bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Variation in Commissural Angle between Fused Leaflets in the Functionally Bicuspid Aortic Valve on Hemodynamics and Tissue Biomechanics
Authors: Sundström Elias , Tretter Justin T.
Published: October 2023

In subjects with functionally bicuspid aortic valves (BAVs) with fusion between the coronary leaflets, there is a natural variation of the commissural angle. What is not fully understood is how this variation influences the hemodynamics and tissue biomechanics. These variables may influence valvar durability and function, both in the native valve and following repair, and influence ongoing aortic dilation. A 3D aortic valvar model was reconstructed from a patient with a normal trileaflet aortic valve using cardiac magnetic resonance (CMR) imaging. Fluid–structure interaction (FSI) simulations were used to compare the effects of the varying commissural angles between the non-coronary with its adjacent coronary leaflet. The results showed that the BAV with very asymmetric commissures (120∘ degree commissural angle) reduces the aortic opening area during peak systole and with a jet that impacts on the right posterior wall proximally of the ascending aorta, giving rise to elevated wall shear stress. This manifests in a shear layer with a retrograde flow and strong swirling towards the fused leaflet side. In contrast, a more symmetrical commissural angle (180∘ degree commissural angle) reduces the jet impact on the posterior wall and leads to a linear decrease in stress and strain levels in the non-fused non-coronary leaflet. These findings highlight the importance of considering the commissural angle in the progression of aortic valvar stenosis, the regional distribution of stresses and strain levels experienced by the leaflets which may predispose to valvar deterioration, and progression in thoracic aortic dilation in patients with functionally bicuspid aortic valves. Understanding the hemodynamics and biomechanics of the functionally bicuspid aortic valve and its variation in structure may provide insight into predicting the risk of aortic valve dysfunction and thoracic aortic dilation, which could inform clinical decision making and potentially lead to improved aortic valvar surgical outcomes.
Protein–Protein Interaction Network Extraction Using Text Mining Methods Adds Insight into Autism Spectrum Disorder
Authors: Nezamuldeen Leena , Jafri Mohsin Saleet
Published: October 2023

Text mining methods are being developed to assimilate the volume of biomedical textual materials that are continually expanding. Understanding protein–protein interaction (PPI) deficits would assist in explaining the genesis of diseases. In this study, we designed an automated system to extract PPIs from the biomedical literature that uses a deep learning sentence classification model, a pretrained word embedding, and a BiLSTM recurrent neural network with additional layers, a conditional random field (CRF) named entity recognition (NER) model, and shortest-dependency path (SDP) model using the SpaCy library in Python. The automated system ensures that it targets sentences that contain PPIs and not just these proteins mentioned in the framework of disease discovery or other context. Our first model achieved 13% greater precision on the Aimed/BioInfr benchmark corpus than the previous state-of-the-art BiLSTM neural network models. The NER model presented in this study achieved 98% precision on the Aimed/BioInfr corpus over previous models. In order to facilitate the production of an accurate representation of the PPI network, the processes were developed to systematically map the protein interactions in the texts. Overall, evaluating our system through the use of 6027 abstracts pertaining to seven proteins associated with Autism Spectrum Disorder completed the manually curated PPI network for these proteins. When it comes to complicated diseases, these networks would assist in understanding how PPI deficits contribute to disease development while also emphasizing the influence of interactions on protein function and biological processes.
Characterisation of Ferritin–Lymphocyte Ratio in COVID-19
Authors: Liu Alexander , Hammond Robert , Chan Kenneth , Chukwuenweniwe Chukwugozie , Johnson Rebecca , Khair Duaa , Duck Eleanor , Olubodun Oluwaseun , Barwick Kristian , Banya Winston , Stirrup James , Donnelly Peter D. , Kaski Juan Carlos , Coates Anthony R. M.
Published: October 2023

Introduction: The ferritin–lymphocyte ratio (FLR) is a novel inflammatory biomarker for the assessment of acute COVID-19 patients. However, the prognostic value of FLR for predicting adverse clinical outcomes in COVID-19 remains unclear, which hinders its clinical translation. Methods: We characterised the prognostic value of FLR in COVID-19 patients, as compared to established inflammatory markers. Results: In 217 study patients (69 years [IQR: 55–82]; 60% males), FLR was weakly correlated with CRP (R = 0.108, p = 0.115) and white cell count (R = −0.144; p = 0.034). On ROC analysis, an FLR cut-off of 286 achieved a sensitivity of 86% and a specificity of 30% for predicting inpatient mortality (AUC 0.60, 95% CI: 0.53–0.67). The negative predictive values of FLR for ruling out mortality, non-invasive ventilation requirement and critical illness (intubation and/or ICU admission) were 86%, 85% and 93%, respectively. FLR performed similarly to CRP (AUC 0.60 vs. 0.64; p = 0.375) for predicting mortality, but worse than CRP for predicting non-fatal outcomes (all p < 0.05). On Kaplan–Meier analysis, COVID-19 patients with FLR values > 286 had worse inpatient survival than patients with FLR ≤ 286, p = 0.041. Conclusions: FLR has prognostic value in COVID-19 patients, and appears unrelated to other inflammatory markers such as CRP and WCC. FLR exhibits high sensitivity and negative predictive values for adverse clinical outcomes in COVID-19, and may be a good “rule-out” test. Further work is needed to improve the sensitivity of FLR and validate its role in prospective studies for guiding clinical management.
Smart Contact Lenses—A Step towards Non-Invasive Continuous Eye Health Monitoring
Authors: Kazanskiy Nikolay L. , Khonina Svetlana N. , Butt Muhammad A.
Published: October 2023

