bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perceptions and decision-making of dental professionals to adopting sustainable waste management behaviour: a Theory of Planned Behaviour analysis
Authors: Lakhani Bhanu , Givati Assaf 
Published: October 2024

AbstractBackground High carbon emissions associated with clinical waste disposal in dentistry pose an environmental and public health concern. Current NHS guidelines do not mandate sustainable waste management resulting in recyclable dental waste being incinerated. In the absence of such policies, decision to implement sustainable waste management practices falls upon dental professionals who rely on their own knowledge and beliefs about the environmental impact of dentistry. Literature exploring barriers to sustainable waste management by dental professionals require further insight on dental professionals' decision-making processes. Therefore, this study uses a behavioural decision-making model - the Theory of Planned Behaviour (TPB) - to explore sustainable waste segregation behaviour of dental professionals based on their attitudes and beliefs about sustainable dentistry and climate change.Methods Fifteen semi-structured interviews were conducted with dental professionals between October and November 2022 in dental practices in Fife, Scotland. Interviews were analysed using Braun and Clarke's reflexive thematic data analysis.Findings Following thematic analysis, eight themes were identified around the participants' attitudes, perceived subjective norms and perceived behavioural control, pointing at the way knowledge gaps and lack of awareness were often linked with attitudes which are associated with low intention to execute sustainable waste management.Conclusions TPB offers a useful framework to understand waste segregation behaviour of dental professionals. Further studies are required to further establish sustainable waste management behaviour.
Active-type piezoelectric smart textiles with antifouling performance for pathogenic control
Authors: Lee Su Eon , Lee Hanna , Kim Jang Hwan , Park Jae Chul , Kyung Sooah , Choi Hayoung , Baek Su Hyun , Park Jun Hyun , Park Sohyun , Kim Jeong-Min , Jo Hye-Jun , Cho Seung Hyeon , Kim Jiwoong , Kim Hojun , Han Seung Ho , Oh Jun Kyun , Kim Bong Hoon 
Published: October 2024

AbstractRecently, an investigation into preventive measures for coronavirus disease 2019 (COVID-19) has garnered considerable attention. Consequently, strategies for the proactive prevention of viral pathogens have also attracted significant interest in the field of wearable devices and electronic textiles research, particularly due to their potential applications in personal protective equipment. In this study, we introduce smart textiles designed with optimized piezoelectric devices that exhibit antifouling performance against microorganisms and actively inactivate viruses. These active-type smart textiles, which incorporate advanced lead zirconate titanate (PZT) ceramics, a stretchable interconnector array, and polymeric fabric, demonstrate effective antifouling capabilities, detaching approximately 90% of Escherichia coli and 75% of SARS-CoV-2. Furthermore, they inactivate viruses, releasing ~26.8 ng of N protein from ruptured SARS-CoV-2, using ultrasonic waves within the wearable platform. Experimental results show that piezoelectric smart textiles significantly reduce the spread of COVID-19 by leveraging the electrical and acoustic properties of PZT ceramics.
Using machine learning to understand social isolation and loneliness in schizophrenia, bipolar disorder, and the community
Authors: Abplanalp Samuel J. , Green Michael F. , Wynn Jonathan K. , Eisenberger Naomi I. , Horan William P. , Lee Junghee , McCleery Amanda , Miklowitz David J. , Reddy L. Felice , Reavis Eric A. 
Published: October 2024

