bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved Carrier-Smoothing Code Algorithm for BDS Satellites with SICB
Authors: Zhang Qichao , Ma Xiaping , Gao Yuting , Huang Gongwen , Zhao Qingzhi
Published: November 2023

Carrier Smoothing Code (CSC), as a low-pass filter, has been widely used in GNSS positioning processing to reduce pseudorange noise via carrier phases. However, current CSC methods do not consider the systematic bias between the code and carrier phase observation, also known as Satellite-induced Code Bias (SICB). SICB has been identified in the BDS-2 and the bias will reduce the accuracy or reliability of the CSC. To confront bias, an improved CSC algorithm is proposed by considering SICB for GEO, IGSO, and MEO satellites in BDS constellations. The correction model of SICB for IGSO/MEO satellites is established by using a 0.1-degree interval piecewise weighted least squares Third-order Curve Fitting Method (TOCFM). The Variational Mode Decomposition combined with Wavelet Transform (VMD-WT) is proposed to establish the correction model of SICB for the GEO satellite. To verify the proposed method, the SICB model was established by collecting 30 Multi-GNSS Experiment (MGEX) BDS stations in different seasons of a year, in which the BDS data of ALIC, KRGG, KOUR, GCGO, GAMG, and SGOC stations were selected for 11 consecutive days to verify the effectiveness of the algorithm. The results show that there is obvious SICB in the BDS-2 Multipath (MP) combination, but the SICB in the BDS-3 MP is smaller and can be ignored. Compared with the modeling in the references, TOCFM is more suitable for IGSO/MEO SICB modeling, especially for the SICB correction at low elevation angles. After the VMD-WT correction, the Root Mean Square Error (RMSE) of SICB of B1I, B2I, and B3I in GEO satellites is reduced by 53.35%, 63.50%, and 64.71% respectively. Moreover, we carried out ionosphere-free Single Point Positioning (IF SPP), Ionosphere-free CSC SPP (IF CSC SPP), CSC single point positioning with the IGSO/MEO SICB Correction based on the TOCFA Method (IGSO/MEO SICB CSC), and CSC single point positioning with the IGSO/MEO/GEO SICB correction based on VMD-WT and TOCFA (IGSO/MEO/GEO SICB CSC), respectively. Compared to IF SPP, the average improvement of the IGSO/MEO/GEO SICB CSC algorithm in the north, east, and up directions was 24.42%, 27.94%, and 24.98%, respectively, and the average reduction in 3D RMSE is 24.54%. Compared with IF CSC SPP, the average improvement of IGSO/MEO/GEO SICB CSC is 7.03%, 6.50%, and 10.48% in the north, east, and up directions, respectively, while the average reduction in 3D RMSE was 9.86%. IGSO/MEO SICB mainly improves the U direction positioning accuracy, and GEO SICB mainly improves the E and U direction positioning accuracy. After the IGSO/MEO/GEO SICB correction, the overall improvement was about 10% and positioning improved to a certain extent.
A Comprehensive Assessment of Multiple High-Resolution Precipitation Grid Products for Monitoring Heavy Rainfall during the “7.20” Extreme Rainstorm Event in China
Authors: Pang Zihao , Zhang Yu , Shi Chunxiang , Gu Junxia , Yang Qingjun , Pan Yang , Wang Zheng , Xu Bin
Published: November 2023

Precipitation products play an important role in monitoring rainstorm processes. This study takes a rare historical event of extreme, heavy precipitation that occurred in Henan Province, China, in July 2021 as a research case. By analyzing the distribution of the spatial and temporal characteristics of precipitation errors, using a probability density function of the occurrence of precipitation and the daily variation pattern, we assess the capability of a radar precipitation estimation product (RADAR), satellite precipitation products (IMERG and GSMAP), a reanalysis product (ERA5) and a precipitation fusion product (the CMPAS) to monitor an extreme rainstorm in the Henan region. The CMPAS has the best fit with the gauge observations in terms of the precipitation area, precipitation maximum and the evolution of the whole process, with a low spatial variability of errors. However, the CMPAS slightly underestimated the precipitation extremum at the peak moment (06:00–08:00). The RADAR product was prone to a spurious overestimation of the originally small rainfall, especially during peak precipitation times, with deviations concentrated in the core precipitation area. The IMERG, GSMAP and ERA5 products have similar performances, all of which failed to effectively capture heavy precipitation in excess of 60 mm/h, with negative deviations in precipitation at mountainfront locations west of northern Henan Province. There is still a need for terrain-specific error revisions for areas with large topographic relief. By merging and processing precipitation data from multiple sources, the accuracy of the CMPAS is better than any single-source precipitation product. The CMPAS has the characteristic advantage of high spatial and temporal resolutions (0.01° × 0.01°/1 h), which play a positive role in precipitation dynamic monitoring, providing early warnings of heavy rainfall processes and hydrological application research.
Data-Driven Landslide Spatial Prediction and Deformation Monitoring: A Case Study of Shiyan City, China
Authors: Sheng Yifan , Xu Guangli , Jin Bijing , Zhou Chao , Li Yuanyao , Chen Weitao
Published: November 2023

