bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence and Classification of C-Shaped Canal and Radix in Mandibular Molars Using Cone-Beam Computed Tomography on Mexican Population
Authors: Armenta Hugo Bojorquez , Mireles Angel Gustavo Romo , Martinez Javier Solis , Alvarez Jesus Pescador , Herrera Yarely Ramos , Maldonado Omar Tremillo , Ojeda Oscar Almeda , Pacheco Jose Salas , Sarabia Gamaliel Ortiz , Castellanos-Juarez Francisco Xavier , Pacheco Sergio Salas
Published: July 2024

The diverse morphological configurations in teeth present clinical challenges in root canal treatment, complicating instrumentation and irrigation processes, which can lead to treatment failure. Understanding anatomical variations, such as C-shaped canals and radix entomolaris, enhances clinical skills and improves long-term endodontic treatment success rates. Cone-beam computed tomography (CBCT) offers superior diagnostic capabilities over conventional radiography, enabling the pre-operative detection of root configurations and canal numbers, facilitating personalized endodontic treatments. A total of 2173 teeth of a Mexican population, including 1057 first mandibular molars and 1116 s mandibular molars, were studied using only CBCT to identify C-shaped canals and radix configurations of patients who were treated from 2018 to 2023 at the Department of Radiology at the Faculty of Dentistry, Juarez University of the State of Durango, Mexico. C-shaped canals were identified in 160 teeth, with a prevalence of 0.2% in first mandibular molars and 14.1% in second mandibular molars. The highest frequency was in the left second mandibular molar (3.7) at 14.8%. Gender differences were significant, with higher prevalence in females (27.3%) compared to males (13.3%). The most common C-shaped canal configuration was type C2 (39.3%). Radix entomolaris was found in 52 teeth, with a prevalence of 3.4% in first mandibular molars and 1.4% in second mandibular molars. This research on a Mexican population using cone-beam computed tomography (CBCT) highlights significant findings in the prevalence and types of C-shaped canals and radix entomolaris in mandibular molars for this population. The left second mandibular molar (3.7) showed the highest prevalence at 14.8%, followed closely by the right second mandibular molar (4.7) at 13.5%, with a significant difference (p < 0.001). We found a significant difference in the prevalence of C-shaped canals between genders (p = 0.004, OR 1.78). Additionally, radix entomolaris (p < 0.001) was more frequently identified in first mandibular molars to a significant degree. These insights underscore the importance of CBCT in diagnosing complex root anatomies, which can greatly enhance the success rates of endodontic procedures by allowing for more tailored and precise treatments for this population.
Biswas–Chatterjee–Sen Model on Solomon Networks with Two Three-Dimensional Lattices
Authors: Oliveira Gessineide Sousa , Alves Tayroni Alencar , Alves Gladstone Alencar , Lima Francisco Welington , Plascak Joao Antonio
Published: July 2024

The Biswas–Chatterjee–Sen (BChS) model of opinion dynamics has been studied on three-dimensional Solomon networks by means of extensive Monte Carlo simulations. Finite-size scaling relations for different lattice sizes have been used in order to obtain the relevant quantities of the system in the thermodynamic limit. From the simulation data it is clear that the BChS model undergoes a second-order phase transition. At the transition point, the critical exponents describing the behavior of the order parameter, the corresponding order parameter susceptibility, and the correlation length, have been evaluated. From the values obtained for these critical exponents one can confidently conclude that the BChS model in three dimensions is in a different universality class to the respective model defined on one- and two-dimensional Solomon networks, as well as in a different universality class as the usual Ising model on the same networks.
Effective Temporal Graph Learning via Personalized PageRank
Authors: Liao Ziyu , Liu Tao , He Yue , Lin Longlong
Published: July 2024

Graph representation learning aims to map nodes or edges within a graph using low-dimensional vectors, while preserving as much topological information as possible. During past decades, numerous algorithms for graph representation learning have emerged. Among them, proximity matrix representation methods have been shown to exhibit excellent performance in experiments and scale to large graphs with millions of nodes. However, with the rapid development of the Internet, information interactions are happening at the scale of billions every moment. Most methods for similarity matrix factorization still focus on static graphs, leading to incomplete similarity descriptions and low embedding quality. To enhance the embedding quality of temporal graph learning, we propose a temporal graph representation learning model based on the matrix factorization of Time-constrained Personalize PageRank (TPPR) matrices. TPPR, an extension of personalized PageRank (PPR) that incorporates temporal information, better captures node similarities in temporal graphs. Based on this, we use Single Value Decomposition or Nonnegative Matrix Factorization to decompose TPPR matrices to obtain embedding vectors for each node. Through experiments on tasks such as link prediction, node classification, and node clustering across multiple temporal graphs, as well as a comparison with various experimental methods, we find that graph representation learning algorithms based on TPPR matrix factorization achieve overall outstanding scores on multiple temporal datasets, highlighting their effectiveness.
Feature-Enhanced Multi-Task Learning for Speech Emotion Recognition Using Decision Trees and LSTM
Authors: Wang Chun , Shen Xizhong
Published: July 2024

