bluuebunny/crossref_metadata_2025 huggingface dataset:
LRFFNet: Large Receptive Field Feature Fusion Network for Semantic Segmentation of SAR Images in Building Areas
Authors: Peng Bo , Zhang Wenyi , Hu Yuxin , Chu Qingwei , Li Qianqian
Published: December 2022

There are limited studies on the semantic segmentation of high-resolution synthetic aperture radar (SAR) images in building areas due to speckle noise and geometric distortion. For this challenge, we propose the large receptive field feature fusion network (LRFFNet), which contains a feature extractor, a cascade feature pyramid module (CFP), a large receptive field channel attention module (LFCA), and an auxiliary branch. SAR images only contain single-channel information and have a low signal-to-noise ratio. Using only one level of features extracted by the feature extractor will result in poor segmentation results. Therefore, we design the CFP module; it can integrate different levels of features through multi-path connection. Due to the problem of geometric distortion in SAR images, the structural and semantic information is not obvious. In order to pick out feature channels that are useful for segmentation, we design the LFCA module, which can reassign the weight of channels through the channel attention mechanism with a large receptive field to help the network focus on more effective channels. SAR images do not include color information, and the identification of ground object categories is prone to errors, so we design the auxiliary branch. The branch uses the full convolution structure to optimize training results and reduces the phenomenon of recognizing objects outside the building area as buildings. Compared with state-of-the-art (SOTA) methods, our proposed network achieves higher scores in evaluation indicators and shows excellent competitiveness.
AgentI2P: Optimizing Image-to-Point Cloud Registration via Behaviour Cloning and Reinforcement Learning
Authors: Yan Shen , Zhang Maojun , Peng Yang , Liu Yu , Tan Hanlin
Published: December 2022

Image-to-point cloud registration refers to finding relative transformation between the camera and the reference frame of the 3D point cloud, which is critical for autonomous driving. Recently, a two-stage “frustum point cloud classification + camera pose optimization” pipeline has shown impressive results on this task. This paper focuses on the second stage and reformulates the optimization procedure as a Markov decision process. An initial pose is modified incrementally, sequentially aligning a virtual 3D point observation towards a previous classification solution. We consider such an iterative update process as a reinforcement learning task and, to this end, propose a novel agent (AgentI2P) to conduct decision making. To guide AgentI2P, we employ behaviour cloning (BC) and reinforcement learning (RL) techniques: cloning an expert to learn accurate pose movement and reinforcing an alignment reward to improve the policy further. [We demonstrate the effectiveness and efficiency of our approach on Oxford Robotcar and KITTI datasets. The (RTE, RRE) metrics are (1.34m,1.46∘) on Oxford Robotcar and (3.90m,5.94∘) on KITTI, and the inference time is 60 ms, both achieving state-of-the-art performance]. The source code will be publicly available upon publication of the paper.
Deep Encoder–Decoder Network-Based Wildfire Segmentation Using Drone Images in Real-Time
Authors: Muksimova Shakhnoza , Mardieva Sevara , Cho Young-Im
Published: December 2022

Wildfire is a hazardous natural phenomenon that leads to significant human fatalities, catastrophic environmental damages, and economic losses. Over the past few years, the intensity and frequency of fires have increased worldwide. Studies have been conducted to develop distinctive solutions to minimize forest fires. Systems for distant fire detection and monitoring have been established, showing improvements in data collection and fire characterization. However, wildfires cover vast areas, making other proposed ground systems unsuitable for optimal coverage. Unmanned aerial vehicles (UAVs) have become the subject of active research in recent years. Deep learning-based image-processing methods demonstrate improved performance in various tasks, including detection and segmentation, which can be utilized to develop modern forest firefighting techniques. In this study, we established a novel two-pathway encoder–decoder-based model to detect and accurately segment wildfires and smoke from the images captured using UAVs in real-time. Our proposed nested decoder uses pre-activated residual blocks and an attention-gating mechanism, thereby improving segmentation accuracy. Moreover, to facilitate robust and generalized training, we prepared a new dataset comprising actual incidences of forest fires and smoke, varying from small to large areas. In terms of practicality, the experimental results reveal that our method significantly outperforms existing detection and segmentation methods, despite being lightweight. In addition, the proposed model is reliable and robust for detecting and segmenting drone camera images from different viewpoints in the presence of wildfire and smoke.
Semi-Supervised Framework with Autoencoder-Based Neural Networks for Fault Prognosis
Authors: Rosa Tiago Gaspar da , Melani Arthur Henrique de Andrade , Pereira Fabio Henrique , Kashiwagi Fabio Norikazu , Souza Gilberto Francisco Martha de , Salles Gisele Maria De Oliveira
Published: December 2022

