bluuebunny/crossref_metadata_2025 huggingface dataset:
Local Anesthesia in Piglets Undergoing Castration—A Comparative Study to Investigate the Analgesic Effects of Four Local Anesthetics Based on Defensive Behavior and Side Effects
Authors: Abendschön Nora , Senf Steffanie , Deffner Pauline , Miller Regina , Grott Andrea , Werner Julia , Saller Anna M. , Reiser Judith , Weiß Christine , Zablotski Yury , Fischer Johannes , Bergmann Shana , Erhard Michael H. , Baumgartner Christine , Ritzmann Mathias , Zöls Susanne
Published: September 2020

The aim of the present study was to investigate the effect of four local anesthetics on pain relief during surgical castration under standardized conditions in conscious piglets. Therefore, 71 male piglets (three to seven days) were distributed into control groups (handling, castration without anesthesia or analgesia) and local anesthetic trial groups (procaine, lidocaine, bupivacaine, mepivacaine). Then, 20 min prior to castration, animals of the treatment groups, except piglets in the handling group, received an injection of a local anesthetic or sodium chloride of 0.5 mL intratesticularly and 0.5 mL subscrotally. During injection and castration, defensive behavior was evaluated. Locomotor activity, as well as postoperative bleeding, wound healing and average daily weight gain were assessed to detect side effects. The injection caused increased defensive movements, significantly in the bupivacaine group. Lidocaine and mepivacaine significantly reduced defensive movements during castration, and procaine and bupivacaine only during severing of the spermatic cord. Impairments of locomotor activity were found in piglets injected with lidocaine, bupivacaine or sodium chloride. Considering healing, bleeding and weight gain, no negative impacts were observed. In conclusion, lidocaine and mepivacaine were able to achieve significant pain relief during the castration procedure, whereas procaine and bupivacaine only during the severing of the spermatic cord. Moreover, the injection of bupivacaine seemed to be painful itself.
Remedying Contact Dermatitis in Broiler Chickens with Novel Flooring Treatments
Authors: Freeman Nathan , Tuyttens Frank A. M. , Johnson Alexa , Marshall Victoria , Garmyn An , Jacobs Leonie
Published: September 2020

Contact dermatitis (footpad dermatitis (FPD), hock burns, and breast dermatitis) is a welfare issue for broiler chickens, causing pain and behavioral restrictions. Once lesions develop, often nothing is done to remedy the issue for the affected flock. Our objective was to evaluate novel flooring treatments at the flock level by providing preventative and remedial treatments against contact dermatitis, plumage soiling, and gait impairment. Broilers (n = 546) were housed in 42 pens, with 13 birds/pen. The flooring treatments (four) included used litter (NEG), new pine shavings replaced regularly (POS), a mat filled with 1% povidone-iodine solution (MAT), and the iodine mat placed on a slatted floor (SLAT). Flooring treatments were provided from day one of age (preventative approach; PREV) or day 29 (remedial approach; REM). Contact dermatitis, soiling, gait, and weight were recorded weekly (seven birds/pen). Results showed a treatment effect for all measures, dependent on bird age. Overall, the POS treatment resulted in the best welfare outcomes (FPD, hock burns, and gait). The worst contact dermatitis was found in the MAT and SLAT groups. NEG birds showed little contact dermatitis, opposite to expectations. Weights were lower for PREV-POS in week seven only. The treatments with povidone-iodine were deemed ineffective against contact dermatitis. Access to clean litter prevented and remedied contact dermatitis, and a comparable approach may be commercially feasible.
Antibiotic Consumption Patterns in European Countries May Be Associated with the Incidence of Major Carcinomas
Authors: Ternák Gábor , Berényi Károly , Sümegi András , Szenczi Ágnes , Fodor Barbara , Németh Balázs , Kiss István
Published: September 2020

The possible role of the altered intestinal microbiome in the development of malignancies has been raised recently in several publications. Among external factors, antibiotics are considered to be the most important agent capable of producing dysbiosis in the gut flora, either temporally or permanently. The human microbiome has several beneficial effects in terms of maintaining appropriate human health, but its alteration has been implicated in the development of many illnesses. Our basic aim was to explore a possible relationship between the consumption of different antibiotic classes and the incidence of the most common cancer types (male, female) in European countries. A database of the average, yearly antibiotic consumption (1997–2018) has been developed and the consumption figures were compared to the eight, most frequent cancer incidence calculated for 2018 in 30 European countries. Pearson correlation has indicated different degrees of positive (supportive) and negative (inhibitor) significant associations between antibiotic consumption figures and cancer prevalence. It has been observed that certain antibiotic classes with positive correlation probably augment the incidence of certain cancer types, while others, with negative correlation, may show some inhibitory effect. The relatively higher or lower consumption pattern of different classes of antibiotics could be related to certain cancer prevalence figures in different European countries. Our results indicated that countries with relatively high consumption of narrow-spectrum penicillin (J01CE, J01CF) and tetracycline (J01A), like certain Scandinavian countries, showed a higher incidence of female colorectal cancer, female lung cancer, melanoma, breast, prostate and uterus corpus cancer. Countries with relatively higher consumption of broad-spectrum penicillin (J01CA, J01CR) and some broad-spectrum antibiotics (J01D, J01F, J01M), like Greece, Hungary, Slovakia, France, etc. showed a higher incidence rate of male lung cancer and male bladder cancer. The higher incidence rate of different cancer types showed association with the higher consumption of antibiotics with “augmenting” properties and with less consumption of antibiotics with “inhibitory” properties.
The Prevalence of Multidrug Resistance of Helicobacter pylori and Its Impact on Eradication in Korea from 2017 to 2019: A Single-Center Study
Authors: Park Jae Yong , Shin Tae-Seop , Kim Ji Hyun , Yoon Hong Jip , Kim Beom Jin , Kim Jae Gyu
Published: September 2020

