bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Downhole Robot Actuator System and Mechanical Behavior Analyses of the PRSM by Considering Elastic Errors and Radial Loads
Authors: Dong Xuelian , Zhu Haiyan , Liu Qingyou , Wang Qiaozhu , Wang Xingming
Published: August 2022

This paper designs a new class of actuators for the downhole traction robot system to achieve high-accuracy transmission, which is realized by the planetary roller screw mechanism (PRSM). As the downhole environment is a non-structure one, which increases the difficulty of the load analyses and distributions of the downhole robot system to complete a predesigned mission. Traditional achievements about the mechanical behavior analyses of PRSM ignore the effects of radial loads and torque elastic deformation errors, which are inevitable for the downhole robot actuator, and the results of which would affect the load distribution and fatigue life of the PRSM-aided actuator. To assist the complex task, in this study the mechanical behavior analyses of PRSM for the downhole robot system are investigated by considering axial loads, torque elastic deformation errors, and radial loads. Moreover, the calculation models for contact load distribution and fatigue life are established by utilizing the equivalent contact load and Hertz contact theory. Two cases for the robot actuator in the downhole environment are addressed, the results of which indicate that the contact load change and decrease with the thread growth direction of the PRSM, the first several threads bore most of the loads, and the last several threads only took a few loads. Additionally, the fatigue life reduces sharply under the condition that the axial loads, radial loads, and rotation speeds increase. Compared with the other two effectors, the fatigue life is more sensitive to the radial loads. The results show the sustainability of the presented screw–roller–nut and provide a potential reference for the downhole robot actuator motion analyses.
Analyzing Decision-Making Factors of Green Design for Kid’s Toys Based on the Concept of Product Lifecycle
Authors: Tu Jui-Che , Chu Ku-Hsi , Gao Ding-Ze , Yang Chun
Published: August 2022

In promoting the SDGs (Sustainable Development Goals), increasing attention has been given to environmental pollution and abnormal climate issues. In particular, a large number of products made of plastic materials have caused harm to the environment. Secondly, with the improvement of average spending power, many parents are more willing to buy toys for their children. However, the lifespan of kid’s toys is often short, and most materials are made of plastic, which also causes issues as they are not easy to break down and are difficult to recycle. This study investigates the concept of the product life cycle in kid’s toys and explores the decision-making factors of green design. First, analysis and induction were conducted through literature collection. Through semi-structured interviews with experts, the design dimensions related to the green design of kid’s toys and the elements that affect the willingness of consumption by consumption values and behavior were obtained. After the questionnaire survey and data analysis, the design factors and purchasing decision factors of green design for the product life cycle and consumption values and behavior of kid’s toys were obtained. Finally, combined with kid’s toy design, green design, product life cycle and consumers’ consumption values and behavior, the decision-making factors for the green design of kid’s toys were extracted, which included (1) using non-toxic materials; (2) designing for maintainability and disassembly of the toy; (3) refining the toys to be artistic and collectable; (4) upgrading the educational functions of toys; (5) improving the recycling of toys; (6) emphasizing green packing; (7) creating a green brand and increasing product visibility; and (8) advocating the value of green design for toys. In addition to supplying green design considerations for kid’s toys to designers and companies, the results can also be used as an important reference with regard to the research topics of product life cycle, toy design and development for the sustainable designs of products.
Plum Pox Virus Genome-Based Vector Enables the Expression of Different Heterologous Polypeptides in Nicotiana benthamiana Plants
Authors: Achs Adam , Glasa Miroslav , Šubr Zdeno
Published: August 2022

Plant viral vectors have become a promising tool for the rapid and cost-effective production of recombinant proteins in plants. Among the numerous genera of viruses that have been used for heterologous expression, potyviruses offer several advantages, such as polyprotein expression strategy or a broad host range. In our work, the expression vectors pAD/pAD-agro based on the plum pox virus (PPV) genome were used for the heterologous expression of different foreign polypeptides: alfalfa mosaic virus capsid protein (AMV CP), zucchini yellow mosaic virus capsid protein (ZYMV CP), the small heat-shock protein of Cronobacter sakazakii fused with hexahistidine (sHSP-his), a fragment of influenza A virus hemagglutinin (HA2-2), influenza A virus protein PB1-F2, SARS-CoV-2 nucleocapsid protein (CoN2-his), and its N- and C-terminal fragments (CoN-1-his and CoN3-his, respectively), each fused with a hexahistidine anchor. Particular proteins differed in their accumulation, tissue localization, stability, and solubility. The accumulation rate of produced polypeptides varied from low (N, hemagglutinin fragment) to relatively high (plant viral CPs, N-terminal fragment of N, PB1-F2). Some proteins preferentially accumulated in roots (sHSP, hemagglutinin fragment, PB1-F2), showing signs of proteolytic degradation in leaf tissues. Thus, each expression requires an individual approach and optimization. Here, we summarize our several-year experiments and discuss the usefulness of the pAD/pADep vector system.
Analysis of CBCT Bone Density Using the Hounsfield Scale
Authors: Morar Leonard , Băciuț Grigore , Băciuț Mihaela , Bran Simion , Colosi Horațiu , Manea Avram , Almășan Oana , Dinu Cristian
Published: August 2022

