bluuebunny/crossref_metadata_2025 huggingface dataset:
Inclusion of Sainfoin in the Diet Might Alter Strongyle Infection in Naturally Infected Horses
Authors: Grimm Pauline , Laroche Noémie , Julliand Samy , Sorci Gabriele
Published: April 2022

It is increasingly difficult to control equine strongyles with synthetic drugs, as resistance is commonly observed. Here, we investigated the possible anthelmintic effect of sainfoin (Onobrychis viciifolia), a polyphenol-rich legume, in naturally infected horses. On Day 0 (D0), 17 horses were allocated to three different homogenous groups in terms of fecal egg count (FEC): the control group (CONT) received a diet composed on a DM basis of 83% hay and 17% wheat bran, while in the sainfoin 1 (SF1) and sainfoin 2 (SF2) groups, half or all wheat bran, respectively, was replaced by dehydrated sainfoin pellets. The infection dynamics were monitored by weekly FEC, from D0 to D84. On D28, all horses were treated with fenbendazole. Larval motility was assessed from coprocultures at D0, D28, D56 and D84. Horses in Group SF2 had lower FEC from D7 to D28. After fenbendazole treatment, no effect of the diet was measured on FEC. Both before and after anthelmintic treatment, larvae from horses consuming sainfoin were less motile than larvae from the CONT group. These results suggest that sainfoin has an in vivo anthelmintic activity in naturally infected horses, although this effect appears to be context-dependent.
Precision-Cut Tumor Slices (PCTS) as an Ex Vivo Model in Immunotherapy Research
Authors: Dimou Paraskevi , Trivedi Sumita , Liousia Maria , D'Souza Reena R. , Klampatsa Astero
Published: April 2022

Precision-cut tumor slices (PCTS) have recently emerged as important ex vivo human tumor models, offering the opportunity to study individual patient responses to targeted immunotherapies, including CAR-T cell therapies. In this review, an outline of different human tumor models available in laboratory settings is provided, with a focus on the unique characteristics of PCTS. Standard PCTS generation and maintenance procedures are outlined, followed by an in-depth overview of PCTS utilization in preclinical research aiming to better understand the unique functional characteristics of cytotoxic T cells within human tumors. Furthermore, recent studies using PCTS as an ex vivo model for predicting patient responses to immunotherapies and other targeted therapies against solid tumors are thoroughly presented. Finally, the advantages and limitations of the PCTS models are discussed. PCTS are expected to gain momentum and be fully utilized as a significant tool towards better patient stratification and personalized medicine.
Anti-Caries Effect of a Mouthwash Containing Sambucus williamsii var. coreana Extract: A Randomized, Double-Blind, Placebo-Controlled Clinical Trial
Authors: Kim Yu-Rin , Nam Seoul-Hee
Published: April 2022

This study was performed to verify the clinical effect of a mouthwash containing Sambucus williamsii var. coreana extract on the acid production of oral bacteria and bacteria involved in dental caries. A randomized, double-blind, and placebo-controlled trial was conducted on 66 patients of the following groups: a Sambucus williamsii var. coreana extract gargle group (n = 34) and a saline solution gargle group (n = 32). According to the application time of a mouthwash (before gargle application, immediately after gargle application, and five days after gargle application), we examined the emergence of dental caries-causing bacteria by PCR analysis and changes in the amount of acid production in dental plaque through a Cariview test. As a result of verifying the effect of inhibiting and preventing dental caries in the oral environment, the dental caries-causing bacteria decreased in the Sambucus williamsii var. coreana extract gargle group compared to the saline gargle group. In particular, Streptococcus mutans showed a marked decrease from immediately after application of gargle to 5 days after application. In addition, the mouthwash containing Sambucus williamsii var. coreana extract did not cause acid production and had low dental caries activity. A mouthwash containing Sambucus williamsii var. coreana extract, a natural substance, can be used as an anti-dental caries agent and be commercialized as an effective dental caries prevention agent that is safe for teeth and has an excellent antibacterial effect.
Antibacterial Fractions from Erodium cicutarium Exposed—Clinical Strains of Staphylococcus aureus in Focus
Authors: Ljoljić Bilić Vanja , Gašić Uroš M. , Milojković-Opsenica Dušanka , Rimac Hrvoje , Vuković Rodriguez Jadranka , Vlainić Josipa , Brlek-Gorski Diana , Kosalec Ivan
Published: April 2022

Followed by a buildup of its phytochemical profile, Erodium cicutarium is being subjected to antimicrobial investigation guided with its ethnobotanical use. The results of performed in vitro screening on Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans strains, show that E. cicutarium has antimicrobial activity, with a particular emphasis on clinical S. aureus strains—both the methicillin sensitive (MSSA) and the methicillin resistant (MRSA) S. aureus. Experimental design consisted of general methods (the serial microdilution broth assay and the agar well diffusion assay), as well as observing bactericidal/bacteriostatic activity through time (the “time-kill” assay), investigating the effect on cell wall integrity and biofilm formation, and modulation of bacterial hemolysis. Observed antibacterial activity from above-described methods led to further activity-guided fractionation of water and methanol extracts using bioautography coupled with UHPLC-LTQ OrbiTrap MS4. It was determined that active fractions are predominantly formed by gallic acid derivatives and flavonol glycosides. Among the most active phytochemicals, galloyl-shikimic acid was identified as the most abundant compound. These results point to a direct connection between galloyl-shikimic acid and the observed E. cicutarium antibacterial activity, and open several new research approaches for future investigation.
Induction of Heme Oxygenase-1 by 15d-Prostaglandin J2 Mediated via a ROS-Dependent Sp1 and AP-1 Cascade Suppresses Lipopolysaccharide-Triggered Interleukin-6 Expression in Mouse Brain Microvascular Endothelial Cells
Authors: Yang Chien-Chung , Hsiao Li-Der , Shih Ya-Fang , Chang Ching-I , Yang Chuen-Mao
Published: April 2022

