bluuebunny/crossref_metadata_2025 huggingface dataset:
Free to Circulate: An Update on the Epidemiological Dynamics of Porcine Circovirus 2 (PCV-2) in Italy Reveals the Role of Local Spreading, Wild Populations, and Foreign Countries
Authors: Franzo Giovanni , Tinello Susanna , Grassi Laura , Tucciarone Claudia Maria , Legnardi Matteo , Cecchinato Mattia , Dotto Giorgia , Mondin Alessandra , Martini Marco , Pasotto Daniela , Menandro Maria Luisa , Drigo Michele
Published: March 2020

Porcine circovirus 2 (PCV-2) is one of the most impactful and widespread pathogens of the modern swine industry. Unlike other DNA viruses, PCV-2 is featured by a remarkable genetic variability, which has led to the emergence and recognition of different genotypes, some of which (PCV-2a, 2b, and 2d) have alternated over time. Currently, PCV-2d is considered the most prevalent genotype, and some evidence of differential virulence and vaccine efficacy have been reported. Despite the potential practical relevance, the data on PCV-2 epidemiology in Italy are quite outdated and do not quantify the actual circulation of this genotype in Italy. In the present study, 82 complete ORF2 sequences were obtained from domestic pigs and wild boars sampled in Northern Italy in the period 2013–2018 and merged with those previously obtained from Italy and other countries. A combination of phylogenetic, haplotype network, and phylodynamic analyses were used to genotype the collected strains and evaluate the temporal trend and the spatial and host spread dynamics. A rising number of PCV-2d detections was observed in domestic pigs, particularly since 2013, reaching a detection frequency comparable to PCV-2b. A similar picture was observed in wild boars, although a lower sequence number was available. Overall, the present study demonstrates the extreme complexity of PCV-2 molecular epidemiology in Italy, the significant spread across different regions, the recurrent introduction from foreign countries, and the frequent occurrence of recombination events. Although a higher viral flux occurred from domestic to wild populations than vice versa, wild boars seem to maintain PCV-2 infection and spread it over relatively long distances.
A Review on Design of Upper Limb Exoskeletons
Authors: Gull Muhammad Ahsan , Bai Shaoping , Bak Thomas
Published: March 2020

Exoskeleton robotics has ushered in a new era of modern neuromuscular rehabilitation engineering and assistive technology research. The technology promises to improve the upper-limb functionalities required for performing activities of daily living. The exoskeleton technology is evolving quickly but still needs interdisciplinary research to solve technical challenges, e.g., kinematic compatibility and development of effective human–robot interaction. In this paper, the recent development in upper-limb exoskeletons is reviewed. The key challenges involved in the development of assistive exoskeletons are highlighted by comparing available solutions. This paper provides a general classification, comparisons, and overview of the mechatronic designs of upper-limb exoskeletons. In addition, a brief overview of the control modalities for upper-limb exoskeletons is also presented in this paper. A discussion on the future directions of research is included.
Multi-Source and Multi-Temporal Image Fusion on Hypercomplex Bases
Authors: Schmitt Andreas , Wendleder Anna , Kleynmans Rüdiger , Hell Maximilian , Roth Achim , Hinz Stefan
Published: March 2020

This article spanned a new, consistent framework for production, archiving, and provision of analysis ready data (ARD) from multi-source and multi-temporal satellite acquisitions and an subsequent image fusion. The core of the image fusion was an orthogonal transform of the reflectance channels from optical sensors on hypercomplex bases delivered in Kennaugh-like elements, which are well-known from polarimetric radar. In this way, SAR and Optics could be fused to one image data set sharing the characteristics of both: the sharpness of Optics and the texture of SAR. The special properties of Kennaugh elements regarding their scaling—linear, logarithmic, normalized—applied likewise to the new elements and guaranteed their robustness towards noise, radiometric sub-sampling, and therewith data compression. This study combined Sentinel-1 and Sentinel-2 on an Octonion basis as well as Sentinel-2 and ALOS-PALSAR-2 on a Sedenion basis. The validation using signatures of typical land cover classes showed that the efficient archiving in 4 bit images still guaranteed an accuracy over 90% in the class assignment. Due to the stability of the resulting class signatures, the fuzziness to be caught by Machine Learning Algorithms was minimized at the same time. Thus, this methodology was predestined to act as new standard for ARD remote sensing data with an subsequent image fusion processed in so-called data cubes.
MODIS Fractional Snow Cover Mapping Using Machine Learning Technology in a Mountainous Area
Authors: Liu Changyu , Huang Xiaodong , Li Xubing , Liang Tiangang
Published: March 2020

