bluuebunny/crossref_metadata_2025 huggingface dataset:
The Compound Effects of Highway Reconstruction and Climate Change on Vegetation Activity over the Qinghai Tibet Plateau: The G318 Highway as a Case Study
Authors: Guo Linghui , Li Yao , Luo Yuanyuan , Gao Jiangbo , Zhang Hebing , Zou Youfeng , Wu Shaohong
Published: November 2023

The Qinghai–Tibet Plateau (QTP) is among one of the most sensitive regions to global environmental change worldwide. Although climate change and engineering construction on the QTP have jointly modified the regional vegetation activity, little is known about how this affects the vegetation variation. Using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data from 2000–2021, this study investigated the spatiotemporal variation of vegetation activity and the compound effects of climate change and reconstruction along the Tibetan section of the G318 national highway (TG318) through a novel contribution quantification model and partial correlation analysis, as well as through a structural equation model (SEM). The results showed that the mean growing-season EVI increased significantly at a rate of about 0.0020/year in the western side of the TG318 after reconstruction but fluctuated in the east. Reconstruction generally had a significant effect on the mean growing-season EVI, with contributions of 7.67%, 19.12%, 18.24%, and −4.15% in different sections of the TG318, whereas climate change contributed from −10.14% to 8.84% of the total variation. The mean growing-season EVI negatively correlated with snow cover and minimum temperature in humid and sub-humid regions, whereas it was positively related with vapor pressure in semi-arid regions. Moreover, there existed an obvious lag effect of climate change on the mean growing-season EVI, with lag time generally decreasing from west to east and apparent heterogeneity among different months and regions. These findings will help better understand the environmental impacts along the engineering corridors and provide a scientific basis for ecological conservation in the QTP regions.
Differences in the Vertical Distribution of Aerosols, Nitrogen Dioxide, and Formaldehyde between Islands and Inland Areas: A Case Study in the Yangtze River Delta of China
Authors: Ou Jinping , Hu Qihou , Xing Chengzhi , Zhu Yizhi , Feng Jiaxuan , Wang Xinqi , Ji Xiangguang , Lin Hua , Yin Hao , Liu Cheng
Published: November 2023

Due to the difference of industrialization degree and meteorological conditions, there are obvious differences in the composition of air pollution between islands and inland areas. With Zhoushan (ZS) and Nanjing (NJ) representing islands and inland cities in the Yangtze River Delta, the differences in vertical distribution of atmospheric components were investigated. A combination of multi-axial differential optical absorption spectroscopy (MAX-DOAS), weather research and forecasting (WRF), and potential source contribution function (PSCF) models were used to obtain vertical distribution data for aerosols, nitrogen dioxide (NO2) and formaldehyde (HCHO), meteorological factors, and pollution sources in summer 2019. The findings indicate that, except for the aerosol extinction coefficient (AE), the atmospheric composition at the ZS site was not significantly stratified. However, the AE, NO2, and HCHO at NJ all displayed a decreasing trend with altitude. Here is the interesting finding that the ZS site has a higher AE value than the NJ site, while NJ displays higher NO2 and HCHO columns than the ZS site. This discrepancy was primarily attributable to Zhoushan City’s extremely low traffic emissions when compared to inland cities. In addition, HCHO in the YRD region was significantly affected by human activities. Analysis of potential pollution sources found that regional transport contributed to differences in atmospheric composition at different altitudes in different regions. Aerosols, NO2, and HCHO in Nanjing were significantly affected by transport in inland areas. Aerosols in Zhoushan were easily affected by transport in the Yellow Sea and East China Sea, and NO2 and HCHO were significantly affected by transport contributions from surrounding areas in inland areas. The study strongly suggests that land and sea breezes play an important role in the vertical distribution of aerosols over island regions.
Spatial–Temporal Mapping and Landscape Influence of Aquaculture Ponds in the Yangtze River Economic Belt from 1985 to 2020
Authors: Meng Yaru , Zhang Jiajun , Yang Xiaomei , Wang Zhihua
Published: November 2023

Most current research on aquaculture ponds focuses on coastal areas, leaving a gap in understanding of inland regions, such as the strategically significant Yangtze River Economic Belt in China. This study introduces an intelligent extraction method for extensive monitoring of aquaculture ponds in Yangtze River Economic Belt, using Landsat and Sentinel data from 1985 to 2020 with five-year intervals based on the Google Earth Engine (GEE) platform. Land cover change data were also analyzed to understand the impact of aquaculture-related changes. Results indicate a significant increase in aquaculture ponds in the Yangtze River Economic Belt from 3235.51 km2 to 14,207.08 km2 between 1985 and 2020. Aquaculture activity primarily shifted eastward from 1985 to 2015, then westward from 2015 to 2020. Approximately 2018.36 km2 of aquatic areas underwent conversion, mainly to water bodies or croplands, with fewer transitions to impervious surfaces, grasslands, or forests. This study highlights that inland areas can also experience significant increases in aquaculture ponds, particularly alongside large rivers, and that the environmental impacts of these changes differ from those in coastal areas, warranting specific attention.
Salient Arithmetic Data Extraction from Brain Activity via an Improved Deep Network
Authors: Khaleghi Nastaran , Hashemi Shaghayegh , Ardabili Sevda Zafarmandi , Sheykhivand Sobhan , Danishvar Sebelan
Published: November 2023

