bluuebunny/crossref_metadata_2025 huggingface dataset:
Magnetic Phase Coexistence and Hard–Soft Exchange Coupling in FePt Nanocomposite Magnets
Authors: Crisan O. , Dan I. , Palade P. , Crisan A. D. , Leca A. , Pantelica A.
Published: August 2020

With the aim of demonstrating phase coexistence of two magnetic phases in an intermediate annealing regime and obtaining highly coercive FePt nanocomposite magnets, two alloys of slightly off-equiatomic composition of a binary Fe-Pt system were prepared by dynamic rotation switching and ball milling. The alloys, with a composition Fe53Pt47 and Fe55Pt45, were subsequently annealed at 400 °C and 550 °C and structurally and magnetically characterized by means of X-ray diffraction, 57Fe Mössbauer spectrometry and Superconducting Quantum Interference Device (SQUID) magnetometry measurements. Gradual disorder–order phase transformation and temperature-dependent evolution of the phase structure were monitored using X-ray diffraction of synchrotron radiation. It was shown that for annealing temperatures as low as 400 °C, a predominant, highly ordered L10 phase is formed in both alloys, coexisting with a cubic L12 soft magnetic FePt phase. The coexistence of the two phases is evidenced through all the investigating techniques that we employed. SQUID magnetometry hysteresis loops of samples annealed at 400 °C exhibit inflection points that witness the coexistence of the soft and hard magnetic phases and high values of coercivity and remanence are obtained. For the samples annealed at 500 °C, the hysteresis loops are continuous, without inflection points, witnessing complete exchange coupling of the hard and soft magnetic phases and further enhancement of the coercive field. Maximum energy products comparable with values of current permanent magnets are found for both samples for annealing temperatures as low as 500 °C. These findings demonstrate an interesting method to obtain rare earth-free permanent nanocomposite magnets with hard–soft exchange-coupled magnetic phases.
Anthocyanin-Enriched Riceberry Rice Extract Inhibits Cell Proliferation and Adipogenesis in 3T3-L1 Preadipocytes by Downregulating Adipogenic Transcription Factors and Their Targeting Genes
Authors: Kongthitilerd Phutthida , Suantawee Tanyawan , Cheng Henrique , Thilavech Thavaree , Marnpae Marisa , Adisakwattana Sirichai
Published: August 2020

Riceberry rice (Oryza sativa L.) is a new pigmented variety of rice from Thailand. Despite its high anthocyanin content, its effect on adipogenesis and adipocyte function remains unexplored. We investigated whether Riceberry rice extract (RBE) impacted cell proliferation by examining viability and cell cycle, using preadipocyte 3T3-L1 cells. To test RBE’s effect on adipocyte formation, cells were cultured in adipogenic medium supplemented with extract and adipocyte number and triglyceride levels were quantified. Furthermore, Akt1 phosphorylation along with RT-qPCR and intracellular calcium imaging were performed to obtain an insight into its mechanism of action. The effect of RBE on adipocyte function was investigated using glucose uptake and lipolysis assays. Treatment of cells with RBE decreased preadipocyte number without cytotoxicity despite inducing cell cycle arrest (p < 0.05). During adipogenic differentiation, RBE supplementation reduced adipocyte number and triglyceride accumulation by downregulating transcription factors (e.g., PPARγ, C/EBPα, and C/EBPβ) and their target genes (p < 0.05). The Akt1 phosphorylation was decreased by RBE but insignificance, however, the extract failed to increase intracellular calcium signals. Finally, the treatment of adipocytes with RBE reduced glucose uptake by downregulating Glut4 mRNA expression and enhanced isoproterenol-induced lipolysis (p < 0.05). These findings suggest that RBE could potentially be used in the treatment of obesity by inhibiting adipocyte formation and proliferation.
Oral Administration of Sargassum horneri Improves the HDM/DNCB-Induced Atopic Dermatitis in NC/Nga Mice
Authors: Han Eui Jeong , Fernando Ilekuttige Priyan Shanura , Kim Hyun-Soo , Jeon You-Jin , Madusanka Dissanayaka Mudiyanselage Dinesh , Dias Mawalle Kankanamge Hasitha Madhawa , Jee Youngheun , Ahn Ginnae
Published: August 2020

The present study investigated the protective effects of Sargassum horneri (S. horneri) ethanol extract (SHE) against atopic dermatitis (AD), known as an abnormal immune response in house dust mite (HDM)/2,4-dinitrochlorobenzene (DNCB)-stimulated NC/Nga mice. The oral administration of SHE attenuated the AD symptoms, including the skin dermatitis severity, transepidermal water loss (TEWL), and ear edema in HDM/DNCB-stimulated mice. Moreover, the histological analysis revealed that SHE improved epidermal hyperplasia and hyperkeratosis, and reduced the dermal infiltrations of mast cells and eosinophils. Moreover, SHE downregulated the expression levels of cytokines (interleukin (IL)-6, IL-10, and interferon (IFN)-γ) and chemokines (Regulated on Activation, Normal T Cell Expressed and Secreted (RANTES), Eotaxin, and Thymus and activation-regulated chemokine (TARC)) by decreasing the expression levels of atopic initiators (IL-25 and IL-33) in HDM/DNCB-stimulated skin. The oral administration of SHE decreased the spleen size, reducing expression levels of AD-related cytokines (IL-4, IL-5, IL-6, IL-10, IL-13, IFN-γ, and TARC) by regulating the expressions of Tbx21 (T-bet), GATA Binding Protein 3 (GATA-3), and Signal transducer and activator of transcription 3 (STAT3). Moreover, SHE significantly attenuated the serum immunoglobulin (Ig)G1 and IgG2a levels in HDM/DNCB-stimulated mice. Collectively, these results suggest that S. horneri could be an ingredient of functional food against abnormal immune response.
The Environmental Impact of the Athlete’s Plate Nutrition Education Tool
Authors: Reguant-Closa Alba , Roesch Andreas , Lansche Jens , Nemecek Thomas , Lohman Timothy G , Meyer Nanna L
Published: August 2020

