bluuebunny/crossref_metadata_2025 huggingface dataset:
Ascertaining the Ideality of Photometric Stereo Datasets under Unknown Lighting
Authors: Crabu Elisa , Pes Federica , Rodriguez Giuseppe , Tanda Giuseppa
Published: August 2023

The standard photometric stereo model makes several assumptions that are rarely verified in experimental datasets. In particular, the observed object should behave as a Lambertian reflector, and the light sources should be positioned at an infinite distance from it, along a known direction. Even when Lambert’s law is approximately fulfilled, an accurate assessment of the relative position between the light source and the target is often unavailable in real situations. The Hayakawa procedure is a computational method for estimating such information directly from data images. It occasionally breaks down when some of the available images excessively deviate from ideality. This is generally due to observing a non-Lambertian surface, or illuminating it from a close distance, or both. Indeed, in narrow shooting scenarios, typical, e.g., of archaeological excavation sites, it is impossible to position a flashlight at a sufficient distance from the observed surface. It is then necessary to understand if a given dataset is reliable and which images should be selected to better reconstruct the target. In this paper, we propose some algorithms to perform this task and explore their effectiveness.
The Effect of Rootstock on the Activity of Key Enzymes in Acid Metabolism and the Expression of Related Genes in ‘Cabernet Sauvignon’ Grapes
Authors: Zhang Meng , Yao Ruiyun , Bai Ru , Gao Dengtao , Zhao Baolong , Sun Junli , Bao Yaqi , Ouyang Zhenglong
Published: August 2023

The types and contents of organic acids in wine grapes determine wine quality. To explore the effects of different rootstocks on the acid metabolism of ‘Cabernet Sauvignon’ grapes, various perennial rootstock–scion combinations were used as experimental materials. High-performance liquid chromatography (HPLC) was used to determine citric acid, tartaric acid, and malic acid contents during fruit development. Succinic acid and oxalic acid contents and the activity of related enzymes were measured using spectrophotometry. The expression levels of related genes were measured using a real-time fluorescence quantitative method. The results showed that all four rootstock types significantly reduced oxalic acid and citric acid contents in the grapes, while increasing succinic acid content to varying degrees. Employing 110R, SO4, and Kangzhen3 rootstocks increased tartaric acid and malic acid contents. Enzyme activity analysis revealed that 110R, SO4, and Kangzhen3 rootstocks increased the NAD-MDH enzyme activity, which positively correlated with malic acid content. Simultaneously, these rootstocks reduced the NADP-ME enzyme activity level. NAD-MDH and PEPC gene expression levels were higher in ‘Cabernet Sauvignon’ grapes grafted with 110R, SO4, and Kangan3 rootstocks compared to control self-rooted seedlings. Grafting these three rootstocks enhanced malic acid accumulation in ‘Cabernet Sauvignon’ grapes.
Productive Performances of Slow-Growing Chicken Breeds and Their Crosses with a Commercial Strain in Conventional and Free-Range Farming Systems
Authors: Fiorilla Edoardo , Birolo Marco , Ala Ugo , Xiccato Gerolamo , Trocino Angela , Schiavone Achille , Mugnai Cecilia
Published: August 2023

Local chicken breeds play a vital role in promoting sustainability by preserving genetic diversity, enhancing resilience, and supporting local economies. These breeds are adapted to local climates and conditions, requiring fewer external resources and inputs for their maintenance. By conserving and utilizing local chicken breeds, sustainable farming practices can be incentivized, maintaining ecosystem balance and ensuring food security for future generations. The present study aimed at evaluating the growth performance and slaughter traits of two local Italian chicken breeds (Bionda Piemontese and Robusta Maculata) and their crosses with a medium-growth genotype (Sasso chicken®) reared in conventional and free-range farming systems. The conventional system used a high-energy high-protein diet in a closed barn with controlled temperature, humidity, and lighting, and a stocking density of 33 kg/m2. The free-range system used a low-input diet (low-energy low-protein diet composed of local and GMO-free feed ingredients), uncontrolled environmental conditions, and a stocking density of 21 kg/m2 in a barn with free access to an outdoor area. The birds were slaughtered at 84 days of age in both systems. The crossbred chickens showed the best results for growth performance in both farming systems compared to local breeds. Within genotype, the final live weight of chickens was similar in the two farming systems. In conclusion, slow-growth crossbreeds should be used in alternative farming systems, demonstrating better performance than pure local breeds.
Recent Case Histories of Carbon-Neutral Activity Using Ground Improvement Technology in Japan
Authors: Kitazume Masaki
Published: August 2023

