bluuebunny/crossref_metadata_2025 huggingface dataset:
Pathological, Morphological, Cytogenomic, Biochemical and Molecular Data Support the Distinction between Colletotrichum cigarro comb. et stat. nov. and Colletotrichum kahawae
Authors: Cabral Ana , Azinheira Helena G. , Talhinhas Pedro , Batista Dora , Ramos Ana Paula , Silva Maria do Céu , Oliveira Helena , Várzea Vítor
Published: April 2020

The genus Colletotrichum has witnessed tremendous variations over the years in the number of species recognized, ranging from 11 to several hundreds. Host-specific fungal species, once the rule, are now the exception, with polyphagous behavior regarded as normal in this genus. The species Colletotrichum kahawae was created to accommodate the pathogens that have the unique ability to infect green developing coffee berries causing the devastating Coffee Berry Disease in Africa, but its close phylogenetic relationship to a polyphagous group of fungi in the C. gloeosporioides species complex led some researchers to regard these pathogens as members of a wider species. In this work we combine pathological, morphological, cytogenomic, biochemical, and molecular data of a comprehensive set of phylogenetically-related isolates to show that the Coffee Berry Disease pathogen forms a separate species, C. kahawae, and also to assign the closely related fungi, previously in C. kahawae subsp. cigarro, to a new species, C. cigarro comb. et stat. nov. This taxonomic clarification provides an opportunity to link phylogeny and functional biology, and additionally enables a much-needed tool for plant pathology and agronomy, associating exclusively C. kahawae to the Coffee Berry Disease pathogen.
Physical Dormancy Release in Medicago truncatula Seeds Is Related to Environmental Variations
Authors: Renzi Juan Pablo , Duchoslav Martin , Brus Jan , Hradilová Iveta , Pechanec Vilém , Václavek Tadeáš , Machalová Jitka , Hron Karel , Verdier Jerome , Smýkal Petr
Published: April 2020

Seed dormancy and timing of its release is an important developmental transition determining the survival of individuals, populations, and species in variable environments. Medicago truncatula was used as a model to study physical seed dormancy at the ecological and genetics level. The effect of alternating temperatures, as one of the causes releasing physical seed dormancy, was tested in 178 M. truncatula accessions over three years. Several coefficients of dormancy release were related to environmental variables. Dormancy varied greatly (4–100%) across accessions as well as year of experiment. We observed overall higher physical dormancy release under more alternating temperatures (35/15 °C) in comparison with less alternating ones (25/15 °C). Accessions from more arid climates released dormancy under higher experimental temperature alternations more than accessions originating from less arid environments. The plasticity of physical dormancy can probably distribute the germination through the year and act as a bet-hedging strategy in arid environments. On the other hand, a slight increase in physical dormancy was observed in accessions from environments with higher among-season temperature variation. Genome-wide association analysis identified 136 candidate genes related to secondary metabolite synthesis, hormone regulation, and modification of the cell wall. The activity of these genes might mediate seed coat permeability and, ultimately, imbibition and germination.
The Plasma Membrane—An Integrating Compartment for Mechano-Signaling
Authors: Ackermann Frank , Stanislas Thomas
Published: April 2020

Plants are able to sense their mechanical environment. This mechanical signal is used by the plant to determine its phenotypic features. This is true also at a smaller scale. Morphogenesis, both at the cell and tissue level, involves mechanical signals that influence specific patterns of gene expression and trigger signaling pathways. How a mechanical stress is perceived and how this signal is transduced into the cell remains a challenging question in the plant community. Among the structural components of plant cells, the plasma membrane has received very little attention. Yet, its position at the interface between the cell wall and the interior of the cell makes it a key factor at the nexus between biochemical and mechanical cues. So far, most of the key players that are described to perceive and maintain mechanical cell status and to respond to a mechanical stress are localized at or close to the plasma membrane. In this review, we will focus on the importance of the plasma membrane in mechano-sensing and try to illustrate how the composition of this dynamic compartment is involved in the regulatory processes of a cell to respond to mechanical stress.
Efficient Micropropagation Protocol for the Conservation of the Endangered Aloe peglerae, an Ornamental and Medicinal Species
Authors: Hlatshwayo Nontobeko A. , Amoo Stephen O. , Olowoyo Joshua O. , Doležal Karel
Published: April 2020

