bluuebunny/crossref_metadata_2025 huggingface dataset:
Conductive Biomass Films Containing Graphene Oxide and Cationic Cellulose Nanofibers for Electric-Heating Applications
Authors: Liang Shanqing , Wang Huicong , Tao Xin
Published: April 2021

A low-voltage biomass matrix and flexible electric-heating composite with graphene oxide (GO) and cationic cellulose nanofiber (CCNF) were fabricated by ultrasonic dispersion and suction filtration. The main results show that the tensile strength and strain of the films decreased with an increase in the GO content, but the thermal stability increased. The GO/CCNF film underwent rapid thermal decomposition at 250–350 °C, and the maximum degradation temperature was higher by 19 °C compared to that of the pure CCNF film. It was found that the electrical conductivity increased from 0.013 to 2.96 S/cm with an increase in the GO content from 20 to 60 wt%, resulting in an increase in the power density from 122 to 2456 W/m2. The films could rapidly attain the temperature within 50 s, and the heat transferred by radiation and convection was 21.62 mW/°C, thereby exhibiting excellent electric heating response. Moreover, the film demonstrated a stable electric-heating cycle after a 12.5 h cycling test and meets the requirements of low-temperature electric heating products under the 36 V electric safety limit, which expands the potential applications of biomass-derived cellulose nanofibers.
Impact of the Level of Adherence to Mediterranean Diet on the Parameters of Metabolic Syndrome: A Systematic Review and Meta-Analysis of Observational Studies
Authors: Bakaloudi Dimitra Rafailia , Chrysoula Lydia , Kotzakioulafi Evangelia , Theodoridis Xenophon , Chourdakis Michail
Published: April 2021

High adherence to the Mediterranean diet (MD) has been associated with a lower prevalence of Metabolic Syndrome (MetS). The present study aimed to investigate the impact of MD adherence on parameters of MetS. A systematic literature search was performed in PubMed, Cochrane Central Registry of Clinical Trials (CENTRAL), Scopus, EMBASE, Web of Science and Google Scholar databases. Observational studies that recorded adherence to MD and components/measures of the MetS, such as waist circumference (WC), blood pressure (BP), fasting blood glucose (FBG), high-density lipoprotein (HDL) cholesterol and triglycerides (TG), were included in this study. A total of 58 studies were included in our study. WC and TG were significantly lower in the high adherence MD group (SMD: −0.20, (95%CI: −0.40, −0.01), SMD: −0.27 (95%CI: −0.27, −0.11), respectively), while HDL cholesterol was significantly higher in the same group (SMD: −0.28 (95%CI: 0.07, 0.50). There was no difference in FBG and SBP among the two groups (SMD: −0.21 (95%CI: −0.54, 0.12) & SMD: −0.15 (95%CI: −0.38, 0.07), respectively). MD may have a positive impact on all parameters of MetS. However, further research is needed in this field.
Anti-Inflammatory and Immunomodulatory Properties of Fermented Plant Foods
Authors: Shahbazi Roghayeh , Sharifzad Farzaneh , Bagheri Rana , Alsadi Nawal , Yasavoli-Sharahi Hamed , Matar Chantal
Published: April 2021

Fermented plant foods are gaining wide interest worldwide as healthy foods due to their unique sensory features and their health-promoting potentials, such as antiobesity, antidiabetic, antihypertensive, and anticarcinogenic activities. Many fermented foods are a rich source of nutrients, phytochemicals, bioactive compounds, and probiotic microbes. The excellent biological activities of these functional foods, such as anti-inflammatory and immunomodulatory functions, are widely attributable to their high antioxidant content and lactic acid-producing bacteria (LAB). LAB contribute to the maintenance of a healthy gut microbiota composition and improvement of local and systemic immunity. Besides, antioxidant compounds are involved in several functional properties of fermented plant products by neutralizing free radicals, regulating antioxidant enzyme activities, reducing oxidative stress, ameliorating inflammatory responses, and enhancing immune system performance. Therefore, these products may protect against chronic inflammatory diseases, which are known as the leading cause of mortality worldwide. Given that a large body of evidence supports the role of fermented plant foods in health promotion and disease prevention, we aim to discuss the potential anti-inflammatory and immunomodulatory properties of selected fermented plant foods, including berries, cabbage, and soybean products, and their effects on gut microbiota.
Dietary Micronutrients and Risk of Chronic Kidney Disease: A Cohort Study with 12 Year Follow-Up
Authors: Lee Juyeon , Oh Kook-Hwan , Park Sue-Kyung
Published: April 2021

