bluuebunny/crossref_metadata_2025 huggingface dataset:
Low Pre-Transplant Caveolin-1 Serum Concentrations Are Associated with Acute Cellular Tubulointerstitial Rejection in Kidney Transplantation
Authors: Emmerich Florian , Zschiedrich Stefan , Reichenbach-Braun Christine , Süsal Caner , Minguet Susana , Pauly Marie-Christin , Seidl Maximilian
Published: April 2021

Acute and chronic transplant rejections due to alloreactivity are essential contributors to graft loss. However, the strength of alloreactivity is biased by non-immunological factors such as ischemia reperfusion injury (IRI). Accordingly, protection from IRI could be favorable in terms of limiting graft rejection. Caveolin-1 (Cav-1) is part of the cell membrane and an important regulator of intracellular signaling. Cav-1 has been demonstrated to limit IRI and to promote the survival of a variety of cell types including renal cells under stress conditions. Accordingly, Cav-1 could also play a role in limiting anti-graft immune responses. Here, we evaluated a possible association between pre-transplant serum concentrations of Cav-1 and the occurrence of rejection during follow-up in a pilot study. Therefore, Cav-1-serum concentrations were analyzed in 91 patients at the time of kidney transplantation and compared to the incidence of acute and chronic rejection. Higher Cav-1 levels were associated with lower occurrence of acute cellular tubulointerstitial rejection episodes.
Accidental Impurities in Epitaxial Pb(Zr0.2Ti0.8)O3 Thin Films Grown by Pulsed Laser Deposition and Their Impact on the Macroscopic Electric Properties
Authors: Boni Georgia Andra , Chirila Cristina Florentina , Stancu Viorica , Amarande Luminita , Pasuk Iuliana , Trupina Lucian , Istrate Cosmin Marian , Radu Cristian , Tomulescu Andrei , Neatu Stefan , Pintilie Ioana , Pintilie Lucian
Published: April 2021

Structural and electrical properties of epitaxial Pb(Zr0.2Ti0.8)O3 films grown by pulsed laser deposition from targets with different purities are investigated in this study. One target was produced in-house by using high purity precursor oxides (at least 99.99%), and the other target was a commercial product (99.9% purity). It was found that the out-of-plane lattice constant is about 0.15% larger and the a domains amount is lower for the film grown from the commercial target. The polarization value is slightly lower, the dielectric constant is larger, and the height of the potential barrier at the electrode interfaces is larger for the film deposited from the pure target. The differences are attributed to the accidental impurities, with a larger amount in the commercial target as revealed by composition analysis using inductive coupling plasma-mass spectrometry. The heterovalent impurities can act as donors or acceptors, modifying the electronic characteristics. Thus, mastering impurities is a prerequisite for obtaining reliable and reproducible properties and advancing towards all ferroelectric devices.
The Effect of High Lignin Content on Oxidative Nanofibrillation of Wood Cell Wall
Authors: Jonasson Simon , Bünder Anne , Berglund Linn , Hertzberg Magnus , Niittylä Totte , Oksman Kristiina
Published: April 2021

Wood from field-grown poplars with different genotypes and varying lignin content (17.4 wt % to 30.0 wt %) were subjected to one-pot 2,2,6,6-Tetramethylpiperidin-1-yl)oxyl catalyzed oxidation and high-pressure homogenization in order to investigate nanofibrillation following simultaneous delignification and cellulose oxidation. When comparing low and high lignin wood it was found that the high lignin wood was more easily fibrillated as indicated by a higher nanofibril yield (68% and 45%) and suspension viscosity (27 and 15 mPa·s). The nanofibrils were monodisperse with diameter ranging between 1.2 and 2.0 nm as measured using atomic force microscopy. Slightly less cellulose oxidation (0.44 and 0.68 mmol·g−1) together with a reduced process yield (36% and 44%) was also found which showed that the removal of a larger amount of lignin increased the efficiency of the homogenization step despite slightly reduced oxidation of the nanofibril surfaces. The surface area of oxidized high lignin wood was also higher than low lignin wood (114 m2·g−1 and 76 m2·g−1) which implicates porosity as a factor that can influence cellulose nanofibril isolation from wood in a beneficial manner.
Biocompatible Magnetic Colloidal Suspension Used as a Tool for Localized Hyperthermia in Human Breast Adenocarcinoma Cells: Physicochemical Analysis and Complex In Vitro Biological Profile
Authors: Moacă Elena-Alina , Watz Claudia-Geanina , Socoliuc Vlad , Racoviceanu Roxana , Păcurariu Cornelia , Ianoş Robert , Cîntă-Pînzaru Simona , Tudoran Lucian , Nekvapil Fran , Iurciuc Stela , Șoica Codruța , Dehelean Cristina-Adriana
Published: April 2021

