bluuebunny/crossref_metadata_2025_split huggingface dataset:
Action of the Euclidean versus projective group on an agent’s internal space in curiosity driven exploration
Authors: Sergeant-Perthuis Grégoire , Ruet Nils , Ognibene Dimitri , Tisserand Yvain , Williford Kenneth , Rudrauf David 
Published: January 2025

Abstract
According to the Projective Consciousness Model (PCM), in human spatial awareness, 3-dimensional projective geometry structures information integration and action planning through perspective taking within an internal representation space. The way different perspectives are related to and transform a world model defines a specific perception and imagination scheme. In mathematics, such a collection of transformations corresponds to a ‘group’, whose ‘actions’ characterize the geometry of a space. Imbuing world models with a group structure may capture different agents’ spatial awareness and affordance schemes. We used group action as a special class of policies for perspective-dependent control. We explored how such a geometric structure impacts agents’ behaviors, comparing how the Euclidean versus projective groups act on epistemic value in active inference, drive curiosity, and exploration. We formally demonstrate and simulate how the groups induce distinct behaviors in a simple search task. The projective group’s nonlinear magnification of information transformed epistemic value according to the choice of frame, generating behaviors of approach toward objects with uncertain locations due to limited sampling. The Euclidean group had no effect on epistemic value: no action was better than the initial idle state. In structuring a priori an agent’s internal representation, we show how geometry can play a key role in information integration and action planning. Our results add further support to the PCM.
Presentation and surgical management approaches of giant presacral and sacral schwannomas: a case report and systematic review and meta-analysis
Authors: Sarhan Khalid , Serag Ibrahim , Sabry Amin , Elghareeb Hossam , Shahein Mostafa 
Published: January 2025

Abstract

Background
Giant sacral and presacral schwannomas are very rare conditions and their prevalence is estimated to account for only 0.3 to 3.3% of overall schwannomas. Current published literature about these tumors is limited to case reports and small case series. In this paper we systematically reviewed and analyzed the available literature on giant sacral schwannomas focusing on identifying the presenting symptoms, Klimo type, surgical approach, recurrence rate and postoperative complications.

Methods
Following the PRISMA guidelines, we conducted a literature search on electronic databases to obtain the relevant studies until March 2024. We included reports of surgically managed giant sacral schwannomas; either involving tumor of at least 2 adjacent vertebra or had a maximum diameter of 5 cm or more. Presenting symptoms, tumor size, morphology, surgical approach and postoperative complications were reported.

Results
A total of 102 studies with 201 unique patients were included in our analysis (mean age 45.4 ± 9.8, 49.7% females). The most common presenting symptoms were lower extremity radicular pain (19.5%), lower back pain (14.1%), lower extremity numbness or paresthesia (9%), and constipation (7.6%). Most surgeries used an open posterior approach (40.1%) or open anterior approach (33.5%). Postoperative complications occurred in (29.3%) of patients and 10% had local recurrence or progression of their tumor. On linear regression the volume of the tumor could significantly predict the estimated amount of blood loss (P = 0.03). We found that an anterior approach was far more likely to be used in patients with Klimo type III, (P < 0.001). Similarly, posterior approach was mostly used for Klimo type I and type II (P < 0.001).

Conclusion
The management approach of giant sacral and presacral schwannomas are mainly tailored according to the tumor size and location. Due to the benign nature and the overall recurrence rate of the tumor, frequent imaging follow-up is required after safe resection with adequate clean margins.
Cardiovascular safety of osteoanabolic agents
Authors: Takeuchi Yasuhiro 
Published: January 2025

Abstract

Purpose
Several osteoanabolic agents have been developed to build new bone more efficiently than anti-resorptive drugs. Among them, romosozumab, an anti-sclerostin antibody, is a potent pharmacological tool to prevent fractures in osteoporosis patients. The efficacy of romosozumab in preventing osteoporotic fractures is robust. However, there remains a concern about increased cardiovascular (CV) adverse events related to romosozumab. Available data have been reviewed to address this concern.