This paper presents a generic framework for fault prognosis using autoencoder-based deep learning methods. The proposed approach relies upon a semi-supervised extrapolation of autoencoder reconstruction errors, which can deal with the unbalanced proportion between faulty and non-faulty data in an industrial context to improve systems’ safety and reliability. In contrast to supervised methods, the approach requires less manual data labeling and can find previously unknown patterns in data. The technique focuses on detecting and isolating possible measurement divergences and tracking their growth to signalize a fault’s occurrence while individually evaluating each monitored variable to provide fault detection and prognosis. Additionally, the paper also provides an appropriate set of metrics to measure the accuracy of the models, which is a common disadvantage of unsupervised methods due to the lack of predefined answers during training. Computational results using the Commercial Modular Aero Propulsion System Simulation (CMAPSS) monitoring data show the effectiveness of the proposed framework.
Rope Jumping Strength Monitoring on Smart Devices via Passive Acoustic Sensing
Authors: Hou Xiaowen , Liu Chao
Published: December 2022

Rope jumping, as a fitness exercise recommended by many sports medicine practitioners, can improve cardiorespiratory capacity and physical coordination. Existing rope jump monitoring systems have limitations in terms of convenience, comfort, and exercise intensity evaluation. This paper presents a rope jump monitoring system using passive acoustic sensing. Our system exploits the off-the-shelf smartphone and headphones to capture the user’s rope-jumping sound and breathing sound after exercise. Given the captured acoustic data, the system uses a short-time energy-based approach and the high correlation between rope jumping cycles to detect the rope-jumping sound frames, then applies a dual-threshold endpoint detection algorithm to calculate the number of rope jumps. Finally, our system performs regression predictions of exercise intensity based on features extracted from the jumping speed and the mel spectrograms of the user’s breathing sound. The significant advantage of the system lies in the solution of the problem of poorly characterized mel spectrograms. We employ an attentive mechanism-based GAN to generate optimized breathing sound mel spectrograms and apply domain adversarial adaptive in the network to improve the migration capability of the system. Through extensive experiments, our system achieves (on average) 0.32 and 2.3% error rates for the rope jumping count and exercise intensity evaluation, respectively.
Effect of Source Mispositioning on the Repeatability of 4D Vertical Seismic Profiling Acquired with Distributed Acoustic Sensors
Authors: Isaenkov Roman , Tertyshnikov Konstantin , Yurikov Alexey , Shashkin Pavel , Pevzner Roman
Published: December 2022

Vertical seismic profiling (VSP) with distributed acoustic sensing (DAS) is an increasingly popular evolving technique for reservoir monitoring. DAS technology enables permanent fibre installations in wells and simultaneous seismic data recording along an entire borehole. Deploying the receivers closer to the reservoir allows for better detectability of smaller signals. A high level of repeatability is essential for the robust time-lapse monitoring of geological reservoirs. One of the prominent factors of repeatability degradation is a shift between source/receiver locations (mispositioning) during baseline and monitor surveys. While the mispositioning effect has been extensively studied for surface 4D seismic, the number of such studies for VSP is quite limited. To study the effects of source mispositioning on time-lapse data repeatability, we performed two VSP experiments at two on-shore sites with vibroseis. The first study was carried out at the Otway International Test Centre during Stage 3 of the Otway project and showed that the effect of source mispositioning on repeatability is negligible in comparison with the effect of temporal variations of the near-surface conditions. To avoid these limitations, we conducted a same-day controlled experiment at the Curtin University site. This second experiment showed that the effect of source mispositioning on repeatability is controlled by the degree of lateral variations of the near-surface conditions. Unlike in marine seismic measurements, lateral variations of near-surface properties can be strong and rapid and can degrade the repeatability for shifts of the source of a few meters. The greater the mispositioning, the higher the chance of such significant variations. When the near-surface conditions are laterally homogeneous, the effect of typical source mispositioning is small, and in all practical monitoring applications its contribution to non-repeatability is negligible.
Individuals with and without Visual Impairments Use a Force Feedback Device to Identify the Friction and Hardness of Haptic Surfaces
Authors: Papadopoulos Konstantinos , Koustriava Eleni , Georgoula Evangelia , Kalpia Vaia
Published: December 2022

The general purpose of this study is to promote access to haptic virtual environments. Using a haptic device, people with and without visual impairments (VI) are able to feel different textures and compare these textures based on different surface properties, i.e., friction and hardness. The objectives of this study were to examine the following: (a) whether the variables of friction and hardness were identifiable through the Touch device (Phantom Omni) and could therefore function as 3D haptic variables; (b) if there were differences between people with VI and sighted individuals in terms of their performance; (c) the differences that should exist between the values of each variable so that the virtual surfaces could be identified as different to each other; and (d) if the individual characteristics of participants have an impact on their performance. The results showed that it is necessary to use surfaces which are differentiated based on the degree of friction and hardness because the haptic properties of a virtual object are then better perceived. Individuals with VI need more time and more effort to understand friction and hardness, respectively. With the motivation of increasing access to object perception for people with VI in a virtual environment, accessibility advisors and experts can extract useful information for the development of functional and efficient 3D objects for haptic perception.
A Digital Architecture for the Real-Time Tracking of Wearing off Phenomenon in Parkinson’s Disease
Authors: Mezzina Giovanni , De Venuto Daniela
Published: December 2022

