bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition
Authors: Yang Jung-Hwan , Kim Seong-Yong , Lim Soo-Chul
Published: March 2023

In robotics, tactile perception is important for fine control using robot grippers and hands. To effectively incorporate tactile perception in robots, it is essential to understand how humans use mechanoreceptors and proprioceptors to perceive texture. Thus, our study aimed to investigate the impact of tactile sensor arrays, shear force, and the positional information of the robot’s end effector on its ability to recognize texture. A deep learning network was employed to classify tactile data from 24 different textures that were explored by a robot. The input values of the deep learning network were modified based on variations in the number of channels of the tactile signal, the arrangement of the tactile sensor, the presence or absence of shear force, and the positional information of the robot. By comparing the accuracy of texture recognition, our analysis revealed that tactile sensor arrays more accurately recognized the texture compared to a single tactile sensor. The utilization of shear force and positional information of the robot resulted in an improved accuracy of texture recognition when using a single tactile sensor. Furthermore, an equal number of sensors placed in a vertical arrangement led to a more accurate distinction of textures during exploration when compared to sensors placed in a horizontal arrangement. The results of this study indicate that the implementation of a tactile sensor array should be prioritized over a single sensor for enhanced accuracy in tactile sensing, and the use of integrated data should be considered for single tactile sensing.
Monolayer Graphene Terahertz Detector Integrated with Artificial Microstructure
Authors: Jiang Mengjie , Zhang Kaixuan , Lv Xuyang , Wang Lin , Zhang Libo , Han Li , Xing Huaizhong
Published: March 2023

Graphene, known for its high carrier mobility and broad spectral response range, has proven to be a promising material in photodetection applications. However, its high dark current has limited its application as a high-sensitivity photodetector at room temperature, particularly for the detection of low-energy photons. Our research proposes a new approach for overcoming this challenge by designing lattice antennas with an asymmetric structure for use in combination with high-quality monolayers of graphene. This configuration is capable of sensitive detection of low-energy photons. The results show that the graphene terahertz detector-based microstructure antenna has a responsivity of 29 V·W−1 at 0.12 THz, a fast response time of 7 μs, and a noise equivalent power of less than 8.5 pW/Hz1/2. These results provide a new strategy for the development of graphene array-based room-temperature terahertz photodetectors.
EDPNet: An Encoding–Decoding Network with Pyramidal Representation for Semantic Image Segmentation
Authors: Chen Dong , Li Xianghong , Hu Fan , Mathiopoulos P. Takis , Di Shaoning , Sui Mingming , Peethambaran Jiju
Published: March 2023

This paper proposes an encoding–decoding network with a pyramidal representation module, which will be referred to as EDPNet, and is designed for efficient semantic image segmentation. On the one hand, during the encoding process of the proposed EDPNet, the enhancement of the Xception network, i.e., Xception+ is employed as a backbone to learn the discriminative feature maps. The obtained discriminative features are then fed into the pyramidal representation module, from which the context-augmented features are learned and optimized by leveraging a multi-level feature representation and aggregation process. On the other hand, during the image restoration decoding process, the encoded semantic-rich features are progressively recovered with the assistance of a simplified skip connection mechanism, which performs channel concatenation between high-level encoded features with rich semantic information and low-level features with spatial detail information. The proposed hybrid representation employing the proposed encoding–decoding and pyramidal structures has a global-aware perception and captures fine-grained contours of various geographical objects very well with high computational efficiency. The performance of the proposed EDPNet has been compared against PSPNet, DeepLabv3, and U-Net, employing four benchmark datasets, namely eTRIMS, Cityscapes, PASCAL VOC2012, and CamVid. EDPNet acquired the highest accuracy of 83.6% and 73.8% mIoUs on eTRIMS and PASCAL VOC2012 datasets, while its accuracy on the other two datasets was comparable to that of PSPNet, DeepLabv3, and U-Net models. EDPNet achieved the highest efficiency among the compared models on all datasets.
Rethinking LEO Mega-Constellation Routing to Provide Fast Internet Access Services
Authors: Yang Zijian , Tian Feng , Jin Jifeng , Liu Huijie
Published: March 2023

In the realm of providing space-based internet access services, utilizing large-scale low Earth orbit (LEO) satellite networks have emerged as a promising solution for bridging the digital divide and connecting previously unconnected regions. The deployment of LEO satellites can augment terrestrial networks, with increased efficiency and reduced costs. However, as the size of LEO constellations continues to grow, the routing algorithm design of such networks faces numerous challenges. In this study, we present a novel routing algorithm, designated as Internet Fast Access Routing (IFAR), aimed at facilitating faster internet access for users. The algorithm consists of two main components. Firstly, we develop a formal model that calculates the minimum number of hops between any two satellites in the Walker-Delta constellation, along with the corresponding forwarding direction from source to destination. Then, a linear programming is formulated, to match each satellite to the visible satellite on the ground. Upon receipt of user data, each satellite then forwards the data only to the set of visible satellites that correspond to its own satellite. To validate the efficacy of IFAR, we conduct extensive simulation work, and the experimental results showcase the potential of IFAR to enhance the routing capabilities of LEO satellite networks and improve the overall quality of space-based internet access services.
IDBD-Based Beamforming Algorithm for Improving the Performance of Phased Array Radar in Nonstationary Environments
Authors: Wang Shihan , Chen Tao , Wang Hongjian
Published: March 2023