According to the age-old adage, while eyes are often considered the gateway to the soul, they might also provide insights into a more pragmatic aspect of our health: blood sugar levels. This potential breakthrough could be realized through the development of smart contact lenses (SCLs). Although contact lenses were first developed for eyesight correction, new uses have recently become available. In the near future, it might be possible to monitor a variety of ocular and systemic disorders using contact lens sensors. Within the realm of glaucoma, SCLs present a novel prospect, offering a potentially superior avenue compared to traditional management techniques. These lenses introduce the possibility of non-invasive and continuous monitoring of intraocular pressure (IOP) while also enabling the personalized administration of medication as and when needed. This convergence holds great promise for advancing glaucoma care. In this review, recent developments in SCLs, including their potential applications, such as IOP and glucose monitoring, are briefly discussed.
Optimal Design of Nonlinear Negative-Stiffness Damper with Flexible Support for Mitigating Cable Vibration
Authors: Liu Guanliang , Zhou Peng , Yu Tong , Li Zeping
Published: October 2023

Negative-stiffness damper is a promising device to mitigate cable vibrations effectively. In contrast to traditional rigid supports, recent study has found that flexible supports are actually beneficial for enhancing the performance of negative-stiffness dampers. This study extends the understanding of the impact of support flexibility under nonlinear condition, followed by an optimization process to obtain required negative-stiffness dampers and corresponding supports. First, taking damping nonlinearity into account, a unified model is established for the negative-stiffness damper with flexible support. Theoretical equivalent negative stiffness and damping are obtained for a linear case, followed by numerical verification. Thereafter, equivalent parameters under a friction case are presented. Experiments are conducted to validate the analytical derivation. Then, problem formulation is developed for the controlled cable. Optimization process is proposed to determine the required negative-stiffness damper and support for multimodal cable vibration. A series of numerical simulations are performed to demonstrate the design process. Moreover, nonlinear examples are presented to show the potential for improving control performance. As indicated by the research results, a flexible support is capable of amplifying the equivalent negative stiffness and damping under linear and nonlinear conditions. For multimodal cable vibration, it is sufficient to determine the optimized negative stiffness and support by only considering the highest mode. Nonlinear negative-stiffness dampers exhibit superior performance due to the leakage of vibration energy toward high-order modes.
Dynamic Response Analysis of Wedge-Shaped Rock Slopes under Harmonic Wave Action
Authors: Du Yihan , Xu Wenzhi , Han Wei , Huang Bo , Liu Hui , Du Xuze
Published: October 2023

In dynamic disasters involving rock slopes, wedge failures formed by complex structural discontinuities are more predominant, and the dynamic response associated with them remains a classic concern in rock slope engineering. To address this concern, this paper utilized refined modeling to analyze a wedge-shaped rock slope by inputting horizontal harmonics as loads. We conducted dynamic response analyses by varying the inclination of the structural surface on the wedge-shaped rock slope, the axial offset angle, the friction coefficient, and the configuration of the single sliding surface. The results in this paper indicate that for wedge-shaped and single-sliding-surface configurations of rock slopes, with an increase in the structural surface inclination angle, the dynamic response of the sliding body, stress distribution, excellent frequency, and spectrum values all increase. Furthermore, wedge-shaped rock slopes’ dynamic responses are more significant than those of single-sliding-surface rock slopes. For wedge-shaped rock slopes, increases in the axial offset angle and structural surface friction coefficient reduce the dynamic response, excellent frequency, and spectrum values. Meanwhile, within the context of the axial offset angle conditions in wedge-shaped rock slopes, the dynamic response, excellent frequency, and spectrum values are better than the variations in the structural surface friction coefficient. Under the influence of these factors, stress concentration occurs at the sliding fronts of rock slopes.
Mechanistic Insights into Eosinophilic Esophagitis: Therapies Targeting Pathophysiological Mechanisms
Authors: Massironi Sara , Mulinacci Giacomo , Gallo Camilla , Elvevi Alessandra , Danese Silvio , Invernizzi Pietro , Vespa Edoardo
Published: October 2023