AbstractSocial disconnection, including objective social isolation and subjective loneliness, is linked to substantial health risks. Yet, little is known about the predictors of social disconnection in individuals with mental illness. Here, we used machine learning to identify predictors of social isolation and loneliness in schizophrenia (N = 72), a psychiatric condition associated with social disconnection. For comparison, we also included two other groups: a psychiatric comparison sample of bipolar disorder (N = 48) and a community sample enriched for social isolation (N = 151). We fitted statistical models of social isolation and loneliness within and across groups. Each model included five candidate predictors: social avoidance motivation, depression, nonsocial cognition, social anhedonia, and social cognition. The results showed that social anhedonia explained unique variance in social isolation and loneliness in all samples, suggesting that it contributes to social isolation and loneliness broadly. However, nonsocial cognition explained unique variance in social isolation only within schizophrenia. Thus, social anhedonia could be a potential intervention target across populations, whereas nonsocial cognition may play a unique role in determining social disconnection in schizophrenia.
Evaluation of mrkD, pgaC and wcaJ as biomarkers for rapid identification of K. pneumoniae biofilm infections from endotracheal aspirates and bronchoalveolar lavage
Authors: Devanga Ragupathi Naveen Kumar , Muthuirulandi Sethuvel Dhiviya Prabaa , Ganesan Anju , Murugan Dhivya , Baskaran Ashtawarthani , Wannigama Dhammika Leshan , Monk Peter N. , Karunakaran Esther , Veeraraghavan Balaji 
Published: October 2024

AbstractKlebsiella pneumoniaehas been identified as one of the most important opportunistic pathogens responsible for nosocomial infections. Antibiotic resistance and the ability to form biofilms are the two main factors involved in the persistence of infections. Conventional detection methods involve culture isolation and identification followed by biofilm assay that takes 48–72 h. Timely detection of biofilm-forming resistant pathogens is essential to appropriately treat the infection with the right dose and combinations. The present study focuses on evaluating an RT-PCR panel usingmrkD,pgaC, andwcaJ genes to screen for biofilm-formingK. pneumoniaefrom ETA/BAL specimens. The assay accurately identifiedK. pneumoniaeharboring samples with a limit of detection of 1 ng/µl total RNA. Representative culture-negative-PCR-positive samples were subjected to metagenomics which identifiedK. pneumoniaereads in these samples confirming the specificity of RT-PCR.mrkD andpgaC act asK. pneumoniaespecific identification whereaswcaJ acts as a negative marker for biofilm-formingK. pneumoniae. In addition, RT-PCR results correlated well with the phenotypic biofilm-forming assay. This RT-PCR assay is the first of its kind for rapid identification of biofilm-formingK. pneumoniae. The result of this study highlights that the rapid detection ofK. pneumoniaebiofilms based on the RT-PCR results coupled with clinical conditions would be appropriate to treat emerging infections or to prevent re-infections in clinical settings.
Magnetic resonance microscopy for submillimeter samples in a horizontal MR scanner
Authors: Hüfken Thomas , Lobmeyer Tobias , Gahr Bernd , Bschorr Fabian , Speidel Tobias , Just Steffen , Rasche Volker 
Published: October 2024

AbstractThe spatial resolution in magnetic resonance imaging is mainly limited by low SNR, which is commonly addressed by long measurement times or dedicated hardware. In single digit micron resolutions, diffusion becomes a further limiting factor since depending on the gradient strength, the diffusion length of particles may approach the target resolutions. Spatial resolution improvement has been addressed by microscopy inserts comprising dedicated gradient systems and RF-coils, usually designed for NMR spectrometers that are often equipped with a deuterium lock for field drift compensations. The presented microscopy insert has been designed to provide single-digit micron resolutions on horizontal preclinical imaging systems utilizing their full imaging and user interface capabilities. The incorporated gradient provides an efficiency of 0.135 T/(m∙A) which in combination with the system’s gradient amplifiers yields a maximum of 27 T/m. With the additional low noise amplifier added to the RF-path a three-fold SNR improvement could be achieved for small samples. Furthermore, a modified constant time imaging sequence was introduced to improve the capability of the setup for ultra‐high-resolution imaging demonstrated on zebrafish embryos at different development stages with (9 μm)³ resolution.
Multicellular ovarian cancer spheroids: novel 3D model to mimic tumour complexity
Authors: Flörkemeier Inken , Antons Lisa K. , Weimer Jörg P. , Hedemann Nina , Rogmans Christoph , Krüger Sandra , Scherließ Regina , Dempfle Astrid , Arnold Norbert , Maass Nicolai , Bauerschlag Dirk O. 
Published: October 2024

