bluuebunny/crossref_metadata_2025 huggingface dataset:
Triplet-Metric-Guided Multi-Scale Attention for Remote Sensing Image Scene Classification with a Convolutional Neural Network
Authors: Wang Hong , Gao Kun , Min Lei , Mao Yuxuan , Zhang Xiaodian , Wang Junwei , Hu Zibo , Liu Yutong
Published: June 2022

Remote sensing image scene classification (RSISC) plays a vital role in remote sensing applications. Recent methods based on convolutional neural networks (CNNs) have driven the development of RSISC. However, these approaches are not adequate considering the contributions of different features to the global decision. In this paper, triplet-metric-guided multi-scale attention (TMGMA) is proposed to enhance task-related salient features and suppress task-unrelated salient and redundant features. Firstly, we design the multi-scale attention module (MAM) guided by multi-scale feature maps to adaptively emphasize salient features and simultaneously fuse multi-scale and contextual information. Secondly, to capture task-related salient features, we use the triplet metric (TM) to optimize the learning of MAM under the constraint that the distance of the negative pair is supposed to be larger than the distance of the positive pair. Notably, the MAM and TM collaboration can enforce learning a more discriminative model. As such, our TMGMA can avoid the classification confusion caused by only using the attention mechanism and the excessive correction of features caused by only using the metric learning. Extensive experiments demonstrate that our TMGMA outperforms the ResNet50 baseline by 0.47% on the UC Merced, 1.46% on the AID, and 1.55% on the NWPU-RESISC45 dataset, respectively, and achieves performance that is competitive with other state-of-the-art methods.
Examining Impact of Speed Recommendation Algorithm Operating in Autonomous Road Signs on Minimum Distance between Vehicles
Authors: Sroczyński Andrzej , Kurowski Adam , Zaporowski Szymon , Czyżewski Andrzej
Published: June 2022

An approach to a new kind of recommendation system design that suggests safe speed on the road is presented. Real data obtained on roads were used for the simulations. As part of a project related to autonomous road sign development, a number of measurements were carried out on both local roads and expressways. A speed recommendation model was created based on gathered traffic data employing the traffic simulator. Depending on the traffic volume and atmospheric conditions prevailing on the road, as well as the surface conditions, the proposed system recommends the safe speed for passing vehicles by influencing the distance from the preceding vehicle to prevent collisions. The observed effect of the system application was an increase in the minimal distance between vehicles in most simulations.
Shifts in Salt Marsh Vegetation Landcover after Debris Flow Deposition
Authors: Silva Germán D. , Roberts Dar A. , McFadden Joseph P. , King Jennifer Y.
Published: June 2022

On 9 January 2018, Carpinteria Salt Marsh Reserve received a large quantity of sediment following debris flows in Montecito, California. Because disturbances potentially impact the ecosystem services and functions that wetlands provide, an understanding of how the ecosystem responded to the debris flows is important for the management of salt marsh systems. However, a lack of field data before and after this disturbance makes this task impossible to complete by field methods alone. To address this gap, we used Sentinel-2 satellite imagery to calculate landcover fractions and spectral indices to produce maps of landcover before, during, and after the debris flow using a random forest classifier. Change detection showed that vegetation extent in November 2020 approached pre-debris flow conditions. While total vegetated area experienced little net change (0.15% decrease), there was a measurable change in the areal extent of vegetation type, with high marsh vegetation transitioning to mid marsh vegetation in regions that initially showed an increase in bare soil cover. These results are uniquely quantifiable using remote sensing techniques and show that disturbance due to debris flows may affect ecosystem function via plant community change. These impacts will need to be taken into consideration when managing wetlands prone to depositional events.
Combining Multichannel RSSI and Vision with Artificial Neural Networks to Improve BLE Trilateration
Authors: Naghdi Sharareh , O’Keefe Kyle
Published: June 2022

The demands for accurate positioning and navigation applications in complex indoor environments such as emergency call positioning, fire-fighting services, and rescue operations are increasing continuously. Indoor positioning approaches apply different types of sensors to increase the accuracy of the user’s position. Among these technologies, Bluetooth Low Energy (BLE) appeared as a popular alternative due to its low cost and energy efficiency. However, BLE faces challenges related to Received Signal Strength Indicator (RSSI) fluctuations caused by human body shadowing. This work presents a method to compensate RSSI values by applying Artificial Neural Network (ANN) algorithms to RSSI measurements from three BLE advertising channels and a wearable camera as an additional source of information for the presence or absence of human obstacles. The resulting improved RSSI values are then converted into ranges using path loss models, and trilateration is applied to obtain indoor localization. The proposed artificial system provides significantly better localization solutions than fingerprinting or trilateration using uncorrected RSSI values.
An Integrated INS/LiDAR SLAM Navigation System for GNSS-Challenging Environments
Authors: Abdelaziz Nader , El-Rabbany Ahmed
Published: June 2022

