bluuebunny/crossref_metadata_2025 huggingface dataset:
Microbial Communities and Sulfate-Reducing Microorganisms Abundance and Diversity in Municipal Anaerobic Sewage Sludge Digesters from a Wastewater Treatment Plant (Marrakech, Morocco)
Authors: El Houari Abdelaziz , Ranchou-Peyruse Magali , Ranchou-Peyruse Anthony , Bennisse Rhizlane , Bouterfas Radia , Goni Urriza Maria Soledad , Qatibi Abdel-Ilah , Guyoneaud Rémy
Published: October 2020

Both molecular analyses and culture-dependent isolation were combined to investigate the diversity of sulfate-reducing prokaryotes and explore their role in sulfides production in full-scale anaerobic digesters (Marrakech, Morocco). At global scale, using 16S rRNA gene sequencing, Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, Synergistetes, and Euryarchaeota were the most dominant phyla. The abundance of Archaea (3.1–5.7%) was linked with temperature. The mcrA gene ranged from 2.18 × 105 to 1.47 × 107 gene copies.g−1 of sludge. The sulfate-reducing prokaryotes, representing 5% of total sequences, involved in sulfides production were Peptococcaceae, Syntrophaceae, Desulfobulbaceae, Desulfovibrionaceae, Syntrophobacteraceae, Desulfurellaceae, and Desulfobacteraceae. Furthermore, dsrB gene ranged from 2.18 × 105 to 1.92 × 107 gene copies.g−1 of sludge. The results revealed that exploration of diversity and function of sulfate-reducing bacteria may play a key role in decreasing sulfide production, an undesirable by-product, during anaerobic digestion.
Long-Term Performance of Anti-Freeze Protection System of a Solar Thermal System
Authors: Pater Sebastian
Published: October 2020

In a moderate, transitory climate, to prevent freezing of outdoor pipes and collectors in solar thermal systems, anti-freezing fluids are commonly used. There is little experience of using water without any additives as a solar thermal fluid in such a climate. Based on these findings, to fill the knowledge gap this article presents the long-term results of thermal performance and anti-freeze protection of a solar heating system with heat pipe evacuated tube collectors with water as a solar thermal fluid. The operation of this system under real conditions was analysed for five years in southern Poland. The annual value of solar insolation ranged from 839 to almost 1000 kWh/m2. The monthly efficiency of the solar collectors from March to October was usually higher than 25%, and the lowest was between November and January. The anti-freeze protection system consumed annually from 7 to 13% of the heat generated by the collectors in the installation. Supporting the operation of the central heating system in the building during the winter season highly improved the efficiency of the solar collectors. Results show that it is possible to use water without any additives as a solar thermal fluid in a moderate, transitory climate.
Study of Performance, Emissions, and Combustion of a Common-Rail Injection Engine Fuelled with Blends of Cocos nucifera Biodiesel with Diesel Oil
Authors: Teoh Yew Heng , How Heoy Geok , Le Thanh Danh , Nguyen Huu Tho
Published: October 2020

Renewable alternatives to fossil fuels, such as biodiesel, are necessary to lessen emission of greenhouse gases that are causing climate change. Using a high-pressure, medium-duty, common-rail, turbocharged four-cylinder diesel engine, this work studies the effect of adding Cocos nucifera biodiesel to conventional diesel on exhaust emissions, engine performance, and combustion characteristics. An analysis and characterization of the key physicochemical properties of diesel, biodiesel, and biodiesel–diesel blends were carried out. The engine was fuelled with pure petroleum diesel and blended diesel containing a 10%, 20%, 30%, and 50% volume of coconut oil at full throttle and six different speed settings, respectively. The results showed relatively close physicochemical properties between the biodiesel blend and conventional petroleum fuel. Observations made over the entire speed range indicated that a higher coconut oil biodiesel (COB) content lowers the torque and brake power compared to diesel. In the case of engine exhaust gas, a reduction in carbon monoxide (CO) and smoke emissions were observed. Notably, COB50 gives out the highest nitrogen oxides (NOx) but it is raised even for other blends. The experimental results also demonstrated that a higher COB content achieves a lower peak pressure while the peak heat release rate (PHRR) was lower than that of conventional diesel as the speed of the engine increases.
A Novel Approach Integrating Intuitionistic Fuzzy Analytical Hierarchy Process and Goal Programming for Chickpea Cultivar Selection under Stress Conditions
Authors: Karacan Ilknur , Senvar Ozlem , Arslan Ozlem , Ekmekçi Yasemin , Bulkan Serol
Published: October 2020

