bluuebunny/crossref_metadata_2025 huggingface dataset:
System Configurations and Operational Concepts for Highly Efficient Utilization of Power-to-Heat in A-CAES
Authors: Dreißigacker Volker , Belik Sergej
Published: March 2019

The increasing share of renewable energies requires the installation of large-scale electricity storage capacities in addition to grid expansion. Significant contribution to reach this goal is provided by adiabatic compressed air energy storage power plants (A-CAES), key elements in future electricity transmission systems. This technology allows efficient, local zero-emission electricity storage on the basis of compressed air in underground caverns in combination with thermal energy storage systems and, in contrast to pumped storage power plants (PSPP), it demands no overground geological requirements. Despite the achieved success of A-CAES systems in terms of efficiency and cost, further improvements in dynamics and flexibility are needed. One promising solution to fulfil these dynamic requirements is based on the integration of an additional power-to-heat element (P2H) operating during the charging periods. This modification allows increased power plant flexibility and further cost reductions due to increased thermal storage densities but is simultaneously associated with concept-dependent decreasing total round trip efficiencies. For the identification of suitable configurations, adequate concepts must be elaborated, and the influence on round trip efficiency as well as on cost reduction potential must be investigated. For this purpose, a system model for a two-stage A-CAES configuration is established and used for large simulation studies related to P2H locations and power, thermal energy storage systems, and central process variables. Therefore, time-efficient model reductions with well-justified assumptions are conducted, offering a simplified transient implementation of thermal energy options in the system simulation. On the basis of a promising P2H configuration including high potentials for cost reduction and moderate losses in round trip efficiency, an alternative concept is presented offering high exergetic utilization and additional cost reductions, which can be treated as a base for upgrading the existing CAES power plants and for modifying operational concepts.
Grassmann Manifold Based State Analysis Method of Traffic Surveillance Video
Authors: Qin Peng , Zhang Yong , Wang Boyue , Hu Yongli
Published: March 2019

For a contemporary intelligent transport system, congestion state analysis of traffic surveillance video (TSV) is one of the most crucial and intricate research topics because of the rapid development of transportation systems, the sustained growth of surveillance facilities on road, which lead to massive traffic flow data, and the inherent characteristics of our analysis target. Traditional methods on feature extractions are usually operated on Euclidean space in general, which are not accurate for high-dimensional TSV data analysis. This paper proposes a Grassmann manifold based neural network model to analysis TSV data , by mapping the video data from high dimensional Euclidean space to Grassmann manifold space, and considering the inner relation among adjacent cameras. The accuracy of the traffic congestion is improved, compared with several traditional methods. Experimental results are conducted to validate the accuracy of our method and to investigate the effects of different factors on performance.
Joint Detection and Classification of Singing Voice Melody Using Convolutional Recurrent Neural Networks
Authors: Kum Sangeun , Nam Juhan
Published: March 2019

Singing melody extraction essentially involves two tasks: one is detecting the activity of a singing voice in polyphonic music, and the other is estimating the pitch of a singing voice in the detected voiced segments. In this paper, we present a joint detection and classification (JDC) network that conducts the singing voice detection and the pitch estimation simultaneously. The JDC network is composed of the main network that predicts the pitch contours of the singing melody and an auxiliary network that facilitates the detection of the singing voice. The main network is built with a convolutional recurrent neural network with residual connections and predicts pitch labels that cover the vocal range with a high resolution, as well as non-voice status. The auxiliary network is trained to detect the singing voice using multi-level features shared from the main network. The two optimization processes are tied with a joint melody loss function. We evaluate the proposed model on multiple melody extraction and vocal detection datasets, including cross-dataset evaluation. The experiments demonstrate how the auxiliary network and the joint melody loss function improve the melody extraction performance. Furthermore, the results show that our method outperforms state-of-the-art algorithms on the datasets.
Energy Storage System Controller Design for Suppressing Electromechanical Oscillation of Power Systems
Authors: Yang Bo , Li Guanjun , Tang Wencheng , Hu Anping , Zhang Donghui , Wu Yongbin
Published: March 2019

Through the feedback of the rotor speed and/or the grid frequency, an energy storage system (ESS) can effectively suppress the electromechanical oscillation of a power system. This paper proposes a novel control strategy and controller parameter design method for ESSs to achieve the desired performance of oscillation suppression, including smaller frequency and rate of change of frequency (ROCOF) deviation than their threshold values. Firstly, a dynamic model of the electromechanical time scale of a synchronous generator dominated power system with ESS was established. Then, based on the dynamic model and the electric torque analysis method, the mechanism of an ESS with the feedback signal of the rotor speed to suppress the electromechanical oscillation was investigated. Finally, the controller parameter design method for the ESS was developed to achieve the desired performance of oscillation suppression. With the help of the well-designed ESS, the electromechanical oscillation of a synchronous generator dominated power system can be effectively suppressed in shorter transient response times, and the grid frequency deviation and the ROCOF can be limited to below their threshold values. The simulation results also verify the effectiveness of the proposed control strategy and the controller parameter design method.
Electro-Optical Imaging Technology Based on Microlens Array and Fiber Interferometer
Authors: Yang Fan , Yan Wei , Tian Peng , Li Fanxin , Peng Fupin
Published: March 2019