Levodopa administration is currently the most common treatment to alleviate Parkinson’s Disease (PD) symptoms. Nevertheless, prolonged use of Levodopa leads to a wearing-off (WO) phenomenon, causing symptoms to reappear. To build a personalized treatment plan aiming to manage PD and its symptoms effectively, there is a need for a technological system able to continuously and objectively assess the WO phenomenon during daily life. In this context, this paper proposes a WO tracker able to exploit neuromuscular data acquired by a dedicated wireless sensor network to discriminate between a Levodopa benefit phase and the reappearance of symptoms. The proposed architecture has been implemented on a heterogeneous computing platform, that statistically analyzes neural and muscular features to identify the best set of features to train the classifier model. Eight models among shallow and deep learning approaches are analyzed in terms of performance, timing and complexity metrics to identify the best inference engine. Experimental results on five subjects experiencing WO, showed that, in the best case, the proposed WO tracker can achieve an accuracy of ~84%, providing the inference in less than 41 ms. It is possible by employing a simple fully-connected neural network with 1 hidden layer and 32 units.
EEG Signal Processing for Biomedical Applications
Authors: Tran Yvonne
Published: December 2022

Electroencephalography (EEG) signals are used widely in clinical and research settings [...]
Reliability of Repeated Nordic Hamstring Strength in Rugby Players Using a Load Cell Device
Authors: Chavarro-Nieto Christian , Beaven Martyn , Gill Nicholas , Hébert-Losier Kim
Published: December 2022

Hamstring strain injuries are one of the most common injuries in Rugby Union players, representing up to 15% of all sustained injuries. The Nordic eccentric hamstring test assesses the maximal hamstring eccentric strength and imbalances between limbs. Asymmetries and deficits in hamstring strength between legs are commonly assessed and used as screening methods to prevent injuries which can only be proven effective if hamstring strength measures are reliable over time. We conducted a repeated-measures reliability study with 25 male Rugby Union players. Nordic eccentric strength and bilateral strength balance was assessed. Three testing sessions were undertaken over three consecutive weeks. Intrasession and intersession reliabilities were assessed using typical errors (TE), coefficient of variations (CV), and intraclass correlation coefficients (ICC). Our results showed good intrasession reliability (ICC = 0.79–0.90, TE = 26.8 N to 28.9 N, CV = 5.5% to 6.7%), whilst intersession reliability was fair for mean and the max (ICC = 0.52–0.64, TE = 44.1 N to 55.9 N, CV from 7.4% to 12.5%). Regarding the bilateral strength balance ratios, our results showed good intrasession reliability (ICC = 0.62–0.89, TE = 0.5, CV = 4.4% to 7.2%), whilst the intersession reliability for mean and max values was fair (ICC = 0.52–0.54) with a good absolute intersession reliability CV ranging from 8.2% to 9.6%. Assessing the Nordic eccentric hamstring strength and the bilateral strength balance in Rugby players using a load cell device is a feasible method to test, and demonstrated good intrasession and fair intersession reliability. Nordic eccentric strength assessment is a more practical and functional test than isokinetic; we provide data from Rugby Union players to inform clinicians, and to establish normative values in this cohort.
An AI-Based Colonic Polyp Classifier for Colorectal Cancer Screening Using Low-Dose Abdominal CT
Authors: Alkabbany Islam , Ali Asem M. , Mohamed Mostafa , Elshazly Salwa M. , Farag Aly
Published: December 2022

Among the non-invasive Colorectal cancer (CRC) screening approaches, Computed Tomography Colonography (CTC) and Virtual Colonoscopy (VC), are much more accurate. This work proposes an AI-based polyp detection framework for virtual colonoscopy (VC). Two main steps are addressed in this work: automatic segmentation to isolate the colon region from its background, and automatic polyp detection. Moreover, we evaluate the performance of the proposed framework on low-dose Computed Tomography (CT) scans. We build on our visualization approach, Fly-In (FI), which provides “filet”-like projections of the internal surface of the colon. The performance of the Fly-In approach confirms its ability with helping gastroenterologists, and it holds a great promise for combating CRC. In this work, these 2D projections of FI are fused with the 3D colon representation to generate new synthetic images. The synthetic images are used to train a RetinaNet model to detect polyps. The trained model has a 94% f1-score and 97% sensitivity. Furthermore, we study the effect of dose variation in CT scans on the performance of the the FI approach in polyp visualization. A simulation platform is developed for CTC visualization using FI, for regular CTC and low-dose CTC. This is accomplished using a novel AI restoration algorithm that enhances the Low-Dose CT images so that a 3D colon can be successfully reconstructed and visualized using the FI approach. Three senior board-certified radiologists evaluated the framework for the peak voltages of 30 KV, and the average relative sensitivities of the platform were 92%, whereas the 60 KV peak voltage produced average relative sensitivities of 99.5%.
The Effect of the Weight and Type of Equipment on Shoulder and Back Muscle Activity in Surface Electromyography during the Overhead Press—Preliminary Report
Authors: Błażkiewicz Michalina , Hadamus Anna
Published: December 2022