Traditional navigation systems rely on GNSS/inertial navigation system (INS) integration, in which the INS can provide reliable positioning during short GNSS outages. However, if the GNSS outage persists for prolonged periods of time, the performance of the system will be solely dependent on the INS, which can lead to a significant drift over time. As a result, the need to integrate additional onboard sensors is essential. This study proposes a robust loosely coupled (LC) integration between the INS and LiDAR simultaneous mapping and localization (SLAM) using an extended Kalman filter (EKF). The proposed integrated navigation system was tested for three different driving scenarios and environments using the raw KITTI dataset. The first scenario used the KITTI residential datasets, totaling 48 min, while the second case study considered the KITTI highway datasets, totaling 7 min. For both case studies, a complete absence of the GNSS signal was assumed for the whole trajectory of the vehicle in all drives. In contrast, the third case study considered the use of minimal assistance from GNSS, which mimics the intermittent receipt and loss of GNSS signals for different driving environments. The positioning results of the proposed INS/LiDAR SLAM integrated system outperformed the performance of the INS for the residential datasets with an average reduction in the root mean square error (RMSE) in the horizontal and up directions of 88% and 32%, respectively. For the highway datasets, the RMSE reductions were 70% and 0.2% for the horizontal and up directions, respectively.
Effect of Triclosan and Silver Nanoparticles on DNA Damage Investigated with DNA-Based Biosensor
Authors: Blaškovičová Jana , Labuda Ján
Published: June 2022

Triclosan (TCS) is a broad-spectrum antimicrobial agent widely used in personal care, healthcare, and clinical practice. One of the most important aspects of toxicological profiling of compounds is their interaction with DNA. In human cells, TCS causes a significant reduction in DNA methylation. The involvement of TCS in chromosomal aberrations, DNA damage, and strand breaks, as well as DNA damage from TCS degradation products, was reported. AgNPs share similarities with TCS in terms of antimicrobial properties, enter the body after exposure, and are used even together with TCS in oral care products. Therefore, their mutual effect on the DNA is of interest. In this study, the electrochemical behavior of TCS on a glassy carbon electrode (GCE) and the biosensor with salmon sperm dsDNA (DNA/GCE), DNA damage by TCS present in phosphate buffer solution pH 7.4 and an additional effect of the immobilized AgNP layer on such DNA damage have been investigated. Two different sizes of AgNPs (about 15 and 37 nm) were tested. Using square-wave voltammetric signals of nucleobases, the portion of survived DNA was 64% in the presence of 15 nm AgNPs compared to 55% in its absence. The protective effect of AgNPs on DNA against TCS-induced DNA damage was found.
Deterioration of Electrical Load Forecasting Models in a Smart Grid Environment
Authors: Azeem Abdul , Ismail Idris , Jameel Syed Muslim , Romlie Fakhizan , Danyaro Kamaluddeen Usman , Shukla Saurabh
Published: June 2022

Smart Grid (S.G.) is a digitally enabled power grid with an automatic capability to control electricity and information between utility and consumer. S.G. data streams are heterogenous and possess a dynamic environment, whereas the existing machine learning methods are static and stand obsolete in such environments. Since these models cannot handle variations posed by S.G. and utilities with different generation modalities (D.G.M.), a model with adaptive features must comply with the requirements and fulfill the demand for new data, features, and modality. In this study, we considered two open sources and one real-world dataset and observed the behavior of ARIMA, ANN, and LSTM concerning changes in input parameters. It was found that no model observed the change in input parameters until it was manually introduced. It was observed that considered models experienced performance degradation and deterioration from 5 to 15% in terms of accuracy relating to parameter change. Therefore, to improve the model accuracy and adapt the parametric variations, which are dynamic in nature and evident in S.G. and D.G.M. environments. The study has proposed a novel adaptive framework to overcome the existing limitations in electrical load forecasting models.
Near-Infrared Spectroscopy as a Potential COVID-19 Early Detection Method: A Review and Future Perspective
Authors: Raypah Muna E. , Faris Asma Nadia , Mohd Azlan Mawaddah , Yusof Nik Yusnoraini , Suhailin Fariza Hanim , Shueb Rafidah Hanim , Ismail Irneza , Mustafa Fatin Hamimi
Published: June 2022

The coronavirus disease 2019 (COVID-19) pandemic is a worldwide health anxiety. The rapid dispersion of the infection globally results in unparalleled economic, social, and health impacts. The pathogen that causes COVID-19 is known as a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A fast and low-cost diagnosis method for COVID-19 disease can play an important role in controlling its proliferation. Near-infrared spectroscopy (NIRS) is a quick, non-destructive, non-invasive, and inexpensive technique for profiling the chemical and physical structures of a wide range of samples. Furthermore, the NIRS has the advantage of incorporating the internet of things (IoT) application for the effective control and treatment of the disease. In recent years, a significant advancement in instrumentation and spectral analysis methods has resulted in a remarkable impact on the NIRS applications, especially in the medical discipline. To date, NIRS has been applied as a technique for detecting various viruses including zika (ZIKV), chikungunya (CHIKV), influenza, hepatitis C, dengue (DENV), and human immunodeficiency (HIV). This review aims to outline some historical and contemporary applications of NIRS in virology and its merit as a novel diagnostic technique for SARS-CoV-2.
Deep Neural Networks Applied to Stock Market Sentiment Analysis
Authors: Correia Filipe , Madureira Ana Maria , Bernardino Jorge
Published: June 2022