Heme oxygenase-1 (HO-1) has been shown to exert antioxidant, anti-inflammatory, and anti-apoptotic effects in various types of cells. Therefore, the induction of HO-1 is an excellent rationale for the development of protective drugs. 15-Deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2) can modulate the expression of antioxidant defense proteins and be beneficial for neuroinflammation. Brain endothelial cells play an important role in the pathophysiology of brain disorders. Whether 15d-PGJ2 can induce HO-1 expression and protect against the inflammatory responses in mouse brain microvascular endothelial (bEnd.3) cells remains unclear. Here, we reveal that 15d-PGJ2 stimulated HO-1 protein and mRNA expression in a time- and concentration-dependent manner in bEnd.3 cells, which was attenuated by diphenyleneiodonium chloride (DPI) and MitoTempo. Thus, activation of NADPH oxidase (NOX)- and mitochondria-derived reactive oxygen species (ROS) mediated 15d-PGJ2-induced HO-1 expression. ROS generation could cause phosphorylation of protein kinase C (PKC)δ, leading to HO-1 expression, which was suppressed by Rottlerin (selective inhibitor PKCδ), DPI, and MitoTempo. We further demonstrated that phosphorylation of c-Jun N-terminal kinase (JNK)1/2 participated in 15d-PGJ2-upregulated HO-1 expression, which was blocked by SP600125 or Rottlerin. Moreover, 15d-PGJ2-induced HO-1 expression was mediated through the activation of c-Jun (a subunit of activator protein 1 (AP-1)) and specificity protein 1 (Sp1), leading to their interaction with the HO-1 promoter, revealed by chromatin immunoprecipitation assay, which was attenuated by SP600125, Mithramycin A, or Tanshinone II A. We further verified the anti-inflammatory effect of HO-1 expression. Our results showed that 15d-PGJ2-induced HO-1 could mitigate the lipopolysaccharide-triggered interleukin-6 expression and secretion, as measured by an ELISA assay kit. These results suggest that 15d-PGJ2-induced HO-1 expression is mediated through the activation of NOX- and mitochondria-derived ROS-dependent PKCδ/JNK1/2/Sp1 and the AP-1 signaling pathway and protects against inflammatory responses in bEnd.3 cells.
Carnosic Acid and Carnosol Display Antioxidant and Anti-Prion Properties in In Vitro and Cell-Free Models of Prion Diseases
Authors: Karagianni Korina , Pettas Spyros , Kanata Eirini , Lioulia Elisavet , Thune Katrin , Schmitz Matthias , Tsamesidis Ioannis , Lymperaki Evgenia , Xanthopoulos Konstantinos , Sklaviadis Theodoros , Dafou Dimitra
Published: April 2022

Prion diseases are transmissible encephalopathies associated with the conversion of the physiological form of the prion protein (PrPC) to the disease-associated (PrPSc). Despite intense research, no therapeutic or prophylactic agent is available. The catechol-type diterpene Carnosic acid (CA) and its metabolite Carnosol (CS) from Rosmarinus officinalis have well-documented anti-oxidative and neuroprotective effects. Since oxidative stress plays an important role in the pathogenesis of prion diseases, we investigated the potential beneficial role of CA and CS in a cellular model of prion diseases (N2a22L cells) and in a cell-free prion amplification assay (RT-QuIC). The antioxidant effects of the compounds were confirmed when N2a22L were incubated with CA or CS. Furthermore, CA and CS reduced the accumulation of the disease-associated form of PrP, detected by Western Blotting, in N2a22L cells. This effect was validated in RT-QuIC assays, indicating that it is not associated with the antioxidant effects of CA and CS. Importantly, cell-free assays revealed that these natural products not only prevent the formation of PrP aggregates but can also disrupt already formed aggregates. Our results indicate that CA and CS have pleiotropic effects against prion diseases and could evolve into useful prophylactic and/or therapeutic agents against prion and other neurodegenerative diseases.
Dietary Iron Restriction Improves Muscle Function, Dyslipidemia, and Decreased Muscle Oxidative Stress in Streptozotocin-Induced Diabetic Rats
Authors: Vargas-Vargas Manuel Alejandro , Saavedra-Molina Alfredo , Gómez-Barroso Mariana , Peña-Montes Donovan , Cortés-Rojo Christian , Miguel Huerta , Trujillo Xochitl , Montoya-Pérez Rocío
Published: April 2022

