bluuebunny/crossref_metadata_2025 huggingface dataset:
Intrapulmonary and Systemic Pharmacokinetics of Colistin Following Nebulization of Low-Dose Colistimethate Sodium in Patients with Ventilator-Associated Pneumonia Caused by Carbapenem-Resistant Acinetobacter baumannii
Authors: Lee Dong-Hwan , Kim Shin-Young , Kim Yong-Kyun , Jung So-Young , Jang Ji-Hoon , Jang Hang-Jea , Lee Jae-Ha
Published: March 2024

Colistimethate sodium (CMS) nebulization is associated with reduced systemic toxicity compared to intravenous injection, with potentially enhanced clinical efficacy. This study aimed to assess the pharmacokinetic (PK) properties of colistin during low-dose CMS nebulization in patients with ventilator-associated pneumonia (VAP) caused by carbapenem-resistant Acinetobacter baumannii. A nonlinear mixed-effects modeling approach was applied to develop population PK models for colistin in both epithelial lining fluid (ELF) and plasma. Twenty patients participated, and 80 ELF and 100 plasma samples were used for model development. Median colistin concentrations measured in ELF were 614-fold, 408-fold, and 250-fold higher than in plasma at 1, 3, and 5 h, respectively. Time courses in both ELF and plasma were best described by a one-compartment model with a Weibull absorption process. When the final model was simulated, the maximum free concentration and area under the free colistin concentration–time curve at steady state over 24 h in the plasma were approximately 1/90 and 1/50 of the corresponding values in ELF at steady state, respectively. For an A. baumannii MIC of 1 mg/L, inhaling 75 mg of CMS at 6 h intervals was deemed appropriate, with dose adjustments needed for MICs exceeding 2 mg/L. Using a nebulizer for CMS resulted in a notably higher exposure of colistin in the ELF than plasma, indicating the potential of nebulization to reduce systemic toxicity while effectively treating VAP.
Role of β-Lactamase Inhibitors as Potentiators in Antimicrobial Chemotherapy Targeting Gram-Negative Bacteria
Authors: Zhang Song , Liao Xinyu , Ding Tian , Ahn Juhee
Published: March 2024

Since the discovery of penicillin, β-lactam antibiotics have commonly been used to treat bacterial infections. Unfortunately, at the same time, pathogens can develop resistance to β-lactam antibiotics such as penicillins, cephalosporins, monobactams, and carbapenems by producing β-lactamases. Therefore, a combination of β-lactam antibiotics with β-lactamase inhibitors has been a promising approach to controlling β-lactam-resistant bacteria. The discovery of novel β-lactamase inhibitors (BLIs) is essential for effectively treating antibiotic-resistant bacterial infections. Therefore, this review discusses the development of innovative inhibitors meant to enhance the activity of β-lactam antibiotics. Specifically, this review describes the classification and characteristics of different classes of β-lactamases and the synergistic mechanisms of β-lactams and BLIs. In addition, we introduce potential sources of compounds for use as novel BLIs. This provides insights into overcoming current challenges in β-lactamase-producing bacteria and designing effective treatment options in combination with BLIs.
Two-Generation Toxicity Study of the Antioxidant Compound Propyl-Propane Thiosulfonate (PTSO)
Authors: Cascajosa-Lira Antonio , Guzmán-Guillén Remedios , Pichardo Silvia , Baños Alberto , de la Torre Jose , Ayala-Soldado Nahum , Moyano-Salvago M. , Ortiz-Jaraba Isabel , Cameán Ana , Jos Angeles
Published: March 2024

Propyl-propane thiosulfonate (PTSO), an antioxidant organosulfur compound present in the genus Allium, has become a potential natural additive for food and feed, as well as a possible biopesticide for pest control in plants. A toxicological assessment is necessary to verify its safety for livestock, consumers, and the environment. As part of the risk assessment of PTSO, this study was designed to explore its potential reproductive toxicity in mice following the OECD 416 guideline. The investigation spans two generations to comprehensively evaluate potential reproductive, teratogenic, and hereditary effects. A total of 80 CD1 mice per sex and generation were subjected to PTSO exposure during three phases (premating, gestation, and lactation). This evaluation encompassed three dose levels: 14, 28, and 55 mg PTSO/kg b.w./day, administered through the feed. No clinical changes or mortality attributed to the administration of PTSO were observed in the study. Some changes in the body weight and food consumption were observed, but not related to sex or in a dose-dependent manner. The two parental generations (F0, F1) exhibited normal reproductive performance, and the offspring (F1 and F2) were born without any abnormalities. The serum sexual hormone levels (progesterone -P-, testosterone -T-, estradiol -E2-, follicular stimulating hormone -FSH-, and luteinizing hormone -LH-) were in a normal range. Although significant changes were observed in the sperm analysis in the case of F0 group, no variation was found for F1 group, and no alterations in fertility were recorded either. The absolute organ weights and relative organ weight/body weight and organ weight/brain weight ratios, and the complete histopathological study, showed no significant alterations in males and females for all the generations considered. Considering all the results obtained, PTSO is not considered a reproductive or developmental toxicant in mice under the assayed conditions. These results support the good safety profile of PTSO for its potential application in the agrifood sector.
N-Acetylcysteine, N-Acetylcysteine Amide, and Thioredoxin Mimetic Peptides Regenerate Mercaptoalbumin and Exhibit Antioxidant Activity
Authors: Eligini Sonia , Munno Marco , Modafferi Gloria , Atlas Daphne , Banfi Cristina
Published: March 2024

