bluuebunny/crossref_metadata_2025 huggingface dataset:
Oral Health Status and Patterns of Dental Service Utilization of Adolescents in Lesotho, Southern Africa
Authors: Jessani Abbas , Quadri Mir Faeq Ali , Lefoka Pulane , El-Rabbany Abdul , Hooper Kirsten , Lim Hyun Ja , Ndobe Eketsang , Brondani Mario , Laronde Denise M.
Published: February 2021

This study aimed to characterize the best predictors for unmet dental treatment needs and patterns of dental service utilization by adolescents in the Kingdom of Lesotho, Southern Africa. A self-reported 40-item oral health survey was administered, and clinical oral examinations were conducted in public schools in Maseru from August 10 to August 25, 2016. Associations between psychosocial factors with oral health status and dental service utilization were evaluated using simple, bivariate, and multivariate regressions. Five hundred and twenty-six survey responses and examinations were gathered. The mean age of student participants was 16.4 years of age, with a range between 12 and 19 years of age. More than two thirds (68%; n = 355) of participants were female. The majority reported their quality of life (84%) and general health to be good/excellent (81%). While 95% reported that oral health was very important, only 11% reported their personal dental health as excellent. Three percent reported having a regular family dentist, with the majority (85%) receiving dental care in a hospital or medical clinic setting; only 14% had seen a dental professional within the previous two years. The majority of participants did not have dental insurance (78%). Clinical examination revealed tooth decay on 30% of mandibular and maxillary molars; 65% had some form of gingivitis. In multivariate analysis, not having dental education and access to a regular dentist were the strongest predictors of not visiting a dentist within the last year. Our results suggest that access to oral health care is limited in Lesotho. Further patient oral health education and regular dental care may make an impact on this population.
Methadone, Metoclopramide and Metronidazole Interaction Causing Torsades de Pointes
Authors: Gnanapandithan Karthik , Karthik Nishrutha , Gerber Jaime
Published: February 2021

There are several classes of medications that can cause prolongation of the corrected QT (QTc) interval and potentially Torsades de Pointes (TdP). Most of these medications are commonly used in the emergency department, and interaction between these medications increases the risk of this iatrogenic complication. We describe a patient on methadone therapy who developed TdP after she received metoclopramide and metronidazole. Interaction between different classes of medications can increase the risk of QTc prolongation and TdP. Awareness of this condition and its risk factors need continuous reinforcement among all hospital personnel to reduce the risk of this life-threatening complication.
Sputter Deposited Metal Layers Embedded in Composites—From Fundamentals to Applications
Authors: Cougnon Florian , Kersemans Mathias , Van Paepegem Wim , Depla Diederik
Published: February 2021

Due to the low heat flux towards the substrate, magnetron sputter deposition offers the possibility to deposit thin films on heat sensitive materials such as fiber-reinforced polymers, also known as composite materials. Passive thermal probe measurements during the sputter deposition of metal layers show indeed that the temperature increase remains well below 25 °C for film thicknesses up to 600 nm. The latter thickness threshold is based on the influence of embedded metal films on the adhesion of the composite plies. Films thicker than this threshold deteriorate the mechanical integrity of the composite. The introduction of the uncured composite in the vacuum chamber strongly affects the base pressure by outgassing of impurities from the composite. The impurities affect the film properties as illustrated by their impact on the Seebeck coefficient of sputter deposited thermocouples. The restrictions to embed thin films in composites, as illustrated by both the heat flux measurements, and the study on the influence of impurities, are however not insurmountable. The possibility to use embedded thin films will be briefly demonstrated in different applications such as digital volume image correlation, thermocouples, and de-icing.
Microstructure and Properties of Cold Sprayed NiCrAl Coating on AZ91D Magnesium Alloy
Authors: Zhao Xiangwei , Dong Tianshun , Fu Binguo , Li Guolu , Liu Qi , Li Yanjiao
Published: February 2021

Herein, a NiCrAl coating was prepared on the AZ91D magnesium alloy by cold spraying technology. The microstructure, wear resistance, and corrosion resistance of the cold sprayed NiCrAl coating were studied and compared with two NiCrAl coatings prepared by plasma spraying. The results showed that the porosity of the two-plasma sprayed NiCrAl coatings was 3.21% and 2.66%, respectively, while that of the cold sprayed NiCrAl coating was only 0.68%. The hardness of the cold sprayed NiCrAl coating (650 HV0.1) was higher than those of the two-plasma sprayed NiCrAl coatings (300 HV0.1, 400 HV0.1). In the abrasion resistance test, the cold sprayed NiCrAl coating showed a lower friction coefficient (0.346), less wear volume (3.026 mm3), and superior wear resistance accordingly compared with the two-plasma sprayed NiCrAl coatings. Moreover, the scanning electron microscopy (SEM) morphology at the bottom of the wear trace of the cold sprayed NiCrAl coating showed a compact mechanically mixed layers (MML) structure, and its wear mechanism was mainly abrasive wear, with some fatigue wear. In the electrochemical test, the corrosion current density of the cold sprayed NiCrAl coating (4.404 × 10−2 A·cm−2) was much lower than those of two plasma sprayed coatings (25.96 A·cm−2, 26.98 A·cm−2), indicating that the cold sprayed NiCrAl coating had superior corrosion resistance. Therefore, preparing a cold sprayed NiCrAl coating is a feasible method to comprehensively improve the wear resistance and corrosion resistance of the AZ91D magnesium alloy.
A Power Dissipation Monitoring Circuit for Intrusion Detection and Botnet Prevention on IoT Devices
Authors: Myridakis Dimitrios , Myridakis Paul , Kakarountas Athanasios
Published: February 2021