To reduce the volume and weight of traditional optical telescopes effectively, this article proposes an electro-optical imaging technology based on a microlens array and fiber interferometer. Pairs of microlenses in the microlens array collect light and couple it into a fiber interferometer to form interference fringes. Then the amplitude and phase of a large number of interferometer baselines are analyzed to generate images. In this work, the principle of electro-optical imaging technology has been analyzed according to the partially coherent light theory. The microlens-array arrangement method and baseline pairing method have been optimized for arbitrary targets. From the simulation results, it was found that the imaging resolution depends on the maximum baseline length, and the imaging quality could be effectively improved by adjusting the Nyquist sampling density and baseline pairing method. This technology can provide an important reference for the miniaturization and complanation of imaging systems.
A Robust Brain MRI Segmentation and Bias Field Correction Method Integrating Local Contextual Information into a Clustering Model
Authors: Zhang Zhe , Song Jianhua
Published: March 2019

The segmentation results of brain magnetic resonance imaging (MRI) have important guiding significance for subsequent clinical diagnosis and treatment. However, brain MRI segmentation is a complex and challenging problem due to the inevitable noise or intensity inhomogeneity. A novel robust clustering with local contextual information (RC_LCI) model was used in this study which accurately segmented brain MRI corrupted by noise and intensity inhomogeneity. For pixels in the neighborhood of the central pixel, a weighting scheme combining local contextual information was used to generate the corresponding anisotropic weight to update the current central pixel and thus remove noisy pixels. Then, a multiplicative framework consisting of the product of a real image and a bias field could effectively segment brain MRI and estimate the bias field. Further, a linear combination of basis functions was introduced to guarantee the bias field properties. Therefore, compared with state-of-the-art models, the segmentation result obtained by RC_LCI was increased by 0.195 ± 0.125 in terms of the Jaccard similarity coefficient. Both visual experimental results and quantitative evaluation demonstrate the superiority of RC_LCI on real and synthetic images.
Improving Eight-State Continuous Variable Quantum Key Distribution by Applying Photon Subtraction
Authors: Peng Qingquan , Wu Xiaodong , Guo Ying
Published: March 2019

We propose a new method to effectively improve the performance of a quantum key distribution with eight-state continuous variables by the photon subtraction method. This operation is effective in increasing and distilling Gaussian entanglement between quantum states, and can be easily realized by existing technology. Simulation results show that the channel-loss tolerance of the eight-state continuous variable quantum key distribution (CVQKD) protocol can be extended by the appropriate photon subtraction algorithm; namely, single-photon subtraction.
Determination of Fracture Properties of Concrete Using Size and Boundary Effect Models
Authors: Gao Xiaofeng , Liu Chunfeng , Tan Yaosheng , Yang Ning , Qiao Yu , Hu Yu , Li Qingbin , Koval Georg , Chazallon Cyrille
Published: March 2019

Tensile strength and fracture toughness are two essential material parameters for the study of concrete fracture. The experimental procedures to measure these two fracture parameters might be complicated due to their dependence on the specimen size or test method. Alternatively, based on the fracture test results only, size and boundary effect models can determine both parameters simultaneously. In this study, different versions of boundary effect models developed by Hu et al. were summarized, and a modified Hu-Guan’s boundary effect model with a more appropriate equivalent crack length definition is proposed. The proposed model can correctly combine the contributions of material strength and linear elastic fracture mechanics on the failure of concrete material with any maximum aggregate size. Another size and boundary model developed based on the local energy concept is also introduced, and its capability to predict the fracture parameters from the fracture test results of wedge-splitting and compact tension specimens is first validated. In addition, the classical Bažant’s Type 2 size effect law is transformed to its boundary effect shape with the same equivalent crack length as Koval-Gao’s size and boundary effect model. This improvement could extend the applicability of the model to infer the material parameters from the test results of different types of specimens, including the geometrically similar specimens with constant crack-length-to-height ratios and specimens with different initial crack-length-to-height ratios. The test results of different types of specimens are adopted to verify the applicability of different size and boundary effect models for the determination of fracture toughness and tensile strength of concrete material. The quality of the extrapolated fracture parameters of the different models are compared and discussed in detail, and the corresponding recommendations for predicting the fracture parameters for dam concrete are proposed.
Image Pragmatics and Film as a Lived Practice in the Documentary Work of Hani Susumu and Tsuchimoto Noriaki
Authors: Jesty Justin
Published: March 2019

