bluuebunny/crossref_metadata_2025 huggingface dataset:
Microcomb-Driven Optical Convolution for Car Plate Recognition
Authors: He Zhenming , Cheng Junwei , Liu Xinyu , Wu Bo , Zhou Heng , Dong Jianji , Zhang Xinliang
Published: August 2023

The great success of artificial intelligence (AI) calls for higher-performance computing accelerators, and optical neural networks (ONNs) with the advantages of high speed and low power consumption have become competitive candidates. However, most of the reported ONN architectures have demonstrated simple MNIST handwritten digit classification tasks due to relatively low precision. A microring resonator (MRR) weight bank can achieve a high-precision weight matrix and can increase computing density with the assistance of wavelength division multiplexing (WDM) technology offered by dissipative Kerr soliton (DKS) microcomb sources. Here, we implement a car plate recognition task based on an optical convolutional neural network (CNN). An integrated DKS microcomb was used to drive an MRR weight-bank-based photonic processor, and the computing precision of one optical convolution operation could reach 7 bits. The first convolutional layer was realized in the optical domain, and the remaining layers were performed in the electrical domain. Totally, the optoelectronic computing system (OCS) could achieve a comparable performance with a 64-bit digital computer for character classification. The error distribution obtained from the experiment was used to emulate the optical convolution operation of other layers. The probabilities of the softmax layer were slightly degraded, and the robustness of the CNN was reduced, but the recognition results were still acceptable. This work explores an MRR weight-bank-based OCS driven by a soliton microcomb to realize a real-life neural network task for the first time and provides a promising computational acceleration scheme for complex AI tasks.
Airy Transform of the New Power-Exponent-Phase Vortex Beam
Authors: Lin Qidong , Zhang Hao , Hu Zhiquan , Lu Xiaotan , Lu Xingyuan , Cai Yangjian , Zhao Chengliang
Published: August 2023

A new power-exponent-phase vortex beam with nonlinear phase winding has shown flexible control freedom compared with conventional vortex beams. In order to further enrich the modulation freedom and expand the ability of self-healing to meet current application requirements, we conducted a detailed study on the characteristics of the Airy transform of the new power-exponent-phase vortex beam. The influences of the Airy function, the power exponent, and the topological charge on normalized intensity and phase distributions are investigated theoretically and experimentally. More importantly, the self-healing properties of the new power-exponent-phase vortex beam with and without the Airy transform are compared. This shows that the new power-exponent-phase vortex beam with the Airy transform exhibits better self-healing ability when obstructed by obstacles. This study has potential applications in optical trapping and free-space optical communication.
Multi-Sized Granular Suspension Transport Modeling for the Control of Lost Circulation and Formation Damage in Fractured Oil and Gas Reservoirs
Authors: Liu Jinhua , Zhang Yayun , Zhang Dujie , Li Fan , Zhou Hexiang , Xu Chengyuan , Wang Weiji
Published: August 2023

Transport and retention of multi-sized suspended granules are common phenomena in fracture media of oil, gas and geothermal reservoirs. It can lead to severe permeability damage and productivity decline, which has a significant impact on the efficient development of underground resources. However, the granule transport and retention behaviors remain not well understood and quantified. The novel stochastic model is proposed for the multi-sized suspended granule transport in naturally fractured reservoirs accounting for granule retention and fracture clogging kinetics. A percolation fracture network is proposed considering fracture connectivity evolution during suspended granule transport. Granule retention and fracture clogging dynamics equations are proposed to account for incomplete fracture clogging by retained granules. The microscale stochastic model is allowed for upscaling to predict the multi-sized granule transport behavior in naturally fractured reservoirs. The model solution exhibits preferential plugging of fractures with sizes equal to or below the granule size. Multi-sized suspended granule shows great advantages over mono-sized suspended granule in the control of permeability damage induced by granule retention and fracture clogging. The retained granule concentration and permeability damage rate decrease with fracture network connectivity improvement. The experimental investigation on size-exclusion suspended granule flow has been performed. The model-based prediction of the retained granule concentration and permeability variation history shows good agreement with the experimental data, which verifies the developed model.
Decentralized Control Strategy for Participation of Electric Vehicles in Distribution Voltage Control
Authors: Fang Xin , Li Juan , Yuan Yubo , Yuan Xiaodong
Published: August 2023

With the accelerating transportation electrification, increasing numbers of electric vehicles (EVs) are connected to distribution networks via electric vehicle charging stations (EVCSs). Due to the uncertain charging behaviors of EV users, concentrated high-power EV charging during peak hours can result in significant undervoltage issues, affecting the regular operation of distribution networks and having detrimental effects on regular EV charging. Conventional EV charging scheduling methods are conducted in a centralized way, requiring extensive investment in communication infrastructure and intensive computing power. Accordingly, this paper proposes a novel decentralized voltage control scheme with the participation of EVs and EVCSs. The proposed control scheme first divides the distribution network into clusters based on a modified modularity index. Then, it applies the rolling optimization-based control of the EVs and EVCSs within each cluster to solve the regional voltage problems. The optimization window length is self-adapted based on the monitored states of the grid-connected EVs and EVCSs. Case studies show that the proposed decentralized voltage control strategy could effectively address the undervoltage violation issues and alleviate the pressure on peak shaving during peak hours, while satisfying the charging requirements of EV users.
An Exploration of the Evolution of the Loong Mother Belief System in Lingnan: Formation and Transformation
Authors: He Yan , Wu Rongqiao
Published: August 2023

