bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of Video Observation Data for Volcanic Activity Monitoring Using Computer Vision and Modern Neural NetWorks (on Klyuchevskoy Volcano Example)
Authors: Korolev Sergey , Sorokin Aleksei , Urmanov Igor , Kamaev Aleksandr , Girina Olga
Published: December 2021

Currently, video observation systems are actively used for volcano activity monitoring. Video cameras allow us to remotely assess the state of a dangerous natural object and to detect thermal anomalies if technical capabilities are available. However, continuous use of visible band cameras instead of special tools (for example, thermal cameras), produces large number of images, that require the application of special algorithms both for preliminary filtering out the images with area of interest hidden due to weather or illumination conditions, and for volcano activity detection. Existing algorithms use preselected regions of interest in the frame for analysis. This region could be changed occasionally to observe events in a specific area of the volcano. It is a problem to set it in advance and keep it up to date, especially for an observation network with multiple cameras. The accumulated perennial archives of images with documented eruptions allow us to use modern deep learning technologies for whole frame analysis to solve the specified task. The article presents the development of algorithms to classify volcano images produced by video observation systems. The focus is on developing the algorithms to create a labelled dataset from an unstructured archive using existing and authors proposed techniques. The developed solution was tested using the archive of the video observation system for the volcanoes of Kamchatka, in particular the observation data for the Klyuchevskoy volcano. The tests show the high efficiency of the use of convolutional neural networks in volcano image classification, and the accuracy of classification achieved 91%. The resulting dataset consisting of 15,000 images and labelled in three classes of scenes is the first dataset of this kind of Kamchatka volcanoes. It can be used to develop systems for monitoring other stratovolcanoes that occupy most of the video frame.
Classification of Typical Tree Species in Laser Point Cloud Based on Deep Learning
Authors: Chen Jianchang , Chen Yiming , Liu Zhengjun
Published: December 2021

We propose the Point Cloud Tree Species Classification Network (PCTSCN) to overcome challenges in classifying tree species from laser data with deep learning methods. The network is mainly composed of two parts: a sampling component in the early stage and a feature extraction component in the later stage. We used geometric sampling to extract regions with local features from the tree contours since these tend to be species-specific. Then we used an improved Farthest Point Sampling method to extract the features from a global perspective. We input the intensity of the tree point cloud as a dimensional feature and spatial information into the neural network and mapped it to higher dimensions for feature extraction. We used the data obtained by Terrestrial Laser Scanning (TLS) and Unmanned Aerial Vehicle Laser Scanning (UAVLS) to conduct tree species classification experiments of white birch and larch. The experimental results showed that in both the TLS and UAVLS datasets, the input tree point cloud density and the highest feature dimensionality of the mapping had an impact on the classification accuracy of the tree species. When the single tree sample obtained by TLS consisted of 1024 points and the highest dimension of the network mapping was 512, the classification accuracy of the trained model reached 96%. For the individual tree samples obtained by UAVLS, which consisted of 2048 points and had the highest dimension of the network mapping of 1024, the classification accuracy of the trained model reached 92%. TLS data tree species classification accuracy of PCTSCN was improved by 2–9% compared with other models using the same point density, amount of data and highest feature dimension. The classification accuracy of tree species obtained by UAVLS was up to 8% higher. We propose PCTSCN to provide a new strategy for the intelligent classification of forest tree species.
Soil Organic Carbon Content Prediction Using Soil-Reflected Spectra: A Comparison of Two Regression Methods
Authors: Ribeiro Sharon Gomes , Teixeira Adunias dos Santos , de Oliveira Marcio Regys Rabelo , Costa Mirian Cristina Gomes , Araújo Isabel Cristina da Silva , Moreira Luis Clenio Jario , Lopes Fernando Bezerra
Published: December 2021

Quantifying the organic carbon content of soil over large areas is essential for characterising the soil and the effects of its management. However, analytical methods can be laborious and costly. Reflectance spectroscopy is a well-established and widespread method for estimating the chemical-element content of soils. The aim of this study was to estimate the soil organic carbon (SOC) content using hyperspectral remote sensing. The data were from soils from two localities in the semi-arid region of Brazil. The spectral reflectance factors of the collected soil samples were recorded at wavelengths ranging from 350–2500 nm. Pre-processing techniques were employed, including normalisation, Savitzky–Golay smoothing and first-order derivative analysis. The data (n = 65) were examined both jointly and by soil class, and subdivided into calibration and validation to independently assess the performance of the linear methods. Two multivariate models were calibrated using the SOC content estimated in the laboratory by principal component regression (PCR) and partial least squares regression (PLSR). The study showed significant success in predicting the SOC with transformed and untransformed data, yielding acceptable-to-excellent predictions (with the performance-to-deviation ratio ranging from 1.40–3.38). In general, the spectral reflectance factors of the soils decreased with the increasing levels of SOC. PLSR was considered more robust than PCR, whose wavelengths from 354 to 380 nm, 1685, 1718, 1757, 1840, 1876, 1880, 2018, 2037, 2042, and 2057 nm showed outstanding absorption characteristics between the predicted models. The results found here are of significant practical value for estimating SOC in Neosols and Cambisols in the semi-arid region of Brazil using VIS-NIR-SWIR spectroscopy.
Biophysical Effects of Temperate Forests in Regulating Regional Temperature and Precipitation Pattern across Northeast China
Authors: Jiao Yue , Bu Kun , Yang Jiuchun , Li Guangshuai , Shen Lidu , Liu Tingxiang , Yu Lingxue , Zhang Shuwen , Zhang Hengqing
Published: December 2021

