bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome Subtraction and Comparison for the Identification of Novel Drug Targets against Mycobacterium avium subsp. hominissuis
Authors: Uddin Reaz , Siraj Bushra , Rashid Muhammad , Khan Ajmal , Ahsan Halim Sobia , Al-Harrasi Ahmed
Published: May 2020

Mycobacterium avium complex (MAC) is a major cause of non-tuberculous pulmonary and disseminated diseases worldwide, inducing bronchiectasis, and affects HIV and immunocompromised patients. In MAC, Mycobacterium avium subsp. hominissuis is a pathogen that infects humans and mammals, and that is why it is a focus of this study. It is crucial to find essential drug targets to eradicate the infections caused by these virulent microorganisms. The application of bioinformatics and proteomics has made a significant impact on discovering unique drug targets against the deadly pathogens. One successful bioinformatics methodology is the use of in silico subtractive genomics. In this study, the aim was to identify the unique, non-host and essential protein-based drug targets of Mycobacterium avium subsp. hominissuis via in silico a subtractive genomics approach. Therefore, an in silico subtractive genomics approach was applied in which complete proteome is subtracted systematically to shortlist potential drug targets. For this, the complete dataset of proteins of Mycobacterium avium subsp. hominissuis was retrieved. The applied subtractive genomics method, which involves the homology search between the host and the pathogen to subtract the non-druggable proteins, resulted in the identification of a few prioritized potential drug targets against the three strains of M. avium subsp. Hominissuis, i.e., MAH-TH135, OCU466 and A5. In conclusion, the current study resulted in the prioritization of vital drug targets, which opens future avenues to perform structural as well as biochemical studies on predicted drug targets against M. avium subsp. hominissuis.
Brucella abortus Proliferates in Decidualized and Non-Decidualized Human Endometrial Cells Inducing a Proinflammatory Response
Authors: Zavattieri Lucía , Ferrero Mariana C. , Alonso Paiva Iván M. , Sotelo Agustina D. , Canellada Andrea M. , Baldi Pablo C.
Published: May 2020

Brucella spp. have been associated with abortion in humans and animals. Although the mechanisms involved are not well established, it is known that placental Brucella infection is accompanied by inflammatory phenomena. The ability of Brucella abortus to infect and survive in human endometrial stromal cells (T-HESC cell line) and the cytokine response elicited were evaluated. B. abortus was able to infect and proliferate in both non-decidualized and decidualized T-HESC cells. Intracellular proliferation depended on the expression of a functional virB operon in the pathogen. B. abortus internalization was inhibited by cytochalasin D and to a lower extent by colchicine, but was not affected by monodansylcadaverine. The infection did not induce cytotoxicity and did not alter the decidualization status of cells. B. abortus infection elicited the secretion of IL-8 and MCP-1 in either decidualized or non-decidualized T-HESC, a response also induced by heat-killed B. abortus and outer membrane vesicles derived from this bacterium. The stimulation of T-HESC with conditioned media from Brucella-infected macrophages induced the production of IL-6, MCP-1 and IL-8 in a dose-dependent manner, and this effect was shown to depend on IL-1β and TNF-α. The proinflammatory responses of T-HESC to B. abortus and to factors produced by infected macrophages may contribute to the gestational complications of brucellosis.
Experimental Infection of Newly Hatched Domestic Ducklings via Japanese Encephalitis Virus-Infected Mosquitoes
Authors: Di Di , Li Chenxi , Zhang Junjie , Hameed Muddassar , Wang Xin , Xia Qiqi , Li Hui , Xi Shumin , Li Zongjie , Liu Ke , Li Beibei , Shao Donghua , Qiu Yafeng , Wei Jianchao , Ma Zhiyong
Published: May 2020

Japanese encephalitis virus (JEV) is a zoonotic pathogen that is maintained by mosquito vectors and vertebrate hosts including birds in a natural transmission cycle. Domestic ducklings are sensitive to JEV infection, but the clinical responses of domestic ducklings to natural JEV infection are unknown. In this study, we simulated the natural JEV infection of domestic ducklings via JEV-infected mosquito bites to evaluate the pathogenicity of JEV in domestic ducklings. Specific pathogen-free domestic ducklings were infected at day 2 post-hatching with JEV-infected Culex pipiens mosquito bites and monitored for clinical responses. Among 20 ducklings exposed to JEV-infected mosquitoes, six showed mild and non-characteristic clinical signs starting at two days post-infection, then died suddenly with neurological signs of opisthotonos (a condition of spasm of the back muscles causing the head and limbs to bend backward and the trunk to arch forward) between two and three days post-infection. The mortality of the affected ducklings was 30% (6/20). Multifocal lymphohistiocytic perivascular cuffs and lymphohistiocytic meningitis were macroscopically observed in the affected duckling brains. JEV was detected in the cytoplasm of neuronal cells in the affected duckling brains by immunohistochemical assays and was recovered from the affected duckling brains by viral isolation. These observations indicated that JEV infection via mosquito bites causes mortality associated with viral encephalitis in newly hatched domestic ducklings, thus demonstrating the potential pathogenicity of JEV in domestic ducklings under natural conditions.
Curcumin, Curcumin Nanoparticles and Curcumin Nanospheres: A Review on Their Pharmacodynamics Based on Monogastric Farm Animal, Poultry and Fish Nutrition
Authors: Moniruzzaman Mohammad , Min Taesun
Published: May 2020