Landslide susceptibility mapping (LSM) is significant for landslide risk assessment. However, there remains no consensus on which method is optimal for LSM. This study implements a dynamic approach to landslide hazard mapping by integrating spatio-temporal probability analysis with time-varying ground deformation velocity derived from the MT-InSAR (Multi-Temporal InSAR) method. Reliable landslide susceptibility maps (LSMs) can inform landslide risk managers and government officials. First, sixteen factors were selected to construct a causal factor system for LSM. Next, Pearson correlation analysis, multicollinearity analysis, information gain ratio, and GeoDetector methods were applied to remove the least important factors of STI, plan curvature, TRI, and slope length. Subsequently, information quantity (IQ), logistic regression (LR), frequency ratio (FR), artificial neural network (ANN), random forest (RF), support vector machine (SVM), and convolutional neural network (CNN) methods were performed to construct the LSM. The results showed that the distance to a river, slope angle, distance from structure, and engineering geological rock group were the main factors controlling landslide development. A comprehensive set of statistical indicators was employed to evaluate these methods’ effectiveness; sensitivity, F1-measure, and AUC (area under the curve) were calculated and subsequently compared to assess the performance of the methods. Machine learning methods’ training and prediction accuracy were higher than those of statistical methods. The AUC values of the IQ, FR, LR, BP-ANN, RBF-ANN, RF, SVM, and CNN methods were 0.810, 0.854, 0.828, 0.895, 0.916, 0.932, 0.948, and 0.957, respectively. Although the performance order varied for other statistical indicators, overall, the CNN method was the best, while the BP-ANN and RBF-ANN method was the worst among the five examined machine methods. Hence, adopting the CNN approach in this study can enhance LSM accuracy, catering to the needs of planners and government agencies responsible for managing landslide-prone areas and preventing landslide-induced disasters.
Quantification of Vegetation Phenological Disturbance Characteristics in Open-Pit Coal Mines of Arid and Semi-Arid Regions Using Harmonized Landsat 8 and Sentinel-2
Authors: Wang Bing , Li Peixian , Zhu Xiaoya
Published: November 2023

Open-pit mining activities inevitably affect the surrounding ecological environment. Therefore, it is crucial to clarify the disturbance characteristics of open-pit mining activities on the surrounding vegetation and scientifically implement ecological restoration projects. This study investigates the impact of open-pit coal mining in arid and semi-arid regions on surrounding vegetation from a vegetation phenology perspective. Initially, we construct a high-frequency time series of vegetation indices by Harmonized Landsat 8 and Sentinel-2 surface reflectance dataset (HLS). These time series are then fitted using the Double Logistic and Asymmetric Gaussian methods. Subsequently, we quantify three pivotal phenological phases: Start of Season (SOS), End of Season (EOS), and Length of Season (LOS) from the fitted time series. Finally, utilizing mine boundaries as spatial units, we create a buffer zone of 100 m increments to statistically analyze changes in phenological phases. The results reveal an exponential variation in vegetation phenological metrics with increasing distance from the mining areas of Heidaigou-Haerwusu (HDG-HEWS), Mengxiang (MX), and Xingda (XD) in northwest China. Then, we propose a method to identify the disturbance range. HDG-HEWS, MX, and XD mining areas exhibit disturbance ranges of 1485.39 m, 1571.47 m, and 671.92 m for SOS, and 816.72 m, 824.73 m, and 468.92 m for EOS, respectively. Mineral dust is one of the primary factors for the difference in the disturbance range. The HDG-HEWS mining area exhibits the most significant disruption to vegetation phenological metrics, resulting in a delay of 6.4 ± 3.4 days in SOS, an advancement of 4.3 ± 3.9 days in the EOS, and a shortening of 6.7 ± 3.5 days in the LOS. Furthermore, the overlapping disturbance zones of the two mining areas exacerbate the impact on phenological metrics, with disturbance intensities for SOS, EOS, and LOS being 1.38, 1.20, and 1.33 times those caused by a single mining area. These research results are expected to provide a reference for the formulation of dust suppression measures and ecological restoration plans for open-pit mining areas.
Rumen Content from Slaughterhouse as an Alternative Inoculum Source for In Vitro Analysis of Feeds: A Multivariate Approach
Authors: Alba Henry Daniel Ruiz , Lima Victor Guimarães Oliveira , Carvalho Silvana Teixeira , Ítavo Luis Carlos Vinhas , Pinto Luis Fernando Batista , Carneiro Paulo Luiz Souza , Oliveira Ronaldo Lopes
Published: November 2023

The objective of the current study was to compare the rumen inoculum of slaughtered cattle with the ruminal inoculum of cannulated cattle; additionally, determine its reliability in the in vitro analysis of ruminant feeds throughout a multivariate approach. Five male bovines (weight 320 ± 9.4 kg; mean ± standard deviation) provided with ruminal cannula and between five and seven bovines slaughtered in slaughterhouse were used. The evaluations were carried out following a completely randomized design. The data obtained were subjected to different multivariate analyzes to determine the reliability of the ruminal inoculum of animals slaughtered in commercial slaughterhouses compared to that obtained from cannulated animals. The relative contribution indicated that the in vitro dry matter digestibility (IVDMD, 50.75%) and in vitro neutral detergent fiber digestibility (IVNDFD, 29.83%) analysis influence 80.13% of the results to determine the reliability of the ruminal inoculum from slaughtered cattle. Furthermore, it was determined that the first two principal components (IVNDFD and acetic acid production) are the ones that influence the results by 89.87%. The grouping of diets using the Tocher optimization method and the dendrogram shows the formation of six groups and two groups, respectively. The grouping shows that the ruminal inoculum source was not the limiting parameter in the evaluation. Rumen inoculum from cattle slaughtered in a commercial slaughterhouse (with unknown diet) has potential as an alternative for the in vitro analysis of cattle feed, provided that the lignin concentration in the diet is less than 35.5 g/kg DM.
Analysis of the Impact of Atmospheric Models on the Orbit Prediction of Space Debris
Authors: Ding Yigao , Li Zhenwei , Liu Chengzhi , Kang Zhe , Sun Mingguo , Sun Jiannan , Chen Long
Published: November 2023