Chickpea (Cicer arietinum L.) is a quite high nutrient and widespread legume that is consumed globally. Similar to many plants, chickpea is sensitive to environmental stresses. The major goal of the breeders is to achieve the most tolerant cultivars. This study aims to determine the tolerance level of chickpea cultivars against cold and drought stresses. The cultivars in the scope of this study are the ones that are officially identified and grown in Turkey. Ranking alternatives according to multiple criteria is difficult and requires a systematic approach. Thus, a coherent multi criteria decision making (MCDM) methodology is proposed in order to ease the ranking process. The methodology includes integration of intuitionistic fuzzy analytical hierarchy process (IF-AHP) with group decision making (GDM) and goal programming (GP). This integration presents a robust ranking according to criteria that are appraised by talented experts. Applying the methodology to the data, results in the order of chickpea cultivars with regard to their cumulative tolerance to cold and drought stresses. Diyar 95 spearheads this list with its utmost performance. The main contribution of this study is the proposition of the powerful MCDM approach with systematic procedure for the ranking process of cultivars. The proposed methodology has a generic structure that can be applied to various stress problems for different plants.
Optimization Using Response Surface Methodology (RSM) for Biodiesel Synthesis Catalyzed by Radiation-Induced Kenaf Catalyst in Packed-Bed Reactor
Authors: Zabaruddin Nur Haryani , Abdullah Luqman Chuah , Mohamed Nor Hasimah , Choong Thomas Shean Yaw
Published: October 2020

In this study, continuous transesterification of refined palm oil by using radiation-induced kenaf denoted as anion exchange kenaf catalyst in a packed-bed reactor was developed. The application of full factorial design and response surface methodology (RSM) based on the central composite design (CCD) was used to design the process and analyzed the effect of reactor operating variables such as packed bed height, the molar ratio of oil to ethanol and volumetric flow rate on the production of fatty acid ethyl ester (FAEE). The statistical analysis results showed that all three operating parameters affect the reaction efficiency significantly. The optimum conditions were determined to be 9.81 cm packed bed height, a molar ratio at 1:50, and a volumetric flow rate of 0.38 mL min−1. Three tests were carried out to verify the optimum combination of process parameters. The predicted and actual values of molar conversion fatty acid ethyl ester (FAEE) molar conversion were 97.29% and 96.87%, respectively. The reusability of kenaf fiber-based catalysts is discussed with a specially highlighted on fiber dissolution, leaching, and fouling. Nevertheless, the impurities absorption properties of anion exchange kenaf catalyst towards biodiesel production could eventually simplify the biodiesel purification steps and cost. In sum, anion exchange kenaf catalyst shows the potential commercial applications to transesterification of FAEE in a packed-bed reactor.
Electric Field-Driven Direct Interspecies Electron Transfer for Bioelectrochemical Methane Production from Fermentable and Non-Fermentable Substrates
Authors: Oh Gyung-Geun , Song Young-Chae , Bae Byung-Uk , Lee Chae-Young
Published: October 2020

The bioelectrochemical methane production from acetate as a non-fermentable substrate, glucose as a fermentable substrate, and their mixture were investigated in an anaerobic sequential batch reactor exposed to an electric field. The electric field enriched the bulk solution with exoelectrogenic bacteria (EEB) and electrotrophic methanogenic archaea, and promoted direct interspecies electron transfer (DIET) for methane production. However, bioelectrochemical methane production was dependent on the substrate characteristics. For acetate as the substrate, the main electron transfer pathway for methane production was DIET, which significantly improved methane yield up to 305.1 mL/g chemical oxygen demand removed (CODr), 77.3% higher than that in control without the electric field. For glucose, substrate competition between EEB and fermenting bacteria reduced the contribution of DIET to methane production, resulting in the methane yield of 288.0 mL/g CODr, slightly lower than that of acetate. In the mixture of acetate and glucose, the contribution of DIET to methane production was less than that of the single substrate, acetate or glucose, due to the increase in the electron equivalent for microbial growth. The findings provide a better understanding of electron transfer pathways, biomass growth, and electron transfer losses depending on the properties of substrates in bioelectrochemical methane production.
Artificial Immune System in Doing 2-Satisfiability Based Reverse Analysis Method via a Radial Basis Function Neural Network
Authors: Alzaeemi Shehab Abdulhabib , Sathasivam Saratha
Published: October 2020

A radial basis function neural network-based 2-satisfiability reverse analysis (RBFNN-2SATRA) primarily depends on adequately obtaining the linear optimal output weights, alongside the lowest iteration error. This study aims to investigate the effectiveness, as well as the capability of the artificial immune system (AIS) algorithm in RBFNN-2SATRA. Moreover, it aims to improve the output linearity to obtain the optimal output weights. In this paper, the artificial immune system (AIS) algorithm will be introduced and implemented to enhance the effectiveness of the connection weights throughout the RBFNN-2SATRA training. To prove that the introduced method functions efficiently, five well-established datasets were solved. Moreover, the use of AIS for the RBFNN-2SATRA training is compared with the genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), and artificial bee colony (ABC) algorithms. In terms of measurements and accuracy, the simulation results showed that the proposed method outperformed in the terms of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). The introduced method outperformed the existing four algorithms in the aspect of robustness, accuracy, and sensitivity throughout the simulation process. Therefore, it has been proven that the proposed AIS algorithm effectively conformed to the RBFNN-2SATRA in relation to (or in terms of) the average value of training of RMSE rose up to 97.5%, SBC rose up to 99.9%, and CPU time by 99.8%. Moreover, the average value of testing in MAE was rose up to 78.5%, MAPE was rose up to 71.4%, and was capable of classifying a higher percentage (81.6%) of the test samples compared with the results for the GA, DE, PSO, and ABC algorithms.
Bioactive Compounds and Antioxidant Capacity of Moringa Leaves Grown in Spain Versus 28 Leaves Commonly Consumed in Pre-Packaged Salads
Authors: González-Romero Jaime , Arranz-Arranz Sandra , Verardo Vito , García-Villanova Belén , Guerra-Hernández Eduardo J.
Published: October 2020