The overhead press is a multi-joint exercise that has the potential to use a high external load due to the cooperation of many muscle groups. The purpose of this study was to compare the activity of shoulder and back muscles during the overhead press with a kettlebell and a dumbbell. Surface electromyography (EMG) for the anterior and posterior deltoid, upper and lower trapezius, serratus anterior, and spinal erectors was analysed for 20 subjects. Participants performed the four trials of pressing kettlebell and dumbbell, weighted at 6 kg, and 70% of one maximum repetition (1RM) in the sitting position. Statistical analysis was performed using a non-parametric Friedman test and a post-hoc test of Dunn Bonferroni. No significant differences were found in the activation of assessed muscles when comparing dumbbell to kettlebell press trials with the same load (6 kg and 70% of 1RM). However, muscle activity of all muscles except the upper trapezius was always higher for kettlebell pressing. Different center of gravity locations in the kettlebell versus the dumbbell can increase shoulder muscle activity during the overhead press. However, more studies are required to confirm these results.
Joint Resource Management and Trajectory Optimization for UAV-Enabled Maritime Network
Authors: Yu Guanding , Ding Xin , Liu Shengli
Published: December 2022

Due to the lack of places to employ communication infrastructures, there are many coverage blind zones in maritime communication networks. Benefiting from the high flexibility and maneuverability, unmanned aerial vehicles (UAVs) have been proposed as a promising method to provide broadband maritime coverage for these blind zones. In this paper, a multi-UAV-enabled maritime communication model is proposed, where UAVs are deployed to provide the transmission service for maritime users. To improve the performance of the maritime communication systems, an optimization problem is formulated to maximize the minimum average throughput among all users by jointly optimizing the user association, power allocation, and UAV trajectory. To derive the solutions with a low computational complexity, we decompose this problem into three subproblems, namely user association optimization, power allocation optimization, and UAV trajectory optimization. Then, a joint iterative algorithm is developed to achieve the solutions based on the successive convex approximation and interior-point methods. Extensive simulation results validate the effectiveness of the proposed algorithm and demonstrate that UAVs can be used to enhance the maritime coverage.
Quantification of Error Sources with Inertial Measurement Units in Sports
Authors: Kamstra Haye , Wilmes Erik , van der Helm Frans C. T.
Published: December 2022

Background: Inertial measurement units (IMUs) offer the possibility to capture the lower body motions of players of outdoor team sports. However, various sources of error are present when using IMUs: the definition of the body frames, the soft tissue artefact (STA) and the orientation filter. Methods to minimize these errors are currently being used without knowing their exact influence on the various sources of errors. The goal of this study was to present a method to quantify each of the sources of error of an IMU separately. Methods: An optoelectronic system was used as a gold standard. Rigid marker clusters (RMCs) were designed to construct a rigid connection between the IMU and four markers. This allowed for the separate quantification of each of the sources of error. Ten subjects performed nine different football-specific movements, varying both in the type of movement, and in movement intensity. Results: The error of the definition of the body frames (11.3–18.7 deg RMSD), the STA (3.8–9.1 deg RMSD) and the error of the orientation filter (3.0–12.7 deg RMSD) were all quantified separately for each body segment. Conclusions: The error sources of IMU-based motion analysis were quantified separately. This allows future studies to quantify and optimize the effects of error reduction techniques.
Product Assembly Assistance System Based on Pick-To-Light and Computer Vision Technology
Authors: Hercog Darko , Bencak Primož , Vincetič Uroš , Lerher Tone
Published: December 2022

Product assembly is often one of the last steps in the production process. Product assembly is often carried out by workers (assemblers) rather than robots, as it is generally challenging to adapt automation to any product. When assembling complex products, it can take a long time before the assembler masters all the steps and can assemble the product independently. Training time has no added value; therefore, it should be reduced as much as possible. This paper presents a custom-developed system that enables the guided assembly of complex and diverse products using modern technologies. The system is based on pick-to-light (PTL) modules, used primarily in logistics as an additional aid in the order picking process, and Computer Vision technology. The designed system includes a personal computer (PC), several custom-developed PTL modules and a USB camera. The PC with a touchscreen visualizes the assembly process and allows the assembler to interact with the system. The developed PC application guides the operator through the assembly process by showing all the necessary assembly steps and parts. Two-step verification is used to ensure that the correct part is picked out of the bin, first by checking that the correct pushbutton on the PTL module has been pressed and second by using a camera with a Computer Vision algorithm. The paper is supported by a use case demonstrating that the proposed system reduces the assembly time of the used product. The presented solution is scalable and flexible as it can be easily adapted to show the assembly steps of another product.
Replacing Histogram with Smooth Empirical Probability Density Function Estimated by K-Moments
Authors: Koutsoyiannis Demetris
Published: December 2022

Whilst several methods exist to provide sample estimates of the probability distribution function at several points, for the probability density of continuous stochastic variables, only a gross representation through the histogram is typically used. It is shown that the newly introduced concept of knowable moments (K-moments) can provide smooth empirical representations of the distribution function, which in turn can yield point and interval estimates of the density function at a large number of points or even at any arbitrary point within the range of the available observations. The proposed framework is simple to apply and is illustrated with several applications for a variety of distribution functions.
The Interdisciplinary Approach to the Conceptualization of the Image of the Arctic and the North in the Mass Consciousness: An Example of Russian Students
Authors: Kornilova Elena Vladimirovna
Published: December 2022

