bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Dietary Limonene Supplementation on Growth Performance and Immunological Parameters of Common Carp, Cyprinus carpio, Challenged by Aeromonas hydrophila
Authors: Yousefi Morteza , Hoseini Seyyed Morteza , Abdel Rahman Afaf N. , Vatnikov Yury Anatolyevich , Kulikov Evgeny Vladimirovich , Kharlitskaya Elena Valentinovna , Seleznev Sergey Borisovich
Published: October 2023

This study examined the impact of dietary limonene treatment on the growth performance, immune response, and disease resistance of common carp, Cyprinus carpio. The fish were fed with either a control diet (CTL; no limonene supplementation) or four experimental diets containing 50 (50 L), 100 (100 L), 200 (200 L), and 400 (400 L) mg/kg limonene over a 70-day period, followed by Aeromonas hydrophila challenge. The 200 L treatment resulted in a significant decrease in FCR compared to the CTL treatment. The highest post-challenge mortality was associated with the CTL treatment (62.7%), while the 200 L treatment had the lowest mortality (30.7%). Before the challenge, dietary limonene significantly increased humoral and skin mucosal immune parameters compared to the CTL treatment. The highest leukocyte, lymphocyte counts, skin mucosal protease activity, and intestinal lactic acid bacteria were observed in the 200 L treatment before the challenge. The highest plasma lysozyme activity was observed in the 400 L treatment, whereas the highest skin mucosal lysozyme and peroxidase activities were observed in the 100 L and 200 L treatments before the challenge. There were no significant differences in the blood neutrophil, monocyte, and eosinophil counts, humoral alternative complement activity, skin mucosal alkaline phosphatase activity, and the intestinal total viable bacteria among the treatments before the challenge. After the challenge, the 200 L treatment exhibited the highest leukocyte, neutrophil, and monocyte count, skin mucosal immune parameters, and intestinal lactic acid bacteria, whereas the highest blood eosinophil count was observed in the 100 L, 200 L, and 400 L treatments. At this time, the lowest blood lymphocyte counts were observed in the 100 L and 200 L, but the lowest intestinal total viable bacteria were observed in the 100 L, 200 L, and 400 L treatments. Based on these findings, dietary limonene at 200 mg/kg is ideal for common carp to promote feed efficiency, innate immunity boosting, and resistance against A. hydrophila.
A New Species of Spelaeometra Polhemus & Ferreira, 2018 (Hemiptera: Heteroptera: Hydrometridae) from a Hotspot of Troglobites in Brazil, Serra do Ramalho Karst Area
Authors: Cordeiro Isabelle R. S. , Bichuette Maria Elina , Moreira Felipe F. F.
Published: October 2023

Spelaeometra Polhemus & Ferreira, 2018 (Hemiptera: Heteroptera: Hydrometridae) is a monotypic and troglobitic genus, recently described based on material collected in the state of Minas Gerais, Brazil. From specimens collected in the Gruna do Enfurnado Cave in the Serra do Ramalho karst area, municipality of Coribe, state of Bahia, Brazil, we describe Spelaeometra hypogea Cordeiro & Moreira, sp. nov. and compare it with Spelaeometra gruta Polhemus & Ferreira, 2018. The new species is diagnosed by the general body color being pale-yellow to light-brown; antennal segments I and II being subequal in length; the reduced gular lobe, not covering any labial segment; the male proctiger without apical projections; and the male paramere with convex dorsal margin after the curvature, with a narrow hook-like apex.
Does Size Matter? Testicular Volume and Its Predictive Ability of Sperm Production in Rams
Authors: Montes-Garrido Rafael , Anel-Lopez Luis , Riesco Marta F. , Neila-Montero Marta , Palacin-Martinez Cristina , Soriano-Úbeda Cristina , Boixo Juan Carlos , de Paz Paulino , Anel Luis , Alvarez Mercedes
Published: October 2023

Over the years, testicular volume has been used to evaluate the reproductive capacity of rams and the effects of different factors related to reproductive performance. The aim of this study was to determine the most suitable tool and formula to calculate testicular volume under field conditions to guarantee a more accurate determination of sperm production. First, testicles from 25 rams (n = 50) were measured in vivo and postmortem using calipers and ultrasonography during the breeding season (BS). The accurate testicular volume (ATV) was calculated through water displacement. In addition, the sexual status of donor rams was evaluated during a period of four years in a reproduction center, and the three most crucial groups in terms of genetic value and seminal collections were studied in the second part of this experiment: ER-NBS (Elite rams during the non-breeding season), ER-BS-S (Elite rams with a standard frequency of seminal collection), and ER-BS-O (Elite rams with a high frequency of seminal collection). The total testicular volume (TTV), testosterone (T), and total spermatozoa obtained from two consecutive ejaculates in the same day (SPERM) were measured, and the relationship between SPERM and TTV and T was analyzed to predict SPERM. Although all published formulas revealed statistically significant differences (p ≤ 0.05) from the ATV, our proposed formula (ItraULE) (Testicular volume = L × W × D × 0.61) did not show significant differences. In the second part of the study, in the ER as a model donor ram for its high genetic value and high demand from farmers, TTV and T showed strong positive correlations with SPERM (r = 0.587, p = 0.007 NBS; r = 0.684, p = 0.001 BS-S; r = 0.773, p < 0.0001 BS-O). Moreover, formulas were established to predict SPERM in these practical scenarios. In conclusion, the use of ultrasonography and a new formula adapted to rams could improve the prediction of SPERM considering crucial factors such as season and semen collection frequency.
Dietary Betaine Attenuates High-Carbohydrate-Diet-Induced Oxidative Stress, Endoplasmic Reticulum Stress, and Apoptosis in Mandarin Fish (Siniperca chuatsi)
Authors: Li Hongyan , Zeng Yanzhi , Zheng Xinyu , Wang Guangjun , Tian Jingjing , Gong Wangbao , Xia Yun , Zhang Kai , Li Zhifei , Xie Wenping , Xie Jun , Yu Ermeng
Published: October 2023

