bluuebunny/crossref_metadata_2025 huggingface dataset:
Adolescents’ Food Purchasing Patterns in The School Food Environment: Examining the Role of Perceived Relationship Support and Maternal Monitoring
Authors: Hermans Roel C.J. , Smit Koen , van den Broek Nina , Evenhuis Irma J. , Veldhuis Lydian
Published: March 2020

The school food environment plays a role in adolescents’ dietary behaviors. In this study, adolescents’ food purchasing patterns in and around school and its potential relationship with perceived maternal relationship support and maternal monitoring were examined. Data were collected in The Netherlands in 2017. A total of 726 adolescents (45.8% boys; Mage = 13.78 ± 0.49) and 713 mothers (Mage = 45.05 ± 4.45) participated. Adolescents’ frequency of bringing and purchasing foods was assessed via a Food Frequency Questionnaire (FFQ). Relationship support and monitoring were measured via self-report questionnaires. Structural Equation Modelling (SEM) was conducted to examine associations between adolescents’ food purchasing patterns, relationship support, and monitoring. Results indicated that adolescents brought food and drinks mostly from home, and infrequently purchased these products in and around school. Yet, differences exist between subgroups of adolescents. Relationship support was positively associated with bringing fruit, vegetables and salad and negatively associated with purchasing sweet snacks. No associations were found for monitoring. These findings indicate that family-home determinants of healthy and unhealthy eating are important factors to consider when examining the impact of the school food environment on adolescents’ food purchasing patterns. This has implications for policy makers who aim to develop and implement measures to improve adolescents’ eating in and around school.
Stricter Adherence to Dietary Approaches to Stop Hypertension (DASH) and Its Association with Lower Blood Pressure, Visceral Fat, and Waist Circumference in University Students
Authors: Navarro-Prado Silvia , Schmidt-RioValle Jacqueline , Montero-Alonso Miguel A. , Fernández-Aparicio Ángel , González-Jiménez Emilio
Published: March 2020

How diet affects blood pressure (BP) in young adults has not been studied in sufficient depth. For this purpose, we analyzed adherence to the Dietary Approaches to Stop Hypertension (DASH) dietary pattern and BP in Spanish university students. The sample population of our cross-sectional study consisted of 244 subjects (18–31 years old), who were in good health. Measurements were taken of their systolic and diastolic BP. A food frequency questionnaire and 72 h food record were used to assess their dietary intake in the previous year. The resulting DASH score was based on foodstuffs that were emphasized or minimized in the DASH diet. Analysis of covariance adjusted for potential confounding factors showed that the mean values for systolic BP, visceral fat rating, and waist circumference (WC) of the subjects in the upper third of the DASH score were significantly lower than those of the subjects in the lower third (for systolic BP: mean difference −4.36 mmHg, p = 0.004; for visceral fat rating: mean difference −0.4, p = 0.024; for waist circumference: mean difference −3.2, p = 0.019). Stricter adherence to the DASH dietary pattern led to a lower BP, visceral fat rating, and WC values in these university students. Nevertheless, further prospective studies are needed to confirm these results.
Impact of Vigorous-Intensity Physical Activity on Body Composition Parameters, Lipid Profile Markers, and Irisin Levels in Adolescents: A Cross-Sectional Study
Authors: Morelli Catia , Avolio Ennio , Galluccio Angelo , Caparello Giovanna , Manes Emanuele , Ferraro Simona , De Rose Daniela , Santoro Marta , Barone Ines , Catalano Stefania , Andò Sebastiano , Sisci Diego , Giordano Cinzia , Bonofiglio Daniela
Published: March 2020

In adolescence, health status is influenced by several factors, including dietary pattern and physical activity (PA) which are crucial elements of lifestyle in terms of prevention and treatment of metabolic and chronic diseases. The current study aimed to explore the impact of the different intensity levels of PA along with the adherence to a Mediterranean diet (MD), on body composition indices and metabolic parameters in a cohort of adolescents, thereby investigating potential predictors of health behavior in youth. This cross-sectional study was carried out among 92 participants (44 girls and 48 boys, aged 14 to 17 years), which were divided into the following three groups according to intensity levels of PA: Group A (physical inactivity), Group B (moderate PA), and Group C (vigorous-intensity PA). The Questionnaire of Adherence to the Mediterranean Diet (KIDMED test) was used to assess both diet composition and adherence to a MD. All subjects underwent anthropometric measurements, bio-impedentiometric analysis for body composition parameters, and biochemical and hormonal measurements. The majority of adolescents (60.87%) had a medium adherence to the MD, and even a better distribution of food rates was found in adolescents performing vigorous-intensity PA. A comparison of anthropometric measurements and body composition parameters among groups showed that body mass index and fat mass (FM) were significantly lower while body cell mass (BCM), free fat mass (FFM), phase angle (PhA), and total body water (TBW) were higher in Group C adolescents as compared with those of Group A. In Group C, insulin resistance (HOMA-IR) was reduced and insulin levels were inversely associated with FFM (r = −0.454 and p = 0.004) and directly correlated with FM (r = 0.331 and p = 0.003). In the same Group C, we observed elevated serum irisin levels and lower lipid profile markers as compared with Group A. Interestingly, irisin negatively correlated with both total cholesterol (r = −0.428 and p = 0.04) and LDL (r = −0.468 and p = 0.02) in Group C. Finally, a receiver operator characteristic curve (ROC) analysis revealed irisin, LDL, HDL, and body composition variables (FFM, BMC, PhA, and TBW) as the most predictive measures for vigorous-intensity PA. Our results highlight the importance of developing healthy lifestyle programs that include improving the intensity of PA among a young population as a superior strategy for ensuring a better quality of life.
Vitamin D Status in Japanese Adults: Relationship of Serum 25-Hydroxyvitamin D with Simultaneously Measured Dietary Vitamin D Intake and Ultraviolet Ray Exposure
Authors: Asakura Keiko , Etoh Norihito , Imamura Haruhiko , Michikawa Takehiro , Nakamura Takahiro , Takeda Yuki , Mori Sachie , Nishiwaki Yuji
Published: March 2020