Diabetes mellitus is a chronic degenerative disease characterized by hyperglycemia and oxidative stress. Iron catalyzes free radical overproduction. High iron concentrations have previously been reported to promote an increase in oxidative stress; however, the effect of iron restriction in diabetes has not yet been explored, so we tested to see if iron restriction in diabetic rats reduces oxidative damage and improved muscle function. Wistar rats were assigned to 4 groups: Control; Diabetic; Diabetic rats with a high iron diet, and Diabetic with dietary iron restriction. After 8 weeks the rats were sacrificed, the muscles were extracted to prepare homogenates, and serum was obtained for biochemical measurements. Low iron diabetic rats showed an increase in the development of muscle strength in both muscles. Dietary iron restriction decreased triglyceride concentrations compared to the untreated diabetic rats and the levels of extremely low-density lipoproteins. Aggravation of lipid peroxidation was observed in the diabetic group with a high iron diet, while these levels remained low with iron restriction. Iron restriction improved muscle strength development and reduced fatigue times; this was related to better lipid profile control and decreased oxidant stress markers.
The Effect of Vapor Pressure Deficit Regulation on the Growth of Tomato Plants Grown in Different Planting Environments
Authors: Noh Hyemin , Lee Jihyun
Published: April 2022

Vapor pressure deficit (VPD) has been identified as an increasingly important driver of plant functioning, and thus VPD regulation has been widely recognized as having the potential to improve plant growth and productivity. We monitored the trend of the VPD and observed the effect of VPD regulation by irrigating the water using VPD control equipment that automatically inserts fogging water when the VPD exceeds 1.2 kPa. Tomato crops were planted in soil, coconut fiber, and soil above poly vinyl chloride trays to observe the effectiveness of VPD regulation and the planting environment. As a result, there was no significant difference in the effect of VPD regulation on the overall growth stages of tomato crops whether they grew in soil, trays with soil, or trays with coconut fiber. However, in the case of crops grown in a tray with coconut fiber, the initial growth was similar, but the total yield and total commercial yield showed approximately 89% and 88% improvement, respectively. The number of total fruits was also improved by 49% on average.
The Effect of Adding Spices to Green Walnut Tinctures on Their Polyphenolic Profile, Antioxidant Capacity and Action on Renal Cells
Authors: Miłek Michał , Marcinčáková Dana , Kolesárová Mária , Legáthová Diana , Dżugan Małgorzata
Published: April 2022

Green walnuts—unripe fruits of Juglans regia L. are known for their many biological activities and therapeutic potential. Tinctures based on unripe walnuts (samples 1 and 2) and tinctures with the addition of spices (ginger, cloves, bay leaves, juniper fruit: samples 3–6) were tested for polyphenol profile and antioxidant capacity. The effect on a normal monkey kidney epithelial cell line (VERO) was evaluated. For monitoring the changes in cell proliferation, real-time cell analysis (xCELLigence system) was employed and cell viability was measured by the MTS test. All tinctures showed the presence of polyphenols, mainly phenolic acids, flavonoids, and naphthoquinones, and in the sample with cloves, eugenol was found. Addition of spices increased the antioxidant capacity. Tinctures show a dose-dependent cytotoxic effect. The lowest concentrations (125 µg mL−1) of both tinctures without additives (1 and 2) and with bay leaves (4) did not adversely affect (p > 0.05) and even supported cell proliferation (p < 0.05) in comparison to the control cells without treatment. Viability was lower in all cells except for the cells treated with tincture with cloves addition (p > 0.05). It indicates the beneficial effect of cloves enrichment and supports the assumption that the appropriate dosage of tinctures is necessary to be safe for the consumers.
Exploring Early Prediction of Chronic Kidney Disease Using Machine Learning Algorithms for Small and Imbalanced Datasets
Authors: Silveira Andressa C. M. da , Sobrinho Álvaro , Silva Leandro Dias da , Costa Evandro de Barros , Pinheiro Maria Eliete , Perkusich Angelo
Published: April 2022

Chronic kidney disease (CKD) is a worldwide public health problem, usually diagnosed in the late stages of the disease. To alleviate such issue, investment in early prediction is necessary. The purpose of this study is to assist the early prediction of CKD, addressing problems related to imbalanced and limited-size datasets. We used data from medical records of Brazilians with or without a diagnosis of CKD, containing the following attributes: hypertension, diabetes mellitus, creatinine, urea, albuminuria, age, gender, and glomerular filtration rate. We present an oversampling approach based on manual and automated augmentation. We experimented with the synthetic minority oversampling technique (SMOTE), Borderline-SMOTE, and Borderline-SMOTE SVM. We implemented models based on the algorithms: decision tree (DT), random forest, and multi-class AdaBoosted DTs. We also applied the overall local accuracy and local class accuracy methods for dynamic classifier selection; and the k-nearest oracles-union, k-nearest oracles-eliminate, and META-DES for dynamic ensemble selection. We analyzed the models’ performances using the hold-out validation, multiple stratified cross-validation (CV), and nested CV. The DT model presented the highest accuracy score (98.99%) using the manual augmentation and SMOTE. Our approach can assist in designing systems for the early prediction of CKD using imbalanced and limited-size datasets.
Solving a Multi-Class Traffic Assignment Model with Mixed Modes
Authors: Ryu Seungkyu , Kim Minki
Published: April 2022