Albumin (HSA) is the most abundant circulating protein and plays a pivotal role in maintaining the redox state of the plasma. Three HSA proteoforms have been identified based on the redox state of cysteine 34. These proteoforms comprise of the reduced state (HSA-SH) referred to as mercaptoalbumin, non-mercaptoalbumin-1, containing a disulfide with small thiols such as cysteine (HSA-Cys), and non-mercaptoalbumin-2, representing the higher oxidized proteoform. Several clinical studies have shown a relationship between an individual’s serum HSA redox status and the severity of diseases such as heart failure, diabetes mellitus, and liver disease. Furthermore, when HSA undergoes oxidation, it can worsen certain health conditions and contribute to their advancement. This study aimed to evaluate the ability of the redox compounds AD4/NACA and the thioredoxin mimetic (TXM) peptides TXM-CB3, TXM-CB13, and TXM-CB30 to regenerate HSA-SH and to enhance its redox activity. The HSA proteoforms were quantified by LC-MS, and the antioxidant activity was determined using dichlorofluorescin. Each of the compounds exhibited a significant increase in HSA-SH and a reduction in HSA-Cys levels. The increase in HSA-SH was associated with a recovery of its antioxidant activity. In this work, we unveil a novel mechanistic facet of the antioxidant activity of AD4/NACA and TXM peptides. These results suggest an additional therapeutic approach for addressing oxidative stress-related conditions.
Odor Impact Assessment via Dispersion Model: Comparison of Different Input Meteorological Datasets
Authors: Tagliaferri Francesca , Facagni Laura , Invernizzi Marzio , Ferrer Hernández Adrian Luis , Hernández-Garces Anel , Sironi Selena
Published: March 2024

Dispersion modeling is a useful tool for reproducing the spatial–temporal distribution of pollutants emitted by industrial sites, particularly in the environmental odor field. One widely used tool, accepted by regulatory agencies for environmental impact assessments, is the CALPUFF model, which requires a large number of input variables, including meteorological and orographical variables. The reliability of model results depends on the accuracy of these input variables. The present research aims to discuss a comparative study of odor dispersion modeling by initializing the CALMET meteorological processor with different input data: surface and upper air observational meteorological data, 3D prognostic data, and a blend of prognostic and measured data. Two distinct sources (a point and an area source) and two different simulation domains in Cuba and Italy are considered. The analysis of results is based on odor impact criteria enforced in some Italian regions by computing the 98th percentile of odor peak concentrations on an annual basis. For the area source, simulation results reveal that the ‘OBS’ and ‘HYBRID’ modes are largely comparable, whereas prognostic data tend to underestimate the odor concentrations, likely due to a reduced percentage of wind calms. For point sources, different input meteorological settings provide comparable results, with no significant differences.
Validation of a Simple Device for the Evaluation of Ankle Plantar- and Dorsi-Flexor Forces Consistent with Standard Clinical Evaluations
Authors: Rogati Giulia , Caravaggi Paolo , Martelli Andrea , Fognani Roberta , Leardini Alberto , Baleani Massimiliano
Published: March 2024

Measuring the forces produced at the ankle joint is critical to diagnose musculoskeletal pathologies. In standard clinical practice, ankle force is often assessed through manual joint manipulation and visual observation. This study introduces a simple apparatus, the Ankle Force Transducer (AFT), based on a uniaxial load cell capable of measuring ankle forces in conditions consistent with clinical evaluations. The AFT can be placed at the extremity of any examination couch to measure ankle forces in plantarflexion and dorsiflexion. The repeatability of the AFT was assessed in 30 healthy subjects across three sessions and in two knee postures. One patient with foot-drop condition was evaluated using the same apparatus. The intra-session coefficient of variation for plantarflexion and dorsiflexion forces was around 5% and 8%, respectively. The dominant leg exhibited greater forces than the non-dominant one, and the fully extended knee resulted in significantly larger forces with respect to the flexed knee (p < 0.001). The foot-drop patient showed a 90% reduction in dorsiflexion force in the affected limb. The AFT appears to be a user-friendly tool used to measure ankle forces, which has the potential to provide more repeatable and objective measurements of ankle forces with respect to operator-dependent evaluations.
A Geophysical Investigation of the Pâclele Mici Mud Volcano in Romania Using Deep Geoelectrical Surveys
Authors: Mihai Andrei , Gerea Alexandra , Tataru Dragoș , Nastase Eduard , Grecu Bogdan
Published: March 2024