The temperate forests in Northeast China are an important ecological barrier. However, the way in which temperate forests regulate the regional temperature and water cycling remains unclear. In this study, we quantitatively evaluated the role that temperate forests play in the regulation of the regional temperature and precipitation by combining remote sensing observations with a state-of-the-art regional climate model. Our results indicated that the forest ecosystem could slightly warm the annual air temperature by 0.04 ± 0.02 °C and bring more rainfall (17.49 ± 3.88 mm) over Northeast China. The temperature and precipitation modification function of forests varies across the seasons. If the trees were not there, our model suggests that the temperature across Northeast China would become much colder in the winter and spring, and much hotter in the summer than the observed climate. Interestingly, the temperature regulation from the forest ecosystem was detected in both forested regions and the adjacent agricultural areas, suggesting that the temperate forests in Northeast China cushion the air temperature by increasing the temperature in the winter and spring, and decreasing the temperature in the summer over the whole region. Our study also highlights the capacity of temperate forests to regulate regional water cycling in Northeast China. With high evapotranspiration, the forests could transfer sufficient moisture to the atmosphere. Combined with the associated moisture convergence, the temperate forests in Northeast China brought more rainfall in both forest and agricultural ecosystems. The increased rainfall was mainly concentrated in the spring and summer; these seasons accounted for 93.82% of the total increase in rainfall. These results imply that temperate forests make outstanding contributions to the maintainance of the sustainable development of agriculture in Northeast China.
Shared Blocks-Based Ensemble Deep Learning for Shallow Landslide Susceptibility Mapping
Authors: Kavzoglu Taskin , Teke Alihan , Yilmaz Elif Ozlem
Published: December 2021

Natural disaster impact assessment is of the utmost significance for post-disaster recovery, environmental protection, and hazard mitigation plans. With their recent usage in landslide susceptibility mapping, deep learning (DL) architectures have proven their efficiency in many scientific studies. However, some restrictions, including insufficient model variance and limited generalization capabilities, have been reported in the literature. To overcome these restrictions, ensembling DL models has often been preferred as a practical solution. In this study, an ensemble DL architecture, based on shared blocks, was proposed to improve the prediction capability of individual DL models. For this purpose, three DL models, namely Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM), together with their ensemble form (CNN–RNN–LSTM) were utilized to model landslide susceptibility in Trabzon province, Turkey. The proposed DL architecture produced the highest modeling performance of 0.93, followed by CNN (0.92), RNN (0.91), and LSTM (0.86). Findings proved that the proposed model excelled the performance of the DL models by up to 7% in terms of overall accuracy, which was also confirmed by the Wilcoxon signed-rank test. The area under curve analysis also showed a significant improvement (~4%) in susceptibility map accuracy by the proposed strategy.
Temporal Information Extraction for Afforestation in the Middle Section of the Yarlung Zangbo River Using Time-Series Landsat Images Based on Google Earth Engine
Authors: Fu Hao , Zhao Wei , Zhan Qiqi , Yang Mengjiao , Xiong Donghong , Yu Daijun
Published: December 2021

Afforestation is one of the most efficient ways to control land desertification in the middle section of the Yarlung Zangbo River (YZR) valley. However, the lack of a quantitative way to record the planting time of artificial forest (AF) constrains further management for these forests. The long-term archived Landsat images (including the Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI)) provide a good opportunity to capture the temporal change information about AF plantations. Under the condition that there would be an abrupt increasing trend in the normalized difference vegetation index (NDVI) time-series curve after afforestation, and this characteristic can be thought of as the indicator of the AF planting time. To extract the indicator, an algorithm based on the Google Earth Engine (GEE) for detecting this trend change point (TCP) on the maximum NDVI time series within the growing season (May to September) was proposed. In this algorithm, the time-series NDVI was initially smoothed and segmented into two subspaces. Then, a trend change indicator Sdiff was calculated with the difference between the fitting slopes of the subspaces before and after each target point. A self-adaptive method was applied to the NDVI series to find the right year with the maximum TCP, which is recorded as the AF planting time. Based on the proposed method, the AF planting time of the middle section of the YZR valley from 1988 to 2020 was derived. The detected afforestation temporal information was validated by 222 samples collected from the field survey, with a Pearson correlation coefficient of 0.93 and a root mean squared error (RMSE) of 2.95 years. Meanwhile, the area distribution of the AF planted each year has good temporal consistency with the implementation of the eco-reconstruction project. Overall, the study provides a good way to map AF planting times that is not only helpful for sustainable management of AF areas but also provides a basis for further research on the impact of afforestation on desertification control.
Geomorphology, Mineralogy, and Geochronology of Mare Basalts and Non-Mare Materials around the Lunar Crisium Basin
Authors: Lu Xuejin , Cao Haijun , Ling Zongcheng , Fu Xiaohui , Qiao Le , Chen Jian
Published: December 2021