Global warming due to greenhouse gas emissions has led to record-breaking heat waves, torrential rains and droughts on a global scale in recent years. For this reason, people around the world are more keenly aware of the need to reduce greenhouse gas emissions. The construction industry is one of these sources of greenhouse gas emissions. A lot of ground improvement techniques have been developed and applied to improve the physical and mechanical properties of soil in order to achieve stability improvement, ground settlement control, reinforcement, liquefaction prevention, etc. These techniques use a lot of natural materials such as sand and crushed stone and industrial products such as cement. In order to reduce their environmental impact and to economize these techniques, many kinds of industrial waste and by-products have been beneficially used in many types of ground improvement techniques. In response to the growing awareness of carbon neutrality in recent years, it is necessary to further promote initiatives such as the beneficial use of the industrial materials that have been used so far and the development of new materials and construction methods to reduce carbon dioxide emissions. It is expected that various biomass materials will be applied in ground improvement techniques to enhance “negative emission technology”. In this paper, recent developments and applications of certain sorts of environmentally friendly ground improvement techniques, soil densification techniques and soil stabilization techniques are briefly introduced. It is to be expected that these will be further developed and applied to contribute to the reduction in carbon dioxide emissions.
Collaborative Search and Target Capture of AUV Formations in Obstacle Environments
Authors: Hu Xinyu , Shi Yu , Bai Guiqiang , Chen Yanli
Published: August 2023

When performing cooperative search operations underwater, multi-autonomous underwater vehicles formations may encounter array-type obstacles such as gullies and bumps. To safely traverse the obstacle domain, this paper balances convergence time, transformation distance and sensor network power consumption, and proposes a Formation Comprehensive Cost (FCC) model to achieve collision avoidance of the formations. The FCC model is used instead of the fitness function of the genetic algorithm to solve the assignment of capture positions and the improved neural self-organizing map (INSOM) algorithm is proposed to achieve efficient path-planning during the capture process. The simulation experiments in 3D space verify that the proposed scheme can improve the efficiency of robot deployment while ensuring safety.
HPC Platform for Railway Safety-Critical Functionalities Based on Artificial Intelligence
Authors: Labayen Mikel , Medina Laura , Eizaguirre Fernando , Flich José , Aginako Naiara
Published: August 2023

The automation of railroad operations is a rapidly growing industry. In 2023, a new European standard for the automated Grade of Automation (GoA) 2 over European Train Control System (ETCS) driving is anticipated. Meanwhile, railway stakeholders are already planning their research initiatives for driverless and unattended autonomous driving systems. As a result, the industry is particularly active in research regarding perception technologies based on Computer Vision (CV) and Artificial Intelligence (AI), with outstanding results at the application level. However, executing high-performance and safety-critical applications on embedded systems and in real-time is a challenge. There are not many commercially available solutions, since High-Performance Computing (HPC) platforms are typically seen as being beyond the business of safety-critical systems. This work proposes a novel safety-critical and high-performance computing platform for CV- and AI-enhanced technology execution used for automatic accurate stopping and safe passenger transfer railway functionalities. The resulting computing platform is compatible with the majority of widely-used AI inference methodologies, AI model architectures, and AI model formats thanks to its design, which enables process separation, redundant execution, and HW acceleration in a transparent manner. The proposed technology increases the portability of railway applications into embedded systems, isolates crucial operations, and effectively and securely maintains system resources.
System Dynamics Modeling for Effective Strategies in Water Pollution Control: Insights and Applications
Authors: Mousavi S. Hooman , Kavianpour M. R. , Alcaraz Jorge Luis García , Yamini Omid A.
Published: August 2023

Water pollution is a significant environmental challenge with implications for both the natural world and human well-being. To better understand and manage the complex interactions within water pollution systems, such as waste dumping in the sea, system dynamics modeling has emerged as a valuable tool. This simulation-based approach employs feedback loops and cause-and-effect relationships to capture the dynamic behavior of such systems over time. By simulating various waste disposal scenarios and assessing their impacts on the environment and human health, system dynamics modeling aids policymakers and waste managers in devising effective strategies for the sustainable management of dumping sites into the sea. In this manuscript, we present a system dynamics approach to model water pollution control. Our study entails the development of a conceptual model that encompasses pollution sources, pollutant transport and fate, and their effects on water quality and human health. By calibrating and validating the model using data from a case study in Charleston Harbor, South Carolina, United States, we ensure its accuracy and reliability. The results highlight the model’s versatility in simulating different pollution control scenarios, particularly those involving dredging discharge and powerhouse effluent. Through these simulations, we gain valuable insights into the potential impacts of various pollution control measures on water pollution dynamics. Our research underscores the significance of system dynamics modeling in comprehending intricate water pollution systems, including those associated with waste dumping in the sea. By identifying effective strategies for water pollution control, this approach offers invaluable support in safeguarding marine ecosystems and human communities. In conclusion, system dynamics modeling proves to be a powerful tool for sustainable water pollution management. This research demonstrates its utility in analyzing dumping sites in the sea and provides essential findings to inform effective pollution control strategies. Emphasizing the broader context of water pollution, this study contributes to advancing knowledge and fostering sustainable practices to protect our precious water resources.
MicroRNA miR-263b-5p Regulates Developmental Growth and Cell Association by Suppressing Laminin A in Drosophila
Authors: Kim Chae Jeong , Kim Hyun Ho , Kim Hee Kyung , Lee Sojeong , Jang Daegyu , Kim Chanhyeok , Lim Do-Hwan
Published: August 2023