Speech emotion recognition (SER) plays an important role in human-computer interaction (HCI) technology and has a wide range of application scenarios in medical medicine, psychotherapy, and other applications. In recent years, with the development of deep learning, many researchers have combined feature extraction technology with deep learning technology to extract more discriminative emotional information. However, a single speech emotion classification task makes it difficult to effectively utilize feature information, resulting in feature redundancy. Therefore, this paper uses speech feature enhancement (SFE) as an auxiliary task to provide additional information for the SER task. This paper combines Long Short-Term Memory Networks (LSTM) with soft decision trees and proposes a multi-task learning framework based on a decision tree structure. Specifically, it trains the LSTM network by computing the distances of features at different leaf nodes in the soft decision tree, thereby achieving enhanced speech feature representation. The results show that the algorithm achieves 85.6% accuracy on the EMO-DB dataset and 81.3% accuracy on the CASIA dataset. This represents an improvement of 11.8% over the baseline on the EMO-DB dataset and 14.9% on the CASIA dataset, proving the effectiveness of the method. Additionally, we conducted cross-database experiments, real-time performance analysis, and noise environment analysis to validate the robustness and practicality of our method. The additional analyses further demonstrate that our approach performs reliably across different databases, maintains real-time processing capabilities, and is robust to noisy environments.
Control Strategy of Flywheel Energy Storage System for Improved Model Reference Adaptive System Based on Tent-Sparrow Search Algorithm
Authors: Song Gengling , Wu Zhenkui , Zheng Xuechen , Zhang Jihong , Yang Peihong , Zhang Zilei
Published: July 2024

This study addresses speed sensor aging and electrical parameter variations caused by prolonged operation and environmental factors in flywheel energy storage systems (FESSs). A model reference adaptive system (MRAS) flywheel speed observer with parameter identification capabilities is proposed to replace traditional speed sensors. The proposed method uses reference and adjustable models to identify the stator resistance and permanent magnet flux (PM Flux) to mitigate the adverse effects of electrical parameter changes on control performance. The Tent chaotic mapping-improved Sparrow Search Algorithm (SSA) optimizes the Proportional-Integral (PI) controller parameters for the dual closed-loop and MRAS speed adaptation laws of the flywheel motor. Moreover, a self-switching parameter identification (SSPI) scheme, which constructs a cost function based on the current, parameter identification, and speed errors, is proposed to prevent inaccuracies in parameter identification. The MRAS observer selects the appropriate PI adaptive mechanism based on the error values, thereby enhancing identification accuracy. Simulink simulations show significant improvements in the rapidity and accuracy of the Tent-SSA optimized MRAS flywheel speed observer, enhancing the stability and robustness of the flywheel rotor. Experimental validation on a constructed FESS platform confirms the feasibility of this method.
A Reference Paper Collection System Using Web Scraping
Authors: Naing Inzali , Aung Soe Thandar , Wai Khaing Hsu , Funabiki Nobuo
Published: July 2024

Collecting reference papers from the Internet is one of the most important activities for progressing research and writing papers about their results. Unfortunately, the current process using Google Scholar may not be efficient, since a lot of paper files cannot be accessed directly by the user. Even if they are accessible, their effectiveness needs to be checked manually. In this paper, we propose a reference paper collection system using web scraping to automate paper collections from websites. This system can collect or monitor data from the Internet, which is considered as the environment, using Selenium, a popular web scraping software, as the sensor; this examines the similarity against the search target by comparing the keywords using the Bert model. The Bert model is a deep learning model for natural language processing (NLP) that can understand context by analyzing the relationships between words in a sentence bidirectionally. The Python Flask is adopted at the web application server, where Angular is used for data presentations. For the evaluation, we measured the performance, investigated the accuracy, and asked members of our laboratory to use the proposed method and provide their feedback. Their results confirm the method’s effectiveness.
A Wideband Hybrid Envelope Tracking Supply Modulator with Slew-Rate-Enhanced Linear Amplifier
Authors: Zhang Kaida , Wu Jianhui , Zhuang Huabao , Shi Zhening , Lyu Xiaofeng , Wang Zhiyu , Chen Hua , Yu Faxin
Published: July 2024

A wideband hybrid envelope tracking supply modulator (HETSM) with a slew-rate-enhanced linear amplifier (LA) is described in this work. The proposed slew-rate enhancement (SRE) structure introduces a parallel auxiliary current path directly to the gate of the class-AB output stage, significantly accelerating the charging and discharging processes of the Miller capacitor without modifying the operating point of the remaining LA. The current delivered via this supplementary path shows a rapid increase, with changes in input voltage, culminating in diminished quiescent current levels. The supply modulator is fabricated in a 180 nm CMOS process. The measurement results show that HETSM is able to track a 100 MHz, 16QAM signal accurately, achieving the maximum efficiency of 87.4% at a 5.12 W output power, with a load that consists of a 5 Ω resistor and a paralleled 100 pF capacitor. The proposed LA realizes a slew rate of −1857/+1239 V/μs and a bandwidth of 226.6 MHz under a 24 mA quiescent current.
Handling Power Depletion in Energy Harvesting IoT Devices
Authors: Kang Young-myoung , Lim Yeon-sup
Published: July 2024