Adaptive array processing technology for a phased array radar is usually based on the assumption of a stationary environment; however, in real-world scenarios, nonstationary interference and noise deteriorate the performance of the traditional gradient descent algorithm, in which the learning rate of the tap weights is fixed, leading to errors in the beam pattern and a reduced output signal-to-noise ratio (SNR). In this paper, we use the incremental delta-bar-delta (IDBD) algorithm, which has been widely used for system identification problems in nonstationary environments, to control the time-varying learning rates of the tap weights. The designed iteration formula for the learning rate ensures that the tap weights adaptively track the Wiener solution. The results of numerical simulations show that in a nonstationary environment, the traditional gradient descent algorithm with a fixed learning rate has a distorted beam pattern and reduced output SNR; however, the IDBD-based beamforming algorithm, in which a secondary control mechanism is used to adaptively update the learning rates, showed a similar beam pattern and output SNR to a traditional beamformer in a Gaussian white noise background; that is, the main beam and null satisfied the pointing constraints, and the optimal output SNR was obtained. Although the proposed algorithm contains a matrix inversion operation, which has considerable computational complexity, this operation could be replaced by the Levinson–Durbin iteration due to the Toeplitz characteristic of the matrix; therefore, the computational complexity could be decreased to O(n), so additional computing resources are not required. Moreover, according to some intuitive interpretations, the reliability and stability of the algorithm are guaranteed.
Adaptive Bitline Voltage Countermeasure for Neighbor Wordline Interference in 3D NAND Flash Memory-Based Sensors
Authors: Fan Hanshui , Tian Xuan , Peng Huiting , Shen Yinfeng , Li Liang , Li Ming , Gao Liming
Published: March 2023

Three-dimensional NAND flash memory is widely used in sensor systems as an advanced storage medium that ensures system stability through fast data access. However, in flash memory, as the number of cell bits increases and the process pitch keeps scaling, the data disturbance becomes more serious, especially for neighbor wordline interference (NWI), which leads to a deterioration of data storage reliability. Thus, a physical device model was constructed to investigate the NWI mechanism and evaluate critical device factors for this long-standing and intractable problem. As simulated by TCAD, the change in channel potential under read bias conditions presents good consistency with the actual NWI performance. Using this model, NWI generation can be accurately described through the combination of potential superposition and a local drain-induced barrier lowering (DIBL) effect. This suggests that a higher bitline voltage (Vbl) transmitted by the channel potential can restore the local DIBL effect, which is ever weakened by NWI. Furthermore, an adaptive Vbl countermeasure is proposed for 3D NAND memory arrays, which can significantly minimize the NWI of triple-level cells (TLC) in all state combinations. The device model and the adaptive Vbl scheme were successfully verified by TCAD and 3D NAND chip tests. This study introduces a new physical model for NWI-related problems in 3D NAND flash, while providing a feasible and promising voltage scheme as a countermeasure to optimize data reliability.
Three-Dimensional Immersion Scanning Technique: A Scalable Low-Cost Solution for 3D Scanning Using Water-Based Fluid
Authors: Gonçalves Ricardo Spyrides Boabaid Pimentel , Haueisen Jens
Published: March 2023

Three-dimensional scanning technology has been traditionally used in the medical and engineering industries, but these scanners can be expensive or limited in their capabilities. This research aimed to develop low-cost 3D scanning using rotation and immersion in a water-based fluid. This technique uses a reconstruction approach similar to CT scanners but with significantly less instrumentation and cost than traditional CT scanners or other optical scanning techniques. The setup consisted of a container filled with a mixture of water and Xanthan gum. The object to be scanned was submerged at various rotation angles. A stepper motor slide with a needle was used to measure the fluid level increment as the object being scanned was submerged into the container. The results showed that the 3D scanning using immersion in a water-based fluid was feasible and could be adapted to a wide range of object sizes. The technique produced reconstructed images of objects with gaps or irregularly shaped openings in a low-cost fashion. A 3D printed model with a width of 30.7200 ± 0.2388 mm and height of 31.6800 ± 0.3445 mm was compared to its scan to evaluate the precision of the technique. Its width/height ratio (0.9697 ± 0.0084) overlaps the margin of error of the width/height ratio of the reconstructed image (0.9649 ± 0.0191), showing statistical similarities. The signal-to-noise ratio was calculated at around 6 dB. Suggestions for future work are made to improve the parameters of this promising, low-cost technique.
Steel Strip Defect Sample Generation Method Based on Fusible Feature GAN Model under Few Samples
Authors: Yi Cancan , Chen Qirui , Xu Biao , Huang Tao
Published: March 2023