The Nectarian-aged Crisium basin exhibits an extremely thin crust and complicated lunar geological history. This large multi-ring impact basin is characterized by prolonged lunar volcanism ranging from the Imbrian age to the Eratosthenian period, forming the high-Ti mare unit, low-Ti mare basalts, and very low-Ti mare unit. We produced an updated geological map of the Crisium basin and defined four mare units (Im1: 3.74 Ga; Im2: 3.49 Ga; Im3: 3.56 Ga; EIm: 2.49 Ga) in terms of distinct composition and mineralogy. Olivine was widely determined in the Ti-rich Im1, implying the hybridization source in the lunar mantle with the occurrence of small-scale convective overturn. The major phase of low-Ti basaltic volcanism occurred c.a. 3.5 Ga, forming Im2 and Im3 in the western area. The youngest mare unit (EIm) has slight variations of pyroxene compositions, implying a decrease of calcic content of basaltic volcanisms with time. Later, distal material transports from large impact events in highlands could complicate the mixing of local mare basalts in the Copernicus age, especially the Im3 unit. The identified olivine-bearing outcrops and widely Mg-rich materials (Mg# > 70, where Mg# = molar 100 × Mg/(Mg + Fe)) in the western highlands, assumed to be the occurrence of the Mg-suite candidates, require future lunar exploration missions to validate.
Variations in Stratospheric Gravity Waves Derived from Temperature Observations of Multi-GNSS Radio Occultation Missions
Authors: Luo Jia , Hou Jialiang , Xu Xiaohua
Published: December 2021

The spatial–temporal distribution of the global gravity wave (GW) potential energy (Ep) at the lower stratosphere of 20–35 km is studied using the dry temperature profiles from multi- Global Navigation Satellite System (GNSS) radio occultation (RO) missions, including CHAMP, COSMIC, GRACE, and METOP-A/B/C, during the 14 years from 2007 to 2020, based on which the linear trends of the GW Ep and the responses of GW Ep to solar activity, quasi biennial oscillation (QBO), and El Niño-Southern Oscillation (ENSO) are analyzed using the multivariate linear regression (MLR) method. It is found that the signs and the magnitudes of the trends of GW Ep during each month vary at different altitude ranges and over different latitudes. At 25–35 km of the middle and high latitudes, GW Ep values generally show significant negative trends in almost all months, and the values of the negative trends become smaller in the regions closer to the poles. The distribution of the deseasonalized trends in the monthly zonal-mean GW Ep demonstrates that the GW activities are generally declining from 2007 to 2020 over the globe. The responses of GW Ep to solar activity are found to be mostly positive at 20–35 km over the globe, and the comparison between the distribution pattern of the deseasonalized trends in the GW activities and that of the responses of GWs to solar activity indicates that the sharp decline in solar activity from 2015 to 2017 might contribute to the overall attenuation of gravity wave activity during the 14 years. Significant negative responses of GW Ep to QBO are found at 30–35 km over 30° S–25° N, and the negative responses extend to the mid and high latitudes in the southern hemisphere at 20–30 km. The responses of GW Ep to QBO change to be significantly positive at 20–30 km over 15° S–15° N, which demonstrates that the zonal wind field should be the main factor affecting the GW activities at 20–30 km over the tropics. The responses of GW Ep at 20–35 km to ENSO are found to be positive over 15° S–15° N, while at 30–35 km over 15° N–30° N and at 20–35 km near 50° N, significant negative responses of GW Ep to ENSO exist.
Compatibility of Different Formulations in Pentravan® and Pentravan® Plus for Transdermal Drug Delivery
Authors: Polonini Hudson , Taylor Sarah , Zander Clark
Published: December 2021