Nanotechnology is an emerging field of science that is widely used in medical sciences. However, it has limited uses in monogastric farm animal as well as fish and poultry nutrition. There are some works that have been done on curcumin and curcumin nanoparticles as pharmaceutics in animal nutrition. However, studies have shown that ingestion of curcumin or curcumin nanoparticles does not benefit the animal health much due to their lower bioavailability, which may result because of low absorption, quick metabolism and speedy elimination of curcumin from the animal body. For these reasons, advanced formulations of curcumin are needed. Curcumin nanospheres is a newly evolved field of nanobiotechnology which may have beneficial effects in terms of growth increment, anti-microbial, anti-inflammatory and neuroprotective effects on animal and fish health by means of nanosphere forms that are biodegradable and biocompatible. Thus, this review aims to highlight the potential application of curcumin, curcumin nanoparticles and curcumin nanospheres in the field of monogastric farm animal, poultry and fish nutrition. We do believe that the review provides the perceptual vision for the future development of curcumin, curcumin nanoparticles and curcumin nanospheres and their applications in monogastric farm animal, poultry and fish nutrition.
Construction of an Onion (Allium cepa L.) Genetic Linkage Map Using Genotyping-by-Sequencing Analysis with a Reference Gene Set and Identification of QTLs Controlling Anthocyanin Synthesis and Content
Authors: Choi Yousoo , Kim Sunggil , Lee Jundae
Published: May 2020

Anthocyanins, the pigmented flavonoids responsible for red and blue colors in horticultural products, promote human health by preventing cancers and lowering the risk of cardiovascular disease. Red onions contain several cyanidin- and peonidin-based anthocyanins. In this study, we constructed a single-nucleotide polymorphism (SNP)-based genetic linkage map in an F2 segregating population derived from a cross between the inbred line ‘SP3B’ (yellow bulb) and the doubled haploid line ‘H6′ (red bulb) to identify quantitative trait loci (QTLs) for total anthocyanin content of onion bulbs using a genotyping-by-sequencing (GBS) analysis based on a reference gene set. A total of 101.9 Gbp of raw sequences were generated using an Illumina HiSeq 2500 system and a total of 1625 SNP loci were identified with the criteria of three minimum depths, lower than 30% missing rate, and more than 5% minor allele frequency. As a result, an onion genetic linkage map consisting of 319 GBS-based SNP loci and 34 high-resolution melting (HRM) markers was constructed with eight linkage groups and a total genetic distance of 881.4 cM. In addition, the linkage groups were assigned to corresponding chromosomes by comparison with the reference genetic map OH1×5225 through marker development based on common transcripts. The analysis revealed one major QTL, qAS7.1, for anthocyanin synthesis and two significant QTLs, qAC4.1 and qAC4.2, for anthocyanin content. The QTL qAS7.1, located on chromosome 7 with a phenotypic variation of 87.61%, may be a dihydroflavonol 4-reductase (DFR) gene that determines whether the bulb color is red or yellow. The QTLs qAC4.1 and qAC4.2 are separately positioned on chromosome 4 with R2 values of 19.43% and 26.28%, respectively. This map and QTL information will contribute to marker development and breeding for high anthocyanin content in bulb onion.
Effect of Poly(vinyl alcohol) on Nanoencapsulation of Budesonide in Chitosan Nanoparticles via Ionic Gelation and Its Improved Bioavailability
Authors: Michailidou Georgia , Ainali Nina Maria , Xanthopoulou Eleftheria , Nanaki Stavroula , Kostoglou Margaritis , Koukaras Emmanuel N. , Bikiaris Dimitrios N.
Published: May 2020

Chitosan (CS) is a polymer extensively used in drug delivery formulations mainly due to its biocompatibility and low toxicity. In the present study, chitosan was used for nanoencapsulation of a budesonide (BUD) drug via the well-established ionic gelation technique and a slight modification of it, using also poly(vinyl alcohol) (PVA) as a surfactant. Scanning electron microscopy (SEM) micrographs revealed that spherical nanoparticles were successfully prepared with average sizes range between 363 and 543 nm, as were measured by dynamic light scattering (DLS), while zeta potential verified their positive charged surface. X-ray diffraction (XRD) patterns revealed that BUD was encapsulated in crystalline state in nanoparticles but with a lower degree of crystallinity than the neat drug, which was also proven by differential scanning calorimetry (DSC) and melting peak measurements. This could be attributed to interactions that take place between BUD and CS, which were revealed by FTIR and by an extended computational study. An in vitro release study of budesonide showed a slight enhancement in the BUD dissolution profile, compared to the neat drug. However, drug release was substantially increased by introducing PVA during the nanoencapsulation procedure, which is attributed to the higher amorphization of BUD on these nanoparticles. The release curves were analyzed using a diffusion model that allows estimation of BUD diffusivity in the nanoparticles.
Performance Comparison of Industrially Produced Formaldehyde Using Two Different Catalysts
Authors: Shakeel Kamran , Javaid Muqaddam , Muazzam Yusra , Naqvi Salman Raza , Taqvi Syed Ali Ammar , Uddin Fahim , Mehran Muhammad Taqi , Sikander Umair , Niazi M. Bilal Khan
Published: May 2020

