Search results for: deep soil mixing column

Authors: Jesse Silas Mshelia, Michael Mamman Degri, Akeweta Emmanuel Samaila

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This review was conducted in the North-Eastern part of Nigeria where there are a lot of challenges of poverty and low level of productivity of farmlands as a result of dwindling soil fertility and dependence on crops that are not so much adopted to the soil and climatic condition and the prevailing farming systems of the area which is predominantly mixed cropping. The crops that are neglected are well fitted into this system of production and yield better with the low level of input and management and give a higher profit margin. These crops, the farmers have mastered the production techniques, but do not have the scientific knowledge to improve the quality of the seed and the products hence need the intervention of modern technologies to benefit maximally from the full potentials of these crops.

Keywords: farming systems, neglected crops, potentials, underutilised

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Authors: Hamid Mohammadi, S. H. Eftekhar Afzali

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The irregular usage of chemical fertilizer cause different types of water and soil pollution and problems in health of human in past decades and organic fertilizer has been considered more and more. Mycorrhizal fungi have symbiosis with plant families and significantly effect on plant growth. Proper management of these symbiosis causes to reduce the usage of chemical fertilizers and absorb nutrition especially phosphor. Pistacia vera is endemic in Iran and is one of the most important products for this country. Considering special circumstances of pistachio orchards according to increasing salinity of water and soil and mismanagement of fertilizer reveals the necessity of the usage of Mycorrhizal fungi in these orchards.

Keywords: pistachio, mycorhiza, nutrition, salinity

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Authors: C. S. Jeba Samuel

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Soil, especially from oil field has posed a great hazard for terrestrial and marine ecosystems. The traditional treatment of oil contaminated soil cannot degrade the crude oil completely. So far, biodegradation proves to be an efficient method. During biodegradation, crude oil is used as the carbon source and addition of nitrogenous compounds increases the microbial growth, resulting in the effective breakdown of crude oil components to low molecular weight components. The present study was carried out to evaluate the biodegradation of crude oil by hydrocarbon-degrading microorganism Pseudomonas aeruginosa isolated from natural environment like oil contaminated soil. Pseudomonas aeruginosa, an oil degrading microorganism also called as hydrocarbon utilizing microorganism (or “HUM” bug) can utilize crude oil as sole carbon source. In this study, the biodegradation of crude oil was conducted with modified mineral basal salt medium and nitrogen sources so as to increase the degradation. The efficacy of the plasmid from the isolated strain was incorporated into E.coli DH5 α host to speed up the degradation of oil. The usage of molecular techniques has increased oil degradation which was confirmed by the degradation of aromatic and aliphatic rings of hydrocarbons and was inferred by the lesser number of peaks in Fourier Transform Infrared Spectroscopy (FTIR). The gas chromatogram again confirms better degradation by transformed cells by the lesser number of components obtained in the oil treated with transformed cells. This study demonstrated the technical feasibility of using direct inoculation of transformed cells onto the oil contaminated region thereby leading to the achievement of better oil degradation in a shorter time than the degradation caused by the wild strain.

Keywords: biodegradation, aromatic rings, plasmid, hydrocarbon, Fourier Transform Infrared Spectroscopy (FTIR)

