bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Fun through Gamification to Improve Engagement in MOOC
Authors: Borrás-Gené Oriol , Martínez-Núñez Margarita , Martín-Fernández Luis
Published: July 2019

Massive Open Online Courses (MOOCs), regardless of their topic, are a perfect space to generate, through virtual learning communities associated with them, very valuable resources for their participants and, in general, anyone interested in the topic covered. If in the design of these learning spaces, elements specific to games are added to them, which is known as gamification, we can try to increase the engagement of the student towards the course and, therefore, towards the community. This paper presents an experience of a MOOC of Universidad Rey Juan Carlos (Spain) with a connectivist approach. Aspects such as fun and motivation have been worked on in the design, through the application of gamified activities and the use of elements from social networks, considered as gamification, with the aim of increasing participation and engagement within a Facebook group, used as a community to support the course. We have analyzed aspects such as enjoyment and motivation, the result of which has been active participation and high engagement within the MOOC community in the form of content and especially great interaction, highlighting the existence of continuous activity once the edition of the MOOC is finished, as a consequence of a habit generated in the student.
Simplified Method to Estimate the Moment Capacity of Circular Columns Repaired with UHPC
Authors: Farzad Mahsa , Rastkar Siavash , Sadeghnejad Amir , Azizinamini Atorod
Published: July 2019

Ultra high-performance concrete (UHPC) application, to enhance the mechanical strength of axially loaded reinforced concrete bridge substructure elements, was proposed and investigated in an earlier study. The results recommended that depending on the UHPC shell thickness, this method may cause shifting of the critical section to undesired locations, due to over-strengthening of the repaired section, and this should be a design consideration. This paper proposes a new simplified analytical approach to calculate the bending moment capacity of the repaired circular section. This method relies on hand calculations and only requires basic material properties (compressive and tensile strengths). The results from the simplified approach are validated with a well-established numerical sectional analysis method. The proposed approach may be considered simple and more straightforward for professional engineers.
A Spectral Filter Array Camera for Clinical Monitoring and Diagnosis: Proof of Concept for Skin Oxygenation Imaging
Authors: Bauer Jacob Renzo , Bruins Arnoud A. , Hardeberg Jon Yngve , Verdaasdonk Rudolf M.
Published: July 2019

The emerging technology of spectral filter array (SFA) cameras has great potential for clinical applications, due to its unique capability for real time spectral imaging, at a reasonable cost. This makes such cameras particularly suitable for quantification of dynamic processes such as skin oxygenation. Skin oxygenation measurements are useful for burn wound healing assessment and as an indicator of patient complications in the operating room. Due to their unique design, in which all pixels of the image sensor are equipped with different optical filters, SFA cameras require specific image processing steps to obtain meaningful high quality spectral image data. These steps include spatial rearrangement, SFA interpolations and spectral correction. In this paper the feasibility of a commercially available SFA camera for clinical applications is tested. A suitable general image processing pipeline is proposed. As a ’proof of concept’ a complete system for spatial dynamic skin oxygenation measurements is developed and evaluated. In a study including 58 volunteers, oxygenation changes during upper arm occlusion were measured with the proposed SFA system and compared with a validated clinical device for localized oxygenation measurements. The comparison of the clinical standard measurements and SFA results show a good correlation for the relative oxygenation changes. This proposed processing pipeline for SFA cameras shows to be effective for relative oxygenation change imaging. It can be implemented in real time and developed further for absolute spatial oxygenation measurements.
Fuel Cell Application for Investigating the Quality of Electricity from Ship Hybrid Power Sources
Authors: Jeon Hyeonmin , Kim Seongwan , Yoon Kyoungkuk
Published: July 2019

Since recent marine application of fuel cell systems has been due largely limited to small-sized ships, this paper was aimed to investigate the technical applicability of molten carbonate fuel cell (MCFC) for medium and large-sized ships, using a 180 kW class hybrid test bed with combined power sources: A 100 kW MCFC, a 30 kW battery and a 50 kW diesel generator. This study focused primarily on determining whether the combined system designed in consideration of actual marine power system configuration could function properly. A case study was conducted with a 5500 Twenty-foot Equivalent Unit (TEU) container vessel. The operation profile was collected and analyzed in order to develop electric load scenarios applicable to the power system. Throughout the experiment, we evaluated the power quality of the voltage and frequency in the process of synchronization and de-synchronization across the power sources. Therefore, research results revealed that power quality continued to be excellent. This outcome provides insight into the technical reliability of MCFC application on large marine vessels.
Effect of Hygrothermal Aging and Surface Treatment on the Dynamic Mechanical Behavior of Flax Fiber Reinforced Composites
Authors: Wang Xiaomeng , Petrů Michal
Published: July 2019