Formaldehyde is an important industrial chemical that is a strong-smelling and colorless gas. It is used in a number of processes such as making household products and building materials, glues and adhesives, resins, certain insulation materials, etc. Formaldehyde can be produced industrially using air and methanol as raw materials in the presence of metal oxide catalyst or silver-based catalyst. The operating conditions and requirements of the process depend on the type of catalyst used. Therefore, a comparative study of both processes was conducted, and the results were compared. It was observed that the silver-based catalyst process has a compact plant size since the amount of air required is halved as compared to the metal oxide process. Thus, it appears that the silver-based catalyst process is more suitable for small-scale production due to its compact size and reduced utility cost.
Preliminary Testing of Ultrasound/Microwave-Assisted Extraction (U/M-AE) for the Isolation of Geraniin from Nephelium lappaceum L. (Mexican Variety) Peel
Authors: Hernández-Hernández Cristian , Aguilar Cristóbal Noé , Flores-Gallegos Adriana Carolina , Sepúlveda Leonardo , Rodríguez-Herrera Raúl , Morlett-Chávez Jesús , Govea-Salas Mayela , Ascacio-Valdés Juan
Published: May 2020

The rambutan peel (RP) is a relevant source of bioactive molecules, which could be used for application in cosmetics, food, and pharmaceutical areas. Total soluble polyphenol content was extracted from Mexican variety rambutan peels using an emergent ultrasound/microwave-assisted extraction (U/M-AE) technology. Five extractions were performed using different mass/volume and ethanol/water ratios; 1:16-0; 1:16-70; 1:8-0; 1:8-70; 1:12-30. Condition 1:16-0 was defined as the best extraction condition with 0% ethanol percentage (only water). The content of total soluble polyphenols was 307.57 mg/g. The total bound polyphenol content was 26.53 mg/g. Besides, two separation processes were made with the soluble fraction; the first one was performed using Amberlite XAD-16 (Sigma-Aldrich, Saint Louis, MO, USA), and seven polyphenolic compounds were obtained. The second one was performed using a preparative HPLC (Varian, Palo Alto, CA, USA) equipment obtained fraction where three compounds were obtained: geraniin (main compound), ellagic acid, and ellagic acid pentoside. The major compound isolated in the two separations was geraniin, according to HPLC/ESI/MS (High Performance Liquid Chromatography/ElectroSpray Ionization/Mass) analysis.
Scope and Limitations of Modelling, Simulation, and Optimisation of a Spiral Wound Reverse Osmosis Process-Based Water Desalination
Authors: Alsarayreh Alanood A. , Al-Obaidi Mudhar A. , Patel Raj , Mujtaba Iqbal M.
Published: May 2020

The reverse osmosis (RO) process is one of the best desalination methods, using membranes to reject several impurities from seawater and brackish water. To systematically perceive the transport phenomena of solvent and solutes via the membrane texture, several mathematical models have been developed. To date, a large number of simulation and optimisation studies have been achieved to gauge the influence of control variables on the performance indexes, to adjust the key variables at optimum values, and to realise the optimum production indexes. This paper delivers an intensive review of the successful models of the RO process and both simulation and optimisation studies carried out on the basis of the models developed. In general, this paper investigates the scope and limitations of the RO process, as well as proving the maturity of the associated perspective methodologies.
3D Point Cloud Analysis for Damage Detection on Hyperboloid Cooling Tower Shells
Authors: Makuch Maria , Gawronek Pelagia
Published: May 2020

The safe operation and maintenance of the appropriate strength of hyperboloid cooling towers require special supervision and a maintenance plan that takes into consideration the condition of the structure. With three series of terrestrial laser scanning data, the paper presents an automatic inspection system for reinforced concrete cooling tower shells that ensures detection and measurement of damage together with the verification of the quality and durability of surface repairs as required by industry standards. The proposed solution provides an automatic sequence of algorithm steps with low computational requirements. The novel method is based on the analysis of values of the local surface curvature determined for each point in the cloud using principal component analysis and transformed using the square root function. Data segmentation into cloud points representing a uniform shell and identified defects was carried out using the region growing algorithm. The extent of extracted defects was defined through vectorisation with a convex hull. The proposed diagnostics strategy of reinforced concrete hyperboloid cooling towers was drafted and validated using an object currently under repair but in continuous service for fifty years. The results of detection and measurement of defects and verification of surface continuity at repaired sites were compared with traditional diagnostics results. It was shown that the sequence of algorithm steps successfully identified all cavities, scaling, and blisters in the shell recorded in the expert report (recognition rate—100%). Cartometric vectorisation of defects determined the scope of necessary shell repairs offering higher performance and detail level than direct contact measurement from suspended platforms. Analysis of local geometric features of repaired surfaces provided a reliable baseline for the evaluation of the repairs aimed at restoring the protective properties of the concrete surround, desirable especially in the warranty period.
Satellite-Observed Soil Moisture as an Indicator of Wildfire Risk
Authors: Thomas Ambadan Jaison , Oja Matilda , Gedalof Ze’ev , Berg Aaron A.
Published: May 2020