Interpretation of neural activity in response to stimulations received from the surrounding environment is necessary to realize automatic brain decoding. Analyzing the brain recordings corresponding to visual stimulation helps to infer the effects of perception occurring by vision on brain activity. In this paper, the impact of arithmetic concepts on vision-related brain records has been considered and an efficient convolutional neural network-based generative adversarial network (CNN-GAN) is proposed to map the electroencephalogram (EEG) to salient parts of the image stimuli. The first part of the proposed network consists of depth-wise one-dimensional convolution layers to classify the brain signals into 10 different categories according to Modified National Institute of Standards and Technology (MNIST) image digits. The output of the CNN part is fed forward to a fine-tuned GAN in the proposed model. The performance of the proposed CNN part is evaluated via the visually provoked 14-channel MindBigData recorded by David Vivancos, corresponding to images of 10 digits. An average accuracy of 95.4% is obtained for the CNN part for classification. The performance of the proposed CNN-GAN is evaluated based on saliency metrics of SSIM and CC equal to 92.9% and 97.28%, respectively. Furthermore, the EEG-based reconstruction of MNIST digits is accomplished by transferring and tuning the improved CNN-GAN’s trained weights.
EEG Amplitude Modulation Analysis across Mental Tasks: Towards Improved Active BCIs
Authors: Rosanne Olivier , Alves de Oliveira Alcyr , Falk Tiago H.
Published: November 2023

Brain–computer interface (BCI) technology has emerged as an influential communication tool with extensive applications across numerous fields, including entertainment, marketing, mental state monitoring, and particularly medical neurorehabilitation. Despite its immense potential, the reliability of BCI systems is challenged by the intricacies of data collection, environmental factors, and noisy interferences, making the interpretation of high-dimensional electroencephalogram (EEG) data a pressing issue. While the current trends in research have leant towards improving classification using deep learning-based models, our study proposes the use of new features based on EEG amplitude modulation (AM) dynamics. Experiments on an active BCI dataset comprised seven mental tasks to show the importance of the proposed features, as well as their complementarity to conventional power spectral features. Through combining the seven mental tasks, 21 binary classification tests were explored. In 17 of these 21 tests, the addition of the proposed features significantly improved classifier performance relative to using power spectral density (PSD) features only. Specifically, the average kappa score for these classifications increased from 0.57 to 0.62 using the combined feature set. An examination of the top-selected features showed the predominance of the AM-based measures, comprising over 77% of the top-ranked features. We conclude this paper with an in-depth analysis of these top-ranked features and discuss their potential for use in neurophysiology.
Local Peaks Search Method for Solving Lamb Waves’ Dispersion Equation of Laminated Structures and the Application
Authors: Gong Jiayuan , Chen Hongyang
Published: November 2023

To study the acoustic characteristics of sound scattered from laminated structures such as elastic plates and shells, it is usually required to solve the Lamb waves’ dispersion equations. Many traditional root-finding methods such as bisection, the Newton–Raphson method, and the Muller method are not able to tackle the problem completely. A simple but powerful method named local peaks search (LPS) is proposed to overcome their drawbacks. Firstly, the non-zero part of the dispersion equation is defined as the dispersion function, and its reciprocal is used to transform the zeros (i.e., roots) into local peaks. Secondly, the chosen complex domain is discretized, and the coarse local domains where the local peaks exist are determined by the direct search method globally. Thirdly, the Muller method is applied to obtain the refined locations of local peaks. Lastly, in order to refine the results, a hierarchical scheme is designed and the iteration of the above procedures is implemented; the error is set to be 10−16 as the stop criteria. The accuracy of the LPS method is validated by comparing it with the bisection method for the problem of elastic plates in the vacuum. The acoustic echo structures are analyzed experimentally. By computation of Lamb waves’ phase velocity, the critical angles are derived numerically and compared with the results acquired by an experiment using monostatic sound transducers. In this way, it is validated that the elastic scattered wave components are the highlights shown in the time-angle figure. Furthermore, the work can be applied for non-destructive testing, especially underwater structural health monitoring.
A Multichannel Conflict-Free Mac Protocol for Enhancing RPMA Scalability
Authors: Alsaeedi Enas Ali , Bouabdallah Fatma
Published: November 2023

