bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation and Sustained-Release Performance of PLGA Microcapsule Carrier System
Authors: Ren Shuaikai , Wang Chunxin , Guo Liang , Xu Congcong , Wang Yan , Sun Changjiao , Cui Haixin , Zhao Xiang
Published: July 2021

Microcapsules have been widely studied owing to their biocompatibility and potential for application in various areas, particularly drug delivery. However, the size of microcapsules is difficult to control, and the size distribution is very broad via various encapsulation techniques. Therefore, it is necessary to obtain microcapsules with uniform and tailored size for the construction of controlled-release drug carriers. In this study, emulsification and solvent evaporation methods were used to prepare a variety of ovalbumin-loaded poly (lactic-co-glycolic acid) (PLGA) microcapsules to determine the optimal preparation conditions. The particle size of the PLGA microcapsules prepared using the optimum conditions was approximately 200 nm, which showed good dispersibility with an ovalbumin encapsulation rate of more than 60%. In addition, porous microcapsules with different pore sizes were prepared by adding a varying amount of porogen bovine serum albumin (BSA) to the internal water phase. The release curve showed that the rate of protein release from the microcapsules could be controlled by adjusting the pore size. These findings demonstrated that we could tailor the morphology and structure of microcapsules by regulating the preparation conditions, thus controlling the encapsulation efficiency and the release performance of the microcapsule carrier system. We envision that this controlled-release novel microcapsule carrier system shows great potential for biomedical applications.
Temperature-Dependent Excitonic Photoluminescence and Nonlinear Absorption of CdTe Nanocrystal/Polyvinyl Alcohol Films
Authors: Chang Qing , Sui Jingrong , Chai Zhijun , Wu Wenzhi
Published: July 2021

The temperature dependence of the excitonic photoluminescence (PL) and nonlinear absorption characteristics of CdTe nanocrystals (NCs)/polyvinyl alcohol (PVA) film are investigated using steady-state/time-resolved PL spectroscopy and Z-scan methods. The excitonic PL peaks of CdTe NCs can be observed at the wavelengths from 560 to 670 nm, with size changes from 2.1 to 3.9 nm. From the temperature-dependent PL spectra, the smaller photon energy of the PL emission peak, the rapidly decreasing PL intensity, and the wider linewidth are observed with increasing temperature from 80 to 300 K. It is revealed that the excitonic PL is composed of both trapped state and band-edge excitonic state, which presents biexponential fitting dynamics. The short-lived species is due to the surface-trapped state recombination in NCs, which has a photogenerated trapped channel and a time-resolved peak shift. The species with a long-lived lifetime is ascribed to the intrinsic excitonic recombination. Through the femtosecond Z-scan method, the nonlinear absorption coefficient becomes smaller with the increase in the size of the NCs. The optical properties of the CdTe NC/PVA film show the potential of II-VI traditional NCs as display and luminescent materials that can utilize the combination of excitonic PL and nonlinear absorption for expanded functionality.
Solvent-Mediated Structural Evolution Mechanism from Cs4PbBr6 to CsPbBr3 Crystals
Authors: La Porta Felipe A. , Masi Sofia
Published: July 2021

The study of the solvent-mediated structural evolution mechanism of the Cs4PbBr6 powders prepared using the solvothermal method is presented. The Cs4PbBr6 powders with a rhombohedral structure and an intense green emission (i.e., mainly due to the presence of complex defect states in the forbidden gap), which is stable in its solid-state form, but a distinct behavior is observed in different dispersions, easily detectable when irradiated with ultraviolet (UV) light. Depending on the polarity of the solvent, a change in the emission color from green to red is observed, easily detectable when irradiated with ultraviolet (UV) light. Our findings suggest that the solvent polarity affects the surface decomposition process, leading to a different change in composition, structure and crystal shape. This peculiar behavior plays a pivotal role in the control of the properties of Cs4PbBr6, and this study, therefore, offers a fundamental understanding needed for Cs4PbBr6 potential future applications.
The Impact of a Culinary Coaching Telemedicine Program on Home Cooking and Emotional Well-Being during the COVID-19 Pandemic
Authors: Silver Julie K. , Finkelstein Adi , Minezaki Kaya , Parks Kimberly , Budd Maggi A. , Tello Monique , Paganoni Sabrina , Tirosh Amir , Polak Rani
Published: July 2021

The coronavirus pandemic enforced social restrictions with abrupt impacts on mental health and changes to health behaviors. From a randomized clinical trial, we assessed the impact of culinary education on home cooking practices, coping strategies and resiliency during the first wave of the COVID-19 pandemic (March/April 2020). Participants (n = 28) were aged 25–70 years with a BMI of 27.5–35 kg/m2. The intervention consisted of 12 weekly 30-min one-on-one telemedicine culinary coaching sessions. Coping strategies were assessed through the Brief Coping with Problems Experienced Inventory, and resiliency using the Brief Resilient Coping Scale. Home cooking practices were assessed through qualitative analysis. The average use of self-care as a coping strategy by the intervention group was 6.14 (1.66), compared to the control with 4.64 (1.69); p = 0.03. While more intervention participants had high (n = 5) and medium (n = 8) resiliency compared to controls (n = 4, n = 6, respectively), this difference was not significant (p = 0.33). Intervention participants reported using home cooking skills such as meal planning and time saving techniques during the pandemic. The key findings were that culinary coaching via telemedicine may be an effective intervention for teaching home cooking skills and promoting the use of self-care as a coping strategy during times of stress, including the COVID-19 pandemic.
The Effects of Crocodile Blood Supplementation on Delayed-Onset Muscle Soreness
Authors: Paratthakonkun Chirawat , Vimuttipong Vipu , Nana Alisa , Chaijenkij Kornkit , Soonthornworasiri Ngamphol , Arthan Dumrongkiet
Published: July 2021