We investigated the association between dietary micronutrient intakes and the risk of chronic kidney disease (CKD) in the Ansan-Ansung study of the Korean Genome and Epidemiologic Study (KoGES), a population-based prospective cohort study. Of 9079 cohort participants with a baseline estimate glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 and a urine albumin to creatinine ratio (UACR) <300 mg/g and who were not diagnosed with CKD, we ascertained 1392 new CKD cases over 12 year follow-up periods. The risk of CKD according to dietary micronutrient intakes was presented using hazard ratios (HRs) and 95% confidence intervals (95% CIs) in a full multivariable Cox proportional hazard models, adjusted for multiple micronutrients and important clinico-epidemiological risk factors. Low dietary intakes of phosphorus (<400 mg/day), vitamin B2 (<0.7 mg/day) and high dietary intake of vitamin B6 (≥1.6 mg/day) and C (≥100 mg/day) were associated with an increased risk of CKD stage 3B and over, compared with the intake at recommended levels (HR = 6.78 [95%CI = 2.18–21.11]; HR = 2.90 [95%CI = 1.01–8.33]; HR = 2.71 [95%CI = 1.26–5.81]; HR = 1.83 [95%CI = 1.00–3.33], respectively). In the restricted population, excluding new CKD cases defined within 2 years, an additional association with low folate levels (<100 µg/day) in higher risk of CKD stage 3B and over was observed (HR = 6.72 [95%CI = 1.40–32.16]). None of the micronutrients showed a significant association with the risk of developing CKD stage 3A. Adequate intake of micronutrients may lower the risk of CKD stage 3B and over, suggesting that dietary guidelines are needed in the general population to prevent CKD.
Curcuma Longa, the “Golden Spice” to Counteract Neuroinflammaging and Cognitive Decline—What Have We Learned and What Needs to Be Done
Authors: Berry Alessandra , Collacchi Barbara , Masella Roberta , Varì Rosaria , Cirulli Francesca
Published: April 2021

Due to the global increase in lifespan, the proportion of people showing cognitive impairment is expected to grow exponentially. As target-specific drugs capable of tackling dementia are lagging behind, the focus of preclinical and clinical research has recently shifted towards natural products. Curcumin, one of the best investigated botanical constituents in the biomedical literature, has been receiving increased interest due to its unique molecular structure, which targets inflammatory and antioxidant pathways. These pathways have been shown to be critical for neurodegenerative disorders such as Alzheimer’s disease and more in general for cognitive decline. Despite the substantial preclinical literature on the potential biomedical effects of curcumin, its relatively low bioavailability, poor water solubility and rapid metabolism/excretion have hampered clinical trials, resulting in mixed and inconclusive findings. In this review, we highlight current knowledge on the potential effects of this natural compound on cognition. Furthermore, we focus on new strategies to overcome current limitations in its use and improve its efficacy, with attention also on gender-driven differences.
Development and Validation of the Brief Nursing Stress Scale (BNSS) in a Sample of End-of-Life Care Nurses
Authors: Sansó Noemí , Vidal-Blanco Gabriel , Galiana Laura
Published: April 2021

Nursing has been identified as a very stressful profession. Specifically in end-of-life care, nurses frequently experience stressful situations related to death and dying. This study aims to develop and validate a short scale of stress in nurses, the Brief Nursing Stress Scale. A cross-sectional survey of Spanish end-of-life care professionals was conducted; 129 nurses participated. Analyses included a confirmatory factor analysis of the Brief Nursing Stress Scale, estimation of reliability, relation with sex, age and working place, and the estimation of a structural equation model in which BNSS predicted burnout and work satisfaction The confirmatory factor analysis showed an adequate fit: χ2(9) = 20.241 (p = 0.017); CFI = 0.924; SRMR = 0.062; RMSEA = 0.098 [0.040,0.156]. Reliability was 0.712. Women and men showed no differences in stress. Younger nurses and those working in hospital compared to homecare showed higher levels of stress. A structural equation model showed nursing stress positively predicted burnout, which in turn negatively predicted work satisfaction. Nursing stress also had an indirect, negative effect on work satisfaction. The Brief Nursing Stress Scale showed adequate estimates of validity, reliability, and predictive power in a sample of end-of-life care nurses. This is a short, easy-to-use measure that could be employed in major batteries assessing quality of healthcare institutions.
Uncommon Non-Candida Yeasts in Healthy Turkeys—Antimicrobial Susceptibility and Biochemical Characteristic of Trichosporon Isolates
Authors: Bobrek Kamila , Sokół Ireneusz , Gaweł Andrzej
Published: April 2021

The microbiota of the gastrointestinal tract of humans and animals is inhabited by a diverse community of bacteria, fungi, protozoa, and viruses. In cases where there is an imbalance in the normal microflora or an immunosuppression on the part of the host, these opportunistic microorganisms can cause severe infections. The study presented here evaluates the biochemical and antifungal susceptibility features of Trichosporon spp., uncommon non-Candida strains isolated from the gastrointestinal tract of healthy turkeys. The Trichosporon coremiiforme and Trichosporon (Apiotrichum) montevideense accounted for 7.7% of all fungi isolates. The biochemical tests showed that Trichosporon coremiiforme had active esterase (C4), esterase-lipase (C8) valine arylamidase, naphthol-AS-BI phosphohydrolase, α-galactosidase, and β-glucosidase. Likewise, Trichosporon montevideense demonstrated esterase-lipase (C8), lipase (C14), valine arylamidase, naphthol-AS-BI phosphohydrolase, α-galactosidase, and β-glucosidase activity. T.coremiiforme and T. monteviidense isolated from turkeys were itraconazole resistant and amphotericin B, fluconazole, and voriconazole susceptible. Compared with human isolates, the MIC range and MIC values of turkey isolates to itraconazole were in a higher range limit in both species, while MIC values to amphotericin B, fluconazole, and voriconazole were in a lower range limit. Furthermore, the obtained ITS1—5.8rRNA—ITS2 fragment sequences were identical with T. coremiiforme and T. montevideense sequences isolated from humans indicating that these isolates are shared pathogens.
Quantitative Assessment of the Entry through Mechanical Transport in Aircraft of Rift Valley Fever Virus-Infected Mosquitoes into Previously Unaffected Areas
Authors: Filippitzi Maria-Eleni , Saegerman Claude
Published: April 2021

