bluuebunny/crossref_metadata_2025 huggingface dataset:
Study Confirms Safety and Effectiveness of Intra-Articular Glucocorticoids for Painful Hip Dislocation in Children and Young Adults with Neurologic Impairment
Authors: Benvenuto Simone , Barbi Egidio , Boaretto Silvia , Landolfo Matteo , Rispoli Francesco , Cozzi Giorgio , Carbone Marco
Published: August 2023

Background: Hip dislocation is a common source of pain in children with neurologic impairment. When medical interventions fail, orthopedic surgery does not guarantee a definitive result as the displacement may continue postoperatively and a second operation is often required. Methods: Retrospective analysis of data regarding the safety and effectiveness of an intra-articular corticosteroid injection (IACI) in 11 patients, aged 15 ± 5 years old, collected through a telephonic questionnaire administered to parents. Results: 21 IACIs were performed, a mean number of 1.9 ± 1.5 times for each patient, at a mean age (of the first IACI) of 13.5 ± 5 years. According to the parents, the IACI significantly lowered the number of participants experiencing pain (82% reduction) and using analgesics (60% reduction). There was also a significant improvement in the children’s hip mobility (63% reduction in patients experiencing stiffness), decubitus (90% reduction in obligated positioning), behavior (80% reduction in lamenting or crying patients), sleep quality (87.5% reduction in patients awakening every night), and caregivers’ quality of life (91% reduction in worried parents). The mean reported duration of the IACIs’ benefit was 5.4 ± 2.4 months (range 1–9), with a positive correlation with the number of IACIs (r = 0.48; p-value = 0.04) and a negative correlation with the age at the first injection (r = −0.71; p-value = 0.02). The only reported adverse event was mild local swelling in one child. Conclusions: the IACI could represent a safe and effective intervention for painful hip dislocation, both before and after surgery, with a long-lasting benefit which seems to increase as multiple IACIs are performed.
Simulations of Effects of Geometric and Material Parameters on the Interfacial Stress of the Thermal Barrier Coatings with Free Edges
Authors: Tao Qiannan , Wang Yanrong , Yang Shun , Liu Yihui
Published: August 2023

Interfacial stress between layers of thermal barrier coatings near free edges is a critical factor that may cause turbine blades to fail. This paper uses simulation methods to reveal the effects of variations in geometric and material parameters on the stress of thermal barrier coatings. The stress distributions of a disk-shaped coating–substrate system undergoing thermal mismatch are calculated by an analytical method and the finite element method. The analytical solution reveals that the coefficient of thermal expansion, elasticity modulus, Poisson’s ratio, and thickness of each layer affect interfacial stress between coatings and substrate. The simulation results exhibit significant concentrations of the normal and shear stresses, which make the coating system prone to cracking and spalling from the free edge. The parametric analysis highlights that the thermal mismatch strain affects the stress magnitude. The region affected by free edges becomes larger with increasing thickness, elasticity modulus, and Poisson’s ratio of the topcoat. Finally, two integral parameters are proposed to represent the stress state near the free edge related to mode I and II fracture, respectively. The parameters, not sensitive to the grid density, are validated by experiments.
Mn(III)–Salen Complexes with Metallophilic Interactions
Authors: Šilha Tomáš , Herchel Radovan , Nemec Ivan
Published: August 2023

We synthesized a series of five novel Mn–salen-based compounds (1a–1c, 2a, 2b) through the reaction between precursor chloride complexes and potassium silver/gold dicyanide. The prepared compounds were structurally and magnetically characterized. Our findings revealed that all the Mn(III) central atoms exhibited an axially elongated coordination polyhedron, leading to the observation of axial magnetic anisotropy as indicated by the negative axial magnetic parameter D, which was determined through fitting the experimental magnetic data and supported by theoretical CASSCF/NEVPT2 calculations. Furthermore, we observed magnetic-exchange interactions only in compounds with a special supramolecular topology involving O–H···O hydrogen-bonded dimers. In these cases, the weak magnetic exchange (J/cm−1 = −0.58(2) in 1b and −0.73(7) in 2b) was mediated by the O–H···O hydrogen bonds. These findings were further supported by BS–DFT calculations, which predicted weak antiferromagnetic exchanges in these complexes and ruled out exchange interactions mediated by diamagnetic cyanido metallo–complex bridges. Additionally, we investigated the observed Ag···π (1b) and Au···Au (2b) interactions using QT–AIM calculations, confirming their non-covalent nature. We compared these results with previously reported Mn–salen-based compounds with metallophilic interactions arising from the presence of the [Ag/Au(CN)2]− bridging units.
The Subterranean Species of the Vjetrenica Cave System in Bosnia and Herzegovina
Authors: Delić Teo , Pipan Tanja , Ozimec Roman , Culver David C. , Zagmajster Maja
Published: August 2023