Wildfires are a concerning issue in Canada due to their immediate impact on people’s lives, local economy, climate, and environment. Studies have shown that the number of wildfires and affected areas in Canada has increased during recent decades and is a result of a warming and drying climate. Therefore, identifying potential wildfire risk areas is increasingly an important aspect of wildfire management. The purpose of this study is to investigate if remotely sensed soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) satellite can be used to identify potential wildfire risk areas for better wildfire management. We used the National Fire Database (NFDB) fire points and polygons to group the wildfires according to ecozone classifications, as well as to analyze the SMOS soil moisture data over the wildfire areas, between 2010–2017, across fourteen ecozones in Canada. Timeseries of 3-day, 5-day, and 7-day soil moisture anomalies prior to the onset of each wildfire occurrence were examined over the ecozones individually. Overall, the results suggest, despite the coarse-resolution, SMOS soil moisture products are potentially useful in identifying soil moisture anomalies where wildfire hot-spots may occur.
Characterization of the Uniformity of High-Flux CdZnTe Material
Authors: Veale Matthew Charles , Booker Paul , Cross Simon , Hart Matthew David , Jowitt Lydia , Lipp John , Schneider Andreas , Seller Paul , Wheater Rhian Mair , Wilson Matthew David , Hansson Conny Christoffer Tobias , Iniewski Krzysztof , Marthandam Pramodha , Prekas Georgios
Published: May 2020

Since the late 2000s, the availability of high-quality cadmium zinc telluride (CdZnTe) has greatly increased. The excellent spectroscopic performance of this material has enabled the development of detectors with volumes exceeding 1 cm3 for use in the detection of nuclear materials. CdZnTe is also of great interest to the photon science community for applications in X-ray imaging cameras at synchrotron light sources and free electron lasers. Historically, spatial variations in the crystal properties and temporal instabilities under high-intensity irradiation has limited the use of CdZnTe detectors in these applications. Recently, Redlen Technologies have developed high-flux-capable CdZnTe material (HF-CdZnTe), which promises improved spatial and temporal stability. In this paper, the results of the characterization of 10 HF-CdZnTe detectors with dimensions of 20.35 mm × 20.45 mm × 2.00 mm are presented. Each sensor has 80 × 80 pixels on a 250-μm pitch and were flip-chip-bonded to the STFC HEXITEC ASIC. These devices show excellent spectroscopic performance at room temperature, with an average Full Width at Half Maximum (FWHM) of 0.83 keV measured at 59.54 keV. The effect of tellurium inclusions in these devices was found to be negligible; however, some detectors did show significant concentrations of scratches and dislocation walls. An investigation of the detector stability over 12 h of continuous operation showed negligible changes in performance.
Feasibility of a Sensor-Based Technological Platform in Assessing Gait and Sleep of In-Hospital Stroke and Incomplete Spinal Cord Injury (iSCI) Patients
Authors: Hendriks Maartje M. S. , Vos-van der Hulst Marije , Keijsers Noel L. W.
Published: May 2020

Recovery of the walking function is one of the most common rehabilitation goals of neurological patients. Sufficient and adequate sleep is a prerequisite for recovery or training. To objectively monitor patients’ progress, a combination of different sensors measuring continuously over time is needed. A sensor-based technological platform offers possibilities to monitor gait and sleep. Implementation in clinical practice is of utmost relevance and has scarcely been studied. Therefore, this study examined the feasibility of a sensor-based technological platform within the clinical setting. Participants (12 incomplete spinal cord injury (iSCI), 13 stroke) were asked to wear inertial measurement units (IMUs) around the ankles during daytime and the bed sensor was placed under their mattress for one week. Feasibility was established based on missing data, error cause, and user experience. Percentage of missing measurement days and nights was 14% and 4%, respectively. Main cause of lost measurement days was related to missing IMU sensor data. Participants were not impeded, did not experience any discomfort, and found the sensors easy to use. The sensor-based technological platform is feasible to use within the clinical rehabilitation setting for continuously monitoring gait and sleep of iSCI and stroke patients.
Vulnerability Assessment of Buildings due to Land Subsidence Using InSAR Data in the Ancient Historical City of Pistoia (Italy)
Authors: Ezquerro Pablo , Del Soldato Matteo , Solari Lorenzo , Tomás Roberto , Raspini Federico , Ceccatelli Mattia , Fernández-Merodo José , Casagli Nicola , Herrera Gerardo
Published: May 2020