Periodized nutrition is necessary to optimize training and enhance performance through the season. The Athlete’s Plate (AP) is a nutrition education tool developed to teach athletes how to design their plates depending on training load (e.g., volume × intensity), from easy (E), moderate (M) to hard (H). The AP was validated, confirming its recommendations according to international sports nutrition guidelines. However, the AP had significantly higher protein content than recommended (up to 2.9 ± 0.5 g·kg−1·d−1; p < 0.001 for H male). The aim of this study was to quantify the environmental impact (EnvI) of the AP and to evaluate the influence of meal type, training load, sex and registered dietitian (RD). The nutritional contents of 216 APs created by 12 sport RDs were evaluated using Computrition Software (Hospitality Suite, v. 18.1, Chatsworth, CA, USA). The EnvI of the AP was analyzed by life cycle assessment (LCA) expressed by the total amount of food on the AP, kg, and kcal, according to the Swiss Agricultural Life Cycle Assessment (SALCA) methodology. Higher EnvI is directly associated with higher training load when the total amount of food on the plate is considered for E (5.7 ± 2.9 kg CO2 eq/day); M (6.4 ± 1.5 kg CO2 eq/day); and H (8.0 ± 2.1 kg CO2 eq/day). Global warming potential, exergy and eutrophication are driven by animal protein and mainly beef, while ecotoxicity is influenced by vegetable content on the AP. The EnvI is influenced by the amount of food, training load and sex. This study is the first to report the degree of EnvI in sports nutrition. These results not only raise the need for sustainability education in sports nutrition in general, but also the urgency to modify the AP nutrition education tool to ensure sports nutrition recommendations are met, while not compromising the environment.
Beneficial Effects of Vitamin K Status on Glycemic Regulation and Diabetes Mellitus: A Mini-Review
Authors: Ho Hsin-Jung , Komai Michio , Shirakawa Hitoshi
Published: August 2020

Type 2 diabetes mellitus is a chronic disease that is characterized by hyperglycemia, insulin resistance, and dysfunctional insulin secretion. Glycemic control remains a crucial contributor to the progression of type 2 diabetes mellitus as well as the prevention or delay in the onset of diabetes-related complications. Vitamin K is a fat-soluble vitamin that plays an important role in the regulation of the glycemic status. Supplementation of vitamin K may reduce the risk of diabetes mellitus and improve insulin sensitivity. This mini-review summarizes the recent insights into the beneficial effects of vitamin K and its possible mechanism of action on insulin sensitivity and glycemic status, thereby suppressing the progression of diabetes mellitus.
Effect of Serotype and Strain Diversity on Dengue Virus Replication in Australian Mosquito Vectors
Authors: Ekwudu O’mezie , Marquart Louise , Webb Lachlan , Lowry Kym S. , Devine Gregor J. , Hugo Leon E. , Frentiu Francesca D.
Published: August 2020

Dengue virus (DENV) is the most important mosquito-borne viral pathogen of humans, comprising four serotypes (DENV-1 to -4) with a myriad of genotypes and strains. The kinetics of DENV replication within the mosquito following ingestion of a blood meal influence the pathogen’s ability to reach the salivary glands and thus the transmission potential. The influence of DENV serotype and strain diversity on virus kinetics in the two main vector species, Aedes aegypti and Ae. albopictus, has been poorly characterized. We tested whether DENV replication kinetics vary systematically among serotypes and strains, using Australian strains of the two vectors. Mosquitoes were blood fed with two strains per serotype, and sampled at 3, 6, 10 and 14-days post-exposure. Virus infection in mosquito bodies, and dissemination of virus to legs and wings, was detected using qRT-PCR. For both vectors, we found significant differences among serotypes in proportions of mosquitoes infected, with higher numbers for DENV-1 and -2 versus other serotypes. Consistent with this, we observed that DENV-1 and -2 generally replicated to higher RNA levels than other serotypes, particularly at earlier time points. There were no significant differences in either speed of infection or dissemination between the mosquito species. Our results suggest that DENV diversity may have important epidemiological consequences by influencing virus kinetics in mosquito vectors.
Bioreactor-Grown Bacillus of Calmette and Guérin (BCG) Vaccine Protects Badgers against Virulent Mycobacterium bovis When Administered Orally: Identifying Limitations in Baited Vaccine Delivery
Authors: Lesellier Sandrine , Birch Colin P. D. , Davé Dipesh , Dalley Deanna , Gowtage Sonya , Palmer Simonette , McKenna Claire , Williams Gareth A. , Ashford Roland , Weyer Ute , Beatham Sarah , Coats Julia , Nunez Alex , Sanchez-Cordon Pedro , Spiropoulos John , Powell Stephen , Sawyer Jason , Pascoe Jordan , Hendon-Dunn Charlotte , Bacon Joanna , Chambers Mark A.
Published: August 2020