Delayed-onset muscle soreness (DOMS) is associated with increases in acute inflammatory and biochemical markers, muscle swelling, pain, and reduced functional performance. This study aimed to investigate the preventative effects of crocodile blood supplementation on DOMS induced by eccentric exercise. Sixteen healthy males were randomly allocated to either a crocodile blood (CB, n = 8) or a placebo (PL, n = 8) treatment. Participants receiving the CB treatment consumed four capsules of freeze–dried CB powder (1 g day−1) over 18 days. Participants receiving the other treatment were administered a placebo over the same period. An eccentric exercise protocol was performed, and functional performance, visual analogue scale (VAS)-measured pain, knee range of movement (ROM), thigh circumference (swelling), and cytokines, enzymes, and biochemical parameters were assessed immediately after exercise as well as after 24 h, 48 h, and 72 h. CB supplementation could significantly maintain maximum voluntary isometric contraction (MVIC) at 24 h (p = 0.001) and 48 h after exercise (p = 0.001) when comparing values at different times for the CB group. In the CB group, thigh circumference decreased only immediately after eccentric exercise (p = 0.031) in comparison with pre-eccentric exercise values. An 18-day supplementation (1 g day−1) of crocodile blood does aid in the maintenance of functional performance and muscle swelling after eccentric exercise. Our data indicate that 1 g day−1 of crocodile blood supplementation should be safe for human consumption.
Docosahexaenoic Acid Suppresses Expression of Adipogenic Tetranectin through Sterol Regulatory Element-Binding Protein and Forkhead Box O Protein in Pigs
Authors: Yang Jui-Ting , Chen Yu-Jen , Huang Chao-Wei , Wang Ya-Chin , Mersmann Harry J. , Wang Pei-Hwa , Ding Shih-Torng
Published: July 2021

Tetranectin (TN), a plasminogen-binding protein originally involved in fibrinolysis and bone formation, was later identified as a secreted adipokine from human and rat adipocytes and positively correlated with adipogenesis and lipid metabolism in adipocytes. To elucidate the nutritional regulation of adipogenic TN from diets containing different sources of fatty acids (saturated, n-6, n-3) in adipocytes, we cloned the coding region of porcine TN from a cDNA library and analyzed tissue expressions in weaned piglets fed with 2% soybean oil (SB, enriched in n-6 fatty acids), docosahexaenoic acid oil (DHA, an n-3 fatty acid) or beef tallow (BT, enriched in saturated and n-9 fatty acids) for 30 d. Compared with tissues in the BT- or SB-fed group, expression of TN was reduced in the adipose, liver and lung tissues from the DHA-fed group, accompanied with lowered plasma levels of triglycerides and cholesterols. This in vivo reduction was also confirmed in porcine primary differentiated adipocytes supplemented with DHA in vitro. Then, promoter analysis was performed. A 1956-bp putative porcine TN promoter was cloned and transcription binding sites for sterol regulatory-element binding protein (SREBP)-1c or forkhead box O proteins (FoxO) were predicted on the TN promoter. Mutating binding sites on porcine TN promoters showed that transcriptional suppression of TN by DHA on promoter activity was dependent on specific response elements for SREBP-1c or FoxO. The inhibited luciferase promoter activity by DHA on the TN promoter coincides with reduced gene expression of TN, SREBP-1c, and FoxO1 in human embryonic kidney HEK293T cells supplemented with DHA. To conclude, our current study demonstrated that the adipogenic TN was negatively regulated by nutritional modulation of DHA both in pigs in vivo and in humans/pigs in vitro. The transcriptional suppression by DHA on TN expression was partly through SREBP-1c or FoxO. Therefore, down-regulation of adipogenic tetranectin associated with fibrinolysis and adipogenesis may contribute to the beneficial effects of DHA on ameliorating obesity-induced metabolic syndromes such as atherosclerosis and adipose dysfunctions.
Evaluating Anticancer and Immunomodulatory Effects of Spirulina (Arthrospira) platensis and Gamma-Tocotrienol Supplementation in a Syngeneic Mouse Model of Breast Cancer
Authors: Subramaiam Hemavathy , Chu Wan-Loy , Radhakrishnan Ammu Kutty , Chakravarthi Srikumar , Selvaduray Kanga Rani , Kok Yih-Yih
Published: July 2021

