bluuebunny/crossref_metadata_2025 huggingface dataset:
Interaction of Remdesivir with Clinically Relevant Hepatic Drug Uptake Transporters
Authors: Nies Anne T. , König Jörg , Hofmann Ute , Kölz Charlotte , Fromm Martin F. , Schwab Matthias
Published: March 2021

Remdesivir has been approved for treatment of COVID-19 and shortens the time to recovery in hospitalized patients. Drug transporters removing remdesivir from the circulation may reduce efficacy of treatment by lowering its plasma levels. Information on the interaction of remdesivir with drug transporters is limited. We therefore assessed remdesivir as substrate and inhibitor of the clinically relevant hepatic drug uptake transporters organic anion transporting poly-peptide (OATP)-1B1 (SLCO1B1), its common genetic variants OATP1B1*1b, OATP1B1*5, OATP1B1*15, as well as OATP1B3 (SLCO1B3), OATP2B1 (SLCO2B1) and organic cation transporter (OCT)-1 (SLC22A1). Previously established transporter-overexpressing cells were used to measure (i) cellular remdesivir uptake and (ii) cellular uptake of transporter probe substrates in the presence of remdesivir. There was a high remdesivir uptake into vector-transfected control cells. Moderate, but statistically significant higher uptake was detected only for OATP1B1-, OATP1B1*1b and OATP1B1*15-expressing cells when compared with control cells at 5 µM. Remdesivir inhibited all investigated transporters at 10 µM and above. In conclusion, the low uptake rates suggest that OATP1B1 and its genetic variants, OATP1B3, OATP2B1 and OCT1 are not relevant for hepatocellular uptake of remdesivir in humans. Due to the rapid clearance of remdesivir, no clinically relevant transporter-mediated drug-drug interactions are expected.
Taking Particle Tracking into Practice by Novel Software and Screening Approach: Case-Study of Oral Lipid Nanocarriers
Authors: Plaza-Oliver María , Cano Emilio L. , Arroyo-Jimenez María Mar , Gámez Matías , Lozano-López María Victoria , Santander-Ortega Manuel J.
Published: March 2021

The success on the design of new oral nanocarriers greatly depends on the identification of the best physicochemical properties that would allow their diffusion across the mucus layer that protects the intestinal epithelium. In this context, particle tracking (PT) has arisen in the pharmaceutical field as an excellent tool to evaluate the diffusion of individual particles across the intestinal mucus. In PT, the trajectories of individual particles are characterized by the mean square displacement (MSD), which is used to calculate the coefficient of diffusion (D) and the anomalous diffusion parameter (α) as MSD=4Dτα. Unfortunately, there is no stablished criteria to evaluate the goodness-of-fit of the experimental data to the mathematical model. This work shows that the commonly used R2 parameter may lead to an overestimation of the diffusion capacity of oral nanocarriers. We propose a screening approach based on a combination of R2 with further statistical parameters. We have analyzed the effect of this approach to study the intestinal mucodiffusion of lipid oral nanocarriers, compared to the conventional screening approach. Last, we have developed software able to perform the whole PT analysis in a time-saving, user-friendly, and rational fashion.
Inhibitory Effects of Schisandra Lignans on Cytochrome P450s and Uridine 5′-Diphospho-Glucuronosyl Transferases in Human Liver Microsomes
Authors: Seo Hyung-Ju , Ji Seung-Bae , Kim Sin-Eun , Lee Gyung-Min , Park So-Young , Wu Zhexue , Jang Dae Sik , Liu Kwang-Hyeon
Published: March 2021

Schisandra chinensis has been widely used as a traditional herbal medicine to treat chronic coughs, fatigue, night sweats, and insomnia. Numerous bioactive components including lignans have been identified in this plant. Lignans with a dibenzocyclooctadiene moiety have been known to possess anti-cancer, anti-inflammatory, and hepatoprotective activity. Fragmentary studies have reported the ability of some lignans to modulate some cytochrome P450 (P450) enzymes. Herein, we investigated the drug interaction potential of six dibenzocyclooctadiene lignans (schisandrin, gomisin A, B, C, and N, and wuweizisu C) on nine P450 enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A) and six uridine 5′-diphosphoglucuronosyl transferase (UGT) enzymes (UGT1A1, 1A3, 1A4, 1A6, 1A9, and 2B7) using human liver microsomes. We found that lignans with one or two methylenedioxyphenyl groups inhibited CYP2B6, CYP2C8, CYP2C9, CYP2C19, and CYP2E1 activities in a time- and concentration-dependent like their CYP3A inhibition. In comparison, these lignans do not induce time-dependent inhibition of CYP1A2, CYP2A6, and CYP2D6. The time-dependent inhibition of gomisin A against CYP2C8, CYP2C19, and CYP3A4 was also elucidated using glutathione as a trapping reagent of reactive carbene metabolites given that gomisin A strongly inhibits these P450 enzymes in a time-dependent manner. A glutathione conjugate of gomisin A was generated in reactions with human recombinant CYP2C8, CYP2C19, and CYP3A4. This suggests that the time-dependent inhibition of gomisin A against CYP2C8, CYP2C9, and CYP3A4 is due to the production of carbene reactive metabolite. Six of the lignans we tested inhibited the activities of six UGT to a limited extent (IC50 > 15 μM). This information may aid the prediction of possible drug interactions between Schisandra lignans and any co-administered drugs which are mainly metabolized by P450s.
Performance Evaluation of Underwater Wireless Optical Communication System by Varying the Environmental Parameters
Authors: Li Dong-Chang , Chen Chia-Chun , Liaw Shien-Kuei , Afifah Shofuro , Sung Jiun-Yu , Yeh Chien-Hung
Published: March 2021