The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the processing of large C-B and radar images can be used to highlight temporal and spatial deformation anomalies, and their detailed analysis and postprocessing to generate operative products for final users. In this work, the wide-area mapping capability of Sentinel-1 was used in synergy with the COSMO-SkyMed high resolution SAR data to characterize ground subsidence affecting the urban fabric of the city of Pistoia (Tuscany Region, central Italy). Line of sight velocities were decomposed on vertical and E–W components, observing slight horizontal movements towards the center of the subsidence area. Vertical displacements and damage field surveys allowed for the calculation of the probability of damage depending on the displacement velocity by means of fragility curves. Finally, these data were translated to damage probability and potential loss maps. These products are useful for urban planning and geohazard management, focusing on the identification of the most hazardous areas on which to concentrate efforts and resources.
Performance Optimization of FD-SOI Hall Sensors Via 3D TCAD Simulations
Authors: Fan Linjie , Bi Jinshun , Xi Kai , Majumdar Sandip , Li Bo
Published: May 2020

This work investigates the behavior of fully depleted silicon-on-insulator (FD-SOI) Hall sensors with an emphasis on their physical parameters, namely the aspect ratio, doping concentration, and thicknesses. Via 3D-technology computer aided design (TCAD) simulations with a galvanomagnetic transport model, the performances of the Hall voltage, sensitivity, efficiency, offset voltage, and temperature characteristics are evaluated. The optimal structure of the sensor in the simulation has a sensitivity of 86.5 mV/T and an efficiency of 218.9 V/WT at the bias voltage of 5 V. In addition, the effects of bias, such as the gate voltage and substrate voltage, on performance are also simulated and analyzed. Optimal structure and bias design rules are proposed, as are some adjustable trade-offs that can be chosen by designers to meet their own Hall sensor requirements.
From Sensor to Cloud: An IoT Network of Radon Outdoor Probes to Monitor Active Volcanoes
Authors: Terray Luca , Royer Laurent , Sarramia David , Achard Cyrille , Bourdeau Etienne , Chardon Patrick , Claude Alexandre , Fuchet Jérôme , Gauthier Pierre-Jean , Grimbichler David , Mezhoud Jérémy , Ogereau Francis , Vandaële Richard , Breton Vincent
Published: May 2020

While radon in soil gases has been identified for decades as a potential precursor of volcanic eruptions, there has been a recent interest for monitoring radon in air on active volcanoes. We present here the first network of outdoor air radon sensors that was installed successfully on Mt. Etna volcano, Sicily, Italy in September 2019. Small radon sensors designed for workers and home dosimetry were tropicalized in order to be operated continuously in harsh volcanic conditions with an autonomy of several months. Two stations have been installed on the south flank of the volcano at ~3000 m of elevation. A private network has been deployed in order to transfer the measurements from the stations directly to a server located in France, using a low-power wide-area transmission technology from Internet of Things (IoT) called LoRaWAN. Data finally feed a data lake, allowing flexibility in data management and sharing. A first analysis of the radon datasets confirms previous observations, while adding temporal information never accessed before. The observed performances confirm IoT solutions are very adapted to active volcano monitoring in terms of range, autonomy, and data loss.
Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data Classification
Authors: Vanarse Anup , Espinosa-Ramos Josafath Israel , Osseiran Adam , Rassau Alexander , Kasabov Nikola
Published: May 2020

Existing methods in neuromorphic olfaction mainly focus on implementing the data transformation based on the neurobiological architecture of the olfactory pathway. While the transformation is pivotal for the sparse spike-based representation of odor data, classification techniques based on the bio-computations of the higher brain areas, which process the spiking data for identification of odor, remain largely unexplored. This paper argues that brain-inspired spiking neural networks constitute a promising approach for the next generation of machine intelligence for odor data processing. Inspired by principles of brain information processing, here we propose the first spiking neural network method and associated deep machine learning system for classification of odor data. The paper demonstrates that the proposed approach has several advantages when compared to the current state-of-the-art methods. Based on results obtained using a benchmark dataset, the model achieved a high classification accuracy for a large number of odors and has the capacity for incremental learning on new data. The paper explores different spike encoding algorithms and finds that the most suitable for the task is the step-wise encoding function. Further directions in the brain-inspired study of odor machine classification include investigation of more biologically plausible algorithms for mapping, learning, and interpretation of odor data along with the realization of these algorithms on some highly parallel and low power consuming neuromorphic hardware devices for real-world applications.
Recognition of Rare Low-Moral Actions Using Depth Data
Authors: Du Kanghui , Kaczmarek Thomas , Brščić Dražen , Kanda Takayuki
Published: May 2020

