bluuebunny/crossref_metadata_2025 huggingface dataset:
A Shipborne Photon-Counting Lidar for Depth-Resolved Ocean Observation
Authors: Shen Xue , Kong Wei , Chen Peng , Chen Tao , Huang Genghua , Shu Rong
Published: July 2022

Depth-resolved information is essential for ocean research. For this study, we developed a shipborne photon-counting lidar for depth-resolved oceanic plankton observation. A pulsed fiber laser with frequency doubling to 532 nm acts as a light source, generating a single pulse at the micro-joule level with a pulse width of less than 1 ns. The receiver is capable of simultaneously detecting the elastic signal at two orthogonal polarization states, the Raman scattering from seawater, and the fluorescence signal from chlorophyll A. The data acquisition system utilizes the photon-counting technique to record each photon event, after which the backscattering signal intensity can be recovered by counting photons from multiple pulses. Benefitting from the immunity of this statistical detection method to the ringing effect of the detector and amplifier circuit, high-sensitivity and high-linearity backscatter signal measurements are realized. In this paper, we analyze and correct the after-pulse phenomenon of high-linearity signals through experiments and theoretical simulations. Through the after-pulse correction, the lidar attenuation coefficient retrieved from the corrected signal are in good agreement with the diffuse attenuation coefficients calculated from the in situ instrument, indicating the potential of this shipborne photon-counting lidar for ocean observation applications.
An Artificial Neural Network Algorithm to Retrieve Chlorophyll a for Northwest European Shelf Seas from Top of Atmosphere Ocean Colour Reflectance
Authors: Hadjal Madjid , Medina-Lopez Encarni , Ren Jinchang , Gallego Alejandro , McKee David
Published: July 2022

Chlorophyll-a (Chl) retrieval from ocean colour remote sensing is problematic for relatively turbid coastal waters due to the impact of non-algal materials on atmospheric correction and standard Chl algorithm performance. Artificial neural networks (NNs) provide an alternative approach for retrieval of Chl from space and results for northwest European shelf seas over the 2002–2020 period are shown. The NNs operate on 15 MODIS-Aqua visible and infrared bands and are tested using bottom of atmosphere (BOA), top of atmosphere (TOA) and Rayleigh corrected TOA reflectances (RC). In each case, a NN architecture consisting of 3 layers of 15 neurons improved performance and data availability compared to current state-of-the-art algorithms used in the region. The NN operating on TOA reflectance outperformed BOA and RC versions. By operating on TOA reflectance data, the NN approach overcomes the common but difficult problem of atmospheric correction in coastal waters. Moreover, the NN provides data for regions which other algorithms often mask out for turbid water or low zenith angle flags. A distinguishing feature of the NN approach is generation of associated product uncertainties based on multiple resampling of the training data set to produce a distribution of values for each pixel, and an example is shown for a coastal time series in the North Sea. The final output of the NN approach consists of a best-estimate image based on medians for each pixel, and a second image representing uncertainty based on standard deviation for each pixel, providing pixel-specific estimates of uncertainty in the final product.
VIGIA: A Thermal and Visible Imagery System to Track Volcanic Explosions
Authors: Vásconez Freddy , Moussallam Yves , Harris Andrew J. L. , Latchimy Thierry , Kelfoun Karim , Bontemps Martial , Macías Carlos , Hidalgo Silvana , Córdova Jorge , Battaglia Jean , Mejía Jessica , Arrais Santiago , Vélez Luis , Ramos Cristina
Published: July 2022

The monitoring of the frequency, intensity/magnitude and dynamics of explosive events at volcanoes in a state of unrest is key to surveying and forecasting their activity. Thermal and visual video observations of eruptive phenomena, and their correlation with data from deformation and seismic networks, are often limited by technical constraints including lack of time synchronisation, data volumes and power consumption. Several solutions are currently available and here we present an instrument designed for the permanent and real-time observation of volcanic explosive events in the visible and thermal infrared wavelengths, the output of which can be fully synchronised with ancillary monitoring data. Our system (VIGIA: visual and infrared ground-based imagery analyser) follows an edge computing approach whereby information is processed on-site, and periodic reports are sent to the local observatory and the system “decides” when to acquire high-temporal resolution data so as to capture key explosive events. As a permanent installation, VIGIA enables the continuous, long-term and time-synchronised observation of volcanic activity while reducing power consumption and data volumes. We suggest that VIGIA-style instruments could provide useful scientific and monitoring information, and provide here the key details of the components, assembly, and code so that observatories can replicate the system and build their own VIGIA at minimal cost. We use the Reventador volcano, in Ecuador, as a case study to present the capabilities of the instrument.
Online Hybrid Learning Methods for Real-Time Structural Health Monitoring Using Remote Sensing and Small Displacement Data
Authors: Entezami Alireza , Arslan Ali Nadir , De Michele Carlo , Behkamal Bahareh
Published: July 2022