Underwater wireless optical communication (UWOC) has been considered a promising technology for high-speed underwater transmission. Some Gb/s level UWOC systems applying visible light have been demonstrated with a transmission distance of several meters or more. Many of the previous works focus on the advanced technologies to push the systems’ capacity–distance performance. However, practical environmental factors issue such as flow turbulence and temperature variation are seldom studied through specific statistical/theoretical models. In this paper, a UWOC system using a 450 nm blue light laser source was set up using a 1.5-m water tank with mirrors located on both sides for single or multiple reflections corresponding to different transmission distances. The blue laser was modulated by a 1.25 Gbps NRZ-OOK format with PRBS of 7, 24 or 31, respectively, for system performance comparison. The bit error rate (BER) values were measured in 1.5, 3.0 and 6 m, respectively, for system evaluation. At room temperature, the BER value was down to 10 × 10−8 for a 1.25 Gbps data rate in a 6 m transmission. Then, the UWOC transmission system experiment was carried out under several environmental parameters such as temperature, turbulence, artificial seawater by adding salt to simulate practical application in river or sea. When a submerged motor with an output of 1200 L/h was used as a water flow turbulence source, the impact to BER and transmission quality was negligible. For the temperature change issue, the experiment shows that around the original temperature of 25 °C had the best BER as compared to other temperature ranges from 10 to 50 °C. For artificial seawater issues by adding salt to simulate the real seawater environment. The transmission distance was only 3-m instead of 6 m, mainly due to particle scattering and water disturbance. With the motor pump on, the power penalty was 1 dB at 10 × 10−8 BER when compared to the motor pump off.
Response of Three Greek Populations of Aegilops triuncialis (Crop Wild Relative) to Serpentine Soil
Authors: Karatassiou Maria , Giannakoula Anastasia , Tsitos Dimitrios , Stefanou Stefanos
Published: March 2021

A common garden experiment was established to investigate the effects of serpentine soil on the photosynthetic and biochemical traits of plants from three Greek populations of Aegilops triuncialis. We measured photosynthetic and chlorophyll fluorescence parameters, proline content, and nutrient uptake of the above plants growing in serpentine and non-serpentine soil. The photochemical activity of PSII was inhibited in plants growing in the serpentine soil regardless of the population; however, this inhibition was lower in the Aetolia-Acarnania population. The uptake and the allocation of Ni, as well as that of some other essential nutrient elements (Ca, Mg, Fe, Mn), to upper parts were decreased with the lower decrease recorded in the Aetolia-Acarnania population. Our results showed that excess Ni significantly increased the synthesis of proline, an antioxidant compound that plays an important role in the protection against oxidative stress. We conclude that the reduction in the photosynthetic performance is most probably due to reduced nutrient supply to the upper plant parts. Moreover, nickel accumulation in the roots recorded in plants from all three populations seems to be a mechanism to alleviate the detrimental effects of the serpentine soil stress. In addition, our data suggest that the population from Aetolia-Acarnania could be categorized among the nickel excluders.
Cell Suspension Culture and In Vitro Screening for Drought Tolerance in Soybean Using Poly-Ethylene Glycol
Authors: Mishra Nishi , Tripathi Manoj Kumar , Tiwari Sushma , Tripathi Niraj , Sapre Swapnil , Ahuja Ashok , Tiwari Sharad
Published: March 2021

Soybean (Glycine max (L) Merrill) is used in India mostly as a substantial fund of protein and oil, which makes the crop significantly important. Somaclonal variation has been researched as a base of additional variability for drought in soybean. In the present experiment calli/cell clumps/embryoids rose from immature and mature embryonic axis and cotyledons explants were exposed to different concentrations of polyethylene glycol (PEG6000). A discontinuous method proved to be superior as it permitted the calli/embryoids/cell clumps to regain their regeneration competence. A total of 64 (12.21%) plantlets of genotype JS335 and 78 (13.13%) of genotype JS93-05 were regenerated after four consequent subcultures on the selection medium with an effective lethal concentration of 20% PEG6000, and proliferated calli/embryoids/cell clumps were further subcultured on Murashige and Skoog regeneration medium supplemented with 0.5 mgL−1 each of α-napthalene acetic acid (NAA), 6-benzyladenine (BA) and Kinetin (Kn), 20.0 gL−1 sucrose and 7.5 gL−1 agar. Putative drought-tolerant plantlets were acquired from genotype JS93-05 (38) in more numbers compared to genotype JS335 (26). Random decamer primers confirmed the presence of variability between mother plants and regenerated plants from both the genotypes. Since these plantlets recovered from tolerant calli/embryoids/cell clumps selected from the medium supplemented with PEG6000, the possibility exists that these plants may prove to be tolerant against drought stress.
Identification of Bacterial Blight Resistance Loci in Rice (Oryza sativa L.) against Diverse Xoo Thai Strains by Genome-Wide Association Study
Authors: Korinsak Siriporn , Darwell Clive T. , Wanchana Samart , Praphaisal Lawan , Korinsak Siripar , Thunnom Burin , Patarapuwadol Sujin , Toojinda Theerayut
Published: March 2021