Nutrition can modulate host immune responses as well as promote anticancer effects. In this study, two nutritional supplements, namely gamma-tocotrienol (γT3) and Spirulina, were evaluated for their immune-enhancing and anticancer effects in a syngeneic mouse model of breast cancer (BC). Five-week-old female BALB/c mice were fed Spirulina, γT3, or a combination of Spirulina and γT3 (Spirulina + γT3) for 56 days. The mice were inoculated with 4T1 cells into their mammary fat pad on day 28 to induce BC. The animals were culled on day 56 for various analyses. A significant reduction (p < 0.05) in tumor volume was only observed on day 37 and 49 in animals fed with the combination of γT3 + Spirulina. There was a marked increase (p < 0.05) of CD4/CD127+ T-cells and decrease (p < 0.05) of T-regulatory cells in peripheral blood from mice fed with either γT3 or Spirulina. The breast tissue of the combined group showed abundant areas of necrosis, but did not prevent metastasis to the liver. Although there was a significant increase (p < 0.05) of MIG-6 and Cadherin 13 expression in tumors from γT3-fed animals, there were no significant (p > 0.05) differences in the expression of MIG-6, Cadherin 13, BIRC5, and Serpine1 upon combined feeding. This showed that combined γT3 + Spirulina treatment did not show any synergistic anticancer effects in this study model.
Recruitment, Retention and Compliance of Overweight Inactive Adults with Intermediate Hyperglycaemia to a Novel Walking Intervention
Authors: Faulkner Maria , McNeilly Andrea , Davison Gareth , Rowe David , Hewitt Allan , Nevill Alan , Duly Ellie , Trinick Tom , Murphy Marie
Published: July 2021

This study evaluated the effectiveness of strategies used to recruit and retain overweight, inactive adults with intermediate hyperglycaemia (IHG) to a novel walking programme. Participant compliance to the nine-month randomised controlled trial (RCT) is also presented. Inactive overweight (BMI ≥ 25 kg/m2) adults (N = 42; n = 19 male, n = 23 female) aged between 18–65 years, with IHG were identified via three recruitment strategies (NHS database reviews, diabetic clinics, and a University population). Participants were randomly assigned to either Intervention Group (IG n = 22; n = 11 male, n = 11 female) or Usual Care (UC n = 20; n = 8 male, n = 12 female). IG followed a nine-month novel behaviour change intervention where they walked in accordance with physical activity guidelines using the beat of music to maintain appropriate cadence. UC received standard physical activity advice. Recruitment, retention, and intervention compliance were calculated using descriptive statistics (means or frequencies). Recruiting from a University population was the most successful strategy (64.2% response rate) followed by NHS database reviews (35.8%) and then diabetic clinics (0%). Study retention was ≥80% in both groups throughout the RCT. Intervention compliance was highest from baseline to four months (70.1 ± 39.2%) and decreased as the study progressed (43.4 ± 56.1% at four to six months and 37.5 ± 43.5% at follow-up). In total, 71.4% of IG walking completed throughout the study was at least moderate intensity. A novel walking intervention incorporating the use of music along with behaviour change techniques appears to positively influence the recruitment, retention, and walking compliance of this population.
Higher Ventricular-Arterial Coupling Derived from Three-Dimensional Echocardiography Is Associated with a Worse Clinical Outcome in Systemic Sclerosis
Authors: Tona Francesco , Zanatta Elisabetta , Montisci Roberta , Muraru Denisa , Beccegato Elena , De Zorzi Elena , Benvenuti Francesco , Civieri Giovanni , Cozzi Franco , Iliceto Sabino , Doria Andrea
Published: July 2021

Primary myocardial involvement is common in systemic sclerosis (SSc). Ventricular-arterial coupling (VAC) reflecting the interplay between ventricular performance and arterial load, is a key determinant of cardiovascular (CV) performance. We aimed to investigate VAC, VAC-derived indices, and the potential association between altered VAC and survival free from death/hospitalization for major adverse CV events (MACE) in scleroderma. Only SSc patients without any anamnestic and echocardiographic evidence of primary myocardial involvement who underwent three-dimensional echocardiography (3DE) were included in this cross-sectional study and compared with healthy matched controls. 3DE was used for noninvasive measurements of end-systolic elastance (Ees), arterial elastance (Ea), VAC (Ea/Ees) and end-diastolic elastance (Eed); the occurrence of death/hospitalization for MACE was recorded during follow-up. Sixty-five SSc patients (54 female; aged 56 ± 14 years) were included. Ees (p = 0.04), Ea (p = 0.04) and Eed (p = 0.01) were higher in patients vs. controls. Thus, VAC was similar in both groups. Ees was lower and VAC was higher in patients with diffuse cutaneous form (dcSSc) vs. patients with limited form (lcSSc) (p = 0.001 and p = 0.02, respectively). Over a median follow-up of 4 years, four patients died for heart failure and 34 were hospitalized for CV events. In patients with VAC > 0.63 the risk of MACE was higher (HR 2.5; 95% CI 1.13–5.7; p = 0.01) and survival free from death/hospitalization was lower (p = 0.005) than in those with VAC < 0.63. Our study suggests that VAC may be impaired in SSc patients without signs and symptoms of primary myocardial involvement. Moreover, VAC appears to have a prognostic role in SSc.
Antiviral Activity of Isoquinolone Derivatives against Influenza Viruses and Their Cytotoxicity
Authors: Jang Yejin , Han Jinhe , Li Xiaoli , Shin Hyunjin , Cho Won-Jea , Kim Meehyein
Published: July 2021