Total antioxidant capacity (TAC) evaluated by ferric ion reducing antioxidant power (FRAP) assay, ABTS, DPPH, and Oxygen radical absorbance capacity (ORAC) assay, and total polyphenol content (TPC) by Folin–Ciocalteu were determined in Moringa oleifera leaves (MO) grown in Spain, and compared with 28 different vegetable leaves pre-packaged for consumption as a salad. Total carotenoids, flavonoids, and chlorophylls were also determined in the samples with highest TAC. Two different extraction procedures were applied to obtain the methanolic fraction and the lipophilic and hydrophilic fractions. The highest TAC and TPC contents were found in MO. High values were also found in red chicory, “lollo rosso”, and oak lettuce. The lowest TAC and TPC values were obtained in iceberg lettuce. The correlations between the extraction procedures and methods assayed were high and statistically significant. In the light of these results, we suggest the addition of MO to the existing range of fresh-cut salad foods would increase their antioxidant content by up to six times.
Group Key Management Scheme for Multicast Communication Fog Computing Networks
Authors: Dong Mai Trung , Xu Haitao
Published: October 2020

In group key management, the implementation of encryption often fails because multicast communication does not provide reliable linkage. In this paper, a new group key management scheme is proposed for multicast communication in fog computing networks. In the proposed scheme, any legal fog user belonging to a fog node will be able to decrypt a ciphertext encrypted by a secret shared key. The shared secret key is divided into key segments. In the rekeying operation process, each key segment is split into two factors with its shared production mechanism. The key updates are required to belong to the fog provider or the group management device. Fog users will have independent key segments unchanged. Then, the cost, the message of rekeying, and the dependence on credible channels will be decreased. This method can resist collusion attacks and ensure backward security and forward security, even if the number of users leaving is larger than the threshold value. Our scheme is also suitable for untrusted affiliate networks.
Mathematical Modeling of Hydrodynamics in Bioreactor by Means of CFD-Based Compartment Model
Authors: Krychowska Agnieszka , Kordas Marian , Konopacki Maciej , Grygorcewicz Bartłomiej , Musik Daniel , Wójcik Krzysztof , Jędrzejczak-Silicka Magdalena , Rakoczy Rafał
Published: October 2020

This study presents the procedure of deriving a compartmental model (CM) based on an analysis obtained from the computational fluid dynamics (CFD) model of a bioreactor. The CM is composed of two parts, a structural (that takes into account the architecture of the mathematical model), and a parametric part (which contains the extrinsic parameters of the model). The CM is composed of the branches containing the set of perfectly mixed continuous stirred-tank reactors (CSTRs) in a configuration that matches the bioreactor’s flow patterns. Therefore, this work’s main objective was to develop a mathematical model that incorporated the flow field obtained by CFD technique. The proposed mathematical model was validated by means of the experimental data in the form of the residence time distribution (RTD) measurements.
Improving the Inner Surface State of Thick-Walled Tubes by Heat Treatments with Internal Quenching Considering a Simulation Based Optimization
Authors: Mühl Fabian , Klug Moritz , Dietrich Stefan , Schulze Volker
Published: October 2020

Internal Quenching is an innovative heat treatment method for difficult to access component sections. Especially, the microstructure, as well as the residual stress state at inner surfaces, of thick-walled tubes can be adjusted with the presented flexible heat treatment process. Based on multiphysical FE-models of two different steels, a simulative optimization study, considering different internal quenching strategies, was performed in order to find the optimal cooling conditions. The focus hereby was on the adjustment of a martensitic inner surface with high compressive residual stresses. The simulatively determined optimal cooling strategies were carried out experimentally and analyzed. A good agreement of the resulting hardness and residual stresses was achieved, validating the presented Fe-model of the Internal Quenching process. The shown results also indicate that the arising inner surface state is very sensitive to the transformation behavior of the used steel. Furthermore, the presented study shows that a preliminary simulative consideration of the heat treatment process helps to evaluate significant effects, reducing the experimental effort and time.
Thermal Performance of T-shaped Obstacles in a Solar Air Heater
Authors: Ahn Seung-Yong , Kim Kwang-Yong
Published: October 2020

This paper proposes T-shaped ribs as obstacles attached to the heat absorber plate in a rectangular solar air heater to promote heat transfer. The thermal and aerodynamic performance of the solar heater was numerically evaluated using three-dimensional Reynolds-averaged Navier–Stokes equations with the shear stress transport turbulence model. A parameter study was performed using the ratios of rib height to channel height, rib width to channel width, and rib width to rib height. The area-averaged Nusselt number and friction factor were selected as the performance parameters of the solar air heater to evaluate the heat transfer and friction loss, respectively. In addition, the performance factor was defined as the ratio of the area-averaged Nusselt number to the friction factor. The maximum area-averaged Nusselt number was found at h/e = 0.83 for a fixed rib area. Compared with triangular ribs, the T-shaped ribs showed up to a 65 % higher area-averaged Nusselt number and up to a 49.7% higher performance factor.
Adaptive Monitoring of Biotechnological Processes Kinetics
Authors: Lyubenova Velislava , Ignatova Maya , Roeva Olympia , Junne Stefan , Neubauer Peter
Published: October 2020

