bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development, validation and reliability of scales and items for heat wave risk assessment of pregnant women
Authors: KC Ashish , Maharjan Sujeena , Basnet Omkar , Malla Honey , Gurung Rejina , Pokharel Sunil Mani , Ghimire Gyanu Kumari , Vaezghasemi Masoud , Schröders Julia 
Published: August 2024

AbstractIntroduction: The 1.2 °C rise of global ambient temperature since the pre-industrial era has led to an increase the intensity and frequency of heatwaves. Given the heightened vulnerability of pregnant women to heat stress, there is an urgent need for tools which accurately assess the knowledge, risk, and perception of pregnant woman toward heatwaves, enabling effective policy actions. In this research, we developed and validated tools to evaluate pregnant women’s perceptions of heat wave risks and behaviors. Method: We developed 50 items across seven constructs using the Health Belief Model, identified through a systematic literature review. The constructs comprised 8 Knowledge(K) items, 4 in Perceived Vulnerability (PV), 5 in Perceived Severity (PS), 6 in Perceived Benefit (PB), 4 in Perceived Barrier (PBa), 5 in Cue to Action(Cu) and 18 in Adaptation(A). Cognitive testing was performed with a separate group of pregnant women(n = 20). The tested tools were then administered to 120 pregnant women residing during the spring-summer 2023. Construct validation utilized exploratory factor analysis. Results: The Principal Axis Factoring Method was employed in the EFA with oblimin rotation for 51 items, considering communality > 0.20, and aiming to extract three factors. Across the three factors with Cronbach’s alpha > 0.70, a total of 11 items were distributed. Factor 1 included Perceived Severity (PS1, PS2, PS3 and PS5); Factor 2 included Cue to Action (Cu1, Cu2, Cu3, and Cu4); and Factor 3 encompassed Perceived Vulnerability (PV1, PV2, PV4). Only two of the retained items had factor loadings > 0.50, namely PV4 and PS5. Consequently, the three constructs measuring Perceived Severity, Cues to Action, and Perceived Vulnerability using the HBM among pregnant women were deemed valid. Conclusion: Our study has successfully validated a highly reliable tool which stands ready for application in assessing pregnant women’s risk perception regarding heatwaves.
Impact of occlusal stabilization splints on global body posture: a prospective clinical trial
Authors: Hampe Tristan , Fürstberger Laura , Kordsmeyer Tobias L. , Penke Lars , Mahler Alannah M. , Mäder Clemens M. , Bürgers Ralf , Krohn Sebastian 
Published: August 2024

Abstract
Objectives
Body posture of patients with temporomandibular disorders (TMD) has been investigated using different methods, whereas outcome and conclusions were controversial. The present clinical trial aimed to investigate the effects of splint therapy on global body posture.

Materials and methods
24 subjects (20 females, 4 males; age 24.2 ± 4.0 years) with TMD symptoms were examined clinically (RDC/TMD) and subsequently, splint fabrication was initiated. Along with routine therapy, all subjects underwent three-dimensional pre- and post-treatment full body scans in standing and upright sitting posture using a Vitus Smart XXL 3D scanner. Each scan was acquired in triplicate and evaluated in duplicate, measuring twelve standing and nine sitting postural parameters. Influencing factors were analyzed using analysis of variance (ANOVA), and additional Bland-Altman analyses verified the significance of the ANOVA results.

Results
The increase of Forward Head angles and the decrease of Round Shoulders angles were consistent for both positions and sides. Forward Head angles were significantly influenced by limited mandibular mobility and myofascial pain. Round Shoulders angles showed a significant correlation with myofascial pain, joint noises and the absence of limited mandibular mobility.

Conclusion
The influence of occlusal splints on global posture is limited and only small effects on cervicocranial parameters were found. In the present study, the average head position of post treatment measurements was more centered on the body’s core, whereas the shoulders were tilted more anteriorly.