Efficient energy management is a significant task in Internet-of-Things (IoT) devices because typical IoT devices have the constraint of a limited power supply. In particular, energy harvesting IoT devices must be tolerant of complex and varying temporal/spatial environments for energy availability. Several schemes have been proposed to manage energy usage in IoT devices, such as duty-cycle control, transmission power control, and task scheduling. However, these approaches need to deal with the operating conditions particular to energy harvesting devices, e.g., power depletion according to energy harvesting conditions. In this paper, regarding a wireless sensor network (WSN) as a representative IoT device, we propose an Energy Intelligence Platform Module (EIPM) for energy harvesting WSNs. The EIPM provides harvested energy status prediction, checkpointing, and task execution control to ensure continuous operation according to energy harvesting conditions while minimizing required hardware/software overheads such as additional measurement components and computations. Our experiment results demonstrate that the EIPM successfully enables a device to cope with energy insufficiency under various harvesting conditions.
Driving Reality vs. Simulator: Data Distinctions
Authors: Piaseczna Natalia , Doniec Rafał , Sieciński Szymon , Barańska Klaudia , Jędrychowski Marek , Grzegorzek Marcin
Published: July 2024

As the automotive industry undergoes a phase of rapid transformation driven by technological advancements, the integration of driving simulators stands out as an important tool for research and development. The usage of such simulators offers a controlled environment for studying driver behavior; the alignment of data, however, remains a complex aspect that warrants a thorough investigation. This research investigates driver state classification using a dataset obtained from real-road and simulated conditions, recorded through JINS MEME ES_R smart glasses. The dataset encompasses electrooculography signals, with a focus on standardizing and processing the data for subsequent analysis. For this purpose, we used a recurrent neural network model, which yielded a high accuracy on the testing dataset (86.5%). The findings of this study indicate that the proposed methodology could be used in real scenarios and that it could be used for the development of intelligent transportation systems and driver monitoring technology.
TRNSYS Simulation of a Bi-Functional Solar-Thermal-Energy-Storage-Assisted Heat Pump System
Authors: Wang Mingzhen , Hu Eric , Chen Lei
Published: July 2024

The escalating energy demands in buildings, particularly for heating and cooling demands met by heat pumps, have placed a growing stress on energy resources. The bi-functional thermal diode tank (BTDT) is proposed as thermal energy storage to improve the heating and cooling performances of heat pumps in both summer and winter. The BTDT is an insulated water tank with a gravity heat pipe (GHP), which can harvest and store heat passively from sun radiation and the external environment during the daytime. In summer, it harvests and stores cold energy from the air and night sky during the daytime. The performance of the BTDT-assisted heat pump (BTDT-HP) system in Adelaide, Australia, during the 2021–2022 summer and winter seasons was evaluated by conducting a TRNSYS simulation. This study revealed that the BTDT-HP system outperformed the reference ASHP system, where up to 8% energy in heating and 39.75% energy in cooling could be saved. An overall reduction in the energy consumption of 18.89% was achieved. Increasing the BTDT volume and GHP panel area enabled the tank to store more thermal and cold energy across the winter and summer seasons, thereby improving the system’s performance. The maximum ESPs were found to be 31.6% and 41.2% for heating and cooling for the study case under optimal conditions. When the GHP panel area was fixed at 15 m2, the BTDT volume should be at least 28 m3 for the BTDT-HP system, boasting cooling and heating capacities of 40 kW and 43.2 kW, to achieve positive energy savings.
The Effect of Residence Time during the Hydrothermal Carbonization Process of Sewage Sludge on the Properties of Hydrochar
Authors: Czerwińska Klaudia , Mikusińska Joanna , Błoniarz Aleksandra , Śliz Maciej , Wilk Małgorzata
Published: July 2024

The optimal process conditions concerning the hydrothermal carbonization of digested sewage sludge are crucial to the economically effective technology needed to produce a solid product, hydrochar, for energy purposes. Accordingly, different residence times, 0.5 h, 1 h and 2 h, were investigated in order to understand the effect of residence time on the process. Furthermore, the physical and chemical properties of hydrochar were investigated and compared to the raw material. For these reasons, analyses describing fuel properties were performed, including ultimate and proximate analyses, HHV, and TGA analysis. The latter method was employed to study the combustion process of solid samples. In addition, the oxide content of different elements within the ash of solid samples was determined using the XRF method to calculate indices related to operational problems during the combustion process. The results confirmed that time did not matter significantly and the physical and chemical properties of hydrochar were very similar to each other. However, the contact angle for 2 h of residence time confirmed that a longer processing time resulted in a more hydrophobic character of hydrochar and enabled more effective dewaterability of hydrothermal slurry. It was also noted that the hydrothermal carbonization process affected the sewage sludge in a positive way. In brief, the results confirmed that the hydrochar was a brittle, moderately hydrophilic, solid carbon-containing product that provided a different combustion performance than the raw sewage sludge.
The Distributed Parameter Model of an Electro-Pneumatic System Actuated by Pneumatic Artificial Muscles with PWM-Based Position Control
Authors: Kotkas Lyubov , Donskoy Anatolij , Zharkovskii Aleksandr , Zhurkin Nikita
Published: July 2024