Due to the shortage of defect samples and the high cost of labelling during the process of hot-rolled strip production in the metallurgical industry, it is difficult to obtain a large quantity of defect data with diversity, which seriously affects the identification accuracy of different types of defects on the steel surface. To address the problem of insufficient defect sample data in the task of strip steel defect identification and classification, this paper proposes the Strip Steel Surface Defect-ConSinGAN (SDE-ConSinGAN) model for strip steel defect identification which is based on a single-image model trained by the generative adversarial network (GAN) and which builds a framework of image-feature cutting and splicing. The model aims to reduce training time by dynamically adjusting the number of iterations for different training stages. The detailed defect features of training samples are highlighted by introducing a new size-adjustment function and increasing the channel attention mechanism. In addition, real image features will be cut and synthesized to obtain new images with multiple defect features for training. The emergence of new images is able to richen generated samples. Eventually, the generated simulated samples can be directly used in deep-learning-based automatic classification of surface defects in cold-rolled thin strips. The experimental results show that, when SDE-ConSinGAN is used to enrich the image dataset, the generated defect images have higher quality and more diversity than the current methods do.
RIOT: Recursive Inertial Odometry Transformer for Localisation from Low-Cost IMU Measurements
Authors: Brotchie James , Li Wenchao , Greentree Andrew D. , Kealy Allison
Published: March 2023

Inertial localisation is an important technique as it enables ego-motion estimation in conditions where external observers are unavailable. However, low-cost inertial sensors are inherently corrupted by bias and noise, which lead to unbound errors, making straight integration for position intractable. Traditional mathematical approaches are reliant on prior system knowledge, geometric theories and are constrained by predefined dynamics. Recent advances in deep learning, which benefit from ever-increasing volumes of data and computational power, allow for data-driven solutions that offer more comprehensive understanding. Existing deep inertial odometry solutions rely on estimating the latent states, such as velocity, or are dependent on fixed-sensor positions and periodic motion patterns. In this work, we propose taking the traditional state estimation recursive methodology and applying it in the deep learning domain. Our approach, which incorporates the true position priors in the training process, is trained on inertial measurements and ground truth displacement data, allowing recursion and learning both motion characteristics and systemic error bias and drift. We present two end-to-end frameworks for pose invariant deep inertial odometry that utilises self-attention to capture both spatial features and long-range dependencies in inertial data. We evaluate our approaches against a custom 2-layer Gated Recurrent Unit, trained in the same manner on the same data, and tested each approach on a number of different users, devices and activities. Each network had a sequence length weighted relative trajectory error mean ≤0.4594 m, highlighting the effectiveness of our learning process used in the development of the models.
Measurements of Small Frequency Differences by Dual Mode 4 MHz Quartz Sensors
Authors: Matko Vojko
Published: March 2023

We proposed a method for measuring frequency differences of the order of a few Hz with an experimental error lower than 0.0001% by using two 4 MHz quartz oscillators, the frequencies of which are very close (a few 10 Hz difference) due to the dual mode operation (differential mode with two temperature-compensated signal frequencies or a mode with one signal and one reference frequency). We compared the existing methods for measuring frequency differences with the new method which is based on counting the number of transitions through zero within one beat period of the signal. The measuring procedure requires equal experimental conditions (temperature, pressure, humidity, parasitic impedances etc.) for both quartz oscillators. To ensure equal resonant conditions for oscillation two quartz crystals are needed, which form a temperature pair. The frequencies and resonant conditions of both oscillators must be almost equal, which is achieved by an external inductance or capacitance. In such a way, we minimized all the external effects and ensured highly stable oscillations and high sensitivity of the differential sensors. The counter detects one beat period by an external gate signal former. By using the method of counting transitions through zero within one beat period, we reduced the measuring error by three orders of magnitude, compared to the existing methods.
Multilevel Continua of Mothers, Fathers and Childless Women and Men’s Work–Life “Choices” and Their Constraints, Enablers and Consequences
Authors: Turnbull Beth , Taket Ann , Graham Melissa
Published: March 2023

Gendered and classed working, parenting and other life contexts create multifaceted interactions between quantitative (including time and effort-intensive) and qualitative (including needs, interests, aspirations and identities) work and life contexts. This research aimed to understand mothers, fathers and childless women and men’s gendered and classed strategies for managing multifaceted work and life interactions in their multilevel contexts. The research consisted of a qualitative case study of a large Australian organisation that ostensibly prioritised diversity and inclusion and offered flexible working arrangements to all employees. A grounded theory approach was used to analyse forty-seven employees’ responses to open-ended questions in a self-administered questionnaire, combined with iterative in-depth interviews with 10 employees. The findings suggested mothers, fathers, childless women and men’s nuanced strategies for managing multifaceted work–life interactions were explained by multilevel continua of “choices” between incompatible quantitative and qualitative work and life contexts, embedded in gendered and classed individual, family, community, organisational and societal constraints, enablers and consequences, which inhibited agency to make genuine work–life choices. These “choices” reflected and reinforced societally and organisationally hegemonic working, mothering, fathering and childlessness discourses.
Review the Development and Evolution of Aesthetic Education in Chinese Schools from a Policy Perspective
Authors: Li Huimei , Pang Xiaoyi , Li Chuanjun
Published: March 2023