Structural health monitoring (SHM) by using remote sensing and synthetic aperture radar (SAR) images is a promising approach to assessing the safety and the integrity of civil structures. Apart from this issue, artificial intelligence and machine learning have brought great opportunities to SHM by learning an automated computational model for damage detection. Accordingly, this article proposes online hybrid learning methods to firstly deal with some major challenges in data-driven SHM and secondly detect damage via small displacement data from SAR images in a real-time manner. The proposed methods contain three main parts: (i) data augmentation by Hamiltonian Monte Carlo and slice sampling for addressing the problem of small displacement data, (ii) data normalization by an online deep transfer learning algorithm for removing the effects of environmental and/or operational variability from augmented data, and (iii) feature classification via a scalar novelty score. The major contributions of this research include proposing two online hybrid unsupervised learning methods and providing effective frameworks for online damage detection. A small set of displacement samples extracted from SAR images of TerraSar-X regarding a long-term monitoring scheme of the Tadcaster Bridge in United Kingdom is applied to validate the proposed methods.
Five Guiding Principles to Make Jupyter Notebooks Fit for Earth Observation Data Education
Authors: Wagemann Julia , Fierli Federico , Mantovani Simone , Siemen Stephan , Seeger Bernhard , Bendix Jörg
Published: July 2022

There is a growing demand to train Earth Observation (EO) data users in how to access and use existing and upcoming data. A promising tool for data-related training is computational notebooks, which are interactive web applications that combine text, code and computational output. Here, we present the Learning Tool for Python (LTPy), which is a training course (based on Jupyter notebooks) on atmospheric composition data. LTPy consists of more than 70 notebooks and has taught over 1000 EO data users so far, whose feedback is overall positive. We adapted five guiding principles from different fields (mainly scientific computing and Jupyter notebook research) to make the Jupyter notebooks more educational and reusable. The Jupyter notebooks developed (i) follow the literate programming paradigm by a text/code ratio of 3, (ii) use instructional design elements to improve navigation and user experience, (iii) modularize functions to follow best practices for scientific computing, (iv) leverage the wider Jupyter ecosystem to make content accessible and (v) aim for being reproducible. We see two areas for future developments: first, to collect feedback and evaluate whether the instructional design elements proposed meet their objective; and second, to develop tools that automatize the implementation of best practices.
Investigation of the Removal of Several Micropollutants Presenting Different Ozone Reactivities from Natural Potable Water Matrix by the Application of Ozonation with the Use of SiO2 and Al2O3 as Catalysts
Authors: Psaltou Savvina , Kaprara Efthimia , Tsaragklis Apostolos , Mitrakas Manassis , Zouboulis Anastasios
Published: July 2022

The aim of this study was to investigate the correlation between solid materials and micropollutants, aiming to enhance the removal of the latter during the application of the ozonation process. For that purpose, two solid materials (SiO2 and Al2O3) presenting catalytic activity were used for the removal of eight micropollutants from natural potable water, containing them either separately or in a mixture, by ozonation. The studied micropollutants, presenting different physicochemical properties, are atrazine, ibuprofen, p-CBA (ozone-resistant compounds), benzotriazole, caffeine (with moderate ozone reactivity), carbamazepine, fluoxetine, paracetamol (easily oxidized by ozone). The residual concentrations of carbamazepine, paracetamol, and fluoxetine were found to be lower than 5.9 μg/L, 1.2 μg/L, and 15.5 μg/L, respectively, after 1 min of oxidation time in all studied systems. In contrast, benzotriazole and caffeine removal was enhanced by the addition of catalysts; in both cases the best catalyst was SiO2. Regarding the ozone-resistant compounds, both examined materials enhanced the removal of ibuprofen and p-CBA; however, the best was found to be SiO2 and Al2O3, respectively. In contrast, Al2O3 cannot be considered as an effective catalyst for the removal of atrazine, which presents chemical affinity only with SiO2 and for this reason it can be removed to a higher extent by its presence. Similar results were observed in the study of the mixture, although in this system, the residual concentration of all micropollutants was found to be under the detection limit after the application of catalytic ozonation.
Sex Education for Students with an Intellectual Disability: Teachers’ Experiences and Perspectives
Authors: Strnadová Iva , Loblinzk Julie , Danker Joanne
Published: July 2022

Background: Sex education assists students in the development of a healthy sexual identity and relationships. However, students with an intellectual disability tend to receive less holistic sex education as compared to students without a disability. In this inclusive study, we explored the perspectives of 10 high school teachers through interviews and focus groups on how students with an intellectual disability are informed about sexual relationships and prepared for their future life living with as much autonomy as possible, including living with a partner and becoming parents. Method: The interviews and focus groups were analysed using the inductive content analysis. Results: Data analysis revealed three themes: (a) sex education; (b) self-determination and self-advocacy skills; and (c) teachers’ concerns. Conclusions: Several recommendations are discussed. These include incorporating sexuality education-related goals in an Individualised Learning Plan (ILP); teachers adopting a rights-based approach and focusing on students’ self-determination, agency, and rights regarding sex education; and providing schools with necessary resources to teach sex education.
Robust Prediction of Shear Strength of SFRC Using Artificial Neural Networks
Authors: Odeh Ruba , Alawadi Roaa
Published: July 2022