Assessing bone density in prospective dental implant sites is crucial both for choosing the implant type and for planning a drilling procedure that will ensure the implant’s primary stability and osseointegration. This study aimed to investigate possible differences between the bone densities of various edentulous sites in the maxilla and mandible. The study was conducted on a group of forty partly edentulous patients who underwent radiological examination by scanning the areas of interest using cone beam computed tomography (CBCT). Hounsfield units (HU) were analyzed using dedicated software. Higher HU were observed at the site of mandibular central incisors compared to the site of maxillary central incisors. The HU values in the mandibular first molars region were higher than those of the maxillary first molars. Buccal vs. lingual or palatal cortical HU values did not differ significantly. Within the limitations of this study, it can be stated that an objective assessment of site-specific bone density before the installation of dental implants may provide valuable clinical information for the selection of implant size and the planning of a patient-specific drilling protocol.
Anxiety, Depression and Post-Traumatic Stress Disorder in Physicians Compared to Nurses during the COVID-19 Pandemic: An Observational, Cross Sectional, Multicentric Study
Authors: Lupo Roberto , Botti Stefano , Rizzo Alessandra , Lezzi Alessia , Calabrò Antonino , Conte Luana , Petrelli Cosimo , Longo Cosimo , Vitale Elsa
Published: August 2022

(1) Background: The coronavirus pandemic has highlighted the precarious health situation of our country, thanks to the grueling workloads caused by understaffing and fear of contracting COVID-19. By considering this critical situation, frontline healthcare professionals who have been directly involved in the diagnosis, treatment, and care of SARS-CoV-2 patients are now at risk of developing psychological distress and other mental health symptoms, accomplices of the fear of contracting the COVID-19 and the exhausting workloads. (2) Methods: An observational, cross-sectional, multicenter study was conducted by administering an online questionnaire to all Italian physicians and nurses who worked during the COVID-19 pandemic. The questionnaire consists of socio-demographic characteristics, an assessment of anxiety levels with the State-Trait Anxiety Inventory (STAI), which also assessed trait and state anxiety, the Beck Depression Inventory (BDI) to evaluate the condition of depressive severity, and, finally, the Impact of Event Scale–Revised (IES–R), which was administered in order to quantify the post-traumatic stress disorder (PTSD) among the participants. (3) Results: A total of 770 Italian healthcare workers were enrolled in this study. Of these, 95 (12.30%) were physicians and 675 (87.70%) were nurses. By considering PTSD, anxiety, and depression levels between the physicians and nurses recruited, a significant difference was reported in the STAI-1 assessment, as both physicians and nurses reported slight and moderate levels (p = 0.033). (4) Conclusions: Physicians and nurses, who have been subjected to physical impoverishment, with the infinite physical forces spent to support the pace of work at the limits of the possible, but above all mental capacity, with the anxiety of having to face an unknown enemy, such as COVID-19. This has resulted in a significant increase in anxiety, depression, post-traumatic symptoms, and sleep disturbances, with possible repercussions not only on the quality of life of the physicians and nurses but also on the quality of assistance provided.
A Single-Case Series Trial of Emotion-Regulation and Relationship Safety Intervention for Youth Affected by Sexual Exploitation
Authors: Laird Jessica J. , Klettke Bianca , Mattingley Sophie , Hallford David J. , Hall Kate
Published: August 2022

Child sexual exploitation (CSE) is a significant global problem. Interventions implemented with youth affected by CSE frequently target singular adjacent issues (e.g., substance misuse or running away); however, research indicates these interventions are most efficacious when they simultaneously treat CSE sequelae (e.g., emotion dysregulation) paired with relationship skill-building; yet few such interventions exist. Furthermore, the evidence-based reports on CSE research currently lacks rigorous research methods, such as the use of validated measures and the provision of robust outcome data. The current study aimed to implement a combined emotion regulation and safe-relationships intervention (ERIC + YR: emotion regulation, impulse control and ‘your relationships’) in a community service providing outreach for young women affected by CSE. A randomised single-case series design was used to test the effects of ERIC + YR on emotion regulation strategies, psychological wellbeing, relationship safety knowledge and behaviours, across repeated measurements for young women affected by CSE (N = 2; Mage = 18.00). Phase A consisted of baseline measures for two to three weeks. Phase B consisted of 8-sessions of ERIC + YR delivered across three to six weeks by practitioners who had undertaken ERIC + YR training. Data collection included pre/post intervention measures as well as a daily questionnaire delivered via a smartphone application. While results showed clinically significant and reliable improvements in psychological wellbeing, no other outcome measures showed change between pre and post-intervention. The current study contributes to the evidence-base as an initial step in illuminating how an empirically driven intervention can be delivered as an adjunctive treatment for youth affected by CSE. Implications inform the current evidence-base, with future directions for intervention research discussed.
Spatial Planning of the Coastal Marine Socioecological System—Case Study: Punta Carnero, Ecuador
Authors: Escandón-Panchana Jenny , Elao Vallejo Rafael , Escandón-Panchana Paulo , Velastegui-Montoya Andrés , Herrera-Franco Gricelda
Published: August 2022