The recent developments of FRP (fiber reinforced polymer) are towards the growth and usage of natural FRP in the field of engineering due to both environmental and economic benefits. Flax fiber is one of the most commonly used natural fibers. One of the critical factors affecting the mechanical behavior of FFRP (flax fiber reinforced polymer) is hygrothermal aging. Some experimental works have been conducted to investigate the effect of hydrothermal aging on static behavior of FFRP. However, fewer efforts have been made to study its damping properties after hydrothermal aging. In this paper, the effect of surface treatment (including alkalization, silanization, acetylation and alkali-silanization) on dynamic mechanical behavior of FFRP under hygrothermal aging is studied. The results show that water resistance and damping properties of FFRP are improved after surface treatment. The acetylation treated FFRP exhibits excellent damping performance among all treated specimens.
A Portfolio Choice Problem in the Framework of Expected Utility Operators
Authors: Georgescu Irina , Fono Louis Aimé
Published: July 2019

Possibilistic risk theory starts from the hypothesis that risk is modeled by fuzzy numbers. In particular, in a possibilistic portfolio choice problem, the return of a risky asset will be a fuzzy number. The expected utility operators have been introduced in a previous paper to build an abstract theory of possibilistic risk aversion. To each expected utility operator, one can associate the notion of possibilistic expected utility. Using this notion, we will formulate in this very general context a possibilistic portfolio choice problem. The main results of the paper are two approximate calculation formulas for the corresponding optimization problem. The first formula approximates the optimal allocation with respect to risk aversion and investor’s prudence, as well as the first three possibilistic moments. Besides these parameters, in the second formula, the temperance index of the utility function and the fourth possibilistic moment appear.
The Geometry of the Generalized Gamma Manifold and an Application to Medical Imaging
Authors: Rebbah Sana , Nicol Florence , Puechmorel Stéphane
Published: July 2019

The Fisher information metric provides a smooth family of probability measures with a Riemannian manifold structure, which is an object in information geometry. The information geometry of the gamma manifold associated with the family of gamma distributions has been well studied. However, only a few results are known for the generalized gamma family that adds an extra shape parameter. The present article gives some new results about the generalized gamma manifold. This paper also introduces an application in medical imaging that is the classification of Alzheimer’s disease population. In the medical field, over the past two decades, a growing number of quantitative image analysis techniques have been developed, including histogram analysis, which is widely used to quantify the diffuse pathological changes of some neurological diseases. This method presents several drawbacks. Indeed, all the information included in the histogram is not used and the histogram is an overly simplistic estimate of a probability distribution. Thus, in this study, we present how using information geometry and the generalized gamma manifold improved the performance of the classification of Alzheimer’s disease population.
Unsteady Magnetohydrodynamic Convective Fluid Flow of Oldroyd-B Model Considering Ramped Wall Temperature and Ramped Wall Velocity
Authors: Tiwana Mazhar Hussain , Mann Amer Bilal , Rizwan Muhammad , Maqbool Khadija , Javeed Shumaila , Raza Saqlain , Khan Mansoor Shaukat
Published: July 2019

This paper examines unsteady magnetohydrodynamic (MHD) convective fluid flow described by the Oldroyd-B model using ramped wall temperature and velocity simultaneously. The fluid flow is closed to an infinite vertical flat plate immersed through a porous medium. Laplace transformation is used to find solutions of momentum and energy equations. Afterwards, the Nusselt number and skin friction coefficient are obtained. A parametric study is performed to investigate the effects of ramped velocity and temperature (at wall) on the considered fluid flow model.
A New Method to Study the Periodic Solutions of the Ordinary Differential Equations Using Functional Analysis
Authors: Kadry Seifedine , Alferov Gennady , Ivanov Gennady , Korolev Vladimir , Selitskaya Ekaterina
Published: July 2019

In this paper, a new theorems of the derived numbers method to estimate the number of periodic solutions of first-order ordinary differential equations are formulated and proved. Approaches to estimate the number of periodic solutions of ordinary differential equations are considered. Conditions that allow us to determine both upper and lower bounds for these solutions are found. The existence and stability of periodic problems are considered.
2D Hybrid Steady-State Magnetic Field Model for Linear Induction Motors
Authors: Aleksandrov Samuil R. , Overboom Timo T. , Lomonova Elena A.
Published: July 2019

This paper presents a 2D hybrid steady-state magnetic field model, capable of accurately modeling the electromagnetic behavior in a linear induction motor, including primary slotting, finite yoke length, and longitudinal end-effects by primary motion. This model integrates a complex harmonic modeling technique with a discretized magnetic equivalent circuit model. The Fourier model is applied to regions with homogeneous material properties, e.g., air regions and the track of the motor, while the magnetic equivalent circuit (MEC) approach is used for the regions containing non-homogeneous material properties, e.g., the primary of the linear induction motor (LIM). By only meshing the domains containing highly-permeable materials, the computational effort is reduced in comparison with the finite element method (FEM). The model is applied to a double-layer single-sided LIM, and the resulting thrust and normal forces show an excellent agreement with respect to finite element analysis and measurement data.
New Discorhabdin Alkaloids from the Antarctic Deep-Sea Sponge Latrunculia biformis
Authors: Li Fengjie , Peifer Christian , Janussen Dorte , Tasdemir Deniz
Published: July 2019