Today, the analysis and synthesis methods of electro-pneumatic systems with position control actuated by pneumatic artificial muscles (PAMs) are quite well known. In these methods, pneumatic artificial muscle is considered as an object with lumped parameters. However, the PAM is an object with distributed parameters, where the pressure, density, and mass flow rate of gas are varied along the bladder length. Thus, in the case of certain design parameters of the pneumatic artificial muscle and certain frequencies of the supply pressure, resonant gas oscillations affected by the wave processes in the bladder may occur. Thereby, in the PWM-driven PAM-actuated system, certain operation frequencies of the control pneumatic valve can cause oscillations of gas in the bladder and in the connected pipeline. These processes could lead to vibrations of the executive device. To solve this practical problem, a distributed parameter model of the PAM that takes into account the pressure fluctuations in the bladder and in the pipeline was elaborated. Also, in this work, a new method in which the wave processes are described by ordinary differential equations instead of partial differential equations was proposed.
Reducing CO2 Emissions through the Strategic Optimization of a Bulk Carrier Fleet for Loading and Transporting Polymetallic Nodules from the Clarion-Clipperton Zone
Authors: Cepowski Tomasz , Kacprzak Paweł
Published: July 2024

As global maritime cargo transportation intensifies, managing CO2 emissions from ships becomes increasingly crucial. This article explores optimizing bulk carrier fleets for transporting polymetallic nodules (PMNs) from the Clarion-Clipperton Zone (CCZ) to reduce CO2 emissions. Our analysis shows that larger bulk carriers, despite greater drifting forces from environmental conditions, emit less CO2 over the entire transport mission, including loading and transit. Deploying large ships in global maritime trade could significantly reduce CO2 emissions. This study also introduces a novel artificial neural network (ANN) model to estimate drifting forces during loading operations and proposes a new method for estimating CO2 emissions, considering environmental conditions and ship seakeeping properties. These findings highlight the importance of fleet size optimization and effective operational planning in achieving environmental sustainability in maritime transport.
Recent Advancements in Geothermal Energy Piles Performance and Design
Authors: Khalil Ahmed , Attom Mousa , Khan Zahid , Astillo Philip Virgil , El-Kadri Oussama M.
Published: July 2024

Geothermal energy piles or ground heat exchange (GHE) systems embrace a sustainable source of energy that utilizes the geothermal energy naturally found inside the ground in order to heat and/or cool buildings. GHE is a highly innovative system that consists of energy loops within foundation elements (shallow foundations or piles) through which a heat carrier fluid circulates, enabling heat extraction or storage in the ground. Despite the innovation and potential of GHE systems, there are significant challenges in harmonizing their thermal and mechanical designs due to the complex interactions involved. This review critically examines state-of-the-art design methodologies developed to address these complexities, providing insights into the most recent advancements in GHE performance and design. Key findings include innovative techniques such as advanced numerical modeling to predict thermomechanical behavior, the use of different pipe configurations to optimize heat transfer, and strategies to minimize thermal stress on the foundation. Additionally, this review identifies research gaps, including the need for more comprehensive full-scale experimental validations, the impact of soil properties on system performance, and the long-term effects of thermal cycling on pile integrity. These insights aim to contribute to a better understanding of the thermomechanical behavior of energy piles, ultimately facilitating more accurate and effective design solutions.
The Evolution of Flow Structures and Coolant Coverage in Double-Row Film Cooling with Upstream Forward Jets and Downstream Backward Jets
Authors: Shangguan Yanqin , Cao Fei
Published: July 2024

The spatiotemporal evolution of the flow structures and coolant coverage of double-row film cooling with upstream forward jets and downstream backward jets, having a significant impact on film-cooling performance, is studied using the simplified thermal lattice Boltzmann method (STLBM). Moreover, the effect of the inclination angle of downstream backward jets is considered. The high-performance simulations of film cooling have been conducted by using our verified in-house solver. Results show that special flow structures, such as a sand dune-shaped protrusion, appear in double-row film cooling with upstream forward jets and downstream backward jets, which is mainly because of the blockage effect resulting from the coolant jet with backward injection. The interaction among structures results in the generation of an anti-counterrotating vortex pair (anti-CVP). The anti-CVP with the downwash motion can result in the attachment of coolant to the bottom wall, which promotes the stability and lateral coverage of coolant film. The momentum and heat transport are strengthened as the backward jet is injected into the boundary layer of the mainstream. Although the downstream evolution of the backward jet is not very smooth, its core attaches closely to the bottom wall due to the downwash motion of anti-CVP. Moreover, there is an obvious backflow zone shown in the trailing edge of the downstream backward jet with a large inclination angle. The obvious backflow makes the coolant attach to the bottom wall well. Therefore, the film cooling effectiveness is improved as the inclination angle of the downstream backward jet varies from αdown=135° to αdown=155°, with a constant blowing ratio of BR=0.5. In addition, the fluctuation of the bottom wall’s temperature is weak due to the stable coverage of the coolant layer under αdown=155°. The film-cooling performance with an inclination angle of αdown=155° is the best among all the cases studied in this work. This work provides essential insights into film cooling with backward coolant injection and contributes to obtaining a complete understanding of film cooling with backward coolant injection.
The Role of Blockchain-Secured Digital Twins in Promoting Smart Energy Performance-Based Contracts for Buildings
Authors: Nour El-Din Mohamed , Poças Martins João , Ramos Nuno M. M. , Pereira Pedro F.
Published: July 2024