The Western Balkan’s Vjetrenica Cave in southern Bosnia and Herzegovina is renowned for high richness of subterranean species. However, the data on its fauna have been published only in monographs printed in a small number of copies, making them hardly accessible to the wider scientific community. To overcome this issue, we compiled the data from published monographs with the data from our own recent field surveys. Further, as they are connected via water channels or small crevices in bedrock, we defined the Vjetrenica Cave System as a system comprising Vjetrenica and Bjelušica Caves and Lukavac Spring. Altogether, 93 troglobiotic, i.e., obligate subterranean aquatic (48) and terrestrial (45), taxa were reported for the system, verifying the Vjetrenica Cave System as the second richest locality in subterranean biodiversity in the world. The global uniqueness of the system is also reflected in the fact that as many as 40 troglobiotic species were described from the system. Finally, we reviewed the factors endangering this unique subterranean community and questioned whether it will withstand human-induced changes and pressures due to infrastructural development in southern Bosnia and Herzegovina.
DFA-Net: Multi-Scale Dense Feature-Aware Network via Integrated Attention for Unmanned Aerial Vehicle Infrared and Visible Image Fusion
Authors: Shen Sen , Li Di , Mei Liye , Xu Chuan , Ye Zhaoyi , Zhang Qi , Hong Bo , Yang Wei , Wang Ying
Published: August 2023

Fusing infrared and visible images taken by an unmanned aerial vehicle (UAV) is a challenging task, since infrared images distinguish the target from the background by the difference in infrared radiation, while the low resolution also produces a less pronounced effect. Conversely, the visible light spectrum has a high spatial resolution and rich texture; however, it is easily affected by harsh weather conditions like low light. Therefore, the fusion of infrared and visible light has the potential to provide complementary advantages. In this paper, we propose a multi-scale dense feature-aware network via integrated attention for infrared and visible image fusion, namely DFA-Net. Firstly, we construct a dual-channel encoder to extract the deep features of infrared and visible images. Secondly, we adopt a nested decoder to adequately integrate the features of various scales of the encoder so as to realize the multi-scale feature representation of visible image detail texture and infrared image salient target. Then, we present a feature-aware network via integrated attention to further fuse the feature information of different scales, which can focus on specific advantage features of infrared and visible images. Finally, we use unsupervised gradient estimation and intensity loss to learn significant fusion features of infrared and visible images. In addition, our proposed DFA-Net approach addresses the challenges of fusing infrared and visible images captured by a UAV. The results show that DFA-Net achieved excellent image fusion performance in nine quantitative evaluation indexes under a low-light environment.
Improved Adaptive Multipoint Optimal Minimum Entropy Deconvolution and Application on Bearing Fault Detection in Random Impulsive Noise Environments
Authors: Wei Yu , Xu Yuanbo , Hou Yinlong , Li Long
Published: August 2023

Random impulsive noise is a special kind of noise, which has strong impact features and random disturbances with large amplitude, short duration, and long intervals. This type of noise often displays nonGaussianity, while common background noise obeys Gaussian distribution. Hence, random impulsive noise greatly differs from common background noise, which renders many commonly used approaches in bearing fault diagnosis inapplicable. In this work, we explore the challenge of bearing fault detection in the presence of random impulsive noise. To deal with this issue, an improved adaptive multipoint optimal minimum entropy deconvolution (IAMOMED) is introduced. In this IAMOMED, an envelope autocorrelation function is used to automatically estimate the cyclic impulse period instead of setting an approximate period range. Moreover, the target vector in the original MOMED is rearranged to enhance its practical applicability. Finally, particle swarm optimization is employed to determine the optimal filter length for selection purposes. According to these improvements, IAMOMED is more suitable for detecting bearing fault features in the case of random impulsive noise when compared to the original MOMED. The contrast experiments demonstrate that the proposed IAMOMED technique is capable of effectively identifying fault characteristics from the vibration signal with strong random impulsive noise and, in addition, it can accurately diagnose the fault types. Thus, the proposed method provides an alternative fault detection tool for rotating machinery in the presence of random impulsive noise.
Outage Performance Analysis of Improper Gaussian Signaling for Two-User Downlink NOMA Systems with Imperfect Successive Interference Cancellation
Authors: Liu Yaxuan , Gao Huadong , Cheng Hao , Xia Yili , Pei Wenjiang
Published: August 2023

The improper Gaussian signaling (IGS) technique can improve the achievable rate of an interference-limited network by fully exploiting the second-order statistics of complex signaling. This paper addresses the outage performance analysis of a two-user downlink non-orthogonal multiple access (NOMA) system using the IGS technique in the presence of imperfect successive interference cancellation (SIC). The strong channel user (SU) adopts the IGS, while the weak channel user (WU) adopts the traditional proper Gaussian signaling (PGS). Considering a practical scenario where the transmitter has obtained the statistics of the channel coefficients instead of the instantaneous channel state information (CSI), the expressions of the achievable rates of both users under residual interference due to imperfect SIC are derived, together with their outage probabilities, subject to predetermined target rates and channel statistics. Given a fixed transmit power of the WU, both the transmit power and the degree of impropriety of the SU are optimized to minimize the outage probability subject to the outage constraint of the WU. Numerical results are provided to assess the benefits of the proposed IGS-based downlink NOMA system, which are consistent with the analysis.
Storytelling with Music in Initial Teacher Education: A Comparative Study between Braga (Portugal) and Galicia (Spain)
Authors: Chao-Fernández Rocío , da Silva Sara Reis , Gillanders Carol
Published: August 2023