The sponge genus Latrunculia is a prolific source of discorhabdin type pyrroloiminoquinone alkaloids. In the continuation of our research interest into this genus, we studied the Antarctic deep-sea sponge Latrunculia biformis that showed potent in vitro anticancer activity. A targeted isolation process guided by bioactivity and molecular networking-based metabolomics yielded three known discorhabdins, (−)-discorhabdin L (1), (+)-discorhabdin A (2), (+)-discorhabdin Q (3), and three new discorhabdin analogs (−)-2-bromo-discorhabdin D (4), (−)-1-acetyl-discorhabdin L (5), and (+)-1-octacosatrienoyl-discorhabdin L (6) from the MeOH-soluble portion of the organic extract. The chemical structures of 1–6 were elucidated by extensive NMR, HR-ESIMS, FT-IR, [α]D, and ECD (Electronic Circular Dichroism) spectroscopy analyses. Compounds 1, 5, and 6 showed promising anticancer activity with IC50 values of 0.94, 2.71, and 34.0 µM, respectively. Compounds 1–6 and the enantiomer of 1 ((+)-discorhabdin L, 1e) were docked to the active sites of two anticancer targets, topoisomerase I-II and indoleamine 2,3-dioxygenase (IDO1), to reveal, for the first time, the binding potential of discorhabdins to these proteins. Compounds 5 and 6 are the first discorhabdin analogs with an ester function at C-1 and 6 is the first discorhabdin bearing a long-chain fatty acid at this position. This study confirms Latrunculia sponges to be excellent sources of chemically diverse discorhabdin alkaloids.
Efficacy of Compounds Isolated from Streptomyces olivaceus against the Morphogenesis and Virulence of Candida albicans
Authors: Meng Lili , Sun Changli , Zhang Chunyan , Song Shihao , Sun Xiuyun , Ju Jianhua , Deng Yinyue
Published: July 2019

Candida albicans is a type of commensal fungi which causes serious infections in immunocompromised patients and contributes to high mortality. In the present study, we identified that the extract from Streptomyces olivaceus SCSIO T05 inhibited hypha and biofilm formation of C. albicans. Seven compounds were isolated and evaluated for their effects on the biological functions and virulence of C. albicans. Two leading compounds, compound 1 (sorbicillin) and compound 2 (3-methyl-N-(2′-phenethyl)-butyrylamide) were identified as exhibiting strong activity against C. albicans morphological transition, adhesion activity, cytotoxicity, and adhesion to human cells, in a dose-dependent manner. Notably, compound 2 inhibited C. albicans infection in mouse oral mucosal models. Transcriptomic analysis and real-time PCR results revealed that compound 2 most likely inhibited the biological functions of C. albicans cells by regulating the expression levels of HWP1, TEC1, ALS1, IFD6, and CSH1, which are associated with filament formation and cell adhesion. Our results suggest that the candidate compounds present excellent efficacy against C. albicans pathogenicity and that they can be developed as potential options for the clinical treatment of candidiasis.
Is Abdominal Aortic Aneurysm Behavior after Endovascular Repair Associated with Aneurysm Wall Density on Computed Tomography Angiography?
Authors: Skrebūnas Arminas , Lengvenis Givi , Builytė Inga Urtė , Žulpaitė Rūta , Bliūdžius Rytis , Purlys Petras , Baltrūnas Tomas , Misonis Nerijus , Matačiūnas Mindaugas , Marinskis Germanas , Vajauskas Donatas
Published: July 2019

Background and objectives: Abdominal aortic aneurysm (AAA) growth is unpredictable after the endovascular aneurysm repair (EVAR). Continuing aortic wall degradation and weakening due to hypoxia may have a role in post-EVAR aneurysm sac growth. We aimed to assess the association of aortic wall density on computed tomography angiography (CTA) with aneurysm growth following EVAR. Materials and Methods: A total of 78 patients were included in the study. The control group consisted of 39 randomly assigned patients without aortic pathology. Post-EVAR aneurysm sac volumes on CTA were measured twice during the follow-up period to estimate aneurysm sac behavior. A maximum AAA sac diameter, aortic wall and lumen densities in Hounsfield units (HU) on CTA were measured. A relative aortic wall density (the ratio of aortic wall to lumen densities) was calculated. A statistical data analysis was performed using standard methods. Results: An increase in the AAA sac volume was observed in 12 (30.8%) cases. Median relative aortic wall density on CTA scores in both the patient and the control group at the level of the diaphragm were similar: 0.15 (interquartile range (IQR), 0.11–0.18) and 0.16 (IQR 0.11–0.18), p = 0.5378, respectively. The median (IQR) relative aortic wall density score at the level of the maximum AAA diameter in the patient group was lower than at the level below renal arteries in the control group: 0.10 (0.07–0.12) and 0.17 (0.12–0.23), p < 0.0001, respectively. The median (IQR) relative growing AAA sac wall density score was lower than a relative stable/shrinking AAA sac wall density score: 0.09 (0.06–0.10) and 0.11 (0.09–0.13), p = 0.0096, respectively. Conclusions: A lower aortic aneurysm wall density on CTA may be associated with AAA growth after EVAR.
Investigation of the Potential Effects of Host Genetics and Probiotic Treatment on the Gut Bacterial Community Composition of Aquaculture-raised Pacific Whiteleg Shrimp, Litopenaeus vannamei
Authors: Landsman Angela , St-Pierre Benoit , Rosales-Leija Misael , Brown Michael , Gibbons William
Published: July 2019