A number of Aloe species are facing an extremely high risk of extinction due to habitat loss and over-exploitation for medicinal and ornamental trade. The last global assessment of Aloe peglerae Schönland (in 2003) ranked its global conservation status as ‘endangered’ with a decreasing population trend. In the National Red List of South African Plants, the extremely rapid decline of this species has resulted in its conservation status being elevated from ‘endangered’ to ‘critically endangered’ based on recent or new field information. This dramatic decline necessitates the development of a simple, rapid and efficient micropropagation protocol as a conservation measure. An in vitro propagation protocol was therefore established with the regeneration of 12 shoots per shoot-tip explant within 8 weeks using Murashige and Skoog (MS) medium supplemented with 2.5 µM meta-topolin riboside (an aromatic cytokinin). The rooting of the shoots with a 100% frequency on half-strength MS medium without any plant growth resulted in additional six shoots produced per cultured shoot. The resultant plantlets were successfully acclimatized with a 100% survival frequency after 6 weeks. Overall, the developed protocol can result in the production of 3906 transplantable shoots that are ready for rooting per annum from a single shoot-tip explant. It is simple and efficient for seedling production in the ex situ cultivation and conservation of the endangered A. peglerae.
Natural and Synthetic Polymers for Bone Scaffolds Optimization
Authors: Donnaloja Francesca , Jacchetti Emanuela , Soncini Monica , Raimondi Manuela T.
Published: April 2020

Bone tissue is the structural component of the body, which allows locomotion, protects vital internal organs, and provides the maintenance of mineral homeostasis. Several bone-related pathologies generate critical-size bone defects that our organism is not able to heal spontaneously and require a therapeutic action. Conventional therapies span from pharmacological to interventional methodologies, all of them characterized by several drawbacks. To circumvent these effects, tissue engineering and regenerative medicine are innovative and promising approaches that exploit the capability of bone progenitors, especially mesenchymal stem cells, to differentiate into functional bone cells. So far, several materials have been tested in order to guarantee the specific requirements for bone tissue regeneration, ranging from the material biocompatibility to the ideal 3D bone-like architectural structure. In this review, we analyse the state-of-the-art of the most widespread polymeric scaffold materials and their application in in vitro and in vivo models, in order to evaluate their usability in the field of bone tissue engineering. Here, we will present several adopted strategies in scaffold production, from the different combination of materials, to chemical factor inclusion, embedding of cells, and manufacturing technology improvement.
Co-Microencapsulation of Anthocyanins from Cornelian Cherry Fruits and Lactic Acid Bacteria in Biopolymeric Matrices by Freeze-Drying: Evidences on Functional Properties and Applications in Food
Authors: Enache Iuliana Maria , Vasile Aida Mihaela , Enachi Elena , Barbu Vasilica , Stănciuc Nicoleta , Vizireanu Camelia
Published: April 2020

Cornus mas was used in this study as a rich source of health-promoting bioactives. The cornelian cherries were used to extract the polyphenols and anthocyanins. The chromatographic profile of the Cornus mas fruit extract revealed the presence of several anthocyanins, mainly delphinidin, cyanidin and pelargonidin glycosides. The extract was co-microencapsulated with Lactobacillus casei ssp. paracasei in a unique combination of whey protein isolates, inulin and chitosan by freeze-drying, with an encapsulation efficiency of 89.16 ± 1.23% for anthocyanins and 80.33 ± 0.44% for lactic acid bacteria. The pink-red colored powder showed a total anthocyanins content of 19.86 ± 1.18 mg cyanidin-3-glucoside/g dry weight (DW), yielding an antioxidant activity of 54.43 ± 0.73 mMol Trolox/g DW. The viable cells were 9.39 × 109 colony forming units (CFU)/g DW. The confocal microscopy analysis revealed the microencapsulated powder as a complex one, with several large formations containing smaller aggregates, consisting of the lactic acid bacteria cells, the cornelian cherries’ bioactive compounds and the biopolymers. The powder was tested for stability over 90 days, showing a decrease of 50% in anthocyanins and 37% in flavonoids content, with no significant changes in antioxidant activity and CFU. The powder showed a significant inhibitory effect against the α-amylase of 89.72 ± 1.35% and of 24.13 ± 0.01% for α-glucosidase. In vitro digestibility studies showed a significant release of anthocyanins in gastric juice, followed by a decrease in intestinal simulated conditions. The functional properties of the powder were tested by addition into a yogurt, highlighting a higher and more stable antioxidant activity at storage when compared to the control.
Dissipative Particle Dynamics Modeling of Polyelectrolyte Membrane–Water Interfaces
Authors: Sengupta Soumyadipta , Lyulin Alexey
Published: April 2020

Previous experiments of water vapor penetration into polyelectrolyte membrane (PEM) thin films have indicated the influence of the water concentration gradient and polymer chemistry on the interface evolution, which will eventually affect the efficiency of the fuel cell operation. Moreover, PEMs of different side chains have shown differences in water cluster structure and diffusion. The evolution of the interface between water and polyelectrolyte membranes (PEMs), which are used in fuel cells and flow batteries, of three different side-chain lengths has been studied using dissipative particle dynamics (DPD) simulations. Higher and faster water uptake is usually beneficial in the operation of fuel cells and flow batteries. The simulated water uptake increased with the increasing side chain length. In addition, the water uptake was rapid initially and slowed down afterwards, which is in agreement with the experimental observations. The water cluster formation rate was also found to increase with the increasing side-chain length, whereas the water cluster shapes were unaffected. Water diffusion in the membranes, which affects proton mobility in the PEMs, increased with the side-chain length at all distances from the interface. In conclusion, side-chain length was found to have a strong influence on the interface water structure and water penetration rates, which can be harnessed for the better design of PEMs. Since the PEM can undergo cycles of dehydration and rehydration, faster water uptake increases the efficiency of these devices. We show that the longer side chains with backbone structure similar to Nafion should be more suitable for fuel cell/flow battery usage.
Electrospinning of Essential Oils
Authors: Mele Elisa
Published: April 2020