Bovine tuberculosis (TB) in Great Britain adversely affects animal health and welfare and is a cause of considerable economic loss. The situation is exacerbated by European badgers (Meles meles) acting as a wildlife source of recurrent Mycobacterium bovis infection to cattle. Vaccination of badgers against TB is a possible means to reduce and control bovine TB. The delivery of vaccine in oral bait holds the best prospect for vaccinating badgers over a wide geographical area. There are practical limitations over the volume and concentration of Bacillus of Calmette and Guérin (BCG) that can be prepared for inclusion in bait. The production of BCG in a bioreactor may overcome these issues. We evaluated the efficacy of oral, bioreactor-grown BCG against experimental TB in badgers. We demonstrated repeatable protection through the direct administration of at least 2.0 × 108 colony forming units of BCG to the oral cavity, whereas vaccination via voluntary consumption of bait containing the same preparation of BCG did not result in demonstrable protection at the group-level, although a minority of badgers consuming bait showed immunological responses and protection after challenge equivalent to badgers receiving oral vaccine by direct administration. The need to deliver oral BCG in the context of a palatable and environmentally robust bait appears to introduce such variation in BCG delivery to sites of immune induction in the badger as to render experimental studies variable and inconsistent.
Development of High-Density Genetic Linkage Maps and Identification of Loci for Chestnut Gall Wasp Resistance in Castanea spp.
Authors: Torello Marinoni Daniela , Nishio Sogo , Valentini Nadia , Shirasawa Kenta , Acquadro Alberto , Portis Ezio , Alma Alberto , Akkak Aziz , Pavese Vera , Cavalet-Giorsa Emile , Botta Roberto
Published: August 2020

Castanea sativa is an important multipurpose species in Europe for nut and timber production as well as for its role in the landscape and in the forest ecosystem. This species has low tolerance to chestnut gall wasp (Dryocosmus kuriphilus Yasumatsu), which is a pest that was accidentally introduced into Europe in early 2000 and devastated forest and orchard trees. Resistance to the gall wasp was found in the hybrid cultivar ‘Bouche de Bétizac’ (C. sativa × C. crenata) and studied by developing genetic linkage maps using a population derived from a cross between ‘Bouche de Bétizac’ and the susceptible cultivar ‘Madonna’ (C. sativa). The high-density genetic maps were constructed using double-digest restriction site-associated DNA-seq and simple sequence repeat markers. The map of ‘Bouche de Bétizac’ consisted of 1459 loci and spanned 809.6 cM; the map of ‘Madonna’ consisted of 1089 loci and spanned 753.3 cM. In both maps, 12 linkage groups were identified. A single major QTL was recognized on the ‘Bouche de Bétizac’ map, explaining up to 67–69% of the phenotypic variance of the resistance trait (Rdk1). The Rdk1 quantitative trait loci (QTL) region included 11 scaffolds and two candidate genes putatively involved in the resistance response were identified. This study will contribute to C. sativa breeding programs and to the study of Rdk1 genes.
Plasticized Polystyrene by Addition of -Diene Based Molecules for Defect-Less CVD Graphene Transfer
Authors: Nasir Tuqeer , Kim Bum Jun , Hassnain Muhammad , Lee Sang Hoon , Jeong Byung Joo , Choi Ik Jun , Kim Youngho , Yu Hak Ki , Choi Jae-Young
Published: August 2020

Chemical vapor deposition of graphene on transition metals is the most favored method to get large scale homogenous graphene films to date. However, this method involves a very critical step of transferring as grown graphene to desired substrates. A sacrificial polymer film is used to provide mechanical and structural support to graphene, as it is detached from underlying metal substrate, but, the residue and cracks of the polymer film after the transfer process affects the properties of the graphene. Herein, a simple mixture of polystyrene and low weight plasticizing molecules is reported as a suitable candidate to be used as polymer support layer for transfer of graphene synthesized by chemical vapor deposition (CVD). This combination primarily improves the flexibility of the polystyrene to prevent cracking during the transfer process. In addition, the polymer removal solvent can easily penetrate between the softener molecules, so that the polymer film can be easily dissolved after transfer of graphene, thereby leaving no residue. This facile method can be used freely for the large-scale transfer of 2D materials.
Near-Infrared Radiation-Based Mild Photohyperthermia Therapy of Non-Melanoma Skin Cancer with PEGylated Reduced Nanographene Oxide
Authors: Costa-Almeida Raquel , Bogas Diana , Fernandes José R. , Timochenco Licínia , Silva Filipa A. L. S. , Meneses João , Gonçalves Inês C. , Magalhães Fernão D. , Pinto Artur M.
Published: August 2020