Marine-coastal ecosystems are productive and valuable habitats worldwide due to their significant contributions to human wellbeing. However, human activities, limited territorial planning, and unsustainable demand and consumption of natural goods and services put pressure on marine-coastal ecosystems. In this sense, marine-coastal planning is a management tool to contrast these forces because it manages different human activities on the coast and in the oceans over space and time, strengthening political, social, and tourist development and the economy of the territory. Our objective is to propose marine-coastal spatial planning strategies through an ecosystem-based approach for allocating a mangrove and estuarine zone conservation area. The study methodology is: (i) Compilation of information from the study area with an emphasis on regulations and protected areas. (ii) Analysis of human relations with marine-coastal ecosystems. (iii) Mapping and zoning of the conservation area. (iv) Analysis of the strengths, weaknesses, opportunities, threats and threats, weaknesses, opportunities, strengths (SWOT–TWOS) matrix to recommend strategies and guarantee the viability of marine-coastal protection. The results show zoning maps of the sector proposed as a conservation area comprising mangroves and an estuarine zone. It also approaches governance strategies or conservation management measures and protection of the marine-coastal space. Finally, as a recommendation, we propose improvements to the current municipal ordinances, guaranteeing the management and protection of the study area, and furthering achievements in the comprehensive development of land-use planning.
Availability of Automatic Identification System (AIS) Based on Spectral Analysis of Mean Time to Repair (MTTR) Determined from Dynamic Data Age
Authors: Jaskólski Krzysztof
Published: August 2022

Good marine practice and proper operation of navigation, radio navigation, and radio communication systems are nowadays of key importance for marine navigation safety. This applies to merchant vessels and navy ships and effectively monitoring unmanned vehicles along a set route. Technological progress has contributed to developing equipment for ships and unmanned vehicles, which are fitted out with devices of the automatic identification system (AIS). One of the issues in AIS operation is limited-service availability, which manifests itself in the presence of incomplete data for the navigation parameters sent by radio, compressed in dynamic data messages. This results in the unusability of the system information for ships equipped with an AIS transponder. This paper aims to develop an AIS service availability model based on the mean time of incomplete navigation parameter occurrence in AIS data messages and to present the test results in the time and frequency domain using a mathematical method—Fast Fourier Transform. The study results refer to five basic navigation parameters and are indicative of a high service availability index—over 0.99 for three out of the five navigation parameters tested. Data recorded by a ship’s system receiver were the key source of practical knowledge concerning the limitations of AIS service availability. The experiment revealed interruptions in regular data inflow from navigation devices. In effect, a description was provided of a functional relationship based on a spectral analysis of the frequencies of the times occurring between service repair (time to repair—TTR), and the use of the model to analyze other variables was proposed.
MS-IAF: Multi-Scale Information Augmentation Framework for Aircraft Detection
Authors: Zhao Yuliang , Li Jian , Li Weishi , Shan Peng , Wang Xiaoai , Li Lianjiang , Fu Qiang
Published: August 2022

Aircrafts have been an important object of study in the field of multi-scale image object detection due to their important strategic role. However, the multi-scale detection of aircrafts and their key parts from remote sensing images can be a challenge, as images often present complex backgrounds and obscured conditions. Most of today’s multi-scale datasets consist of independent objects and lack mixed annotations of aircrafts and their key parts. In this paper, we contribute a multi-scale aircraft dataset (AP-DATA) consisting of 7000 aircraft images that were taken in complex environments and obscured conditions. Our dataset includes mixed annotations of aircrafts and their key parts. We also present a multi-scale information augmentation framework (MS-IAF) to recognize multi-scale aircrafts and their key parts accurately. First, we propose a new deep convolutional module ResNeSt-D as the backbone, which stacks scattered attention in a multi-path manner and makes the receptive field more suitable for the object. Then, based on the combination of Faster R-CNN with ResNeSt-D, we propose a multi-scale feature fusion module called BFPCAR. BFPCAR overcomes the attention imbalance problem of the non-adjacent layers of the FPN module by reducing the loss of information between different layers and including more semantic features during information fusion. Based on AP-DATA, a dataset with three types of features, the average precision (AP) of MS-IAF reached 0.884, i.e., 2.67% higher than that of the original Faster R-CNN. The APs of these two modules were improved by 2.32% and 1.39%, respectively. The robustness of our proposed model was validated using the open sourced RSOD remote sensing image dataset, and the best accuracy was achieved.
Validation and Analysis of MISR and POLDER Aerosol Products over China
Authors: Jiao Sunxin , Li Mingyang , Fan Meng , Li Zhongbin , Xu Benben , Tao Jinhua , Chen Liangfu
Published: August 2022