This study presents the potential effects of the genetic background and use of probiotics on the gut bacterial composition of Pacific whiteleg shrimp (Litopenaeus vannamei) grown in an indoor aquaculture facility. The strains investigated were Shrimp Improvement Systems (SIS, Islamorada, FL, USA), a strain genetically selected for disease resistance, and an Oceanic Institute (OI, Oahu, HI, USA) strain, selected for growth performance. BioWish 3P (BioWish Technologies, Cincinnati, OH, USA) was the selected probiotic. The study consisted of two separate trials, where all shrimp were raised under standard industry conditions and fed the same diet. Shrimp were stocked in 2920 L production tanks at a density of 200/m3 and acclimated for 14 days. After the acclimation period, triplicate tanks were supplemented daily for a duration of 28 days with probiotics, while three other tanks did not receive any treatment (controls). During the 28-day trial period, there was no statistically supported difference (p > 0.05) in either performance or health status as a result of genetic background or probiotic treatment. However, differences in gut bacterial composition, as assessed by high throughput sequencing of amplicons generated from the V1-V3 region of the bacterial 16S rRNA gene, were observed. The relative abundance of five major operational taxonomic units (OTUs) were found to vary significantly across experimental groups (p < 0.05). Notably, operational taxonomic unit (OTU) SD_Shr-00006 was at its highest abundance in d43 SIS samples, with levels greater than d71 samples of the same genetic line or any of the OI shrimp samples. OTUs for SD_Shr-00098 displayed a similar type of profile, but with highest abundance in the OI genetic line and lowest in the SIS shrimp. SD_Shr-00004 showed an opposite profile, with highest abundance in the SIS d71 samples and lowest in the SIS d43 samples. Together, these results suggest that host genetic background can be an important determinant of gut bacterial composition in aquaculture-raised whiteleg shrimp and indicate that development of strategies to manipulate the microbiome of this important seafood will likely need to be customized depending on the genetic line.
Developing Gut Microbiota Exerts Colonisation Resistance to Clostridium (syn. Clostridioides) difficile in Piglets
Authors: Grześkowiak Łukasz , Dadi Temesgen Hailemariam , Zentek Jürgen , Vahjen Wilfried
Published: July 2019

Clostridium (syn. Clostridioides) difficile is considered a pioneer colonizer and may cause gut infection in neonatal piglets. The aim of this study was to explore the microbiota-C. difficile associations in pigs. We used the DNA from the faeces of four sows collected during the periparturient period and from two to three of their piglets (collected weekly until nine weeks of age) for the determination of bacterial community composition (sequencing) and C. difficile concentration (qPCR). Furthermore, C. difficile-negative faeces were enriched in a growth medium, followed by qPCR to verify the presence of this bacterium. Clostridium-sensu-stricto-1 and Lactobacillus spp. predominated the gut microbiota of the sows and their offspring. C. difficile was detected at least once in the faeces of all sows during the entire sampling period, albeit at low concentrations. Suckling piglets harboured C. difficile in high concentrations (up to log10 9.29 copy number/g faeces), which gradually decreased as the piglets aged. Enrichment revealed the presence of C. difficile in previously C. difficile-negative sow and offspring faeces. In suckling piglets, the C. difficile level was negatively correlated with carbohydrate-fermenting bacteria, and it was positively associated with potential pathogens. Shannon and richness diversity indices were negatively associated with the C. difficile counts in suckling piglets. This study showed that gut microbiota seems to set conditions for colonisation resistance against C. difficile in the offspring. However, this conclusion requires further research to include host-specific factors.
Inferring Drug-Related Diseases Based on Convolutional Neural Network and Gated Recurrent Unit
Authors: Xuan Ping , Zhao Lianfeng , Zhang Tiangang , Ye Yilin , Zhang Yan
Published: July 2019

Predicting novel uses for drugs using their chemical, pharmacological, and indication information contributes to minimizing costs and development periods. Most previous prediction methods focused on integrating the similarity and association information of drugs and diseases. However, they tended to construct shallow prediction models to predict drug-associated diseases, which make deeply integrating the information difficult. Further, path information between drugs and diseases is important auxiliary information for association prediction, while it is not deeply integrated. We present a deep learning-based method, CGARDP, for predicting drug-related candidate disease indications. CGARDP establishes a feature matrix by exploiting a variety of biological premises related to drugs and diseases. A novel model based on convolutional neural network (CNN) and gated recurrent unit (GRU) is constructed to learn the local and path representations for a drug-disease pair. The CNN-based framework on the left of the model learns the local representation of the drug-disease pair from their feature matrix. As the different paths have discriminative contributions to the drug-disease association prediction, we construct an attention mechanism at the path level to learn the informative paths. In the right part, a GRU-based framework learns the path representation based on path information between the drug and the disease. Cross-validation results indicate that CGARDP performs better than several state-of-the-art methods. Further, CGARDP retrieves more real drug-disease associations in the top part of the prediction result that are of concern to biologists. Case studies on five drugs demonstrate that CGARDP can discover potential drug-related disease indications.
The Effect of Chitosan Derivatives on the Compaction and Tension Generation of the Fibroblast-populated Collagen Matrix
Authors: Doan K. Tu , Kshetri Pratiksha , Attamakulsri Natthapume , Newsome Derek R. , Zhou Feifan , Murray Cynthia K. , Chen Wei R. , Xu Gang , Vaughan Melville B.
Published: July 2019