Recently, there has been a sharp increase in the production of smart devices and related networks, and consequently the Internet of Things. One concern for these devices, which is constantly becoming more critical, is their protection against attacks due to their heterogeneity and the absence of international standards to achieve this goal. Thus, these devices are becoming vulnerable, with many of them not even showing any signs of malfunction or suspicious behavior. The aim of the present work is to introduce a circuit that is connected in series with the power supply of a smart device, specifically an IP camera, which allows analysis of its behavior. The detection circuit operates in real time (real-time detection), sampling the supply current of the device, processing the sampled values and finally indicating any detection of abnormal activities, based on a comparison to normal operation conditions. By utilizing techniques borrowed by simple power analysis side channel attack, it was possible to detect deviations from the expected operation of the IP camera, as they occurred due to intentional attacks, quarantining the monitored device from the rest of the network. The circuit is analyzed and a low-cost implementation (under 5US$) is illustrated. It achieved 100% success in the test results, showing excellent performance in intrusion detection.
Deep Feature Fusion of Fingerprint and Online Signature for Multimodal Biometrics
Authors: Leghari Mehwish , Memon Shahzad , Dhomeja Lachhman Das , Jalbani Akhtar Hussain , Chandio Asghar Ali
Published: February 2021

The extensive research in the field of multimodal biometrics by the research community and the advent of modern technology has compelled the use of multimodal biometrics in real life applications. Biometric systems that are based on a single modality have many constraints like noise, less universality, intra class variations and spoof attacks. On the other hand, multimodal biometric systems are gaining greater attention because of their high accuracy, increased reliability and enhanced security. This research paper proposes and develops a Convolutional Neural Network (CNN) based model for the feature level fusion of fingerprint and online signature. Two types of feature level fusion schemes for the fingerprint and online signature have been implemented in this paper. The first scheme named early fusion combines the features of fingerprints and online signatures before the fully connected layers, while the second fusion scheme named late fusion combines the features after fully connected layers. To train and test the proposed model, a new multimodal dataset consisting of 1400 samples of fingerprints and 1400 samples of online signatures from 280 subjects was collected. To train the proposed model more effectively, the size of the training data was further increased using augmentation techniques. The experimental results show an accuracy of 99.10% achieved with early feature fusion scheme, while 98.35% was achieved with late feature fusion scheme.
Symptom Tracking and Experimentation Platform for Covid-19 or Similar Infections
Authors: Petrellis Nikos , Adam George K.
Published: February 2021

Remote symptom tracking is critical for the prevention of Covid-19 spread. The qualified medical staff working in the call centers of primary health care units have to take critical decisions often based on vague information about the patient condition. The congestion and the medical protocols that are constantly changing often lead to incorrect decisions. The proposed platform allows the remote assessment of symptoms and can be useful for patients, health institutes and researchers. It consists of mobile desktop applications and medical sensors connected to cloud infrastructure. The unique features offered by the proposed solution are: (a) dynamic adaptation of Medical Protocols (MP) is supported (for the definition of alert rules, sensor sampling strategy and questionnaire structure) covering different medical cases (pre- or post-hospitalization, vulnerable population, etc.), (b) anonymous medical data can be statistically processed in the context of the research about an infection such as Covid-19, (c) reliable diagnosis is supported since several factors are taken into consideration, (d) the platform can be used to drastically reduce the congestion in various healthcare units. For the demonstration of (b), new classification methods based on similarity metrics have been tested for cough sound classification with an accuracy in the order of 90%.
Multi-Band Electromagnetically-Induced-Transparency Metamaterial Based on the Near-Field Coupling of Asymmetric Split-Ring and Cut-Wire Resonators in the GHz Regime
Authors: Nam Man Hoai , Hanh Vu Thi Hong , Tuong Nguyen Ba , Tung Bui Son , Khuyen Bui Xuan , Lam Vu Dinh , Chen Liang Yao , Lee Young Pak
Published: February 2021

A metamaterial (MM), mimicking electromagnetically-induced transparency (EIT) in the GHz regime, was demonstrated numerically and experimentally by exploiting the near-field coupling of asymmetric split-ring and cut-wire resonators. By moving the resonators towards each other, the original resonance dip was transformed to a multi-band EIT. The phenomenon was explained clearly through the excitation of bright and dark modes. The dispersion characteristic of the proposed MM was also investigated, which showed a strongly-dispersive behavior, leading to a high group index and a time delay of the MM. Our work is expected to contribute a simple way to develop the potential devices based on the multi-band EIT effect.
Thermophysical Properties of Kaolin–Zeolite Blends up to 1100 °C
Authors: Ondruška Ján , Húlan Tomáš , Sunitrová Ivana , Csáki Štefan , Łagód Grzegorz , Struhárová Alena , Trník Anton
Published: February 2021

