bluuebunny/crossref_metadata_2025 huggingface dataset:
Reduction of Protein Bound Methionine Sulfoxide by a Periplasmic Dimethyl Sulfoxide Reductase
Authors: Tarrago Lionel , Grosse Sandrine , Lemaire David , Faure Laetitia , Tribout Mathilde , Siponen Marina I. , Kojadinovic-Sirinelli Mila , Pignol David , Arnoux Pascal , Sabaty Monique
Published: July 2020

In proteins, methionine (Met) can be oxidized into Met sulfoxide (MetO). The ubiquitous methionine sulfoxide reductases (Msr) A and B are thiol-oxidoreductases reducing MetO. Reversible Met oxidation has a wide range of consequences, from protection against oxidative stress to fine-tuned regulation of protein functions. Bacteria distinguish themselves by the production of molybdenum-containing enzymes reducing MetO, such as the periplasmic MsrP which protects proteins during acute oxidative stress. The versatile dimethyl sulfoxide (DMSO) reductases were shown to reduce the free amino acid MetO, but their ability to reduce MetO within proteins was never evaluated. Here, using model oxidized proteins and peptides, enzymatic and mass spectrometry approaches, we showed that the Rhodobacter sphaeroides periplasmic DorA-type DMSO reductase reduces protein bound MetO as efficiently as the free amino acid L-MetO and with catalytic values in the range of those described for the canonical Msrs. The identification of this fourth type of enzyme able to reduce MetO in proteins, conserved across proteobacteria and actinobacteria, suggests that organisms employ enzymatic systems yet undiscovered to regulate protein oxidation states.
Best Practices on Metamodel-Based Photovoltaic Monitoring System with Prediction Method for Photovoltaic Power Generation
Authors: Jang Woo Sung , Hong Je Seong , Kim Jang Hwan , Jeon Byung Kook , Kim R. Young Chul
Published: July 2020

HS Solar Energy Company Inc. in Sejong city, Korea, has a big problem on how to monitor heterogeneous inverters with different protocols. Still a current photovoltaic power plant with different inverters, it has attracted significant attention to its experience of difficulties in monitoring integrated power generation. To solve this problem for the company, we adapt a metamodel mechanism to easily manage and integrate heterogeneous data into a metamodel-based data format. The existing metamodel-based photovoltaic monitoring system (M-PVMS) of the HS solar energy company also needs to simply predict the photovoltaic power generation in a day for small farm owners in the countryside. Therefore, we propose a method for predicting the power generation of M-PVMS panels using the gated recurrent unit (GRU) algorithm, which supports real-time learning to predict the photovoltaic system behavior that rapidly accumulates data in real time. As a result, we can predict the power generation for small farm owners with a probability of 96.353%.
Novel Motion Sickness Minimization Control via Fuzzy-PID Controller for Autonomous Vehicle
Authors: Saruchi Sarah ‘Atifah , Mohammed Ariff Mohd Hatta , Zamzuri Hairi , Amer Noor Hafizah , Wahid Nurbaiti , Hassan Nurhaffizah , Kassim Khairil Anwar Abu
Published: July 2020

In terms of vehicle dynamics, motion sickness (MS) occurs because of the large lateral acceleration produced by inappropriate wheel turning. In terms of passenger behavior, subjects experience MS because they normally tilt their heads towards the direction of lateral acceleration. Relating these viewpoints, the increment of MS originates from the large lateral acceleration produced by the inappropriate wheel’s turn, which then causes greater head movement with respect to the lateral acceleration direction. Therefore, this study proposes the utilization of fuzzy-proportional integral derivative (PID) controller for an MS minimization control structure, where the interaction of the lateral acceleration and head tilt concept is adopted to diminish the lateral acceleration. Here, the head movement is used as the controlled variable to compute the corrective wheel angle. The estimation of the head movement is carried out by an estimation model developed by the radial basis function neural network (RBFNN) method. An experiment involving a driving simulator was conducted, to verify the proposed control system’s performance in regard to the autonomous vehicle’s passengers. The results show that the averages of motion sickness incidence (MSI) index can be lowered by 3.95% for single lap and 11.49% for ten laps.
Development of a Highly Densified Magnetic Sheet for Inductors and Advanced Processes through Silane Surface Treatment of Fe Nanopowder
Authors: Lee Taegyu , Jung Hyeonjin , Song Yeonghwan , Cho Seungchan , Kim Dong-Hyun , Kim Yangdo , Lee Yoon-Seok , Park Yongho , Choi Moonhee
Published: July 2020

For developing subminiature and highly integrated multilayer inductors, soft magnetic powder was used; however, its ferrite magnetic component is characterized by high resistivity and reduced direct current saturation, leading to the deterioration of the inductor under high currents. Therefore, herein, to improve the electromagnetic properties of thin-film inductors, Fe nanopowder was used to increase the volume fraction of magnetic sheets. Surface treatment was performed by using silane coupling agents, which improved the bonding strength and dispersibility of the Fe nanopowder with a heterogeneous epoxy binder. For uniform surface treatment on the nanopowder, the silane-treated powder was aged for 24 h, at a temperature of 3 °C. The surface-treated Fe nanopowder was used with a mixing ratio of the soft magnetic powder (coarse:fine:nano) of 7:2.5:0.5 wt.%; this was successful in producing a flexible and highly densified magnetic sheet. As a result, the volume fraction of the magnetic sheet for thin-film inductors to which a low-temperature aging-treated nanopowder was applied was significantly improved.
Tridimensional Long-Term Finite Element Analysis of Reinforced Concrete Structures with Rate-Type Creep Approach
Authors: Di Luzio Giovanni , Cedolin Luigi , Beltrami Carlo
Published: July 2020