Magnetic iron oxide nanoparticles are the most desired nanomaterials for biomedical applications due to their unique physiochemical properties. A facile single-step process for the preparation of a highly stable and biocompatible magnetic colloidal suspension based on citric-acid-coated magnetic iron oxide nanoparticles used as an effective heating source for the hyperthermia treatment of cancer cells is presented. The physicochemical analysis revealed that the magnetic colloidal suspension had a z-average diameter of 72.7 nm at 25 °C with a polydispersity index of 0.179 and a zeta potential of −45.0 mV, superparamagnetic features, and a heating capacity that was quantified by an intrinsic loss power analysis. Raman spectroscopy showed the presence of magnetite and confirmed the presence of citric acid on the surfaces of the magnetic iron oxide nanoparticles. The biological results showed that breast adenocarcinoma cells (MDA-MB-231) were significantly affected after exposure to the magnetic colloidal suspension with a concentration of 30 µg/mL 24 h post-treatment under hyperthermic conditions, while the nontumorigenic (MCF-10A) cells exhibited a viability above 90% under the same thermal setup. Thus, the biological data obtained in the present study clearly endorse the need for further investigations to establish the clinical biological potential of synthesized magnetic colloidal suspension for magnetically triggered hyperthermia.
Assessment of Body Composition and Dietary Intake in Nursing-Home Residents: Could Lessons Learned from the COVID-19 Pandemic Be Used to Prevent Future Casualties in Older Individuals?
Authors: Keser Irena , Cvijetić Selma , Ilić Ana , Colić Barić Irena , Boschiero Dario , Ilich Jasminka Z.
Published: April 2021

The population of older adults, especially those living in the nursing homes, is growing. The sedentary lifestyle and possible poor nutrition in nursing homes place residents (NHRs) at risk for body composition impairments, malnutrition, and, subsequently, numerous chronic diseases. The aim of this study was to assess body composition (including body fluids) and dietary intake in NHRs. The association between osteosarcopenic adiposity syndrome (OSA) and its components, osteopenic adiposity (OA), sarcopenic adiposity (SA), and adiposity-only (AD), and specific macro- and micro-nutrients was evaluated as well. The study included 84 participants (82.1% women), aged 65.3–95.2 years. Body composition was assessed with an advanced bioelectrical impedance device BIA-ACC® and dietary intake was assessed via 24-h recall and analyzed using “Nutrition” software. The majority (95%) of participants were overweight with a high body fat and low muscle and bone mass, leading to a high prevalence of OSA (>50%), OA (13%), and AD (26%). There were only a few participants with SA, and they were not analyzed. The highest extracellular water/total body water ratio was observed in the OSA participants, indicating a heightened inflammatory state. Participants in all three body composition categories had a similar nutrient intake, with protein, fiber, omega-3 fatty acids, and almost all micronutrients being far below recommendations. In conclusion, a high prevalence of OSA among NHRs accompanied by a poor dietary intake, could place these residents at a very high risk for COVID-19 infections. Therefore, optimization of body composition and nutritional status should be included along with standard medical care in order to provide better health maintenance, particularly in the COVID-19 era.
From Food to Genes: Transcriptional Regulation of Metabolism by Lipids and Carbohydrates
Authors: Bravo-Ruiz Inés , Medina Miguel Ángel , Martínez-Poveda Beatriz
Published: April 2021

Lipids and carbohydrates regulate gene expression by means of molecules that sense these macronutrients and act as transcription factors. The peroxisome proliferator-activated receptor (PPAR), activated by some fatty acids or their derivatives, and the carbohydrate response element binding protein (ChREBP), activated by glucose-derived metabolites, play a key role in metabolic homeostasis, especially in glucose and lipid metabolism. Furthermore, the action of both factors in obesity, diabetes and fatty liver, as well as the pharmacological development in the treatment of these pathologies are indeed of high relevance. In this review we present an overview of the discovery, mechanism of activation and metabolic functions of these nutrient-dependent transcription factors in different tissues contexts, from the nutritional genomics perspective. The possibility of targeting these factors in pharmacological approaches is also discussed. Lipid and carbohydrate-dependent transcription factors are key players in the complex metabolic homeostasis, but these factors also drive an adaptive response to non-physiological situations, such as overeating. Possibly the decisive role of ChREBP and PPAR in metabolic regulation points to them as ideal therapeutic targets, but their pleiotropic functions in different tissues makes it difficult to “hit the mark”.
Dietary Changes among Adults in The Netherlands in the Period 2007–2010 and 2012–2016. Results from Two Cross-Sectional National Food Consumption Surveys
Authors: Dinnissen Ceciel S. , Ocké Marga C. , Buurma-Rethans Elly J. M. , van Rossum Caroline T. M.
Published: April 2021

Insight into dietary trends is important for the development and evaluation of dietary policies. The aim of this study is to describe changes in dietary intakes of Dutch adults and to evaluate these changes by age, gender, and education. In 2007–2010 and 2012–2016, two national food consumption surveys were conducted including 2106 and 1540 adults, respectively. Data collection included two non-consecutive 24 h dietary recalls. Mean habitual intakes of foods and nutrients relevant for a healthy diet of both surveys were estimated. Between the two periods the mean consumption of red or processed meat, dairy, sodium and alcohol and the ratio of whole-grain to cereal products decreased by 4–30% and the consumption of fibre and unsaturated fatty acids increased by about 3% and 6%, respectively. For most food groups, changes in consumption were comparable for both sexes and in all age groups. A healthier consumption pattern and several favorable changes were observed among higher-educated people. Most, but not all, changes in food consumption are favorable from a public health point of view. However, there is still a large potential for further improvements. A healthier consumption pattern was observed in adults with a higher educational level which calls for attention to social disparities when developing dietary policies.
Diet Significantly Influences the Immunopathology and Severity of Kidney Injury in Male C57Bl/6J Mice in a Model Dependent Manner
Authors: Brus John E. , Quan Daniel L. , Wiley Kristin J. , Browning Brittney , Ter Haar Hannah , Lutz Riley , Houghton Jeffrey F. , Gigliotti Joseph C.
Published: April 2021