Vitamin D insufficiency/deficiency is prevalent worldwide. We investigated the effect of vitamin D intake and ultraviolet ray (UV) exposure on serum vitamin D concentration in Japan. A total of 107 healthy adult participants were recruited from Hokkaido (43° N) and Kumamoto (33° N) prefectures. All participants undertook surveys in both summer and winter. Serum 25-hydroxyvitamin D (25(OH)D3) was examined, and vitamin D intake was assessed with a diet history questionnaire. UV exposure was measured with a wearable UV dosimeter. Regression analysis was performed to investigate the relationship between these factors, with covariates such as sun avoidance behavior. The prevalence of vitamin D insufficiency (serum 25(OH)D3; 12 ng/mL (30 nmol/L) ≤ and <20 ng/mL (50 nmol/L))/deficiency (<12 ng/mL) was 47.7% in summer and 82.2% in winter. UV exposure time was short in Kumamoto (the urban area), at 11.6 min in summer and 14.9 min in winter. In Hokkaido (the rural area), UV exposure time was 58.3 min in summer and 22.5 min in winter. Vitamin D intake was significantly associated with serum 25(OH)D3, and a 1 μg/1000kcal increase in intake was necessary to increase 25(OH)D3 by 0.88 ng/mL in summer and by 1.7 ng/mL in winter. UV exposure time was significantly associated with serum 25(OH)D3 in summer, and a 10 min increase in UV exposure time was necessary to increase 25(OH)D3 by 0.47 ng/mL. Although consideration of personal occupation and lifestyle is necessary, most Japanese may need to increase both vitamin D intake and UV exposure.
The Therapeutic Potential of Breast Milk-Derived Extracellular Vesicles
Authors: Galley Jeffrey D. , Besner Gail E.
Published: March 2020

In the past few decades, interest in the therapeutic benefits of exosomes and extracellular vesicles (EVs) has grown exponentially. Exosomes/EVs are small particles which are produced and exocytosed by cells throughout the body. They are loaded with active regulatory and stimulatory molecules from the parent cell including miRNAs and enzymes, making them prime targets in therapeutics and diagnostics. Breast milk, known for years to have beneficial health effects, contains a population of EVs which may mediate its therapeutic effects. This review offers an update on the therapeutic potential of exosomes/EVs in disease, with a focus on EVs present in human breast milk and their remedial effect in the gastrointestinal disease necrotizing enterocolitis. Additionally, the relationship between EV miRNAs, health, and disease will be examined, along with the potential for EVs and their miRNAs to be engineered for targeted treatments.
Nutrition, Health, and Disease: Role of Selected Marine and Vegetal Nutraceuticals
Authors: Corzo Lola , Fernández-Novoa Lucía , Carrera Iván , Martínez Olaia , Rodríguez Susana , Alejo Ramón , Cacabelos Ramón
Published: March 2020

The investigation of new alternatives for disease prevention through the application of findings from dietary and food biotechnology is an ongoing challenge for the scientific community. New nutritional trends and the need to meet social and health demands have inspired the concept of functional foods and nutraceuticals which, in addition to their overall nutritional value, present certain properties for the maintenance of health. However, these effects are not universal. Nutrigenetics describes how the genetic profile has an impact on the response of the body to bioactive food components by influencing their absorption, metabolism, and site of action. The EbioSea Program, for biomarine prospection, and the Blue Butterfly Program, for the screening of vegetable-derived bioproducts, have identified a new series of nutraceuticals, devoid of side effects at conventional doses, with genotype-dependent preventive and therapeutic activity. Nutrigenomics and nutrigenetics provide the opportunity to explore the inter-individual differences in the metabolism of and response to nutrients, achieving optimal results. This fact leads to the concept of personalized nutrition as opposed to public health nutrition. Consequently, the development and prescription of nutraceuticals according to the individual genetic profile is essential to improve their effectiveness in the prevention and natural treatment of prevalent diseases.
Comparison of Omega-3 Eicosapentaenoic Acid Versus Docosahexaenoic Acid-Rich Fish Oil Supplementation on Plasma Lipids and Lipoproteins in Normolipidemic Adults
Authors: Yang Zhi-Hong , Amar Marcelo , Sampson Maureen , Courville Amber B. , Sorokin Alexander V. , Gordon Scott M. , Aponte Angel M. , Stagliano Michael , Playford Martin P. , Fu Yi-Ping , Yang Shanna , Mehta Nehal N. , Remaley Alan T.
Published: March 2020