AbstractIn vitro, spheroid models have become well established in cancer research because they can better mimic certain characteristics of in vivo tumours. However, interaction with the tumour microenvironment, such as cancer-associated fibroblasts, plays a key role in tumour progression. We initially focused on the interaction of tumour cells with fibroblasts. To model this interaction, we developed a spheroid model of ovarian cancer and fibroblasts. To this end, ovarian cancer cell lines and ex vivo primary cells were simultaneously and sequentially seeded with fibroblasts in a scaffold-free system at different ratios and subsequently characterized with respect to changes in morphology, proliferation, and viability. We demonstrated that co-cultures are able to form by far more compact spheroids, especially in cells that form aggregates in mono-culture. In addition, the co-cultures were able to increase proliferation and sensitivity to cisplatin. Simultaneous seeding led fibroblasts invade the core in both cell lines and primary cells. These results show differences in formation, firmness, and size between co-culture and mono-culture. Our model is designed to better represent and characterize the mutual influencing factors of fibroblasts and tumour cells. Fibroblast-supplemented multicellular spheroids are a valuable tool for tumour microenvironment interaction and new drug discovery.
Integrating Kalman filter noise residue into U-Net for robust image denoising: the KU-Net model
Authors: Soniya S. , Sriharipriya K. C. 
Published: October 2024

AbstractIn low-level image processing, where the main goal is to reconstruct a clean image from a noise-corrupted version, image denoising continues to be a critical challenge. Although recent developments have led to the introduction of complex architectures to improve denoising performance, these models frequently have more parameters and higher computational demands. Here, we propose a new, simplified architecture called KU-Net, which is intended to achieve better denoising performance while requiring less complexity. KU-Net is an extension of the basic U-Net architecture that incorporates gradient information and noise residue from a Kalman filter. The network’s ability to learn is improved by this deliberate incorporation, which also helps it better preserve minute details in the denoised images. Without using Image augmentation, the proposed model is trained on a limited dataset to show its resilience in restricted training settings. Three essential inputs are processed by the architecture: gradient estimations, the predicted noisy image, and the original noisy grey image. These inputs work together to steer the U-Net’s encoding and decoding stages to generate high-quality denoised outputs. According to our experimental results, KU-Net performs better than traditional models, as demonstrated by its superiority on common metrics like the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR). KU-Net notably attains a PSNR of 26.60 dB at a noise level of 50, highlighting its efficacy and potential for more widespread use in image denoising.
The European Green Deal and turbulence for non-member states
Authors: Leiren Merethe Dotterud , Farstad Fay 
Published: October 2024

AbstractThe European Green Deal (EGD) has had a significant impact on EU member states. In this article, we examine the extent to which it can also have large consequences for non-members. Based on a qualitative approach comparing Norway and the UK, and drawing on a burgeoning literature on ‘turbulence’, we ask whether the EGD creates turbulence in non-member states, what the nature of this turbulence is, and whether the extent and nature of turbulence varies with how closely affiliated a non-member is with the EU. Despite the ambitious climate policies of both countries, we identify a significant amount of turbulence generated by the EGD. Interestingly, we also find that turbulence increases with a closer EU-affiliation. However, our analysis also reveals an impressive capacity in both countries to adapt to their turbulent conditions, and a surprising durability of climate and energy policy in the face of turbulence.
La tétine pour réduire le risque de mort inattendue du nourrisson : pourquoi, quand, comment ?
Authors: Soyer Yves , Amat Philippe 
Published: October 2024

L’expression « Mort inattendue du nourrisson » (MIN) a été retenue par le groupe de travail de la Haute autorité de santé (HAS) pour désigner tout « décès survenant brutalement chez un nourrisson de moins de deux ans alors que rien, dans ses antécédents connus, ne pouvait le laisser prévoir ». Malgré un contexte de baisse générale, les taux de décès par MIN demeurent encore élevés notamment en France, avec de grandes disparités interrégionales. L’ harmonisation de la prévention et de la prise en charge doit être recherchée et soutenue. L’ utilisation de la tétine est une des pistes possibles. Elle serait associée à une réduction du risque de MIN. Les auteurs proposent un arbre de prise de décision. Il synthétise les informations à donner aux parents sur quand commencer, comment gérer et quand arrêter le port d’une tétine pour réduire le risque de MIN.
Vers une étude du temps dérivé en psychologie et psychopathologie
Authors: Barthélémy Jean-Marie 
Published: October 2024