(1): Rift Valley Fever (RVF) is a zoonotic disease of significant international health concern and considered as an emerging risk to Europe, where no RVF outbreaks in humans or animals have been reported so far. (2): Using a stochastic approach, we estimated the risk of RVF virus (RVFV) introduction during the period of May to October (the period when mosquito populations, including RVFV potential vectors, are present in European countries), into previously unaffected areas (e.g., United Kingdom, UK) via virus-carrying vectors traveling in commercial aircraft from RVF-affected countries (e.g., East Africa); (3): On average N = 68 (95% CI: 0–337), RVF-virus-infected mosquitoes are estimated to be mechanically transported by planes (with N = 0 as most likely), in direct flights from RVF-affected East African countries to the UK, between May and October. This estimate is considered as low but not negligible. The model developed should be easily scaled up to other European countries by amending appropriately country-specific variables (e.g., number of flights between countries) in order to map the areas/airports of higher risk and inform risk management per country accordingly and to adopt risk-mitigation measures.
Sonoporation Using Nanoparticle-Loaded Microbubbles Increases Cellular Uptake of Nanoparticles Compared to Co-Incubation of Nanoparticles and Microbubbles
Authors: Snipstad Sofie , Hanstad Sigurd , Bjørkøy Astrid , Mørch Ýrr , de Lange Davies Catharina
Published: April 2021

Therapeutic agents can benefit from encapsulation in nanoparticles, due to improved pharmacokinetics and biodistribution, protection from degradation, increased cellular uptake and sustained release. Microbubbles in combination with ultrasound have been shown to improve the delivery of nanoparticles and drugs to tumors and across the blood-brain barrier. Here, we evaluate two different microbubbles for enhancing the delivery of polymeric nanoparticles to cells in vitro: a commercially available lipid microbubble (Sonazoid) and a microbubble with a shell composed of protein and nanoparticles. Various ultrasound parameters are applied and confocal microscopy is employed to image cellular uptake. Ultrasound enhanced cellular uptake depending on the pressure and duty cycle. The responsible mechanisms are probably sonoporation and sonoprinting, followed by uptake, and to a smaller degree enhanced endocytosis. The use of commercial Sonazoid microbubbles leads to significantly lower uptake than when using nanoparticle-loaded microbubbles, suggesting that proximity between cells, nanoparticles and microbubbles is important, and that mainly nanoparticles in the shell are taken up, rather than free nanoparticles in solution.
Low Noise Short Wavelength Infrared Avalanche Photodetector Using SB-Based Strained Layer Superlattice
Authors: Dehzangi Arash , Li Jiakai , Razeghi Manijeh
Published: April 2021

We demonstrate low noise short wavelength infrared (SWIR) Sb-based type II superlattice (T2SL) avalanche photodiodes (APDs). The SWIR GaSb/(AlAsSb/GaSb) APD structure was designed based on impact ionization engineering and grown by molecular beam epitaxy on a GaSb substrate. At room temperature, the device exhibits a 50% cut-off wavelength of 1.74 µm. The device was revealed to have an electron-dominated avalanching mechanism with a gain value of 48 at room temperature. The electron and hole impact ionization coefficients were calculated and compared to give a better prospect of the performance of the device. Low excess noise, as characterized by a carrier ionization ratio of ~0.07, has been achieved.
State-of-Art of Standard and Innovative Materials Used in Cranioplasty
Authors: Siracusa Valentina , Maimone Giuseppe , Antonelli Vincenzo
Published: April 2021

Cranioplasty is the surgical technology employed to repair a traumatic head injury, cerebrovascular disease, oncology resection and congenital anomalies. Actually, different bone substitutes are used, either derived from biological products such as hydroxyapatite and demineralized bone matrix or synthetic ones such as sulfate or phosphate ceramics and polymer-based substitutes. Considering that the choice of the best material for cranioplasty is controversial, linked to the best operation procedure, the intent of this review was to report the outcome of research conducted on materials used for such applications, comparing the most used materials. The most interesting challenge is to preserve the mechanical properties while improving the bioactivity, porosity, biocompatibility, antibacterial properties, lowering thickness and costs. Among polymer materials, polymethylmethacrylate and polyetheretherketone are the most motivating, due to their biocompatibility, rigidity and toughness. Other biomaterials, with ecofriendly attributes, such as polycaprolactone and polylactic acid have been investigated, due to their microstructure that mimic the trabecular bone, encouraging vascularization and cell–cell communications. Taking into consideration that each material must be selected for specific clinical use, the main limitation remains the defects and the lack of vascularization, consequently porous synthetic substitutes could be an interesting way to support a faster and wider vascularization, with the aim to improve patient prognosis.
H2S-Sensing Studies Using Interdigitated Electrode with Spin-Coated Carbon Aerogel-Polyaniline Composites
Authors: Bibi Aamna , Rubio Yuola Rose M. , Santiago Karen S. , Jia His-Wei , Ahmed Mahmoud M. M. , Lin Yi-Feng , Yeh Jui-Ming
Published: April 2021