This paper focuses on two discrete bodies of work, Hani Susumu’s films of the late 1950s and Tsuchimoto Noriaki’s Minamata documentaries of the early 1970s, to trace the emergence of the cinéma vérité mode of participant-observer, small-crew documentary in Japan and to suggest how it shapes the work of later social documentarists. It argues that Hani Susumu’s emphasis on duration and receptivity in the practice of filmmaking, along with his pragmatic understanding of the power of the cinematic image, establish a fundamentally different theoretical basis and set of questions for social documentary than the emphasis on mobility and access, and the attendant question of truth that tend to afflict the discourse of cinéma vérité in the U.S. and France. Tsuchimoto Noriaki critically adopts and develops Hani’s theoretical and methodological framework in his emphasis on long-running involvement with the subjects of his films and his practical conviction that the image is not single-authored, self-sufficient, or meaningful in and of itself, but emerges from collaboration and must be embedded in a responsive social practice in order to meaningfully reach an audience. Hani and Tsuchimoto both believe that it is possible for filmmakers and the film itself to be fundamentally processual and intersubjective: grounded in actual collaboration, but also underwritten by a belief that intersubjective processes are more basic to human being than “the individual,” let alone “the author.” This paper explores the implications for representation and ethics of this basic difference in vérité theory and practice in Japan.
What’s the Use of Culture? Cinematographers and the Culture Film in Japan in the Early 1940s
Authors: Miyao Daisuke
Published: March 2019

In the early 1940s Japan, cinematographers and critics feverishly discussed the notions of immediacy and authorship in relation to documentary practices. The status of cinematographers as the authors of the images that they shot was particularly questioned in those conversations due to the mechanical nature of the motion picture camera. This article mainly focuses on the discussions in the journal Eiga Gijutsu (Film Technology) in 1941–1942 over the notion of culture, and examines how cinematographers imagined their new roles in documentary practices in the cinema.
Transcriptome Analysis of Yamame (Oncorhynchus masou) in Normal Conditions after Heat Stress
Authors: Kraitavin Waraporn , Yoshitake Kazutoshi , Igarashi Yoji , Mitsuyama Susumu , Kinoshita Shigeharu , Kambayashi Daisuke , Watabe Shugo , Asakawa Shuichi
Published: March 2019

Understanding the mechanism of high-temperature tolerance in cold-freshwater fish is crucial for predicting how certain species will cope with global warming. In this study, we investigated temperature tolerance in masu salmon (Oncorhynchus masou, known in Japan as ‘yamame’), an important aquaculture species. By selective breeding, we developed a group of yamame (F2) with high-temperature tolerance. This group was subjected to a high-temperature tolerance test and divided into two groups: High-temperature tolerant (HT) and non-high-temperature tolerant (NT). RNA was extracted from the gill and adipose fin tissues of each group, and the mRNA expression profiles were analyzed using RNA sequencing. A total of 2893 differentially expressed genes (DEGs) from the gill and 836 from the adipose fin were identified by comparing the HT and NT groups. Functional analyses were then performed to identify associated gene ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The HT group showed a high expression of heat shock protein 70 (HSP70) gene and enriched gene expression in the extracellular matrix (ECM), cell junction, and adhesion pathways in gill tissues compared to the NT group. The HT group also exhibited highly expressed genes in glycolysis and showed lower expression of the genes in the p53 signaling pathway in adipose fin tissues. Taken together, the difference of expression of some genes in the normal condition may be responsible for the difference in heat tolerance between the HT and NT yamame in the heat stress condition.
Comparison of the Neuroprotective Effects of Aspirin, Atorvastatin, Captopril and Metformin in Diabetes Mellitus
Authors: Paseban Maryam , Mohebbati Reza , Niazmand Saeed , Sathyapalan Thozhukat , Sahebkar Amirhossein
Published: March 2019

Objective: The aim of this study was to investigate the effect of combined intake of a high dose of aspirin, atorvastatin, captopril and metformin on oxidative stress in the brain cortex and hippocampus of streptozotocin (STZ)-induced diabetic rats. Material and methods: Rats were randomly divided into the following 11 groups: control and diabetic (D), as well as 9 groups that were treated with metformin (M, 300 mg/kg) or aspirin (ASA, 120 mg/kg) alone or in different combinations with captopril (C, 50 mg/kg) and/or atorvastatin (AT, 40 mg/kg) as follows: (D + M), (D + ASA), (D + M + ASA), (D + M + C), (D + M + AT), (D + M + C + ASA), (D + M + C + AT), (D + M + AT + ASA) and (D + M + C + AT + ASA). The rats in treatment groups received drugs by gavage daily for six weeks. Serum lipid profile and levels of oxidative markers in the brain cortex and hippocampus tissues were evaluated. Results: The levels of malondialdehyde in the brain cortex and hippocampus in all the treated groups decreased significantly (p < 0.05). There was a significant increase in the total thiol concentration as well as catalase activity in treated rats in (M + AT), (M + C + ASA), (M + C + AT), (M + AT + ASA) and (M + C + AT + ASA) groups in cortex and hippocampus in comparison with the diabetic rats (p < 0.05). Also, the superoxide dismutase activity in all treated rats with medications was significantly increased compared to the diabetic rats (p < 0.05–0.01). Conclusion: Our findings showed that the combined use of high-dose aspirin, metformin, captopril and atorvastatin potentiated their antioxidant effects on the brain, and hence could potentially improve cognitive function with their neuroprotective effects on hippocampus.
Quantification of Fecal Short Chain Fatty Acids by Liquid Chromatography Tandem Mass Spectrometry—Investigation of Pre-Analytic Stability
Authors: Liebisch Gerhard , Ecker Josef , Roth Sebastian , Schweizer Sabine , Öttl Veronika , Schött Hans-Frieder , Yoon Hongsup , Haller Dirk , Holler Ernst , Burkhardt Ralph , Matysik Silke
Published: March 2019