Since the promulgation of the first school education regulations in the early 20th century, Chinese school aesthetic education has gone through its first century of history. Six stages of development have been formed in this century of vicissitudes, namely, the budding period, the starting period, the salvation movement period, the tortuous development period, the reconstruction period, and the modernization period of the new era. From a historical point of view, we can sort out and analyze the policies of school aesthetic education, and we can learn that Chinese school aesthetic education has always insisted on the direction of building socialism with Chinese characteristics, guided by the principles of Marxist aesthetics and the achievements of specific Chinese practice as the methodology, adhered to the direction of cultural development of socialism with Chinese characteristics, and aimed at cultivating qualified builders and successors for the comprehensive development of socialism with Chinese characteristics. Aesthetic education in Chinese schools places a prominent place on “establishing, cultivating and clarifying morality”, emphasizes the role of “beauty” in “goodness”, and follows the aesthetic guideline of “unity of beauty and goodness”. Art education and its practical activities are the main content of school aesthetic education. The formation mechanism, laws, and characteristics of the sustainable development of school aesthetic education in China are summarized from the perspective of the century-old school aesthetic education policy, which is of theoretical guidance for the study of the future development of school aesthetic education in China.
Reform of Electrical Engineering Undergraduate Teaching and the Curriculum System in the Context of the Energy Internet
Authors: Zhang Dongdong , Rong Cunhao , Goh Hui Hwang , Liu Hui , Li Xiang , Zhu Hongyu , Wu Thomas
Published: March 2023

After the concept of the Energy Internet was proposed in the last century, it has become a topic of great interest in recent years with the development of related technologies and the growing environmental problems. At the same time, the new technology brought by it also poses new challenges for the electrical engineering specialty, which is inseparable from power plants, power grids and other power facilities. How to reform the electrical engineering specialty to better meet the challenges it brings has become a problem that cannot be ignored. This paper comprehensively analyzes the current development status of the Energy Internet, key technologies involved in the concept of the Energy Internet, and problems in current talent training. This paper proposes to carry out curriculum reform through two main lines and to further optimize the curriculum structure, thus forming a more reasonable training program.
Assessing the Ecosystem Health of Large Drinking-Water Reservoirs Based on the Phytoplankton Index of Biotic Integrity (P-IBI): A Case Study of Danjiangkou Reservoir
Authors: Qin Mingqing , Fan Panpan , Li Yuying , Wang Hongtian , Wang Wanping , Liu Han , Messyasz Beata , Goldyn Ryszard , Li Bailian
Published: March 2023

As an important component of reservoir ecosystems, phytoplankton is often used as an indicator to assess the health of water ecosystems such as lakes and reservoirs. The exploration the phytoplankton index of biotic integrity (P-IBI) has been proposed to assess the ecological health of the large drinking-water reservoirs. This study investigated phytoplankton communities and environmental variables at 19 sampling sites in the Danjiangkou Reservoir from October 2019 to July 2021. Results showed that 170 species of phytoplankton from 9 phyla were detected in Danjiangkou Reservoir, and the total density varied from 0.61 × 105 to 36.64 × 105 cells/L, with the mean value of 8.83 × 105 cells/L. The P-IBI values were higher in winter and lower in spring in terms of time, and the spatial trend of P-IBI values from high to low was outlet of the reservoir > entrance of Dan Reservoir > entrance of Han Reservoir > Han Reservoir > Dan Reservoir. Linear regression analysis showed that the evaluation results of P-IBI and the comprehensive trophic level index (TLI) evaluation were generally consistent. Redundancy analysis (RDA) showed significant correlations between P-IBI and candidate indicators and major environmental factors with significant differences between seasons. The P-IBI is an effective tool to evaluate the ecological health of large drinking-water reservoirs and could provide some scientific reference for the ecological health assessment of large drinking-water reservoirs.
In Search for Meaning? Modelling Generation Z Spiritual Travel Motivation Scale—The Case of Serbia
Authors: Stojsavljević Rastislav , Vujičić Miroslav D. , Stankov Uglješa , Stamenković Igor , Masliković Dejan , Carmer Adam B. , Polić Darko , Mujkić Dino , Bajić Marko
Published: March 2023