Energy performance-based contracts (EPCs) offer a promising solution for enhancing the energy performance of buildings, which is an overarching step towards achieving Net Zero Carbon Buildings, addressing climate change and improving occupants’ comfort. Despite their potential, their execution is constrained by difficulties that hinder their diffusion in the architecture, engineering, construction, and operation industry. Notably, the Measurement and Verification process is considered a significant impediment due to data sharing, storage, and security challenges. Nevertheless, there have been minimal efforts to analyze research conducted in this field systematically. A systematic analysis of 113 identified journal articles was conducted to fill this gap. A paucity of research tackling the utilization of digital technologies to enhance the implementation of EPCs was found. Consequently, this article proposes a framework integrating Digital Twin and Blockchain technologies to provide an enhanced EPC execution environment. Digital Twin technology leverages the system by monitoring and evaluating energy performance in real-time, predicting future performance, and facilitating informed decisions. Blockchain technology ensures the integrity, transparency, and accountability of information. Moreover, a private Blockchain infrastructure was originally introduced in the framework to eliminate high transaction costs related to on-chain storage and potential concerns regarding the confidentiality of information in open distributed ledgers.
Numerical Simulation Method for the Aeroelasticity of Flexible Wind Turbine Blades under Standstill Conditions
Authors: Wu Xianyou , Liu Rongxiang , Li Yan , Lv Pin , Gao Chuanqiang , Feng Kai
Published: July 2024

With the trend towards larger and lighter designs of wind turbines, blades are progressively being developed to have longer and more flexible configurations. Under standstill conditions, the separated flow induced by a wide range of incident flow angles can cause complex aerodynamic elastic phenomena on blades. However, classical momentum blade element theory methods show limited applicability at high angles of attack, leading to significant inaccuracies in wind turbine performance prediction. In this paper, the geometrically accurate beam theory and high-fidelity CFD method are combined to establish a bidirectional fluid–structure coupling model, which can be used for the prediction of the aeroelastic response of wind turbine blades and the analysis of fluid–structure coupling. Aeroelastic calculations are carried out for a single blade under different working conditions to analyze the influence of turbulence, gravity and other parameters on the aeroelastic response of the blade. The results show that the dominant frequency of the vibration deformation response in the edgewise direction is always the same as the first-order edgewise frequency of the blade when the incoming flow condition is changed. The loading of gravity will make the aeroelastic destabilization of the blade more significant, which indicates that the influence of gravity should be taken into account in the design of the aeroelasticity of the wind turbine. Increasing the turbulence intensity will change the dominant frequency of the vibration response in the edgewise direction, and at the same time, it will be beneficial to the stabilization of the aeroelasticity response.
Variability of Water Use Efficiency of Gmelina arborea Plantations in the Tropical Dry Forest of Colombia
Authors: López Aguirre Ana Milena , Barrios Trilleras Alonso
Published: July 2024

Effective forest management strategies to adapt to climate change are essential. Water use efficiency (WUE), which integrates biomass production and water consumption, is a key indicator of forest adaptation. This study evaluated the WUE of Gmelina arborea plantations in the tropical dry forest and identified the main influencing factors, with implications for silviculture and management. Data on total biomass (TB) and total volume (V) were obtained from permanent sample plots in the upper and lower Magdalena River basin in Colombia. WUE was calculated as m3 of V (WUEV) or kg of TB (WUETB) per m3 of evapotranspired water. Significant regional differences were found, with higher WUE in the Caribbean plains (WUETB = 1 kg m−3 and WUEV = 0.0018 m3 m−3) compared to the inter-Andean valleys (WUETB = 0.77 kg m−3 and WUEV = 0.013 m3 m−3). Stand variables had the greatest influence on WUE, showing positive associations with site productivity and stand density measures. Soil variables such as texture, available water, and calcium content, along with a drier climate, were crucial for achieving higher WUE. The study underscores the importance of comprehensive site selection and effective silvicultural practices to maximize WUE and productivity, especially in the context of climate change.
Modifications of the Structural, Nutritional, and Allergenic Properties of Atlantic Cod Induced by Novel Thermal Glycation Treatments
Authors: Dong Xin , Raghavan Vijaya
Published: July 2024

This study aimed to assess the effect of novel thermal glycation, utilizing microwave processing (100−150 °C) combined with sugars (glucose and lactose), on the in vitro protein digestibility, peptides, secondary structures, microstructures, and allergenic properties of Atlantic cod. The research demonstrated that microwave heating at 150 °C with glucose significantly reduced cod allergenicity by up to 16.16%, while also enhancing in vitro protein digestibility to 69.05%. Glucose was found to be more effective than lactose in conjunction with microwave heating in reducing the allergenicity of Atlantic cod. Moreover, treatments conducted at 150 °C were more effective in increasing in vitro protein digestibility and peptide content compared to those at 100 °C. This study revealed that the novel processing technique of thermal glycation effectively reduced the allergenicity of Atlantic cod. It also offered fresh insights into the potential benefits of combining microwave heating with sugars.
Globally Optimal Relative Pose and Scale Estimation from Only Image Correspondences with Known Vertical Direction
Authors: Yu Zhenbao , Ye Shirong , Liu Changwei , Jin Ronghe , Xia Pengfei , Yan Kang
Published: July 2024