Background: Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) have both shared and different cardiovascular effects, and commonly used fish oil supplements have considerably varied EPA/DHA ratios. Aims: We compared the effects of fish oil supplements with different EPA/DHA ratios on lipoprotein metabolism. Methods: In a double-blind, randomized cross-over study, normolipidemic adults (n = 30) consumed 12 g/day of EPA-rich (EPA/DHA: 2.3) or DHA-rich (EPA/DHA: 0.3) fish oil for 8-weeks, separated by an 8-week washout period. Results: Both fish oil supplements similarly lowered plasma TG levels and TG-related NMR parameters versus baseline (p < 0.05). There were no changes in plasma cholesterol-related parameters due to either fish oil, although on-treatment levels for LDL particle number were slightly higher for DHA-rich oil compared with EPA-rich oil (p < 0.05). Both fish oil supplements similarly altered HDL subclass profile and proteome, and down regulated HDL proteins related to inflammation, with EPA-rich oil to a greater extent. Furthermore, EPA-rich oil increased apoM abundance versus DHA-rich oil (p < 0.05). Conclusions: Overall, fish oil supplements with varied EPA/DHA ratios had similar effects on total lipids/lipoproteins, but differences were observed in lipoprotein subfraction composition and distribution, which could impact on the use of EPA versus DHA for improving cardiovascular health.
Using the Internet: Nutrition Information-Seeking Behaviours of Lay People Enrolled in a Massive Online Nutrition Course
Authors: Adamski Melissa , Truby Helen , M. Klassen Karen , Cowan Stephanie , Gibson Simone
Published: March 2020

People’s accessibility to nutrition information is now near universal due to internet access, and the information available varies in its scientific integrity and provider expertise. Understanding the information-seeking behaviours of the public is paramount for providing sound nutrition advice. This research aims to identify who learners in a nutrition-focused Massive Open Online Course (MOOC) turn to for nutrition information, and how they discuss the information they find. A multi-methods approach explored the information-seeking and sharing behaviours of MOOC learners. Summative content analysis, and an exploratory, inductive, qualitative approach analysed learners’ posts in MOOC discussion forums. From 476 posts, the majority (58.6%) of nutrition information sources learners reported were from websites. Providers of nutrition information were most commonly (34%) tertiary educated individuals lacking identifiable nutrition qualifications; 19% had no identifiable author information, and only 5% were from nutrition professionals. Qualitative themes identified that learners used nutrition information to learn, teach and share nutrition information. Consistent with connectivist learning theory, learners contributed their own sources of nutrition information to discussions, using their own knowledge networks to teach and share information. Nutrition professionals need to understand the principles of connectivist learning behaviours in order to effectively engage the public.
Associations between Body Appreciation and Disordered Eating in a Large Sample of Adolescents
Authors: Baceviciene Migle , Jankauskiene Rasa
Published: March 2020

Body appreciation is one of the main facets of a positive body image. The present study aimed to examine the psychometric properties of the Lithuanian version of the Body Appreciation Scale-2 (BAS-2-LT) and test the associations between body appreciation and disordered eating in a large sample of adolescents of both genders. Method: The sample consisted of 1412 adolescents (40.2% were boys). The ages ranged from 15 to 18 years (92.4% were 17), with a mean age of 16.9 (SD = 0.5) for girls and 17.0 (SD = 0.4) for boys. Participants completed the BAS-2-LT alongside the measures of body dissatisfaction, disordered eating, body mass index, self-esteem, body functionality, and participation in sports. Linear regressions were used to test the associations between study variables and disordered eating. Results: BAS-2-LT replicated the original one-dimensional structure in girls and boys. Invariance across genders was established. The instrument showed good internal consistency and temporal stability. Body appreciation was negatively correlated with higher levels of body mass index, body dissatisfaction, and disordered eating. Positive associations were observed between body appreciation, self-esteem, body functionality, and sports participation. Higher levels of body appreciation decreased the risk of disordered eating behaviors in both genders. Conclusions: The results of the present study support the psychometric properties of BAS-2-LT. Body appreciation is associated with lower disordered eating in adolescent girls and boys. These findings present empirical support for the development of interventions programs that promote positive body images and aim to prevent disordered eating in adolescent boys and girls.
Identification and Genome Analysis of Vibrio coralliilyticus Causing Mortality of Pacific Oyster (Crassostrea gigas) Larvae
Authors: Kim Hyoun Joong , Jun Jin Woo , Giri Sib Sankar , Chi Cheng , Yun Saekil , Kim Sang Guen , Kim Sang Wha , Han Se Jin , Kwon Jun , Oh Woo Taek , Lee Sung Bin , Kim Ji Hyung , Park Se Chang
Published: March 2020