The extensive and sometimes unregulated use of synthetic chemicals, such as drugs, preservatives, and pesticides, is posing big threats to global health, the environment, and food security. This has stimulated the research of new strategies to deal with bacterial infections in animals and humans and to eradicate pests. Plant extracts, particularly essential oils, have recently emerged as valid alternatives to synthetic drugs, due to their properties which include antibacterial, antifungal, anti-inflammatory, antioxidant, and insecticidal activity. This review discusses the current research on the use of electrospinning to encapsulate essential oils into polymeric nanofibres and achieve controlled release of these bioactive compounds, while protecting them from degradation. The works here analysed demonstrate that the electrospinning process is an effective strategy to preserve the properties of essential oils and create bioactive membranes for biomedical, pharmaceutical, and food packaging applications.
Synergistic Effects of Hybrid Carbonaceous Fillers of Carbon Fibers and Reduced Graphene Oxides on Enhanced Heat-Dissipation Capability of Polymer Composites
Authors: Lee Yun Seon , Yu Jaesang , Shim Sang Eun , Yang Cheol-Min
Published: April 2020

In this study, we investigated the synergistic effects of thermally conductive hybrid carbonaceous fillers of mesophase pitch-based carbon fibers (MPCFs) and reduced graphene oxides (rGOs) on the thermal conductivity of polymer matrix composites. Micro-sized MPCFs with different lengths (50 μm, 200 μm, and 6 mm) and nano-sized rGOs were used as the thermally conductive fillers used for the preparation of the heat-dissipation polymer composites. For all MPCF fillers with a different length, the thermal conductivity values of the MPCF/epoxy composites were proportional to the MPCF length and loading amount (0–50 wt%) of MPCFs. For an MPCF:rGO weight ratio of 49:1 (total loading amount of 50 wt%), the thermal conductivity values of MPCF-rGO/epoxy composites loaded with MPCFs of 50 μm, 200 μm, and 6 mm increased from 5.56 to 7.98 W/mK (approximately 44% increase), from 7.36 to 9.80 W/mK (approximately 33% increase), and from 11.53 to 12.58 W/mK (approximately 9% increase) compared to the MPCF/epoxy composites, respectively, indicating the synergistic effect on the thermal conductivity enhancement. The rGOs in the MPCF-rGO/epoxy composites acted as thermal bridges between neighboring MPCFs, resulting in the formation of effective heat transfer pathways. In contrast, the MPCF-rGO/epoxy composites with MPCF:rGO weight ratios of 48:2 and 47:3 decreased the synergistic effect more significantly compared to rGO content of 1 wt%, which is associated with the agglomeration of rGO nanoparticles. The synergistic effect was inversely proportional to the MPCF length. A theoretical approach, the modified Mori-Tanaka model, was used to estimate the thermal conductivity values of the MPCF-rGO/epoxy composites, which were in agreement with the experimentally measured values for MPCF-rGO/epoxy composites loaded with short MPCF lengths of 50 and 200 μm.
Hybrid Vesicle Stability under Sterilisation and Preservation Processes Used in the Manufacture of Medicinal Formulations
Authors: Seneviratne Rashmi , Jeuken Lars J. C. , Rappolt Michael , Beales Paul A.
Published: April 2020

Sterilisation and preservation of vesicle formulations are important considerations for their viable manufacture for industry applications, particular those intended for medicinal use. Here, we undertake an initial investigation of the stability of hybrid lipid-block copolymer vesicles to common sterilisation and preservation processes, with particular interest in how the block copolymer component might tune vesicle stability. We investigate two sizes of polybutadiene-block-poly(ethylene oxide) polymers (PBd12-PEO11 and PBd22-PEO14) mixed with the phospholipid 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) considering the encapsulation stability of a fluorescent cargo and the colloidal stability of vesicle size distributions. We find that autoclaving and lyophilisation cause complete loss of encapsulation stability under the conditions studied here. Filtering through 200 nm pores appears to be viable for sterilisation for all vesicle compositions with comparatively low release of encapsulated cargo, even for vesicle size distributions which extend beyond the 200 nm filter pore size. Freeze-thaw of vesicles also shows promise for the preservation of hybrid vesicles with high block copolymer content. We discuss the process stability of hybrid vesicles in terms of the complex mechanical interplay between bending resistance, stretching elasticity and lysis strain of these membranes and propose strategies for future work to further enhance the process stability of these vesicle formulations.
Temporal Layers in Heritage Tourism: Christianity and Islam in an Algarvian Chapel
Authors: Oliveira Marcelo G. , Luzia Isabel
Published: April 2020