Installing multi-camera systems and inertial measurement units (IMUs) in self-driving cars, micro aerial vehicles, and robots is becoming increasingly common. An IMU provides the vertical direction, allowing coordinate frames to be aligned in a common direction. The degrees of freedom (DOFs) of the rotation matrix are reduced from 3 to 1. In this paper, we propose a globally optimal solver to calculate the relative poses and scale of generalized cameras with a known vertical direction. First, the cost function is established to minimize algebraic error in the least-squares sense. Then, the cost function is transformed into two polynomials with only two unknowns. Finally, the eigenvalue method is used to solve the relative rotation angle. The performance of the proposed method is verified on both simulated and KITTI datasets. Experiments show that our method is more accurate than the existing state-of-the-art solver in estimating the relative pose and scale. Compared to the best method among the comparison methods, the method proposed in this paper reduces the rotation matrix error, translation vector error, and scale error by 53%, 67%, and 90%, respectively.
Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria
Authors: Lee Jiyoung , Leitner Michael , Paulus Gernot
Published: July 2024

Studying the spatiotemporal dynamics of crime is crucial for accurate crime geography research. While studies have examined crime patterns related to weekdays, seasons, and specific events, there is a noticeable gap in research on nighttime crimes. This study focuses on crimes occurring during the nighttime, investigating the temporal definition of nighttime crime and the correlation between nighttime lights and criminal activities. The study concentrates on four types of nighttime crimes, assault, theft, burglary, and robbery, conducting univariate and multivariate analyses. In the univariate analysis, correlations between nighttime crimes and nighttime light (NTL) values detected in satellite images and between streetlight density and nighttime crimes are explored. The results highlight that nighttime burglary strongly relates to NTL and streetlight density. The multivariate analysis delves into the relationships between each nighttime crime type and socioeconomic and urban infrastructure variables. Once again, nighttime burglary exhibits the highest correlation. For both univariate and multivariate regression models the geographically weighted regression (GWR) outperforms ordinary least squares (OLS) regression in explaining the relationships. This study underscores the importance of considering the location and offense time in crime geography research and emphasizes the potential of using NTL in nighttime crime analysis.
Methodology of Mosaicking and Georeferencing for Multi-Sheet Early Maps with Irregular Cuts Using the Example of the Topographic Chart of the Kingdom of Poland
Authors: Kuna Jakub , Panecki Tomasz , Zawadzki Mateusz
Published: July 2024

The Topographic Chart of the Kingdom of Poland (pol. Topograficzna Karta Królestwa Polskiego, commonly referred to as ‘the Quartermaster’s Map’, hereinafter: TKKP) is the first Polish modern topographic map of Poland (1:126,000, 1843). Cartographic historians acclaim its conception by the General Quartermaster of the Polish Army, noting its editorial principles and technical execution as exemplars of the early 19th-century cartographic standards. Today, it stands as a national heritage relic, furnishing invaluable insights into the former Polish Kingdom’s topography. Although extensively utilised in geographical and historical inquiries, the TKKP has yet to undergo a comprehensive geomatic investigation and publication as spatial data services. Primarily, this delay stems from the challenges of mosaicking and georeferencing its 60 constituent sheets, owing to the uncertain mathematical framework and irregular sheet cuts. In 2023, the authors embarked on rectifying this by creating a unified TKKP mosaic and georeferencing the map to contemporary reference data benchmarks. This endeavour involved scrutinising the map’s mathematical accuracy and verifying prior findings. The resultant product is accessible via the ‘Maps with the Past’ platform, developed by the Institute of History of the Polish Academy of Sciences The dissemination of raster data services adhering to OGC standards such as WMTS (Web Map Tile Service), ECW (Enhanced Compression Wavelet), and COG (Cloud Optimized GeoTIFF) facilitates the swift and seamless integration of the generated data into web and GIS tools. The digital edition of the TKKP emerges as a pivotal resource for investigations spanning natural and anthropogenic environmental transformations, sustainable development, and cultural heritage studies.
Oxidative Metabolism as a Cause of Lipid Peroxidation in the Execution of Ferroptosis
Authors: Fujii Junichi , Imai Hirotaka
Published: July 2024