In this paper, an approach for the monitoring of biotechnological process kinetics is proposed. The kinetics of each process state variable is presented as a function of two time-varying unknown parameters. For their estimation, a general software sensor is derived with on-line measurements as inputs that are accessible in practice. The stability analysis with a different number of inputs shows that stability can be guaranteed for fourth- and fifth-order software sensors only. As a case study, the monitoring of the kinetics of processes carried out in stirred tank reactors is investigated. A new tuning procedure is derived that results in a choice of only one design parameter. The effectiveness of the proposed procedure is demonstrated with experimental data from Bacillus subtilis fed-batch cultivations.
A Tale of Maize, Palm, and Pine: Changing Socio-Ecological Interactions from Pre-Classic Maya to the Present Day in Belize
Authors: Rushton Elizabeth A. C. , Whitney Bronwen S. , Metcalfe Sarah E.
Published: October 2020

The environmental impact of the ancient Maya, and subsequent ecological recovery following the Terminal Classic decline, have been the key foci of research into socio-ecological interactions in the Yucatán peninsula. These foci, however, belie the complex pattern of resource exploitation and agriculture associated with post-Classic Maya societies and European colonisation. We present a high-resolution, 1200-year record of pollen and charcoal data from a 52-cm short core extracted from New River Lagoon, near to the European settlement of Indian Church, northern Belize. This study complements and extends a previous 3500-year reconstruction of past environmental change, located 1-km north of the new record and adjacent to the ancient Maya site of Lamanai. This current study shows a mixed crop production and palm agroforestry management strategy of the ancient Maya, which corroborates previous evidence at Lamanai. Comparison of the two records suggests that core agricultural and agroforestry activities shifted southwards, away from the centre of Lamanai, beginning at the post-Classic period. The new record also demonstrates that significant changes in land-use were not associated with drought at the Terminal Classic (ca. CE 1000) or the European Encounter (ca. CE 1500), but instead resulted from social and cultural change in the post-Classic period (CE 1200) and new economies associated with the British timber trade (CE 1680). The changes in land-use documented in two adjacent records from the New River Lagoon underline the need to reconstruct human–environment interactions using multiple, spatially, and temporally diverse records.
Measurement of the X-ray Elastic Constants of Amorphous Polycarbonate
Authors: Kawamura Yuki , Akiniwa Yoshiaki
Published: October 2020

In polymer materials, residual stress introduced during injection molding affects yield reduction due to deformation during molding and delayed fracture during operation, so the establishment of nondestructive stress evaluation of polymer products is desirable. The X-ray elastic constants of polycarbonate were measured for the purpose of obtaining fundamental data for X-ray stress measurement of amorphous polymer materials. The structural function was obtained from the diffraction data, and the strain measured by X-ray was determined from the shift of the first peak by the Q-space method. The peak position was determined using the pseudo-Voigt function approximation method and the diffraction line width method. The Young’s modulus measured by X-ray obtained by the diffraction line width method was close to the mechanical value. Although these values varied widely, they changed depending on the peak ratio. A simple and practical measurement method directly using the raw profile data was also discussed. The Young’s modulus determined by the diffraction line width method decreased with increasing peak ratio. On the other hand, the values determined by the pseudo-Voigt method were almost constant, irrespective of the peak ratio. The strain calculated by the line width method was determined more accurately than that by the pseudo-Voigt method.
Characterization of Dislocation Rearrangement in FCC Metals during Work Hardening Using X-ray Diffraction Line-Profile Analysis
Authors: Nakagawa Koutarou , Hayashi Momoki , Takano-Satoh Kozue , Matsunaga Hirotaka , Mori Hiroyuki , Maki Kazunari , Onuki Yusuke , Suzuki Shigeru , Sato Shigeo
Published: October 2020

Multiplication and rearrangement of dislocations in face-centered cubic (FCC) metals during tensile deformation are affected by grain size, stacking fault energy (SFE), and solute elements. X-ray diffraction (XRD) line-profile analysis can evaluate the dislocation density (ρ) and dislocation arrangement (M) from the strength of the interaction between dislocations. However, the relationship between M and ρ has not been thoroughly addressed. In this study, multiplication and rearrangement of dislocations in FCC metals during tensile deformation was evaluated by XRD line-profile analysis. Furthermore, the effects of grain size, SFE, and solute elements on the extent of dislocation rearrangement were evaluated with varying M values during tensile deformation. M decreased as the dislocation density increased. By contrast, grain size and SFE did not exhibit a significant influence on the obtained M values. The influence of solute species and concentration of solute elements on M changes were also determined. In addition, the relationship between dislocation substructures and M for tensile deformed metals were also explained. Dislocations were loosely distributed at M > 1, and cell walls gradually formed by gathering dislocations at M < 1. While cell walls became thicker with decreasing M in metals with low stacking fault energy, thin cell walls with high dislocation density formed for an M value of 0.3 in metals with high stacking fault energy.
TERESA Target Area at ELI Beamlines
Authors: Tryus Maksym , Grepl Filip , Chagovets Timofej , Velyhan Andriy , Giuffrida Lorenzo , Stancek Stanislav , Kantarelou Vasiliki , Istokskaia Valeria , Schillaci Francesco , Zakova Martina , Psikal Jan , Nevrkla Michal , Lazzarini Carlo Maria , Grittani Gabriele Maria , Goncalves Leonardo , Nawaz Muhammad Fahad , Cupal Josef , Koubíkova Lucia , Buck Samuel , Weiss Jiri , Peceli Davorin , Szotkowski Petr , Majer Karel , Naylon Jack Alexander , Green Jonathan Tyler , Kramer Daniel , Rus Bedrich , Korn Georg , Levato Tadzio , Margarone Daniele
Published: October 2020