Although there is an indeterminacy in terminology, we can understand adding sounds and music to children’s stories as the relationships created between verbal language (words), music language (sounds or silence), and body language (gestures and movements), that intertwine, strengthening the message intended to be communicated and allowing learning to be addressed in a holistic manner. This quantitative study, of a descriptive nature, aims to identify the previous experiences of student teachers in Galicia and the northern region of Portugal, related to putting sounds to children’s stories and the training received in this field during their university studies. The data suggest that creative practices related to storytelling through music or adding sounds to children’s stories and/or creating atmospheres in early childhood and primary education, despite providing great benefits, are neither as usual nor as enriching as would be expected, at least in the Spanish context. In relation to initial teacher education, the results are even less encouraging in both contexts, as the majority of students had received training in creating sound stories but stated that they were not satisfied with their experiences, as they did not believe they were trained or had acquired the necessary tools for the integration of this methodological strategy in the school classroom.
‘Zero Gravity’: Impact of COVID-19 Pandemic on the Professional Intentions and Career Pathway Vision of Sport Management Students
Authors: Glebova Ekaterina , López-Carril Samuel
Published: August 2023

The pandemic caused by the SARS-CoV-2 virus has transformed the professional landscape and people’s career expectations. Especially among students, who now face new challenges not foreseen when they started their studies before the pandemic. Nevertheless, to date, there are no specific studies that examine in depth how the restrictions associated with the COVID-19 pandemic have reshaped the professional expectations of future sport managers. To address this research gap, the main purpose of the study is to explore how COVID-19 pandemic has affected the professional intentions and career plans of sport management students. To this end, we share the visions collected in written essays, that a group of 90 students from the Paris Saclay University (France) have concerning their professional future and the impact of the COVID-19 pandemic on it. The essays were qualitatively analyzed based on the self-concept theory of career development through the person–environment perspective. The findings suggest that the COVID-19 outbreak influenced sport management students’ self-concept, their future workplace and employment time choice planning, and overall, their vision and intention for their career path. Accordingly, sports management educators, educational institutions, and policymakers need to ensure that sport management curricula and teaching practices address the new demands of the sports industry prompted by the pandemic, together with the expectations and educational needs of the sport management students.
Bilingual Home Literacy Experiences and Early Biliteracy Development among Chinese–Canadian First Graders
Authors: Li Guofang , Zhen Fubiao , Lin Zhen , Gunderson Lee
Published: August 2023

This study was designed to examine the role of early bilingual home literacy experiences (HLE) (including parent–child shared reading, parents’ direct teaching in Chinese and English, the availability of books in both languages, and children’s access to digital devices for bilingual learning) in the biliteracy development of 66 Chinese–Canadian first graders during the COVID-19 pandemic. Descriptive analyses reveal that overall, parents report higher engagement in English than in Chinese across the four HLE measures. Parent’s engagement in bilingual HLE differs by gender, SES, and immigration status. Pearson correlational analyses of English reading, decoding, and bilingual oral receptive vocabulary reveal that the four dimensions of HLE are not strongly related to English early literacy skills but are positively related to Chinese receptive vocabulary. Finally, hierarchical regression analyses indicate that the availability of books in Chinese and parent–child shared reading in Chinese are key factors associated with Chinese receptive vocabulary score variance; the amount of time using digital devices is found to be significantly related to English reading comprehension, but not Chinese vocabulary; and parents’ direct teaching is not significant with either English early literacy skills or Chinese receptive vocabulary. These findings have important implications for parental engagement in early bilingual home literacy activities and early literacy instruction in school.
CAS-UNet: A Retinal Segmentation Method Based on Attention
Authors: You Zeyu , Yu Haiping , Xiao Zhuohan , Peng Tao , Wei Yinzhen
Published: August 2023

Retinal vessel segmentation is an important task in medical image analysis that can aid doctors in diagnosing various eye diseases. However, due to the complexity and blurred boundaries of retinal vessel structures, existing methods face many challenges in practical applications. To overcome these challenges, this paper proposes a retina vessel segmentation algorithm based on an attention mechanism, called CAS-UNet. Firstly, the Cross-Fusion Channel Attention mechanism is introduced, and the Structured Convolutional Attention block is used to replace the original convolutional block of U-Net to achieve channel enhancement for retinal blood vessels. Secondly, an Additive Attention Gate is added to the skip-connection layer of the network to achieve spatial enhancement for retinal blood vessels. Finally, the SoftPool pooling method is used to reduce information loss. Experimental results using the CHASEDB1 and DRIVE datasets show that the proposed algorithm achieves an accuracy of 96.68% and 95.86%, and a sensitivity of 83.21% and 83.75%, respectively. The proposed CAS-UNet thus outperforms the existing U-Net-based classic algorithms.
Image Sampling Based on Dominant Color Component for Computer Vision
Authors: Wang Saisai , Cui Jiashuai , Li Fan , Wang Liejun
Published: August 2023