Ferroptosis is a type of nonapoptotic cell death that is characteristically caused by phospholipid peroxidation promoted by radical reactions involving iron. Researchers have identified many of the protein factors that are encoded by genes that promote ferroptosis. Glutathione peroxidase 4 (GPX4) is a key enzyme that protects phospholipids from peroxidation and suppresses ferroptosis in a glutathione-dependent manner. Thus, the dysregulation of genes involved in cysteine and/or glutathione metabolism is closely associated with ferroptosis. From the perspective of cell dynamics, actively proliferating cells are more prone to ferroptosis than quiescent cells, which suggests that radical species generated during oxygen-involved metabolism are responsible for lipid peroxidation. Herein, we discuss the initial events involved in ferroptosis that dominantly occur in the process of energy metabolism, in association with cysteine deficiency. Accordingly, dysregulation of the tricarboxylic acid cycle coupled with the respiratory chain in mitochondria are the main subjects here, and this suggests that mitochondria are the likely source of both radical electrons and free iron. Since not only carbohydrates, but also amino acids, especially glutamate, are major substrates for central metabolism, dealing with nitrogen derived from amino groups also contributes to lipid peroxidation and is a subject of this discussion.
Neuroprotection of Transcranial Cortical and Peripheral Somatosensory Electrical Stimulation by Modulating a Common Neuronal Death Pathway in Mice with Ischemic Stroke
Authors: Lee Hongju , Lee Juyeon , Jung Dahee , Oh Harim , Shin Hwakyoung , Choi Byungtae
Published: July 2024

Therapeutic electrical stimulation, such as transcranial cortical stimulation and peripheral somatosensory stimulation, is used to improve motor function in patients with stroke. We hypothesized that these stimulations exert neuroprotective effects during the subacute phase of ischemic stroke by regulating novel common signaling pathways. Male C57BL/6J mouse models of ischemic stroke were treated with high-definition (HD)-transcranial alternating current stimulation (tACS; 20 Hz, 89.1 A/mm2), HD-transcranial direct current stimulation (tDCS; intensity, 55 A/mm2; charge density, 66,000 C/m2), or electroacupuncture (EA, 2 Hz, 1 mA) in the early stages of stroke. The therapeutic effects were assessed using behavioral motor function tests. The underlying mechanisms were determined using transcriptomic and other biomedical analyses. All therapeutic electrical tools alleviated the motor dysfunction caused by ischemic stroke insults. We focused on electrically stimulating common genes involved in apoptosis and cell death using transcriptome analysis and chose 11 of the most potent targets (Trem2, S100a9, Lgals3, Tlr4, Myd88, NF-kB, STAT1, IL-6, IL-1β, TNF-α, and Iba1). Subsequent investigations revealed that electrical stimulation modulated inflammatory cytokines, including IL-1β and TNF-α, by regulating STAT1 and NF-kB activation, especially in amoeboid microglia; moreover, electrical stimulation enhanced neuronal survival by activating neurotrophic factors, including BDNF and FGF9. Therapeutic electrical stimulation applied to the transcranial cortical- or periphery-nerve level to promote functional recovery may improve neuroprotection by modulating a common neuronal death pathway and upregulating neurotrophic factors. Therefore, combining transcranial cortical and peripheral somatosensory stimulation may exert a synergistic neuroprotective effect, further enhancing the beneficial effects on motor deficits in patients with ischemic stroke.
Efficient In Vitro Regeneration System and Comparative Transcriptome Analysis Offer Insight into the Early Development Characteristics of Explants from Cotyledon with Partial Petiole in Small-Fruited Pepper (Capsicum annuum)
Authors: Li Xiaoqi , Mushtaq Naveed , Xing Na , Wu Shuhua , Liu Jiancheng , Wang Zhiwei
Published: July 2024

In our research, we utilized six small-fruited pepper germplasms as materials, selected cotyledons with the petiole and hypocotyls as explants, and conducted in vitro regeneration studies. Our outcomes specify that the most suitable explant is cotyledon with the petiole, and the suitable genotype is HNUCA341. The optimal medium for inducing and elongating adventitious buds for this genotype is Murashige and Skoog medium (MS) + 9.12 μM Zeatin (ZT) + 0.57 μM 3-Indoleacetic acid (IAA), with a bud induction rate of 44.4%. The best rooting induction medium is MS + 1.14 μM IAA, with a rooting rate of 86.7%. Research on the addition of exogenous hormones has revealed that the induction speed of buds in small-fruited pepper (HNUCA341) in the combination of ZT and IAA hormones (abbreviated as ZI) is quicker, and the induction effect is better. The histological observations indicate that ZI treatment accelerates the initiation of explant division and differentiation, causing a shorter duration of vascular-bundle tissue production. The plant hormone signaling pathway was significantly enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, including ARR9 (LOC107843874, LOC107843885), ARR4 (LOC107848380, LOC107862455), AHK4 (LOC107870540), AHP1 (LOC107839518), LAX2 (LOC107846008), SAUR36 (LOC107852624), IAA8 (LOC107841020), IAA16 (LOC107839415), PYL4 (LOC107843441), and PYL6 (LOC107871127); these significantly enriched genes may be associated with in vitro regeneration. In addition, the carbon metabolism pathway and plant mitogen-activated protein kinase (MAPK) signaling pathway are also significantly enriched in KEGG. The results of the Gene Ontology (GO) analysis revealed that differentially expressed genes related to carbon metabolism and fixation, photosynthesis and MAPK signaling pathways were upregulated under ZI treatment. It was found that they might be associated with enhanced regeneration in vitro. Furthermore, we also screened out differentially expressed transcription factors, primarily from the MYB, bHLH, AP2/ERF, and NAC families. Overall, our work accumulated important data for the in-depth analysis of the molecular mechanism of in vitro regeneration of pepper, and provides valuable germplasm for establishing an efficient stable pepper genetic-transformation system based on tissue culture.
Identifying Diagnostic Markers and Constructing Predictive Models for Oxidative Stress in Multiple Sclerosis
Authors: Ma Yantuanjin , Wang Fang , Zhao Qiting , Zhang Lili , Chen Shunmei , Wang Shufen
Published: July 2024

