bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Determination Influence of Flow Disturbances behind the Knife Gate Valve on the Indications of the Ultrasonic Flow Meter with Clamp-On Sensors on Pipelines
Authors: Piechota Piotr , Synowiec Piotr , Andruszkiewicz Artur , Wędrychowicz Wiesław , Wróblewska Elżbieta , Mrowiec Andrzej
Published: May 2023

The aim of this work is to experimentally determine and evaluate the value of the correction factor for ultrasonic flow meters in order to improve their accuracy. This article concerns flow velocity measurement with the use of an ultrasonic flow meter in the area of disturbed flow behind the distorting element. Clamp-on ultrasonic flow meters are popular among measurement technologies due to their high accuracy and easy, non-invasive installation, because the sensors are mounted directly on the outer surface of the pipe. In industrial applications, installation space is usually limited and, therefore, flow meters frequently have to be mounted directly behind flow disturbances. In such cases, it is necessary to determine the value of the correction factor. The disturbing element was a knife gate valve, a valve often used in flow installations. Water flow velocity tests were performed using an ultrasonic flow meter with clamp-on sensors on the pipeline. The research was performed in 2 series of measurements with different Reynolds numbers of 35,000 and 70,000, which correspond to a velocity of approximately 0.9 m/s and 1.8 m/s. The tests were carried out at different distances from the source of interference, within the range of 3–15 DN (pipe nominal diameter). The position of the sensors at successive measurement points on the circuit of the pipeline was changed by 30 degrees. Flow velocity measurements were carried out for two different levels of the valve’s closure: 1/3 and 1/2 of the valve’s height. For the collected velocity values at single measurement points, the values of the correction coefficient, K, were determined. The results of the tests and calculations prove that compensation error of measurement performed behind the disturbance without keeping the required straight sections of the pipeline is possible by using the factor K*. The analysis of the results made it possible to identify the optimal measuring point at a distance from the knife gate valve as being smaller than specified in the standards and recommendations.
Comparison of Common Algorithms for Single-Pixel Imaging via Compressed Sensing
Authors: Zhao Wenjing , Gao Lei , Zhai Aiping , Wang Dong
Published: May 2023

Single-pixel imaging (SPI) uses a single-pixel detector instead of a detector array with a lot of pixels in traditional imaging techniques to realize two-dimensional or even multi-dimensional imaging. For SPI using compressed sensing, the target to be imaged is illuminated by a series of patterns with spatial resolution, and then the reflected or transmitted intensity is compressively sampled by the single-pixel detector to reconstruct the target image while breaking the limitation of the Nyquist sampling theorem. Recently, in the area of signal processing using compressed sensing, many measurement matrices as well as reconstruction algorithms have been proposed. It is necessary to explore the application of these methods in SPI. Therefore, this paper reviews the concept of compressive sensing SPI and summarizes the main measurement matrices and reconstruction algorithms in compressive sensing. Further, the performance of their applications in SPI through simulations and experiments is explored in detail, and then their advantages and disadvantages are summarized. Finally, the prospect of compressive sensing with SPI is discussed.
Method for Automatic Estimation of Instantaneous Frequency and Group Delay in Time–Frequency Distributions with Application in EEG Seizure Signals Analysis
Authors: Jurdana Vedran , Vrankic Miroslav , Lopac Nikola , Jadav Guruprasad Madhale
Published: May 2023

Instantaneous frequency (IF) is commonly used in the analysis of electroencephalogram (EEG) signals to detect oscillatory-type seizures. However, IF cannot be used to analyze seizures that appear as spikes. In this paper, we present a novel method for the automatic estimation of IF and group delay (GD) in order to detect seizures with both spike and oscillatory characteristics. Unlike previous methods that use IF alone, the proposed method utilizes information obtained from localized Rényi entropies (LREs) to generate a binary map that automatically identifies regions requiring a different estimation strategy. The method combines IF estimation algorithms for multicomponent signals with time and frequency support information to improve signal ridge estimation in the time–frequency distribution (TFD). Our experimental results indicate the superiority of the proposed combined IF and GD estimation approach over the IF estimation alone, without requiring any prior knowledge about the input signal. The LRE-based mean squared error and mean absolute error metrics showed improvements of up to 95.70% and 86.79%, respectively, for synthetic signals and up to 46.45% and 36.61% for real-life EEG seizure signals.
Research on Cloud-Edge-End Collaborative Computing Offloading Strategy in the Internet of Vehicles Based on the M-TSA Algorithm
Authors: Xu Qiliang , Zhang Guo , Wang Jianping
Published: May 2023