Diet is a leading causative risk factor for morbidity and mortality worldwide, yet it is rarely considered in the design of preclinical animal studies. Several of the nutritional inadequacies reported in Americans have been shown to be detrimental to kidney health; however, the mechanisms responsible are unclear and have been largely attributed to the development of diabetes or hypertension. Here, we set out to determine whether diet influences the susceptibility to kidney injury in male C57Bl/6 mice. Mice were fed a standard chow diet, a commercially available “Western” diet (WD), or a novel Americanized diet (AD) for 12 weeks prior to the induction of kidney injury using the folic acid nephropathy (FAN) or unilateral renal ischemia reperfusion injury (uIRI) models. In FAN, the mice that were fed the WD and AD had worse histological evidence of tissue injury and greater renal expression of genes associated with nephrotoxicity as compared to mice fed chow. Mice fed the AD developed more severe renal hypertrophy following FAN, and gene expression data suggest the mechanism for FAN differed among the diets. Meanwhile, mice fed the WD had the greatest circulating interleukin-6 concentrations. In uIRI, no difference was observed in renal tissue injury between the diets; however, mice fed the WD and AD displayed evidence of suppressed inflammatory response. Taken together, our data support the hypothesis that diet directly impacts the severity and pathophysiology of kidney disease and is a critical experimental variable that needs to be considered in mechanistic preclinical animal studies.
An Intermittent Fasting Mimicking Nutrition Bar Extends Physiologic Ketosis in Time Restricted Eating: A Randomized, Controlled, Parallel-Arm Study
Authors: Huang Angie W. , Wei Min , Caputo Sara , Wilson Melissa L. , Antoun Joseph , Hsu William C.
Published: April 2021

There has been increasing interest in time-restricted eating to attain intermittent fasting’s metabolic benefits. However, a more extended daily fast poses many challenges. This study was designed to evaluate the effects of a 200-calorie fasting-mimicking diet (FMD) energy bar formulated to prolong ketogenesis and mitigate fasting-associated side effects. A randomized, controlled study was conducted comparing the impact of consuming an FMD bar vs. continued water fast, after a 15-h overnight fast. Subjects in the FMD group showed a 3-h postprandial beta-hydroxybutyrate (BHB) level and 4-h postprandial BHB area under the curve (AUC0–4) that were non-inferior to those who continued with the water fast (p = 0.891 and p = 0.377, respectively). The postprandial glucose AUC0–4 in the FMD group was non-inferior to that in the water fast group (p = 0.899). A breakfast group served as a control, which confirmed that the instrument used in home glucose and ketone monitoring functioned as expected. The results indicate that FMD bar consumption does not interfere with the physiological ketogenesis associated with overnight fasting and could be used to facilitate the practice of time-restricted eating or intermittent fasting.
Genomic Identification of Multidrug-Resistant Salmonella Virchow Monophasic Variant Causing Human Septic Arthritis
Authors: Wang Zhenyu , Xu Haiyan , Chu Chao , Tang Yuanyue , Li Qiuchun , Jiao Xinan
Published: April 2021

The monophasic variant of Salmonella Typhimurium has emerged and increased rapidly worldwide during the past two decades. The loss of genes encoding the second-phase flagella and the acquirement of the multi-drug resistance cassette are the main genomic characteristics of the S. Typhimurium monophasic variant. In this study, two Salmonella strains were isolated from the knee effusion and feces of a 4-year-old girl who presented with a case of septic arthritis and fever, respectively. Primary serovar identification did not detect the second-phase flagellar antigens of the strains using the classical slide agglutination test. Whole-genome sequencing analysis was performed to reveal that the replacement of the fljAB operon by a 4.8-kb cassette from E. coli caused the non-expression of phase-2 flagellar antigens of the strains, which were confirmed to be a novel S. Virchow monophasic variant (Salmonella 6,7,14:r:-) by core-genome multi-locus sequence typing (cgMLST). Compared to the 16 published S. Virchow genomes, the two strains shared a unique CRISPR type of VCT12, and showed a close genetic relationship to S. Virchow BCW_2814 and BCW_2815 strains, isolated from Denmark and China, respectively, based on cgMLST and CRISPR typing. Additionally, the acquisition of Salmonella genomic island 2 (SGI2) with an antimicrobial resistance gene cassette enabled the strains to be multidrug-resistant to chloramphenicol, tetracycline, trimethoprim, and sulfamethoxazole. The emergence of the multidrug-resistant S. Virchow monophasic variant revealed that whole-genome sequencing and CRISPR typing could be applied to identify the serovaraints of Salmonella enterica strains in the national Salmonella surveillance system.
Seasonal Stability of SARS-CoV-2 in Biological Fluids
Authors: Kwon Taeyong , Gaudreault Natasha N. , Richt Juergen A.
Published: April 2021