The article is devoted to the integrated interdisciplinary study of multiple aspects of the conceptosphere of the Arctic and the North and its representation in the collective consciousness of Russian students. The purposes of this paper are to examine the current status of the creation of an integrated paradigm of knowledge about the Arctic in humanities and the social sciences, and to draw conclusions about the emerging trends of understanding of the cultural and symbolic constants of the Arctic area. The respondents (students of Saint Petersburg Mining University) gave 2357 responses to the stimulus “the Arctic” in the course of the free associative experiment. The obtained associates were distributed into culturally significant thematic groups. The main thesis of this study is that the meaningfulness of the image of the Arctic and the North is in many respects determined by key ideas present in the collective consciousness, and by the life priorities and orientations of today’s young people. The idea of the extreme, severe conditions, and the danger of this region of the Earth dominates in minds of Russian students. Nevertheless, this land is rich in natural resources and is a unique platform for a wide range of research. A further tendency is identified in the formation of the image of the Arctic and the North in the mass media: new trends are affected by geopolitical factors, focusing on the pivotal role of the Arctic area as a territory of national interests. The creation of a “conflict image” of the Arctic region is counterproductive. In this regard, it is necessary to put into practice the concept of Arctic solidarity, in order to promote integration processes in the exploration of the circumpolar region.
Reliability and Practical Use of a Commercial Device for Measuring Punch and Kick Impact Kinetics
Authors: Del Vecchio Luke , Whitting John , Hollier Jennifer , Keene Annabelle , Climstein Mike
Published: December 2022

Martial arts, boxing and combat sports such as mixed martial arts participation have gained popularity in recent years internationally. One common aspect to these sports is the training and skill in maximizing strike impact of punches and kicks, referred to as impact kinetics, with commercial devices now available to assess punching and kicking power in athletes training facilities and gyms. We, therefore, assessed the reliability of a commercial device, the PowerKubeTM (Strike Research Ltd., Norwich, England) via the technical error of measurement (TEM) in both linear and non-linear simulated strikes to the center of target, off-center, level and inclined in a laboratory setting. The highest mean impact power resulted from level, center strikes (5782 ± 230 W) followed by level, off-center strikes (4864 ± 119 W, p < 0.05), inclined center strikes (4500 ± 220 W, p < 0.05), and inclined, off-center strikes (3390 ± 151). Peak power reductions ranged from 15.9% (level, off-center) to a maximum of 41.4% (incline, off-center) compared to the level, center strikes. Coaches are advised to take steps such as videoing strikes with high sampling rates to better ensure consistency in impact orientation, being perpendicular and centered on the strike pad, to best capture the peak power of kicks or punches.
Decoupling Characteristics and Torque Analytical Model of Sharing-Suspension-Windings Bearingless Switched Reluctance Motor Considering Flux-Linkage Saturation
Authors: Hao Wenmei , Hao Jie , Wang Zhifu , Hao Yi
Published: December 2022

As its name indicates, the bearingless switched reluctance motor does not have windings or permanent magnets on the rotor. This has the advantages of simple structure, high reliability and easy control. The sharing-suspension-windings bearingless switched reluctance motor inherits the above characteristics, and has obvious advantages in the research field of bearingless motors with its motor structure of decoupling torque and radial force. In this paper, the sharing-suspension-windings bearingless switched reluctance motor is taken as the research object. The finite element model of the sharing-suspension-windings bearingless switched reluctance prototype is established. The electromagnetic characteristics of the prototype are analyzed. As the premise of motor suspension, the structural decoupling of torque and radial force is analyzed and experimentally verified. Then, the flux-linkage saturation of the motor is derived at the position where the stator and rotor are completely aligned and the stator and rotor are completely unaligned. The torque model of the motor is derived based on the flux-linkage saturation, and the accuracy of the model is verified by the fitting comparison between the theory and the finite element simulation. It lays a theoretical foundation for the subsequent structure optimization design research of the sharing-suspension-windings bearingless switched reluctance motor.
The Impact of Supply Chain Integration on Operational Performance: An Empirical Study
Authors: Masa’deh Ra’ed , Muheisen Ismail , Obeidat Bader , Bany Mohammad Ashraf
Published: December 2022

Manufacturing companies nowadays are under constant pressure to deliver high-quality products at the lowest possible prices within the shortest possible time even under the most unpredictable economic situations. Supply chain integration has a critical impact on operational performance. Nevertheless, this impact has not been consistent and showed mixed results throughout the literature. This study aimed to examine the impact of technology management in terms of supply chain integration on operational performance. The research model was empirically validated using 317 valid survey responses from the Jordanian food and beverage industry, which were subjected to quantitative research design and regression analysis. Results showed that supply chain integration had a direct significant impact on operational performance, and all three dimensions of the theoretical model contributed significantly to operational performance. This study suggests the critical need to create and implement proper supply chain integration strategies and technologies, both internally and externally, to enhance their performance and competitive advantage. Moreover, future research needs to extend this work to other industries, cultures, and nations, while investigating the moderating or mediating effects of other key variables along with using alternative sampling strategies.
The Impact of Ambidextrous Innovation Human Capital on the Technological Innovation Efficiency and Stage Efficiency of Big Data Enterprises
Authors: Liu Chang , Xiao Hui-Lin
Published: December 2022