The worldwide expansion of cultural and heritage tourism presents several opportunities for destination development, but also poses significant challenges in terms of management. This is especially true when different, overlapping, and potentially conflicting meanings coexist in the same location, as when distinct layers of the history of a site are unearthed by archaeology. Considering faith as confidence in the perpetuation of identities, an element common to both heritage and religion, this paper presents the results of a study of the heritagization process of a Christian chapel in Loulé (Algarve, Portugal), where traces of the city’s Islamic past were uncovered, and of the strategies implemented considering the site’s overlapping meanings. The results indicate that the embracement, rather than the suppression, of dissonant layers of significance in the heritagization of a religious site can contribute to a community’s richer sense of its enduring memory through a new dialogue with its multifaceted past and the validation of previously disregarded traces of its identity.
Disability, Anthropology, and Flourishing with God: A Kierkegaardian Account
Authors: Cockayne Joshua
Published: April 2020

How can the writings of Søren Kierkegaard address contemporary issues in the theology of disability? For while it is surely true that Kierkegaard had ‘no concept of “disability” in the contemporary sense’ of the term, I will argue that there is much in Kierkegaard’s writings that addresses issues related to disability. I begin by exploring Kierkegaard’s discussion of suffering and its application to disability theology. I argue that while this has some application, it doesn’t get to the heart of the issue, since a theology of disability must address more than the issue of suffering. Instead, I argue, we should look to Kierkegaard’s anthropology because it is here that we find a vision of what it is to be truly human, and, therefore, how we might understand what it means for those with disabilities to be truly human. To do this, I outline the account of the human being as spirit in The Sickness Unto Death, noting its inability to include certain individuals with severe cognitive disabilities. A straightforward reading of Sickness suggests that Kierkegaard would think of those with cognitive disabilities as similar to non-human animals in various respects. Noting the shortcomings of such an approach, I then offer a constructive amendment to Kierkegaard’s anthropology that can retain Kierkegaard’s concern that true human flourishing is found only in relationship with God. While Kierkegaard’s emphasis on teleology can be both affirming and inclusive for those with disability, I argue that we need to look to Kierkegaard’s account of ‘neighbor’ in Works of Love to overcome the difficulties with his seemingly exclusive anthropology.
Estimation of Forest Growing Stock Volume with UAV Laser Scanning Data: Can It Be Done without Field Data?
Authors: Puliti Stefano , Breidenbach Johannes , Astrup Rasmus
Published: April 2020

Laser scanning data from unmanned aerial vehicles (UAV-LS) offer new opportunities to estimate forest growing stock volume ( V ) exclusively based on the UAV-LS data. We propose a method to measure tree attributes and using these measurements to estimate V without the use of field data for calibration. The method consists of five steps: i) Using UAV-LS data, tree crowns are automatically identified and segmented wall-to-wall. ii) From all detected tree crowns, a sample is taken where diameter at breast height (DBH) can be recorded reliably as determined by visual assessment in the UAV-LS data. iii) Another sample of crowns is taken where tree species were identifiable from UAV image data. iv) DBH and tree species models are fit using the samples and applied to all detected tree crowns. v) Single tree volumes are predicted with existing allometric models using predicted species and DBH, and height directly obtained from UAV-LS. The method was applied to a Riegl-VUX data set with an average density of 1130 points m−2 and 3 cm orthomosaic acquired over an 8.8 ha managed boreal forest. The volumes of the identified trees were aggregated to estimate plot-, stand-, and forest-level volumes which were validated using 58 independently measured field plots. The root-mean-square deviance ( R M S D % ) decreased when increasing the spatial scale from the plot (32.2%) to stand (27.1%) and forest level (3.5%). The accuracy of the UAV-LS estimates varied given forest structure and was highest in open pine stands and lowest in dense birch or spruce stands. On the forest level, the estimates based on UAV-LS data were well within the 95% confidence interval of the intense field survey estimate, and both estimates had a similar precision. While the results are encouraging for further use of UAV-LS in the context of fully airborne forest inventories, future studies should confirm our findings in a variety of forest types and conditions.
Cluster Low-Streams Regression Method for Hyperspectral Radiative Transfer Computations: Cases of O2 A- and CO2 Bands
Authors: del Águila Ana , Efremenko Dmitry S. , Molina García Víctor , Kataev Michael Yu.
Published: April 2020

Current atmospheric composition sensors provide a large amount of high spectral resolution data. The accurate processing of this data employs time-consuming line-by-line (LBL) radiative transfer models (RTMs). In this paper, we describe a method to accelerate hyperspectral radiative transfer models based on the clustering of the spectral radiances computed with a low-stream RTM and the regression analysis performed for the low-stream and multi-stream RTMs within each cluster. This approach, which we refer to as the Cluster Low-Streams Regression (CLSR) method, is applied for computing the radiance spectra in the O2 A-band at 760 nm and the CO2 band at 1610 nm for five atmospheric scenarios. The CLSR method is also compared with the principal component analysis (PCA)-based RTM, showing an improvement in terms of accuracy and computational performance over PCA-based RTMs. As low-stream models, the two-stream and the single-scattering RTMs are considered. We show that the error of this approach is modulated by the optical thickness of the atmosphere. Nevertheless, the CLSR method provides a performance enhancement of almost two orders of magnitude compared to the LBL model, while the error of the technique is below 0.1% for both bands.
Laser Micromachining of Lithium Niobate-Based Resonant Sensors towards Medical Devices Applications
Authors: Al-Shibaany Zeyad Yousif Abdoon , Penchev Pavel , Hedley John , Dimov Stefan
Published: April 2020