The TERESA (TEstbed for high REpetition-rate Sources of Accelerated particles) target area, recently commissioned with the L3-HAPLS laser at Extreme Light Infrastructure (ELI)-Beamlines, is presented. Its key technological sections (vacuum and control systems, laser parameters and laser beam transport up to the target) are described, along with an overview of the available plasma diagnostics and targetry, tested at relativistic laser intensities. Perspectives of the TERESA laser–plasma experimental area at ELI-Beamlines are briefly discussed.
Judges 19-21: The Disasters of the Community of Virtue
Authors: Cohen Richard
Published: October 2020

This paper is an ethical exegesis of the biblical story of Gibeah, which concludes the Book of Judges (19–21), to show the catastrophic failure of the anti-political politics of the “community of virtue”, i.e., the rejection of power for the sake of moral society, such as proposed by libertarians, neo-liberals, anarchists and utopians. I consider Kant’s statement of the political problem: given humanity’s unsocial sociality, where each person is tempted to act as an exception to universal law, humans need rulers, but how to obtain rulers who are not themselves ruled by power, and become tyrannical, rather than being ruled by justice? The solution proposed by “the community of virtue” would reject power altogether and replace it with society regulated exclusively according to the moral virtue of its members. The Bible’s story of Gibeah shows graphically and conclusively the failure of any such attempt. Instead, as with normative political philosophy, the Bible endorses the rule of a king, i.e., the rule of the state, and a politics whereby power is disciplined to serve justice because it is rooted in Torah, i.e., a fundamental covenant, charter or constitution, aware and vigilant regarding the ambiguities and temptations of sovereignty, and therefore, ideally, always open to critique. As exemplified by biblical prophets, political protest against injustices perpetrated by the powerful against the least—widow, orphan, stranger—is at once religious obligation and true patriotism.
Sentinel-1 Cross Ratio and Vegetation Optical Depth: A Comparison over Europe
Authors: Vreugdenhil Mariette , Navacchi Claudio , Bauer-Marschallinger Bernhard , Hahn Sebastian , Steele-Dunne Susan , Pfeil Isabella , Dorigo Wouter , Wagner Wolfgang
Published: October 2020

Vegetation products based on microwave remote sensing observations, such as Vegetation Optical Depth (VOD), are increasingly used in a variety of applications. One disadvantage is the often coarse spatial resolution of tens of kilometers of products retrieved from microwave observations from spaceborne radiometers and scatterometers. This can potentially be overcome by using new high-resolution Synthetic Aperture Radar (SAR) observations from Sentinel-1. However, the sensitivity of Sentinel-1 backscatter to vegetation dynamics, or its use in radiative transfer models, such as the water cloud model, has only been tested at field to regional scale. In this study, we compared the cross-polarization ratio (CR) to vegetation dynamics as observed in microwave-based Vegetation Optical Depth from coarse-scale satellites over Europe. CR was obtained from Sentinel-1 VH and VV backscatter observations at 500 m sampling and resampled to the spatial resolution of VOD from the Advanced SCATterometer (ASCAT) on-board the Metop satellite series. Spatial patterns between median CR and ASCAT VOD correspond to each other and to vegetation patterns over Europe. Analysis of temporal correlation between CR and ASCAT VOD shows that high Pearson correlation coefficients (Rp) are found over croplands and grasslands (median Rp > 0.75). Over deciduous broadleaf forests, negative correlations are found. This is attributed to the effect of structural changes in the vegetation canopy which affect CR and ASCAT VOD in different ways. Additional analysis comparing CR to passive microwave-based VOD shows similar effects in deciduous broadleaf forests and high correlations over crop- and grasslands. Though the relationship between CR and VOD over deciduous forests is unclear, results suggest that CR is useful for monitoring vegetation dynamics over crop- and grassland and a potential path to high-resolution VOD.
Comparing the Assimilation of SMOS Brightness Temperatures and Soil Moisture Products on Hydrological Simulation in the Canadian Land Surface Scheme
Authors: Nambiar Manoj K. , Ambadan Jaison Thomas , Rowlandson Tracy , Bartlett Paul , Tetlock Erica , Berg Aaron A.
Published: October 2020