Basement membranes (BMs) play important roles under various physiological conditions in animals, including ecdysozoans. During development, BMs undergo alterations through diverse intrinsic and extrinsic regulatory mechanisms; however, the full complement of pathways controlling these changes remain unclear. Here, we found that fat body-overexpression of Drosophila miR-263b, which is highly expressed during the larval-to-pupal transition, resulted in a decrease in the overall size of the larval fat body, and ultimately, in a severe growth defect accompanied by a reduction in cell proliferation and cell size. Interestingly, we further observed that a large proportion of the larval fat body cells were prematurely disassociated from each other. Moreover, we present evidence that miR-263b-5p suppresses the main component of BMs, Laminin A (LanA). Through experiments using RNA interference (RNAi) of LanA, we found that its depletion phenocopied the effects in miR-263b-overexpressing flies. Overall, our findings suggest a potential role for miR-263b in developmental growth and cell association by suppressing LanA expression in the Drosophila fat body.
Fast-Response Non-Contact Flexible Humidity Sensor Based on Direct-Writing Printing for Respiration Monitoring
Authors: Chen Xiaojun , Ma Kanglin , Ou Jialin , Mo Deyun , Lian Haishan , Li Xin , Cui Zaifu , Luo Yihui
Published: August 2023

Respiratory monitoring is crucial for evaluating health status and identifying potential respiratory diseases such as respiratory failure, bronchitis, and pneumonia. Humidity sensors play a significant role in this regard, and efforts are being made to improve their performance. However, achieving ideal sensor parameters such as sensitivity, detection range, and response speed is challenging. In this work, we propose a flexible preparation method for a double-layer humidity sensor using PDMS as a substrate and a GNP/MWCNT composite material as a sensor element. This sensor exhibits high sensitivity (1.4 RH-1), a wide detection range (20–90%), ultra-fast response (0.35 s) and recovery (2.5 s), high repetitiveness (500 cycles), good long-term stability, and excellent flexibility. Due to these advantages, this sensor has potential applications in real-time clinical and home medical care, such as accurate human respiratory monitoring and non-invasive skin humidity monitoring. Hence, this humidity sensor can be a powerful tool to monitor respiratory moisture levels for diagnosing and treating respiratory diseases effectively.
A Review of Concrete Carbonation and Approaches to Its Research under Irradiation
Authors: Medvedev Vyacheslav , Pustovgar Andrey
Published: August 2023

The current state of knowledge on concrete carbonation has proven that this phenomenon is one of the key factors influencing the reinforced concrete durability reduction during the operational period. To date, the carbonation process has been researched quite deeply; however, the dependence of its course on a variety of external and internal factors poses a significant problem in service life predictions for concrete constructions. The development of nuclear infrastructure around the world in recent years has set scientists the task of investigating such processes in conditions different from those usual for industrial and civil construction. In particular, information in open sources on the course of the carbonation process under irradiation conditions is insufficient. The manuscript analyzes the existing data on concrete carbonation, including a review of the main methods for studying the carbonation process, key factors influencing the course of this process, applied methods of mathematical analysis, predictive models of service life, dynamics of carbonation development, and the application of such analytical models in practice. The available information about the carbonation process under various types of irradiations on the causes, dynamics, and mechanisms of carbonation and corrosion processes occurring in reinforced concrete during operation is also considered. Based on the results of the analysis carried out in the study, recommendations are given for further development in the research field of carbonation process in concrete structures of nuclear power plants in order to comprehensively predict their service life.
Applicability of CMOD to Obtain the Actual Fracture Toughness of Rightly-Cracked Fibrous Concrete Beams
Authors: Abdallah Mahmoud A. , Elakhras Ahmed A. , Reda Ramy M. , Sallam Hossam El-Din M. , Moawad Mohamed
Published: August 2023

Unfortunately, most of the previous work studying the fracture toughness of fibrous composites has deliberately ignored bridging the fiber onto the pre-crack/notch surfaces by creating such a crack as a through-thickness crack (TTC). Furthermore, no standard specifications for measuring the fracture toughness of fibrous composites have considered the fiber bridging through the pre-notch. Only a few pieces of research, no more than fingers on one hand, have addressed this problem by creating an actual crack, i.e., a matrix crack (MC) instead of a TTC. The challenge these researchers face is the inability to calculate the fracture toughness directly through the stress intensity factor (SIF) relationship because there is no geometry correction factor equation, f(a/d), for an MC. The main objective of the present work is to calculate f(a/d) and ascertain a relationship between the SIF and crack mouth opening displacement (CMOD) for an MC numerically using 3-D finite element analysis. An experimental program was also conducted to measure the fracture toughness of three types of concrete beams: high-strength concrete (HSC) beams with a TTC, HSC beams with an MC, and fiber-reinforced concrete (FRC) beams with an MC. The results showed that FRC beams with an MC have the highest fracture toughness and, subsequently, the highest resistance to crack growth. The numerical results revealed a suggested relationship between the SIF and CMOD of FRC beams with an MC. This relation was used to predict the fracture toughness of FRC with an MC by the critical value of CMOD measured experimentally.
Study on Settlement of Self-Compacting Solidified Soil in Foundation Pit Backfilling Based on GA-BP Neural Network Model
Authors: Yuan Ze , Gao Lei , Chen Hejin , Song Song
Published: August 2023