Eosinophilic esophagitis (EoE) is a chronic inflammatory disease characterized by eosinophilic infiltration of the esophagus. It arises from a complex interplay of genetic predisposition (susceptibility loci), environmental triggers (allergens and dietary antigens), and a dysregulated immune response, mainly mediated by type 2 T helper cell (Th2)-released cytokines, such as interleukin (IL)-4, IL-5, and IL-13. These cytokines control eosinophil recruitment and activation as well as tissue remodeling, contributing to the characteristic features of EoE. The pathogenesis of EoE includes epithelial barrier dysfunction, mast cell activation, eosinophil degranulation, and fibrosis. Epithelial barrier dysfunction allows allergen penetration and promotes immune cell infiltration, thereby perpetuating the inflammatory response. Mast cells release proinflammatory mediators and promote eosinophil recruitment and the release of cytotoxic proteins and cytokines, causing tissue damage and remodeling. Prolonged inflammation can lead to fibrosis, resulting in long-term complications such as strictures and dysmotility. Current treatment options for EoE are limited and mainly focus on dietary changes, proton-pump inhibitors, and topical corticosteroids. Novel therapies targeting key inflammatory pathways, such as monoclonal antibodies against IL-4, IL-5, and IL-13, are emerging in clinical trials. A deeper understanding of the complex pathogenetic mechanisms behind EoE will contribute to the development of more effective and personalized therapeutic strategies.
Tuft Cells: Detectors, Amplifiers, Effectors and Targets in Parasite Infection
Authors: Campillo Poveda Marta , Britton Collette , Devaney Eileen , McNeilly Tom N. , Gerbe François , Jay Philippe , Maizels Rick M.
Published: October 2023

Tuft cells have recently emerged as the focus of intense interest following the discovery of their chemosensory role in the intestinal tract, and their ability to activate Type 2 immune responses to helminth parasites. Moreover, they populate a wide range of mucosal tissues and are intimately connected to immune and neuronal cells, either directly or through the release of pharmacologically active mediators. They are now recognised to fulfil both homeostatic roles, in metabolism and tissue integrity, as well as acting as the first sensors of parasite infection, immunity to which is lost in their absence. In this review we focus primarily on the importance of tuft cells in the intestinal niche, but also link to their more generalised physiological role and discuss their potential as targets for the treatment of gastrointestinal disorders.
Analysis of the Gálvez–Davison Index for the Forecasting Formation and Evolution of Convective Clouds in the Tropics: Western Cuba
Authors: Fuentes-Alvarez Tahimy , González-Jardines Pedro M. , Fernández-Alvarez José C. , de la Torre Laura , Añel Juan A.
Published: October 2023

The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.
Manufacturing and Properties of Various Ceramic-Embedded Composite Fabrics for Protective Clothing in Gas and Oil Industries Part II: Thermal Wear Comfort via Thermal Manikin
Authors: Kim Hyun-Ah
Published: October 2023

Thermal wear comfort for workwear clothing plays a vital role in maintaining comfortable water- and moisture-vapor-permeable properties while wearing clothing. In particular, thermal wear comfort measured using a thermal manikin is required in the protective workwear clothing market because their use provides objective data concerning the actual wearing performance of the clothing. This paper investigated the thermal wear comfort properties of various ceramic-embedded composite fabrics for workwear clothing worn in gas and oil industries produced from new schemes. The thermal insulation rate (Clo value) of Al2O3(Aluminum oxide)/graphite, ZnO(zinc oxide)/ZrC(zirconium carbide) and ZnO/ATO(antimony tin oxide)-embedded clothing was greater (25.5, 24.7 and 16.9%, respectively) than that of regular clothing (control), which was in accordance with the results (15.0, 13.8 and 11.3% higher, respectively) of the heat retention rate (I) of fabric specimens. It revealed that ZnO- and ATO-embedded yarns mixed with ZrC particles enhanced thermal wear comfort and had superior anti-static and UV-protective properties. Considering UV-protective and anti-static protective clothing worn in gas and oil industries and cold weather regions, it can be concluded that ZnO/ZrC-incorporated fabric is suitable because it showed superior thermal wear comfort with excellent UV-protective and acceptable anti-static properties. Meanwhile, assuming high functional performance for protective clothing worn in winter and factories, ZnO/ATO-incorporated fabric is pertinent to fabricating protective clothing for cold weather regions.
Using Machine Learning and Routing Protocols for Optimizing Distributed SPARQL Queries in Collaboration
Authors: Warnke Benjamin , Fischer Stefan , Groppe Sven
Published: October 2023

Due to increasing digitization, the amount of data in the Internet of Things (IoT) is constantly increasing. In order to be able to process queries efficiently, strategies must, therefore, be found to reduce the transmitted data as much as possible. SPARQL is particularly well-suited to the IoT environment because it can handle various data structures. Due to the flexibility of data structures, however, more data have to be joined again during processing. Therefore, a good join order is crucial as it significantly impacts the number of intermediate results. However, computing the best linking order is an NP-hard problem because the total number of possible linking orders increases exponentially with the number of inputs to be combined. In addition, there are different definitions of optimal join orders. Machine learning uses stochastic methods to achieve good results even with complex problems quickly. Other DBMSs also consider reducing network traffic but neglect the network topology. Network topology is crucial in IoT as devices are not evenly distributed. Therefore, we present new techniques for collaboration between routing, application, and machine learning. Our approach, which pushes the operators as close as possible to the data source, minimizes the produced network traffic by 10%. Additionally, the model can reduce the number of intermediate results by a factor of 100 in comparison to other state-of-the-art approaches.
Image Quality and Quantitative PET Parameters of Low-Dose [18F]FDG PET in a Long Axial Field-of-View PET/CT Scanner
Authors: Calderón Eduardo , Schmidt Fabian P. , Lan Wenhong , Castaneda-Vega Salvador , Brendlin Andreas S. , Trautwein Nils F. , Dittmann Helmut , la Fougère Christian , Kiefer Lena Sophie
Published: October 2023