The potential therapeutic benefit of transdermal delivery systems for some active pharmaceutical ingredients (APIs) has been well-established for decades within the scientific community. However, together with the clinical efficacy, there is the need for an evaluation of the stability of such APIs in bases with known transdermal capabilities, which is necessary to provide the compounding pharmacist with confidence when providing transdermal products. In this study, the stability of danazol, metformin HCl, and resveratrol as individual ingredients, as well as metformin HCl, resveratrol, and Vitamin D3 in combinations at bracketed high and low concentrations, were evaluated over a period of 6 months, using a ready-to-use transdermal vehicle for compounding pharmacies (Pentravan® or Pentravan® Plus). The five formulations tested (F1: Danazol 50 mg/g + MiodesinTM 85 mg/g in Pentravan®, F2: Metformin HCl 200 mg/g in Pentravan®, F3: Resveratrol 200 mg/g in Pentravan®, F4: Metformin HCl 100 mg/g + Resveratrol 100 mg/g + Vitamin D3 5000 IU in Pentravan®, and F5: Metformin HCl 200 mg/g + Resveratrol 200 mg/g + Vitamin D3 5000 IU in Pentravan® Plus) presented a beyond-use date of at least 6 months, presenting high convenience for the compounding pharmacies.
Gender and Financialization of the Criminal Justice System
Authors: Servon Lisa , Esquier Ava , Tiley Gillian
Published: December 2021

(1) The increase in women’s mass incarceration over the past forty years raises questions about how justice-involved women experience the financial aspects of the criminal justice system. (2) We conducted in-depth interviews with twenty justice-involved women and seven criminal law and reentry professionals, and conducted courtroom observations in southeastern Pennsylvania. (3) The results from this exploratory research reveal that women’s roles as caregivers, their greater health needs, and higher likelihood of being poor creates barriers to paying fines and fees and exacerbates challenges in reentry. (4) These challenges contribute to a cycle of prolonged justice involvement and financial instability.
Urban Boundary Demarcation—An iCN Model Approach
Authors: Jayasinghe Amila , Kalpana Lindamullage Don Charls Hasintha Nawod , Abenayake Charithmali Chethika , Mahanama Pelpola Kankanamge Seneviratne
Published: December 2021

During the last two decades, determining the urban boundaries of cities has become one of the major concerns in the urban and regional planning subject domains. Many scholars have tried to model the change of urban boundaries as it helps with sustainable development, population projections and social policy making, but such efforts have been futile, owing to the complex nature of urbanization and the theoretical and technical limitations of the proposed applications. Hence, many countries continue to rely on the administrative boundary demarcation, which rarely represent the actual urbanizing pattern. In such context, this study utilized the “Intersection-Based Clustered Network Model—(iCN Model)” to determine the urban boundaries of cities and selected Sri Lanka as the study area and considered few cities to test the model empirically, with satellite imagery classified urban boundaries. The findings of the study depict that the iCN Model is capable of capturing the complex and dynamic socioeconomic interdependencies of cities via the transportation network configurations. Therefore, the proposed approach is an excellent proxy to derive the urban boundaries of cities, which correspond with the same, derived by the satellite imageries. The proposed model is entirely based on open-source GIS applications and is free to implement and modify using the methods described in this paper.
Performing Hybridity or Deflecting Islamophobia? Adaptable Identity Management amongst Young British Pakistani Muslims
Authors: Khan Fatima , Mythen Gabe
Published: December 2021

This article engages with issues of identity construction and maintenance as expressed by a group of young British Pakistanis living in the North-West of England. Drawing on primary data from a qualitative study, we examine the ways in which Muslim identities are maintained, negotiated, and protected in relation to everyday situated cultural experiences. Nested within a context in which Islamophobia is pervasive, we discuss four salient processes of identity management articulated by participants: cherry picking; strategic adaption; ambassadorship and active resistance. Whilst these processes are to be considered as porous rather than mutually exclusive, our analysis elucidates evidence of both nimble and creative individual identity management and also an entrenchment of collective pride. We posit that, for the participants in this study, such practices constitute a grounded, pragmatic response to living in an environment in which their religious beliefs, political values and cultural commitments are frequently questioned within public life, the media and the political sphere.
The Intersection of Reproductive, Work-Life Balance and Early-Education and Care Policies: ‘Solo’ Mothers by Choice in the UK and Spain
Authors: Bravo-Moreno Ana
Published: December 2021

This article focuses on women who have opted to be mothers on their own by choice in the UK and Spain, and how their access to assisted reproductive technologies in the National Health Service was affected because they were 35 years old or older, forcing them to go to private clinics for their treatment. Having given birth to their children, the participants face a second obstacle: the lack of policies that support work-life balance. A third obstacle also arises, in the form of a lack of childcare and early-education provision, particularly in the UK. The last two obstacles affect the whole population, but they are intensified in the case of solo-mother-families where the mother is responsible for simultaneously being the caregiver and the sole economic provider. Solo motherhood by choice highlights the impact of the absence of these policies, and the inequalities that result from current contemporary conceptualizations of family, woman and early-childhood-care and education. This article draws on ethnographic research that took place in the UK and Spain where I conducted 60 in-depth interviews and participant observations. The aim is to provide an analysis capable of capturing and confronting how inequalities affect women-mothers-workers and their children.
Out-of-Place Content: How Repetitive, Offensive, and Opinion-Challenging Social Media Posts Shape Users’ Unfriending Strategies in Spain
Authors: Jordá Beatriz , Cañedo Azahara , Bene Márton , Goyanes Manuel
Published: December 2021