In this study, the thermophysical properties such as the thermal expansion, thermal diffusivity and conductivity, and specific heat capacity of ceramic samples made from kaolin and natural zeolite are investigated up to 1100 °C. The samples were prepared from Sedlec kaolin (Czech Republic) and natural zeolite (Nižný Hrabovec, Slovakia). Kaolin was partially replaced with a natural zeolite in the amounts of 10, 20, 30, 40, and 50 mass%. The measurements were performed on cylindrical samples using thermogravimetric analysis, a horizontal pushrod dilatometer, and laser flash apparatus. The results show that zeolite in the samples decreases the values of all studied properties (except thermal expansion), which is positive for bulk density, porosity, thermal diffusivity, and conductivity. It has a negative effect for thermal expansion because shrinkage increases with the zeolite content. Therefore, the optimal amount of zeolite in the sample (according to the studied properties) is 30 mass%.
Purification and Crystallographic Analysis of a Novel Cold-Active Esterase (HaEst1) from Halocynthiibacter arcticus
Authors: Jeon Sangeun , Hwang Jisub , Yoo Wanki , Chang Joo Won , Do Hackwon , Kim Han-Woo , Kim Kyeong Kyu , Lee Jun Hyuck , Kim T. Doohun
Published: February 2021

This report deals with the purification, characterization, and a preliminary crystallographic study of a novel cold-active esterase (HaEst1) from Halocynthiibacter arcticus. Primary sequence analysis reveals that HaEst1 has a catalytic serine in G-x-S-x-G motif. The recombinant HaEst1 was cloned, expressed, and purified. SDS-PAGE and zymographic analysis were carried out to characterize the properties of HaEst1. A single crystal of HaEst1 was obtained in a solution containing 10% (w/v) PEG 8000/8% ethylene glycol, 0.1 M Hepes-NaOH, pH 7.5. Diffraction data were collected to 2.10 Å resolution with P21 space group. The final Rmerge and Rp.i.m values were 7.6% and 3.5% for 50–2.10 Å resolution. The unit cell parameters were a = 35.69 Å, b = 91.21 Å, c = 79.15 Å, and β = 96.9°.
Increased Tenascin C, Osteopontin and HSP90 Levels in Plasmatic Small Extracellular Vesicles of Pediatric ALK-Positive Anaplastic Large Cell Lymphoma: New Prognostic Biomarkers?
Authors: Lovisa Federica , Garbin Anna , Crotti Sara , Di Battista Piero , Gallingani Ilaria , Damanti Carlotta Caterina , Tosato Anna , Carraro Elisa , Pillon Marta , Mafakheri Erfan , Romanato Filippo , Gaffo Enrico , Biffi Alessandra , Bortoluzzi Stefania , Agostini Marco , Mussolin Lara
Published: February 2021

Over the past 15 years, several biological and pathological characteristics proved their significance in pediatric anaplastic lymphoma kinase (ALK)-positive anaplastic large-cell lymphoma (ALCL) prognostic stratification. However, the identification of new non-invasive disease biomarkers, relying on the most important disease mechanisms, is still necessary. In recent years, plasmatic circulating small extracellular vesicles (S-EVs) gathered great importance both as stable biomarker carriers and active players in tumorigenesis. In the present work, we performed a comprehensive study on the proteomic composition of plasmatic S-EVs of pediatric ALCL patients compared to healthy donors (HDs). By using a mass spectrometry-based proteomics approach, we identified 50 proteins significantly overrepresented in S-EVs of ALCL patients. Gene Ontology enrichment analysis disclosed cellular components and molecular functions connected with S-EV origin and vesicular trafficking, whereas cell adhesion, glycosaminoglycan metabolic process, extracellular matrix organization, collagen fibril organization and acute phase response were the most enriched biological processes. Of importance, consistently with the presence of nucleophosmin (NPM)-ALK fusion protein in ALCL cells, a topological enrichment analysis based on Reactome- and Kyoto Encyclopedia of Genes and Genomes (KEGG)-derived networks highlighted a dramatic increase in proteins of the phosphatidylinositol 3-kinase (PI3K)/AKT pathway in ALCL S-EVs, which included heat shock protein 90-kDa isoform alpha 1 (HSP90AA1), osteopontin (SPP1/OPN) and tenascin C (TNC). These results were validated by Western blotting analysis on a panel of ALCL and HD cases. Further research is warranted to better define the role of these S-EV proteins as diagnostic and, possibly, prognostic parameters at diagnosis and for ALCL disease monitoring.
Seeking Medical Assistance for Dysphonia Is Associated with an Improved Survival Rate in Laryngeal Cancer: Real-World Evidence
Authors: Lu Yi-An , Tsai Ming-Shao , Lee Li-Ang , Lee Shu-Ru , Lin Li-Yun , Chang Chain-Fen , Lin Wan-Ni , Hsin Li-Jen , Liao Chun-Ta , Li Hsueh-Yu , Wen Yu-Wen , Fang Tuan-Jen
Published: February 2021