The transmission of SARS-CoV-2 occurs by close contact with infected persons through droplets, the inhalation of infectious aerosols, and the exposure to contaminated surfaces. Previously, we determined the virus stability on different types of surfaces under indoor and seasonal climatic conditions. SARS-CoV-2 survived the longest on surfaces under winter conditions, followed by spring/fall and summer conditions, suggesting the seasonal pattern of stability on surfaces. However, under natural conditions, the virus is secreted in various biological fluids from infected humans. In this respect, it remains unclear how long the virus survives in various types of biological fluids. This study explores SARS-CoV-2 stability in virus-spiked human biological fluids under different environmental conditions by determining the virus half-life. The virus was stable for up to 21 days in nasal mucus, sputum, saliva, tear, urine, blood, and semen; it remained infectious significantly longer under winter and spring/fall conditions than under summer conditions. In contrast, the virus was only stable up to 24 h in feces and breast milk. These findings demonstrate the potential risk of infectious biological fluids in SARS-CoV-2 transmission and have implications for its seasonality.
Molecular Modeling of Protein Corona Formation and Its Interactions with Nanoparticles and Cell Membranes for Nanomedicine Applications
Authors: Lee Hwankyu
Published: April 2021

The conformations and surface properties of nanoparticles have been modified to improve the efficiency of drug delivery. However, when nanoparticles flow through the bloodstream, they interact with various plasma proteins, leading to the formation of protein layers on the nanoparticle surface, called protein corona. Experiments have shown that protein corona modulates nanoparticle size, shape, and surface properties and, thus, influence the aggregation of nanoparticles and their interactions with cell membranes, which can increases or decreases the delivery efficiency. To complement these experimental findings and understand atomic-level phenomena that cannot be captured by experiments, molecular dynamics (MD) simulations have been performed for the past decade. Here, we aim to review the critical role of MD simulations to understand (1) the conformation, binding site, and strength of plasma proteins that are adsorbed onto nanoparticle surfaces, (2) the competitive adsorption and desorption of plasma proteins on nanoparticle surfaces, and (3) the interactions between protein-coated nanoparticles and cell membranes. MD simulations have successfully predicted the competitive binding and conformation of protein corona and its effect on the nanoparticle–nanoparticle and nanoparticle–membrane interactions. In particular, simulations have uncovered the mechanism regarding the competitive adsorption and desorption of plasma proteins, which helps to explain the Vroman effect. Overall, these findings indicate that simulations can now provide predications in excellent agreement with experimental observations as well as atomic-scale insights into protein corona formation and interactions.
Effect of Application Amounts on In Vitro Dermal Absorption Test Using Caffeine and Testosterone
Authors: Im Jueng-Eun , Kim Hyang Yeon , Lee Jung Dae , Park Jin-Ju , Kang Kyung-Soo , Kim Kyu-Bong
Published: April 2021

Dermal absorption of chemicals is a key factor in risk assessment. This study investigated the effects of different amounts of application on dermal absorption and suggested an appropriate application dose for proper dermal absorption. Caffeine and testosterone were chosen as test compounds. An in vitro dermal absorption test was performed using a Franz diffusion cell. Different amounts (5, 10, 25, and 50 mg (or µL)/cm2) of semisolid (cream) and liquid (solution) formulations containing 1% caffeine and 0.1% testosterone were applied to rat and minipig (Micropig®) skins. After 24 h, the concentrations of both compounds remaining on the skin surface and in the stratum corneum, dermis and epidermis, and receptor fluid were determined using LC-MS / MS or HPLC. Dermal absorption of both compounds decreased with increasing amounts of application in both skin types (rat and minipig) and formulations (cream and solution). Especially, dermal absorptions (%) of both compounds at 50 mg (or µL)/cm2 was significantly lower compared to 5 or 10 mg (or µL)/cm2 in both rat and minipig skins. Therefore, a low dose (5 or 10 mg (or µL)/cm2) of the formulation should be applied to obtain conservative dermal absorption.
Heat Unit Requirements of “Flame Seedless” Table Grape: A Tool to Predict Its Harvest Period in Protected Cultivation
Authors: Alonso Francisca , Chiamolera Fernando M. , Hueso Juan J. , González Mónica , Cuevas Julián
Published: April 2021