The rise of a patriarchal society has led to a prevalent perception of male superiority over women, which is reflected in the gender-based disparities within the deity system of China. However, in contrast to the situation in the Central Plains, the Lingnan region assigns a significant social status to women, as evidenced by the active worship of female deities. Among them, the Loong Mother stands out as a highly revered goddess in Lingnan’s mythology. This paper investigates the evolution of the Loong Mother’s deification from a mortal woman, and explores the varying religious principles of Buddhism, Taoism, and Confucianism, as well as their influence on the veneration of female deities in Lingnan. Additionally, this paper analyzes the Loong Mother’s portrayal within civil society. Despite undergoing continuous transformation to cater to diverse religious traditions and societal needs, the goddess’s actions and functions ultimately reflect her creation and shaping by the community.
Assessing the Spatial–Temporal Pattern of Spring Maize Drought in Northeast China Using an Optimised Remote Sensing Index
Authors: Wang Yihao , Wu Yongfeng , Ji Lin , Zhang Jinshui , Meng Linghua
Published: August 2023

Northeast China plays a pivotal role in producing commodity grains. The precipitation and temperature distribution during the growth season is impacted by geographical and climate factors, rendering the region vulnerable to drought. However, relying on a single index does not reflect the severity and extent of drought in different regions. This research utilised the random forest (RF) model for screening remote sensing indices. Relative soil moisture (RSM) was employed to compare seven commonly used indices: the temperature vegetation dryness index (TVDI), vegetation supply water index (VSWI), vegetation condition index (VCI), temperature condition index (TCI), vegetation health index (VHI), multi-band drought index (MBDI), and normalised difference drought index (NDDI). The effectiveness of these indices for monitoring drought during different developmental stages of spring maize was evaluated. Trend rates were employed to investigate the temporal changes in drought patterns of spring maize from 2003 to 2020, and the Sen + Mann–Kendall test was used to analyse spatial variations. The results showed the following: (1) The seven remote sensing indices could accurately track drought during critical growth stages with the TVDI demonstrating higher applicability than the other six indices. (2) The application periods of two TVDIs with different parameters differed for the drought monitoring of spring maize in different developmental periods. The consistency and accuracy of the normalised difference vegetation index (NDVI)-based TVDI (TVDIN) were 5.77% and 34.62% higher than those of the enhanced vegetation index (EVI)-based TVDI (TVDIE), respectively, in the early stage. In contrast, the TVDIE exhibited 13.46% higher consistency than the TVDIN in the middle stage, and the accuracy was the same. During the later stage, the TVDIE showed significantly higher consistency and accuracy than the TVDIN with consistency increases of 9.61% and 38.64%, respectively. (3) The drought trend in northeast China increased from 2003 to 2020, exhibiting severe spring drought and a weakening of the drought in summer. The southern, southwestern, and northwestern parts of northeast China showed an upward drought trend; the drought-affected areas accounted for 37.91% of the study area. This paper identified the most suitable remote sensing indices for monitoring drought in different developmental stages of spring maize. The results provide a comprehensive understanding of the spatial–temporal patterns of drought during the past 18 years. These findings can be used to develop a dynamic agricultural drought monitoring model to ensure food security.
Spatio-Temporal Variation of Critical Relative Humidity Based on Multiple Datasets
Authors: Zhang Weiyuan , Li Jiming , Xu Sihang , Zhao Yang , Jian Bida
Published: August 2023

Clouds remain an important source of uncertainty in climate simulations, in large part because subgrid processes are not well represented. Critical relative humidity (RHc) is an important metric for subgrid-scale variability in humidity in cloud parameterization. Based on CloudSat and CALIPSO satellite data, we explored the spatial and temporal distribution characteristics of RHc, assessed the ability of ERA-5 and MERRA-2 reanalysis and CMIP-6 climate models to characterise humidity subgrid variability and further explored the influence of meteorological factors and aerosols. The statistical results showed that there was significant variation in the spatial distribution of RHc, with large variations in both latitude and altitude, as well as more pronounced monthly variations, and that there were differences in monthly variations between regions. Both the reanalysis data and the climate models were able to reproduce similar spatial and temporal distribution patterns but differed significantly in their specific values. The temporal correlations with satellite observations were also relatively poor. In addition, aerosols and meteorological conditions affected the distribution of RHc by influencing the cloud fraction at a certain relative humidity level, indicating that their influence needs to be considered in future parameterization schemes.
Estimation of Tropical Cyclone Intensity via Deep Learning Techniques from Satellite Cloud Images
Authors: Tong Biao , Fu Jiyang , Deng Yaxue , Huang Yongjun , Chan Pakwai , He Yuncheng
Published: August 2023