PET/CT scanners with a long axial field-of-view (LAFOV) provide increased sensitivity, enabling the adjustment of imaging parameters by reducing the injected activity or shortening the acquisition time. This study aimed to evaluate the limitations of reduced [18F]FDG activity doses on image quality, lesion detectability, and the quantification of lesion uptake in the Biograph Vision Quadra, as well as to assess the benefits of the recently introduced ultra-high sensitivity mode in a clinical setting. A number of 26 patients who underwent [18F]FDG-PET/CT (3.0 MBq/kg, 5 min scan time) were included in this analysis. The PET raw data was rebinned for shorter frame durations to simulate 5 min scans with lower activities in the high sensitivity (HS) and ultra-high sensitivity (UHS) modes. Image quality, noise, and lesion detectability (n = 82) were assessed using a 5-point Likert scale. The coefficient of variation (CoV), signal-to-noise ratio (SNR), tumor-to-background ratio (TBR), and standardized uptake values (SUV) including SUVmean, SUVmax, and SUVpeak were evaluated. Subjective image ratings were generally superior in UHS compared to the HS mode. At 0.5 MBq/kg, lesion detectability decreased to 95% (HS) and to 98% (UHS). SNR was comparable at 1.0 MBq/kg in HS (5.7 ± 0.6) and 0.5 MBq/kg in UHS (5.5 ± 0.5). With lower doses, there were negligible reductions in SUVmean and SUVpeak, whereas SUVmax increased steadily. Reducing the [18F]FDG activity to 1.0 MBq/kg (HS/UHS) in a LAFOV PET/CT provides diagnostic image quality without statistically significant changes in the uptake parameters. The UHS mode improves image quality, noise, and lesion detectability compared to the HS mode.
Image Quality and Diagnostic Performance of Accelerated 2D Hip MRI with Deep Learning Reconstruction Based on a Deep Iterative Hierarchical Network
Authors: Herrmann Judith , Afat Saif , Gassenmaier Sebastian , Koerzdoerfer Gregor , Lingg Andreas , Almansour Haidara , Nickel Dominik , Werner Sebastian
Published: October 2023

Objectives: Hip MRI using standard multiplanar sequences requires long scan times. Accelerating MRI is accompanied by reduced image quality. This study aimed to compare standard two-dimensional (2D) turbo spin echo (TSE) sequences with accelerated 2D TSE sequences with deep learning (DL) reconstruction (TSEDL) for routine clinical hip MRI at 1.5 and 3 T in terms of feasibility, image quality, and diagnostic performance. Material and Methods: In this prospective, monocentric study, TSEDL was implemented clinically and evaluated in 14 prospectively enrolled patients undergoing a clinically indicated hip MRI at 1.5 and 3T between October 2020 and May 2021. Each patient underwent two examinations: For the first exam, we used standard sequences with generalized autocalibrating partial parallel acquisition reconstruction (TSES). For the second exam, we implemented prospectively undersampled TSE sequences with DL reconstruction (TSEDL). Two radiologists assessed the TSEDL and TSES regarding image quality, artifacts, noise, edge sharpness, diagnostic confidence, and delineation of anatomical structures using an ordinal five-point Likert scale (1 = non-diagnostic; 2 = poor; 3 = moderate; 4 = good; 5 = excellent). Both sequences were compared regarding the detection of common pathologies of the hip. Comparative analyses were conducted to assess the differences between TSEDL and TSES. Results: Compared with TSES, TSEDL was rated to be significantly superior in terms of image quality (p ≤ 0.020) with significantly reduced noise (p ≤ 0.001) and significantly improved edge sharpness (p = 0.003). No difference was found between TSES and TSEDL concerning the extent of artifacts, diagnostic confidence, or the delineation of anatomical structures (p > 0.05). Example acquisition time reductions for the TSE sequences of 52% at 3 Tesla and 70% at 1.5 Tesla were achieved. Conclusion: TSEDL of the hip is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared with TSES, reducing the acquisition time significantly.
Skeletal Fracture Detection with Deep Learning: A Comprehensive Review
Authors: Su Zhihao , Adam Afzan , Nasrudin Mohammad Faidzul , Ayob Masri , Punganan Gauthamen
Published: October 2023