The volume of data is growing exponentially and becoming more valuable to organizations that collect it, from e-commerce data, shipping, audio and video logs, text messages, internet search queries, stock market activity, financial transactions, the Internet of Things, and various other sources. The major challenges are related with the way to extract insights from such a rich data environment and whether Deep Learning can be successful with Big Data. To get some insight on these topics, social network data are employed as a case study on how sentiments can affect decisions in stock market environments. In this paper, we propose a generalized Deep Learning-based classification framework for Stock Market Sentiment Analysis. This work comprises the study, the development, and implementation of an automatic classification system based on Deep Learning and the validation of its adequacy and efficiency in any scenario, particularly Stock Market Sentiment Analysis. Distinct datasets and several Deep Learning approaches with different layers and embedded techniques are used, and their performances are evaluated. These developments show how Deep Learning reacts to distinct contexts. The results also give context on how different techniques with different parameter combinations react to certain types of data. Convolution obtained the best results when dealing with complex data inputs, and long short-term layers kept a memory of data, allowing inputs which are not as common to still be considered for decisions. The models that resulted from Stock Market Sentiment Analysis datasets were applied with some success to real-life problems. The best models reached accuracies of 73% in training and 69% in certain test datasets. In a simulation, a model was able to provide a Return on Investment of 4.4%. The results contribute to understanding how to process Big Data efficiently using Deep Learning and specialized hardware techniques.
HPLC-MS, GC and NMR Profiling of Bioactive Lipids of Human Milk and Milk of Dairy Animals (Cow, Sheep, Goat, Buffalo, Camel, Red Deer)
Authors: Lagutin Kirill , MacKenzie Andrew , Bloor Stephen , Scott Dawn , Vyssotski Mikhail
Published: June 2022

For non-bovine milks, information regarding bioactive lipids is fragmented, unreliable or unavailable. The purpose of the current study was to analyse bioactive lipids in the milk of dairy animals using modern analytical methods to achieve the most reliable results. Bioactive lipids in human milk were also analysed and used as a reference. A suite of modern analytical methods was employed, namely High Performance Liquid Chromatography-Mass Spectrometry (HPLC-MS), Gas Chromatography (GC) and Nuclear Magnetic Resonance (NMR). The total lipid content was determined, and phospholipid, fatty acid, neutral glycosphingolipids and ganglioside (GM3 and GD3) levels were measured. Lipid classes in selected milks were reliably characterised for the first time, including gangliosides in deer, camel and sheep; cerebrosides in deer, camel and buffalo; plasmalogens in deer, buffalo and goat and phospholipids in deer. Our study demonstrated the advantage of utilising a range of analytical techniques in order to characterise a diverse set of bioactive lipids.
Podcasting: The Radio of Generation Z in Spain
Authors: Galán-Arribas Rafael , Herrero-Gutiérrez Francisco-Javier , Frutos-Esteban Francisco-Javier
Published: June 2022

The fact that traditional radio is synchronous and unidirectional, with little or no room for interaction and content selection, is one of the main reasons why young people have turned their backs on it. In retrospect, conventional radio never cared for the younger generation, never designing strategies to bring them in. As a result, radio lost its relevance and it does not feature as part of young people’s digital diet. Over the last year, the number of podcast consumers has steadily increased, which is causing this format to become more and more cemented in society. It could be a way to gain younger listeners, an opportunity not to be missed by the radio industry. In the past, young people continued to listen to the radio as they got older, but that is no longer the case nor is radio seen as the go-to resource for new musical content. The challenge for radio is clear: regaining its influence through proposals with added value to differentiate itself from global platforms. In order to carry out this research, a total of 410 young university students were surveyed. The results show what the current picture is in such a changing atmosphere. It has been observed that this audience bases their audio consumption on personal preferences, they mainly access it via social media and they would find it useful and interesting to create their own podcast. This paper includes a podcast where academic experts and audio professionals, interviewed for the doctoral thesis “xxx (anonymity for review)”, reflect on the strategies that radio should adopt in order to gain young listeners.
Hannah’s Suffering: The Power of Voice
Authors: House-Niamke Stephanie M.
Published: June 2022