Antimicrobial resistance is one of the major factors determining the efficacy of Helicobacter pylori eradication therapy. This study aimed to estimate the recent prevalence of multidrug resistance of H. pylori and its impact on eradication in Korea. A total of 174 patients were prospectively enrolled at Chung-Ang University Hospital from 2017 to 2019. H. pylori strains were isolated from the gastric body and antrum. The minimum inhibitory concentrations of antibiotics were determined by the serial twofold agar dilution method. Eradication results were reviewed and analyzed in connection with antibiotic resistance. The prevalence of H. pylori infection was 51.7% (90/174). The culture success rate was 77.8% (70/90). The resistance rates for clarithromycin, metronidazole, amoxicillin, tetracycline, levofloxacin, and moxifloxacin were 28.6% (20/70), 27.1% (19/70), 20.0% (14/70), 18.6% (13/70), 42.9% (30/70), and 42.9% (30/70), respectively. The multidrug resistance (resistance to two or more classes of antimicrobials) rate was 42.9% (30/70). Dual resistance to clarithromycin and metronidazole was confirmed in 8.6% (6/70). Eradication with a first-line treatment was successful in 75% (36/48), and those who received second-line treatment all achieved successful eradication. The rate of multidrug resistance is increasing, and standard triple therapy (STT) is no longer an acceptable first-line option for H. pylori eradication in Korea.
Synthesis of 4,4′-(4-Formyl-1H-pyrazole-1,3-diyl)dibenzoic Acid Derivatives as Narrow Spectrum Antibiotics for the Potential Treatment of Acinetobacter Baumannii Infections
Authors: Delancey Evan , Allison Devin , KC Hansa Raj , Gilmore David F. , Fite Todd , Basnakian Alexei G. , Alam Mohammad A.
Published: September 2020

Acinetobacter baumannii has emerged as one of the most lethal drug-resistant bacteria in recent years. We report the synthesis and antimicrobial studies of 25 new pyrazole-derived hydrazones. Some of these molecules are potent and specific inhibitors of A. baumannii strains with a minimum inhibitory concentration (MIC) value as low as 0.78 µg/mL. These compounds are non-toxic to mammalian cell lines in in vitro studies. Furthermore, one of the potent molecules has been studied for possible in vivo toxicity in the mouse model and found to be non-toxic based on the effect on 14 physiological blood markers of organ injury.
Uterine Dysfunction in Diabetic Mice: The Role of Hydrogen Sulfide
Authors: Mitidieri Emma , Vanacore Domenico , Turnaturi Carlotta , Sorrentino Raffaella , d’Emmanuele di Villa Bianca Roberta
Published: September 2020

It is well-known that the physiological uterine peristalsis, related to several phases of reproductive functions, plays a pivotal role in fertility and female reproductive health. Here, we have addressed the role of hydrogen sulfide (H2S) signaling in changes of uterine contractions driven by diabetes in non-obese diabetic (NOD) mice, a murine model of type-1 diabetes mellitus. The isolated uterus of NOD mice showed a significant reduction in spontaneous motility coupled to a generalized hypo-contractility to uterotonic agents. The levels of cyclic nucleotides, cAMP and cGMP, notoriously involved in the regulation of uterus homeostasis, were significantly elevated in NOD mouse uteri. This increase was well-correlated with the higher levels of H2S, a non-specific endogenous inhibitor of phosphodiesterases. The exposure of isolated uterus to L-cysteine (L-Cys), but not to sodium hydrogen sulfide, the exogenous source of H2S, showed a weak tocolytic effect in the uterus of NOD mice. Western blot analysis revealed a reorganization of the enzymatic expression with an upregulation of 3-mercaptopyruvate-sulfurtransferase (3-MST) coupled to a reduction in both cystathionine-β-synthase (CBS) and cystathionine-γ-lyase (CSE) expression. In conclusion, the increased levels of cyclic nucleotides dysregulate the uterus peristalsis and contractility in diabetic mice through an increase in basal H2S synthesis suggesting a role of 3-MST.
Memory-Enhancing Effects of Origanum majorana Essential Oil in an Alzheimer’s Amyloid beta1-42 Rat Model: A Molecular and Behavioral Study
Authors: Postu Paula Alexandra , Gorgan Dragos Lucian , Cioanca Oana , Russ Manuela , Mikkat Stefan , Glocker Michael Otto , Hritcu Lucian
Published: September 2020