Clinical relevance
Understanding the limited influence of occlusal splints on cervicocranial parameters underscores the need for multimodal treatment strategies for TMD patients.
GMMDA: Gaussian mixture modeling of graph in latent space for graph data augmentation
Authors: Li Yanjin , Xu Linchuan , Yamanishi Kenji 
Published: August 2024

AbstractGraph data augmentation (GDA), which manipulates graph structure and/or attributes, has been demonstrated as an effective method for improving the generalization of graph neural networks on semi-supervised node classification. As a data augmentation technique, label preservation is critical, that is, node labels should not change after data manipulation. However, most existing methods overlook the label preservation requirements. Determining the label-preserving nature of a GDA method is highly challenging, owing to the non-Euclidean nature of the graph structure. In this study, for the first time, we formulate a label-preserving problem (LPP) in the context of GDA. The LPP is formulated as an optimization problem in which, given a fixed augmentation budget, the objective is to find an augmented graph with minimal difference in data distribution compared to the original graph. To solve the LPP problem, we propose GMMDA, a generative data augmentation (DA) method based on Gaussian mixture modeling (GMM) of a graph in a latent space. We designed a novel learning objective that jointly learns a low-dimensional graph representation and estimates the GMM. The learning is followed by sampling from the GMM, and the samples are converted back to the graph as additional nodes. To uphold label preservation, we designed a minimum description length (MDL)-based method to select a set of samples that produces the minimum shift in the data distribution captured by the GMM. Through experiments, we demonstrate that GMMDA can improve the performance of graph convolutional network on Cora, Citeseer and Pubmed by as much as $$7.75\%$$

7.75
%

, $$8.75\%$$

8.75
%

and $$5.87\%$$

5.87
%

, respectively, significantly outperforming the state-of-the-art methods.
Securing the IoT ecosystem: ASIC-based hardware realization of Ascon lightweight cipher
Authors: Khan Safiullah , Inayat Kashif , Muslim Fahad Bin , Shah Yasir Ali , Atif Ur Rehman Muhammad , Khalid Ayesha , Imran Malik , Abdusalomov Akmalbek 
Published: August 2024

AbstractThe Internet of Things (IoT) nodes consist of sensors that collect environmental data and then perform data exchange with surrounding nodes and gateways. Cybersecurity attacks pose a threat to the data security that is being transmitted in any IoT network. Cryptographic primitives are widely adopted to address these threats; however, the substantial computation demands limit their applicability in the IoT ecosystem. In addition, each IoT node varies with respect to the area and throughput (TP) requirements, thus demanding flexible implementation for encryption/decryption processes. To solve these issues, this work implements the NIST lightweight cryptography standard, Ascon, on a SAED 32 nm process design kit (PDK) library by employing loop folded, loop unrolled and fully unrolled architectures. The fully unrolled architecture can achieve the highest TP but at the cost of higher area utilisation. Unrolling by a lower factor results in lower area implementations, enabling the exploration of design space to tackle the trade-off between area and TP performance of the design. The implementation results show that, for loop folded architecture, Ascon-128 and Ascon-128a require 36.7k $$\upmu \textrm{m}^{2}$$

μ

m
2

and 38.5k $$\upmu \textrm{m}^{2}$$

μ

m
2

chip area, respectively compared to 277.1k $$\upmu \textrm{m}^{2}$$

μ

m
2

and 306.6k $$\upmu \textrm{m}^{2}$$

μ

m
2

required by their fully unrolled implementations. The proposed implementation strategies can adjust the number of rounds to accommodate the varied requirements of IoT ecosystems. An implementation with an open-source 45 nm PDK library is also undertaken for enhanced generalization and reproducibility of the results.
Multiple habitat graphs: how connectivity brings forth landscape ecological processes
Authors: Savary Paul , Clauzel Céline , Foltête Jean-Christophe , Vuidel Gilles , Girardet Xavier , Bourgeois Marc , Martin François-Marie , Ropars Lise , Garnier Stéphane 
Published: August 2024

Abstract
Purpose
Habitat connectivity is integral to current biodiversity science and conservation strategies. Originally, the connectivity concept stressed the role of individual movements for landscape-scale processes. Connectivity determines whether populations can survive in sub-optimal patches (i.e., source-sink effects), complete life cycles relying on different habitat types (i.e., landscape complementation), and benefit from supplementary resources distributed over the landscape (i.e., landscape supplementation). Although the past decades have witnessed major improvements in habitat connectivity modeling, most approaches have yet to consider the multiplicity of habitat types that a species can benefit from. Without doing so, connectivity analyses potentially fail to meet one of their fundamental purposes: revealing how complex individual movements lead to landscape-scale ecological processes.