This paper presents a general procedure for a rate-type creep analysis (based on the use of the continuous retardation spectrum) which avoids the need of recalculating the Kelvin chain stiffness elements at each time step. In this procedure are incorporated three different creep constitutive relations, two recommended by national codes such as the ACI (North-American) and EC2 (European) building codes and one by the RILEM research association. The approximate expressions of the different creep functions with the corresponding Dirichlet series are generated using the continuous retardation spectrum approach based on the Post–Widder formula. The proposed rate-type formulation is implemented into a 3D finite element code and applied to study the long-term deflections of a prestressed concrete bridge built in Romania, which crosses a wide artificial channel that connects the Danube river to the port of Constanta in the Black Sea.
A New Method to Lightweight Magnesium Using Syntactic Composite Core
Authors: Matli Penchal Reddy , Sheng Joshua Goh Yong , Parande Gururaj , Manakari Vyasaraj , Chua Beng Wah , Wong Stephen Chee Khuen , Gupta Manoj
Published: July 2020

Light weighting of magnesium-based materials is crucial for its extensive use in transportation applications. Hybrid processing of these materials in a shell-core pattern can substantially improve the specific properties of magnesium. In the present study, the Mg/Mg-20GMB (glass microballoon) hybrid composite was prepared using a disintegrated melt deposition technique. Microstructural characterization and mechanical properties of the developed as-cast Mg/Mg-20GMB hybrid composite were investigated. Results revealed that a unified metallurgical interface was formed between the Mg-20GMB core material and the pure Mg shell. Energy dispersive X-ray spectroscopy (EDX) results confirmed the existence of Mg2Si as the secondary phase in the Mg-20GMB core material. The hybrid Mg/Mg-20GMB composite exhibited much superior compressive yield strength (↑71.6%), lower ultimate compressive strength (↓23.25%), and enhanced ductility (↑186.48%) when compared to as-cast pure magnesium.
Batch Stirred-Tank Green Extraction of Salvia fruticosa Mill. Polyphenols Using Newly Designed Citrate-Based Deep Eutectic Solvents and Ultrasonication Pretreatment
Authors: Grigorakis Spyros , Halahlah Abedalghani , Makris Dimitris P.
Published: July 2020

A series of citrate salts were tested as hydrogen bond acceptors to synthesize deep eutectic solvents (DES) based on lactic acid and glycerol, used as hydrogen bond donors. The DES produced were then screened to identify the highest performing system for the effective extraction of polyphenolic phytochemicals from the medicinal plant Salvia fruticosa Mill. (Greek sage). The most efficacious DES was the one composed of lactic acid and sodium citrate dibasic, at a molar ratio of 15:1 (LA-SCDB15). Furthermore, for the first time there has been evidence concerning DES pH and extraction efficiency. Using this solvent, a batch, stirred-tank extraction process was developed, by employing ultrasonication pretreatment and response surface methodology. The optimal settings determined were stirring speed 900 rpm, proportion of DES/water 77% (w/v), and ultrasonication pretreatment time 15 min. By adjusting these optimal settings, the predicted maximum total polyphenol yield was calculated to be 79.93 ± 1.92 mg gallic acid equivalents g−1 dry mass. The examination of temperature effects demonstrated that the batch, stirred-tank extraction stage was very energy-efficient, with a barrier of 7.64 kJ mol−1. Comparison of the extraction of Salvia fruticosa polyphenols with other green processes previously developed, illustrated the high extraction capacity of LA-SCDB15. The major polyphenols identified in the extracts produced under optimized settings were chlorogenic acid, luteolin 7-O-glucuronide and rosmarinic acid.
An Overview of Material Extrusion Troubleshooting
Authors: Hsiang Loh Giselle , Pei Eujin , Gonzalez-Gutierrez Joamin , Monzón Mario
Published: July 2020

Material extrusion (ME) systems offer end-users with a more affordable and accessible additive manufacturing (AM) technology compared to other processes in the market. ME is often used to quickly produce low-cost prototyping with the freedom of scalability where parts can be produced in different geometries, quantities and sizes. As the use of desktop ME machines has gained widespread adoption, this review paper discusses the key design strategies and considerations to produce high quality ME parts, as well as providing actional advice to aid end-users in quickly identifying and efficiently troubleshooting issues since current information is often fragmented and incomplete. The systemic issues and solutions concerning desktop ME processes discussed are not machine-specific, covering categories according to printer-associated, deposition-associated and print quality problems. The findings show that the majority of issues are associated with incorrect printer calibration and parameters, hardware, material, Computer Aided Design (CAD) model and/or slicing settings. A chart for an overview of ME troubleshooting is presented allowing designers and engineers to straightforwardly determine the possible contributing factors to a particular problem.
Simulation Study on the Influence of Multifrequency Ultrasound on Transient Cavitation Threshold in Different Media
Authors: Dong Hu , Zou Xiao , Qian Shengyou
Published: July 2020