Atmospheric drag is an important influencing factor in precise orbit determination and the prediction of low-orbit space debris. It has received widespread attention. Currently, calculating atmospheric drag mainly relies on different atmospheric density models. This experiment was designed to explore the impact of different atmospheric density models on the orbit prediction of space debris. In the experiment, satellite laser ranging data published by the ILRS (International Laser Ranging Service) were used as the basis for the precise orbit determination for space debris. The prediction error of space debris orbits at different orbital heights using different atmospheric density models was used as a criterion to evaluate the impact of atmospheric density models on the determination of space-target orbits. Eight atmospheric density models, DTM78, DTM94, DTM2000, J71, RJ71, JB2006, MSIS86, and NRLMSISE00, were compared in the experiment. The experimental results indicated that the DTM2000 atmospheric density model is best for determining and predicting the orbits of LEO (low-Earth-orbit) targets.
Human Posture Estimation: A Systematic Review on Force-Based Methods—Analyzing the Differences in Required Expertise and Result Benefits for Their Utilization
Authors: Helmstetter Sebastian , Matthiesen Sven
Published: November 2023

Force-based human posture estimation (FPE) provides a valuable alternative when camera-based human motion capturing is impractical. It offers new opportunities for sensor integration in smart products for patient monitoring, ergonomic optimization and sports science. Due to the interdisciplinary research on the topic, an overview of existing methods and the required expertise for their utilization is lacking. This paper presents a systematic review by the PRISMA 2020 review process. In total, 82 studies are selected (59 machine learning (ML)-based and 23 digital human model (DHM)-based posture estimation methods). The ML-based methods use input data from hardware sensors—mostly pressure mapping sensors—and trained ML models for estimating human posture. The ML-based human posture estimation algorithms mostly reach an accuracy above 90%. DHMs, which represent the structure and kinematics of the human body, adjust posture to minimize physical stress. The required expert knowledge for the utilization of these methods and their resulting benefits are analyzed and discussed. DHM-based methods have shown their general applicability without the need for application-specific training but require expertise in human physiology. ML-based methods can be used with less domain-specific expertise, but an application-specific training of these models is necessary.
Human Respiration Rate Measurement with High-Speed Digital Fringe Projection Technique
Authors: Lorenz Anna Lena , Zhang Song
Published: November 2023

This paper proposes a non-contact continuous respiration monitoring method based on Fringe Projection Profilometry (FPP). This method aims to overcome the limitations of traditional intrusive techniques by providing continuous monitoring without interfering with normal breathing. The FPP sensor captures three-dimensional (3D) respiratory motion from the chest wall and abdomen, and the analysis algorithms extract respiratory parameters. The system achieved a high Signal-to-Noise Ratio (SNR) of 37 dB with an ideal sinusoidal respiration signal. Experimental results demonstrated that a mean correlation of 0.95 and a mean Root-Mean-Square Error (RMSE) of 0.11 breaths per minute (bpm) were achieved when comparing to a reference signal obtained from a spirometer.
Long-Range Network of Air Quality Index Sensors in an Urban Area
Authors: Dobra Ionut-Marian , Dobra Vladut-Alexandru , Dobra Adina-Alexandra , Harja Gabriel , Folea Silviu , Gavra Vlad-Dacian
Published: November 2023

In recent times the escalating pollution within densely populated metropolitan areas has emerged as a significant and pressing concern. Authorities are actively grappling with the challenge of devising solutions to promote a cleaner and more environmentally friendly urban landscapes. This paper outlines the potential of establishing a LoRa node network within a densely populated urban environment. Each LoRa node in this network is equipped with an air quality measurement sensor. This interconnected system efficiently transmits all the analyzed data to a gateway, which subsequently sends it to a server or database in real time. These data are then harnessed to create a pollution map for the corresponding area, providing users with the opportunity to assess local pollution levels and their recent variations. Furthermore, this information proves valuable when determining the optimal route between two points in the city, enabling users to select the path with the lowest pollution levels, thus enhancing the overall quality of the urban environment. This advantage contributes to alleviating congestion and reducing excessive pollution often concentrated behind buildings or on adjacent streets.
Smartphone Photogrammetric Assessment for Head Measurements
Authors: Quispe-Enriquez Omar C. , Valero-Lanzuela Juan José , Lerma José Luis
Published: November 2023