Greenhouse cultivation of table grapes is a challenge due to difficulties imposed by their perennial habit and chilling requirements. Despite difficulties, greenhouse cultivation allows ripening long before that in the open field. Nonetheless, for harvesting “Flame Seedless” in the most profitable periods, a cultural practices timetable has to be established. In this context, an estimation of development rate as a function of temperature becomes essential. This work puts forward a procedure to determine “Flame Seedless” threshold temperatures and heat requirements from bud break to ripening. “Flame Seedless” required an average of 1633 growing degree days (GDD) in the open field with a base temperature of 5 °C and an upper threshold temperature of 30 °C. Strikingly, only 1542 GDD were required within the greenhouse. This procedure forecast “Flame Seedless” ripening with an accuracy of three and six days in the open field and greenhouse, improving predictions based on the average number of days between bud break and ripening. The procedure to predict oncoming harvest date was found satisfactory, just four days earlier than the real date. If we used the typical meteorological year instead of the average year, then the prediction was greatly improved since harvest was forecast just one day before its occurrence.
Preparation and Characterization of Chitosan-Coated Manganese-Ferrite Nanoparticles Conjugated with Laccase for Environmental Bioremediation
Authors: Apriceno Azzurra , Silvestro Ilaria , Girelli Annamaria , Francolini Iolanda , Pietrelli Loris , Piozzi Antonella
Published: April 2021

Bioremediation with immobilized enzymes has several advantages, such as the enhancement of selectivity, activity, and stability of biocatalysts, as well as enzyme reusability. Laccase has proven to be a good candidate for the removal of a wide range of contaminants. In this study, naked or modified MnFe2O4 magnetic nanoparticles (MNPs) were used as supports for the immobilization of laccase from Trametes versicolor. To increase enzyme loading and stability, MNPs were coated with chitosan both after the MNP synthesis (MNPs-CS) and during their formation (MNPs-CSin situ). SEM analysis showed different sizes for the two coated systems, 20 nm and 10 nm for MNPs-CS and MNPs-CSin situ, respectively. After covalent immobilization of laccase by glutaraldehyde, the MNPs-CSin situ-lac and MNPs-CS-lac systems showed a good resistance to temperature denaturation and storage stability. The most promising system for use in repeated batches was MNPs-CSin situ-lac, which degraded about 80% of diclofenac compared to 70% of the free enzyme. The obtained results demonstrated that the MnFe2O4-CSin situ system could be an excellent candidate for the removal of contaminants.
Pole Location and Input Constrained Robust Fuzzy Control for T-S Fuzzy Models Subject to Passivity and Variance Requirements
Authors: Qiao Hongyu , Chang Wen-Jer , Lin Yann-Horng , Lin Yu-Wei
Published: April 2021

In this paper, a robust fuzzy controller for stochastic nonlinear systems subject to multiple performance constraints is discussed. To solve the problem of stochastic behaviors in nonlinear systems, the covariance control theory and passive control theory are applied based on the concept of energy. Additionally, the pole placement method is considered for the better transient behaviors of the system responses. However, it is known that the control inputs and maximum overshoot of the system responses may become bigger at the same time when the settling time or converge rate of the system is required to be faster. Due to this reason, the input constraint is also considered in the fuzzy controller design method to limit the value of the control gain. Moreover, an effective robust control method is applied to deal with the perturbation of the nonlinear systems. Based on the above performance constraints, the sufficient conditions can be obtained to achieve the stability in the sense of mean square and the multi-performance requirements. Finally, simulation results of the nonlinear synchronous generator system are presented to verify the feasibility and efficiency of the proposed control method.
Comprehensive Analysis of Mutation-Based and Expressed Genes-Based Pathways in Head and Neck Squamous Cell Carcinoma
Authors: Keam Bhumsuk , Park Jin-Young , Kim Jin-Pyo , Kim Gun-Do , Yu Yun-Suk , Cho Sang-Hee , Kim Sangwoo , Ahn Hee-Kyung , Chun Sang-Hoon , Kwon Jung-Hye , Yun Tak , Kim Ji-Won , Kim Ji-Eun , Ahn Myung-Ju , Kim Joo-Hang , Yun Hwan-Jung
Published: April 2021

Over- or under-expression of mRNA results from genetic alterations. Comprehensive pathway analyses based on mRNA expression are as important as single gene level mutations. This study aimed to compare the mutation- and mRNA expression-based signaling pathways in head and neck squamous cell carcinoma (HNSCC) and to match these with potential drug or druggable pathways. Altogether, 93 recurrent/metastatic HNSCC patients were enrolled. We performed targeted gene sequencing using Illumina HiSeq-2500 for NGS, and nanostring nCounter® for mRNA expression; mRNA expression was classified into over- or under-expression groups based on the expression. We investigated mutational and nanostring data using the CBSJukebox® system, which is a big-data driven platform to analyze druggable pathways, genes, and protein-protein interaction. We calculated a Treatment Benefit Prediction Score (TBPS) to identify suitable drugs. By mapping the high score interaction genes to identify druggable pathways, we found highly related signaling pathways with mutations. Based on the mRNA expression and interaction gene scoring model, several pathways were found to be associated with over- and under-expression. Mutation-based pathways were associated with mRNA under-expressed genes-based pathways. These results suggest that HNSCCs are mainly caused by the loss-of-function mutations. TBPS found several matching drugs such as immune checkpoint inhibitors, EGFR inhibitors, and FGFR inhibitors.
Online Peer Counseling for Suicidal Ideation: Participant Characteristics and Reasons for Using or Refusing This Service
Authors: Weiss Maren , Hildebrand Anja , Braun-Scharm Hellmuth , Stemmler Mark
Published: April 2021