(1) Background: Patients with laryngeal cancer usually present with dysphonia. However, some studies reported that the duration from dysphonia to cancer diagnosis has been prolonged significantly in recent years. This study aimed to evaluate that in the initial dysphonia-related diagnosis and the interval between the diagnosis of laryngeal cancer may affect the overall survival (OS). (2) Methods: The 1997–2013 Longitudinal Health Insurance Database was used in this study. A propensity score with 1-to-1 matching was applied to balance the baseline characteristics. The OS was examined by the Kaplan-Meier method and log-rank test. (3) Results: A total of 2753 patients with a first primary laryngeal cancer diagnosis were identified. The patients without prior dysphonia-related diagnosis (PD−) group did have a significantly worse five-year survival (p = 0.015) comparing with those with a prior dysphonia-related diagnosis (PD+) group among glottic cancer patients. The group with a shorter dysphonia-to-diagnosis interval had a better five-year OS than the prolonged group (p = 0.007) in laryngeal cancer. (4) Conclusions: Looking for medical assistance before a diagnosis of glottic cancer is associated with a better overall survival, while a diagnostic delay of more than 30 days from the first medical examination for dysphonia is associated with a worse outcome among in patients with laryngeal cancer.
The Importance of Multimodality Imaging in the Diagnosis and Management of Patients with Infiltrative Cardiomyopathies: An Update
Authors: Sascău Radu , Anghel Larisa , Clement Alexandra , Bostan Mădălina , Radu Rodica , Stătescu Cristian
Published: February 2021

Infiltrative cardiomyopathies (ICMs) comprise a broad spectrum of inherited and acquired conditions (mainly amyloidosis, sarcoidosis, and hemochromatosis), where the progressive buildup of abnormal substances within the myocardium results in left ventricular hypertrophy and manifests as restrictive physiology. Noninvasive multimodality imaging has gradually eliminated endomyocardial biopsy from the diagnostic workup of infiltrative cardiac deposition diseases. However, even with modern imaging techniques’ widespread availability, these pathologies persist in being largely under- or misdiagnosed. Considering the advent of novel, revolutionary pharmacotherapies for cardiac amyloidosis, the archetypal example of ICM, a standardized diagnostic approach is warranted. Therefore, this review aims to emphasize the importance of contemporary cardiac imaging in identifying specific ICM and improving outcomes via the prompt initiation of a targeted treatment.
Significant Changes in Serum MicroRNAs after High Tibial Osteotomy in Medial Compartmental Knee Osteoarthritis: Potential Prognostic Biomarkers
Authors: Kwak Yoon Hae , Kwak Dae-Kyung , Moon Hyun-Soo , Kim Nan Young , Yee Jae-Sung , Yoo Je-Hyun
Published: February 2021

High tibial osteotomy (HTO) is an effective alternative for medial compartmental knee osteoarthritis (OA). Circulating microRNAs (miRNAs) are known to serve as OA-related biomarkers. The present study investigated the differential expression of serum miRNAs before and after HTO to identify potential miRNAs as prognostic biomarkers. miRNA-polymerase chain reaction (PCR) arrays were used to screen for miRNAs in the serum at preoperative and 6-month postoperative time points from six patients, and the differentially expressed miRNAs identified in the profiling stage were validated using real-time PCR at post-operative months 6 and 18 in 27 other HTO-treated patients. Among 84 miRNAs involved in the inflammatory process, three (miR-19b-3p, miR-29c-3p, and miR-424-5p) showed differential expression patterns in the profiling stage (p = 0.011, 0.015, and 0.021, respectively). Levels of these three and four other miRNAs (miR-140-3p, miR-454-3p, miR-let-7e-5p, and miR-885-5p) known to be related to OA progression were evaluated in the serum of 27 patients. Only four miRNAs (miR-19b-3p, miR-140-3p, miR-454-3p, and miR-let-7e-5p) were significantly upregulated at postoperative month 6 (p = 0.003, 0.005, 0.004, and 0.004, respectively), and only miR-140-3p was significantly upregulated up to 18 months after operation (p = 0.003). Together, this study reveals the significantly upregulated serum miRNAs after HTO as potential prognostic biomarkers; however, further studies are warranted to elucidate their clinical implications.
Development of a Radiographic Index for Periodontitis
Authors: Shaker Zeyad M. H. , Parsa Azin , Moharamzadeh Keyvan
Published: February 2021

The use of radiographic indices is noticeably diminished due to the lack of simplicity and standardisation among the existing ones. The aim of this study was to introduce a radiographic index to aid clinicians in determining the extent and severity of interproximal alveolar bone loss (iABL), in relation to individual root lengths, among patients suffering from periodontitis. A retrospective analysis of 50 anonymised dental panoramic tomograms (DPTs) of patients with periodontitis was conducted. Visual interpretation of iABL was recorded by a single investigator and by 20 volunteering clinicians for the ‘worst site’ in each quintet. Results were compared to a gold standard quantification method. Intra-examiner and inter-examiner agreement were measured using the Kappa coefficient and the intra-class correlation coefficient, respectively. Validity was assessed using Cramér’s V test. The mean intra-examiner agreement on the severity and pattern of iABL was 0.808 (K) and 0.802 (K), respectively. A stronger overall inter-examiner agreement was noted when the severity in contrast to the pattern of iABL and presence/absence of furcation involvement were analysed. The statistically significant total mean agreement values from this correlation coefficient were 0.892 and 0.739, respectively. A very strong association between all the visual interpretations carried out by all participants and the gold standard measurements was evident. Within the limitations of this study, the proposed radiographic index may serve as a simple, yet valid and reliable, adjunctive screening tool to further assist clinicians in determining the extent and severity of iABL in patients with periodontitis.
Novel Femto Laser Patterning of High Translucent Zirconia as an Alternative to Conventional Particle Abrasion
Authors: Tzanakakis Emmanouil-George C. , Beketova Anastasia , Papadopoulou Lambrini , Kontonasaki Eleana , Tzoutzas Ioannis G.
Published: February 2021