To improve the poor accuracy of the MODIS (Moderate Resolution Imaging Spectroradiometer) daily fractional snow cover product over the complex terrain of the Tibetan Plateau (RMSE = 0.30), unmanned aerial vehicle and machine learning technologies are employed to map the fractional snow cover based on MODIS over this terrain. Three machine learning models, including random forest, support vector machine, and back-propagation artificial neural network models, are trained and compared in this study. The results indicate that compared with the MODIS daily fractional snow cover product, the introduction of a highly accurate snow map acquired by unmanned aerial vehicles as a reference into machine learning models can significantly improve the MODIS fractional snow cover mapping accuracy. The random forest model shows the best accuracy among the three machine learning models, with an RMSE (root-mean-square error) of 0.23, especially over forestland and shrubland, with RMSEs of 0.13 and 0.18, respectively. Although the accuracy of the support vector machine and back-propagation artificial neural network models are worse over forestland and shrubland, their average errors are still better than that of MOD10A1. Different fractional snow cover gradients also affect the accuracy of the machine learning algorithms. Nevertheless, the random forest model remains stable in different fractional snow cover gradients and is, therefore, the best machine learning algorithm for MODIS fractional snow cover mapping in Tibetan Plateau areas with complex terrain and severely fragmented snow cover.
Quantifying the Effects of Hurricanes Irma and Maria on Coastal Water Quality in Puerto Rico using Moderate Resolution Satellite Sensors
Authors: Hernández William J. , Ortiz-Rosa Suhey , Armstrong Roy A. , Geiger Erick F. , Eakin C. Mark , Warner Robert A.
Published: March 2020

Coastal, benthic communities, such as coral reefs, are at particular risk due to poor water quality caused by hurricanes. In addition to the physical impacts from wave action and storm surge, hurricanes bring significant rainfall resulting in increased runoff from land. Hurricanes Irma and Maria caused record or near-record floods at many locations across Puerto Rico and resulted in major impacts on coastal and benthic ecosystems from heavy rainfall and river discharge. In this study, we use imagery from the moderate resolution Visible Infrared Imaging Radiometer Suite (VIIRS) satellite to quantify the impacts of hurricanes Irma and Maria, which struck Puerto Rico during September 2017, on the water quality of the coastal waters of Puerto Rico using the chlorophyll-a (Chl-a) and the diffuse attenuation coefficient at 490 nm (Kd490) products. The objectives include: (1) quantify the water quality and light attenuation after the hurricanes; (2) compare this event to the climatology of these parameters, and 3) evaluate long-term exposure and exceedances of various coastal areas to low levels of turbidity. The Chl-a inner shelf values increased in 2017 during the months of June (8% above baseline), July (17%), August (5%), September (8%), October (19%), and November (28%) when compared to 2012–2016 baseline data. The values for Chl-a concentration reached and exceeded 0.45 µg/L by August 2017 and persisted above that value until December 2017. The Kd490 inner shelf values for 2017 increased (in percent) for the months of June (4% above baseline), July (9%), August (10%), September (5%), October (12%), and November (7%) when compared to 2012–2016 baseline data. The values of Kd490 in August, September, and December 2017 were the highest seen during 2012–2017. Even with the limitations of spatial resolution and loss of data to cloud cover, the 6-year imagery time-series analysis can provide a useful evaluation of the effects of these two hurricanes on the coastal water quality in Puerto Rico, and quantify the exposure of benthic habitats to higher nutrient and turbidity levels.
An Effective Way to Map Land-Use Intensity with a High Spatial Resolution Based on Habitat Type and Environmental Data
Authors: Meier Eliane Seraina , Indermaur Alexander , Ginzler Christian , Psomas Achilleas
Published: March 2020

Mapping and monitoring agricultural land-use intensity (LUI) changes are essential for understanding their effects on biodiversity. Current land-use models provide a rather coarse spatial resolution, while in-situ measurements of LUI cover only a limited extent and are time-consuming and expensive. The purpose of this study is to evaluate the feasibility of using habitat type, topo-climatic, economic output, and remote-sensing data to map LUI at a high spatial resolution. To accomplish this, we first rated the habitat types across the agricultural landscape in terms of the amount and frequency of fertiliser input, pesticide input, ploughing, grazing, mowing, harvesting, and biomass output. We consolidated these ratings into one LUI index per habitat type that we then related to topo-climatic, economic output, and remote-sensing predictors. The results showed that the LUI index was strongly related to plant indicator values for mowing tolerance and soil nutrient content and to aerial nitrogen deposition, and thus, is an adequate index. Topo-climatic, and, to a smaller extent, economic output and remote-sensing predictors, proved suitable for mapping LUI. Large- to medium-scale patterns are explained by topo-climatic predictors, while economic output predictors explain medium-scale patterns and remote-sensing predictors explain local-scale patterns. With the fine-scale LUI map produced from this study, it is now possible to estimate within unvarying land-use classes, the effect on agrobiodiversity of an increase in LUI on fertile and accessible lands and of a decrease of LUI by the abandonment of marginal agricultural lands, and thus, provide a valuable base for understanding the effects of LUI on biodiversity. Due to the worldwide availability of remote-sensing and climate data, our methodology can be easily applied to other countries where habitat-type data are available. Given their low explanatory power, economic output variables may be omitted if not available.
Hybrid Dynamic Traffic Model for Freeway Flow Analysis Using a Switched Reduced-Order Unknown-Input State Observer
Authors: Guo Yuqi , Li Bin , Christie Matthew Daniel , Li Zongzhi , Sotelo Miguel Angel , Ma Yulin , Liu Dongmei , Li Zhixiong
Published: March 2020