Estimating the intensity of tropical cyclones (TCs) is usually involved as a critical step in studies on TC disaster warnings and prediction. Satellite cloud images (SCIs) are one of the most effective and preferable data sources for TC research. Despite the great achievements in various SCI-based studies, accurate and efficient estimation of TC intensity still remains a challenge. In recent years, machine learning (ML) techniques have gained fast development and shown significant potential in dealing with big data, particularly with images. This study focuses on the objective estimation of TC intensity based on SCIs via a comprehensive usage of some advanced deep learning (DL) techniques and smoothing methods. Two estimation strategies are proposed and examined which, respectively, involve one and two functional stages. The one-stage strategy uses Vision Transformer (ViT) or Deep Convolutional Neutral Network (DCNN) as the regression model for directly identifying TC intensity, while the second strategy involves a classification stage that aims to stratify SCI samples into a few intensity groups and a subsequent regression stage that specifies the TC intensity. Further efforts are made to improve the estimation accuracy by using smoothing manipulations (via four specific smoothing techniques) in the scenarios of the aforementioned two strategies and their fusion. Results show that DCNN performs better than ViT in the one-stage strategy, while using ViT as the classification model and DCNN as the regression model can result in the best performance in the two-stage strategy. It is interesting that although the strategy of singly using DCNN wins out over any concerned two-stage strategy, the fusion of the two strategies outperforms either the one-stage strategy or the two-stage strategy. Results also suggest that using smoothing techniques are beneficial for the improvement of estimation accuracy. Overall, the best performance is achieved by using a hybrid strategy that consists of the one-stage strategy, the two-stage strategy and smoothing manipulation. The associated RMSE and MAE values are 9.81 kt and 7.51 kt, which prevail over those from most existing studies.
Estimating Blood Pressure during Exercise with a Cuffless Sphygmomanometer
Authors: Hayashi Kenta , Maeda Yuka , Yoshimura Takumi , Huang Ming , Tamura Toshiyo
Published: August 2023

Accurately measuring blood pressure (BP) is essential for maintaining physiological health, which is commonly achieved using cuff-based sphygmomanometers. Several attempts have been made to develop cuffless sphygmomanometers. To increase their accuracy and long-term variability, machine learning methods can be applied for analyzing photoplethysmogram (PPG) signals. Here, we propose a method to estimate the BP during exercise using a cuffless device. The BP estimation process involved preprocessing signals, feature extraction, and machine learning techniques. To ensure the reliability of the signals extracted from the PPG, we employed the skewness signal quality index and the RReliefF algorithm for signal selection. Thereafter, the BP was estimated using the long short-term memory (LSTM)-based neural network. Seventeen young adult males participated in the experiments, undergoing a structured protocol composed of rest, exercise, and recovery for 20 min. Compared to the BP measured using a non-invasive voltage clamp-type continuous sphygmomanometer, that estimated by the proposed method exhibited a mean error of 0.32 ± 7.76 mmHg, which is equivalent to the accuracy of a cuff-based sphygmomanometer per regulatory standards. By enhancing patient comfort and improving healthcare outcomes, the proposed approach can revolutionize BP monitoring in various settings, including clinical, home, and sports environments.
Combined Cardiac and Respiratory Monitoring from a Single Signal: A Case Study Employing the Fantasia Database
Authors: Brandwood Benjamin M. , Naik Ganesh R. , Gunawardana Upul , Gargiulo Gaetano D.
Published: August 2023

This study proposes a novel method for obtaining the electrocardiogram (ECG) derived respiration (EDR) from a single lead ECG and respiration-derived cardiogram (RDC) from a respiratory stretch sensor. The research aims to reconstruct the respiration waveform, determine the respiration rate from ECG QRS heartbeat complexes data, locate heartbeats, and calculate a heart rate (HR) using the respiration signal. The accuracy of both methods will be evaluated by comparing located QRS complexes and inspiration maxima to reference positions. The findings of this study will ultimately contribute to the development of new, more accurate, and efficient methods for identifying heartbeats in respiratory signals, leading to better diagnosis and management of cardiovascular diseases, particularly during sleep where respiration monitoring is paramount to detect apnoea and other respiratory dysfunctions linked to a decreased life quality and known cause of cardiovascular diseases. Additionally, this work could potentially assist in determining the feasibility of using simple, no-contact wearable devices for obtaining simultaneous cardiology and respiratory data from a single device.
Present-Day Tectonic Stress Evolution in Southern Yunnan Based on Focal Mechanisms
Authors: Fan Wenjie , Zhu Ye , Ji Yingfeng , Feng Lili , Zhu Weiling , Qu Rui
Published: August 2023