Background: currently applied surface treatments for zirconia bonding may create undesired microcracks and surface flaws. The aim of the present study was to evaluate the efficacy of alternative surface treatments on the shear bond strength of high translucency zirconia to 10-Methacryloyloxydecyl dihydrogen phosphate (MDP)-containing resin-based cement. Methods: fifty disk-shaped specimens (10 mm × 5 mm) were fabricated from a commercial yttria-stabilized zirconia with 5 mole% yttrium oxide tetragonal zirconia polycrystal (5Y-TZP), and underwent air-abrasion with alumina particles (50 μm-AL50 and 90 μm-AL90), glass beads (GB 10–60 μm), and ablation with femtosecond laser (FEMTO). Shear bond strength was evaluated with a universal testing machine under a crosshead speed of 0.5 mm/min until fracture. Fracture type was evaluated with an optical stereomicroscope. Differences among groups were evaluated by one-way ANOVA and Bonferroni pairwise comparison tests (p < 0.05). Results: the highest shear bond strength values were presented by the laser treated group (23.97 ± 3.7 MPa). No statistically significant differences were found among the Cl, Al50, Al90 and FEMTO groups. The lowest mean value was presented by the glass-beads treated group (11.93 ± 2.88 MPa) which was significantly lower compared to all other groups (p < 0.001). Conclusions: under the limitations of this in vitro study, femtosecond laser treatment of High-translucent monolithic zirconia (HTZ) ceramics is a promising alternative method for the mechanical retention of resin cements.
Development and Psychometric Properties of a Scale to Measure Resilience among Portuguese University Students: Resilience Scale-10
Authors: Jardim Jacinto , Pereira Anabela , Bártolo Ana
Published: February 2021

Higher education students lack skills to deal in a positive way with the crises inherent to the developmental phase in which they find themselves. However, the complexity of the current global context adds an urgent need for them to be resilient. For this purpose, it is necessary to evaluate their capacity for resilience, which requires the use of instruments that are easy to access, useful, simple, and fast. In this sense, this study aimed to develop and validate a scale to assess students’ resilience in the face of adversity. The scale was administered to a sample of 2030 Portuguese higher education students. The results obtained pointed towards a factorial structure composed of two factors named “self-determination” and “adaptability”, which showed good internal consistency. Therefore, this scale proved to be a valid measure to assess resilience among the university population. Future studies may consider this variable as an intervention target since it can be a predictor of success in phases of change and crisis.
Elastic Downsampling: An Adaptive Downsampling Technique to Preserve Image Quality
Authors: García Aranda Jose J. , Alarcón Granero Manuel , Juan Quintanilla Francisco Jose , Caffarena Gabriel , García-Carmona Rodrigo
Published: February 2021

This paper presents a new adaptive downsampling technique called elastic downsampling, which enables high compression rates while preserving the image quality. Adaptive downsampling techniques are based on the idea that image tiles can use different sampling rates depending on the amount of information conveyed by each block. However, current approaches suffer from blocking effects and artifacts that hinder the user experience. To bridge this gap, elastic downsampling relies on a Perceptual Relevance analysis that assigns sampling rates to the corners of blocks. The novel metric used for this analysis is based on the luminance fluctuations of an image region. This allows a gradual transition of the sampling rate within tiles, both horizontally and vertically. As a result, the block artifacts are removed and fine details are preserved. Experimental results (using the Kodak and USC Miscelanea image datasets) show a PSNR improvement of up to 15 dB and a superior SSIM (Structural Similarity) when compared with other techniques. More importantly, the algorithms involved are computationally cheap, so it is feasible to implement them in low-cost devices. The proposed technique has been successfully implemented using graphics processors (GPU) and low-power embedded systems (Raspberry Pi) as target platforms.
Steel Bar Counting from Images with Machine Learning
Authors: Hernández-Ruiz Ana Caren , Martínez-Nieto Javier Alejandro , Buldain-Pérez Julio David
Published: February 2021

Counting has become a fundamental task for data processing in areas such as microbiology, medicine, agriculture and astrophysics. The proposed SA-CNN-DC (Scale Adaptive—Convolutional Neural Network—Distance Clustering) methodology in this paper is designed for automated counting of steel bars from images. Its design consists of two Machine Learning techniques: Neural Networks and Clustering. The system has been trained to count round and squared steel bars, obtaining an average detection accuracy of 98.81% and 98.57%, respectively. In the steel industry, counting steel bars is a time consuming task which highly relies on human labour and is prone to errors. Reduction of counting time and resources, safety and productivity of employees and high confidence of the inventory are some of the advantages of the proposed methodology in a steel warehouse.
Transparent Control Flow Transfer between CPU and Accelerators for HPC
Authors: Granhão Daniel , Canas Ferreira João
Published: February 2021