This work presents a case study of a geoelectrical exploration of understudied mud volcanoes in Romania, specifically the Pâclele Mici mud volcano from Buzău County. Using a geoelectrical technique facilitated by the distributed network of V-FullWaver equipment, we present, to our knowledge, the first deep 3D case study of a mud volcano in the country. The findings indicate that while geoelectrical surveys in such environments are met with important challenges in terms of soil conductivity, they nonetheless provide a viable approach to uncovering the complex structures and processes of mud volcanoes. We map a part of the mud volcano, showing that the active subsurface part corresponds only partly with what is visible on the surface, and suggest a framework for an in-depth analysis of the extensive mud volcano area.
A Laser-Induced Breakdown Spectroscopy (LIBS) Instrument for In-Situ Exploration with the DLR Lightweight Rover Unit (LRU)
Authors: Schröder Susanne , Seel Fabian , Dietz Enrico , Frohmann Sven , Hansen Peder Bagge , Lehner Peter , Fonseca Prince Andre , Sakagami Ryo , Vodermayer Bernhard , Wedler Armin , Börner Anko , Hübers Heinz-Wilhelm
Published: March 2024

In the framework of the Helmholtz ARCHES project, a multitude of robots, including rovers and drones, were prepared for the autonomous exploration of a test site at the foothills of Mt. Etna, Sicily—a terrain resembling extraterrestrial locations such as the Moon. To expand the suite of tools and sensors available for the exploration and investigation of the test site, we developed a laser-induced breakdown spectroscopy (LIBS) instrument for the geochemical analysis of local geological samples. In alignment with the mission scenario, this instrument is housed in a modular payload box that can be attached to the robotic arm of the Lightweight Rover Unit 2 (LRU2), allowing the rover to use the instrument autonomously in the field. A compact Nd:YAG laser is utilized for material ablation, generating a micro-plasma that is subsequently analyzed with a small fiber-coupled spectrometer. A single-board computer controls the LIBS hardware components for data acquisition. In this study, we provide details of the ARCHES LIBS instrument implementation, report on preceding laboratory tests where the LRU2 operated the LIBS module for the first time, and showcase the results obtained during the successful ARCHES space analogue demonstration mission campaign in summer 2022 in Sicily.
Exposure Time to Work-Related Hazards and Factors Affecting Musculoskeletal Pain in Nurses
Authors: Kim Woo Jin , Jeong Byung Yong
Published: March 2024

Nurses who work in hospitals are exposed to various occupational hazards and are recognized as having high rates of musculoskeletal pain. This study aims to estimate the level of exposure to work-related hazards for nurses working in hospitals and derive factors that affect back pain, upper limb pain, and lower limb pain. This study was conducted on 462 nurses from the 6th Korean Working Condition Survey (KWCS) data, deriving exposure time related to physical, biochemical, and ergonomic hazards. Also, using binomial logistic regression analysis, this study determines the factors influencing musculoskeletal pain by comprehensively considering work-related factors and physical, biochemical, and ergonomic hazards. The exposure time for standing is the highest, followed by repetitive movements, awkward postures, patient lifting/carrying, infection, heavy object handling, and vibration. The average exposure times to occupational hazards were higher for nurses experiencing pain in their back, upper limbs, and lower limbs than those without pain complaints. Factors that contribute to back pain include years of work experience (p = 0.002), type of healthcare establishment (p = 0.001), exposure level to vibration (p = 0.029), and awkward posture level (p < 0.001). Factors affecting upper limb pain include the type of shift work (p = 0.013), handling heavy objects (p < 0.001), awkward postures (p = 0.033), and repetitive movements (p = 0.002). The factors that influence lower limb pain are awkward posture (p = 0.001), patient lifting/carrying (p = 0.002), and repetitive movements (p = 0.006). This study emphasizes the importance of implementing strategies to improve occupational hazards to prevent or alleviate musculoskeletal pain. These findings provide practical guidance for managing risk factors and preventing musculoskeletal disorders among nursing professionals.
Estimation of Systolic and Diastolic Blood Pressure for Hypertension Identification from Photoplethysmography Signals
Authors: De Oliveira Hygo Sousa , Pinto Rafael Albuquerque , Souto Eduardo James Pereira , Giusti Rafael
Published: March 2024

Continuous monitoring plays a crucial role in diagnosing hypertension, characterized by the increase in Arterial Blood Pressure (ABP). The gold-standard method for obtaining ABP involves the uncomfortable and invasive technique of cannulation. Conversely, ABP can be acquired non-invasively by using Photoplethysmography (PPG). This non-invasive approach offers the advantage of continuous BP monitoring outside a hospital setting and can be implemented in cost-effective wearable devices. PPG and ABP signals differ in scale values, which creates a non-linear relationship, opening avenues for the utilization of algorithms capable of detecting non-linear associations. In this study, we introduce Neural Model of Blood Pressure (NeuBP), which estimates systolic and diastolic values from PPG signals. The problem is treated as a binary classification task, distinguishing between Normotensive and Hypertensive categories. Furthermore, our research investigates NeuBP’s performance in classifying different BP categories, including Normotensive, Prehypertensive, Grade 1 Hypertensive, and Grade 2 Hypertensive cases. We evaluate our proposed method by using data from the publicly available MIMIC-III database. The experimental results demonstrate that NeuBP achieves results comparable to more complex models with fewer parameters. The mean absolute errors for systolic and diastolic values are 5.02 mmHg and 3.11 mmHg, respectively.
Enhancing Reliability in Wind Turbine Power Curve Estimation
Authors: Marti-Puig Pere , Hernández Jose Ángel , Solé-Casals Jordi , Serra-Serra Moises
Published: March 2024