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Authors: Neritan Shkodrani

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On November 26, 2019, an earthquake hit the central western part of Albania. It was assessed as Mw 6.4. Its epicenter was located offshore north western Durrës, about 7 km north of the city. In this paper, the consequences of settlements of very soft soils have been discussed for the case of a residential building, mentioned as “K Building”, which was suffering a significant tilting after the earthquake. “KBuilding” is an RC framed building having 12+1 (basement) storiesand a floor area of 21000 m2. The construction of the building was completed in 2012. “KBuilding”, located in Durres city, suffered severe non-structural damage during November 26, 2019, Durrës Earthquake sequences. During the in-site inspections immediately after the earthquake, the general condition of the buildings, the presence of observable settlements on the ground, and the crack situation in the structure were determined, and damage inspection were performed. It was significant to note that the “K Building” presented tilting that might be attributed, as it was believed at the beginning, partially to the failure of the columns of the ground floor and partially to liquefaction phenomena, but it did not collapse. At the first moment was not clear if the foundation had a bearing capacity failure or the foundation failed because of the soil liquefaction. Geotechnical soil investigations by using CPTU test were executed, and their data are usedto evaluatebearing capacity, consolidation settlement of the mat foundation, and soil liquefaction since they were believed to be the main reasons of this building tilting.Geotechnical soil investigation consist in 5 (five) Static Cone Penetration tests with pore pressure measurement (piezocone test). They reached a penetration depth of 20.0 m to 30.0 mand, clearly shown the presence of very soft and organic soils in the soil profile of the site. Geotechnical CPT based analysis of bearing capacity, consolidation, and secondary settlement are applied, and results are reported for each test. These results shown very small values of allowable bearing capacity and very high values of consolidation and secondary settlements. Liquefaction analysis based on the data of CPTU tests and the characteristics of ground shaking of the mentioned earthquake has shown the possibility of liquefaction for some layers of the considered soil profile, but the estimated vertical settlements are at a small range and clearly shown that the main reason of the building tilting was not related to the consequences of liquefaction, but was an existing settlement caused from the applied bearing pressure of this building. All the CPTU tests were carried out on August 2021, almost two years after the November 26, 2019, Durrës Earthquake and when the building itself was demolished. After removing the mat foundation on September 2021, it was possible to carry out CPTU tests even on the footprint of the existing building, which made possible to observe the effects of long time applied of foundation bearing pressure to the consolidation on the considered soil profile.

Keywords: bearing capacity, cone penetration test, consolidation settlement, secondary settlement, soil liquefaction, etc

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Authors: Thidarat Duangyod, Chanida Palanuvej, Nijsiri Ruangrungsi

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Pentace burmanica Kurz., belonging to the Malvaceae family, is commonly used for anti-diarrhea in Thai traditional medicine. A method for quantification of (+)-catechin and (-)-epicatechin in P. burmanica stem bark from 12 different Thailand markets by reverse-phase high performance liquid chromatography (HPLC) was investigated and validated. The analysis was performed by a Shimadzu DGU-20A3 HPLC equipped with a Shimadzu SPD-M20A photo diode array detector. The separation was accomplished with an Inersil ODS-3 column (5 µm x 4.6 x 250 mm) using 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B) as mobile phase at the flow rate of 1 ml/min. The isocratic was set at 20% B for 15 min and the column temperature was maintained at 40 ºC. The detection was at the wavelength of 280 nm. Both (+)-catechin and (-)-epicatechin existed in the ethanolic extract of P. burmanica stem bark. The content of (-)-epicatechin was found as 59.74 ± 1.69 µg/mg of crude extract. In contrast, the quantitation of (+)-catechin content was omitted because of its small amount. The method was linear over a range of 5-200 µg/ml with good coefficients (r2 > 0.99) for (+)-catechin and (-)-epicatechin. Limit of detection values were found to be 4.80 µg/ml for (+)-catechin and 5.14 µg/ml for (-)-epicatechin. Limit of quantitation of (+)-catechin and (-)-epicatechin were of 14.54 µg/ml and 15.57 µg/ml respectively. Good repeatability and intermediate precision (%RSD < 3) were found in this study. The average recoveries of both (+)-catechin and (-)-epicatechin were obtained with good recovery in the range of 91.11 – 97.02% and 88.53 – 93.78%, respectively, with the %RSD less than 2. The peak purity indices of catechins were more than 0.99. The results suggested that HPLC method proved to be precise and accurate and the method can be conveniently used for (+)-catechin and (-)-epicatechin determination in ethanolic extract of P. burmanica stem bark. Moreover, the stem bark of P. burmanica was found to be a rich source of (-)-epicatechin.

Keywords: pentace burmanica, (+)-catechin, (-)-epicatechin, high performance liquid chromatography

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Authors: Mathodzi Nditsheni, Olawole Emmanuel Aina, Joshua Oluwole Olowoyo