Filtering strategies enable social media users to remove undesired content from their feeds, potentially creating homophilic environments. Although previous studies have addressed the individual-level factors and content features that influence these decisions, few have solely focused on users’ perceptions. Accordingly, this study applies social exchange theory to understand how users socially construct the process of unfriending. Based on 30 in-depth interviews with young Spaniards, we identify a widespread pattern of rejection over repetitive, opinion-challenging, and offensive posts, which we conceptualize as out-of-place content, a type of social media stimulus that hinders substantive online exchanges and challenges users’ understanding of social reality and individual values. This study contributes to current literature on unfriending by suggesting that filtering strategies are implemented gradually when posts overwhelm users’ tolerance threshold. Our findings also suggest that their deployment hinges on the closeness of the relationship between peers and social commitments formed in specific platforms. Future research is needed to assess to what extent the patterns identified in our interviews are present in the overall population.
Exploring Residents’ Perceptions and Attitudes towards Sustainable Tourism Development in Traditional Villages: The Lens of Stakeholder Theory
Authors: Song Hongmei , Zhu Chris , Fong Lawrence Hoc Nang
Published: December 2021

As Chinese traditional villages are receiving increasing attention from the country, society and business in terms of sustainable tourism development, their residents’ perceptions have not been thoroughly investigated. To contribute to the literature, this qualitative study, which was based on stakeholder theory, conducted semi-structured in-depth interviews with 12 different stakeholders in Hongcun, one of the most well-known traditional villages in China. Using grounded theory approach, this study found that residents’ perceptions and attitudes of sustainable development differed in four main areas—economic, environmental, social, and cultural—and several sub-themes were developed to influence these four areas. The study results have important theoretical and practical implications for current sustainable tourism development in traditional villages. In particular, these results have substantial value for the country, society, and business levels with respect to developing traditional village sustainable tourism based on the perceptions and attitudes of the residents.
Sustainable Hospital Management by a Cross SWOT Analysis in a Medium-Sized Hospital
Authors: Miura Shin-ichiro , Nose Daisuke , Kanamori Katsutoshi , Imaizumi Satoshi , Shimura Hideo , Saku Keijiro
Published: December 2021

The medical working environment in small and medium-sized hospitals is becoming more intense, and the coronavirus epidemic has threatened the hospital management base in Japan. To establish the future sustainable management of hospitals using internal and external environmental data, a cross SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis may be a very useful tool. A cross SWOT analysis considers four strategies: an offensive strategy (SO), a confrontation strategy (ST), a strengthening strategy (WO) and a defense strategy (WT). Here, using a cross SWOT analysis, we consider the future direction of an older medium-sized hospital as one case. The most important issue is to balance the interests of hospital management with those of patients. As a sustainable strategy for this purpose, we forecast the medical situation in the Fukuoka-Itoshima Medical Area, including the Fukuoka-Nishi area in Japan, and the future profitability of a medium-sized hospital for the next 30 to 40 years. Based on the data, we used a cross SWOT analysis to analyze the current situation at the hospital and formulated measures to realize innovations at the hospital that respond to the needs of patients and the community. According to this analysis, for the future sustainable management as a hospital, we should plan to become a more community-based by increasing our capacity to treat elderly inpatients and outpatients with cardiovascular, gastrointestinal and respiratory diseases and to increase the number of beds dedicated to community comprehensive care. Furthermore, through close cooperation with highly specialized and advanced medical institutions, we need to create a new type of regional medical cooperation that can bridge the gap between regional medical care and advanced medical care. We also need to open a cardiovascular-rhythm center and a gastrointestinal endoscopy center and establish an appropriate working system for staff. The future direction for this older hospital should include plans for relocation and reconstruction, considering the balance between expected changes in income and expenses. In conclusion, we performed a cross SWOT analysis with SO, ST, WO and WT. The analysis can be a very useful tool for planning the future direction of hospitals using internal and external environmental data, and our older hospital should eventually be able to achieve sustainable developmental innovations by rebuilding while working on various strategies.
A Synopsis of Croton (Euphorbiaceae) in Michoacán, Mexico
Authors: Steinmann Victor
Published: November 2021

A taxonomic and nomenclatural review of the genus Croton (Euphorbiaceae) in the Mexican state of Michoacán is presented. Six sections and 20 species are here reported. The greatest diversity is in the Balsas Depression province, where at least 12 species occur. There is a strong tendency to thrive in tropical deciduous forest. An identification key is provided, and for each species, the following information is included: protologue citation, type information, habit, habitat, and elevation within the state, regional and global distribution, and phenology. Relevant synonyms are listed, as too are herbarium specimens. Lectotypes are designated for Croton draco, C. niveus, and C. calvescens. One species, Croton rojasii, is described as new and illustrated with photos. It is known only from tropical deciduous forest in the Zicuirán-Infiernillo Biosphere Reserve, at elevations from 400 to 700 m. It belongs to sect. Geiseleria and is remarkable because of the strongly unequal pistillate sepals, the larger of which becoming accrescent and exceeding the fruit.
Thermoplastics and Photopolymer Desktop 3D Printing System Selection Criteria Based on Technical Specifications and Performances for Instructional Applications
Authors: Jo Bruce W. , Song Christina Soyoung
Published: December 2021