The assessment of cranial deformation is relevant in the field of medicine dealing with infants, especially in paediatric neurosurgery and paediatrics. To address this demand, the smartphone-based solution PhotoMeDAS has been developed, harnessing mobile devices to create three-dimensional (3D) models of infants’ heads and, from them, automatic cranial deformation reports. Therefore, it is crucial to examine the accuracy achievable with different mobile devices under similar conditions so prospective users can consider this aspect when using the smartphone-based solution. This study compares the linear accuracy obtained from three smartphone models (Samsung Galaxy S22 Ultra, S22, and S22+). Twelve measurements are taken with each mobile device using a coded cap on a head mannequin. For processing, three different bundle adjustment implementations are tested with and without self-calibration. After photogrammetric processing, the 3D coordinates are obtained. A comparison is made among spatially distributed distances across the head with PhotoMeDAS vs. ground truth established with a Creaform ACADEMIA 50 while-light 3D scanner. With a homogeneous scale factor for all the smartphones, the results showed that the average accuracy for the S22 smartphone is −1.15 ± 0.53 mm, for the S22+, 0.95 ± 0.40 mm, and for the S22 Ultra, −1.8 ± 0.45 mm. Worth noticing is that a substantial improvement is achieved regardless of whether the scale factor is introduced per device.
Minimum Detection Concentration of Hydrogen in Air Depending on Substrate Type and Design of the 3ω Sensor
Authors: Oh Dong-Wook , Kang Kwangu , Lee Jung-Hee
Published: November 2023

Hydrogen has emerged as a promising carbon-neutral fuel source, spurring research and development efforts to facilitate its widespread adoption. However, the safe handling of hydrogen requires precise leak detection sensors due to its low activation energy and explosive potential. Various detection methods exist, with thermal conductivity measurement being a prominent technique for quantifying hydrogen concentrations. However, challenges remain in achieving high measurement sensitivity at low hydrogen concentrations below 1% for thermal-conductivity-based hydrogen sensors. Recent research explores the 3ω method’s application for measuring hydrogen concentrations in ambient air, offering high spatial and temporal resolutions. This study aims to enhance hydrogen leak detection sensitivity using the 3ω method by conducting thermal analyses on sensor design variables. Factors including substrate material, type, and sensor geometry significantly impact the measurement sensitivity. Comparative evaluations consider the minimum detectable hydrogen concentration while accounting for the uncertainty of the 3ω signal. The proposed suspended-type 3ω sensor is capable of detecting hydrogen leaks in ambient air and provides real-time measurements that are ideal for monitoring hydrogen diffusion. This research serves to bridge the gap between precision and real-time monitoring of hydrogen leak detection, promising significant advancements in the related safety applications.
Integral Imaging Display System Based on Human Visual Distance Perception Model
Authors: Deng Lijin , Li Zhihong , Gu Yuejianan , Wang Qi
Published: November 2023

In an integral imaging (II) display system, the self-adjustment ability of the human eye can result in blurry observations when viewing 3D targets outside the focal plane within a specific range. This can impact the overall imaging quality of the II system. This research examines the visual characteristics of the human eye and analyzes the path of light from a point source to the eye in the process of capturing and reconstructing the light field. Then, an overall depth of field (DOF) model of II is derived based on the human visual system (HVS). On this basis, an II system based on the human visual distance (HVD) perception model is proposed, and an interactive II display system is constructed. The experimental results confirm the effectiveness of the proposed method. The display system improves the viewing distance range, enhances spatial resolution and provides better stereoscopic display effects. When comparing our method with three other methods, it is clear that our approach produces better results in optical experiments and objective evaluations: the cumulative probability of blur detection (CPBD) value is 38.73%, the structural similarity index (SSIM) value is 86.56%, and the peak signal-to-noise ratio (PSNR) value is 31.12. These values align with subjective evaluations based on the characteristics of the human visual system.
Reinforcement Learning Algorithms for Autonomous Mission Accomplishment by Unmanned Aerial Vehicles: A Comparative View with DQN, SARSA and A2C
Authors: Jiménez Gonzalo Aguilar , de la Escalera Hueso Arturo , Gómez-Silva Maria J.
Published: November 2023

Unmanned aerial vehicles (UAV) can be controlled in diverse ways. One of the most common is through artificial intelligence (AI), which comprises different methods, such as reinforcement learning (RL). The article aims to provide a comparison of three RL algorithms—DQN as the benchmark, SARSA as a same-family algorithm, and A2C as a different-structure one—to address the problem of a UAV navigating from departure point A to endpoint B while avoiding obstacles and, simultaneously, using the least possible time and flying the shortest distance. Under fixed premises, this investigation provides the results of the performances obtained for this activity. A neighborhood environment was selected because it is likely one of the most common areas of use for commercial drones. Taking DQN as the benchmark and not having previous knowledge of the behavior of SARSA or A2C in the employed environment, the comparison outcomes showed that DQN was the only one achieving the target. At the same time, SARSA and A2C did not. However, a deeper analysis of the results led to the conclusion that a fine-tuning of A2C could overcome the performance of DQN under certain conditions, demonstrating a greater speed at maximum finding with a more straightforward structure.
Livelihood Changes, Spatial Anticontagion Policy Effects, and Structural Resilience of National Food Systems in a Sub-Saharan African Country Context: A Panel Machine Learning Approach
Authors: Frimpong Stephen , Frimpong Harriet , Owusu Alex Barimah , Boateng Isaac Duah , Adjei Benjamin
Published: November 2023