Methods
Published articles on romosozumab of which pivotal randomized controlled trials (RCTs), meta-analyses of RCTs, pharmacovigilance investigations, and retrospective observational clinical studies using real-world data were collected through PubMed and other available tools.

Results
Meta-analyses of RCTs of romosozumab compared to placebo and other anti-osteoporosis drugs have left room for controversy in the CV safety of romosozumab. Investigations of the real-world data also provide no conclusive evidence in this issue.

Conclusion
We need more robust evidence to establish an appropriate and reasonable guide to prescribe romosozumab in our clinical practice.
Biopesticide transplant dips and foliar acaricide applications for control of cyclamen mite (Phytonemus pallidus) in strawberry
Authors: Renkema Justin M. 
Published: January 2025

Abstract
Cyclamen mite (Phytonemus pallidus) causes injury to new growth of strawberry plants and is difficult to control because it is protected by folded leaves and plant crowns. Since cyclamen mite is easily transferred from strawberry nurseries to fruiting fields, dipping transplants in biopesticides may reduce initial populations. However, cyclamen mite numbers at 1 and 3 months-after-planting, and yield and cyclamen mite injury to fruit in the following season did not differ among transplants immersed for 30 s in Captiva® Prime, EcoTrol® EC, Landscape Oil, SuffOil-X® or Kopa Insecticidal Soap or the untreated control. Cyclamen mite is primarily controlled with foliar applications of acaricides, but there are few registered products. In greenhouse experiments, fenazaquin and pyridaben reduced cyclamen mite numbers by more than 90% in new leaves compared to the control, similar to that of the standard abamectin. New leaf injury ratings were reduced from 1 on average (scale of 0–3; 0 = no injury) pre-application to 0.25–0.5 for fenazaquin, pyridaben, and abamectin-treated plants compared to increasing to 2 for control plants 2 weeks after application. Spiromesifen and chlorfenapyr reduced cyclamen mite numbers in folded leaves in one greenhouse experiment. In the field, all acaricides reduced cyclamen mite numbers by 90–99% at 2- and 6-weeks post-application and by 75–90% at 10 months post-application. Abamectin and pyridaben resulted in 0.5–1.0% of strawberries with cyclamen mite damage compared to 3.0% for the control. All acaricides except chlorfenapyr improved strawberry yield and size. Overall, fenazaquin, pyridaben and spiromesifen should help diversify the chemical toolbox for cyclamen mite in field strawberry.
Post-Fire Performance of Binary-Blended Geopolymer Concrete Structural Members
Authors: Kanagaraj Balamurali , Anand N. , Andrushia Diana , Cashell Katherine A. 
Published: January 2025

Abstract
Owing to the ever-increasing climate crisis, it is essential that the construction sector endeavors to reduce its contribution to global carbon emissions. The cement and associated by-products used in the production of concrete are a significant contributor to the carbon footprint in construction, and there should be replaced by suitable and more sustainable materials if and where possible. Such materials, sometimes called ‘green’ materials, include geopolymer concrete (GPC), which can reduce or eliminate the use of cement in concrete mix design. Although significant research focus has been given to GPC in recent years, there is very limited data on the post-fire behaviour. Accordingly, in the current paper, three different types of binary-blended GPC elements were cast and subjected to a standard fire for various durations. These included a mix made up of 100% fly ash (FA), another using FA and ground granulated blast furnace slag (FG) and a third combination comprising FA and metakaolin (FM). The test specimens were examined under a variety of conditions, after cooling. The test results illustrate that GPC beams deform in a similar manner to cement-based concrete beams at ambient temperature and therefore, the deformations can be evaluated through a strain compatibility methodology. However, the same does not apply to GPC beams following exposure to fire conditions as the structural behaviour was shown to degrade with increased temperature exposure. All of the post-fire tests were supplemented with image analysis to measure the influence that elevated temperature has on the concrete quality. The results show that the FG blended mix provides an effective yet more sustainable concrete mix compared to the FA and FM blended mixes.
Reactivity of belite in calcium sulfoaluminate-based cements
Authors: Pérez-Bravo Raquel , Koufany Imane , Cuesta Ana , Bescher Eric P. , Aranda Miguel A. G. , Santacruz Isabel , De la Torre Angeles G. 
Published: January 2025