The assessment of shear behavior in SFRC beams is a complex problem that depends on several parameters. This research aims to develop an artificial neural network (ANN) model that has six inputs nodes that represent the fiber volume (Vf), fiber factor (F), shear span to depth ratio (a/d), reinforcement ratio (ρ), effective depth (d), and concrete compressive strength (fc′) to predict shear capacity of steel fiber-reinforced concrete beams, using 241 data test gathered from previous researchers. The proposed ANN model provides a good implementation and superior accuracy for predicting shear strength compared to previous literature, with a Root Mean Square Error (RMSE) of 0.87, the average ratio (vtest/vpredicted) of 1.00, and the coefficient of variation of 22%. It was shown from parametric analysis the reinforcement ratio and shear span to depth ratio contributed the most impact on the shear strength. It can also be noticed that all parameters have a nearly linear impact on the shear strength except the shear span to depth ratio has an exponential effect.
Mismatch and Coupling: A Study on the Synergistic Development of Tourism-Economy-Ecology Systems in the Pearl River Delta
Authors: Tang Bo , Luo Hao
Published: July 2022

The integrated study of the tourism-economy-ecosystem plays a significant role in regional high-quality development. In this study, methods including the Spatial Mismatch Hypothesis (SMH), coupling coordination degree and a gravity model are adopted in combination to explore the evolution characteristics of the Tourism-Economy-Ecology (TEE) systems in the Pearl River Delta (PRD) from 2009 to 2019 from four perspectives: development level, spatial mismatch, coupling coordination and spatial mismatch-coupling coordination. The research results are presented as follows. Firstly, the overall development level of the three subsystems shows improvement, the overall pattern of tourism and economic development levels shows similarity, the polarization of tourism development reaches a relatively significant level, and the changes in the ecological subsystem are more significant than those in other subsystems. Secondly, the spatial mismatch direction and level of cities are relatively stable, and the mismatch index of high-grade cities varies considerably, while the tourism subsystem contributes significantly to the occurrence of spatial mismatch in the regional system. Thirdly, the coupling and coordination level of the system in the east is higher than in the west, with a vast majority of them in the state of near-mismatch, while the coupling and coordination state is more stable in most cities and tends to be coordinated. Guangzhou, Shenzhen and Foshan represent the crucial nodes of regional system coupling and coordination. The opening of high-speed railway lines enhances the connection between cities, and it remains necessary to enhance the coupling and coordination across various economic circles. Lastly, according to the comparison of spatial mismatch-coupling coordination linkage, these cities can be classified into three categories: prominent core cities, coordinating sub-cities, and potential peripheral cities. To be specific, Guangzhou and Shenzhen represent prominent core cities, Dongguan, Foshan and Huizhou represent coordinated secondary cities, and Zhuhai, Zhongshan, Jiangmen and Zhaoqing represent potential peripheral cities.
Towards Sustainable Internationalization of Higher Education: Innovative Marketing Strategies for International Student Recruitment
Authors: Hung Nguyen-Tan , Yen Kuo-Liang
Published: July 2022

Globalization and internationalization have received increasing attention from researchers in the field of education management over the past decade, who have found that internationalization is an indispensable component in the sustainable development of higher education (HE). This research aims to construct Innovative Marketing Strategies (IMS) for international student recruitment and contribute to the sustainable internationalization of higher education (IoHE). A literature review was used to construct an Innovative Marketing Strategies questionnaire. Data collected from 300 international students studying in Taiwan were used for a feasibility analysis in order to construct the final questionnaire, and survey data collected from 522 participants were used for more in-depth statistical analysis of the final strategies. The research results indicate that combining the marketing mix 4C with an innovative strategy (IS) approach provides sustainable recruitment marketing strategies toward higher education institution internationalization from a customer-oriented perspective. The IMS in this study includes 2 dimensions, 10 strategies, and 32 indicators. Additionally, a comprehensive analysis demonstrating the perspectives of international students with respect to the strategies was also conducted. This research contributes to the theoretical development and practical implementation of sustainable HE internationalization management. Discussions and recommendations based on the results of this study are also given.
Antibiotic-Resistant Gene Behavior in Constructed Wetlands Treating Sewage: A Critical Review
Authors: Monsalves Naomi , Leiva Ana María , Gómez Gloria , Vidal Gladys
Published: July 2022

The main objective of this review is to evaluate the performance of constructed wetlands (CWs) used to reduce antibiotic-resistant genes (ARGs) during sewage treatment. To accomplish this objective, statistical and correlation analyses were performed using published data to determine the influence of operational and design parameters on ARG reduction in CWs. The effects of design and operational parameters, such as different CW configurations, seasonality, monoculture and polyculture, support medium, and hydraulic retention time (HRT), on ARG removals, were analyzed. A comparison of ARG reduction under different CW configurations showed that the hybrid configuration of surface flow (SF)–vertical subsurface flow (VSSF) achieved the highest reductions, with values of 1.55 ulog. In this case, aeration is considered an important factor to reduce ARGs in CWs, and it should be considered in future studies. However, statistical analyses showed that the ARG reductions under different CW configurations were not significant (p > 0.05). The same behavior was observed when the effects of operational factors on ARG reductions were analyzed (p > 0.05). The results of this study show that CWs are not optimal technologies to reduce ARGs in sewage. The combination of CWs with advanced wastewater technologies can be a solution for enhancing ARG reduction and reducing the spread of antibiotic resistance.
Land Utilization, Landscape Pattern, and Ecological Efficiency: An Empirical Analysis of Discrimination and Overlap from Suining, China
Authors: Ge Xichen , Sun Liang , Chen Jiongzhen , Cai Shuangrong
Published: July 2022

