bluuebunny/crossref_metadata_2025 huggingface dataset:
Radiological Diagnosis and Advances in Imaging of Vertebral Compression Fractures
Authors: Miao Kathleen H. , Miao Julia H. , Belani Puneet , Dayan Etan , Carlon Timothy A. , Cengiz Turgut Bora , Finkelstein Mark
Published: September 2024

Vertebral compression fractures (VCFs) affect 1.4 million patients every year, especially among the globally aging population, leading to increased morbidity and mortality. Often characterized with symptoms of sudden onset back pain, decreased vertebral height, progressive kyphosis, and limited mobility, VCFs can significantly impact a patient’s quality of life and are a significant public health concern. Imaging modalities in radiology, including radiographs, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) studies and bone scans, play crucial and evolving roles in the diagnosis, assessment, and management of VCFs. An understanding of anatomy, and the extent to which each imaging modality serves to elucidate that anatomy, is crucial in understanding and providing guidance on fracture severity, classification, associated soft tissue injuries, underlying pathologies, and bone mineral density, ultimately guiding treatment decisions, monitoring treatment response, and predicting prognosis and long-term outcomes. This article thus explores the important role of radiology in illuminating the underlying anatomy and pathophysiology, classification, diagnosis, treatment, and management of patients with VCFs. Continued research and advancements in imaging technologies will further enhance our understanding of VCFs and pave the way for personalized and effective management strategies.
Experimental Study of the Random Wave-Induced Hydrodynamics and Soil Response in a Porous Seabed Around Double Piles
Authors: Wang Mingqing , Si Wenqi , Gao Yaru , Cui Lin , Jeng Dong-Sheng , Sun Ke , Chen Bing , Zhao Hongyi
Published: September 2024

The evaluation of the wave-induced pore pressures around the offshore piles has attracted great attentions among coastal engineers, because they have been commonly used as foundations of numerous marine infrastructures. This paper presents comparative studies of the random wave-induced transient seabed response around single and double piles in a sandy seabed through a series of wave flume experiments. The influences of relative spacing ratios, wave incidence angles, and front pile diameters under different random wave parameters on oscillatory pore pressures in the vicinity of double piles are examined. In addition, variations in wave profiles and dynamic wave pressures surrounding single and double piles are quantitatively analyzed. Based on the experimental results, the following conclusions can be drawn: (1) under the influence of random waves, the wave profiles around the double piles exhibit obvious irregularity and nonlinearity; (2) the shielding effect existing in the tandem piles results in lower dynamic wave pressures around the rear pile compared to the front pile; (3) the pore pressures on the front surface of the double piles decrease with increasing soil depth, with a decreasing attenuation rate at each layer; (4) when the relative spacing ratio G/D2=3, the group-pile effect weakens, leading to an increase in the pore pressures around the rear pile, approaching the results of a single pile under conditions of lower significant wave heights or periods; (5) the intense disturbance effect caused by large wave incidence angles exacerbates the pore pressure response around the double piles; (6) when the diameter of the front pile in the tandem piles increases, it enhances the shielding effect, thus suppressing the seabed response around the rear pile. In contrast, it causes an increase in the wave surface around the double piles, exacerbating the pore pressure response in the seabed. The latter effect becomes more pronounced when the significant wave height is larger.
Pore Characteristics of Hydrate-Bearing Sediments from Krishna-Godavari Basin, Offshore India
Authors: Guan Wen , Yang Hailin , Lu Xindi , Lu Hailong
Published: September 2024

Pore-filling hydrates are the main occurrence forms of marine gas hydrates. Pore characteristics are a vital factor affecting the thermodynamic properties of hydrates and their distribution in sediments. Currently, the characterization of the pore system for hydrate-bearing reservoirs are little reported. Therefore, this paper focuses on the Krishna-Godavari Basin, via various methods to characterize the hydrate-bearing sediments in the region. The results showed that X-ray diffraction (XRD) combined with scanning electron microscopy (SEM) and cast thin section (CTS) can better characterize the mineral composition in the reservoir, high-pressure mercury injection (HPMI) focused on the contribution of pore size to permeability, constant-rate mercury injection (CRMI) had the advantage of distinguishing between the pore space and pore throat, and nuclear magnetic resonance cryoporometry (NMRC) technique can not only obtain the pore size distribution of nanopores with a characterization range greater than nitrogen gas adsorption (N2GA), but also quantitatively describe the trend of fluids in the pore system with temperature. In terms of the pore system, the KG Basin hydrate reservoir develops nanopores, with a relatively dispersed mineral distribution and high content of pyrite. Rich pyrite debris and foraminifera-rich paleontological shells are observed, which leads to the development of intergranular pores and provides more nanopores. The pore throat concentration and connectivity of the reservoir are high, and the permeability of sediments in the same layer varies greatly. The reason for this phenomenon is the significant difference in average pore radius and pore size contribution to pore permeability. This article provides a reference and guidance for exploring the thermodynamic stability of hydrates in sediments and the exploration and development of hydrates by characterizing the pores of hydrate reservoirs.
A Study on Offshore Anchor Selection with a Focus on Torpedo Anchor Stability and Performance
Authors: Chang Hung-Chun , Noorizadegan Amir , Liu Yi-Hsiu , Ma Kai-Tung
Published: September 2024