Les entrelacs d’un trajet personnel de praticien, chercheur et enseignant en psychopathologie et psychologie clinique, avec une réflexion prolongée sur les divers registres d’inscription d’une temporalité vécue, qui prirent source aux œuvres et destins croisés d’Eugène Minkowski et Françoise Minkowska, créent l’opportunité d’un regard à la fois introspectif, rétrospectif et prospectif sur les dimensions dialectiques de la méthode phénoméno-structurale dont la dénomination dédoublée porte la marque. La notion de « temps dérivé » que nous proposons comme petite pierre contributive en marge, fil rouge et continuité dans cette publication, tente de définir quelques-uns de ses contours et détours auxquels elle nous a conduit jusqu’ici et des potentialités qu’elle nous semble contenir et détenir, prometteuses d’un essor où des perspectives d’avenir pour la psychiatrie et de la psychopathologie pourraient trouver place respectable en redéfinissant leurs rôles et aspirations.
Quantile via Moments Panel Data Analysis: Dissecting Political Regimes and the Spectrum of Internal Conflicts
Authors: Parsons Brandon , Marie Joseph St. , Pauly Robert 
Published: October 2024

AbstractThis study investigates whether the political regime affects internal conflicts and specific types (e.g., civil war, political violence, and civil disorder). The study reveals that even incremental movements toward democracy are associated with reduced internal conflict, challenging some elements of the inverted U hypothesis. Moreover, factors such as government stability are better indicators of smaller-scale forms of internal conflict than the political regime type. Finally, scenarios of acute internal conflict, cultural tension, and government instability serve as more reliable indicators, implying that these elements eclipse the stabilizing influence of a regime's progression toward a more inclusive government.
In-plane thermal conductivity measurements of Si μ-cantilevers using the suspended thermo-reflectance (STR) technique
Authors: Sarkar Dipta , Singh Gurpreet , Yilbas Bekir S. , Mansoor Saad B. , Al-Qahtani Hussain , Leseman Zayd C. 
Published: October 2024

The Suspended Thermoreflectance (STR) technique is described in this paper. This optoelectronic measurement tool performs thermal characterization of freestanding micro-/nanoscale materials. STR performs thermal mapping at the submicron level and produces unconstrained thermal conductivity unlike other optical measurement techniques where independent conductivity measurement is not possible due to their reliance on heat capacity. STR works by changing the temperature of a material and collecting the associated change in light reflection from multiple points on the sample surface. Reflection is a function of the material being tested, the wavelength of the probe light, geometry, and the composition of the specimen for transparent and quasi-transparent materials. In this article, Si μ-cantilevers are studied. In addition, a thermal analytical model is developed and incorporated with optical equations to characterize the conductivity of the Si μ-cantilevers. The analytical model is compared with a finite element model to check its applicability in the STR experiment and data analysis. To validate the technique, the thermal conductivity of 2 and 3 µm thick Si μ-cantilevers was determined using STR at a temperature range of 20–350 K and compared to simulations using the equation of phonon radiative transfer and literature values.
Supplementary comparisons of reference measuring systems of electric capacitance and loss dissipation factor on AC high voltage of power frequency COOMET 604/RU-a/13 (COOMET.EM-S18)
Authors: Kiselev Victor , Leonov Alexey , Dubrovskaya Tatiana , Styblikova Renata , Gelovani Manana , Kikalo Valery 
Published: October 2024

Main text
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Enhanced detection of glyphosate with a Co-MOF integrated opto-electrochemical sensor
Authors: Sankhla Lakshya , Kushwaha Himmat Singh 
Published: October 2024