Short chain fatty acids (SCFAs) are generated by the degradation and fermentation of complex carbohydrates, (i.e., dietary fiber) by the gut microbiota relevant for microbe–host communication. Here, we present a method for the quantification of SCFAs in fecal samples by liquid chromatography tandem mass spectrometry (LC-MS/MS) upon derivatization to 3-nitrophenylhydrazones (3NPH). The method includes acetate, propionate, butyrate, and isobutyrate with a run time of 4 min. The reproducible (coefficients of variation (CV) below 10%) quantification of SCFAs in human fecal samples was achieved by the application of stable isotope labelled internal standards. The specificity was demonstrated by the introduction of a quantifier and qualifier ions. The method was applied to investigate the pre-analytic stability of SCFAs in human feces. Concentrations of SCFA may change substantially within hours; the degree and kinetics of these changes revealed huge differences between the donors. The fecal SCFA level could be preserved by the addition of organic solvents like isopropanol. An analysis of the colon content of mice either treated with antibiotics or fed with a diet containing a non-degradable and -fermentable fiber source showed decreased SCFA concentrations. In summary, this fast and reproducible method for the quantification of SCFA in fecal samples provides a valuable tool for both basic research and large-scale studies.
Cytosporone B as a Biological Preservative: Purification, Fungicidal Activity and Mechanism of Action against Geotrichum citri-aurantii
Authors: Yin Chunxiao , Liu Hongxin , Shan Yang , Gupta Vijai Kumar , Jiang Yueming , Zhang Weimin , Tan Haibo , Gong Liang
Published: March 2019

To prevent citrus decay caused by Geotrichum citri-aurantii, 12 natural products were isolated from two endophytic fungi, in which cytosporone B was shown to have excellent bioactivity for control of G. citri-aurantii with median effect concentration (EC50) of 26.11 μg/mL and minimum inhibitory concentration (MIC) of 105 μg/mL, and also significantly reduced the decay of sugar orange during the in vivo trials. In addition, cytosporone B could alter the morphology of G. citri-aurantii by causing distortion of the mycelia and loss of membrane integrity. Differentially expressed genes (DEGs) between cytosporone B-treated and -untreated samples were revealed by Illumina sequencing, including 3540 unigenes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that most DEGs were related to metabolic production and cell membrane. These findings suggest cytosporone B is a promising biological preservative to control citrus decay and reveal the action mechanism of cytosporone B in relation to the destruction of the fungal cell membrane at both morphological and molecular levels.
The Transformative Possibilities of the Microbiota and Mycobiota for Health, Disease, Aging, and Technological Innovation
Authors: Jones Lucas , Kumar Jessica , Mistry Adil , Sankar Chittoor Mana Thriveen , Perry George , Reddy V. Prakash , Obrenovich Mark
Published: March 2019

The gut microbiota is extremely important for the health of the host across its lifespan. Recent studies have elucidated connections between the gut microbiota and neurological disease and disorders such as depression, anxiety, Alzheimer’s disease (AD), autism, and a host of other brain illnesses. Dysbiosis of the normal gut flora can have negative consequences for humans, especially throughout key periods during our lifespan as the gut microbes change with age in both phenotype and number of bacterial species. Neurologic diseases, mental disorders, and euthymic states are influenced by alterations in the metabolites produced by gut microbial milieu. We introduce a new concept, namely, the mycobiota and microbiota-gut-brain neuroendocrine axis and discuss co-metabolism with emphasis on means to influence or correct disruptions to normal gut flora throughout the lifespan from early development to old age. These changes involve inflammation and involve the permeability of barriers, such as the intestine blood barrier, the blood–brain barrier, and others. The mycobiota and microbiota–gut–brain axis offer new research horizons and represents a great potential target for new therapeutics, including approaches based around inflammatory disruptive process, genetically engineered drug delivery systems, diseased cell culling “kill switches”, phage-like therapies, medicinal chemistry, or microbial parabiosis to name a few.
Layered Double Hydroxides as Bifunctional Catalysts for the Aryl Borylation under Ligand-Free Conditions
Authors: Silva Lorenna C. L. L. F. , Neves Vinícius A. , Ramos Vitor S. , Silva Raphael S. F. , Campos José B. de , Silva Alexsandro A. da , Malta Luiz F. B. , Senra Jaqueline D.
Published: March 2019

Organic derivatives of boron, such as boronic esters and acids, are important precursors for a wide range of environmental, energy, and health applications. Several catalytic methods for their synthesis have been reported, even though with the use of toxic and structurally complex ligands. Herein, we demonstrate preliminary studies envisaging the synthesis of boronic esters from an inexpensive catalytic system based on Cu/Al layered double hydroxides (LDH) in the presence of Na2PdCl4. The Cu/ Al LDHs were prepared according to coprecipitation method and characterized by X-ray diffraction (XRD) (with Rietveld refinement) to evaluate the contamination with malachite and other phases. Preliminary catalytic results suggest that pure Cu/Al LDH has potential for the borylation of aryl iodides/ bromides in the absence of base. Indeed, a synergic effect between copper and palladium is possibly related to the catalytic efficiency.
Blockage Detection and Diagnosis of Externally Parallelized Monolithic Microreactors
Authors: Tonomura Osamu , Taniguchi Satoshi , Nishi Kazuki , Nagaki Aiichiro , Yoshida Jun-ichi , Hirose Katsuyuki , Ishizuka Norio , Hasebe Shinji
Published: March 2019