Accurate power curve modeling is essential to continuously evaluate the performance of a wind turbine (WT). In this work, we characterize the wind power curves using SCADA data acquired at a frequency of 5 min in a wind farm (WF) consisting of five WTs. Regarding the non-parametric methods, we select artificial neural networks (ANNs) to make curve estimations. Given that, we have the curves provided by the manufacturer of the WTs given by some very precisely measured pair of wind speed and power points. We can evaluate the difference between the manufacturer characterization and the ones estimated with the data provided by the SCADA system. Before the estimation, we propose a method of filtering the anomalies based on the characteristics provided by the manufacturer. We use three-quarters of the available data for curve estimation and one-quarter for the test. One WT suffered a break in the test part, so we can check how the test estimates reflect this problem in its wind-power curve compared to the estimations obtained in the WTs that worked adequately.
Mechanics and Stability of Force Chain Arch in Excavated Granular Material
Authors: Wang Meimei , Zheng Jianwei , Xue Shanshan
Published: March 2024

Rock and soil masses in geotechnical engineering projects, such as tunnels, mines and slopes, undergo relative motion, exhibiting mechanical characteristics of solid–fluid transition under critical conditions. This work analyzes the characteristics of the solid–fluid transition interface and the mode of load transfer through biaxial compression particle flow photoelastic experiments on granular materials. The study documents that this interface forms an arch shape, marked by a force chain arch. The granular material exhibits two distinct states depending on its position: below the arch, the granular material is in a solid–fluid transitional state, with bearing capacity reduced, while above the arch, it is in a stable solid state, capable of bearing the overlying rock layer’s load. The presence of the force chain arch alters the direction of the originally downward-transferring load, redirecting it along the trajectory of the arch. Analysis of the force and stability of the force chain arch revealed that the arch shape parameters and boundary loads control the instability of the arch. Changes in the overlying and lateral loads lead to different types of instability of the force chain arch. The findings of the study are crucial for underground engineering construction and for the prevention of geological disasters related to granular material.
Smart Contract-Based Right-of-Way Trade with Game Theory in Blockchain-Enabled Internet of Vehicles
Authors: Li Cheng , Wu Hao , Lu Yunlong , Xiong Lei , Dong Chen , Li Jing
Published: March 2024

The Internet of Vehicles (IoV) has a significant impact on improving traffic efficiency and driving safety. In this paper, we propose an intelligent transportation credit system based on blockchain, and design a crossroad passing smart contract that allows time-sensitive convoys to pass a crossroad earlier by paying traffic tokens for right-of-way trade. Second, this paper formulates the time–cost optimization problem under the premise of protecting the privacy of preceding convoys. Based on game theory with incomplete information, two right-of-way optimal bid strategies are given. Both theoretical analysis and simulation prove that the strategy proposed in this paper effectively reduces the waiting time of time-sensitive vehicles at a crossroad and increases the trade success probability, which, in turn, improves the expected total profit of convoys and achieves Pareto improvement.
Camouflaged Object Detection Based on Deep Learning with Attention-Guided Edge Detection and Multi-Scale Context Fusion
Authors: Wen Yalin , Ke Wei , Sheng Hao
Published: March 2024

In nature, objects that use camouflage have features like colors and textures that closely resemble their background. This creates visual illusions that help them hide and protect themselves from predators. This similarity also makes the task of detecting camouflaged objects very challenging. Methods for camouflaged object detection (COD), which rely on deep neural networks, are increasingly gaining attention. These methods focus on improving model performance and computational efficiency by extracting edge information and using multi-layer feature fusion. Our improvement is based on researching ways to enhance efficiency in the encode–decode process. We have developed a variant model that combines Swin Transformer (Swin-T) and EfficientNet-B7. This model integrates the strengths of both Swin-T and EfficientNet-B7, and it employs an attention-guided tracking module to efficiently extract edge information and identify objects in camouflaged environments. Additionally, we have incorporated dense skip links to enhance the aggregation of deep-level feature information. A boundary-aware attention module has been incorporated into the final layer of the initial shallow information recognition phase. This module utilizes the Fourier transform to quickly relay specific edge information from the initially obtained shallow semantics to subsequent stages, thereby more effectively achieving feature recognition and edge extraction. In the latter phase, which is focused on deep semantic extraction, we employ a dense skip joint attention module to enhance the decoder’s performance and efficiency, ensuring accurate capture of deep-level information, feature recognition, and edge extraction. In the later stage of deep semantic extraction, we use a dense skip joint attention module to improve the decoder’s performance and efficiency in capturing precise deep information. This module efficiently identifies the specifics and edge information of undetected camouflaged objects across channels and spaces. Differing from previous methods, we introduce an adaptive pixel strength loss function for handling key captured information. Our proposed method shows strong competitive performance on three current benchmark datasets (CHAMELEON, CAMO, COD10K). Compared to 26 previously proposed methods using 4 measurement metrics, our approach exhibits favorable competitiveness.
Visualization Program Design for Complex Piping Systems in Marine Engine Simulation Systems
Authors: Wu Xiaoyu , He Zhibin , Wei Zhenghao , Zhang Qi , Fan Zhibo
Published: March 2024