In comparison to conventional human-driven vehicles (HVs), connected and automated vehicles (CAVs) provide benefits (e.g., reducing travel time and improving safety). However, before the period of fully CAVs appears, there will be a situation in which both HVs and CAVs are present, and the traffic flow pattern may differ from that of a single class (e.g., HV or CAV). In this study, we developed a multi-class traffic assignment problem (TAP) for a transportation network that explicitly considered mixed modes (e.g., HV and CAV). As a link’s travel time is dependent on the degree of mixed flows, each mode required an asymmetric interaction cost function. For TAP, the multi-class user equilibrium (UE) model was used for the route choice model. A route-based variational inequality (VI) formulation was used to represent the multi-class TAP and solve it using the gradient projection (GP) algorithm. It has been demonstrated that the GP algorithm is an effective route-based solution for solving the single-class user equilibrium (UE) problem. However, it has rarely been applied to solving asymmetric UE problems. In this study, the single-class GP algorithm was extended to solve the multi-class TAP. The numerical results indicated the model’s efficacy in capturing the features of the proposed TAP utilizing a set of simple networks and real transportation networks. Additionally, it demonstrated the computational effectiveness of the GP algorithm in solving the multi-class TAP.
Altering the Supply of Shielding Gases to Fabricate Distinct Geometry in GMA Additive Manufacturing
Authors: Silwal Bishal , Pudasaini Niraj , Roy Sougata , Murphy Anthony B. , Nycz Andrzej , Noakes Mark W.
Published: April 2022

Wire arc additive manufacturing (WAAM) is the process by which large, metallic structures are built, layer-by-layer, using a welding arc to melt wire feedstock. In this process, the proper selection of the shielding gas plays a vital role in the achievement of structurally acceptable part geometries and quality surface finishes. In this study, the authors used either a ternary mix (He, Ar and CO2) or a binary mix (Ar and CO2) of shielding gases to deposit wall geometries using an open loop-controlled WAAM system developed at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility. The binary blend produced a wider and shorter geometry, while the ternary blend resulted in a narrower build that was more equivalent to the CAD geometry. The data indicated that the binary blend provided a higher oxygen concentration in the weld as compared to that of the ternary blend. The results imply that the arc characteristics and heat input had a significantly higher impact on the weld penetration than the surface tension effect of surface active elements. This was further verified by developing and applying a high-fidelity computational fluid dynamics (CFD) model of the thermophysical properties of gas mixtures. The results from the model showed that, while the influence of increased oxygen concentration on the surface tension for the binary blend led to a deeper penetration, the ternary blend gave rise to heat flux to the workpiece.
IMPA versus Cloud Analysis and IDA: Different Methods to Evaluate Structural Seismic Fragility
Authors: Contiguglia Carlotta Pia , Pelle Angelo , Briseghella Bruno , Nuti Camillo
Published: April 2022

Well-known methods for seismic performance assessment, such as incremental dynamic analysis (IDA), multi-stripes analysis (MSA) and the cloud method, involve nonlinear response time-history analyses to characterize the relationship between the chosen damage measure versus intensity measure. Over the past two decades, many authors have proposed simplified procedures or nonlinear static approaches to develop fragility. In these procedures, the capacity of the system is evaluated by nonlinear static procedures (i.e., the capacity spectrum method (CSM), the N2 method, modal pushover analysis (MPA)) and the demand is derived by response spectra. In addition to the familiar ones, incremental modal pushover analysis (IMPA) is a novel nonlinear static procedure proposed in recent years, and it is used in this research to present an IM-based fragility estimation. The accuracy and effectiveness of different methods to assess vulnerability are investigated by comparing fragility curves derived by MPA-based cloud analysis, IMPA and cloud analysis against IDA. The comparison gives valuable insights on the influence of scaling on different sets of records; however, a more extended validation is needed to confirm the obtained results and draw more general conclusions. Results arise from two relatively small bins of record motions differing by ranges of Joyner-Boore distance and scattered in a range of magnitude are presented.
Modeling and Simulation of Household Appliances Power Consumption
Authors: Villanueva Daniel , San-Facundo Diego , Miguez-García Edelmiro , Fernández-Otero Antonio
Published: April 2022

The consumption of household appliances tends to increase. Therefore, the application of energy efficiency measurements is urgently needed to reduce the levels of power consumption. Over the last years, various methods have been used to predict household electricity consumption. As a novelty, this paper proposed a method of predicting the consumption of household appliances by evaluating statistical distributions (Kolmogorov–Smirnov Test and Pearson’s X2 test). To test the veracity of the evaluations, first, a set of random values was simulated for each hour, and their respective averages were calculated. These were compared with the averages of the real values for each hour. With the exception of HVAC during working days, great results were obtained. For the refrigerator, the maximum error was 3.91%, while for the lighting, it was 4.27%. At the point of consumption, the accuracy was even higher, with an error of 1.17% for the dryer while for the washing machine and dishwasher, their minimum errors were less than 1%. The error results confirm that the applied methodology is perfectly acceptable for modeling household appliance consumption and consequently predicting it. However, these consumptions can be only extrapolated to dwellings with similar surface areas and habitats.
Blockchain-Based Internet of Things Access Control Technology in Intelligent Manufacturing
Authors: Zhai Peng , He Jingsha , Zhu Nafei
Published: April 2022