Fibrotic diseases, such as Dupuytren’s contracture (DC), involve excess scar tissue formation. The differentiation of fibroblasts into myofibroblasts is a significant mechanism in DC, as it generates tissue contraction in areas without wound openings, leading to the deposition of scar tissue, and eventually flexing one or more fingers in a restrictive fashion. Additionally, DC has a high recurrence rate. Previously, we showed that N-dihydrogalactochitosan (GC), an immunostimulant, inhibited myofibroblast differentiation in a DC fibroblast culture. Our goal of this study was to expand our previous study to include other DC and normal cell lines and other chitosan derivatives (GC and single-walled carbon nanotube-conjugated GC) to determine the specific mechanism of inhibition. Derivative-incorporated and vehicle control (water) anchored fibroblast-populated collagen matrices (aFPCM) were used to monitor compaction (anchored matrix height reduction) using microscopy and optical coherence tomography (OCT) for six days. Fibroblasts were unable to compact chitosan derivative aFPCM to the same extent as vehicle control aFPCM in repeated experiments. Similarly, chitosan derivative aFPCM contracted less than control aFPCM when released from anchorage. Proliferative myofibroblasts were identified by the presence of alpha smooth muscle actin via myofibroblast proliferative assay. In all tested conditions, a small percentage of myofibroblasts and proliferative cells were present. However, when aFPCM were treated with transforming growth factor-beta 1 (TGF-β1), all tested samples demonstrated increased myofibroblasts, proliferation, compaction, and contraction. Although compaction and contraction were reduced, there was sufficient tension present in the chitosan derivative aFPCM to allow exogenous stimulation of the myofibroblast phenotype.
The High Efficiency of Anionic Dye Removal Using Ce-Al13/Pillared Clay from Darbandikhan Natural Clay
Authors: K. Aziz Bakhtyar , M. Salh Dler , Kaufhold Stephan , Bertier Pieter
Published: July 2019

Natural clay from Darbandikhan (DC) was evaluated in its natural form, after acid activation (ADC), and after pillaring (PILDC) as a potential adsorbent for the adsorption of methyl orange (MO) as a model anionic dye adsorbate. The effect of different clay treatments was investigated using X-Ray Diffraction (XRD), X-Ray Fluorescence (XRF), Scanning Electron Microscope (SEM) and Fourier-Transform Infrared Spectroscopy (FT-IR), and N2 physisorption analysis. Both acid activation and pillaring resulted in a significant increase in adsorption affinity, respectively. The adsorption favored acidic pH for the anionic dye (MO). The adsorption process was found to follow pseudo-second-order kinetics with activation energies of 5.9 and 40.1 kJ·mol−1 for the adsorption of MO on ADC and PILDC, respectively, which are characteristic of physical adsorption. The adsorption isotherms (Langmuir, Redlich-Peterson and Freundlich) were fitted well to the experimental data. The specific surface area of the natural clay was very low (22.4 m2·g−1) compared to high-class adsorbent materials. This value was increased to 53.2 m2·g−1 by the pillaring process. Nevertheless, because of its local availability, the activated materials may be useful for the cleaning of local industrial wastewaters.
Discovery of (5-Phenylfuran-2-yl)methanamine Derivatives as New Human Sirtuin 2 Inhibitors
Authors: Wang Lijiao , Li Chao , Chen Wei , Song Chen , Zhang Xing , Yang Fan , Wang Chen , Zhang Yuanyuan , Qian Shan , Wang Zhouyu , Yang Lingling
Published: July 2019

Human sirtuin 2 (SIRT2), a member of the sirtuin family, has been considered as a promising drug target in cancer, neurodegenerative diseases, type II diabetes, and bacterial infections. Thus, SIRT2 inhibitors have been involved in effective treatment strategies for related diseases. Using previously established fluorescence-based assays for SIRT2 activity tests, the authors screened their in-house database and identified a compound, 4-(5-((3-(quinolin-5-yl)ureido)methyl)furan-2-yl)benzoic acid (20), which displayed 63 ± 5% and 35 ± 3% inhibition against SIRT2 at 100 μM and 10 μM, respectively. The structure-activity relationship (SAR) analyses of a series of synthesized (5-phenylfuran-2-yl)methanamine derivatives led to the identification of a potent compound 25 with an IC50 value of 2.47 μM, which is more potent than AGK2 (IC50 = 17.75 μM). Meanwhile, 25 likely possesses better water solubility (cLogP = 1.63 and cLogS = −3.63). Finally, the molecular docking analyses indicated that 25 fitted well with the induced hydrophobic pocket of SIRT2.
Solvation Free Energy Simulation for Rosmarinic Acid Extraction from Orthosiphon stamineus
Authors: Lau Cher Haan , Chua Lee Suan
Published: July 2019