Tectonic extrusion bypassing the eastern Himalayan syntaxis results in a significant increase in regional stress instability and the associated frequent occurrence of earthquakes in southern Yunnan, China. However, the stress field, and the relationship between the focal mechanism of earthquakes and stress evolution in southern Yunnan, remain enigmatic. In this paper, using a modified grid point test method, we calculated the focal mechanism of ML ≥ 2.5 earthquakes in southern Yunnan (22–25° N, 100–104° E) from January 2009 to June 2023. Utilizing the solutions of historical earthquake focal mechanisms, we obtained the present-day regional tectonic stress field in southern Yunnan via inversion. The results indicate complex and diverse seismic focal mechanisms, and the main types of earthquakes are strike-slip events, followed by normal fault and reverse fault events. The orientations of the maximum and minimum principal stress axes rotate in a clockwise direction from northeast to southwest. The internal stress orientation distribution of the rhombic Sichuan–Yunnan block in the study area is consistent, and the block boundary zone is the site where stress deflection occurs, and the regional tectonic stress field is influenced by the interaction among different blocks. The distribution of R-value in the Lamping–Simao block gradually increases from north to south, indicating that the compressive stress required for material transport becomes relatively small. Combined with the geological and tectonic background of the study area, our results suggest that the speed of block movement gradually decreases from north to south; the distribution of R-value in the South China block is significantly smaller than that of the interior of the Sichuan–Yunnan rhombus, and the proportion of compressive stresses is larger, indicating a stronger extrusion in this region, which may be related to the fact that the Sichuan–Yunnan rhombus is strongly resisted by the South China block in the east.
Transformer Decoder-Based Enhanced Exploration Method to Alleviate Initial Exploration Problems in Reinforcement Learning
Authors: Kyoung Dohyun , Sung Yunsick
Published: August 2023

In reinforcement learning, the epsilon (ε)-greedy strategy is commonly employed as an exploration technique This method, however, leads to extensive initial exploration and prolonged learning periods. Existing approaches to mitigate this issue involve constraining the exploration range using expert data or utilizing pretrained models. Nevertheless, these methods do not effectively reduce the initial exploration range, as the exploration by the agent is limited to states adjacent to those included in the expert data. This paper proposes a method to reduce the initial exploration range in reinforcement learning through a pretrained transformer decoder on expert data. The proposed method involves pretraining a transformer decoder with massive expert data to guide the agent’s actions during the early learning stages. After achieving a certain learning threshold, the actions are determined using the epsilon-greedy strategy. An experiment was conducted in the basketball game FreeStyle1 to compare the proposed method with the traditional Deep Q-Network (DQN) using the epsilon-greedy strategy. The results indicated that the proposed method yielded approximately 2.5 times the average reward and a 26% higher win rate, proving its enhanced performance in reducing exploration range and optimizing learning times. This innovative method presents a significant improvement over traditional exploration techniques in reinforcement learning.
Fast Three-Dimensional Posture Reconstruction of Motorcyclists Using OpenPose and a Custom MATLAB Script
Authors: Barberi Emmanuele , Chillemi Massimiliano , Cucinotta Filippo , Sfravara Felice
Published: August 2023

Ergonomics focuses on the analysis of the interaction between human beings and their working environment. During the riding of a motorbike, ergonomics studies the rider’s posture on the motorbike. An incorrect posture can lead to physical and psychological discomfort, and can affect the perception of risk and the handling of the motorcycle. It is important for motorcyclists to adopt a good riding posture, for their health and road safety. The aim of this work is to propose a fast, cheap, and sufficiently robust method for the 3D reconstruction of the posture assumed by a motorcyclist. The stereo vision and the application of OpenPose made it possible to obtain a 3D reconstruction of the key points, and their evolution over time. The evaluation of the distances between the 3D key points, which represent the length of the various parts of the body, appears to remain sufficiently stable over time, and faithful to the real distances, as taken on the motorcyclist themself. The 3D reconstruction obtained can be applied in different fields: ergonomics, motorsport training, dynamics, and fluid dynamics analysis.
Analytical Performance of the Factory-Calibrated Flash Glucose Monitoring System FreeStyle Libre2TM in Healthy Women
Authors: Jin Zhuoxiu , Thackray Alice E. , King James A. , Deighton Kevin , Davies Melanie J. , Stensel David J.
Published: August 2023

Continuous glucose monitoring (CGM) is used clinically and for research purposes to capture glycaemic profiles. The accuracy of CGM among healthy populations has not been widely assessed. This study assessed agreement between glucose concentrations obtained from venous plasma and from CGM (FreeStyle Libre2TM, Abbott Diabetes Care, Witney, UK) in healthy women. Glucose concentrations were assessed after fasting and every 15 min after a standardized breakfast over a 4-h lab period. Accuracy of CGM was determined by Bland–Altman plot, 15/15% sensor agreement analysis, Clarke error grid analysis (EGA) and mean absolute relative difference (MARD). In all, 429 valid CGM readings with paired venous plasma glucose (VPG) values were obtained from 29 healthy women. Mean CGM readings were 1.14 mmol/L (95% CI: 0.97 to 1.30 mmol/L, p < 0.001) higher than VPG concentrations. Ratio 95% limits of agreement were from 0.68 to 2.20, and a proportional bias (slope: 0.22) was reported. Additionally, 45% of the CGM readings were within ±0.83 mmol/L (±15 mg/dL) or ±15% of VPG, while 85.3% were within EGA Zones A + B (clinically acceptable). MARD was 27.5% (95% CI: 20.8, 34.2%), with higher MARD values in the hypoglycaemia range and when VPG concentrations were falling. The FreeStyle Libre2TM CGM system tends to overestimate glucose concentrations compared to venous plasma samples in healthy women, especially during hypoglycaemia and during glycaemic swings.
Reflection Symmetry Detection in Earth Observation Data
Authors: Podgorelec David , Lukač Luka , Žalik Borut
Published: August 2023