Methods
To bridge this conceptual and methodological gap, we propose to include multiple habitat types in spatial graph models of habitat connectivity, where nodes traditionally represent a single habitat type. Multiple habitat graphs will improve how we model connectivity and related landscape ecological processes, and how they are impacted by land cover changes.

Results
In three case studies, we use these graphs to model (i) source-sink effects, (ii) landscape supplementation, and (iii) complementation processes, in urban ecosystems, agricultural landscapes, and amphibian habitat networks, respectively. A new version of the Graphab open-source software implements the proposed approach.

Conclusion
Multiple habitat graphs help address crucial conservation challenges (e.g., urban sprawl, biological control, climate change) by representing more accurately the dynamics of populations, communities, and their interactions. Our approach thereby extends the ecologist’s toolbox and aims at fostering the alignment between landscape ecology theory and practice.
Commutative Poisson algebras from deformations of noncommutative algebras
Authors: Mikhailov Alexander V. , Vanhaecke Pol 
Published: August 2024

AbstractIt is well-known that a formal deformation of a commutative algebra $$\mathcal {A}$$
A
leads to a Poisson bracket on $$\mathcal {A}$$
A
and that the classical limit of a derivation on the deformation leads to a derivation on $$\mathcal {A}$$
A
, which is Hamiltonian with respect to the Poisson bracket. In this paper we present a generalization of it for formal deformations of an arbitrary noncommutative algebra $$\mathcal {A}$$
A
. The deformation leads in this case to a Poisson algebra structure on $$\Pi (\mathcal {A}){:}{=}Z(\mathcal {A})\times (\mathcal {A}/Z(\mathcal {A}))$$

Π
(
A
)
:
=
Z
(
A
)
×
(
A
/
Z
(
A
)
)

and to the structure of a $$\Pi (\mathcal {A})$$

Π
(
A
)

-Poisson module on $$\mathcal {A}$$
A
. The limiting derivations are then still derivations of $$\mathcal {A}$$
A
, but with the Hamiltonian belong to $$\Pi (\mathcal {A})$$

Π
(
A
)

, rather than to $$\mathcal {A}$$
A
. We illustrate our construction with several cases of formal deformations, coming from known quantum algebras, such as the ones associated with the nonabelian Volterra chains, Kontsevich integrable map, the quantum plane and the quantized Grassmann algebra.
Human herpesvirus reactivation and its potential role in the pathogenesis of post-acute sequelae of SARS-CoV-2 infection
Authors: Gáspár Zsófia , Szabó Bálint Gergely , Ceglédi Andrea , Lakatos Botond 
Published: August 2024

AbstractThe emergence of SARS-CoV-2 has precipitated a global pandemic with substantial long-term health implications, including the condition known as post-acute sequelae of SARS-CoV-2 infection (PASC), commonly referred to as Long COVID. PASC is marked by persistent symptoms such as fatigue, neurological issues, and autonomic dysfunction that persist for months beyond the acute phase of COVID-19. This review examines the potential role of herpesvirus reactivation, specifically Epstein-Barr virus (EBV) and cytomegalovirus (CMV), in the pathogenesis of PASC. Elevated antibody titers and specific T cell responses suggest recent herpesvirus reactivation in some PASC patients, although viremia is not consistently detected. SARS-CoV-2 exhibits endothelial trophism, directly affecting the vascular endothelium and contributing to microvascular pathologies. These pathologies are significant in PASC, where microvascular dysfunction may underlie various chronic symptoms. Similarly, herpesviruses like CMV also exhibit endothelial trophism, which may exacerbate endothelial damage when reactivated. Evidence suggests that EBV and CMV reactivation could indirectly contribute to the immune dysregulation, immunosenescence, and autoimmune responses observed in PASC. Additionally, EBV may play a role in the genesis of neurological symptoms through creating mitochondrial dysfunction, though direct confirmation remains elusive. The reviewed evidence suggests that while herpesviruses may not play a direct role in the pathogenesis of PASC, their potential indirect effects, especially in the context of endothelial involvement, warrant further investigation.
The effect of cognitive reserve on the cognitive connectome in healthy ageing
Authors: Habich Annegret , Garcia-Cabello Eloy , Abbatantuono Chiara , Gonzalez-Burgos Lissett , Taurisano Paolo , Dierks Thomas , Barroso José , Ferreira Daniel 
Published: August 2024