Hannah’s story in the Old Testament has been written about considerably by Jewish feminists, womanist theologians, and other biblical scholars. This paper strives to build upon these works in asking the reader to consider Hannah’s story from a liberatory theological theory of suffering by Sölle, as well as a postmodern and non-religious lens as discussed by Sandoval’s Theory of Oppositional Consciousness in Methodology of the Oppressed and Lorde’s “Transformation of Silence into Language and Action”. This paper asks if this narrative can serve as an example of taking back one’s power by confronting a complex system of power and oppression for Black women. Intercessory prayer aptly defines the personal as political, especially with the multiple minoritized identities of Hannah. I argue that Hannah’s story can serve as a complex narrative of differential consciousness and the reclamation of one’s own power, by using her voice. Her audacity to correct a prophet, fight for her valid desire of motherhood, and determine her own happiness is evidence of an empowerment ethic that is necessary for minoritized women in a post-modern era and political climate where the erasure of all forms of difference and consciousness is the priority.
Criminal Legal Systems and the Disability Community: An Overview
Authors: Leotti Sandra M. , Slayter Elspeth
Published: June 2022

While the scale and scope of the criminal legal system is often discussed with attention to racial disproportionalities, the fact that disabled people are overrepresented at all points in the system is less discussed by social workers. Disabled people come into contact with the criminal legal system as suspects, defendants, incarcerated persons, victims, and witnesses. Compared to people without disabilities, disabled people are more likely to experience victimization, be arrested, be charged with a crime, and serve longer prison sentences once convicted. These trends are even more profound for disabled people with intersecting marginalized identities, such as people of color, women, poor people, and those who identify as LGBTQ. This article provides an overview of the connections between disability, law enforcement, and practices of imprisonment in the United States. We provide a historical overview of the involvement of disabled people in the criminal legal system, review the prevalence of disability in the criminal legal system, and then discuss the unique ways in which disabled people are impacted by the criminal legal system. We conclude by providing recommendations for social work practice and advocacy based in disability justice.
Comparing the Effects of Class Origins versus Race in the Intergenerational Transmission of Poverty
Authors: Sakamoto Arthur , Hsu Li , Jalufka Mary E.
Published: June 2022

Building upon prior research on intergenerational income mobility, we assess class effects versus racial effects on the probability of becoming a poor adult, broken down by gender. We define the class effect (for each race-and-gender group) as the difference between the probability that a person who was born into the lowest income quintile becomes poor and the probability that a person who was born into the highest income quintile becomes poor. For each minority-by-gender group, using Whites as the baseline, the racial effect is defined as the average racial differential in the probability of becoming a poor adult, irrespective of class origins. The results indicate that, for all minority-by-gender groups, the class effect is larger than the racial effect. Our findings underscore the continuing significance of the comparatively large effects of class origins, which have not been adequately acknowledged in recent research.
Effects of the COVID-19 Pandemic on the Lives of Women with Different Socioeconomic Backgrounds and Victimization Experiences in Portugal
Authors: Teixeira Ana Lúcia , Cerejo Dalila , Rosa Maria do Rosário , Lisboa Manuel
Published: June 2022

The heavy economic, social, and psychological toll of pandemic lockdowns around the world and their disproportionate effect on women are widely acknowledged, but different socioeconomic backgrounds and contexts may influence the degree to which stay-at-home measures impact their lives. Additionally, knowing that violence against women tends to increase during times of crisis, we are testing if the additional burden of victimization represents an added load to the perceived social impacts of the lockdown. Using 2021 survey data from a random sample of 1541 Portuguese women, the paper explores, through logistic regression models, the social impact of the lockdown on the lives of women, its socioeconomic determinants, and the role played by violence against women during the pandemic. The results show that the COVID-19 pandemic lockdown did not equally affect all facets of women’s social lives, and women with higher education status and that experienced income reductions due to the measures taken to control the pandemic are more prone to experience a more severe negative impact of the lockdown on the various facets of their lives. Additionally, having been a victim during the pandemic partially mediates the effect of education and income reduction on the social outcomes of the lockdown.
Stubborn Exercise Responders–Where to Next?
Authors: Bell Leo R. , Gabbett Tim J. , Davis Gregory M. , Wallen Matthew P. , O’Brien Brendan J.
Published: June 2022

There is a wide variance in the magnitude of physiological adaptations after resistance or endurance training. The incidence of “non” or “poor” responders to training has been reported to represent as high as 40% of the project’s sample. However, the incidence of poor responders to training can be ameliorated with manipulation of either the training frequency, intensity, type and duration. Additionally, global non-response to cardio-respiratory fitness training is eliminated when evaluating several health measures beyond just the target variables as at least one or more measure improves. More research is required to determine if altering resistance training variables results in a more favourable response in individuals with an initial poor response to resistance training. Moreover, we recommend abandoning the term “poor” responders, as ultimately the magnitude of change in cardiorespiratory fitness in response to endurance training is similar in “poor” and “high” responders if the training frequency is subsequently increased. Therefore, we propose “stubborn” responders as a more appropriate term. Future research should focus on developing viable physiological and lifestyle screening tests that identify likely stubborn responders to conventional exercise training guidelines before the individual engages with training. Exerkines, DNA damage, metabolomic responses in blood, saliva and breath, gene sequence, gene expression and epigenetics are candidate biomarkers that warrant investigation into their relationship with trainability. Crucially, viable biomarker screening tests should show good construct validity to distinguish between different exercise loads, and possess excellent sensitivity and reliability. Furthermore “red flag” tests of likely poor responders to training should be practical to assess in clinical settings and be affordable and non-invasive. Early identification of stubborn responders would enable optimization of training programs from the onset of training to maintain exercise motivation and optimize the impact on training adaptations and health.
Error Analysis of Measuring the Diameter, Tree Height, and Volume of Standing Tree Using Electronic Theodolite
Authors: Yao Qing , Wang Jia , Zhang Junping , Xiong Nina
Published: June 2022