Using a one-step thermal reduction and non-covalent chemical functionalization process, PEGylated reduced nanographene oxide (rGOn-PEG) was produced from nanographene oxide (GOn) and characterized in terms of particle size, dispersion stability, chemistry, and photothermal properties, in view of its use for photothermal therapy (PTT) of non-melanoma skin cancer. GOn infrared spectrum presented more intense bands assigned to oxygen containing functional groups than observed for rGOn-PEG. GOn C/O ratio decreased more than 50% comparing with rGOn-PEG and nitrogen was present in the latter (N at % = 20.6) due to introduction of PEG-NH2. Thermogravimetric analysis allowed estimating the amount of PEG in rGOn-PEG to be of about 56.1%. Simultaneous reduction and PEGylation increased the lateral dimensions from 287 ± 139 nm to 521 ± 397 nm, as observed by transmission electron microscopy and dynamic light scattering. rGOn-PEG exhibited ≈13-fold higher absorbance in the near-infrared radiation (NIR) region, as compared to unmodified GOn. Low power (150 mW cm−2) NIR irradiation using LEDs resulted in rGOn-PEG heating up to 47 °C, which is within the mild PTT temperature range. PEGylation strongly enhanced the dispersibility of rGOn in physiological media (phosphate buffered saline, fetal bovine serum, and cell culture medium) and also improved the biocompatibility of rGOn-PEG, in comparison to GOn (25–250 μg mL−1). After a single NIR LED irradiation treatment of 30 min, a decrease of ≈38% in A-431 cells viability was observed for rGOn-PEG (250 μg mL−1). Together, our results demonstrate the potential of irradiating rGOn-PEG using lower energy, cheaper, smaller, and safer LEDs, as alternative to high power lasers, for NIR mild hyperthermia therapy of cancer, namely non-melanoma skin cancer.
On the Synergistic Effect of Multi-Walled Carbon Nanotubes and Graphene Nanoplatelets to Enhance the Functional Properties of SLS 3D-Printed Elastomeric Structures
Authors: Rollo Gennaro , Ronca Alfredo , Cerruti Pierfrancesco , Gan Xin Peng , Fei Guoxia , Xia Hesheng , Gorokhov Gleb , Bychanok Dzmitry , Kuzhir Polina , Lavorgna Marino , Ambrosio Luigi
Published: August 2020

Elastomer-based porous structures realized by selective laser sintering (SLS) are emerging as a new class of attractive multifunctional materials. Herein, a thermoplastic polyurethane (TPU) powder for SLS was modified by 1 wt.% multi-walled carbon nanotube (MWCNTs) or a mixture of MWCNTs and graphene (GE) nanoparticles (70/30 wt/wt) in order to investigate on both the synergistic effect provided by the two conductive nanostructured carbonaceous fillers and the correlation between formulation, morphology, and final properties of SLS printed porous structures. In detail, porous structures with a porosity ranging from 20% to 60% were designed using Diamond (D) and Gyroid (G) unit cells. Results showed that the carbonaceous fillers improve the thermal stability of the elastomeric matrix. Furthermore, the TPU/1 wt.% MWCNTs-GE-based porous structures exhibit excellent electrical conductivity and mechanical strength. In particular, all porous structures exhibit a robust negative piezoresistive behavior, as demonstrated from the gauge factor (GF) values that reach values of about −13 at 8% strain. Furthermore, the G20 porous structures (20% of porosity) exhibit microwave absorption coefficients ranging from 0.70 to 0.91 in the 12–18 GHz region and close to 1 at THz frequencies (300 GHz–1 THz). Results show that the simultaneous presence of MWCNTs and GE brings a significant enhancement of specific functional properties of the porous structures, which are proposed as potential actuators with relevant electro-magnetic interference (EMI) shielding properties.
Adsorption and Release of Rose Bengal on Layer-by-Layer Films of Poly(Vinyl Alcohol) and Poly(Amidoamine) Dendrimers Bearing 4-Carboxyphenylboronic Acid
Authors: Yoshida Kentaro , Yamaguchi Akane , Midorikawa Hiroki , Kamijo Toshio , Ono Tetsuya , Dairaku Takenori , Sato Takaya , Fujimura Tsutomu , Kashiwagi Yoshitomo , Sato Katsuhiko
Published: August 2020

Phenylboronic acid-bearing polyamidoamine dendrimer (PBA-PAMAM)/poly(vinyl alcohol) (PVA) multilayer films were prepared through the layer-by-layer (LbL) deposition of PBA-PAMAM solution and PVA solution. PBA-PAMAM/PVA films were constructed successfully through the formation of boronate ester bonds between the boronic acid moiety in PBA and 1,3-diol units in PVA. When the (PBA-PAMAM/PVA)5 films were immersed in rose bengal (RB) solution, RB was adsorbed onto the LbL films. The amount of RB adsorbed was higher in the LbL films immersed in acidic solution than in basic solution. The release of RB from the LbL films was also promoted in the basic solution, while it was suppressed in the acidic solution. The boronic acid ester is oxidized to phenol by hydrogen peroxide (H2O2) and the carbon-boron bond is cleaved, so that the (PBA-PAMAM/PVA)5 films can be decomposed by immersion in H2O2 solution. Therefore, when RB-adsorbed (PBA-PAMAM/PVA)5 films were immersed in H2O2 solution, the release of RB was moderately promoted when the solution was weakly acidic.
Bayesian Calibration of the Aquacrop-OS Model for Durum Wheat by Assimilation of Canopy Cover Retrieved from VENµS Satellite Data
Authors: Upreti Deepak , Pignatti Stefano , Pascucci Simone , Tolomio Massimo , Huang Wenjiang , Casa Raffaele
Published: August 2020