In order to predict the settlement of self-compacting solidified soil in foundation pit backfilling, finite element software is used to study the influence of soil properties and the surrounding structural properties of the foundation pit on the settlement of backfilled self-compacting solidified soil based on a foundation pit project in the city of Nanjing. The degree of influence of various factors influencing settlement is considered, a grey relational grade analysis is conducted, and input layer parameters of the neural network are determined based on the results of the grey relational grade analysis. Based on the GA-BP neural network model, the settlement of soil is predicted using numerical simulation results. The results reveal that the settlement and structural disturbance of self-compacting solidified soil after backfilling are smaller than those of fine silty sand; self-compacting solidified soil significantly improves the engineering performance of excavated soil. In the grey relational grade analysis, the six influencing factors that have high correlation with soil settlement can be used as input layer parameters for the neural network model. Among them, the correlation degree between elastic modulus and soil settlement is the highest, reaching 0.8402. The correlation degrees of the remaining five influencing factors are above 0.5, and the values are close. The GA-BP neural network can improve the overfitting situation of a BP neural network trapped in local optima, with R2 reaching 0.9999 and RMSE only 0.0018 mm, achieving high-precision prediction of settlement of self-compacting solidified soil.
Dung Beetle Optimization with Deep Feature Fusion Model for Lung Cancer Detection and Classification
Authors: Alamgeer Mohammad , Alruwais Nuha , Alshahrani Haya Mesfer , Mohamed Abdullah , Assiri Mohammed
Published: August 2023

Lung cancer is the main cause of cancer deaths all over the world. An important reason for these deaths was late analysis and worse prediction. With the accelerated improvement of deep learning (DL) approaches, DL can be effectively and widely executed for several real-world applications in healthcare systems, like medical image interpretation and disease analysis. Medical imaging devices can be vital in primary-stage lung tumor analysis and the observation of lung tumors from the treatment. Many medical imaging modalities like computed tomography (CT), chest X-ray (CXR), molecular imaging, magnetic resonance imaging (MRI), and positron emission tomography (PET) systems are widely analyzed for lung cancer detection. This article presents a new dung beetle optimization modified deep feature fusion model for lung cancer detection and classification (DBOMDFF-LCC) technique. The presented DBOMDFF-LCC technique mainly depends upon the feature fusion and hyperparameter tuning process. To accomplish this, the DBOMDFF-LCC technique uses a feature fusion process comprising three DL models, namely residual network (ResNet), densely connected network (DenseNet), and Inception-ResNet-v2. Furthermore, the DBO approach was employed for the optimum hyperparameter selection of three DL approaches. For lung cancer detection purposes, the DBOMDFF-LCC system utilizes a long short-term memory (LSTM) approach. The simulation result analysis of the DBOMDFF-LCC technique of the medical dataset is investigated using different evaluation metrics. The extensive comparative results highlighted the betterment of the DBOMDFF-LCC technique of lung cancer classification.
Structure and Properties of Cermet Coatings Produced by Vacuum-Arc Evaporation of a High-Entropy Alloy
Authors: Ivanov Yurii F. , Akhmadeev Yuriy Kh. , Krysina Olga V. , Koval Nikolai N. , Shugurov Vladimir V. , Petrikova Elizaveta A. , Prokopenko Nikita A. , Tolkachev Oleg S.
Published: August 2023

Multilayer cermet coatings based on a TiNbZrTaHf high-entropy alloy were produced on solid substrates by plasma-assisted vacuum-arc deposition. The assisting multicomponent metal-gas plasma was generated by evaporating TiNbZrTaHf cathodes in a gas mixture of nitrogen and argon. It was found that the coatings were nanocrystalline in structure (with nanocrystal sizes ranging from 2.5 to 4 nm). The metallic layer had a body-centered cubic lattice (a = 0.33396 nm), and the ceramic layer had a face-centered cubic lattice (a = 0.44465 nm). Transition layers formed between the substrate and the metallic layer and between the metallic and the ceramic layers were revealed. The hardness of the coatings was 36.7 GPa and their Young’s modulus was 323 GPa.
Primary and Secondary Teachers’ Conceptions, Perceptions and Didactic Experience about Heritage: The Case of Andorra
Authors: Yáñez Cristina , Fernández Ares , Solé-Llussà Anna , Ballesté Marc
Published: August 2023