Multi-angle polarization measurement is an important technical means of satellite remote sensing applied to aerosol monitoring. By adding angle information and polarization measurements, aerosol optical and microphysical properties can be more comprehensively and accurately retrieved. The accuracy of aerosol retrieval can reflect the advantages and specific accuracy improvement of multi-angle polarization. In this study, the Multi-angle Imaging SpectroRadiometer (MISR) V23 aerosol products and the Polarization and Directionality of the Earth’s Reflectance (POLDER) GRASP “high-precision” archive were evaluated with the Aerosol Robotic Network (AERONET) observations over China. Validation of aerosol optical depth (AOD), absorbing aerosol optical depth (AAOD), and the Ångström exponent (AE) properties was conducted. Our results show that the AOD inversion accuracy of POLDER-3/GRASP is higher with the correlation coefficient (R) of 0.902, slope of 0.896, root mean square error (RMSE) of 0.264, mean absolute error (MAE) of 0.190, and about 40.71% of retrievals within the expected error (EE, ± 0.05+0.2×AODAERONET) lines. For AAOD, the performance of two products is poor, with better results for POLDER-3/GRASP data. POLDER-3/GRASP AE also has higher R of 0.661 compared with that of MISR AE (0.334). According to the validation results, spatiotemporal distribution, and comparison with other traditional scalar satellite data, the performance of multi-angle polarization observations is better and is suitable for the retrieval of aerosol properties.
Flood Inflow Estimation in an Ungauged Simple Serial Cascade of Reservoir System Using Sentinel-2 Multi-Spectral Imageries: A Case Study of Imjin River, South Korea
Authors: Kim Jin Gyeom , Kang Boosik , Kim Sungmo
Published: August 2022

The Imjin River is a representative transboundary river in the Korean Peninsula, originating from North Korea and flowing into South Korea. Upstream of Imjin River, on the North Korean side, is the Hwanggang Dam, with a 350 million m3 of storage capacity, which is in operation for power generation and water supply. The sharing of the operation information of Hwanggang Dam has been limited due to political and military tension. South Korea has constructed the Gunnam Flood Control Reservoir downstream of the Imjin River to prevent potential flood damage due to the urgent and unilateral release from the Hwanggang Dam. However, it is difficult to manage the flood of the Imjin River basin under the situation of limited shared real-time information on the Hwanggang Dam operation. In this study, a hydrological analysis system was established to estimate the inflow and release of the Hwanggang Dam by building a lumped hydrological model and an Auto ROM (Reservoir Operation Method)-based reservoir operation algorithm. To estimate the inflow of the Gunnam Flood Control Reservoir, the water level of the Hwanggang Dam was calculated using the Sentinel-2 multi-spectral images, and the hydrological analysis system was calibrated. The evaluation index of the water level of the ungauged Hwanggang Dam derived from January 2017 to August 2020 using the hydrological analysis system was shown to have a coefficient of determination of 0.76 and an RMSE of 3.97 m. In the case of the flood event in August 2020, the coefficient of determination of the flood inflow in the Gunnam Flood Control Zone was calculated to be 0.86.
Satellite Imagery-Based Identification of High-Risk Areas of Schistosome Intermediate Snail Hosts Spread after Flood
Authors: Qiu Juan , Han Dongfeng , Li Rendong , Xiao Ying , Zhu Hong , Xia Jing , Jiang Jie , Han Yifei , Shao Qihui , Yan Yi , Li Xiaodong
Published: August 2022

Snail intermediate host monitoring and control are essential for interrupting the parasitic disease schistosomiasis. Identifying large-scale high-risk areas of snail spread after floods has been greatly facilitated by remote sensing imagery. However, previous studies have usually assumed that all inundation areas carry snails and may have overestimated snail spread areas. Furthermore, these studies only used a single environmental factor to estimate the snail survival risk probability, failing to analyze multiple variables, to accurately distinguish the snail survival risk in the snail spread areas. This paper proposes a systematic framework for early monitoring of snail diffusion to accurately map snail spread areas from remote sensing imagery and enhance snail survival risk probability estimation based on the snail spread map. In particular, the flooded areas are extracted using the Sentinel-1 Dual-Polarized Water Index based on synthetic aperture radar images to map all-weather flooding areas. These flood maps are used to extract snail spread areas, based on the assumption that only inundation areas that spatially interacted with (i.e., are close to) the previous snail distribution regions before flooding are identified as snail spread areas, in order to reduce the misclassification in snail spread area identification. A multiple logistic regression model is built to analyze how various types of snail-related environmental factors, including the normalized difference vegetation index (NDVI), wetness, river and channel density, and landscape fractal dimension impact snail survival, and estimate its risk probabilities in snail spread area. An experiment was conducted in Jianghan Plain, China, where snails are predominantly linearly distributed along the tributaries and water channels of the middle and lower reaches of the Yangtze River. The proposed method could accurately map floods under clouds, and a total area of 231.5 km2 was identified as the snail spread area. The snail survival risk probabilities were thus estimated. The proposed method showed a more refined snail spread area and a more reliable degree of snail survival risk compared with those of previous studies. Thus, it is an efficient way to accurately map all-weather snail spread and survival risk probabilities, which is helpful for schistosomiasis interruption.
Interpretable Passive Multi-Modal Sensor Fusion for Human Identification and Activity Recognition
Authors: Yuan Liangqi , Andrews Jack , Mu Huaizheng , Vakil Asad , Ewing Robert , Blasch Erik , Li Jia
Published: August 2022