Crop growth models play an important role in agriculture management, allowing, for example, the spatialized estimation of crop yield information. However, crop model parameter calibration is a mandatory step for their application. The present work focused on the regional calibration of the Aquacrop-OS model for durum wheat by assimilating high spatial and temporal resolution canopy cover data retrieved from VENµS satellite images. The assimilation procedure was implemented using the Bayesian approach with the recent implementation of the Markov chain Monte Carlo (MCMC)-based Differential Evolution Adaptive Metropolis (DREAM) algorithm DREAM(KZS). The fraction of vegetation cover (fvc) was retrieved from the VENµS satellite images for two years, during the durum wheat growing seasons of 2018 and 2019 in Central Italy. The retrieval was based on a hybrid method using PROSAIL Radiative Transfer Model (RTM) simulations for training a Gaussian Process Regression (GPR) algorithm, combined with Active Learning to reduce the computational cost. The Aquacrop-OS model was calibrated with the fvc data of 2017–2018 for the Maccarese farm in Central Italy and validated with the 2018–2019 data. The retrieval accuracy of the fvc from the VENµS images were the Coefficient of Determination (R2) = 0.76, Root Mean Square Error (RMSE) = 0.09, and Relative Root Mean Square Error (RRMSE) = 11.6%, when compared with the ground-measured fvc. The MCMC results are presented in terms of Gelman–Rubin R statistics and MR statistics, Markov chains, and marginal posterior distribution functions, which are summarized with the mean values for the most sensitive crop parameters of the Aquacrop-OS model subjected to calibration. When validating for the fvc, the R2 of the model for year (2018–2019) ranged from 0.69 to 0.86. The RMSE, Relative Error (RE), Relative Variability (α), and Relative Bias (β) ranged from 0.15 to 0.44, 0.19 to 2.79, 0.84 to 1.45, and 0.91 to 1.95, respectively. The present work shows the importance of the calibration of the Aquacrop-OS (AOS) crop water productivity model for durum wheat by assimilating remote sensing information from VENµS satellite data.
Activity Energy Expenditure Predicts Clinical Average Levels of Physical Activity in Older Population: Results from Salus in Apulia Study
Authors: Bortone Ilaria , Castellana Fabio , Lampignano Luisa , Zupo Roberta , Moretti Biagio , Giannelli Gianluigi , Panza Francesco , Sardone Rodolfo
Published: August 2020

Self-report questionnaires are a valuable method of physical activity measurement in public health research; however, accuracy is often lacking. Resolving the differences between self-reported and objectively measured physical activity is an important surveillance challenge currently facing population health experts. The present work aims at providing the relationship between activity energy expenditure estimated from wrist-worn accelerometers and intensity of self-reported physical activity (InCHIANTI structured interview questionnaire) in a sub-cohort of a population-based study on aging in Southern Italy. Linear regression was used to test the association between measured and reported physical activity. We found that activity energy expenditure predicted clinical average levels of PA assessed through InCHIANTI classification.
Conical Microstructure Flexible High-Sensitivity Sensing Unit Adopting Chemical Corrosion
Authors: Wang Yangyang , Deng Jiangyu , Duan Junping , Zhang Binzhen
Published: August 2020

Sensor technology is one of the three pillars of information technology. This paper aims to discuss the problems of insensitive detection, poor stability, and uncomfortable wearing of sensors in the fields of human–computer interaction, 5G communication, and medical detection. A sensing unit with a microstructured flexible sensing front end is a cone-like structure with a single size of 18–22 μm. They are evenly distributed and can reach 2500 units per square millimeter. In the pressure range, the sensitivity of the sensor unit is 0.6 KPa−1 (no microstructure sensitivity at 0.15 KPa−1), and the response time is fast (<600 ms). After 400 repeated stretching experiments, the sensor unit can still maintain a stable output signal. Due to its flexible characteristics (50% tensile conductivity), the sensor unit can act on human skin and other curved surfaces. According to the prepared sensing unit, good test results can be obtained on the testing of mechanical devices, curved surfaces of human bodies, and non-contact methods. It is observed that the flexible sensor can be applied to various test occasions, and the manufacturing process of the sensing unit will provide new ideas and methods for the preparation of the flexible sensor technology.
A Novel Paradigm for Underwater Monitoring Using Mobile Sensor Networks
Authors: Babić Anja , Lončar Ivan , Arbanas Barbara , Vasiljević Goran , Petrović Tamara , Bogdan Stjepan , Mišković Nikola
Published: August 2020

This paper presents a novel autonomous environmental monitoring methodology based on collaboration and collective decision-making among robotic agents in a heterogeneous swarm developed within the project subCULTron, tested in a realistic marine environment. The swarm serves as an underwater mobile sensor network for exploration and monitoring of large areas. Different robotic units enable outlier and fault detection, verification of measurements and recognition of environmental anomalies, and relocation of the swarm throughout the environment. The motion capabilities of the robots and the reconfigurability of the swarm are exploited to collect data and verify suspected anomalies, or detect potential sensor faults among the swarm agents. The proposed methodology was tested in an experimental setup in the field in two marine testbeds: the Lagoon of Venice, Italy, and Biograd an Moru, Croatia. Achieved experimental results described in this paper validate and show the potential of the proposed approach.
Flexible Textile-Based Pressure Sensing System Applied in the Operating Room for Pressure Injury Monitoring of Cardiac Operation Patients
Authors: Shih De-Fen , Wang Jyh-Liang , Chao Sou-Chih , Chen Yin-Fa , Liu Kuo-Sheng , Chiang Yi-Shan , Wang Chi , Chang Min-Yu , Yeh Shu-Ling , Chu Pao-Hsien , Lai Chao-Sung , Shye Der-Chi , Ho Lun-Hui , Yang Chia-Ming
Published: August 2020

