bluuebunny/crossref_metadata_2025 huggingface dataset:
Whey Protein Supplementation Improves the Glycemic Response and May Reduce Non-Alcoholic Fatty Liver Disease Related Biomarkers in Women with Polycystic Ovary Syndrome (PCOS)
Authors: Zumbro Emily L. , Rao Manisha , Balcom-Luker Shenavia , Broughton K. Shane , LeMieux Monique J.
Published: July 2021

Polycystic ovary syndrome (PCOS) increases type 2 diabetes and non-alcoholic fatty liver disease (NAFLD) with insulin resistance. We hypothesized that a 35 g whey preload would improve insulin sensitivity and glucose handling while reducing biomarkers associated with NAFLD. Twenty-nine age-matched women (CON = 15, PCOS = 14) completed oral glycemic tolerance tests following baseline (Day 0) as well as an acute (Day 1) and short-term whey supplementation (Day 7). Whey had an interaction effect on glucose (p = 0.02) and insulin (p = 0.03), with glucose remaining stable and insulin increasing with whey supplementation. Insulin sensitivity (p < 0.01) improved with whey associated with increased glucagon secretion (p < 0.01). Alanine aminotransferase (ALT), and aspartate aminotransferase (AST) remained unchanged, but “day” had an effect on the AST:ALT ratio (p = 0.04), whereas triglycerides and sex hormone binding globulin overall were greater in the PCOS group (p < 0.05). Total cholesterol decreased in PCOS (by 13%) and CON (by 8%) (NS). HepG2 cells treated with plasma from participants before and after whey decreased lipid accumulation in the PCOS group after whey (p < 0.05). Whey provided an insulinogenic and glycemic homeostatic effect in women with PCOS with the potential to combat NAFLD-consequences.
TIMER: A Clinical Study of Energy Restriction in Women with Gestational Diabetes Mellitus
Authors: Tsirou Efrosini , Grammatikopoulou Maria G. , Nigdelis Meletios P. , Taousani Eleftheria , Savvaki Dimitra , Assimakopoulos Efstratios , Tsapas Apostolos , Goulis Dimitrios G.
Published: July 2021

Medical nutrition therapy is an integral part of gestational diabetes mellitus (GDM) management; however, the prescription of optimal energy intake is often a difficult task due to the limited available evidence. The present pilot, feasibility, parallel, open-label and non-randomized study aimed to evaluate the effect of a very low energy diet (VLED, 1600 kcal/day), or a low energy diet (LED, 1800 kcal/day), with or without personalized exercise sessions, among women with GDM in singleton pregnancies. A total of 43 women were allocated to one of four interventions at GDM diagnosis: (1) VLED (n = 15), (2) VLED + exercise (n = 4), (3) LED (n = 16) or (4) LED + exercise (n = 8). Primary outcomes were gestational weight gain (GWG), infant birth weight, complications at delivery and a composite outcomes score. Secondary outcomes included type of delivery, prematurity, small- for-gestational-age (SGA) or large-for-gestational-age (LGA) infants, macrosomia, Apgar score, insulin use, depression, respiratory quotient (RQ), resting metabolic rate (RMR) and middle-upper arm circumference (MUAC). GWG differed between intervention groups (LED median: 12.0 kg; VLED: 5.9 kg). No differences were noted in the type of delivery, infant birth weight, composite score, prevalence of prematurity, depression, RQ, Apgar score, MUAC, or insulin use among the four groups. Regarding components of the composite score, most infants (88.4%) were appropriate-for-gestational age (AGA) and born at a gestational age of 37–42 weeks (95.3%). With respect to the mothers, 9.3% experienced complications at delivery, with the majority being allocated at the VLED + exercise arm (p < 0.03). The composite score was low (range 0–2.5) for all mother-infant pairs, indicating a “risk-free” pregnancy outcome. The results indicate that adherence to a LED or VLED induces similar maternal, infant and obstetrics outcomes.
Fatty Acids Quality in Middle Eastern Traditional Dishes, Arabic Sweets and Market Foods Frequently Consumed in Lebanon
Authors: Hoteit Maha , Zoghbi Edwina , Rady Alissar , Shankiti Iman , Al-Jawaldeh Ayoub
Published: July 2021

The prevalence of diet-related non-communicable diseases is on the rise in the countries of the Eastern Mediterranean, including Lebanon. This study aimed to provide data on fatty acid profiles and ratios of Lebanese composite dishes, Arabic sweets, and market foods. Methods: Thirty types of traditional dishes, collected from five different Lebanese governorates, thirty-seven types of Arabic sweets and forty-six market food products were considered for analysis. Food samples were chemically analyzed for total, unsaturated and saturated fatty acids. The range of total fatty acids in composite dishes, Arabic sweets, and market food products was between 1.2–11.7 g/100 g, 5.3–25.8 g/100 g, and 0.5–100 g/100 g, respectively. Additionally, the range of saturated fatty acids in composite dishes, Arabic sweets, and market food products was between 0.5–4.9 g/100 g, 2.5–23.6 g/100 g and 0.1–56.4 g/100 g, respectively. Furthermore, about 75% of these foods were poor in unsaturated fatty acids. Regarding saturated fatty acid, the polyunsaturated to monounsaturated (P.M.S) ratio was lower than the recommended ratio of 1:1:1 in 96% of samples. To conclude, there is a need to prioritize fat content in foods and consider processing modifications in the food production system with the aim of achieving a higher P:M:S ratio intake among the population.
Synergistic Interaction in the Analgesic-Like Effects of Maqui Berry and Citrus Is Antagonized by Sweeteners
Authors: Agulló Vicente , González-Trujano María Eva , Hernandez-Leon Alberto , Estrada-Camarena Erika , Pellicer Francisco , García-Viguera Cristina
Published: July 2021