Human monitoring applications in indoor environments depend on accurate human identification and activity recognition (HIAR). Single modality sensor systems have shown to be accurate for HIAR, but there are some shortcomings to these systems, such as privacy, intrusion, and costs. To combat these shortcomings for a long-term monitoring solution, an interpretable, passive, multi-modal, sensor fusion system PRF-PIR is proposed in this work. PRF-PIR is composed of one software-defined radio (SDR) device and one novel passive infrared (PIR) sensor system. A recurrent neural network (RNN) is built as the HIAR model for this proposed solution to handle the temporal dependence of passive information captured by both modalities. We validate our proposed PRF-PIR system for a potential human monitoring system through the data collection of eleven activities from twelve human subjects in an academic office environment. From our data collection, the efficacy of the sensor fusion system is proven via an accuracy of 0.9866 for human identification and an accuracy of 0.9623 for activity recognition. The results of the system are supported with explainable artificial intelligence (XAI) methodologies to serve as a validation for sensor fusion over the deployment of single sensor solutions. PRF-PIR provides a passive, non-intrusive, and highly accurate system that allows for robustness in uncertain, highly similar, and complex at-home activities performed by a variety of human subjects.
A Compact Four-Port MIMO Antenna for UWB Applications
Authors: Wu Aiting , Zhao Mingyang , Zhang Pengquan , Zhang Zhonghai
Published: August 2022

A compact four-port multiple-input multiple-output (MIMO) antenna for ultrawideband (UWB) applications is presented in this paper. The proposed antenna has four unit cell antennas. Each unit cell is placed orthogonal to its adjacent elements. The radiation element of each unit cell is composed of a cut semicircular patch and a stepped microstrip feed line. The whole ground on the back side consists of four parts of defective ground and their extended branches, which are connected through a “卍” structure. The main decoupling technology used in the MIMO antenna is polarization diversity. In addition, protruded ground and parasitic elements are added to achieve a higher isolation. This compact antenna has a small area of 45 mm × 45 mm and is printed on a single layer substrate (FR4) with an εr = 4.4 and a thickness of 1.6 mm. This antenna has an impedance bandwidth (S11 < −10 dB) of 3.1–13.1 GHz (123%) and an isolation of less than −17 dB. The envelope correction coefficient (ECC) is less than 0.02 and the average gain is 4 dBi. The ultrawide bandwidth and compact size of the proposed antenna make it a promising candidate for UWB applications.
Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain
Authors: Hakim Mohammed , Omran Abdoulhadi A. Borhana , Inayat-Hussain Jawaid I. , Ahmed Ali Najah , Abdellatef Hamdan , Abdellatif Abdallah , Gheni Hassan Muwafaq
Published: August 2022

The massive environmental noise interference and insufficient effective sample degradation data of the intelligent fault diagnosis performance methods pose an extremely concerning issue. Realising the challenge of developing a facile and straightforward model that resolves these problems, this study proposed the One-Dimensional Convolutional Neural Network (1D-CNN) based on frequency-domain signal processing. The Fast Fourier Transform (FFT) analysis is initially utilised to transform the signals from the time domain to the frequency domain; the data was represented using a phasor notation, which separates magnitude and phase and then fed to the 1D-CNN. Subsequently, the model is trained with White Gaussian Noise (WGN) to improve its robustness and resilience to noise. Based on the findings, the proposed model successfully achieved 100% classification accuracy from clean signals and simultaneously achieved considerable robustness to noise and exceptional domain adaptation ability. The diagnosis accuracy retained up to 97.37%, which was higher than the accuracy of the CNN without training under noisy conditions at only 43.75%. Furthermore, the model achieved an accuracy of up to 98.1% under different working conditions, which was superior to other reported models. In addition, the proposed model outperformed the state-of-art methods as the Signal-to-Noise Ratio (SNR) was lowered to −10 dB achieving 97.37% accuracy. In short, the proposed 1D-CNN model is a promising effective rolling bearing fault diagnosis.
Indoor Visual-Based Localization System for Multi-Rotor UAVs
Authors: Bertoni Massimiliano , Michieletto Stefano , Oboe Roberto , Michieletto Giulia
Published: August 2022