Image sampling is a fundamental technique for image compression, which greatly improves the efficiency of image storage, transmission, and applications. However, existing sampling algorithms primarily consider human visual perception and discard irrelevant information based on subjective preferences. Unfortunately, these methods may not adequately meet the demands of computer vision tasks and can even lead to redundancy because of the different preferences between human and computer. To tackle this issue, this paper investigates the key features of computer vision. Based on our findings, we propose an image sampling method based on the dominant color component (ISDCC). In this method, we utilize a grayscale image to preserve the essential structural information for computer vision. Then, we construct a concise color feature map based on the dominant channel of pixels. This approach provides relevant color information for computer vision tasks. We conducted experimental evaluations using well-known benchmark datasets. The results demonstrate that ISDCC adapts effectively to computer vision requirements, significantly reducing the amount of data needed. Furthermore, our method has a minimal impact on the performance of mainstream computer vision algorithms across various tasks. Compared to other sampling approaches, our proposed method exhibits clear advantages by achieving superior results with less data usage.
A Practical Non-Profiled Deep-Learning-Based Power Analysis with Hybrid-Supervised Neural Networks
Authors: Kong Fancong , Wang Xiaohua , Pu Kangran , Zhang Jingqi , Dang Hua
Published: August 2023

With the rapid advancement of deep learning, the neural network has become the primary approach for non-profiled side-channel attacks. Nevertheless, challenges arise in practical applications due to noise in collected power traces and the substantial amount of data required for training deep learning neural networks. Additionally, acquiring measuring equipment with exceptionally high sampling rates is difficult for average researchers, further obstructing the analysis process. To address these challenges, in this paper, we propose a novel architecture for non-profiled differential deep learning analysis, employing a hybrid-supervised neural network. The architecture incorporates a self-supervised autoencoder to enhance the features of power traces before they are utilized as training data for the supervised neural network. Experimental results demonstrate that the proposed architecture not only outperforms traditional differential deep learning networks by providing a more obvious distinction, but it also achieves key discrimination with reduced computational costs. Furthermore, the architecture is evaluated using small-scale and downsampled datasets, confirming its ability recover correct keys under such conditions. Moreover, the altered architecture designed for data resynchronization was proved to have the ability to distinguish the correct key from small-scale and desynchronized datasets.
Enhancing Performance and Security in the Metaverse: Latency Reduction Using Trust and Reputation Management
Authors: Awan Kamran Ahmad , Ud Din Ikram , Almogren Ahmad , Kim Byung-Seo
Published: August 2023

In the rapidly evolving landscape of distributed systems, security stands as a significant challenge, especially in the face of network node attacks. Such threats introduce profound complexities into the dynamics of security protocols, trust management, and resource allocation, issues further amplified by the metaverse’s exponential growth. This paper proposes an innovative solution, offering unique technical contributions to address these multi-faceted challenges. We unveil a trust-based resource allocation framework designed to facilitate the secure and efficient sharing of computational resources within the metaverse. This system has the potential to markedly diminish latency, thereby enhancing overall performance. In parallel, we introduce a reputation system that systematically monitors latency across a spectrum of metaverse entities, providing valuable insights for making informed resource allocation decisions. Moreover, we advocate for a decentralized trust management system, specifically designed to withstand potential security breaches without reliance on a centralized authority. This significantly fortifies both system security and user trust. Alongside this, we unveil an inventive proof-of-trust consensus mechanism that fosters trust and collaboration among metaverse entities during resource allocation, thereby cultivating a more secure ecosystem. Our proposed model poses a robust challenge to malicious entities, and it substantially bolsters the security architecture. The simulation results lend substantial credence to the effectiveness of our approach, demonstrating significant improvements in latency reduction, scalability, and the detection of malicious nodes, thereby outperforming existing methodologies.
Improving Question Answering over Knowledge Graphs with a Chunked Learning Network
Authors: Zuo Zicheng , Zhu Zhenfang , Wu Wenqing , Wang Wenling , Qi Jiangtao , Zhong Linghui
Published: August 2023

The objective of knowledge graph question answering is to assist users in answering questions by utilizing the information stored within the graph. Users are not required to comprehend the underlying data structure. This is a difficult task because, on the one hand, correctly understanding the semantics of a problem is difficult for machines. On the other hand, the growing knowledge graph will inevitably lead to information retrieval errors. Specifically, the question-answering task has three difficulties: word abbreviation, object complement, and entity ambiguity. An object complement means that different entities share the same predicate, and entity ambiguity means that words have different meanings in different contexts. To solve these problems, we propose a novel method named the Chunked Learning Network. It uses different models according to different scenarios to obtain a vector representation of the topic entity and relation in the question. The answer entity representation that yields the closest fact triplet, according to a joint distance metric, is returned as the answer. For sentences with an object complement, we use dependency parsing to construct dependency relationships between words to obtain more accurate vector representations. Experiments demonstrate the effectiveness of our method.
Rule-Based Architectural Design Pattern Recognition with GPT Models
Authors: Jánki Zoltán Richárd , Bilicki Vilmos
Published: August 2023

