bluuebunny/crossref_metadata_2025 huggingface dataset:
Mouthguard Use Effect on the Biomechanical Response of an Ankylosed Maxillary Central Incisor during a Traumatic Impact: A 3-Dimensional Finite Element Analysis
Authors: Borges Alexandre Luiz Souto , Dal Piva Amanda Maria de Oliveira , Concílio Laís Regiane da Silva , Paes-Junior Tarcisio José de Arruda , Tribst João Paulo Mendes
Published: November 2020

(1) Background: Trauma is a very common experience in contact sports; however, there is an absence of data regarding the effect of athletes wearing mouthguards (MG) associated with ankylosed maxillary central incisor during a traumatic impact. (2) Methods: To evaluate the stress distribution in the bone and teeth in this situation, models of maxillary central incisor were created containing cortical bone, trabecular bone, soft tissue, root dentin, enamel, periodontal ligament, and antagonist teeth were modeled. One model received a MG with 4-mm thickness. Both models were subdivided into finite elements. The frictionless contacts were used and a nonlinear dynamic impact analysis was performed in which a rigid object hit the model at 1 m·s−1. For each model, an ankylosed periodontal ligament was simulated totaling 4 different situations. The results were presented in von-Mises stress maps. (3) Results: A higher stress concentration in teeth and bone was observed for the model without a MG and with ankylosed tooth (19.5 and 37.3 MPa, respectively); the most promising mechanical response was calculated for patients with healthy periodontal ligament and MG in position (1.8 and 7.8 MPa, respectively). (4) Conclusions: The MG’s use is beneficial for healthy and ankylosed teeth, since it acts by dampening the generated stresses in bone, dentin, enamel and periodontal ligament. However, patients with ankylosed tooth are more prone to root fracture even when the MG is in position compared to a healthy tooth.
Combined Optimization Prediction Model of Regional Wind Power Based on Convolution Neural Network and Similar Days
Authors: Li Yalong , Yang Fan , Zha Wenting , Yan Licheng
Published: November 2020

With the continuous optimization of energy structures, wind power generation has become the dominant new energy source. The strong random fluctuation of natural wind will bring challenges to power system dispatching, so it is necessary to predict wind power. In order to improve the short-term prediction accuracy of regional wind power, this paper proposes a new combination prediction model based on convolutional neural network (CNN) and similar days analysis. Firstly, the least square fitting and batch normalization (BN) are used to preprocess the data, and then the recent historical wind power data set for CNN is established. Secondly, the Pearson correlation coefficient and cosine similarity combination method are utilized to find similar days in the long-term data set, and the prediction model based on similar days is constructed by the weighting method. Finally, based on the particle swarm optimization (PSO) method, a combined forecasting model is established. The results show that the combined model can accurately predict the future short-term wind power curve, and the prediction accuracy is improved to different extents compared to a single method.
Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation
Authors: Napole Cristian , Barambones Oscar , Calvo Isidro , Derbeli Mohamed , Silaa Mohammed Yousri , Velasco Javier
Published: November 2020

Piezoelectric actuators (PEA) are devices that are used for nano- microdisplacement due to their high precision, but one of the major issues is the non-linearity phenomena caused by the hysteresis effect, which diminishes the positioning performance. This study presents a novel control structure in order to reduce the hysteresis effect and increase the PEA performance by using a fuzzy logic control (FLC) combined with a Hammerstein–Wiener (HW) black-box mapping as a feedforward (FF) compensation. In this research, a proportional-integral-derivative (PID) was contrasted with an FLC. From this comparison, the most accurate was taken and tested with a complex structure with HW-FF to verify the accuracy with the increment of complexity. All of the structures were implemented in a dSpace platform to control a commercial Thorlabs PEA. The tests have shown that an FLC combined with HW was the most accurate, since the FF compensate the hysteresis and the FLC reduced the errors; the integral of the absolute error (IAE), the root-mean-square error (RMSE), and relative root-mean-square-error (RRMSE) for this case were reduced by several magnitude orders when compared to the feedback structures. As a conclusion, a complex structure with a novel combination of FLC and HW-FF provided an increment in the accuracy for a high-precision PEA.
Use of Correlated Data for Nonparametric Prediction of a Spatial Target Variable
Authors: García-Soidán Pilar , Cotos-Yáñez Tomás R.
Published: November 2020

The kriging methodology can be applied to predict the value of a spatial variable at an unsampled location, from the available spatial data. Furthermore, additional information from secondary variables, correlated with the target one, can be included in the resulting predictor by using the cokriging techniques. The latter procedures require a previous specification of the multivariate dependence structure, difficult to characterize in practice in an appropriate way. To simplify this task, the current work introduces a nonparametric kernel approach for prediction, which satisfies good properties, such as asymptotic unbiasedness or the convergence to zero of the mean squared prediction error. The selection of the bandwidth parameters involved is also addressed, as well as the estimation of the remaining unknown terms in the kernel predictor. The performance of the new methodology is illustrated through numerical studies with simulated data, carried out in different scenarios. In addition, the proposed nonparametric approach is applied to predict the concentrations of a pollutant that represents a risk to human health, the cadmium, in the floodplain of the Meuse river (Netherlands), by incorporating the lead level as an auxiliary variable.
Astaxanthin Reduces Stemness Markers in BT20 and T47D Breast Cancer Stem Cells by Inhibiting Expression of Pontin and Mutant p53
Authors: Ahn Yong Tae , Kim Min Sung , Kim Youn Sook , An Won Gun
Published: November 2020