Through the introduction of multifrequency ultrasound technology, remarkable results have been achieved in tissue ablation and other aspects. By using the nonlinear dynamic equation of spherical bubble, the effects of the combination mode of multifrequency ultrasound, the peak negative pressure and its duration, the phase angle difference, and the polytropic index on the transient cavitation threshold in four different media of water, blood, brain, and liver are simulated and analyzed. The simulation results show that under the same frequency difference and initial bubble radius, the transient cavitation threshold of the high-frequency, triple-frequency combination is higher than that of the low-frequency, triple-frequency combination. When the lowest frequency of triple frequencies is the same, the larger the frequency difference, the higher the transient cavitation threshold. When the initial bubble radius is small, the frequency difference has little effect on the transient cavitation threshold of the triple-frequency combination. With the increase of initial bubble radius, the influence of frequency difference on the transient cavitation threshold of the higher frequency combination of triple frequency is more obvious than that of the lower frequency combination of triple frequency. When the duration of peak negative pressure or peak negative pressure of the multifrequency combined ultrasound is longer than that of the single-frequency ultrasound, the transient cavitation threshold of the multifrequency combined ultrasound is lower than that of the single-frequency ultrasound; on the contrary, the transient cavitation threshold of the multifrequency combined ultrasound is higher than that of the single-frequency ultrasound. When the phase angle difference of multifrequency excitation is zero, the corresponding transient cavitation threshold is the lowest, while the change of the polytropic index has almost no effect on the transient cavitation threshold for the multifrequency combination. The research results can provide a reference for multifrequency ultrasound to reduce the transient cavitation threshold, which is of great significance for the practical application of cavitation.
Forward Transformation from Reactive Near-Field to Near and Far-Field at Millimeter-Wave Frequencies
Authors: Pfeifer Serge , Fallahi Arya , Xi Jingtian , Neufeld Esra , Kuster Niels
Published: July 2020

With the advent of 5G mobile communications at millimeter-wave frequencies, the assessment of the maximum averaged power density on numerous surfaces close to the transmitter will become a requirement. This makes phasor knowledge about the electric and magnetic fields an inevitable requirement. To avoid the burdensome measurement of these field quantities in the entire volume of interest, phase reconstruction algorithms from measurements over a plane in the far-field region are being extensively developed. In this paper, we extended the previously developed method of phase reconstruction to evaluate the near and far-field of sources with bounded uncertainty, which is robust with respect to noisy data and optimized for a minimal number of measurement points at a distance as close as λ /5 from the source. The proposed procedure takes advantage of field integral equations and electric field measurements with the EUmmWVx probe to evaluate the field phasors close to the radiation source and subsequently obtain the field values in the whole region of interest with minimal computation and measurement costs. The main constraints are the maximal noise level regarding the peak electric field and measurement plane size with respect to the percentage of transmitted power content. The measurement of a third plane overcomes some of the noise issues. The method was evaluated by simulations of a wide range of antennas at different noise levels and at different distances and by measurements of four different antennas. A successful reconstruction in the near and far-field was achieved both qualitatively and quantitatively for distances between 2.5–150 mm from the antenna and noise levels of −24 dB from the peak. The deviation of reconstruction from the simulation reference for the peak spatial-average power density with an averaging area of 1 cm 2 was, in all cases, well within the uncertainty budget of 0.6 dB, if the reconstruction planes captured >95% of the total radiated power. The proposed new method is very promising for compliance assessment and can reduce test time considerably.
Tunable Plasmonic Talbot Effect Based on Graphene Monolayer
Authors: Ma Huanxi , Su Shaojian , Zhou Hengjie , Zhao Zeyang , Lin Zhili , Qiu Weibin
Published: July 2020

In this article, the plasmonic Talbot effect supported by a graphene monolayer is investigated theoretically when surface plasmon polaritons (SPPs) are excited on the graphene. The Talbot effect distance is studied by varying the chemical potential, wavelength and the period of grating. The Talbot distance increases with the period in a parabolic way, and exhibits the opposite trends with respect to the chemical potential and wavelength. Moreover, the full width at half maximum (FWHM) of the Talbot image is recorded as a function of chemical potential and the wavelength. This study provides a new approach for sub-wavelength scale imaging and extends the applications of Talbot effect as well as graphene-based plasmonic devices.
A New Perspective of Multiple Roller Compaction of Microcrystalline Cellulose for Overcoming Re-Compression Drawbacks in Tableting Processing
Authors: Abu Fara Deeb , Rashid Iyad , Al-Hmoud Linda , Chowdhry Babur Z. , Badwan Adnan A.
Published: July 2020