Origanum L. (Lamiaceae) is an important genus of medicinal and aromatic plants used in traditional medicine since ancient times as culinary herbs and remedies. The aim of the present study was to evaluate the chemical composition, as well as the biochemical and cellular activities of freshly prepared Origanum majorana L. essential oil (OmEO) in an Alzheimer’s disease (AD) amyloid beta1-42 (Aβ1-42) rat model. OmEO (1% and 3%) was inhaled for 21 consecutive days, while Aβ1-42 was administered intracerebroventricularly to induce AD-like symptoms. Our data demonstrate that OmEO increased antioxidant activity and enhanced brain-derived neurotrophic factor (BDNF) expression, which in concert contributed to the improvement of cognitive function of animals. Moreover, OmEO presented beneficial effects on memory performance in Y-maze and radial arm-maze tests in the Aβ1-42 rat AD model.
Improved Saccharomyces cerevisiae Strain in Pure and Sequential Fermentation with Torulaspora delbrueckii for the Production of Verdicchio Wine with Reduced Sulfites
Authors: Agarbati Alice , Canonico Laura , Comitini Francesca , Ciani Maurizio
Published: September 2020

The application of yeast strains that are low producers of sulfur compounds is actually required by winemakers for the production of organic wine. This purpose could be satisfied using a native Saccharomyces cerevisiae strain improved for oenological aptitudes. Moreover, to improve the aromatic complexity of wines, sequential fermentations carried out with S. cerevisiae/non-Saccharomyces yeast is widely used. For these reasons, in the present work an improved native S. cerevisiae low producer of sulfite and sulfide compounds was evaluated in pure and in sequential fermentation with a selected Torulaspora delbrueckii. Additionally, the influence of grape juices coming from three different vintages under winery conditions was evaluated. In pure fermentation, improved native S. cerevisiae strain exhibited a behavior related to vintage, highlighting that the composition of grape juice affects the fermentation process. In particular, an increase in ethyl octanoate (vintage 2017) and phenyl ethyl acetate (vintage 2018) was detected. Moreover, isoamyl acetate was highly consistent and could be a distinctive aroma of the strain. The sequential fermentation T. delbrueckii/S. cerevisiae determined an increase in aroma compounds such as phenyl ethyl acetate and ethyl hexanoate. In this way, it was possible to produce Verdicchio wine with reduced sulfites and characterized by a peculiar aromatic taste.
Hybrid Fuzzy Regression Analysis Using the F-Transform
Authors: Jung Hye-Young , Lee Woo-Joo , Choi Seung Hoe
Published: September 2020

This paper proposes a hybrid estimation algorithm for independently estimating the response function for the center and the response function for the spread in fuzzy regression model. The proposed algorithm combines the least absolute deviations estimation with discriminant analysis. In addition, the F-transform is used to convert spreads of the dependent variable into several groups. Two examples show that our method is superior to the existing methods based on the fuzzy regression model that assumes the same function for spread and center.
Structural Analysis and Design of Reinforced Concrete Bridge Corbels
Authors: Cattaneo Sara , Crespi Pietro , Biolzi Luigi
Published: September 2020

Post-installed systems for the anchorage of safety barriers to bridge corbels are widely used today thanks to their flexibility and easiness of installation. Because of commonly found in situ boundary constraints, however, the design requirements for post-installed fasteners and rebars are frequently not satisfied or only partially satisfied. This paper assesses the mechanical response of a corbel where an innovative solution concerning the placement of post-installed reinforcement in reinforced concrete members was suggested. With reference to the refurbishment of bridge curbs, which usually requires concrete removal in the damaged top layers, the proposed method was based on the introduction of additional U-shaped post-installed rebars connecting the existing portion of the corbel to the newly cast top layer, in order to allow the transfer of the tension pull-out force exerted by the posts restraining the safety barrier. The layout investigated in this paper consisted of three anchors connecting the baseplate of the post supporting the safety barrier to the corbel (a layout commonly found in Italy). These anchors transfer the external actions (bending moment and shear) to the corbel thanks to the formation of a strut-and-tie system where the U-shaped rebars and the existing reinforcement play a crucial role. A strut-and-tie model of the corbel was presented to allow the use of a simplified approach to assess the safety of the corbel. The tests on real-scale specimens were also modeled numerically and additional models were considered to evaluate the effect of characteristics parameters (i.e., size of the corbel, existing shear reinforcement, etc.) on the overall response of the corbel.
The Analysis of Shape Features for the Purpose of Exercise Types Classification Using Silhouette Sequences
Authors: Gościewska Katarzyna , Frejlichowski Dariusz
Published: September 2020