The livelihood changes due to the COVID-19 policies in low-income and transitional economies serve as a lever for gauging the structural resilience of national food systems. Yet, few studies have addressed the cascading effects of the pandemic policies on the livelihood changes of farming system actors or modeled and provided coherent hypotheses about the transitory structural shifts at the micro-level. Other studies on the subject have either captured the early impacts of the pandemic on food systems with limited or no insight into the sub-Saharan African context or have used macro-level data, due to sparsely available micro-level data. These early insights are relevant for the design of early warning systems. However, an ongoing and deeper insight into the effects of pandemic policies is critical, since new and more comprehensive policies are needed to address the economic fallout and the extenuating effects of COVID-19 on food supply chain disruptions. The overriding questions are as follows: what are the effects of the pandemic policies on the livelihoods of food system actors and are there spatial-economic variations in the effects of the pandemic policies on the livelihoods of the farming system actors? Using 2019 and 2020 primary data from 836 farming system actors in Ghana, we offer fresh insights into the transitory micro-level livelihood changes caused by the COVID-19 anticontagion policies. We analyzed the data using the generalized additive, subset regression, classical linear, and logistic regression models in a machine learning framework. We show that the changes in the livelihood outcomes of the food system actors in Ghana coincide with the nature of pandemic mitigation policies adopted in the spatial units. We found that the lockdown policies had a negative and significant effect on the livelihoods of the farming system actors in the lockdown areas. The policies also negatively affected the livelihoods of the farming system actors in distant communities that shared no direct boundary with the lockdown areas. On the contrary, the lockdown policies positively affected the livelihoods of the farming system actors in the directly contiguous communities to the lockdown areas. We also document the shifts in the livelihood outcomes of the farming system actors, such as income, employment, food demand, and food security in the different spatial policy areas.
The Impact of E-Learning Technologies on Entrepreneurial and Sustainability Performance
Authors: Liu Sichu , Sun Hongyi , Zhuang Jiahao , Xiong Rui
Published: November 2023

After the pandemic, education will not go back to a 100% offline mode since the application of e-learning technologies (ELTs) cannot be avoided. Therefore, their impact should be studied for future education development. Most future entrepreneurs are attending school today. Therefore, universities need to supply necessary education to encourage students to cope with future conditions and development. At the same time, due to the increasing attention being paid to the harmony between ecology and prosperity, the sustainability aspect of entrepreneurship education needs to be emphasized as well. This study investigates the impact of ELTs on entrepreneurial education performance (including personal skills, product skills, and business skills), sustainability efficacy, and their impact on sustainability awareness. Data were collected from a master’s degree class on entrepreneurship at a Hong Kong university and SmartPLS was used to analyze the data. It was found that ELTs have a significant relationship with entrepreneurial performance and sustainability efficacy. Meanwhile, sustainability efficacy also has a significant relationship with sustainability awareness. However, no significant relationship between entrepreneurial skills and sustainability awareness was identified. The results indicate that ELTs can improve students’ entrepreneurial skills and sustainability awareness, which proves the effectiveness of ELTs and provides support for their application in future entrepreneurship education.
Synthesis and Characterization of Na3SbS4 Solid Electrolytes via Mechanochemical and Sintered Solid-State Reactions: A Comparative Study
Authors: Thairiyarayar Celastin Bebina , Huang Chia-Hung , Gandomi Yasser Ashraf , Hsieh Chien-Te , Liu Wei-Ren
Published: November 2023

A sulfide-based solid electrolyte is an enticing non-organic solid-state electrolyte developed under ambient conditions. Na3SbS4, a profoundly enduring substance capable of withstanding exceedingly elevated temperatures and pressures, emerges as a focal point. Within this investigation, we employ dual distinct techniques to fabricate Na3SbS4, encompassing ball milling and the combination of ball milling with sintering procedures. A remarkable ionic conductivity of 3.1 × 10−4 S/cm at room temperature (RT), coupled with a meager activation energy of 0.21 eV, is achieved through a bifurcated process, which is attributed to the presence of tetragonal Na3SbS4 (t-NSS). Furthermore, we delve into the electrochemical performance and cyclic longevity of the Na2/3Fe1/2Mn1/2O2|t-NSS|Na system within ambient environs. It reveals 160 mAh/g initial charge and 106 mAh/g discharge capacities at 0.01 A/g current density. Furthermore, a cycle life test conducted at 0.01 A/g over 30 cycles demonstrates stable and reliable performance. The capacity retention further highlights its enduring energy storage capabilities. This study underscores the sustainable potential of Na3SbS4 as a solid-state electrolyte for advanced energy storage systems.
A Numerical Method for Evaluating the Collapse of High-Steep Scarp Slopes Based on the Bonded Block Model–Discrete Fracture Network Model
Authors: Sun Zening , Qiu Shili , Yan Siquan , Wang Zaiquan
Published: November 2023