This study is dedicated to the development of an advanced ship piping network programming tool to address the challenges faced by traditional text-based design and computation methods when dealing with complex and large-data-volume piping systems, such as burdensome programming tasks, high error rates, and difficulty in troubleshooting faults. Leveraging Microsoft’s WPF technology and the C# language, combined with Excel as a data input platform, this tool provides an intuitive graphical user interface, allowing users to intuitively build and analyze ship piping network models by dragging and dropping controls. The tool not only simplifies the design process of complex piping systems but also significantly improves efficiency and accuracy through automated data processing and calculations. It supports user customization of key pipeline characteristics, such as maximum flow and direction, further enhancing the applicability and accuracy of the piping network model. In addition, with optimized interaction design and data management methods, the tool significantly reduces the learning difficulty for users, while improving the reliability of design and efficiency of troubleshooting. The results of this study show the tool not only technically outperforms traditional methods but also provides a new efficient, intuitive, and user-friendly tool for the teaching and engineering applications of ship piping networks, paving a new path for the design and optimization of ship piping network systems, with significant practical application value and theoretical significance. Looking forward, this tool is expected to play a broader role in the instruction and industrial practices associated with ship piping networks, moving the field toward more efficient and intelligent development.
RunsGuard Framework: Context Aware Cricket Game Strategy for Field Placement and Score Containment
Authors: Hussain Aatif , Arshad Shazia , Hassan Awais
Published: March 2024

Sports analytics utilizes data analysis techniques and computational methods to gain insights, make informed decisions, and facilitate improvements in the performance of individuals and teams. Cricket is one of the most popular games and continues to evolve worldwide. The availability of ball-by-ball data demands in-depth investigation of player strategies, team dynamics, and the impact of contextual variables. Existing studies explored various aspects of cricket analytics, including detecting key events, predicting outcomes, and ranking teams. However, the literature lacks a comprehensive integrated framework that processes unstructured sports commentary, extracts actionable insights, conducts a thorough player analysis, and develops strategic plans while considering contextual factors. This work aims to propose a bowling and fielding strategy to contain a batsman. For this purpose, we developed a comprehensive context-aware framework that collects data, extracts insights from commentary, identifies player strengths and weaknesses, and proposes cricket bowling and fielding strategies according to the given context. To evaluate this work, we implemented a case study that simulated different scenarios, and our framework suggested bowling and fielding strategies. In these simulations, the proposed strategies consistently demonstrated a substantial reduction in the number of runs that were scored. On average, the framework reduces the batsman’s score rate by 33%. These findings underscore the practical effectiveness of research in optimizing field placement and effectively reducing scoring opportunities. Finally, by bridging the gap between data analytics and cricket game strategy, this methodology provides a competitive advantage to coaches, captains, and players. In the future, we aim to involve temporal patterns to understand the evolving behavior of players.
Linked Coupling Faults Detection by Multirun March Tests
Authors: Mrozek Ireneusz , Yarmolik Vyacheslav N.
Published: March 2024

This paper addresses the problem of describing the complex linked coupling faults of memory devices and formulating the necessary and sufficient conditions for their detection. The main contribution of the proposed approach is based on using a new formal model of such faults, the critical element of which is the introduction of roles and scenarios performed by the cells involved in the fault. Three roles are defined such that the cells of the complex linked coupling faults perform, namely, the roles of the aggressor (A), the victim (V), and both (B), performed by two cells simultaneously in relation to each other. The memory march test and applied address sequence and background determine the scenario for implementing the roles of memory faulty cells. The necessary and sufficient conditions for detecting linked coupling faults are given based on a new formal model. Formally, the undetectable linked coupling faults are defined, and the conditions for their detection are formulated using multirun memory march tests. The experimental investigation confirmed the validity of the proposed formulated statements. Based on the example of a linked coupling fault, this study demonstrates the fulfillment of the necessary and sufficient conditions for its detection using a single march test. As demonstrated in this article, employing the approach proposed by the authors, a two-pass march C test, for instance, enables the attainment of 55.42% fault coverage for linked coupling faults, inclusive of undetectable faults identified by the single-pass march test.
A Novel Physics-Guided Neural Network for Predicting Fatigue Life of Materials
Authors: Yang Dexin , Jin Afang , Li Yun
Published: March 2024

A physics-guided neural network (PGNN) is proposed to predict the fatigue life of materials. In order to reduce the complexity of fatigue life prediction and reduce the data required for network training, the PGNN only predicts the fatigue performance parameters under a specific loading environment, and calculates the fatigue life by substituting the load into the fatigue performance parameters. The advantage of this is that the network does not need to evaluate the effect of numerical changes in the load on fatigue life. The load only needs to participate in the error verification, which reduces the dimension of the function that the neural network needs to approximate. The performance of the PGNN is verified using published data. Due to the reduction in the complexity of the problem, the PGNN can use fewer training samples to obtain more accurate fatigue life prediction results and has a certain extrapolation ability for the changes in trained loading environment parameters. The prediction process of the PGNN for fatigue life is not completely a black box, and the prediction results are helpful for scholars to further study the fatigue phenomenon.
Modal Parameter Identification of a Structure Under Earthquake via a Wavelet-Based Subspace Approach
Authors: Su Wei-Chih , Chen Liane-Jye , Huang Chiung-Shiann
Published: March 2024