The rapid urbanization in recent decades has highlighted the impact of rural land utilization, which further affects the spatial structure and efficiency of rural ecosystems. Optimizing the structure of urban green infrastructure is an effective way to alleviate the fragmentation of rural landscapes, coordinate the relationship between rural development and ecosystem services, and ensure sustainable rural development. The purpose of this paper is to provide a clear direction for the optimization of construction for the sustainable development of rural green infrastructure (RGI). This study provides a new method for RGI identification and analysis by taking Suining County, a typical rural area on the North China Plain, as an example. Morphological spatial pattern analysis (MSPA) was used to distinguish different space scenery elements in RGI and combine them with land utilization elements, so as to obtain two types of overlapping degree data in each village and town. We further combined the overlapping degree data with ecological efficiency indicators to evaluate the spatial structure construction priorities of different land use components in the RGI system. The results show that the MSPA and ecological efficiency analysis method proposed in this paper are conducive to qualitative and quantitative analysis of the relationship between land use type, spatial structure, and ecological efficiency in the RGI system and are suitable for the construction of a green infrastructure network. This method can be used to better understand the spatial distribution and priority of green infrastructure networks to achieve sustainable rural development on the North China Plain.
Phosphorus Sorption in Soils and Clay Fractions Developed from Different Parent Rocks in Limpopo Province, South Africa
Authors: Oyebanjo Omosalewa , Ekosse Georges-Ivo , Odiyo John
Published: July 2022

Phosphorus (P) sorption dynamics in soils have implications for the environment and soil fertility. Soils and clay fractions that were developed from basalt, granite, arkosic sandstone, and gneiss in Limpopo Province, South Africa were analysed for their P adsorption characteristics and external phosphorus requirements (EPR). The relationship between the P adsorption parameters and EPR of the soils and clay fractions were also assessed. The Langmuir adsorption isotherms for the soils and clay fractions gave a better fit with slightly higher R-square values relative to the Freundlich adsorption isotherms. The Langmuir P sorption maxima were between 285.71 and 833.33 mg/kg and 238.09 and 625.0 mg/kg for the soils and clay fractions, respectively, and the EPR values ranged from 7.78 to 92.91 mgP/kg and 5.13 to 65.85 mgP/kg for the soils and clay fractions, respectively. The variations in the EPR suggest a single, uniform P fertiliser application to the soils could cause under-fertilisation and over-fertilisation problems. The soils that were developed from basalt, relative to the others, showed no risk to the water quality in the region at the current rate of P fertiliser application. The P sorption parameters of the soils and clay fractions showed no statistically significant differences. Hence, the P sorption parameters of the clay fractions could be reliable predictors of the P sorption and buffering in their respective soils.
Implementation of the Global Reporting Initiative Social Sustainability Indicators: A Multi-Case Study Approach Using Brazilian Construction Companies
Authors: Passos Neto George , Kohlman Rabbani Emilia Rahnemay , Valdes-Vasquez Rodolfo , Alencar Luciana H.
Published: July 2022

This study aims to assess the applicability and adherence to social sustainability indicators by large and medium-sized construction companies in Pernambuco, Brazil. The study measures the importance and influence of these indicators in companies’ decision-making processes. The social indicators from the Global Reporting Initiative (GRI) were selected as they come from a globally recognized and widespread organization. The research focuses on nine companies by conducting semi-structured interviews, site visits, and data validation through observations. The results indicate that most of the indicators were considered to have a high level of importance. However, these indicators are not as influential in decision-making as their importance suggests they should be. Currently, only 26% of the indicators are being measured by the companies, covering only three of the 19 GRI categories. The categories reported are occupational safety and health, local communities, and customer privacy. Most companies would be able to report the other 16 categories with minimal additional effort. A prioritization matrix is presented according to the importance and influence of the indicators and the effort to implement them. Overall, this study reveals that companies could easily measure most social sustainability indicators, making it possible to implement more sustainable decisions with less effort.
The Construction and Application of E-Learning Curricula Evaluation Metrics for Competency-Based Teacher Professional Development
Authors: Chen Chun-Wei , Huang Neng-Tang , Hsiao Hsien-Sheng
Published: July 2022