[U25] is a German online-peer-counseling service for adolescents with suicidal ideation, who typically do not seek or receive adequate counseling. We conducted an online survey in order to compare persons who receive online counseling by [U25] compared to those who are visitors of [U25] websites but do not (yet) receive counseling. Via online survey, all visitors to the [U25] websites were invited to fill in a questionnaire on sociodemographic data, utilization reasons, and barriers. Our final sample consisted of n = 318 counseling clients, n = 1127 persons who have not yet sought help but intend to do so (“prospective clients”), and n = 444 persons who do not consider [U25] counseling for themselves (“refusers”). Clients were more often female and showed positive attitudes toward online counseling. Low perceived need for counseling was the most frequent barrier reported by the refusers, whereas fear of stigma and practical barriers were rarely reported; younger and male refusers reported needing to write down one’s problems as a barrier more often. Self-selection might reduce generalizability of our results. Online counseling can facilitate receiving psychosocial support for young persons with suicidal ideation, particularly if barriers are addressed.
Understanding Moral Disagreement: A Christian Perspectivalist Approach
Authors: McAllister Blake
Published: April 2021

Deep moral disagreements exist between Christians and non-Christians. I argue that Christians should resist the temptation to pin all such disagreements on the irrationality of their disputants. To this end, I develop an epistemological framework on which both parties can be rational—the key being that their beliefs are formed from different perspectives and, hence, on the basis of different sets of evidence. I then alleviate concerns that such moral perspectivalism leads to relativism or skepticism, or that it prohibits rational discourse. I end by exploring new avenues for resolving deep moral disagreements opened up by the perspectivalist approach.
An Overview of Verification and Validation Challenges for Inspection Robots
Authors: Fisher Michael , Cardoso Rafael C. , Collins Emily C. , Dadswell Christopher , Dennis Louise A. , Dixon Clare , Farrell Marie , Ferrando Angelo , Huang Xiaowei , Jump Mike , Kourtis Georgios , Lisitsa Alexei , Luckcuck Matt , Luo Shan , Page Vincent , Papacchini Fabio , Webster Matt
Published: April 2021

The advent of sophisticated robotics and AI technology makes sending humans into hazardous and distant environments to carry out inspections increasingly avoidable. Being able to send a robot, rather than a human, into a nuclear facility or deep space is very appealing. However, building these robotic systems is just the start and we still need to carry out a range of verification and validation tasks to ensure that the systems to be deployed are as safe and reliable as possible. Based on our experience across three research and innovation hubs within the UK’s “Robots for a Safer World” programme, we present an overview of the relevant techniques and challenges in this area. As the hubs are active across nuclear, offshore, and space environments, this gives a breadth of issues common to many inspection robots.
Sea Ice Classification of SAR Imagery Based on Convolution Neural Networks
Authors: Khaleghian Salman , Ullah Habib , Kræmer Thomas , Hughes Nick , Eltoft Torbjørn , Marinoni Andrea
Published: April 2021

We explore new and existing convolutional neural network (CNN) architectures for sea ice classification using Sentinel-1 (S1) synthetic aperture radar (SAR) data by investigating two key challenges: binary sea ice versus open-water classification, and a multi-class sea ice type classification. The analysis of sea ice in SAR images is challenging because of the thermal noise effects and ambiguities in the radar backscatter for certain conditions that include the reflection of complex information from sea ice surfaces. We use manually annotated SAR images containing various sea ice types to construct a dataset for our Deep Learning (DL) analysis. To avoid contamination between classes we use a combination of near-simultaneous SAR images from S1 and fine resolution cloud-free optical data from Sentinel-2 (S2). For the classification, we use data augmentation to adjust for the imbalance of sea ice type classes in the training data. The SAR images are divided into small patches which are processed one at a time. We demonstrate that the combination of data augmentation and training of a proposed modified Visual Geometric Group 16-layer (VGG-16) network, trained from scratch, significantly improves the classification performance, compared to the original VGG-16 model and an ad hoc CNN model. The experimental results show both qualitatively and quantitatively that our models produce accurate classification results.
Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels
Authors: Groh Andreas , Horwath Martin
Published: April 2021

We derived gravimetric mass change products, i.e., gridded and basin-averaged mass changes, for the Antarctic Ice Sheet (AIS) from time-variable gravity-field solutions acquired by the Gravity Recovery and Climate Experiment (GRACE) mission and its successor GRACE-FO, covering more than 18 years. For this purpose, tailored sensitivity kernels (TSKs) were generated for the application in a regional integration approach. The TSKs were inferred in a formal optimization approach minimizing the sum of both propagated mission errors and leakage errors. We accounted for mission errors by means of an empirical error covariance model, while assumptions on signal variances of potential sources of leakage were used to minimize leakage errors. To identify the optimal parameters to be used in the TSK generation, we assessed a set of TSKs by quantifying signal leakage from the processing of synthetic data and by inferring the noise level of the derived basin products. The finally selected TSKs were used to calculate mass change products from GRACE/GRACE-FO Level-2 spherical harmonic solutions covering 2002-04 to 2020-07. These products were compared to external data sets from satellite altimetry and the input–output method. For the period under investigation, the mass balance of the AIS was quantified to be −90.9±43.5 Gt a−1, corresponding to a mean sea-level rise of 0.25±0.12 mm a−1.
Toward Large-Scale Mapping of Tree Crops with High-Resolution Satellite Imagery and Deep Learning Algorithms: A Case Study of Olive Orchards in Morocco
Authors: Lin Chenxi , Jin Zhenong , Mulla David , Ghosh Rahul , Guan Kaiyu , Kumar Vipin , Cai Yaping
Published: April 2021