Architectural design patterns are essential in software development because they offer proven solutions to large-scale structural problems in software systems and enable developers to create software that is more maintainable, scalable, and comprehensible. Model-View-Whatever (MVW) design patterns are prevalent in many areas of software development, but their use in Web development is on the rise. There are numerous subtypes of MVW design patterns applicable to Web systems, but there is no exhaustive listing of them. Additionally, it is unclear how these subtypes can be utilized in contemporary Web development, as their usage is typically unconscious. Here, we discuss and define the most prevalent MVW design patterns used in Web development, as well as provide Angular framework examples and guidance on when to employ a particular design pattern. On the premise of the primary characteristics of design patterns, we created a rule system that large language models (LLMs) can comprehend without doubt. Here, we demonstrate how effectively Generative Pre-trained Transformer (GPT) models can identify various design patterns based on our principles and verify the quality of our recommendations. Together, our solution and GPT models constitute an effective natural language processing (NLP) solution capable of detecting MVW design patterns in Angular projects with an average accuracy of 90%.
Eddy Current Braking Force Analysis of a Water-Cooled Ironless Linear Permanent Magnet Synchronous Motor
Authors: Wang Mengyao , Zhang Lu , Yang Kai , Xu Junjie , Du Chunyu
Published: August 2023

The ironless linear permanent magnet synchronous motor (ILPMSM) is highly compact, easy to control, and exhibits minimal thrust fluctuations, making it an ideal choice for direct loading applications requiring precise positioning accuracy in linear motor test rigs. To address the issue of temperature rise resulting from increased primary winding current and to simultaneously enhance thrust density while minimizing thrust fluctuations, this paper introduces a bilateral-type ILPMSM with a cooling water jacket integrated between the dual-layer windings of the primary movers. The primary winding of the motor adopts a dual-layer coreless structure where the upper and lower windings are closely spaced and cooled by a non-conductive metal cooling water jacket, while the dual-sided secondary employs a Halbach permanent magnet array. The motor’s overall braking force is a combination of the electromagnetic braking force generated by the energized windings and the eddy current braking force induced on the cooling water jacket. This paper specifically focuses on the analysis of the eddy current braking force. Initially, the motor’s geometry and working principle are presented. Subsequently, the equivalent magnetization intensity method is employed to determine the no-load air gap magnetic density resulting from the Halbach array. An analytical model is then developed to derive expressions for the eddy current density and braking force induced in the water-cooling jacket. The accuracy of the analytical method is validated through finite element analysis. Then, a comparative analysis of the braking forces in two primary cooling structures, namely the inter-cooled type and the two-side cooled type ILPMSM, is conducted. Moreover, the characteristics of the eddy current braking force are thoroughly examined concerning motor size parameters and operating conditions. This paper provides a solid theoretical foundation for the subsequent optimization design of the proposed motor.
Cogging Force Reduction and Profile Smoothening Methods for a Slot-Spaced Permanent Magnet Linear Alternator
Authors: Cheng Chin-Hsiang , Dhanasekaran Surender
Published: August 2023

A Permanent Magnet Linear Alternator (PMLA) works seamlessly with a Free Piston Stirling Engine (FPSE) to convert short-stroke and high-frequency linear motion to electric power. Cogging force is an unavoidable opposition force acting on the translator, limiting the linear motion from the driving force, which shortens the lifespan of the machine, causing oscillatory power output and increased maintenance costs. This research focuses on the methods to reduce the cogging force acting on the translator of a slot-spaced PMLA by making geometrical changes to the structure of the machine. The profile of the cogging force is made to be in line with the displacement profile of the translator to avoid unnecessary vibrations and damaging the piston of the FPSE. The changes made also influence the induced voltage. Bringing a balance between reduced voltage and cogging force with minor geometrical changes and a sinusoidal cogging force profile is the outcome of this work.
Alternative Methods of Replacing Electric Batteries in Public Transport Vehicles
Authors: Masłowski Dariusz , Kulińska Ewa , Krzewicki Łukasz
Published: August 2023

Current electric vehicle solutions offer the possibility of a fully electrified bus fleet, although due to financial constraints, most cities cannot afford it. Therefore, the possibility of battery replacement is a needed alternative to the electrification process of a city’s bus fleet. The aim of this study is to investigate the needs of cities and present the concept of battery replacement in an electric bus. The research was based on two groups of selected Polish cities: (1) up to 150,000 inhabitants, and (2) up to 1 million inhabitants. The research part includes an analysis of the means of transport in provincial cities in Poland, an analysis of the kilometers covered by the city fleet, the average distances covered by buses per day, and an estimate of the number of battery replacements. The concept is based on current technological solutions. The description of the concept includes the proposed battery and the technology used, the placement of the battery in the vehicle, and the replacement scheme. Research indicates that the concept can be used with existing technology but will be more justifiable for a larger city due to the higher fleet load. The paper shows the importance of researching bus electrification solutions and that modern solutions can improve existing urban networks in cities.
The Impact of Bend–Twist Coupling on Structural Characteristics and Flutter Limit of Ultra-Long Flexible Wind Turbine Composite Blades
Authors: Li Bei , Tian De , Wu Xiaoxuan , Meng Huiwen , Su Yi
Published: August 2023