Heterogeneous platforms with FPGAs have started to be employed in the High-Performance Computing (HPC) field to improve performance and overall efficiency. These platforms allow the use of specialized hardware to accelerate software applications, but require the software to be adapted in what can be a prolonged and complex process. The main goal of this work is to describe and evaluate mechanisms that can transparently transfer the control flow between CPU and FPGA within the scope of HPC. Combining such a mechanism with transparent software profiling and accelerator configuration could lead to an automatic way of accelerating regular applications. In this work, a mechanism based on the ptrace system call is proposed, and its performance on the Intel Xeon+FPGA platform is evaluated. The feasibility of the proposed approach is demonstrated by a working prototype that performs the transparent control flow transfer of any function call to a matching hardware accelerator. This approach is more general than shared library interposition at the cost of a small time overhead in each accelerator use (about 1.3 ms in the prototype implementation).
A Machine Learning Approach for Anomaly Detection in Industrial Control Systems Based on Measurement Data
Authors: Mokhtari Sohrab , Abbaspour Alireza , Yen Kang K. , Sargolzaei Arman
Published: February 2021

Attack detection problems in industrial control systems (ICSs) are commonly known as a network traffic monitoring scheme for detecting abnormal activities. However, a network-based intrusion detection system can be deceived by attackers that imitate the system’s normal activity. In this work, we proposed a novel solution to this problem based on measurement data in the supervisory control and data acquisition (SCADA) system. The proposed approach is called measurement intrusion detection system (MIDS), which enables the system to detect any abnormal activity in the system even if the attacker tries to conceal it in the system’s control layer. A supervised machine learning model is generated to classify normal and abnormal activities in an ICS to evaluate the MIDS performance. A hardware-in-the-loop (HIL) testbed is developed to simulate the power generation units and exploit the attack dataset. In the proposed approach, we applied several machine learning models on the dataset, which show remarkable performances in detecting the dataset’s anomalies, especially stealthy attacks. The results show that the random forest is performing better than other classifier algorithms in detecting anomalies based on measured data in the testbed.
Comparison of Sneo-Based Neural Spike Detection Algorithms for Implantable Multi-Transistor Array Biosensors
Authors: Saggese Gerardo , Tambaro Mattia , Vallicelli Elia A. , Strollo Antonio G. M. , Vassanelli Stefano , Baschirotto Andrea , Matteis Marcello De
Published: February 2021

Real-time neural spike detection is an important step in understanding neurological activities and developing brain-silicon interfaces. Recent approaches exploit minimally invasive sensing techniques based on implanted complementary metal-oxide semiconductors (CMOS) multi transistors arrays (MTAs) that limit the damage of the neural tissue and provide high spatial resolution. Unfortunately, MTAs result in low signal-to-noise ratios due to the weak capacitive coupling between the nearby neurons and the sensor and the high noise power coming from the analog front-end. In this paper we investigate the performance achievable by using spike detection algorithms for MTAs, based on some variants of the smoothed non-linear energy operator (SNEO). We show that detection performance benefits from the correlation of the signals detected by the MTA pixels, but degrades when a high firing rate of neurons occurs. We present and compare different approaches and noise estimation techniques for the SNEO, aimed at increasing the detection accuracy at low SNR and making it less dependent on neurons firing rates. The algorithms are tested by using synthetic neural signals obtained with a modified version of NEUROCUBE generator. The proposed approaches outperform the SNEO, showing a more than 20% increase on averaged sensitivity at 0 dB and reduced dependence on the neuronal firing rate.
Buck-Boost/Flyback Hybrid Converter for Solar Power System Applications
Authors: Tseng Sheng-Yu , Fan Jun-Hao
Published: February 2021

This paper proposes a hybrid converter to supply power from solar power source to load. Since power is generated by solar power, which depends on the intensity of solar power, the power generated by the solar power does not keep at a constant power. Therefore, the proposed system needs a battery to balance power between solar power and load. When the proposed one uses the battery to balance powers, the proposed circuit requires a charger and discharger. To simplify the proposed converter, a buck-boost converter and flyback converter can be combined to implement the battery charging and discharging functions. With this approach, the proposed converter can be operated with zero-voltage switching (ZVS) at turn-on transition to reduce switching loss of switch when the proposed one is operated in the discharging mode. In addition, the proposed hybrid converter has several merits, which are less component counts, lighter weight, smaller size and higher conversion efficiency. As compared with the conventional counterparts with hard-switching circuit, the proposed one can increase conversion efficiency of 4% and achieve efficiency of 85% under full load condition when the proposed one is operated in the discharging mode. Experimental results which are obtained from a prototype with output voltage of 10 V and maximum output power 20 W have been implemented to verify its feasibility. It is suitable for an electronic sign indicating LED within 200 W, which is used in the night time.
A New Peak-Shaving Model Based on Mixed Integer Linear Programming with Variable Peak-Shaving Order
Authors: Cheng Xianliang , Feng Suzhen , Huang Yanxuan , Wang Jinwen
Published: February 2021

Peak-shaving is a very efficient and practical strategy for a day-ahead hydropower scheduling in power systems, usually aiming to appropriately schedule hourly (or in less time interval) power generations of individual plants so as to smooth the load curve while enforcing the energy production target of each plant. Nowadays, the power marketization and booming development of renewable energy resources are complicating the constraints and diversifying the objectives, bringing challenges for the peak-shaving method to be more flexible and efficient. Without a pre-set or fixed peak-shaving order of plants, this paper formulates a new peak-shaving model based on the mixed integer linear programming (MILP) to solve the scheduling problem in an optimization way. Compared with the traditional peak-shaving methods that need to determine the order of plants to peak-shave the load curve one by one, the present model has better flexibility as it can handle the plant-based operating zones and prioritize the constraints and objectives more easily. With application to six cascaded hydropower reservoirs on the Lancang River in China, the model is tested efficient and practical in engineering perspective.
Macroalgae
Authors: Pereira Leonel
Published: February 2021