To realize stable operation of a microchemical system, it is necessary to develop a process monitoring method that can detect and diagnose blocked microreactors. In this study, a system composed of five monolithic microreactors and a split-and-recombine-type flow distributor (SRFD) was developed for Suzuki–Miyaura coupling. Firstly, the effects of operating conditions on the yield was examined by using a single microreactor. After that, an optimal design problem was formulated to maximize the blockage detection performance by adjusting the channel resistances of the SRFD and the sensor locations in the SRFD under the design constraints. To efficiently solve the problem, a pressure drop compartment model, which is analogous to electrical resistance networks, was used. The optimally designed system was experimentally evaluated from the viewpoint of the capability of continuous operation and the blockage detection and diagnosis performance. The evaluation results show that continuous operation was successfully carried out for one hour, and that the artificially generated blockage of each microreactor was accurately identified. The developed system minimized the process performance degradation due to blockage.
Mitochondrial Biogenesis and Mitochondrial Reactive Oxygen Species (ROS): A Complex Relationship Regulated by the cAMP/PKA Signaling Pathway
Authors: Bouchez Cyrielle , Devin Anne
Published: March 2019

Mitochondrial biogenesis is a complex process. It requires the contribution of both the nuclear and the mitochondrial genomes and therefore cross talk between the nucleus and mitochondria. Cellular energy demand can vary by great length and it is now well known that one way to adjust adenosine triphosphate (ATP) synthesis to energy demand is through modulation of mitochondrial content in eukaryotes. The knowledge of actors and signals regulating mitochondrial biogenesis is thus of high importance. Here, we review the regulation of mitochondrial biogenesis both in yeast and in mammalian cells through mitochondrial reactive oxygen species.
Surface Modification of 3D Printed PLA Objects by Fused Deposition Modeling: A Review
Authors: Baran Eda Hazal , Erbil H. Yildirim
Published: March 2019

Polylactic acid (PLA) filaments are very popular as a thermoplastic source used in the 3D printing field by the “Fused Deposition Modeling” method in the last decade. The PLA market is expected to reach 5.2 billion US dollars in 2020 for all of its industrial uses. On the other hand, 3D printing is an expanding technology that has a large economic potential in many industries where PLA is one of the main choices as the source polymer due to its ease of printing, environmentally friendly nature, glossiness and multicolor appearance properties. In this review, we first reported the chemical structure, production methods, general properties, and present market of the PLA. Then, the chemical modification possibilities of PLA and its use in 3D printers, present drawbacks, and the surface modification methods of PLA polymers in many different fields were discussed. Specifically, the 3D printing method where the PLA filaments are used in the extrusion-based 3D printing technologies is reviewed in this article. Many methods have been proposed for the permanent surface modifications of the PLA where covalent attachments were formed such as alkaline surface hydrolysis, atom transfer polymerization, photografting by UV light, plasma treatment, and chemical reactions after plasma treatment. Some of these methods can be applied for surface modifications of PLA objects obtained by 3D printing for better performance in biomedical uses and other fields. Some recent publications reporting the surface modification of 3D printed PLA objects were also discussed.
The Importance of Measuring Students’ Opinions and Attitudes
Authors: Sanz-Pérez E. S.
Published: March 2019

The data presented in this article are related to a research carried out at the University Rey Juan Carlos in Spain. Chemical Engineering taught as a subject across three Energy Engineering-based degree streams was evaluated for two academic years. Student insight on course development, their own expectations and results, and the evaluation system were explored via a 33-item survey, receiving 47 full responses. The present contribution provides the full responses obtained from students to the survey administered. The received data were studied applying thorough statistical analyses used to infer conclusions. The full set of data are made public here independently from the research article.
Development of Rapid Extraction Method of Mycobacterium avium Subspecies paratuberculosis DNA from Bovine Stool Samples
Authors: Hansen Sören , Roller Marco , Alslim Lamia , Böhlken-Fascher Susanne , Fechner Kim , Czerny Claus-Peter , Abd El Wahed Ahmed
Published: March 2019