This paper introduces a novel wavelet-based methodology for identifying the modal parameters of a structure in the aftermath of an earthquake. Our proposed approach seamlessly combines a subspace method with a stationary wavelet packet transform. By relocating the subspace method into the wavelet domain and introducing a weighting function, complemented by a moving window technique, the efficiency of our approach is significantly augmented. This enhancement ensures the precise identification of the time-varying modal parameters of a structure. The capacity of the stationary wavelet packet transform for rich signal decomposition and exceptional time-frequency localization is harnessed in our approach. Different subspaces within the stationary wavelet packet transform encapsulate signals with distinct frequency sub-bands, leveraging the fine filtering property to not only discern modes with pronounced modal interference, but also identify numerous modes from the responses of a limited number of measured degrees of freedom. To validate our methodology, we processed numerically simulated responses of both time-invariant and time-varying six-floor shear buildings, accounting for noise and incomplete measurements. Additionally, our approach was applied to the seismic responses of a cable-stayed bridge and the nonlinear responses of a five-story steel frame during a shaking table test. The identified modal parameters were meticulously compared with published results, underscoring the applicability and reliability of our approach for processing real measured data.
Enhancing Sequence Movie Recommendation System Using Deep Learning and KMeans
Authors: Siet Sophort , Peng Sony , Ilkhomjon Sadriddinov , Kang Misun , Park Doo-Soon
Published: March 2024

A flood of information has occurred, making it challenging for people to find and filter their favorite items. Recommendation systems (RSs) have emerged as a solution to this problem; however, traditional Appenrecommendation systems, including collaborative filtering, and content-based filtering, face significant challenges such as data scalability, data scarcity, and the cold-start problem, all of which require advanced solutions. Therefore, we propose a ranking and enhancing sequence movie recommendation system that utilizes the combination model of deep learning to resolve the existing issues. To mitigate these challenges, we design an RSs model that utilizes user information (age, gender, occupation) to analyze new users and match them with others who have similar preferences. Initially, we construct sequences of user behavior to effectively predict the potential next target movie of users. We then incorporate user information and movie sequence embeddings as input features to reduce the dimensionality, before feeding them into a transformer architecture and multilayer perceptron (MLP). Our model integrates a transformer layer with positional encoding for user behavior sequences and multi-head attention mechanisms to enhance prediction accuracy. Furthermore, the system applies KMeans clustering to movie genre embeddings, grouping similar movies and integrating this clustering information with predicted ratings to ensure diversity in the personalized recommendations for target users. Evaluating our model on two MovieLens datasets (100 Kand 1 M) demonstrated significant improvements, achieving RMSE, MAE, precision, recall, and F1 scores of 1.0756, 0.8741, 0.5516, 0.3260, and 0.4098 for the 100 K dataset, and 0.9927, 0.8007, 0.5838, 0.4723, and 0.5222 for the 1 M dataset, respectively. This approach not only effectively mitigates cold-start and scalability issues but also surpasses baseline techniques in Top-N item recommendations, highlighting its efficacy in the contemporary environment of abundant data.
Validation of a New Method for Continuous Flare Combustion Efficiency Monitoring
Authors: Tao Chong , Chow Jon , Sui Lei , Wang Anan , Bottino Gerard , Evans Peter , Newman David , Venuturumilli Raj , Lowe Jon , Liekens Johan
Published: March 2024

A new method is described for calculating flare combustion efficiency (CE) and destruction and removal efficiency (DRE) using a numerical parametric model. The method combines key variables that affect flare performance including the flare vent gas net heating value (NHV), flare design, flow rate, exit velocity, and inert gas composition, alongside the environmental influence of crosswind speed. Each effect is characterized using a parametric model derived from experimental testing data and computational fluid dynamics (CFD). The inclusion of CFD allows the model to be extended into the high-wind conditions that cannot be adequately controlled for in empirical testing yet represent some of the most challenging conditions in which to maintain good combustion. This new parametric model method (PMM) is coupled with ultrasonic flowmeters from which the molecular weight and net heating value of the flare gas can be derived using the vent gas speed of sound measurement. In doing so, this method provides a reliable continuous flare combustion efficiency measure that can be deployed at scale with minimum hardware updates. The system was verified using an extractive sampling method with tests conducted on three full-scale industrial flares including non-assisted, single-arm pressure-assisted, and multi-arm pressure-assisted flare designs. A total of seventy valid test points were carried out with varying flow rate and flare gas heating value, covering a CE range from 46–100%. The uncertainty of the method was assessed using both traditional error propagation and Monte Carlo methodology. The results from the new method agree with the extractive method to within 0.8% in the ≥98% DRE region where flares are expected to operate to limit the impacts of flaring as a source of methane as a greenhouse gas. Uncertainty analysis revealed that the larger DRE discrepancy for DRE ≤ 98% correlates to the measurement uncertainties for both methods.
Trend Projections of Potential Evapotranspiration in Yangtze River Delta and the Uncertainty
Authors: Ding Lu , Yu Yi , Zhang Shaobo
Published: March 2024