Based on a resource-based view, we explore the relationship between ambidextrous innovation human capital and the efficiency of technological innovation and its stage efficiency in big data enterprises. We divide their technological innovation into two stages: technological development and the commercialization of technological achievements. For a more reasonable efficiency measurement, we construct an efficiency evaluation index system based on the entropy value method (EVM) and the analytical hierarchy process (AHP), and we measure and evaluate their technological innovation efficiency from both static and dynamic perspectives. We conduct an empirical analysis with a sample of Chinese big data listed companies from 2014–2017. After regression analysis and its robustness test, we find that ambidextrous innovation human capital has a significant impact on the technological innovation efficiency of big data enterprises, that incremental innovation human capital and radical innovation human capital have opposite impact relationships in the technological development stage and that radical innovation human capital may have a more significant economic significance on the efficiency of commercializing technological achievements of big data enterprises. In the course of our analysis, we also find some other relevant findings. Finally, we formulate some relevant management suggestions.
Sustainable Control of Galinsoga parviflora with Oxyfluorfen, Flumioxazin, and Linuron Application in Two Soils Cultivated with Garlic
Authors: Paula Dilma F. de , Silva Elisa Maria G. da , Silva Laryssa B. X. da , Lima Alessandro da C. , Billu Patrick B. , Reis Marcelo R. dos , Mendes Kassio F.
Published: December 2022

Herbicides applied in PRE-emergence enables sustainable weed control. The objective of this study was to evaluate the control of gallant soldier (Galinsoga parviflora) with the residual herbicides oxyfluorfen, flumioxazin, and linuron in soils cultivated with garlic from two regions of Brazil: Rio Paranaíba-MG (Oxisol) and Curitibanos-SC (Ultisol). The efficiency of the herbicides was evaluated at the following doses: oxyfluorfen (0, 3, 6, 12, 24, 48, 96, 192, 384, and 768 g a.i. ha−1), flumioxazin (0, 2, 4, 6, 8, 15, 30, 40, 60, and 120 g a.i. ha−1), and linuron (0, 30, 40, 50, 100, 200, 400, 800, 1600, and 2430 g a.i. ha−1). The degree of damage on the 7th, 14th, and 21st day after emergence (DAE) and dry matter on the 21st day after emergence (DAE) were determined to evaluate the control (C80) and the growth reduction (GR80) of 80% of the plant, respectively, compared to the treatment without herbicide. Three herbicides were effective at the control of G. parviflora, with the C80 at 21 DAE on Ultisol being 81.82, 4.59, and 141.26 g a.i. ha−1, and a GR80 of 61, 8.3, and 151.3 g a.i. ha−1 for oxyfluorfen, flumioxazin, and linuron, respectively. On the other hand, on Oxisol (lower clay content and soil organic matter), the doses were lower, with the C80 at 21 DAE at 20.85, 3.50, and 118 g a.i. ha−1, and a GR80 of 54, 4.03, and 101.23 g a.i. ha−1, respectively. This weed showed higher control under flumioxazin compared to the other herbicides in both soils. The use of low doses of residual herbicides contributes to sustainable weed control in garlic growing in the field.
Aerodynamic Force and Aeroelastic Response Characteristics Analyses for the Galloping of Ice-Covered Four-Split Transmission Lines in Oblique Flows
Authors: Chen Zhaoqing , Cai Weijie , Su Jin , Nan Bo , Zeng Cong , Su Ning
Published: December 2022

In order to study the galloping mechanism of ice-covered four-split transmission lines in oblique flows, the aerodynamic forces and aero-elastic response characteristics of the crescent-shaped four-split ice-covered transmission lines are investigated through wind tunnel tests on rigid and aero-elastic models. According to Den Hartog and Nigel’s galloping theories, the damping coefficients are calculated based on the experimental data. The results show that the crescent-shaped ice-covered four-split transmission lines usually suffer from torsional galloping. Furthermore, based on the aero-elastic wind tunnel data, the galloping is characterized by an elliptical trajectory, negative damping ratio, and a negative strain at hanging position. In addition, the galloping appears to be more prone to occur under oblique flows, with a larger galloping amplitude and a lower critical wind speed. This might be because an out-of-plane vibration of the third-order mode is excited at a lower wind speed, leading to a coupled resonance between in-plane and out-of-plane vibrations at the third-order mode with a frequency ratio of 1:1. The experimental results in this paper can also be used to verify the fluid-structure interaction simulation method of ice-covered transmission lines.
Influence of Mowing and Trampling on the Allelopathy and Weed Suppression Potential of Digitaria ciliaris and Cyperus microiria
Authors: Biramahire Bienvenu , Appiah Kwame Sarpong , Tojo Seishu , Fujii Yoshiharu , Chosa Tadashi
Published: December 2022