The internet of things (IoT) revolutionized human life, whereby a large number of interrelated devices are connected to exchange data in order to accomplish many tasks, leading to the rapid growth of connected devices, reaching the tens of billions. The Low Power Wide Area (LPWA) protocols paradigm has emerged to satisfy the IoT application requirements, especially in terms of long-range communication and low power consumption. However, LPWA technologies still do not completely meet the scalability requirement of IoT applications. The main critical issues are the restrictive duty cycle regulations of the sub-GHz band in which most LPWA technologies operate, as well as the random access to the medium. Ingenu Random Phase Multiple Access (RPMA) is an LPWA technology that uses the 2.4 GHz band that is not subject to the duty cycle constraint. Furthermore, RPMA uses Direct-Sequence Spread Spectrum (DSSS) as a modulation technique; hence, it is an excellent candidate technology for handling scalable LPWA networks. In this paper, we perform mathematical and simulation analysis to assess RPMA scalability and the factors that affect it, especially when all the available channels are used. The results indicate that RPMA has impressive scalability. Indeed, by taking advantage of the multichannel feature in RPMA, the network capacity can be increased by up to 38 times. Aditionally, randomly selecting the Spreading Factors (SF) degrades the network scalability, as working on higher SFs will increase the probability of collision. Thus, we proposed an SF distribution algorithm that ensures effective packet delivery with minimum collision.
Damage Mechanism of HgCdTe Focal Plane Array Detector Irradiated Using Mid-Infrared Pulse Laser
Authors: Zhang Yin , Zheng Changbin , Liu Yang , Wang Yunzhe , Xu Yongbo , Shao Junfeng
Published: November 2023

To investigate the damage threshold and mechanism of a mid-infrared HgCdTe focal plane array (FPA) detector, relevant experimental and theoretical studies were conducted. The line damage threshold of a HgCdTe FPA detector may be within the range of 0.59 Jcm−2 to 0.71 Jcm−2. The full frame damage threshold of the detector may be in the range of 0.86 Jcm−2 to 1.17 Jcm−2. Experimental results showed that when the energy density reaches 1.17 Jcm−2, the detector exhibits irreversible full frame damage and is completely unable to image. Based on the finite element method, a three-dimensional model of HgCdTe FPAs detector was established to study the heat transfer mechanism, internal stress, and damage sequence. When HgCdTe melts, we think that the detector is damaged. Under these conditions, the theoretical damage threshold calculated using the detector model is 0.55 Jcm−2. The difference between theoretical and experimental values was analyzed. The relationship between damage threshold and pulse width was also studied. It was found that when the pulse width is less than 1000 ns, the damage threshold characterized by peak power density is inversely proportional to pulse width. This relationship can help us predict the experimental damage threshold of an FPA detector. This model is reasonable and convenient for studying the damage of FPA detectors with a mid-infrared pulse laser. The research content in this article has important reference significance for the damage and protection of HgCdTe FPA detectors.
Changes in Anthropometric Characteristics and Isokinetic Muscle Strength in Elite Team Sport Players during an Annual Training Cycle
Authors: Papaevangelou Evangelia , Papadopoulou Zacharoula , Mandroukas Athanasios , Michaildis Yiannis , Nikolaidis Pantelis , Margaritelis Nikos , Metaxas Thomas
Published: November 2023

The aim of the present research was to investigate the variation in the anthropometric characteristics and the isokinetic muscle strength of elite female team sport players during a season (29–36 weeks). Three groups of female athletes that consisted of soccer (n = 19; age, 23.2 ± 4.3 years), basketball (n = 26, 21.1 ± 5.4 years) and handball players (n = 26, 21.1 ± 4.2 years) underwent anthropometric and isokinetic measurements at the beginning of the preparation period, in the middle and at the end of the competitive season. Isokinetic peak torque values of the hamstrings (H) and quadriceps (Q), as well as the conventional strength ratios of H:Q, were tested on an isokinetic dynamometer at angular velocities of 60, 180 and 300°·s−1. Body weight, lean body mass and body fat of all groups decreased from the first to the third testing session (p < 0.05). Isokinetic peak torque gradually increased during the three measurements (p < 0.05). The soccer players had lower body weight and body fat compared to the basketball and handball players (p < 0.05). Isokinetic peak torque in knee flexion did not show any difference between the sports at any angular velocity or knee movement (flexion and extension), with an exception of the 180°·s−1. The improvement observed for all athletes can be attributed to the training programs that collectively characterize these team sports.
Coping with Permanent Liminality: Social Understanding and Action through Theatre in Late Communist Hungary
Authors: Szakolczai Arpad
Published: November 2023