Timely and accurate monitoring of tree crop extent and productivities are necessary for informing policy-making and investments. However, except for a very few tree species (e.g., oil palms) with obvious canopy and extensive planting, most small-crown tree crops are understudied in the remote sensing domain. To conduct large-scale small-crown tree mapping, several key questions remain to be answered, such as the choice of satellite imagery with different spatial and temporal resolution and model generalizability. In this study, we use olive trees in Morocco as an example to explore the two abovementioned questions in mapping small-crown orchard trees using 0.5 m DigitalGlobe (DG) and 3 m Planet imagery and deep learning (DL) techniques. Results show that compared to DG imagery whose mean overall accuracy (OA) can reach 0.94 and 0.92 in two climatic regions, Planet imagery has limited capacity to detect olive orchards even with multi-temporal information. The temporal information of Planet only helps when enough spatial features can be captured, e.g., when olives are with large crown sizes (e.g., >3 m) and small tree spacings (e.g., <3 m). Regarding model generalizability, experiments with DG imagery show a decrease in F1 score up to 5% and OA to 4% when transferring models to new regions with distribution shift in the feature space. Findings from this study can serve as a practical reference for many other similar mapping tasks (e.g., nuts and citrus) around the world.
A Submonthly Surface Water Classification Framework via Gap-Fill Imputation and Random Forest Classifiers of Landsat Imagery
Authors: Labuzzetta Charles , Zhu Zhengyuan , Chang Xinyue , Zhou Yuyu
Published: April 2021

Global surface water classification layers, such as the European Joint Research Centre’s (JRC) Monthly Water History dataset, provide a starting point for accurate and large scale analyses of trends in waterbody extents. On the local scale, there is an opportunity to increase the accuracy and temporal frequency of these surface water maps by using locally trained classifiers and gap-filling missing values via imputation in all available satellite images. We developed the Surface Water IMputation (SWIM) classification framework using R and the Google Earth Engine computing platform to improve water classification compared to the JRC study. The novel contributions of the SWIM classification framework include (1) a cluster-based algorithm to improve classification sensitivity to a variety of surface water conditions and produce approximately unbiased estimation of surface water area, (2) a method to gap-fill every available Landsat image for a region of interest to generate submonthly classifications at the highest possible temporal frequency, (3) an outlier detection method for identifying images that contain classification errors due to failures in cloud masking. Validation and several case studies demonstrate the SWIM classification framework outperforms the JRC dataset in spatiotemporal analyses of small waterbody dynamics with previously unattainable sensitivity and temporal frequency. Most importantly, this study shows that reliable surface water classifications can be obtained for all pixels in every available Landsat image, even those containing cloud cover, after performing gap-fill imputation. By using this technique, the SWIM framework supports monitoring water extent on a submonthly basis, which is especially applicable to assessing the impact of short-term flood and drought events. Additionally, our results contribute to addressing the challenges of training machine learning classifiers with biased ground truth data and identifying images that contain regions of anomalous classification errors.
Application and Evaluation of a Deep Learning Architecture to Urban Tree Canopy Mapping
Authors: Wang Zhe , Fan Chao , Xian Min
Published: April 2021

Urban forest is a dynamic urban ecosystem that provides critical benefits to urban residents and the environment. Accurate mapping of urban forest plays an important role in greenspace management. In this study, we apply a deep learning model, the U-net, to urban tree canopy mapping using high-resolution aerial photographs. We evaluate the feasibility and effectiveness of the U-net in tree canopy mapping through experiments at four spatial scales—16 cm, 32 cm, 50 cm, and 100 cm. The overall performance of all approaches is validated on the ISPRS Vaihingen 2D Semantic Labeling dataset using four quantitative metrics, Dice, Intersection over Union, Overall Accuracy, and Kappa Coefficient. Two evaluations are performed to assess the model performance. Experimental results show that the U-net with the 32-cm input images perform the best with an overall accuracy of 0.9914 and an Intersection over Union of 0.9638. The U-net achieves the state-of-the-art overall performance in comparison with object-based image analysis approach and other deep learning frameworks. The outstanding performance of the U-net indicates a possibility of applying it to urban tree segmentation at a wide range of spatial scales. The U-net accurately recognizes and delineates tree canopy for different land cover features and has great potential to be adopted as an effective tool for high-resolution land cover mapping.
Mapping Riparian Habitats of Natura 2000 Network (91E0*, 3240) at Individual Tree Level Using UAV Multi-Temporal and Multi-Spectral Data
Authors: Belcore Elena , Pittarello Marco , Lingua Andrea Maria , Lonati Michele
Published: April 2021