In this paper, new scientific insights in relation to the re-compaction of microcrystalline cellulose (MCC; Avicel®® PH-101) under specific compaction conditions are reported. MCC was subjected to multiple compaction cycles (1st, 2nd, and 3rd) under high compaction pressures, up to 20,000 kPa, using a roller compactor of 100 kg/h capacity. Initially, granules from the 1st and 2nd compaction cycles produced tablets with lower crushing strength compared to those made from the original non-compacted MCC. Tablet weakness was found to be correlated to the generation of a higher intra-granular pore size (diameter) and hence higher tablet porosity compared to that of the original MCC particles. Using Kawakita and Heckel compression analyses, it is suggested that such behavior is attributed to the formation of harder granules of re-compressed powder with a larger diameter than non-compacted MCC particles. Moreover, these granules resulted in a reduction in powder bed volume after the powders were subjected to the 1st and 2nd compaction cycles. Surprisingly, granules resulting from the 3rd compaction cycle produced tablets displaying a higher crushing force than non-compacted MCC. Results from compression analysis indicated a reduction in both the intra-granular pore size (diameter) and in tablet porosity of Avicel PH-101-3rd compaction cycle compared to that of the original non-compacted MCC. It is concluded that intense compression causes shedding of one or more layer from MCC fibers exposing new surfaces with strong binding ability. The foregoing results infer that intensified roller compaction can be employed to improve MCC powder compactibility without any deleterious effects on compact strength.
Influence of Three Dental Implant Surfaces on Cell Viability and Bone Behavior. An In Vitro and a Histometric Study in a Rabbit Model
Authors: Rizo-Gorrita María , Fernandez-Asian Ignacio , Garcia-de-Frenza Andreina , Vazquez-Pachon Celia , Serrera-Figallo Maria-Angeles , Torres-Lagares Daniel , Gutierrez-Perez Jose-Luis
Published: July 2020

The chemical composition and the surface characteristics of dental implants are factors that have a decisive effect on the osseointegration process. The surface characterization at the compositional and topographic level of three dental implants available in the market was performed with different surface treatments: (1) sandblasted and acid etched surface (SLA), (2) hydroxyapatite (HA) and tricalcium phosphate (TCP) blasted surface (HA/TCP), and (3) HA-blasted and non-etching acid washed surface (HA + AW). In addition, an in vitro viability study of MG-63 osteoblast cells was performed with a JC-1 test. To complete the study, an in vivo study was conducted in New Zealand rabbits. The study analyzed the histometric characteristics of the bone formed around the implants at the level of area, volume, bone density, accumulated bone density, and bone–implant contact (BIC). The rabbits were sacrificed at 6 weeks after implants were placed in the tibial metaphysis. No statistically significant differences were observed at the level of cell viability or histometric parameters between the different study groups (p > 0.05). SLA and HA/TCP surfaces were the ones that obtained a higher BIC value. Taking into account the limitations of this study, it can be concluded that the different implant surfaces analyzed favor a good bone response.
Pipelined Dynamic Scheduling of Big Data Streams
Authors: Souravlas Stavros , Anastasiadou Sofia
Published: July 2020

We are currently living in the big data era, in which it has become more necessary than ever to develop “smart” schedulers. It is common knowledge that the default Storm scheduler, as well as a large number of static schemes, has presented certain deficiencies. One of the most important of these deficiencies is the weakness in handling cases in which system changes occur. In such a scenario, some type of re-scheduling is necessary to keep the system working in the most efficient way. In this paper, we present a pipeline-based dynamic modular arithmetic-based scheduler (PMOD scheduler), which can be used to re-schedule the streams distributed among a set of nodes and their tasks, when the system parameters (number of tasks, executors or nodes) change. The PMOD scheduler organizes all the required operations in a pipeline scheme, thus reducing the overall processing time.
OpenMP Implementation of a Novel Potential-Field-Data Source-Growth-Based Inversion Approach for 3D Salt Imaging in Deepwater Gulf of Mexico
Authors: Vera Naín , Couder-Castañeda Carlos , Hernández Jorge , Trujillo-Alcántara Alfredo , Orozco-del-Castillo Mauricio , Ortiz-Aleman Carlos
Published: July 2020

Potential-field-data imaging of complex geological features in deepwater salt-tectonic regions in the Gulf of Mexico remains an open active research field. There is still a lack of resolution in seismic imaging methods below and in the surroundings of allochthonous salt bodies. In this work, we present a novel three-dimensional potential-field-data simultaneous inversion method for imaging of salt features. This new approach incorporates a growth algorithm for source estimation, which progressively recovers geological structures by exploring a constrained parameter space; restrictions are posed from a priori geological knowledge of the study area. The algorithm is tested with synthetic data corresponding to a real complex salt-tectonic geological setting commonly found in exploration areas of deepwater Gulf of Mexico. Due to the huge amount of data involved in three-dimensional inversion of potential field data, the use of parallel computing techniques becomes mandatory. In this sense, to alleviate computational burden, an easy to implement parallelization strategy for the inversion scheme through OpenMP directives is presented. The methodology was applied to invert and integrate gravity, magnetic and full tensor gradient data of the study area.
High-Precision Cutting Edge Radius Measurement of Single Point Diamond Tools Using an Atomic Force Microscope and a Reverse Cutting Edge Artifact
Authors: Zhang Kai , Cai Yindi , Shimizu Yuki , Matsukuma Hiraku , Gao Wei
Published: July 2020