Industry 4.0, smart homes, and the Internet of Things are boosting the employment of autonomous aerial vehicles in indoor environments, where localization is still challenging, especially in the case of close and cluttered areas. In this paper, we propose a Visual Inertial Odometry localization method based on fiducial markers. Our approach enables multi-rotor aerial vehicle navigation in indoor environments and tackles the most challenging aspects of image-based indoor localization. In particular, we focus on a proper and continuous pose estimation, working from take-off to landing, at several different flying altitudes. With this aim, we designed a map of fiducial markers that produces results that are both dense and heterogeneous. Narrowly placed tags lead to minimal information loss during rapid aerial movements while four different classes of marker size provide consistency when the camera zooms in or out according to the vehicle distance from the ground. We have validated our approach by comparing the output of the localization algorithm with the ground-truth information collected through an optoelectronic motion capture system, using two different platforms in different flying conditions. The results show that error mean and standard deviation can remain constantly lower than 0.11 m, so not degrading when the aerial vehicle increases its altitude and, therefore, strongly improving similar state-of-the-art solutions.
Design Validation of a Low-Cost EMG Sensor Compared to a Commercial-Based System for Measuring Muscle Activity and Fatigue
Authors: Bawa Anthony , Banitsas Konstantinos
Published: August 2022

Electromyography (EMG) sensors have been used for measuring muscle signals and for diagnosing neuromuscular disease. Available commercial EMG sensor are expensive and not easily available for individuals. The aim of the study is to validate our designed low-cost sensor against a well-known commercial system for measuring muscle activity and fatigue assessment. The evaluation of the designed system was done through a series of dynamic exercises performed by volunteers. Our low-cost EMG sensor and the commercially available system were placed on the vastus lateralis muscle to concurrently record the signal in a maximum voluntary contraction (MVC). The signal analysis was done using two validation indicators: Spearman’s correlation, and intra-class cross correlation on SPSS 26.0 version. For the muscle fatigue assessment, the root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) indicators were used. The results at the peak and mean level muscle contraction intensity were computed. The relative agreement for the two systems was excellent at peak level muscle contraction range (ICC 0.74–0.92), average 0.83 and mean level muscle contraction intensity range (ICC 0.65–0.85) with an average of 0.74. The Spearman’s correlation average was 0.76 with the range of (0.71–0.85) at peak level contraction, whiles the mean level contraction average was 0.71 at a range of (0.62–0.81). In determining muscle fatigue, the RMS and MAV showed increasing values in the time domain, while the MEF decreased in the frequency domain. Overall, the results indicated a good to excellent agreement of the two systems and confirmed the reliability of our design. The low-cost sensor also proved to be suitable for muscle fatigue assessment. Our designed system can therefore be implemented for rehabilitation, sports science, and ergonomics.
Injuries and Fatalities Related to Skid Steers: 2015–2020
Authors: Gorucu Serap , Weichelt Bryan , Burke Richard
Published: August 2022

Skid steers are versatile self-propelled machines that are regularly used in a variety of recreational applications and occupational industries. They can be hazardous for both operators and bystanders. The purpose of this paper is to describe patterns of skid steer injuries in the US from 2015 to 2020. Data were obtained from Occupational Safety and Health Administration (OSHA) accident reports and the severe injury database. Agriculture-related incidents were obtained from AgInjuryNews. The study identified 312 skid steer-related injuries (2015–2020) in OSHA, with an additional 68 agricultural injuries identified using AIN. Construction, administrative and waste management, and agriculture industries were the top three industries with the highest number of injuries. Bystander workers experienced a higher number of injuries than operators. Contact with the machine was the most prevalent and more fatal than the other injury events. Agricultural skid steer injuries involved a broad age range of victims, from very young children to adults. These findings emphasize the need for improved safety engineering and clear safety guidelines for skid steer operators and those who are around skid steers. With the increased prevalence of skid steers across industries, it is imperative to have cohesive and comprehensive safety regulations, guidelines, and policy enforcement.
The Consequences of Gender Inequality on Latin America’s Economic Growth: Macroeconomic Evidence
Authors: Koengkan Matheus , Fuinhas José Alberto , Belucio Matheus , Kazemzadeh Emad , Poveda Yormy Eliana Melo , Alavijeh Nooshin Karimi , Santiago Renato
Published: August 2022

This research analysed the effect of gender inequality on the economic growth of seventeen countries in the Latin America and Caribbean (LAC) region from 1990 to 2016 using an ordinary least squares (OLS) regression model with fixed effects and a quantiles via moments model. Electricity consumption from new renewable energy sources, general government capital stock, private capital stock, trade openness, and urban population were used as control variables, and a battery of preliminary and post-estimation tests were conducted to guarantee the adequacy and suitability of both methodologies. The OLS model with fixed effects supports that gender inequality negatively affects gross domestic product (GDP) per capita. The quantiles via moments (QvM) model confirms the results of the OLS model with fixed effects and reveals that with increasing quantiles (25th, 50th, and 75th), gender inequality leads to decreases in LAC countries’ growth. LAC countries’ policymakers and institutions should improve gender equality to reach a higher development level and a more prosperous society. Developing policies that contribute to increasing women’s participation in the labour market, reducing the gender pay gap, supporting women’s education and training, constructing a more women-friendly and less patriarchal society, and developing measures to limit violence against women and early pregnancy and maternal mortality rates and increase women’s decision-making positions, particularly in public policy decision making, must be implemented.
Informal Learning with a Gender Perspective Transmitted by Influencers through Content on YouTube and Instagram in Spain
Authors: Arias-Rodriguez Alicia , Sánchez-Bello Ana
Published: August 2022