Astaxanthin (AST) is a product made from marine organisms that has been used as an anti-cancer supplement. It reduces pontin expression and induces apoptosis in SKBR3, a breast cancer cell line. Using Western blotting and qRT-PCR analyses, this study revealed that in the T47D and BT20 breast cancer cell lines, AST inhibits expression of pontin and mutp53, as well as the Oct4 and Nanog cancer stem cell (CSC) stemness genes. In addition, we explored the mechanism by which AST eradicates breast cancer cells using pontin siRNAs. Pontin knockdown by pontin siRNA reduced proliferation, Oct4 and Nanog expression, colony and spheroid formation, and migration and invasion abilities in breast cancer cells. In addition, reductions in Oct4, Nanog, and mutp53 expression following rottlerin treatment confirmed the role of pontin in these cells. Therefore, pontin may play a central role in the regulation of CSC properties and in cell proliferation following AST treatment. Taken together, these findings demonstrate that AST can repress CSC stemness genes in breast cancer cells, which implies that AST therapy could be used to improve the efficacy of other anti-cancer therapies against breast cancer cells.
A Machine Learning Model Accurately Predicts Ulcerative Colitis Activity at One Year in Patients Treated with Anti-Tumour Necrosis Factor α Agents
Authors: Popa Iolanda Valentina , Burlacu Alexandru , Mihai Catalina , Prelipcean Cristina Cijevschi
Published: November 2020

Background and objectives: The biological treatment is a promising therapeutic option for ulcerative colitis (UC) patients, being able to induce subclinical and long-term remission. However, the relatively high costs and the potential toxicity have led to intense debates over the most appropriate criteria for starting, stopping, and managing biologics in UC. Our aim was to build a machine learning (ML) model for predicting disease activity at one year in UC patients treated with anti-Tumour necrosis factor α agents as a useful tool to assist the clinician in the therapeutic decisions. Materials and Methods: Clinical and biological parameters and the endoscopic Mayo score were collected from 55 UC patients at the baseline and one year follow-up. A neural network model was built using the baseline endoscopic activity and four selected variables as inputs to predict whether a UC patient will have an active or inactive endoscopic disease at one year, under the same therapeutic regimen. Results: The classifier achieved an excellent performance predicting the disease activity at one year with an accuracy of 90% and area under curve (AUC) of 0.92 on the test set and an accuracy of 100% and an AUC of 1 on the validation set. Conclusions: Our proposed ML solution may prove to be a useful tool in assisting the clinicians’ decisions to increase the dose or switch to other biologic agents after the model’s validation on independent, external cohorts of patients.
Behind Taxonomic Variability: The Functional Redundancy in the Tick Microbiome
Authors: Estrada-Peña Agustín , Cabezas-Cruz Alejandro , Obregón Dasiel
Published: November 2020

The taxonomic composition and diversity of tick midgut microbiota have been extensively studied in different species of the genera Rhipicephalus, Ixodes, Amblyomma, Haemaphysalis, Hyalomma, Dermacentor, Argas and Ornithodoros, while the functional significance of bacterial diversity has been proportionally less explored. In this study, we used previously published 16S amplicon sequence data sets from three Ixodes scapularis cohorts, two of uninfected nymphs, and one of larvae experimentally infected with Borrelia burgdorferi, to test the functional redundancy of the tick microbiome. We predicted the metabolic profiling of each sample using the state-of-the-art metagenomics tool PICRUSt2. The results showed that the microbiomes of all I. scapularis samples share only 80 taxa (24.6%, total 324), while out of the 342 metabolic pathways predicted, 82.7%, were shared by all the ticks. Borrelia-infected larvae lack 15.4% of pathways found in the microbiome of uninfected nymphs. Taxa contribution analysis showed that the functional microbiome of uninfected ticks was highly redundant, with, in some cases, up to 198 bacterial taxa contributing to a single pathway. However, Borrelia-infected larvae had a smaller redundancy with 6.7% of pathways provided by more than 100 genera, while 15.7–19.2% of pathways were provided by more than 100 genera in the two cohorts of uninfected ticks. In addition, we compared the functional profiles of three microbial communities from each data set, identified through a network-based approach, and we observed functional similarity between them. Based on the functional redundancy and functional similarity of the microbiome of ticks in different developmental stages and infection status, we concluded that the tick gut microbiota is a self-regulating community of very diverse bacteria contributing to a defined set of metabolic pathways and functions with yet unexplored relevance for tick fitness and/or bacterial community stability. We propose a change of focus in which the tick microbiome must be analyzed in all dimensions, highlighting their functional traits, instead of the conventional taxonomic profiling.
Intestinal Anti-Inflammatory Activity of Terpenes in Experimental Models (2010–2020): A Review
Authors: Araruna Maria Elaine , Serafim Catarina , Alves Júnior Edvaldo , Hiruma-Lima Clelia , Diniz Margareth , Batista Leônia
Published: November 2020