Today, students at universities in advanced countries typically enroll in colleges, such as the College of Education, which offer interdisciplinary programs for undergraduates in their first and second years, allowing them to explore personal interests, experience educational research fields, complete their integrated curricula, and then choose a major in their third year. To cooperate with the government’s epidemic prevention policies and measures in the post-COVID-19 era, the trend of e-learning and distance teaching has accelerated the establishment of integrated online curricula with interdisciplinary programs for undergraduates in the College of Education to facilitate effective future teacher professional development (TPD). Therefore, it is very important to construct e-learning curricula evaluation metrics for competency-based teacher professional development (CB-TPD) and to implement them in teaching practice. This research used social network analysis (SNA) methods, approaches, and theoretical concepts, such as affiliation networks and bipartite graphs comprised of educational occupational titles and common professional competencies (i.e., Element Name and ID), as well as knowledge, skills, abilities, and other characteristics (KSAOs), from the U.S. occupational information network (O*NET) 26.1 OnLine database, to collect data on the occupations of educational professionals. This study also used Gephi network analysis and visualization software to carry out descriptive statistics of keyword co-occurrences to measure their centrality metrics, including weighted degree centrality, degree centrality, betweenness centrality, and closeness centrality, and to verify their importance and ranking in professional competency in eight categories of educational professionals (i.e., three categories of special education teachers and five categories of teachers, except special education). The analysis of the centrality metrics identified the educational common professional competency (ECPC) keyword co-occurrences, which were then used to design, develop, and apply e-learning curricula evaluation metrics for CB-TPD. The results of this study can be used as a reference for conducting related academic research and cultivating educational professionals’ online curricula, including ECPC keywords, integrated curricula design and the development of transdisciplinary programs, and teacher education, as well as to facilitate the construction and application of future e-learning curricula evaluation metrics for CB-TPD.
Sustainability Strategies and Contractual Arrangements in the Italian Pasta Supply Chain: An Analysis under the Neo Institutional Economics Lens
Authors: Ciliberti Stefano , Stanco Marcello , Frascarelli Angelo , Marotta Giuseppe , Martino Gaetano , Nazzaro Concetta
Published: July 2022

Contracts represent key governance mechanisms along the supply chain to pursue collective sustainable strategies in line with new citizen-consumers’ preferences for sustainable products. Adopting an embedded multiple case study approach, this paper explores and analyzes 11 cases of contractual relationships between Italian semolina and pasta producers and farmers in order to investigate whether sustainability strategies affect the design of contracts and the related consequences. Findings reveal that different sustainability strategies correspond to different design and combinations of (both monetary and nonmonetary) contractual incentives aimed to centralize property and decision rights. What emerges is that stronger sustainability strategies entail a higher degree of buyers’ control over strategic investments (such as land and seeds) as well as wider provision of technical assistance and knowledge and innovation transfer toward farmers. Therefore, mutual gains seem at stake, even if socio-economic implications of the shift in decisional and control rights from farmers toward buyers shall be neglected, to ensure a better coherence with the farm to fork strategy and sustainable development goals.
Long-Term Landscape Dynamics to Assess Land Degradation Hypotheses—An Exploratory Study of Evidence from Travelers’ Narrations
Authors: Detsis Vassilis , Gkadolou Eleni , Koutsovoulou Katerina , Tolias Georgios
Published: July 2022

The present study aims to provide a method for extending the scope of empirical landscape studies into the more distant past and to use it to contribute to the discourse on land degradation in the Mediterranean area. In many areas of the world, the lack of spatially explicit sources, such as historical land cover maps and cadasters, is an obstacle to extending the study of landscape dynamics in the past. Information mined from travelers’ texts can be used to overcome it. Landscape descriptions retrieved from W.M. Leake’s narration of his travels in Peloponnese, Greece, in 1805 and 1806, were georeferenced and used to test for the occurrence of land degradation by comparing historical to current landscapes. A widespread transition of natural vegetation to agricultural areas was found mostly in low altitudes. Limited rewilding occurred on steeper slopes. About a third of the historical Greek fir forests were degraded to open stands. A total of 40% of the locations covered by deciduous oak forests were converted to agricultural areas; most of the rest of these locations were converted to vegetation types characteristic of lower precipitation and soil fertility. Long-term dynamics can be efficiently assessed using narrations as a source of information. The comparison of early 19th century descriptions with the current condition suggests that limited land degradation did take place in the previous centuries in the study area.
CSVAG: Optimizing Vertical Handoff Using Hybrid Cuckoo Search and Genetic Algorithm-Based Approaches
Authors: Jha Keshav , Gupta Akhil , Alabdulatif Abdulatif , Tanwar Sudeep , Safirescu Calin Ovidiu , Mihaltan Traian Candin
Published: July 2022

One of the primary challenges that wireless technology in the present generation is facing is always best connected (ABC) service. This is possible only when the wireless overlay networks follow a cooperative and coordinated process. Vertical handoff is one such process. Concerning this process, the main challenge is to develop algorithms that take care of optimal connection management with proper resource utilization for uninterrupted mobility. In this paper, we develop a new hybrid cuckoo search (CS) and genetic algorithm (GA) that maximizes the performance of heterogeneous wireless systems in terms of minimizing latency, handover failure probability, and enhancing the throughput. We focus on an optimized simulation framework to demonstrate the advantage of our hybrid model. It can be discerned from the simulation analysis that the proposed hybrid technique increases throughput by 17% and 8% compared to the cuckoo search and genetic algorithms applied individually. The performance of the proposed scheme is promising for applications wherein the handoff mechanisms have to be optimized to control frequent handoffs to further reduce the power consumption of user equipment.
Multi-Task Conformer with Multi-Feature Combination for Speech Emotion Recognition
Authors: Seo Jiyoung , Lee Bowon
Published: July 2022

