), and methane to carbon dioxide ratio (1:1). The model predicts CH4 and CO2 conversions of 76.76% and 82.0%, respectively, and an H2/CO ratio of 1.02, compared to experimental results showing CH4 conversion at 74.56%, CO2 conversion at 83.25%, and an H2/CO ratio of 1.01. The model demonstrates excellent agreement with the experimental observations, exhibiting less than 3% error.

Graphical Abstract
A nested primal–dual iterated Tikhonov method for regularized convex optimization
Authors: Aleotti Stefano , Bonettini Silvia , Donatelli Marco , Prato Marco , Rebegoldi Simone
Published: September 2024

Proximal–gradient methods are widely employed tools in imaging that can be accelerated by adopting variable metrics and/or extrapolation steps. One crucial issue is the inexact computation of the proximal operator, often implemented through a nested primal–dual solver, which represents the main computational bottleneck whenever an increasing accuracy in the computation is required. In this paper, we propose a nested primal–dual method for the efficient solution of regularized convex optimization problems. Our proposed method approximates a variable metric proximal–gradient step with extrapolation by performing a prefixed number of primal–dual iterates, while adjusting the steplength parameter through an appropriate backtracking procedure. Choosing a prefixed number of inner iterations allows the algorithm to keep the computational cost per iteration low. We prove the convergence of the iterates sequence towards a solution of the problem, under a relaxed monotonicity assumption on the scaling matrices and a shrinking condition on the extrapolation parameters. Furthermore, we investigate the numerical performance of our proposed method by equipping it with a scaling matrix inspired by the Iterated Tikhonov method. The numerical results show that the combination of such scaling matrices and Nesterov-like extrapolation parameters yields an effective acceleration towards the solution of the problem.
Individual and contextual effects of attention in risky choice
Authors: Hirmas Alejandro , Engelmann Jan B. , Weele Joël van der
Published: September 2024

We investigate the role of visual attention in risky choice in a rich experimental dataset that includes eye-tracking data. We first show that attention is not reducible to individual and contextual variables, which explain only 20% of attentional variation. We then decompose attentional variation into individual average attention and trial-wise deviations of attention to capture different cognitive processes. Individual average attention varies by individual, and can proxy for individual preferences or goals (as in models of “rational inattention” or goal-directed attention). Trial-wise deviations of attention vary within subjects and depend on contextual factors (as in models of “salience” or stimulus-driven attention). We find that both types of attention predict behavior: average individual attention patterns are correlated with individual levels of loss aversion and capture part of this individual heterogeneity. Adding trial-wise deviations of attention further improves model fit. Our results show that a decomposition of attention into individual average attention and trial-wise deviations of attention can capture separable cognitive components of decision making and provides a useful tool for economists and researchers from related fields interested in decision-making and attention.
Peripartum cardiomyopathy: a comprehensive and contemporary review
Authors: Sigauke Farai Russell , Ntsinjana Hopewell , Tsabedze Nqoba
Published: September 2024

Cardiovascular disease is a major non-communicable disease globally, with increasing prevalence, posing a significant public health challenge. It is the leading non-obstetric cause of perinatal morbidity and mortality, with a substantial number of cardiac fatalities occurring in individuals without any known pre-existing cardiovascular disease. Peripartum cardiomyopathy is a type of de novo heart failure that occurs in pregnant women in the late stages of pregnancy or following delivery. Despite extensive research, diagnosing and managing peripartum cardiomyopathy remains challenging, resulting in significant morbidity and mortality. Recent advancements and novel approaches have been made to better understand and manage peripartum cardiomyopathy, including molecular and non-molecular biomarkers, genetic predisposition and risk prediction, targeted therapies, multidisciplinary care, and improved patient education. This narrative review provides a comprehensive overview and new perspectives on peripartum cardiomyopathy, covering its epidemiology, updated pathophysiological mechanisms, diagnosis, management, and future research directions for healthcare professionals, researchers, and clinicians.
Sense-Bestowal and Sense-Withdrawal
Authors: Breazu Remus
Published: September 2024