This paper presents the idea of using simple shape features for action recognition based on binary silhouettes. Shape features are analysed as they change over time within an action sequence. It is shown that basic shape characteristics can discriminate between short, primitive actions performed by a single person. The proposed approach is tested on the Weizmann database using a various number of classes. Binary foreground masks (silhouettes) are replaced with convex hulls, which highlights some shape characteristics. Centroid locations are combined with some other simple shape descriptors. Each action sequence is represented using a vector with shape features and Discrete Fourier Transform. Classification is based on leave-one-sequence-out approach and employs Euclidean distance, correlation coefficient or C1 correlation. A list of processing steps for action recognition is explained and followed by some experiments that yielded accuracy exceeding 90%. The idea behind the presented approach is to develop a solution for action recognition that could be applied in a kind of human activity recognition system associated with the Ambient Assisted Living concept, helping adults increasing their activity levels by monitoring them during exercises.
An Experimental Study of a Bottom-Hinged Wave Energy Converter with a Reflection Wall in Regular Waves—Focusing on Behavioral Characteristics
Authors: Cho Yong-Hwan , Nakamura Tomoaki , Mizutani Norimi , Lee Kwang-Ho
Published: September 2020

The hybrid system of wave energy converters (WECs) using coastal structures is an attractive issue in terms of a decrease in construction costs and an improvement of the ability to capture wave energy. Most studies on the utilization of reflected waves from structures, which is one of the hybrid systems, are limited to mathematical analysis based on linear theories. Therefore, this paper presents fundamental experimental results in the presence of a reflection wall simplified as a coastal structure behind a bottom-hinged flap-type WEC under unidirectional regular waves. The behavioral characteristics and the power generation efficiency ke of the flap were investigated, focusing on wave steepness, initial water depth, and distance from the reflection wall. The results show that the condition of the initial water depth being smaller than the flap height is more effective in terms of avoiding unstable rotating of the flap. The maximum ke appeared slightly far from the node position of the standing waves because the flap shape and the power take-off (PTO) damping induce the phase difference between the reciprocating behavior of the flap and the period of the standing wave. The results imply that the optimum position of a WEC is dependent on WEC shape, PTO damping, and installation water depth.
Compression of Vehicle Trajectories with a Variational Autoencoder
Authors: Rákos Olivér , Aradi Szilárd , Bécsi Tamás , Szalay Zsolt
Published: September 2020

The perception and prediction of the surrounding vehicles’ trajectories play a significant role in designing safe and optimal control strategies for connected and automated vehicles. The compression of trajectory data and the drivers’ strategic behavior’s classification is essential to communicate in vehicular ad-hoc networks (VANETs). This paper presents a Variational Autoencoder (VAE) solution to solve the compression problem, and as an added benefit, it also provides classification information. The input is the time series of vehicle positions along actual real-world trajectories obtained from a dataset containing highway measurements, which also serves as the target. During training, the autoencoder learns to compress and decompress this data and produces a small, few element context vector that can represent vehicle behavior in a probabilistic manner. The experiments show how the size of this context vector affects the performance of the method. The method is compared to other approaches, namely, Bidirectional LSTM Autoencoder and Sparse Convolutional Autoencoder. According to the results, the Sparse Autoencoder fails to converge to the target for the specific tasks. The Bidirectional LSTM Autoencoder could provide the same performance as the VAE, though only with double context vector length, proving that the compression capability of the VAE is better. The Support Vector Machine method is used to prove that the context vector can be used for maneuver classification for lane changing behavior. The utilization of this method, considering neighboring vehicles, can be extended for maneuver prediction using a wider, more complex network structure.
Study on Dynamic Behavior of Bridge Pier by Impact Load Test Considering Scour
Authors: Lee Myungjae , Yoo Mintaek , Jung Hyun-Seok , Kim Ki Hyun , Lee Il-Wha
Published: September 2020

In this study, for the establishment of a safety evaluation method, non-destructive tests were performed by developing a full-scale model pier and simulating scour on the ground adjacent to a field pier. The surcharge load (0–250 kN) was applied to the full-scale model pier to analyze the load’s effect on the stability. For analyzing the pier’s behavior according to the impact direction, an impact was applied in the bridge axis direction, pier length direction, and pier’s outside direction. The impact height corresponded to the top of the pier. A 1-m deep scour was simulated along one side of the ground, which was adjacent to the pier foundation. The acceleration was measured using accelerometers when an impact was applied. The natural frequency, according to the impact direction and surcharge load, was calculated using a fast Fourier transform (FFT). In addition, the first mode (vibratory), second mode (vibratory), and third modes (torsion) were analyzed according to the pier behavior using the phase difference, and the effect of the scour occurrence on the natural frequency was analyzed. The first mode was most affected by the surcharge load and scour. The stability of the pier can be determined using the second mode, and the direction of the scour can be determined using the third mode.
A Blockchain-Based OCF Firmware Update for IoT Devices
Authors: Witanto Elizabeth Nathania , Oktian Yustus Eko , Lee Sang-Gon , Lee Jin-Heung
Published: September 2020