Along with automatic speech recognition, many researchers have been actively studying speech emotion recognition, since emotion information is as crucial as the textual information for effective interactions. Emotion can be divided into categorical emotion and dimensional emotion. Although categorical emotion is widely used, dimensional emotion, typically represented as arousal and valence, can provide more detailed information on the emotional states. Therefore, in this paper, we propose a Conformer-based model for arousal and valence recognition. Our model uses Conformer as an encoder, a fully connected layer as a decoder, and statistical pooling layers as a connector. In addition, we adopted multi-task learning and multi-feature combination, which showed a remarkable performance for speech emotion recognition and time-series analysis, respectively. The proposed model achieves a state-of-the-art recognition accuracy of 70.0 ± 1.5% for arousal in terms of unweighted accuracy on the IEMOCAP dataset.
Types of Maintenance Based on Uncertain Data Envelope Analysis
Authors: Lu Mengqiao , Li Shuyu , Wen Meilin
Published: July 2022

Nowadays, one of the main challenges of marine maintenance is how to select an optimum maintenance strategy for each component of the complex ship machinery system. The uncertainty of the parameters is one of the main difficulties encountered. For example, engineers and experts are always questioning the credibility and integrity of the data collected, and historical maintenance records may also be lost during maintenance. The above data asymmetry will also lead to parameter uncertainty, which directly affects the accuracy of the prediction results. This paper proposes a method for determining maintenance types of ship equipment based on uncertainty theory and the Data Envelopment Analysis (DEA) model. Firstly, this paper constructs an uncertain maintenance optimization model (UMOM) based on the classic Data Envelopment Analysis model. Then, we converted the UMOM into an equivalent deterministic model for easy calculation by the uncertainty theory. Finally, a case study is given to verify this model. The results will conclude that the UMOM can meet the need for a reasonable classification of maintenance types of mechanical equipment in a marine system and provide valuable information for systemic management and storage.
The Occurrence of Five Unregulated Mycotoxins Most Important for Traditional Dry-Cured Meat Products
Authors: Lešić Tina , Vulić Ana , Vahčić Nada , Šarkanj Bojan , Hengl Brigita , Kos Ivica , Polak Tomaž , Kudumija Nina , Pleadin Jelka
Published: July 2022

This study investigated the occurrence of 5 unregulated mycotoxins in a total of 250 traditional dry-cured meat products sampled in 2020 and 2021 in five Croatian regions (eastern, northern, central, western, and southern). Aflatoxin B1 (AFB1), ochratoxin A (OTA), sterigmatocystin (STC), citrinin (CIT), and cyclopiazonic acid (CPA) concentrations were related to the geographical region of the product’s origin and to local weather. The results revealed the contamination of 27% of samples, namely, STC in 4% of samples in concentrations of up to 3.93 µg/kg, OTA in 10% of samples in concentrations of up to 4.81 µg/kg, and CPA in 13% of samples in concentrations of up to 335.5 µg/kg. No AFB1 or CIT contamination was seen. Although no statistically significant differences in concentrations of individual mycotoxins across the production regions were found, differences in mycotoxin occurrence were revealed. The eastern and western regions, with moderate climate, delivered the largest number of contaminated samples, while the southern region, often compared with subtropics, delivered the smallest, so that the determined mycotoxins were probably mainly produced by the Penicillium rather than the Aspergillus species. Due to the interaction of various factors that may affect mycotoxin biosynthesis during production, the detected concentrations cannot be related solely to the weather.
Multiple Receptors Involved in Invasion and Neuropathogenicity of Canine Distemper Virus: A Review
Authors: Zhao Jianjun , Ren Yanrong
Published: July 2022

The canine distemper virus (CDV) is a morbillivirus that infects a broad range of terrestrial carnivores, predominantly canines, and is associated with high mortality. Similar to another morbillivirus, measles virus, which infects humans and nonhuman primates, CDV transmission from an infected host to a naïve host depends on two cellular receptors, namely, the signaling lymphocyte activation molecule (SLAM or CD150) and the adherens junction protein nectin-4 (also known as PVRL4). CDV can also invade the central nervous system by anterograde spread through olfactory nerves or in infected lymphocytes through the circulation, thus causing chronic progressive or relapsing demyelination of the brain. However, the absence of the two receptors in the white matter, primary cultured astrocytes, and neurons in the brain was recently demonstrated. Furthermore, a SLAM/nectin-4-blind recombinant CDV exhibits full cell-to-cell transmission in primary astrocytes. This strongly suggests the existence of a third CDV receptor expressed in neural cells, possibly glial cells. In this review, we summarize the recent progress in the study of CDV receptors, highlighting the unidentified glial receptor and its contribution to pathogenicity in the host nervous system. The reviewed studies focus on CDV neuropathogenesis, and neural receptors may provide promising directions for the treatment of neurological diseases caused by CDV. We also present an overview of other neurotropic viruses to promote further research and identification of CDV neural receptors.
Incidence and Characteristics of Adverse Events after COVID-19 Vaccination in a Population-Based Programme
Authors: Bonzano Laura , Djuric Olivera , Mancuso Pamela , Fares Lidia , Brancaccio Raffaele , Ottone Marta , Bisaccia Eufemia , Vicentini Massimo , Cocconcelli Alessia , Motolese Alfonso , Boyko Rostyslav , Giorgi Rossi Paolo , Motolese Alberico
Published: July 2022