Although physiologically pain has a protective function, in many diseases, it is one of the most prominent symptoms. Today, new trends are focused on finding more natural alternatives to conventional treatments to alleviate it. Thereby, the purpose of this investigation was to obtain preclinical data of the antinociceptive properties of a lyophilized obtained from a newly designed maqui–citrus beverage alone and added with different sweeteners. To achieve this objective, maqui berry and citrus pharmacological activity were studied separately, as well as the interaction of both ingredients. In addition, due to the controversy generated regarding the intake of sugars, related to different metabolic diseases, the influence of different sweeteners (stevia, sucralose, or sucrose) was studied to determine their possible influence on the bioactive compounds of this product. For the attainment of our goals, a pharmacological evaluation, using the 1% formalin test, a nociceptive pain model in mice, was performed by using a sub-efficacious dosage of Maqui (25 mg/kg, i.p.) alone and combined with citrus, and then compared with the effects obtained in the presence of the different sweeteners. As a result, the antinociceptive response of the maqui was synergized in the presence of citrus in the neurogenic and inflammatory phases of the formalin test. However, this response was partially or totally reduced in the presence of the sweeteners. Our study gives preclinical evidence that a combination of maqui and citrus might exert beneficial actions to relieve pain, whereas the presence of sweeteners could reduce or avoid it.
Biological Control of Take-All and Growth Promotion in Wheat by Pseudomonas chlororaphis YB-10
Authors: Xu Wen , Xu Lingling , Deng Xiaoxu , Goodwin Paul H. , Xia Mingcong , Zhang Jie , Wang Qi , Sun Runhong , Pan Yamei , Wu Chao , Yang Lirong
Published: July 2021

Wheat is a worldwide staple food crop, and take-all caused by Gaeumannomyces graminis var. tritici can lead to a tremendous decrease in wheat yield and quality. In this study, strain YB-10 was isolated from wheat rhizospheric soil and identified as Pseudomonas chlororaphis by morphology and 16S rRNA gene sequencing. Pseudomonas chlororaphis YB-10 had extracellular protease and cellulase activities and strongly inhibited the mycelium growth of Gaeumannomyces graminis var. tritici in dual cultures. Up to 87% efficacy of Pseudomonas chlororaphis YB-10 in controlling the take-all of seedlings was observed in pot experiments when wheat seed was coated with the bacterium. Pseudomonas chlororaphis YB-10 was also positive for indole acetic acid (IAA) and siderophore production, and coating wheat seed with the bacterium significantly promoted the growth of seedlings at 107 and 108 CFU/mL. Furthermore, treatment with Pseudomonas chlororaphis YB-10 increased activities of the wheat defense-related enzymes POD, SOD, CAT, PAL and PPO in seedlings, indicating induced resistance against pathogens. Overall, Pseudomonas chlororaphis YB-10 is a promising new seed-coating agent to both promote wheat growth and suppress take-all.
Investigating Potential Applications of the Fish Anti-Microbial Peptide Pleurocidin: A Systematic Review
Authors: McMillan Katelyn A. M. , Coombs Melanie R. Power
Published: July 2021

The anti-microbial peptide (AMP) pleurocidin is found in winter flounder (Pseudopleuronectes americanus), an Atlantic flounder species. There is promising evidence for clinical, aquaculture, and veterinary applications of pleurocidin. This review provides an overview of the current literature available on pleurocidin to guide future research directions. By fully elucidating pleurocidin’s mechanism of action and developing novel treatments against pathogenic microbes, populations of flatfish and humans can be protected. This review consulted publications from PubMed and Environment Complete with search terms such as “pleurocidin”, “winter flounder”, and “antimicrobial”. The fish immune system includes AMPs as a component of the innate immune system. Pleurocidin, one of these AMPs, has been found to be effective against various Gram-positive and Gram-negative bacteria. More investigations are required to determine pleurocidin’s suitability as a treatment against antibiotic-resistant pathogens. There is promising evidence for pleurocidin as a novel anti-cancer therapy. The peptide has been found to display potent anti-cancer effects against human cancer cells. Research efforts focused on pleurocidin may result in novel treatment strategies against antibiotic-resistant bacteria and cancer. More research is required to determine if the peptide is a suitable candidate to be developed into a novel anti-microbial treatment. Some of the microbes susceptible to the peptide are also pathogens of fish, suggesting its suitability as a therapeutic treatment for fish species.
Development and Characterization of n-Propyl Gallate Encapsulated Solid Lipid Nanoparticles-Loaded Hydrogel for Intranasal Delivery
Authors: Sabir Fakhara , Katona Gábor , Ismail Ruba , Sipos Bence , Ambrus Rita , Csóka Ildikó
Published: July 2021