In this paper, carbon aerogel (CA)-polyaniline (PANI) composites were prepared and first applied in the study of H2S gas sensing. Here, 1 and 3 wt% of as-obtained CA powder were blended with PANI to produce composites, which are denoted by PANI-CA-1 and PANI-CA-3, respectively. For the H2S gas-sensing studies, the interdigitated electrode (IDE) was spin-coated by performing PANI and PANI-CA composite dispersion. The H2S gas-sensing properties were studied in terms of the sensor’s sensitivity, selectivity and repeatability. IDE coated with PANI-CA composites, as compared with pristine PANI, achieved higher sensor sensitivity, higher selectivity and good repeatability. Moreover, composites that contain higher loading of CA (e.g., 3 wt%) perform better than composites with lower loading of CA. At 1 ppm, PANI-CA-3 displayed increased sensitivity of 452% at relative humidity of 60% with a fast average response time of 1 s compared to PANI.
Enhanced Resistance to Amylolysis in Rice Kernels through Interaction with Chlorogenic Acid
Authors: Li Yi-Ling , Huang Yu-Wen , Wu Min-Zi , Wu Tsung-Yen , Lai Ping-Shan , Sun Nan-Nong , Saw Chiou-Yeong , Li Chia-Wei , Chau Chi-Fai
Published: April 2021

In this study, rice-phenolic acid complexes were prepared by processing rice kernels in chlorogenic acid (CGA) solutions of different concentrations, followed by heating at different adsorption times. An adsorption treatment of 80 °C for 3 h effectively enhanced the complexation of rice samples with CGA (3.86 mg/g) and imparted antioxidant capacities to the complex. An apparent interaction between CGA and rice starch molecules was suggested by electrospray ionization mass spectrometry analysis. Our results revealed that rice samples were functionalized with CGA by modifying their physicochemical properties by increasing swelling ability (9.1%) and breakdown value (24.7%), and retarding retrogradation (−9.8%). The complexation of rice with a high dose of CGA could significantly reduce in vitro and in vivo starch digestibility by 41.9% and 23.0%, respectively, relative to control. This treatment is considered a potential way to confer rice with an increased resistance to digestion, along with desirable pasting properties.
Selective Adsorption of CR (VI) onto Amine-Modified Passion Fruit Peel Biosorbent
Authors: Zhao Xiaolei , Zheng Junli , You Shaohong , Du Linlin , Liu Chongmin , Chen Kaiwei , Liu Yuanli , Ma Lili
Published: April 2021

This study aimed to prepare surface amino-riched passion fruit peel (DAPFP) by amination reaction with low-cost biomaterials and use it as a biosorbent to adsorb Cr (VI). The specific physicochemical and structural properties of DAPFP were characterized by SEM, EDS, XRD, TG, Zeta, XPS, and FT-IR. The effects of pH value, initial concentration, adsorption time, coexisting ions, and temperature on the adsorption of Cr (VI) were systematically investigated. The results showed that within 90 min, DAPFP could reduce the concentration of Cr (VI) solution (1 mg/L−1) to an allowable safe level of drinking water (0.05 mg/L−1) specified by the World Health Organization. The adsorption process complies with pseudo-second-order kinetics and the Langmuir isotherm model. The adsorption capacity of the prepared biosorbent could reach 675.65 mg/g−1. The results of thermodynamic studies confirmed that the adsorption process was a self-discharging heat process. DAPFP also showed good reusability; even after being used repeatedly five times, it still showed excellent adsorption performance. FT-IR and XPS analyses showed that electrostatic attraction and reduction were the main reasons for the adsorption. By virtue of its low cost and excellent adsorption performance, DAPFP has a potential practical application as an adsorbent in treating Cr (VI) containing wastewater.
Bead Geometry Prediction Model for 9% Nickel Laser Weldment, Part 1: Global Regression Model vs. Modified Regression Model
Authors: Kim Jisun , Kim Jaewoong , Pyo Changmin , Chun Kwangsan
Published: April 2021

Due to its excellent toughness and stiffness in cryogenic conditions, 9% nickel steel is applied to LNG storage facilities, and its usage is increasing as a result of changes in environmental regulations. A study was conducted on the development of a predictive model to optimize the laser welding process of 9% nickel steel, and two prediction models were developed using one hundred data points obtained through experiments. A global regression model used as a general prediction model and a modified regression model using the p-value of the analysis of variance were developed, and their prediction performance was compared. It was found that the modified regression model was superior to the global regression model in terms of predicting the bead shape, including parameters such as penetration depth, bead height, and area ratio.
Microporous Oxide-Based Surface-Enhanced Raman Scattering Film for Quadrillionth Detection of Mercury Ion (II)
Authors: Tangsuwanjinda Sripansuang , Chen Yu-Yu , Lai Ching-Hsiang , Jhou Guan-Ting , Chiang Yu-Wei , Cheng Hsin-Ming
Published: April 2021