Geotechnical engineering works in deep-incised valleys or open-pit mining areas often encounter high-steep scarp slopes with a slope angle greater than 75°. This type of slope directly threatens the safety of construction personnel, so assessing their stability is essential to ensure construction safety. The natural geometry of high-steep scarp slopes possesses complexity in terms of geometric morphology, structural features of rock mass, and occurrence mechanisms of collapse. There is little research and less emphasis on the evaluation of the collapse risk of high-steep scarp slopes. In particular, the fracture of intact rock or rock bridges is generally ignored in the analysis of collapse processes. A bonded block model (BBM)–discrete fracture network (DFN) coupling characterization model for the high-steep scarp slope is proposed based on a high-steep scarp slope containing dominant joint sets on the left bank of the dam site of the Huangzangsi Water Conservancy Project (Qinghai Province, China). By using the model, the complex geometric forms of the surface of the high-steep scarp slope are quantified, and the fracture process of falling rock masses as well as the controlling effect of dominant joints on the collapse of the scarp slope are revealed. A strength reduction method based on the BBM–DFN model is constructed, and the safety factor of the collapse-prone scarp slope is evaluated. The research results show that (1) the BBM–DFN model can be used to describe the local collapse process; (2) the occurrence of dominant joints plays an important part in controlling the collapse process; (3) there are differences in the safety factor of the scarp slope with different coupling methods; the collapse and failure modes also differ. For safety considerations, the safety factor of the scarp slope on the left bank of the dam site area is determined to be 1.85. The research findings can be used to guide the safety assessment of high-steep scarp slopes and the formulation of both collapse risk prevention and control measures to ensure construction safety in high-steep scarp slope areas.
Sustainable Aspects of Startups among Generation Z—Motivations and Uncertainties among Students in Higher Educations
Authors: Papp-Váry Árpád , Pacsi Diána , Szabó Zoltán
Published: November 2023

While technology is developing rapidly, natural resources are being exploited with more and more factories. Global environmental problems draw attention to the issue of sustainability as a warning sign. In this situation, encouraging the development of green innovative technologies and supporting green startups has become particularly important. Sustainable development is an important goal for every country, and it means a global competitive advantage if the given country supports the spread of green technologies. It is therefore the responsibility of leading politicians to create an enabling economic environment to encourage young people to become conscious, green-minded entrepreneurs. In this study, we delve into the driving factors compelling young individuals to venture into entrepreneurship. This exploration combines both quantitative and qualitative research methods. A cohort of 280 Hungarian university students participated in an online questionnaire survey as part of the quantitative segment, while the qualitative research component involved scrutinizing young people’s perspectives on enterprises and startups through focus group discussions. The research aims to unveil the motivations and primary concerns of Z-generation university students when contemplating entrepreneurship, as well as their perspectives on the significance of sustainability in this context. The outcomes of this study could serve as a catalyst for the establishment of more environmentally-conscious and sustainable businesses and startups.
Responses of a Modular Floating Wind TLP of MarsVAWT Supporting a 10 MW Vertical Axis Wind Turbine
Authors: Boo Sung Youn , Shelley Steffen Allan , Griffith D. Todd , Escalera Mendoza Alejandra S.
Published: November 2023

Offshore floating wind foundations supporting a large wind turbine require a large yard facility or significant facility upgrades for their fabrication. To overcome the cost increase associated with facility upgrades, an innovative lightweight modular floating foundation is developed. The foundation comprises multiple modules to enable their assembly on water, offering many benefits and expanding fabrication options for a reduction in the overall cost of the platform. In this paper, the foundation modules and their assembly are briefly described, and an analysis of the platform’s dynamic responses is presented. The modular foundation includes a modular and lightweight tension leg platform (TLP) called “MarsVAWT” which supports a Darrieus 10 MW vertical axis wind turbine (VAWT). The platform is moored with highly pretensioned wire rope tendons. The responses of the platform are analyzed in the time domain in a semi-coupled manner under the turbine operating and parked conditions for an offshore site in the US Northeast. The tower base shear forces and bending moments increase considerably with the combination of wind and waves, compared to those with wind only. The tendon tensions on the weatherside in the operating condition at high wind speeds are comparable to the values of the 50-year extreme (parked). The tendon tension increases are highly correlated to the platform pitch, as well as the horizontal and vertical velocities and vertical acceleration at the tendon porch. The modular platform performances and tendon designs are confirmed to comply with industry standards and practices.
Perspectivas filosóficas en la educación del siglo XXI
Authors: Magallanes Payan José Arturo
Published: November 2023

El propósito del presente trabajo es identificar y describir las influencias discursivo-hegemónicas en el fenómeno educativo contemporáneo, sus sincronías y disonancias. Para el análisis se parte  de las perspectivas del ejercicio de la filosofía que ofrecen varios autores, principalmente la que expone Alain Badiou de sutura filosófica, esto para sintetizar las imbricaciones entre ciencia y política y mostrar cómo constituyen su organización de subjetividades y prácticas al interior del proceso de enseñanza-aprendizaje. Se exponen esas imbricaciones y cómo se articulan los conceptos (competencias, eficacia, éxito), suturas (tecnocracia pospolítica) y tendencias (paradigma sociotécnico y cultura digital) como una manera de explicar y describir como influyen en la lógica educativa actual. Finalmente, se enmarca una posible tendencia que el análisis de estos elementos ofreció, una pedagogía instruccionista en la cual la operatividad exitosa de la información es el factor determinante.
Marketing Strategy for Cibaduyut UKM Craftsmen Shoes During the Covid-19 Pandemic
Authors: Muttaqin Rizqi , Saputera Denny , Dewi Rina Ariyanthi , Moenardy Dwi Fauziansyah , Santoso* Rizal Budi , Alam Gilang Nur
Published: November 2023