The ability to measure diameter, tree height, and tree volume is of great value in forestry investigations. These three factors are not considered together when error analyses of measurement results are conducted. The aim of this study was to quantify the system error analysis of the three factors mentioned above. Based on the principle of electronic theodolite non-destructive measurement of stem and error propagation theory, a mathematical model for calculating diameter, tree height, and volume error was derived to calculate the error in theoretical measurements. Moreover, a method utilizing F tests was proposed for analyzing the relative error based on the diameter, tree height, and volume factors. A total of 87 trees in Beijing were chosen as the experimental sample; the trees were divided into three sample groups according to size. The accuracy was assessed using the traditional method. The results showed that the error varied slightly with the size of the tree. The system error of the measured diameter was 0.44–0.59%; for tree height, this was 0.29–0.89%, and for the volume, it was 0.31–0.99%. There were no significant differences between the measured values and the true values of the resolved wood. The relative mean errors of volume, tree height, and diameter in practice were 4.47%, 1.18%, and 2.02%, respectively. The results suggest that the precision in electronic theodolite measurements in China is much higher than the accuracy requirement of relative error not exceeding 3–5%.
A Study on Sustainable Entrepreneurial Behavior in China from Multiple Perspectives
Authors: Yang Jiaqi , Ai Jun , Fan Linjie
Published: June 2022

Sustainable entrepreneurship is an economic activity that integrates entrepreneurial activities with environmental and social sustainability, which is a frontier research field that integrates the triple bottom line of economy, environment, and society. A comprehensive survey was conducted in this study by collecting data from 203 potential entrepreneurs in China, such as employees with work experience, freelancers, and college students, by means of a questionnaire in March 2022. Structural equation modeling (SEM) was employed to investigate the research hypotheses considered, testing the impact of entrepreneurial intention on sustainable entrepreneurial behavior from the perspective of risk perception and institutional environment. The reliability and validity of the measurements are demonstrated. The outcomes from the conducted analyses show that entrepreneurial intention and risk perception do not directly affect sustainable entrepreneurial behavior, while entrepreneurial intention significantly affects risk perception. Moreover, risk perception serves a mediating role in the relationship between entrepreneurial intention and sustainable entrepreneurship. The institutional environment positively predicts sustainable entrepreneurship behavior and could even have a greater effect by reducing risk perception. Hence, this study suggests that the government should provide policy and financial support to create an open, stable, and inclusive institutional environment, to reduce the cost and risk of innovation and entrepreneurship. At the same time, it also provides theoretical and practical references for potential entrepreneurs to improve their entrepreneurial intention and carry out sustainable entrepreneurial behavior.
Water Security in the Anthropocene: A Dialectical Water–Man Interaction Model
Authors: Ganoulis Jacques
Published: June 2022

The impacts of human activities have been detected in geological strata by rock radiometry and fossil recognition. They represent the timeline of Man–Nature interaction in different periods of climate change over a long duration. A notable exception is the human footprint during the industrial period, starting in the 18th century. Due to the severity of human impact during the last few decades, some scientists have suggested calling this era the “Anthropocene”. One of the main challenges in the Anthropocene is to achieve water security with innovative approaches aiming to improve natural water resources management, policy, and governance. In this paper, it is suggested to reformulate the Water–Man interaction as the union of two opposites: conflict and cooperation. Their dialectical unification by conflict resolution leads to a new model of water resources management and policy that can initiate a harmonious symbiosis between Man and nature, minimize externalities, and increase water resilience.
Perception of Cultured Meat as a Basis for Market Segmentation: Empirical Findings from Croatian Study
Authors: Faletar Ivica , Cerjak Marija
Published: June 2022

Many studies have already addressed the perception of cultured meat, but the segmentation of potential consumers has not been adequately investigated. Based on an online survey in Croatia with 411 valid responses, four socio-demographically characterized segments were identified. The key differentiators between the segments relate to consumers’ moral and ethical concerns about cultured meat and their perceptions of the impact of cultured meat production on the economy. The multinomial logistic regression used to describe the segments found that the segments differed from the reference segment (Concerned) in terms of support for public research and funding of cultured meat, the willingness to consume it, and religiosity. These results help provide deeper insight into the profiles of potential consumers of cultured meat.
A Taxonomy of Social-Network-Utilization Strategies for Emerging High-Technology Firms
Authors: Riverola Carla , Dedehayir Ozgur , Miralles Francesc
Published: June 2022