The integration of information systems and physical systems is the development trend of today’s manufacturing industry. Intelligent manufacturing is a new model of manufacturing, based on advanced manufacturing technology with human–machine–material collaboration. Internet of Things technology is the core technology of intelligent manufacturing, and access control technology is one of the main measures to ensure the security of the IoT. In view of the problem that the existing IoT access control model does not support distributed and fine-grained dynamic access control, this paper uses the characteristics of blockchain, such as decentralization and non-tampering, combined with the attribute-based access control (ABAC) method, to propose a distributed access control method, applicable to the IoT environment in the process of intelligent manufacturing. This paper describes a fine-grained access control policy by defining the access control attribute values in a formal language, which supports complex logic operations in the policy and enhances the expressiveness of the model. Distributed access control decision making, using smart contracts for blockchain, improves the decision-making efficiency of the access control model, increases the post-facto audit of the access control behavior, and improves the overall security of IoT data protection. The paper concludes with proof of security and a performance analysis, and the experimental results, such as storage and computing overheads, show that this method can provide fine-grained, dynamic, and distributed access control for devices in intelligent manufacturing, ensuring the security and reliability of access control for IoT devices.
Blade Shape Optimization and Analysis of a Propeller for VTOL Based on an Inverse Method
Authors: Xia Xinglu , Ma Dongli , Zhang Liang , Liu Xing’an , Cong Keran
Published: April 2022

With the rapid development of vertical takeoff and landing (VTOL) aircraft, the blade design of a propeller suitable for VTOL aircraft with a wide range of operating conditions has become a challenging and popular task. This paper proposes a multi-objective optimization framework for a VTOL propeller using an inverse design method at the cruising stage, which is developed from the Betz optimum theory and blade element momentum theory (BEMT). Different from passing studies, the maximum thrust-to-weight ratio at hover (MTWRH) is taken as one of the two objectives in this paper, which is closely related to the wind-resistance capability and maneuverability during takeoff and landing. The other objective is the energy consumption of the whole mission profile. A fixed pitch propeller (FPP) and a variable pitch propeller (VPP) are both optimized using the proposed framework for the Vahana A3 tilt-wing aircraft and validated by the computational fluid dynamics (CFD) method. The influences of the level flight energy ratio, hover disk loading and cruising speed toward the optimization result are analyzed, respectively. The results show that the MTWRH has a significant impact on the optimization result both for the FPP and VPP. A comparison between the two propeller forms validates the advantages of the VPP both in energy saving and takeoff maneuverability. The quantitative rules of this advantage with the level flight energy ratio are calculated to provide a reference for choosing the appropriate form. Overall, the methodology and general rules presented in this paper support the propeller optimization and form selection for VTOL aircraft.
Performance-Driven Yield Optimization of High-Frequency Structures by Kriging Surrogates
Authors: Koziel Slawomir , Pietrenko-Dabrowska Anna
Published: April 2022

Uncertainty quantification is an important aspect of engineering design, as manufacturing tolerances may affect the characteristics of the structure. Therefore, the quantification of these effects is indispensable for an adequate assessment of design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated with EM-driven statistical analysis often turn out to be unendurable. Recently, a performance-driven modeling technique has been proposed that may be employed for uncertainty quantification purposes and can enable circumventing the aforementioned difficulties. Capitalizing on this idea, this paper discusses a procedure for fast and simple surrogate-based yield optimization of high-frequency structures. The main concept of the approach is a tailored definition of the surrogate domain, which is based on a couple of pre-optimized designs that reflect the directions featuring maximum variability of the circuit responses with respect to its dimensions. A compact size of such a domain allows for the construction of an accurate metamodel therein using moderate numbers of training samples, and subsequently, it is employyed to enhance the yield. The implementation details are dedicated to a particular type of device. Results obtained for a ring-slot antenna and a miniaturized rat-race coupler imply that the cost of yield optimization process can be reduced to few dozens of EM analyses.
Theoretical Investigation for Angle Measurement Based on Femtosecond Maker Fringe
Authors: Li Kuangyi , Astuti Wijayanti Dwi , Sato Ryo , Matsukuma Hiraku , Gao Wei
Published: April 2022

This paper proposes to utilize a femtosecond Maker fringe for angular measurement to expand the measurement range by using the characteristic of the multiple visible peaks in the Maker fringe. Four different z-cut nonlinear materials and three different polarization combinations of SHG were considered in the study, and various theoretical results are calculated for both the intensity-based angle measurement and the frequency-domain angle measurement. As a result, the p-s polarization shows a significant angle dependence in the range of ±20° compared with the other polarization. In addition, the BBO and KDP are superior to the other investigated materials because of the relatively higher sensitivity and visibility. The refractive index difference was introduced in this paper, and it was applied to explain the angle measurement performance of the Maker fringe successfully.
Comparison of the Biological Properties of Plasma-Treated Solution and Solution of Chemical Reagents
Authors: Pavlik Tatyana Ivanovna , Gusein-zade Namik Guseynaga-ogly , Kolik Leonid Viktorovich , Shimanovskii Nikolay L’vovich
Published: April 2022