To investigate the impact of betaine on high-carbohydrate-diet-induced oxidative stress and endoplasmic reticulum (ER) stress, mandarin fish (Siniperca chuatsi) (23.73 ± 0.05 g) were fed with control (NC), betaine (BET), high carbohydrate (HC), and high carbohydrate + betaine (HC + BET) diets for 8 weeks. The results showed that betaine significantly promoted the growth of mandarin fish irrespective of the dietary carbohydrate levels. The HC diet induced oxidative stress, as evidenced by significantly elevated MDA levels. The HC diet significantly stimulated the mRNA levels of genes involved in ER stress (ire1, perk, atf6, xbp1, eif2α, atf4, chop), autophagy (ulk1, becn1, lc3b), and apoptosis (bax). However, betaine mitigated HC-diet-induced oxidative stress by modulating antioxidant enzymes and alleviated ER stress by regulating the mRNA of genes in the PERK-eIF2a-ATF4 pathway. Additionally, betaine significantly reduced the mRNA levels of becn1 and bax, along with the apoptosis rate, indicating a mitigating effect on autophagy and apoptosis. Overall, dietary betaine improved growth, attenuated HC-diet-induced oxidative stress and ER stress, and ultimately alleviated apoptosis in mandarin fish. These findings provide evidence for the use of betaine in aquafeeds to counter disruptive effects due to diets containing high carbohydrate levels.
Numerical Simulation Study on Application of T-Shaped Composite Pile Support System in Super-Large Foundation Pit Support Engineering
Authors: Lu Jiaqi , Jiang Huihuang
Published: October 2023

To reduce the impact of the one-time excavation of deep and large foundation pits on nearby subway tunnels, the excavation should be performed separately; thus, a T-shaped pile support system was studied. First, several foundation pit support structures were compared and selected, and a pile support system was proposed. In terms of space, a T-shaped support structure was formed to reduce the spatial requirements of the foundation pit. Through finite element software, a 1:1 restoration of the foundation pit using a T-shaped pile support system was carried out. The stress characteristics and support effect of the support structure were studied under two working conditions of symmetric and asymmetric excavation. The study found that there was a central effect on the foundation pit using a T-shaped pile support system, that is, the support piles farther away from the center of the T-shaped structure gradually increased the maximum pile bending moment and displacement owing to the constraints of vertical piles and the influence of the pit angle effect, respectively. In the case of symmetrical excavation, the T-shaped structure was simplified into a triangular structure, and the stress form of this type of structure could be reduced to a cantilever double-row pile structure, which met the requirements of pit excavation. The application of a T-shaped pile support structure can provide new design ideas for foundation pit engineering near regional subway lines.
Detection of Multidrug-Resistant RND Efflux Pumps and Regulatory Proteins in Antibiotic-Resistant P. aeruginosa Recovered from Hospital Wastewater Effluent in the Eastern Cape Province of South Africa
Authors: Okafor Joan U. , Nwodo Uchechukwu U.
Published: October 2023

P. aeruginosa (P. aeruginosa) is a problematic hospital agent that is a global challenge due to the ineffectiveness of some conventional antimicrobial therapies. Multidrug-resistant (MDR) P. aeruginosa has distinct action modes, including beta-lactamase production, porin gene repression, and efflux pump overexpression. This current research work focuses on efflux pumps (MexAB-OprM, MexCD-OprJ, MexXY-OprN) and their regulatory proteins (NfxB, MexR, MexZ, NalC, NalD) in MDR P. aeruginosa isolated from hospital wastewater effluent. The sequence analysis of the main transporter MexB was also performed. Following antibiotic resistance profiling and polymerase chain reaction (PCR) amplification of the efflux pump genes, the association of the efflux pump proteins with antibiotic resistance was investigated and analysed statistically. Fifty-seven (57) multidrug-resistant isolates were obtained from 81 PCR-confirmed P. aeruginosa isolates. Of the MDR P. aeruginosa isolates, the following rates were recorded: MexA (96.5%), MexB (100%), OprM (96.5%), MexC (100%), MexD (74.1%), OprJ (63.7%), MexX (89.6%), and OprN (51.7%). Additionally, the regulatory proteins had the following rates: NfxB (31.6%), NalC (15.8%), NalD (12.2%), MexZ (3.5%), and MexR (3.5%). The efflux pumps and regulatory proteins are strongly associated with antibiotic resistance, implying that P. aeruginosa antibiotic resistance is heavily influenced by these efflux pumps and regulatory genes. The MexB DNA sequences had numerous substitutions and poor alignment with divergent regions, and hence they have a possible role in increased antibiotic resistance. The absence of regulatory genes in most MDR P. aeruginosa isolates in the current research may have permitted transcription of the efflux pump operons, thus also increasing the antibiotic resistance burden.
Testing a Generalized Two-Equation Turbulence Model for Computational Aerodynamics of a Mid-Range Aircraft
Authors: Rossano Viola , De Stefano Giuliano
Published: October 2023