Lack of network transparency limits entrepreneurs’ effective utilization of their networks for resource acquisition. Virtual platforms (e.g., SNS-Social Networking Sites) have the potential to leverage entrepreneurial networks. The purpose of this study is to understand why and how technology-based entrepreneurs use social media to effectively access resources and, in turn, shed light on how they overcome network transparency in the early stages of their new venture formation process. Through in-depth interviews with the (co-) founders of 18 technology-based start-ups, this work reports a four-way taxonomy of strategic use of SNS. This research provides new theoretical insights for the technoentrepreneurship literature and reports practical insights for entrepreneurs on how to use social media effectively. Furthermore, this work is a guide for future research looking at digital literacy in entrepreneurship.
Individual Social Capital and Community Participation: An Empirical Analysis of Guangzhou, China
Authors: Fu Tianlan , Mao Sanqin
Published: June 2022

A social capital framework has been widely adopted to interpret participatory behaviors. While there is substantial literature regarding the effects of community-based social capital on grassroots participation, less attention has been paid to the relationship between different sources of social capital and community participation. This is particularly relevant for understanding community development undergone restructuring of individual social capital, such as China. To address this deficiency in the literature, this paper integrates both individual and social capital that is accessed within and outside a community to analyze their relation to different forms of community participation. Multilevel analysis is based on a large-scale community survey conducted in Guangzhou at the end of 2012. The results reveal a shift in social relations such that personal social resources are now mainly accessed outside the community. They further reveal that social resources outside communities are consistently and significantly related to all forms of participation. This implies that although residents’ personal networks have gradually diffused out of their communities, this has not only not reduced their enthusiasm toward the communities themselves but also facilitated participation in community affairs.
Consequences and Challenges of the Fourth Industrial Revolution and the Impact on the Development of Employability Skills
Authors: Bikse Veronika , Grinevica Liva , Rivza Baiba , Rivza Peteris
Published: June 2022

The aim of this research study is to perform an analysis of the consequences and impact of the fourth industrial revolution on the development of employability skills and to identify possible solutions to help overcome these challenges. The research methodology applied in this research study involves examining and analysing literature and Internet sources. To identify possible solutions for the development of employability skills in the context of challenges of the fourth industrial revolution, the Analytic Hierarchy Process (AHP) was used. The results of the research indicate that the promotion of youth employability requires close cooperation between educational institutions and entrepreneurs, as well as that significant attention should be paid to investment in human capital and the digital transformation of business. The research expands and provides insights into the situation in Latvia regarding the impact of the fourth industrial revolution on the development of employability skills and performed an analysis of the main possible solutions for the successful development of employability skills in Latvia that can be ensured by investing in human capital and improving the business environment, the digital transformation of SMEs and the modernization of the education system. In this context, it is crucial to promote more collaboration among educators, academics, policymakers, and practitioners.
Centrifuge Modeling of Chloride Ions Completely Breakthrough Kaolin Clay Liner
Authors: Zeng Xing , Su Jia , Wang Hengyu , Gao Tong
Published: June 2022

The 2 m thick compacted clay liner with a permeability coefficient of 1 × 10−7 cm/s is required in the Chinese technical specifications about landfills. The processes of chloride ion completely breakthrough low permeability barriers (k ≤ 1 × 10−7 cm/s) were modeled at 50 g in a geo-centrifuge. A measuring system was used to monitor solute velocity and conductivity. The entire process of chloride ion completely breaking through 2 m Kaolin clay liner was modeled successfully, which provided a valuable testing technology for centrifuge modeling of contaminant transport through low-permeable clay. The analyses results indicated the breakthrough time of conservative pollutant for the 2 m clay liner with a hydraulic conductivity of 1.0 × 10−9 m/s under Δhw of 40 m was 1.6 years. As for strongly adsorptive pollutants, the breakthrough time t0.1 increased by 9 times when Rd increased from 1 to 10, which indicates that the effect of Rd on the performance of the liner was significant.
Response of Runoff to Meteorological Factors Based on Time-Varying Parameter Vector Autoregressive Model with Stochastic Volatility in Arid and Semi-Arid Area of Weihe River Basin
Authors: Zeng Wenying , Song Songbai , Kang Yan , Gao Xuan , Ma Rui
Published: June 2022