A long-term, sustainable solution to weed infestation is extremely desirable because weeds have the potential to reduce crop productivity and the aesthetic appeal of the environment. In this study, the impacts of mowing and varying degrees of trampling pressure on the suppression of weeds, alongside wound-induced changes in the allelopathic potential, of the rhizosphere soil and the root exudates of southern crabgrass (Digitaria ciliaris) and Asian flatsedge (Cyperus microiria) were evaluated under both field and greenhouse conditions. The field study results showed that all trampling treatments induced the relative suppression of weed growth. Grass weeds showed higher resistance to trampling than broad-leaved weeds. However, laboratory bioassays showed that light trampling caused a significant increase in the growth-inhibitory effects of southern crabgrass rhizosphere soil on lettuce. Moreover, mowing (9.11% of control) and trampling (16.4% of control) resulted in a marginal increase in the growth-inhibitory effects of root exudates released from southern crabgrass. Furthermore, the growth-inhibitory activities of the Asian flatsedge rhizosphere soil were significantly reduced after heavy trampling pressure. Moreover, mowing and trampling resulted in marginal reductions in the growth-inhibitory activities of root exudates released from Asian flatsedge against lettuce (i.e., 18.7% and 28.5%, respectively). In general, mowing and varying degrees of trampling induced contrasting and integrated impacts on weed suppression as well as the allelopathic potential of both southern crabgrass and Asian flatsedge.
Impact of a Food Education Session on Vegetables Plate Waste in a Portuguese School Canteen
Authors: Marques Cátia , Lima João P. M. , Fialho Sónia , Pinto Ezequiel , Baltazar Ana Lúcia
Published: December 2022

Several authors have shown that vegetables a re the most commonly wasted component in school lunches and enhance the importance of food education on topics such as food waste and vegetable consumption. The present research evaluated the efficacy of a single session of food education on vegetables waste and consumption. The data collection was focused on primary school students from a school located in Guarda district (Portugal). A vegetable selective aggregate weighing from the lunch plate was required in two distinct phases: before and after a single 30 min nutritionist’s intervention. The variables collected were the quantities of vegetables produced, leftovers and plate waste. Through these weighings, it was possible to measure the variables: distributed vegetables, consumed vegetables, vegetables waste, leftovers index, plate waste index. The use of materials such as a scale, suitable containers, gown, disposable gloves, cap and office supplies were necessary. In total during the two phases, 870 meals were evaluated. Measures of central tendency and statistical analysis tests were used. At the end of the present research, it was possible to verify significant results in the reduction of the vegetables leftovers index and in the increase in vegetable consumption per capita, through the nutritionist’s intervention. There were significant differences in the reduction of the index of vegetable leftovers and in the increase in the consumption of vegetables per capita and no significant differences in total vegetable waste. Potential causes and strategies for future research were also discussed. This study demonstrates how a nutritionist’s intervention, in a school context, could translate into behavioral change in nutrition and sustainability terms.
The Impact of Resettlement in Urban Market Redevelopment on Income Inequality, Its Determinants, and Implications for the Resettled Population: Applying the Kejetia New Market Exemplar, Ghana
Authors: Mensah Francis , Shi Guoqing , Yu Qingnian , Boadi Emmanuel Bosompem , Andam Francis Akorful , Bofah Nicholas Anarfi
Published: December 2022

Resettlement has become inevitable and necessary for urban market redevelopment to be implemented in developing countries, yet it impacts the livelihoods of the displaced population. In Ghana, studies have contributed significantly to the social processes, however, income inequality is rare. Therefore, the present study contributes to the knowledge gap by examining the impact of resettlement on income inequality in Kejetia market redevelopment in Ghana, and discusses their determinants and the implications for traders and drivers before, during, and after resettlement. Mixed methods were adopted using semi-structured interviews for field data. Theil’s T-Statistic was explored to measure inequality into three decompositions; ‘between-groups,’ ‘within-groups,’ and ‘overall’ inequalities to understand its form and trends across the three resettlement stages. The study findings showed complex inequalities in forms and trends at each stage. In addition, the findings lay bare the determinants and implications of income inequalities. Generally, the study concludes that the resettlement project not only induced unsatisfactory incomes and inequality, but equity concerns for traders’ and drivers’ groups, particularly the latter. The key implication of the research is the importance of influencing scholars and policy practitioners to give attention to the income inequality effects from resettlement in urban market redevelopment.
Type I Shapovalov Wave Spacetimes in the Brans–Dicke Scalar-Tensor Theory of Gravity
Authors: Osetrin Konstantin , Filippov Altair , Kirnos Ilya , Osetrin Evgeny
Published: December 2022