The rapid identification of Mycobacterium avium subspecies paratuberculosis (MAP) infected animals within the herd is essential for preventing the spread of the disease as well as avoiding human exposure. Although culture is seen as the gold standard, there are various molecular assays available i.e., polymerase chain reaction (PCR) or isothermal amplification technique (recombinase polymerase amplification (RPA)) for the detection of MAP. The accuracy of the molecular assays is highly dependent on the DNA extraction method. In order to establish a rapid point of need system for the detection of MAP DNA from stool samples, we developed a rapid DNA extraction protocol (MAP DNA SpeedXtract) specified for use in combination with the RPA. The whole procedure from “sample in” to “result out” was conducted in a mobile suitcase laboratory. The DNA extraction is based on reverse purification by magnetic beads, which reduces the required technical demand. The MAP DNA SpeedXtract was performed within 25 min and only three pipetting steps were needed. The amplification and detection time were 20 min in RPA. The sensitivity and specificity of the developed protocol in comparison with the lab-based silica membrane column extraction and real-time PCR were 90.9% (n = 22) and 100% (n = 23), respectively. In conclusion, we established a rapid and reliable protocol for the extraction and detection of MAP DNA. All reagents are cold chain independent. The entire setup is ideal for point of need identification of MAP infected cases.
An In-Vitro Analysis of Microleakage of Self-Adhesive Fissure Sealant vs. Conventional and GIC Fissure Sealants
Authors: Gorseta Kristina , Borzabadi-Farahani Ali , Vrazic Tara , Glavina Domagoj
Published: March 2019

Background: The microleakage of a self-adhesive composite, a glass ionomer fissure sealant and a conventional resin-based fissure sealant were compared. Materials and methods: Fifty intact human molars with well-delineated pits and fissures were used and divided into 5 groups (n = 10). Group 1 specimens were etched (37% phosphoric acid) and sealed with conventional resin-based sealant (Helioseal F, Ivoclar Vivadent). Both Group 2 and 3 specimens were sealed with self-adhesive composite (Constic, DMG), but in Group 3, specimens were also etched (37% phosphoric acid). In Groups 4 and 5, specimens were sealed with a GIC sealant (Equia Fill, GC Company), but Group 5 was also exposed to thermo-light curing (TLC) with a LED polymerization unit (60 s). Subsequently, specimens were thermocycled (1800 cycles, dwelling time of 10 s), immersed in 50% silver nitrate solution (45 min), placed in a photo-developing solution (Kodak) under a lamp (120 W, 6 h), and cut into 3–4 slices. Marginal leakage (dye penetration depth) was evaluated under a light microscope and the worst score of each specimen was recorded (0–3). Results: Constic showed the lowest microleakage (Constic: 80% scored 0 or 1), followed by Helioseal (30% scored 0 or 1) (p = 0.037). Microleakage in groups sealed with Constic (with and without etching) were not different (p = 0.473). The quality of seal deteriorated after etching when Constic was used. However, TLC improved the seal when GIC sealant was used (p = 0.016) and also in comparison to Helioseal (p = 0.004). The TLC GIC sealant (Equia Fill, 90% scored 0 or 1) performed well, similar to self-adhesive composite (Constic, 80% scored 0 or 1) (p = 0.206). Conclusion: The present findings suggest that the self-adhesive sealant and the GIC sealant that were exposed to TLC had comparable sealing ability and superior sealing characteristics compared to the conventional resin-based sealant. A long-term clinical trial is needed to assess the intra-oral performance.
About Universality and Thermodynamics of Turbulence
Authors: Geneste Damien , Faller Hugues , Nguyen Florian , Shukla Vishwanath , Laval Jean-Philippe , Daviaud Francois , Saw Ewe-Wei , Dubrulle Bérengère
Published: March 2019

This paper investigates the universality of the Eulerian velocity structure functions using velocity fields obtained from the stereoscopic particle image velocimetry (SPIV) technique in experiments and direct numerical simulations (DNS) of the Navier-Stokes equations. It shows that the numerical and experimental velocity structure functions up to order 9 follow a log-universality (Castaing et al. Phys. D Nonlinear Phenom. 1993); this leads to a collapse on a universal curve, when units including a logarithmic dependence on the Reynolds number are used. This paper then investigates the meaning and consequences of such log-universality, and shows that it is connected with the properties of a “multifractal free energy”, based on an analogy between multifractal and thermodynamics. It shows that in such a framework, the existence of a fluctuating dissipation scale is associated with a phase transition describing the relaminarisation of rough velocity fields with different Hölder exponents. Such a phase transition has been already observed using the Lagrangian velocity structure functions, but was so far believed to be out of reach for the Eulerian data.
Application of Laplace–Adomian Decomposition Method for the Analytical Solution of Third-Order Dispersive Fractional Partial Differential Equations
Authors: Shah Rasool , Khan Hassan , Arif Muhammad , Kumam Poom
Published: March 2019

In the present article, we related the analytical solution of the fractional-order dispersive partial differential equations, using the Laplace–Adomian decomposition method. The Caputo operator is used to define the derivative of fractional-order. Laplace–Adomian decomposition method solutions for both fractional and integer orders are obtained in series form, showing higher convergence of the proposed method. Illustrative examples are considered to confirm the validity of the present method. The fractional order solutions that are convergent to integer order solutions are also investigated.
Quantum Image Encryption Scheme Using Arnold Transform and S-box Scrambling
Authors: Liu Hui , Zhao Bo , Huang Linquan
Published: March 2019