With the advancement of additive manufacturing technologies in their material processing methodologies and variety of material selection, 3D printers are widely used in both academics and industries for various applications. It is no longer rare to have a portable and small desktop 3D printer and manufacture your own designs in a few hours. Desktop 3D printers vary in their functions, prices, materials used, and applications. Among many desktop 3D printers with various features, it is often challenging to select the best one for target applications and usages. In this paper, commercially available and carefully selected thermoplastic and photopolymer desktop 3D printers are introduced, and some representative models’ specifications and performances are compared with each other for user selection with respect to instructional applications. This paper aims to provide beginner-level or advanced-level end-users of desktop 3D printers with basic knowledge, selection criteria, a comprehensive overview of 3D printing technologies, and their technical features, helping them to evaluate and select the right 3D printers for a wide range of applications.
A Deep Learning-Based Dirt Detection Computer Vision System for Floor-Cleaning Robots with Improved Data Collection
Authors: Canedo Daniel , Fonseca Pedro , Georgieva Petia , Neves António J. R.
Published: December 2021

Floor-cleaning robots are becoming increasingly more sophisticated over time and with the addition of digital cameras supported by a robust vision system they become more autonomous, both in terms of their navigation skills but also in their capabilities of analyzing the surrounding environment. This document proposes a vision system based on the YOLOv5 framework for detecting dirty spots on the floor. The purpose of such a vision system is to save energy and resources, since the cleaning system of the robot will be activated only when a dirty spot is detected and the quantity of resources will vary according to the dirty area. In this context, false positives are highly undesirable. On the other hand, false negatives will lead to a poor cleaning performance of the robot. For this reason, a synthetic data generator found in the literature was improved and adapted for this work to tackle the lack of real data in this area. This synthetic data generator allows for large datasets with numerous samples of floors and dirty spots. A novel approach in selecting floor images for the training dataset is proposed. In this approach, the floor is segmented from other objects in the image such that dirty spots are only generated on the floor and do not overlap those objects. This helps the models to distinguish between dirty spots and objects in the image, which reduces the number of false positives. Furthermore, a relevant dataset of the Automation and Control Institute (ACIN) was found to be partially labelled. Consequently, this dataset was annotated from scratch, tripling the number of labelled images and correcting some poor annotations from the original labels. Finally, this document shows the process of generating synthetic data which is used for training YOLOv5 models. These models were tested on a real dataset (ACIN) and the best model attained a mean average precision (mAP) of 0.874 for detecting solid dirt. These results further prove that our proposal is able to use synthetic data for the training step and effectively detect dirt on real data. According to our knowledge, there are no previous works reporting the use of YOLOv5 models in this application.
Metagenomic Analysis for Evaluating Change in Bacterial Diversity in TPH-Contaminated Soil after Soil Remediation
Authors: Kim Jin-Wook , Hong Young-Kyu , Kim Hyuck-Soo , Oh Eun-Ji , Park Yong-Ha , Kim Sung-Chul
Published: December 2021

Soil washing and landfarming processes are widely used to remediate total petroleum hydrocarbon (TPH)-contaminated soil, but the impact of these processes on soil bacteria is not well understood. Four different states of soil (uncontaminated soil (control), TPH-contaminated soil (CS), after soil washing (SW), and landfarming (LF)) were collected from a soil remediation facility to investigate the impact of TPH and soil remediation processes on soil bacterial populations by metagenomic analysis. Results showed that TPH contamination reduced the operational taxonomic unit (OTU) number and alpha diversity of soil bacteria. Compared to SW and LF remediation techniques, LF increased more bacterial richness and diversity than SW, indicating that LF is a more effective technique for TPH remediation in terms of microbial recovery. Among different bacterial species, Proteobacteria were the most abundant in all soil groups followed by Actinobacteria, Acidobacteria, and Firmicutes. For each soil group, the distribution pattern of the Proteobacteria class was different. The most abundant classed were Alphaproteobacteria (16.56%) in uncontaminated soils, Deltaproteobacteria (34%) in TPH-contaminated soils, Betaproteobacteria (24%) in soil washing, and Gammaproteobacteria (24%) in landfarming, respectively. TPH-degrading bacteria were detected from soil washing (23%) and TPH-contaminated soils (21%) and decreased to 12% in landfarming soil. These results suggest that soil pollution can change the diversity of microbial groups and different remediation techniques have varied effective ranges for recovering bacterial communities and diversity. In conclusion, the landfarming process of TPH remediation is more advantageous than soil washing from the perspective of bacterial ecology.
Τemporal Variation in Pesticide Residues in Citrus Fruits from Chios, Greece, before and after the Development of an Integrated Pest Management Strategy (IPMS): A Five-Year Study (LIFE13 ENV GR/000414)
Authors: Bempelou Eleftheria , Anagnostopoulos Christos , Kiousi Maroula , Malatou Panagiota , Liapis Konstantinos , Kouloussis Nikos , Mavraganis Vassilis , Papadopoulos Nikolaos T.
Published: December 2021