What are algae? Algae are organisms that perform photosynthesis; that is, they absorb carbon dioxide and release oxygen (therefore they have chlorophyll, a group of green pigments used by photosynthetic organisms that convert sunlight into energy via photosynthesis) and live in water or in humid places. Algae have great variability and are divided into microalgae, small in size and only visible through a microscope, and macroalgae, which are larger in size, up to more than 50 m (the maximum recorded was 65 m), and have a greater diversity in the oceans. Thus, the term “algae” is commonly used to refer to “marine macroalgae or seaweeds”. It is estimated that 1800 different brown macroalgae, 6200 red macroalgae, and 1800 green macroalgae are found in the marine environment. Although the red algae are more diverse, the brown ones are the largest.
Ash Trees (Fraxinus spp.) in Urban Greenery as Possible Invasion Gates of Non-Native Phyllactinia Species
Authors: Pastirčáková Katarína , Adamčíková Katarína , Bacigálová Kamila , Caboň Miroslav , Mikušová Petra , Senko Dušan , Svitok Marek , Adamčík Slavomír
Published: February 2021

Two Phyllactinia species have been associated with powdery mildew on leaves of ash trees (Fraxinus) in Eurasia, Phyllactinia fraxinicola U. Braun & H.D. Shin from Southeast Asia and Phyllactinia fraxini (DC.) Fuss from Europe. Non-native ash trees are planted in urban greeneries in both Europe and Southeast Asia, but so far, the two Phyllactinia species have not been reported from the same area. Our molecular analysis of European material consisting of 55 Phyllactinia specimens from 15 countries confirmed the absence of P. fraxinicola in Europe. In Europe, we confirmed P. fraxini on all three European native ash species and on the introduced Asian ash species, Fraxinus. chinensis ssp. Rhynchophylla (Hance) A.E. Murray and Fraxinus mandshurica Rupr, planted in arboreta. Among the 11 collections examined from Southeast Asia, 3 were identified as P. fraxini and 8 as P. fraxinicola. The environmental niches of the two Phyllactinia species do not show significant overlap in the multidimensional space defined by bioclimatic variables. This suggests that the Asian species P. fraxinicola is not adapted to conditions prevailing in most of Europe and does not represent an invasive threat across the continent. Models of the potential distribution of Phyllactinia species do not overlap in Europe, but there are some areas to the northwest that could be susceptible to invasion by P. fraxinicola.
The Possibility of Using the Chapman–Richards and Näslund Functions to Model Height–Diameter Relationships in Hemiboreal Old-Growth Forest in Estonia
Authors: Nigul Kristi , Padari Allar , Kiviste Andres , Noe Steffen M. , Korjus Henn , Laarmann Diana , Frelich Lee E. , Jõgiste Kalev , Stanturf John A. , Paluots Teele , Põldveer Eneli , Kängsepp Vivika , Jürgenson Harli , Metslaid Marek , Kangur Ahto
Published: February 2021

In light of the difficulties in stand volume estimation of natural forests, we analyzed height–diameter relationships and derived a set of height estimation equations for volume estimation for naturally developing forest ecosystems, using the Järvselja old-growth and the Laeva commercial forest in Estonia as a case study. This contribution presents an approach to model individual tree height–diameter relationships for Scots pine, common aspen, silver and downy birch, Norway spruce, black alder, gray alder, linden species, European ash, Norway maple, deciduous species and coniferous species in multi-size and mixed-species naturally developing stands in Estonia. Single-tree-level data were collected in 2013. Two methods were used to obtain stand-level data: whole surface inventory and partial surface inventory. To model the height–diameter relationship in naturally developed mixed-species forest stands in order to predict single tree height based on observed diameter at breast height, we applied nonlinear mixed models where we applied the Chapman–Richards and Näslund models as fixed-effects and the influence of the species contribution at the sites as random effects. The fixed-effects followed a set of criteria: (1) height starts at h = 1.3; d = 0; (2) the applied functions are monotonically increasing with a clear inflection point and 3) the fixed-effect model has an asymptotic value) in a naturally developed mixed-species forest.
Extractives of Stemwood and Sawmill Residues of Scots Pine (Pinus sylvestris L.) for Biorefining in Four Climatic Regions in Finland—Phenolic and Resin Acid Compounds
Authors: Verkasalo Erkki , Möttönen Veikko , Roitto Marja , Vepsäläinen Jouko , Kumar Anuj , Ilvesniemi Hannu , Siwale Workson , Julkunen-Tiitto Riitta , Raatikainen Olavi , Sikanen Lauri
Published: February 2021