Bacterial leaf blight (BLB) is a serious disease affecting global rice agriculture caused by Xanthomonas oryzae pv. oryzae (Xoo). Most resistant rice lines are dependent on single genes that are vulnerable to resistance breakdown caused by pathogen mutation. Here we describe a genome-wide association study of 222 predominantly Thai rice accessions assayed by phenotypic screening against 20 Xoo isolates. Loci corresponding to BLB resistance were detected using >142,000 SNPs. We identified 147 genes according to employed significance thresholds across chromosomes 1–6, 8, 9 and 11. Moreover, 127 of identified genes are located on chromosomal regions outside estimated Linkage Disequilibrium influences of known resistance genes, potentially indicating novel BLB resistance markers. However, significantly associated SNPs only occurred across a maximum of six Xoo isolates indicating that the development of broad-spectrum Xoo strain varieties may prove challenging. Analyses indicated a range of gene functions likely underpinning BLB resistance. In accordance with previous studies of accession panels focusing on indica varieties, our germplasm displays large numbers of SNPs associated with resistance. Despite encouraging data suggesting that many loci contribute to resistance, our findings corroborate previous inferences that multi-strain resistant varieties may not be easily realised in breeding programs without resorting to multi-locus strategies.
Short Rotation Intensive Culture of Willow, Spent Mushroom Substrate and Ramial Chipped Wood for Bioremediation of a Contaminated Site Used for Land Farming Activities of a Former Petrochemical Plant
Authors: Fortin Faubert Maxime , Hijri Mohamed , Labrecque Michel
Published: March 2021

The aim of this study was to investigate the bioremediation impacts of willows grown in short rotation intensive culture (SRIC) and supplemented or not with spent mushroom substrate (SMS) and ramial chipped wood (RCW). Results did not show that SMS significantly improved either biomass production or phytoremediation efficiency. After the three growing seasons, RCW-amended S. miyabeana accumulated significantly more Zn in the shoots, and greater increases of some PAHs were found in the soil of RCW-amended plots than in the soil of the two other ground cover treatments’ plots. Significantly higher Cd concentrations were found in the shoots of cultivar ‘SX61’. The results suggest that ‘SX61’ have reduced the natural attenuation of C10-C50 that occurred in the unvegetated control plots. The presence of willows also tended to increase the total soil concentrations of PCBs. Furthermore, we found that many contaminant concentrations were subject to seasonal oscillations, showing average increases throughout the whole experimental site after a growing period, while showing significantly different variations, such as lesser increases or even decreases, after a dormant period. These observations suggest that contaminants may have leached or degraded faster in untreated conditions, and conversely to have mobilized towards trees through water flow driven by plant transpiration during growing seasons.
Phenolic Compounds from Leaves and Flowers of Hibiscus roseus: Potential Skin Cosmetic Applications of an Under-Investigated Species
Authors: dos Santos Nascimento Luana Beatriz , Gori Antonella , Raffaelli Andrea , Ferrini Francesco , Brunetti Cecilia
Published: March 2021

The use of plant extracts in skin-care cosmetics is a modern trend due to their richness in polyphenols that act as anti-aging molecules. Hibiscus roseus is a perennial species naturalized in Italy, with beautiful soft pink flowers; its phenolic composition and biological activities have not been studied yet. The aim of this study was to characterize and quantify the phenolics and to evaluate the antioxidant, sun protection factor (SPF), and anti-collagenase activities of the ethanolic extracts of H. roseus leaves (HL) and flowers (HF). p-Coumaric, chlorogenic, and trans-ferulic acids derivatives as well as quercetin and kaempferol flavonoids were the main phenolic compounds detected. Catechin, epicatechin, kaempferol-3-O-rutinoside, kaempferol-3-O-glucoside, kaempferol-7-O-glucoside, tiliroside, oenin, and peonidin-3-O-glucoside were detected only in HF, while phloridzin was exclusive from HL, which also showed greater amounts of hydroxycinnamic acid derivatives. HF was richer in flavonoids and total phenolics, also exhibiting greater antioxidant capacity. The SPF and anti-collagenase activity of both extracts were similar and comparable to those of synthetic standards. The overall results demonstrate that H. roseus extracts are promising sources of bioactive phenolic compounds that could be potentially applied as anti-aging agents in skin-care cosmetics.
Marine Algae Incorporated Polylactide Acid Patch: Novel Candidate for Targeting Osteosarcoma Cells without Impairing the Osteoblastic Proliferation
Authors: Veziroglu Salih , Ayna Mustafa , Kohlhaas Theresa , Sayin Selin , Fiutowski Jacek , Mishra Yogendra Kumar , Karayürek Fatih , Naujokat Hendrik , Saygili Eyüp Ilker , Açil Yahya , Wiltfang Jörg , Faupel Franz , Aktas Oral Cenk , Gülses Aydin
Published: March 2021