The generalized k-ω formulation provides a relatively new flexible eddy-viscosity Reynolds-averaged Navier–Stokes modeling approach to turbulent flow simulation, where free coefficients allow for fine-tuning and optimal adjusting of the turbulence closure procedure. The present study addressed the calibration of this versatile model for the aerodynamic design of an innovative mid-range commercial airplane by carrying out a series of simulations for varying model coefficients. Comparing the different solutions with each other, as well as with reference experimental and higher-fidelity numerical data, the performance of the generalized procedure in predicting the aerodynamic loading on the aircraft model was systematically examined. While drawing particular attention to the high-lift regime, the set of model parameters giving the best results was practically determined.
3D Point Cloud Completion Method Based on Building Contour Constraint Diffusion Probability Model
Authors: Ye Bo , Wang Han , Li Jingwen , Jiang Jianwu , Lu Yanling , Gao Ertao , Yue Tao
Published: October 2023

Building point cloud completion is the process of reconstructing missing parts of a building’s point cloud, which have been affected by external factors during data collection, to restore the original geometric shape of the building. However, the uncertainty in filling point positions in the areas where building features are missing makes it challenging to recover the original distribution of the building’s point cloud shape. To address this issue, we propose a point cloud generation diffusion probability model based on building outline constraints. This method constructs building-outline-constrained regions using information related to the walls on the building’s surface and adjacent roofs. These constraints are encoded by an encoder and fused into latent codes representing the incomplete building point cloud shape. This ensures that the completed point cloud adheres closely to the real geometric shape of the building by constraining the generated points within the missing areas. The quantitative and qualitative results of the experiment clearly show that our method performs better than other methods in building point cloud completion.
The Question of Studying Information Entropy in Poetic Texts
Authors: Kozhemyakina Olga , Barakhnin Vladimir , Shashok Natalia , Kozhemyakina Elina
Published: October 2023

One of the approaches to quantitative text analysis is to represent a given text in the form of a time series, which can be followed by an information entropy study for different text representations, such as “symbolic entropy”, “phonetic entropy” and “emotional entropy” of various orders. Studying authors’ styles based on such entropic characteristics of their works seems to be a promising area in the field of information analysis. In this work, the calculations of entropy values of the first, second and third order for the corpus of poems by A.S. Pushkin and other poets from the Golden Age of Russian Poetry were carried out. The values of “symbolic entropy”, “phonetic entropy” and “emotional entropy” and their mathematical expectations and variances were calculated for given corpora using the software application that automatically extracts statistical information, which is potentially applicable to tasks that identify features of the author’s style. The statistical data extracted could become the basis of the stylometric classification of authors by entropy characteristics.
Combined Application of Filter Cake and Macadamia Husk Compost Affects Soil Fertility and Plant Mineral Content of Orange-Fleshed Sweet Potatoes
Authors: Fatokun Kayode , Motsa Nozipho M. , Cloete Jacque , Radebe Samkelo , Nkomo Mbukeni A.
Published: October 2023

A greenhouse pot experiment was conducted to investigate the influence of the combined application of filter cake and macadamia husk compost (FC+MHC) on the soil fertility and dry matter partitioning of Beauregard and 199062.1 cultivars of orange-fleshed sweet potato. The effects of the two organic wastes on the mineral nutrients in the leaves and the storage roots of the 199062.1 cultivar were also investigated. In addition to FC+MHC, four other treatments—filter cake only (FC), macadamia husk compost only (MHC), inorganic fertilizer only (IF), a combination of filter cake and inorganic fertilizer (FC+IF), a combination of macadamia husk compost and inorganic fertilizer (MHC+IF), and a control (CONT)—were included in the investigation for the purpose of comparison. To achieve this, 1 kg of compost was homogenized with 20 kg of soil and filled into graduated 25 L buckets. The experimental design was completely randomized. The plants were grown for 4 months. The results indicated that all treatments altered the soil fertility positively. There were indications that both filter cake and macadamia husk compost inhibited the absorption of iron (Fe), copper (Cu), and aluminum (Al). Also, zinc (Zn) and phosphorus (P) deficiencies in the initial soil were corrected after the application of the organic wastes. In terms of yield, FC+MHC was better than all other treatments. The outcome of this study will no doubt greatly benefit the resource-poor farmers of Northern KwaZulu-Natal who are involved in the production of orange-fleshed sweet potatoes.
The Online Identification of the Behaviour of Pollutants inside the Tunnel Tube
Authors: Hrbček Jozef , Ždánsky Juraj , Nemec Dušan , Hruboš Marián
Published: October 2023