Compliance with vaccination is linked to its safety. In Italy, a plan to identify people who could be at an increased risk of adverse events (AEs) was defined so they could be vaccinated in a protected setting. We conducted an audit to describe the process of AE risk assessment and occurrence in the Reggio Emilia Province in Italy in people who received any of the four COVID-19 vaccines currently used in Italy. Incidence of AEs was calculated by dose and type of vaccine and type of setting (standard vs. protected). After 182,056 first doses were administered, 521 (0.3%) AEs were reported. Most of the AEs were non-serious (91.4%) and non-allergic (92.7%). The percentage of AEs was similar in both settings: 0.3% in the standard setting and 0.2% in the protected setting. However, the incidence of AEs was higher among those who had an allergist visit than among those who did not (IR 666.7 vs. 124.9). All deaths (1.6/100.000) occurred in standard settings and after the Pfizer and Moderna vaccines. The incidence of AEs was lower after the second dose (IR 286.2 vs. 190.3), except for mRNA vaccines, for which it was higher after the second dose (IR 169.8 vs. 251.8). Although vaccination in a protected medical setting could reassure patients with a history of allergies to be vaccinated, allergy history and other anamnestic information is not useful in predicting the risk of COVID-19 vaccine-related AEs in the general population.
A Green Approach Based on Micro-X-ray Fluorescence for Arsenic, Micro- and Macronutrients Detection in Pteris vittata
Authors: Capobianco Giuseppe , Bonifazi Giuseppe , Serranti Silvia , Marabottini Rosita , Antenozio Maria Luisa , Cardarelli Maura , Brunetti Patrizia , Stazi Silvia Rita
Published: July 2022

In this study, benchtop micro-X-ray fluorescence spectrometry (µXRF) was evaluated as a green and cost-effective multielemental analytical technique for P. vittata. Here, we compare the arsenic (As) content values obtained from the same samples by µXRF and inductively coupled plasma-optical emissions spectrometry (ICP–OES). To obtain samples with different As concentrations, fronds at different growth time points were collected from P. vittata plants grown on two natural As-rich soils with either high or moderate As (750 and 58 mg/kg). Dried samples were evaluated using multielement-µXRF analysis and processed by PCA. The same samples were then analysed for multielement concentrations by ICP–OES. We show that As concentrations detected by ICP–OES, ranging from 0 to 3300 mg/kg, were comparable to those obtained by µXRF. Similar reliability was obtained for micro- and macronutrient concentrations. A positive correlation between As and potassium (K) contents and a negative correlation between As and iron (Fe), calcium (Ca) and manganese (Mn) contents were found at both high and moderate As. In conclusion, we demonstrate that this methodological approach based on μXRF analysis is suitable for monitoring the As and element contents in dried plant tissues without any chemical treatment of samples and that changes in most nutrient concentrations can be strictly related to the As content in plant tissue.
On the Use of Gridded Data Products for Trend Assessment and Aridity Classification in a Mediterranean Context: The Case of the Apulia Region
Authors: My Lorenzo , Di Bacco Mario , Scorzini Anna Rita
Published: July 2022

Large-scale gridded climatic data can be useful for the assessment of climate variability and change as a basis for understanding and monitoring natural hazards, as well as for determining appropriate coping strategies. However, an evaluation of the accuracy of these data products against local observational measurements over the different regions of the globe is always required, as these large-scale data may be affected by systematic errors, which can affect the results of downstream applications. Therefore, this study was carried out to evaluate the performances of two long-term gridded datasets in reproducing station-based precipitation and temperature data over the Apulia region (southern Italy) for the period 1956–2019, with a particular focus on the effect of using the different data sources on the results of trend analyses and aridity classification. The results revealed that the considered gridded data products allow only general indications on the spatial and temporal behavior of climatic variables over the Apulia region, especially in regard to precipitation data.
Groundwater Vulnerability to Pollution Assessment
Authors: Canora Filomena , Sdao Francesco
Published: July 2022

Water scarcity and pollution have arisen as global issues in the twenty-first century [...]
EV Senseless Orderly Charging Technology for High User Participation Rate in Residential Area
Authors: Yang Ye , Duan Wenjun , Wang Wen , Zhang Xiaoqing , Peng Xiaofeng , Han Qingwen , Li Yao , Li Shuaihua , Gao Shiqiao
Published: July 2022

Private cars are the most active and important incremental factor in the electric vehicle market and are expected to account for 80% of the new energy vehicle sales market by 2030. As the most common charging scenario for private cars, orderly charging in the community can optimize the distribution load curve by dynamically adjusting charging time and power of electric vehicles, so as to achieve peak-load shaving and turn electric vehicles into a friendly load to the distribution grid. However, after the traditional orderly charging strategy was released, the complexity of the operation on the user’s side was a heavy strike to the user’s willingness to participate in orderly charging, resulting in the quite low participation rate and insufficient demonstration of the characteristics of EV’s elastic power demand. To solve this issue, the paper proposes a senseless orderly charging strategy with user charging demand prediction and substation capacity constraint considered to minimize user charging fee or maximize service provider revenue. After a five-month practical application, the proposed strategy was found to effectively improve the user participation rate in orderly charging and to regulate electric vehicles as an elastic load to meet the grid demand.
FFAKTOR PREDISPOSISI SEBAGAI PENENTU KEPATUHAN TERHADAP PROTOKOL KESEHATAN PENCEGAHAN COVID-19 PADA SISWA SEKOLAH DASAR DI KOTA BANDUNG
Authors: Syarief Osman , Irmawartini Irmawartini , Rosmana Dadang
Published: July 2022