Spiritual travel is increasingly viewed as an asset for the development of sustainable tourism. A great deal of research has been conducted on travel motivation to comprehend spiritually-motivated travel, but less is known about Generation Z’s travel motivation. This subject is relevant since Generation Z will represent the travel market of the future. Therefore, managers of spiritually-themed locations must understand the characteristics of their prospective visitors (Generation Z) in order to create more comprehensive tourism offerings. We use exploratory and confirmatory factor analysis to validate the scale and inferential statistics to analyse the data regarding the main socio-demographic characteristics. Spiritual and Canonical Experiences, Escapism, Ascetic Life, and Social Interactions, Natural and Cultural Values, Religious Events, and Active Participation were identified as the main dimensions in this study. In our conclusion, the ramifications of the findings for destination management and marketing are examined.
Study on Seismic Damage Risk Assessment of Mountain Tunnel Based on the Extension Theory
Authors: Chen Changjian , Zou Wei , Geng Ping , Gu Wenqi , Yuan Feiyun , He Chuan
Published: March 2023

In this paper, the extension method is applied to the assessment of seismic damage risk in mountain tunnels. Based on various considerations such as the geological conditions of the tunnel site, the state of the tunnel, the structural situation and the earthquake, the seismic damage risk assessment index for mountainous tunnels is proposed. The range of values of different assessment indexes under each grade is quantified. The seismic damage risk of the tunnel is divided into four classes, and assessed based on the extension theory. The specific assessment process is as follows: Firstly, five tunnels affected by the Wenchuan earthquake were selected to construct the matter element to be assessed, and construct the classical domain and nodal domain; then, the entropy weight method and analytical hierarchy process (AHP) were used to determine the weights of each index; finally, the correlation function values were calculated to obtain the seismic damage risk level of the tunnels. Among them, the seismic damage risk level of the Longchi tunnel and Longxi tunnel is “high risk”, and the seismic damage risk level of the Longdongzi tunnel, Youyi tunnel and Maanshi tunnel is “moderate risk”. The five tunnels are sorted according to the eigenvalues of the seismic damage risk level as follows: Longchi tunnel > Longxi tunnel > Longdongzi tunnel > Youyi tunnel > Maanshi tunnel. Combined with the seismic damage investigation of the Wenchuan earthquake, the actual seismic damage of tunnel is consistent with the assessment results, which verifies the accuracy and effectiveness of this method. The seismic damage risk assessment model for mountain tunnels proposed in this paper has certain reference value for the future seismic damage risk assessment of tunnels.
China’s Biogas Industry’s Sustainable Transition to a Low-Carbon Plan—A Socio-Technical Perspective
Authors: Wang Yanbo , Zhi Boyao , Xiang Shumin , Ren Guangxin , Feng Yongzhong , Yang Gaihe , Wang Xiaojiao
Published: March 2023

China’s biogas industry has experienced ups and downs over the past two decades, with various challenges pointing to misplaced expectations that biogas technology is overly focused on energy production. With the promotion of China’s low-carbon strategy, a more rational and sustainable transformation strategy is crucial for the development of the biogas industry. To elucidate the sustainable development process of the biogas industry, this study applies the socio-technical transition theory and the strategic niche management (SNM) approach to understand the multi-regime interactions of biogas systems and their possible future paths. At present, the Chinese biogas industry needs to abandon the expectation of energy recovery and establish the expectation of multi-functional combination, especially including nutrient cycling. This study proposes a sustainable transformation path for the biogas industry and predicts three phases based on the type of socio-technological transformation path: a transformation path to 2030 to promote niche innovation and develop core technologies; a reconfiguration path from 2030 to 2050, which will require a lot of trials and errors; and the expansion of market share in 2050 through technology replacement. This study highlights the importance of niche experimentations and broad advocacy coalitions for the biogas industry. This research also illustrates how the transformation of China’s biogas industry can be achieved through incremental innovation with consistent policy support.
Sustainability of Agriculture: A Study of Digital Groundwater Supervision
Authors: Zhu Jie , Zhou Xiangyang , Guo Jin
Published: March 2023

Groundwater depletion caused by agricultural irrigation is a worldwide problem. Digital technology has the potential to mitigate the groundwater over-exploitation problem by precisely restricting agriculture groundwater withdrawal and borewell construction. This study estimates how farmers respond to a pilot on digital groundwater supervision, which was implemented by the county government to limit the number and clarify property rights of irrigation borewells. By utilizing this recent pilot in rural China, we assess the causal impact of the digital groundwater supervision pilot on farmers’ water-saving irrigation (WSI) behaviors and investigate the heterogeneity effects and mechanisms related to the policy contents. A difference-in-differences (DID) strategy is applied to address the treatment effect of the digital groundwater supervision pilot. The results, which were based on a unique plot-crop-level panel dataset, indicate that farmers reduced water use after the pilot implementation, with most of the responses created through introducing water-saving technology and reducing water use intensity rather than through reducing irrigated acreage. In addition, village supervision, information, and cooperative incentives positively encourage farmers to adopt WSI technologies.
When Do You Enter? Entrepreneurial Firms’ Entry Timing and Product Performance in the Digital Platform Market
Authors: Chen Xuelin , Zhou Dongmei , Zhan Ziying , Lu Ruoyu
Published: March 2023