In the Internet of Vehicles scenario, the in-vehicle terminal cannot meet the requirements of computing tasks in terms of delay and energy consumption; the introduction of cloud computing and MEC is an effective way to solve the above problem. The in-vehicle terminal requires a high task processing delay, and due to the high delay of cloud computing to upload computing tasks to the cloud, the MEC server has limited computing resources, which will increase the task processing delay when there are more tasks. To solve the above problems, a vehicle computing network based on cloud-edge-end collaborative computing is proposed, in which cloud servers, edge servers, service vehicles, and task vehicles themselves can provide computing services. A model of the cloud-edge-end collaborative computing system for the Internet of Vehicles is constructed, and a computational offloading strategy problem is given. Then, a computational offloading strategy based on the M-TSA algorithm and combined with task prioritization and computational offloading node prediction is proposed. Finally, comparative experiments are conducted under task instances simulating real road vehicle conditions to demonstrate the superiority of our network, where our offloading strategy significantly improves the utility of task offloading and reduces offloading delay and energy consumption.
Ensembles of Convolutional Neural Networks and Transformers for Polyp Segmentation
Authors: Nanni Loris , Fantozzi Carlo , Loreggia Andrea , Lumini Alessandra
Published: May 2023

In the realm of computer vision, semantic segmentation is the task of recognizing objects in images at the pixel level. This is done by performing a classification of each pixel. The task is complex and requires sophisticated skills and knowledge about the context to identify objects’ boundaries. The importance of semantic segmentation in many domains is undisputed. In medical diagnostics, it simplifies the early detection of pathologies, thus mitigating the possible consequences. In this work, we provide a review of the literature on deep ensemble learning models for polyp segmentation and develop new ensembles based on convolutional neural networks and transformers. The development of an effective ensemble entails ensuring diversity between its components. To this end, we combined different models (HarDNet-MSEG, Polyp-PVT, and HSNet) trained with different data augmentation techniques, optimization methods, and learning rates, which we experimentally demonstrate to be useful to form a better ensemble. Most importantly, we introduce a new method to obtain the segmentation mask by averaging intermediate masks after the sigmoid layer. In our extensive experimental evaluation, the average performance of the proposed ensembles over five prominent datasets beat any other solution that we know of. Furthermore, the ensembles also performed better than the state-of-the-art on two of the five datasets, when individually considered, without having been specifically trained for them.
Low Latency TOE with Double-Queue Structure for 10Gbps Ethernet on FPGA
Authors: Yang Dan , Xu Xuhan , Chen Tianyang , Chen Yanhao , Zhang Junjie
Published: May 2023

The TCP protocol is a connection-oriented and reliable transport layer communication protocol which is widely used in network communication. With the rapid development and popular application of data center networks, high-throughput, low-latency, and multi-session network data processing has become an immediate need for network devices. If only a traditional software protocol stack is used for processing, it will occupy a large amount of CPU resources and affect network performance. To address the above issues, this paper proposes a double-queue storage structure for a 10G TCP/IP hardware offload engine based on FPGA. Furthermore, a TOE reception transmission delay theoretical analysis model for interaction with the application layer is proposed, so that the TOE can dynamically select the transmission channel based on the interaction results. After board-level verification, the TOE supports 1024 TCP sessions with a reception rate of 9.5 Gbps and a minimum transmission latency of 600 ns. When the TCP packet payload length is 1024 bytes, the latency performance of TOE’s double-queue storage structure improves by at least 55.3% compared to other hardware implementation approaches. When compared with software implementation approaches, the latency performance of TOE is only 3.2% of the software approaches.
Ultrasonic Energy and Data Transfer through a Metal—Liquid Multi-Layer Channel Enhanced by Automatic Gain and Carrier Control
Authors: Pereira Raphael B. , Braga Arthur M. B. , Kubrusly Alan C.
Published: May 2023

Ultrasonic communication and power transfer are attractive solutions when conventional electromagnetic-based or wired connections are unfeasible. Most ultrasonic communication applications concern a single-solid barrier. Nevertheless, some relevant scenarios can be composed of several fluid—solid media, through which communication and power transfer are intended. Due to its multi-layer nature, insertion loss and, consequently, the system efficiency considerably decrease. This paper presents an ultrasonic system capable of simultaneously power transferring and transmitting data through a set of two flat steel plates separated by a fluid layer using a pair of co-axially aligned piezoelectric transducers on opposite sides of the barrier. The system is based on frequency modulation and adopts a novel technique for automatic gain and automatic carrier control. The modems used herein were developed specifically for this application, rendering the system able to transfer data at a rate of 19,200 bps, using the frequency shift keying (FSK) modulation scheme and simultaneously transferring 66 mW of power through two flat steel plates (5 mm) separated by a fluid layer (100 mm), which completely supplied a pressure and temperature sensor. The proposed automatic gain control allowed a higher data transmission rate and the automatic carrier control reduced power consumption. The former reduced the transmission error from 12% to 5%, while the latter reduced the global power consumption from 2.6 W to 1.2 W. The proposed system is promising for monitoring applications such as oil wellbore structural health monitoring systems.
Active Alignment of Large-Aperture Space Telescopes for Optimal Ellipticity Performance
Authors: Bai Xiaoquan , Gu Xixi , Xu Boqian , Jiang Fengyi , Lu Zhirong , Xu Shuyan , Ju Guohao
Published: May 2023