Exact solutions for Shapovalov wave spacetimes of type I in Brans–Dicke’s scalar-tensor theory of gravity are constructed. Shapovalov wave spacetimes describe gravitational wave models that allow for the the separation of wave variables in privileged coordinate systems. In contrast to general relativity, the vacuum field equations of the Brans–Dicke scalar-tensor theory of gravity lead to exact solutions for type I Shapovalov spaces, allowing for the the construction of observational tests to detect such wave disturbances. Furthermore, the equations for the trajectories of the test particles are obtained for the models considered.
Leaching Mechanism and Health Risk Assessment of As and Sb in Tailings of Typical Antimony Mines: A Case Study in Yunnan and Guizhou Province, Southwest China
Authors: Bai Ziyou , He Yinping , Han Zhiwei , Wu Fuzhong
Published: December 2022

The weathering and leaching of mining tailings have released large amounts of antimony (Sb) and arsenic (As), causing serious pollution in the surrounding soil, water, and sediments. To understand the leaching characteristics of Sb and As in mining tailings, Zuoxiguo and Qinglong mining tailings were collected for analysis. The average content of Sb in Zuoxiguo and Qinglong tailings was 5902.77 mg/kg and 1426.43 mg/kg, respectively, while that of As was 412.53 mg/kg and 405.26 mg/kg, respectively, which exceeded the local background value. Furthermore, the concentrations of Sb in the leachate of Zuoxiguo and Qinglong increased with time; the average Sb concentration in the leachate of Zuoxiguo and Qinglong was 1470.48 μg/L and 70.20 μg/L, respectively, while that of the As concentration was 31.20 μg/L and 6.45 μg/L, respectively. This suggests that the concentrations of Sb and As in the leachate of Zuoxiguo are both higher than those in the leachate of Qinglong and that the pH of the leachate of Zuoxiguo and Qinglong significantly changed within the first day under different initial pH conditions, and tended to be between 6 and 8, after one day. The results of the average health risk index showed that As in the leachate from Zuoxiguo and Qinglong for children was 5.67 × 10−4 and 9.13 × 10−5, respectively, and 4.43 × 10−4 and 7.16 × 10−5, respectively, for adults. As in the leachate from Zuoxiguo poses serious carcinogenic risks for residents, and in the study area, As poses a serious threat to human health. Therefore, the local government must manage As in these areas.
Defective Interfering Particles of Influenza Virus and Their Characteristics, Impacts, and Use in Vaccines and Antiviral Strategies: A Systematic Review
Authors: Wu Min , Zhou Entong , Sheng Rui , Fu Xiaoshu , Li Jiemin , Jiang Chunlai , Su Weiheng
Published: December 2022

Defective interfering particles (DIPs) are particles containing defective viral genomes (DVGs) generated during viral replication. DIPs have been found in various RNA viruses, especially in influenza viruses. Evidence indicates that DIPs interfere with the replication and encapsulation of wild-type viruses, namely standard viruses (STVs) that contain full-length viral genomes. DIPs may also activate the innate immune response by stimulating interferon synthesis. In this review, the underlying generation mechanisms and characteristics of influenza virus DIPs are summarized. We also discuss the potential impact of DIPs on the immunogenicity of live attenuated influenza vaccines (LAIVs) and development of influenza vaccines based on NS1 gene-defective DIPs. Finally, we review the antiviral strategies based on influenza virus DIPs that have been used against both influenza virus and SARS-CoV-2. This review provides systematic insights into the theory and application of influenza virus DIPs.
Determinants of the Level of Anti-SARS-CoV-2 IgG ANTibodiEs after Vaccination (DANTE-SIRIO 7) Study in a Large Cohort of Healthcare Workers
Authors: Krintus Magdalena , Piasecki Maciej , Lackowski Piotr , Buszko Katarzyna , Kubica Aldona , Kosobucka-Ozdoba Agata , Michalski Piotr , Pietrzykowski Lukasz , Stolarek Wioleta , Wojcik Agata , Tomczak Maria , Wojtal Emilia , Krys Jacek , Wlodarczyk Zbigniew , Kubica Jacek
Published: December 2022

The aim of this study was to determine anti-SARS-CoV-2 IgG concentrations and their major determinants in healthcare workers (HCWs) after full vaccination with the BNT162b2 vaccine. We recruited 847 individuals vaccinated with two doses of the BNT162b2 vaccine, who completed the questionnaire, and whose antibody concentrations were tested after 3 and 6 months after full vaccination. Anti-SARS-CoV-2 IgG levels were measured on the routinely employed Siemens Atellica system. The cutoff for positivity was ≥21.8 BAU/mL. Three and 6 months after vaccination, the majority of participants were seropositive. Median concentrations of anti-SARS-CoV-2 IgG significantly decreased from 1145 BAU/mL (IQR: 543–2095) to 225 BAU/mL (IQR: 100–510). Major positive determinants of antibody levels were fever after both doses of vaccine, prior-COVID-19 exposure, and muscle pain after the first dose. Lack of symptoms after the second dose and time since vaccination were significant negative determinants of anti-SARS-CoV-2 IgG concentrations. No other factors, including age and gender, or underlying comorbidities had a significant effect on antibody levels in HCWs. The anti-SARS-CoV-2 response after two doses of BNT162b2 vaccine was independently associated with prior-COVID-19 exposure, time since vaccination, and the occurrence of symptoms after either dose of vaccine. Easily reportable adverse reactions may facilitate the identification of immune response in HCWs.