Influenza viruses are one of the major causative agents for human respiratory infections. Currently, vaccines and antivirals approved for preventing and treating viral infections are available. However, limited protection efficacy and frequent emergence of drug-resistant viruses stand for a need for the development of antivirals with different chemical skeletons from existing drugs. Screening of a chemical library identified an isoquinolone compound (1) as a hit with 50% effective concentrations (EC50s) between 0.2 and 0.6 µM against the influenza A and B viruses. However, it exhibited severe cytotoxic effects with a 50% cytotoxic concentration (CC50) of 39.0 µM in canine kidney epithelial cells. To address this cytotoxic issue, we synthesized an additional 22 chemical derivatives. Through structure-activity, as well as structure-cytotoxicity relationship studies, we discovered compound 21 that has higher EC50 values ranging from 9.9 to 18.5 µM, but greatly alleviated cytotoxicity with a CC50 value over 300 µM. Mode-of-action and cell type-dependent antiviral experiments indicated that it targets viral polymerase activity and functions also in human cells. Here, we present a new class of viral polymerase inhibitors with a core skeleton of isoquinolone, of which antiviral activity could be better improved through following design and synthesis of its derivatives for drug development.
Post-Processing Techniques for the Improvement of Liposome Stability
Authors: Yu Ji Young , Chuesiang Piyanan , Shin Gye Hwa , Park Hyun Jin
Published: July 2021

Liposomes have been utilized as a drug delivery system to increase the bioavailability of drugs and to control the rate of drug release at the target site of action. However, the occurrence of self-aggregation, coalescence, flocculation and the precipitation of aqueous liposomes during formulation or storage can cause degradation of the vesicle structure, leading to the decomposition of liposomes. To increase the stability of liposomes, post-processing techniques have been applied as an additional process to liposomes after formulation to remove water and generate dry liposome particles with a higher stability and greater accessibility for drug administration in comparison with aqueous liposomes. This review covers the effect of these techniques including freeze drying, spray drying and spray freeze drying on the stability, physicochemical properties and drug encapsulation efficiency of dry liposomes. The parameters affecting the properties of liposomes during the drying process are also highlighted in this review. In addition, the impact of using a protective agent to overcome such limitations of each process is thoroughly discussed through various studies.
Machine Learning Uncovers Adverse Drug Effects on Intestinal Bacteria
Authors: McCoubrey Laura E. , Elbadawi Moe , Orlu Mine , Gaisford Simon , Basit Abdul W.
Published: July 2021

The human gut microbiome, composed of trillions of microorganisms, plays an essential role in human health. Many factors shape gut microbiome composition over the life span, including changes to diet, lifestyle, and medication use. Though not routinely tested during drug development, drugs can exert profound effects on the gut microbiome, potentially altering its functions and promoting disease. This study develops a machine learning (ML) model to predict whether drugs will impair the growth of 40 gut bacterial strains. Trained on over 18,600 drug–bacteria interactions, 13 distinct ML models are built and compared, including tree-based, ensemble, and artificial neural network techniques. Following hyperparameter tuning and multi-metric evaluation, a lead ML model is selected: a tuned extra trees algorithm with performances of AUROC: 0.857 (±0.014), recall: 0.587 (±0.063), precision: 0.800 (±0.053), and f1: 0.666 (±0.042). This model can be used by the pharmaceutical industry during drug development and could even be adapted for use in clinical settings.
Natural Rubber-TiO2 Nanocomposite Film for Triboelectric Nanogenerator Application
Authors: Bunriw Weeraya , Harnchana Viyada , Chanthad Chalathorn , Huynh Van Ngoc
Published: July 2021

In this research, natural rubber (NR)-TiO2 nanocomposites were developed for triboelectric nanogenerator (TENG) application to harvest mechanical energy into electrical energy. Rutile TiO2 nanoparticles were used as fillers in NR material to improve dielectric properties so as to enhance the energy conversion performance of the NR composite TENG. The effect of filler concentration on TENG performance of the NR-TiO2 composites was investigated. In addition, ball-milling method was employed to reduce the agglomeration of TiO2 nanoparticles in order to improve their dispersion in the NR film. It was found that the TENG performance was significantly enhanced due to the increased dielectric constant of the NR-TiO2 composite films fabricated from the ball-milled TiO2. The TENG, fabricated from the NR-TiO2 composite using 24 h ball-milled TiO2 at 0.5%wt, delivered the highest power density of 237 mW/m2, which was almost four times higher than that of pristine NR TENG. Furthermore, the applications of the fabricated NR-TiO2 TENG as a power source to operate portable electronics devices were also demonstrated.
Recovering World-Welcoming Words: Language, Metaphysics, and the Voice of Nature
Authors: Gerlier Valentin
Published: July 2021