Deep learning models have shown great promise in diagnosing skeletal fractures from X-ray images. However, challenges remain that hinder progress in this field. Firstly, a lack of clear definitions for recognition, classification, detection, and localization tasks hampers the consistent development and comparison of methodologies. The existing reviews often lack technical depth or have limited scope. Additionally, the absence of explainable facilities undermines the clinical application and expert confidence in results. To address these issues, this comprehensive review analyzes and evaluates 40 out of 337 recent papers identified in prestigious databases, including WOS, Scopus, and EI. The objectives of this review are threefold. Firstly, precise definitions are established for the bone fracture recognition, classification, detection, and localization tasks within deep learning. Secondly, each study is summarized based on key aspects such as the bones involved, research objectives, dataset sizes, methods employed, results obtained, and concluding remarks. This process distills the diverse approaches into a generalized processing framework or workflow. Moreover, this review identifies the crucial areas for future research in deep learning models for bone fracture diagnosis. These include enhancing the network interpretability, integrating multimodal clinical information, providing therapeutic schedule recommendations, and developing advanced visualization methods for clinical application. By addressing these challenges, deep learning models can be made more intelligent and specialized in this domain. In conclusion, this review fills the gap in precise task definitions within deep learning for bone fracture diagnosis and provides a comprehensive analysis of the recent research. The findings serve as a foundation for future advancements, enabling improved interpretability, multimodal integration, clinical decision support, and advanced visualization techniques.
Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria
Authors: Yamin Dina , Uskoković Vuk , Wakil Abubakar , Goni Mohammed , Shamsuddin Shazana , Mustafa Fatin , Alfouzan Wadha , Alissa Mohammed , Alshengeti Amer , Almaghrabi Rana , Fares Mona , Garout Mohammed , Al Kaabi Nawal , Alshehri Ahmad , Ali Hamza , Rabaan Ali , Aldubisi Fatimah , Yean Chan , Yusof Nik
Published: October 2023

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.
Mature Triphyllic Cystic Teratoma of the Posterior Mediastinum in a Fetus: A Case Report and Literature Review
Authors: Salzillo Cecilia , Quaranta Andrea , De Biasi Giovanni , Cazzato Gerardo , Serio Gabriella , Vimercati Antonella , Nicolì Pierpaolo , Resta Leonardo , Marzullo Andrea
Published: October 2023

A teratoma is a neoplasm composed of cell populations or tissues that are reminiscent, in their appearance, of normal elements derived from at least two embryonic layers. Fetal mature teratomas are normally benign, cystic, and typically occur along the midline, while they are rare in the posterior mediastinum. Teratomas are frequently solitary; however, they may sometimes be associated with other congenital anomalies and/or with chromosomal abnormalities. Clinically, they are often asymptomatic but can occasionally cause compression symptoms. Prenatal diagnoses are uncommon and made with ultrasonography; differential diagnosis with other congenital conditions is mandatory. We report the case of a 21 weeks of gestational age old fetus with a mature triphyllic fetal cystic teratoma, grade 0, located in the right posterior mediastinum. The tumor presented as a 3 cm wide cystic mass that caused a contralateral shift of the surrounding structures. Histological examination later revealed the presence of derivatives of the three germ layers, such as hyaline cartilage, smooth muscle, nervous tissue, and a respiratory-type epithelium.
DoubleStrokeNet: Bigram-Level Keystroke Authentication
Authors: Neacsu Teodor , Poncu Teodor , Ruseti Stefan , Dascalu Mihai
Published: October 2023

Keystroke authentication is a well-established biometric technique that has gained significant attention due to its non-intrusive and continuous characteristics. The method analyzes the unique typing patterns of individuals to verify their identity while interacting with the keyboard, both virtual and hardware. Current deep-learning approaches like TypeNet and TypeFormer focus on generating biometric signatures as embeddings for the entire typing sequence. The authentication process is defined using the Euclidean distances between the new typing embedding and the saved biometric signatures. This paper introduces a novel approach called DoubleStrokeNet for authenticating users through keystroke analysis using bigram embeddings. Unlike conventional methods, our model targets the temporal features of bigrams to generate user embeddings. This is achieved using a Transformer-based neural network that distinguishes between different bigrams. Furthermore, we employ self-supervised learning techniques to compute embeddings for both bigrams and users. By harnessing the power of the Transformer’s attention mechanism, the DoubleStrokeNet approach represents a significant departure from existing methods. It allows for a more precise and accurate assessment of user authenticity, specifically emphasizing the temporal characteristics and latent representations of bigrams in deriving user embeddings. Our experiments were conducted using the Aalto University keystrokes datasets, which include 136 million keystrokes from 168,000 subjects using physical keyboards and 63 million keystrokes acquired on mobile devices from 60,000 subjects. The DoubleStrokeNet outperforms the TypeNet-based authentication system using 10 enrollment typing sequences, achieving Equal Error Rate (EER) values of 0.75% and 2.35% for physical and touchscreen keyboards, respectively.
Decentralized Multi-Layered Architecture to Strengthen the Security in the Internet of Things Environment Using Blockchain Technology
Authors: Alhusayni Ahmed , Thayananthan Vijey , Albeshri Aiiad , Alghamdi Saleh
Published: October 2023

Smart devices are connected to IoT networks and the security risks are substantial. Using blockchain technology, which is decentralized and distributed, 5G-enabled IoT networks might be able to tackle security issues. In order to simplify the implementation and security of IoT networks, we propose a multi-level blockchain security model. As part of the multi-level architecture, the communication between levels is facilitated by clustering. IoT networks define unknown clusters with applications that utilize the evolutionary computation method coupled with anatomy simulation and genetic methodologies. Authentication and authorization are performed locally by the super node. The super node and relevant base stations can communicate using local private blockchain implementations. A blockchain improves security and enhances trustworthiness by providing network authentication and credibility assurance. The proposed model is developed using the open-source Hyperledger Fabric blockchain platform. Stations communicate securely using a global blockchain. Compared to the earlier reported clustering algorithms, simulations demonstrate the efficacy of the proposed algorithm. In comparison with the global blockchain, the lightweight blockchain is more suitable for balancing network throughput and latency.
Certificateless Encryption Supporting Multi-Ciphertext Equality Test with Proxy-Assisted Authorization
Authors: Dong Siyue , Zhao Zhen , Wang Baocang , Gao Wen , Zhang Shanshan
Published: October 2023