AbstractDuring ageing, different cognitive functions decline at different rates. Additionally, cognitive reserve may influence inter-individual variability in age-related cognitive decline. These complex relationships can be studied by constructing a so-called cognitive connectome and characterising it with advanced graph-theoretical network analyses. This study examined the effect of cognitive reserve on the cognitive connectome across age. A total of 334 cognitively healthy participants were stratified into early middle age (37–50 years; n = 110), late middle age (51–64 years; n = 106), and elderly (65–78 years; n = 118) groups. Within each age group, individuals were subdivided into high and low cognitive reserve. For each subgroup, a cognitive connectome was constructed based on correlations between 47 cognitive variables. Applying graph theory, different global network measures were compared between the groups. Graph-theoretical network analyses revealed that individuals with high cognitive reserve were characterized by a stable cognitive connectome across age groups. High cognitive reserve groups only differed in modularity. In contrast, individuals with low cognitive reserve showed a marked reconfiguration of cognitive connectomes across age groups with differences extending over a variety of network measures including network strength, global efficiency, modularity, and small-worldness. Our results suggest a stabilizing effect of cognitive reserve on the cognitive connectome. Gaining further insights into these findings and underlying mechanisms will contribute to our understanding of age-related cognitive decline and guide the development of strategies to preserve cognitive function in ageing.
Beyond cancer treatment: dermo-aesthetic and other wellness recommendations for breast cancer patients
Authors: Falcón González Alejandro , Gallegos Sancho María Isabel , González Flores Encarnación , Galve Calvo Elena , Ruiz Vozmediano Julia , Domingo García Paloma , López Martos Ricardo , Sánchez Rivas Elena , Iglesias Urraca Carmen María , Gómez Calvo Ana Isabel , De Mariscal Polo Amaia , Ramos-Medina Rocío , Rivero Maria , Martínez Marín Virginia 
Published: August 2024

AbstractBreast cancer, a prevalent malignancy among women, has various physical and psychological impacts. This comprehensive review offers an in-depth look at multidisciplinary dermo-aesthetic intervention approaches, emphasizing the balance between oncological therapies and the management of these effects. The information presented spans specialties such as aesthetic medicine, plastic surgery, dermatology, physiotherapy, nutrition, odontology, and gynecology. This review, which serves as a clinical guide, aims to establish a safe protocol for non-medical interventions involving oncologists, physicians, and specialists from various areas in patients with breast cancer focused on improving their quality of life. This work offers personalized and integrative care strategies for the eradication of cancer. However, it is still necessary for patients to consult with their oncologist before undergoing any dermo aesthetic treatment. However, it is still necessary for patients to consult with their oncologist before undergoing any dermo aesthetic treatment.
On Finite Parts of Divergent Complex Geometric Integrals and Their Dependence on a Choice of Hermitian Metric
Authors: Svensson Ludvig 
Published: August 2024

AbstractLet X be a reduced complex space of pure dimension. We consider divergent integrals of certain forms on X that are singular along a subvariety defined by the zero set of a holomorphic section of some holomorphic vector bundle $$E \rightarrow X$$

E
→
X

. Given a choice of Hermitian metric on E we define a finite part of the divergent integral. Our main result is an explicit formula for the dependence on the choice of metric of the finite part.
Structural and optical properties of Cr3+ doped SiO2 nanophosphor
Authors: Koao L. F. , Phokojoe R. A. , Moji R. G. , Motloung S. V. , Motaung T. E. , Swart H. C. 
Published: August 2024