As is well known, sense-bestowal (Sinngebung) is a fundamental concept in Husserl’s transcendental phenomenology. Husserl considers that everything, including nonsense or absurdity, is a result of consciousness’ production of sense. In the following article, I will argue against this thesis. More precisely, I claim that there are experiences that are not characterised by sense-bestowal. These experiences, which, in my view, are directly related to Husserl’s concept of limit-phenomena, can be called sense-withdrawal experiences. In order to show this, the paper has the following structure: First, I will analyse the highly nuanced concept of sense-bestowal, drawing connections to the notion of constitution. Second, I will introduce the concept of limit-phenomena, which I will interpret in terms of sense-refusing experiences. This, in turn, will enable me to delve into the concept of sense-withdrawal, which will serve as the focal point of the final segment of the paper.
Patterns of Conflict and Post-Conflict Affiliation in Propithecus diadema and Eulemur fulvus
Authors: Ostad Rahimi Sara , Caillaud Damien , Lutz Meredith C.
Published: September 2024

Group-living in primates provides benefits but also entails competition and aggression. To retain the positive fitness-enhancing advantages of social bonding, individuals can reconcile past aggression. Reconciliation has been extensively studied in haplorrhine primates and occurs more frequently in more tolerant species, but whether this pattern extends to strepsirrhine primates, including lemurs, remains unclear, particularly given the differences in behavioral biology between the two primate suborders. We examined the occurrence of reconciliation behavior and its relationship with dominance hierarchy characteristics in wild populations of Propithecus diadema and Eulemur fulvus. We collected behavioral data on dominance and affiliation behaviors in the Maromizaha Protected Area, Madagascar, focusing on three P. diadema groups and two E. fulvus groups over 14 months between 2015 and 2020. The dominance hierarchies differed between species, with P. diadema exhibiting steeper within-group hierarchies than E. fulvus. We found evidence of reconciliation behavior in P. diadema, as affiliation was more likely to follow conflicts than during control periods, but we did not find this effect in E. fulvus. Furthermore, reconciliation tendencies in P. diadema were higher in male–male dyads and those with disparate ranks. These findings suggest that dominance hierarchy structure may be an important factor influencing reconciliation behavior across primates, although the nuances of the relationship seem to vary between our two strepsirrhine study species and traditional haplorrhine patterns. Further research is needed to determine whether these patterns are species-, site-, or group-specific. In conclusion, these results further our understanding of the differences between strepsirrhine and haplorrhine social evolution.
Mobilizing the Cultural Backlash: An Analysis of the Reception of Russian Strategic Narratives in a Far-Right Online Ecosystem
Authors: Valisa Jessica
Published: September 2024

This article analyzes the reception of Russian strategic narratives to understand which discursive elements contribute to their success, and especially to their adoption in the discourse emerging from far-right online outlets employing a qualitative approach. The analysis of a textual corpus of several hundred website-based articles from Italian far-right outlets revealed how Russia is imagined as an ideal and alternative political model, described as a harbinger of morality, independence, and culture, and it is juxtaposed to a weak and culturally decadent West. The result of the analysis shows how themes pertaining to the grievances of the cultural backlash majorly contribute to the themes informing the discourse summarized above, thus uncovering an important feature contributing to the success of such propaganda efforts among disenfranchised domestic publics.
Pregnancy rate and time to pregnancy after recurrent implantation failure (RIF)—a prospective cohort follow-up study
Authors: Stevens Brentjens Linda B. P. M. , Roumen Relinde J. E. , Smits Luc , Derhaag Josien , Romano Andrea , van Golde Ron J. T. , den Hartog Janneke E.
Published: September 2024

Purpose

The goal of this study was to determine ongoing pregnancy rate, time to pregnancy and embryo transfers to pregnancy within a cohort of patients with recurrent implantation failure (RIF).