This paper introduces a new methodology for reconstructing vehicle densities of freeway segments by utilizing the limited data collected by traffic-counting sensors and developing a macroscopic traffic stream model formulated as a switched reduced-order state observer design problem with unknown or partially known inputs. Specifically, the traffic network is modeled as a hybrid dynamic system in a state space that incorporates unknown inputs. For freeway segments with traffic-counting sensors installed, vehicle densities are directly computed using field traffic count data. A reduced-order state observer is designed to analyze traffic state transitions for freeway segments without field traffic count data to indirectly estimate the vehicle densities for each freeway segment. A simulation-based experiment is performed applying the methodology and using data of a segment of Beijing Jingtong freeway in Beijing, China. The model execution results are compared with the field data associated with the same freeway segment, and highly consistent results are achieved. The proposed methodology is expected to be adopted by traffic engineers to evaluate freeway operations and develop effective management strategies.
Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity
Authors: Campbell Evan , Phinyomark Angkoon , Scheme Erik
Published: March 2020

This manuscript presents a hybrid study of a comprehensive review and a systematic (research) analysis. Myoelectric control is the cornerstone of many assistive technologies used in clinical practice, such as prosthetics and orthoses, and human-computer interaction, such as virtual reality control. Although the classification accuracy of such devices exceeds 90% in a controlled laboratory setting, myoelectric devices still face challenges in robustness to variability of daily living conditions. The intrinsic physiological mechanisms limiting practical implementations of myoelectric devices were explored: the limb position effect and the contraction intensity effect. The degradation of electromyography (EMG) pattern recognition in the presence of these factors was demonstrated on six datasets, where classification performance was 13% and 20% lower than the controlled setting for the limb position and contraction intensity effect, respectively. The experimental designs of limb position and contraction intensity literature were surveyed. Current state-of-the-art training strategies and robust algorithms for both effects were compiled and presented. Recommendations for future limb position effect studies include: the collection protocol providing exemplars of at least 6 positions (four limb positions and three forearm orientations), three-dimensional space experimental designs, transfer learning approaches, and multi-modal sensor configurations. Recommendations for future contraction intensity effect studies include: the collection of dynamic contractions, nonlinear complexity features, and proportional control.
Secrecy Performance Analysis of Wireless Powered Sensor Networks Under Saturation Nonlinear Energy Harvesting and Activation Threshold
Authors: Shang Xiaohui , Yin Hao , Wang Yida , Li Mu , Wang Yong
Published: March 2020

In this paper, we investigate the impact of saturation nonlinear energy harvesting (EH) and activation threshold on the multiuser wireless powered sensor networks (WPSNs) from the physical layer security (PLS) perspective. In particular, for improving the secrecy performance, the generalized multiuser scheduling (GMS) scheme is exploited, in which the Kth strongest sensor is chosen based on the legitimate link. For evaluating the impact of various key parameters on the security of system, we obtain the exact closed-form expressions for secrecy outage probability (SOP) under linear EH (LEH), saturation nonlinear EH (SNEH) and saturation nonlinear EH with activation threshold (SNAT), respectively, and solve the maximization problem of secure energy efficiency (SEE). Simulation results demonstrate that: (1) the number of source sensors, the EH efficiency and the transmit power of power beacon (PB) all have positive impact on SOP, and the smaller generalized selection coefficient is advantageous for secrecy performance; (2) LEH is an ideal situation for SNEH when the saturation threshold is large enough and SNEH is a special situation for SNAT when the activation threshold is low enough; (3) the time-switching factor and the activation threshold both have an important impact on the secrecy performance, which are worth considering carefully.
A Systematic Analysis of Narrowband IoT Quality of Service
Authors: Matz Andreas Philipp , Fernandez-Prieto Jose-Angel , Cañada-Bago Joaquin , Birkel Ulrich
Published: March 2020

Narrowband-IoT (NB-IoT) is part of a novel group of access technologies referred to as Low-Power Wide Area Networks (LPWANs), which provide energy-efficient and long-range network access to IoT devices. Although NB-IoT Release 13 has been deployed by Mobile Network Operators (MNO), detailed Quality of Service (QoS) evaluations in public networks are still rare. In this paper, systematic physical layer measurements are conducted, and the application layer performance is verified. Special consideration is given to the influence of the radio parameters on the application layer QoS. Additionally, NB-IoT is discussed in the context of typical smart metering use cases. The results indicate that NB-IoT meets most theoretical Third Generation Partnership Project (3GPP) design goals in a commercial deployment. NB-IoT provides a wide coverage by using signal repetitions, which improve the receiver sensitivity, but simultaneously increase the system latency. The maximum data rates are consistent over a wide range of coverage situations. Overall, NB-IoT is a reliable and flexible LPWAN technology for sensor applications even under challenging radio conditions. Four smart metering transmission categories are analyzed, and NB-IoT is verified to be appropriate for applications that are not latency sensitive.
Racquet Sports Recognition Using a Hybrid Clustering Model Learned from Integrated Wearable Sensor
Authors: Xia Kun , Wang Hanyu , Xu Menghan , Li Zheng , He Sheng , Tang Yusong
Published: March 2020