Theatre is the modern liminoid equivalent of ritual liminality, according to Victor Turner. It is also, like most arts, a Janus-faced phenomenon: on one hand, it is a way to systematically infect the public with mimetic desire and rivalry (this is the aspect emphasised, quite rightly, by Plato and René Girard); on the other, it also enables the public expression of views about the contemporary state of social and political life that otherwise would be difficult to speak about, or even censored. As an example, this article will turn to the 1970s in Hungary, when the communist regime had become much softened, though at the same time generated the impression, in everyone, that it would last forever. More concretely, it will first shortly present and analyse the quite unique story of the Kaposvár theatre, which during the decade changed, through a peculiar combination of ‘liminal’ factors, from a boring provincial spectacle to the number one theatrical event of the country, avidly followed by students and intellectuals, especially from the capital. An epilogue is devoted to the masterly article by Elemér Hankiss, the most important and influential intellectual living then in Hungary who became, for a time, the consensus president of the Hungarian Television after the collapse of communism. It exposes the infantilising character of communist power by analysing a series of theatrical performances staged in a leading Budapest theatre in the late 1970s. Infantile adults are evidently caught in a permanent liminality, so Hankiss shows how theatre indeed was a main instrument in diagnosing the worst aspect of life under communist rule, its permanent liminality, reinforcing uncertainty and hopelessness.
Comparison of Different Coach Competition Micro-Cycle Planning Strategies in Professional Soccer
Authors: Marín Kévin , Castellano Julen
Published: November 2023

Background: Coaches propose training strategies to develop their playing model, but the impact on the conditional demand of players is unknown. The objective of this study aimed to assess the conditional demands associated with five competitive micro-cycle (Mi) planning strategies put forth by professional soccer coaches. The dependent locomotor variables were: total distance traveled (TD, in m), high-speed running distance (TD21, >21 km·h−1, in m), sprint distance (TD27, >27 km·h−1, in m), acceleration load (aLoaD, in AU) and number of accelerations (ACC2, >2 m·s−2 in n) and decelerations (DEC2, <−2 m·s−2 in n). The activity profile of the players was monitored during each training session using a global positioning system (GPS) during four seasons (2018–2019 to 2021–2022). Regardless of the coach, the sessions furthest from Mi (MD+1, MD-4 and MD-3) were the most conditionally demanding, where TD27 was especially stimulated on MD-3 (ES = 0.7, 0.2/1.2, mean and range; p < 0.05); furthermore, MD-2 was the least demanding session of all the trainers (ES = −2.4, −2.6/−1.5, mean and range; p < 0.01). However, there were nuances regarding the conditional demand among the coaches: Co1 and Co2 proposed a higher conditional demand in the MD-2 and MD-1 sessions (p < 0.05). The conclusion was twofold: elite soccer coaches proposed a horizontal alternation in the weekly distribution of training stimuli; nevertheless, the differences in the style of play of each coach affected the week-planning strategy.
A Human Behaviour Perspective on Horizontal Collaboration to Reduce the Climate Impact of Logistics
Authors: Cruijssen Frans , van Beest Ilja , Kant Goos
Published: November 2023

The transport sector needs to drastically reduce its carbon footprint to comply with the Paris Agreement. In today’s sharing economy, an emerging strategy to contribute to this goal is horizontal collaboration. However, most studies on horizontal collaboration or resource pooling are approached from a theoretical Operations Research perspective, and case studies are usually stylised. At the same time, the uptake of horizontal collaboration in practice is limited. An important explanation for this is that compared to traditional vertical collaboration, coalition formation is much more complex under horizontal collaboration, as some players will be included in the collaborative coalition, while others will be excluded. We conjecture that this renders human behaviour much more important than in more traditional vertical supply chain relations. Therefore, in this paper, we propose a research agenda for an interdisciplinary approach that integrates human behavioural aspects in studies on horizontal supply chain collaboration. We review some vital concepts from social psychology and discuss the importance to the success or failure of horizontal collaboration initiatives to reduce the environment footprint of the logistics sector. We conclude that social psychological insights on mixed-motive interactions are pivotal to understand wicked problems such as Sustainable Development Goal 13 on Climate Action, and that interdisciplinary approaches should therefore receive more attention in academic literature.
Consumers’ Motives on Wine Tourism in Greece in the Post-COVID-19 Era
Authors: Santorinaios Athanasios , Kosma Ioanna S. , Skalkos Dimitris
Published: November 2023

Wine tourism is emerging as one of the most important forms of alternative, sustainable tourism in wine countries, such as Greece, in the post-COVID-19 era. In this paper, consumers’ motives for wine tourism in Greece today are investigated regarding (i) their consumption habits related to wine, (ii) their experience with wine tourism, (iii) the parameters that would encourage their visit to a wine region, such as wine, the winery, and general regional characteristics, and (iv) the source of information consulted for a wine tourism experience. The questionnaire was conducted from April to May 2023, with 595 participants, via the Google Forms platform. The statistical analysis was performed with basic tools, as well as cross and chi-square tests, to analyze the data. The highlights of the results indicate that consumers (the participants of the survey) consume more wine today than before the pandemic (57%) and have previous experience in wine tourism (59.8%), with the majority of them having visited a winery more than once (67.4%). The most popular activity at the winery was found to be wine tasting (46.6%), followed by open discussion about wine (35.2%), and, at the regional level, visiting the sights (46%) and doing activities in nature (30.6%). Future participants are looking for innovation in wine tourism, with trained staff (77.5%) and organized tours (74.3%), the organization of wine festivals and other events (71.9%), opportunities to explore the local community, such as the outdoors (83.5%) and its culture and history (70.9%), during their visit, and available information on wine tourism opportunities online (73%). They also are encouraging the transition of the Greek wine tourism industry to the digital world. Based on the overall results, three types of support are proposed for the successful, sustainable development of wine tourism in wine-producing countries.
Exploration of Riding Behaviors of Food Delivery Riders: A Naturalistic Cycling Study in Changsha, China
Authors: Zhang Zihao , Liu Chenhui
Published: November 2023