This study was aimed to extract rosmarinic acid from Orthosiphon stamineus Benth. (Lamiaceae) in high yield. The mixture of chloroform–ethyl acetate (70:30) was chosen as the solvent system because rosmarinic acid gave the lowest solvation free energy in that solvent system based on the computational solubility prediction. The crude extract of the plant was fractionated by C18 reversed phase absorbent to recover rosmarinic acid. The content of rosmarinic acid was increased from 4.0% w/w to 6.7% w/w after fractionation. The radical scavenging activity of rosmarinic acid rich fraction (IC50 = 38.3 μg/mL) was higher than the crude extract (IC50 = 58.85 μg/mL) based on the DPPH assay. Several phytochemicals were also identified based on the detection of fragment ions of target compounds. Fractions 1 to 3 could be combined to be a rosmarinic acid rich fraction. Simultaneously, the combination of fractions 4 to 6 could obtain a plant fraction rich in rosmarinic acid, sinensetin and eupatorin, whereas fractions 7 to 9 could be combined as a sinensetin rich fraction. The preparation of known phytochemical profile of O. stamineus fraction is highly required for value added product formulation and pharmacological studies, particularly for anti-diabetes and kidney related diseases which had previously been reported attributed to this herbal plant. This is the first study using solvation free energy to predict the suitable solvent system for rosmarinic acid extraction from highly complex herbal sample using the technology of solid phase extraction. The use of solvation free energy simulation is convenient and reliable before wet experiments for time and cost saving.
Accessible Digital Musical Instruments—A Review of Musical Interfaces in Inclusive Music Practice
Authors: Frid Emma
Published: July 2019

Current advancements in music technology enable the creation of customized Digital Musical Instruments (DMIs). This paper presents a systematic review of Accessible Digital Musical Instruments (ADMIs) in inclusive music practice. History of research concerned with facilitating inclusion in music-making is outlined, and current state of developments and trends in the field are discussed. Although the use of music technology in music therapy contexts has attracted more attention in recent years, the topic has been relatively unexplored in Computer Music literature. This review investigates a total of 113 publications focusing on ADMIs. Based on the 83 instruments in this dataset, ten control interface types were identified: tangible controllers, touchless controllers, Brain–Computer Music Interfaces (BCMIs), adapted instruments, wearable controllers or prosthetic devices, mouth-operated controllers, audio controllers, gaze controllers, touchscreen controllers and mouse-controlled interfaces. The majority of the AMDIs were tangible or physical controllers. Although the haptic modality could potentially play an important role in musical interaction for many user groups, relatively few of the ADMIs (14.5%) incorporated vibrotactile feedback. Aspects judged to be important for successful ADMI design were instrument adaptability and customization, user participation, iterative prototyping, and interdisciplinary development teams.
λ-Scale Embedded Active Region Photonic Crystal (LEAP) Lasers for Optical Interconnects
Authors: Matsuo Shinji , Takeda Koji
Published: July 2019

The distances optical interconnects must cover are decreasing as Internet traffic continues to increase. Since short-reach interconnect applications require many transmitters, cost and power consumption are significant issues. Directly modulated lasers with a wavelength-scale active volume will be used as optical interconnects on boards and chips in the future because a small active volume is expected to reduce power consumption. We developed electrically driven photonic crystal (PhC) lasers with a wavelength-scale cavity in which the active region is embedded in a line-defect waveguide of an InP-based PhC slab. We call this a λ-scale embedded active region PhC laser, or a LEAP laser. The device, whose active region has six quantum wells with 2.5 × 0.3 × 0.15 μm3 active volume, exhibits a threshold current of 28 μA and provides 10 fJ/bit of operating energy to 25 Gbit/s NRZ (non-return-to-zero) signals. The fiber-coupled output power is 6.9 μW. We also demonstrate heterogeneous integration of LEAP lasers on a SiO2/Si substrate for low-cost photonic integrated circuits (PICs). The threshold current is 40.5 μA and the output power is 4.4 μW with a bias current of 200 μA. These results indicate the feasibility of using PhC lasers in very-short-distance optical communications.
Thermal Cross Linking of Novel Azide Modified Polymers of Intrinsic Microporosity—Effect of Distribution and the Gas Separation Performance
Authors: Neumann Silvio , Bengtson Gisela , Meis David , Filiz Volkan
Published: July 2019