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The ever-increasing world population is putting extreme pressure on the already limited agricultural resources for food production. Different soil enhancers were introduced by famers to meet the need of the ever-increasing population demand for food. One of the soil enhancers is the municipal waste sludge. This research investigated the differences in the concentrations of trace metals and levels of phytochemicals in four different tomato varieties cultivated on soil treated with municipal waste sludge in Pretoria, South Africa. Fruits were harvested at maturity and analyzed for trace metals and phytochemicals contents using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and a High-Performance Liquid Chromatography (HPLC) respectively. A one-way analysis of variance (ANOVA) was used to determine the differences in the concentrations of trace metals and phytochemical from different tomato varieties were significant. From the study, Rodade tomato bioaccumulated the highest concentrations of Mn, Cr, Cu and Ni, Roma bioaccumulated the highest concentrations of, Cd, Fe and Pb while Heinz bioaccumulated the highest concentrations of As and Zn. Cherry tomato on the other hand, recorded the lowest concentrations for most metals, Cd, Cr, Cu, Mn, Ni, Pb and Zn. The results of the study further showed that phenolic and flavonoids content were higher in the Solanum lycopersicum fruit grown in soils treated with municipal waste sludge. The study also showed that there was an inverse relationship between the levels of trace metals and phytochemicals. The calculated contamination factor values of trace metals like Cr, Cu, Pb and Zn were above the safe value of 1 which indicated that the tomato fruits may be unsafe for human consumption. However, the contamination factor values for the remaining trace metals were well below the safe value of 1. From the results obtained either for the control group or the treatment, the tomato varieties used in the study, bioaccumulated the toxic trace metals in their fruits and some of the values obtained were higher than the acceptable limit, which may then imply that the varieties of tomato used in this study bio accumulated the toxic trace metals from the soil, hence care should be taken when these tomato varieties are either cultivated or harvested from polluted areas

Keywords: trace metals, flavonoids, phenolics, waste sludge, tomato, contamination factors

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Authors: V. Rangarajan, Priyanka Kaushal

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This study investigates the effectiveness of a typical Earth Air Heat Exchanger (EATHE) for energy efficient space cooling in an urban environment typified by space and soil-related constraints that preclude an optimal design. It involves the development of a three-dimensional numerical transient model that is validated by measurements at a live site in India. It is found that the model accurately predicts the soil temperatures at various depths as well as the EATHE outlet air temperature. The study shows that such an EATHE, even when designed under constraints, does provide effective space cooling especially during the hot months of the year.

Keywords: earth air heat exchanger (EATHE), India, MATLAB, model, simulation

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Authors: André C. Silva, Mariana R. Barros, Elenice M. S. Silva, Douglas. Y. Marinho, Diego F. Lopes, Débora N. Sousa, Raphael S. Tomáz

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Modern agriculture requires productivity, efficiency and quality. Therefore, there is need for agricultural limestone implementation that provides adequate amounts of calcium and magnesium carbonates in order to correct soil acidity. During the limestone process, fine particles (with average size under 400#) are generated. These particles do not have economic value in agricultural and metallurgical sectors due their size. When limestone is used for agriculture purposes, these fine particles can be easily transported by wind generated air pollution. Therefore, briquetting, a mineral processing technique, was used to mitigate this problem resulting in an agglomerated product suitable for agriculture use. Briquetting uses compressive pressure to agglomerate fine particles. It can be aided by agglutination agents, allowing adjustments in shape, size and mechanical parameters of the mass. Briquettes can generate extra profits for mineral industry, presenting as a distinct product for agriculture, and can reduce the environmental liabilities of the fine particles storage or disposition. The produced limestone briquettes were subjected to shatter and water action resistance tests. The results show that after six minutes completely submerged in water, the briquettes where fully diluted, a highly favorable result considering its use for soil acidity correction.

Keywords: agglomeration, briquetting, limestone, soil acidity correction

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Authors: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

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Rangelands in semi-arid areas provide a good source for feeding huge numbers of animals and serving environmental, economic and social importance; therefore, these areas are considered economically very important for the pastoral sector in Sudan. This paper investigates the means of differentiating between different rangelands sites according to soil types using principal component analysis to assist in monitoring and assessment purposes. Three rangeland sites were identified in the study area as flat sandy sites, sand dune site, and hard clay site. Principal component analysis (PCA) was used to reduce the number of factors needed to distinguish between rangeland sites and produce a new set of data including the most useful spectral information to run satellite image processing. It was performed using selected types of data (two vegetation indices, topographic data and vegetation surface reflectance within the three bands of MODIS data). Analysis with PCA indicated that there is a relatively high correspondence between vegetation and soil of the total variance in the data set. The results showed that the use of the principal component analysis (PCA) with the selected variables showed a high difference, reflected in the variance and eigenvalues and it can be used for differentiation between different range sites.