Methods

IVF patients with RIF were included after referral to the RIF outpatient clinic. They received a questionnaire 1 year after inclusion. If data was missing, medical files were examined to determine pregnancy outcomes and conception methods. The ability of the RIF outpatient clinic to improve pregnancy chance or increase the number of patients who elected to continue treatment was beyond the scope of this study.

Results

The cumulative incidence of ongoing pregnancy in IVF patients with RIF (n = 79) after 1 year of follow-up was 40.5% (95% confidence interval = 30.4–51.5%). Median time to pregnancy was 4 months. Pregnancy incidence increased gradually up to 5 embryo transfers (mostly single embryo transfers). The average embryo transfers to pregnancy were 7.3 transfers.

Conclusion

In IVF patients with RIF, up until the 5th embryo transfer, each transfer represents a good opportunity for ongoing pregnancy. This data can be used to counsel patients that regular treatment continuation seems to be well justified even when IVF patients fulfil the RIF criteria.

Trial registration

CCMO: NL66835.068.18. METC 18–040. OMON: NL-OMON24778
Natural- and redirected walking in virtual reality: Spatial performance and user experience
Authors: De Back Tycho T. , Tinga Angelica M. , Louwerse Max M.
Published: September 2024

Immersive virtual reality offers a range of unique possibilities. One of these is the realistic exploration of virtual worlds using natural walking. This however becomes difficult when the size of the virtual world exceeds that of the available physical space. Redirected walking in virtual reality presents a novel solution to this problem by typically making its users think to be walking in a straight line while they are in fact walking in a curve, thus allowing them to physically walk long distances in confined physical spaces. Yet, few studies have examined the effects of redirected walking on variables such as spatial memory, navigation and user experience as compared to other immersive and non-immersive locomotion methods. In a maze task we examined 1) redirected- and 2) natural walking in immersive virtual reality conditions, and 3) artificial locomotion on a non-immersive desktop monitor. Walked path lengths became shorter and distance estimates, object location memory and user experience improved using natural walking compared to a monitor condition. However, redirected walking yielded similar performance to natural walking while requiring less physical space, opening up possibilities for more pervasive use of real locomotion in virtual environments.
Residual encoder-decoder based architecture for medical image denoising
Authors: Ferdi Abdesselam , Benierbah Said , Nakib Amir
Published: September 2024

High-resolution computed tomography (CT) scans require high doses of X-rays, posing potential health risks to patients, including genetic damage and cancer. Conversely, low doses of X-rays result in noise and artifacts in the reconstructed CT scans. Consequently, the problem of denoising low-dose CT (LDCT) images has become a critical yet challenging issue in the field of CT imaging. However, existing deep learning-based LDCT image denoising methods frequently result in the loss of high-frequency features, such as edges and textures, due to the use of mean squared error loss. To address this issue, we propose a method based on high-frequency feature learning to enhance the denoising performance of existing models. Our method is designed to simultaneously learn the primary task of LDCT image denoising and the auxiliary task of LDCT edge detection, thereby improving the denoising performance without increasing the number of model parameters and the inference time. Our method significantly improves the denoising performance of the RED-CNN model, achieving competitive results compared to state-of-the-art denoising models on the AAPM and Qin-LUNG-CT datasets.
The 3D tree dataset: an artistic experiment using a voxel-based GAN
Authors: Nelson Peter , Mai Jianming , Au Ryan
Published: September 2024

In visual culture, Generative Adversarial Networks (GANs) have been used to generate two-dimensional images, video, and three-dimensional forms. Whilst there are a relatively large number of conditional datasets of two-dimensional images, there are fewer datasets of three-dimensional objects available for training, evaluation, and practical use. In this paper, we introduce a synthetic dataset of 3D trees that provide novel geometric challenges for machine learning and describe our use of this dataset in training and qualitative evaluation via a public exhibition and survey. The 3D Tree Dataset was made using random variations of 76 bespoke tree templates based on art historical references to favor interesting, beautiful, and varied trunk and branch shapes. In generating and experimenting with this dataset, we wanted to know how a geometrically complex series of organic forms would challenge voxel-GANs compared to existing datasets comprising industrial objects such as chairs and cars. As an interdisciplinary project between visual arts and computer science, we used 3D printing and animation to visualize and communicate our outputs to non-specialist audiences. In this paper, we describe and share the 3D Tree Dataset, outline the process of generating the dataset, describe the GAN architecture and application used to test the dataset and discuss the results relative to our artistic and cultural goals.
Experimental validation of escape mechanisms in a bi-stable potential well
Authors: Genda Attila , Fidlin Alexander , Gendelman Oleg
Published: September 2024