A variety of chemical sensing materials and procedures for conveniently detecting mercuric ion (II) (Hg2+) have been extensively explored. The detection challenges for accomplishing a simple, fast, and low investment procedure at the ultrasensitive level are ongoing. Herein we report a quadrillionth level for detecting Hg2+ by the surface-enhanced Raman scattering (SERS) technique. There is an interaction of silver nanoparticles decorated on a zinc-oxide tetrapod structure and coated on FTO glass (Ag@ZnO-FTO) with an organic ligand. 4,4′-Dipyridyl (DPy) performed as being chemisorbed by Ag nanoparticles interacting with a pyridine ring to produce plasmonic hot spots for SERS. The morphology of the surface and porous structure of the tetrapod becomes the powerful platform for enhanced SERS performance of DPy detection. In the absence of the augmentative electrolyte, the enhancement factor for DPy is more than 107. The inhibiting of the aggregation between Ag and DPy was present following the appearance of Hg2+, demonstrated by the quenching of the SERS signal from the DPy molecules. The capability to reproduce and the selectivity of the sensing by DPy were both demonstrated. In addition, the applications for detecting Hg2+ in natural water and beverages were successfully detected. These results demonstrated the SERS sensors had the potential for detecting Hg2+ in practical use.
A Novel Autoregressive Rainflow—Integrated Moving Average Modeling Method for the Accurate State of Health Prediction of Lithium-Ion Batteries
Authors: Huang Junhan , Wang Shunli , Xu Wenhua , Shi Weihao , Fernandez Carlos
Published: April 2021

The accurate estimation and prediction of lithium-ion battery state of health are one of the important core technologies of the battery management system, and are also the key to extending battery life. However, it is difficult to track state of health in real-time to predict and improve accuracy. This article selects the ternary lithium-ion battery as the research object. Based on the cycle method and data-driven idea, the improved rain flow counting algorithm is combined with the autoregressive integrated moving average model prediction model to propose a new prediction for the battery state of health method. Experiments are carried out with dynamic stress test and cycle conditions, and a confidence interval method is proposed to fit the error range. Compared with the actual value, the method proposed in this paper has a maximum error of 5.3160% under dynamic stress test conditions, a maximum error of 5.4517% when the state of charge of the cyclic conditions is used as a sample, and a maximum error of 0.7949% when the state of health under cyclic conditions is used as a sample.
Large Molecular Cluster Formation from Liquid Materials and Its Application to ToF-SIMS
Authors: Moritani Kousuke , Nagata Shogo , Tanaka Atsushi , Goto Kosuke , Inui Norio
Published: April 2021

Since molecular cluster ion beams are expected to have various chemical effects, they are promising candidates for improving the secondary ion yield of Tof-SIMS. However, in order to clarify the effect and its mechanism, it is necessary to generate molecular cluster ion beams with various chemical properties and systematically examine it. In this study, we have established a method to stably form various molecular cluster ion beams from relatively small amounts of liquid materials for a long time by the bubbling method. Furthermore, we applied the cluster ion beams of water, methanol, methane, and benzene to the primary beam of SIMS and compared the molecular ion yields of aspartic acid. The effect of enhancing the yields of [M+H]+ ion of aspartic acid was found to be the largest for the water cluster and small for the methane and benzene clusters. These results indicate that the chemical effect contributes to the desorption/ionization process of organic molecules by the molecular cluster ion beam.
Discipleship in Oriental Orthodox and Evangelical Communities
Authors: Lee Ralph
Published: April 2021

In many countries with a strong Orthodox Christian presence there are tensions between Evangelicals and Orthodox Christians. These tensions are rooted in many theological, ecclesiological, and epistemological differences. In practice, one of the crucial causes of tension comes down to different practical understandings of what a Christian disciple looks like. This paper examines key aspects of discipleship as expressed in revival movements in Orthodox Churches Egypt, India and Ethiopia which are connected to the challenges presented by the huge expansion of Evangelical Protestant mission from the nineteenth century. Key aspects will be evaluated in comparison with aspects that are understood to characterize disciples in Evangelical expressions, including: differing understandings of the sacraments and their place in the life of a disciple; ways in which different traditions engage with the Bible and related literary works; contrasting outlooks on discipleship as an individual and a community way of life; and differing understanding of spiritual disciplines.
Detection of Biogenic Oil Films near Aquaculture Sites Using Sentinel-1 and Sentinel-2 Satellite Images
Authors: Chatziantoniou Andromachi , Karagaitanakis Alexandros , Bakopoulos Vasileios , Papandroulakis Nikos , Topouzelis Konstantinos
Published: April 2021

Biogenic films are very thin surface oils, frequently observed near aquaculture farms, that affect the roughness and the optical properties of the sea surface, making them visible in SAR and multispectral images. The purpose of this study is to investigate the potential of satellite SAR and multispectral sensors in the detection of biogenic oil films near aquaculture farms. Sentinel-1 SAR and Sentinel-2 multispectral data were exploited to detect the films around three aquaculture sites. The study is divided in three stages: (a) preprocessing, (b) main process and (c) accuracy assessment. The preprocessing stage includes subset, filtering, land masking and image corrections. The main process was similar for both datasets, using an adaptive thresholding method to identify dark formations, extract and classify them. Finally, the performance of the algorithm was evaluated based on the estimation of standard classification error statistics. The evaluation of the results was based on empirical photointerpretation and in situ photos. The results are successful and promising, with overall accuracy over 70%, while both sensors are proved to be effective in the detection, with Sentinel-1 SAR presenting slightly better accuracy (81%) than Sentinel-2 MSI (70%). There is no evidence of these films causing stress to the aquaculture farms or the surrounding environment; however, our knowledge on their presence, amount and dissolution is limited and further knowledge could contribute to efficient feeding management and fish welfare.
Joint Geoeffectiveness and Arrival Time Prediction of CMEs by a Unified Deep Learning Framework
Authors: Fu Huiyuan , Zheng Yuchao , Ye Yudong , Feng Xueshang , Liu Chaoxu , Ma Huadong
Published: April 2021