The global pursuit of renewable energy has significantly accelerated offshore wind energy development. Floating offshore wind turbines (FOWTs) are increasingly in the spotlight as they offer superior capabilities for harnessing abundant wind resources in deep-water areas, outperforming traditional fixed-bottom turbines. The deployment and station-keeping of these floating structures are critically dependent on robust mooring systems and the precise selection of anchoring solutions. This paper provides an overview of various anchors, including driven and suction caissons, torpedo, and drag anchors, and their applications in real-world projects. These commonly used anchors were discussed in relation to mooring types, soil conditions, and expected bearing capacities. Torpedo anchor installation failures have been reported in cases where excessive tilt angles occur during deployment. This motivates us to present an in-depth study on the importance of directional stability during installation of torpedo anchors. The study will utilize computational fluid dynamics Star-CCM+ 2402 to analyze and assess the impact of the center of gravity configuration on stabilization. Additionally, theoretical formulas will be used to estimate the holding capacity that the torpedo anchor can provide. These insights are designed to assist wind energy developers in making informed and effective anchoring decisions for floating wind turbine projects.
RNAi-Based Approaches to Control Mycotoxin Producers: Challenges and Perspectives
Authors: Stakheev Alexander A. , Taliansky Michael , Kalinina Natalia O. , Zavriev Sergey K.
Published: September 2024

Mycotoxin contamination of food and feed is a worldwide problem that needs to be addressed with highly efficient and biologically safe techniques. RNA interference (RNAi) is a natural mechanism playing an important role in different processes in eukaryotes, including the regulation of gene expression, maintenance of genome stability, protection against viruses and others. Recently, RNAi-based techniques have been widely applied for the purposes of food safety and management of plant diseases, including those caused by mycotoxin-producing fungi. In this review, we summarize the current state-of-the-art RNAi-based approaches for reducing the aggressiveness of key toxigenic fungal pathogens and mycotoxin contamination of grain and its products. The ways of improving RNAi efficiency for plant protection and future perspectives of this technique, including progress in methods of double-stranded RNA production and its delivery to the target cells, are also discussed.
Increased Cadmium Load, Vitamin D Deficiency, and Elevated FGF23 Levels as Pathophysiological Factors Potentially Linked to the Onset of Acute Lymphoblastic Leukemia: A Review
Authors: Djulejic Vuk , Ivanovski Ana , Cirovic Ana , Cirovic Aleksandar
Published: September 2024

The preventability of acute lymphocytic leukemia during childhood is currently receiving great attention, as it is one of the most common cancers in children. Among the known risk factors so far are those affecting the development of gut microbiota, such as a short duration or absence of breastfeeding, cesarean section, a diet lacking in short-chain fatty acids (SCFAs), the use of antibiotics, absence of infection during infancy, and lack of pets, among other factors. Namely, it has been shown that iron deficiency anemia (IDA) and lack of vitamin D may cause intestinal dysbiosis, while at the same time, both increase the risk of hematological malignancies. The presence of IDA and vitamin D deficiency have been shown to lead to a decreased proportion of Firmicutes in stool, which could, as a consequence, lead to a deficit of butyrate. Moreover, children with IDA have increased blood concentrations of cadmium, which induces systemic inflammation and is linked to the onset of an inflammatory microenvironment in the bone marrow. Finally, IDA and Cd exposure increase fibroblast growth factor 23 (FGF23) blood levels, which in turn suppresses vitamin D synthesis. A lack of vitamin D has been associated with a higher risk of ALL onset. In brief, as presented in this review, there are three independent ways in which IDA increases the risk of acute lymphocytic leukemia (ALL) appearance. These are: intestinal dysbiosis, disruption of vitamin D synthesis, and an increased Cd load, which has been linked to systemic inflammation. All of the aforementioned factors could generate the appearance of a second mutation, such as ETV6/RUNX1 (TEL-AML), leading to mutation homozygosity and the onset of disease. ALL has been observed in both IDA and thalassemia. However, as IDA is the most common type of anemia and the majority of published data pertains to it, we will focus on IDA in this review.
Daily and Weekly Geometric Brownian Motion Stock Index Forecasts
Authors: Sinha Amit
Published: September 2024

In this manuscript, daily and weekly geometric Brownian motion forecasts are obtained and tested for reliability for three indexes, DJIA, NASDAQ and S&P 500. A twenty-year rolling window is used to estimate the drift and diffusion components, and applied to obtain one-period-ahead geometric Brownian motion index values and associated probabilities. Expected values are estimated by totaling up the product of the index value and its associated probabilities, and test for reliability. The results indicate that geometric Brownian-simulated expected index values estimated using one thousand simulations can be reliable forecasts of the actual index values. Expected values estimated using one or ten simulations are not as reliable, while those obtained using at least one hundred simulations could be useful.
Constructing Divisia Monetary Aggregates for the Asian Tigers
Authors: Barnett William A. , Lee JongSoo , Mohiuddin Naowar
Published: September 2024