This article presents a theological–literary response to a concern in contemporary theory with heeding and articulating the speech of nonhuman things. Drawing from Rowan Williams’ metaphysics of poetic addition, I argue that an ‘ecotheological’ literary practice challenges us to become attentive and responsive to the language of the nonhuman, by creatively performing the co-mingling of nonhuman and human language. Drawing from Jean-Louis Chrétien’s phenomenology of the voice, I propose a theological conception of language as a gift of hospitality to the voice of nonhuman things that is also a gift of poetic addition—a ‘saying more’ which, adding being to the world, also manifests its gift-like nature. In contrast to recent critical approaches, I argue for the qualified retrieval of ‘nature’ as a figure both literary and theological, a voice that gives voice to things and speaks by means of human literary production. Through a reading of Shakespeare’s King Lear, I show that the paradoxical and poetic ambiguities of the literary sense of ‘nature’ serve precisely to shed light on its suspect modern iteration, while at the same time taking us beyond critique to enable a cautious yet attentive retrieval of its poetic and symbolic scope.
Reliability of Seismic Performance Assessments for Individual Buildings and Portfolios
Authors: Thiel Charles C. , Zsutty Theodore C. , Lee Yajie J.
Published: July 2021

Seismic performance and loss assessments are required in areas of Insurance, Finance and Public Policy. Providers are Structural Engineers and Risk Management Firms. There are no current procedures to evaluate the epistemic and aleatory uncertainties for such assessments. The essential issue is whether or not there is sufficient reliability in the result to use the result as the basis for risk management decisions and actions. For a single building this may be whether or not a prescribed earthquake performance level is met, life safety or if a portfolio’s vulnerability level is acceptable, whether the. loss for a given time period is less than a stated value. A method based in part on Federal Emergency Management Agency P-695, is developed for evaluating the reliability of performance and/or loss assessments for both individual and portfolios of buildings. Consideration is given to how well the building investigation and corresponding evaluation process have been performed, the qualifications of the person(s) doing the assessment, the thoroughness of the building evaluation, the technical validity of the assessment procedure or model and what computational reliabilities are presented. The method characterizes the uncertainty of each component of the assessment procedure for each building by qualitative determined assignments. The resulting reliability measure is likely to be most useful for determining whether/or not a building has acceptable life safety performance, or if a portfolio has an acceptably low loss risk over a given period of time. In both cases, the reliability must either be sufficient to warrant action, or serve to indicate need for improved assessment.
UAV Path Planning for Reconnaissance and Look-Ahead Coverage Support for Mobile Ground Vehicles
Authors: Jayaweera Herath M. P. C. , Hanoun Samer
Published: July 2021

Path planning of unmanned aerial vehicles (UAVs) for reconnaissance and look-ahead coverage support for mobile ground vehicles (MGVs) is a challenging task due to many unknowns being imposed by the MGVs’ variable velocity profiles, change in heading, and structural differences between the ground and air environments. Few path planning techniques have been reported in the literature for multirotor UAVs that autonomously follow and support MGVs in reconnaissance missions. These techniques formulate the path planning problem as a tracking problem utilizing gimbal sensors to overcome the coverage and reconnaissance complexities. Despite their lack of considering additional objectives such as reconnaissance coverage and dynamic environments, they retain several drawbacks, including high computational requirements, hardware dependency, and low performance when the MGV has varying velocities. In this study, a novel 3D path planning technique for multirotor UAVs is presented, the enhanced dynamic artificial potential field (ED-APF), where path planning is formulated as both a follow and cover problem with nongimbal sensors. The proposed technique adopts a vertical sinusoidal path for the UAV that adapts relative to the MGV’s position and velocity, guided by the MGV’s heading for reconnaissance and exploration of areas and routes ahead beyond the MGV sensors’ range, thus extending the MGV’s reconnaissance capabilities. The amplitude and frequency of the sinusoidal path are determined to maximize the required look-ahead visual coverage quality in terms of pixel density and quantity pertaining to the area covered. The ED-APF was tested and validated against the general artificial potential field techniques for various simulation scenarios using Robot Operating System (ROS) and Gazebo-supported PX4-SITL. It demonstrated superior performance and showed its suitability for reconnaissance and look-ahead support to MGVs in dynamic and obstacle-populated environments.
A Multifeature Learning and Fusion Network for Facial Age Estimation
Authors: Deng Yulan , Teng Shaohua , Fei Lunke , Zhang Wei , Rida Imad
Published: July 2021

Age estimation from face images has attracted much attention due to its favorable and many real-world applications such as video surveillance and social networking. However, most existing studies usually learn a single kind of age feature and ignore other appearance features such as gender and race, which have a great influence on the age pattern. In this paper, we proposed a compact multifeature learning and fusion method for age estimation. Specifically, we first used three subnetworks to learn gender, race, and age information. Then, we fused these complementary features to further form more robust features for age estimation. Finally, we engineered a regression-ranking age-feature estimator to convert the fusion features into the exact age numbers. Experimental results on three benchmark databases demonstrated the effectiveness and efficiency of the proposed method on facial age estimation in comparison to previous state-of-the-art methods. Moreover, compared with previous state-of-the-art methods, our model was more compact with only a 20 MB memory overhead and is suitable for deployment on mobile or embedded devices for age estimation.
A Sustainable Early Warning System Using Rolling Forecasts Based on ANN and Golden Ratio Optimization Methods to Accurately Predict Real-Time Water Levels and Flash Flood
Authors: Alasali Feras , Tawalbeh Rula , Ghanem Zahra , Mohammad Fatima , Alghazzawi Mohammad
Published: July 2021