In recent years, there has been a growing tendency to incorporate teaching proposals related to heritage education in both formal and non-formal contexts. However, heritage is approached from a limited perspective, often without considering a holistic perspective. In this sense, the present study aims to know the conceptions and perceptions of heritage and its teaching in 42 primary and secondary in-service teachers from the three educational systems of Andorra in order to identify, through a semi-structured interview, possible obstacles in their professional knowledge and practice. In general terms, the results show that Natural and Tangible Heritage are the ones most taught in the classrooms due to the previous teachers’ training and professional background. Likewise, regarding the most common methodologies used to learn heritage, teachers highlight visits in situ and the use of educational technologies. Moreover, in-service teachers perceive how heritage education plays a key role in different aspects of their development, such as identity, core values and interest in the subject, amongst others. In order to obtain a holistic approach regarding heritage education, this research is part of a greater-scope project that also considers other stakeholders in the education community that belong to formal and non-formal spheres.
Digital Sequential Scaffolding during Experimentation in Chemistry Education—Scrutinizing Influences and Effects on Learning
Authors: Fleischer Timo , Moser Stephanie , Deibl Ines , Strahl Alexander , Maier Simone , Zumbach Joerg
Published: August 2023

Sequential scaffolding during experimentation can support students in acquiring knowledge and experimentation skills. This study aims to explore students’ understanding and perception of digital sequential scaffolds in chemistry education, investigate predictors of this understanding and perception, and examine the effects on learning outcomes and processes. A total of 183 secondary school students conducted hands-on experiments on redox reactions using digital sequential scaffolds. This study collects data through questionnaires and analyzes prior knowledge, self-perceived experimentation competence, chemistry-related self-concept, and interest as predictors. This research also examines the influence of students’ understanding and perception on cognitive and motivational learning outcomes. The findings show that learners experienced digital sequential scaffolds as helpful and were motivated by them to conduct hands-on experiments. Results also reveal that only students’ prior experience with sequential scaffolds and prior self-perceived experimentation competence significantly predict their understanding of the concept and usage of the digital sequential scaffolds. Regarding motivation, outcomes show that perceived benefit and motivation regarding experimentation predict the motivational outcomes. Overall, our findings contribute to understanding sequential scaffolding in chemistry education and inform instructional design practices.
Phase Stabilization of a Terahertz Wave Using Mach–Zehnder Interference Detection
Authors: Ibrahim Amalina Athira , Li Bo , Ye Shenghong , Shiramizu Takashi , Chen Hanwei , Mikami Yuya , Kato Kazutoshi
Published: August 2023

As a high-frequency carrier, the terahertz (THz) wave is essential for achieving high-data-rate wireless transmission due to its ultra-wide bandwidth. Phase stabilization becomes crucial to enable phase-shift-based multilevel modulation for high-speed data transmission. We developed a Mach–Zehnder interferometric phase stabilization technique for photomixing, which has proved a promising method for phase-stable continuous THz-wave generation. However, this method faced inefficiencies in generating phase-modulated THz waves due to the impact of the phase modulator on the phase stabilization system. By photomixing, which is one of the promising methods for generating THz waves, the phase of the generated THz waves can be controlled in the optical domain so that the stability of the generated THz wave can be controlled by photonics technologies. Thus, we devised a new phase stabilization approach using backward-directional lightwave, which is overlapped with the THz wave generation system. This study presented a conceptual and experimental framework for stabilizing the phase differences of optical carrier signals. We compared the optical domain and transmission performances between forward-directional and backward-directional phase stabilization methods. Remarkably, our results demonstrated error-free transmission at a modulation frequency of 3 Gbit/s and higher.
Self-Regulated Learning and Active Feedback of MOOC Learners Supported by the Intervention Strategy of a Learning Analytics System
Authors: Cobos Ruth
Published: August 2023

MOOCs offer great learning opportunities, but they also present several challenges for learners that hinder them from successfully completing MOOCs. To address these challenges, edX-LIMS (System for Learning Intervention and its Monitoring for edX MOOCs) was developed. It is a learning analytics system that supports an intervention strategy (based on learners’ interactions with the MOOC) to provide feedback to learners through web-based Learner Dashboards. Additionally, edX-LIMS provides a web-based Instructor Dashboard for instructors to monitor their learners. In this article, an enhanced version of the aforementioned system called edX-LIMS+ is presented. This upgrade introduces new services that enhance both the learners’ and instructors’ dashboards with a particular focus on self-regulated learning. Moreover, the system detects learners’ problems to guide them and assist instructors in better monitoring learners and providing necessary support. The results obtained from the use of this new version (through learners’ interactions and opinions about their dashboards) demonstrate that the feedback provided has been significantly improved, offering more valuable information to learners and enhancing their perception of both the dashboard and the intervention strategy supported by the system. Additionally, the majority of learners agreed with their detected problems, thereby enabling instructors to enhance interventions and support learners’ learning processes.
A Novel Container Placement Mechanism Based on Whale Optimization Algorithm for CaaS Clouds
Authors: Alwabel Abdulelah
Published: August 2023