Keywords: principal component analysis, PCA, rangeland sites, semi-arid areas, soil types

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Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

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Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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Authors: Jyh Sheen, Yong-Lin Wang

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This research dedicates to find a different measurement procedure of microwave dielectric properties of ceramic materials with high dielectric constants. For the composite of ceramic dispersed in the polymer matrix, the dielectric constants of the composites with different concentrations can be obtained by various mixture equations. The other development of mixture rule is to calculate the permittivity of ceramic from measurements on composite. To do this, the analysis method and theoretical accuracy on six basic mixture laws derived from three basic particle shapes of ceramic fillers have been reported for dielectric constants of ceramic less than 40 at microwave frequency. Similar researches have been done for other well-known mixture rules. They have shown that both the physical curve matching with experimental results and low potential theory error are important to promote the calculation accuracy. Recently, a modified of mixture equation for high dielectric constant ceramics at microwave frequency has also been presented for strontium titanate (SrTiO3) which was selected from five more well known mixing rules and has shown a good accuracy for high dielectric constant measurements. However, it is still not clear the accuracy of this modified equation for other high dielectric constant materials. Therefore, the five more well known mixing rules are selected again to understand their application to other high dielectric constant ceramics. The other high dielectric constant ceramic, TiO2 with dielectric constant 100, was then chosen for this research. Their theoretical error equations are derived. In addition to the theoretical research, experimental measurements are always required. Titanium dioxide is an interesting ceramic for microwave applications. In this research, its powder is adopted as the filler material and polyethylene powder is like the matrix material. The dielectric constants of those ceramic-polyethylene composites with various compositions were measured at 10 GHz. The theoretical curves of the five published mixture equations are shown together with the measured results to understand the curve matching condition of each rule. Finally, based on the experimental observation and theoretical analysis, one of the five rules was selected and modified to a new powder mixture equation. This modified rule has show very good curve matching with the measurement data and low theoretical error. We can then calculate the dielectric constant of pure filler medium (titanium dioxide) by those mixing equations from the measured dielectric constants of composites. The accuracy on the estimating dielectric constant of pure ceramic by various mixture rules will be compared. This modified mixture rule has also shown good measurement accuracy on the dielectric constant of titanium dioxide ceramic. This study can be applied to the microwave dielectric properties measurements of other high dielectric constant ceramic materials in the future.

Keywords: microwave measurement, dielectric constant, mixture rules, composites

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Authors: M. Agostini, A. Sonato, G. Greco, M. Travagliati, G. Ruffato, E. Gazzola, D. Liuni, F. Romanato, M. Cecchini

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Since their first demonstration in the early 1980s, surface plasmon resonance (SPR) sensors have been widely recognized as useful tools for detecting chemical and biological species, and the interest of the scientific community toward this technology has known a rapid growth in the past two decades owing to their high sensitivity, label-free operation and possibility of real-time detection. Recent works have suggested that a turning point in SPR sensor research would be the combination of SPR strategies with other technologies in order to reduce human handling of samples, improve integration and plasmonic sensitivity. In this light, microfluidics has been attracting growing interest. By properly designing microfluidic biochips it is possible to miniaturize the analyte-sensitive areas with an overall reduction of the chip dimension, reduce the liquid reagents and sample volume, improve automation, and increase the number of experiments in a single biochip by multiplexing approaches. However, as the fluidic channel dimensions approach the micron scale, laminar flows become dominant owing to the low Reynolds numbers that typically characterize microfluidics. In these environments mixing times are usually dominated by diffusion, which can be prohibitively long and lead to long-lasting biochemistry experiments. An elegant method to overcome these issues is to actively perturb the liquid laminar flow by exploiting surface acoustic waves (SAWs). With this work, we demonstrate a new approach for SPR biosensing based on the combination of microfluidics, SAW-induced mixing and the real-time phase-interrogation grating-coupling SPR technology. On a single lithium niobate (LN) substrate the nanostructured SPR sensing areas, interdigital transducer (IDT) for SAW generation and polydimethylsiloxane (PDMS) microfluidic chambers were fabricated. SAWs, impinging on the microfluidic chamber, generate acoustic streaming inside the fluid, leading to chaotic advection and thus improved fluid mixing, whilst analytes binding detection is made via SPR method based on SPP excitation via gold metallic grating upon azimuthal orientation and phase interrogation. Our device has been fully characterized in order to separate for the very first time the unwanted SAW heating effect with respect to the fluid stirring inside the microchamber that affect the molecules binding dynamics. Avidin/biotin assay and thiol-polyethylene glycol (bPEG-SH) were exploited as model biological interaction and non-fouling layer respectively. Biosensing kinetics time reduction with SAW-enhanced mixing resulted in a ≈ 82% improvement for bPEG-SH adsorption onto gold and ≈ 24% for avidin/biotin binding—≈ 50% and 18% respectively compared to the heating only condition. These results demonstrate that our biochip can significantly reduce the duration of bioreactions that usually require long times (e.g., PEG-based sensing layer, low concentration analyte detection). The sensing architecture here proposed represents a new promising technology satisfying the major biosensing requirements: scalability and high throughput capabilities. The detection system size and biochip dimension could be further reduced and integrated; in addition, the possibility of reducing biological experiment duration via SAW-driven active mixing and developing multiplexing platforms for parallel real-time sensing could be easily combined. In general, the technology reported in this study can be straightforwardly adapted to a great number of biological system and sensing geometry.