A tunnel tube is a relatively small space that allows for the accumulation of gaseous and liquid substances containing harmful substances. Given this fact, a ventilation system is the most critical component of a tunnel’s technological equipment, greatly influencing its reliability and safe operation. The dynamic behaviour of pollutants in the tunnel tube is characterized by a significant stochastic component and changing parameters over time due to pressure, airflow, and atmospheric condition changes. This work addresses the issue of modelling individual parts of the tunnel tube for optimal tunnel ventilation control. It is necessary to create a model of a controlled system that is used for predicting process variables to calculate optimal control action. By using recursive identification methods in conjunction with a predictive controller, the proposed concept can be applied to numerous similar applications.
Coverage Optimization of WSNs Based on Enhanced Multi-Objective Salp Swarm Algorithm
Authors: Yang Dan-Dan , Mei Meng , Zhu Yu-Jun , He Xin , Xu Yong , Wu Wei
Published: October 2023

In complex two-dimensional monitoring environments, how to enhance network efficiency and network lifespan while utilizing limited energy resources, and ensuring that wireless sensor networks achieve the required partial coverage of the monitoring area, are the challenges of optimizing coverage in wireless sensor networks.With the premise of ensuring connectivity in the target network area, an enhanced multi-objective salp swarm algorithm based on non-dominated sorting (EMSSA) is proposed in this paper, by jointly optimizing network coverage, node utilization, and network energy balance objectives. Firstly, the logistic chaotic mapping is used to maintain the diversity of the initial salp swarm population. Secondly, to balance global and local search capabilities, a new dynamic convergence factor is introduced. Finally, to escape local optima more effectively, a follower updating strategy is implemented to reduce the blind following of followers while retaining superior individual information. The effectiveness of the strategy is validated through comparative experiments on ZDT and DTLZ test functions, and the proposed algorithm is applied to coverage optimization in WSNs in complex environments. The results demonstrate that the algorithm can adjust coverage thresholds according to different application requirements, providing various effective coverage optimization configurations. With the same preset requirements for partial coverage achieved, both network efficiency and lifespan have been significantly improved.
Geographical Information System Enhancement Using Active Learning-Enhanced Semantic Segmentation
Authors: Youm Sungkwan , Go Sunghyun
Published: October 2023

Images captured by drones are increasingly used in various fields, including geographic information management. This study evaluates a procedure that incorporates active learning semantic segmentation for verifying the building registration ledger. Several semantic segmentation techniques were evaluated to extract building information, with ResNet identified as the most effective method for accurately recognizing building roofs. Using active learning, the training data were refined by removing instances with low similarity, leading to improved network performance of the model. The procedure was demonstrated to identify discrepancies between the building information system and the inferred label images, as well as to detect labeling errors on a training dataset. Through this research, the geographic information system dataset is enhanced with minimal human oversight, offering significant potential for urban planning and building detection advancements.
Assessment of Water Availability and Environmental Influence on People’s Lives in a Small Basin in the Hinterland of Pernambuco, Using the SUPer and UAV
Authors: Luz Gabrielly Gregório da , Miranda Rodrigo de Queiroga , Galvíncio Josicleda Domiciano
Published: October 2023

Water scarcity is a worldwide concern considering that water is a limited resource and essential for life. In Brazil, approximately 30% of its population lives in a semi-arid region covering about 20% of the country’s territorial extension, which is one of the areas that most suffers from a lack of water. The lack of water, mainly in the northeast of the country, has been a problem for years, as people who live in this territory suffer for months from the poor distribution of this resource, which increases the degree of inequality between the regions of the country. The research aims to show the effect of the hydrological cycle on the quality of vegetation and how such processing can end up affecting people’s lives and the environment. This study carried out a temporal analysis from 1961 to 2021. The hydrological model system used to assess water availability was the Pernambuco Hydrological Response Units SUPer-System. UAV (Unmanned Aerial Vehicles) was used to view the relationship between living and environmental conditions. The results showed a difference between the water balance today and in the future due to climate change. Thus, it is concluded that climate change will have different impacts at a small scale as well as on people’s living conditions as a result of different characteristics of the environment. It is very important to carry out studies on a detailed scale to provide better public policies for mitigating the effects of climate change on people’s lives.
The Center of Resistance of an Impacted Maxillary Canine: A Finite Element Analysis
Authors: Oh Sewoong , Choi Youn-Kyung , Kim Yong-Il , Kim Seong-Sik , Park Soo-Byung , Kim Sung-Hun
Published: October 2023