Racquet sports can provide positive benefits for human healthcare. A reliable detection device that can effectively distinguish movement with similar sub-features is therefore needed. In this paper, a racquet sports recognition wristband system and a multilayer hybrid clustering model are proposed to achieve reliable activity recognition and perform number counting. Additionally, a Bluetooth mesh network enables communication between a phone and wristband, and sets-up the connection between multiple devices. This allows users to track their exercise through the phone and share information with other players and referees. Considering the complexity of the classification algorithm and the user-friendliness of the measurement system, the improved multi-layer hybrid clustering model applies three-level K-means clustering to optimize feature extraction and segmentation and then uses the density-based spatial clustering of applications with noise (DBSCAN) algorithm to determine the feature center of different movements. The model can identify unlabeled and noisy data without data calibration and is suitable for smartwatches to recognize multiple racquet sports. The proposed system shows better recognition results and is verified in practical experiments.
Performance Evaluation of Convolutional Neural Network for Hand Gesture Recognition Using EMG
Authors: Asif Ali Raza , Waris Asim , Gilani Syed Omer , Jamil Mohsin , Ashraf Hassan , Shafique Muhammad , Niazi Imran Khan
Published: March 2020

Electromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still insufficient for natural control. Recent advancements in deep learning have shown tremendous progress in biosignal processing. Multiple architectures have been proposed yielding high accuracies (>95%) for offline analysis, yet the delay caused due to optimization of the system remains a challenge for its real-time application. From this arises a need for optimized deep learning architecture based on fine-tuned hyper-parameters. Although the chance of achieving convergence is random, however, it is important to observe that the performance gain made is significant enough to justify extra computation. In this study, the convolutional neural network (CNN) was implemented to decode hand gestures from the sEMG data recorded from 18 subjects to investigate the effect of hyper-parameters on each hand gesture. Results showed that the learning rate set to either 0.0001 or 0.001 with 80-100 epochs significantly outperformed (p < 0.05) other considerations. In addition, it was observed that regardless of network configuration some motions (close hand, flex hand, extend the hand and fine grip) performed better (83.7% ± 13.5%, 71.2% ± 20.2%, 82.6% ± 13.9% and 74.6% ± 15%, respectively) throughout the course of study. So, a robust and stable myoelectric control can be designed on the basis of the best performing hand motions. With improved recognition and uniform gain in performance, the deep learning-based approach has the potential to be a more robust alternative to traditional machine learning algorithms.
Characteristic Test Analysis of Graphene Plus Optical Microfiber Coupler Combined Device and Its Application in Fiber Lasers
Authors: Yu Yang , Chen Hao , Zhang Zhenfu , Chen Dingbo , Wang Jianfei , Wei Zhengtong , Yang Junbo , Yan Peiguang
Published: March 2020

In this study, a graphene and optical microfiber coupler (OMC) integrated device (GOMC) was proposed and fabricated. After its characteristic analysis and testing, it was applied to the development of adjustable multi-wavelength fiber lasers. By integrating the OMC with graphene, the polarization dependence of OMC was enhanced. Meanwhile, the novel GOMC was given the capabilities of filtering, coupling, beam splitting, and polarization correlation. When the GOMC was integrated as a filter and beam splitter into the ring cavity of the fiber laser, the proposed GOMC-based fiber laser could achieve single-wavelength and multi-wavelength regulated output. The laser had a 3 dB linewidth of less than 30 pm, a signal-to-noise ratio of approximately 40 dB, and an output power fluctuation of less than 1 dB. The GOMC could also be used for the development of functional devices, such as adjustable mode lockers and mode coupling selectors, which provide an excellent experimental platform for new fiber lasers and the research of multi-dimensional light-field manipulation.
Gait Recognition and Understanding Based on Hierarchical Temporal Memory Using 3D Gait Semantic Folding
Authors: Luo Jian , Tjahjadi Tardi
Published: March 2020

Gait recognition and understanding systems have shown a wide-ranging application prospect. However, their use of unstructured data from image and video has affected their performance, e.g., they are easily influenced by multi-views, occlusion, clothes, and object carrying conditions. This paper addresses these problems using a realistic 3-dimensional (3D) human structural data and sequential pattern learning framework with top-down attention modulating mechanism based on Hierarchical Temporal Memory (HTM). First, an accurate 2-dimensional (2D) to 3D human body pose and shape semantic parameters estimation method is proposed, which exploits the advantages of an instance-level body parsing model and a virtual dressing method. Second, by using gait semantic folding, the estimated body parameters are encoded using a sparse 2D matrix to construct the structural gait semantic image. In order to achieve time-based gait recognition, an HTM Network is constructed to obtain the sequence-level gait sparse distribution representations (SL-GSDRs). A top-down attention mechanism is introduced to deal with various conditions including multi-views by refining the SL-GSDRs, according to prior knowledge. The proposed gait learning model not only aids gait recognition tasks to overcome the difficulties in real application scenarios but also provides the structured gait semantic images for visual cognition. Experimental analyses on CMU MoBo, CASIA B, TUM-IITKGP, and KY4D datasets show a significant performance gain in terms of accuracy and robustness.
Ionization Gas Sensor Using Suspended Carbon Nanotube Beams
Authors: Arunachalam Shivaram , Izquierdo Ricardo , Nabki Frederic
Published: March 2020