Vibrio coralliilyticus is known as a coral pathogen that also infects marine bivalve larvae worldwide. It is considered to be one of the major constraints in artificial marine bivalve seed production as it causes mortality. In this study, we first isolated and characterized a high virulent of V. coralliilyticus designated as SNUTY-1 that was the cause of Pacific oyster larvae mortality in Korea. In the pathogenicity test, exposure to 2.14 × 105 CFU/mL for 24 h caused mortality to 88.65 ± 2.4% of the tested healthy Pacific oyster larvae. SNUTY-1 showed anti-microbial resistance to β-lactams, such as penicillins, cephalosporins, and carbapenems. We sequenced and assembled the complete genome of SNUTY-1 (5,842,676 bp), consisting of two chromosomes (Chr I and Chr II) and two plasmids (pSNUTY1 and pSNUTY2). The COG functional analysis confirmed that Chr I had more genes associated with basic cellular functions in comparison to Chr II. The results of the phylogenetic trees based on OrthoANI values indicated that the SNUTY-1 was closely related to V. coralliilyticus strains. SNUTY-1 had a unique plasmid (pSNUTY2), which could mean that the Korean isolate is different from other sequenced V. coralliilyticus strains from different geographical origins. Toxic proteins such as cytolysin/hemolysin and extracellular metalloprotease genes were encoded on Chr I and Chr II of SNUTY-1. These data facilitate the control of V. coralliilyticus infections in aquaculture by providing valuable insights into the biodiversity of this organism and valuable information for the study of virulence factors.
Effectiveness of Sulfadoxine–Pyrimethamine for Intermittent Preventive Treatment of Malaria and Adverse Birth Outcomes in Pregnant Women
Authors: Mlugu Eulambius M. , Minzi Omary , Asghar Muhammad , Färnert Anna , Kamuhabwa Appolinary A.R. , Aklillu Eleni
Published: March 2020

Effectiveness of intermittent preventive treatment in pregnancy with sulfadoxine–pyrimethamine (IPTp-SP) for prevention of malaria and adverse birth outcomes can be compromised by parasites-resistance to sulfadoxine–pyrimethamine. This study prospectively evaluated the effectiveness of IPTp-SP in Southeast Tanzania. From January 2017 to May 2019, HIV-negative and malaria-negative (mRDT) pregnant women attending their first antenatal-care visit in the second or third trimester (n = 500) were enrolled to receive monthly IPTp-SP and followed the protocol till delivery. The primary outcome was the prevalence of histopathological placental malaria. Secondary outcomes were anemia, malaria parasites detected during pregnancy and at delivery, adverse birth outcomes (low-birth-weight [LBW], premature birth, fetal anemia, still birth, and spontaneous abortion). Rates of histopathological placental malaria, any parasitemia at delivery (placental, cord or maternal), and any adverse birth outcome were 9.4%, 20.9%, and 26.5%, respectively. Rates of symptomatic malaria and parasitemia during pregnancy were 2.8% and 16%, respectively. Histopathological placental malaria significantly increased the odds of any adverse birth outcomes, particularly LBW. IPTp-SP with more than or equal to three doses significantly improved birth weight and reduced the risk of LBW by 56% compared to <3 SP doses (p = 0.009). IPTp-SP with more than or equal to three doses is still effective in improving birth weight. However, the detection of histopathological placental-malaria in one-tenth and parasitemia in one-fifth of pregnant women reflects the need to optimize the prevention of malaria during pregnancy.
Preparation, Characterization, and Evaluation of Cisplatin-Loaded Polybutylcyanoacrylate Nanoparticles with Improved In Vitro and In Vivo Anticancer Activities
Authors: Ghaferi Mohsen , Amari Samar , Vivek Mohrir Bhalchandra , Raza Aun , Ebrahimi Shahmabadi Hasan , Alavi Seyed Ebrahim
Published: March 2020

This study aimed to evaluate the therapeutic efficacy of the cisplatin encapsulated into polybutylcyanoacrylate (PBCA) nanoparticles for the treatment of kidney cancer. The nanoformulation was successfully developed using the miniemulsion polymerization method and characterized in terms of size, size distribution, drug loading and encapsulation efficiencies, drug release behavior, in vitro cytotoxicity effects, in vivo toxicity, and therapeutic effects. Cisplatin-loaded PBCA nanoparticles were confirmed to be in nanoscale with the drug entrapment efficiency of 23% and controlled drug release profile, in which only 9% of the loaded drug was released after 48 h. The nanoparticles caused an increase in the cytotoxicity effects of cisplatin against renal cell adenocarcinoma cells (ACHN) (2.3-fold) and considerably decreased blood urea nitrogen and creatinine concentrations when compared to the standard cisplatin (1.6-fold and 1.5-fold, respectively). The nanoformulation also caused an increase in the therapeutic effects of cisplatin by 1.8-fold, in which a reduction in the mean tumor size was seen (3.5 mm vs. 6.5 mm) when compared to the standard cisplatin receiver rats. Overall, cisplatin-loaded PBCA nanoparticles can be considered as a promising drug candidate for the treatment of kidney cancer due to its potency to reduce the side effects of cisplatin and its toxicity and therapeutic effects on cancer-bearing Wistar rats.
Advancing Pharmacy Practice through an Innovative Ambulatory Care Transitions Program at an Academic Medical Center
Authors: Cavanaugh Jamie , Pinelli Nicole , Eckel Stephen , Gwynne Mark , Daniels Rowell , Hawes Emily M.
Published: March 2020