This paper experimentally studies escape mechanisms in a bi-stable potential well, focusing on critical forcing values depending on system damping, excitation frequency, and initial phase. The experimental setup has a rotational degree of freedom. It comprises a vertical shaft with adjustable air bearings and a copper disk that increases the moment of inertia and serves as an adjustable eddy current brake. The system also includes two coil springs that provide restoring moments. External momentum is provided by an electric motor controlled through a function generator. The paper describes the identification of system parameters and compares numerical and experimental results, validating previous theoretical and numerical findings regarding the saddle and maximum escape mechanisms.
Impact of Different Packaging Configurations on A Topical Cream Product
Authors: Mohammed Yousuf H. , Namjoshi S. N. , Telaprolu K. C. , Jung N. , Shewan H. M. , Stokes J. R. , Benson H. A. E. , Grice J. E. , Raney S. G. , Rantou E. , Windbergs Maike , Roberts Michael S.
Published: September 2024

Purpose

The objective of this study was to investigate whether different dispensing processes can alter the physicochemical and structural (Q3) attributes of a topical cream product, and potentially alter its performance.

Methods

Acyclovir cream, 5% (Zovirax®) is sold in the UK and other countries in a tube and a pump packaging configurations. The structural attributes of the cream dispensed from each packaging configuration were analyzed by optical microscopy, confocal Raman microscopy and cryo-scanning electron microscopy. Rheological behavior of the products was also evaluated. Product performance (rate and extent of skin delivery) was assessed by in vitro permeation tests (IVPT) using heat-separated human epidermis mounted in static vertical (Franz-type) diffusion cells.

Results

Differences in Q3 attributes and IVPT profiles were observed with creams dispensed from the two packaging configurations, even though the product inside each packaging appeared to be the same in Q3 attributes. Visible globules were recognized in the sample dispensed from the pump, identified as dimethicone globules by confocal Raman microscopy. Differences in rheological behaviour could be attributed to these globules as products not dispensed through the pump, demonstrated a similar rheological behaviour. Further, IVPT confirmed a reduced rate and extent to delivery across human epidermis from the product dispensed through a pump.

Conclusions

Different methods of dispensing topical semisolid products can result in metamorphosis and Q3 changes that may have the potential to alter the bioavailability of an active ingredient. These findings have potential implications for product developers and regulators, related to the manufacturing and comparative testing of reference standard and prospective generic products dispensed from different packaging configurations.
An optimization of traditional CPU emulation techniques for execution on a quantum computer
Authors: Fitzjohn James , Wilson George , Vicinanza Domenico , Winckles Adrian
Published: September 2024

The use and adoption of quantum computers by the wider computing community is diminished by the need to adopt new programming techniques. These techniques involve moving from a high-level language where the programmer can define and manipulate objects, to a quantum model where the programmer defines and configures the circuits at a gate level. Previous work by the authors aimed to ease this transition through the use of a software development kit (Qx86 SDK) that emulates a traditional CPU for execution on a quantum computer, but only delivered a raw capability. The current work now presents a number of new methods that extends and improves the SDK's capability. These methods include optimizing traditional logic gate emulation, multiple gate simplification methods, reducing the number of required qubits and alternative optimized techniques for many CPU instructions. A quantum machine code mapping method is described that enhances the emulation of a traditional/quantum hybrid CPU prototype. While still orders of magnitude slower than the performance of a traditional CPU in terms of arithmetic, logic and bitwise operations, execution speed is shown to be markedly improved (in some cases by more than 1,000%) and without introducing any unrealistic requirements (that is, all execution can be performed utilizing less than 32 qubits). The usefulness of the SDK has now been enhanced as a reference guide, where the programmer/researcher can contrast traditional methods versus multiple quantum methods of execution.
Access, Choice, and Pleasure: Towards a New Model of Disability Sexual Rights
Authors: Pikkel Rina B.
Published: September 2024