Inflammatory bowel diseases (IBDs) refer to a group of disorders characterized by inflammation in the mucosa of the gastrointestinal tract, which mainly comprises Crohn’s disease (CD) and ulcerative colitis (UC). IBDs are characterized by inflammation of the intestinal mucosa, are highly debilitating, and are without a definitive cure. Their pathogenesis has not yet been fully elucidated; however, it is assumed that genetic, immunological, and environmental factors are involved. People affected by IBDs have relapses, and therapeutic regimens are not always able to keep symptoms in remission over the long term. Natural products emerge as an alternative for the development of new drugs; bioactive compounds are promising in the treatment of several disorders, among them those that affect the gastrointestinal tract, due to their wide structural diversity and biological activities. This review compiles 12 terpenes with intestinal anti-inflammatory activity evaluated in animal models and in vitro studies. The therapeutic approach to IBDs using terpenes acts basically to prevent oxidative stress, combat dysbiosis, restore intestinal permeability, and improve the inflammation process in different signaling pathways.
Albumin-Albumin/Lactosylated Core-Shell Nanoparticles: Therapy to Treat Hepatocellular Carcinoma for Controlled Delivery of Doxorubicin
Authors: Teran-Saavedra Nayelli Guadalupe , Sarabia-Sainz Jose Andrei , Velázquez-Contreras Enrique Fernando , Ramos-Clamont Montfort Gabriela , Pedroza-Montero Martín , Vazquez-Moreno Luz
Published: November 2020

Doxorubicin (Dox) is the most widely used chemotherapeutic agent and is considered a highly powerful and broad-spectrum for cancer treatment. However, its application is compromised by the cumulative side effect of dose-dependent cardiotoxicity. Because of this, targeted drug delivery systems (DDS) are currently being explored in an attempt to reduce Dox systemic side-effects. In this study, DDS targeting hepatocellular carcinoma (HCC) has been designed, specifically to the asialoglycoprotein receptor (ASGPR). Dox-loaded albumin-albumin/lactosylated (core-shell) nanoparticles (tBSA/BSALac NPs) with low (LC) and high (HC) crosslink using glutaraldehyde were synthesized. Nanoparticles presented spherical shapes with a size distribution of 257 ± 14 nm and 254 ± 14 nm, as well as an estimated surface charge of −28.0 ± 0.1 mV and −26.0 ± 0.2 mV, respectively. The encapsulation efficiency of Dox for the two types of nanoparticles was higher than 80%. The in vitro drug release results showed a sustained and controlled release profile. Additionally, the nanoparticles were revealed to be biocompatible with red blood cells (RBCs) and human liver cancer cells (HepG2 cells). In cytotoxicity assays, Dox-loaded nanoparticles decrease cell viability more efficiently than free Dox. Specific biorecognition assays confirmed the interaction between nanoparticles and HepG2 cells, especially with ASGPRs. Both types of nanoparticles may be possible DDS specifically targeting HCC, thus reducing side effects, mainly cardiotoxicity. Therefore, improving the quality of life from patients during chemotherapy.
The Identification of Cotton Fibers Dyed with Reactive Dyes for Forensic Purposes
Authors: Śmigiel-Kamińska Daria , Wąs-Gubała Jolanta , Stepnowski Piotr , Kumirska Jolanta
Published: November 2020

Some of the most common microtraces that are currently collected at crime scenes are fragments of single fibers. The perpetrator leaves them at a crime scene or takes them away, for example, on their clothing or body. In turn, the microscopic dimensions of such traces mean that the perpetrator does not notice them and therefore usually does not take action to remove them. Cotton and polyester fibers dyed by reactive and dispersion dyes, respectively, are very popular within clothing products, and they are hidden among microtraces at the scene of a crime. In our recently published review paper, we summarized the possibilities for the identification of disperse dyes of polyester fibers for forensic purposes. In this review, we are concerned with cotton fibers dyed with reactive dyes. Cotton fibers are natural ones that cannot easily be distinguished on the basis of morphological features. Consequently, their color and consequently the dye composition are often their only characteristics. The presented methods for the identification of reactive dyes could be very interesting not only for forensic laboratories, but also for scientists working in food, cosmetics or pharmaceutical/medical sciences.
Sigma-2 Receptor—A Potential Target for Cancer/Alzheimer’s Disease Treatment via Its Regulation of Cholesterol Homeostasis
Authors: Yang Kai , Zeng Cheng , Wang Changcai , Sun Meng , Yin Dan , Sun Taolei
Published: November 2020

The sigma receptors were classified into sigma-1 and sigma-2 receptor based on their different pharmacological profiles. In the past two decades, our understanding of the biological and pharmacological properties of the sigma-1 receptor is increasing; however, little is known about the sigma-2 receptor. Recently, the molecular identity of the sigma-2 receptor has been identified as TMEM97. Although more and more evidence has showed that sigma-2 ligands have the ability to treat cancer and Alzheimer’s disease (AD), the mechanisms connecting these two diseases are unknown. Data obtained over the past few years from human and animal models indicate that cholesterol homeostasis is altered in AD and cancer, underscoring the importance of cholesterol homeostasis in AD and cancer. In this review, based on accumulated evidence, we proposed that the beneficial roles of sigma-2 ligands in cancer and AD might be mediated by their regulation of cholesterol homeostasis.
Activity of Pterostilbene Metabolites against Liver Steatosis in Cultured Hepatocytes
Authors: Trepiana Jenifer , Krisa Stéphanie , Portillo María Puy
Published: November 2020