Ellipticity performance of space telescopes is important for exploration of dark matter. However, traditional on-orbit active optical alignment of space telescopes often takes “minimum wavefront error across the field of view” as the correction goal, and the ellipticity performance after correcting the wave aberration is not optimal. This paper proposes an active optical alignment strategy to achieve optimal ellipticity performance. Based on the framework of nodal aberration theory (NAT), the aberration field distribution corresponding to the optimal full field-of-view ellipticity is determined using global optimization. The degrees of freedom (DOFs) of the secondary mirror and the folded flat mirror are taken as the compensation DOFs to achieve the optimal ellipticity performance. Some valuable insights into aberration field characteristics corresponding to optimal ellipticity performance are presented. This work lays a basis for the correction of ellipticity for complicated optical systems.
A Novel Method for Recognizing Space Radiation Sources Based on Multi-Scale Residual Prototype Learning Network
Authors: Liu Pengfei , Guo Lishu , Zhao Hang , Shang Peng , Chu Ziyue , Lu Xiaochun
Published: May 2023

As a basic task and key link of space situational awareness, space target recognition has become crucial in threat analysis, communication reconnaissance and electronic countermeasures. Using the fingerprint features carried by the electromagnetic signal to recognize is an effective method. Because traditional radiation source recognition technologies are difficult to obtain satisfactory expert features, automatic feature extraction methods based on deep learning have become popular. Although many deep learning schemes have been proposed, most of them are only used to solve the inter-class separable problem and ignore the intra-class compactness. In addition, the openness of the real space may invalidate the existing closed-set recognition methods. In order to solve the above problems, inspired by the application of prototype learning in image recognition, we propose a novel method for recognizing space radiation sources based on a multi-scale residual prototype learning network (MSRPLNet). The method can be used for both the closed- and open-set recognition of space radiation sources. Furthermore, we also design a joint decision algorithm for an open-set recognition task to identify unknown radiation sources. To verify the effectiveness and reliability of the proposed method, we built a set of satellite signal observation and receiving systems in a real external environment and collected eight Iridium signals. The experimental results show that the accuracy of our proposed method can reach 98.34% and 91.04% for the closed- and open-set recognition of eight Iridium targets, respectively. Compared to similar research works, our method has obvious advantages.
A Comprehensive Survey on Multi-Agent Reinforcement Learning for Connected and Automated Vehicles
Authors: Yadav Pamul , Mishra Ashutosh , Kim Shiho
Published: May 2023

Connected and automated vehicles (CAVs) require multiple tasks in their seamless maneuverings. Some essential tasks that require simultaneous management and actions are motion planning, traffic prediction, traffic intersection management, etc. A few of them are complex in nature. Multi-agent reinforcement learning (MARL) can solve complex problems involving simultaneous controls. Recently, many researchers applied MARL in such applications. However, there is a lack of extensive surveys on the ongoing research to identify the current problems, proposed methods, and future research directions in MARL for CAVs. This paper provides a comprehensive survey on MARL for CAVs. A classification-based paper analysis is performed to identify the current developments and highlight the various existing research directions. Finally, the challenges in current works are discussed, and some potential areas are given for exploration to overcome those challenges. Future readers will benefit from this survey and can apply the ideas and findings in their research to solve complex problems.
MDED-Framework: A Distributed Microservice Deep-Learning Framework for Object Detection in Edge Computing
Authors: Seo Jihyun , Jang Sumin , Cha Jaegeun , Choi Hyunhwa , Kim Daewon , Kim Sunwook
Published: May 2023

The demand for deep learning frameworks capable of running in edge computing environments is rapidly increasing due to the exponential growth of data volume and the need for real-time processing. However, edge computing environments often have limited resources, necessitating the distribution of deep learning models. Distributing deep learning models can be challenging as it requires specifying the resource type for each process and ensuring that the models are lightweight without performance degradation. To address this issue, we propose the Microservice Deep-learning Edge Detection (MDED) framework, designed for easy deployment and distributed processing in edge computing environments. The MDED framework leverages Docker-based containers and Kubernetes orchestration to obtain a pedestrian-detection deep learning model with a speed of up to 19 FPS, satisfying the semi-real-time condition. The framework employs an ensemble of high-level feature-specific networks (HFN) and low-level feature-specific networks (LFN) trained on the MOT17Det dataset, achieving an accuracy improvement of up to AP50 and AP0.18 on MOT20Det data.
The Monitoring and Management of an Operating Environment to Enhance the Safety of a Container-Type Energy Storage System
Authors: Park Hye-Yeon , Lee Jin-Wook , Park Sung-Won , Son Sung-Yong
Published: May 2023