This study explores the response characteristics of runoff to the variability of meteorological factors. A modified vector autoregressive (VAR) model is proposed by combining time-varying parameters (TVP) and stochastic volatility (SV). Markov chain Monte Carlo (MCMC) is used to estimate parameters. The TVP-SV-VAR model of daily runoff response to the variability of meteorological factors is established and applied to the daily runoff series from the Linjiacun hydrological station, Shaanxi Province, China. It is found that the posterior estimates of the stochastic volatility of the four variables fluctuate significantly with time, and the variance fluctuations of runoff and precipitation have strong synchronicity. The simultaneous impact of precipitation and evaporation on the pulse of runoff is close to 0. Runoff has a positive impulse response to precipitation, which decreases as the lag time increases, and a negative impulse response to temperature and evaporation with fluctuation. The response speed is precipitation > evaporation > temperature. The TVP-SV-VAR model avoids the hypothesis of homoscedasticity of variance and allows the variance to be randomly variable, which significantly improves the analysis performance. It provides theoretical support for the study of runoff response and water resource management under the conditions of climate change.
Mg-Al Layered Double Hydroxide Doped Activated Carbon Composites for Phosphate Removal from Synthetic Water: Adsorption and Thermodynamics Studies
Authors: Khalil Abdelrahman K. A. , Dweiri Fikri , Almanassra Ismail W. , Chatla Anjaneyulu , Atieh Muataz Ali
Published: June 2022

Increased phosphate concentration in water bodies has led to eutrophication, and its removal is an inevitable requirement of sustainable wastewater purification systems. In this study, MgAl layered doubled hydroxide (LDH) composites doped on the surface of activated carbon (AC/MgAl LDH) with various (Mg + Al) total metal loading (5 wt%, 10 wt%, and 15 wt%) were prepared by the co-precipitation method. The influence of (Mg + Al) total metal loading onto AC was examined to remove phosphate ions from aqueous solutions. The effect of adsorption parameters, including adsorbent dosage, initial solution pH, initial phosphate concentration, contact time, and experiment temperature, were investigated via batch adsorption experiments. The adsorption results demonstrated that the phosphate adsorption capacity significantly improved with increasing the (Mg + Al) metal loading on the surface of AC. The maximum Langmuir phosphate adsorption capacity was 337.2 mg phosphate per gram of AC/MgAl-3 LDH composite (15 wt% Mg + Al) composite at pH ~6.3, 22 °C, and 1 g/L of adsorbent. The kinetic data were best fitted with the pseudo-second order model. The initial solution pH notably influenced the phosphate removal by AC/MgAl-3 LDH composite with a maximum removal at pH 2.3. According to the spent adsorbent characterization results, the dominant mechanisms of phosphate removal by AC/MgAl-3 LDH were electrostatic interactions, ion exchange, and inner-sphere complexation. The phosphate adsorption capacity was gradually increased with increasing the experiment temperature, suggesting an endothermic adsorption process. Overall, the AC/MgAl LDH composites pave the way for an effective strategy for phosphate removal from aqueous solutions.
An Experimental Study of Paddy Drainage Treatment by Zeolite and Effective Microorganisms (EM)
Authors: Wu Shuyu , Zhang Zhuangzhuang , Li Jiang , Wu Tianao , Jiao Xiyun
Published: June 2022

Eco-ditch systems have increasingly been designed and applied as a strategy to decrease the risks of water eutrophication and contamination pollution for sustainable agriculture. The main goal of this study was to evaluate the water quality of eco-ditch substrates amended with zeolite and Effective Microorganisms (EM), such as pH, dissolved oxygen concentration (DO), ammonium nitrogen concentration (NH4+-N), and nitrate nitrogen concentration (NO3−-N). Laboratory experiments were conducted with four single substrates (soil, none substrates, natural zeolite, and zeolite loaded with EM bacteria) and two mixed substrates (soil and varying proportions of the additives, 0, 5 and 15%, m/m). Results showed that the concentration of NH4+-N was decreased with the increasing rates of additives, and zeolite loaded with EM bacteria had the highest nitrogen removal rate (97.90%) under static experimental condition. The application rate of 15% zeolite loaded with EM bacteria on the eco-ditch exerted a better effect on NH4+-N and NO3−-N removal without pH reduction, decreased by 87.19% for NH4+-N and 30.33% for NO3−-N, respectively. Path analysis showed that zeolite addition had a rapid effect (path coefficient = −0.972) on free NH4+-N ions adsorption in early 1–3 days, then EM loaded at zeolite further decreased NH4+-N (path coefficient = −0.693) and NO3−-N (path coefficient = −0.334) via bacterial metabolism. Based on the results, the applications of natural zeolite and Effective Microorganisms (EM) at an appropriate rate (15%, m/m) can significantly improve water quality of paddy drainage via exerting effects on nitrogen removal.
The Seasonal Labor Hoarding in Tourist Enterprises—Choice or Necessity?
Authors: Radlińska Kamila , Gardziejewska Bogusława
Published: June 2022