Aimed at the riding safety issue of food delivery riders in China who mainly travel by electric bikes, a naturalistic cycling study was conducted by collecting the naturalistic cycling data of dozens of food delivery riders in Changsha, China, to identify their riding characteristics. It was found that the participating food delivery riders are mainly undereducated young male adults, and the primary reason for them to take the job is the flexible working hours. Furthermore, they frequently work overtime and admit to often committing risky riding behaviors to deliver food on time. The analysis of their riding trajectories indicates that they delivered orders all day long, rather than just at mealtimes. They mainly work within 3 km of the delivery station, and the average riding radius was 2.39 km. Male riders, riders working less than one year, and riders with high school education had a relatively fast riding speed. These findings provide valuable new insights for agencies to understand the riding characteristics of food delivery riders and to formulate the appropriate countermeasures to improve their occupational safety.
Photovoltaic Power Forecasting Approach Based on Ground-Based Cloud Images in Hazy Weather
Authors: Lu Zhiying , Chen Wenpeng , Yan Qin , Li Xin , Nie Bing
Published: November 2023

Haze constitutes a pivotal meteorological variable with notable implications for photovoltaic power forecasting. The presence of haze is anticipated to lead to a reduction in the output power of photovoltaic plants. Therefore, achieving precise forecasts of photovoltaic power in hazy conditions holds paramount significance. This study introduces a novel approach to forecasting photovoltaic power under haze conditions, leveraging ground-based cloud images. Firstly, the aerosol scattering coefficient is introduced as a pivotal parameter for characterizing photovoltaic power fluctuations influenced by haze. Additionally, other features, such as sky cloud cover, color attributes, light intensity, and texture characteristics, are considered. Subsequently, the Spearman correlation coefficient is applied to calculate the correlation between feature sequences and photovoltaic power. Effective features are then selected as inputs and three models—LSTM, SVM, and XGBoost—are employed for training and performance analysis. After comparing with existing technologies, the predicted results have achieved the best performance. Finally, using actual data, the effectiveness of the aerosol scattering coefficient is confirmed, by exhibiting the highest correlation index, as a pivotal parameter for forecasting photovoltaic output under the influence of haze. The results demonstrate that the aerosol scattering coefficient enhances the forecast accuracy of photovoltaic power in both heavy and light haze conditions by 1.083% and 0.599%, respectively, while exerting minimal influence on clear days. Upon comprehensive evaluation, it is evident that the proposed forecasting method in this study offers substantial advantages for accurately predicting photovoltaic power output in hazy weather scenarios.
Digital Innovative Governance of the Indonesian Creative Economy: A Governmental Perspective
Authors: Dellyana Dina , Arina Nina , Fauzan Tribowo Rachmat
Published: November 2023

The digital transformation of the creative economy has presented Indonesia with a unique set of challenges and opportunities, demanding innovative governance strategies to navigate this dynamic landscape. This research focuses on the nuanced governance mechanisms employed by the Indonesian government to foster, regulate, and harness the full potential of its digital creative economy. Utilizing a qualitative methodology, this study investigates the experiences, perspectives, and actions of key governmental actors, policymakers, and stakeholders. Semi-structured interviews and document analysis reveal the intricate interplay between government policies and civil servants in Indonesia that takes place in order to manage the creative economy in this developing country. The findings shed light on the adaptive strategies and policies implicated in the creative economy, providing insights into the understanding and collaboration between civil servants that can inform not only Indonesia, but also other nations seeking to harness the transformative power of this rapidly evolving sector. This research contributes to a deeper understanding of the complex relationship between governance and the creative economy, highlighting the need for a digital innovation co-creation scheme by which civil servants can navigate the digital age of creative industries.
Hydrochemical Characteristics and Sources of Lithium in Carbonate-Type Salt Lake in Tibet
Authors: Zhou Jiangdi , Li Binkai , He Maoyong , Jiao Jiangang , Tang Zhongli , Li Zhengyan
Published: November 2023