Soil moisture is a key variable used to describe water and energy exchanges at the land surface/atmosphere interface. Therefore, there is widespread interest in the use of soil moisture retrievals from passive microwave satellites. In the assimilation of satellite soil moisture data into land surface models, two approaches are commonly used. In the first approach brightness temperature (TB) data are assimilated, while in the second approach retrieved soil moisture (SM) data from the satellite are assimilated. However, there is not a significant body of literature comparing the differences between these two approaches, and it is not known whether there is any advantage in using a particular approach over the other. In this study, TB and SM L2 retrieval products from the Soil Moisture and Ocean Salinity (SMOS) satellite are assimilated into the Canadian Land Surface Scheme (CLASS), for improved soil moisture estimation over an agricultural region in Saskatchewan. CLASS is the land surface component of the Canadian Earth System Model (CESM), and the Canadian Seasonal and Interannual Prediction System (CanSIPS). Our results indicated that assimilating the SMOS products improved the soil moisture simulation skill of the CLASS. Near surface soil moisture assimilation also resulted in improved forecasts of root zone soil moisture (RZSM) values. Although both techniques resulted in improved forecasts of RZSM, assimilation of TB resulted in the superior estimates.
Rapid Determination of Nutrient Concentrations in Hass Avocado Fruit by Vis/NIR Hyperspectral Imaging of Flesh or Skin
Authors: Kämper Wiebke , Trueman Stephen J. , Tahmasbian Iman , Bai Shahla Hosseini
Published: October 2020

Fatty acid composition and mineral nutrient concentrations can affect the nutritional and postharvest properties of fruit and so assessing the chemistry of fresh produce is important for guaranteeing consistent quality throughout the value chain. Current laboratory methods for assessing fruit quality are time-consuming and often destructive. Non-destructive technologies are emerging that predict fruit quality and can minimise postharvest losses, but it may be difficult to develop such technologies for fruit with thick skin. This study aimed to develop laboratory-based hyperspectral imaging methods (400–1000 nm) for predicting proportions of six fatty acids, ratios of saturated and unsaturated fatty acids, and the concentrations of 14 mineral nutrients in Hass avocado fruit from 219 flesh and 194 skin images. Partial least squares regression (PLSR) models predicted the ratio of unsaturated to saturated fatty acids in avocado fruit from both flesh images (R2 = 0.79, ratio of prediction to deviation (RPD) = 2.06) and skin images (R2 = 0.62, RPD = 1.48). The best-fit models predicted parameters that affect postharvest processing such as the ratio of oleic:linoleic acid from flesh images (R2 = 0.67, RPD = 1.63) and the concentrations of boron (B) and calcium (Ca) from flesh images (B: R2 = 0.61, RPD = 1.51; Ca: R2 = 0.53, RPD = 1.71) and skin images (B: R2 = 0.60, RPD = 1.55; Ca: R2 = 0.68, RPD = 1.57). Many quality parameters predicted from flesh images could also be predicted from skin images. Hyperspectral imaging represents a promising tool to reduce postharvest losses of avocado fruit by determining internal fruit quality of individual fruit quickly from flesh or skin images.
Multidimensional Measures of Physical Activity and Their Association with Gross Motor Capacity in Children and Adolescents with Cerebral Palsy
Authors: Gerber Corinna N. , Carcreff Lena , Paraschiv-Ionescu Anisoara , Armand Stéphane , Newman Christopher J.
Published: October 2020

The current lack of adapted performance metrics leads clinicians to focus on what children with cerebral palsy (CP) do in a clinical setting, despite the ongoing debate on whether capacity (what they do at best) adequately reflects performance (what they do in daily life). Our aim was to measure these children’s habitual physical activity (PA) and gross motor capacity and investigate their relationship. Using five synchronized inertial measurement units (IMU) and algorithms adapted to this population, we computed 22 PA states integrating the type (e.g., sitting, walking, etc.), duration, and intensity of PA. Their temporal sequence was visualized with a PA barcode from which information about pattern complexity and the time spent in each of the six simplified PA states (PAS; considering PA type and duration, but not intensity) was extracted and compared to capacity. Results of 25 children with CP showed no strong association between motor capacity and performance, but a certain level of motor capacity seems to be a prerequisite for the achievement of higher PAS. Our multidimensional performance measurement provides a new method of PA assessment in this population, with an easy-to-understand visual output (barcode) and objective data for clinical and scientific use.
A Theoretical and Experimental Study of a Piezoelectric Pump with Two Elastic Chambers
Authors: Zhao Xiaolong , Zhao Dingxuan , Guo Qinghe
Published: October 2020