Flutter is an instability phenomenon that can occur in wind turbine blades due to fluid–structure interaction, particularly for longer and more flexible blades. Aeroelastic tailoring through bend–twist coupling is an effective method to enhance the aeroelastic performance of blades. In this study, we investigate the impact of bend–twist coupling on the structural performance and flutter limit of the IEA 15 MW blade, which is currently the longest reference wind turbine blade, and determine the optimal layup configuration that maximizes the flutter speed. The blade is modeled by NuMAD and iVABS, and the cross-section properties are obtained by PreComb and VABS. The accuracy of the blade model is verified in terms of stiffness and frequency. The bend–twist coupling is implemented by changing the fiber angle of the skin and spar cap considering symmetric and asymmetric layups. The flutter limits of both the baseline and the bend–twist coupled blade are evaluated based on HAWC2. The results show that the angle of spar cap carbon fiber has a greater effect on the blade’s structural properties and flutter speed than the skin fiber. Varying the spar cap carbon fiber angle increases the flutter speed, with the effect being more significant for the symmetric layup, up to 9.66% at a fiber angle of 25 degrees. In contrast, the variation in skin fiber angle has a relatively small impact on flutter speed—within ±3%.
Optimal Design and Operation of Hybrid Renewable Energy Systems for Oakland University
Authors: Alhawsawi Edrees Yahya , Habbi Hanan Mikhael D. , Hawsawi Mansour , Zohdy Mohamed A.
Published: August 2023

This research paper presents a comprehensive study on the optimal planning and design of hybrid renewable energy systems for microgrid (MG) applications at Oakland University. The HOMER Pro platform analyzes the technical, economic, and environmental aspects of integrating renewable energy technologies. The research also focuses on the importance of addressing unmet load in the MG system design to ensure the university’s electricity demand is always met. By optimizing the integration of various renewable energy technologies, such as solar photovoltaic (PV), energy storage system (ESS), combined heat and power (CHP), and wind turbine energy (WT), the study aims to fulfill the energy requirements while reducing reliance on traditional grid sources and achieving significant reductions in greenhouse gas emissions. The proposed MG configurations are designed to be scalable and flexible, accommodating future expansions, load demands changes, and technological advancements without costly modifications or disruptions. By conducting a comprehensive analysis of technical, economic, and environmental factors and addressing unmet load, this research contributes to advancing renewable energy integration within MG systems. It offers a complete guide for Oakland University and other institutions to effectively plan, design, and implement hybrid renewable energy solutions, fostering a greener and more resilient campus environment. The findings demonstrate the potential for cost-effective and sustainable energy solutions, providing valuable guidance for Oakland University’s search for energy resilience and environmental surveillance, which has a total peak load of 9.958 MW. The HOMER simulation results indicate that utilizing all renewable resources, the estimated net present cost (NPC) is a minimum of USD 30 M, with a levelized energy cost (LCOE) of 0.00274 USD/kWh. In addition, the minimum desired load will be unmetered on some days in September.
Synergistic Effect of Water-Soluble Hydroxylated Multi-Wall Carbon Nanotubes and Graphene Nanoribbons Coupled with Tetra Butyl Ammonium Bromide on Kinetics of Carbon Dioxide Hydrate Formation
Authors: Wang Shu-Li , Xiao Yan-Yun , Zhou Shi-Dong , Jiang Kun , Yu Yi-Song , Rao Yong-Chao
Published: August 2023

In this work, the thermodynamics and kinetics of hydrate formation in 9.01 wt% tetra butyl ammonium bromide (TBAB) mixed with water-soluble hydroxylated multi-wall carbon nanotube (MWCNTol) systems were characterized by measuring hydrate formation conditions, induction time, and final gas consumption. The results showed that MWCNTols had little effect on the phase equilibrium of CO2 hydrate formation. Nanoparticles (graphene nanoribbons (GNs) and MWCNTols) could significantly shorten the induction time. When the concentration was ≤0.06 wt%, MWCNTols had a better effect on the induction time than the GN system, and the maximum reduction in induction time reached 44.22%. The large surface area of MWCNTols could provide sites for heterogeneous nucleation, thus shortening the induction time of hydrate formation. Furthermore, adding different concentrations of nanoparticles to the 9.01 wt% TBAB solution effectively increased the final gas consumption, and the maximum increase was 10.44% of the 9.01 wt% TBAB + 0.08 wt% GN system. Meanwhile, the suitable initial pressure and experimental temperature could also promote the hydrate formation and increase the motivation in hydrate formation. The 9.01 wt% TBAB + 0.02 wt% MWCNTol system had the best effect at 3.5 MPa and 277.15 K. The induction time was reduced by 66.67% and the final gas consumption was increased by 284.11% compared to those of the same system but at a different initial pressure and experimental temperature. This work helps to promote the industrial application of hydrate technology in CO2 capture and storage.
Research on the Dynamic Response of a Steel Catenary Riser in the Touchdown Zone under Pigging Conditions
Authors: Zhu Xiaoxiao , Fu Yunlei , Wang Yutao , Wang Lulu , Lao Liyun
Published: August 2023