With the development of green energy, the demand for lithium resources has increased sharply, and salt lakes are an important source of lithium. In China, the Qinghai–Tibet Plateau has substantial lithium resources, and the Bangor Co Salt Lake is a typical Li-rich carbonate salt lake in northern Tibet. Research into the lithium source of the lake is of great significance for future sustainable industrial development. This article selects the Bangor Co Salt Lake recharge water system (river and cold spring water) and brine samples as the research objects, conducts hydrochemical composition and isotope testing of the water body, and determines the anions, cations, and B isotopes of the samples. This article uses the Piper three-line diagram, Gibbs diagram, and ion ratio relationship to study the hydrochemical characteristics and major ion sources of recharge water systems and salt lakes. The results indicate that the hydrochemical type has transitioned from the strong carbonate type to the moderate carbonate type from the recharge area to the lake area. The major source of ions in lakes is the weathering products of carbonate rocks, followed by evaporite and silicate solutes. The enrichment of lithium in salt lakes is mainly related to the contribution of rivers, followed by geothermal-related cold springs, and early sedimentary carbonate minerals may also make potential contributions. These findings provide a scientific basis for the mechanism of lithium enrichment, as well as for the further development and evaluation of lithium resources.
Effect of Ametryn Herbicide and Soil Organic Matter Content on Weed Growth, Herbicide Persistence, and Yield of Sweet Corn (Zea mays)
Authors: Sumekar Yayan , Widayat Dedi , Umiyati Uum , Aprilia Ajeng Cahya , Gafur Abdul
Published: November 2023

This study examines the impact of weeds on sweet corn, where weeds compete for essential elements, such as nutrients, water, sunlight, and space for growth. In general, the use of herbicides is meant to suppress weed growth. Soil organic matter is important for plant growth and affects herbicide persistence. This study aimed to explore the interaction between ametryn herbicide and soil organic matter content and its impacts on weed growth, herbicide persistence, and sweet corn yield. The experiment was initiated in 2022 at the Experimental Station of the Faculty of Agriculture, Padjadjaran University, Indonesia, using a Split-Plot Design in a Randomized Complete Block Design (RCBD), with three replicates. The experiments consisted of three levels of organic matter, i.e., low, medium, and high, and six levels of ametryn herbicide at 0.0 (control), 0.5, 1.0, 1.5, 2.0, and 2.5 kg a.i./ha. The results indicated that the apparent interaction between ametryn herbicide doses of 1.5, 2.0, and 2.5 kg a.i./ha and the three levels of the organic matter content totally suppressed weed growth. However, the effects of the interaction between ametryn herbicide and organic matter content on the herbicide persistence and the sweet corn yield were not obvious. Ametryn yielded excellent positive results on sweet corn yield. Bioassay analysis showed that the lowest persistence of ametryn herbicide was in line with the highest content of organic matter.
Dam Sustainability’s Interdependency with Climate Change and Dam Failure Drivers
Authors: Abu-Afifeh Qusay , Rahbeh Michel , Al-Afeshat Aya , Al-Omari Saif , Qutishat Tala Amer , Brezat Ali , Alkayed Ali
Published: November 2023

The complex interplay between the drivers of dam failure and climate change factors constitutes a central focus of this study. Variations in temperature and precipitation patterns have profound effects on dam storage volume, quality, and structural stability. This research serves two purposes. First, it employs the Wroclaw Taxonomic Method (WTM) to construct a comprehensive indicator called the Index of Sustainable Dams (ISD). The King Talal Dam (KTD) was chosen as a case study using data spanning from 2011 to 2022, encompassing 14 variables. Second, the Granger Causality Test (GCT) is applied to examine the causal connections between the ISD, climate change, and dam failure. The research provides an in-depth evaluation of the KTD in terms of the ISD and its three critical dimensions: environmental, economic, and social. It also reveals substantial bidirectional causality relationships between the ISD, climate change (as measured by mean maximum and minimum temperature and mean annual precipitation), and dam failure (as measured by dam age, sediment yield, and storage). The analysis confirms a strong interdependence among the drivers of climate change, dam failure, and dam sustainability. Moreover, combining the WTM and the GCT is efficient for assessing the sustainability of various dam types.
Detection of Arsenic, Chromium, Cadmium, Lead, and Mercury in Fish: Effects on the Sustainable and Healthy Development of Aquatic Life and Human Consumers
Authors: Tolkou Athanasia K. , Toubanaki Dimitra K. , Kyzas George Z.
Published: November 2023