Remote monitoring sensor systems play a significant role in the evaluation and minimization of natural disasters and risk. This article presents a sustainable and real-time early warning system of sensors employed in flash flood prediction by using a rolling forecast model based on Artificial Neural Network (ANN) and Golden Ratio Optimization (GROM) methods. This Early Flood Warning System (EFWS) aims to support decision makers by providing reliable and accurate information and warning about any possible flood events within an efficient lead-time to reduce any damages due to flash floods. In this work, to improve the performance of the EFWS, an ANN forecast model based on a new optimization method, GROM, is developed and compared to the traditional ANN model. Furthermore, due to the lack of literature regarding the optimal ANN structural model for forecasting the flash flood, this paper is one of the first extensive investigations into the impact of using different exogenous variables and parameters on the ANN structure. The effect of using a rolling forecast model compared to fixed model on the accuracy of the forecasts is investigated as well. The results indicate that the rolling ANN forecast model based on GROM successfully improved the model accuracy by 40% compared to the traditional ANN model and by 93.5% compared to the fixed forecast model.
Behavioral Modeling of DC/DC Converters in Self-Powered Sensor Systems with Modelica
Authors: Kokert Jan , Reindl Leonhard M. , Rupitsch Stefan J.
Published: July 2021

DC/DC converters are the essential component of power management in applications such as self-powered systems. Their simulation plays an important role in the configuration, analysis and design. A major drawback is the lack of behavioral models for DC/DC converters for long-term simulations (days or months). Available models are cycle-to-cycle-based due to the switch-mode nature of the converters and are therefore not applicable. In this work, we present a new behavioral model of a DC/DC power converter. The model is based on a thorough discussion of the model aspects that are relevant for self-powered systems, such as electrical representation and the causal connection if input and output. The model implementation is shown in the Modelica language and is available as an open-source library. The highlights of the model are a feedback controller for operation at the maximum power point (MPP), a loss-based efficiency function, and the start/stop behavior. The model’s capabilities are demonstrated in a 24h-experiment to predict voltage levels and the conversion efficiency.
Examples of the Use of the ARAMIS 3D Measurement System for the Susceptibility to Deformation Tests for the Selected Mixtures of Coal Mining Wastes
Authors: Walotek Konrad , Bzówka Joanna , Ciołczyk Adrian
Published: July 2021

This paper presents the ARAMIS 3D system and examples of deformation susceptibility test results made on mixtures of coal mining waste and recycled tire rubber bound with the use of hydraulic binders. The ARAMIS 3D system is a measurement tool based on 3D scanning of the surface of the tested material. On the basis of the obtained 3D video image, the system allows for the continuous observation of the displacements occurring on the surface of the tested object during its load. This allows for a very detailed determination of the deformation distribution during the material loading. These types of measurement systems can be very useful, especially in the case of testing composite materials and testing materials under cyclic load conditions.
Received Signal Strength Fingerprinting-Based Indoor Location Estimation Employing Machine Learning
Authors: Polak Ladislav , Rozum Stanislav , Slanina Martin , Bravenec Tomas , Fryza Tomas , Pikrakis Aggelos
Published: July 2021

The fingerprinting technique is a popular approach to reveal location of persons, instruments or devices in an indoor environment. Typically based on signal strength measurement, a power level map is created first in the learning phase to align with measured values in the inference. Second, the location is determined by taking the point for which the recorded received power level is closest to the power level actually measured. The biggest limit of this technique is the reliability of power measurements, which may lack accuracy in many wireless systems. To this end, this work extends the power level measurement by using multiple anchors and multiple radio channels and, consequently, considers different approaches to aligning the actual measurements with the recorded values. The dataset is available online. This article focuses on the very popular radio technology Bluetooth Low Energy to explore the possible improvement of the system accuracy through different machine learning approaches. It shows how the accuracy–complexity trade-off influences the possible candidate algorithms on an example of three-channel Bluetooth received signal strength based fingerprinting in a one dimensional environment with four static anchors and in a two dimensional environment with the same set of anchors. We provide a literature survey to identify the machine learning algorithms applied in the literature to show that the studies available can not be compared directly. Then, we implement and analyze the performance of four most popular supervised learning techniques, namely k Nearest Neighbors, Support Vector Machines, Random Forest, and Artificial Neural Network. In our scenario, the most promising machine learning technique being the Random Forest with classification accuracy over 99%.
Cyberattack on Flight Safety: Detection and Mitigation Using LoRa
Authors: Ronen Rony , Ben-Moshe Boaz
Published: July 2021