The paper is a continuation of our work on the dynamic load in piezoelectric pumps. In the study, the dynamic load of liquid in the pipelines was proposed as a key factor that limits the output performance of piezoelectric pumps. To decrease the dynamic load, a piezoelectric pump with two elastic chambers was proposed in our previous published work. In this paper, the performance and key parameters of the piezoelectric pump with two elastic chambers were studied through theoretical analyses and experimental tests. After establishing the mathematical model of the piezoelectric pump with two elastic chambers, the paper theoretically analyzed the performance of the pump and the effect of different structural parameters on the performance. Then prototypes with a range of structural parameters were developed and tested. As revealed from the test results, the elastic chamber effectively decreased the dynamic load of the liquid in the pipelines and the flow rate of the prototype with two elastic chambers was higher than that of the prototype with one or no elastic chamber. However, the elastic chamber did not lead to the increase in the maximum output backpressure of the prototype. Adopting an elastic diaphragm exhibiting a smaller stiffness or a larger diameter could help decrease the dynamic load of the liquid. The elastic chamber more significantly impacted the flow rate of the piezoelectric pump with long pipelines. The pump chamber height had a significant effect on the output performance of the piezoelectric pump with two elastic chambers, which is consistent with the conventional piezoelectric pump. At the height of 0.2 mm, the flow rate of the prototype with two elastic chambers was peaked at 7.7 mL/min; at the height of 0.05 mm, the output backpressure reached the highest of 28.2 kPa. The dynamic load could decrease the amplitude of the piezoelectric vibrator, whereas the prototype with two elastic chambers could effectively reduce the impact of dynamic load on the piezoelectric vibrator. The flow rate decreased almost linearly with the backpressure. Under the same backpressure, the flow rate of the prototype with two elastic chambers was higher than that of the prototype without elastic chamber, and the flow rate difference between the two prototypes gradually decreased with the backpressure.
Discriminative Sparse Filtering for Multi-Source Image Classification
Authors: Han Chao , Zhou Deyun , Yang Zhen , Xie Yu , Zhang Kai
Published: October 2020

Distribution mismatch caused by various resolutions, backgrounds, etc. can be easily found in multi-sensor systems. Domain adaptation attempts to reduce such domain discrepancy by means of different measurements, e.g., maximum mean discrepancy (MMD). Despite their success, such methods often fail to guarantee the separability of learned representation. To tackle this issue, we put forward a novel approach to jointly learn both domain-shared and discriminative representations. Specifically, we model the feature discrimination explicitly for two domains. Alternating discriminant optimization is proposed to obtain discriminative features with an l2 constraint in labeled source domain and sparse filtering is introduced to capture the intrinsic structures exists in the unlabeled target domain. Finally, they are integrated in a unified framework along with MMD to align domains. Extensive experiments compared with state-of-the-art methods verify the effectiveness of our method on cross-domain tasks.
Countering DDoS Attacks in SIP Based VoIP Networks Using Recurrent Neural Networks
Authors: Nazih Waleed , Hifny Yasser , Elkilani Wail S. , Dhahri Habib , Abdelkader Tamer
Published: October 2020

Many companies have transformed their telephone systems into Voice over IP (VoIP) systems. Although implementation is simple, VoIP is vulnerable to different types of attacks. The Session Initiation Protocol (SIP) is a widely used protocol for handling VoIP signaling functions. SIP is unprotected against attacks because it is a text-based protocol and lacks defense against the growing security threats. The Distributed Denial of Service (DDoS) attack is a harmful attack, because it drains resources, and prevents legitimate users from using the available services. In this paper, we formulate detection of DDoS attacks as a classification problem and propose an approach using token embedding to enhance extracted features from SIP messages. We discuss a deep learning model based on Recurrent Neural Networks (RNNs) developed to detect DDoS attacks with low and high-rate intensity. For validation, a balanced real traffic dataset was built containing three attack scenarios with different attack durations and intensities. Experiments show that the system has a high detection accuracy and low detection time. The detection accuracy was higher for low-rate attacks than that of traditional machine learning.
DNAzyme Sensor for the Detection of Ca2+ Using Resistive Pulse Sensing
Authors: Heaton Imogen , Platt Mark
Published: October 2020

DNAzymes are DNA oligonucleotides that can undergo a specific chemical reaction in the presence of a cofactor. Ribonucleases are a specific form of DNAzymes where a tertiary structure undergoes cleavage at a single ribonuclease site. The cleavage is highly specificity to co-factors, which makes them excellent sensor recognition elements. Monitoring the change in structure upon cleavage has given rise to many sensing strategies; here we present a simple and rapid method of following the reaction using resistive pulse sensors, RPS. To demonstrate this methodology, we present a sensor for Ca2+ ions in solution. A nanoparticle was functionalised with a Ca2+ DNAzyme, and it was possible to follow the cleavage and rearrangement of the DNA as the particles translocate the RPS. The binding of Ca2+ caused a conformation change in the DNAzyme, which was monitored as a change in translocation speed. A 30 min assay produced a linear response for Ca2+ between 1–9 μm, and extending the incubation time to 60 min allowed for a concentration as low as 0.3 μm. We demonstrate that the signal is specific to Ca2+ in the presence of other metal ions, and we can quantify Ca2+ in tap and pond water samples.
Influence of Toothed Rail Parameters on Impact Vibration Meshing of Mountainous Self-Propelled Electric Monorail Transporter
Authors: Liu Yue , Hong Tiansheng , Li Zhen
Published: October 2020