The objective of the present study was to develop n-propyl gallate-loaded solid lipid nanoparticles (PG-SLNs) in a hydrogel (HG) formulation using Transcutol-P (TC-P) as a permeation enhancer. Modified solvent injection technique was applied to produce optimized PG-SLNs via the Quality by Design approach and central composite design. The in vitro mucoadhesion, scavenging activity, drug release, permeation studies of PG from PG-SLNs-loaded HG were evaluated under simulated nasal conditions. Compared with in vitro release behavior of PG from SLNs, the drug release from the PG-SLNs-loaded HG showed a lower burst effect and sustained release profile. The cumulative permeation of PG from PG-SLNs-loaded HG with TC-P was 600 μg/cm2 within 60 min, which is 3–60-fold higher than PG-SLNs and native PG, respectively. Raman mapping showed that the distribution of PG-SLNs was more concentrated in HG having lower concentrations of hyaluronic acid. The scavenging assay demonstrated increased antioxidant activity at higher concentrations of HG. Due to enhanced stability and mucoadhesive properties, the developed HG-based SLNs can improve nasal absorption by increasing residence time on nasal mucosa. This study provides in vitro proof of the potential of combining the advantages of SLNs and HG for the intranasal delivery of antioxidants.
Bioprintable Lung Extracellular Matrix Hydrogel Scaffolds for 3D Culture of Mesenchymal Stromal Cells
Authors: Falcones Bryan , Sanz-Fraile Héctor , Marhuenda Esther , Mendizábal Irene , Cabrera-Aguilera Ignacio , Malandain Nanthilde , Uriarte Juan J. , Almendros Isaac , Navajas Daniel , Weiss Daniel J. , Farré Ramon , Otero Jorge
Published: July 2021

Mesenchymal stromal cell (MSC)-based cell therapy in acute respiratory diseases is based on MSC secretion of paracrine factors. Several strategies have proposed to improve this are being explored including pre-conditioning the MSCs prior to administration. We here propose a strategy for improving the therapeutic efficacy of MSCs based on cell preconditioning by growing them in native extracellular matrix (ECM) derived from the lung. To this end, a bioink with tunable stiffness based on decellularized porcine lung ECM hydrogels was developed and characterized. The bioink was suitable for 3D culturing of lung-resident MSCs without the need for additional chemical or physical crosslinking. MSCs showed good viability, and contraction assays showed the existence of cell–matrix interactions in the bioprinted scaffolds. Adhesion capacity and length of the focal adhesions formed were increased for the cells cultured within the lung hydrogel scaffolds. Also, there was more than a 20-fold increase of the expression of the CXCR4 receptor in the 3D-cultured cells compared to the cells cultured in plastic. Secretion of cytokines when cultured in an in vitro model of lung injury showed a decreased secretion of pro-inflammatory mediators for the cells cultured in the 3D scaffolds. Moreover, the morphology of the harvested cells was markedly different with respect to conventionally (2D) cultured MSCs. In conclusion, the developed bioink can be used to bioprint structures aimed to improve preconditioning MSCs for therapeutic purposes.
Extruded-Calendered Sheets of Fully Recycled PP/Opaque PET Blends: Mechanical and Fracture Behaviour
Authors: Loaeza David , Cailloux Jonathan , Pérez Orlando Santana , Sánchez-Soto Miguel , Maspoch Maria Lluïsa
Published: July 2021

This work presents the experimental results of the mechanical and fracture behaviour of three polymeric blends prepared from two recycled plastics, namely polypropylene and opaque poly (ethylene terephthalate), where the second one acted as a reinforcement phase. The raw materials were two commercial degrees of recycled post-consumer waste, i.e., rPP and rPET-O. Sheets were manufactured by a semi-industrial extrusion-calendering process. The mechanical and fracture behaviours of manufactured sheets were analyzed via tensile tests and the essential work of fracture approach. SEM micrographics of cryofractured sheets revelated the development of in situ rPP/rPET-O microfibrillar composites when 30 wt.% of rPET-O was added. It was observed that the yield stress was not affected with the addition of rPET-O. However, the microfibrillar structure increased the Young’s modulus by more than a third compared with rPP, fulfilling the longitudinal value predicted by the additive rule of mixtures. Regarding the EWF analysis, the resistance to crack initiation was highly influenced by the resistance to its propagation owing to morphology-related instabilities during tearing. To analyze the initiation stage, a partition energy method was successfully applied by splitting the total work of fracture into two specific energetic contributions, namely initiation and propagation. The results revelated that the specific essential initiation-related work of fracture was mainly affected by rPET-O phase. Remarkably, its value was significantly improved by a factor of three with the microfibrillar structure of rPET-O phase. The results allowed the exploration of the potential ability of manufacturing in situ MFCs without a “precursor” morphology, providing an economical way to promote the recycling rate of PET-O, as this material is being discarded from current recycling processes.
Geometric Measurements on a CNC Machining Device as an Element of Closed Door Technology
Authors: Bomba Grzegorz , Ornat Artur , Gierlak Piotr
Published: July 2021