The paper offers a comprehensive exploration of the concept of disability sexual rights by integrating insights from both legal and sociological frameworks. Sexuality is an integral and inseparable part of human existence, encompassing a wide range of biological, physiological, psychological, and social aspects. Our understanding of sexuality developed over time, and contemporary social models view sexuality as shaped by social, cultural, and political factors. The rise of disability studies and social and critical models marked a significant shift in the way disabled sexuality is perceived. These studies underpin social aspects and constructions that contribute to the disabling process. Current Literature situates disability and sexuality within broader sociological frameworks of sexual citizenship, disability legal studies, and human rights, emphasizing the importance of recognizing disability sexual rights in forming an inclusive society. We examine the evolution of human rights discourse, mainly focusing on disability sexual rights as a marginalized subject within the human rights and disability rights agendas. We conclude by weaving together theories from disability studies, sexual citizenship, and law, proposing a new theoretical model of sexual rights that situates them in the intersection of disability, sexuality, law, and society. The model suggests three essential elements that cover the full scope of disability sexual rights: Access, choice, and pleasure. These elements can be applied to all aspects of disabled sexuality, encompassing sexual needs, participation, and autonomy.
Timing-aware analysis of shared cache interference for non-preemptive scheduling
Authors: Fischer Thilo L. , Falk Heiko
Published: September 2024

In multi-core architectures, the last-level cache (LLC) is often shared between cores. Sharing the LLC leads to inter-core interference, which impacts system performance and predictability. This means that tasks running in parallel on different cores may experience additional LLC misses as they compete for cache space. To compute a task’s worst-case execution time (WCET), a safe bound on the inter-core cache interference has to be determined. We propose an interference analysis for set-associative shared least-recently-used caches. The analysis leverages timing information to establish tight bounds on the worst-case interference and classifies individual accesses as either cache hits or potential cache misses. We evaluated the analysis performance for systems containing 2 and 4 cores using shared caches up to 64 KB. The evaluation shows an average WCET reduction of up to 23.3% for dual-core systems and 8.5% for quad-core systems.
Effect of Halide Ions on the TiO2-mediated Photocatalysis of Carbendazim in Aqueous Medium Under Near-ultraviolet Light Irradiation
Authors: Bragetta Margherita , Germani Raimondo , Tiecco Matteo , Alabed Husam B. R. , Del Giacco Tiziana
Published: September 2024

The degradation of carbendazim (CBZ) through TiO2 photocatalysis, in the presence of halide ions and under near-UV light irradiation, was investigated. HPLC–MS technique was used to characterize the photoproducts. Spectrophotometric analysis showed that CBZ degraded slowly in TiO2 aqueous dispersions containing no salt (CBZ conversion of 6% after ca. 5 h of irradiation). The photodegradation efficiency increased particularly by addition of bromide salts. Indeed, CBZ reached complete degradation after ca. 30 min at the maximum concentration of NaBr used (0.05 M). Two significant aspects have emerged from the data analysis: the bromide role is to cause inhibition of the electron–hole recombination, a reaction known to be competitive with the reactive process; CBZ photodegradation is especially initiated by direct hole transfer pathway, whereas the OH• role is crucial in the catalyst regeneration process. Degradation attempts under sunlight appeared promising for a more sustainable photocatalytic process.
Establishment and characterization of novel spontaneously immortalized larval cell lines from sablefish Anoplopoma fimbria
Authors: Friesen Eric R. , Long Amy K. , Garver Kyle A.
Published: September 2024