Presently, plasma-treated solutions (PTS) are widely introduced into medicine. Plasma-activated solutions contain various reactive forms of oxygen and nitrogen which provide the desired biological effects. Yet it remains unclear exactly which components of the treated solution are the most important and what the difference is between the plasma-treated solution and a chemically prepared solution composed of the same components. In this work, we show that the chemically prepared mixture of nitrites, nitrates, and hydrogen peroxide with concentrations similar to the plasma-treated solution exerts a fundamentally different effect on a cell culture. The chemically prepared solution has higher cyto- and genotoxicity and causes necrosis, while under the action of the plasma-treated solution, apoptotic processes develop in the cells slowly.
Characterization in Relevant Icing Conditions of Two Superhydrophobic Coatings
Authors: Piscitelli Filomena
Published: April 2022

The formation of ice can be very detrimental to flight safety, since the ice accumulated on the surfaces of the aircraft can alter both the aerodynamics and the weight, leading in some cases to catastrophic stall situations. To date, only active Ice Protection Systems (IPS), which require energy to work, are being employed. The use of passive coatings able to prevent, delay, or reduce ice accretion in real flight icing conditions can be viewed as a valuable instrument to reduce the environmental footprint of aircraft. The majority of work in the literature focuses on testing superhydrophobic coatings at a speed equal to or lower than 50 m/s or rather in combination with an active system. The present study was aimed at understanding the effectiveness of two superhydrophobic coatings applied on two NACA0015 wing profiles in reducing the ice formation in relevant flight icing conditions, through tests carried out in an Icing Wind Tunnel at 50 and 95 m/s and at temperatures ranging between −3 and −23 °C. Results demonstrated that at temperatures higher than −12 °C, at both 50 and 95 m/s, with exposure time ranging between 72 and 137 s, the developed coatings can be helpful in reducing the ice accretion by 12 to 100%.
The Quantification of Salivary Flow and pH and Stomatognathic System Rehabilitation Interference in Patients with Oral Diseases, Post-Radiotherapy
Authors: Bulancea Bogdan Petru , Checherita Laura Elisabeta , Foia Georgeta Liliana , Stamatin Ovidiu , Teslaru Silvia , Lupu Iulian Costin , Ciobanu Delia Gabriela , Cernei Eduard-Radu , Carmen Grierosu , Postolache Mariana , Froicu Eliza Maria , Halitchi Liliana Gabriela , Aminov Liana
Published: April 2022

Xerostomia is a common complication post-radiotherapy in patients with oral cancer. The acute and long-term side effects can considerably reduce the patient’s quality of life. The aim of our study was to perform analysis of salivary flow and pH in patients after radiotherapy. Methodology: Clinical and laboratory evaluations were conducted in the 2014–2019 period; out of a total 58 subjects aged between 45 and 84, 28 individuals with oral cancer were selected from St. Spiridon Hospital, Clinic of Maxillo-facial Surgery and Oncology Hospital, Iasi post-radiotherapy. Results: Significant downsized mean values of the hydrogen ion concentration (pH) in saliva (p < 0.001) were recorded in patients after radiotherapy, pH value = 4.580 (±1.051). The mean value of resting salivary flow (MRSF) was significantly lower for the group of patients with radiotherapy (MRSF) = 0.145 mL/min. In 89.29% of cases (25 post-radiotherapy cases), in order to perform oral complex rehabilitation treatment, several endodontic and periodontal treatments were performed. A total of 78.57% of the cases received complex oral rehabilitation as mobile or hybrid prostheses or fixed solutions. Conclusion: Understanding post-radiotherapy salivary biochemic modifications in patients with oral cancer could be of critical importance, in view of related oral disorder prevention.
Deep Learning Applied to Chest Radiograph Classification—A COVID-19 Pneumonia Experience
Authors: Furtado Adhvan , Andrade Leandro , Frias Diego , Maia Thiago , Badaró Roberto , Nascimento Erick G. Sperandio
Published: April 2022

Due to the recent COVID-19 pandemic, a large number of reports present deep learning algorithms that support the detection of pneumonia caused by COVID-19 in chest radiographs. Few studies have provided the complete source code, limiting testing and reproducibility on different datasets. This work presents Cimatec_XCOV19, a novel deep learning system inspired by the Inception-V3 architecture that is able to (i) support the identification of abnormal chest radiographs and (ii) classify the abnormal radiographs as suggestive of COVID-19. The training dataset has 44,031 images with 2917 COVID-19 cases, one of the largest datasets in recent literature. We organized and published an external validation dataset of 1158 chest radiographs from a Brazilian hospital. Two experienced radiologists independently evaluated the radiographs. The Cimatec_XCOV19 algorithm obtained a sensitivity of 0.85, specificity of 0.82, and AUC ROC of 0.93. We compared the AUC ROC of our algorithm with a well-known public solution and did not find a statistically relevant difference between both performances. We provide full access to the code and the test dataset, enabling this work to be used as a tool for supporting the fast screening of COVID-19 on chest X-ray exams, serving as a reference for educators, and supporting further algorithm enhancements.
Improving a PGNAA Technique to Detect Heavy Metals in Solid Samples
Authors: AlMisned Ghada , Al-Abdullah Tariq , Liadi Fatai , Hawsawi Adil
Published: April 2022