The temporal variation in pesticide residues in Kampos, of Chios Island, in Greece, was determined between June 2014 and October 2019. Monitoring of residues took place before and after the development of an Integrated Pest Management Strategy (IPMS) for the sustainable control of the Mediterranean fruit fly (medfly) based on mass trapping with the non-toxic and environmentally friendly attractant Biodelear. A total of 1252 samples of citrus fruits, collected from 12 experimental citrus orchards, were analyzed for the presence of 353 active substances and metabolites of pesticides. A modified QuEChERS method and sensitive chromatographic techniques were used. During preparatory monitoring for the project, the most frequently detected pesticides were the insecticides chlorpyrifos, deltamethrin and spirotetramat; the fungicides propamocarb, dimethomorph and mepanipyrim; and the synergist piperonyl butoxide. The implementation of the IPMS to address medfly resulted in a dramatic reduction in the pesticides detected in citrus fruits during confirmatory monitoring, with no detectable residues—which may cause serious problems to human health—in any of the samples analyzed at the end of the project, thus enhancing consumer safety.
Ultrasonographic Evaluation of Three Approaches for Botulinum Toxin Injection into Tibialis Posterior Muscle in Chronic Stroke Patients with Equinovarus Foot: An Observational Study
Authors: Spina Stefania , Facciorusso Salvatore , Botticelli Chiara , Intiso Domenico , Ranieri Maurizio , Colamaria Antonio , Fiore Pietro , Ciritella Chiara , Genêt François , Santamato Andrea
Published: December 2021

Spastic equinovarus (SEV) foot deformity is commonly observed in patients with post-stroke spasticity. Tibialis posterior (TP) is a common target for botulinum toxin type-A (BoNT-A) injection, as a first-line treatment in non-fixed SEV deformity. For this deep muscle, ultrasonographic guidance is crucial to achieving maximum accuracy for the BoNT-A injection. In current clinical practice, there are three approaches to target the TP: an anterior, a posteromedial, and a posterior. To date, previous studies have failed to identify the best approach for needle insertion into TP. To explore the ultrasonographic characteristics of these approaches, we investigated affected and unaffected legs of 25 stroke patients with SEV treated with BoNT-A. We evaluated the qualitative (echo intensity) and quantitative (muscle depth, muscle thickness, overlying muscle, subcutaneous tissue, cross-sectional area) ultrasound characteristics of the three approaches for TP injection. In our sample, we observed significant differences among almost all the parameters of the three approaches, except for the safety window. Moreover, our analysis showed significant differences in cross-sectional area between treated and untreated. Advantages and disadvantages of each approach were investigated. Our findings can thus provide a suitable reference for clinical settings, especially for novice operators.
Development of a Candidate Multi-Epitope Subunit Vaccine against Klebsiella aerogenes: Subtractive Proteomics and Immuno-Informatics Approach
Authors: Umar Ahitsham , Haque Asma , Alghamdi Youssef Saeed , Mashraqi Mutaib M , Rehman Abdur , Shahid Farah , Khurshid Mohsin , Ashfaq Usman Ali
Published: December 2021

Klebsiella aerogenes is a Gram-negative bacterium which has gained considerable importance in recent years. It is involved in 10% of nosocomial and community-acquired urinary tract infections and 12% of hospital-acquired pneumonia. This organism has an intrinsic ability to produce inducible chromosomal AmpC beta-lactamases, which confer high resistance. The drug resistance in K. aerogenes has been reported in China, Israel, Poland, Italy and the United States, with a high mortality rate (~50%). This study aims to combine immunological approaches with molecular docking approaches for three highly antigenic proteins to design vaccines against K. aerogenes. The synthesis of the B-cell, T-cell (CTL and HTL) and IFN-γ epitopes of the targeted proteins was performed and most conserved epitopes were chosen for future research studies. The vaccine was predicted by connecting the respective epitopes, i.e., B cells, CTL and HTL with KK, AAY and GPGPG linkers and all these were connected with N-terminal adjuvants with EAAAK linker. The humoral response of the constructed vaccine was measured through IFN-γ and B-cell epitopes. Before being used as vaccine candidate, all identified B-cell, HTL and CTL epitopes were tested for antigenicity, allergenicity and toxicity to check the safety profiles of our vaccine. To find out the compatibility of constructed vaccine with receptors, MHC-I, followed by MHC-II and TLR4 receptors, was docked with the vaccine. Lastly, in order to precisely certify the proper expression and integrity of our construct, in silico cloning was carried out. Further studies are needed to confirm the safety features and immunogenicity of the vaccine.
Human Papilloma Virus Vaccination: Focus on the Italian Situation
Authors: Gabutti Giovanni , d’Anchera Erica , De Motoli Francesco , Savio Marta , Stefanati Armando
Published: December 2021