An ionization sensor based on suspended carbon nanotubes (CNTs) was presented. A suspended CNT beam was fabricated by a low-temperature surface micromachining process using SU8 photoresist as the sacrificial layer. Application of a bias to the CNT beam generated very high non-linear electric fields near the tips of individual CNTs sufficient to ionize target gas molecules and initiate a breakdown current. The sensing mechanism of the CNT ionization sensor was discussed. The sensor response was tested in air, nitrogen, argon, and helium ambients. Each gas demonstrated a unique breakdown signature. Further, the sensor was tested with gaseous mixtures. The sensor exhibited good long-term stability and had comparable performance to other reported CNT-based ionization sensors in literature, which use high-temperature vapor deposition methods to grow CNTs. The sensor notably allowed for lower ionization voltages due to its reduced ionization gap size.
High-Efficiency Wavelet Compressive Fusion for Improving MEMS Array Performance
Authors: Liang Siyuan , Zhu Weilong , Zhao Feng , Wang Congyi
Published: March 2020

With the rapid development of microelectromechanical systems (MEMS) technology, low-cost MEMS inertial devices have been widely used for inertial navigation. However, their application range is greatly limited in some fields with high precision requirements because of their low precision and high noise. In this paper, to improve the performance of MEMS inertial devices, we propose a highly efficient optimal estimation algorithm for MEMS arrays based on wavelet compressive fusion (WCF). First, the algorithm uses the compression property of the multiscale wavelet transform to compress the original signal, fusing the compressive data based on the support. Second, threshold processing is performed on the fused wavelet coefficients. The simulation result demonstrates that the proposed algorithm performs well on the output of the inertial sensor array. Then, a ten-gyro array system is designed for collecting practical data, and the frequency of the embedded processor in our verification environment is 800 MHz. The experimental results show that, under the normal working conditions of the MEMS array system, the 100 ms input array data require an approximately 75 ms processing delay when employing the WCF algorithm to support real-time processing. Additionally, the zero-bias instability, angle random walk, and rate slope of the gyroscope are improved by 8.0, 8.0, and 9.5 dB, respectively, as compared with the original device. The experimental results demonstrate that the WCF algorithm has outstanding real-time performance and can effectively improve the accuracy of low-cost MEMS inertial devices.
Influence of Embedding Fiber Optical Sensors in CFRP Film Adhesive Joints on Bond Strength
Authors: Grundmann Neele , Brüning Hauke , Tserpes Konstantinos , Strohbach Tim , Mayer Bernd
Published: March 2020

The increasing utilization of carbon fiber reinforced plastic (CFRP) in the aeronautical industry calls for a structural health monitoring (SHM) system for adhesively bonded CFRP joints. Optical glass fiber with inscribed fiber Bragg gratings (FBGs) is a promising technology for a SHM system. This paper investigates the intrusive effect of embedding optical glass fibers carrying FBGs on adhesive bond strength and adhesive layer thickness and quality. Embedding the optical glass fibers directly in the adhesive bond has the advantage of directly monitoring the targeted structure but poses the risk of significantly reducing the bond strength. Optical glass fibers with different cladding diameters (50, 80, 125 µm) and coating types (polyimide, with a thickness of 3−8 µm, and acrylate, with a thickness of ~35 µm) are embedded in structural and repair film adhesives here. Without embedded optical glass fibers, the film adhesives have an adhesive layer thickness of ~90 µm (structural) and ~100 µm (repair) after curing. The intrusive effect of the fiber embedding on the adhesive bond strength is investigated here with quasi static and fatigue single lap joint (SLJ) tensile shear tests. Also, the influence of hydrothermal aging procedures on the quasi static tensile shear strength is investigated. It is found that optical glass fibers with a total diameter (glass fiber cladding + coating) of ~145 µm significantly reduce the quasi static tensile shear strength and increase the adhesive layer thickness and number of air inclusions (or pores) in the structural film adhesive joints. In the repair adhesive joints, no significant reduction of quasi static tensile shear strength is caused by the embedding of any of the tested fiber types and diameters. However, an increase in the adhesive layer thickness is detected. In both adhesive films, no effect on the quasi-static tensile shear strength is detected when embedding optical glass fibers with total diameters <100 µm. The applied aging regime only affects the repair film adhesive joints, and the structural film adhesive joints show no significant reduction. A polyimide-coated 80 µm optical glass fiber is selected for fatigue SLJ tensile shear tests in combination with the more sensitive structural film adhesive. No significant differences between the S-N curves and tensile shear fatigue strength of the reference samples without embedded optical fibers and the samples carrying the polyimide-coated 80 µm optical glass fibers are detected. Thus, it is concluded that the influences of embedding optical glass fibers with total diameters <100 µm on the fatigue limit of the tested film adhesive joints is negligible.
Piezoceramic-Based Damage Monitoring of Concrete Structure for Underwater Blasting
Authors: Si Jianfeng , Zhong Dongwang , Xiong Wei
Published: March 2020