As the usage growth rate of Internet of Things (IoT) devices is increasing, various issues related to these devices need attention. One of them is the distribution of the IoT firmware update. The IoT devices’ software development does not end when the manufacturer sells the devices to the market. It still needs to be kept updated to prevent cyber-attacks. The commonly used firmware update process, over-the-air (OTA), mostly happens in a centralized way, in which the IoT devices directly download the firmware update from the manufacturer’s server. This central architecture makes the manufacturer’s server vulnerable to single-point-of-failure and latency issues that can delay critical patches from being applied to vulnerable devices. The Open Connectivity Foundation (OCF) is one organization contributing to providing interoperability services for IoT devices. In one of their subject areas, they provide a firmware update protocol for IoT devices. However, their firmware update process does not ensure the integrity and security of the patches. In this paper, we propose a blockchain-based OCF firmware update for IoT devices. Specifically, we introduce two types of firmware update protocol, direct and peer-to-peer updates, integrated into OCF firmware update specifications. In the direct scenario, the device, through the IoT gateway, can download the new firmware update from the manufacturer’s server. Meanwhile, in the peer-to-peer scheme, the device can query the update from the nearby gateways. We implemented our protocol using Raspberry Pi hardware and Ethereum-based blockchain with the smart contracts to record metadata of the manufacturer’s firmware updates. We evaluated the proposed system’s performance by measuring the average throughput, the latency, and the firmware update distribution’s duration. The analysis results indicate that our proposal can deliver firmware updates in a reasonable duration, with the peer-to-peer version having a faster completion time than the direct one.
Pore Structure and Water Transfer in Pietra d’Aspra Limestone: A Neutronographic Study
Authors: Randazzo Luciana , Paladini Giuseppe , Venuti Valentina , Crupi Vincenza , Ott Frédéric , Montana Giuseppe , Ricca Michela , Rovella Natalia , La Russa Mauro Francesco , Majolino Domenico
Published: September 2020

Neutron radiography (NR) was here applied to study the effects of two different commercially available consolidants on the water absorption properties in a particular type of limestone (biocalcarenite), known as Pietra d’Aspra stone, which is one of the most extensively used lithotypes in Sicilian Baroque buildings. Our attention was mainly focused on the evaluation, using a fast and nondestructive visualization of water motion through capillarity, of the effectiveness of such layers as consolidating agents in view of preserving and maintaining both old and modern structures. The biocalcarenite was treated with nanosilica (Nano Estel®) and nanolime (CaLoSil®) by brushing it until full saturation, and then artificially weathered by salt crystallization and temperature/relative humidity jumps. Liquid distribution and height of the water front were monitored as a function of time. Significant differences in the water suction behavior among all the investigated samples were highlighted, which allowed us to gain insight into the coating/substrate interaction mechanisms which regulate the fluid mobility inside the porous network of the limestone.
On the Use of a Simplified Slip Limit Equation to Predict Screw Self-Loosening of Dental Implants Subjected to External Cycling Loading
Authors: Armentia Mikel , Abasolo Mikel , Coria Ibai , Bouzid Abdel-Hakim
Published: September 2020

Self-loosening of the prosthetic screws is a major mechanical problem affecting roughly 10% of dental implants, according to the literature. This phenomenon may lead to micro-movements that produce crestal bone loss, peri-implantitis, or structural failure of the implant assembly. In this paper, a simple and effective tool to predict self-loosening under masticatory loads is presented. The loads acting on the screw are obtained from a simple finite element (FE) model, and introduced in a mathematical formula that calculates the torque needed to loosen the screw; self-loosening will occur when this torque becomes zero. In this sense, all the parameters involved in self-loosening phenomenon can be easily identified, and their effect quantified. For validating purposes, 90 experimental tests were performed in a direct stress test bench. As a result, a powerful tool with a maximum experimental error of 7.6% is presented, allowing dental implant manufacturers to predict eventual occurrence of self-loosening in their developed dental implant products and take corrective actions at preliminary design stage. Furthermore, the following clinical implications can be directly derived from the methodology: a higher screw preload, that is a higher tightening torque, improves self-loosening response of the dental implant and, similarly, for a given preload force, higher friction coefficient and screw metric, as well as lower pitch and thread angle values, are also found to be beneficial.
A Comparison of Power Quality Disturbance Detection and Classification Methods Using CNN, LSTM and CNN-LSTM
Authors: Garcia Carlos Iturrino , Grasso Francesco , Luchetta Antonio , Piccirilli Maria Cristina , Paolucci Libero , Talluri Giacomo
Published: September 2020