This paper presents a micromachining process for lithium niobate (LiNbO3) material for the rapid prototyping of a resonant sensor design for medical devices applications. Laser micromachining was used to fabricate samples of lithium niobate material. A qualitative visual check of the surface was performed using scanning electron microscopy. The surface roughness was quantitatively investigated using an optical surface profiler. A surface roughness of 0.526 μm was achieved by laser micromachining. The performance of the laser-micromachined sensor has been examined in different working environments and different modes of operation. The sensor exhibits a Quality-factor (Q-factor) of 646 in a vacuum; and a Q-factor of 222 in air. The good match between the modelling and experimental results shows that the laser-micromachined sensor has a high potential to be used as a resonance biosensor.
Closed-Loop Attention Restoration Theory for Virtual Reality-Based Attentional Engagement Enhancement
Authors: Li Gang , Zhou Shihong , Kong Zhen , Guo Mengyuan
Published: April 2020

Today, as media and technology multitasking becomes pervasive, the majority of young people face a challenge regarding their attentional engagement (that is, how well their attention can be maintained). While various approaches to improve attentional engagement exist, it is difficult to produce an effect in younger people, due to the inadequate attraction of these approaches themselves. Here, we show that a single 30-min engagement with an attention restoration theory (ART)-inspired closed-loop software program (Virtual ART) delivered on a consumer-friendly virtual reality head-mounted display (VR-HMD) could lead to improvements in both general attention level and the depth of engagement in young university students. These improvements were associated with positive changes in both behavioral (response time and response time variability) and key electroencephalography (EEG)-based neural metrics (frontal midline theta inter-trial coherence and parietal event-related potential P3b). All the results were based on the comparison of the standard Virtual ART tasks (control group, n = 15) and closed-loop Virtual ART tasks (treatment group, n = 15). This study provides the first case of EEG evidence of a VR-HMD-based closed-loop ART intervention generating enhanced attentional engagement.
Visual Feedback Control of a Rat Ankle Angle Using a Wirelessly Powered Two-Channel Neurostimulator
Authors: Takeuchi Masaru , Watanabe Keita , Ishihara Kanta , Miyamoto Taichi , Tokutake Katsuhiro , Saeki Sota , Aoyama Tadayoshi , Hasegawa Yasuhisa , Kurimoto Shigeru , Hirata Hitoshi
Published: April 2020

Peripheral nerve disconnections cause severe muscle atrophy and consequently, paralysis of limbs. Reinnervation of denervated muscle by transplanting motor neurons and applying Functional Electrical Stimulation (FES) onto peripheral nerves is an important procedure for preventing irreversible degeneration of muscle tissues. After the reinnervation of denervated muscles, multiple peripheral nerves should be stimulated independently to control joint motion and reconstruct functional movements of limbs by the FES. In this study, a wirelessly powered two-channel neurostimulator was developed with the purpose of applying selective FES to two peripheral nerves—the peroneal nerve and the tibial nerve in a rat. The neurostimulator was designed in such a way that power could be supplied wirelessly, from a transmitter coil to a receiver coil. The receiver coil was connected, in turn, to the peroneal and tibial nerves in the rat. The receiver circuit had a low pass filter to allow detection of the frequency of the transmitter signal. The stimulation of the nerves was switched according to the frequency of the transmitter signal. Dorsal/plantar flexion of the rat ankle joint was selectively induced by the developed neurostimulator. The rat ankle joint angle was controlled by changing the stimulation electrode and the stimulation current, based on the Proportional Integral (PI) control method using a visual feedback control system. This study was aimed at controlling the leg motion by stimulating the peripheral nerves using the neurostimulator.
High Repetition Rate Mid-Infrared Differential Absorption Lidar for Atmospheric Pollution Detection
Authors: Gong Yu , Bu Lingbing , Yang Bin , Mustafa Farhan
Published: April 2020

Developments in mid-infrared Differential Absorption Lidar (DIAL), for gas remote sensing, have received a significant amount of research in recent years. In this paper, a high repetition rate tunable mid-infrared DIAL, mounted on a mobile platform, has been built for long range remote detection of gas plumes. The lidar uses a solid-state tunable optical parametric oscillator laser, which can emit laser pulse with repetition rate of 500 Hz and between the band from 2.5 μm to 4 μm. A monitoring channel has been used to record the laser energy in real-time and correct signals. Convolution correction technology has also been incorporated to choose the laser wavelengths. Taking NO2 and SO2 as examples, lidar system calibration experiment and open field observation experiment have been carried out. The observation results show that the minimum detection sensitivity of NO2 and SO2 can reach 0.07 mg/m3, and 0.31 mg/m3, respectively. The effective temporal resolution can reach second level for the high repetition rate of the laser, which demonstrates that the system can be used for the real-time remote sensing of atmospheric pollution gas.
LiDAR Point Cloud Recognition of Overhead Catenary System with Deep Learning
Authors: Lin Shuai , Xu Cheng , Chen Lipei , Li Siqi , Tu Xiaohan
Published: April 2020