This study constructs Divisia monetary aggregates for the “Asian Tigers”—Hong Kong (1999–2024), South Korea (2009–2024), Singapore (1991–2021), and Taiwan (2005–2024)—and assesses whether Divisia monetary aggregates explain nominal GDP better than simple-sum money. Our findings demonstrate that Divisia indices respond more sensitively to economic shocks. For Hong Kong and Taiwan, narrow Divisia money provides the best explanations for fluctuations in nominal GDP. Our results suggest that Divisia monetary aggregates can be beneficial for monetary policy analysis in these territories and underscore the importance of further research into the empirical performance of Divisia monetary aggregates in macroeconomic prediction.
Exploring the Usefulness of Real Options Theory for Foreign Affiliate Divestments: Real Abandonment Options’ Applications
Authors: Čirjevskis Andrejs
Published: September 2024

Scholars propose that future research on real options theory should shift attention away from option buying during the first investment stage and toward option execution after investment. Researchers maintain that it would be interesting to explore the circumstances under which investors decide to withdraw their investments, thereby exercising the option to abandon their investments. The present research seeks to fill the gap in the literature and investigate the applicability of real options theory when an organization enhances sustainability policies while focusing on disciplined capital allocation through exit strategies. With case study data on Natura &Co’s divestment strategy for the Body Shop in November 2023, a real options analysis revealed the method’s practical advantages and disadvantages. This paper investigates real options theory in the context of the divestments of foreign affiliates, providing unique viewpoints and enhancing the theory beyond previous knowledge while also increasing our understanding of the divestiture phenomenon. This study concludes with a review of this paper’s theoretical contributions to real options theory, the managerial and practical/social implications of real options applications in general, and the valuation methods of abandonment options in particular, shedding light on the potential of future research.
Evaluating the Impact of Long-Term Demographic Changes on Local Participation in Italian Rural Policies (2014–2020): A Spatial Autoregressive Econometric Model
Authors: Mantino Francesco , De Fano Giovanna , Asaro Gianluca
Published: September 2024

This study elaborates on a typology of demographic change and tests this definition at the lowest granular level (LAU2, municipality) with official data. This typology distinguishes between fragile and resilient municipalities based on population dynamics (in terms of duration and intensity) over 1991–2021. This study’s second aim is to elaborate a spatial autoregressive econometric model to evaluate to what extent and in which direction the rate of participation of potential beneficiaries of the Rural Development Programmes (RDPs) of 2014–2020 is affected by demographic change and other explanatory variables. Regression models compare the results of the OLS (aspatial) and spatial autoregressive models (SAR) of four types of participation rates (all RDP schemes; all LEADER schemes; sectoral schemes of RDP and LEADER; non-sectoral schemes of RDPs and LEADER). This comparison makes it possible to understand the differences between centralised and decentralised management and between sectoral and broader rural-targeted schemes. The results of the models appear attractive in interpreting the role of RDP instruments in different regions and local areas. First, the rate of participation is strongly dependent on macro-regional differences. Regarding the demographic factors at the local level, this study highlights that demographic fragility does not necessarily hamper the use of RDP measures. Conversely, the participation rate in RDP policy schemes seems particularly significant in very fragile areas, whereas significance has yet to be proved in other demographic typologies. This result holds particularly true for the policy uptake of non-sectoral schemes. Furthermore, LEADER decentralised interventions fit the fragile areas more than resilient and vital ones due to the territorially targeted approach followed by the Local Action Groups.
Comparative Study of Cognitive Differences in Rural Landscapes Based on Eye Movement Experiments
Authors: Wang Yanbo , Li Kankan , Li Jiaxin , Hao Tiange , Zhou Zhishu
Published: September 2024

With the booming development of rural tourism, the users of rural environments are gradually becoming more diverse. Both tourists and villagers are the main appreciators of rural landscapes, but the cognitive similarities and differences in rural landscape between the two have not yet been explored. Therefore, taking Wangshang Village, located in Shaanxi Province, China as a case study, this research used a combination of quantitative analysis (eye-tracking technology) and qualitative analysis (semi-structured interviews) to compare and analyze the cognitive similarities and differences of rural landscapes between tourists and villagers. The experimental results showed that the cognitive similarities and differences in rural landscapes between tourists and villagers are mainly reflected in their level of cognition, observation methods, and key elements of focus. The reasons for cognitive differences are due to the different living backgrounds of the two groups of subjects, as well as their varying levels of familiarity, novelty, and personal needs towards rural landscapes. In conclusion, studying the cognitive differences between the two groups of participants, tourists and villagers, can help address the homogenization problem faced by rural landscapes. Meanwhile, the results of this study also provide theoretical guidance and methodological support for rural landscape design.
A Corpus-Based Study of Spatial Frames of References in Early Child Mandarin Chinese
Authors: Wu Dandan , Degotardi Sheila , Li Hui , Tong Nga Yui
Published: September 2024