A periodic pigging operation performed to clean off sediment and provide operators with detailed health information for a pipeline is mandatorily required. The research on pigging-induced issues for the steel catenary riser (SCR), one of the key parts in offshore hydrocarbon recovery pipelines between the floating production system and the seabed, has been scarce until now. As a result, there is an urgent need for theories to guide the pigging operation to ensure safe pigging is achieved in deepwater risers. In this paper, a study aiming to determine the effects of the pigging impact load and the pigging-induced slugging load on the dynamic response of the riser is reported. A SCR pigging model was established and proposed based on the finite element analysis (FEA) method. The stress distribution and displacement of the SCR were investigated under the pigging conditions, with the consideration of the effects of waves, currents, and floating platform movements. It was found that the pigging load has large effects on the stress and displacement of the touchdown zone (TDZ), especially the touchdown point (TDP). The displacement of the TDZ in the Y (vertical) direction is more significant than that in the X (horizontal) direction under pigging conditions, and the maximum displacement of the TDZ in the Y direction is proportional to the weight of the pig, as well as the length of the pigging-induced slugging.
Optimization of Cooling Channel Structure of Bipolar Plate for Proton Exchange Membrane Fuel Cells Based on CFD Analysis
Authors: Wang Wenbin , Jia Haoran , Li Guoxiang , Sun Wen , Sun Ke , Bai Shuzhan , Cheng Hao
Published: August 2023

The working temperature affects the performance of PEMFC, so a reasonable and efficient cooling channel is necessary to control the working temperature in an efficient area. In this study, the channel structure of the bipolar plate for PEMFC is analyzed using the FLUENT simulation calculation method. The influence of cell size and cooling water flow direction on cell temperature distribution is analyzed, including an examination of the channel ridge width, depth, and aspect ratio of the bipolar plate. After comparing and analyzing three ridge width sizes (0.5 mm, 1.5 mm and 2 mm) in the paper, it was found that a ridge width of 2 mm had the best heat transfer performance. And it was found that a groove depth of 0.5 mm had the best heat transfer performance when comparing three groove depth dimensions (0.5 mm, 1 mm and 1.5 mm). The aspect ratio size parameters had almost no effect on the maximum and average temperatures of the electric stacks, while the relative flow direction of cooling water had a great influence on the temperature distribution of the bipolar plate.
The Effects of Korean Pine and Manchurian Walnut Monocultures and Mixed Plantations on Soil Fungal and Bacterial Communities
Authors: Shen Fangyuan , Liu Ning , Wang Yujiao , Liu Huifeng , Jia Haikuan , Yang Lixue
Published: August 2023

(1) Background: Korean pine (Pinus koraiensis) and Manchurian walnut (Juglans mandshurica) are the main tree species for plantation regeneration in Northeast China, and the mixed plantation of them is one of the typical measures adopted to address the decline in stand productivity in long-term monocultures. However, little is known about the effects of Korean pine and Manchurian walnut monocultures and mixed plantations on soil microbial diversity, composition, and functional groups. (2) Methods: We used ITS and 16S rRNA gene sequencing to detect fungal and bacterial communities and used the FUNGuild, FAPROTAX, and Bugbase databases to predict their functional groups. (3) Results: Fungal and bacterial alpha diversity were always higher in Manchurian walnut monocultures than in Korean pine monocultures. The plantation type had a greater impact on the fungal composition than the bacterial composition. The fungal functional groups were significantly affected by the plantation type (p < 0.05), while the bacterial functional groups were barely changed among all plantation types. The soil available nutrient content was the most important soil factor in shaping the microbial community structures and functional groups. (4) Conclusions: Shifts in fungal community compositions and functional groups might play a dominant role in soil nutrient cycling across the different plantation types in Northeast China.
Dynamics of Physicochemical Properties, Flavor, and Microbial Communities of Salt-Free Bamboo Shoots during Natural Fermentation: Correlation between Microorganisms and Metabolites
Authors: Xu Xiaofeng , Long Zhijian , Du Wanning , Chen Qiyang , Zhang Yu , Hu Shanglian
Published: August 2023