The paper presents a new algorithm for reflection symmetry detection, which is specialized to detect maximal symmetric patterns in an Earth observation (EO) dataset. First, we stress the particularities that make symmetry detection in EO data different from detection in other geometric sets. The EO data acquisition cannot provide exact pairs of symmetric elements and, therefore, the approximate symmetry must be addressed, which is accomplished by voxelization. Besides this, the EO data symmetric patterns in the top view usually contain the most useful information for further processing and, thus, it suffices to detect symmetries with vertical symmetry planes. The algorithm first extracts the so-called interesting voxels and then finds symmetric pairs of line segments, separately for each horizontal voxel slice. The results with the same symmetry plane are then merged, first in individual slices and then through all the slices. The detected maximal symmetric patterns represent the so-called partial symmetries, which can be further processed to identify global and local symmetries. LiDAR datasets of six urban and natural attractions in Slovenia of different scales and in different voxel resolutions were analyzed in this paper, demonstrating high detection speed and quality of solutions.
Assessing Spatiotemporal and Quality Alterations in Paretic Upper Limb Movements after Stroke in Routine Care: Proposal and Validation of a Protocol Using IMUs versus MoCap
Authors: Merlau Baptiste , Cormier Camille , Alaux Alexia , Morin Margot , Montané Emmeline , Amarantini David , Gasq David
Published: August 2023

Accurate assessment of upper-limb movement alterations is a key component of post-stroke follow-up. Motion capture (MoCap) is the gold standard for assessment even in clinical conditions, but it requires a laboratory setting with a relatively complex implementation. Alternatively, inertial measurement units (IMUs) are the subject of growing interest, but their accuracy remains to be challenged. This study aims to assess the minimal detectable change (MDC) between spatiotemporal and quality variables obtained from these IMUs and MoCap, based on a specific protocol of IMU calibration and measurement and on data processing using the dead reckoning method. We also studied the influence of each data processing step on the level of between-system MDC. Fifteen post-stroke hemiparetic subjects performed reach or grasp tasks. The MDC for the movement time, index of curvature, smoothness (studied through the number of submovements), and trunk contribution was equal to 10.83%, 3.62%, 39.62%, and 25.11%, respectively. All calibration and data processing steps played a significant role in increasing the agreement. The between-system MDC values were found to be lower or comparable to the between-session MDC values obtained with MoCap, meaning that our results provide strong evidence that using IMUs with the proposed calibration and processing steps can successfully and accurately assess upper-limb movement alterations after stroke in clinical routine care conditions.
Statistical Modeling of Implicit Functional Relations
Authors: Lipovetsky Stan
Published: August 2023

This study considers the statistical estimation of relations presented by implicit functions. Such structures define mutual interconnections of variables rather than outcome variable dependence by predictor variables considered in regular regression analysis. For a simple case of two variables, pairwise regression modeling produces two different lines of each variable dependence using another variable, but building an implicit relation yields one invertible model composed of two simple regressions. Modeling an implicit linear relation for multiple variables can be expressed as a generalized eigenproblem of the covariance matrix of the variables in the metric of the covariance matrix of their errors. For unknown errors, this work describes their estimation by the residual errors of each variable in its regression by the other predictors. Then, the generalized eigenproblem can be reduced to the diagonalization of a special matrix built from the variables’ covariance matrix and its inversion. Numerical examples demonstrate the eigenvector solution’s good properties for building a unique equation of the relations between all variables. The proposed approach can be useful in practical regression modeling with all variables containing unobserved errors, which is a common situation for the applied problems.
Towards a Sustainable Future: A Systematic Review of Mobile Learning and Studies in Higher Education
Authors: Asadullah Md , Yeasmin Minara , Alam Abid Fakhre , Alsolami Abdulaziz , Ahmad Naved , Atoum Ibrahim
Published: August 2023

In recent years, mobile learning has emerged as a promising educational paradigm, revolutionizing the landscape of higher education. As the world confronts escalating environmental challenges and calls for sustainable solutions, it becomes essential to explore the potential of mobile learning to contribute to a more sustainable future. This review encompasses a comprehensive analysis of the existing literature, focusing on empirical studies, theoretical frameworks, and case studies conducted between 2002 and 2021. A substantial corpus of 981 articles were selected for in-depth examination by employing rigorous inclusion and exclusion criteria. The findings reveal that mobile learning has witnessed significant growth and diversification within higher education, with pervasive adoption across various disciplines and student populations. The identified studies present many innovative mobile learning strategies, encompassing mobile applications, gamified learning platforms, augmented reality experiences, and location-based learning. In conclusion, this systematic review underscores the substantial potential of mobile learning in higher education toward a sustainable future. By harnessing technological innovations, promoting eco-friendly practices, and fostering digital inclusivity, institutions can embark on a transformative journey that enhances educational outcomes and contributes to environmental preservation and global sustainability efforts. Future research should focus on exploring new avenues for sustainable mobile learning and conducting longitudinal studies to assess the long-term impact of mobile learning initiatives on educational outcomes and environmental conservation.
The Impact of Consumer’s Adaptation to the Creative Culture of Theme Parks on Review Usefulness
Authors: Li Shugang , Dou Qian , Chen Hui , Yu Zhaoxu
Published: August 2023