Pressure injury is the most important issue facing paralysis patients and the elderly, especially in long-term care or nursing. A new interfacial pressure sensing system combined with a flexible textile-based pressure sensor array and a real-time readout system improved by the Kalman filter is proposed to monitor interfacial pressure progress in the cardiac operation. With the design of the Kalman filter and parameter optimization, noise immunity can be improved by approximately 72%. Additionally, cardiac operation patients were selected to test this developed system for the direct correlation between pressure injury and interfacial pressure for the first time. The pressure progress of the operation time was recorded and presented with the visible data by time- and 2-dimension-dependent characteristics. In the data for 47 cardiac operation patients, an extreme body mass index (BMI) and significantly increased pressure after 2 h are the top 2 factors associated with the occurrence of pressure injury. This methodology can be used to prevent high interfacial pressure in high-risk patients before and during operation. It can be suggested that this system, integrated with air mattresses, can improve the quality of care and reduce the burden of the workforce and medical cost, especially for pressure injury.
Horizontal Pod Autoscaling in Kubernetes for Elastic Container Orchestration
Authors: Nguyen Thanh-Tung , Yeom Yu-Jin , Kim Taehong , Park Dae-Heon , Kim Sehan
Published: August 2020

Kubernetes, an open-source container orchestration platform, enables high availability and scalability through diverse autoscaling mechanisms such as Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler and Cluster Autoscaler. Amongst them, HPA helps provide seamless service by dynamically scaling up and down the number of resource units, called pods, without having to restart the whole system. Kubernetes monitors default Resource Metrics including CPU and memory usage of host machines and their pods. On the other hand, Custom Metrics, provided by external software such as Prometheus, are customizable to monitor a wide collection of metrics. In this paper, we investigate HPA through diverse experiments to provide critical knowledge on its operational behaviors. We also discuss the essential difference between Kubernetes Resource Metrics (KRM) and Prometheus Custom Metrics (PCM) and how they affect HPA’s performance. Lastly, we provide deeper insights and lessons on how to optimize the performance of HPA for researchers, developers, and system administrators working with Kubernetes in the future.
A Multimodal Localization Framework Design for IoT Applications
Authors: Aernouts Michiel , Lemic Filip , Moons Bart , Famaey Jeroen , Hoebeke Jeroen , Weyn Maarten , Berkvens Rafael
Published: August 2020

Multiple Radio Access Technology (multi-RAT) communication with Low Power Wide Area Networks (LPWAN) significantly increases the flexibility of Internet of Things (IoT) applications. Location-based services that build upon such a multimodal communication architecture are able to switch to an optimal localization method depending on the constraints of the active wireless technology. Furthermore, the resulting location estimate can aid location-based handover mechanisms to reduce the energy consumption of a multi-RAT IoT device. In this research, we present our design of a multimodal localization framework and illustrate the benefit of such a framework with two IoT use case examples. For the first use case, valuable artwork is tracked during transportation to a museum. In the second use case, we monitor the usage and location of large construction tools. Finally, we propose how our localization framework can be improved to deal with implementation challenges and to reduce location estimation errors.
Collaborative Filtering to Predict Sensor Array Values in Large IoT Networks
Authors: Ortega Fernando , González-Prieto Ángel , Bobadilla Jesús , Gutiérrez Abraham
Published: August 2020

Internet of Things (IoT) projects are increasing in size over time, and some of them are growing to reach the whole world. Sensor arrays are deployed world-wide and their data is sent to the cloud, making use of the Internet. These huge networks can be used to improve the quality of life of the humanity by continuously monitoring many useful indicators, like the health of the users, the air quality or the population movements. Nevertheless, in this scalable context, a percentage of the sensor data readings can fail due to several reasons like sensor reliabilities, network quality of service or extreme weather conditions, among others. Moreover, sensors are not homogeneously replaced and readings from some areas can be more precise than others. In order to address this problem, in this paper we propose to use collaborative filtering techniques to predict missing readings, by making use of the whole set of collected data from the IoT network. State of the art recommender systems methods have been chosen to accomplish this task, and two real sensor array datasets and a synthetic dataset have been used to test this idea. Experiments have been carried out varying the percentage of failed sensors. Results show a good level of prediction accuracy which, as expected, decreases as the failure rate increases. Results also point out a failure rate threshold below which is better to make use of memory-based approaches, and above which is better to choose model-based methods.
Evaluation of Hyperparameter Optimization in Machine and Deep Learning Methods for Decoding Imagined Speech EEG
Authors: Cooney Ciaran , Korik Attila , Folli Raffaella , Coyle Damien
Published: August 2020

Classification of electroencephalography (EEG) signals corresponding to imagined speech production is important for the development of a direct-speech brain–computer interface (DS-BCI). Deep learning (DL) has been utilized with great success across several domains. However, it remains an open question whether DL methods provide significant advances over traditional machine learning (ML) approaches for classification of imagined speech. Furthermore, hyperparameter (HP) optimization has been neglected in DL-EEG studies, resulting in the significance of its effects remaining uncertain. In this study, we aim to improve classification of imagined speech EEG by employing DL methods while also statistically evaluating the impact of HP optimization on classifier performance. We trained three distinct convolutional neural networks (CNN) on imagined speech EEG using a nested cross-validation approach to HP optimization. Each of the CNNs evaluated was designed specifically for EEG decoding. An imagined speech EEG dataset consisting of both words and vowels facilitated training on both sets independently. CNN results were compared with three benchmark ML methods: Support Vector Machine, Random Forest and regularized Linear Discriminant Analysis. Intra- and inter-subject methods of HP optimization were tested and the effects of HPs statistically analyzed. Accuracies obtained by the CNNs were significantly greater than the benchmark methods when trained on both datasets (words: 24.97%, p < 1 × 10–7, chance: 16.67%; vowels: 30.00%, p < 1 × 10–7, chance: 20%). The effects of varying HP values, and interactions between HPs and the CNNs were both statistically significant. The results of HP optimization demonstrate how critical it is for training CNNs to decode imagined speech.
Epitaxial Growth of Sc0.09Al0.91N and Sc0.18Al0.82N Thin Films on Sapphire Substrates by Magnetron Sputtering for Surface Acoustic Waves Applications
Authors: Bartoli Florian , Streque Jérémy , Ghanbaja Jaafar , Pigeat Philippe , Boulet Pascal , Hage-Ali Sami , Naumenko Natalya , Redjaïmia A. , Aubert Thierry , Elmazria Omar
Published: August 2020