Human papilloma virus (HPV) is a viral agent whose transmission occurs mainly by sexual means. It causes different pathological conditions in both males and females, ranging from benign pathologies up to cancers. The introduction of vaccination has certainly had a major impact in terms of reducing the incidence of both HPV infections and diseases but in the European Union and the European Economic Area (EU/EEA) there are still about more than 13,000 deaths due to cervical cancer each year. To date in Europe and in Italy there are three vaccines available (bi-, tetra-, and nonvalent vaccines). The vaccination campaign started irregularly in Europe and Italy in 2007, with pre-adolescent girls as the primary target. Later, other cohorts were introduced such as 12-year-old boys, additional cohorts of >25-year-old women, women who already underwent cervical surgery and other subjects entitled to free vaccination. The COVID-19 pandemic has strongly impacted on public health services, particularly on vaccinations that, especially during the first pandemic phase, have been often delayed and/or canceled. The most affected vaccinations by the pandemic have been the non-mandatory ones, particularly those addressing the adolescent and adult population, such as immunization against papillomavirus. To date the achievement of the coverage target set by the Italian National Immunization Plan (NIP) has not yet been achieved. The aim of this work is to summarize the current situation in Italy and to discuss the strategies that have been implemented to increase overall vaccination coverage rates.
Determinants of COVID-19 Vaccine Acceptance among the Adult Population of Bangladesh Using the Health Belief Model and the Theory of Planned Behavior Model
Authors: Patwary Muhammad Mainuddin , Bardhan Mondira , Disha Asma Safia , Hasan Mehedi , Haque Md. Zahidul , Sultana Rabeya , Hossain Md. Riad , Browning Matthew H. E. M. , Alam Md. Ashraful , Sallam Malik
Published: December 2021

Vaccination is undoubtedly one of the most effective strategies to halt the COVID-19 pandemic. The current study aimed to investigate the acceptance of COVID-19 vaccination and its associated factors using two health behavior change frameworks: the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). A total of 639 Bangladeshi adults (mean age: 24 years) participated in a cross-sectional online study between July and August 2021. The questionnaire covered questions regarding vaccine intentions, sociodemographic features, health status, perceived trust in/satisfaction with health authorities, reasons for vaccine hesitancy, and factors related to the health behavior change frameworks. Hierarchical logistic regression was employed to determine associations between these predictors and vaccine acceptance. The intention to get a COVID-19 vaccination was expressed among 85% of the participants. In fully adjusted models, students and respondents with more normal body weights reported higher intentions to get vaccinated. Respondents were also more likely to seek vaccination if they reported greater levels of perceived susceptibility, benefits, and cues to action, as well as lower levels of barriers and self-efficacy. Fear of future vaccine side effects was the most common reason for COVID-19 vaccine hesitancy and was expressed by 94% of the vaccine-hesitant respondents. These factors should be considered by health authorities in Bangladesh and perhaps other countries when addressing the plateauing COVID-19 vaccination rates in many populations.
Motivating Seasonal Influenza Vaccination and Cross-Promoting COVID-19 Vaccination: An Audience Segmentation Study among University Students
Authors: Lee Daisy , Rundle-Thiele Sharyn , Li Gabriel
Published: December 2021

In the response to the coronavirus pandemic, much attention has been invested in promoting COVID-19 vaccination. However, the impact of seasonal influenza should not be neglected, particularly during the winter influenza surge. Currently, most influenza vaccination campaigns target at healthcare workers or high-risk population groups, while COVID-19 vaccination programmes are targeting the whole population as a single homogeneous group. There is limited research on the promotion of influenza vaccination for university students who study, live, and socialise in close contact with a large variety of people on campus, resulting in a low vaccination rate among this underserved group. Thus, a vaccination programme tailored for university students should be developed to increase protection against influenza-like illnesses and complications, and to help achieve herd immunity across populations who spread viruses. WHO has advocated the potential value of social marketing in vaccination campaigns and highlighted the need for audience segmentation as a major prerequisite component of intervention design. This study aims to identify distinct and homogeneous groups of university students based on sociodemographic, psychographic, and behavioural attributes to inform interventions. Two-step cluster analysis was applied in a sample size of 530 university students and revealed four segments that demonstrate statistically significant differences in their attitudes, behaviours, intentions, and responses to promotion messages about seasonal influenza and COVID-19 vaccination. The findings provide a detailed understanding of segment characteristics among university students that can be applied to develop an effective social marketing campaign that can motivate influenza vaccination and cross-promote uptake of the COVID-19 vaccine.