In the era of information overload and repetitive reviews, there has been limited exploration into the influence of consumers’ cultural adaptation to creative symbols in theme parks on the usefulness of online reviews, which is significant for enhancing tourism experiences, targeted marketing, personalized services, and informed tourism choices. This study aims to bridge this gap by examining how cultural adaptation factors interact and impact the review usefulness, and by considering the role of cultural adaptation in simplifying information during consumer decision-making processes. Additionally, the study investigates how consumers’ decision reference points, represented by advanced ticket levels, moderate their attention to attribute consistency when evaluating the review usefulness. A sample of 5929 valid consumer reviews of Disney theme parks from 2019 to 2022 on Meituan.com is analyzed using latent semantic analysis and Tobit regression to test the proposed hypotheses. We find that high symbolic creativity reviews stimulate cultural adaptation and increase attention to service attributes when evaluating review usefulness. Moreover, advanced ticket levels do not moderate the usefulness of extremely negative reviews. However, they do have a moderating effect on the usefulness of extremely positive reviews, with the direction of moderation differing based on the levels of symbolic creativity.
Digital Inequities: Promoting Digital Justice during the COVID-19 Pandemic
Authors: Child Gregory Scott , Song Kim
Published: August 2023

This qualitative study examines the actions taken by 12 US content teachers during the pandemic to provide their emergent bilingual learners (EBLs) with a digitally just education. When the pandemic forced schools to close their doors and transition to a virtual setting, teachers were faced with the reality that EBLs lacked the digital resources, skills, and literacies to successfully participate in virtual schooling. Based on the theory of digital justice, which seeks to promote digital equity for minoritized populations, this investigation was carried out to better understand how content teachers supported their EBLs during the pandemic. Through a series of semi-structured focus group interviews, data were collected and analyzed through open and axial coding. The findings from this study revealed how teachers provided technology for their EBLs, which strategies they took to support EBLs’ digital literacy development, and how virtual instruction impacted educational expectations. The findings also highlighted the issue of who was responsible for providing digital justice which has large implications on providing socially just educational experiences. This work emphasizes the importance of not only closing the digital divide, but also proactively developing EBLs’ digital skills and literacies necessary for 21st-century careers.
Climate Change Exposure and Firm Performance: Does Managerial Ability Matter?
Authors: Almaghrabi Khadija S.
Published: August 2023

Using a firm-level measure of climate change exposure, this study examines the role of managerial ability in the association between climate change exposure and corporate performance. Based on a sample of 43,620 firm-year observations over the period between 2001 and 2021, the study documents that although increased climate change exposure reduces corporate performance, managerial ability moderates this relationship. Specifically, this study shows that higher managerial ability mitigates the negative effect of climate change risk on financial performance and cash flow volatility reported by prior studies. These results hold across different specifications and when addressing the potential endogeneity issue concerning managerial ability. The findings of this study are essential to build a complete picture of the effect of climate change exposure on corporate performance. A key implication of the findings is that firms exposed to climate change risk are encouraged to enhance their managerial ability to overcome the negative impact of climate change exposure on corporate performance.
Association between Immunogenicity of a Monovalent Parenteral P2-VP8 Subunit Rotavirus Vaccine and Fecal Shedding of Rotavirus following Rotarix Challenge during a Randomized, Double-Blind, Placebo-Controlled Trial
Authors: Fellows Tamika , Page Nicola , Fix Alan , Flores Jorge , Cryz Stanley , McNeal Monica , Iturriza-Gomara Miren , Groome Michelle J.
Published: August 2023

A correlate of protection for rotavirus (RV) has not been consistently identified. Shedding of RV following an oral rotavirus vaccine (ORV) challenge has been investigated as a potential model to assess protection of parenteral RV vaccines. We previously showed that shedding of a challenge ORV dose was significantly reduced among recipients of a parenteral monovalent RV subunit vaccine (P2-VP8-P[8]) compared to placebo recipients. This secondary data analysis assessed the association between fecal shedding of RV, as determined by ELISA one week after receipt of a Rotarix challenge dose at 18 weeks of age, and serum RV-specific antibody responses, one and six months after vaccination with the third dose of the P2-VP8-P[8] vaccine or placebo. We did not find any association between serum RV-specific immune responses measured one month post-P2-VP8-P[8] vaccination and fecal shedding of RV post-challenge. At nine months of age, six months after the third P2-VP8-P[8] or placebo injection and having received three doses of Rotarix, infants shedding RV demonstrated higher immune responses than non-shedders, showing that RV shedding is reflective of vaccine response following ORV. Further evaluation is needed in a larger sample before fecal shedding of an ORV challenge can be used as a measure of field efficacy in RV vaccine trials.
An Integrated Framework for Environmental and Social Life Cycle Assessments in PET Bottle Waste Management: A Case Study in Brazil
Authors: Martin Eduardo J. P. , Oliveira Deborah S. B. L. , Oliveira Luiza S. B. L. , Bezerra Barbara S.
Published: August 2023