The digital platform market has evolved into a critical location for firms to engage in innovation and entrepreneurship. However, there is no clear answer to the question of when entrepreneurial firms should enter the digital platform market in order to gain a sustainable competitive advantage. A balanced panel and an individual fixed effect model were built using monthly product data from game developers on the Steam platform. Furthermore, in accordance with first-mover advantage theory, this study empirically investigated the impact of entry timing on product performance of entrepreneurial firms in the digital platform market, as well as the moderating effect of product updates. The results show that the impact of entrepreneurial firms’ entry timing on product performance in the digital platform market has a U-shaped relationship, which is moderated by product updates. These findings not only have implications for entrepreneurs looking to compete in the digital platform market, but also contribute to the sustainable development of the digital platform ecosystem.
Technology Transfer Model for Small-Scale Farms
Authors: Flórez Gómez Leidy Y. , Pico Mendoza Johanna , Guerrero Cesar D. , Carreño Alexandra Espinosa
Published: March 2023

Small-scale farms make an important contribution to food security, but they lack technification, especially in the global south. This article proposes a new model, namely, Model H, as a reference by which to facilitate technological transfer and appropriation in small producer sectors. Starting with the identification of interactions with the environment and the characterization of the transfer and appropriation process with respect to information and communication technologies, a five-stage framework is established to create and validate the new model. Based on key elements, functionalities, and five variables identified as a common ground for the transfer and appropriation of technologies, Model H is presented as a five-layer, user-centered model that aims to include in the transfer and appropriation of the solutions of all the individuals and entities that participate throughout the process. The model is validated through a pilot test using an intelligent irrigation technology called AgroRIEGO. In the process of technology transfer and appropriation, this pilot study helped to identify implementation obstacles and the importance of knowledge management as an effective channel for the exchange of information in a pertinent and timely manner.
Large-Deformation Failure Mechanism and Stability Control of a Swelling Soft Rock Roadway in a Sea Area: A Case Study in Eastern China
Authors: Dong Ling , Wang Dong , Sun Xiaoming , Jiang Yujing , Luan Hengjie , Xu Huichen , Li Baocheng , Cai Feng
Published: March 2023

Coal mining in sea areas has higher requirements for geological support systems, technical equipment levels, and safety production capacities because of the complex engineering geological conditions of underwater coal mines. In this paper, the deformation failure mechanism and stability control of a typical swelling soft rock roadway in the Beizao coal mine in a sea area are studied. A series of mechanical experiments and theoretical analyses were conducted to research the mechanical properties and reasons for the deformation failure of the swelling soft rock roadway. The type of the large-deformation failure mechanism of the soft rock roadway was identified as type IIIABC, which could be converted to a simple one, such as type IIB. The proposed stability control measure, containing constant-resistance large-deformation bolts, steel mesh, floor hollow grouting cables, and steel fiber concrete, was applied to the site. A good supporting effect was achieved, which could provide a beneficial reference for swelling soft rock roadways in sea areas.
Power of Social Media Marketing: How Perceived Value Mediates the Impact on Restaurant Followers’ Purchase Intention, Willingness to Pay a Premium Price, and E-WoM?
Authors: Bushara Meimona Abdelrhim , Abdou Ahmed Hassan , Hassan Thowayeb H. , Sobaih Abu Elnasr E. , Albohnayh Abdullah Saleh Mohammed , Alshammari Waleed Ghazi , Aldoreeb Mohammed , Elsaed Ahmed Anwar , Elsaied Mohamed Ahmed
Published: March 2023

The introduction of social media in the restaurant sector has changed the manner in which customers communicate with businesses. Social media marketing activities (SMMAs), such as customization, entertainment, trendiness, and interaction may have a substantial impact on followers’ perceived value and consumer behavioral intentions. Therefore, this research aims to investigate the impact of SMMAs on restaurant social media followers’ purchase intentions (PUR), willingness to pay a premium price (WPP), and e-WoM. Additionally, drawing on the Stimulus-Organism-Response (S-O-R) model, we seek to explore the mediation impact of perceived value (PV) in these relationships. To achieve this, an online questionnaire was developed for data collection from a convenience sample of casual-dining restaurant followers in Saudi Arabia. A sample of 433 social media followers was studied using PLS-SEM for testing the study hypotheses. The findings highlighted the significant positive impact of SMMAs on followers’ PV, PUR, e-WoM, and WPP. Further, PV partially significantly mediated the relationship between SMMAs and their consequences. Consequently, providing relevant, up-to-date, and entertaining content; responsiveness to customer needs and feedback; and positive brand engagement significantly contributed to enhancing restaurant followers’ perceived value, which sequentially improves their purchase intention, boosts positive e-WoM, and promotes the possibility of WPP for restaurant products and services. This research provides restaurant operators and marketers with valuable insights into how SMMAs influence followers’ behavioral intentions and enhances their understanding of how perceived value can be utilized to capitalize on the benefits of social media.
A Convolutional Neural Network for Coastal Aquaculture Extraction from High-Resolution Remote Sensing Imagery
Authors: Deng Jinpu , Bai Yongqing , Chen Zhengchao , Shen Ting , Li Cong , Yang Xuan
Published: March 2023