This study examines the developmental pattern of spatial frames of reference (FoRs) in Chinese preschoolers using the naturalistic data elicited from the Beijing Early Childhood Mandarin Corpus. Altogether, 2837 static spatial sentences were identified from the corpus, and 785 of them used FoRs; thus, they were analysed using the seven-class FoRs coding system developed from the literature review. The results indicated that: (1) six classes were produced by the Beijing preschoolers, including the direct reference (DR), geomorphic reference (GR), landmark-based reference (LBR), object-centred reference (OCR), relative reference (RR), and people-centred reference (PCR). But, the absolute reference (AR) frequently used by Beijing adults was not produced by the preschoolers; (2) significant age differences were found in the utterances with reference and demonstrative sentences and were also identified in the production of OCR, PCR, and RR; (3) there were no significant gender or gender x age effects in the production of FoRs, except for the no-frame sentences; and (4) there was a stable and consistent pattern of FoRs allocation by age, and the most frequently used was OCR. All these findings indicate interactions among language, culture, and cognition.
Experimental Research on Pollution-Free Alcohol Cutting Fluid in Scratching of Single-Crystal Copper Material
Authors: Wu Xian , Li Benchi , Sun Ke , Fang Congfu , Shen Jianyun
Published: September 2024

Cutting fluid can improve the heat dissipation and lubrication in the cutting process and thus increase the machining quality. In this work, a pollution-free alcohol solution was proposed as the cutting fluid in an ultra-precision cutting process to explore green cutting fluids. The scratching experiments were conducted with the alcohol cutting fluid to study its effect on the cutting process. It is found that the use of an alcohol cutting fluid, on average, reduces the tangential and normal force about 27–53%, but exhibits few effects on the friction coefficient in the cutting process. Compared to dry cutting, the alcohol cutting fluid reduces the exposed shear slip steps on the outside surface of the chip, which implies the decreased chip deformation degree of workpiece material in the cutting process. The alcohol cutting fluid can reduce microburrs and decrease the machined surface roughness Ra from 21 nm to 9.9 nm in the ultra-precision turning application on single-crystal copper material.
Promoting Synergies to Improve Manufacturing Efficiency in Industrial Material Processing: A Systematic Review of Industry 4.0 and AI
Authors: Ahmmed Md Sazol , Isanaka Sriram Praneeth , Liou Frank
Published: September 2024

The manufacturing industry continues to suffer from inefficiency, excessively high prices, and uncertainty over product quality. This statement remains accurate despite the increasing use of automation and the significant influence of Industry 4.0 and AI on industrial operations. This review details an extensive analysis of a substantial body of literature on artificial intelligence (AI) and Industry 4.0 to improve the efficiency of material processing in manufacturing. This document includes a summary of key information (i.e., various input tools, contributions, and application domains) on the current production system, as well as an in-depth study of relevant achievements made thus far. The major areas of attention were adaptive manufacturing, predictive maintenance, AI-driven process optimization, and quality control. This paper summarizes how Industry 4.0 technologies like Cyber-Physical Systems (CPS), the Internet of Things (IoT), and big data analytics have been utilized to enhance, supervise, and monitor industrial activities in real-time. These techniques help to increase the efficiency of material processing in the manufacturing process, based on empirical research conducted across different industrial sectors. The results indicate that Industry 4.0 and AI both significantly help to raise manufacturing sector efficiency and productivity. The fourth industrial revolution was formed by AI, technology, industry, and convergence across different engineering domains. Based on the systematic study, this article critically explores the primary limitations and identifies potential prospects that are promising for greatly expanding the efficiency of smart factories of the future by merging Industry 4.0 and AI technology.
Multi-Physical Field, Coupled, Mixed Lubrication Analysis of Hydraulic Reciprocating Vacuum Lip Seal
Authors: Zhao Yan , Cai Zhihui , Feng Ziming , Chen Wenzheng , Yuan Heng
Published: September 2024

Engineering practice has demonstrated that seal failure can result in severe leakage and wear, reducing the efficiency of hydraulic systems and even leading to major safety risks. Currently, analyses of the thermal aspect of seal interfaces are relatively limited, with most studies focusing on mechanical analysis. However, in actual applications, temperature has a significant impact on sealing performance. In this paper, nonlinear elastomechanics, viscous fluid mechanics, micro-contact mechanics, micro-deformation theory, and thermodynamics are coupled to establish a mixed lubrication model considering the thermal effect. The reliability of the mixed lubrication model is verified through experiments, and the temperature distribution of the oil film in the sealing area and the temperature distribution of the seal ring are simulated. Finally, the effects of the reciprocating speed, root mean square roughness, fluid medium pressure, and seal pre-compression on seal friction force and leakage are investigated. The results show that the heat generated in the sealing area accumulates at the bottom of the V-ring. Under the same conditions, compared with the instroke, the temperature-rise area of the outstroke is biased to the left and the increase in temperature is greater. In addition, the piston rod speed and the preliminary compression of the seal ring have a greater impact on the overall seal friction force and leakage. Under a lower seal pre-compression, the RMS roughness has a great influence on the leakage and friction in the outstroke, while the impact of the internal stroke is limited.
Unsteady Flow Behaviors and Vortex Dynamic Characteristics of a Marine Centrifugal Pump under the Swing Motion
Authors: Yuan Ye , Junejo Abdul Rahim , Wang Jun , Chen Bo
Published: September 2024