Penyakit Covid 19 merupakan penyakit saluran pernafasan akut yang parah. Penyakit Covid 19 sudah menyebar ke seluruh dunia termasuk Indonesia dan sudah menjadi pandemi. Perlu dilakukan uoaya pencegahan penularan untuk semua kelompok, termasuk siswa Sekolah Dasar (siswa SD). Patuh protokol kesehatan Covid 19 merupakan salah satu upaya pencegahan covid 19. Protokol kesehatan Covid 19 antara lain terdiri dari mencuci tangan pakai air mengalir dan sabun, memakai masker, menjaga jarak, menghindari kerumunan dan peningkatan daya tahan tubuh. Predisposisi merupakan salah satu faktor pembentukan perilaku termasuk perilaku patuh terhadap protokol kesehatan covid 19. Penelitian ini bertujuan untuk mengetahui hubungan faktor predisposisi dengan kepatuhan terhadap protokol kesehatan covid 19. Penelitian dilakukan secara crossectional. Sampel peneliitian adalah 441 siswa SD di Kota Bandung. Pengumpulan data dengan wawacancara. Data di analisis statistik univaribel, bivariabel dan multivariabel. Hasil penelitian menemukan bahwa siswa SD Kota Bandung yang patuh terhadap protokol kesehatan sebesar 54,0%. Faktor predisposisi yang berhubungan signifikan dengan kepatuhan terhadap prokotol kesehatan covid 19  adalah pengetahuan ( p =0,0001), sikap (p =0,003) dan keyakinan ( p =0,0001). Kesimpulan belum semua siswa SD di Kota Bandung patuh protokol kesehatan covid 19, sehingga berisiko untuk tertular covid 19 jika dilakukan pembelajaran tatap muka.
ESTIMATION OF MALONDIALDEHYDE LEVELS IN CANNED MILK, YOGHURT, AND CREAM IN BAGHDAD CITY AS AN OXIDATIVE FACTOR
Authors: Alkhatib Mussa M.
Published: July 2022

An investigation into the concentrations of Malondialdehyde (MDA) in milk, yogurt and cream from various Baghdad supermarkets was the goal of this study. The results of this study show that out of a total of 125 samples, 45 (36 %), 14 (11.2 %), and 17 (13.6 %) positive samples were randomly collected from milk, yogurt, and cream from various supermarkets. Al-Ghazaliya and Abu Ghraib were found to have a significant (p≤ 0.05) difference in the mean value of MDA in milk samples (3.8140.416 and 3.9311.422 μmol/l). Some samples, such as those from Yarmouk in yogurt andMansour, Al-Ghazaliya and Abu Ghraib in Cream samples, contained 7.322–2.311 μmol/l. Because of the importance of dairy products in human nutrition, this investigation is necessary. Infrequently, as a result of our import and the wide variety of sources from which it is derived. Mutagenic and cytotoxic effects on human health are possible side effects of MDA exposure
Exposição fetal à metanfetamina e à cocaína: efeitos cognitivo-comportamentais
Authors: Cardoso de Souza Custodio Juliana , D’Ávila Camargo Luísa , Ribeiro Cruz Pereira Luiza , Perini Zamprogno Nathália , Guilherme Bedim Trancoso Marcos , Da Silva Barreiros Amanda , Pirola Santos Luísa , Bubach Ribeiro Alves Catarina
Published: July 2022

Introdução. Os efeitos da exposição pré-natal à cocaína e à metanfetamina ainda são obscuros. Tal questão apresenta grande importância, visto que essas drogas são consumidas mundialmente. Objetivo. Identificar na literatura relacionada as principais consequências da exposição fetal à cocaína e à metanfetamina no desenvolvimento cognitivo e comportamental de pré-escolares. Método. Revisão da literatura realizada nas bases de dados Pubmed, Lilacs e na Biblioteca Virtual de Saúde (BVS), durante abril e maio de 2020, atualizada em abril de 2021. Em todas as bases, usou-se os descritores do DeCS “Methamphetamine”, “Cocaine”, “Pregnancy” e “Preschool”. No Pubmed, também se utilizou “Prenatal Exposure Delayed Effects” e “Learning Disabilities”. Na BVS e no Lilacs, acrescentou-se o termo “Cognitive development”. Os artigos foram filtrados com base no seu idioma de publicação, população, substância de estudo, título e resumo. Resultados. Na amostra inicial, havia 111 artigos, destes, 10 foram selecionados. Adicionou-se a esse quantitativo 15 estudos. Alguns autores apontaram que a exposição fetal aos entorpecentes pode gerar atividade neurológica anormal, defeitos na aquisição da linguagem, hiperatividade e TDAH, desinibição comportamental, déficits cognitivos, dificuldade de leitura, além de distúrbios de socialização, comportamento agressivo e problemas de externalização. Conclusão. Não há consenso no meio científico se a exposição pré-natal à cocaína e à metanfetamina prejudica de forma direta o desenvolvimento cognitivo e comportamental dos infantos. Contudo, alguns trabalhos reiteram que o uso desses entorpecentes durante a gestação pode acarretar diversos problemas na maturação fetal. O fato dessa temática ser pouco estudada ressalta a necessidade de novas pesquisas e trabalhos de campo.