This paper presents a measurement method for high-precision cutting edge radius of single point diamond tools using an atomic force microscope (AFM) and a reverse cutting edge artifact based on the edge reversal method. Reverse cutting edge artifact is fabricated by indenting a diamond tool into a soft metal workpiece with the bisector of the included angle between the tool’s rake face and clearance face perpendicular to the workpiece surface on a newly designed nanoindentation system. An AFM is applied to measure the topographies of the actual and the reverse diamond tool cutting edges. With the proposed edge reversal method, a cutting edge radius can be accurately evaluated based on two AFM topographies, from which the convolution effect of the AFM tip can be reduced. The accuracy of the measurement of cutting edge radius is significantly influenced by the geometric accuracy of reverse cutting edge artifact in the proposed measurement method. In the nanoindentation system, the system operation is optimized for achieving high-precision control of the indentation depth of reverse cutting edFigurege artifact. The influence of elastic recovery and the AFM cantilever tip radius on the accuracy of cutting edge radius measurement are investigated. Diamond tools with different nose radii are also measured. The reliability and capability of the proposed measurement method for cutting edge radius and the designed nanoindentation system are demonstrated through a series of experiments.
Modeling Photovoltaic Potential for Bus Shelters on a City-Scale: A Case Study in Lisbon
Authors: Santos Teresa , Lobato Killian , Rocha Jorge , Tenedório José António
Published: July 2020

The 2030 Agenda for Sustainable Development set 17 Sustainable Development Goals (SDGs). These include ensuring access to affordable, reliable, sustainable and modern energy for all (SGD7) and making cities and human settlements inclusive, safe, resilient and sustainable (SGD11). Thus, across the globe, major cities are moving in the smart city direction, by, for example, incorporating photovoltaics (PV), electric buses and sensors to improve public transportation. We study the concept of integrated PV bus stop shelters for the city of Lisbon. We identified the suitable locations for these, with respect to solar exposure, by using a Geographic Information System (GIS) solar radiation map. Then, using proxies to describe tourist and commuter demand, we determined that 54% of all current city bus stop shelters have the potential to receive PV-based solutions. Promoting innovative solutions such as this one will support smart mobility and urban sustainability while increasing quality of life, the ultimate goal of the Smart Cities movement.
Synthesis and Characterization of Free-Stand Graphene/Silver Nanowire/Graphene Nano Composite as Transparent Conductive Film with Enhanced Stiffness
Authors: Guo Chuanrui , Li Yanxiao , Zhu Yanping , Wu Chenglin , Chen Genda
Published: July 2020

As-grown graphene via chemical vapor deposition (CVD) has potential defects, cracks, and disordered grain boundaries induced by the synthesis and transfer process. Graphene/silver nanowire/graphene (Gr/AgNW/Gr) sandwich composite has been proposed to overcome these drawbacks significantly as the AgNW network can provide extra connections on graphene layers to enhance the stiffness and electrical conductivity. However, the existing substrate (polyethylene terephthalate (PET), glass, silicon, and so on) for composite production limits its application and mechanics behavior study. In this work, a vacuum annealing method is proposed and validated to synthesize the free-stand Gr/AgNW/Gr nanocomposite film on transmission electron microscopy (TEM) grids. AgNW average spacing, optical transmittance, and electrical conductivity are characterized and correlated with different AgNW concentrations. Atomic force microscope (AFM) indentation on the free-stand composite indicates that the AgNW network can increase the composite film stiffness by approximately 460% with the AgNW concentration higher than 0.6 mg/mL. Raman spectroscopy shows the existence of a graphene layer and the disturbance of the AgNW network. The proposed method provides a robust way to synthesize free-stand Gr/AgNW/Gr nanocomposite and the characterization results can be utilized to optimize the nanocomposite design for future applications.
The Mineral Composition of Milk from High-Yielding Dairy Cows Depending on the Month of Lactation and Udder Health
Authors: Nogalska Anna , Momot Martyna , Nogalski Zenon
Published: July 2020

The aim of this study was to determine the effects of the month of lactation and udder health of high-yielding Polish Holstein-Friesian (PHF) cows on daily milk production and the content of K, Ca, Na, Mg and Zn in milk. The experimental materials comprised 380 milk samples collected from 38 cows. The highest average daily milk yield (49.1 kg) was noted in cows in the second month of lactation and, considering udder health, in cows whose milk contained 201,000 to 400,000 somatic cells per mL on average (denoting risk of mastitis). The K content of milk increased (p < 0.05) in successive months of lactation, whereas the opposite trend was observed in the Zn content of milk. The average content of Ca (842 mg∙dm−3), Na (344.5 mg dm−3) and Mg (98.5 mg dm−3) in milk was below the lower limits of the normal physiological ranges. Milk from cows with healthy udders (≤200,000 somatic cells per mL) had the highest concentration of K, whereas the levels of Na and Zn were highest in milk from cows with clinical mastitis (> 1 mln somatic cells per mL). Udder inflammation was accompanied by an increase in the levels of Na and Zn in milk. The high content of Na and Zn in milk can be an additional indicator of mastitis in cows.
A Systematic Mapping Study on Research in Anemia Assessment with Non-Invasive Devices
Authors: Dimauro Giovanni , Caivano Danilo , Di Pilato Pierangelo , Dipalma Alessandro , Camporeale Mauro Giuseppe
Published: July 2020