Hospital readmissions are common and often preventable, leading to unnecessary burden on patients, families, and the health care system. The purpose of this descriptive communication is to share the impact of an interdisciplinary, outpatient clinic-based care transition intervention on clinical, organizational, and financial outcomes. Compared to usual care, the care transition intervention decreased the median time to Internal Medicine Clinic (IMC) or any clinic follow-up visit by 5 and 4 days, respectively. By including a pharmacist in the hospital follow-up visit, the program significantly reduced all-cause 30-day hospital readmission rates (9% versus 26% in usual care) and the composite endpoint of 30-day health care utilization, which is defined as readmission and emergency department (ED) rates (19% versus 44% usual care). Over the course of one year, this program can prevent 102 30-day hospital readmissions with an estimated cost reduction of $1,113,000 per year. The pharmacist at the IMC collaborated with the Family Medicine Clinic (FMC) pharmacist to standardize practices. In the FMC, the hospital readmission rate was 6.5% for patients seen by a clinic-based pharmacist within 30 days of discharge compared to 20% for those not seen by a pharmacist. This transitions intervention demonstrated a consistent and recognizable contribution from pharmacists providing direct patient care and practicing in the ambulatory care primary care settings that has been replicated across clinics at our academic medical center.
Foucault for Heisman: College Football and the Liturgies of Power
Authors: Smith Jason M.
Published: March 2020

This essay attempts to give a new sort of answer to the question of whether or not sport and sports fandom are a religion through the work of Foucault on “power.” Looking specifically at college football in North America, I examine the ways in which Foucault’s different variations of power have and still do function within what we call “big-time” college football. I thus proffer that Foucault’s oeuvre helps us to see the sport and religion question in a new way—not as two phenomena similar in practice but in modes of power. I conclude by offering suggestions for how Foucault’s work might offer suggestions for imagining new configurations of collegiate athletics and its governance.
The Local Promotion of Mazu: The Intersection of Lineage, Textual Representation, Confucian Values, and Temples in Late Imperial China
Authors: Zhang Yanchao
Published: March 2020

This article explores the role that local elites played in the development of the Mazu cult, a local goddess cult in Putian district in late imperial China. I argue that local elites were central in the promotion and transmission of the cult. Through compiling and writing key Confucian texts featuring Mazu, they reshaped, manipulated, and represented certain aspects of her cult in accordance with their interests. As a result of the activities of local elites, Mazu became associated with the Lin lineage, an influential local lineage. In this manner, Mazu came to be seen as an expression of the lineage’s authority, as well as an imperial protector embodying local loyalty to the state and a daughter who was the paradigm filial piety. In addition to the literary production, local elites, in particular the descendants from the Lin lineage, established an ancestral hall of Lin in the port of Xianliang dedicated to Mazu, further sanctioning divinely the local elites’ authority and privilege in the community. I conclude that the locally promoted version of goddess worship operated at the intersection of state interests, Confucian ideology, the agency of local elites, and the dynamics of popular religiosity.
Love me for the Sake of the World: “Goddess Songs” in Tantric Buddhist Maṇḍala Rituals
Authors: Stephenson Jackson
Published: March 2020

The presence of Apabhraṃśa in tantric Buddhist texts has long been noted by scholars, overwhelmingly explained away as an example of “Twilight language” (saṃdhā-bhāṣā). However, when one looks closer at the vast number of Apabhraṃśa verses in this canon, one finds recurring patterns, themes, and even tropes. This begs for deeper study, as well as establishing a taxonomy of these verses based on their place and use. This paper focuses on a specific subset of Apabhraṃśa verses: “goddess songs” in maṇḍala visualization rituals. These verses are sung by yoginīs at specific moments in esoteric Buddhist ritual syntax; while the sādhaka is absorbed in enstatic emptiness, four yoginīs call out to him with sexually charged appeals, begging him to return to the world and honor their commitments to all sentient beings. When juxtaposed with other Apabhraṃśa verses in tantric Buddhist texts, these songs express an immediacy and intimacy that stands out in both form and content from the surrounding text. This essay argues that Apabhraṃśa is a conscious stylistic choice for signaling intimate and esoteric passages in tantric literature, and so the vast number of Apabhraṃśa verses in this corpus should be reexamined in this light.
Recovering Missing Trajectory Data for Mobile Laser Scanning Systems
Authors: Zhong Mianqing , Sui Lichun , Wang Zhihua , Yang Xiaomei , Zhang Chuanshuai , Chen Nan
Published: March 2020