The paper proposes a lossless quantum image encryption scheme based on substitution tables (S-box) scrambling, mutation operation and general Arnold transform with keys. First, the key generator builds upon the foundation of SHA-256 hash with plain-image and a random sequence. Its output value is used to yield initial conditions and parameters of the proposed image encryption scheme. Second, the permutation and gray-level encryption architecture is built by discrete Arnold map and quantum chaotic map. Before the permutation of Arnold transform, the pixel value is modified by quantum chaos sequence. In order to get high scrambling and randomness, S-box and mutation operation are exploited in gray-level encryption stage. The combination of linear transformation and nonlinear transformation ensures the complexity of the proposed scheme and avoids harmful periodicity. The simulation shows the cipher-image has a fairly uniform histogram, low correlation coefficients closed to 0, high information entropy closed to 8. The proposed cryptosystem provides 2256 key space and performs fast computational efficiency (speed = 11.920875 Mbit/s). Theoretical analyses and experimental results prove that the proposed scheme has strong resistance to various existing attacks and high level of security.
Teacher Beliefs and Emotion Expression in Light of Support for Student Psychological Needs: A Qualitative Study
Authors: Jiang Jingwen , Vauras Marja , Volet Simone , Salo Anne-Elina
Published: March 2019

This study explored teacher beliefs and emotion expression via six semi-structured interviews with teachers, and discussed the findings in relation to the Self-Determination Theory, which addresses teacher support for autonomy, competence, and relatedness. The findings showed that teacher beliefs about their roles as educators, carers, and providers of reassurance reflected expressing clear expectation, caring for students, and considering student perspectives and feelings; teacher beliefs about equality between teachers and students appeared connected with trust in students and encouragement of their self-initiation; teacher beliefs about closeness to students reflected caring for students; teacher expression of negative emotions by discussing the problem with students conveyed explanatory rationales for expected student behaviors. This study revealed that teacher beliefs about teacher-student power relations may be connected with teacher appraisals of student misbehaviors. The findings also suggest that teachers need to discuss the problem with students rather than lose their temper or suppress their emotion when they feel a need to direct-stage anger. Future research could investigate teachers’ faking a particular emotion, such as faking indifference as revealed in the present study. Future research could also explore the reason for and harmfulness of embracing beliefs, e.g., negative expression of anger as a safety belt.
An Efficient Streaming Accelerator for Low Bit-Width Convolutional Neural Networks
Authors: Chen Qinyu , Fu Yuxiang , Song Wenqing , Cheng Kaifeng , Lu Zhonghai , Zhang Chuan , Li Li
Published: March 2019

Convolutional Neural Networks (CNNs) have been widely applied in various fields, such as image recognition, speech processing, as well as in many big-data analysis tasks. However, their large size and intensive computation hinder their deployment in hardware, especially on the embedded systems with stringent latency, power, and area requirements. To address this issue, low bit-width CNNs are proposed as a highly competitive candidate. In this paper, we propose an efficient, scalable accelerator for low bit-width CNNs based on a parallel streaming architecture. With a novel coarse grain task partitioning (CGTP) strategy, the proposed accelerator with heterogeneous computing units, supporting multi-pattern dataflows, can nearly double the throughput for various CNN models on average. Besides, a hardware-friendly algorithm is proposed to simplify the activation and quantification process, which can reduce the power dissipation and area overhead. Based on the optimized algorithm, an efficient reconfigurable three-stage activation-quantification-pooling (AQP) unit with the low power staged blocking strategy is developed, which can process activation, quantification, and max-pooling operations simultaneously. Moreover, an interleaving memory scheduling scheme is proposed to well support the streaming architecture. The accelerator is implemented with TSMC 40 nm technology with a core size of 0.17 mm 2 . It can achieve 7.03 TOPS/W energy efficiency and 4.14 TOPS/mm 2 area efficiency at 100.1 mW, which makes it a promising design for the embedded devices.
Impact of Polarization Distortions on Geometrical Structure Retrieval of Moving Man-Made Targets in ISAR Images
Authors: Liu Qiaoling , Pang Chen , Li Yongzhen , Wang Xuesong
Published: March 2019

In this paper, the impact of several polarization distortions on geometrical structure retrieval of man-made targets in inverse synthetic aperture radar (ISAR) images is assessed. For polarimetric ISAR, the polarization distortions are usually composed of crosstalk and channel imbalance. For non-stationary targets, a residual phase error exists between two columns of the scattering matrix in the alternate transmission and simultaneous reception (ATSR) mode, especially when the radar frequency is high. These two kinds of distortions have varying influences on different targets, as well as different decomposition methods. Some theoretical derivations and numerical analyses are given to reveal the impact of these distortions on Cameron decomposition. To evaluate the impact of these distortions on geometrical structure retrieval, we use the numerical results and real data of an unmanned aerial vehicle (UAV) called Frontier to perform error analysis of both the decomposition and the retrieved size of the designated structures of the UAV. Some numerical evaluations were conducted from the perspective of system design, and these results can be useful for the practical radar system.
Optimal Image-Based Guidance of Mobile Manipulators using Direct Visual Servoing
Authors: Belmonte Álvaro , Ramón José , Pomares Jorge , Garcia Gabriel , Jara Carlos
Published: March 2019