Advancements in container technology can improve the efficiency of cloud systems by reducing the initiation time of virtual machines (VMs) and improving portability. Therefore, many cloud service providers offer cloud services based on the container as a service (CaaS) model. Container placement (CP) is a mechanism that allocates containers to a pool of VMs by mapping new containers to VMs and simultaneously considering VM placements on physical machines. The CP mechanism can serve several purposes, such as reducing power consumption and optimizing resource availability. This study presents directed container placement (DCP), a novel policy for placing containers in CaaS cloud systems. DCP extends the whale optimization algorithm, an optimization technique aimed at reducing the power consumption in cloud systems with a minimum effect on the overall performance. The proposed mechanism is evaluated against established methods, namely, improved genetic algorithm and discrete whale optimization using two criteria: energy savings and search time. The experiments demonstrate that DCP consumes approximately 78% less power and reduces the search time by approximately 50% in homogeneous clouds. In addition, DCP saves power by approximately 85% and reduces the search time by approximately 30% in heterogeneous clouds.
A Study on Pavement Classification and Recognition Based on VGGNet-16 Transfer Learning
Authors: Zou Junyi , Guo Wenbin , Wang Feng
Published: August 2023

The types of road surfaces on which intelligent connected cars operate are complicated and varied, and current research lacks the achievement of real-time and reasonably high accuracy for road surface categorization. In this research, we provide a deep learning-based technique for classifying and identifying road surfaces that makes use of an improved (VGGNet-16) model, in conjunction with a transfer learning strategy, to gather data from the road surface in front of the car using an on-board camera. To accurately classify data based on obtained road surface photos, the dataset is first preprocessed, then pretrained weights are frozen, and the network is initialized using transfer learning parameters. In order to explore the accuracy analysis of the various models regarding the identification of six types of road surfaces, comparisons were made via the VGG16, AlexNet, InceptionV3, and ResNet50 models, using the same parameter values. The experimental findings demonstrate that the improved VGGNet-16 model, combined with the transfer learning approach, achieves 96.87% accuracy for the classification and recognition of pavements, demonstrating the improved network model’s superior accuracy for these tasks. Additionally, the driving recorder of the vehicle may be used as the sensor to complete pavement detection, which has significant financial advantages.
Multi-Scenario Millimeter Wave Channel Measurements and Characteristic Analysis in Smart Warehouse at 28 GHz
Authors: Mi Hang , Ai Bo , He Ruisi , Wu Tong , Zhou Xin , Zhong Zhangdui , Zhang Haoxiang , Chen Ruifeng
Published: August 2023

Smart warehouses are revolutionizing traditional logistics operations by incorporating advanced technologies such as Internet of Things, robotics, and artificial intelligence. In these complex and dynamic environments, control and operation instructions need to be transmitted through wireless networks. Therefore, wireless communication plays a crucial role in enabling efficient and reliable operations. Meanwhile, channel measurements and modeling in smart warehouse scenarios are essential for understanding and optimizing wireless communication performance. By accurately characterizing radio channels, communication systems can be better designed and deployed to meet unique challenges in smart warehouse scenarios. In this paper, we present an overview of smart warehouse scenarios and explore channel characteristics in smart warehouse scenarios. We conducted a measurement campaign for millimeter wave radio channels in smart warehouse scenarios. A vector network analyzer-based channel sounder was exploited to record channel characteristics at 28 GHz. Based on the measurements, large-scale channel parameters, including path loss, root-mean-square (RMS) delay spread, and Rician K factor were investigated. The unique channel characteristics in smart warehouse scenarios were explored.
High-Density Genetic Map and QTL Analysis in Cunninghamia lanceolate: Insights into Growth and Wood-Color Traits
Authors: Chen Xingbin , Xiong Caiyun , Lou Yongfeng , Xu Haining , Cheng Qiangqiang , Sun Shiwu , Xiao Fuming
Published: August 2023

Cunninghamia lanceolata is one of the most important tree species in China due to its significance both in economy and ecology. The aims of the present study were to construct a high-density genetic map and identify a quantitative trait locus (QTL) for C. lanceolata. In this study, an F1 population comprising 81 individuals was developed. Using specific length amplified fragment sequencing (SLAF-seq) technology, a total of 254,899 loci were found to be polymorphic. After linkage analysis, 2574 markers were used to construct genetic linkage maps. Specifically, 1632 markers were allocated to 11 linkage groups (LGs) for the female map, 1038 for the male map, and 2574 for the integrated map. The integrated map consisted of 4596 single-nucleotide polymorphisms (SNPs) loci, resulting in an average of 1.79 SNP loci per SLAF marker. The marker coverage was 1665.76 cM for the female map, 1436.39 cM for the male map, and 1748.40 cM for the integrated map. The average interval between two adjacent mapped markers was 1.03 cM, 1.40 cM, and 0.68 cM for the female map, male map, and integrated map, respectively. Using the integrated map, we performed interval mapping (logarithm of odds, LOD > 2.0) to detect traits of interest. We identified a total of 2, 1, 2, 5, 1, 2, 1, and 3 QTLs for diameter at breast height, heartwood diameter, heartwood proportion, heartwood a*, heartwood b*, heartwood L*, sapwood a*, and sapwood L*, respectively. The number of markers associated with each QTL ranged from 1 to 14, and each marker explained phenotypic variances ranging from 12.70% to 23.60%. Furthermore, a common QTL was identified for diameter at breast height and heartwood color a*, while another common QTL was observed for heartwood color L* and heartwood color a*. These findings suggest possible pleiotropic effects of the same genes on these traits. In conclusion, we successfully constructed high-density genetic maps for C. lanceolata using the SLAF-seq method with an F1 population. Notably, these linkage maps represent the most comprehensive and densest ones available to date for C. lanceolata and will facilitate future chromosome assignments for C. lanceolata whole-genome sequencing. These identified QTLs will serve as a valuable resource for conducting fine-scale QTL mapping and implementing marker-assisted selection in C. lanceolata, particularly for growth and wood-color traits.
β-Caryophyllene-Loaded Microemulsion-Based Topical Hydrogel: A Promising Carrier to Enhance the Analgesic and Anti-Inflammatory Outcomes
Authors: Alharthi Sitah , Ziora Zyta Maria , Mustafa Gulam , Chaubey Pramila , El Kirdasy Ahmed Farag , Alotaibi Ghallab
Published: August 2023