Contribution: This paper examines the literature dealing with the non-invasive estimate of anemia (NEA), and analyzes if the research is developing scientifically with adequate empirical validation. This paper reveals a trend in NEA studies towards an increasing interest in estimating anemia using conjunctiva pallor. Background: Supporting clinical developments and processes to reduce personal discomfort and allow extensive screening needs substantial efforts in researching non-invasive techniques to evaluate anemia. Research Questions: The main aims of this study are the analysis of the area of interest explored in the NEA literature, the evaluation of the peculiarities of papers, giving special consideration to empirical ones, examining them from the point of view of the daily improvement of doctors and healthcare personnel activities and the daily life of patients; and the identification of any considerable research gap to encourage further investigations on new topics. Methodology: The systematic mapping study has been elected as the optimal approach to probe the NEA literature since it defines a rigorous process for data retrieving and interpretation. Findings: Research in this sector is very active, especially in the most populated countries in the world and focuses on improving the technologies currently on the market and on proposing new solutions, especially portable and usable by everyone. A new trend in camera and smartphone-based devices is identified.
CNN-Based Illumination Estimation with Semantic Information
Authors: Choi Ho-Hyoung , Kang Hyun-Soo , Yun Byoung-Ju
Published: July 2020

For more than a decade, both academia and industry have focused attention on the computer vision and in particular the computational color constancy (CVCC). The CVCC is used as a fundamental preprocessing task in a wide range of computer vision applications. While our human visual system (HVS) has the innate ability to perceive constant surface colors of objects under varying illumination spectra, the computer vision is facing the color constancy challenge in nature. Accordingly, this article proposes novel convolutional neural network (CNN) architecture based on the residual neural network which consists of pre-activation, atrous or dilated convolution and batch normalization. The proposed network can automatically decide what to learn from input image data and how to pool without supervision. When receiving input image data, the proposed network crops each image into image patches prior to training. Once the network begins learning, local semantic information is automatically extracted from the image patches and fed to its novel pooling layer. As a result of the semantic pooling, a weighted map or a mask is generated. Simultaneously, the extracted information is estimated and combined to form global information during training. The use of the novel pooling layer enables the proposed network to distinguish between useful data and noisy data, and thus efficiently remove noisy data during learning and evaluating. The main contribution of the proposed network is taking CVCC to higher accuracy and efficiency by adopting the novel pooling method. The experimental results demonstrate that the proposed network outperforms its conventional counterparts in estimation accuracy.
A Cooperative Human-Robot Interface for Constrained Manipulation in Robot-Assisted Endonasal Surgery
Authors: Colan Jacinto , Nakanishi Jun , Aoyama Tadayoshi , Hasegawa Yasuhisa
Published: July 2020

Endoscopic endonasal surgery (EES) is a minimally invasive technique for removal of pituitary adenomas or cysts at the skull base. This approach can reduce the invasiveness and recovery time compared to traditional open surgery techniques. However, it represents challenges to surgeons because of the constrained workspace imposed by the nasal cavity and the lack of dexterity with conventional surgical instruments. While robotic surgical systems have been previously proposed for EES, issues concerned with proper interface design still remain. In this paper, we present a cooperative, compact, and versatile bimanual human-robot interface aimed to provide intuitive and safe operation in robot-assisted EES. The proposed interface is attached to a robot arm and holds a multi-degree-of-freedom (DOF) articulated forceps. In order to design the required functionalities in EES, we consider a simplified surgical task scenario, with four basic instrument operations such as positioning, insertion, manipulation, and extraction. The proposed cooperative strategy is based on the combination of force based robot control for tool positioning, a virtual remote-center-of-motion (VRCM) during insertion/extraction tasks, and the use of a serial-link interface for precise and simultaneous control of the position and the orientation of the forceps tip. Virtual workspace constraints and motion scaling are added to provide safe and smooth control of our robotic surgical system. We evaluate the performance and usability of our system considering reachability, object manipulability, and surgical dexterity in an anatomically realistic human head phantom compared to the use of conventional surgical instruments. The results demonstrate that the proposed system can improve the precision, smoothness and safety of the forceps operation during an EES.
Error Analysis Method of Geometrically Incomplete Similarity of End-Plate Connection Based on Linear Regression
Authors: Zhao Dongzhuo , Wang Zhan , Pan Jianrong , Wang Peng
Published: July 2020

Due to the limitations of processing errors, test conditions and other factors, geometric similarity errors in scale tests of steel structure joints are difficult to avoid, but the research on this error is little known. Based on the similarity theory and the basic idea of the component method, this paper deduces the similar macro conditions of beam–column end-plate connections and derives the main influencing factors of geometric similarity of these types of structures. Aiming at the factor of the thickness of the end-plate, the formation mechanism of the geometrically incomplete similarity error of this type of node was studied. Through the establishment of accurate finite element models for parameterized analysis, the influence of end plate thickness on incomplete similarity error is analyzed. Based on this model and linear regression analysis methods, the prediction formulas of geometric incomplete similarity errors of beam–column end-plate connections have been established, which can significantly reduce similar errors due to end plate thickness. This article aims to propose a method for simulating the distribution of incompletely similar errors and provide a reference for the research of similar problems.
Regional Seismic Damage Simulation of Corroded RC Frame Structures: A Case Study of Shenzhen City
Authors: Xiong Chen , Deng Xiangbin , Liang Yanmei , Li Qiangsheng , Huang Jin , Lin Xuchuan , Li Dawang
Published: July 2020