The aim of this study was to calculate the center of resistance (COR) of an impacted maxillary canine according to the stages of pericoronal tissue healing using the finite element method (FEM). The maxillary canine model was three-dimensionally scanned, and the structures surrounding the tooth were modeled using a computer-aided design program. The COR was calculated in the buccolingual (BL) and mesiodistal (MD) directions using the FEM. After applying a single force to a specific point of the tooth, several counter moments were applied to compensate for this at the same point. Thereafter, the displacement curve of the tooth axis for each counter moment was plotted. The intersection points between the displacement curves corresponded to the COR. At the beginning of healing, the COR of the MD and BL direction was located at 38.1% and 38.7% of the root length from the cementoenamel junction, respectively. At the end of healing, the COR of the MD and BL direction was located at 44.6% and 49.8% of the crown length from the cementoenamel junction, respectively. The COR of the impacted maxillary canine gradually shifts to the coronal side as the healing of the pericoronal tissue occurs.
CQDFormer: Cyclic Quasi-Dynamic Transformers for Hourly Origin-Destination Estimation
Authors: Li Guanzhou , Wu Jianping , He Yujing , Li Duowei
Published: October 2023

Due to the inherent difficulty in direct observation of traffic demand (including generation, attraction, and assignment), the estimation of origin–destination (OD) poses a significant and intricate challenge in the realm of Intelligent Transportation Systems. As the state-of-the-art methods usually focus on a single traffic demand distribution, accurate estimation of OD in the face of diverse traffic demand and road structures remains a formidable task. To this end, this study proposes a novel model, Cyclic Quasi-Dynamic Transformers (CQDFormer), which leverages forward and backward neural networks for effective OD estimation and traffic assignment. The employment of quasi-dynamic assumption and self-attention mechanism enables CQDFormer to capture the diverse and non-linear characteristics inherent in traffic demand. We utilize calibrated simulations to generate traffic count-OD pairwise data. Additionally, we incorporate real prior matrices and traffic count data to mitigate the distributional shift between simulation and the reality. The proposed CQDFormer is examined using Simuation of Urban Mobility (SUMO), on a large-scale downtown area in Haikou, China, comprising 2328 roads and 1171 junctions. It is found that CQDFormer shows satisfied convergence performance, and achieves a reduction of RMSE by 46.98%, MAE by 45.40% and MAPE by 29.76%, in comparison to the state-of-the-art method with the best performance.
Adaptive Deep Clustering Network for Retinal Blood Vessel and Foveal Avascular Zone Segmentation
Authors: Khan Azaz , Hao Jinyi , Dong Zihao , Li Jinping
Published: October 2023

Optical coherence tomography angiography (OCTA) is a new non-invasive imaging technology that provides detailed visual information on retinal biomarkers, such as the retinal vessel (RV) and the foveal avascular zone (FAZ). Ophthalmologists use these biomarkers to detect various retinal diseases, including diabetic retinopathy (DR) and hypertensive retinopathy (HR). However, only limited study is available on the parallel segmentation of RV and FAZ, due to multi-scale vessel complexity, inhomogeneous image quality, and non-perfusion, leading to erroneous segmentation. In this paper, we proposed a new adaptive segmented deep clustering (ASDC) approach that reduces features and boosts clustering performance by combining a deep encoder–decoder network with K-means clustering. This approach involves segmenting the image into RV and FAZ parts using separate encoder–decoder models and then employing K-means clustering on each part separated by the encoder–decoder models to obtain the final refined segmentation. To deal with the inefficiency of the encoder–decoder network during the down-sampling phase, we used separate encoding and decoding for each task instead of combining them into a single task. In summary, our method can segment RV and FAZ in parallel by reducing computational complexity, obtaining more accurate interpretable results, and providing an adaptive approach for a wide range of OCTA biomarkers. Our approach achieved 96% accuracy and can adapt to other biomarkers, unlike current segmentation methods that rely on complex networks for a single biomarker.
Heat Transfer Enhancement by Mitigating the Adverse Effects of Crossflow in a Multi-Jet Impingement Cooling System in Hexagonal Configuration by Coaxial Cylindrical Protrusion—Guide Vane Pairs
Authors: Untuç Ahmet Hikmet , Unverdi Salih Ozen
Published: October 2023

A novel compound multi-jet impingement system for enhanced cooling of a flat surface by augmenting its area with cylindrical protrusions (CPs) equipped with coaxial guide vanes (CGVs) and reducing deflection of jets by crossflow has been developed for high-heat removal applications. The cooling performance of coaxial circular jets impinging on the top faces of CPs placed in hexagonal configuration on a flat plate is evaluated by three-dimensional (3D) computational fluid dynamics (CFD) simulations. Jets impinging on the top faces of the protrusions are directed to their lateral faces and then to the base plate by the CGVs around the protrusions, resulting in up to 62.8% improvement in heat transfer rate with a minor increase in pressure drop. Effects of protrusion height and diameter on the pressure drop and cooling performance are studied for jet Reynolds (Re number range of 5000–20,000. Due to both shortened jet impingement lengths as the height of protrusions is increased and directing the expended fluid away from the impinging jets by CGVs, adverse effects of jet–crossflow interactions on cooling performance and fluid pumping power are significantly reduced. Performance evaluation criterion (PEC) of the novel compound multi-jet impingement cooling system (CMJICS) can be as high as 1.52.
A New Traffic System on Driver Sensitivity and Safe Distance Headway
Authors: Khan Zawar H. , Altamimi Ahmed B.
Published: October 2023