Pterostilbene is a dimethyl ether derivative of resveratrol, less metabolized than its analogue, due to the substitution of two hydroxyl groups with methoxyl groups. Nevertheless, the amounts of pterostilbene phase II metabolites found in plasma and tissues are higher than those of the parent compound. The first aim of this study was to assess whether pterostilbene-4′-O-glucuronide (PT-G) and pterostilbene-4′-O-sulfate (PT-S) were able to prevent triglyceride accumulation in AML12 (alpha mouse liver 12) hepatocytes. This being the case, we aimed to analyze the mechanisms involved in their effects. For this purpose, an in vitro model mimicking the hepatocyte situation in fatty liver was developed by incubating mouse AML12 hepatocytes with palmitic acid (PA). For cell treatments, hepatocytes were incubated with 1, 10 or 25 µM of pterostilbene, pterostilbene-4′-O-glucuronide or pterostilbene-4′-O-sulfate for 18 h. Triglycerides and cell viability were assessed by a commercial kit and crystal violet assay, respectively. Protein expression of enzymes and transporters involved in triglyceride metabolism was analyzed by immunoblot. The results showed for the first time the anti-steatotic effect of pterostilbene metabolites and thus, that they contribute to the preventive effect induced by pterostilbene on steatosis in in vivo models. This anti-steatotic effect is mainly due to the inhibition of de novo lipogenesis.
Anthocyanins Derived from Vitis coignetiae Pulliat Contributes Anti-Cancer Effects by Suppressing NF-κB Pathways in Hep3B Human Hepatocellular Carcinoma Cells and In Vivo
Authors: Kim Min Jeong , Paramanantham Anjugam , Lee Won Sup , Yun Jeong Won , Chang Seong Hwan , Kim Dong Chul , Park Hyeon Soo , Choi Yung Hyun , Kim Gon Sup , Ryu Chung Ho , Shin Sung Chul , Hong Soon Chan
Published: November 2020

We previously demonstrated that anthocyanins from the fruits of Vitis coignetiae Pulliat (AIMs) induced the apoptosis of hepatocellular carcinoma cells. However, many researchers argued that the concentrations of AIMs were too high for in vivo experiments. Therefore, we performed in vitro at lower concentrations and in vivo experiments for the anti-cancer effects of AIMs. AIMs inhibited the cell proliferation of Hep3B cells in a dose-dependent manner with a maximum concentration of 100 µg/mL. AIMs also inhibited the invasion and migration at 100 µg/mL concentration with or without the presence of TNF-α. To establish the relevance between the in vitro and in vivo results, we validated their effects in a Xenograft model of Hep3B human hepatocellular carcinoma cells. In the in vivo test, AIMs inhibited the tumorigenicity of Hep3B cells in the xenograft mouse model without showing any clinical signs of toxicity or any changes in the body weight of mice. AIMs inhibited the activation NF-κB and suppressed the NF-κB-regulated proteins, intra-tumoral microvessel density (IMVD) and the Ki67 activity of Hep3B xenograft tumors in athymic nude mice. In conclusion, this study indicates that AIMs have anti-cancer effects (inhibition of proliferation, invasion, and angiogenesis) on human hepatocellular carcinoma xenograft through the inhibition of NF-κB and its target protein.
Cross-Platform Usability Model Evaluation
Authors: Majrashi Khalid , Hamilton Margaret , Uitdenbogerd Alexandra L. , Al-Megren Shiroq
Published: November 2020

It is becoming common for several devices to be utilised together to access and manipulate shared information spaces and migrate tasks between devices. Despite the increased worldwide use of cross-platform services, there is limited research into how cross-platform service usability can be assessed. This paper presents a novel cross-platform usability model. The model employs the think-aloud protocol, observations, and questionnaires to reveal cross-platform usability problems. Two Likert scales were developed for measuring overall user satisfaction of cross-platform usability and user satisfaction with the seamlessness of the transition between one device and another. The paper further employs a series of objective measures for the proposed model. The viability and performance of the model were examined in the context of evaluating three cross-platform services across three devices. The results demonstrate that the model is a valuable method for assessing and quantifying cross-platform usability. The findings were thoroughly analysed and discussed, and subsequently used to refine the model. The model was also evaluated by eight user experience experts and seven out of the eight agreed that it is useful.
Early Infant Formula Feeding Impacts Urinary Metabolite Profile at 3 Months of Age
Authors: Rosa Fernanda , Mercer Kelly E. , Lin Haixia , Sims Clark R. , Pack Lindsay M. , Goode Grace , Badger Thomas , Andres Aline , Yeruva Laxmi
Published: November 2020