Keywords: biosensor, microfluidics, surface acoustic wave, surface plasmon resonance

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Authors: Manfred Szerencsits, Christine Weinberger, Maximilian Kuderna, Franz Feichtinger, Eva Erhart, Stephan Maier

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Cover or catch crops have beneficial effects for soil, water, erosion, etc. If harvested, they also provide feedstock for biogas without competition for arable land in regions, where only one main crop can be produced per year. On average gross energy yields of approx. 1300 m³ methane (CH₄) ha^-1 can be expected from 4.5 tonnes (t) of cover crop dry matter (DM) in Austria. Considering the total energy invested from cultivation to compression for biofuel use a net energy yield of about 1000 m³ CH₄ ha^-1 is remaining. With the straw of grain maize or Corn Cob Mix (CCM) similar energy yields can be achieved. In comparison to catch crops remaining on the field as green manure or to complete fallow between main crops the effects on soil, water and climate can be improved if cover crops are harvested without soil compaction and digestate is returned to the field in an amount equivalent to cover crop removal. In this way, the risk of nitrate leaching can be reduced approx. by 25% in comparison to full fallow. The risk of nitrous oxide emissions may be reduced up to 50% by contrast with cover crops serving as green manure. The effects on humus content and erosion are similar or better than those of cover crops used as green manure when the same amount of biomass was produced. With higher biomass production the positive effects increase even if cover crops are harvested and the only digestate is brought back to the fields. The ecological footprint of arable farming can be reduced by approx. 50% considering the substitution of natural gas with CH₄ produced from cover crops.

Keywords: biogas, cover crops, catch crops, land use competition, sustainable agriculture

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Authors: F. Zouai, F. Z. Benabid, S. Bouhelal, D. Benachour

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Reinforced plastics or nanocomposites have attracted considerable attention in scientific and industrial fields because a very small amount of clay can significantly improve the properties of the polymer. The polymeric matrices used in this work are two saturated polyesters, i.e., polyethylene terephthalate (PET) and polyethylene naphthalate (PEN). The success of processing compatible blends, based on poly(ethylene terephthalate) (PET)/poly(ethylene naphthalene) (PEN)/clay nanocomposites in one step by reactive melt extrusion is described. Untreated clay was first purified and functionalized ‘in situ’ with a compound based on an organic peroxide/ sulfur mixture and (tetramethylthiuram disulfide) as the activator for sulfur. The PET and PEN materials were first separately mixed in the molten state with functionalized clay. The PET/4 wt% clay and PEN/7.5 wt% clay compositions showed total exfoliation. These compositions, denoted nPET and nPEN, respectively, were used to prepare new n(PET/PEN) nanoblends in the same mixing batch. The n(PET/PEN) nanoblends were compared to neat PET/PEN blends. The blends and nanocomposites were characterized using various techniques. Microstructural and nanostructural properties were investigated. Fourier transform infrared spectroscopy (FTIR) results showed that the exfoliation of tetrahedral clay nanolayers is complete, and the octahedral structure totally disappears. It was shown that total exfoliation, confirmed by wide-angle X-ray scattering (WAXS) measurements, contributes to the enhancement of impact strength and tensile modulus. In addition, WAXS results indicated that all samples are amorphous. The differential scanning calorimetry (DSC) study indicated the occurrence of one glass transition temperature Tg, one crystallization temperature Tc and one melting temperature Tm for every composition.