Sablefish Anoplopoma
fimbria is a groundfish of the North Pacific Ocean typically found in sea floor habitat at depths to 2700 m. Prized as a food fish with exceptionally high market value, sablefish aquaculture has been sought to provide a sustainable source of this fish to meet market demands. While commercial culture has successfully produced market-sized fish in Pacific coastal environments, production has been hampered by disease and the overall lack of information on sablefish health and immunology. To begin to address these knowledge gaps, herein we describe the isolation and characterization of spontaneously immortalized sablefish larval cell lines (AFL). Six sublines were established from pools of early yolk-sac larvae, while attempts to develop tissue-specific–derived cell lines were unsuccessful. The six yolk-sac larval cell lines each display two morphologies in culture, an elongated fibroblast-like cell type, and a rounded squamous or epithelial-like cell type. Cytogenetic characterization suggests that both cell types are diploid (2n = 48) with 24 pairs of chromosomes, 23 pairs of autosomes, and 1 pair of sex chromosomes. A small proportion (11%) of AFL cells display tetraploidy. Incubation temperature and medium composition experiments revealed HEPES buffered L-15 media containing 10–20% FBS at temperatures between 15 and 18° C yielded optimal cell growth. These growth characteristics suggest that sablefish larval cells display a robustness for varying growth conditions. The establishment of AFL cell lines provides a foundational tool to study the physiology, health, immunology, and cell and molecular biology of sablefish.
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Authors: Dai Enyan , Zhao Tianxiang , Zhu Huaisheng , Xu Junjie , Guo Zhimeng , Liu Hui , Tang Jiliang , Wang Suhang
Published: September 2024

Graph neural networks (GNNs) have made rapid developments in the recent years. Due to their great ability in modeling graph-structured data, GNNs are vastly used in various applications, including high-stakes scenarios such as financial analysis, traffic predictions, and drug discovery. Despite their great potential in benefiting humans in the real world, recent study shows that GNNs can leak private information, are vulnerable to adversarial attacks, can inherit and magnify societal bias from training data and lack interpretability, which have risk of causing unintentional harm to the users and society. For example, existing works demonstrate that attackers can fool the GNNs to give the outcome they desire with unnoticeable perturbation on training graph. GNNs trained on social networks may embed the discrimination in their decision process, strengthening the undesirable societal bias. Consequently, trust-worthy GNNs in various aspects are emerging to prevent the harm from GNN models and increase the users’ trust in GNNs. In this paper, we give a comprehensive survey of GNNs in the computational aspects of privacy, robustness, fairness, and explainability. For each aspect, we give the taxonomy of the related methods and formulate the general frameworks for the multiple categories of trustworthy GNNs. We also discuss the future research directions of each aspect and connections between these aspects to help achieve trustworthiness.
A Cubic Pure Half-Spinor Approach to High Performance Photon-Counting Computerized X-ray Tomography – Transcendence of the Brauer Mirror Symmetry Functor –
Authors: Schempp Walter J.
Published: September 2024

The goal of this paper is to present a spectral theory of advanced photon-counting computerized X-ray tomography, which is a promising microelectronical semiconductor wafer X-ray technique on the verge of becoming clinically feasible and has the potential to dramatically alter the clinical application of computer-aided medical diagnosis in the upcoming decades. In analogy to the deep fact that any real division algebra has dimension 1, 2, 4 or 8, the isogeneous third Galois cohomological, mirror symmetrical approach to high spatial resolution spectral photon-counting computerized tomography establishes that the exceptional Lie group $$\textrm{Spin}(8,\mathbb {R})$$

Spin
(
8
,
R
)

is the only one of the spin group spectrum $$\{\textrm{Spin}(n,\mathbb {R})\mid n \ge 1\}$$

{
Spin
(
n
,
R
)
∣
n
≥
1
}

to admit a triality automorphism. It is the exceptional phenomenon of triality which is able to produce by the spin representation theory of the exceptional Lie group of octonions $$\mathbb {O}$$
O
the spectral shaped digital signals of spectral photon-counting computerized X-ray tomography. Similarly to spin echo magnetic resonance tomography, the mathematical approach to spectral high performance computerized tomography is based on the isogeneously invariant, projectively weighted, symplectic coadjoint orbit picture $$\mathfrak {Lie}(\mathcal {N})^*/\textrm{CoAd}(\mathcal {N})$$