Abstract
The hydration behavior of belite phase in different cements is not well understood. Belite hydrates very slowly but there are reports with faster hydration kinetics. Here, the hydration behavior of belite phase in a commercial belite calcium sulfoaluminate (BCSA) cement has been investigated. The BCSA cement was hydrated with two water-to-cement ratios, 0.50 and 0.65 and at two temperatures, 20 and 40 °C. Studies of calorimetry, NMR, laboratory X-ray powder diffraction (XRPD), thermal analysis (TA) of the pastes, and mass balance calculations have been performed. The calorimetric and LXRPD studies showed that with sufficient water for the hydration reactions to take place, i.e., w/c = 0.65, the degree of reaction of belite is 30% at 7 days and above 60% at 35 days, at 40 °C. The 29Si and 27Al MAS-NMR and TA studies confirmed the reactivity of belite under conditions of sufficient water (thermodynamic requirement) and at high temperature (kinetic requirement). This was demonstrated by the presence of stratlingite by 27Al MAS-NMR and TA. Finally, it was found that ~ 12 mass% of the added water remains unbound, but it is unavailable for the progression of hydration reactions in the studied experimental conditions.
Efficient federated unlearning under plausible deniability
Authors: Varshney Ayush K. , Torra Vicenç 
Published: January 2025

Abstract
Privacy regulations like the GDPR in Europe and the CCPA in the US allow users the right to remove their data from machine learning (ML) applications. Machine unlearning addresses this by modifying the ML parameters in order to forget the influence of a specific data point on its weights. Recent literature has highlighted that the contribution from data point(s) can be forged with some other data points in the dataset with probability close to one. This allows a server to falsely claim unlearning without actually modifying the model’s parameters. However, in distributed paradigms such as federated learning (FL), where the server lacks access to the dataset and the number of clients are limited, claiming unlearning in such cases becomes a challenge. An honest server must modify the model parameters in order to unlearn. This paper introduces an efficient way to achieve machine unlearning in FL, i.e., federated unlearning, by employing a privacy model which allows the FL server to plausibly deny the client’s participation in the training up to a certain extent. Specifically, we demonstrate that the server can generate a Proof-of-Deniability, where each aggregated update can be associated with at least x (the plausible deniability parameter) client updates. This enables the server to plausibly deny a client’s participation. However, in the event of frequent unlearning requests, the server is required to adopt an unlearning strategy and, accordingly, update its model parameters. We also perturb the client updates in a cluster in order to avoid inference from an honest but curious server. We show that the global model satisfies

$$(\epsilon , \delta )$$

(
ϵ
,
δ
)

-differential privacy after T number of communication rounds. The proposed methodology has been evaluated on multiple datasets in different privacy settings. The experimental results show that our framework achieves comparable utility while providing a significant reduction in terms of memory (

$$\approx $$

≈

30 times), as well as retraining time (1.6-500769 times). The source code for the paper is available https://github.com/Ayush-Umu/Federated-Unlearning-under-Plausible-Deniability.
Ergostane-type steroids from mushrooms of Pleurotus genus
Authors: Kikuchi Takashi 
Published: January 2025

Abstract
Steroids are physiologically important compounds for animals, plants, and fungi, and they have significantly contributed to drug discovery for many years. Fungi mainly biosynthesize ergostane-type steroids such as ergosterol. However, after the basic skeleton is biosynthesized, chemical transformations can lead to the cleavage or rearrangement of the fundamental skeleton of steroids. The cleaved (seco) and rearranged (abeo) steroids are chemically and pharmacologically intriguing because they often exhibit biological activities. As ergostane-type steroids including the normal, seco, and abeo types have been isolated from the mushrooms of the Pleurotus genus, this review focuses on them as a resource of ergostane-type steroids, providing their distribution, structure determination, and biological activity.