This article aims to explain the marketing strategy for MSME shoemakers in the Cibaduyut area during the Covid-19 pandemic. The purpose of this study was to determine the effect of the Covid-19 pandemic on MSMEs shoe craftsmen in the Cibaduyut area and the efforts of these MSMEs in utilizing digital platforms to maintain their business during the Covid-19 pandemic. The research method uses qualitative methods through interviews and observation as well as literature and data reduction. This research shows the challenges faced by MSMEs in utilizing digital platforms and provides recommendations for improving marketing strategies so that MSMEs can utilize digital platforms more effectively.

Keywords: Cibaduyut; Mix Marketing; MSME; Shoesmakers; Marketing Strategy
Enhancing Employee Performance: Rewards, Training, and Work Ethics at the Education Office of the Bangka Belitung Islands Province
Authors: Yahya Yanda , Hamsani Hamsani , Reniati* Reniati
Published: November 2023

This research was motivated by the existing condition where employees have not been able to work optimally in a government institution. The study aims to analyze and examine the influence of rewards, training, and work ethic on Employee Performance in the Education Authority of Bangka Belitung Island Province. This research is descriptive in nature. The quantitative research method was employed because the data obtained are numerical and derived from questionnaires, with a total sample size of 64 respondents, determined through a saturated sample method. The analytical model used was multiple linear regression, with t-tests, f-tests, and coefficients of determination. The research results indicate that rewards, training, and work ethic, individually, have a positive and significant impact on the performance of employees in the Education Authority of Bangka Belitung Island Province. Through this research, institutions can review the factors leading to low employee performance in the variables of rewards, training, and work ethic.

Keywords: Reward; Training; Work Ethic; Employee Performance; Education Office
IMPLEMENTASI ALGORITMA APRIORI UNTUK MENENTUKAN PRODUK TERLARIS PADA TOKO I_DOCRAFT
Authors: Anton Anton - , Naufal Naufal
Published: November 2023

The sales of pajama products on i_docraft have not yet leveraged data mining algorithms to analyze transactional data for optimizing sales. To avoid underperforming pajama models and determine which pajama models sell well, the utilization of the Apriori algorithm is necessary. The Apriori algorithm can discern these patterns based on transactional data. This study conducts a transactional data analysis using data mining with the Apriori algorithm. By employing this algorithm, the most frequently sold pajama products can be identified, allowing for prioritization of these models and the development of marketing strategies for other types of pajamas based on a comparison of their strengths and commonly high sales figures. The processed data yields associations rules for concurrently sold pajama items. Based on the results of the final association rules meeting both predetermined minimum support and confidence criteria, for instance, if a product with item code 7 (Cherrypie Nightdress) is purchased, then a product with item code 17 (3 in 1 Lotso Set) will likely be bought with a support value of 22.58% and a confidence value of 100%.
The Development of Thinking Skills in English as a Second Language Methodology Classroom
Authors: Gembaruk Alla
Published: November 2023

This article focuses on an important aspect of modern education – the development of thinking skills. The purpose of this article is to outline the way thinking skills are developed in English as a Second Language (ESL) Methodology. The research was undertaken at Pavlo Tychyna Uman State Pedagogical University.
The methodology is based on a review of academic literature, analyses of core Curriculum and ESL Methodology course books, and a generalization of our own ESL Methodology teaching experience.
Results. The notion of thinking skills is revealed and their role for language learning is emphasized in the article. It is concluded that the development of thinking skills greatly depends on the quality of instruction, hence the requirement to enhance the ability of preservice teachers to develop thinking skills in their learners. To understand students’ readiness to develop thinking skills in their learners the PRESETT Curriculum on Methodology (Bachelor’s Level) and ESL Methodology coursebooks were thoroughly studied in terms of the aspects relevant to this research. The general overview of the core Curriculum in terms of the suggested modules, units and learning outcomes proved that the development of higher-order thinking skills is one of its main objectives.
According to the core Curriculum thinking skills are developed through a range of teaching approaches, among them task-based learning, the use of case studies, simulations, group projects and problem solving. Such modes of teaching and learning promote high level interaction as well as the high level of thinking skills development. The analysis of the ESL Methodology coursebooks provides much more detailed overview of the activities practiced during the sessions, thus giving additional support for the research. It is proposed that competencies can be improved by means of HOT skills activities in the ESL Methodology classes.
Conclusions. The research findings have enriched our understanding of thinking skills and highlighted the importance of their development in preservice teachers so that they are able to develop thinking skills in their future leaners. Taken together, the research results suggest that both thinking skills and life skills, such as communication, teamwork, critical thinking, problem-solving, information literacy, creativity, etc., are focused on in both the PRESETT Curriculum on Methodology and in the ESL Methodology coursebooks.
Cell Acquisition Method Validation by Flow Cytometry for MCTI CIMATEC HDT RNA Vaccine Immunogenicity Evaluation Against SARS-CoV-2
Authors: Elen Azevedo da Costa  , Carlos Augusto Oliveira Júnior  , Alana Costa de Oliveira  , Emanuelle de Souza Santos  , Milena Botelho Pereira Soares  , Bruna Aparecida Souza Machado
Published: November 2023