Due to the effects of swing motion, the performances and internal flow characteristics of marine centrifugal pump undergo some unsteady variations in the marine environment. The hydraulic test system with six degree of freedom parallel motion platform is established to study the pump performance characteristics at the different heel angles of steady roll position and pitch position. The pump head gradually decreases as heel angle increases. The pump head has decreased by 7% to reach the minimum at the 15° heel angle of roll position. At the same heel angle, the head at the roll position is lower than that at the pitch position under the rated flow condition. The fluid in the impeller passage is subjected to the additional inertial force of roll motion or pitch motion under unsteady swing motion, inducing some flow bias phenomena in the velocity field. The unsteady development of flow velocity induces the intense vortex motion, and the shedding and dissipation of interblade vortices are affected. The periodic flow-induced pulsation characteristics obviously appear in the impeller passage. The pulsation periodicity and pressure amplitude are influenced due to the swing motion. The pitch motion induces the greater hydraulic excitation and fluid-induced vibration amplitude. In addition to the pressure pulsation at the low frequencies, the pulsation amplitude at 20 times the shaft frequency is evident under pitch motion.
Some Combined Results from Eneström–Kakeya and Rouché Theorems on the Generalized Schur Stability of Polynomials and the Stability of Quasi-Polynomials-Application to Time-Delay Systems
Authors: De la Sen Manuel
Published: September 2024

This paper derives some generalized Schur-type stability results of polynomials based on several forms and generalizations of the Eneström–Kakeya theorem combined with the Rouché theorem. It is first investigated, under sufficiency-type conditions, the derivation of the eventually generalized Schur stability sufficient conditions which are not necessarily related to the zeros of the polynomial lying in the unit open circle. In a second step, further sufficient conditions were introduced to guarantee that the above generalized Schur stability property persists within either the same above complex nominal stability region or in some larger one. The classical weak and, respectively, strong Schur stability in the closed and, respectively, open complex unit circle centred at zero are particular cases of their corresponding generalized versions. Some of the obtained and proved results are further generalized “ad hoc” for the case of quasi-polynomials whose zeros might be interpreted, in some typical cases, as characteristic zeros of linear continuous-time delayed time-invariant dynamic systems with commensurate constant point delays.
Optimizing Convolutional Neural Network Architectures
Authors: Balderas Luis , Lastra Miguel , Benítez José M.
Published: September 2024

Convolutional neural networks (CNNs) are commonly employed for demanding applications, such as speech recognition, natural language processing, and computer vision. As CNN architectures become more complex, their computational demands grow, leading to substantial energy consumption and complicating their use on devices with limited resources (e.g., edge devices). Furthermore, a new line of research seeking more sustainable approaches to Artificial Intelligence development and research is increasingly drawing attention: Green AI. Motivated by an interest in optimizing Machine Learning models, in this paper, we propose Optimizing Convolutional Neural Network Architectures (OCNNA). It is a novel CNN optimization and construction method based on pruning designed to establish the importance of convolutional layers. The proposal was evaluated through a thorough empirical study including the best known datasets (CIFAR-10, CIFAR-100, and Imagenet) and CNN architectures (VGG-16, ResNet-50, DenseNet-40, and MobileNet), setting accuracy drop and the remaining parameters ratio as objective metrics to compare the performance of OCNNA with the other state-of-the-art approaches. Our method was compared with more than 20 convolutional neural network simplification algorithms, obtaining outstanding results. As a result, OCNNA is a competitive CNN construction method which could ease the deployment of neural networks on the IoT or resource-limited devices.
A Composition Formula for the Modified Analytic Function Space Fourier–Feynman Transform
Authors: Chung Hyun Soo
Published: September 2024

Composition formula is one of the most important research topics in functional analysis theory. Various relationships can be obtained using the composition formula. Since the generalized Brownian motion process used in this paper has a non-zero mean function, there are many restrictions on obtaining a composition formula for the modified analytic function space Fourier–Feynman transform. This paper contains an idea of how the composition Formula (9) below is established for the modified analytic function space Fourier–Feynman transform on function space. Using this idea, we are able to solve a problem that had never been solved before.
The Forecasting of the Spread of Infectious Diseases Based on Conditional Generative Adversarial Networks
Authors: Krivorotko Olga , Zyatkov Nikolay
Published: September 2024