Sour bamboo shoot is a Chinese fermented vegetable with unique flavors and is favored by local consumers. In this study, at different fermentation times, the texture of bamboo shoots and the changing rules of pH, titratable acid (TA), reduced sugar, and nitrite in bamboo shoot fermentation broth were explored. Headspace solid-phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the dominant aroma compounds. 16S rRNA high-throughput sequencing technology (HTS) was employed to investigate the core microbial communities. The results show that the chewiness, fracturability, hardness, and pH decreased, while TA increased during the 60-day fermentation. The contents of reducing sugar and nitrite peaked on the 14th day of fermentation and then decreased. A total of 80 volatile compounds were detected during sour bamboo shoot fermentation, with 2,4-Di-tert-butylphenol having the highest concentration. Among them, 12 volatile compounds (VIP ≥ 1) were identified as characteristic aroma substances of sour bamboo shoots. The dominant bacterial phyla in sour bamboo shoots were Firmicutes and Proteobacteria, while Bacillus and Acinetobacter were the dominant genus. Correlation analysis showed that Firmicutes exhibited a positive correlation with 3,6-Nonadien-1-ol, (E,Z)-, Oxalic acid, isobutyl hexyl ester, and (-)-O-Acetylmalic anhydride, whereas Bacillus exhibited a negative correlation with Silanediol, dimethyl-, and Oxime-, methoxy-phenyl-. A detailed picture of the microbial community of fermented bamboo shoots has been provided by this study, and it may provide insight into the Chinese traditional fermented vegetable microbial structure.
Optimization of Biomass Cultivation from Tuber borchii and Effect of Additives on Triterpenoid Production
Authors: Fu Yu-Rong , Nargotra Parushi , Kuo Chia-Hung , Liu Yung-Chuan
Published: August 2023

Edible fungi are renowned for producing biologically active secondary metabolites that possess anti-tumor activity, protect the liver and have other benefits. The cultivation of truffle mycelia through submerged fermentation has gained interest in the production of metabolites for bio-medicinal purposes. In the present study, Tuber borchii was cultivated by submerged fermentation to produce both biomass and triterpenoids. Various additives, including palmitic acid, stearic acid, linoleic acid, chitosan, CaCl2 and limonene, were investigated to enhance triterpenoid production. It was observed that increasing the medium’s linoleic acid concentration to 1 g/L increased the production of triterpenoids to 129.29 ± 6.5 mg/L, which was 2.94 times higher than the control. A number of variables, including potassium and magnesium ion concentrations and carbon and nitrogen sources and concentrations, were considered to ascertain the ideal conditions for T. borchii growth in submerged fermentation. The best concentrations for glucose, yeast extract, peptone, malt extract, KH2PO4 and MgSO4·7H2O in submerged fermentation were 19.45, 4.58, 7.91, 5.3, 0.58 and 0.82 g/L, respectively, according to response surface methodology. Validation analysis revealed that the experimental values and the predicted values were in good agreement. Under ideal circumstances, the maximum dry cell weight (2.980.18 g/L), which was 1.39 times greater than the control, was attained. Finally, the addition of 1.5 g/L linoleic acid on day 14 to the optimal medium elevated the triterpenoid production to 212.63 ± 16.58 mg/L, which was a 4.84-fold increase compared to the control.
The Microbial Community in a Substrate of Solid-State Fermentation by Lentinula edodes: A Preliminary Study
Authors: Eilertsen Lill , Hultberg Malin , Lee Natuschka , Saroj Paramjeet , Swaine Mark , Chen Feng , Xiong Shaojun
Published: August 2023

Edible-fungal-based solid-state fermentation holds promise for sustainable food and biofuel production. Understanding the role of microbial communities in fungal substrates is crucial. Birch-based substrates were treated with autoclaving (121 °C, at 2 bar) or hot air pasteurization (75–100 °C), followed by incubation with and without shiitake (Lentinula edodes) inoculum. Mycelial growth was monitored by CO2 release and microbial biomass by phosphate-lipid fatty acid (PLFA). DNA sequencing was used to analyze the microbial communities. Results showed successful colonization of shiitake on all substrates, regardless of pasteurization temperatures and coexisting microbes. Total microbial respiration (CO2) and PLFA biomass showed no significant differences between pasteurization regimes. However, significant microbial differences were found between shiitake-inoculated and non-inoculated treatments. DNA sequencing revealed the dominance of Phyllobacterium, Sphingomonas, and Pelomonas genera in all inoculated substrates, while non-inoculated substrates were abundant in Bacillus spp. and Paenibacillus spp. of the Firmicutes phylum. This study provides preliminary insights into the microbial community in birch-based shiitake substrates, facilitating further investigation of bacteria involved in shiitake mycelium growth promotion and biochemical conversion for biofuel production.
Metabolic Engineering of Microorganisms to Produce L-Aspartate and Its Derivatives
Authors: Shi Aiqin , Liu Yan , Jia Baolei , Zheng Gang , Yao Yanlai
Published: August 2023

Metabolic engineering is a promising strategy to realize green synthesis of valued chemicals derived from petroleum. According to the literature, cell factories for producing L-aspartate and its derivatives (β-alanine, ectoine, 3-hydroxypropionate, D-pantothenic acid and L-homoserine) have been developed. In this review, we firstly introduced the functions, applications and markets of L-aspartate and its derivatives. Then, the current research progress on microbial production of them was elaborated in detail. Finally, we have discussed the limiting factors and given some suggestions for realizing applications of engineered bacteria in the industry, including metabolic engineering of the bacteria to increase the titer, yield and productivity of the target products, fermentation condition optimization and downstream purification. With the development of novel technologies and increased investments in synthetic biology, it is promising to realize sustainable production of L-aspartate and its derivatives at the industrial scale in the future.