The article discusses the quality testing of a measuring system consisting of a CNC machine with measuring probes. The research was conducted in a broader context regarding the implementation of the closed door technology, i.e., production without human intervention, in an aviation plant manufacturing aircraft gearbox systems. This technology may involve automated measuring operations performed in machining centers, and not in measuring laboratories, provided that the quality of the measurements is appropriate. The aim of the study was to investigate whether the CNC machining device can be used to measure the geometric features of aircraft gearbox housing. For this purpose, measurement experiments were carried out with the use of three different probes. Measurements were carried out using four sequences of increasing complexity, so that, after error analysis, it was possible to find the causes of possible irregularities. A reference ring with known dimensions and position in the working space of the machine was used for the measurements performed as part of the assessment of the measurement system. The quality of the measurements was evaluated with the use of repeatability and reproducibility testing and statistical process control. The analysis results showed that the tested measurement system ensures adequate accuracy and repeatability, and the measurement process is characterized with adequate efficiency in relation to the manufacturing tolerance of the components produced using the machine. Thus, it was proven that the measurement process can be carried out on a machining device, which enables its integration into the closed door technology.
Computer Vision-Based Microcalcification Detection in Digital Mammograms Using Fully Connected Depthwise Separable Convolutional Neural Network
Authors: Rehman Khalil ur , Li Jianqiang , Pei Yan , Yasin Anaa , Ali Saqib , Mahmood Tariq
Published: July 2021

Microcalcification clusters in mammograms are one of the major signs of breast cancer. However, the detection of microcalcifications from mammograms is a challenging task for radiologists due to their tiny size and scattered location inside a denser breast composition. Automatic CAD systems need to predict breast cancer at the early stages to support clinical work. The intercluster gap, noise between individual MCs, and individual object’s location can affect the classification performance, which may reduce the true-positive rate. In this study, we propose a computer-vision-based FC-DSCNN CAD system for the detection of microcalcification clusters from mammograms and classification into malignant and benign classes. The computer vision method automatically controls the noise and background color contrast and directly detects the MC object from mammograms, which increases the classification performance of the neural network. The breast cancer classification framework has four steps: image preprocessing and augmentation, RGB to grayscale channel transformation, microcalcification region segmentation, and MC ROI classification using FC-DSCNN to predict malignant and benign cases. The proposed method was evaluated on 3568 DDSM and 2885 PINUM mammogram images with automatic feature extraction, obtaining a score of 0.97 with a 2.35 and 0.99 true-positive ratio with 2.45 false positives per image, respectively. Experimental results demonstrated that the performance of the proposed method remains higher than the traditional and previous approaches.
DMAS Beamforming with Complementary Subset Transmit for Ultrasound Coherence-Based Power Doppler Detection in Multi-Angle Plane-Wave Imaging
Authors: Shen Che-Chou , Chu Yen-Chen
Published: July 2021

Conventional ultrasonic coherent plane-wave (PW) compounding corresponds to Delay-and-Sum (DAS) beamforming of low-resolution images from distinct PW transmit angles. Nonetheless, the trade-off between the level of clutter artifacts and the number of PW transmit angle may compromise the image quality in ultrafast acquisition. Delay-Multiply-and-Sum (DMAS) beamforming in the dimension of PW transmit angle is capable of suppressing clutter interference and is readily compatible with the conventional method. In DMAS, a tunable p value is used to modulate the signal coherence estimated from the low-resolution images to produce the final high-resolution output and does not require huge memory allocation to record all the received channel data in multi-angle PW imaging. In this study, DMAS beamforming is used to construct a novel coherence-based power Doppler detection together with the complementary subset transmit (CST) technique to further reduce the noise level. For p = 2.0 as an example, simulation results indicate that the DMAS beamforming alone can improve the Doppler SNR by 8.2 dB compared to DAS counterpart. Another 6-dB increase in Doppler SNR can be further obtained when the CST technique is combined with DMAS beamforming with sufficient ensemble averaging. The CST technique can also be performed with DAS beamforming, though the improvement in Doppler SNR and CNR is relatively minor. Experimental results also agree with the simulations. Nonetheless, since the DMAS beamforming involves multiplicative operation, clutter filtering in the ensemble direction has to be performed on the low-resolution images before DMAS to remove the stationary tissue without coupling from the flow signal.
A Parametric Logarithmic Image Processing Framework Based on Fuzzy Graylevel Accumulation by the Hamacher T-Conorm
Authors: Vertan Constantin , Florea Corneliu , Florea Laura
Published: July 2021

It has been proven that Logarithmic Image Processing (LIP) models provide a suitable framework for visualizing and enhancing digital images acquired by various sources. The most visible (although simplified) result of using such a model is that LIP allows the computation of graylevel addition, subtraction and multiplication with scalars within a fixed graylevel range without the use of clipping. It is claimed that a generalized LIP framework (i.e., a parameterized family of LIP models) can be constructed on the basis of the fuzzy modelling of gray level addition as an accumulation process described by the Hamacher conorm. All the existing LIP and LIP-like models are obtained as particular cases of the proposed framework in the range corresponding to real-world digital images.
Pairwise Registration Algorithm for Large-Scale Planar Point Cloud Used in Flatness Measurement
Authors: Shu Zichao , Cao Songxiao , Jiang Qing , Xu Zhipeng , Tang Jianbin , Zhou Qiaojun
Published: July 2021