New epidemics encourage the development of new mathematical models of the spread and forecasting of infectious diseases. Statistical epidemiology data are characterized by incomplete and inexact time series, which leads to an unstable and non-unique forecasting of infectious diseases. In this paper, a model of a conditional generative adversarial neural network (CGAN) for modeling and forecasting COVID-19 in St. Petersburg is constructed. It takes 20 processed historical statistics as a condition and is based on the solution of the minimax problem. The CGAN builds a short-term forecast of the number of newly diagnosed COVID-19 cases in the region for 5 days ahead. The CGAN approach allows modeling the distribution of statistical data, which allows obtaining the required amount of training data from the resulting distribution. When comparing the forecasting results with the classical differential SEIR-HCD model and a recurrent neural network with the same input parameters, it was shown that the forecast errors of all three models are in the same range. It is shown that the prediction error of the bagging model based on three models is lower than the results of each model separately.
AGV Scheduling for Optimizing Irregular Air Cargo Containers Handling at Airport Transshipment Centers
Authors: Li Jie , Zou Mingkai , Lv Yaqiong , Sun Di
Published: September 2024

Airport transshipment centers play a pivotal role in global logistics networks, enabling the swift and efficient transfer of cargo, which is essential for maintaining supply-chain continuity and reducing delivery times. The handling of irregularly shaped air cargo containers presents new constraints for automated guided vehicles (AGVs), as these shapes can complicate loading and unloading processes, directly impacting overall operational efficiency, turnaround times, and the reliability of cargo handling. This study focuses on optimizing the scheduling of AGVs to enhance cargo-handling efficiency at these hubs, particularly for managing irregular air cargo containers. A mixed-integer linear programming (MILP) model is developed, validated for feasibility with the Gurobi solver, and designed to handle large-scale operations. It incorporates a novel approach by integrating a simulated annealing optimized genetic algorithm (GA). The experimental results demonstrate that the designed algorithm can solve models of considerable size within 8 s, offering superior time efficiency compared to the solver, and an average solution quality improvement of 12.62% over the genetic algorithm, significantly enhancing both the model’s efficiency and scalability. The enhanced AGV scheduling not only boosts operational efficiency but also ensures better integration within the global logistics framework. This research provides a robust foundation for future advancements in logistics technology, offering both theoretical and practical insights into optimizing complex transportation networks.
Constraint Qualifications and Optimality Conditions for Multiobjective Mathematical Programming Problems with Vanishing Constraints on Hadamard Manifolds
Authors: Upadhyay Balendu Bhooshan , Ghosh Arnav , Treanţă Savin , Yao Jen-Chih
Published: September 2024

In this paper, we investigate constraint qualifications and optimality conditions for multiobjective mathematical programming problems with vanishing constraints (MOMPVC) on Hadamard manifolds. The MOMPVC-tailored generalized Guignard constraint qualification (MOMPVC-GGCQ) for MOMPVC is introduced in the setting of Hadamard manifolds. By employing MOMPVC-GGCQ and the intrinsic properties of Hadamard manifolds, we establish Karush–Kuhn–Tucker (KKT)-type necessary Pareto efficiency criteria for MOMPVC. Moreover, we introduce several MOMPVC-tailored constraint qualifications and develop interrelations among them. In particular, we establish that the MOMPVC-tailored constraint qualifications introduced in this paper turn out to be sufficient conditions for MOMPVC-GGCQ. Suitable illustrative examples are furnished in the framework of well-known Hadamard manifolds to validate and demonstrate the importance and significance of the derived results. To the best of our knowledge, this is the first time that constraint qualifications, their interrelations, and optimality criteria for MOMPVC have been explored in the framework of Hadamard manifolds.
Optimizing Fleet Size in Point-to-Point Shared Demand Responsive Transportation Service: A Network Decomposition Approach
Authors: Xie Fudong , Wang Ce , Duan Housheng
Published: September 2024

With increasing urbanization and the demand for efficient, flexible transportation solutions, demand-responsive transportation services (DTRS) has emerged as a viable alternative to traditional public transit. However, determining the optimal fleet size to balance the investment and operational revenue remains a significant challenge for service providers. In this article, we address the optimization of fleet size in point-to-point shared demand DRTS, which widely operates within many cities. To capture the uncertain passenger demands in the future when planning the fleet size currently, we model this problem with a framework of two-stage stochastic programming with recourse. Fleet sizing decisions are made in the first stage before the uncertain demands are revealed. After the uncertainty is revealed, the second stage involves making additional decisions to maximize operational revenue. The objective is to optimize the total revenue of the first-stage decisions and the expected revenue of the recourse actions. To solve this practical problem, we resort to the Model Predictive Control method (MPC) and propose a network decomposition approach that first converts the transportation network to a nodal tree structure and then develops a Nodal Tree Recourse with Dependent Arc Capacities (NTRDAC) algorithm to obtain the exact value of the expected recourse functions. In the experiments, NTRDAC is able to produce results within seconds for transportation networks with over 30 nodes. In contrast, a commercial solver is only capable of solving networks with up to five nodes. The stability tests show that NTRDAC remains robust as the problem size varies. Lastly, the value of the stochastic solution (VSS) was evaluated, and the results indicate that it consistently outperforms the expected value solutions. Numerical experiments show that the performance of the NTRDAC algorithm is quite encouraging and fit for large-scale practical problems.
Free Vibration of Graphene Nanoplatelet-Reinforced Porous Double-Curved Shells of Revolution with a General Radius of Curvature Based on a Semi-Analytical Method
Authors: Wang Aiwen , Zhang Kairui
Published: September 2024