Global warming may increase potential evapotranspiration (ETp), reducing the water resources in Yangzi River Delta. Therefore, it is important to investigate the trend of ETp there under the background of climate change. To this purpose, the systematic biases in temperature outputs of 24 global climate models (GCMs) under 3 shared socioeconomic pathways—representative concentration pathways (SSPs) emission scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5)—are first corrected by using 8 bias correction methods. Then, the trend of ETp in Yangtze River Delta is projected by using 4 ETp calculation formulas (Blaney–Criddle, Hargreaves–Samani, Makkink, and Priestley–Taylor). The uncertainty of the projections is estimated and decomposed by using multi-way analysis of variance frameworks. The influence of uncertainty on the projected change signal is quantified by using the signal-to-noise ratio. The results show that all emission scenarios indicate robust increments of ETp. Specifically, relative to 1971~2000, ETp will increase by 0.14~0.17 mm d−1 (5.7~6.8%) during 2021~2050 and by 0.21~0.41 mm d−1 (8.5~16.7%) during 2061~2090, respectively. During 2021~2050, the uncertainty of ETp projections is dominantly contributed by the main effects of GCM (63%) and the ETp calculation formula (24%). During 2061~2090, it is mainly contributed by the main effect of GCM (36%), followed by the main effects of the emission scenario (34%) and the ETp calculation formula (18%). The ETp projections are generally reliable and robust during the two projection periods.
Variations in Maximum and Minimum Temperature in Mount Qomolangma during 1971–2020
Authors: Wang Shunjiu
Published: March 2024

Based on the daily maximum and minimum temperature observational data during 1971–2020, the variabilities of the maximum and minimum temperature of Mount Qomolangma are analyzed. The daily maximum temperature is 25.8 °C and the daily minimum temperature is −31.4 °C during the study period in Mount Qomolangma. Overall, there has been an upward trend with decadal laps for both maximum and minimum temperature. On monthly, seasonal, and annual scales, neither maximum temperature nor minimum temperature time series exhibit an increasing trend from 1971 to 2020. The increasing trends in monthly minimum temperature are even more pronounced than those in maximum temperature. Abrupt changes are noted in both monthly, seasonal, and annual maximum and minimum temperature time series. Specifically, an abrupt change in annual maximum temperature occurred in the 1980s, while an abrupt change in annual minimum temperature occurred in the 1990s. Differences between the north and south slope of Mount Qomolangma are evident, with temperature fluctuations of the north slope being more extreme than those of south slope. The seasonal and annual maximum temperature of the north slope is higher than that of the south slope, except for winter, and the seasonal and annual minimum temperatures of the north slope are all lower than those of the south slope. The tendences of maximum and minimum temperatures in the north slope are more dominant than those in the south slope. The findings are beneficial for understanding the characteristics of local climate change on the Tibetan plateau and to underscore the significant role of Mount Qomolangma in the context of global warming.
A Comprehensive Review of Assessing Storm Surge Disasters: From Traditional Statistical Methods to Artificial Intelligence-Based Techniques
Authors: Zhang Yuxuan , Zhang Tianyu
Published: March 2024

In the context of global climate change and rising sea levels, the adverse impacts of storm surges on the environment, economy, and society of affected areas are becoming increasingly significant. However, due to differences in geography, climate, and other conditions among the affected areas, a single method for assessing the risk of storm surge disasters cannot be fully applicable to all regions. To address this issue, an increasing number of new methods and models are being applied in the field of storm surge disaster risk assessment. This paper introduces representative traditional statistical methods, numerical simulation methods, and artificial intelligence-based techniques in this field. It compares these assessment methods in terms of accuracy, interpretability, and implementation difficulty. The paper emphasizes the importance of selecting appropriate assessment methods based on specific conditions and scientifically combining various methods in practice to improve the accuracy and reliability of storm surge disaster risk assessments.
Neural Network-Based Classifier for Collision Classification and Identification for a 3-DOF Industrial Robot
Authors: Mahmoud Khaled H. , Abdel-Jaber G. T. , Sharkawy Abdel-Nasser
Published: March 2024

In this paper, the aim is to classify torque signals that are received from a 3-DOF manipulator using a pattern recognition neural network (PR-NN). The output signals of the proposed PR-NN classifier model are classified into four indicators. The first predicts that no collisions occur. The other three indicators predict collisions on the three links of the manipulator. The input data to train the PR-NN model are the values of torque exerted by the joints. The output of the model predicts and identifies the link on which the collision occurs. In our previous work, the position data for a 3-DOF robot were used to estimate the external collision torques exerted by the joints when applying collisions on each link, based on a recurrent neural network (RNN). The estimated external torques were used to design the current PR-NN model. In this work, the PR-NN model, while training, could successfully classify 56,592 samples out of 56,619 samples. Thus, the model achieved overall effectiveness (accuracy) in classifying collisions on the robot of 99.95%, which is almost 100%. The sensitivity of the model in detecting collisions on the links “Link 1, Link 2, and Link 3” was 97.9%, 99.7%, and 99.9%, respectively. The overall effectiveness of the trained model is presented and compared with other previous entries from the literature.
The Generalized 3-Connectivity of Exchanged Folded Hypercubes
Authors: Ning Wantao , Li Hao
Published: March 2024