Riparian habitats provide a series of ecological services vital for the balance of the environment, and are niches and resources for a wide variety of species. Monitoring riparian environments at the intra-habitat level is crucial for assessing and preserving their conservation status, although it is challenging due to their landscape complexity. Unmanned aerial vehicles (UAV) and multi-spectral optical sensors can be used for very high resolution (VHR) monitoring in terms of spectral, spatial, and temporal resolutions. In this contribution, the vegetation species of the riparian habitat (91E0*, 3240 of Natura 2000 network) of North-West Italy were mapped at individual tree (ITD) level using machine learning and a multi-temporal phenology-based approach. Three UAV flights were conducted at the phenological-relevant time of the year (epochs). The data were analyzed using a structure from motion (SfM) approach. The resulting orthomosaics were segmented and classified using a random forest (RF) algorithm. The training dataset was composed of field-collected data, and was oversampled to reduce the effects of unbalancing and size. Three-hundred features were computed considering spectral, textural, and geometric information. Finally, the RF model was cross-validated (leave-one-out). This model was applied to eight scenarios that differed in temporal resolution to assess the role of multi-temporality over the UAV’s VHR optical data. Results showed better performances in multi-epoch phenology-based classification than single-epochs ones, with 0.71 overall accuracy compared to 0.61. Some classes, such as Pinus sylvestris and Betula pendula, are remarkably influenced by the phenology-based multi-temporality: the F1-score increased by 0.3 points by considering three epochs instead of two.
Smart City Solution Engineering
Authors: Delsing Jerker
Published: April 2021

Many smart city applications have been proposed and demonstrated over the years; however, moving to large-scale deployment is still scarce. A contributing factor to this scarcity is the lack of well-established engineering methodologies for large-scale smart city applications. This paper addresses engineering methodologies and tools for large-scale smart city application engineering, implementation, deployment, and evolution. A model-based engineering approach based on IoT, SOA, and SysML is proposed and applied to a smart streetlight application. Engineering considerations for streetlight area enlargement and updated technology generations with additional capabilities are discussed. The proposed model-based engineering approach provides considerable scaling simplifications and opportunities for considerable savings on engineering costs. The model-based engineering approach also provides good documentation that enables technology evolution specifications that support both maintenance and emerging behaviours.
Assessing the Impacts of Climate Variations on the Potato Production in Bangladesh: A Supply and Demand Model Approach
Authors: Jannat Arifa , Ishikawa-Ishiwata Yuki , Furuya Jun
Published: April 2021

From the perspective of nutritional security, we investigated the influence of climate change on potato production in Bangladesh using a supply and demand model by considering the potato as an important non-cereal food crop. To provide an outlook on the variation in potato supplies and market prices under changing climatic factors (temperature, rainfall, and solar-radiation), the yield, area, import, and demand functions were assessed using district-level time-series data of Bangladesh (1988–2013), disaggregated into seven climatic zones. Results suggest that temperatures above or below the optimal range (18–22 °C) lowered yields. Little rainfall and low solar radiation hinder potato cultivation areas during the potato maturity stage. During the simulated period, the annual production was projected to rise from 88 to 111 million metric tons (MT), with an equilibrium farm price of 155 to 215 US dollars MT−1. Between 2014 and 2030, the nation’s per-capita potato intake is expected to increase from 49 to 55 kg year−1 because of changing dietary patterns. According to the estimated equilibrator, scenario simulations that incorporated various dimensions of Intergovernmental Panel on Climate Change (IPCC) scenarios indicate that potato production and consumption can increase in the future.
Construction Sector Contribution to Economic Stability: Malaysian GDP Distribution
Authors: Alaloul Wesam Salah , Musarat Muhammad Ali , Rabbani Muhammad Babar Ali , Iqbal Qaiser , Maqsoom Ahsen , Farooq Waqas
Published: April 2021

The construction sector exerts an exceptional impact on economic development all over the world. Adequate buildings and infrastructures made by the construction sector ensure that a country reaches certain targets like social development, industrialization, freight transportation, sustainable development, and urbanization. This study aims to determine the construction sector’s connectivity with other sectors through complex linkages that contribute immensely to the economy and gross domestic product (GDP). The data were collected from the Department of Statistics Malaysia and the World Bank from the year 1970 to 2019, and the Pearson correlation test, the cointegration test, and the Granger causality test were conducted. The vector error correction model (VECM) was created for short-term and long-term equilibrium analysis and impulse response function (IRF) was performed to study construction industry behavior. Afterwards, the forecasting was done for the year 2020 to 2050 of the Malaysian economy and GDP for the required sectors. It was revealed that some sectors, such as agriculture and services, have forward linkages while other sectors, such as manufacturing and mining, are independent of construction sector causality, which signifies the behavior of the contributing sectors when a recession occurs, hence generating significant revenue. The Malaysian economy is moving towards sustainable production with more emphasis on the construction sector. The outcome can be used as a benchmark by other countries to achieve sustainable development. The significance of this study is its usefulness for experts all over the world in terms of allocating resources to make the construction sector a sustainable sector after receiving a shock. A sustainable conceptual framework has been suggested for global application that shows the factors involved in the growth of the construction industry to ensure its sustainable development with time.