AbstractSiO2:x% Cr3+ (0 ≤ x ≤ 8) nanopowder samples were synthesized using the sol-gel method. The effect of Cr3+ doping concentration on the SiO2 nanoparticles was studied for possible application in light-emitting diodes (LEDs). Structure and optical properties of undoped and Cr3+ doped SiO2 nanoparticles were investigated in detail. X-ray diffraction (XRD) results confirmed the amorphous phase for undoped SiO2 (A-SiO2) nanopowder. However, above 0.8% Cr3+ there were secondary peaks due rhombohedral structure of chromium (III) oxide (R-Cr2O3). Ultraviolet-visible spectroscopy (UV-Vis) spectra showed a reflectance peak at around 320 nm for the undoped sample. The results showed that when the concentration of Cr3+ is increased there was an emergence of reflectance peaks at around 309, 419, and 553 nm which were attributed to the presence of the Cr2O3 lattices. The photoluminescence (PL) results revealed that with an increase in the amount of Cr3+, the maximum peaks in blue and near red emerge at around 2.82 and 1.89 eV, respectively. Those peaks may be due to defects within both SiO2 and R-Cr2O3. The emission peaks of undoped and Cr3+ doped SiO2 match well with the Uv-vis results. The international illumination colour chromaticity showed that above 0.8% Cr3+ the colour shifts from yellow to blue with an increase in Cr3+ concentration. The investigation indicated that Cr3+ doped SiO2 have a potential application in blue and yellow LED chips for lighting.
Position paper on high fidelity simulations for coupled processes, multi-physics and chemistry in geological disposal of nuclear waste
Authors: Churakov S. V. , Claret F. , Idiart A. , Jacques D. , Govaerts J. , Kolditz O. , Prasianakis N.I. , Samper J. 
Published: August 2024

AbstractThis opinion paper describes the major coupled T(Thermal)-H(Hydro)-M(Mechanical)-C(Chemical) processes in geological repository systems and the frontier of related model development. Particular focus is made on the analysis of existing approaches and open research questions with respect to the further development of coupled codes and models for realistic multi-scale simulations of repository systems. These include the use of machine learning and artificial intelligence in acceleration of computer codes; sensitivity analysis, inverse modelling and optimisation; software engineering and collaborative platforms for model development.
Navigating Process Drift: The Power of CUSUM in Monitoring Air Quality Processes and Maintenance Operations
Authors: Riaz Muhammad , Alshammari Huda , Abbas Nasir , Mahmood Tahir 
Published: August 2024

AbstractNowadays, manufacturers face intense pressure to maintain a high standard of quality. Due to the damage to machine components, manufacturing processes degrade over time, resulting in substandard products. Generally, statistical process control tools such as control charts aid in identifying patterns and trends indicative of process changes. This investigation delves into the effectiveness of cumulative sum control charts using the sample mean and median as plotting statistics. Run-length measurements assess performance after the charts experience linear and quadratic drifts in non-normal setups under zero- and steady-state conditions. The findings reveal that Cumulative Sum (CUSUM) charts outperform zero-state monitoring compared to steady-state monitoring. Notably, the CUSUM chart for the mean is suitable for normal and Gamma distributions, exhibiting a greater ability for drift detection under biased and unbiased Average Run Lengths. This study offers valuable insights into enhancing manufacturing quality through effectively implementing and comparing Shewhart, Exponentially Weighted Moving Average, and CUSUM charts. By evaluating their performance under various conditions and comparing them with other control chart methods, this research provides valuable guidance for industries seeking to improve process monitoring and product quality. It is essential to acknowledge that the findings are based on specific experimental conditions and may not fully capture the complexity of real-world manufacturing environments. For practical purposes, the suggested charts are also applied to real-world case studies, including air quality (focusing on five metal oxide chemistry sensors: carbon monoxide concentration, non-metonic hydrocarbons, benzene, total nitrogen oxides, and nitrogen dioxide) and maintenance data (including air temperature, rotating speed, and equipment failure).
A systematic study of data augmentation for protected AES implementations
Authors: Li Huimin , Perin Guilherme 
Published: August 2024

AbstractSide-channel attacks against cryptographic implementations are mitigated by the application of masking and hiding countermeasures. Hiding countermeasures attempt to reduce the Signal-to-Noise Ratio of measurements by adding noise or desynchronization effects during the execution of the cryptographic operations. To bypass these protections, attackers adopt signal processing techniques such as pattern alignment, filtering, averaging, or resampling. Convolutional neural networks have shown the ability to reduce the effect of countermeasures without the need for trace preprocessing, especially alignment, due to their shift invariant property. Data augmentation techniques are also considered to improve the regularization capacity of the network, which improves generalization and, consequently, reduces the attack complexity. In this work, we deploy systematic experiments to investigate the benefits of data augmentation techniques against masked AES implementations when they are also protected with hiding countermeasures. Our results show that, for each countermeasure and dataset, a specific neural network architecture requires a particular data augmentation configuration to achieve significantly improved attack performance. Our results clearly show that data augmentation should be a standard process when targeting datasets with hiding countermeasures in deep learning-based side-channel attacks.