The implementation of an energy storage system (ESS) as a container-type package is common due to its ease of installation, management, and safety. The control of the operating environment of an ESS mainly considers the temperature rise due to the heat generated through the battery operation. However, the relative humidity of the container often increases by over 75% in many cases because of the operation of the air conditioner which pursues temperature-first control. Humidity is a major factor which can cause safety issues such as fires owing to insulation breakdown caused by condensation. However, the importance of humidity control in ESS is underestimated compared to temperature control. In this study, temperature and humidity monitoring and management issues were addressed for a container-type ESS by building sensor-based monitoring and control systems. Furthermore, a rule-based air conditioner control algorithm was proposed for temperature and humidity management. A case study was conducted to compare the conventional and proposed control algorithms and verify the feasibility of the proposed algorithm. The results showed that the proposed algorithm reduced the average humidity by 11.4% compared to the value achieved with the existing temperature control method while also maintaining the temperature.
Separation of Co(II) and Ni(II) Using an Analog of Glycine-Betaine Based on Task-Specific Ionic Liquids
Authors: Boulafrouh Lamia , Boudesocque Stéphanie , Mohamadou Aminou , Dupont Laurent
Published: May 2023

A series of salts based on ethyl ester glycine-betaine derivatives, viz tri(n-pentyl)[2-ethoxy-2-oxoethyl]ammonium bromide, have been synthesized. These cations generate hydrophobic ionic liquids (ILs) with bis(trifluoromethylsulfonyl)imide (Tf2N−) or dicyanamide (Dca−) anions. These new analogues of glycine-betaine-based ionic liquids (AGB-ILs) were characterized using spectroscopic methods (IR, 1H, and 13C NMR) and elemental analysis. These AGB-ILs were used for the selective separation of Ni(II) and Co(II) in saline media using pure ILs phase or ILs diluted in organic solvent. Interestingly, extraction of Co(II) and Ni(II) in Dca-based AGB-ILs can be enhanced using salts with chaotropic anions such as NaNO3 (E > 90% for Co(II) and E = 85% for Ni(II)). Tf2N−-based ionic liquids do not extract Ni(II) or Co(II) even in NaCl 4M. Dca−-based ILs lead to a quasi-quantitative extraction of Co(II), while extraction of Ni(II) is limited to a few percent (17%) leading to separation factors higher than 100, ensuring a good separation of both metals. Cobalt could be back-extracted from the ionic liquid phase with water or with an aqueous solution of Na2SO4, which limits the release of the AGB cation in aqueous media, thus preserving its integrity. Results obtained by AGB-ILs diluted in organic solvent were comparable to those obtained with the pure AGB-ILs phase, indicating that this strategy can be deployed on systems working continuously out of equilibrium since the extraction mechanisms involve fast equilibria.
Anti-Racist Perspectives of Sustainabilities
Authors: Datta Ranjan
Published: May 2023

This Special Issue centers on anti-racist and decolonial perspectives of sustainability [...]
Developmental Outcomes for Young People Participating in Informal and Lifestyle Sports: A Scoping Review of the Literature, 2000–2020
Authors: Säfvenbom Reidar , Strittmatter Anna-Maria , Bernhardsen Guro Pauck
Published: May 2023

The aim of this study is to review the literature on lifestyle sports and lifestyle sport contexts with regard to the developmental potential they may represent in young people’s everyday lives. The review applies a relational developmental systems approach to youth development. The eligibility criteria are based on the phenomenon of interest and outcomes. Hence, we include studies examining the associations between young people performing lifestyle sports and potential developmental outcomes: mental, biological, social, and behavioral. The present study shows that the volume of research on informal lifestyle sport is rather extensive and that studies on the way these activity contexts may affect developmental processes in youth are diverse and wide ranging. The studies suggest that performing lifestyle sports may have several beneficial health and skills outcomes. Furthermore, positive associations are suggested between involvement in lifestyle sport contexts such as climbing, snowboarding, parkour, tricking, kiting, and surfing and (a) mental outcomes such joy, happiness, freedom, euphoria, motivation, self-efficacy, and well-being; (b) social outcomes such as gender equality, network building, social inclusion, interaction, friendship; and (c) behavioral outcomes such as identity, creativity, and expressions of masculinity and/or femininity. The review performed indicates that lifestyle sport contexts are flexible according to needs and desires that exist among the practitioners and that the human and democratic origins of these contexts make them supportive for positive movement experiences and for positive youth development. The findings have implications for PE teachers, social workers, policymakers, sport organizations, and urban architecture, in that providing lifestyle sport opportunities in the everyday lives of young people will foster a holistic development in a positive way.
Using the Transparency of Supply Chain Powered by Blockchain to Improve Sustainability Relationships with Stakeholders in the Food Sector: The Case Study of Lavazza
Authors: Gazzola Patrizia , Pavione Enrica , Barge Arianna , Fassio Franco
Published: May 2023