Fast and accurate prediction of the geoeffectiveness of coronal mass ejections (CMEs) and the arrival time of the geoeffective CMEs is urgent, to reduce the harm caused by CMEs. In this paper, we present a new deep learning framework based on time series of satellites’ optical observations that can give both the geoeffectiveness and the arrival time prediction of the CME events. It is the first time combining these two demands in a unified deep learning framework with no requirement of manually feature selection and get results immediately. The only input of the deep learning framework is the time series images from synchronized solar white-light and EUV observations. Our framework first uses the deep residual network embedded with the attention mechanism to extract feature maps for each observation image, then fuses the feature map of each image by the feature map fusion module and determines the geoeffectiveness of CME events. For the geoeffective CME events, we further predict its arrival time by the deep residual regression network based on group convolution. In order to train and evaluate our proposed framework, we collect 2400 partial-/full-halo CME events and its corresponding images from 1996 to 2018. The F1 score and Accuracy of the geoeffectiveness prediction can reach 0.270% and 75.1%, respectively, and the mean absolute error of the arrival time prediction is only 5.8 h, which are both significantly better than well-known deep learning methods and can be comparable to, or even better than, the best performance of traditional methods.
Validation of Satellite-Based Precipitation Products from TRMM to GPM
Authors: Wang Jianxin , Petersen Walter A. , Wolff David B.
Published: April 2021

The global precipitation measurement mission (GPM) has been in operation for seven years and continues to provide a vast quantity of global precipitation data at finer temporospatial resolutions with improved accuracy and coverage. GPM’s signature algorithm, the integrated multisatellite retrievals for GPM (IMERG) is a next-generation of precipitation product expected for wide variety of research and operational applications. This study evaluates the latest version (V06B) of IMERG and its predecessor, the tropical rainfall measuring mission (TRMM) multisatellite precipitation (TMPA) 3B42 (V7) using ground-based and gauge-corrected multiradar multisensor system (MRMS) precipitation products over the conterminous United States (CONUS). The spatial distributions of all products are analyzed. The error characteristics are further examined for 3B42 and IMERG in winter and summer by an error decomposition approach, which partitions total bias into hit bias, biases due to missed precipitation and false precipitation. The volumetric and categorical statistical metrics are used to quantitatively evaluate the performance of the two satellite-based products. All products show a similar precipitation climatology with some regional differences. The two satellite-based products perform better in the eastern CONUS than in the mountainous Western CONUS. The evaluation demonstrates the clear improvement in IMERG precipitation product in comparison with its predecessor 3B42, especially in reducing missed precipitation in winter and summer, and hit bias in winter, resulting in better performance in capturing lighter and heavier precipitation.
Fast Bayesian Compressed Sensing Algorithm via Relevance Vector Machine for LASAR 3D Imaging
Authors: Tian Bokun , Zhang Xiaoling , Li Liang , Pu Ling , Pu Liming , Shi Jun , Wei Shunjun
Published: April 2021

Because of the three-dimensional (3D) imaging scene’s sparsity, compressed sensing (CS) algorithms can be used for linear array synthetic aperture radar (LASAR) 3D sparse imaging. CS algorithms usually achieve high-quality sparse imaging at the expense of computational efficiency. To solve this problem, a fast Bayesian compressed sensing algorithm via relevance vector machine (FBCS–RVM) is proposed in this paper. The proposed method calculates the maximum marginal likelihood function under the framework of the RVM to obtain the optimal hyper-parameters; the scattering units corresponding to the non-zero optimal hyper-parameters are extracted as the target-areas in the imaging scene. Then, based on the target-areas, we simplify the measurement matrix and conduct sparse imaging. In addition, under low signal to noise ratio (SNR), low sampling rate, or high sparsity, the target-areas cannot always be extracted accurately, which probably contain several elements whose scattering coefficients are too small and closer to 0 compared to other elements. Those elements probably make the diagonal matrix singular and irreversible; the scattering coefficients cannot be estimated correctly. To solve this problem, the inverse matrix of the singular matrix is replaced with the generalized inverse matrix obtained by the truncated singular value decomposition (TSVD) algorithm to estimate the scattering coefficients correctly. Based on the rank of the singular matrix, those elements with small scattering coefficients are extracted and eliminated to obtain more accurate target-areas. Both simulation and experimental results show that the proposed method can improve the computational efficiency and imaging quality of LASAR 3D imaging compared with the state-of-the-art CS-based methods.
Earthquake Source Investigation of the Kanallaki, March 2020 Sequence (North-Western Greece) Based on Seismic and Geodetic Data
Authors: Svigkas Nikos , Kiratzi Anastasia , Antonioli Andrea , Atzori Simone , Tolomei Cristiano , Salvi Stefano , Polcari Marco , Bignami Christian
Published: April 2021