A new macroscopic traffic system is devised that observes the transition distance between the vehicles and driver sensitivity during traffic evolution. The driver sensitivity in this system is based on the traversed time over a 200 m road section and speed (velocity). In addition, the proposed system considers the safe distance headway as the distance between vehicles changes. An analogy system for vehicle flow behavior is devised from a spring–mass system with changes in traffic. The proposed system can characterize traffic evolution for small and large changes in density. Furthermore, the changes in the travel of traffic rearwards during congestion and forward during smooth flow are dependent on driver sensitivity, transition distance, and safe distance headway. The proposed traffic system is hyperbolic. The Payne Whitham traffic system is based on uniform constant velocity for different conditions, which characterizes traffic evolution unrealistically. The proposed traffic system and the Payne Whitham system are assessed over a 2000 m circular road for large changes in density in two examples. Both the Payne Whitham and proposed traffic systems are numerically implemented with the first order centered scheme in Matlab. The discretization stability of both systems is enforced with the Courant–Friedrich–Levy (CFL) condition. The proposed system with lower driver sensitivity evolves with larger changes, whereas the proposed system with larger density has smaller changes in density and velocity. The simulation results showed that the traffic evolution with the proposed system is more appropriate than with the Payne Whitham system.
Numerical Simulation Study on the Performance of Buried Pipelines under the Action of Faults
Authors: Zhang Rulin , Wang Chen , Li Shuai , Zhang Jixin , Liu Wenjing
Published: October 2023

The present paper investigates the mechanical behavior of buried steel pipelines crossing an active fault. Permanent ground deformation induced by an earthquake will cause serious damage to buried steel pipelines, resulting in buckling failure or even cracking damage to pipelines. Based on ABAQUS software, version 6.13., the model of an interacting soil–pipeline system is established, accounting for large strains and displacements and nonlinear material behavior, as well as contact and friction at the soil–pipeline interface. Numerical analysis is conducted through the incremental application of fault displacement. Combined with the force and deformation characteristics of buried pipelines, a strain-based design criterion is chosen to study the vertical displacement, axial compressive, and tensile strain of buried pipelines, etc. This paper focuses on the effects of horizontal fault displacement, fault type, and fault angle on the structural response of the pipe. The failure of the pipeline, such as wall wrinkling, local buckling, or rupture is identified. Furthermore, the effects of the pipeline internal pressure and pipe wall thickness are investigated. The results show that, when the pipeline depth is 1.5 m under the action of the fault, the buried pipeline will not be subject to beam buckling damage, and both tensile damage and shell buckling damage will occur. In this case, the critical displacement of the tensile failure is more than three times that of the shell buckling failure, which indicates that shell buckling damage is a greater threat to the pipeline. The pipeline is most susceptible to damage under the action of a strike-slip reverse fault. When the fault angle is equal to 45 degrees, the pipeline is more likely to be damaged, while it is relatively safe at a fault angle with 90 degrees. The results of this investigation can determine the fault displacement during pipeline failure and provide some reference for pipeline design.
Oat and Oat Processed Products—Technology, Composition, Nutritional Value, and Health
Authors: Leszczyńska Danuta , Wirkijowska Anna , Gasiński Alan , Średnicka-Tober Dominika , Trafiałek Joanna , Kazimierczak Renata
Published: October 2023

Oat has been known in food technology and human nutrition for a very long time. Its rich chemical composition and high nutritional value make it of interest to scientists in the field of food processing technology as well as nutritionists. Low-processed, whole-grain oat products rich in biologically active substances with well-proven preventive and therapeutic effects include not only dehulled oat grains and groats but also a wide range of breakfast cereals. These products fit into the definition of functional foods and are considered excellent prebiotics. The continuous development of cereal processing technologies can improve existing cereal products and help to create new ones; however, it also increases the possibility of raw material over-processing, thus decreasing its functional properties. Therefore, monitoring technological progress and the quality of the products obtained is of great value and interest for nutritionists and consumers. The work presented here aims at systematizing existing knowledge on oat products, their impact on human health, and progress in oat processing technology. It also brings insight into various new avenues for the utilization of oat products in food technology.
Bending Strength Evaluation of Three Dimensional Double Rachel Geosynthetic Cementitious Composite Mat (GCCM) under Environmental Conditions
Authors: Ko Eunhee , Lim Daeyoung , Kim Seunghyun , Youk Jiho , Jeon Hanyong
Published: October 2023

In this study, a reinforced geosynthetic cementitious composite mat (GCCM) with improved structural stability and reinforcement efficiency through yarn-in-lay technology was designed and manufactured. Additionally, a blowing agent was added to relax the cross-sectional reduction caused by the rapid curing and shrinkage for reduction of installation period. The impact resistance results showed a significant increase compared to the pre-reinforcement values. Through the analysis of blowing agent content, concrete filling ratio, and bending strength of the double raschel GCCM, optimal conditions were determined. Therefore, the double raschel GCCM showed improved flexural strength even after a short curing period of 10 days, along with excellent durability under environmental conditions.
Multi-Scale Residual Depthwise Separable Convolution for Metro Passenger Flow Prediction
Authors: Li Taoying , Liu Lu , Li Meng
Published: October 2023