The use of electronic loads has improved many aspects of everyday life, permitting more efficient, precise and automated process. As a drawback, the nonlinear behavior of these systems entails the injection of electrical disturbances on the power grid that can cause distortion of voltage and current. In order to adopt countermeasures, it is important to detect and classify these disturbances. To do this, several Machine Learning Algorithms are currently exploited. Among them, for the present work, the Long Short Term Memory (LSTM), the Convolutional Neural Networks (CNN), the Convolutional Neural Networks Long Short Term Memory (CNN-LSTM) and the CNN-LSTM with adjusted hyperparameters are compared. As a preliminary stage of the research, the voltage and current time signals are simulated using MATLAB Simulink. Thanks to the simulation results, it is possible to acquire a current and voltage dataset with which the identification algorithms are trained, validated and tested. These datasets include simulations of several disturbances such as Sag, Swell, Harmonics, Transient, Notch and Interruption. Data Augmentation techniques are used in order to increase the variability of the training and validation dataset in order to obtain a generalized result. After that, the networks are fed with an experimental dataset of voltage and current field measurements containing the disturbances mentioned above. The networks have been compared, resulting in a 79.14% correct classification rate with the LSTM network versus a 84.58% for the CNN, 84.76% for the CNN-LSTM and a 83.66% for the CNN-LSTM with adjusted hyperparameters. All of these networks are tested using real measurements.
The Effect of Synthesis Procedure on Hydrogen Peroxidase-Like Catalytic Activity of Iron Oxide Magnetic Particles
Authors: Mukherjee Atripan , Ashrafi Amir M. , Svec Pavel , Richtera Lukáš , Přibyl Jan , Brtnický Martin , Kynicky Jindrich , Adam Vojtěch
Published: September 2020

A comparative study was carried out using magnetic nanoparticles (MNPs) for the fabrication of non-enzymatic sensors for the continuous and rapid detection and monitoring of H2O2. Various MNPs, differing in terms of their synthesis procedure and modification, were synthesized and characterized by different techniques. The electrochemical catalytic activity of the synthesized MNPs toward the reduction in H2O2 was investigated by cyclic voltammetry. The naked MNPs showed the highest catalytic activity among all the synthesized MNPs. The biosensor based on the naked MNPs was then applied in the determination of H2O2 using chronoamperometry. The parameters such as the applied cathodic potential and the amount of MNPs on the developed biosensor were optimized. Moreover, the analytical figures of merit, including reproducibility (RSD = 6.14%), sensitivity (m = 0.0676 µA µM−1), limit of detection (LOD) = 27.02 µmol L−1, and limit of quantification (LOQ) = 89.26 µmol L−1 of the developed biosensor indicate satisfactory analysis. Finally, MNPs were successfully utilized for the determination of H2O2 in milk.
Clarification of Features of the Wheel Movement with a Perspective Constructive Scheme on a Rail
Authors: Mikhailov Evgeny , Semenov Stanislav , Kliuiev Sergii , Dižo Ján , Blatnický Miroslav , Gerlici Juraj , Harušinec Jozef , Kovtanets Maxim
Published: September 2020

The article presents the continuation of studies of the features of the wheel movement the traditional and perspective constructive scheme on a rail. Unlike the traditional design, the perspective constructive scheme of the wheel allows independent relative rotation of the support surface wheel and of its guide surface (flange) relative to their common axis of rotation. Previous authors’ works did not take into account the influence of the level of slippage in the main contact of the wheel with the rail on the value of the slippage rate in its flange contact. This article further examines the influence of this factor for both wheel designs. The results of the presented studies confirm the possibility of reducing slippage in the flange contact with the rail for a wheel of a promising design scheme in comparison with a traditional wheel. Reducing the power of friction forces in the contact of the wheel flange of a promising design scheme will reduce the resistance to movement of such a wheel along the rail, especially in curved track sections.
Osseointegration of Maxillary Dental Implants in Diabetes Mellitus Patients: A Randomized Clinical Trial Human Histomorphometric Study
Authors: Sam Lyly , Chattipakorn Siriporn , Khongkhunthian Pathawee
Published: September 2020

Background: Survival of dental implants in well-controlled Type 2 diabetes (T2DM) was found to be comparable to that in healthy patients. However, to our best knowledge, there have been no studies of the bone histomorphometry of osseointegration in patients with Type 2 diabetes. Purpose: To compare bone-implant-contact (BIC) and new bone formation between well-controlled Type 2 diabetes with HbA1c of less than 8% and healthy controls. Methods: 10 diabetic (T2DM) patients and 10 healthy controls were selected. Each patient received a 2.5 mm × 5 mm micro-implant in the maxilla, in either the premolar or first molar area. After 8 weeks of healing, the micro-implant was retrieved using a trephine bur and sent for bone histomorphometric analysis. A commercial titanium implant was immediately placed as the conventional treatment. Results: The mean BIC (30.73%) in T2DM patients was significantly lower than in the healthy patients (41.75%) (p = 0.01). New bone formation around the implant surface was reduced in T2DM patients (36.25%) compared to that in the control group (44.14%) (p = 0.028). The Pearson correlation coefficient revealed a strong correlation between increased HbA1c and decreased BIC (p < 0.05) and decreased new bone formation (p < 0.05). Conclusions: Within the limitation of this study, bone-to-implant contact and bone healing around dental implants in T2DM patients were significantly lower than in healthy patients.
A Fast Ray-tracing Method for Locating Mining-Induced Seismicity by Considering Underground Voids
Authors: Peng Pingan , Jiang Yuanjian , Wang Liguan , He Zhengxiang , Tu Siyu
Published: September 2020