High-speed railways have been one of the most popular means of transportation all over the world. As an important part of the high-speed railway power supply system, the overhead catenary system (OCS) directly influences the stable operation of the railway, so regular inspection and maintenance are essential. Now manual inspection is too inefficient and high-cost to fit the requirements for high-speed railway operation, and automatic inspection becomes a trend. The 3D information in the point cloud is useful for geometric parameter measurement in the catenary inspection. Thus it is significant to recognize the components of OCS from the point cloud data collected by the inspection equipment, which promotes the automation of parameter measurement. In this paper, we present a novel method based on deep learning to recognize point clouds of OCS components. The method identifies the context of each single frame point cloud by a convolutional neural network (CNN) and combines some single frame data based on classification results, then inputs them into a segmentation network to identify OCS components. To verify the method, we build a point cloud dataset of OCS components that contains eight categories. The experimental results demonstrate that the proposed method can detect OCS components with high accuracy. Our work can be applied to the real OCS components detection and has great practical significance for OCS automatic inspection.
Toward Using Wearables to Remotely Monitor Cognitive Frailty in Community-Living Older Adults: An Observational Study
Authors: Razjouyan Javad , Najafi Bijan , Horstman Molly , Sharafkhaneh Amir , Amirmazaheri Mona , Zhou He , Kunik Mark E. , Naik Aanand
Published: April 2020

Physical frailty together with cognitive impairment (Cog), known as cognitive frailty, is emerging as a strong and independent predictor of cognitive decline over time. We examined whether remote physical activity (PA) monitoring could be used to identify those with cognitive frailty. A validated algorithm was used to quantify PA behaviors, PA patterns, and nocturnal sleep using accelerometer data collected by a chest-worn sensor for 48-h. Participants (N = 163, 75 ± 10 years, 79% female) were classified into four groups based on presence or absence of physical frailty and Cog: PR-Cog-, PR+Cog-, PR-Cog+, and PR+Cog+. Presence of physical frailty (PR-) was defined as underperformance in any of the five frailty phenotype criteria based on Fried criteria. Presence of Cog (Cog-) was defined as a Mini-Mental State Examination (MMSE) score of less than 27. A decision tree classifier was used to identify the PR-Cog- individuals. In a univariate model, sleep (time-in-bed, total sleep time, percentage of sleeping on prone, supine, or sides), PA behavior (sedentary and light activities), and PA pattern (percentage of walk and step counts) were significant metrics for identifying PR-Cog- (p < 0.050). The decision tree classifier reached an area under the curve of 0.75 to identify PR-Cog-. Results support remote patient monitoring using wearables to determine cognitive frailty.
Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution
Authors: Bulot Florentin Michel Jacques , Russell Hugo Savill , Rezaei Mohsen , Johnson Matthew Stanley , Ossont Steven James Johnston , Morris Andrew Kevin Richard , Basford Philip James , Easton Natasha Hazel Celeste , Foster Gavin Lee , Loxham Matthew , Cox Simon James
Published: April 2020

Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min , and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response.
Concrete Crack Monitoring Using a Novel Strain Transfer Model for Distributed Fiber Optics Sensors
Authors: Bassil Antoine , Chapeleau Xavier , Leduc Dominique , Abraham Odile
Published: April 2020

In this paper, we study the strain transfer mechanism between a host material and an optical fiber. A new analytical model handling imperfect bonding between layers is proposed. A general expression of the crack-induced strain transfer from fractured concrete material to optical fiber is established in the case of a multilayer system. This new strain transfer model is examined through performing wedge splitting tests on concrete specimens instrumented with embedded and surface-mounted fiber optic cables. The experimental results showed the validity of the crack-induced strain expression fitted to the distributed strains measured using an Optical Backscattering Reflectometry (OBR) system. As a result, precise estimations of the crack openings next to the optical cable location were achieved, as well as the monitoring of the optical cable response through following the strain lag parameter.
Recent Development on the Electrochemical Detection of Selected Pesticides: A Focused Review
Authors: Noori Jafar Safaa , Mortensen John , Geto Alemnew
Published: April 2020