Accurate prediction of metro passenger flow helps operating departments optimize scheduling plans, alleviate passenger flow pressure, and improve service quality. However, existing passenger flow prediction models tend to only consider the historical passenger flow of a single station while ignoring the spatial relationships between different stations and correlations between passenger flows, resulting in low prediction accuracy. Therefore, a multi-scale residual depthwise separable convolution network (MRDSCNN) is proposed for metro passenger flow prediction, which consists of three pivotal components, including residual depthwise separable convolution (RDSC), multi-scale depthwise separable convolution (MDSC), and attention bidirectional gated recurrent unit (AttBiGRU). The RDSC module is designed to capture local spatial and temporal correlations leveraging the diverse temporal patterns of passenger flows, and then the MDSC module is specialized in obtaining the inter-station correlations between the target station and other heterogeneous stations throughout the metro network. Subsequently, these correlations are fed into AttBiGRU to extract global interaction features and obtain passenger flow prediction results. Finally, the Hangzhou metro passenger inflow and outflow data are employed to assess the model performance, and the results show that the proposed model outperforms other models.
Real-Time Optical Detection of Artificial Coating Defects in PBF-LB/P Using a Low-Cost Camera Solution and Convolutional Neural Networks
Authors: Klamert Victor , Achsel Timmo , Toker Efecan , Bublin Mugdim , Otto Andreas
Published: October 2023

Additive manufacturing plays a decisive role in the field of industrial manufacturing in a wide range of application areas today. However, process monitoring, and especially the real-time detection of defects, is still an area where there is a lot of potential for improvement. High defect rates should be avoided in order to save costs and shorten product development times. Most of the time, effective process controls fail because of the given process parameters, such as high process temperatures in a laser-based powder bed fusion, or simply because of the very cost-intensive measuring equipment. This paper proposes a novel approach for the real-time and high-efficiency detection of coating defects on the powder bed surface during the powder bed fusion of polyamide (PBF-LB/P/PA12) by using a low-cost RGB camera system and image recognition via convolutional neural networks (CNN). The use of a CNN enables the automated detection and segmentation of objects by learning the spatial hierarchies of features from low to high-level patterns. Artificial coating defects were successfully induced in a reproducible and sustainable way via an experimental mechanical setup mounted on the coating blade, allowing the in-process simulation of particle drag, part shifting, and powder contamination. The intensity of the defect could be continuously varied using stepper motors. A low-cost camera was used to record several build processes with different part geometries. Installing the camera inside the machine allows the entire powder bed to be captured without distortion at the best possible angle for evaluation using CNN. After several training and tuning iterations of the custom CNN architecture, the accuracy, precision, and recall consistently reached >99%. Even defects that resembled the geometry of components were correctly classified. Subsequent gradient-weighted class activation mapping (Grad-CAM) analysis confirmed the classification results.
Special Issue: Intelligent Systems for Railway Infrastructure
Authors: Lee Jaesun , Sharma Sunil Kumar
Published: October 2023

Railway infrastructure plays a crucial role in the efficient operation of transportation systems across the globe [...]
A Reinforcement Learning Framework with Oversampling and Undersampling Algorithms for Intrusion Detection System
Authors: Abedzadeh Najmeh , Jacobs Matthew
Published: October 2023

Intrusion detection systems (IDSs) play a pivotal role in safeguarding networks and systems against malicious activities. However, the challenge of imbalanced datasets significantly impacts IDS research, skewing learning models towards the majority class and diminishing accuracy for the minority class. This study introduces the Reinforcement Learning (RL) Framework with Oversampling and Undersampling Algorithm (RLFOUA) to address imbalanced datasets. RLFOUA combines RL with diverse resampling algorithms, creating an adaptive learning environment. It integrates the novel True False Rate Synthetic Minority Oversampling Technique (TFRSMOTE) algorithm, emphasizing data-level approaches. Additionally, RLFOUA employs a cost-sensitive approach based on classification metrics. Using the CSE-CIC-IDS2018 and NSL-KDD datasets, RLFOUA demonstrates substantial improvement over existing resampling techniques. Achieving an accuracy of 0.9981 for NSL-KDD and 0.9846 for CSE-CIC-IDS2018, the framework’s performance is evaluated using F1 score, accuracy, precision, recall, and a proposed Index Metric (IM). RLFOUA presents a significant advancement in addressing class imbalance challenges in IDS. It shows an average accuracy improvement of 21.5% compared to the recent resampling technique AESMOTE on the NSL-KDD dataset.
Exploring User Experience in Sustainable Transport with Explainable AI Methods Applied to E-Bikes
Authors: Laqua Annika , Schnee Jan , Pletinckx Jo , Meywerk Martin
Published: October 2023