Heavy metals are among the most important pollutants that threaten the aquatic environment when their concentrations exceed certain limits. Some of these metals and metalloids are beneficial and necessary for fish, but others, such as arsenic (As), chromium (Cr), cadmium (Cd), lead (Pb) and mercury (Hg), are non-essential and toxic. In reviewing the recent relevant literature, 4 different continents, 13 different countries, and more than 50 different fish species were analyzed in terms of As, Cr, Cd, Pb and Hg concentrations. According to the comparative results, it was found that in Tercan Dam Lake, Turkey, the highest concentration of Cr was detected in Capoeta umbla (2.455 mg/kg), and of As in Ctenopharyngodon idella (0.774 mg/kg) species. Greater values than the permissible limits of FAO/WHO in terms of As were also found in Andalusia, Southern Spain, in Mullus surmuletus (0.427 mg/kg), and Sardina pilchardus (0.561 mg/kg) and in Sprattus sprattus (0.636 mg/kg) in the Baltic Sea, but a remarkably high content of As (8.48 mg/kg) was determined in Penaeus notialis, found in Guinea, Africa. Moreover, Cd concentration was low to nil in almost all cases, with the exception of Amblyceps mangois species collected from the Dhaleshwari River in Bangladesh, which showed the highest value (0.063 mg/kg). Finally, extremely high levels of Pb were found in Plectropomus pessuliferus (5.05 mg/kg) and Epinephelus summana (2.80 mg/kg) in Jeddah, Saudi Arabia. The Hg content in fish was under the permissible limit in almost all cases, with megrim and red mullet from the Andalusian Sea exhibiting a relatively higher content (0.091 and 0.067 mg/kg). In general, the sequence of accumulation of toxic elements in fish was As > Cr > Pb > Cd > Hg.
Measuring Residents’ and Visitors’ Satisfaction with Sustainable Tourism—The Case of “Rusanda” Nature Park, Vojvodina Province
Authors: Trišić Igor , Privitera Donatella , Ristić Vladica , Štetić Snežana , Stanić Jovanović Sara , Nechita Florin
Published: November 2023

The Nature Park “Rusanda” (NPR) is a designated area under the second category of national protection. Situated in the Vojvodina Province, in the northern region of Serbia, its accessibility to a substantial number of international visitors is enhanced by its proximity to Romania and Hungary. Lake Rusanda and the salt marsh habitats render this region a sanctuary for rare avian species. This ecological significance has led to the NPR being designated as an IBA area—an Important Bird and Biodiversity Area by Birdlife. Beyond its natural attributes, the NPR stands out for its diverse cultural heritage, stemming from the local population residing in its immediate vicinity. A notable characteristic is the diverse ethnic makeup, contributing to a wide array of cultures, traditional attire, original folk music, customs, and cuisine, collectively forming a distinctive cultural heritage unique to this part of Vojvodina. To assess the status of sustainable tourism and its impact on the satisfaction of both residents and tourists within the NPR, the Prism of Sustainability model (PoS) is employed. In the quantitative approach, a survey questionnaire was utilized as a research tool, with a total of 840 participants included through a randomized sampling technique. Regression analysis of the study’s results indicates that sustainable tourism exerts a significant influence on the contentment of local people and tourists in the NPR. Given the presence of diverse ecological and societal elements, in addition to the existence of rare flora and fauna species, the central thrust in tourism development should focus on preserving and involving local residents in the planning and progress of tourism initiatives. The primary types of tourism that are poised for success in the NPR encompass ecotourism, wellness and spa tourism, nature-based tourism, birdwatching, scientific research tourism, and excursions.
Predicting Generation of Different Demolition Waste Types Using Simple Artificial Neural Networks
Authors: Cha Gi-Wook , Park Choon-Wook , Kim Young-Chan , Moon Hyeun Jun
Published: November 2023

In South Korea, demolition waste (DW) management has become increasingly significant owing to the rising number of old buildings. Effective DW management requires an efficient approach that accurately quantifies and predicts the generation of DW (DWG) of various types, which necessitates access to the required information or technology capable of achieving this. Hence, we developed an artificial intelligence-based model that predicts the generation of ten DW types, specifically from buildings in redevelopment areas. We used an artificial neural network algorithm with <10 neurons in the hidden layer to derive individual input variables and optimal hyperparameters for each DW type. All DWG prediction models achieved an average validation and test prediction performance (R2) of 0.970 and 0.952, respectively, with their ratios of percent deviation ≥ 2.5, verifying them as excellent models. Moreover, Shapley additive explanations analysis revealed that DWG was most impacted by the floor area for all DW types, with a positive correlation with DWG. Conversely, other factors showed either a positive or negative correlation with DWG, depending on the DW type. The study findings may assist demolition companies and local governments in making informed decisions for efficient DW management and resource allocation by accurately predicting the generation of various types of DW.
A Review of the Direct Measurement of Total OH Reactivity: Ambient Air and Vehicular Emission
Authors: Yang Xinping
Published: November 2023

Total OH reactivity, an index utilized to evaluate the overall effect of atmospheric reactive species on hydroxyl radicals, has been assessed over the past half century, particularly in ambient air. The direct measurement of OH reactivity for vehicular sources has also been conducted, further enhancing our understanding of chemical compounds and processes in source emissions. However, the current summary on OH reactivity dominantly focuses on ambient, and the review of OH reactivity measurements and characteristics for vehicular sources was lacking. Herein, we comprehensively reviewed and compared the measurement techniques, values of total OH reactivity, reactive chemical species, and missing OH reactivity for ambient air and vehicular sources involving exhaust and evaporation. The OH reactivity values for ambient air are comparable to those for evaporative emission (around 0–102 s−1), whereas they are all lower by 2–3 orders of magnitude than exhaust emission. In areas dominated by anthropogenic emissions, inorganic reactivity dominates the OH reactivity, while in biogenic-dominated areas, organic reactivity is the main contributor. For vehicular sources, inorganic reactivity dominates the calculated OH reactivity for exhaust emissions, while volatile organic compound reactivity (especially alkene reactivity) can almost explain all the calculated OH reactivity for evaporative emissions. The missing reactivity for ambient air and vehicular emission might derive from unmeasured, even unknown, organic species. We finally discussed possible new directions for future studies of total OH reactivity.
Assessing Corporate Vendor Selection in the Oil and Gas Industry: A Review of Green Strategies and Carbon Reduction Options
Authors: Otsubo Yumihito , Chapman Andrew J.
Published: November 2023