Food product safety and quality are considered to be of the utmost significance on a global scale. Highly publicized food safety incidents have significantly increased public interest in food traceability, defined as “the ability to track any food, feed, food-producing animal or substance that will be used for consumption, through all stages of production, processing, and distribution” (European Union). The World Health Organization (WHO) suggests that governments, producers, and consumers work together to ensure food safety, which calls for the dissemination of pertinent information throughout complex food value networks. Therefore, it is in the best interest of profit-driven businesses to implement information systems for tracking food goods, a significant byproduct of which is the likelihood of increased profitability. This paper aims to explore the ample possibilities for such implementations that are now available thanks to blockchain technology. In particular, the goal is to explore the dynamics of this technology and identify how it helps to create good customer relationships. For this purpose, the case of Lavazza, an important Italian roasted coffee company that has recently introduced a blockchain-tracked product to the market, is analyzed in detail, including all the steps that made the application of the technology possible and how it was finally communicated to the consumer. The case study offers a concrete example that resulted from both stakeholders’ internal need for greater traceability and consumers’ external need for greater transparency regarding the company’s sourcing processes. In this pilot project, collaboration among all the entities that are part of the chain was essential to delivering a formative, customized, and ultimately, easy-to-understand experience to the end consumer. Finally, Lavazza is an example of a company that decided to challenge itself by following a trend that will be increasingly present in future socioeconomic scenarios.
The Characterization of Slovinky Sludge Bed Material Using Spectroscopic Methods
Authors: Kozakova Lubica , Kanuchova Maria , Bakalar Tomas , Pavolova Henrieta
Published: May 2023

Slovakia has a long and distinguished tradition in the field of mining and in the processing of raw materials such as gold, silver, copper, and iron ores. In medieval times, the area that is today’s Slovakia was one of the most important producers and processors of sulfide ore, which was processed specifically by flotation. Flotation waste is the remains of fine-grained materials that are deposited in sludge beds after mining and mineral processing activities. Flotation waste also contains residues of heavy metals, which can pose a potential risk to the surrounding environment. The areas with this deposited material (heaps and sludge beds) have been classified as an environmental threat and require regular monitoring by government bodies. The Slovinky sludge bed is one of these areas. The aim of the work was therefore to investigate the selected physico-chemical properties of sludge flotation waste using spectroscopic methods (XPS, XRF, and AAS). Our findings showed that the concentrations of Cu, Zn, and Ni exceeded the limits set by the relevant legislation by several fold even two decades after the end of mining and processing activities. Although the sludge bed material is alkaline, our results showed that the sludge bed material could be a potential source of selected heavy metals. The obtained data could help in the protection and restoration of areas affected by the mining and processing of sulfide ore.
Electric Field Distribution on Zinc Oxide Pills in Gapless Surge Arresters Using Finite Element Method and Evolutionary Optimization Algorithms in HVAC Systems
Authors: Ghayedi Morteza , Jasinski Michal
Published: May 2023

This article proposes a new method for the optimal design of zinc oxide arresters based on electric field distribution on the zinc oxide column using smart algorithms and finite element analysis. This design prevents premature aging of zinc oxide tablets, especially the initial and final tablets of the column, which have a higher voltage gradient than other parts of the arrester, and subsequently increases the sustainability of the network. The spacer height, fiberglass layer thickness, and grading ring diameter and its location were taken as the problem variables. The surge arrester was designed in AC/DC mode and two-dimensional symmetry using the COMSOL Multiphysics package. For the first time, rational Bezier curves were also used for the arrester design. This paper presents an optimization approach that combines and dynamically links the electrostatic modeling process and the particle swarm optimization (PSO) and differential evolution (DE) algorithms. The proposed approach is a general method that can be used in the design of high-voltage equipment. The results showed that the lifetime and reliability were increased by reducing voltage variations in the ZnO column. Therefore, maintenance cost and implementation of a surge arrester would be reduced. Finally, the external surface of the porcelain housing was placed under the influence of uniform distribution of electric field.
The Construction of Critical Factors for Successfully Introducing Chatbots into Mental Health Services in the Army: Using a Hybrid MCDM Approach
Authors: Hsu Ming-Ching
Published: May 2023

Previous research has shown that although military personnel are at high risk of developing mental disorders because of the excessive stress caused by their work, they also display low levels of intention to seek assistance because of the military culture. This, in turn, creates exorbitant costs for their respective countries. With the rapid development of artificial intelligence (AI)-related digital technologies, chatbots have been successfully applied to mental health services. Although the introduction of chatbots into the military to assist with mental health services is not common, it may become a future trend. This study aims to construct the critical factors for introducing chatbots into mental health services in the military, the relationships between the effects, and a weighting system, to ensure that the introduction of chatbots complies with sustainable practices. This includes four stages. In the initial stage, in accordance with the AI-readiness framework, in combination with the findings of previous research and specialist recommendations, preliminary indicators and items were developed. In the second stage, Fuzzy Delphi was used to confirm each dimension and indicator. In the third stage, using DEMATEL, an influential-network-relation map (INRM) of dimensions and indicators was created. In the fourth stage, using DANP, the relationships between the effects of the indicators and the weighting system were established. The findings of this study indicated that: (1) the key to success includes four dimensions and twenty-one indicators; (2) there is an interdependent relationship between the four dimensions and twenty-one indicators, and they influence each other; and (3) the four dimensions are technologies, goals, boundaries, and activities, in order of importance. Finally, specific suggestions are put forward to provide references for future practical applications and research, drawing on the results of this research.
Analysis of Noise Levels in Typical Passenger Cars
Authors: Przydatek Grzegorz , Ryniewicz Andrzej , Irimia Oana , Tomozei Claudia , Mosnegutu Emilian , Bodziony Marcin
Published: May 2023