There is a growing consensus that nutritional programming may persist and influence risk for several chronic diseases in adulthood. In the present study, we used urinary metabolic analysis in assessing diet effects on early-life metabolism. Urine samples from healthy three-month-old infants fed human milk (HM; n = 93), cow’s milk-based infant formula [MF; n = 80], or soy protein-based infant formula (SF; n = 76) were analyzed with an untargeted metabolomics approach using GC-TOF MS. PLS-DA and ANOVA analyses were performed using MetaboAnalyst (v4.0). A total of 150 metabolites differed significantly among the feeding groups, including dietary-specific patterns of urinary metabolites of sugars, sugar alcohols, amino acids, and polyphenols. Urinary metabolites may mirror the infant’s overall metabolism and serve as a noninvasive tool to examine the neonatal effects of diet on early-infant metabolism.
Vegans, Vegetarians and Pescatarians Are at Risk of Iodine Deficiency in Norway
Authors: Groufh-Jacobsen Synne , Hess Sonja Y. , Aakre Inger , Folven Gjengedal Elin Lovise , Blandhoel Pettersen Kristina , Henjum Sigrun
Published: November 2020

Low iodine intakes have been documented in different population groups in Norway. We aimed to assess iodine status, dietary intake, supplement and macroalgae use, and iodine knowledge in vegans, vegetarians and pescatarians. In this study, 115 vegans, 55 vegetarians and 35 pescatarians from the Oslo region of Norway, aged 18–60 years, participated. A spot urine sample was collected along with a dietary assessment of iodine intake, supplement and macroalgae use. The median urinary iodine concentration (MUIC) in vegans was 43 µg/L (moderate iodine deficiency), in vegetarians 67 µg/L and in pescatarians 96 µg/L (mild iodine deficiency). In multiple linear regression analysis, use of iodine supplements was one of the strongest predictors of UIC. About half of the participants had median 24-h iodine intakes below estimated average requirement (EAR) of 100 µg/day. Fifty percent had low knowledge score, while 27% had very low knowledge score. Vegans, vegetarians and possibly pescatarians in Norway, are unable to reach the recommended iodine intake merely from food and are dependent on iodine supplements. There is an urgent need for dietary guidance targeting vegans, vegetarians and pescatarians to avoid inadequate iodine intake in non-supplement users, as well as avoiding excess iodine intake in macroalgae users.
Growth and Development of Preschool Children (12–60 Months): A Review of the Effect of Dairy Intake
Authors: Clark David C. , Cifelli Christopher J. , Pikosky Matthew A.
Published: November 2020

Undernutrition in young children is a global health issue. The ability to meet energy and nutrient needs during this critical stage of development is necessary, not only to achieve physical and mental potential but also socio-economic achievement later in life. Given ongoing discussions regarding optimization of dietary patterns to support achievement of the Sustainable Development Goals established by the United Nations, it is important to identify foods/food groups that have shown efficacy in reducing the negative impacts of undernutrition in young children. This narrative review addresses the impact of dairy intake, with a focus on linear growth, cognitive development and weight gain in early childhood (12–60 months). The impact of country economic status is also examined, to help elucidate regional specific recommendations and/or future research needs. Overall, the body of research addressing this age group is somewhat limited. Based on the data available, there is a positive association between dairy intake and linear growth. The impact of milk or dairy products on cognitive development is less clear due to a lack of evidence and is a gap in the literature that should be addressed. Regarding the impact on body weight, the majority of evidence suggests there is either no association or an inverse association between milk intake by preschool children on overweight and obesity later in life. This evidence is exclusively in high income countries, however, so additional work in lower income countries may be warranted.
Effective Medium Theory for Multi-Component Materials Based on Iterative Method
Authors: Nazarov Ravshanjon , Zhang Tianmiao , Khodzitsky Mikhail
Published: November 2020

For biomedical applications in the terahertz band, composites such as macromolecule compounds, biotissues and phantoms are studied. A description of dielectric properties of composite materials using mathematical models has its own fundamental and technological importance. In this work, we present an iterative effective medium theory for multi-component materials. The model has good performance in describing composite materials with more than two components. The theory is evaluated by comparing with the complex permittivity of three different composite materials. A comparison with other commonly used models is given in the form of relative errors.
Preparation of Hybrid Polyaniline/Nanoparticle Membranes for Water Treatment Using an Inverse Emulsion Polymerization Technique under Sonication
Authors: Chajanovsky Itamar , Suckeveriene Ran Y.
Published: November 2020

This manuscript describes a novel in situ interfacial dynamic inverse emulsion polymerization process under sonication of aniline in the presence of carbon nanotubes (CNT) and graphene nanoparticles in ethanol. This polymerization method is simple and very rapid (up to 10 min) compared to other techniques reported in the literature. During polymerization, the nanoparticles are coated with polyaniline (PANI), forming a core-shell structure, as confirmed by high-resolution scanning electron microscopy (HRSEM) and Fourier-Transform Infrared (FTIR) measurements. The membrane pore sizes range between 100–200 nm, with an average value of ~119 ± 28.3 nm. The film resistivity decreased when treated with alcohol, and this behavior was used for selection of the most efficient alcohol as a solvent for this polymerization technique. The membrane permeability of the PANI grafted CNT was lower than the CNT reference, thus demonstrating better membranal properties. As measured by water permeability, these are ultrafiltration membranes. An antimicrobial activity test showed that whereas the reference nanoparticle Bucky paper developed a large bacterial colony, the PANI grafted CNT sample had no bacterial activity. The thicker, 2.56 mm membranes exhibited high salt removal properties at a low pressure drop. Such active membranes comprise a novel approach for future water treatment applications.
Impact of Process Parameters and Bulk Properties on Quality of Dried Hops
Authors: Raut Sharvari , Gersdorff Gardis J. E. von , Münsterer Jakob , Kammhuber Klaus , Hensel Oliver , Sturm Barbara
Published: November 2020