Detecting and recognizing low-moral actions in public spaces is important. But low-moral actions are rare, so in order to learn to recognize a new low-moral action in general we need to rely on a limited number of samples. In order to study the recognition of actions from a comparatively small dataset, in this work we introduced a new dataset of human actions consisting in large part of low-moral behaviors. In addition, we used this dataset to test the performance of a number of classifiers, which used either depth data or extracted skeletons. The results show that both depth data and skeleton based classifiers were able to achieve similar classification accuracy on this dataset (Top-1: around 55%, Top-5: around 90%). Also, using transfer learning in both cases improved the performance.
Drivers’ Visual Perception Quantification Using 3D Mobile Sensor Data for Road Safety
Authors: Choi Kanghee , Byun Giyoung , Kim Ayoung , Kim Youngchul
Published: May 2020

To prevent driver accidents in cities, local governments have established policies to limit city speeds and create child protection zones near schools. However, if the same policy is applied throughout a city, it can be difficult to obtain smooth traffic flows. A driver generally obtains visual information while driving, and this information is directly related to traffic safety. In this study, we propose a novel geometric visual model to measure drivers’ visual perception and analyze the corresponding information using the line-of-sight method. Three-dimensional point cloud data are used to analyze on-site three-dimensional elements in a city, such as roadside trees and overpasses, which are normally neglected in urban spatial analyses. To investigate drivers’ visual perceptions of roads, we have developed an analytic model of three types of visual perception. By using this proposed method, this study creates a risk-level map according to the driver’s visual perception degree in Pangyo, South Korea. With the point cloud data from Pangyo, it is possible to analyze actual urban forms such as roadside trees, building shapes, and overpasses that are normally excluded from spatial analyses that use a reconstructed virtual space.
An Improved Pulse-Coupled Neural Network Model for Pansharpening
Authors: Li Xiaojun , Yan Haowen , Xie Weiying , Kang Lu , Tian Yi
Published: May 2020

Pulse-coupled neural network (PCNN) and its modified models are suitable for dealing with multi-focus and medical image fusion tasks. Unfortunately, PCNNs are difficult to directly apply to multispectral image fusion, especially when the spectral fidelity is considered. A key problem is that most fusion methods using PCNNs usually focus on the selection mechanism either in the space domain or in the transform domain, rather than a details injection mechanism, which is of utmost importance in multispectral image fusion. Thus, a novel pansharpening PCNN model for multispectral image fusion is proposed. The new model is designed to acquire the spectral fidelity in terms of human visual perception for the fusion tasks. The experimental results, examined by different kinds of datasets, show the suitability of the proposed model for pansharpening.
Integrated Circuit Design for Radiation-Hardened Charge-Sensitive Amplifier Survived up to 2 Mrad
Authors: Lee Changyeop , Cho Gyuseong , Unruh Troy , Hur Seop , Kwon Inyong
Published: May 2020

According to the continuous development of metal-oxide semiconductor (MOS) fabrication technology, transistors have naturally become more radiation-tolerant through steadily decreasing gate-oxide thickness, increasing the tunneling probability between gate-oxide and channel. Unfortunately, despite this radiation-hardened property of developed transistors, the field of nuclear power plants (NPPs) requires even higher radiation hardness levels. Particularly, total ionizing dose (TID) of approximately 1 Mrad could be required for readout circuitry under severe accident conditions with 100 Mrad around a reactor in-core required. In harsh radiating environments such as NPPs, sensors such as micro-pocket-fission detectors (MPFD) would be a promising technology to be operated for detecting neutrons in reactor cores. For those sensors, readout circuits should be fundamentally placed close to sensing devices for minimizing signal interferences and white noise. Therefore, radiation hardening ability is necessary for the circuits under high radiation environments. This paper presents various integrated circuit designs for a radiation hardened charge-sensitive amplifier (CSA) by using SiGe 130 nm and Si 180 nm fabrication processes with different channel widths and transistor types of complementary metal-oxide-semiconductor (CMOS) and bipolar CMOS (BiCMOS). These circuits were tested under γ–ray environment with Cobalt-60 of high level activity: 490 kCi. The experiment results indicate amplitude degradation of 2.85%–34.3%, fall time increase of 201–1730 ns, as well as a signal-to-noise ratio (SNR) of 0.07–11.6 dB decrease with irradiation dose increase. These results can provide design guidelines for radiation hardening operational amplifiers in terms of transistor sizes and structures.
A Paper-Based Device for Ultrasensitive, Colorimetric Phosphate Detection in Seawater
Authors: Racicot Joan M. , Mako Teresa L. , Olivelli Alexander , Levine Mindy
Published: May 2020

High concentrations of certain nutrients, including phosphate, are known to lead to undesired algal growth and low dissolved oxygen levels, creating deadly conditions for organisms in marine ecosystems. The rapid and robust detection of these nutrients using a colorimetric, paper-based system that can be applied on-site is of high interest to individuals monitoring marine environments and others affected by marine ecosystem health. Several techniques for detecting phosphate have been reported previously, yet these techniques often suffer from high detection limits, reagent instability, and the need of the user to handle toxic reagents. In order to develop improved phosphate detection methods, the commonly used molybdenum blue reagents were incorporated into a paper-based, colorimetric detection system. This system benefited from improved stabilization of the molybdenum blue reagent as well as minimal user contact with toxic reagents. The colorimetric readout from the paper-based devices was analyzed and quantified using RGB analyses (via ImageJ), and resulted in the detection of phosphate at detection limits between 1.3 and 2.8 ppm in various aqueous media, including real seawater.
Holding Complexity: Lessons from Team-Teaching an Interdisciplinary Collegiate Course on Urban Sustainability
Authors: Keeley Melissa , Benton-Short Lisa
Published: May 2020