In this paper, an optimized three-dimensional (3D) pairwise point cloud registration algorithm is proposed, which is used for flatness measurement based on a laser profilometer. The objective is to achieve a fast and accurate six-degrees-of-freedom (6-DoF) pose estimation of a large-scale planar point cloud to ensure that the flatness measurement is precise. To that end, the proposed algorithm extracts the boundary of the point cloud to obtain more effective feature descriptors of the keypoints. Then, it eliminates the invalid keypoints by neighborhood evaluation to obtain the initial matching point pairs. Thereafter, clustering combined with the geometric consistency constraints of correspondences is conducted to realize coarse registration. Finally, the iterative closest point (ICP) algorithm is used to complete fine registration based on the boundary point cloud. The experimental results demonstrate that the proposed algorithm is superior to the current algorithms in terms of boundary extraction and registration performance.
A Fast and Precise Tool for Multi-Layer Planar Coil Self-Inductance Calculation
Authors: Faria Andreia , Marques Luís , Ferreira Carlos , Alves Filipe , Cabral Jorge
Published: July 2021

An open-source tool that allows for a fast and precise analytical calculation of multi-layer planar coils self-inductance, without any geometry limitation is proposed here. The process of designing and simulating planar coils to achieve reliable results is commonly limited on accuracy and or geometry, or are too time-consuming and expensive, thus a tool to speed up this design process is desired. The model is based on Grover equations, valid for any geometry. The validation of the tool was performed through the comparison with experimental measurements, Finite Element Model (FEM) simulations, and the main analytical methods usually used in literature, with errors registered to be below 2.5%, when compared to standard FEM simulations, and when compared to experimental measurements they are below 10% in the case of the 1-layer coils, and below 5% in the 2-layer coils (without taking into consideration the coil connectors). The proposed model offers a new approach to the calculation of the self-inductance of planar coils of several layers that combines precision, speed, independence of geometry, easy interaction, and no need for extra resources.
Development of Real-Time Time Gated Digital (TGD) OFDR Method and Its Performance Verification
Authors: Kishida Kinzo , Guzik Artur , Nishiguchi Ken’ichi , Li Che-Hsien , Azuma Daiji , Liu Qingwen , He Zuyuan
Published: July 2021

Distributed acoustic sensing (DAS) in optical fibers detect dynamic strains or sound waves by measuring the phase or amplitude changes of the scattered light. This contrasts with other distributed (and more conventional) methods, such as distributed temperature (DTS) or strain (DSS), which measure quasi-static physical quantities, such as intensity spectrum of the scattered light. DAS is attracting considerable attention as it complements the conventional distributed measurements. To implement DAS in commercial applications, it is necessary to ensure a sufficiently high signal-noise ratio (SNR) for scattered light detection, suppress its deterioration along the sensing fiber, achieve lower noise floor for weak signals and, moreover, perform high-speed processing within milliseconds (or sometimes even less). In this paper, we present a new, real-time DAS, realized by using the time gated digital-optical frequency domain reflectometry (TGD-OFDR) method, in which the chirp pulse is divided into overlapping bands and assembled after digital decoding. The developed prototype NBX-S4000 generates a chirp signal with a pulse duration of 2 μs and uses a frequency sweep of 100 MHz at a repeating frequency of up to 5 kHz. It allows one to detect sound waves at an 80 km fiber distance range with spatial resolution better than a theoretically calculated value of 2.8 m in real time. The developed prototype was tested in the field in various applications, from earthquake detection and submarine cable sensing to oil and gas industry applications. All obtained results confirmed effectiveness of the method and performance, surpassing, in conventional SM fiber, other commercially available interrogators.
Multi-Directional Scene Text Detection Based on Improved YOLOv3
Authors: Xiao Liyun , Zhou Peng , Xu Ke , Zhao Xiaofang
Published: July 2021

To address the problem of low detection rate caused by the close alignment and multi-directional position of text words in practical application and the need to improve the detection speed of the algorithm, this paper proposes a multi-directional text detection algorithm based on improved YOLOv3, and applies it to natural text detection. To detect text in multiple directions, this paper introduces a method of box definition based on sliding vertices. Then, a new rotating box loss function MD-Closs based on CIOU is proposed to improve the detection accuracy. In addition, a step-by-step NMS method is used to further reduce the amount of calculation. Experimental results show that on the ICDAR 2015 data set, the accuracy rate is 86.2%, the recall rate is 81.9%, and the timeliness is 21.3 fps, which shows that the proposed algorithm has a good detection effect on text detection in natural scenes.
Combined Punctual and Diffused Monitoring of Concrete Structures Based on Dielectric Measurements
Authors: Cataldo Andrea , Schiavoni Raissa , Masciullo Antonio , Cannazza Giuseppe , Micelli Francesco , De Benedetto Egidio
Published: July 2021

This work presents a microwave reflectometry-based system for monitoring large concrete structures (during the curing process and also while the structure is in use), through the combined use of punctual and diffused sensing elements. In particular, the adoption of punctual probes on a reference concrete specimen allows the development of an innovative and accurate calibration procedure, useful to obtain the value of the water content on a larger structure made of the same material. Additionally, a wire-like diffused sensing element can be permanently embedded in buildings and used to monitor the structure along the entire length of the sensing element. The adopted diffused sensing element can be used not only to detect dielectric variation during the curing process, but also throughout the service life of the structure. The combined use of punctual and diffused sensing elements represents an important innovation from a procedural point of view, able to provide detailed and quantitative information on the health status of the structure both during and after construction.
Effectiveness of Robotic Exoskeleton-Assisted Gait Training in Spinocerebellar Ataxia: A Case Report
Authors: Kim San-Ha , Han Jae-Young , Song Min-Keun , Choi In-Sung , Park Hyeng-Kyu
Published: July 2021