Public key encryption with equality test (PKEET) is a cryptographic primitive that enables a tester to determine, without decryption, whether two ciphertexts encrypted with different public keys generate from the same message. In previous research, public key encryption with equality test (PKEET) was extended to include identity-based encryption with equality test (IBEET), thereby broadening the application of PKEET. Subsequently, certificateless encryption with equality test (CLEET) was introduced to address the key escrow problem in IBEET. However, existing CLEET schemes suffer from inefficiency and potential information leakage when dealing with multiple ciphertexts due to the need for pairwise equality tests. To address this issue, we propose a concept of certificateless encryption supporting multi-ciphertext equality test with proxy-assisted authorization (CLE-MET-PA). CLE-MET-PA incorporates the functionality of the multi-ciphertext equality test into CLEET, enabling a tester to perform a single equality test on multiple ciphertexts to determine whether the underlying plaintexts are equal, without revealing any additional information. This enhances the security of our scheme while significantly reducing the computational overhead compared to multiple pairwise equality tests, making our scheme more efficient. Additionally, our approach integrates proxy-assisted authorization, allowing users to delegate a proxy to grant authorizations for equality tests on their behalf when offline. Importantly, the proxy token used in our scheme does not include any portion of the user’s private key, providing enhanced protection compared to traditional PKEET schemes in which the user token is often part of the user’s private key. We construct a concrete CLE-MET-PA scheme and prove that it achieves CPA security and attains CCA security through an FO transformation.
Extraction, Enzymatic Modification, and Anti-Cancer Potential of an Alternative Plant-Based Protein from Wolffia globosa
Authors: Siriwat Warin , Ungwiwatkul Sunisa , Unban Kridsada , Laokuldilok Thunnop , Klunklin Warinporn , Tangjaidee Pipat , Potikanond Saranyapin , Kaur Lovedeep , Phongthai Suphat
Published: October 2023

The global plant-based protein demand is rapidly expanding in line with the increase in the world’s population. In this study, ultrasonic-assisted extraction (UAE) was applied to extract protein from Wolffia globosa as an alternative source. Enzymatic hydrolysis was used to modify the protein properties for extended use as a functional ingredient. The successful optimal conditions for protein extraction included a liquid to solid ratio of 30 mL/g, 25 min of extraction time, and a 78% sonication amplitude, providing a higher protein extraction yield than alkaline extraction by about 2.17-fold. The derived protein was rich in essential amino acids, including leucine, valine, and phenylalanine. Protamex and Alcalase were used to prepare protein hydrolysates with different degrees of hydrolysis, producing protein fragments with molecular weights ranging between <10 and 61.5 kDa. Enzymatic hydrolysis caused the secondary structural transformations of proteins from β-sheets and random coils to α-helix and β-turn structures. Moreover, it influenced the protein functional properties, particularly enhancing the protein solubility and emulsifying activity. Partial hydrolysis (DH3%) improved the foaming properties of proteins; meanwhile, an excess hydrolysis degree reduced the emulsifying stability and oil-binding capacity. The produced protein hydrolysates showed potential as anti-cancer peptides on human ovarian cancer cell lines.
Single Ultrasonic-Assisted Washing for Eco-Efficient Production of Mackerel (Auxis thazard) Surimi
Authors: Panpipat Worawan , Tongkam Pornthip , Çavdar Hasene Keskin , Chaijan Manat
Published: October 2023

This study highlights a promising single washing method for producing dark-fleshed mackerel surimi aided by ultrasonication in conjunction with cold carbonated water containing 0.6% NaCl and mixed antioxidants (0.5% EDTA/0.2% sodium erythorbate/0.2% sodium tripolyphosphate) (CSA). Different washing periods (5, 10, and 15 min) with and without ultrasound were tested. Unwashed mince (A1) and conventional water-washed surimi (10 min/cycle, 3 cycles) (A2) were used as controls. A3, A4, and A5 were subjected to ultrasound-assisted washing for 5, 10, and 15 min, respectively, whereas A6, A7, and A8 had non-ultrasound-assisted washing for 5, 10, and 15 min. Results showed that the surimi yield decreased as the ultrasonic treatment time increased from 5 to 15 min (p < 0.05). Increased ultrasonic time resulted in greater protein denaturation, protein oxidation, myoglobin removal, and lipid oxidation in surimi (p < 0.05). Surimi produced by CSA ultrasonication for 5 min (A3), on the other hand, had a comparable overall quality to A2 surimi (p > 0.05). The correspondence gel (A3) outperformed the control gel (A2) in terms of gel strength, whiteness, and water-holding capacity (p < 0.05). The formation of regularly continuous, more organized, and smooth network structures in surimi gel was observed in A2 and A3 gels, whereas sparse and larger pore sizes were noticed in surimi gels produced by longer ultrasonic treatment. All of the surimi gels had identical FTIR spectra, indicating that the functional groups of the protein gel were consistent throughout. As a result, a single 5 min CSA-ultrasonic washing could potentially yield surimi of comparable quality to conventional washing. This could pave the way for the development of dark-fleshed fish surimi, which would require less washing time and produce less waste water.
Effects of Lactic Acid Bacteria Fermentation on the Physicochemical Properties of Rice Flour and Rice Starch and on the Anti-Staling of Rice Bread
Authors: Dou Xinlai , Ren Xuyang , Zheng Qiumei , He Yinyuan , Lv Mingshou , Liu Linlin , Yang Ping , Hao Yanlin , Chen Fenglian , Tang Xiaozhi
Published: October 2023