For S⊆V(G),κG(S) denotes the maximum number k of edge disjoint trees T1,T2,…,Tk in G, such that V(Ti)∩V(Tj)=S for any i,j∈{1,2,…,k} and i≠j. For an integer 2≤r≤|V(G)|, the generalized r-connectivity of G is defined as κr(G)=min{κG(S)|S⊆V(G)and|S|=r}. In fact, κ2(G) is the traditional connectivity of G. Hence, the generalized r-connectivity is an extension of traditional connectivity. The exchanged folded hypercube EFH(s,t), in which s≥1 and t≥1 are positive integers, is a variant of the hypercube. In this paper, we find that κ3(EFH(s,t))=s+1 with 3≤s≤t.
Optimal Construction for Decoding 2D Convolutional Codes over an Erasure Channel
Authors: Pinto Raquel , Spreafico Marcos , Vela Carlos
Published: March 2024

In general, the problem of building optimal convolutional codes under a certain criteria is hard, especially when size field restrictions are applied. In this paper, we confront the challenge of constructing an optimal 2D convolutional code when communicating over an erasure channel. We propose a general construction method for these codes. Specifically, we provide an optimal construction where the decoding method presented in the bibliography is considered.
[SBP]BF4 Additive Stabilizing Zinc Anode by Simultaneously Regulating the Solvation Shell and Electrode Interface
Authors: Zhang Xingyun , Su Kailimai , Hu Yue , Xue Kaiyuan , Wang Yan , Han Minmin , Lang Junwei
Published: March 2024

The zinc anode mainly faces technical problems such as short circuits caused by the growth of dendrite, low coulomb efficiency, and a short cycle life caused by side reactions, which impedes the rapid development of aqueous zinc-ion batteries (AZIBs). Herein, a common ionic liquid, 1,1-Spirobipyrrolidinium tetrafluoroborate ([SBP]BF4), is selected as a new additive for pure ZnSO4 electrolyte. It is found that this additive could regulate the solvation sheath of hydrated Zn2+ ions, promote the ionic mobility of Zn2+, homogenize the flux of Zn2+, avoid side reactions between the electrolyte and electrode, and inhibit the production of zinc dendrites by facilitating the establishment of an inorganic solid electrolyte interphase layer. With the 1% [SBP]BF4-modified electrolyte, the Zn||Zn symmetric cell delivers an extended plating/stripping cycling life of 2000 h at 1 mA cm−2, which is much higher than that of the cell without additives (330 h). As a proof of concept, the Zn‖V2O5 battery using the [SBP]BF4 additive shows excellent cycling stability, maintaining its specific capacity at 97 mAh g−1 after 2000 cycles at 5 A g−1, which is much greater than the 46 mAh g−1 capacity of the non-additive battery. This study offers zinc anode stabilization through high-efficiency electrolyte engineering.
Off-Label Use of an External Hand Fixator for Craniomaxillofacial Fractures—An Anatomical Feasibility Study
Authors: Wichlas Florian , Necchi Marco , Gruber Teresa , Hofmann Valeska , Deininger Susanne , Deininger Sebastian Hubertus Markus , Deluca Amelie , Steidle-Kloc Eva , Pruszak Jan , Wittig Jörn , Deininger Christian
Published: March 2024

Background: The lack of resources limits the treatment of craniomaxillofacial fractures (CMF) in low-income countries (LIC). Therefore, Barton bandages and/or interdental wiring are considered in these regions. Fracture reduction is maintained by permanent occlusion for 6 weeks, which often leads to limited compliance and dissatisfying results. The aim of this cadaver-based study is to evaluate the feasibility of the use of an external face fixator (EFF) for the treatment of CMF, its biomechanical values and to define the optimal pin insertion points and angles. Materials and Methods: An AO hand fixator was used. CMF of types Le Fort 1–3 with split fractures of the hard palate were treated with EFF on 13 anatomical specimens. Fractures were created using a chisel, and pins were placed in specific anatomical regions. The maximal pull-out force [N] of pins was analysed by a tensile force gauge, and Fmax of the mandibular pins was evaluated. Computer tomography scans were performed on the healthy, fractured and EFF-treated skulls. Results: The pull-out forces for the single pins were mandibular pins (n = 15, median 488.0 N), supraorbital pins (n = 15, median 455.0 N), zygomatic pins (n = 14, median 269.1 N), medial hard palate pins (n = 12, median 208.4 N) and lateral hard palate pins (n = 8, median 49.6 N). Conclusions: The results indicate that the operation technique is feasible, and the stability of the EFF is sufficient for maintaining the reduction. The required pins can safely be inserted into the described areas with good reduction results. Using EFF offers a feasible alternative to the non-surgical treatment of CMF in LIC.