The accurate localization of mining-induced seismicity is crucial to underground mines. However, the constant velocity model is used by traditional location methods without considering the great difference in wave velocity between rock mass and underground voids. In this paper, to improve the microseismicity location accuracy in mines, we present a fast ray-tracing method to calculate the ray path and travel time from source to receiver considering underground voids. First, we divide the microseismic monitoring area into two categories of mediums—voids and non-voids—using a flexible triangular patch to model the surface model of voids, which can accurately describe any complicated three-dimensional (3D) shape. Second, the nodes are divided into two categories. The first category of the nodes is the vertex of the model, and the second category of the nodes is arranged at a certain step length on each edge of the 3D surface model to improve the accuracy of ray tracing. Finally, the set of adjacent nodes of each node is calculated, and then we obtain the shortest travel time from the source to the receiver based on the Dijkstra algorithm. The performance of the proposed method is tested by numerical simulation. Results show that the proposed method is faster and more accurate than the traditional ray-tracing methods. Besides, the proposed ray-tracing method is applied to the microseismic source localization in the Huangtupo Copper and Zinc Mine. The location accuracy is significantly improved compared with the traditional method using the constant velocity model and the FMM-based location method.
A New Technology for Smooth Blasting without Detonating Cord for Rock Tunnel Excavation
Authors: Ma Chunde , Xie Weibin , Liu Zelin , Li Qiyue , Xu Jiaqing , Tan Guanshuang
Published: September 2020

In this paper, the aim is to achieve safe, rapid excavation of an extra-long, large-cross-section highway tunnel in Eastern Tianshan, as well as to reduce production costs, simplify production processes, reduce cycle time, and improve production efficiency. In this study, we explored a new technology for smooth blasting without a detonating cord. A series of sympathetic detonation experiments were conducted in the tunnel face to determine critical distances. The critical distance for No. 2 rock emulsion explosive under blasthole constraints was successfully measured to be approximately 1.0–1.1 m. Based on the critical distance, a new charging structure was designed for tunnel excavation. To assess the influence of the new charging structure on blasting performance, its economic benefits, and its feasibility, full-section tests were performed in the East Tianshan Tunnel. The application of the new charging structure produced good smooth blasting results. It not only simplified the charging process and produced smooth blasting without detonating cord in peripheral holes, but also guaranteed normal excavation, an appropriate tunnel profile, and reasonable overbreak and underbreak volumes. This had remarkable economic benefits and possesses better promotional value.
Study on the Effect of Structure Parameters on NO Oxidation in DBD Reactor under Oxygen-Enriched Condition
Authors: Cai Yunkai , Lu Lin , Li Peng
Published: September 2020

To improve NO oxidation and energy efficiency, the effect of dielectric barrier discharge reactor structure on NO oxidation was studied experimentally in simulated diesel exhaust at atmospheric pressure. The mixture of 15% O2/N2 (balance)/860 ppm NOX (92% NO + 8% NO2) was used as simulated diesel exhaust. The results show that DBD reactor with 100-mm electrode length has the highest oxidation degree of NOX and energy efficiency. NO oxidation efficiency is promoted and the generation of NO is inhibited significantly by increasing the inner electrode diameter. Increasing the inner electrode diameter not only improve the E/N, but also makes the distribution of E/N more concentrated in the gas gap. The secondary electron emission coefficient (γ) of electrode material is closely related to electron energy and cannot be considered as a constant, which causes the different performance of electrode material for NO oxidation under different gas gap conditions. Compared with the rod electrode, the screw electrode has a higher electric field strength near the top of the screw, which promotes the generation of N radicals and inhibits the generation of O radicals. Rod electrode has a higher NO oxidation and energy efficiency than screw electrode under oxygen-enriched condition.
Real-Time Identification of Dynamic Loads Using Inverse Solution and Kalman Filter
Authors: Jiang Jinhui , Luo Shuyi , Mohamed M. Shadi , Liang Zhongzai
Published: September 2020

Evaluating dynamic loads in real time is crucial for health monitoring, fault diagnosis and fatigue analysis in aerospace, automotive and earthquake engineering among other vibration related applications. Developing such algorithms can be vital for several safety and performance functionalities. Therefore, over the past few years the identification of dynamic loads has attracted a lot of attention; however, little literature on the online identification can be found. In this paper, we propose an online-identification method of structural dynamic loads so that the dynamic load is evaluated in real time and while the system response is still being measured. This is achieved by significantly improving the identification efficiency while retaining a high accuracy. The proposed method which is based on Kalman filter, is introduced in detail for a finite as well as an infinite number of degrees of freedom. Starting from an initial guess of the state vector we evaluate the error covariance, which then helps to identify the value of the excitation force using a weighted least square method and minimizing the covariance unbiased estimation. This is repeated at certain time intervals i.e., time steps where the state vector is updated in real time as acceleration measurements are updated. The feasibility of the method is validated using numerical simulations and an experimental verification where a detailed LabVIEW (National Instruments Ltd.) implementation is provided.
Identification of Players Ranking in E-Sport
Authors: Urbaniak Karol , Wątróbski Jarosław , Sałabun Wojciech
Published: September 2020

Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports.
Simplified Seismic Vulnerability Assessment Methods: A Comparative Analysis with Reference to Regional School Building Stock in Italy
Authors: Ceroni F. , Caterino N. , Vuoto A.
Published: September 2020

The paper compares several simplified methods proposed in the literature for assessing the seismic vulnerability of existing buildings. Type and number of input and output data, limitations of use for different structural typologies, and complexity of use are examined for each methodology to identify the most suitable for assessing the vulnerability of a given class of buildings, based on the available data, the computational effort, and the type of vulnerability judgment. The selected methods were applied to a sample of school buildings located in the province of Naples (Italy). Data were available due to a digital platform and were used to verify the possibility of providing reliable large scale vulnerability judgments based on a reduced set of information, without carrying out additional surveys. The most simplified methods were applied to a sample of about a thousand of buildings, while more detailed methods, needing more information, were applied to a smaller sample. The comparison between the results obtained from different methods allows highlighting advantages and weaknesses of each, so as to identify the convenience in their use according to the specific available information and the objectives of the analysis, finally to evaluate which is more or less safe.
Simultaneous Analysis of Seven Neonicotinoids in Commercial Milk Samples Using an UHPLC-MS/MS Method
Authors: Huang Yu-Fang , Huang Yi-Min , Lee Hsin-Jui
Published: September 2020

A liquid–liquid extraction and ultra high-performance liquid chromatography tandem mass spectrometry (UHPLC–MS/MS) method was developed for simultaneous analysis of the residues of seven neonicotinoid insecticides (NEOs), namely acetamiprid, clothianidin, dinotefuran, imidacloprid, thiacloprid, thiamethoxam, and nitenpyram, in commercial milk samples. The method had a good linearity (R2 > 0.992) and a limit of detection range of 0.004–0.15 μg/kg. The average recovery range was 89–119% with an intraday precision of 1.4–10.3% at spiking levels of 8, 12, and 16 μg/kg. The validated method was employed for routine analysis of the aforementioned seven NEOs in commercial milk samples obtained randomly from a supermarket in Miaoli (Taiwan). The detected thiamethoxam and clothianidin levels were 3.4 and 80 μg/kg, respectively.
Content and Privacy Protection in JPEG Images by Reversible Visual Transformation
Authors: Cao Xin , Huang Yuxuan , Wu Hao-Tian , Cheung Yiu-ming
Published: September 2020

With the popularity of cloud computing and social networks, more and more JPEG images are stored and distributed. Consequently, how to protect privacy and content in JPEG images has become an important issue. Although traditional encryption schemes can be employed, the file format of JPEG images is changed so that their usage may be affected. In this paper, a reversible visual transformation algorithm is proposed to protect content in JPEG images. Specifically, the DC coefficient in each user-selected block is modified, while the information required to recover it is reversibly hidden into AC coefficients. Then the signs of AC coefficients in the selected blocks are flipped and the blocks are further scrambled with a secret key. By embedding the location information of the selected blocks in a transformed image, the original image can be exactly recovered when needed. Besides, regions to be protected can be arbitrarily chosen without substantially affecting the rest of the image. The experimental results on a set of JPEG images validate the efficacy and reversibility of the proposed algorithm. In addition, good performance is achieved in terms of invisibility of the protected content, image quality, file size preservation and security.
Harmonic-Modal Hybrid Reduced Order Model for the Efficient Integration of Non-Linear Soil Dynamics
Authors: Germoso Claudia , Duval Jean Louis , Chinesta Francisco
Published: September 2020

Nonlinear behavior of soils during a seismic event has a predominant role in current site response analysis. Soil response analysis, and more concretely laboratory data, indicate that the stress-strain relationship of soils is nonlinear and exhibits hysteresis. An equivalent linearization method, in which non-linear characteristics of shear modulus and damping factor of soils are modeled as equivalent linear relations of the shear strain is usually applied, but this assumption, however, may lead to a conservative approach of the seismic design. In this paper, we propose an alternative analysis formulation, able to address forced response simulation of soils exhibiting their characteristic nonlinear behavior. The proposed approach combines ingredients of modal and harmonic analyses enabling efficient time-integration of nonlinear soil behaviors based on the offline construction of a dynamic response parametric solution by using Proper Generalized Decomposition (PGD)-based model order reduction technique.
Motivating Students for Ear-Training with a Rhythmic Dictation Application
Authors: Pesek Matevž , Suhadolnik Lovro , Šavli Peter , Marolt Matija
Published: September 2020

We present the development and evaluation of a gamified rhythmic dictation application for music theory learning. The application was developed as a web application in the existing Troubadour platform for music ear training. The focus of the developed application was on user experience and engagement. With regards to the former, we developed a responsive and intuitive user interface; for the latter, we included several gamification elements and assessed the impact on the students’ engagement. We report on students’ experience analysis done through questionnaires and background data collected through the platform. We evaluated the rhythmic dictation application with the conservatory-level music theory students through A/B testing in order to independently evaluate the application’s impact. The results show a significant impact of the application on the students’ exam scores.
Applications of Computer Vision in Automation and Robotics
Authors: Okarma Krzysztof
Published: September 2020

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