This paper developed a piezoelectric-transducer-based damage detection of concrete materials after blasting. Two specimens (with or without an energy-relieving structure) were subjected to a 40 m deep-underwater blasting load in an underwater-explosion vessel, and their damage was detected by a multifunctional piezoelectric-signal-monitoring and -analysis system before and after the explosion. Statistical-data analysis of the piezoelectric signals revealed four zones: crushing, fracture, damage, and safe zones. The signal energy was analyzed and calculated by wavelet-packet analysis, and the blasting-damage index was obtained after the concrete specimen was subjected to the impact load of the underwater explosion. The damage of the two specimens gradually decreased from the blast hole to the bottom of the specimen. The damage index of the specimen with the energy-relieving structure differed for the fracture area and the damage area, and the damage protection of the energy-relieving structure was prominent at the bottom of the specimen. The piezoelectric-transducer-based damage monitoring of concrete materials is sensitive to underwater blasting, and with wavelet-packet-energy analysis, it can be used for postblasting damage detection and the evaluation of concrete materials.
Honey Bee Queens and Virus Infections
Authors: Amiri Esmaeil , Strand Micheline K. , Tarpy David R. , Rueppell Olav
Published: March 2020

The honey bee queen is the central hub of a colony to produce eggs and release pheromones to maintain social cohesion. Among many environmental stresses, viruses are a major concern to compromise the queen’s health and reproductive vigor. Viruses have evolved numerous strategies to infect queens either via vertical transmission from the queens’ parents or horizontally through the worker and drones with which she is in contact during development, while mating, and in the reproductive period in the colony. Over 30 viruses have been discovered from honey bees but only few studies exist on the pathogenicity and direct impact of viruses on the queen’s phenotype. An apparent lack of virus symptoms and practical problems are partly to blame for the lack of studies, and we hope to stimulate new research and methodological approaches. To illustrate the problems, we describe a study on sublethal effects of Israeli Acute Paralysis Virus (IAPV) that led to inconclusive results. We conclude by discussing the most crucial methodological considerations and novel approaches for studying the interactions between honey bee viruses and their interactions with queen health.
Metagenomic Detection of Two Vientoviruses in a Human Sputum Sample
Authors: Lázaro-Perona Fernando , Dahdouh Elias , Román-Soto Sergio , Jiménez-Rodríguez Sonia , Rodríguez-Antolín Carlos , de la Calle Fernando , Agrifoglio Alexander , Membrillo Francisco Javier , García-Rodríguez Julio , Mingorance Jesús
Published: March 2020

We used metagenomics to analyze one sputum sample from a patient with symptoms of a respiratory infection that yielded negative results for all pathogens tested. We detected two viral genomes that could be assembled and showed sequence similarity to redondoviruses, a recently described group within the CRESS-DNA viruses. One hundred sputum samples were screened for the presence of these viruses using specific primers. One sample was positive for the same two viruses, and another was positive for one of them. These findings raise questions about a possible role of redondoviruses in respiratory infections in humans.
Development of Next Generation Streptococcus pneumoniae Vaccines Conferring Broad Protection
Authors: Masomian Malihe , Ahmad Zuleeza , Ti Gew Lai , Poh Chit Laa
Published: March 2020

Streptococcus pneumoniae is a major pathogen causing pneumonia with over 2 million deaths annually, especially in young children and the elderly. To date, at least 98 different pneumococcal capsular serotypes have been identified. Currently, the vaccines for prevention of S. pneumoniae infections are the 23-valent pneumococcal polysaccharide-based vaccine (PPV23) and the pneumococcal conjugate vaccines (PCV10 and PCV13). These vaccines only cover some pneumococcal serotypes and are unable to protect against non-vaccine serotypes and unencapsulated S. pneumoniae. This has led to a rapid increase in antibiotic-resistant non-vaccine serotypes. Hence, there is an urgent need to develop new, effective, and affordable pneumococcal vaccines, which could cover a wide range of serotypes. This review discusses the new approaches to develop effective vaccines with broad serotype coverage as well as recent development of promising pneumococcal vaccines in clinical trials. New vaccine candidates are the inactivated whole-cell vaccine strain (Δpep27ΔcomD mutant) constructed by mutations of specific genes and several protein-based S. pneumoniae vaccines using conserved pneumococcal antigens, such as lipoprotein and surface-exposed protein (PspA). Among the vaccines in Phase 3 clinical trials are the pneumococcal conjugate vaccines, PCV-15 (V114) and 20vPnC. The inactivated whole-cell and several protein-based vaccines are either in Phase 1 or 2 trials. Furthermore, the recent progress of nanoparticles that play important roles as delivery systems and adjuvants to improve the performance, as well as the immunogenicity of the nanovaccines, are reviewed.
THE APPLICATION OF ULTRASOUND TO THE NEONATAL SCREENING&NBSP; AND DIAGNOSIS OF SOME CONGENITAL ANOMALIES
Authors: Nguyen Cong Quynh , Nguyen Viet Nhan , Vo Thanh Nhan
Published: March 2020

Key words: neonatal screening and diagnosis, ultrasound, congenital anomalies
ASSESSEMENT OF ORAL HEALTH STATUS OF CHILDREN WITH CLEFT LIP AND/OR PALATE IN THUA THIEN HUE PROVINCE
Authors: Nguyen Van Minh , Nguyen Hong Loi
Published: March 2020