The struggle for gender equality is based on identifying, understanding, and eradicating the causes of inequality. Digital media are and have always been governed by men and, as a consequence, have become another instrument of patriarchy. This article analyses the content created on YouTube and Instagram by four of the most popular influencers in Spain in order to examine the presence of stereotypes and gender roles, the use of sexist or inclusive language, and the influencers’ level of social engagement on issues related to gender equality. A content analysis approach using ATLAS.ti 8 software was chosen, as this method provides information about the sender of the message as the well the message itself and its impact. The findings of the analysis show that influencers transmit sexist roles and stereotypes, use non-inclusive language, and exhibit no social engagement on questions of gender inequality. The study concludes by highlighting the importance of cyberfeminism as a way of promoting gender equality online.
Expectations of Cross-Sector Collaboration in Cultural and Arts Education
Authors: Arnold Marie-Therese , Le Thi Huyen Trang , Kolleck Nina
Published: August 2022

The promotion of dialogues between youth and older adults in the field of cultural education remains one of the most important educational policy tasks in Germany. After all, intergenerational, cultural projects can make an important contribution to reducing ageism, promoting personal development, and dealing with social challenges. Close collaboration between actors from different sectors (school, cultural associations, administration, etc.) is needed to secure such programmes. However, this presupposes that the expectations that the involved actors have regarding the collaboration are transparently examined, discussed and adjusted within the collaborative network in advance. Therefore, the aim is to identify initial indications of different expectations of collaboration between actors from various sectors. In order to answer the research question, 24 semi-structured interviews were conducted in combination with ego-centred network maps in six German municipalities with actors from different fields (schools, administration, cultural associations, etc.). The data were then interpreted using qualitative content analysis. Our results show that actors participate with expectations ranging from different degrees of closeness and distance to the other involved actors. These results allow the first systematisation of individual expectations of actors at the beginning of a collaboration.
Anthropomorphism as a Differentiation Strategy for Standardized Reusable Glass Containers
Authors: Garaus Marion , Garaus Christian , Wolfsteiner Elisabeth , Jermendy Charlotte
Published: August 2022

The steadily increasing amount of waste requires new strategies for package waste reduction. One strategy is to switch from single-use plastic packaging to glass packaging; however, this strategy is only beneficial from an environmental perspective when complemented with a multi-use deposit refund system with standardized glass containers. This implies the loss of package shape as a differentiation criterion, which has been considered a highly relevant marketing instrument in the fast-moving consumer goods markets. Against this background, the current research investigates in an online experiment the suitability of anthropomorphized label designs on prompting purchase intentions in the context of reusable glass jars. The study further investigates the mediating roles of brand attitude and brand interest. Contrary to the postulated hypotheses, anthropomorphized labels negatively impact brand attitude, and the sequential mediation of anthropomorphism on brand interest and brand attitude on purchase intention was significant. Our findings reveal that anthropomorphized labels stimulate brand interest, which in turn positively affects purchase intention. The results emphasize the relevance of brand interest in package design and guides manufacturers, brand managers, and policymakers to effective differentiation strategies for standardized multi-use packages.
Digital Transformation, Ambidextrous Innovation and Enterprise Value: Empirical Analysis Based on Listed Chinese Manufacturing Companies
Authors: Ma Hedan , Jia Xinliang , Wang Xin
Published: August 2022

Text analysis was used in this study to construct the index of digital transformation degree in manufacturing enterprises. On this basis, an empirical test was conducted on the relationship between digital transformation, ambidextrous innovation, and enterprise value. The results show that: digital transformation has a significant positive impact on the enterprise value of manufacturing enterprises. Digital transformation can promote the rise of enterprise value through technological innovation, business model innovation, and their combination, where ambidextrous innovation plays a mediating role. For manufacturing enterprises, the impact of digital transformation on enterprise value has a single-threshold effect and a double-threshold effect, respectively, with technological innovation and business model innovation being the threshold variables. The synergy of technological innovation and business model innovation plays a stronger mediating role compared with a single innovation model. The conclusions of this study have certain theoretical and practical significance for systematically revealing the intermediate mechanism of digital transformation affecting enterprise value and then promoting manufacturing enterprises to make remarkable accomplishments in digital transformation.
Explaining the Differences between the Environmental Impacts of 44 French Artisanal Cheeses
Authors: Cortesi Adeline , Dijoux Laure , Yannou-Le Bris Gwenola , Pénicaud Caroline
Published: August 2022