Aquaculture has important economic and environmental benefits. With the development of remote sensing and deep learning technology, coastline aquaculture extraction has achieved rapid, automated, and high-precision production. However, some problems still exist in extracting large-scale aquaculture based on high-resolution remote sensing images: (1) the generalization of large-scale models caused by the diversity of remote sensing in breeding areas; (2) the confusion of breeding target identification caused by the complex background interference of land and sea; (3) the boundary of the breeding area is difficult to extract accurately. In this paper, we built a comprehensive sample database based on the spatial distribution of aquaculture, and expanded the sample database by using confusing land objects as negative samples. A multi-scale-fusion superpixel segmentation optimization module is designed to solve the problem of inaccurate boundaries, and a coastal aquaculture network is proposed. Based on the coastline aquaculture dataset that we labelled and produced ourselves, we extracted cage culture areas and raft culture areas near the coastline of mainland China based on high-resolution remote sensing images. The overall accuracy reached 94.64% and achieved a state-of-the-art performance.
Backward-Facing Analysis for the Preliminary Estimation of the Vehicle Fuel Consumption
Authors: Tabacu Stefan , Popa Dragos
Published: March 2023

In this paper, a methodology for the estimation of fuel consumption using backward-facing analysis is presented. The method for the determination of fuel consumption was based on the evaluation of the total work required to drive the vehicle along a specific drive cycle. At the same time, the potential fuel economy was estimated using the energy that can be harvested from the wheel. The results obtained using this model were compared with complex MATLAB/Simulink models developed using the forward-facing strategy. The MATLAB Simulink model details conventional and hybrid vehicle models capable of estimating fuel consumption. The components of the longitudinal forces opposing the vehicle during driving were investigated and analyzed using the results of the analytical and simulation models. The procedure can be successfully applied to provide a quick estimate of the fuel consumption performance before detailing complex simulation models.
Starlike Functions Associated with Secant Hyperbolic Function
Authors: Bano Khadija , Raza Mohsan , Xin Qin , Tchier Fairouz , Malik Sarfraz Nawaz
Published: March 2023

Motivated by the recent work on the symmetric domains, this article investigates certain features of symmetric domain which are caused by the secant hyperbolic functions. Geometric characteristics of analytic functions associated with secant hyperbolic functions are discussed, which include the inclusion results, structural formula, certain sharp radii results such as radius of starlikeness and convexity of order α. It also finds a radius for ratios of analytic functions associated with Euler numbers.
Impact of Genetic Polymorphisms in Modifier Genes in Determining Fetal Hemoglobin Levels in Beta-Thalassemia
Authors: Tripathi Poonam , Agarwal Sarita , Mandal Kausik , Gupta Anshul , Sarangi Aditya Narayan
Published: March 2023

Genetic polymorphisms in Quantitative Trait Loci (QTL) genes such as BCL11A, HBS1L-MYB and KLF1 have been reported to influence fetal hemoglobin (HbF) levels. This prospective study was planned to evaluate the role of genetic polymorphisms in QTL genes as determinant of HbF levels in beta thalassemia major patients. The study was carried out on 100 thalassemia major patients. Blood samples were collected in EDTA and plain vials for biochemical and molecular evaluation. The BCL11A, HBS1L-MYB and KLF1 genotypes were determined using a polymerase chain reaction (PCR)-based method. Red Blood Cell (RBC) indices and HbF levels were assessed. In silico analysis was assessed using loss-of-function tool (Lof Tool). Statistical difference and genetic comparisons between groups were evaluated by using SPSS for Windows, version 16.0 (SPSS Inc., Chicago, IL, USA). Comparisons between quantitative variables were carried out after data explored for normality using Kolmogorov–Smirnov test of normality. Logistic regression was used for computation of ORs and 95% CIs (Confidence Interval). We observed association of HbF levels in thalassemia major patients with the polymorphisms in BCL11A (rs11886868 rs7557939; rs1427407 and rs766432) and HBS1L-MYB (rs9399137) gene. The results of this study indicated that the presence of polymorphisms on modifier genes are strongly associated with an increase in HbF levels in thalassemia major patients. Further research with a larger sample size and with other genes of modifier genes is required.
Geoheritage Threats in South African National Parks
Authors: Matshusa Khodani , Leonard Llewellyn
Published: March 2023