Musculoskeletal pain and inflammation can vary from localised pain like pain in the shoulders and neck to widespread pain like fibromyalgia, and as per estimates, around 90% of humans have experienced such pain. Oral non-steroidal anti-inflammatory drugs (NSAIDs) are frequently prescribed for such conditions but are associated with concerns like gastric irritation and bleeding. In the present study, a microemulsion-based gel comprising β-caryophyllene, isopropyl myristate, Tween 80, and normal saline was prepared as a topical option for managing topical pain and inflammation. The globules of the microemulsion were below 100 nm with a zetapotential of around −10 mV. The drug entrapment was >87% with a drug loading of >23%. The permeation studies established better skin permeation (20.11 ± 0.96 μg cm−2 h−1) and retention of the drug (4.96 ± 0.02%) from the developed system vis-à-vis the conventional product (9.73 ± 0.35 μg cm−2 h−1; 1.03 ± 0.01%). The dermatokinetic studies established the better pharmacokinetic profile of the bioactive in the epidermis and dermis layers of the skin. The anti-inflammatory potential in carrageenan-induced rat paw oedema was more pronounced than the conventional product (~91% vis-à-vis ~77%), indicating a better pharmacodynamic outcome from the developed system. The nanotechnology-based natural bioactive product with improved efficacy and drug loading can provide a better alternative for the management of musculoskeletal pain.
Exploring the Role of Birth Environment on Italian Mothers’ Emotional Experience during Childbirth
Authors: Migliorini Laura , Setola Nicoletta , Naldi Eletta , Rompianesi Maria Chiara , Iannuzzi Laura , Cardinali Paola
Published: August 2023

The physical environment is one of the factors that affect mother’s experience of childbirth and psychological health. A woman’s childbirth experience has been found to influence not only the mother’s own health and future births but also the well-being of her child and family. The present study’s objective was to investigate mothers’ perceptions of spatial-physical humanization, affective quality of place, and emotions during childbirth. To achieve this goal, the first part of our work was dedicated to selecting two birth environments (hospital and birth center) with different degrees of humanization. The methods include observations and field survey which mainly concerned the environmental quality of the spaces and the layout of the birth unit, and self-report questionnaire about perceived environment, affective quality attributed to place, and delivery experience. Participants are 66 low-risk women, choosing hospital or birth center. The findings indicate an enhanced perception of both the spatial-physical aspects and the social and functional aspects of the care unit among mothers who give birth at the birth center. These same mothers also report a more positive perception of the childbirth experience. In conclusion, this study contributes to the understanding of the role of birth environments in shaping mothers’ emotional experiences during childbirth.
Augmentation of Cathepsin Isoforms in Diabetic db/db Mouse Kidneys Is Associated with an Increase in Renal MARCKS Expression and Proteolysis
Authors: Gholam Mohammed F. , Bala Niharika , Dogan Yunus E. , Alli Abdel A.
Published: August 2023

The expression of the myristoylated alanine-rich C-kinase substrate (MARCKS) family of proteins in the kidneys plays an important role in the regulation of the renal epithelial sodium channel (ENaC) and hence overall blood pressure regulation. The function of MARCKS is regulated by post-translational modifications including myristoylation, phosphorylation, and proteolysis. Proteases known to cleave both ENaC and MARCKS have been shown to contribute to the development of high blood pressure, or hypertension. Here, we investigated protein expression and proteolysis of MARCKS, protein expression of multiple protein kinase C (PKC) isoforms, and protein expression and activity of several different proteases in the kidneys of diabetic db/db mice compared to wild-type littermate mice. In addition, MARCKS protein expression was assessed in cultured mouse cortical collecting duct (mpkCCD) cells treated with normal glucose and high glucose concentrations. Western blot and densitometric analysis showed less abundance of the unprocessed form of MARCKS and increased expression of a proteolytically cleaved form of MARCKS in the kidneys of diabetic db/db mice compared to wild-type mice. The protein expression levels of PKC delta and PKC epsilon were increased, while cathepsin B, cathepsin S, and cathepsin D were augmented in diabetic db/db kidneys compared to those of wild-type mice. An increase in the cleaved form of MARCKS was observed in mpkCCD cells cultured in high glucose compared to normal glucose concentrations. Taken together, these results suggest that high glucose may contribute to an increase in the proteolysis of renal MARCKS, while the upregulation of the cathepsin proteolytic pathway positively correlates with increased proteolysis of MARCKS in diabetic kidneys, where PKC expression is augmented.
Development and Initial Validation of the in-Session Patient Affective Reactions Questionnaire (SPARQ) and the Rift In-Session Questionnaire (RISQ)
Authors: Stefana Alberto , Langfus Joshua A. , Vieta Eduard , Fusar-Poli Paolo , Youngstrom Eric A.
Published: August 2023