Scandium aluminum nitride (ScxAl1-xN) films are currently intensively studied for surface acoustic waves (SAW) filters and sensors applications, because of the excellent tradeoff they present between high SAW velocity, large piezoelectric properties and wide bandgap for the intermediate compositions with an Sc content between 10 and 20%. In this paper, the growth of Sc0.09Al0.91N and Sc0.18Al0.82N films on sapphire substrates by sputtering method is investigated. The plasma parameters were optimized, according to the film composition, in order to obtain highly-oriented films. X-ray diffraction rocking-curve measurements show a full width at half maximum below 1.5°. Moreover, high-resolution transmission electron microscopy investigations reveal the epitaxial nature of the growth. Electrical characterizations of the Sc0.09Al0.91N/sapphire-based SAW devices show three identified modes. Numerical investigations demonstrate that the intermediate compositions between 10 and 20% of scandium allow for the achievement of SAW devices with an electromechanical coupling coefficient up to 2%, provided the film is combined with electrodes constituted by a metal with a high density.
Energy Efficiency in RF Energy Harvesting-Powered Distributed Antenna Systems for the Internet of Things
Authors: Li Jiaxin , Xiong Ke , Cao Jie , Yang Xi , Liu Tong
Published: August 2020

This paper studies a distributed antenna system (DAS) network with radio frequency (RF) energy harvesting (EH) technology where the distributed antenna ports (DAPs) transmit energy and information to multiple users simultaneously. The time division multiple access (TDMA) protocol is adopted, so for each time slot is allowed to receive information, while the rest of the users harvest energy. In order to maximize the system energy efficiency (EE), subject to the EH requirements and data rate requirements of the users, the transmission time and power assignment are jointly optimized. In order to deal with this non-convex problem, based on Dinkelbach theory and the block-coordinate descent (BCD) scheme, an efficient algorithm is designed to obtain the global optimal solution. Then, simulation results are presented to show that the proposed method achieves much higher system EE compared with benchmark methods. With the increase of the user’s minimum information rate, the system EE decreases rapidly.
A Polynomial-Exponent Model for Calibrating the Frequency Response of Photoluminescence-Based Sensors
Authors: Torre Angel de la , Medina-Rodríguez Santiago , Segura Jose C. , Fernández-Sánchez Jorge F.
Published: August 2020

In this work, we propose a new model describing the relationship between the analyte concentration and the instrument response in photoluminescence sensors excited with modulated light sources. The concentration is modeled as a polynomial function of the analytical signal corrected with an exponent, and therefore the model is referred to as a polynomial-exponent (PE) model. The proposed approach is motivated by the limitations of the classical models for describing the frequency response of the luminescence sensors excited with a modulated light source, and can be considered as an extension of the Stern–Volmer model. We compare the calibration provided by the proposed PE-model with that provided by the classical Stern–Volmer, Lehrer, and Demas models. Compared with the classical models, for a similar complexity (i.e., with the same number of parameters to be fitted), the PE-model improves the trade-off between the accuracy and the complexity. The utility of the proposed model is supported with experiments involving two oxygen-sensitive photoluminescence sensors in instruments based on sinusoidally modulated light sources, using four different analytical signals (phase-shift, amplitude, and the corresponding lifetimes estimated from them).
Multilabel Image Classification Based Fresh Concrete Mix Proportion Monitoring Using Improved Convolutional Neural Network
Authors: Yang Han , Jiao Shuang-Jian , Yin Feng-De
Published: August 2020

Proper and accurate mix proportion is deemed to be crucial for the concrete in service to implement its structural functions in a specific environment and structure. Neither existing testing methods nor previous studies have, to date, addressed the problem of real-time and full-scale monitoring of fresh concrete mix proportion during manufacturing. Green manufacturing and safety construction are hindered by such defects. In this study, a state-of-the-art method based on improved convolutional neural network multilabel image classification is presented for mix proportion monitoring. Elaborately planned, uniformly distributed, widely covered and high-quality images of concrete mixtures were collected as dataset during experiments. Four convolutional neural networks were improved or fine-tuned based on two solutions for multilabel image classification problems, since original networks are tailored for single-label multiclassification tasks, but mix proportions are determined by multiple parameters. Various metrices for effectiveness evaluation of training and testing all indicated that four improved network models showed outstanding learning and generalization ability during training and testing. The best-performing one was embedded into executable application and equipped with hardware facilities to establish fresh concrete mix proportion monitoring system. Such system was deployed to terminals and united with mechanical and weighing sensors to establish integrated intelligent sensing system. Fresh concrete mix proportion real-time and full-scale monitoring and inaccurate mix proportion sensing and warning could be achieved simply by taking pictures and feeding pictures into such sensing system instead of conducting experiments in laboratory after specimen retention.
Application of Artificial Neural Networks for Accurate Determination of the Complex Permittivity of Biological Tissue
Authors: Bonello Julian , Demarco Andrea , Farhat Iman , Farrugia Lourdes , Sammut Charles V.
Published: August 2020