Biodegradable collagen-based materials have been preferred as scaffolds and grafts for diverse clinical applications in density and orthopedy. Besides the advantages of using such bio-originated materials, the use of collagen matrices increases the risk of infection transmission through the cells or the tissues of the graft/scaffold. In addition, such collagen-based solutions are not counted as economically feasible approaches due to their high production cost. In recent years, incorporation of marine algae in synthetic polymers has been considered as an alternative method for preparation grafts/scaffolds since they represent abundant and cheap source of potential biopolymers. Current work aims to propose a novel composite patch prepared by blending Sargassum vulgare powders (SVP) to polylactide (PLA) as an alternative to the porcine-derived membranes. SVP-PLA composite patches were produced by using a modified solvent casting method. Following detailed material characterization to assess the cytocompatibility, human osteoblasts (HOBs) and osteosarcoma cells (SaOS-2) were seeded on neat PLA and SVP-PLA patches. MTT and BrdU assays indicated a greater cytocompatibility and higher proliferation for HOBs cultured on SVP-PLA composite than for those cultured on neat PLA. SaOS-2 cells cultured on SVP-PLA exhibited a significant decrease in cell proliferation. The composite patch described herein exhibits an antiproliferative effect against SaOS-2 cells without impairing HOBs’ adhesion and proliferation.
Synthesis and Characterization of Exopolysaccharide Encapsulated PCL/Gelatin Skin Substitute for Full-Thickness Wound Regeneration
Authors: Hivechi Ahmad , Milan Peiman Brouki , Modabberi Khashayar , Amoupour Moein , Ebrahimzadeh Kaveh , Gholipour Amir Reza , Sedighi Faezeh , Amini Naser , Bahrami S. Hajir , Rezapour Alireza , Hamidi Masoud , Delattre Cédric
Published: March 2021

Loss of skin integrity can lead to serious problems and even death. In this study, for the first time, the effect of exopolysaccharide (EPS) produced by cold-adapted yeast R. mucilaginosa sp. GUMS16 on a full-thickness wound in rats was evaluated. The GUMS16 strain’s EPS was precipitated by adding cold ethanol and then lyophilized. Afterward, the EPS with polycaprolactone (PCL) and gelatin was fabricated into nanofibers with two single-needle and double-needle procedures. The rats’ full-thickness wounds were treated with nanofibers and Hematoxylin and eosin (H&E) and Masson’s Trichrome staining was done for studying the wound healing in rats. Obtained results from SEM, DLS, FTIR, and TGA showed that EPS has a carbohydrate chemical structure with an average diameter of 40 nm. Cell viability assessments showed that the 2% EPS loaded sample exhibits the highest cell activity. Moreover, in vivo implantation of nanofiber webs on the full-thickness wound on rat models displayed a faster healing rate when EPS was loaded into a nanofiber. These results suggest that the produced EPS can be used for skin tissue engineering applications.
Proton Exchange Membrane Electrolyzer Emulator for Power Electronics Testing Applications
Authors: Yodwong Burin , Guilbert Damien , Hinaje Melika , Phattanasak Matheepot , Kaewmanee Wattana , Vitale Gianpaolo
Published: March 2021

This article aims to develop a proton exchange membrane (PEM) electrolyzer emulator. This emulator is realized through an equivalent electrical scheme. It allows taking into consideration the dynamic operation of PEM electrolyzers, which is generally neglected in the literature. PEM electrolyzer dynamics are reproduced by the use of supercapacitors, due to the high value of the equivalent double-layer capacitance value. Steady-state and dynamics operations are investigated in this work. The design criteria are addressed. The PEM electrolyzer emulator is validated by using a 400-W commercial PEM electrolyzer. This emulator is conceived to test new DC-DC converters to supply the PEM ELs and their control as well, avoiding the risk to damage a real electrolyzer for experiment purposes. The proposed approach is valid both for a single cell and for the whole stack emulation.
Investigation on Dynamic Stresses of Pump-Turbine Runner during Start Up in Turbine Mode
Authors: Chen Funan , Bi Huili , Ahn Soo-Hwang , Mao Zhongyu , Luo Yongyao , Wang Zhengwei
Published: March 2021

The startup process occurs frequently for pumped storage units. During this process, the rotating rate that changes rapidly and unsteady flow in runner cause the complex dynamic response of runner, sometimes even resonance. The sharp rise of stress and the large-amplitude dynamic stresses of runner will greatly shorten the fatigue life. Thus, the study of start-up process in turbine mode is critical to the safety operation. This paper introduced a method of coupling one dimensional (1D) pipeline calculation and three-dimensional computational dynamics (3D CFD) simulation to analyze transient unsteady flow in units and to obtain more accurate and reliable dynamic stresses results during start up process. According to the results, stress of the ring near fixed support increased quickly as rotating rate rose and became larger than at fillets of leading edge and band in the later stages of start-up. In addition, it was found that dynamic response can be caused by rotor stator interaction (RSI), but also could even be generated by the severe pressure fluctuation in clearance, which can also be a leading factor of dynamic stresses. This study will facilitate further estimation of dynamic stresses in complex flow and changing rotating rate cases, as well as fatigue analysis of runner during transient operation.
Analysis of Global Warming’s Influence on the Dimensioning of Borehole Heat Exchangers at a Climate-Exposed Site
Authors: Kunz Antonín , Klempa Martin , Bujok Petr , Piotrowski Dawid
Published: March 2021