Graphical abstract
A comparative study of family violence among Hindi-speaking and third-generation English-speaking Australian women
Authors: De Silva Heshani S. , McEwan Troy E. , Shepherd Stephane M. 
Published: January 2025

Abstract
High prevalence and incidence rates of family violence (FV) amongst South Asian communities have been reported internationally. Despite the recognition that culturally and linguistically diverse (CALD) communities within Australia have additional risk factors associated with experiencing FV, Australia has limited research exploring FV amongst one of its fastest growing CALD populations, South Asians. With the Hindi-speaking community accounting for the single largest group within the South Asian community in Australia, this study aimed to address this gap. The 2016 Personal Safety Survey (PSS) was used to explore the prevalence rate and risk factors associated with FV victimisation for Hindi-speaking Australian women and compare this with third-generation English-speaking Australian women. The findings indicated that Hindi-speaking Australian women reported a lower prevalence rate of FV yet had different risk factors associated with their risk of victimisation. Specifically, Hindi-speaking females had only experience-based risk factors (e.g., child abuse) related to their victimisation of FV, whilst third-generation English-speaking females had both experience and situational-based risk factors (e.g., unemployment). These findings are unlikely to be representative of all Hindi-speaking Australians nor of South Asian Australians more broadly, as the survey design may have been biased towards a particular subset of Hindi-speaking Australians who could speak English fluently. Recommendations on how to address such limitations in future studies are discussed.
A Hybrid Method for Segmentation and Recognition of Butterfly Objects in Camouflage Images
Authors: Bayram Erkan , Nabiyev Vasif V. 
Published: January 2025

Abstract
Detecting camouflaged objects in camouflage images is quite challenging due to their closely matching texture, pattern, and color characteristics with the background. Existing binary segmentation solutions cannot easily deal with the problem of detecting camouflaged objects because they have weak boundaries and background-like patterns. The purpose of camouflaged object detection (COD) is to detect objects that very closely resemble the background. In this study, an original camouflage butterfly dataset called ERVA 1.0 is created, consisting of images of 10 butterfly species downloaded from search engines. Additionally, the raw training data is increased with data augmentation techniques. For COD, this study presents a two-stage solution: segmentation and object recognition. The texture features of all test images on the ERVA 1.0 dataset are extracted utilizing the Gabor filter for segmentation. Then, these extracted features are clustered with the K-means algorithm, and the original image is separated into different regions based on texture features. The local binary pattern algorithm and Euclidean distance calculation are used to determine which of these regions belongs to the butterfly object. Following the application of morphological operations on the identified butterfly object region, pretrained models from deep learning techniques were employed to predict the species of the butterfly. Segmentation success rates are 87.89% with the structural similarity method and 83.64% with the Dice similarity coefficient method. Deep learning pretrained models are used to classify the type of the butterfly object obtained after segmentation. Experiment 1 was conducted with un-augmented training data and Experiment 2 with augmented data by applying data augmentation techniques. The highest success rate for Experiment 1 was 92.29% with the InceptionResNetV2 model, and the highest success rate for Experiment 2 is 94.81% with the DenseNet121 model.
A comparative study on the structural, chemical, morphological and electrochemical properties of α-MnO2, β-MnO2 and δ-MnO2 as cathode materials in aqueous zinc-ion batteries
Authors: Chacko Basil , Wuppulluri Madhuri 
Published: January 2025

Abstract
Aqueous zinc-ion batteries (AZIBs) are considered to be highly promising electrochemical energy storage device due to their affordability, inherent safety, large zinc resources, and optimal specific capacity. Among various cathode materials, manganese dioxide (MnO2) stands out for its high voltage, environmental benignity, and theoretical specific capacity. This study systematically investigates the phase formation and structural parameters of α-MnO2, β-MnO2, and δ-MnO2 synthesized via hydrothermal method, employing Rietveld refinement. FTIR and Raman spectroscopy confirms Mn-O and O-H bond formation. BET analysis reveals surface areas, and pore size distribution is calculated with BJH method. High-resolution XPS spectra exhibit a spin energy split of ~ 11.9 eV for Mn 2p confirming the presence of MnO2. Electrochemical studies shows an initial discharge capacities of 230.5, 188.74 and 263.30 mAh g− 1 at 0.1 A g− 1 for α-MnO2, β-MnO2 and δ-MnO2. The EIS spectra revealed the capacitive behaviour and electrode reaction kinetics where a RcT value of 484.14, 327.6, 162.5 Ω for α-MnO2, β-MnO2 and δ-MnO2. These study give insights into relation of various properties of MnO2 with electrochemical performance and its viability in grid storage applications.