In order to reduce the vibration of mountain self-propelled electric monorail transporters (MSEMT) caused by the impact of the meshing of roller gear with toothed rail (MRGTR), and to improve the stability and safety of monorail transporters, this paper theoretically analyzed the MRGTR mechanism of toothed monorail transporters as well as established the MSEMT displacement model and its instantaneous velocity model. The vibration signals of MSEMT with four different parameters of toothed rail were collected by the acceleration sensor and signal acquisition system. The signals were analyzed by the Hilbert envelope demodulation method to investigate the influence of toothed rail parameters on meshing impact vibration. Moreover, taking the vibration acceleration amplitude of MSEMT and the vibration attenuation time of meshing impact as evaluation indexes, a test based on the three-factor and two-level orthogonal test was engaged with factors of toothed rail pressure angle, the ratio of L—the chord length of two adjacent roller centers of a roller gear—and rack pitch p (wheel-tooth ratio) and the load mass of the MSEMT. It showed that the impact of MRGTR was the main excitation source of the vibration of MSEMT. The pressure angle and wheel-tooth ratio both have a significant impact on the smooth operation of MSEMT, the latter to a greater extent. So did the interaction between wheel-tooth ratio and load mass. The amplitude of the characteristic frequency of the MSEMT decreased with the growth of the pressure angle. When the wheel-tooth ratio was cosα, the number of the characteristic frequency was less than that when it was 1, and the amplitude became smaller too. When the pressure angle was 15, the amplitude of vibration acceleration characteristic frequency decreased as a consequence of load mass increasing. At the pressure angle of 25, the amplitude of characteristic frequency decreased with the increase of load mass if the wheel-tooth ratio was 1, and the opposite result occurs in the case when the wheel-tooth ratio was cosα. This paper provides a theoretical basis and reference for improving the impact vibration of MRGTR and optimizing the design of the toothed rail.
A Portable Spectrometric System for Quantitative Prediction of the Soluble Solids Content of Apples with a Pre-calibrated Multispectral Sensor Chipset
Authors: Tran Nhut-Thanh , Fukuzawa Masayuki
Published: October 2020

A portable spectrometric system for nondestructive assessment of the soluble solids content (SSC) of fruits for practical applications has been proposed and its performance has been examined by an experiment on quantitative prediction of the SSC of apples. Although the spectroscopic technique is a powerful tool for predicting the internal qualities of fruits, its practical applications are limited due to its high cost and complexity. In the proposed system, the spectra of apples were collected by a simple optical setup with a cheap pre-calibrated multispectral chipset. An optimal multiple linear regression model with five wavebands at 900, 760, 730, 680, and 535 nm revealed the best performance with the coefficient of determination of prediction and the root mean square error of prediction of 0.861 and 0.403 °Brix, respectively, which was comparable to that of the previous studies using dispersive spectrometers. Compared with previously reported systems using discrete filters or light emitting diodes, the proposed system was superior in terms of manufacturability and reproducibility. The experimental results confirmed that the proposed system had a considerable potential for practical, cost-effective applications of the SSC prediction, not only for apples but also for other fruits.
Recognition of Pashto Handwritten Characters Based on Deep Learning
Authors: Amin Muhammad Sadiq , Yasir Siddiqui Muhammad , Ahn Hyunsik
Published: October 2020

Handwritten character recognition is increasingly important in a variety of automation fields, for example, authentication of bank signatures, identification of ZIP codes on letter addresses, and forensic evidence. Despite improved object recognition technologies, Pashto’s hand-written character recognition (PHCR) remains largely unsolved due to the presence of many enigmatic hand-written characters, enormously cursive Pashto characters, and lack of research attention. We propose a convolutional neural network (CNN) model for recognition of Pashto hand-written characters for the first time in an unrestricted environment. Firstly, a novel Pashto handwritten character data set, “Poha”, for 44 characters is constructed. For preprocessing, deep fusion image processing techniques and noise reduction for text optimization are applied. A CNN model optimized in the number of convolutional layers and their parameters outperformed common deep models in terms of accuracy. Moreover, a set of benchmark popular CNN models applied to Poha is evaluated and compared with the proposed model. The obtained experimental results show that the proposed model is superior to other models with test accuracy of 99.64 percent for PHCR. The results indicate that our model may be a strong candidate for handwritten character recognition and automated PHCR applications.
INS/CNS Deeply Integrated Navigation Method of Near Space Vehicles
Authors: Mu Rongjun , Sun Hongchi , Li Yuntian , Cui Naigang
Published: October 2020

Celestial navigation is required to improve the long-term accuracy preservation capability of near space vehicles. However, it takes a long time for traditional celestial navigation methods to identify the star map, which limits the improvement of the dynamic response ability. Meanwhile, the aero-optical effects caused by the near space environment can lead to the colorization of measurement noise, which affects the accuracy of the integrated navigation filter. In this paper, an INS/CNS deeply integrated navigation method, which includes a deeply integrated model and a second-order state augmented H-infinity filter, is proposed to solve these problems. The INS/CNS deeply integrated navigation model optimizes the attitude based on the gray image error function, which can estimate the attitude without star identification. The second-order state augmented H-infinity filter uses the state augmentation algorithm to whiten the measurement noise caused by the aero-optical effect, which can effectively improve the estimation accuracy of the H-infinity filter in the near space environment. Simulation results show that the proposed INS/CNS deeply integrated navigation method can reduce the computational cost by 50%, while the attitude accuracy is kept within 10” (3 σ). The attitude root mean square of the second-order state augmented H-infinity filter does not exceed 5”, even when the parameter error increases to 50%, in the near space environment. Therefore, the INS/CNS deeply integrated navigation method can effectively improve the rapid response ability of the navigation system and the filtering accuracy in the near space environment, providing a reference for the future design of near space vehicle navigation systems.