Keywords: exfoliation, DRX, DSC, montmorillonite, nanocomposites, PEN, PET, plastograph, reactive melt-mixing

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Praveen Chandramenon, Andrew Gascoyne, Fideline Tchuenbou-Magaia

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Aquaponics offers a simple conclusive solution to the food and environmental crisis of the world. This approach combines the idea of Aquaculture (growing fish) to Hydroponics (growing vegetables and plants in a soilless method). Smart Aquaponics explores the use of smart technology including artificial intelligence and IoT, to assist farmers with better decision making and online monitoring and control of the system. Identification of different growth stages of Swiss Chard plants and predicting its harvest time is found to be important in Aquaponic yield management. This paper brings out the comparative analysis of a standard Aquaponics with a Vermiponics (Aquaponics with worms), which was grown in the controlled environment, by implementing IoT and deep learning-based growth stage segregation and harvest time prediction of Swiss Chards before and after applying an optimal freshwater replenishment. Data collection, Growth stage classification and Harvest Time prediction has been performed with and without water replenishment. The paper discusses the experimental design, IoT and sensor communication with architecture, data collection process, image segmentation, various regression and classification models and error estimation used in the project. The paper concludes with the results comparison, including best models that performs growth stage segregation and harvest time prediction of the Aquaponic and Vermiponic testbed with and without freshwater replenishment.

Keywords: aquaponics, deep learning, internet of things, vermiponics

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Authors: A. A. Embaby, A. Abu Halawa, M. Ramadan

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In Kingdom of Saudi Arabia, there are several areas where expansive soil exists in the form of variable-thicknesses layers in the developed regions. Severe distress to infrastructures can be caused by the development of heave and swelling pressure in this kind of expansive shale. Among the various techniques for expansive soil mitigation, the removal and replacement technique is very popular for lightly loaded structures and shallow foundations. This paper presents the result of an experimental study conducted for evaluating the effect of type and thickness of the cushion soils on mitigation of swelling characteristics of expanded shale. Seven undisturbed shale samples collected from Al Qadsiyah district, which is located in the Tabuk town north Kingdom of Saudi Arabia, are treated with two types of cushion coarse-grained sediments (CCS); sand and gravel. Each type is represented with three thicknesses, 22%, 33% and 44% in relation to the depth of the active zone. The test results indicated that the replacement of expansive shale by CCS reduces the swelling potential and pressure. It is found that the reduction in swelling depends on the type and thickness of CCS. The treatment by removing the original expansive shale and replacing it by cushion sand with 44% thickness reduced the swelling potential and pressure of about 53.29% and 62.78 %, respectively.

Keywords: cushion coarse-grained sediments (CCS), expansive soil, Saudi Arabia, swelling pressure, Tabuk Shale