Lie

(
N
)

∗

/
CoAd

(
N
)

of the real 3-dimensional Heisenberg unipotent Lie group $$\mathcal {N}$$
N
of type $$\textrm{GL}(3,\mathbb {R})$$

GL
(
3
,
R
)

, and its solvable diamond toric Lie group extension.
Lipoteichoic Acid from Lacticaseibacillus rhamnosus GG as a Novel Intracanal Medicament Targeting Enterococcus faecalis Biofilm Formation
Authors: Yoon Ji-Young , Park Somin , Lee Dongwook , Park Ok-Jin , Lee WooCheol , Han Seung Hyun
Published: September 2024

The demand for safe and effective endodontic medicaments to control Enterococcus faecalis biofilms, a contributor to apical periodontitis, is increasing. Recently, lipoteichoic acid (LTA) of family Lactobacillaceae has been shown to have anti-biofilm effects against various oral pathogens. Preliminary experiments showed that LTA purified from Lacticaseibacillus rhamnosus GG (Lgg.LTA) was the most effective against E. faecalis biofilms among LTAs from three Lactobacillaceae including L. rhamnosus GG, Lacticaseibacillus casei, and Lactobacillus acidophilus. Therefore, in this study, we investigated the potential of Lgg.LTA as an intracanal medicament in human root canals infected with E. faecalis. Twenty eight dentinal cylinders were prepared from extracted human teeth, where two-week-old E. faecalis biofilms were formed followed by intracanal treatment with sterile distilled water (SDW), N-2 methyl pyrrolidone (NMP), calcium hydroxide (CH), or Lgg.LTA. Bacteria and biofilms that formed in the root canals were analyzed by scanning electron microscopy and confocal laser scanning microscopy. The remaining E. faecalis cells in the root canals after intracanal medicament treatment were enumerated by culturing and counting. When applied to intracanal biofilms, Lgg.LTA effectively inhibited E. faecalis biofilm formation as much as CH, while SDW and NMP had little effect. Furthermore, Lgg.LTA reduced both live and dead bacteria within the dentinal tubules, indicating the possibility of minimal re-infection in the root canals. Collectively, intracanal application of Lgg.LTA effectively inhibited E. faecalis biofilm formation, implying that Lgg.LTA can be used as a novel endodontic medicament.
Evaluating the persistence and insecticidal effects of emulsifiable concentrate containing Cananga odorata essential oil on survival and enzymatic activity of Spodoptera littoralis
Authors: Ibrahim Samar Sayed , Sammour Elham Ahmed
Published: September 2024

The essential oil of Cananga odorata was prepared as an emulsifiable concentrate formulation and examined for its insecticidal activity against Spodoptera littoralis larvae. The effectiveness of C. odorata oil in both pure and EC formulations was investigated in terms of enzymatic activity and survival. In addition, their persistence effect was studied in semi-field conditions. Benzyl benzoate (18.86%), benzyl acetate (9.18%), β-Maaliene (15.53%), alloaromadendrene (6.41%), cis-Thujopsene (6.16%), cedrene (5.35%), and benzyl alcohol (5.98%) were the most abundant compounds found in C. odorata oil by gas chromatography-mass spectrometry analysis. The EC formulation exhibited the highest toxicity and produced LC values of 0.47, 1.02, and 3.78% for LC40, LC50, and LC90, respectively, compared to 1.05, 1.70, and 4.96%, respectively, resulted from pure oil after 72 h of exposure. Following EC application, the mean survival time was only 3.60 ± 0.57 days, compared to pure oil treatment (7.70 ± 1.11 days) and control (14.0 ± 0.0 days). The LC40 of EC formulation induced a more potent inhibitory effect for the detoxification enzyme carboxylesterases (CarE; α- and β-esterase) and the oxidative stress enzyme superoxide dismutase (SOD). Under semi-field conditions, the cumulative mortality of S. littoralis larvae increased by increasing the exposure time to LC90 of both formulations. The EC formulation had the highest mortality rates for the total exposure period (7 days). According to these results, C. odorata EC formulation demonstrated enhanced toxicity and persistence effects, and it can be utilized as a green bio-insecticide for the management of S. littoralis larvae.
Territorial Patterns of European Innovation in the Context of Different Innovation Output Proxies: A Spatial MGWR-SAR Approach
Authors: Furková Andrea
Published: September 2024