Objective: to assess the dental health and oral hygiene status of subjects with cleft lip and/or palate. Methods: dental and gingival examinations were carried out in 105 children with cleft, using standard dental indices dmft and DMFT. Plaque and gingival indices were scored using the indices of Loe and Silness. Results: the prevalence of dental caries was significantly higher in children with cleft (71.34%) than children without cleft in both deciduous and permanent teeth. The dmft and DMFT indices ware highest in children with CLP (4.21±3.68; 3.55±3.24). Similary, plaque accumulation and gingivitis were significant higher in CL, CLP patients (3.29±1.28; 3.23±1.54) compared with CP patients (2.38±1.74). Conclusion: Cleft patients had higher prevalence of caries and poorer oral hygiene than patients without cleft. The severity of cleft affected on the oral health status. These findings not only provide a baseline for oral health status but also emphasize the need for preventive measures.

Key words: cleft lip, cleft palate, cleft lip and palate, dmft, DMFT, plaque and gingival index
INVESTIGATING ETIOLOGIES AND RENAL HISTOLOGIC PATTERNS IN 6 ELDERLY PATIENTS WITH NEPHROTIC SYNDROME
Authors: Nguyen Bach , Le Thi Thuy Trang , Huynh Ngoc Linh
Published: March 2020

Background: Nephrotic syndrome (NS) is the most common manifestation of glomerular diseases in the elderly and a most common indication of kidney biopsy. NS in the elderly is not as common as the young but more difficult to make diagnosis of etiologies, classification of renal histologic patterns and treatment because NS is frequently associated with various coexisting conditions. In Vietnam, the elderly population has been increased significantly therefore frequency of the elderly patients with NS is also increasing. Kidney biopsy is an invasive technique that is useful in diagnosing etiologies and classifying renal pathology. During recent years, renal pathology and biochemical immunology have been progressing rapidly. Therefore, the results of kidney biopsy are usually potential and valuable in clinical practice. We reported 6 elderly patients with NS performed kidney biopsy in Department of Nephrology, HCMCity during the period from 2/2012 to 12/2014 to investigate etiologies and renal histologic patterns. Materials and method: case report. The reported clinical cases were primary renal amyloidosis, IgA nephropathy secondary to liver cancer, minimal change NS associated with diabetes, NS caused by renal lymphoma infiltration, NS with minimal change associated by interferon and thrombotic microangiopathy. Conclusions: Nephrotic syndrome in the elderly might be associated with coexisting conditions and caused by several primary and secondary causes. Therefore, kidney biopsy should be considered to perform to make exact diagnosis in etiology, and to classify histologic patterns.

Key words: Nephrotic syndrome, elderly, histologic patterns, kidney biopsy
RELATIONS OF SERUM TGF-BETA1 LEVELS WITH AGE, SEX, BMI, BLOOD PRESSURE AND GLOMERULAR FILTRATION RATE IN PATIENT WITH CHRONIC KIDNEY DISEASE
Authors: Nguyen Van Tuan , Vo Tam , Hoang Bui Bao , Le Thi Phuong Anh , Ha Nguyen Tuong Van
Published: March 2020

Renal fibrosis is the main cause leading to end-stage chronic kidney disease. Transforming growth factor - beta 1 (TGF-beta1) have a major role in the process of renal fibrosis. Objectives: To survey the relation of serum TGF beta1 level with: age, sex, BMI, blood pressure and glomerular filtration rate. Method: A cross-sectional study. Results: Levels of serum TGF-beta1; in patients <40 year old, 40-60 year old and > 60 year of age were respectively 39,97 ± 9,76 ng / ml; 36,07 ± 10,10 ng / ml and 38,29 ± 10,87 ng / ml, p> 0,05. In men and women were respectively 36,71 ± 9,12 ng / ml and 40,43 ± 10,54, p> 0,05. In patient group with BMI ≤ 23 and > 23 were respectively 37,95 ± 9,85 ng / ml and 37,58 ± 12,38, p > 0,05. Levels of serum TGF-beta1 positive correlated with systolic blood pressure index (r = 0,40; p < 0,01) and negative correlated with glomerular filtration rate (r = - 0,29; p <0,01). Conclusion: There are no difference of serum TGF-beta1 levels between men and women, between the age groups (<40 years, 40 to < 60 years and ≥ 60 years), between BMI groups < 23 and BMI group ≥ 23. Level of serum TGF-beta1 positive correlated with systolic blood pressure index and negative correlated with glomerular filtration.vKey words: TGF-beta1, chronic kidney disease
RATE AND CLASSIFICATION OF DISLIPIDEMIA IN PATIENTS WITH IMPURE NEPHROTIC SYNDROME
Authors: Vo Tam , Phan Thi Nghia , Nguyen Thi Loc , Nguyen Thanh Minh
Published: March 2020