Graphical Abstract
Efficiency of glass ionomer sealant application in reducing hypersensitivity in MIH-molars in schoolchildren immediately and after 12 weeks
Authors: Karim R. , Baider M. , Splieth C. H. , Schmoeckel J. 
Published: January 2025

Abstract

Aim
This prospective clinical study aimed to clinically investigate the efficiency of (GIC) glass-ionomer cement application (Ionostar Plus + Easy Glaze, VOCO) in reducing hypersensitivity in permanent molars affected by molar incisor hypomineralisation when assessed immediately (15 min) and 12 weeks after its application.

Materials and Methods
Children with at least one hypersensitive MIH-affected permanent molar (MIH-TNI-3 or 4). The pre-treatment status was evaluated and only included if they did not receive a tooth-specific in-office desensitizing treatment within one month. Clinical pain assessments were performed using the schiff score air sensitivity scale (SCASS) and Wong-baker faces Scale (WBFS).

Results
This study involved 25 participants (mean age 8.6 ± 1.85 years) with 43 hypersensitive MIH-molars of which about half were SCASS 3 (n = 24, 55.8%) and SCASS 2 (n = 19, 44.2%). Regarding hypersensitivity, the reported mean SCASS score reduced significantly from 2.56 (± 0.50) at baseline to 1.14 (± 0.96) after 15 min of GIC sealant application and even further to 0.71 (± 0.89) after 12 weeks (P < 0.001, Paired t test). Similarly, reported WBFS scores also significantly reduced from 5.81 (± 2.50; Range = 2–10) at baseline to 2.88 (± 2.31; Range = 0–10) after 15 min and to 2.95 (± 2.17) after 12 weeks, respectively (P < 0.001, Paired t test). The mean reduction in SCASS scores was 1.3 (± 0.6) and 1.4 (± 1.0) for baseline SCASS 2 vs. 3, respectively.

Conclusion
GIC coverage is effective in providing clear instant relief from hypersensitivity in MIH molars in schoolchildren, which improves even further over a period of 12 weeks.
Mape: defending against transferable adversarial attacks using multi-source adversarial perturbations elimination
Authors: Liu Xinlei , Xie Jichao , Hu Tao , Yi Peng , Hu Yuxiang , Huo Shumin , Zhang Zhen 
Published: January 2025

Abstract
Neural networks are vulnerable to meticulously crafted adversarial examples, leading to high-confidence misclassifications in image classification tasks. Due to their consistency with regular input patterns and the absence of reliance on the target model and its output information, transferable adversarial attacks exhibit a notably high stealthiness and detection difficulty, making them a significant focus of defense. In this work, we propose a deep learning defense known as multi-source adversarial perturbations elimination (MAPE) to counter diverse transferable attacks. MAPE comprises the single-source adversarial perturbation elimination (SAPE) mechanism and the pre-trained models probabilistic scheduling algorithm (PPSA). SAPE utilizes a thoughtfully designed channel-attention U-Net as the defense model and employs adversarial examples generated by a pre-trained model (e.g., ResNet) for its training, thereby enabling the elimination of known adversarial perturbations. PPSA introduces model difference quantification and negative momentum to strategically schedule multiple pre-trained models, thereby maximizing the differences among adversarial examples during the defense model’s training and enhancing its robustness in eliminating adversarial perturbations. MAPE effectively eliminates adversarial perturbations in various adversarial examples, providing a robust defense against attacks from different substitute models. In a black-box attack scenario utilizing ResNet-34 as the target model, our approach achieves average defense rates of over 95.1% on CIFAR-10 and over 71.5% on Mini-ImageNet, demonstrating state-of-the-art performance.