The COVID-19 pandemic highlighted the importance of developing and improving techniques that can help diagnose and evaluate the disease’s immunological response. Standardizing methods is necessary to ensure the confidence and reproducibility of the results. Therefore, the objective of this work was to carry out a concurrent validation to compare the reference methods for acquiring data used in the evaluation of the immunogenicity of the Vaccine. RNA MCTI CIMATEC HDT, performed by flow cytometry. From the analysis of the cellular profile through the evaluation of cell size and complexity and expression of immunophenotypic markers, no significant differences were found, demonstrating that the methodology used in the BD FacsMelody cytometer at SENAI/CIMATEC is suitable for obtaining the results.
Se c’è il perito, ci deve essere anche la perita (e sono entrambi vivi e vegeti…)!
Authors: D'Achille Paolo , Thornton Anna M.
Published: November 2023

Una lettrice ci chiede se è corretto che il “titolo abilitativo” di perito industriale sia declinato al femminile come perita industriale. Un altro lettore vorrebbe conoscere l’etimologia della parola.
MITOS DANAU NIBUNG DI DESA SELAGAN JAYA KABUPATEN MUKOMUKO
Authors: Sakroni Sakroni , Utami Iis
Published: November 2023

Masalah  dalam  penelitian  ini  adalah  tentang  jawaban masyarakat terhadap Mite Danau Nibung yang ada di Desa Selagan jaya Kabupeten Mukomuko.Penelitian  ini  bertujuan  untuk  memperoleh pendeskripsian  jawaban masyarakat tentang Mite Danau Nibung. Jenis penelitian  ini adalah  deskriptif kualitatif. Data dalam penelitian ini adalah jawaban dari responden  dari mite yang ada di Danau nibung dan data yang di dapat dari hasil penelitian.  Sumber data dalam penelitian ini adalah artikel yang di tulis oleh  Wahyu amuk  berjudul Asal-usul Legenda  Danau Nibung dan wawancara pada masyarakat yang memahami tentang mite Danau Nibung di Desa Selagan Jaya Kabupaten Mukomuko. Pengumpulan data dilakukan dengan teknik  observasi, wawancara dan dokumentasi. Hasil penelitian menyatakan bahwa mite di Danau Nibung beragam dan berbeda-beda penuturanya dari setiap responden didasari dari perbedaan usia dan pengetahuan tentang  Danau nibung. Mite di Danau nibung diantaranya adalah adanya seorang bernama  Nibung yang dahulu tinggal di Danau Nibung, 7 orang penunggu istana dasar Danau Nibung ,kerajaan sakti rantau batuah di Danau Nibung,  hal yang menyebabkan Danau nibung bisa di sebut legenda dan keistimewaan danau nibung yang tidak di miliki oleh  danau lainya.
IEEE COINS 2023 Contest for In Sensor Machine Learning Computing
Authors: Pau Danilo , Korobitsyn Andrey , Proshin Dmitriy , Zherebtsov Danil , Bianco Marco
Published: November 2023

There is a vast consensus in the embedded system community about the need to support artificial intelligence at the edge. An increasing demand for IoT and automotive devices is experienced with such a mandatory need to provide additional value to the user. Pushing further the need at its extreme, the device becomes a sensing element integrated in a ultra tiny package. To stimulate further progress in that respect a challenge has been set to the 2023 edition of the IEEE COINS conference. This paper describes this challenge as well as its results. It was aimed to let international teams use an end-to-end novel methodology to automatically conceive and deploy machine learning solutions for human activity recognition, as exemplary case study. The target tiny device was an intelligent sensor processor equipped with programmable capabilities to deploy neuton.ai automatically generated machine learning workloads. The contest winning team devised a tiny neural model which achieved balanced accuracy of 81.4% over 24 classes on neuton.ai deep learning framework. The model was deployed on the sensor, clocked at 10 MHz, and required a total memory of 19 KiB and its inference latency was 152 ms.
A ARTE DA LINGUAGEM E DA INTERPRETAÇÃO: REFLETINDO SOBRE O DIREITO E A LITERATURA
Authors: Nakamura Rafael Costa
Published: November 2023

A linguagem é o principal meio de comunicação humana. Apesar dos avanços da epistemologia jurídica em direção à interdisciplinaridade e ao diálogo com diversas outras áreas do conhecimento, observa-se a resistência significativa vinculada ao formalismo. Essa resistência se manifesta na relutância em aceitar outras fontes de conhecimento e suas valiosas contribuições, como é o caso da Literatura. O discurso jurídico é tradicionalmente associado a códigos legislativos e discursos doutrinários. No entanto, existem outros tipos de discurso, como o poético que abordam a lei de maneiras distintas. Abordam-se, portanto, as interações entre direito e literatura, bem como a importância da interpretação e como diferentes formas de interpretação enriquecem a compreensão do direito. Outrossim, destaca-se a natureza política do direito. Observa-se a complexidade da interpretação nas proposições de direito, que não podem ser estritamente descritas ou valoradas. Além disso, aborda-se como o discurso literário o aproxima da sociedade, desafiando o formalismo jurídico e promovendo reflexões sobre questões sociais e éticas.