The improper disposal of PET bottle waste in Brazil jeopardizes the sustainability goals, impacting the social, economic, and environmental aspects. In order to tackle this issue, this study introduces a framework that was developed using a combination of environmental and social life cycle assessments (LCAs), along with a modified Analytic Hierarchy Process (AHP) methodology. Nine disposal scenarios were evaluated in Bauru, Brazil, including various combinations of landfills, sorting cooperatives, and incineration. Environmental (Env-LCA) and social (S-LCA) assessments followed the ISO 14040 standards, with the S-LCA incorporating the UNEP/SETAC guidelines. Scenario 9 was identified as the most sustainable option from the evaluated scenarios, with 100% of the waste sent to sorting cooperatives, with modified collection schemes. Conversely, Scenario 1, with a high landfill percentage, proved to be the least sustainable.
Study of regional features of the creation and functioning of the site of a private medical organization with the introduction of an administration system
Authors:   I. M. Sechenov First Moscow State Medical University, Utkin I. E. , Vyatkina N. Yu. ,   I. M. Sechenov First Moscow State Medical University; Financial University under the Government of the Russian Federation, Moscow
Published: August 2023

The paper studies the regional features of the creation and functioning of the site of a private medical organization with the introduction of an administration system, using the case of the company OOO «El-Med» (Vologda).
DINÁMICA DE LA TRANSFORMACIÓN GENERALIZADA DE BOOLE
Authors: Mendoza Mendoza Nelly Elisenia , Ruiz Leal Luis Bladismir
Published: August 2023

Los estudios realizados a la transformación de Boole B(x) = x − x1 y sus parametrizaciones, en su gran mayoría, se ha hecho desde la perspectiva de la teoría ergódica infinita y recientemente se estudió la ergodicidad para la medida invariante de probabilidad absolutamente continua a la de Lebesgue para Bα (x) = α(x − x1 ) con α ∈ (0, 1). Esos estudios sólo consideran los casos donde la familia de funciones no tienen puntos fijos e inclusive en ese caso no se describe comple- tamente el comportamiento dinámico. Partiendo de esto, se considera una generalización de la transformación de Boole delaformafabc(x)=ax−xb +ccona>0,b>0yc∈Ryserealizaunestudiodesudinámicaparaunconjunto amplio del espacio de los parámetros. Específicamente, se consigue una región del conjunto de parámetros donde fabc es transitivo y presenta una relación, por medio de la conjugación topológica, con la dinámica simbólica ( asociada a el Shift) para un subconjunto del espacio de dos símbolos, lo que justifica su comportamiento caótico en este caso. Se demuestra que existe una región abierta del espacio de parámetros donde fabc es uniformemente robustamente transitivo. También, se prueba que para a > 1, b > 0 y c ∈ R, f posee dos puntos fijos hiperbólicos y entre estos dos puntos existe un conjunto de Cantor invariante uniformemente robustamente transitivo, cuya dinámica es equivalente a la del shift unilateral de dos símbolos.
DAMPAK PENGEMBANGAN INDUSTRI PENGOLAHAN IKAN TERI TERHADAP KONDISI SOSIAL EKONOMI MASYARAKAT (STUDI KASUS : PULAU PASARAN)
Authors: Anjani Prita , Setianingrum Lutfi , Putri Marsista Buana
Published: August 2023

In an effort to develop an anchovy processing industry on Pasaran Island in order to increase the selling value and quality of the processed products, in 2003 the community began to change the fish processing system. The development of this processing industry will certainly have an impact on the socio-economic conditions of the community. This study aims to identify the impact of the development of anchovy processing industry in Pasaran Island on the socio-economic conditions of the community. In responding to this research, quantitative analysis was used to see changes in the socio-economic conditions of the community before and after the development of the fish processing industry. Qualitative descriptive analysis to describe the impact and spatial linkages of Pasaran Island anchovy processing activities on the socio-economic. From the results of the analysis it was found that the development of the anchovy processing industry in Pasaran Island had an impact on the socio-economic conditions of the community. These impacts include changes in employment opportunities, housing conditions, infrastructure development, ownership of living facilities, income and expenses. The impact on employment opportunities such as opening jobs, especially women workers from outside the island. The impact on housing conditions such as the change of buildings from wooden houses to permanent houses. The impact on infrastructure development such as easy access to clean water, electricity and road conditions. The impact on ownership of living facilities such as an increase in the number of ownership of living facilities. Impact on income and expenses such as increased income and expenses. Furthermore, the spatial linkage of anchovy processing activities that agglomerate on Pasaran Island results in an even distribution of the socio-economic conditions of the community.
PENGARUH PERUBAHAN LAHAN PERTANIAN MENJADI NON PERTANIAN TERHADAP ASPEK SOSIAL EKONOMI MASYARAKAT
Authors: Sugiharto Ferdi , Agustin Nela
Published: August 2023