Buildings in coastal cities are susceptible to chloride ion attack and the seismic performance of these buildings can be impaired due to corrosion of reinforcements. In this study, a regional seismic damage simulation method that considers the influence of corrosion-induced seismic performance degradation is proposed. Firstly, the framework of the method is introduced, and the simulation process is presented. Secondly, experimental data of corroded reinforced concrete (RC) components are collected to obtain the reduction rules of component level backbone curve parameters (i.e., initial stiffness, peak carrying capacity, peak displacement, and ultimate carrying capacity). Afterwards, pushover analyses of typical RC frames in different corrosion conditions (i.e., degree of corrosion of components and proportion of corroded components) are conducted to acquire the reduction rules of interstory backbone curve parameters of corroded RC frame structures. Finally, RC frame structures, in Shenzhen city, are simulated using different corrosion scenarios. Simulated results indicate that some buildings along the coastline are affected by airborne chloride-induced corrosion and severe seismic damage can be observed. Moreover, some buildings that are far from the coastline can also experience severe seismic damage due to irregular use of sea sand as constructional material. The proposed method can be used to simulate the seismic performance of corroded RC structures and the outcomes of this study are expected to provide a useful reference for the seismic risk management of coastal cities.
Novel Swarm Intelligence Algorithm for Global Optimization and Multi-UAVs Cooperative Path Planning: Anas Platyrhynchos Optimizer
Authors: Zhang Yong , Wang Pengfei , Yang Liuqing , Liu Yanbin , Lu Yuping , Zhu Xiaokang
Published: July 2020

In this study, a novel type of swarm intelligence algorithm referred as the anas platyrhynchos optimizer is proposed by simulating the cluster action of the anas platyrhynchos. Starting from the core of swarm intelligence algorithm, on the premise of the use of few parameters and ease in implementation, the mathematical model and algorithm flow of the anas platyrhynchos optimizer are given, and the balance between global search and local development in the algorithm is ensured. The algorithm was applied to a benchmark function and a cooperative path planning solution for multi-UAVs as a means of testing the performance of the algorithm. The optimization results showed that the anas platyrhynchos optimizer is more superior in solving optimization problems compared with the mainstream intelligent algorithm. This study provides a new idea for solving more engineering problems.
Lattice Fracture Model for Concrete Fracture Revisited: Calibration and Validation
Authors: Chang Ze , Zhang Hongzhi , Schlangen Erik , Šavija Branko
Published: July 2020

The lattice fracture model is a discrete model that can simulate the fracture process of cementitious materials. In this work, the Delft lattice fracture model is reviewed and utilized for fracture analysis. First, a systematic calibration procedure that relies on the combination of two uniaxial tensile tests is proposed to determine the input parameters of lattice elements—tensile strength, compressive strength and elastic modulus. The procedure is then validated by simulating concrete fracture under complex loading and boundary conditions: Uniaxial compression, three-point bending, tensile splitting, and double-edge-notch beam shear. Simulation results are compared to experimental findings in all cases. The focus of this publication is therefore not only on summarizing existing knowledge and showing the capabilities of the lattice fracture model; but also to fill in an important gap in the field of lattice modeling of concrete fracture; namely, to provide a recommendation for a systematic model calibration using experimental data. Through this research, numerical analyses are performed to fully understand the failure mechanisms of cementitious materials under various loading and boundary conditions. While the model presented herein does not aim to completely reproduce the load-displacement curves, and due to its simplicity results in relatively brittle post-peak behavior, possible solutions for this issue are also discussed in this work.
Bio-Kinetics of Simultaneous Nitrification and Aerobic Denitrification (SNaD) by a Cyanide- Degrading Bacterium Under Cyanide-Laden Conditions
Authors: Mpongwana Ncumisa , Ntwampe Seteno Karabo Obed , Omodanisi Elizabeth Ife , Chidi Boredi Silas , Razanamahandry Lovasoa Christine , Dlangamandla Cynthia , Mukandi Melody Ruvimbo
Published: July 2020

A microorganism isolated and identified as Acinetobacter courvalinii was found to be able to perform sequential free cyanide (CN−) degradation, simultaneous nitrification and aerobic denitrification (SNaD); this ability was associated with the multiphase growth profile of the microorganism when provided with multiple nitrogenous sources. The effect of CN− on SNaD including enzyme expression, activity and protein functionality of Acinetobacter courvalinii was investigated. It was found that CN− concentration of 1.9 to 5.8 mg CN−/L did not affect the growth of Acinetobacter courvalinii. Furthermore, the degradation rates of CN− and ammonium-nitrogen (NH4-N) were found to be 2.2 mg CN−/L/h and 0.40 mg NH4-N/L/h, respectively. Moreover, five models’ (Monod, Moser, Generic Rate law, Haldane, and Andrews) ability to predict SNaD under CN− conditions, indicated that, only the Rate law, Haldane and Andrew’s models, were suited to predict both SNaD and CN− degradation. The effect of CN− on NH4-N, nitrate-nitrogen (NO3−) and nitrite-nitrogen (NO2−) oxidizing enzymes indicated that the CN− did not affect the expression and activity of ammonia monooxygenase (AMO); albeit, reduced the expression and activity of nitrate reductase (NaR) and nitrite reductase (NiR). Nevertheless, a slow decrease in NO2− was observed after the supplementation of CN− to the cultures, thus confirming the activity of NaR and the activation of the denitrification pathway by the CN−. These special characteristics of the Acinetobacter courvalinii isolate, suggests its suitability for the treatment of wastewater containing multiple nitrogenous compounds in which CN− is present.
A Novel Fiber Optic Sensor for Microparticle Velocity Measurement Using Multicore Fiber
Authors: Ma Xin , Sun Zhao , Luo Haimei , Li Xinwan
Published: July 2020