Pesticides are heavily used in agriculture to protect crops from diseases, insects, and weeds. However, only a fraction of the used pesticides reaches the target and the rest slips through the soil, causing the contamination of ground- and surface water resources. Given the emerging interest in the on-site detection of analytes that can replace traditional chromatographic techniques, alternative methods for pesticide measuring have recently encountered remarkable attention. This review gives a focused overview of the literature related to the electrochemical detection of selected pesticides. Here, we focus on the electrochemical detection of three important pesticides; glyphosate, lindane and bentazone using a variety of electrochemical detection techniques, electrode materials, electrolyte media, and sample matrix. The review summarizes the different electrochemical studies and provides an overview of the analytical performances reported such as; the limits of detection and linearity range. This article highlights the advancements in pesticide detection of the selected pesticides using electrochemical methods and point towards the challenges and needed efforts to achieve electrochemical detection suitable for on-site applications.
Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array
Authors: Pan Jie , Jiang Fu
Published: April 2020

Beamspace processing has become much attractive in recent radar and wireless communication applications, since the advantages of complexity reduction and of performance improvements in array signal processing. In this paper, we concentrate on the beamspace DOA estimation of linear array via atomic norm minimization (ANM). The existed generalized linear spectrum estimation based ANM approaches suffer from the high computational complexity for large scale array, since their complexity depends upon the number of sensors. To deal with this problem, we develop a low dimensional semidefinite programming (SDP) implementation of beamspace atomic norm minimization (BS-ANM) approach for DFT beamspace based on the super resolution theory on the semi-algebraic set. Then, a computational efficient iteration algorithm is proposed based on alternating direction method of multipliers (ADMM) approach. We develop the covariance based DOA estimation methods via BS-ANM and apply the BS-ANM based DOA estimation method to the channel estimation problem for massive MIMO systems. Simulation results demonstrate that the proposed methods exhibit the superior performance compared to the state-of-the-art counterparts.
Robust In-Plane Structures Oscillation Monitoring by Terrestrial Photogrammetry
Authors: El-Kadi Omar , El-Shazly Adel , Nassar Khaled
Published: April 2020

Oscillation monitoring commonly requires complex setups integrating various types of sensors associated with intensive computations to achieve an adequate rate of observations and accuracy. This research presents a simple, cost-effective approach that allows two-dimensional oscillation monitoring by terrestrial photogrammetry using non-metric cameras. Tedious camera calibration procedures are eliminated by using a grid target that allows geometric correction to be performed to the frame’s region of interest at which oscillations are monitored. Region-based convolutional neural networks (Faster R-CNN) techniques are adopted to minimize the light exposure limitations, commonly constraining applications of terrestrial photogrammetry. The proposed monitoring procedure is tested at outdoor conditions to check its reliability and accuracy and examining the effect of using Faster R-CNN on monitoring results. The proposed artificial intelligence (AI) aided oscillation monitoring allowed sub-millimeter accuracy monitoring with observation rates up to 60 frames per second and gained the benefit of high optical zoom offered by market available bridge cameras to monitor oscillation of targets 100 m apart with high accuracy.
Keys for Action: An Efficient Keyframe-Based Approach for 3D Action Recognition Using a Deep Neural Network
Authors: Yasin Hashim , Hussain Mazhar , Weber Andreas
Published: April 2020

In this paper, we propose a novel and efficient framework for 3D action recognition using a deep learning architecture. First, we develop a 3D normalized pose space that consists of only 3D normalized poses, which are generated by discarding translation and orientation information. From these poses, we extract joint features and employ them further in a Deep Neural Network (DNN) in order to learn the action model. The architecture of our DNN consists of two hidden layers with the sigmoid activation function and an output layer with the softmax function. Furthermore, we propose a keyframe extraction methodology through which, from a motion sequence of 3D frames, we efficiently extract the keyframes that contribute substantially to the performance of the action. In this way, we eliminate redundant frames and reduce the length of the motion. More precisely, we ultimately summarize the motion sequence, while preserving the original motion semantics. We only consider the remaining essential informative frames in the process of action recognition, and the proposed pipeline is sufficiently fast and robust as a result. Finally, we evaluate our proposed framework intensively on publicly available benchmark Motion Capture (MoCap) datasets, namely HDM05 and CMU. From our experiments, we reveal that our proposed scheme significantly outperforms other state-of-the-art approaches.
Fostering Environmental Awareness with Smart IoT Planters in Campuses
Authors: Tabuenca Bernardo , García-Alcántara Vicente , Gilarranz-Casado Carlos , Barrado-Aguirre Samuel
Published: April 2020

The decrease in the cost of sensors during the last years, and the arrival of the 5th generation of mobile technology will greatly benefit Internet of Things (IoT) innovation. Accordingly, the use of IoT in new agronomic practices might be a vital part for improving soil quality, optimising water usage, or improving the environment. Nonetheless, the implementation of IoT systems to foster environmental awareness in educational settings is still unexplored. This work addresses the educational need to train students on how to design complex sensor-based IoT ecosystems. Hence, a Project-Based-Learning approach is followed to explore multidisciplinary learning processes implementing IoT systems that varied in the sensors, actuators, microcontrollers, plants, soils and irrigation system they used. Three different types of planters were implemented, namely, hydroponic system, vertical garden, and rectangular planters. This work presents three key contributions that might help to improve teaching and learning processes. First, a holistic architecture describing how IoT ecosystems can be implemented in higher education settings is presented. Second, the results of an evaluation exploring teamwork performance in multidisciplinary groups is reported. Third, alternative initiatives to promote environmental awareness in educational contexts (based on the lessons learned) are suggested. The results of the evaluation show that multidisciplinary work including students from different expertise areas is highly beneficial for learning as well as on the perception of quality of the work obtained by the whole group. These conclusions rekindle the need to encourage work in multidisciplinary teams to train engineers for Industry 4.0 in Higher Education.
The Power of Assemblies at Interfaces: Nanosensor Platforms Based on Synthetic Receptor Membranes
Authors: Minamiki Tsukuru , Ichikawa Yuki , Kurita Ryoji
Published: April 2020