Multiple sclerosis (MS) is a chronic disease characterized by inflammation and neurodegeneration of the central nervous system. Despite the significant role of oxidative stress in the pathogenesis of MS, its precise molecular mechanisms remain unclear. This study utilized microarray datasets from the GEO database to analyze differentially expressed oxidative-stress-related genes (DE-OSRGs), identifying 101 DE-OSRGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicate that these genes are primarily involved in oxidative stress and immune responses. Through protein–protein interaction (PPI) network, LASSO regression, and logistic regression analyses, four genes (MMP9, NFKBIA, NFKB1, and SRC) were identified as being closely related to MS. A diagnostic prediction model based on logistic regression demonstrated good predictive power, as shown by the nomogram curve index and DAC results. An immune-cell infiltration analysis using CIBERSORT revealed significant correlations between these genes and immune cell subpopulations. Abnormal oxidative stress and upregulated expression of key genes were observed in the blood and brain tissues of EAE mice. A molecular docking analysis suggested strong binding potentials between the proteins of these genes and several drug molecules, including isoquercitrin, decitabine, benztropine, and curcumin. In conclusion, this study identifies and validates potential diagnostic biomarkers for MS, establishes an effective prediction model, and provides new insights for the early diagnosis and personalized treatment of MS.
Impact of Maternal Pre-Pregnancy Underweight on Cord Blood Metabolome: An Analysis of the Population-Based Survey of Neonates in Pomerania (SNiP)
Authors: Lichtwald Alexander , Ittermann Till , Friedrich Nele , Lange Anja Erika , Winter Theresa , Kolbe Claudia , Allenberg Heike , Nauck Matthias , Heckmann Matthias
Published: July 2024

Intrauterine growth restriction leads to an altered lipid and amino acid profile in the cord blood at the end of pregnancy. Pre-pregnancy underweight is an early risk factor for impaired fetal growth. The aim of this study was to investigate whether a pre-pregnancy body mass index (ppBMI) of <18.5 kg/m2, as early as at the beginning of pregnancy, is associated with changes in the umbilical cord metabolome. In a sample of the Survey of Neonates in Pomerania (SNIP) birth cohort, the cord blood metabolome of n = 240 newborns of mothers with a ppBMI of <18.5 kg/m2 with n = 208 controls (ppBMI of 18.5–24.9 kg/m2) was measured by NMR spectrometry. A maternal ppBMI of <18.5 kg/m2 was associated with increased concentrations of HDL4 cholesterol, HDL4 phospholipids, VLDL5 cholesterol, HDL 2, and HDL4 Apo-A1, as well as decreased VLDL triglycerides and HDL2 free cholesterol. A ppBMI of <18.5 kg/m2 combined with poor intrauterine growth (a gestational weight gain (GWG) < 25th percentile) was associated with decreased concentrations of total cholesterol; cholesterol transporting lipoproteins (LDL4, LDL6, LDL free cholesterol, and HDL2 free cholesterol); LDL4 Apo-B; total Apo-A2; and HDL3 Apo-A2. In conclusion, maternal underweight at the beginning of pregnancy already results in metabolic changes in the lipid profile in the cord blood, but the pattern changes when poor GWG is followed by pre-pregnancy underweight.
Aprotinin (I): Understanding the Role of Host Proteases in COVID-19 and the Importance of Pharmacologically Regulating Their Function
Authors: Padín Juan Fernando , Pérez-Ortiz José Manuel , Redondo-Calvo Francisco Javier
Published: July 2024

Proteases are produced and released in the mucosal cells of the respiratory tract and have important physiological functions, for example, maintaining airway humidification to allow proper gas exchange. The infectious mechanism of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), takes advantage of host proteases in two ways: to change the spatial conformation of the spike (S) protein via endoproteolysis (e.g., transmembrane serine protease type 2 (TMPRSS2)) and as a target to anchor to epithelial cells (e.g., angiotensin-converting enzyme 2 (ACE2)). This infectious process leads to an imbalance in the mucosa between the release and action of proteases versus regulation by anti-proteases, which contributes to the exacerbation of the inflammatory and prothrombotic response in COVID-19. In this article, we describe the most important proteases that are affected in COVID-19, and how their overactivation affects the three main physiological systems in which they participate: the complement system and the kinin–kallikrein system (KKS), which both form part of the contact system of innate immunity, and the renin–angiotensin–aldosterone system (RAAS). We aim to elucidate the pathophysiological bases of COVID-19 in the context of the imbalance between the action of proteases and anti-proteases to understand the mechanism of aprotinin action (a panprotease inhibitor). In a second-part review, titled “Aprotinin (II): Inhalational Administration for the Treatment of COVID-19 and Other Viral Conditions”, we explain in depth the pharmacodynamics, pharmacokinetics, toxicity, and use of aprotinin as an antiviral drug.