Based on domain decomposition, a semi-analytical method (SAM) is applied to analyze the free vibration of double-curved shells of revolution with a general curvature radius made from graphene nanoplatelet (GPL)-reinforced porous composites. The mechanical properties of the GPL-reinforced composition are assessed with the Halpin–Tsai model. The double-curvature shell of revolution is broken down into segments along its axis in accordance with first-order shear deformation theory (FSDT) and the multi-segment partitioning technique, to derive the shell’s functional energy. At the same time, interfacial potential is used to ensure the continuity of the contact surface between neighboring segments. By applying the least-squares weighted residual method (LWRM) and modified variational principle (MVP) to relax and achieve interface compatibility conditions, a theoretical framework for analyzing vibrations is developed. The displacements and rotations are described through Fourier series and Chebyshev polynomials, accordingly, converting a two-dimensional issue into a suite of decoupled one-dimensional problems. The obtained solutions are contrasted with those achieved using the finite element method (FEM) and other existing results, and the current formulation’s validity and precision are confirmed. Example cases are presented to demonstrate the free vibration of GPL-reinforced porous composite double-curved paraboloidal, elliptical, and hyperbolical shells of revolution. The findings demonstrate that the natural frequency of the shell is related to pore coefficients, porosity, the mass fraction of the GPLs, and the distribution patterns of the GPLs.
Adaptive Constraint Relaxation-Based Evolutionary Algorithm for Constrained Multi-Objective Optimization
Authors: Chen Junming , Zhang Kai , Zeng Hui , Yan Jin , Dai Jin , Dai Zhidong
Published: September 2024

The key problem to solving constrained multi-objective optimization problems (CMOPs) is how to achieve a balance between objectives and constraints. Unfortunately, most existing methods for CMOPs still cannot achieve the above balance. To this end, this paper proposes an adaptive constraint relaxation-based evolutionary algorithm (ACREA) for CMOPs. ACREA adaptively relaxes the constraints according to the iteration information of population, whose purpose is to induce infeasible solutions to transform into feasible ones and thus improve the ability to explore the unknown regions. Completely ignoring constraints can cause the population to waste significant resources searching for infeasible solutions, while excessively satisfying constraints can trap the population in local optima. Therefore, balancing constraints and objectives is a crucial approach to improving algorithm performance. By appropriately relaxing the constraints, it induces infeasible solutions to be transformed into feasible ones, thus obtaining more information from infeasible solutions. At the same time, it also establishes an archive for the storage and update of solutions. In the archive update process, a diversity-based ranking is proposed to improve the convergence speed of the algorithm. In the selection process of the mating pool, common density selection metrics are incorporated to enable the algorithm to obtain higher-quality solutions. The experimental results show that the proposed ACREA algorithm not only achieved the best Inverse Generation Distance (IGD) value in 54.6% of the 44 benchmark test problems and the best Hyper Volume (HV) value in 50% of them, but also obtained the best results in seven out of nine real-world problems. Clearly, CP-TSEA outperforms its competitors.
Spider Wasp Optimizer-Optimized Cascaded Fractional-Order Controller for Load Frequency Control in a Photovoltaic-Integrated Two-Area System
Authors: Ekinci Serdar , Izci Davut , Turkeri Cebrail , Ahmad Mohd Ashraf
Published: September 2024

The integration of photovoltaic (PV) systems into traditional power grids introduces significant challenges in maintaining system stability, particularly in multi-area power systems. This study proposes a novel approach to load frequency control (LFC) in a two-area power system, where one area is powered by a PV grid and the other by a thermal generator. To enhance system performance, a cascaded control strategy combining a fractional-order proportional–integral (FOPI) controller and a proportional–derivative with filter (PDN) controller, FOPI(1+PDN), is introduced. The controller parameters are optimized using the spider wasp optimizer (SWO). Extensive simulations are conducted to validate the effectiveness of the SWO-tuned FOPI(1+PDN) controller. The proposed method demonstrates superior performance in reducing frequency deviations and tie-line power fluctuations under various disturbances. The results are compared against other advanced optimization algorithms, each applied to the FOPI(1+PDN) controller. Additionally, this study benchmarks the SWO-tuned controller against recently reported control strategies that were optimized using different algorithms. The SWO-tuned FOPI(1+PDN) controller demonstrates superior performance in terms of faster response, reduced overshoot and undershoot, and better error minimization.
Biotic Interactions Shape Soil Bacterial Beta Diversity Patterns along an Altitudinal Gradient during Invasion
Authors: Wang Yuchao , Xue Wenyan , Lyu Jinlin , Yue Ming , Mao Zhuxin , Shen Xuejian , Wang Xue , Li Yang , Li Qian
Published: September 2024