Medical devices making use of radio frequency (RF) and microwave (MW) fields have been studied as alternatives to existing diagnostic and therapeutic modalities since they offer several advantages. However, the lack of accurate knowledge of the complex permittivity of different biological tissues continues to hinder progress in of these technologies. The most convenient and popular measurement method used to determine the complex permittivity of biological tissues is the open-ended coaxial line, in combination with a vector network analyser (VNA) to measure the reflection coefficient (S11) which is then converted to the corresponding tissue permittivity using either full-wave analysis or through the use of equivalent circuit models. This paper proposes an innovative method of using artificial neural networks (ANN) to convert measured S11 to tissue permittivity, circumventing the requirement of extending the VNA measurement plane to the coaxial line open end. The conventional three-step calibration technique used with coaxial open-ended probes lacks repeatability, unless applied with extreme care by experienced persons, and is not adaptable to alternative sensor antenna configurations necessitated by many potential diagnostic and monitoring applications. The method being proposed does not require calibration at the tip of the probe, thus simplifying the measurement procedure while allowing arbitrary sensor design, and was experimentally validated using S11 measurements and the corresponding complex permittivity of 60 standard liquid and 42 porcine tissue samples. Following ANN training, validation and testing, we obtained a prediction accuracy of 5% for the complex permittivity.
Characterization of Second-Order Reflection Bands from a Cholesteric Liquid Crystal Cell Based on a Wavelength-Swept Laser
Authors: Ahn Soyeon , Ko Myeong Ock , Kim Jong-Hyun , Chen Zhongping , Jeon Min Yong
Published: August 2020

We report the results of an experimental study of the characterization of second-order reflection bands from a cholesteric liquid crystal (CLC) cell that depends on the applied electric field, using a wide bandwidth wavelength-swept laser. The second-order reflection bands around 1300 nm and 1500 nm were observed using an optical spectrum analyzer when an electric field was applied to a horizontally oriented electrode cell with a pitch of 1.77 μm. A second-order reflection spectrum began to appear when the intensity of the electric field was 1.03 Vrms/μm with the angle of incidence to the CLC cell fixed at 36°. The reflectance increased as the intensity of the electric field increased at an angle of incidence of 20°, whereas at an incident angle of 36°, when an electric field of a predetermined value or more was applied to the CLC cell, it was confirmed that deformation was completely formed in the liquid crystal and the reflectance was saturated to a constant level. As the intensity of the electric field increased further, the reflection band shifted to a longer wavelength and discontinuous wavelength shift due to the pitch jump was observed rather than a continuous wavelength increase. In addition, the reflection band changed when the angle of incidence on the CLC cell was changed. As the angle of incidence gradually increased, the center wavelength of the reflection band moved towards shorter wavelengths. In the future, we intend to develop a device for optical wavelength filters based on side-polished optical fibers. This is expected to have a potential application as a wavelength notch filter or a bandpass filter.
A Comprehensive Survey about Thermal Comfort under the IoT Paradigm: Is Crowdsensing the New Horizon?
Authors: Tomat Valentina , Ramallo-González Alfonso P. , Skarmeta Gómez Antonio F.
Published: August 2020

This paper presents a review of technologies under the paradigm 4.0 applied to the study of the thermal comfort and, implicitly, energy efficiency. The research is based on the analysis of the Internet of Things (IoT) literature, presenting a comparison among several approaches adopted. The central objective of the research is to outline the path that has been taken throughout the last decade towards a people-centric approach, discussing how users switched from being passive receivers of IoT services to being an active part of it. Basing on existing studies, authors performed what was a necessary and unprecedented grouping of the IoT applications to the thermal comfort into three categories: the thermal comfort studies with IoT hardware, in which the approach focuses on physical devices, the mimicking of IoT sensors and comfort using Building Simulation Models, based on the dynamic modelling of the thermal comfort through IoT systems, and Crowdsensing, a new concept in which people can express their sensation proactively using IoT devices. Analysing the trends of the three categories, the results showed that Crowdsensing has a promising future in the investigation through the IoT, although some technical steps forward are needed to achieve a satisfactory application to the thermal comfort matter.
Correction: Garcia-Gonzalez, D.; Rivero, D.; Fernandez-Blanco, E.; Luaces, M.R. A Public Domain Dataset for Real-Life Human Activity Recognition Using Smartphone Sensors. Sensors 2020, 20, 2200
Authors: Garcia-Gonzalez Daniel , Rivero Daniel , Fernandez-Blanco Enrique , Luaces Miguel R.
Published: August 2020

The authors wish to make the following corrections to this paper [...]
The Project-Based Firm: A Theoretical Framework for Building Dynamic Capabilities
Authors: Hermano Víctor , Martín-Cruz Natalia
Published: August 2020

The problem of achieving individual project performance has been replaced by the problem of achieving organizational goals through project performance. Only project-based firms able to learn and build project capabilities can successfully compete in today’s dynamic environments. The purpose of this paper is to present a dynamic capability-based framework that sheds light on how project and organizational dynamic capabilities are built and how these dynamic capabilities allow project-based firms to perform in dynamic environments. Our theoretical framework unpacks the processes of building dynamic capabilities inside a project-based firm, discussing the routines and procedures that are useful to manage projects in unstable and dynamic environments and to build and reconfigure organizational capabilities from project-led knowledge.