The seasonality of tourism demand is a natural condition for the functioning of tourist enterprises and affects the choice of employment practice. The aim of the research is to identify the practices of employing workers in tourism industry enterprises and try to understand the determinants of these decisions. The main research questions were what employment practices are used in tourist enterprises and how does the opinion on the condition of the local labor market influence this choice? It was assumed that, in the tourism industry, seasonal fluctuations can be treated the same way cyclical fluctuations are treated in the analysis of dynamic labor demand. The basis for the conclusions was the results of a survey conducted in the tourism industry enterprises in the seaside region of Poland. In the tourist region of the Polish Baltic Sea, 75.6% of tourist enterprises use the practice of total or partial labor hoarding, and 24.4% of enterprises do not use the practice of labor hoarding. They immediately adjust employment to seasonal changes in demand.
Optimization Design of Multi-Factor Combination for Power Generation from an Enhanced Geothermal System by Sensitivity Analysis and Orthogonal Test at Qiabuqia Geothermal Area
Authors: Zhao Yuan , Shu Lingfeng , Chen Shunyi , Zhao Jun , Guo Liangliang
Published: June 2022

In order to explore the optimal mining strategy of a fractured Enhanced Geothermal System (EGS) reservoir, we numerically investigated the influence of seven factors on heat production and conducted an optimization analysis of a multi-factor and multi-level combination by an orthogonal test based on the geological data at the Qiabuqia geothermal field. Seven factors were considered, including five reservoir factors (fracture spacing, fracture permeability, fracture permeability anisotropy, matrix permeability, and heat conductivity) and two operation factors (injected section length and injection rate). The results show that injection rate and fracture permeability have the greatest influence on production performance. Different factor combinations have a great influence on the productivity. The multi-factor and multi-level combination optimization is needed, and the optimization scheme of the EGS can be achieved through the orthogonal test and range analysis. The order of influence degree on the power generation is injection rate > fracture permeability > fracture permeability anisotropy > injected section length > matrix permeability > fracture spacing > heat conductivity. The order of influence degree on the coefficient of performance of the EGS is fracture permeability > injection rate > injected section length > fracture permeability anisotropy > matrix permeability > fracture spacing > heat conductivity. For reservoir stimulation, the stratum with dense natural fractures should be selected as the target EGS reservoir. It is not advisable to acidify the EGS reservoir too much to widen the apertures of the natural fractures. Fracture permeability anisotropy will increase pump energy consumption, but this adverse effect can be greatly reduced if the other parameters are well matched. Matrix permeability and heat conductivity may not be used as indicators in selecting a target reservoir. For project operation, the injected section length should be as long as possible. The injection rate plays a major role in all factors. Special attention should be paid to the value of the injection rate, which should not be too large. The appropriate injection temperature should be determined in accordance with the water source condition and the engineering requirement. If a commercial rate (100 kg/s) is to be obtained, the permeability of the reservoir fracture network needs to be stimulated to be higher. Meanwhile, in order to ensure that the production temperature is both high and stable, it is necessary to further increase the volume of the EGS reservoir.
A Survey of Experts’ Opinions on the Management of the Small Hive Beetle in Italy
Authors: Salvioni Cristina , Champetier Antoine
Published: June 2022

The exotic alien species Aethina tumida, commonly known as the small hive beetle (SHB), was first detected in the Italian region of Calabria in 2014. The SHB is endemic in sub-Saharan Africa and is established in North and Central America, Australia, and many other world regions. Little is known about the effects of SHB introduction in new regions. This article focuses on the economic and regulatory aspects of SHB invasions. It presents the results of a survey questionnaire administered to Italian bee experts and extension agents in the spring of 2019, which documents opinions about the SHB invasion and its management in Italy. The results show that the SHB and Varroa are perceived as major threats to bee health. Over half of respondents agree that SHB eradication is no longer an attainable policy objective in Calabria, and support a policy shift from eradication to control of SHBs. Among respondents, extension agents are the most likely to agree with the need for a policy adjustment. Additional scientific and economic evidence and analysis can help resolve the differences in the opinions of stakeholders about feasible or preferable management policies for the SHB, and crucially, ensure the participation of beekeepers in the surveillance and control efforts.
Preventing Household Food Waste in Italy: A Segmentation of the Population and Suggestions for Action
Authors: Annunziata Azzurra , Muca Francisco Luis , Mariani Angela
Published: June 2022

Household food waste represents one of the main challenges threatening the sustainability of modern food systems globally. As is widely recognised, a deeper understanding of wasteful behaviour profiles is the starting point of designing intervention strategies. The overall objective of this research is to explore the role of psychological factors that influence household wasteful food behaviour in Italy and to profile consumers with heterogeneous personal attitudes towards wasting food. Starting with data collected through a web-based survey realized on a sample of 530 individuals responsible for household shopping, a principal component analysis and a two-step cluster analysis revealed three different segments of consumers with heterogeneous wasteful behaviours. The clusters differ in relation to psychological factors, such as moral attitudes and concerns about and intentions to reduce food waste. The study findings provide insights for implementing prevention, reduction, and recovery strategies tailored to these different consumer profiles.