Spinocerebellar ataxia (SCA) is a hereditary neurodegenerative disorder that presents as ataxia. Due to the decline in balance, patients with SCA often experience restricted mobility and a decreased quality of life. Thus, many studies have emphasized the importance of physiotherapies, including gait training, in SCA patients. However, few studies have examined the effectiveness of robotic gait training in SCA. Here, we report the therapeutic outcomes of exoskeleton-assisted gait training in a patient with SCA. A 23-year-old woman with SCA participated in a gait training program using a powered lower-limb robotic exoskeleton, ANGELLEGS. The 8-week training program consisted of standing training, weight-shifting exercises, and gait training. Several measures of general function, balance, gait, and cardiopulmonary function were applied before, after, and 4 weeks after the program. After the program, overall improvements were found on scales measuring balance and gait function, and these improvements remained at 4 weeks after the program. Cardiopulmonary function was also improved 4 weeks after the program. Robotic exoskeleton gait training can be a beneficial option for training balance, gait, and cardiopulmonary function in SCA.
Framework for In-Field Analyses of Performance and Sub-Technique Selection in Standing Para Cross-Country Skiers
Authors: Carlsen Camilla H. , Kathrin Baumgart Julia , Kocbach Jan , Haugnes Pål , Paulussen Evy M. B. , Sandbakk Øyvind
Published: July 2021

Our aims were to evaluate the feasibility of a framework based on micro-sensor technology for in-field analyses of performance and sub-technique selection in Para cross-country (XC) skiing by using it to compare these parameters between elite standing Para (two men; one woman) and able-bodied (AB) (three men; four women) XC skiers during a classical skiing race. The data from a global navigation satellite system and inertial measurement unit were integrated to compare time loss and selected sub-techniques as a function of speed. Compared to male/female AB skiers, male/female Para skiers displayed 19/14% slower average speed with the largest time loss (65 ± 36/35 ± 6 s/lap) found in uphill terrain. Female Para/AB skiers utilized DP, DK, and DIA, 61/43%, 15/10%, and 25/47% of the distance at low speeds, respectively, while the corresponding numbers for male Para/AB skiers were 58/18%, 1/13%, and 40/69%. At higher speeds, female Para/AB skiers utilized DP and OTHER, 26/52% and 74/48% of the distance, respectively, while corresponding numbers for male Para/AB skiers were 29/66% and 71/34%. This indicates different speed thresholds of the classical sub-techniques for Para than AB skiers. The framework provides a point of departure for large-scale international investigations of performance and related factors in Para XC skiing.
Smart Beamforming for Direct LEO Satellite Access of Future IoT
Authors: Caus Marius , Perez-Neira Ana , Mendez Eduard
Published: July 2021

Non-terrestrial networks (NTN) are expected to play a key role in extending and complementing terrestrial 5G networks in order to provide services to air, sea, and un-served or under-served areas. This paper focuses the attention on the uplink, where terminals are able to establish a direct link with the NTN at Ka-band. To reduce the collision probability when a large population of terminals is transmitting simultaneously, we propose a grant-free access scheme called resource sharing beamforming access (RSBA). We study RBSA for low Earth orbit (LEO) satellite communications with massive multiple-input multiple-output (MIMO). The idea is to benefit from the spatial diversity to decode multiple overlapped signals. We have devised a blind and open-loop beamforming technique, where neither the receiver must carry out brute-force search in azimuth and elevation, nor are the terminals required to report channel state information. Upon deriving the theoretical throughput, we show that RBSA is appropriate for grant-free access to LEO satellite, it reduces the probability of collision, and thus it increases the number of terminals that can access the media. Practical implementation aspects have been tackled, such as the estimation of the required statistics, and the determination of the number of users.
A Low Cost Inkjet-Printed Mass Sensor Using a Frequency Readout Strategy
Authors: Andò Bruno , Baglio Salvatore , Marletta Vincenzo , Crispino Ruben
Published: July 2021

The development of low-cost mass sensors is of unique interest for the scientific community due to the wide range of fields requiring these kind of devices. In this paper, a full inkjet-printed mass sensor is proposed. The device is based on a PolyEthylene Terephthalate (PET) cantilever beam (operating in its first natural frequency) where a strain-sensor and a planar coil have been realized by a low-cost InkJet Printing technology to implement the sensing and actuation strategies, respectively. The frequency readout strategy of the sensor presents several advantages, such as the intrinsic robustness against instabilities of the strain sensor, the residual stress of the cantilever beam, the target mass material, and the distance between the permanent magnet and the actuation coil (which changes as a function of the target mass values). However, the frictionless actuation mode represents another shortcoming of the sensor. The paper describes the sensor design, realization, and characterization while investigating its expected behavior by exploiting dedicate models. The working span of the device is 0–0.36 g while its resolution is in the order of 0.001 g, thus addressing a wide range of potential applications requiring very accurate mass measurements within a narrow operating range.
A Novel Defect Estimation Approach in Wind Turbine Blades Based on Phase Velocity Variation of Ultrasonic Guided Waves
Authors: Raišutis Renaldas , Tiwari Kumar Anubhav , Žukauskas Egidijus , Tumšys Olgirdas , Draudvilienė Lina
Published: July 2021