This study aimed to identify and quantify phenolic and resin acid extractive compounds in Scots pine stemwood and sawmill residues in four climatic regions of Finland to evaluate their most optimal sources for bio-based chemical biorefining and bioenergy products. The sample consisted of 140 trees from 28 stands, and sawdust lots from 11 log stands. NMR for the overall extractive analysis and HPLC for the quantitative estimation of phenolic and resin acid compounds were employed. Correlation analysis, multivariate factor analysis, principle component analysis and multiple linear regression modelling were applied for statistical analysis. HPLC identified 12 extractive compounds and NMR five more resin acids. Pinosylvin (PS), pinosylvin monomethyl ether (PSMME), and partly neolignans/lignans occurred in the largest concentrations. Wood type caused the most variation, heartwood having larger concentrations than sapwood (sawdust between them). Regional differences in the concentrations were smaller, but factor analysis distinguished the northern and the southern regions into their own groups. The results indicated higher concentrations of PS, PSMME, and vanillic acid in southern regions and those of, e.g., PSMME glycoside, lignan 2, and neolignan 1 in northern regions. The rather low concentrations of extractives in stemwood and sawdust imply value-added products, efficient sorting and/or large raw material volumes.
Performance Assessment of Fluidic Oscillators Tested on the NASA Hump Model
Authors: Koklu Mehti
Published: February 2021

Flow separation control over a wall-mounted hump model was studied experimentally to assess the performance of fluidic oscillators (sweeping jet actuators). An array of fluidic oscillators was used to control flow separation. The results showed that the fluidic oscillators were able to achieve substantial control over the separated flow by increasing the upstream suction pressure and downstream pressure recovery. Using the data available in the literature, the performance of the fluidic oscillators was compared to other active flow control (AFC) methods such as steady blowing, steady suction, and zero-net-mass-flux (ZNMF) actuators. Several integral parameters, such as the inviscid flow comparison coefficient, pressure drag coefficient, and modified normal force coefficient, were used as quality metrics in the performance comparison of the AFC methods. These quality metrics indicated the superiority of the steady suction method, especially at lower excitation amplitudes that is followed by the fluidic oscillators, steady blowing, and the ZNMF actuators, respectively. An aerodynamic figure of merit (AFM) was also constructed using the integral parameters and AFC power usage. The AFM results revealed that, for this study, steady suction was the most efficient AFC method at lower excitation amplitudes. The steady suction loses its efficiency as the excitation amplitude increases, and the fluidic oscillators become the most efficient AFC method. Both the steady suction and the fluidic oscillators have an AFM > 1 for the range tested in this study, indicating that they provide a net benefit when the AFC power consumption is also considered. On the other hand, both the steady blowing and ZNMF actuators were found to be inefficient AFC methods (AFM < 1) for the current configuration. Although they improved the flow field by controlling flow separation, the power requirement was more than their benefit.
Microwave Assisted Extraction of Bioactive Carbohydrates from Different Morphological Parts of Alfalfa (Medicago sativa L.)
Authors: Solarte Daniela Alejandra , Ruiz-Matute Ana Isabel , Chito-Trujillo Diana M. , Rada-Mendoza Maite , Sanz María Luz
Published: February 2021

Despite the nutritional properties of alfalfa, its production is mainly for animal feed and it is undervalued as a food source. In this study, the valorization of alfalfa as a potential source of bioactive carbohydrates [inositols, α-galactooligosaccharides (α-GOS)] is presented. A Box–Behnken experimental design was used to optimize the extraction of these carbohydrates from leaves, stems, and seeds of alfalfa by solid–liquid extraction (SLE) and microwave-assisted extraction (MAE). Optimal extraction temperatures were similar for both treatments (40 °C leaves, 80 °C seeds); however, SLE required longer times (32.5 and 60 min vs. 5 min). In general, under similar extraction conditions, MAE provided higher yields of inositols (up to twice) and α-GOS (up to 7 times); hence, MAE was selected for their extraction from 13 alfalfa samples. Pinitol was the most abundant inositol of leaves and stems (24.2–31.0 mg·g−1 and 15.5–22.5 mg·g−1, respectively) while seed extracts were rich in α-GOS, mainly in stachyose (48.8–84.7 mg·g−1). In addition, inositols and α-GOS concentrations of lyophilized MAE extracts were stable for up to 26 days at 50 °C. These findings demonstrate that alfalfa is a valuable source of bioactive carbohydrates and MAE a promising alternative technique to obtain functional extracts.
Rare Earths as Authenticity Markers for the Discrimination of Greek and Turkish Pistachios Using Elemental Metabolomics and Chemometrics
Authors: Kalogiouri Natasa P. , Manousi Natalia , Klaoudatos Dimitris , Spanos Thomas , Topi Vilson , Zachariadis George A.
Published: February 2021

Pistachios are a nutritionally beneficial food source widely consumed all over the world. Pistachios exhibit high content of antioxidants, vitamins and other beneficial micronutrients, including nutrient elements and rare earth elements (REEs). Considering that the concentration of REEs depends on the climate and soil characteristics that vary among different geographical regions, REEs could constitute markers responsible for the geographical discrimination of this nut type. In this study, Greek pistachios with a protected designation of origin (PDO) label from Aegina Island and Fthiotida and Turkish pistachios from Adana were analyzed with inductively coupled plasma mass spectrometry (ICP-MS) to assess their REE profile. La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm and Yb were determined and quantified. The quantification results were further analyzed using the main effect plot, permutational analysis of variance (PERMANOVA), nonmetric multidimensional scaling (nMDS), principal component analysis (PCA) and hierarchical clustering (HCA) to investigate the similarities between the pistachios. A decision tree (DT) was developed for the classification of pistachios according to their geographical origin proving to be a promising and reliable tool for verifying the authenticity of food products on the basis of their REE profile.