AIMS: To determine the rate, level, classification of dislipidemia in impure nephrotic syndrome patients. Patients and method: 47 in-patients with impure nephrotic syndrome at Department of Nephrology – Hue Central Hospital, from March, 2014 to March, 2015. Assess rate of dislipidemia according to guidelines of Asia Pacific Association and Vietnam National Heart Association 1998. Assess level of dislipidemia by NCEP ATPIII (2001) and classify dislipidemia by Fredrickson’s criteria. Results :Mean concentration of CT: 11.53±4.59 mmol/L; TG: 4.21±3.68 mmol/L; LDL-C: 7.55±3.95 mmol/L; HDL-C: 1.78±0.70 mmol/L. 98% of patients have at least abnormal in 1 component of lipidemia. 75% of patients have dislipidemia in all of three components. 94% of patients have high-limit to high CT; 94% of patients have high-limit to high TG; 90% of patients have high-limit to high LDL-C; 11% of patients have low-level of HDL-C. Dislipidemia type II is very common (88%), therein type IIb is found in 75%; type IIa in 13% of cases. Conclusion: In patients with impure nephrotic syndrome, dislipidemia is very common, disorders are in high risk level. Many components of lipidemia are abnormal at the same time, type II is dominant. Key words: nephrotic syndrome, impure, lipidemia.
PCR-RFLP DETECTION OF POINT MUTATIONS CONFERRING RESISTANCE TO CLARITHROMYCIN OF HELICOBACTER PYLORI IN QUANG NGAI
Authors: Pham Ngoc Doanh , Tran Van Huy , Ha Thi Minh Thi
Published: March 2020

Background: Clarithromycin resistance of H-pylori is the main cause leading to treatment failure. Aim: The purpose of this study was to determine the rate of clarithromycin resistance mutation on gene 23S ribosomal popular robonucleotide acid (rRNA) of H-pylori in patients with chronic gastritis in Quang Ngai General Hospital PCR-RFLP. Method: This is a cross-sectional study in 64 patients infected with H-pylori was determined by 3 methods and chronic gastritis proven by histology. Sample collection conducted in Quang Ngai general hospital and molecular biology tests were conducted in the medical genetics department Hue of Medical and Pharmaceutical University. Urease test, histopathological examination and perform HE staining PCR 23S rRNA gene fragment of H-pylori to determine H-pylori infection. Analysis of genetic mutations in the 23S rRNA point is performed by PCR-RFLP technique. Results: Of the 64 biopsies qualify included in the study, 41 samples with clarithromycin resistance point mutations (64%), of which 40 (62.5%) had mutations A2143A, one sample with A2142A (2%). No samples had mutations A2142C and no more than one mutation.Conclusion: This is the first time we report mutations related to clarithromycin of H-pylori in Quang Ngai province. Mutations rate is high (64%), among the common mutations, the most common mutantation is A2143G. Key words: Helicobacter pylori, clarithromycin resistance, PCR-RFLP, point mutations
RESULTS OF ENDOSCOPIC RETROGRADE CHOLANGIOPANCREATOGRAPHY COMBINED WITH SPHINCTEROTOMY IN TREATMENT OF COMMON BILE DUCT STONES
Authors: Vinh Khanh , Tran Van Huy , Trinh Dinh Hy
Published: March 2020

Background: Common bile duct stone is the popular disease which leads to more severe complication. Endoscopic retrograde cholangiopancreatography is a useful therapy in treatment of common bile duct stone. However, the success of this therapy must depend on several specific impacts including the number of stones, stone diameter, diverticulum and endoscopist. Thus, we have performed this research on two major purposes: 1) to evaluate the results and complication of ERCP in treatment of common bile duct stone; and 2) to determine the influential factors causing failure of this therapy. Patients/Research methods: A total of 64 patients are involved in the treatment at the gastrointestinal endoscopic center. Methods: A cross - sectional study. Result: CBD stone with size from 10 – 20mm makes up the highest proportion of 76.7%. A single stone makes up for the large proportion at 68.7%. The successful rate of CBD is 89.1%. The rate of complication is 10.9%. The influential factor for failure of ERCP: The patients undergoing operation have diverticulum and large stone. Conclusion: ERCP is an effective and safe therapy for treatment CDB stone. Key words: Common bile duct stone, endoscopic retrograde cholangiopancreatography.
THE ROLL OF GENERIC DRUGS– QUALITY AND ECONOMIC ASPECT IN TREATMENT
Authors: Tran Huu Dung , Nguyen Phuoc Bich Ngoc
Published: March 2020

Generic drugs have an important role in ensuring the efficacy, safety, and especially the economic aspect of drug use. A generic drug is a pharmaceutical product, usually intended to be interchangeable with an innovator product manufactured without a licence from the innovator company and marketed after the expiry date of the patent or other exclusive rights. At present, unlikely FDA’s regulations, Vietnam’s law does not require all generic drugs launching in the market to prove the bioequivalence, the same efficient and safe as innovator drugs. Because of the rapid growth of the domestic pharmaceutical market, the standard and quality of generic drugs compared with innovator drugs have to be consolidated and proved through trials of bioequivalence, then building the faith of professionals and patients in using generic drugs. Thus the expansion of number and improving quality of the bioequivalence assessment centers become an important task of Vietnam pharmaceutical industry in the context of integration with the global pharmaceutical industry. Key words: generic drugs, innovator drugs, patent, bioequivalence, treatment.