A novel fiber optic sensor is proposed to achieve the measurement of single microparticle velocity in a two-dimensional space by translating the cores of a multicore fiber in their respective directions into independent spatial filters. The measurement of particle velocity with the accuracy of better than 2% and direction angles in a range from 0° to 120° is achieved. Compared with the previous method by means of manual-assembled fiber array, the measurement accuracy can be increased by using only one multicore fiber probe with the features of compact size and low cost. The technique has potential particle velocity measurement applications in environmental monitoring, biological study and combustion research.
Hybrid Bayesian Network Models of Spinal Injury and Slip/Fall Events
Authors: Hughes Richard
Published: July 2020

Background: Biomechanists are often asked to provide expert opinions in legal proceedings, especially personal injury cases. This often involves using deterministic analysis methods, although the expert is expected to opine using a civil standard of “more likely than not” that is inherently probabilistic. Methods: A method is proposed for converting a class of deterministic biomechanical models into hybrid Bayesian networks that produce a probability well suited for addressing the civil standard of proof. The method was developed for spinal injury during lifting. Its generalizability was assessed by applying it to slip and fall events based on the coefficients of friction at the shoe–floor interface. Results: The proposed method is shown to be generalizable beyond lifting by applying it to a slip and fall event. Both the lifting and slip and fall models showed that incorporating evidence of injury could change the probabilities of critical quantities exceeding a threshold from “less likely than not” to “more likely than not.” Conclusions: The present work shows that it is possible to develop Bayesian networks for legal use based on laws of engineering mechanics and probabilistic descriptions of measurement error and human variability.
Elastase/Collagenase Inhibition Compositions of Citrus unshiu and Its Association with Phenolic Content and Anti-Oxidant Activity
Authors: Eun Chang-Ho , Kang Mi-Sook , Kim In-Jung
Published: July 2020

Citrus fruits are rich sources of different phytochemicals for human health due to their high anti-oxidant capacity. However, the anti-aging effect of citrus fruits has not been well understood. In this study, methanol extracts taken at various developmental stages from tissues of Citrus unshiu was used to investigate its anti-aging effect by an elastase/collagenase inhibition assay, and a gas chromatography-mass spectrometry (GC-MS) analysis was carried out to identify the potential anti-aging compositions. The elastase/collagenase inhibitory activity was greatest in the flesh of immature green fruit (i.e., early July flesh (EJF)), and four candidate compounds were selected by GC-MS and evaluated by a collagenase inhibition assay. Three of the four candidate compounds (heptadecanoic acid, D-allose, and 5-hydroxymethyl-2-furaldehyde (HMF)) showed anti-aging activity, and the activity was highest in heptadecanoic acid, followed by D-allose and HMF. The total phenolic content (TPC), total flavonoid content (TFC), and anti-oxidant activity (DPPH and ferric reducing anti-oxidant power (FRAP) assay) were also investigated. Interestingly, the patterns of the total phenolic/flavonoid content and the anti-oxidant activity were different from that of the elastase/collagenase inhibitory activity. Flowers had the most anti-oxidant activity followed by immature fruit, and the fruit peels had more anti-oxidant activity than its flesh at all stages of development. This study demonstrated that the flesh of immature fruit and flowers of C. unshiu could be sources of anti-aging and anti-oxidant agents for human health, respectively.
An Effective Prediction Approach for Moisture Content of Tea Leaves Based on Discrete Wavelet Transforms and Bootstrap Soft Shrinkage Algorithm
Authors: Zhang Min , Guo Jiaming , Ma Chengying , Qiu Guangjun , Ren Junjie , Zeng Fanguo , Lü Enli
Published: July 2020

The traditional method used to determine the moisture content of tea leaves is time consuming and destructive. To address this problem, an effective and non-destructive prediction method based on near-infrared spectroscopy (NIRS) is proposed in this paper. This new method combines discrete wavelet transforms (DWT) with the bootstrap soft shrinkage algorithm (BOSS). To eliminate uninformative or interfering variables, DWT is applied to remove the noise in the spectral data by decomposing the origin spectrum into six layers. BOSS is used to select informative variables by reducing the dimensions of the sub-layers’ reconstruction spectrum. After selecting the effective variables using DWT and BOSS, a prediction model based on partial least squares (PLS) is built. To validate effectiveness and stability of the prediction model, full-spectrum PLS, genetic algorithm PLS (GA-PLS), and interval PLS (iPLS) were compared with the proposed method. The experiment results illustrate that the proposed prediction model outperforms the other classical models considered in this study and shows promise for the prediction of the moisture content in Yinghong No. 9 tea leaves.