Trajectory data are often used as important auxiliary information in preprocessing and extracting the target from mobile laser scanning data. However, the trajectory data stored independently may be lost and destroyed for various reasons, making the data unavailable for the relevant models. This study proposes recovering the trajectory of the scanner from point cloud data following the scanning principles of a rotating mirror. Two approaches are proposed from different input conditions: Ordered three-dimensional coordinates of point cloud data, with and without acquisition time. We recovered the scanner’s ground track through road point density analysis and restored the position of the center of emission of the laser based on plane reconstruction on a single scanning line. The validity and reliability of the proposed approaches were verified in the four typical urban, rural, winding, and viaduct road environments using two systems from different manufacturers. The result deviations of the ground track and scanner trajectory from their actual position were a few centimeters and less than 1 decimeter, respectively. Such an error is sufficiently small for the trajectory data to be used in the relevant algorithms.
High-Resolution Inundation Mapping for Heterogeneous Land Covers with Synthetic Aperture Radar and Terrain Data
Authors: Aristizabal Fernando , Judge Jasmeet , Monsivais-Huertero Alejandro
Published: March 2020

Floods are one of the most wide-spread, frequent, and devastating natural disasters that continue to increase in frequency and intensity. Remote sensing, specifically synthetic aperture radar (SAR), has been widely used to detect surface water inundation to provide retrospective and near-real time (NRT) information due to its high-spatial resolution, self-illumination, and low atmospheric attenuation. However, the efficacy of flood inundation mapping with SAR is susceptible to reflections and scattering from a variety of factors including dense vegetation and urban areas. In this study, the topographic dataset Height Above Nearest Drainage (HAND) was investigated as a potential supplement to Sentinel-1A C-Band SAR along with supervised machine learning to improve the detection of inundation in heterogeneous areas. Three machine learning classifiers were trained on two sets of features dual-polarized SAR only and dual-polarized SAR along with HAND to map inundated areas. Three study sites along the Neuse River in North Carolina, USA during the record flood of Hurricane Matthew in October 2016 were selected. The binary classification analysis (inundated as positive vs. non-inundated as negative) revealed significant improvements when incorporating HAND in several metrics including classification accuracy (ACC) (+36.0%), critical success index (CSI) (+39.95%), true positive rate (TPR) (+42.02%), and negative predictive value (NPV) (+17.26%). A marginal change of +0.15% was seen for positive predictive value (PPV), but true negative rate (TNR) fell −14.4%. By incorporating HAND, a significant number of areas with high SAR backscatter but low HAND values were detected as inundated which increased true positives. This in turn also increased the false positives detected but to a lesser extent as evident in the metrics. This study demonstrates that HAND could be considered a valuable feature to enhance SAR flood inundation mapping especially in areas with heterogeneous land covers with dense vegetation that interfere with SAR.
Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks
Authors: de Bem Pablo , de Carvalho Junior Osmar , Fontes Guimarães Renato , Trancoso Gomes Roberto
Published: March 2020

Mapping deforestation is an essential step in the process of managing tropical rainforests. It lets us understand and monitor both legal and illegal deforestation and its implications, which include the effect deforestation may have on climate change through greenhouse gas emissions. Given that there is ample room for improvements when it comes to mapping deforestation using satellite imagery, in this study, we aimed to test and evaluate the use of algorithms belonging to the growing field of deep learning (DL), particularly convolutional neural networks (CNNs), to this end. Although studies have been using DL algorithms for a variety of remote sensing tasks for the past few years, they are still relatively unexplored for deforestation mapping. We attempted to map the deforestation between images approximately one year apart, specifically between 2017 and 2018 and between 2018 and 2019. Three CNN architectures that are available in the literature—SharpMask, U-Net, and ResUnet—were used to classify the change between years and were then compared to two classic machine learning (ML) algorithms—random forest (RF) and multilayer perceptron (MLP)—as points of reference. After validation, we found that the DL models were better in most performance metrics including the Kappa index, F1 score, and mean intersection over union (mIoU) measure, while the ResUnet model achieved the best overall results with a value of 0.94 in all three measures in both time sequences. Visually, the DL models also provided classifications with better defined deforestation patches and did not need any sort of post-processing to remove noise, unlike the ML models, which needed some noise removal to improve results.
Synthetic Aperture Radar Flood Detection under Multiple Modes and Multiple Orbit Conditions: A Case Study in Japan on Typhoon Hagibis, 2019
Authors: Natsuaki Ryo , Nagai Hiroto
Published: March 2020

Flood detection using a spaceborne synthetic aperture radar (SAR) has become a powerful tool for organizing disaster responses. The detection accuracy is increased by accumulating pre-event observations, whereas applying multiple observation modes results in an inadequate number of observations with the same mode from the same orbit. Recent flood detection studies take advantage of the large number of pre-event observations taken from an identical orbit and observation mode. On the other hand, those studies do not take account of the use of multiple orbits and modes. In this study, we examined how the analysis results suffered when pre-event observations were only taken from a different orbit or mode to that of the post-event observation. Experimental results showed that inundation areas were overlooked under such non-ideal conditions. On the other hand, the detection accuracy could be recovered by combining analysis results from possible alternate datasets and became compatible with ideal cases.
Axis Learning for Orientated Objects Detection in Aerial Images
Authors: Xiao Zhifeng , Qian Linjun , Shao Weiping , Tan Xiaowei , Wang Kai
Published: March 2020