Passenger cars differ in their levels of emitted noise and mileage, which can have a negative impact on the environment and humans. This was confirmed by the results of this study on the noise levels generated by passenger cars that have the same parameters, or are of one type. The loudest place in the tested vehicles turned out to be the combustion engine compartment, with the average noise level exceeding 90 dB and exhibiting a noticeable, significant increase alongside an increase in the mileage of the vehicles. This value of noise intensity is classified as dangerous for the human body. As a result of the conducted tests, it can be concluded that an engine cover is an important element in damping the sounds emitted by an internal combustion engine after the use of an aluminum heat shield to increase noise absorption. In the future, the environmental problem of noise emission from cars can be solved by encouraging the use of quieter, electric vehicles.
Perceived Restorative Potential of Urban Parks by Citizens—A Case Study from Wrocław, Poland
Authors: Szkopiecka Aleksandra , Wyrwa Joanna Patrycja , Chrobak Grzegorz , Kołodyńska Iga , Szewrański Szymon
Published: May 2023

Providing restorative green areas is important, especially in the city, where the level of stress and noise is relatively high. Therefore, green areas, such as urban parks, should provide coherent audio–visual stimuli to achieve positive perception by the residents. Therefore, this study aims to investigate the potential for psychological regeneration in urban parks in terms of visual and soundscape assessment as well as to assess the role of the intensity of different types of sound contributing to the positive perception of the soundscape. In order to achieve this aim, we chose eight urban parks in the city of Wrocław to provide audio and visual stimuli and used a group of young adults as survey respondents. The results show that visual stimuli are perceived as undoubtedly more important than the soundscape, and that talking, footsteps, music, children (playing), birds, and vehicles are the most significant types of sound that contribute to the perception of soundscape depending on the level of intensity of the sound (with children and vehicles being beneficial if they are completely inaudible). We conclude that the quality of the soundscape is essential to improve the restorative potential of urban parks and, in consequence, to improve the well-being and health of the city dwellers, and there is a necessity for strategies and development plans including sensually coherent and inclusive public parks in the city of Wrocław.
Parabolic Air Collectors with an Evacuated Tube Containing Copper Tube and Spiral Strip, and a New Cavity Receiver: Experimental Performance Analysis
Authors: Khlief Ayad K. , Al-Maliki Wisam Abed Kattea , Abdul Wahhab Hasanain A. , Alobaid Falah , Epple Bernd , Abtan Akeel A.
Published: May 2023

Sunray thermal energy is one of the most promising and quickly growing techniques globally. In parabolic trough air collectors (PTAC), receiver design and safety are of paramount importance because of their impact on the overall effectiveness of power plants. However, experimental studies of alternative receivers to improve heat transfer are still to be performed. In this study, a PTAC system was tested experimentally with an evacuated tube: open on one end, containing a copper tube and a spiral strip (case 1), and with a new cavity receiver consisting of several arranged tetragonal pyramidal elements (case 2). Afterward, the results were compared and showed a slightly superior exit air temperature and thermal efficiency performance for case 1. The overall results demonstrate a remarkable convergence of case 2 from case 1 in terms of temperature increase across PTAC, in which the maximum exit air temperature for case 1 is 58.2 °C, a 3.4% increase over case 2 at 0.0105 kg/s mass flow rate. Lastly, the results validate the potential and clarify the specific conclusions of these methods’ application in improving heat exchange in a PTAC.
Towards Communication in Achieving Sustainable Economic Development Goals: The Role of Communication in UAE Media Institutions
Authors: Farhi Faycal , Jeljeli Riadh , Slamene Radouane , Mohsen Merhan , Zamoum Khaled
Published: May 2023

Communication is vital in achieving the economic sustainability of media institutions. They adopt strategies that help organizations to communicate effectively, foster partnerships, and promote the adoption of innovations. This study examined the role of communication in developing the media institutions in the United Arab Emirates to acquire economic sustainability goals. The researchers applied the case study method and selected 500 respondents from the UAE Business-to-Business Communication Database. Research revealed that communication positively affects Emirati media institutions. Public relations and communication practices help these organizations to achieve economic sustainability. It was found that public relations and communication affect these organizations to foster partnerships in terms of ensuring transparent operations and trust building. However, the effect of public relations and communication on promoting innovation remained insignificant, as a slight agreement was shown regarding the relevant phenomenon. It was concluded that economic sustainability holds great significance in the Sustainable Development Goals (SDGs) framework, and communication ensures they are achieved in the best possible manner. As a result, Emirates-based corporate sector organizations acknowledge the significance of public relations and communication and integrate these strategies into their comprehensive business plans to attain sustainable economic growth and development.
The Impact of Internet Use on Production Efficiency of Animal Husbandry: Based on the Evidence of 340 Herdsmen in Inner Mongolia, China
Authors: Chai Zhihui , Tian Mingjun , Yao Fengtong
Published: May 2023