In this study, Lactococcus lactis lactis subspecies 1.2472, Streptococcus thermophilus 1.2718, and thermostable Lactobacillus rhamnosus HCUL 1.1901–1912 were used to ferment rice flour for preparing rice bread. The characteristics of fermented rice bread were studied to elucidate the mechanism by which fermentation improves the anti-staling ability of rice bread. The amylose content of rice flour increased after fermentation. The peak viscosity, attenuation value, final viscosity, recovery value, and gelatinization temperature decreased. Amylopectin was partially hydrolyzed, and the amylose content decreased. The crystallinity of starch decreased, and the minimum crystallinity of Lactococcus lactis subsp. lactis fermented rice starch (LRS) was 11.64%. The thermal characteristics of fermented rice starch, including To, Tp, Tc, and ΔH, were lower than RS (rice starch), and the △H of LRS was the lowest. Meanwhile, LRS exhibited the best anti-staling ability, and with a staling degree of 43.22%. The T22 of the LRF rice flour dough was lower, and its moisture fluidity was the weakest, indicating that moisture was more closely combined with other components. The texture characteristics of fermented rice bread were improved; among these, LRF was the best: the hardness change value was 1.421 times, the elasticity decrease was 2.35%, and the chewability change was 47.07%. There, it provides a theoretical basis for improving the shelf life of bread.
Simultaneous Determination of 12 Preservatives in Pastries Using Gas Chromatography–Mass Spectrometry
Authors: Wang Liyuan , Hu Zhengyan , Chen Jing , Wang Tianjiao , Wu Pinggu , Ying Ying
Published: October 2023

(1) Background: Preservatives may pose a potential threat to human health. To ensure food safety, this study has devised a method that concurrently detects a dozen preservatives (acetic acid, propionic acid, dehydroacetic acid, benzoic acid, sorbic acid, dimethyl fumarate, methyl parahydroxybenzoate, ethyl parahydroxybenzoate, propyl parahydroxybenzoate, isopropyl parahydroxybenzoate, butyl parahydroxybenzoate, and isobutyl parahydroxybenzoate) in pastry, utilizing gas chromatography–mass spectrometry. (2) Methods: The pastry samples were acidified with hydrochloric acid, extracted with acetonitrile via vortexing, purified by hexane and saturated with sodium chloride solution to remove lipids and impurities, and then concentrated via nitrogen blowing. The method was then quantitatively analyzed using GC-MS with the internal standard method after methanol re-dissolution. (3) Results: The results showed that the content of the 12 preservatives had good linearity within the range of 1.0–50 μg/mL, with correlation coefficients all greater than 0.99. The method detection limit was 0.04–2.00 mg/kg and the quantification limit was 0.12–6.67 mg/kg. The average recovery rates of the samples at three different spiked concentrations of low, medium, and high were 70.18–109.22%, and the relative standard deviations were 1.82–9.79% (n = 6). (4) Conclusions: This method requires a small amount of sample, has high sensitivity, and is simple and fast to operate, making it suitable for the simultaneous determination of 12 preservatives in pastry. This approach contributes to the effective surveillance and regulation of preservative usage in pastries, thereby safeguarding public well-being.
Reference Array and Design Consideration for the Next-Generation Event Horizon Telescope
Authors: Doeleman Sheperd S. , Barrett John , Blackburn Lindy , Bouman Katherine L. , Broderick Avery E. , Chaves Ryan , Fish Vincent L. , Fitzpatrick Garret , Freeman Mark , Fuentes Antonio , Gómez José L. , Haworth Kari , Houston Janice , Issaoun Sara , Johnson Michael D. , Kettenis Mark , Loinard Laurent , Nagar Neil , Narayanan Gopal , Oppenheimer Aaron , Palumbo Daniel C. M. , Patel Nimesh , Pesce Dominic W. , Raymond Alexander W. , Roelofs Freek , Srinivasan Ranjani , Tiede Paul , Weintroub Jonathan , Wielgus Maciek
Published: October 2023

We describe the process to design, architect, and implement a transformative enhancement of the Event Horizon Telescope (EHT). This program—the next-generation Event Horizon Telescope (ngEHT)—will form a networked global array of radio dishes capable of making high-fidelity real-time movies of supermassive black holes (SMBH) and their emanating jets. This builds upon the EHT principally by deploying additional modest-diameter dishes to optimized geographic locations to enhance the current global mm/submm wavelength Very Long Baseline Interferometric (VLBI) array, which has, to date, utilized mostly pre-existing radio telescopes. The ngEHT program further focuses on observing at three frequencies simultaneously for increased sensitivity and Fourier spatial frequency coverage. Here, the concept, science goals, design considerations, station siting, and instrument prototyping are discussed, and a preliminary reference array to be implemented in phases is described.
Time-Series Variation of Landslide Expansion in Areas with a Low Frequency of Heavy Rainfall
Authors: Koshimizu Ken’ichi , Uchida Taro
Published: October 2023