Prompt gamma-ray neutron activation analysis (PGNAA) is a useful approach for determining the concentrations of a variety of elements in natural materials, either online or in situ, without affecting their chemical forms in matter. The current research aimed to improve the yield of a portable PGNAA setup using a dc beam of 2.5 MeV neutrons and a CeBr3 detector to record gamma rays from neutron inelastic scatterings. It is impossible to avoid the superimposition of heavy metal gamma rays and those from the detector’s element. However, tests were carried out to improve the signal-to-background ratio. By assessing the minimum detectable concentrations (MDC) of chrome, titanium, and zinc in soil samples, the effectiveness of the new optimization was confirmed. The study shows an improvement in the MDC values.
What Does the Ideal Built-In Car Navigation System Look Like?—An Investigation in the Central European Region
Authors: Vörös Fanni , Gartner Georg , Peterson Michael P. , Kovács Béla
Published: April 2022

Driving is based on effective navigation. When using a navigation device, the user interface, the amount and quality of the underlying data and its representation all effect the quality of navigation. This study evaluates whether drivers in three different countries consider these devices to be useful and what functionality they would prefer. An online questionnaire was used to assess built-in navigation systems. The findings from 213 respondents show that current car GPSs are overloaded with features. Regardless of country, drivers simply require more basic functionality in the interface. It was also noted that the embedded functions in these devices are not fully utilized. In addition, many people use the navigation service to enter a new address while the car is moving. It may be worth examining how this option can be better implemented.
Machine-Learning Approach to Determine Surface Quality on a Reactor Pressure Vessel (RPV) Steel
Authors: Griffin James M. , Mathew Jino , Gasparics Antal , Vértesy Gábor , Uytdenhouwen Inge , Chaouadi Rachid , Fitzpatrick Michael E.
Published: April 2022

Surface quality measures such as roughness, and especially its uncertain character, affect most magnetic non-destructive testing methods and limits their performance in terms of an achievable signal-to-noise ratio and reliability. This paper is primarily focused on an experimental study targeting nuclear reactor materials manufactured from the milling process with various machining parameters to produce varying surface quality conditions to mimic the varying material surface qualities of in-field conditions. From energising a local area electromagnetically, a receiver coil is used to obtain the emitted Barkhausen noise, from which the condition of the material surface can be inspected. Investigations were carried out with the support of machine-learning algorithms, such as Neural Networks (NN) and Classification and Regression Trees (CART), to identify the differences in surface quality. Another challenge often faced is undertaking an analysis with limited experimental data. Other non-destructive methods such as Magnetic Adaptive Testing (MAT) were used to provide data imputation for missing data using other intelligent algorithms. For data reinforcement, data augmentation was used. With more data the problem of ‘the curse of data dimensionality’ is addressed. It demonstrated how both data imputation and augmentation can improve measurement datasets.
Using the ISM Method to Analyze the Relationships between Various Contractor Prequalification Criteria
Authors: Yu Vincent F. , Chiang Fu-Yuan , Le Thi Huynh Anh , Lin Shih-Wei
Published: April 2022

Construction contractors significantly contribute to the progress and success of projects. Contractor prequalification grants tendering rights only to competent contractors. The bidding process is one of the most critical phases in the construction industry. The project leader must assess the general, technical, and financial information of the contractors to prepare an accurate proposal and select the best contractor. In this study, contractor prequalification is considered, along with the complex relationships between various criteria. ISM is a computational method that involves a qualitative and interpretive approach to solving complex problems based on structural mapping of the connections between attributes and their subsequent transformation into a multilevel structural model. Using ISM, we establish a seven-level hierarchy for various contractor prequalification criteria, which are then grouped into four clusters based on their driving power and dependence power. The result of this study shows that ISM can be used to rank complex contractor prequalification criteria and help managers select a qualified contractor in the construction project bidding process during the strategic planning phase.
Distributed Asymmetric Virtual Reality in Industrial Context: Enhancing the Collaboration of Geographically Dispersed Teams in the Pipeline of Maintenance Method Development and Technical Documentation Creation
Authors: Burova Alisa , Palma Paulina Becerril , Truong Phong , Mäkelä John , Heinonen Hanna , Hakulinen Jaakko , Ronkainen Kimmo , Raisamo Roope , Turunen Markku , Siltanen Sanni
Published: April 2022

Virtual Reality (VR) is a critical emerging technology in industrial contexts, as it facilitates collaboration and supports the product development lifecycle. However, its broad adoption is constrained by complex and high-cost integration. The use of VR among devices with various immersion and control levels may solve this obstacle, and increase the scalability of VR technologies. This article presents a case study on applying asymmetry between the COVE-VR platform and Microsoft Teams to enable distributed collaboration of multinational departments and enhance the maintenance method and documentation creation processes. Overall, five remote collaborative sessions were held with 20 experts from four countries. Our findings suggest that asymmetry between head-mounted display and Teams users enhances the quality of communication among geographically dispersed teams and their spatial understanding, which positively influences knowledge transfer and efficiency of industrial processes. Based on qualitative evaluation of the asymmetric VR setup, we further suggest a list of guidelines on how to enhance the collaboration efficiency for low-cost distributed asymmetric VR from three perspectives: organization, collaboration and technology.
Research on Equivalent Static Load of High-Rise/Towering Structures Based on Wind-Induced Responses
Authors: Yang Junhui , Zhang Junfeng , Li Chao
Published: April 2022