A borehole heat exchanger (BHE) presents the most reliable source of geothermal energy for any object where the heat pump system is to be installed. The main objective of BHE optimization in a specific rock massive and for calculated heat consumption is to design a BHE with proper capacity and sustainable performance. One of the most important inputs for the preparation of such a model is the average outer air temperature on the site during the year. While the properties of the local rock massive are from the heat project lifetime view (tens of years) stable, the local average outer temperature fluctuates according to global climate changes. This article presents a study of the impact of climate changes on the dimensioning process of a BHE and consequently on its performance using data from a real installation at a highly climate-exposed site in the Czech Republic. During the dimensioning of a BHE, this study could help to better quantify the objective risks that result from climate changes. However, the results of this study show that the currently calculated impact of an increase in outer temperature is not crucial, but it is advisable to take this new fact into account during the design and dimensioning process, especially for large installations. To study the ground in terms of usable energy potential at climate-exposed locations properly, the available data were critically analyzed and the results were then synthesized in an appropriate way for the needs of the data simulations.
An Overview of the Factors Influencing Apple Cider Sensory and Microbial Quality from Raw Materials to Emerging Processing Technologies
Authors: Calugar Paul Cristian , Coldea Teodora Emilia , Salanță Liana Claudia , Pop Carmen Rodica , Pasqualone Antonella , Burja-Udrea Cristina , Zhao Haifeng , Mudura Elena
Published: March 2021

Given apple, an easily adapted culture, and a large number of apple varieties, the production of apple cider is widespread globally. Through the fermentation process, a series of chemical changes take place depending on the apple juice composition, type of microorganism involved and technology applied. Following both fermentations, alcoholic and malo-lactic, and during maturation, the sensory profile of cider changes. This review summarises the current knowledge about the influence of apple variety and microorganisms involved in cider fermentation on the sensory and volatile profiles of cider. Implications of both Saccharomyces, non-Saccharomyces yeast and lactic acid bacteria, respectively, are discussed. Also are presented the emerging technologies applied to cider processing (pulsed electric field, microwave extraction, enzymatic, ultraviolet and ultrasound treatments, high-pressure and pulsed light processing) and the latest trends for a balanced production in terms of sustainability, authenticity and consumer preferences.
Proteomics Landscape of Alzheimer’s Disease
Authors: Jain Ankit P. , Sathe Gajanan
Published: March 2021

Alzheimer’s disease (AD) is the most prevalent form of dementia, and the numbers of AD patients are expected to increase as human life expectancy improves. Deposition of β-amyloid protein (Aβ) in the extracellular matrix and intracellular neurofibrillary tangles are molecular hallmarks of the disease. Since the precise pathophysiology of AD has not been elucidated yet, effective treatment is not available. Thus, understanding the disease pathology, as well as identification and development of valid biomarkers, is imperative for early diagnosis as well as for monitoring disease progression and therapeutic responses. Keeping this goal in mind several studies using quantitative proteomics platform have been carried out on both clinical specimens including the brain, cerebrospinal fluid (CSF), plasma and on animal models of AD. In this review, we summarize the mass spectrometry (MS)-based proteomics studies on AD and discuss the discovery as well as validation stages in brief to identify candidate biomarkers.
Dalit Theology and Indian Christian History in Dialogue: Constructive and Practical Possibilities
Authors: Ronnevik Andrew
Published: March 2021

In this article, I consider how an integration of Dalit theology and Indian Christian history could help Dalit theologians in their efforts to connect more deeply with the lived realities of today’s Dalit Christians. Drawing from the foundational work of such scholars as James Massey and John C. B. Webster, I argue for and begin a deeper and more comprehensive Dalit reading and theological analysis of the history of Christianity and mission in India. My explorations—touching on India’s Thomas/Syrian, Catholic, Protestant, and Pentecostal traditions—reveal the persistence and complexity of caste oppression throughout Christian history in India, and they simultaneously draw attention to over-looked, empowering, and liberative resources that are bound to Dalit Christians lives, both past and present. More broadly, I suggest that historians and theologians in a variety of contexts—not just in India—can benefit from blurring the lines between their disciplines.
Personal Resources and Spiritual Change among Participants’ Hostilities in Ukraine: The Mediating Role of Posttraumatic Stress Disorder and Turn to Religion
Authors: Niewiadomska Iwona , Jurek Krzysztof , Chwaszcz Joanna , Wośko Patrycja , Korżyńska-Piętas Magdalena
Published: March 2021