This article discusses the development and preliminary validation of a self-report inventory of the patient’s perception of, and affective reaction to, their therapist during a psychotherapy session. First, we wrote a pool of 131 items, reviewed them based on subject matter experts’ review, and then collected validation data from a clinical sample of adult patients in individual therapy (N = 701). We used exploratory factor analysis and item response theory graded response models to select items, confirmatory factor analysis (CFA) to test the factor structure, and k-fold cross-validation to verify model robustness. Multi-group CFA examined measurement invariance across patients with different diagnoses (unipolar depression, bipolar disorder, and neither of these). Three factors produced short scales retaining the strongest items. The in-Session Patient Affective Reactions Questionnaire (SPARQ) has a two-factor structure, yielding a four-item Negative affect scale and a four-item Positive affect scale. The Relationship In-Session Questionnaire (RISQ) is composed of four items from the third factor with dichotomized responses. Both scales showed excellent psychometric properties and evidence of metric invariance across the three diagnostic groups: unipolar depression, bipolar disorder, and neither of these. The SPARQ and the RISQ scale can be used in clinical or research settings, with particular value for capturing the patient’s perspectives about their therapist and session-level emotional processes.
Mechanical and Structural Characterization of Laser-Cladded Medium-Entropy FeNiCr-B4C Coatings
Authors: Okulov Artem , Korobov Yury , Stepchenkov Alexander , Makarov Aleksey , Iusupova Olga , Korkh Yulia , Kuznetsova Tatyana , Kharanzhevskiy Evgeny , Liu Kun
Published: August 2023

Equiatomic medium-entropy alloy (MEA) FeNiCr-B4C (0, 1, and 3 wt.% B4C) coatings were deposited onto an AISI 1040 steel substrate using pulsed laser cladding. Based on an SEM microstructural analysis, it was found that the cross-sections of all the obtained specimens were characterized by an average coating thickness of 400 ± 20 μm, a sufficiently narrow (100 ± 20 μm) “coating–substrate” transition zone, and the presence of a small number of defects, including cracks and pores. An XRD analysis showed that the formed coatings consisted of a single face-centered cubic (FCC) γ-phase and the space group Fm-3m, regardless of the B4C content. However, additional TEM analysis of the FeNiCr coating with 3 wt.% B4C revealed a two-phase FCC structure consisting of grains (FCC-1 phase, Fm-3m) up to 1 µm in size and banded interlayers (FCC-2 phase, Fm-3m) between the grains. The grains were clean with a low density of dislocations. Raman spectroscopy confirmed the presence of B4C carbides inside the FeNiCr (1 and 3 wt.% B4C) coatings, as evidenced by detected peaks corresponding to amorphous carbon and peaks indicating the stretching of C-B-C chains. The mechanical characterization of the FeNiCr-B4C coatings specified that additions of 1 and 3 wt.% B4C resulted in a notable increase in microhardness of 16% and 38%, respectively, with a slight decrease in ductility of 4% and 10%, respectively, compared to the B4C-free FeNiCr coating. Thus, the B4C addition can be considered a promising method for strengthening laser-cladded MEA FeNiCr-B4C coatings.
The Catalytic Effect of Vanadium on Sorption Properties of MgH2-Based Nanocomposites Obtained Using Low Milling Time
Authors: Sekulić Zorana , Novaković Jasmina Grbović , Babić Bojana , Prvulović Milica , Milanović Igor , Novaković Nikola , Rajnović Dragan , Filipović Nenad , Asanović Vanja
Published: August 2023

The effects of catalysis using vanadium as an additive (2 and 5 wt.%) in a high-energy ball mill on composite desorption properties were examined. The influence of microstructure on the dehydration temperature and hydrogen desorption kinetics was monitored. Morphological and microstructural studies of the synthesized sample were performed by X-ray diffraction (XRD), laser particle size distribution (PSD), and scanning electron microscopy (SEM) methods, while differential scanning calorimetry (DSC) determined thermal properties. To further access amorph species in the milling blend, the absorption spectra were obtained by FTIR-ATR analysis (Fourier transform infrared spectroscopy attenuated total reflection). The results show lower apparent activation energy (Eapp) and H2 desorption temperature are obtained for milling bland with 5 wt.% added vanadium. The best explanation of hydrogen desorption reaction shows the Avrami-Erofeev model for parameter n = 4. Since the obtained value of apparent activation energy is close to the Mg-H bond-breaking energy, one can conclude that breaking this bond would be the rate-limiting step of the process.