A method of assessing equivalent static wind loads that can represent all the real ultimate states of a high-rise building and towering structure has still not been fully determined in wind engineering. Based on random vibration theory, the wind-induced response and equivalent static wind loading of high-rise buildings and towering structures are investigated using the vibration decomposition method. Firstly, the structural wind-induced mean response, background response, resonant response and background and resonant coupled response are studied in the time and frequency domains. Secondly, a new gust load factor (GLF) assessment method suitable for wind-induced displacement, bending moment and shear force response at any height of the structure is proposed, and a typical high-rise building is used as an example for comparison with the previous research results, in order to verify the effectiveness of the method in this paper. The results show the following: for high-rise buildings and towering structures, the percentage of the coupled components in the total pulsation response is less than 2%, and the influence can be ignored; the GLF based on bending moment (MGLF) and the GLF based on shear force (QGLF) increase significantly with height, and the traditional GLF methods underestimate the maximum wind effects.
Comparison of Multilayer Neural Network Models in Terms of Success of Classifications Based on EmguCV, ML.NET and Tensorflow.Net
Authors: Magdin Martin , Benc Juraj , Koprda Štefan , Balogh Zoltán , Tuček Daniel
Published: April 2022

In this paper, we compare three different models of multilayer neural networks in terms of their success in the classification phase. These models were designed for EmguCV, ML.NET and Tensorflow.Net libraries, which are currently among the most widely used libraries in the implementation of an automatic recognition system. Using the EmguCV library, we achieved a success rate in the classification of human faces of 81.95% and with ML.NET, which was based on the pre-trained ResNet50 model using convolution layers, up to 91.15% accuracy. The result of the success of the classification process was influenced by the time required for training and also the time required for the classification itself. The Tensorflow.Net model did not show sufficient classification ability when classifying using vector distances; the highest success rate of classification was only 13.31%. Neural networks were trained on a dataset with 1454 photographs of faces involving 43 people. At a time when neural networks are becoming more and more used for applications of different natures, it is necessary to choose the right model in the classification process that will be able to achieve the required accuracy with the minimum time required for training. The application created by us allows the insertion of images and the creation of their own datasets, on the basis of which the user can train a model with its own parameters. Models can then be saved and integrated into other applications.
Non-Plaque Induced Diffuse Gingival Overgrowth: An Overview
Authors: De Falco Domenico , Della Vella Fedora , Scivetti Michele , Suriano Carmela , De Benedittis Michele , Petruzzi Massimo
Published: April 2022

Non-plaque induced diffuse gingival overgrowth represents a broad class of conditions caused by several etiological factors. The aim of this review is to highlight the most recent updates and classifications of all the existent gingival overgrowths. In addition, we highlighted the diagnostic pathway that should be employed in patients affected by gingival overgrowth. Gingival overgrowth can be related to syndromic diseases including a wide spectrum of genetic and chromosomal alterations. However, thanks to scientific sharing and the availability of genetic panels it is possible to obtain an accurate phenotypic identification of well-known syndromes and also to identify new ones. This narrative review shows that through rigid, strict diagnostic protocols, the work of the clinician is greatly facilitated, despite the wide variety of pathologies considered. In conclusion, the exchange of specialists’ competencies and the multidisciplinary management of these patients, are crucial to reach diagnosis and the correct clinical-therapeutic management.
Towards an Extensive Thumb Assist: A Comparison between Whole-Finger and Modular Types of Soft Pneumatic Actuators
Authors: Wang Yuanyuan , Kokubu Shota , Huang Shaoying , Hsueh Ya-Hsin , Yu Wenwei
Published: April 2022

Soft pneumatic actuators used in robotic rehabilitation gloves are classified into two types: whole-finger actuators with air chambers that cover the entire finger and modular actuators with chambers only above the finger joints. Most existing prototypes provide enough finger flexion support, but insufficient independent thumb abduction or opposition support. Even the latest modular soft actuator realized thumb abduction with a sacrifice of range of motion (RoM). Moreover, the advantages and disadvantages of using the two types of soft actuators for thumb assistance have not been made clear. Without an efficient thumb assist, patients’ options for hand function rehabilitation are very limited. Therefore, the objective of this study was to design a modular actuator (M-ACT) that could support multiple degrees of freedom, compare it with a whole-finger type of thumb actuator with three inner chambers (3C-ACT) in terms of the RoM, force output of thumb flexion, and abduction, and use an enhanced Kapandji test to measure both the kinematic aspect of the thumb (Kapandji score) and thumb-tip pinch force. Our results indicated superior single-DoF support capability of the M-ACT and superior multi-DoF support capability of the 3C-ACT. The use of the 3C-ACT as the thumb actuator and the M-ACT as the four-finger actuator may be the optimal solution for the soft robotic glove. This study will aid in the progression of soft robotic gloves for hand rehabilitation towards real rehabilitation practice.