The transformation that occurs in the peri-urban area will cause changes in the morphological peri-urban area and affect changes in the form of agricultural land use and have an impact on changes in the socio-economic conditions of the people in the area. The purpose of this study was to determine the influence of changes in agricultural land to non-agriculture on the socio-economic aspects of the community in Jati Agung. This research uses a deductive approach. The data collection method used primary data from questionnaires and interviews, the secondary data collected from Landsat 8 satellite image and BPS South Lampung Regency in 2013-2020. The method of analysis uses the predominant peri-urban zone classification with urban or predominantly urban characteristics divided into Urban Frame Zones and Urban-rural Frame Zones, which have a percentage of agricultural land use less than 50%. Statistical linear regression method is used to see the effect of the transformation of agricultural land use into non-agriculture on the socio-economic aspects of the peoples. The results of statistical tests show that there is a disproportionate effect with a large effect of 29.5% on the total population, 7.6% on population density, 8.6% on Livelihoods and 20.2% on income.
PERAN NEGARA MELALUI PROGRAM KELUARGA HARAPAN DALAM MENINGKATKAN KESEJAHTERAAN MASYARAKAT DI KECEMATAN MATA OLEO KABUPATEN BOMBANA
Authors: Azhari
Published: August 2023

This study aims to determine the extent of the state's role through PKH in improving the welfare of the people in the Mata Oleo subdistrict, Bombana district. This study used a qualitative method using a purposive sampling technique, the data sources in this study were primary data in the form of interviews and observations and secondary data in the form of journals, books, and other materials related to this research. The role of the state through PKH in improving the welfare of the community, especially the people of the Mata Oleo district, Bombana district has been concretely actualized through 3 (three) component categories including the Education category which seeks to prosper the poor through Elementary School (SD) to High School (SMA) Education. with the hope that in the future people who receive this education can increase the welfare of their families and the environment through the knowledge they gain at school, then the state will provide increased welfare to the Mata Oleo sub-district community through social welfare assistance to people with disabilities as a form of ensuring that all Indonesian citizens are equal before the law, government and social life in general as well as the state seeks to provide protection for pregnant women as a measure to reduce the high rate of maternal mortality and to ensure the long-term survival of mothers and their children so as to improve the quality of the human growth index in the future.
ANCAMAN TERHADAP DEMOKRATISASI DESA DI BALIK PERPANJANGAN MASA JABATAN KEPALA DESA
Authors: Umbu Pariangu  , La Ode Muhammad Elwan
Published: August 2023

The extension of the village head's term of office from 6 years to 9 years as a result of the revision of Law Number 6 of 2014 concerning Villages in Article 39, cannot be separated from the influence of compromises or political transaction relations between politicians in the DPR and village heads related to the 2024 Election. this is to analyze the decision to extend the term of office of the village head, beyond simply articulating the normative wishes of the village heads, namely as a threat to village democratization. The study method is qualitative, through literature studies, explored using data and information sources related to the extension of the position of the village head through the ratification of the revision of Law No. 6 of 2014 concerning Villages in the context of electoral interests in the 2024 elections and threats to village democratization. Then the data is classified and analyzed. The results of the study concluded that the extension of the village head's term of office to 9 years has the potential to threaten village democratization because it has implications for the tendency to abuse power, one of which is with village funds as the object, there is a saturation of the political psychology of the community, and the circulation of village leadership is jammed due to the increasing narrowing of the people's political evaluation space against the village head.
LABORATÓRIOS VIRTUAIS NA EDUCAÇÃO
Authors: Flach Janaína Luana , Zimmer Cínthia Gabriely
Published: August 2023

É amplamente reconhecido que aulas experimentais são grandes aliadas no ensino de química, pois este recurso pedagógico facilita a assimilação de conteúdos teóricos, auxiliando na construção do conhecimento. Contudo, além de poucas escolas disporem de laboratórios, e ainda com a possibilidade do ensino remoto, devido ao advento de surtos pandêmicos, a implementação de aulas práticas pode ser prejudicada. Uma alternativa para complementar essa importante forma de ensinar é a utilização de laboratórios virtuais. Esse recurso proporciona um ambiente controlável para simulação, permitindo que o aluno vivencie experiências virtuais de imersão, com a sensação de realidade e segurança. Nesse contexto, visando investigar o uso dessa ferramenta como uma estratégia de facilitação no aprendizado do ensino de química, analisou-se o uso do software ChemCollective, o qual é disponibilizado em plataformas digitais de forma gratuita, envolvendo o assunto de volumetria por neutralização. A análise abrangeu uma turma de ensino técnico em química integrado ao ensino médio. Para investigar a eficácia no uso dessa ferramenta, foram aplicadas avaliações diagnósticas sobre o assunto de volumetria de neutralização antes e após o uso de aulas simuladas no ChemCollective. Nessa linha, foram realizadas análises estatísticas através da média de acertos da turma. A avaliação dos resultados permitiu identificar uma evolução de acertos relevantes, sinalizando que é uma boa solução tecnológica em tempos de flexibilização do ensino diante da necessidade de ser remoto, além de ser um bom método preparatório para os alunos executarem procedimentos em ambientes reais.