Automatic Dependent Surveillance-Broadcast (ADS-B) is the main communication system currently being used in Air Traffic Control (ATC) around the world. The ADS-B system is planned to be a key component of the Federal Aviation Administration (FAA) NextGen plan, which will manage the increasingly congested airspace in the coming decades. While the benefits of ADS-B are widely known, its lack of security measures and its vulnerability to cyberattacks such as jamming and spoofing is a great concern for flight safety experts. In this paper, we first summarize the cyberattacks and challenges related to ADS-B’s vulnerabilities. Thereafter, we present theoretical and practical methods for implementing an Internet of Things (IoT)-based system as a possible additional safety layer to mitigate the presented cyber-vulnerabilities. Finally, a set of simulations and field experiments is presented to test the expected performance of the suggested IoT flight safety system. We conjecture that the presented system can be implemented in a wide range of civilian airplanes, leading to an improvement in flight safety in cases of cyberattacks or the absence of reliable ADS-B communication.
An Improved Character Recognition Framework for Containers Based on DETR Algorithm
Authors: Zhao Xiaofang , Zhou Peng , Xu Ke , Xiao Liyun
Published: July 2021

An improved DETR (detection with transformers) object detection framework is proposed to realize accurate detection and recognition of characters on shipping containers. ResneSt is used as a backbone network with split attention to extract features of different dimensions by multi-channel weight convolution operation, thus increasing the overall feature acquisition ability of the backbone. In addition, multi-scale location encoding is introduced on the basis of the original sinusoidal position encoding model, improving the sensitivity of input position information for the transformer structure. Compared with the original DETR framework, our model has higher confidence regarding accurate detection, with detection accuracy being improved by 2.6%. In a test of character detection and recognition with a self-built dataset, the overall accuracy can reach 98.6%, which meets the requirements of logistics information identification acquisition.
DOA Estimation Based on Weighted l1-norm Sparse Representation for Low SNR Scenarios
Authors: Zuo Ming , Xie Shuguo , Zhang Xian , Yang Meiling
Published: July 2021

In this paper, a weighted l1-norm is proposed in a l1-norm-based singular value decomposition (L1-SVD) algorithm, which can suppress spurious peaks and improve accuracy of direction of arrival (DOA) estimation for the low signal-to-noise (SNR) scenarios. The weighted matrix is determined by optimizing the orthogonality of subspace, and the weighted l1-norm is used as the minimum objective function to increase the signal sparsity. Thereby, the weighted matrix makes the l1-norm approximate the original l0-norm. Simulated results of orthogonal frequency division multiplexing (OFDM) signal demonstrate that the proposed algorithm has s narrower main lobe and lower side lobe with the characteristics of fewer snapshots and low sensitivity of misestimated signals, which can improve the resolution and accuracy of DOA estimation. Specifically, the proposed method exhibits a better performance than other works for the low SNR scenarios. Outdoor experimental results of OFDM signals show that the proposed algorithm is superior to other methods with a narrower main lobe and lower side lobe, which can be used for DOA estimation of UAV and pseudo base station.
Machine Learning for the Dynamic Positioning of UAVs for Extended Connectivity
Authors: Oliveira Francisco , Luís Miguel , Sargento Susana
Published: July 2021

Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV positioning algorithm responsible for determining suitable positions for the UAVs, with the objective of a more balanced redistribution of traffic, to avoid saturated base stations and decrease the number of users without a connection. The tests performed with real data of user connections through base stations show that, in less restrictive network conditions, the algorithm to dynamically place the UAVs performs significantly better than in more restrictive conditions, reducing significantly the number of users without a connection. We also conclude that the accuracy of the prediction is a very important factor, not only in the reduction of users without a connection, but also on the number of UAVs deployed.
Internet-of-Things Devices in Support of the Development of Echoic Skills among Children with Autism Spectrum Disorder
Authors: Rechowicz Krzysztof J. , Shull John B. , Hascall Michelle M. , Diallo Saikou Y. , O’Brien Kevin J.
Published: July 2021

A significant therapeutic challenge for people with disabilities is the development of verbal and echoic skills. Digital voice assistants (DVAs), such as Amazon’s Alexa, provide networked intelligence to billions of Internet-of-Things devices and have the potential to offer opportunities to people, such as those diagnosed with autism spectrum disorder (ASD), to advance these necessary skills. Voice interfaces can enable children with ASD to practice such skills at home; however, it remains unclear whether DVAs can be as proficient as therapists in recognizing utterances by a developing speaker. We developed an Alexa-based skill called ASPECT to measure how well the DVA identified verbalization by autistic children. The participants, nine children diagnosed with ASD, each participated in 30 sessions focused on increasing vocalizations and echoic responses. Children interacted with ASPECT prompted by instructions from an Echo device. ASPECT was trained to recognize utterances and evaluate them as a therapist would—simultaneously, a therapist scored the child’s responses. The study identified no significant difference between how ASPECT and the therapists scored participants; this conclusion held even when subsetting participants by a pre-treatment echoic skill assessment score. This indicates considerable potential for providing a continuum of therapeutic opportunities and reinforcement outside of clinical settings.
Deposition of a SiO2 Shell of Variable Thickness and Chemical Composition to Carbonyl Iron: Synthesis and Microwave Measurements
Authors: Dolmatov Arthur V. , Maklakov Sergey S. , Zezyulina Polina A. , Osipov Alexey V. , Petrov Dmitry A. , Naboko Andrey S. , Polozov Viktor I. , Maklakov Sergey A. , Starostenko Sergey N. , Lagarkov Andrey N.
Published: July 2021