The theory of conservation of resources (COR) can be used for searching mechanisms which explain spiritual changes caused by trauma. The aim of this paper was to analyze the relationship between distribution of personal resources and spiritual change, as well as the mediating role of posttraumatic stress disorder (PTSD) and turn to religion (stress coping strategy) in this relationship among participants’ hostilities in Ukraine. A total of 314 adults—74 women and 235 men—participated in the study. The mean age was 72.59. Polish adaptation of Hobfoll’s Conservation of Resources-Evaluation (COR-E), the Posttraumatic Stress Disorder (PTSD) Checklist—Civilian Version (PCL-C), the Inventory for Measuring Coping with Stress (MINI-COPE), and The Posttraumatic Growth Inventory (PTGI) were employed in the research. The mediating role of posttraumatic stress disorder and turn to religion in relationship between personal resources loss and spiritual change was confirmed. The turn to religion plays the role of mediator in relationship between personal resources gain/assigning value to personal resources and spiritual change. The results justify the postulate of conducting further research in the field of testing models which take into account the relationship between posttraumatic stress disorder, religious coping stress, and posttraumatic spiritual change. The conducted analyses should include the assumptions of the COR theory as well as psychological, social, and situational factors that could generate spiritual change.
Correction: Hui, Y., et al. Spatio-Temporal Validation of AIRS CO2 Observations Using GAW, HIPPO and TCCON. Remote Sens. 2020, 12, 3583
Authors: Yang Hui , Feng Gefei , Xiang Ru , Xu Yunjing , Qin Yong , Li Songnian
Published: March 2021

The authors would like to make the following correction of [...]
Assimilation of Multi-Source Precipitation Data over Southeast China Using a Nonparametric Framework
Authors: Zhou Yuanyuan , Qin Nianxiu , Tang Qiuhong , Shi Huabin , Gao Liang
Published: March 2021

The accuracy of the rain distribution could be enhanced by assimilating the remotely sensed and gauge-based precipitation data. In this study, a new nonparametric general regression (NGR) framework was proposed to assimilate satellite- and gauge-based rainfall data over southeast China (SEC). The assimilated rainfall data in Meiyu and Typhoon seasons, in different months, as well as during rainfall events with various rainfall intensities were evaluated to assess the performance of this proposed framework. In rainy season (Meiyu and Typhoon seasons), the proposed method obtained the estimates with smaller total absolute deviations than those of the other satellite products (i.e., 3B42RT and 3B42V7). In general, the NGR framework outperformed the original satellites generally on root-mean-square error (RMSE) and mean absolute error (MAE), especially on Nash-Sutcliffe coefficient of efficiency (NSE). At monthly scale, the performance of assimilated data by NGR was better than those of satellite-based products in most months, by exhibiting larger correlation coefficients (CC) in 6 months, smaller RMSE and MAE in at least 9 months and larger NSE in 9 months, respectively. Moreover, the estimates from NGR have been proven to perform better than the two satellite-based products with respect to the simulation of the gauge observations under different rainfall scenarios (i.e., light rain, moderate rain and heavy rain).
Deep Neural Regression Prediction of Motor Imagery Skills Using EEG Functional Connectivity Indicators
Authors: Caicedo-Acosta Julian , Castaño German A. , Acosta-Medina Carlos , Alvarez-Meza Andres , Castellanos-Dominguez German
Published: March 2021

Motor imaging (MI) induces recovery and neuroplasticity in neurophysical regulation. However, a non-negligible portion of users presents insufficient coordination skills of sensorimotor cortex control. Assessments of the relationship between wakefulness and tasks states are conducted to foster neurophysiological and mechanistic interpretation in MI-related applications. Thus, to understand the organization of information processing, measures of functional connectivity are used. Also, models of neural network regression prediction are becoming popular, These intend to reduce the need for extracting features manually. However, predicting MI practicing’s neurophysiological inefficiency raises several problems, like enhancing network regression performance because of the overfitting risk. Here, to increase the prediction performance, we develop a deep network regression model that includes three procedures: leave-one-out cross-validation combined with Monte Carlo dropout layers, subject clustering of MI inefficiency, and transfer learning between neighboring runs. Validation is performed using functional connectivity predictors extracted from two electroencephalographic databases acquired in conditions close to real MI applications (150 users), resulting in a high prediction of pretraining desynchronization and initial training synchronization with adequate physiological interpretability.
Estimation of the Path-Loss Exponent by Bayesian Filtering Method
Authors: Wojcicki Piotr , Zientarski Tomasz , Charytanowicz Malgorzata , Lukasik Edyta
Published: March 2021

Regarding wireless sensor network parameter estimation of the propagation model is a most important issue. Variations of the received signal strength indicator (RSSI) parameter are a fundamental problem of a system based on signal strength. In the present paper, we propose an algorithm based on Bayesian filtering techniques for estimating the path-loss exponent of the log-normal shadowing propagation model for outdoor RSSI measurements. Furthermore, in a series of experiments, we will demonstrate the usefulness of the particle filter for estimating the RSSI data. The stability of this algorithm and the differences in determined path-loss exponent for both method were also analysed. The proposed method of dynamic estimation results in significant improvements of the accuracy of RSSI values when compared with the experimental measurements. It should be emphasised that the path-loss exponent mainly depends on the RSSI data. Our results also indicate that increasing the number of inserted particles does not significantly raise the quality of the estimated parameters.
A High-Accuracy and Power-Efficient Self-Optimizing Wireless Water Level Monitoring IoT Device for Smart City
Authors: Chi Tsun-Kuang , Chen Hsiao-Chi , Chen Shih-Lun , Abu Patricia Angela R.
Published: March 2021