The active collision of the Apulian continental lithosphere with the Eurasian plate characterizes the tectonics of the Epirus region in northwestern Greece, invoking crustal shortening. Epirus has not experienced any strong earthquakes during the instrumental era and thus there is no detailed knowledge of the way the active deformation is being expressed. In March 2020, a moderate size (Mw 5.8) earthquake sequence occurred close to the Kanallaki village in Epirus. The mainshock and major aftershock focal mechanisms are compatible with reverse faulting, on NNW-ESE trending nodal planes. We measure the coseismic surface deformation using radar interferometry and investigate the possible fault geometries based on seismic waveforms and InSAR data. Slip distribution models provide good fits to both nodal planes and cannot resolve the fault plane ambiguity. The results indicate two slip episodes for a 337° N plane dipping 37° to the east and a single slip patch for a 137° N plane dipping 43° to 55° to the west. Even though the area of the sequence is very close to the triple junction of western Greece, the Kanallaki 2020 activity itself seems to be distinct from it, in terms of the acting stresses.
Fast and Sensitive Bacteria Detection by Boronic Acid Modified Fluorescent Dendrimer
Authors: Mikagi Ayame , Tsurufusa Riho , Tsuchido Yuji , Hashimoto Takeshi , Hayashita Takashi
Published: April 2021

This study reports a novel, fast, easy, and sensitive detection method for bacteria which is urgently needed to diagnose infections in their early stages. Our work presents a complex of poly(amidoamine) dendrimer modified by phenylboronic acid and labeled by a fluorescent dansyl group (Dan-B8.5-PAMAM). Our system detects bacteria in 20 min with a sensitivity of approximately 104 colony-forming units (CFU)·mL−1. Moreover, it does not require any peculiar technical skills or expensive materials. The driving force for bacteria recognition is the binding between terminal phenylboronic acids on the probe and bacteria’s surface glycolipids, rather than electrostatic interactions. The aggregation caused by such binding reduces fluorescence. Even though our recognition method does not distinguish between live or dead bacteria, it shows selective antibacterial activity towards Gram-negative bacteria. This study may potentially contribute a new method for the convenient detection and killing of bacteria.
Secure Combination of IoT and Blockchain by Physically Binding IoT Devices to Smart Non-Fungible Tokens Using PUFs
Authors: Arcenegui Javier , Arjona Rosario , Román Roberto , Baturone Iluminada
Published: April 2021

Non-fungible tokens (NFTs) are widely used in blockchain to represent unique and non-interchangeable assets. Current NFTs allow representing assets by a unique identifier, as a possession of an owner. The novelty introduced in this paper is the proposal of smart NFTs to represent IoT devices, which are physical smart assets. Hence, they are also identified as the utility of a user, they have a blockchain account (BCA) address to participate actively in the blockchain transactions, they can establish secure communication channels with owners and users, and they operate dynamically with several modes associated with their token states. A smart NFT is physically bound to its IoT device thanks to the use of a physical unclonable function (PUF) that allows recovering its private key and, then, its BCA address. The link between tokens and devices is difficult to break and can be traced during their lifetime, because devices execute a secure boot and carry out mutual authentication processes with new owners and users that could add new software. Hence, devices prove their trusted hardware and software. A whole demonstration of the proposal developed with ESP32-based IoT devices and Ethereum blockchain is presented, using the SRAM of the ESP32 microcontroller as the PUF.
Table Tennis Tutor: Forehand Strokes Classification Based on Multimodal Data and Neural Networks
Authors: Mat Sanusi Khaleel Asyraaf , Mitri Daniele Di , Limbu Bibeg , Klemke Roland
Published: April 2021

Beginner table-tennis players require constant real-time feedback while learning the fundamental techniques. However, due to various constraints such as the mentor’s inability to be around all the time, expensive sensors and equipment for sports training, beginners are unable to get the immediate real-time feedback they need during training. Sensors have been widely used to train beginners and novices for various skills development, including psychomotor skills. Sensors enable the collection of multimodal data which can be utilised with machine learning to classify training mistakes, give feedback, and further improve the learning outcomes. In this paper, we introduce the Table Tennis Tutor (T3), a multi-sensor system consisting of a smartphone device with its built-in sensors for collecting motion data and a Microsoft Kinect for tracking body position. We focused on the forehand stroke mistake detection. We collected a dataset recording an experienced table tennis player performing 260 short forehand strokes (correct) and mimicking 250 long forehand strokes (mistake). We analysed and annotated the multimodal data for training a recurrent neural network that classifies correct and incorrect strokes. To investigate the accuracy level of the aforementioned sensors, three combinations were validated in this study: smartphone sensors only, the Kinect only, and both devices combined. The results of the study show that smartphone sensors alone perform sub-par than the Kinect, but similar with better precision together with the Kinect. To further strengthen T3’s potential for training, an expert interview session was held virtually with a table tennis coach to investigate the coach’s perception of having a real-time feedback system to assist beginners during training sessions. The outcome of the interview shows positive expectations and provided more inputs that can be beneficial for the future implementations of the T3.
Sensitivity Validation of EWOD Devices for Diagnosis of Early Mortality Syndrome (EMS) in Shrimp Using Colorimetric LAMP–XO Technique
Authors: Sukthang Kreeta , Kampeera Jantana , Sriprachuabwong Chakrit , Kiatpathomchai Wansika , Pengwang Eakkachai , Tuantranont Adisorn , Wechsatol Wishsanuruk
Published: April 2021