The reliability of the wind turbine blade (WTB) evaluation using a new criterion is presented in the work. Variation of the ultrasonic guided waves (UGW) phase velocity is proposed to be used as a new criterion for defect detection. Based on an intermediate value between the maximum and minimum values, the calculation of the phase velocity threshold is used for defect detection, location and sizing. The operation of the proposed technique is verified using simulation and experimental studies. The artificially milled defect having a diameter of 81 mm on the segment of WTB is used for verification of the proposed technique. After the application of the proposed evaluation technique for analysis of the simulated B-scan image, the coordinates of defect edges have been estimated with relative errors of 3.7% and 3%, respectively. The size of the defect was estimated with a relative error of 2.7%. In the case of an experimentally measured B-scan image, the coordinates of defect edges have been estimated with relative errors of 12.5% and 3.9%, respectively. The size of the defect was estimated with a relative error of 10%. The comparative results obtained by modelling and experiment show the suitability of the proposed new criterion to be used for the defect detection tasks solving.
Investigation of the Wind-Induced Airflow Pattern Near the Thies LPM Precipitation Gauge
Authors: Chinchella Enrico , Cauteruccio Arianna , Stagnaro Mattia , Lanza Luca G.
Published: July 2021

The airflow velocity pattern generated by a widely used non-catching precipitation gauge (the Thies laser precipitation monitor or LPM) when immersed in a wind field is investigated using computational fluid dynamics (CFD). The simulation numerically solves the unsteady Reynolds-averaged Navier–Stokes (URANS) equations and the setup is validated against dedicated wind tunnel measurements. The adopted k-ω shear stress transport (SST) turbulence model closely reproduces the flow pattern generated by the complex, non-axisymmetric outer geometry of the instrument. The airflow pattern near the measuring area varies with the wind direction, the most intense recirculating flow and turbulence being observed when the wind blows from the back of the instrument. Quantitative parameters are used to discuss the magnitude of the airflow perturbations with respect to the ideal configuration where the instrument is transparent to the wind. The generated airflow pattern is expected to induce some bias in operational measurements, especially in strong wind conditions. The proposed numerical simulation framework provides a basis to develop correction curves for the wind-induced bias of non-catching gauges, as a function of the undisturbed wind speed and direction.
Evaluation of Precise Microwave Ranging Technology for Low Earth Orbit Formation Missions with Beidou Time-Synchronize Receiver
Authors: Wang Xiaoliang , Wu Shufan , Gong Deren , Shen Qiang , Wang Dengfeng , Damaren Christopher
Published: July 2021

In this study, submillimeter level accuracy K-band microwave ranging (MWR) equipment is demonstrated, aiming to verify the detection of the Earth’s gravity field (EGF) and digital elevation models (DEM), through spacecraft formation flying (SFF) in low Earth orbit (LEO). In particular, this paper introduces in detail an integrated BeiDou III B1C/B2a dual frequency receiver we designed and developed, including signal processing scheme, gain allocation, and frequency planning. The receiver matched the 0.1 ns precise synchronize time-frequency benchmark for the MWR system, verified by a static and dynamic test, compared with a time interval counter synchronization solution. Moreover, MWR equipment ranging accuracy is explored in-depth by using different ranging techniques. The test results show that MWR achieved 40 μm and 1.6 μm/s accuracy for ranging and range rate during tests, using synchronous dual one-way ranging (DOWR) microwave phase accumulation frame, and 6 μm/s range rate accuracy obtained through a one-way ranging experiment. The ranging error sources of the whole MWR system in-orbit are analyzed, while the relative orbit dynamic models, for formation scenes, and adaptive Kalman filter algorithms, for SFF relative navigation designs, are introduced. The performance of SFF relative navigation using MWR are tested in a hardware in loop (HIL) simulation system within a high precision six degree of freedom (6-DOF) moving platform. The final estimation error from adaptive relative navigation system using MWR are about 0.42 mm (range/RMS) and 0.87 μm/s (range rate/RMS), which demonstrated the promising accuracy for future applications of EGF and DEM formation missions in space.
A Hybrid Deep Learning-Driven SDN Enabled Mechanism for Secure Communication in Internet of Things (IoT)
Authors: Javeed Danish , Gao Tianhan , Khan Muhammad Taimoor , Ahmad Ijaz
Published: July 2021

The Internet of Things (IoT) has emerged as a new technological world connecting billions of devices. Despite providing several benefits, the heterogeneous nature and the extensive connectivity of the devices make it a target of different cyberattacks that result in data breach and financial loss. There is a severe need to secure the IoT environment from such attacks. In this paper, an SDN-enabled deep-learning-driven framework is proposed for threats detection in an IoT environment. The state-of-the-art Cuda-deep neural network, gated recurrent unit (Cu- DNNGRU), and Cuda-bidirectional long short-term memory (Cu-BLSTM) classifiers are adopted for effective threat detection. We have performed 10 folds cross-validation to show the unbiasedness of results. The up-to-date publicly available CICIDS2018 data set is introduced to train our hybrid model. The achieved accuracy of the proposed scheme is 99.87%, with a recall of 99.96%. Furthermore, we compare the proposed hybrid model with Cuda-Gated Recurrent Unit, Long short term memory (Cu-GRULSTM) and Cuda-Deep Neural Network, Long short term memory (Cu- DNNLSTM), as well as with existing benchmark classifiers. Our proposed mechanism achieves impressive results in terms of accuracy, F1-score, precision, speed efficiency, and other evaluation metrics.
Retrieving Sun-Induced Chlorophyll Fluorescence from Hyperspectral Data with TanSat Satellite
Authors: Li Shilei , Gao Maofang , Li Zhao-Liang
Published: July 2021