In this paper, a novel self-optimizing water level monitoring methodology is proposed for smart city applications. Considering system maintenance, the efficiency of power consumption and accuracy will be important for Internet of Things (IoT) devices and systems. A multi-step measurement mechanism and power self-charging process are proposed in this study for improving the efficiency of a device for water level monitoring applications. The proposed methodology improved accuracy by 0.16–0.39% by moving the sensor to estimate the distance relative to different locations. Additional power is generated by executing a multi-step measurement while the power self-optimizing process used dynamically adjusts the settings to balance the current of charging and discharging. The battery level can efficiently go over 50% in a stable charging simulation. These methodologies were successfully implemented using an embedded control device, an ultrasonic sensor module, a LORA transmission module, and a stepper motor. According to the experimental results, the proposed multi-step methodology has the benefits of high accuracy and efficient power consumption for water level monitoring applications.
Cascaded Complementary Filter Architecture for Sensor Fusion in Attitude Estimation
Authors: Narkhede Parag , Poddar Shashi , Walambe Rahee , Ghinea George , Kotecha Ketan
Published: March 2021

Attitude estimation is the process of computing the orientation angles of an object with respect to a fixed frame of reference. Gyroscope, accelerometer, and magnetometer are some of the fundamental sensors used in attitude estimation. The orientation angles computed from these sensors are combined using the sensor fusion methodologies to obtain accurate estimates. The complementary filter is one of the widely adopted techniques whose performance is highly dependent on the appropriate selection of its gain parameters. This paper presents a novel cascaded architecture of the complementary filter that employs a nonlinear and linear version of the complementary filter within one framework. The nonlinear version is used to correct the gyroscope bias, while the linear version estimates the attitude angle. The significant advantage of the proposed architecture is its independence of the filter parameters, thereby avoiding tuning the filter’s gain parameters. The proposed architecture does not require any mathematical modeling of the system and is computationally inexpensive. The proposed methodology is applied to the real-world datasets, and the estimation results were found to be promising compared to the other state-of-the-art algorithms.
Surface Potential-Controlled Oscillation in FET-Based Biosensors
Authors: Kim Ji Hyun , Park Seong Jun , Han Jin-Woo , Ahn Jae-Hyuk
Published: March 2021

Field-effect transistor (FET)-based biosensors have garnered significant attention for their label-free electrical detection of charged biomolecules. Whereas conventional output parameters such as threshold voltage and channel current have been widely used for the detection and quantitation of analytes of interest, they require bulky instruments and specialized readout circuits, which often limit point-of-care testing applications. In this study, we demonstrate a simple conversion method that transforms the surface potential into an oscillating signal as an output of the FET-based biosensor. The oscillation frequency is proposed as a parameter for FET-based biosensors owing to its intrinsic advantages of simple and compact implementation of readout circuits as well as high compatibility with neuromorphic applications. An extended-gate biosensor comprising an Al2O3-deposited sensing electrode and a readout transistor is connected to a ring oscillator that generates surface potential-controlled oscillation for pH sensing. Electrical measurement of the oscillation frequency as a function of pH reveals that the oscillation frequency can be used as a sensitive and reliable output parameter in FET-based biosensors for the detection of chemical and biological species. We confirmed that the oscillation frequency is directly correlated with the threshold voltage. For signal amplification, the effects of circuit parameters on pH sensitivity are investigated using different methods, including electrical measurements, analytical calculations, and circuit simulations. An Arduino board to measure the oscillation frequency is integrated with the proposed sensor to enable portable and real-time pH measurement for point-of-care testing applications.
Design and Experimentation of a Self-Sensing Actuator for Active Vibration Isolation System with Adjustable Anti-Resonance Frequency Controller
Authors: Fu Yuan , Li Shusen , Liu Jiuqing , Zhao Bo
Published: March 2021

The vibration isolation system is now indispensable to high-precision instruments and equipment, which can provide a low vibration environment to ensure performance. However, the disturbance with variable frequency poses a challenge to the vibration isolation system, resulting in precision reduction of dynamic modeling. This paper presents a velocity self-sensing method and experimental verification of a vibration isolation system. A self-sensing actuator is designed to isolate the vibration with varying frequencies according to the dynamic vibration absorber structure. The mechanical structure of the actuator is illustrated, and the dynamic model is derived. Then a self-sensing method is proposed to adjust the anti-resonance frequency of the system without velocity sensors, which can also reduce the complexity of the system and prevent the disturbance transmitting along the cables. The self-sensing controller is constructed to track the variable frequency of the disturbance. A prototype of the isolation system equipped with velocity sensors is developed for the experiment. The experiment results show that the closed-loop transmissibility is less than −5 dB in the whole frequency rand and is less than −40 dB around, adding anti-resonance frequency which can be adjusted from 0 Hz to initial anti-resonance frequency. The disturbance amplitude of the payload can be suppressed to 10%.
RF-Based UAV Detection and Identification Using Hierarchical Learning Approach
Authors: Nemer Ibrahim , Sheltami Tarek , Ahmad Irfan , Yasar Ansar Ul-Haque , Abdeen Mohammad A. R.
Published: March 2021