Synthetic sensing materials (artificial receptors) are some of the most attractive components of chemical/biosensors because of their long-term stability and low cost of production. However, the strategy for the practical design of these materials toward specific molecular recognition in water is not established yet. For the construction of artificial material-based chemical/biosensors, the bottom-up assembly of these materials is one of the effective methods. This is because the driving forces of molecular recognition on the receptors could be enhanced by the integration of such kinds of materials at the ‘interfaces’, such as the boundary portion between the liquid and solid phases. Additionally, the molecular assembly of such self-assembled monolayers (SAMs) can easily be installed in transducer devices. Thus, we believe that nanosensor platforms that consist of synthetic receptor membranes on the transducer surfaces can be applied to powerful tools for high-throughput analyses of the required targets. In this review, we briefly summarize a comprehensive overview that includes the preparation techniques for molecular assemblies, the characterization methods of the interfaces, and a few examples of receptor assembly-based chemical/biosensing platforms on each transduction mechanism.
Potential Application of Gold Nanospheres as a Surface Plasmon Resonance Based Sensor for In-Situ Detection of Residual Fungicides
Authors: Nguyen Thi Nhat Hang , Le Ngoc Thuy Trang , Phuong Phong Nguyen Thi , Nguyen Dai Hai , Nguyen-Le Minh-Tri
Published: April 2020

It is essential to develop a simple and sensitive method to rapidly detect residual fungicides in agricultural products to protect human health. So far, little studies have been reported on potential application of gold nanospheres (AuNSps) as a surface plasmon resonance based sensor for in-situ detection of residual fungicides. Therefore, in this study, we investigated the potential application of AuNSps as a surface plasmon resonance based sensor for in-situ detection of fungicides. AuNSps were successfully synthesized via a seed-mediated method with some modifications. Firstly, gold nanoseeds were made during the reduction of chloroauric acid by trisodium citrate dihydrate (TSC). Then, AuNSps were grown from the seeds by using HAuCl4, TSC and EDTA. AuNSps were subsequently dropped on a glass substrate before covered by thiophanate methyl, a broad-spectrum systemic fungicide. The AuNSps coated glass substrate was subsequently dried in the air for further surface-enhanced Raman spectroscopy (SERS) measurements. Optical properties, shape and size of AuNSps were confirmed by UV-vis spectroscopy, XRD, SEM-EDX and TEM. The results showed that AuNSps were successfully synthesized with the size of 53 nm, and their resonance peak was located at 560 nm. The Raman signal intensity of thiophanate methyl covered on AuNSps is higher than that without AuNSps, indicating SERS effects of AuNSps deposited glass substrate.
Using the Decomposition-Based Multi-Objective Evolutionary Algorithm with Adaptive Neighborhood Sizes and Dynamic Constraint Strategies to Retrieve Atmospheric Ducts
Authors: Mai Yanbo , Shi Hanqing , Liao Qixiang , Sheng Zheng , Zhao Shuai , Ni Qingjian , Zhang Wei
Published: April 2020

The traditional method of retrieving atmospheric ducts is to use the special sensor of weather balloons or rocket soundings to obtain information intelligently, and it is very expensive. Today, with the development of technology, it is very convenient to retrieve the atmospheric ducts from Global Navigation Satellite System (GNSS) phase delay and propagation loss observation data, and then the GNSS receiver on the ground forms an automatic receiving sensor. This paper proposes a hybrid decomposition-based multi-objective evolutionary algorithm with adaptive neighborhood sizes (EN-MOEA/ACD-NS), which dynamically imposes some constraints on the objectives. The decomposition-based multi-objective evolutionary algorithm (MOEA/D) updates the solutions through neighboring objectives, the number of which affects the quality of the optimal solution. Properly constraining the optimization objectives can effectively balance the diversity and convergence of the population. The experimental results from the Congress on Evolutionary Computation (CEC) 2009 on test instances with hypervolume (HV), inverted generational distance (IGD), and average Hausdorff distance ∆2 metrics show that the new method performs similarly to the evolutionary algorithm MOEA/ACD-NS, which considers only the dynamic change of the neighborhood sizes. The improved algorithm is applied to the practical problem of jointly retrieving atmospheric ducts with GNSS signals, and its performance further demonstrates its feasibility and practicability.