Protective SiO2 coating deposited to iron microparticles is highly demanded both for the chemical and magnetic performance of the latter. Hydrolysis of tetraethoxysilane is the crucial method for SiO2 deposition from a solution. The capabilities of this technique have not been thoroughly studied yet. Here, two factors were tested to affect the chemical composition and the thickness of the SiO2 shell. It was found that an increase in the hydrolysis reaction time thickened the SiO2 shell from 100 to 200 nm. Moreover, a decrease in the acidity of the reaction mixture not only thickened the shell but also varied the chemical composition from SiO3.0 to SiO8.6. The thickness and composition of the dielectric layer were studied by scanning electron microscopy and energy-dispersive X-ray analysis. Microwave permeability and permittivity of the SiO2-coated iron particles mixed with a paraffin wax matrix were measured by the coaxial line technique. An increase in thickness of the silica layer decreased the real quasi-static permittivity. The changes observed were shown to agree with the Maxwell Garnett effective medium theory. The new method developed to fine-tune the chemical properties of the protective SiO2 shell may be helpful for new magnetic biosensor designs as it allows for biocompatibility adjustment.
Automated Classification of Changes of Direction in Soccer Using Inertial Measurement Units
Authors: Reilly Brian , Morgan Oliver , Czanner Gabriela , Robinson Mark A.
Published: July 2021

Changes of direction (COD) are an important aspect of soccer match play. Understanding the physiological and biomechanical demands on players in games allows sports scientists to effectively train and rehabilitate soccer players. COD are conventionally recorded using manually annotated time-motion video analysis which is highly time consuming, so more time-efficient approaches are required. The aim was to develop an automated classification model based on multi-sensor player tracking device data to detect COD > 45°. Video analysis data and individual multi-sensor player tracking data (GPS, accelerometer, gyroscopic) for 23 academy-level soccer players were used. A novel ‘GPS-COD Angle’ variable was developed and used in model training; along with 24 GPS-derived, gyroscope and accelerometer variables. Video annotation was the ground truth indicator of occurrence of COD > 45°. The random forest classifier using the full set of features demonstrated the highest accuracy (AUROC = 0.957, 95% CI = 0.956–0.958, Sensitivity = 0.941, Specificity = 0.772. To balance sensitivity and specificity, model parameters were optimised resulting in a value of 0.889 for both metrics. Similarly high levels of accuracy were observed for random forest models trained using a reduced set of features, accelerometer-derived variables only, and gyroscope-derived variables only. These results point to the potential effectiveness of the novel methodology implemented in automatically identifying COD in soccer players.
Context-Aware Naming and Forwarding in NDN-Based VANETs
Authors: Zafar Waseeq Ul Islam , Rehman Muhammad Atif Ur , Jabeen Farhana , Kim Byung-Seo , Rehman Zobia
Published: July 2021

Vehicular ad-hoc network (VANET) is a technology that allows ubiquitous mobility to mobile users. Inter-vehicle communication is an integral component of intelligent transportation systems that enables a wide variety of applications where vehicles interact and cooperate with each other, from safety applications to non-safety applications. VANETs applications have different needs (e.g., latency, reliability, delivery priorities, etc.) in terms of delivery effectiveness. In the last decade, named data networking (NDN) gained the attention of the research community for effective content retrieval and dissemination in mobile environments such as VANETs. In NDN, the content’s name has a vital role in storing and retrieving the content effectively and efficiently. In NDN-based VANETs, adaptive content dissemination solutions must be introduced that can make decisions related to forwarding, cache management, etc., based on context information represented by a content name. In this context, our main contributions are two-fold: (i) we present the hierarchical context-aware content-naming (CACN) scheme for NDN-based VANETs that enables naming the safety and non-safety applications, and (ii) we present a decentralized context-aware notification (DCN) protocol that broadcasts event notification information for awareness within the application-based geographical area. Simulation results show that the proposed DCN protocol succeeds in achieving reduced transmissions, bandwidth, and energy compared to existing critical contents dissemination protocols.
Spectral Coexistence of QoS-Constrained and IoT Traffic in Satellite Systems
Authors: Munari Andrea , Clazzer Federico
Published: July 2021

The flourishing of Internet of Things (IoT) applications, characterized by vast transmitter populations and the sporadic transmission of small data units, demands innovative solutions for the sharing of the wireless medium. In this context, satellite connectivity is an important enabler for all scenarios in which terminals are under-served by terrestrial communications and are thus fundamental for providing worldwide coverage. In turn, the design of medium access policies that attain efficient use of the scarce spectrum and can cope with flexible yet unpredictable IoT traffic is of the utmost importance. Starting from these remarks, we investigate in this work the coexistence of a quality of service (QoS)-constrained service with IoT traffic in a shared spectrum as alternative to a more traditional orthogonal allocation among the two services, with an eye on satellite applications. Leaning on analytical tools, we provide achievable rate regions, assuming a slotted ALOHA access method for IoT terminals and accounting for practical aspects, such as the transmission of short packets. Interesting trends emerge, showcasing the benefit of an overlay allocation with respect to segregating the resources for the two services.