The synthesis of polymers of intrinsic microporosity (PIM) modified with azide groups, the cross linkage by nitrene reaction and their performance as gas separation membranes are reported. The azide modification of the spirobisindane units in the polymer backbone was done by post functionalization of methylated spirobisindane containing polymers. These polymers differ in distribution and concentration of the azide group containing spirobisindane units by applying perfectly alternating and randomly distributed copolymers along the polymer chains. To investigate the influence of concentration of the azide groups, additionally the homopolymer of methylated spirobisindane was synthesized and subjected to identical treatments and characterizations as both copolymers. Cross linkage by nitrene reaction was examined by different temperature treatments at 150, 200, 250 and 300 °C. Characterization of the new polymers was performed by NMR, SEC and FT-IR. Furthermore, the crosslinking process was investigated by means of solid state NMR, TGA-FTIR, DSC and isoconversional kinetic analysis performed with TGA. Gas permeability of CO2, N2, CH4, H2 and O2 was determined by time lag experiments and ideal selectivities for several gas pairs were calculated. The two azide groups per repeating unit degrade during thermal treatments by release of nitrogen and form mechanically stable PIM networks, leading to an increase in gas permeability while selectivity remained nearly constant. Measured diffusivity and solubility coefficients revealed differences in the formation of free volume elements depending on distribution and concentration of the azide groups. Aging studies over about five months were performed and physical aging rates (βP) were evaluated with regard to the concentration and distribution of curable azide functionalities. Subsequently, the enhanced sieving effect during aging resulted in membrane materials that surpassed the Robeson upper bound in selected gas pairs.
Maintenance Optimization Model with Sequential Inspection Based on Real-Time Reliability Evaluation for Long-Term Storage Systems
Authors: Bai Senyang , Cheng Zhijun , Guo Bo
Published: July 2019

For long-term storage systems such as rockets and missiles, most of the relevant models and algorithms for inspection and maintenance currently focus on analysis based on periodic inspection. However, considering factors such as the complexity of the degradation mechanisms of these systems, the constraints imposed by failure risk, and the uncertainty caused by environmental factors, it is preferable to dynamically determine the inspection intervals based on real-time status information. This paper investigates the issue of maintenance optimization modelling for long-term storage systems based on real-time reliability evaluation. First, the Wiener process is used to establish a performance degradation model for one critical unit of such a system, and a closed-form expression for the real-time reliability distribution is obtained by using the first-hitting-time theory. Second, sequential inspection intervals are dynamically determined by combining the real-time reliability function with a real-time reliability threshold for the system. Third, a maintenance optimization model is established for the critical unit based on update process theory. An analytical expression for the expected total cost rate is derived, and then, the real-time reliability threshold and the preventive maintenance threshold for the unit are jointly optimized by means of Monte Carlo simulation, with the lowest expected total cost rate as the optimization goal. Finally, two examples of a gyroscope and an alloy blade that are commonly used in the long-term storage systems are considered, and the validity of the proposed model is illustrated by means of a sensitivity analysis of the relevant parameters.
TAEO-A Thermal Aware & Energy Optimized Routing Protocol for Wireless Body Area Networks
Authors: Javed Mohsin , Ahmed Ghufran , Mahmood Danish , Raza Mohsin , Ali Kamran , Ur-Rehman Masood
Published: July 2019

Wireless Body Area Networks (WBANs) are in the spotlight of researchers and engineering industries due to many applications. Remote health monitoring for general as well as military purposes where tiny sensors are attached or implanted inside the skin of the body to sense the required attribute is particularly prominent. To seamlessly accomplish this procedure, there are various challenges, out of which temperature control to reduce thermal effects and optimum power consumption to reduce energy wastage are placed at the highest priority. Regular and consistent operation of a sensor node for a long-time result in a rising of the temperature of respective tissues, where it is attached or implanted. This temperature rise has harmful effects on human tissues, which may lead to the tissue damage. In this paper, a Temperate Aware and Energy Optimized (TAEO) routing protocol is proposed that not only deals with the thermal aspects and hot spot problem, but also extends the stability and lifetime of a network. Analytical simulations are conducted, and the results depict better performance in terms of the network lifetime, throughput, energy preservation, and temperature control with respect to state of the art WBAN protocols.
Quantitative Analysis of Elements in Fertilizer Using Laser-Induced Breakdown Spectroscopy Coupled with Support Vector Regression Model
Authors: Sha Wen , Li Jiangtao , Xiao Wubing , Ling Pengpeng , Lu Cuiping
Published: July 2019

The rapid detection of the elements nitrogen (N), phosphorus (P), and potassium (K) is beneficial to the control of the compound fertilizer production process, and it is of great significance in the fertilizer industry. The aim of this work was to compare the detection ability of laser-induced breakdown spectroscopy (LIBS) coupled with support vector regression (SVR) and obtain an accurate and reliable method for the rapid detection of all three elements. A total of 58 fertilizer samples were provided by Anhui Huilong Group. The collection of samples was divided into a calibration set (43 samples) and a prediction set (15 samples) by the Kennard–Stone (KS) method. Four different parameter optimization methods were used to construct the SVR calibration models by element concentration and the intensity of characteristic line variables, namely the traditional grid search method (GSM), genetic algorithm (GA), particle swarm optimization (PSO), and least squares (LS). The training time, determination coefficient, and the root-mean-square error for all parameter optimization methods were analyzed. The results indicated that the LIBS technique coupled with the least squares–support vector regression (LS-SVR) method could be a reliable and accurate method in the quantitative determination of N, P, and K elements in complex matrix like compound fertilizers.
Performance Enriching Channel Allocation Algorithm for Vehicle-to-Vehicle City, Highway and Rural Network
Authors: Al-Absi Mohammed Abdulhakim , Al-Absi Ahmed Abdulhakim , Lee Hoon Jae
Published: July 2019