Lead instructors discuss the structure, opportunities, and pedagogical challenges of an interdisciplinary team-taught course on urban sustainability involving seven professors from six departments across four of George Washington University’s schools over five years. The teaching team prioritized presenting and exploring diverse perspectives on urban sustainability, seeing a key learning objective of this course in students (1) learning to make links between disciplines; (2) having opportunities to reflect, disagree, share, and develop their own perspectives; and (3) developing a life-long engagement and openness with ideas and learning. This is challenging for many students. To promote student learning and engagement in the class, we utilize active-learning and cooperative discussion techniques, and see these as times that the class reaches “interdisciplinarity”. We employ place-based pedagogical approaches, focusing the class on the case-study (and students’ adopted hometown) of Washington D.C., finding that a “layering” of perspectives on a single city helps students see disciplinary similarities and differences more clearly. For those considering a large-team interdisciplinary course, we stress the importance of a lead instructor for coordination—both conceptually and administratively—and adequate institutional support for this unique and challenging endeavor.
Engineering Education for Sustainable Development: Evaluation Criteria for Brazilian Context
Authors: Rampasso Izabela Simon , Quelhas Osvaldo L. G. , Anholon Rosley , Pereira Marcio B. , Miranda Jocimar D. A. , Alvarenga Wenderson S.
Published: May 2020

Considering the increasing importance of sustainability in future professionals’ education and the role played by engineers in society, this paper aims to analyze the key criteria that should be considered in models to evaluate the insertion level of sustainability into engineering education, considering the Brazilian context. For this, criteria reported in the literature were collected and evaluated by engineering professors. The respondents were asked to classify the criteria as “essential”, “useful, but not essential”, or “not necessary”. Data collected were analyzed through Lawshe’s method. From 15 criteria collected from the literature, 5 were not considered essential to evaluate engineering education for sustainable development (EESD), according to data analysis: C2 (establishment of global partnerships), C4 (encouraging students to volunteer through extracurricular activities), C9 (use of active learning approaches to problem solving to teach aspects related to sustainability), C10 (use of service-learning towards the local community for educational purposes) and C15 (use of sustainability concept in university installations). It was possible to verify that most of these criteria (C2, C4, C10, and C15) were not directly related to engineering curricula, being parallel activities. Regarding C9, active learning approaches can enhance attributes important for students in the context of sustainable development, but they are not goals of EESD. This research contributes to the development of evaluation models for engineering education in the Brazilian context and its findings can also be useful for studies in other countries. No similar study was found in the literature.
Relationship between Emotional Intelligence, Generativity and Self-Efficacy in Secondary School Teachers
Authors: Aparisi David , Granados Lucía , Sanmartín Ricardo , Martínez-Monteagudo María Carmen , García-Fernández José Manuel
Published: May 2020

The aim of this study was to examine the relationship between emotional intelligence (EI), generativity and self-efficacy, identifying different profiles of emotional intelligence. 834 secondary school teachers participated in the study by completing the Trait Meta-Mood Scale–24 (TMMS–24), the Loyola Generativity Scale and the General Self-Efficacy Scale. Cluster analysis identified four EI profiles: the first with high scores in attention and low scores in repair, the second with high scores in all dimensions of EI, the third with low scores in all EI dimensions and a fourth profile with low scores in attention and high scores in repair. Results showed significant statistical differences between the EI profiles found and the different dimensions of generativity and self-efficacy. Logistic regression analysis showed that EI was a statistically significant predictor of generativity, since teachers with high EI scores were more likely to present high scores in positive generativity and self-efficacy and lower probability of presenting high scores in generative doubts.
High-Tech Urban Agriculture in Amsterdam: An Actor Network Analysis
Authors: H. Farhangi Mohsen , Turvani Margherita E. , van der Valk Arnold , Carsjens Gerrit J.
Published: May 2020