Invasive plants have already been observed in the understory of mountain forests, which are often considered a safe shelter for most native plants. Microorganisms might be drivers of plant invasions. Nevertheless, the mechanisms determining variations in microbial community composition (beta diversity) during invasion along altitudinal gradients remain to be elucidated. Here, the elevational patterns and the driving ecological processes (e.g., environmental filtering, co-occurrence patterns, and community assembly processes) of soil bacterial beta diversity were compared between invasive and native plants on the Qinling Mountains. The species turnover dominated bacterial compositional dissimilarities in both invasive and native communities, and its contribution to total beta diversity decreased during invasion. Total soil bacterial dissimilarities and turnover exhibited significant binominal patterns over an altitudinal gradient, with a tipping point of 1413 m. Further analysis showed that the contributions of assembly processes decreased in parallel with an increase in contributions of co-occurrence patterns during the invasion process, indicating that species interdependence rather than niche partitioning is strongly correlated with the bacterial biogeography of invasive communities. Plant invasion affects the relative contributions of stochastic processes and co-occurrence interactions through the regulation of the physiochemical characteristics of soil, and ultimately determines compositional dissimilarities and the components of the bacterial community along altitudinal gradients.
Synergistic Interactions among Vacuum, Solar Heating, and UV Irradiation Enhance the Lethality of Interplanetary Space
Authors: Schuerger Andrew C.
Published: September 2024

A Planetary Atmospheric Chamber (PAC) was used to create simulations of interplanetary conditions to test the spore survival of three Bacillus spp. exposed to interacting conditions of vacuum (VAC), simulated solar heating (HEAT), and simulated solar ultraviolet irradiation (UV). Synergism was observed among the experimental factors for all three Bacillus spp. tested that suggested the increased lethality of HEAT and UV when concomitantly exposed to VAC. The most aggressive biocidal effects were observed for assays with VAC + HEAT + UV conditions run simultaneously over short time-steps. The results were used to predict the accumulation of extremely rapid Sterility Assurance Levels (SALs; def., −12 logs of bioburden reduction) measured in a few minutes to a few hours for external surfaces of interplanetary spacecraft. Furthermore, the results were extrapolated to predict that approx. 1 × 104 SAL exposures might be accumulated for external surfaces on the Europa Clipper spacecraft during a 3.5-year transit time between Venus (0.7 AU) and Mars (1.5 AU) during a series of Venus–Earth–Earth gravity assists (VEEGA trajectory) to Jovian space. The results are applicable to external spacecraft surfaces exposed to direct solar heating and UV irradiation during transits though the inner solar system.
Bifidogenic Effect of Human Milk Oligosaccharides on Pediatric IBD Fecal Microbiota
Authors: Otaru Nize , Bajic Danica , Van den Abbeele Pieter , Vande Velde Saskia , Van Biervliet Stephanie , Steinert Robert E. , Rehman Ateequr
Published: September 2024

The prevalence of pediatric inflammatory bowel disease (pIBD) has been increasing over the last two decades. Yet, treatment strategies are still limited, in part due to the multifactorial nature of the disease and the complex interplay between genetic, environmental, dietary, immune, and gut microbial factors in its etiology. With their direct and indirect anti-inflammatory properties, human milk oligosaccharides (HMOs) are a promising treatment and management strategy for IBD. However, to date there are no insights into how HMOs may affect pIBD microbiota. Here, we compared the effects of 2′fucosyllactose (2′FL), difucosyllactose (DFL), 3′sialyllactose (3′SL), and blends thereof with fructooligosaccharide (FOS) on microbiota functionality (short- and branched-chain fatty acids, pH, and gas production) and composition (quantitative shallow shotgun sequencing) using fecal material from eight different pediatric Crohn’s disease patients inoculated in the SIFR® technology. In general, all HMO treatments significantly increased total short-chain fatty acid production when compared with FOS, despite equal gas production. We found that 2′FL, either alone or in combination with DFL and 3′SL, exhibited a strong acetogenic and propiogenic effect, and 3′SL an acetogenic effect that surpassed the effects observed with FOS. No differences in overall community diversity between HMO- and FOS-treated pIBD microbiota were observed. There was, however, a stronger bifidogenic effect of 2′FL, 3′SL, 2′FL/DFL, and 2′FL/DFL + 3′SL when compared with FOS. In general, 3′SL and HMO blends enriched a broader species profile, including taxa with potentially anti-inflammatory properties, such as Faecalibacterium prausnitzii and Blautia species. This study suggests HMOs as a promising strategy to beneficially alter the gut microbial profile in pIBD.