Future safety applications require the timely delivery of messages between vehicles. The 802.11p has been standardized as the standard Medium Access Control (MAC) protocol for vehicular communication. The 802.11p uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) as MAC. CSMA/CA induces unbounded channel access delay. As a result, it induces high collision. To reduce collision, distributed MAC is required for channel allocation. Many existing approaches have adopted Time Division Multiple Access (TDMA) based MAC design for channel allocation. However, these models are not efficient at utilizing bandwidth. Cognitive radio technique is been adopted by various existing approach for channel allocation in shared channel network to maximize system throughput. However, it induces MAC overhead, and channel allocation on a shared channel network is considered to be an NP-hard problem. This work addresses the above issues. Here we present distributed MAC design PECA (Performance Enriching Channel Allocation) for channel allocation in a shared channel network. The PECA model maximizes the system throughput and reduces the collision, which is experimentally proven. Experiments are conducted to evaluate the performance in terms of throughput, collision and successful packet transmission considering a highly congested vehicular ad-hoc network. Experiments are carried out to show the adaptiveness of proposed MAC design considering different environments such City, Highway and Rural (CHR).
IoT Based Heart Activity Monitoring Using Inductive Sensors
Authors: Brezulianu Adrian , Geman Oana , Zbancioc Marius Dan , Hagan Marius , Aghion Cristian , Hemanth D. Jude , Son Le Hoang
Published: July 2019

This paper presents a system dedicated to monitoring the heart activity parameters using Electrocardiography (ECG) mobile devices and a Wearable Heart Monitoring Inductive Sensor (WHMIS) that represents a new method and device, developed by us as an experimental model, used to assess the mechanical activity of the hearth using inductive sensors that are inserted in the fabric of the clothes. Only one inductive sensor is incorporated in the clothes in front of the apex area and it is able to assess the cardiorespiratory activity while in the prior of the art are presented methods that predict sensors arrays which are distributed in more places of the body. The parameters that are assessed are heart data-rate and respiration. The results are considered preliminary in order to prove the feasibility of this method. The main goal of the study is to extract the respiration and the data-rate parameters from the same output signal generated by the inductance-to-number convertor using a proper algorithm. The conceived device is meant to be part of the “wear and forget” equipment dedicated to monitoring the vital signs continuously.
Fuzzy Clustering Algorithm with Non-Neighborhood Spatial Information for Surface Roughness Measurement Based on the Reflected Aliasing Images
Authors: Zhang Hang , Liu Jian , Chen Lin , Chen Ning , Yang Xiao
Published: July 2019

Due to the limitation of the fixed structures of neighborhood windows, the quality of spatial information obtained from the neighborhood pixels may be affected by noise. In order to compensate this drawback, a robust fuzzy c-means clustering with non-neighborhood spatial information (FCM_NNS) is presented. Through incorporating non-neighborhood spatial information, the robustness performance of the proposed FCM_NNS with respect to the noise can be significantly improved. The results indicate that FCM_NNS is very effective and robust to noisy aliasing images. Moreover, the comparison of other seven roughness indexes indicates that the proposed FCM_NNS-based F index can characterize the aliasing degree in the surface images and is highly correlated with surface roughness (R2 = 0.9327 for thirty grinding samples).
Design and Experimental Validation of a LoRaWAN Fog Computing Based Architecture for IoT Enabled Smart Campus Applications
Authors: Fraga-Lamas Paula , Celaya-Echarri Mikel , Lopez-Iturri Peio , Castedo Luis , Azpilicueta Leyre , Aguirre Erik , Suárez-Albela Manuel , Falcone Francisco , Fernández-Caramés Tiago M.
Published: July 2019

A smart campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university campus. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability. The technologies employed so far to cope with such a scenario are not yet able to manage simultaneously all the previously mentioned demanding requirements. Nevertheless, recent paradigms such as fog computing, which extends cloud computing to the edge of a network, make possible low-latency and location-aware IoT applications. Moreover, technologies such as Low-Power Wide-Area Networks (LPWANs) have emerged as a promising solution to provide low-cost and low-power consumption connectivity to nodes spread throughout a wide area. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is one of the most recent developments, receiving attention both from industry and academia. In this article, the use of a LoRaWAN fog computing-based architecture is proposed for providing connectivity to IoT nodes deployed in a campus of the University of A Coruña (UDC), Spain. To validate the proposed system, the smart campus has been recreated realistically through an in-house developed 3D Ray-Launching radio-planning simulator that is able to take into consideration even small details, such as traffic lights, vehicles, people, buildings, urban furniture, or vegetation. The developed tool can provide accurate radio propagation estimations within the smart campus scenario in terms of coverage, capacity, and energy efficiency of the network. The results obtained with the planning simulator can then be compared with empirical measurements to assess the operating conditions and the system accuracy. Specifically, this article presents experiments that show the accurate results obtained by the planning simulator in the largest scenario ever built for it (a campus that covers an area of 26,000 m 2 ), which are corroborated with empirical measurements. Then, how the tool can be used to design the deployment of LoRaWAN infrastructure for three smart campus outdoor applications is explained: a mobility pattern detection system, a smart irrigation solution, and a smart traffic-monitoring deployment. Consequently, the presented results provide guidelines to smart campus designers and developers, and for easing LoRaWAN network deployment and research in other smart campuses and large environments such as smart cities.