A series of algorithms for satellite retrievals of sun-induced chlorophyll fluorescence (SIF) have been developed and applied to different sensors. However, research on SIF retrieval using hyperspectral data is performed in narrow spectral windows, assuming that SIF remains constant. In this paper, based on the singular vector decomposition (SVD) technique, we present an approach for retrieving SIF, which can be applied to remotely sensed data with ultra-high spectral resolution and in a broad spectral window without assuming that the SIF remains constant. The idea is to combine the first singular vector, the pivotal information of the non-fluorescence spectrum, with the low-frequency contribution of the atmosphere, plus a linear combination of the remaining singular vectors to express the non-fluorescence spectrum. Subject to instrument settings, the retrieval was performed within a spectral window of approximately 7 nm that contained only Fraunhofer lines. In our retrieval, hyperspectral data of the O2-A band from the first Chinese carbon dioxide observation satellite (TanSat) was used. The Bayesian Information Criterion (BIC) was introduced to self-adaptively determine the number of free parameters and reduce retrieval noise. SIF retrievals were compared with TanSat SIF and OCO-2 SIF. The results showed good consistency and rationality. A sensitivity analysis was also conducted to verify the performance of this approach. To summarize, the approach would provide more possibilities for retrieving SIF from hyperspectral data.
A Small and High-Speed Driving Mechanism for 3D Shape Measurement in Monocular Endoscopy
Authors: Nakajima Yoshikazu , Tanigaki Nobuyuki , Sugino Takaaki , Kawase Toshihiro , Onogi Shinya
Published: July 2021

Three-dimensional (3D) shape acquisition has been widely introduced to enrich quantitative analysis with the combination of object shape and texture, for example, surface roughness evaluation in industry and gastrointestinal endoscopy in medicine. Shape from focus is a promising technique to measure substance surfaces in 3D space because no occlusion problem appears in principle, as does with stereo shape measurement, which is another commonly used option. We have been developing endoscopic shape measurement devices and shape reconstruction algorithms. In this paper, we propose a mechanism for driving an image sensor reciprocated for the shape from focus of 3D shape measurement in monocular endoscopy. It uses a stepping motor and a planar-end cam, which transforms the motor rotation to imaging sensor reciprocation, to implement the shape from focus of 3D shape measurement in endoscopy. We test and discuss the device in terms of its driving accuracy and application feasibility for endoscopic 3D shape measurement.
Contextualized Filtering for Shared Cyber Threat Information
Authors: Dimitriadis Athanasios , Prassas Christos , Flores Jose Luis , Kulvatunyou Boonserm , Ivezic Nenad , Gritzalis Dimitris A. , Mavridis Ioannis K.
Published: July 2021

Cyber threat information sharing is an imperative process towards achieving collaborative security, but it poses several challenges. One crucial challenge is the plethora of shared threat information. Therefore, there is a need to advance filtering of such information. While the state-of-the-art in filtering relies primarily on keyword- and domain-based searching, these approaches require sizable human involvement and rarely available domain expertise. Recent research revealed the need for harvesting of business information to fill the gap in filtering, albeit it resulted in providing coarse-grained filtering based on the utilization of such information. This paper presents a novel contextualized filtering approach that exploits standardized and multi-level contextual information of business processes. The contextual information describes the conditions under which a given threat information is actionable from an organization perspective. Therefore, it can automate filtering by measuring the equivalence between the context of the shared threat information and the context of the consuming organization. The paper directly contributes to filtering challenge and indirectly to automated customized threat information sharing. Moreover, the paper proposes the architecture of a cyber threat information sharing ecosystem that operates according to the proposed filtering approach and defines the characteristics that are advantageous to filtering approaches. Implementation of the proposed approach can support compliance with the Special Publication 800-150 of the National Institute of Standards and Technology.
Depth Completion and Super-Resolution with Arbitrary Scale Factors for Indoor Scenes
Authors: Truong Anh Minh , Philips Wilfried , Veelaert Peter
Published: July 2021

Depth sensing has improved rapidly in recent years, which allows for structural information to be utilized in various applications, such as virtual reality, scene and object recognition, view synthesis, and 3D reconstruction. Due to the limitations of the current generation of depth sensors, the resolution of depth maps is often still much lower than the resolution of color images. This hinders applications, such as view synthesis or 3D reconstruction, from providing high-quality results. Therefore, super-resolution, which allows for the upscaling of depth maps while still retaining sharpness, has recently drawn much attention in the deep learning community. However, state-of-the-art deep learning methods are typically designed and trained to handle a fixed set of integer-scale factors. Moreover, the raw depth map collected by the depth sensor usually has many depth data missing or misestimated values along the edges and corners of observed objects. In this work, we propose a novel deep learning network for both depth completion and depth super-resolution with arbitrary scale factors. The experimental results on the Middlebury stereo, NYUv2, and Matterport3D datasets demonstrate that the proposed method can outperform state-of-the-art methods.