Production efficiency is a standard to evaluate the high-quality development of animal husbandry. As an important tool for herdsmen to collect and use information for animal husbandry production and innovation, the internet is not only an inner motivation for improvement of production efficiency but also an important engine for transformation of animal husbandry modernization. It is of practical significance to analyze the impact of internet use on the production efficiency of animal husbandry from the micro-level. This paper, based on the survey data of 340 herdsmen in Inner Mongolia, adopts the Stochastic Frontier Analysis (SFA) model to measure the production efficiency of animal husbandry and selects the Tobit model and moderation effect model to analyze the relationship between internet use and animal husbandry production efficiency under the influence of different capitals. Results show that the production efficiency of animal husbandry is relatively low and internet use has a positive and statistically significant effect on production efficiency; moreover, social capital and financial capital have a negative moderation effect when internet use affects production efficiency. Our findings suggest that the use of internet technology should be paid more attention in order to increase the production efficiency of grass-based animal husbandry in Inner Mongolia.
Sustainable Development of Lithium-Based New Energy in China from an Industry Chain Perspective: Risk Analysis and Policy Implications
Authors: Yuan Jiehui , Liu Zhihong , Zhou Ting , Tang Xiaoming , Yuan Juan , Yuan Wenli
Published: May 2023

Lithium-based new energy is identified as a strategic emerging industry in many countries like China. The development of lithium-based new energy industries will play a crucial role in global clean energy transitions towards carbon neutrality. This paper establishes a multi-dimensional, multi-perspective, and achievable analysis framework to conduct a system analysis for determining the potential risks involved in the sustainable development of lithium-based new energy industries in China and other countries towards a carbon-neutral future. The results show that critical risk points including resource supply risks, overcapacity risks, environmental impact risks, and regulation absence risks have emerged with the large-scale development of the lithium-based new energy industry in China. These will not be helpful for the sustainable development of the lithium-based new energy industry, which will play a vital role in attaining the goal of carbon neutrality. Based on our risk identification, a policy implication analysis was performed to investigate potential policy countermeasures including promoting the exploration and development of domestic lithium resources, improving the coordination degree of the lithium-based new energy industry, adopting green and low-carbon development paths, and improving the quality of industry regulation. Based on our findings, recommendations are proposed to optimize policy formulation and implementation for stimulating the sustainable development of the lithium-based new energy industry towards a carbon-neutral future.
Asymmetry of Sagittal Otolith Shape Based on Inner Ear Side Tested on Mediterranean Red Mullet (Mullus barbatus Linnaeus, 1758): Comparative Analysis of 2D and 3D Otolith Shape Data
Authors: Andrialovanirina Nicolas , Caillault Émilie Poisson , Couette Sébastien , Laffont Rémi , Poloni Lauriane , Lutet-Toti Camille , Mahé Kélig
Published: May 2023

Sagittal otolith shape analysis is one of the most widespread techniques worldwide to discriminate fish stock units, as this proxy integrates both environmental and genetic factors. All previous otolith shape studies have been carried out using two-dimensional (2D) images, a partial representation of the whole shape of the otolith. However, prior to the identification of stock unit boundaries, the influence of other potential drivers controlling the otolith shape must be analysed to limit their bias. In this study, the presence of asymmetry in otolith shape depending on the inner ear side (i.e., left versus right inner ears) was tested by comparing the approaches of 2D and three-dimensional (3D) sagittal otolith shape analyses. Eighty-two red mullet adults (Mullus barbatus) from three locations in the eastern part of the Mediterranean Sea were studied. Fourier harmonic descriptors computed from 2D outlines and spherical harmonic descriptors computed from 3D meshes were used to evaluate otolith shape variation. The results of a multivariate mixed-effects model from 2D images showed that there was no asymmetry effect of inner ear side on the otolith shape in any location. There was, however, a significant geographical effect for the 2D otolith shape between the Adriatic Sea and the Levantine Sea. In contrast, 3D information showed that both side effects and geographical differences were significant. This is the first study comparing 2D and 3D data showing different results on the same sample of red mullet. These results demonstrate the importance of 3D otolith shape analysis for stock discrimination.
Positive Periodic Solutions for a First-Order Nonlinear Neutral Differential Equation with Impulses on Time Scales
Authors: Zhu Shihong , Du Bo
Published: May 2023