The uniqueness and potential of South African geoheritage to contribute to sustainable development is undoubtedly unmatched. However, little is known about the geoheritage threats in South Africa because geoheritage research is geographically skewed to the global North, while little focus is given to the global South. This study characterises the geoheritage threats in South Africa through a qualitative method design. This involved qualitative semi-structured interviews with 16 key informants (from the South African National Parks, national government, local communities as well tour operators, and tourism agencies). Consequently, qualitative content analysis was performed to outline geoheritage threats in South African national parks. The study concludes that the construct of geoheritage threats consists of human- and nature-induced threats. The identified human-induced geoheritage threats include mining, damage to heritage, and loss of biodiversity due to overcrowding. Furthermore, results showed that incorrect management of geoheritage has the potential to cause community conflicts, which can lead to a decrease in tourists visiting the destination. The identified nature-induced geoheritage threats are climate change, floods, and fires. These results suggest the need for the immediate protection of geoheritage sites within and outside protected area in South Africa. Thus, it is necessary to develop protection strategies to conserve South African geoheritage for current and future generations that involve protection areas managers, local communities, government departments and agencies, and academia.
Combined Exposure to Multiple Metals and Kidney Function in a Midlife and Elderly Population in China: A Prospective Cohort Study
Authors: Wang Tianci , Zhang Liming , Liu Yujie , Li Jian , Chen Guochong , Zhou Hui , Yu Lugang , Wan Zhongxiao , Dong Chen , Qin Liqiang , Chen Jingsi
Published: March 2023

[Background] Metal exposure is suspected to be correlated to kidney function. However, the combined effects of co-exposing to multiple metals, especially both toxic and protective metals, have not been completely evaluated. [Method] A prospective cohort study was conducted with the “135” cohort for the evaluation of how plasma metal levels are correlated to kidney function in a midlife and elderly community in southern China. An amount of 1368 subjects without kidney disease at baseline were enrolled in the final analysis. By using linear regression and logistic regression models, the correlation of individual metal values with renal function parameters was assessed. Measuring of the multiple metal exposure level was performed by principal component analysis (PCA). [Results] Diminished renal function, as evaluated based on fast kidney function decline, or estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2, was positively associated with the plasma concentrations of chromium and potassium, but it was negatively associated with selenium and iron (p < 0.05). In multiple-metal analyses, linear and logistic regression models showed that the iron and chromium exposure pattern had a protective effect on renal function, whereas the sodium and potassium exposure pattern and the cadmium and lead exposure pattern increased the risk for fast kidney function decline, and eGFR < 60 mL/min/1.73 m2. [Conclusions] Certain metals, including chromium, potassium, selenium, and iron, were correlated with kidney function in a midlife and elderly community in China. In addition, the potential combined influences of co-exposing to multiple metals were observed.
Geometric Outlines of the Gravitational Lensing and Its Astronomic Applications
Authors: Shen Bin , Yu Mingyang
Published: March 2023

Gravitational lensing is a topic of great application value in the field of astronomy. The properties and research methods of gravitational lensing are closely related to the geometric and relativistic characteristics of the background universe. This review focuses on the theoretical research and application of strong lenses and weak lenses. We first introduce the basic principles of gravitational lensing, focusing on the geometric basis of geometric lensing, the representation of deflection angles, and the curvature relationship in different geometric spaces. In addition, we summarize the wide range of applications of gravitational lensing, including the application of strong gravitational lensing in Schwarzschild black holes, time delay, the cosmic shearing based on weak lensing, the applications in signal extraction, dark matter, and dark energy. In astronomy, through the use of advanced astronomical instruments and computers, analyzing gravitational lensing effects to understand the structure of galaxies in the universe is an important topic at present. It is foreseeable that gravitational lensing will continue to play an important role in the study of cosmology and will enrich our understanding of the universe.
Bacteriolytic Potential of Enterococcus Phage iF6 Isolated from “Sextaphag®” Therapeutic Phage Cocktail and Properties of Its Endolysins, Gp82 and Gp84
Authors: Buzikov Rustam M. , Kazantseva Olesya A. , Piligrimova Emma G. , Ryabova Natalya A. , Shadrin Andrey M.
Published: March 2023

The number of infections caused by antibiotic-resistant strains of bacteria is growing by the year. The pathogenic bacterial species Enterococcus faecalis and Enterococcus faecium are among the high priority candidate targets for the development of new therapeutic antibacterial agents. One of the most promising antibacterial agents are bacteriophages. According to the WHO, two phage-based therapeutic cocktails and two medical drugs based on phage endolysins are currently undergoing clinical trials. In this paper, we describe the virulent bacteriophage iF6 and the properties of two of its endolysins. The chromosome of the iF6 phage is 156,592 bp long and contains two direct terminal repeats, each 2108 bp long. Phylogenetically, iF6 belongs to the Schiekvirus genus, whose representatives are described as phages with a high therapeutic potential. The phage demonstrated a high adsorption rate; about 90% of iF6 virions attached to the host cells within one minute after the phage was added. Two iF6 endolysins were able to lyse enterococci cultures in both logarithmic and stationary growth phases. Especially promising is the HU-Gp84 endolysin; it was active against 77% of enterococci strains tested and remained active even after 1 h incubation at 60 °C. Thus, iF6-like enterococci phages appear to be a promising platform for the selection and development of new candidates for phage therapy.