After multiple simultaneous landslides caused by heavy rainfall, expanding landslides continue to occur for a certain duration. Evaluation of the influencing period of sediment yield due to expanding landslides is vital for comprehensive sediment management of the basin. In this study, we investigated a region with a low frequency of heavy rainfall that has not received its due level of attention until now. Consequently, the transition of expanding landslides depends on the transition of the number of remaining landslides, based on the difference in the frequency of heavy rainfall. Furthermore, the transition of expanding landslides depends on the maximum daily rainfall after the landslides. These findings indicate that “the number of remaining landslides” and “maximum daily rainfall after a landslide” are related factors that determine the period during which expanding landslides frequently occur. An estimation formula based on elapsed time was developed to calculate the number of remaining landslides. An empirical formula for the number of expanding landslides was obtained by multiplying the function of the daily maximum rainfall after the landslide by the estimation formula for the number of remaining landslides. The developed empirical formula can be used effectively for evaluation during periods when rainfall-induced landslides are subject to subsequent expansion.
The Burden of Urinary Tract Infections on Quality of Life and Healthcare in Patients with Interstitial Cystitis
Authors: Baars Cléo , van Ginkel Charlotte , Heesakkers John , Scholtes Mathilde , Martens Frank , Janssen Dick
Published: October 2023

Background: Interstitial cystitis/bladder pain syndrome (IC/BPS) patients are more susceptible to urinary tract infections (UTIs), likely worsening pre-existing symptoms. However, this receives limited attention in guidelines. This study aimed to explore the burden of UTIs on IC/BPS patients’ quality of life and their healthcare. Methods: Two quantitative retrospective database studies were conducted in cystoscopically proven IC/BPS patients: one compiled existing patient survey data (n = 217) from July 2021 to examine physical and emotional UTI burden, and the other used a patient file database (n = 100) from January 2020 to May 2022, focusing on UTI prevalence, healthcare use, urine cultures and antibiotic resistance. Results: A delay in diagnosis was seen in 70% of patients, due to doctors confusing IC/BPS symptoms with UTIs. The UTI prevalence was over 50%; these patients also report anxiety for new UTIs (70%) and worsening of IC/BPS symptoms (60%). Additionally, for UTI+ patients, healthcare consumption was significantly increased in both studies. Antibiotic resistance (80% of cultures) and prophylactic antibiotic use were common. Conclusions: These findings highlight the burden of UTIs on quality of life in IC/BPS patients and the healthcare system. These results emphasize the need for improved UTI guidelines concerning diagnosis, management and prevention for IC/BPS patients to improve quality of life and care.
Metal Complexes of Schiff Bases Prepared from Quinoline-3-Carbohydrazide with 2-Nitrobenzaldehyde, 2-Chlorobenzaldehyde and 2,4-Dihydroxybenzaldehyde: Structure and Biological Activity
Authors: Sunjuk Mahmoud , Al-Najjar Lana , Shtaiwi Majed , El-Eswed Bassam , Sweidan Kamal , Bernhardt Paul , Zalloum Hiba , Al-Essa Luay
Published: October 2023

Three Schiff base ligands, NQ, CQ and HQ, were prepared from the reaction of quinoline-3-carbohydrazide with 2-nitrobenzaldehyde, 2-chlorobenzaldehyde and 2,4-dihydroxybenzaldehyde, respectively, and were investigated for their coordination to Cu (II), Ni(II), Co(II), Cd(II), Cr(III) and Fe(III) chlorides. The NQ preparation and the X-ray structure of NQ and CQ, as well as the transition metal complexes of NQ, CQ and HQ, were reported for the first time. FTIR, 1H-NMR, magnetic susceptibility and elemental analysis were used to study the coordination of ligands to the metal ions. Based on the magnetic susceptibility and elemental analysis results, octahedral structures of the complexes such as [CuL2Cl(OH)], [FeL2Cl2(OH)] and [CoL2Cl(OH)] were proposed for L = NQ, CQ and HQ. The relatively large Cd(II) exhibited [CdL3(OH)2]. The FTIR study revealed that NQ and CQ are coordinated to the metal ions via azomethine nitrogen and carbonyl oxygen while HQ through azomethine nitrogen and phenolic oxygen. Despite the high solvation power of DMSO solvent in 1H-NMR experiments, the azomethine HC=N peak at 9.3 ppm is the most affected by complexation with metal ions. On the other hand, quinoline nitrogen seems to be a weaker coordinating site than the azomethine nitrogen. The HQ ligand, containing phenolic groups, and its complexes with Cu and Ni were found to have inhibitory effects on human breast adenocarcinoma MCF-7 and human chronic myelogenous leukemia K562. Nevertheless, metal ions did not exhibit a significant synergistic effect on the antiproliferative activity of the ligands investigated.