Cheese production causes significant environmental impacts, which have to be reduced. In France, a lot of different cheeses are available, made from different milks but also from different cheese technologies. The goal of this study was to understand the origin of the environmental impact variation between cheeses made from different technologies and milks and produced using different ripening practices. To do so, the environmental impacts of 44 different types of French artisanal cheese, all produced under protected designation of origin (PDO) labels, were assessed using the life cycle assessment. Cheese technologies were fully described and two ripening scenarios were investigated. Results show that the differences of environmental impacts between cheeses mainly come from: the milk type (cow, goat, or sheep), the milk amount needed to produce one kilogram of cheese, the energetic performance of the ripening room, and the ripening time. Such results could be useful to cheesemakers to identify the origin of the environmental impacts of their products and to implement effective actions to reduce them. According to the results, innovations leading to the reduction in electrical consumption during ripening are interesting to explore in order to increase the environmental performance of a cheese.
Leveraging Blockchain and Smart Contract Technologies to Overcome Circular Economy Implementation Challenges
Authors: Kumar Nallapaneni Manoj , Chopra Shauhrat S.
Published: August 2022

Adopting a circular economy (CE) has rapidly emerged among policymakers and business community stakeholders to promote material circularization and ensure sustainable development. While the inclination for a paradigm shift away from the linear economy is evident, many challenges have been quoted in the literature regarding its implementation. Lately, it has become common to propose Information and Communication Technologies (ICT)-based approaches to address these challenges. However, they do not question the practicality of the solutions in the context of CE. This paper aims to find an appropriate digital solution for CE implementation, which is not possible without a complete understanding of the existing challenges. A thorough literature review broadly classified the challenges under five barrier categories: Technological, Financial, Infrastructural, Institutional, and Societal, which was followed up with an investigation into the failure of ICT solutions to address CE challenges. Among the various technologies, blockchain and smart contract technologies show some promise as data-driven decision-making tools; however, they are not without their limitations when applied in the context of CE. This perspective explores the role of blockchain smart contract technology-scape in overcoming CE challenges and presents a circular economy blockchain (CEB) architecture development. The findings suggest that CEB may enable CE business models that improve trust and transparency in supply-chain networks, shared and performance economy platforms, stakeholder participation, and governance and management of organizations. Ultimately, this study highlights critical areas for research and development for the blockchainification of CE.
Towards Crowdfunding Performance through Crowdfunding Digital Platforms: Investigation of Social Capital and Innovation Performance in Emerging Economies
Authors: Yousaf Zahid , Shakaki Obaddah , Isac Nicoleta , Cretu Alina , Hrebenciuc Andrei
Published: August 2022

The current study aims to explore how different owners and investors use digitalcrowdfunding platforms for advertisement and selection of different projects. This connection enhances the number of effective projects and attracts the attention of various entrepreneurs for investment. This research examines the direct impact of the crowdfunding digital-platform on crowdfunding performance as well as the role of the social capital as a mediating variable and innovative performance as a moderating variable. A quantitative approach was used for data collection and analysis. The findings show that digitalcrowdfunding platforms can be predicted through crowdfunding performance. The outcomes show that innovative performance strengthens the relationship between crowdfunding digitalplatforms and crowdfunding performance. This research reveals how fundraisers can improve crowdfunding performance through crowdfunding digitalplatforms, social capital, and innovative performance. Social capital plays a critical role in the enhancement of crowdfunding performance.
Governmental Anti-Pandemic and Subsidy Strategies for Blockchain-Enabled Food Supply Chains in the Post-Pandemic Era
Authors: Liao Changhua , Lu Qihui , Shui Ying
Published: August 2022

Aiming to explore whether governments should choose anti-pandemic or subsidy strategies in the post-pandemic era, this study constructed a three-level food supply chain that was composed of a leading third-party logistics provider, a supplier and a retailer, in which the third-party logistics provider used blockchain technology for food traceability to address consumer concerns about food safety. We then used game theory to analyze the pricing decisions, traceability levels, anti-pandemic effort levels and subsidy levels of the supply chain under different governmental anti-pandemic or subsidy strategies. Our results showed that in all scenarios, the higher the consumer preference for traceability information, the larger the traceability levels and anti-pandemic effort levels and the more favorable the outcome for all parties; thus, governments should improve consumer awareness of pandemic prevention. For the benefit of all parties, governments should adopt anti-pandemic and subsidy strategies simultaneously, even in the post-pandemic era. Interestingly, for the scenario in which governments could only adopt one strategy, when the cost coefficient of traceability was small, the governmental subsidies would actually lead to lower traceability levels of the 3PL. This study could provide decision-making references for governments during the post-pandemic era and a new possibility for blockchain application.
Metamaterials and Symmetry
Authors: Lim Teik-Cheng
Published: August 2022

How are metamaterials related to symmetry [...]
Relation-Theoretic Coincidence and Common Fixed Point Results in Extended Rectangular b-Metric Spaces with Applications
Authors: Sun Yan , Liu Xiaolan
Published: August 2022

The objective of this paper is to obtain new relation-theoretic coincidence and common fixed point results for some mappings F and g via hybrid contractions and auxiliary functions in extended rectangular b-metric spaces, which improve the existing results and give some relevant results. Finally, some nontrivial examples and applications to justify the main results.