Orientated object detection in aerial images is still a challenging task due to the bird’s eye view and the various scales and arbitrary angles of objects in aerial images. Most current methods for orientated object detection are anchor-based, which require considerable pre-defined anchors and are time consuming. In this article, we propose a new one-stage anchor-free method to detect orientated objects in per-pixel prediction fashion with less computational complexity. Arbitrary orientated objects are detected by predicting the axis of the object, which is the line connecting the head and tail of the object, and the width of the object is vertical to the axis. By predicting objects at the pixel level of feature maps directly, the method avoids setting a number of hyperparameters related to anchor and is computationally efficient. Besides, a new aspect-ratio-aware orientation centerness method is proposed to better weigh positive pixel points, in order to guide the network to learn discriminative features from a complex background, which brings improvements for large aspect ratio object detection. The method is tested on two common aerial image datasets, achieving better performance compared with most one-stage orientated methods and many two-stage anchor-based methods with a simpler procedure and lower computational complexity.
Semi-Automatic Methodology for Fire Break Maintenance Operations Detection with Sentinel-2 Imagery and Artificial Neural Network
Authors: Pereira-Pires João E. , Aubard Valentine , Ribeiro Rita A. , Fonseca José M. , Silva João M. N. , Mora André
Published: March 2020

The difficult job of fighting fires and the nearly impossible task to stop a wildfire without great casualties requires an imperative implementation of proactive strategies. These strategies must decrease the number of fires, the burnt area and create better conditions for the firefighting. In this line of action, the Portuguese Institute of Nature and Forest Conservation defined a fire break network (FBN), which helps controlling wildfires. However, these fire breaks are efficient only if they are correctly maintained, which should be ensured by the local authorities and requires verification from the national authorities. This is a fastidious task since they have a large network of thousands of hectares to monitor over a full year. With the increasing quality and frequency of the Earth Observation Satellite imagery with Sentinel-2 and the definition of the FBN, a semi-automatic remote sensing methodology is proposed in this article for the detection of maintenance operations in a fire break. The proposed methodology is based on a time-series analysis, an object-based classification and a change detection process. The change detection is ensured by an artificial neural network, with reflectance bands and spectral indices as features. Additionally, an analysis of several bands and spectral indices is presented to show the behaviour of the data during a full year and in the presence of a maintenance operation. The proposed methodology achieved a relative error lower than 4% and a recall higher than 75% on the detection of maintenance operations.
Mapping and Monitoring Small-Scale Mining Activities in Ghana using Sentinel-1 Time Series (2015–2019)
Authors: Forkuor Gerald , Ullmann Tobias , Griesbeck Mario
Published: March 2020

Illegal small-scale mining (galamsey) in South-Western Ghana has grown tremendously in the last decade and caused significant environmental degradation. Excessive cloud cover in the area has limited the use of optical remote sensing data to map and monitor the extent of these activities. This study investigated the use of annual time-series Sentinel-1 data to map and monitor illegal mining activities along major rivers in South-Western Ghana between 2015 and 2019. A change detection approach, based on three time-series features—minimum, mean, maximum—was used to compute a backscatter threshold value suitable to identify/detect mining-induced land cover changes in the study area. Compared to the mean and maximum, the minimum time-series feature (in both VH and VV polarization) was found to be more sensitive to changes in backscattering within the period of investigation. Our approach permitted the detection of new illegal mining areas on an annual basis. A backscatter threshold value of +1.65 dB was found suitable for detecting illegal mining activities in the study area. Application of this threshold revealed illegal mining area extents of 102 km2, 60 km2 and 33 km2 for periods 2015/2016–2016/2017, 2016/2017–2017/2018 and 2017/2018–2018/2019, respectively. The observed decreasing trend in new illegal mining areas suggests that efforts at stopping illegal mining yielded positive results in the period investigated. Despite the advantages of Synthetic Aperture Radar data in monitoring phenomena in cloud-prone areas, our analysis revealed that about 25% of the Sentinel-1 data, mostly acquired in March and October (beginning and end of rainy season respectively), were unusable due to atmospheric effects from high intensity rainfall events. Further investigation in other geographies and climatic regions is needed to ascertain the susceptibility of Sentinel-1 data to atmospheric conditions.
Predicting Fine Particulate Matter (PM2.5) in the Greater London Area: An Ensemble Approach using Machine Learning Methods
Authors: Danesh Yazdi Mahdieh , Kuang Zheng , Dimakopoulou Konstantina , Barratt Benjamin , Suel Esra , Amini Heresh , Lyapustin Alexei , Katsouyanni Klea , Schwartz Joel
Published: March 2020

Estimating air pollution exposure has long been a challenge for environmental health researchers. Technological advances and novel machine learning methods have allowed us to increase the geographic range and accuracy of exposure models, making them a valuable tool in conducting health studies and identifying hotspots of pollution. Here, we have created a prediction model for daily PM2.5 levels in the Greater London area from 1st January 2005 to 31st December 2013 using an ensemble machine learning approach incorporating satellite aerosol optical depth (AOD), land use, and meteorological data. The predictions were made on a 1 km × 1 km scale over 3960 grid cells. The ensemble included predictions from three different machine learners: a random forest (RF), a gradient boosting machine (GBM), and a k-nearest neighbor (KNN) approach. Our ensemble model performed very well, with a ten-fold cross-validated R2 of 0.828. Of the three machine learners, the random forest outperformed the GBM and KNN. Our model was particularly adept at predicting day-to-day changes in PM2.5 levels with an out-of-sample temporal R2 of 0.882. However, its ability to predict spatial variability was weaker, with a R2 of 0.396. We believe this to be due to the smaller spatial variation in pollutant levels in this area.
Retrieval of Ocean Wind Speed Using Super-Resolution Delay-Doppler Maps
Authors: Wang Hao-Yu , Juang Jyh-Ching
Published: March 2020