Electrowetting-on-dielectric (EWOD) is a microfluidic technology used for manipulating liquid droplets at microliter to nanoliter scale. EWOD has the ability to facilitate the accurate manipulation of liquid droplets, i.e., transporting, dispensing, splitting, and mixing. In this work, EWOD fabrication with suitable and affordable materials is proposed for creating EWOD lab-on-a-chip platforms. The EWOD platforms are applied for the diagnosis of early mortality syndrome (EMS) in shrimp by utilizing the colorimetric loop-mediated isothermal amplification method with pH-sensitive xylenol orange (LAMP–XO) diagnosis technique. The qualitative sensitivity is observed by comparing the limit of detection (LOD) while performing the LAMP–XO diagnosis test on the proposed lab-on-a-chip EWOD platform, alongside standard LAMP laboratory tests. The comparison results confirm the reliability of EMS diagnosis on the EWOD platform with qualitative sensitivity for detecting the EMS DNA plasmid concentration at 102 copies in a similar manner to the common LAMP diagnosis tests.
Validation of a Low-Cost Pavement Monitoring Inertial-Based System for Urban Road Networks
Authors: Loprencipe Giuseppe , de Almeida Filho Flavio Guilherme Vaz , de Oliveira Rafael Henrique , Bruno Salvatore
Published: April 2021

Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, a novel inertial sensor-based system is proposed using a low-cost inertial measurement unit (IMU) and a global positioning system (GPS) module, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to indirectly monitor the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was used. Considering 21 km of roads with different levels of pavement decay, validation measurements were performed using the novel sensor, a high performance inertial based navigation sensor, and a road surface profiler. Therefore, comparisons between awz determined with accelerations measured on the two different inertial sensors are made; in addition, also correlations between awz, and typical pavement indicators such as international roughness index, and ride number were also performed. The results showed very good correlations between the awz values calculated with the two inertial devices (R2 = 0.98). In addition, the correlations between awz values and the typical pavement indices showed promising results (R2 = 0.83–0.90). The proposed sensor may be assumed as a reliable and easy-to-install method to assess the pavement conditions in urban road networks, since the use of traditional systems is difficult and/or expensive.
Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation
Authors: Varouchakis Emmanouil A. , Kamińska-Chuchmała Anna , Kowalik Grzegorz , Spanoudaki Katerina , Graña Manuel
Published: April 2021

The wide availability of satellite data from many distributors in different domains of science has provided the opportunity for the development of new and improved methodologies to aid the analysis of environmental problems and to support more reliable estimations and forecasts. Moreover, the rapid development of specialized technologies in satellite instruments provides the opportunity to obtain a wide spectrum of various measurements. The purpose of this research is to use publicly available remote sensing product data computed from geostationary, polar and near-polar satellites and radar to improve space–time modeling and prediction of precipitation on Crete island in Greece. The proposed space–time kriging method carries out the fusion of remote sensing data with data from ground stations that monitor precipitation during the hydrological period 2009/10–2017/18. Precipitation observations are useful for water resources, flood and drought management studies. However, monitoring stations are usually sparse in regions with complex terrain, are clustered in valleys, and often have missing data. Satellite precipitation data are an attractive alternative to observations. The fusion of the datasets in terms of the space–time residual kriging method exploits the auxiliary satellite information and aids in the accurate and reliable estimation of precipitation rates at ungauged locations. In addition, it represents an alternative option for the improved modeling of precipitation variations in space and time. The obtained results were compared with the outcomes of similar works in the study area.
Handling Data Heterogeneity in Electricity Load Disaggregation via Optimized Complete Ensemble Empirical Mode Decomposition and Wavelet Packet Transform
Authors: Chui Kwok Tai , Gupta Brij B. , Liu Ryan Wen , Vasant Pandian
Published: April 2021

Global warming is a leading world issue driving the common social objective of reducing carbon emissions. People have witnessed the melting of ice and abrupt changes in climate. Reducing electricity usage is one possible method of slowing these changes. In recent decades, there have been massive worldwide rollouts of smart meters that automatically capture the total electricity usage of houses and buildings. Electricity load disaggregation (ELD) helps to break down total electricity usage into that of individual appliances. Studies have implemented ELD models based on various artificial intelligence techniques using a single ELD dataset. In this paper, a powerline noise transformation approach based on optimized complete ensemble empirical model decomposition and wavelet packet transform (OCEEMD–WPT) is proposed to merge the ELD datasets. The practical implications are that the method increases the size of training datasets and provides mutual benefits when utilizing datasets collected from other sources (especially from different countries). To reveal the effectiveness of the proposed method, it was compared with CEEMD–WPT (fixed controlled coefficients), standalone CEEMD, standalone WPT, and other existing works. The results show that the proposed approach improves the signal-to-noise ratio (SNR) significantly.