The agriculture and horticulture sector in the Netherlands is one of the most productive in the world. Although the sector is one of the most advanced and intense agricultural production systems worldwide, it faces challenges, such as climate change and environmental and social unsustainability of industrial production. To overcome these challenges, alternative food production initiatives have emerged, especially in large cities such as Amsterdam. Some initiatives involve producing food in the urban environment, supported by new technologies and practices, so-called high-tech urban agriculture (HTUA). These initiatives make cultivation of plants inside and on top of buildings possible and increase green spaces in urban areas. The emerging agricultural technologies are creating new business environments that are shape d by technology developers (e.g., suppliers of horticultural light emitting diodes (LED) and control environment systems) and developers of alternative food production practices (e.g., HTUA start-ups). However, research shows that the uptake of these technological innovations in urban planning processes is problematic. Therefore, this research analyzes the barriers that local government planners and HTUA developers are facing in the embedding of HTUA in urban planning processes, using the city of Amsterdam as a case study. This study draws on actor-network theory (ANT) to analyze the interactions between planners, technologies, technology developers and developers of alternative food production practices. Several concepts of ANT are integrated into a multi-level perspective on sustainability transitions (MLP) to create a new theoretical framework that can explain how interactions between technologies and planning actors transform the incumbent social–technical regime. The configuration of interactions between social and material entities in technology development and adoption processes in Amsterdam is analyzed through the lens of this theoretical framework. The data in this study were gathered by tracing actors and their connections by using ethnographic research methods. In the course of the integration of new technologies into urban planning practices, gaps between technologies, technology developers, and planning actors have been identified. The results of this study show a lacking connection between planning actors and technology developers, although planning actors do interact with developers of alternative food production practices. These interactions are influenced by agency of artefacts such as visualizations of the future projects. The paper concludes that for the utilization of emerging technologies for sustainability transition of cities, the existing gap between technology developers and planning actors needs to be bridged through the integration of technology development visions in urban agendas and planning processes.
Physical Vulnerability and Local Responses to Flood Damage in Peri-Urban Areas of Dhaka, Bangladesh
Authors: Fatemi Md. Nawrose , Okyere Seth Asare , Diko Stephen Kofi , Kita Michihiro , Shimoda Motoki , Matsubara Shigeki
Published: May 2020

In Eastern Dhaka, perennial flood remains a constant threat to people and livelihoods. Learning from the micro-level experiences of the poor in the peri-urban areas of Dhaka provides insights on the intersections between physical vulnerability, flood response strategies, and adaptive capacity. Through a convergent mixed method, this study examines the physical vulnerability of residential buildings, flood damages, and local physical responses in three neighborhoods of Eastern Dhaka. Results show that the level of damage to buildings is the most important predictor of physical vulnerability to floods. Buildings that are older than 20 years old and built with natural materials are likely to experience high flood damages compared to buildings that are less than 10 years and constructed with durable materials. The study concludes that in addition to socio-economic interventions, a targeted and people-centered flood management regime that pays attention to age, material composition, and structural quality of houses is necessary to build residents’ adaptive capacities and long-term resilience to flooding. This study contributes to the emerging work on grassroots responses to flood vulnerabilities with practical insights for urban planners and disaster management professionals on particular interventions needed to improve the performance of local responses to flood risks and vulnerabilities.
An IoT-based Sharing Plant Factory System for Nature Connectedness Improvement in Built Environment
Authors: Tong Xueting , Wu Zhanwei
Published: May 2020

Under the influence of urbanization, the relationship between human and nature gradually separated, therefore it is difficult for people to obtain the benefits of nature connectedness. In this paper, an IoT-based sharing plant factory is described to improve nature connectedness of people in an indoor environment. The ecological service process of indoor environments is studied through user interviews and surveys, to understand the contact points of ecological services and the design points of sharing plant factories. Based on these points, a product prototype is realized. Finally, the nature connectedness is tested by 13 users comparing the sharing plant factory with traditional plant pots through the revised Inclusion of Nature in the Self and Connectedness to Nature Scale. The results prove that the designed sharing plant factory can effectively improve a user’s nature connectedness. In addition, the efficiency of plant maintenance is greatly improved with the help of a sharing plant factory. The introduction of nature connectedness into ecological design can guide design to pay more attention to the service effect of products. In addition, the introduction of plant factory technology indoors can help ecological service products to function better and provide new ideas for the research of indoor ecological service products.
Ambidextrous Knowledge and Learning Capability: The Magic Potion for Employee Creativity and Sustainable Innovation Performance
Authors: Muñoz-Pascual Lucía , Galende Jesús
Published: May 2020

This paper studies the effect that ambidextrous knowledge, i.e., oriented knowledge within a firm towards the development of exploitation activities and oriented knowledge towards the development of exploration activities, has on employee creativity, research and development, and sustainable product innovation. We contend that both tacit and explicit knowledge affect employee creativity, research and development, and sustainable product innovation. We empirically tested our hypotheses by using multisource data collected from 245 Spanish firms across fourteen industries. Our structural equation models indicate that these two types of individual knowledge predict employee creativity, which in turn strengthens research and development projects, and sustainable product innovation performance. The results confirm that the relationships between knowledge, creativity, research and development, and sustainable product innovation performance are strong with a high learning capability. A multi-group structural analysis also reveals that positive relations between tacit and explicit knowledge, employee creativity, research and development, and sustainable product innovation performance are stronger within firms that have employees with high learning capability. We provide pertinent recommendations for managers. The efforts and investments made in knowledge support the development of new ideas, new research and development projects, and sustainable product innovation success; employee learning capability has a strong influence on knowledge, creativity, and sustainable product innovation.