This paper presents a direct image-based controller to perform the guidance of a mobile manipulator using image-based control. An eye-in-hand camera is employed to perform the guidance of a mobile differential platform with a seven degrees-of-freedom robot arm. The presented approach is based on an optimal control framework and it is employed to control mobile manipulators during the tracking of image trajectories taking into account robot dynamics. The direct approach allows us to take both the manipulator and base dynamics into account. The proposed image-based controllers consider the optimization of the motor signals sent to the mobile manipulator during the tracking of image trajectories by minimizing the control force and torque. As the results show, the proposed direct visual servoing system uses the eye-in-hand camera images for concurrently controlling both the base platform and robot arm. The use of the optimal framework allows us to derive different visual controllers with different dynamical behaviors during the tracking of image trajectories.
Indoor Positioning System: A New Approach Based on LSTM and Two Stage Activity Classification
Authors: Hussain Ghulam , Jabbar Muhammad Shahid , Cho Jun-Dong , Bae Sangmin
Published: March 2019

The number of studies on the development of indoor positioning systems has increased recently due to the growing demands of the various location-based services. Inertial sensors available in commercial smartphones play an important role in indoor localization and navigation owing to their highly accurate localization performance. In this study, the inertial sensors of a smartphone, which generate distinct patterns for physical activities and action units (AUs), are employed to localize a target in an indoor environment. These AUs, (such as a left turn, right turn, normal step, short step, or long step), help to accurately estimate the indoor location of a target. By taking advantage of sophisticated deep learning algorithms, we propose a novel approach for indoor navigation based on long short-term memory (LSTM). The LSTM accurately recognizes physical activities and related AUs by automatically extracting the efficient features from the distinct patterns of the input data. Experiment results show that LSTM provides a significant improvement in the indoor positioning performance through the recognition task. The proposed system achieves a better localization performance than the trivial fingerprinting method, with an average error of 0.782 m in an indoor area of 128.6 m2. Additionally, the proposed system exhibited robust performance by excluding the abnormal activity from the pedestrian activities.
Simulation of Temperature Distribution on the Face Skin in Case of Advanced Personalized Ventilation System
Authors: Szodrai Ferenc , Kalmár Ferenc
Published: March 2019

Energy saving is one of the most important research directions in the building sector. Personalized ventilation systems are energy conscious solutions providing fresh air for the occupants. As a side effect, cooling energy can be saved due to higher convective heat removal. Using the data gathered from previous experiments performed with the developed personalized ventilation system, a ±1.408 °C accurate simulation model was created in ANSYS 19.2 Academic version in order to determine the temperature distribution on the face. In this paper, the method and the first results are presented. It was clearly demonstrated by measurements and simulations that the personalized ventilation equipment used has a considerable effect on the skin temperature of the face. The developed model can be used to analyze the skin temperature on the faces of people using the novel, personalized ventilation equipment. This way the time spent on examination can be reduced considerably.
Drying of Lignite of Various Origins in a Pilot Scale Toroidal Fluidized Bed Dryer using Low Quality Heat
Authors: Pawlak–Kruczek Halina , Czerep Michał , Niedzwiecki Lukasz , Karampinis Emmanouil , Violidakis Ioannis , Avagianos Ioannis , Grammelis Panagiotis
Published: March 2019

An experimental study was carried out for lignites of different places of origin, i.e., Poland, Greece, Romania and Australia, using a toroidal bed dryer. The effect of the temperature on the drying efficiency, including the loss of moisture content over time under fixed drying conditions was the subject of the investigation. The main goal was to confirm the possibility of the use of a toroidal bed as a base for a drying system that could utilize low quality heat from sources such as flue gases from a boiler and determine the optimum parameters for such a system. The conducted study has conclusively proven the feasibility of the use of low temperature heat sources for drying lignite in a toroidal bed. A moisture content of 20% could be achieved for most of the tested lignites, using the toroidal bed, with reasonably short residence times (approx. 30 min) and an air temperature as low as 60 °C. Moreover, the change of the particle size distribution, to some degree, affected the final moisture content due to the entrainment of wet, fine particles. The study also determined that the in-bed attrition of the particles is partially responsible for the generation of fines.
Review on the Use of Diesel–Biodiesel–Alcohol Blends in Compression Ignition Engines
Authors: Niculescu Rodica , Clenci Adrian , Iorga-Siman Victor
Published: March 2019

The use of alternative fuels contributes to the lowering of the carbon footprint of the internal combustion engine. Biofuels are the most important kinds of alternative fuels. Currently, thanks to the new manufacturing processes of biofuels, there is potential to decrease greenhouse gas (GHG) emissions, compared to fossil fuels, on a well-to-wheel basis. Amongst the most prominent alternative fuels to be used in mixtures/blends with fossil fuels in internal combustion (IC) engines are biodiesel, bioethanol, and biomethanol. With this perspective, considerable attention has been given to biodiesel and petroleum diesel fuel blends in compression ignition (CI) engines. Many studies have been conducted to assess the impacts of biodiesel use on engine operation. The addition of alcohols such as methanol and ethanol is also practised in biodiesel–diesel blends, due to their miscibility with the pure biodiesel. Alcohols improve the physico-chemical properties of biodiesel–diesel blends, which lead to improved CI engine operation. This review paper discusses some results of recent studies on biodiesel, bioethanol, and biomethanol production, their physicochemical properties, and also, on the influence of the use of diesel–biodiesel–alcohols blends in CI engines: combustion characteristics, performance, and emissions.