Sustainable modes of transport are being promoted to achieve global climate goals. The perceived user experience is decisive for the choice of transport mode. To increase the share of sustainable transport in total traffic, the user experience is placed into the spotlight, raising the need for appropriate exploration methods. Machine learning (ML) techniques have become increasingly popular in the transport domain, but the black-box nature of ML models poses significant challenges in interpreting the relationship between model input and output. Explainable AI methods (XAI) can fill this gap by providing post hoc interpretation methods for black-box models. The aim of the present work was therefore to assess the potential of XAI to explore user experience in transport. The introduced method was based on a popular XAI method named SHAP (SHapley Additive exPlanations). Applied to the use case of e-bikes, we aimed to explore factors influencing the riding experience on e-bikes. We applied Gaussian process regression to data collected in a cycling study from 55 e-bike riders including rider behaviour, motor power and riding dynamics. Applying SHAP, we compared the riding experience of four rider types identified by hierarchical cluster analysis. The results provide insights into the riding experience on e-bikes: motor power, rider behaviour and riding dynamics were found to be meaningful predictors differing in their impact between rider types. Our results can be regarded as a proof of concept and demonstrate the potential of XAI to enhance the understanding of user experience in transport.
A Real-Time Simulator for Navigation in GNSS-Denied Environments of UAV Swarms
Authors: Zhang He , Miao Cunxiao , Zhang Linghao , Zhang Yunpeng , Li Yufeng , Fang Kaiwen
Published: October 2023

Accurate localization is the foundation of unmanned aerial vehicle (UAV) swarm applications in the global navigation satellite system (GNSS)-denied environment. However, the implementation of UAV formation in the real world is costly and time-consuming, which leads to difficulties in developing navigation algorithms. A real-time simulator for navigation in GNSS-denied environments is proposed, which includes world, model, controller, scene matching navigation (SMN), relative navigation and formation controller modules. Each module can be modified, which means that users can test their own algorithms. A novel inertial-aided SMN (ISMN) algorithm is developed and a relative navigation method that does not rely on inter communication is proposed. ISMN and relative navigation based on a camera and ultrawideband (UWB) are tested on the platform. Based on the developed simulation system, the navigation algorithms can be verified easily, which can reduce the time and personnel requirements during flight testing.
Monitoring, Evaluation, and Improvement Model for Process Precision and Accuracy
Authors: Tsai Chih-Ming , Chiou Kuo-Ching , Chen Kuen-Suan , Yu Chun-Min
Published: October 2023

Process Capability Indices (PCIs) are devices widely used in the industry to evaluate process quality. The commonly used process capability indices all contain accuracy indices and precision indices. As the accuracy index is closer to zero, the process accuracy is higher. The precision index mainly represents the extent of process variation. As the value is smaller, the process variation is smaller, that is, the precision is higher. In fact, process capability indices are the functions of accuracy indices and precision indices. Obviously, as long as accuracy indices and precision indices are controlled, the process capability indices can be controlled as well. Therefore, this study first derived accuracy and precision control charts to observe not only process accuracy but also process precision. Then, this study adopted in-control data to acquire a 100 (1 − α)% confidence region of an accuracy index and a precision index, with which statistical tests were performed. Subsequently, according to the definition of the six sigma quality level, both indices were examined. Furthermore, based on the testing results, suggestions for process improvement were proposed, including correcting the direction of process deviation and deciding whether to reduce process variation. Finally, this study demonstrated the applicability of the proposed model using an empirical example.
Chemical Composition and Antimicrobial Activity of Lavender (Lavandula angustifolia Mill.), Peppermint (Mentha piperita L.), Raspberry Seed (Rubus idaeus L.), and Ylang-Ylang (Cananga odorata (Lam.) Essential Oils—Towards Hurdle Technologies in the Production of Chocolate Mousse
Authors: Denkova Zapryana , Goranov Bogdan , Blazheva Denica , Tomova Teodora , Teneva Desislava , Denkova-Kostova Rositsa , Slavchev Aleksandar , Pagán Rafael , Degraeve Pascal , Kostov Georgi
Published: October 2023

The growing consumer demand for the development of functional foods with a number of benefits for the consumer has led to a considerable increase in the studies focused on examining different natural agents to be included in the composition of newly developed functional foods. The chemical compositions of the essential oils (EOs) of lavender (Lavandula angustifolia Mill.), peppermint (Mentha piperita L.), raspberry seed (Rubus idaeus L.), and ylang-ylang (Cananga odorata (Lam.)) were determined using gas chromatography with a mass selective detector (GC-MS). The antibacterial and antifungal activities of these EOs were examined using a high-throughput 96-well microplate bioassay procedure and the MICs of each EO against each test microorganism were determined. The results indicated significant antimicrobial activity against Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 6538, Salmonella abony NTCC 6017, Pseudomonas aeruginosa NBIMCC 1390, Bacillus subtilis ATCC 19659, Penicillium chrysogenum ATCC 28089, Fusarium moniliforme ATCC 38932, Aspergillus niger ATCC 1015, and Aspergillus flavus ATCC 9643. To explore their potential applications in food preservation, model chocolate mousse food emulsions were prepared that incorporated EOs and/or selected probiotic lactobacilli strains in both free and encapsulated forms. The inclusion of EOs and/or probiotic lactobacilli resulted in enhanced microbial safety and an extended shelf life. Furthermore, the chocolate mousse variants that were biopreserved with the inclusion of probiotic lactobacilli maintained a high viable lactobacillus cell concentration throughout the storage period. As a result, these products would not only be suitable as functional probiotic foods but also as effective delivery vehicles for probiotic lactobacilli.