Unmanned Aerial Vehicles (UAVs) are widely available in the current market to be used either for recreation as a hobby or to serve specific industrial requirements, such as agriculture and construction. However, illegitimate and criminal usage of UAVs is also on the rise which introduces their effective identification and detection as a research challenge. This paper proposes a novel machine learning-based for efficient identification and detection of UAVs. Specifically, an improved UAV identification and detection approach is presented using an ensemble learning based on the hierarchical concept, along with pre-processing and feature extraction stages for the Radio Frequency (RF) data. Filtering is applied on the RF signals in the detection approach to improve the output. This approach consists of four classifiers and they are working in a hierarchical way. The sample will pass the first classifier to check the availability of the UAV, and then it will specify the type of the detected UAV using the second classifier. The last two classifiers will handle the sample that is related to Bebop and AR to specify their mode. Evaluation of the proposed approach with publicly available dataset demonstrates better efficiency compared to existing detection systems in the literature. It has the ability to investigate whether a UAV is flying within the area or not, and it can directly identify the type of UAV and then the flight mode of the detected UAV with accuracy around 99%.
LOCATE-US: Indoor Positioning for Mobile Devices Using Encoded Ultrasonic Signals, Inertial Sensors and Graph-Matching
Authors: Gualda David , Pérez-Rubio María Carmen , Ureña Jesús , Pérez-Bachiller Sergio , Villadangos José Manuel , Hernández Álvaro , García Juan Jesús , Jiménez Ana
Published: March 2021

Indoor positioning remains a challenge and, despite much research and development carried out in the last decade, there is still no standard as with the Global Navigation Satellite Systems (GNSS) outdoors. This paper presents an indoor positioning system called LOCATE-US with adjustable granularity for use with commercial mobile devices, such as smartphones or tablets. LOCATE-US is privacy-oriented and allows every device to compute its own position by fusing ultrasonic, inertial sensor measurements and map information. Ultrasonic Local Positioning Systems (U-LPS) based on encoded signals are placed in critical zones that require an accuracy below a few decimeters to correct the accumulated drift errors of the inertial measurements. These systems are well suited to work at room level as walls confine acoustic waves inside. To avoid audible artifacts, the U-LPS emission is set at 41.67 kHz, and an ultrasonic acquisition module with reduced dimensions is attached to the mobile device through the USB port to capture signals. Processing in the mobile device involves an improved Time Differences of Arrival (TDOA) estimation that is fused with the measurements from an external inertial sensor to obtain real-time location and trajectory display at a 10 Hz rate. Graph-matching has also been included, considering available prior knowledge about the navigation scenario. This kind of device is an adequate platform for Location-Based Services (LBS), enabling applications such as augmented reality, guiding applications, or people monitoring and assistance. The system architecture can easily incorporate new sensors in the future, such as UWB, RFiD or others.
Application of Deep Learning on Millimeter-Wave Radar Signals: A Review
Authors: Abdu Fahad Jibrin , Zhang Yixiong , Fu Maozhong , Li Yuhan , Deng Zhenmiao
Published: March 2021

The progress brought by the deep learning technology over the last decade has inspired many research domains, such as radar signal processing, speech and audio recognition, etc., to apply it to their respective problems. Most of the prominent deep learning models exploit data representations acquired with either Lidar or camera sensors, leaving automotive radars rarely used. This is despite the vital potential of radars in adverse weather conditions, as well as their ability to simultaneously measure an object’s range and radial velocity seamlessly. As radar signals have not been exploited very much so far, there is a lack of available benchmark data. However, recently, there has been a lot of interest in applying radar data as input to various deep learning algorithms, as more datasets are being provided. To this end, this paper presents a survey of various deep learning approaches processing radar signals to accomplish some significant tasks in an autonomous driving application, such as detection and classification. We have itemized the review based on different radar signal representations, as it is one of the critical aspects while using radar data with deep learning models. Furthermore, we give an extensive review of the recent deep learning-based multi-sensor fusion models exploiting radar signals and camera images for object detection tasks. We then provide a summary of the available datasets containing radar data. Finally, we discuss the gaps and important innovations in the reviewed papers and highlight some possible future research prospects.
Multi-Time Resolution Ensemble LSTMs for Enhanced Feature Extraction in High-Rate Time Series
Authors: Barzegar Vahid , Laflamme Simon , Hu Chao , Dodson Jacob
Published: March 2021

Systems experiencing high-rate dynamic events, termed high-rate systems, typically undergo accelerations of amplitudes higher than 100 g-force in less than 10 ms. Examples include adaptive airbag deployment systems, hypersonic vehicles, and active blast mitigation systems. Given their critical functions, accurate and fast modeling tools are necessary for ensuring the target performance. However, the unique characteristics of these systems, which consist of (1) large uncertainties in the external loads, (2) high levels of non-stationarities and heavy disturbances, and (3) unmodeled dynamics generated from changes in system configurations, in combination with the fast-changing environments, limit the applicability of physical modeling tools. In this paper, a deep learning algorithm is used to model high-rate systems and predict their response measurements. It consists of an ensemble of short-sequence long short-term memory (LSTM) cells which are concurrently trained. To empower multi-step ahead predictions, a multi-rate sampler is designed to individually select the input space of each LSTM cell based on local dynamics extracted using the embedding theorem. The proposed algorithm is validated on experimental data obtained from a high-rate system. Results showed that the use of the multi-rate sampler yields better feature extraction from non-stationary time series compared with a more heuristic method, resulting in significant improvement in step ahead prediction accuracy and horizon. The lean and efficient architecture of the algorithm results in an average computing time of 25 μμs, which is below the maximum prediction horizon, therefore demonstrating the algorithm’s promise in real-time high-rate applications.