In this article, we discuss the existence of a positive periodic solution for a first-order nonlinear neutral differential equation with impulses on time scales. Based on the Leggett–Williams fixed-point theorem and Krasnoselskii’s fixed-point theorem, some sufficient conditions are established for the existence of positive periodic solution. An example is given to show the feasibility and application of the obtained results. Since periodic solutions are solutions with symmetry characteristics, the existence conditions for periodic solutions also imply symmetry.
FSVM- and DAG-SVM-Based Fast CU-Partitioning Algorithm for VVC Intra-Coding
Authors: Wang Fengqin , Wang Zhiying , Zhang Qiuwen
Published: May 2023

H.266/VVC introduces the QTMT partitioning structure, building upon the foundation laid by H.265/HEVC, which makes the partitioning more diverse and flexible but also brings huge coding complexity. To better address the problem, we propose a fast CU decision algorithm based on FSVMs and DAG-SVMs to reduce encoding time. The algorithm divides the CU-partitioning process into two stages and symmetrically extracts some of the same CU features. Firstly, CU is input into the trained FSVM model, extracting the standard deviation, directional complexity, and content difference complexity of the CUs, and it uses these features to make a judgment on whether to terminate the partitioning early. Then, the determination of the partition type of CU is regarded as a multi-classification problem, and a DAG-SVM classifier is used to classify it. The extracted features serve as input to the classifier, which predicts the partition type of the CU and thereby prevents unnecessary partitioning. The results of the experiment indicate that compared with the reference software VTM10.0 anchoring algorithm, the algorithm can save 49.38%~58.04% of coding time, and BDBR only increases by 0.76%~1.37%. The video quality and encoding performance are guaranteed while the encoding complexity is effectively reduced.
Probing the Lorentz Invariance Violation via Gravitational Lensing and Analytical Eigenmodes of Perturbed Slowly Rotating Bumblebee Black Holes
Authors: Mangut Mert , Gürsel Huriye , Kanzi Sara , Sakallı İzzet
Published: May 2023

The ability of bumblebee gravity models to explain dark energy, which is the phenomenon responsible for the universe’s observed accelerated expansion, is one of their most significant applications. An effect that causes faster expansion can be linked to how much the Lorentz symmetry of our universe is violated. Moreover, since we do not know what generates dark energy, the bumblebee gravity theory seems highly plausible. By utilizing the physical changes happening around a rotating bumblebee black hole (RBBH), we aim to obtain more specific details about the bumblebee black hole’s spacetime and our universe. However, as researched in the literature, slow-spinning RBBH (SRBBH) spacetime, which has a higher accuracy, will be considered instead of general RBBH. To this end, we first employ the Rindler–Ishak method (RIM), which enables us to study how light is bent in the vicinity of a gravitational lens. We evaluate the deflection angle of null geodesics in the equatorial plane of the SRBBH spacetime. Then, we use astrophysical data to see the effect of the Lorentz symmetry breaking (LSB) parameter on the bending angle of light for numerous astrophysical stars and black holes. We also acquire the analytical greybody factors (GFs) and quasinormal modes (QNMs) of the SRBBH. Finally, we visualize and discuss the results obtained in the conclusion section.
Modelling Neutron-Star Ocean Dynamics
Authors: Gittins Fabian , Celora Thomas , Beri Aru , Andersson Nils
Published: May 2023

We revisit the calculation of mode oscillations in the ocean of a rotating neutron star, which may be excited during thermonuclear X-ray bursts. Our present theoretical understanding of ocean modes relies heavily on the traditional approximation commonly employed in geophysics. The approximation elegantly decouples the radial and angular sectors of the perturbation problem by neglecting the vertical contribution from the Coriolis force. However, as the implicit assumptions underlying it are not as well understood as they ought to be, we examine the traditional approximation and discuss the associated mode solutions. The results demonstrate that, while the approximation may be appropriate in certain contexts, it may not be accurate for rapidly rotating neutron stars. In addition, using the shallow-water approximation, we show analytically how the solutions that resemble r-modes change their nature in neutron-star oceans to behave like gravity waves. We also outline a simple prescription for lifting Newtonian results in a shallow ocean to general relativity, making the result more realistic.
In Vitro Antiviral Activity of Nordihydroguaiaretic Acid against SARS-CoV-2
Authors: Villalobos-Sánchez Erendira , García-Ruiz Daniel , Camacho-Villegas Tanya A. , Canales-Aguirre Alejandro A. , Gutiérrez-Ortega Abel , Muñoz-Medina José E. , Elizondo-Quiroga Darwin E.
Published: May 2023

The coronavirus infectious disease 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has been spreading rapidly worldwide, creating a pandemic. This article describes the evaluation of the antiviral activity of nordihydroguaiaretic acid (NDGA), a molecule found in Creosote bush (Larrea tridentata) leaves, against SARS-CoV-2 in vitro. A 35 µM concentration of NDGA was not toxic to Vero cells and exhibited a remarkable inhibitory effect on the SARS-CoV-2 cytopathic effect, viral plaque formation, RNA replication, and expression of the SARS-CoV-2 spike glycoprotein. The 50% effective concentration for NDGA was as low as 16.97 µM. Our results show that NDGA could be a promising therapeutic candidate against SARS-CoV-2.