The paper seeks to explore the drivers of European innovation represented by three innovation outputs (patent, trademark, and design applications), emphasizing spatial autocorrelation and heterogeneity. It includes data from 202 regions from 22 European Union (EU) Member States, along with 18 regions from Switzerland, Norway, and Serbia in 2019, providing a more comprehensive geographic scope. By considering multiple indicators of innovation output, including patents, trademarks, and design applications, the main objective is to examine spatial innovation spillovers and the heterogeneous responses of regional innovation output to innovation inputs in the context of European regions. To achieve this goal, the main instrument of the analysis is a newly proposed methodological framework called Mixed Geographically Weighted Regression-Spatial Autoregressive (MGWR-SAR) models. The analysis suggests that while all innovation inputs (most-cited publications, research and development expenditure in the business sector, human resources in science and technology, and population density) are justified in increasing all innovation outputs, the strength of particular determinants of innovation might vary across regions. Moreover, the analysis reveals valuable insights into how spatial spillovers influence regional innovation. The impact of spatial connections varies across the regions, with patents showing the strongest linkages, affecting about 92.27% of regions. Although trademarks and designs have fewer spatial connections (approximately 50% of regions), they still play a significant role in innovation. Although patents have traditionally dominated discussions of innovation, the findings reveal the importance of incorporating designs and trademarks as complementary indicators. Overall, the study highlights the need for multiple metrics to comprehensively evaluate innovations.
Comparative genome analysis of endophytic Bacillus amyloliquefaciens MR4: a potential biocontrol agent isolated from wild medicinal plant root tissue
Authors: Yang Kaiying , Dai Xianxing , Maitikadir Zulihumar , Zhang Huijiang , Hao Haiting , Yan Chengcai
Published: September 2024

In this investigation, 396 endophytic bacterial strains from six indigenous medicinal plant species within the Xinjiang Tumor Peak National Nature Reserve were subjected to screening. The strain MR4 emerged as a noteworthy contender, demonstrating pronounced biocontrol capabilities coupled with exceptional cold tolerance. Through morphological scrutiny and comprehensive genomic sequencing, MR4 was identified as Bacillus amyloliquefaciens. Antagonistic assays revealed MR4’s efficacy in suppressing the causative agents of cotton wilt and verticillium wilt, achieving inhibition rates surpassing 50%. Analyses, underpinned by PCR methodologies, indicated MR4’s capacity to biosynthesize a minimum of eight distinct antimicrobial agents. The whole-genome sequencing data indicated that B. amyloliquefaciens MR4 had the genome size and GC content of 4,017,872 bp and 47.14%, respectively, and 4191 coding genes were identified. The genome consists of a single chromosome and one plasmid. Moreover, it was augmented by annotations from various databases, including GO, KEGG, and COG. The pathogenicity of MR4 undergoes evaluation, while predictions concerning MR4’s secondary metabolites have disclosed gene clusters for 13 varieties of these compounds, with particular emphasis on surfactins and fengycin. Comparative analyses with four paradigmatic strains shed light on MR4’s genomic composition and its phylogenetic lineage within the Bacillus genus. The genomic data pertaining to MR4 have been duly submitted to the NCBI GenBank, bearing the accession numbers CP146236 (Chr1) and CP146237 (plas1). This study endeavors to furnish potent microbial resources for the biocontrol and enhancement of plant growth, thereby providing a theoretical groundwork for MR4’s agronomic utilization.

Graphical Abstract