Hops are critical to the brewing industry. In commercial hop drying, a large bulk of hops is dried in multistage kilns for several hours. This affects the drying behavior and alters the amount and chemical composition of the hop oils. To understand these changes, hops of the var. Hallertauer Tradition were dried in bulks of 15, 25 and 35 kg/m² at 60 °C and 0.35 m/s. Additionally, bulks of 25 kg/m² were also dried at 65 °C and 0.45 m/s to assess the effect of change in temperature and velocity, respectively. The results obtained show that bulk weights significantly influence the drying behavior. Classification based on the cone size reveals 45.4% medium cones, 41.2% small cones and 8.6% large cones. The highest ΔE value of 6.3 and specific energy consumption (113,476 kJ/kgH2O) were observed for the 15 kg/m² bulk. Increasing the temperature from 60 °C to 65 °C increased the oil yield losses by about 7% and myrcene losses by 22%. The results obtained show that it is important to define and consider optimum bulk and process parameters, to optimize the hop drying process to improve the process efficiency as well the product quality.
A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM2.5 Concentrations across Great Britain
Authors: Schneider Rochelle , Vicedo-Cabrera Ana , Sera Francesco , Masselot Pierre , Stafoggia Massimo , de Hoogh Kees , Kloog Itai , Reis Stefan , Vieno Massimo , Gasparrini Antonio
Published: November 2020

Epidemiological studies on the health effects of air pollution usually rely on measurements from fixed ground monitors, which provide limited spatio-temporal coverage. Data from satellites, reanalysis, and chemical transport models offer additional information used to reconstruct pollution concentrations at high spatio-temporal resolutions. This study aims to develop a multi-stage satellite-based machine learning model to estimate daily fine particulate matter (PM2.5) levels across Great Britain between 2008–2018. This high-resolution model consists of random forest (RF) algorithms applied in four stages. Stage-1 augments monitor-PM2.5 series using co-located PM10 measures. Stage-2 imputes missing satellite aerosol optical depth observations using atmospheric reanalysis models. Stage-3 integrates the output from previous stages with spatial and spatio-temporal variables to build a prediction model for PM2.5. Stage-4 applies Stage-3 models to estimate daily PM2.5 concentrations over a 1 km grid. The RF architecture performed well in all stages, with results from Stage-3 showing an average cross-validated R2 of 0.767 and minimal bias. The model performed better over the temporal scale when compared to the spatial component, but both presented good accuracy with an R2 of 0.795 and 0.658, respectively. These findings indicate that direct satellite observations must be integrated with other satellite-based products and geospatial variables to derive reliable estimates of air pollution exposure. The high spatio-temporal resolution and the relatively high precision allow these estimates (approximately 950 million points) to be used in epidemiological analyses to assess health risks associated with both short- and long-term exposure to PM2.5.
An Unsupervised Urban Extent Extraction Method from NPP-VIIRS Nighttime Light Data
Authors: Chen Xiuxiu , Zhang Feng , Du Zhenhong , Liu Renyi
Published: November 2020

An accelerating trend of global urbanization accompanying various environmental and urban issues makes frequently urban mapping. Nighttime light data (NTL) has shown great advantages in urban mapping at regional and global scales over long time series because of its appropriate spatial and temporal resolution, free access, and global coverage. However, the existing urban extent extraction methods based on nighttime light data rely on auxiliary data and training samples, which require labor and time for data preparation, leading to the difficulty to extract urban extent at a large scale. This study seeks to develop an unsupervised method to extract urban extent from nighttime light data rapidly and accurately without ancillary data. The clustering algorithm is applied to segment urban areas from the background and multi-scale spatial context constraints are utilized to reduce errors arising from the low brightness areas and increase detail information in urban edge district. Firstly, the urban edge district is detected using spatial context constrained clustering, and the NTL image is divided into urban interior district, urban edge district and non-urban interior district. Secondly, the urban edge pixels are classified by an adaptive direction filtering clustering. Finally, the full urban extent is obtained by merging the urban inner pixels and the urban pixels in urban edge district. The proposed method was validated using the urban extents of 25 Chinese cities, obtained by Landsat8 images and compared with two common methods, the local-optimized threshold method (LOT) and the integrated night light, normalized vegetation index, and surface temperature support vector machine classification method (INNL-SVM). The Kappa coefficient ranged from 0.687 to 0.829 with an average of 0.7686 (1.80% higher than LOT and 4.88% higher than INNL-SVM). The results in this study show that the proposed method is a reliable and efficient method for extracting urban extent with high accuracy and simple operation. These imply the significant potential for urban mapping and urban expansion research at regional and global scales automatically and accurately.
Surface Acoustic Wave Sensor for C-Reactive Protein Detection
Authors: Jeng Ming-Jer , Sharma Mukta , Li Ying-Chang , Lu Yi-Chen , Yu Chia-Yu , Tsai Chia-Lung , Huang Shiang-Fu , Chang Liann-Be , Lai Chao-Sung
Published: November 2020