Abstract
This study presents a new method for detecting the organophosphorus pesticide glyphosate using advanced screen-printed electrodes and enhanced fluorescence. Metal-organic frameworks from cobalt ions were synthesized using a solvothermal method. It is characterized using Raman spectroscopy, FT-IR, and x-ray diffraction techniques. The electrocatalytic behavior of the materials was studied using electrochemical impedance spectroscopy and cyclic voltammetry. Differential pulse voltammetry examined the positive response of plants to glyphosate over a concentration range of 0.55–5.95 mM with a detection limit of 0.334 mM. The fluorescence enhancement ranges from 0.07 mM to 0.67 mM, and the detection limit is 0.0998 mM. Additionally, the selectivity of the proposed opto-electrochemical sensor was evaluated. This selection demonstrates the sensor’s ability to detect glyphosate in complex wastewater matrices. This has important implications for environmental monitoring. By addressing glyphosate contamination, the sensor could significantly advance ecological remediation and monitoring strategies. The selectivity, sensitivity, and ability to operate under harsh conditions represent a significant advance in the development of efficient and reliable glyphosate technology for wastewater treatment and environmental protection. In real-sample matrices, the suggested sensor showed a good recovery of the pesticide that had been spiked.
Influences of short-term and long-term plasticity of memristive synapse on firing activity of neuronal network
Authors: Li 李 Zhi-Jun 志军 , Zhang 张 Jing 晶 
Published: October 2024

Abstract
Synaptic plasticity can greatly affect the firing behavior of neural networks, and it specifically refers to changes in the strength, morphology, and function of synaptic connections. In this paper, a novel memristor model, which can be configured as a volatile and nonvolatile memristor by adjusting its internal parameter, is proposed to mimic the short-term and long-term synaptic plasticity. Then, a bi-neuron network model, with the proposed memristor serving as a coupling synapse and the external electromagnetic radiation being emulated by the flux-controlled memristors, is established to elucidate the effects of short-term and long-term synaptic plasticity on firing activity of the neuron network. The resultant seven-dimensional (7D) neuron network has no equilibrium point and its hidden dynamical behavior is revealed by phase diagram, time series, bifurcation diagram, Lyapunov exponent spectrum, and two-dimensional (2D) dynamic map. Our results show the short-term and long-term plasticity can induce different bifurcation scenarios when the coupling strength increases. In addition, memristor synaptic plasticity has a great influence on the distribution of firing patterns in the parameter space. More interestingly, when exploring the synchronous firing behavior of two neurons, the two neurons can gradually achieve phase synchronization as the coupling strength increases along the opposite directions under two different memory attributes. Finally, a microcontroller-based hardware system is implemented to verify the numerical simulation results.
Design of railway simulation training system based on WebGL
Authors: Han Shibo , Su Hu , Zhao Yuanhang , Ma Chi 
Published: October 2024

Abstract
In order to solve the problems of poor interaction with students and insufficient practicality in the previous railway freight station operation training, this article developed a training system based on WebGL technology that can interact with students and truly display the operation situation of the freight yard. This system is based on the Unity3D engine and WebGL technology. It imports 3D models to build large map scenes, and introduces functions such as cargo bundling and map roaming. The complete designed system is published to the Web through WebGL technology. After experimental analysis, the parking lot training system has solved the problems of poor practicality, little interaction, low efficiency, and narrow coverage in previous teaching. It has promoted the standardization and standardization of training students’ future work, and has effectively improved the professionalism of parking lot managers.
Design and research of high-performance convolutional neural network accelerator based on Chipyard
Authors: Fan Yuxiao 
Published: October 2024

Abstract
Neural network accelerator performs well in the research and verification of neural network models. In this paper, a convolutional neural network accelerator system composed of RISC-V processor core and Gemmini array accelerator is designed in Chisel language within the Chipyard framework, and the acceleration effect of different Gemmini array configurations for different input matrices is further investigated. The result shows that the accelerator system can achieve thousands of times acceleration compared with a single processor for large matrix calculations.