The use of reflected Global Navigation Satellite System (GNSS) signals has shown to be effective for some remote sensing applications. In a GNSS Reflectometry (GNSS-R) system, a set of delay-Doppler maps (DDMs) related to scattered GNSS signals is formed and serves as a measurement of ocean wind speed and roughness. The design of the DDM receiver involves a trade-off between computation/communication complexity and the effectiveness of data retrieval. A fine-resolution DDM reveals more information in data retrieval while consuming more resources in terms of onboard processing and downlinking. As a result, existing missions typically use a compressed or low-resolution DDM as a data product, and a high-resolution DDM is processed for special purposes such as calibration. In this paper, a deep learning, super resolution algorithm is developed to construct a high-resolution DDM based on a low-resolution DDM. This may potentially enhance the data retrieval results with no impact on the instrument design. The proposed method is applied to process the DDM products disseminated by the Cyclone GNSS (CYGNSS) and the effectiveness of wind speed retrieval is demonstrated.
Geographic Disparity in Machine Intelligence Approaches for Archaeological Remote Sensing Research
Authors: Davis Dylan S.
Published: March 2020

A vast majority of the archaeological record, globally, is understudied and increasingly threatened by climate change, economic and political instability, and violent conflict. Archaeological data are crucial for understanding the past, and as such, documentation of this information is imperative. The development of machine intelligence approaches (including machine learning, artificial intelligence, and other automated processes) has resulted in massive gains in archaeological knowledge, as such computational methods have expedited the rate of archaeological survey and discovery via remote sensing instruments. Nevertheless, the progression of automated computational approaches is limited by distinct geographic imbalances in where these techniques are developed and applied. Here, I investigate the degree of this disparity and some potential reasons for this imbalance. Analyses from Web of Science and Microsoft Academic searches reveal that there is a substantial difference between the Global North and South in the output of machine intelligence remote sensing archaeology literature. There are also regional imbalances. I argue that one solution is to increase collaborations between research institutions in addition to data sharing efforts.
AgriLogger: A New Wireless Sensor for Monitoring Agrometeorological Data in Areas Lacking Communication Networks
Authors: Idbella Mohamed , Iadaresta Mariano , Gagliarde Graziano , Mennella Alberto , Mazzoleni Stefano , Bonanomi Giuliano
Published: March 2020

The use of wireless technologies in the field of agriculture, or so-called smart or precision agriculture, is considered as one of the main efforts applied nowadays to multiply the food production on earth. However, wireless sensor network (WSN) technology is still at its early development stage and its application in agriculture and food industry is still rare due to the lack of farmers’ awareness and outreach about the matter. This paper presents a new agro-sensor named AgriLogger with an aim to collect, store for long periods and transmit agrometeorological data represented by temperature and relative humidity in remote areas hard to reach and not served by telecommunication networks. The sensor exhibits long battery life, in the order of 10 years, thanks to low consumption technologies and to hardware sleep/wake up approach. It can be remotely placed on preselected sites through a customized drone. This latter, equipped with a dedicated payload, can then return on the sites where sensors have been placed, and, while hovering, wakes up the single devices and uploads their collected data through local wireless network. Field tests have demonstrated that the sensor, after being placed manually in two different positions, inside and outside a vineyard canopy, is able to collect and store successfully agrometeorological data like temperature and relative humidity. Moreover, the use of a drone potentially allows the collection of data from remote areas and, therefore, is able to provide a periodical monitoring of agro-ecological conditions.
Fast, Resource-Saving, and Anti-Collaborative Attack Trust Computing Scheme Based on Cross-Validation for Clustered Wireless Sensor Networks
Authors: Liu Chuanyi , Li Xiaoyong
Published: March 2020

The trust computing mechanism has an increasing role in the cooperative work of wireless sensor networks. However, the computing speed, resource overhead, and anti-collaborative attack ability of a trust mechanism itself are three key challenging issues for any open and resource-constrained wireless sensor networks. In this study, we propose a fast, resource-saving, and anti-collaborative attack trust computing scheme (FRAT) based on across-validation mechanism for clustered wireless sensor networks. First, according to the inherent relationship among three network entities (which are made up of three types of network nodes, namely base stations, cluster heads, and cluster members), we propose the cross-validation mechanism, which is effective and reliable against collaborative attacks caused by malicious nodes. Then, we adopt a fast and resource-saving trust computing scheme for cooperation between between cluster heads or cluster members. This scheme is suitable for wireless sensor networks because it facilitates resource-saving. Through theoretical analysis and experiments, the feasibility and effectiveness of the trust computing scheme proposed in this study are verified.