A surface acoustic wave (SAW) sensor was investigated for its application in C-reactive protein (CRP) detection. Piezoelectric lithium niobate (LiNbO3) substrates were used to study their frequency response characteristics in a SAW sensor with a CRP sensing area. After the fabrication of the SAW sensor, the immobilization process was performed for CRP/anti-CRP interaction. The CRP/anti-CRP interaction can be detected as mass variations in the sensing area. These mass variations may produce changes in the amplitude of sensor response. It was clearly observed that a CRP concentration of 0.1 μg/mL can be detected in the proposed SAW sensor. A good fitting linear relationship between the detected insertion loss (amplitude) and the concentrations of CRP from 0.1 μg/mL to 1 mg/mL was obtained. The detected shifts in the amplitude of insertion loss in SAW sensors for different CRP concentrations may be useful in the diagnosis of risk of cardiovascular diseases.
In Situ Detection of Water Leakage for Textile-Reinforced Composites
Authors: Regnier Julie , Cayla Aurélie , Campagne Christine , Devaux Eric
Published: November 2020

By incorporating electrically conductive yarns into a waterproof membrane, one can detect epoxy resin cracking or liquid leakage. Therefore, this study examined the electrical conductivity variations of several yarns (metallic or carbon-based) for cracking and water detection. The first observations concerned the detectors’ feasibility by investigating their conductivity variations during both their resin implementation processes and their resin cracking. Throughout this experiment, two phenomena were detected: the compression and the separation of the fibres by the resin. In addition, the resin cracking had an important role in decreasing the yarns’ conductivity. The second part of this study concerned water detection. Two principles were established and implemented, first with yarns and then with yarns incorporated into the resin. First, the principle of absorption was based on the conductivity variation with the yarns’ swelling after contact with water. A short circuit was established by the creation of a conductive path when a drop of water was deposited between two conductive, parallel yarns. Through the influence of the yarns’ properties, this study explored the metallic yarns’ capacity to better detect water with a short circuit and the ability of the carbon-based yarns to detect water by the principle of absorption.
The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis
Authors: Chromy Adam , Zalud Ludek
Published: November 2020

The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D models that include a thermal layer. (1) Background: at present, medicine still exhibits a lack of objective diagnostic methods. As many diseases involve thermal changes, thermography may appear to be a convenient technique for the given purpose; however, there are three limiting problems: exact localization, resolution vs. range, and impossibility of quantification. (2) Methods: the basic principles and benefits of the system are described. The procedures rely on a robotic manipulator with multiple sensors to create a multispectral 3D model. Importantly, the structure is robust, scene-independent, and features quantifiable measurement uncertainty; thus, all of the above problems of medical thermography are resolved. (3) Results: the benefits were demonstrated by several pilot case studies: medicament efficacy assessment in dermatology, objective recovery progress assessment in traumatology, applied force quantification in forensic sciences, exact localization of the cause of pain in physiotherapy, objective assessment of atopic dermatitis, and soft tissue volumetric measurements. (4) Conclusion: the RoScan addresses medical quantification, which embodies a frequent problem in several medical sectors, and can deliver new, objective information to improve the quality of healthcare and to eliminate false diagnoses.
Development of a Mobile Application System for Eco-Accounting
Authors: Huang Hua , Su Daizhong , Peng Wenjie , Wu You
Published: November 2020

Nowadays, eco-accounting is widely used in sustainable consumption and production. In order to incentivise consumers’ sustainable consumption and enhance their environmental awareness, a novel mobile based eco-accounting infrastructure has been developed by this research. It applies the eco-credit values to incentivise the consumer’s recycling activities and utilises the eco-cost values to record the consumer’s footprint obtained through consumption. The infrastructure consists of four modules: the consumer’s eco-account, eco-shopping, eco-recycling and eco-incentives. In order to implement the mobile eco-accounting infrastructure, multiple mobile technologies have been applied to develop the novel functions of the mobile app, including a new QR encryption algorithm, embedded Google maps, advanced Internet-based services and multi-language support. A case study is conducted by demonstrating the consumer’s purchasing and recycling processes. It proves that the novel mobile application system has been successfully developed, which provides an effective support for the implementation and demonstration of the eco-accounting infrastructure.
Developing Goals and Indicators for the Design of Sustainable and Integrated Transport Infrastructure and Urban Spaces
Authors: Yang Liu , van Dam Koen , Zhang Lufeng
Published: November 2020

This paper aims to provide a framework for policy-makers and transportation and urban design professionals to evaluate alternative urban plans and infrastructure design, allowing them to select a set of locally relevant indicators to help assess scenarios considering sustainable development and overall system performance improvement in line with specific project goals. Using methods of systematic review, content analysis, multi-criteria analysis, and expert consultation, a three-level goal system is proposed, leading to the generation of 64 Key Performance Indicators (KPIs), both qualitative and quantitative, and an indicator set of 227 items. To allow stakeholders to apply their own set of indicators, the approaches and tools of measuring these indicators as well as the ways of using this indicator set are presented to assist decision-makers in evaluating and choosing optimal plans and designs.
Game Analysis and Coordination of a Closed-Loop Supply Chain: Perspective of Components Reuse Strategy
Authors: Zhao Xiaomin , Bai Xueli , Fan Zhihui , Liu Ting
Published: November 2020