This paper addresses the global imperative of tackling environmental challenges, particularly in the context of the carbon-intensive oil and gas (O&G) industry, which is one of the heaviest carbon-emitting industries. Competitive advantages in this industry often stem from external connections rather than internal capabilities. How companies assess their business partners, including electric vendors, from an environmental standpoint, using a combination of quantitative and qualitative approaches, was explored using a systematic literature review approach. This literature review delves into the realm of green supply chain management, covering topics, such as carbon cap and trade, carbon offsets, renewable energy, regulations, finance, and vendor selection. Key findings from this review highlighted the limited number and lack of depth of studies regarding the presence and impact of electrical vendors, who play a crucial role in the oil and gas sector. Furthermore, our review identified a general lack of research on green supply chain management metrics, particularly in the context of the oil and gas industry and the roles and technical contributions of electric vendors.
Symmetric Seasonality of Time Series in Interval Prediction for Financial Management of the Branch
Authors: Nikulchev Evgeny , Chervyakov Alexander
Published: November 2023

The paper examines the task of managing the finances of a company with branches when funds are saved on the central company account, from which payments for the expenses of the branches are made. The dynamics of these expenses may have similar dynamics, which makes it possible to build a single model for the entire group. This article is devoted to the construction of theoretical concepts of the nonlinear dynamics approach and the formalization of criteria for combining time series into a single model. We introduce the concept of series with the same type of symmetrical seasonality, based on phase portraits, which allows formalizing the similarity criterion based on symmetry transformations. Considering time series that are recognized as similar, we bypass nonstationarity by considering the series included in the group as realizations of a random process. Finally, the use of new concepts allows solving an important practical problem, reducing the analysis to grouping by seasonal similarity and statistical characteristics of deviations when symmetry transformations are violated.
Symmetry in Safety and Disaster Prevention Engineering
Authors: Yang Yang
Published: November 2023

Due to the in-depth, yet incomplete, research on urban construction in many cities and towns, and the lack of considerations of symmetry, the rapid development of urban construction has led to a variety of urban disasters [...]
Research on Trusted Management of Industrial Internet Identity Analysis Data Based on Blockchain
Authors: Qi Zhibo , Huang Tao , Zhang Boyang , Li Yue , Zhang Xin
Published: November 2023

As an important part of the industrial internet, identity analysis data are growing with the expansion of the field involved in the industrial internet. The management of industrial internet identity analysis data faces many problems, such as complex types, a wide range of information, rapid growth, reduced security, etc. In view of the above problems, a trusted management model of industrial internet identity analysis data based on blockchain is first designed. Meanwhile, the identity analysis data information is analyzed and classified, and industrial data are divided into three levels according to the degree of privacy for hierarchical encryption. Secondly, the “on-chain + off-chain” storage model combining the blockchain main-slave chain and the off-chain database is designed to improve the efficiency of the whole model. Then, a collaborative consensus mechanism suitable for the main-slave multi-chain of the industrial internet is also designed, including slave-chain CIPBFT consensus, inter-chain cross-chain transmission protocol and main chain KZKP consensus. Finally, a prototype system is built to analyze the correctness, security, scalability and consensus efficiency of the model proposed in this study. The results show that the model proposed in this study can be applied to trusted management of data information for industrial internet identity analysis, and also provides an optimized solution for the same problem in fields of the industrial internet.
A New Effective Jackknifing Estimator in the Negative Binomial Regression Model
Authors: Koç Tuba , Koç Haydar
Published: November 2023

The negative binomial regression model is a widely adopted approach when dealing with dependent variables that consist of non-negative integers or counts. This model serves as an alternative regression technique for addressing issues related to overdispersion in count data. Typically, the maximum likelihood estimator is employed to estimate the parameters of the negative binomial regression model. However, the maximum likelihood estimator can be highly sensitive to multicollinearity, leading to unreliable results. To eliminate the adverse effects of multicollinearity in the negative binomial regression model, we propose the use of a jackknife version of the Kibria–Lukman estimator. In this study, we conducted a theoretical comparison between the proposed jackknife Kibria–Lukman negative binomial regression estimator and several existing estimators documented in the literature. To assess the performance of the proposed estimator, we conducted two simulation studies and performed a real data application. The results from both the simulation studies and the real data application consistently demonstrated that the proposed jackknife Kibria–Lukman negative binomial regression estimator outperforms other estimators.