This paper studies a closed-loop supply chain that covers three key members: Manufacturer, new components supplier, and recycled-components supplier. Considering the power of each member in the chain, we use game theory to analyze the optimal decision and coordination, particularly investigating the economic value of components reuse strategy. The results show that, in a decentralized setting, the value of components reuse highly depends on the attributes of the products. For the products with low price elasticity, reuse strategy is only beneficial to the recycled-components suppliers. Further investigation shows the manufacturer can use wholesale price contracts to coordinate and improve the supply chain’s performance.
Managerial Strategies for Long-Term Care Organization Professionals: COVID-19 Pandemic Impacts
Authors: Dias Ana , Scavarda Annibal , Reis Augusto , Silveira Haydee , Ebecken Nelson
Published: November 2020

This paper aims to analyze the strategies that healthcare professionals have adopted during the coronavirus pandemic (COVID-19) in long-term care organizations in Rio de Janeiro city, Brazil, by investigating their competencies—mainly managerial ones. To reach its goals, this paper performs empirical research and theoretical research. For the empirical research, the plans of professionals during COVID-19 pandemic in long-term care organizations are observed, and a questionnaire is applied to analyze observed data integrity. The data are analyzed through the Python and IBM SPSS Statistic programming languages, and descriptive analyses use descriptive statistic proportions, rates, minimum, maximum, mean, median, standard deviation, and coefficient of variation (CV). A non-parametric approach performs repeated measure comparisons using Wilcoxon’s test, while the McNemmar test is used to repeat the categorical variables. Statistical significance is assumed at the 5% level. For the theoretical research, a literature review is developed using scientific databases. The results show that for the searched period, the number of deaths and the number of people infected by COVID-19 in these organizations are low when compared to general statistics of Rio de Janeiro city. This paper concludes that these strategical adoptions have brought significant benefits to long-term care organizations, and it might motivate researchers to develop future studies related to long-term care organizations, helping to fill the literature gap on the subject.
The Impact of the Organizational Culture on Hotel Outsourcing and Sustainable Performance an Empirical Application in the Egyptian Hotel Sector
Authors: Gebril Taha Mahmoud , Espino-Rodríguez Tomás F.
Published: November 2020

In recent years, the concept of an organizational culture in hotels has held an important position on both a theoretical and practical level because this culture significantly affects organizational performance and the strategies adopted by hotels. Therefore, it is considered one of the key factors in determining hotels’ tendency towards outsourcing and sustainable performance. In this study, we aim to analyze the impact of the organizational culture on the level of outsourcing and sustainable performance. To do so, we will use the Competing Values Framework (CVF), which divides organizational culture into four typologies: hierarchical, group, rational, and development cultures. A personal questionnaire was administered to the directors or managers of 114 hotels located in two Egyptian cities: Hurgada and Sharm El Sheikh. The results of the structural model suggest the negative impact of the hierarchical and development cultures on the level of outsourcing. The results show a positive influence of the four types of organizational culture on sustainable performance, suggesting that these hotels have a strong interest in sustainability and the environment. The findings reveal a negative relationship between the level of outsourcing and sustainable performance. Finally, this study presents academic and practical implications, as well as recommendations for future research.
Symmetries in Teleportation Assisted by N-Channels under Indefinite Causal Order and Post-Measurement
Authors: Cardoso-Isidoro Carlos , Delgado Francisco
Published: November 2020

Quantum teleportation has had notorious advances in the last decade, being successfully deployed in the experimental domain. In other terrains, the understanding of indefinite causal order has demonstrated a valuable enhancement in quantum communication to correct channel imperfections. In this work, we address the symmetries underlying imperfect teleportation when it is assisted by indefinite causal order to correct the use of noisy entangled resources. In the strategy being presented, indefinite causal order introduces a control state to address the causal ordering. Then, by using post-selection, it fulfills the teleportation enhancement to recover the teleported state by constructive interference. By analysing primarily sequential teleportation under definite causal order, we perform a comparison basis for notable outcomes derived from indefinite causal order. After, the analysis is conducted by increasing the number of teleportation processes, thus suggesting additional alternatives to exploit the most valuable outcomes in the process by adding weak measurement as a complementary strategy. Finally, we discuss the current affordability for an experimental implementation.
Image Denoising Based on Bivariate Distribution
Authors: Zhao Ping , Zhao Xingyu , Zhao Chun
Published: November 2020

The literature has shown that the performance of the de-noising algorithm was greatly influenced by the dependencies between wavelet coefficients. In this paper, the bivariate probability density function (PDF) was proposed which was symmetric, and the dependencies between the coefficients were considered. The bivariate Cauchy distribution and the bivariate Student’s distribution are special cases of the proposed bivariate PDF. One of the parameters in the probability density function gave the estimation method, and the other parameter can take any real number greater than 2. The algorithm adopted a maximum a posteriori estimator employing the dual-tree complex wavelet transform (DTCWT). Compared with the existing best results, the method is faster and more efficient than the previous numerical integration techniques. The bivariate shrinkage function of the proposed algorithm can be expressed explicitly. The proposed method is simple to implement.