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Authors: S. K. Gali

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Spentwash, An effluent of distillery is an environmental pollutant because of its high load of pollutants (pH: 2-4; BOD>40,000 mg/l, COD>100,000mg/l and TDS >70,000mg/l). But However, after subjecting it to primary treatment (bio-methanation), Its pollutant load gets drastically reduced (pH: 7.5-8.5, BOD<10,000 mg/l) and could be disposed off safely as a source of organic matter and plant nutrients for crop production. With the consent of State Pollution Control Board, the distilleries in Karnataka are taking up ‘one time controlled land application’ of bio-methanated spentwash in farmers’ fields. A monitoring study was undertaken in Belgaum district of Karnataka State with an objective of studying the effect of land application of bio-methanated spent wash of a distillery on soil properties and crop growth. The treated spentwash was applied uniformly to the fallow dry lands in different farmers’ fields during summer, 2012 at recommended rate (based on nitrogen requirement of crops). The application was made at least a fortnight before sowing/planting operations. The analysis of soils collected before land application of spentwash and after harvest of crops revealed that there was no adverse effect of applied spentwash on soil characteristics. A slight build up in soluble salts was observed but, however all the soils recorded EC of less than 2.0 dSm-1. An increase in soil organic carbon (SOC) and available nitrogen (N) by about 10 to 30 % was observed in the spentwash applied soils. The presence of good amount of biodegradable organics in the treated spentwash (BOD of 6550 mg/l) contributed for increase in SOC and N. A substantial build up in available potassium (K) status (50 to 200%) was observed due to spentwash application. This was attributed to the high K content in spentwash (6950 mg/l). The growth of crops in the spentwash applied fields was higher and farmers could get nearly 10 to 20 per cent higher yields, especially in sugarcane and corn. The analysis of ground water samples showed that the quality of water was not affected due to land application of treated spentwash. Apart from realizing higher crop yields, the farmers were able to save money on N and K fertilisers as the applied spentwash met the crop requirement. Hence, it could be concluded that the bio-methanated distillery spentwash can be gainfully utilized in crop production without polluting the environment.

Keywords: bio-methanation, pollutant, potassium status, soil organic carbon

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Authors: W. Meron Mebrahtu, R. Absi

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Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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Authors: Lukáš Plošek, Jaroslav Hynšt, Jaroslav Záhora, Jakub Elbl, Antonín Kintl, Ivana Charousová, Silvia Kovácsová

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Compost can influence soil fertility and plant health. At the same time compost can play an important role in the nitrogen cycle and it can influence leaching of mineral nitrogen from soil to underground water. This paper deals with the influence of compost addition and mineral nitrogen fertilizer on leaching of mineral nitrogen, nitrogen availability in microbial biomass and plant biomass production in the lysimetric experiment. Twenty-one lysimeters were filed with topsoil and subsoil collected in the area of protection zone of underground source of drinking water - Březová nad Svitavou. The highest leaching of mineral nitrogen was detected in the variant fertilized only mineral nitrogen fertilizer (624.58 mg m-2), the lowest leaching was recorded in the variant with high addition of compost (315.51 mg m-2). On the other hand, losses of mineral nitrogen are not in connection with the losses of available form of nitrogen in microbial biomass. Because loss of mineral nitrogen was detected in variant with the least change in the availability of N in microbial biomass. The leaching of mineral nitrogen, yields as well as the results concerning nitrogen availability from the first year of long term experiment suggest that compost can positive influence the leaching of nitrogen into underground water.

Keywords: nitrogen, compost, biomass production, lysimeter

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Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

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One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

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Authors: J. N. Anene, A. A. Bello, C. C. Anene

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The paper carried out a comparative study of the challenges of e-learning in Nigerian universities. The purpose of the study was to determine if there was a significant difference in the challenges faced by students in e-learning in Nigerian Universities. A total of two hundred and twenty-eight students from nine universities constituted the sample for the study. A simple random sampling technique was employed in selecting thirty–two students from one of each university in the six geo-political zones of Nigeria. The questionnaire based on 'yes or no' and column charts constituted the instrument employed in the study. Percentages were used to analyse 'yes or no' while column charts were used to compare responds of the students. The finding of the study revealed that majority of students in all the universities under study claimed that their universities lacked appropriate software, that good quality educational content online was lacking, they also agreed that sustainability of e-learning was not prioritized, that they had no access to appropriate content for ICT-enhanced learning and training and that they had access to affordable and reliable computers. For lecturers, the computer certification should be the first on the list of promotion requirements. The finding of the study revealed that students from seven out of nine universities confirmed that their universities lack of appropriate software whereas the other two claimed that they have appropriate software. Also, out of nine universities, two disagreed to the fact that good quality educational content online lacked, whereas seven agreed that they lacked good quality educational content online. The finding of the study also revealed that most of the respondents in almost all the university under study agreed that sustainability of e-learning was not prioritized. The study recommended among other that the Nigerian Government should make concerted effort to provide the enablement for all lecturers and students to become computer literate. This should be done within a time frame, and at the end of the computer course, certificates should be issued, and no student should graduate in his or her field of study without passing the computer course.

Keywords: e-learning, developing countries, computer literacy, ICT

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Authors: Mohammad Moridzadeh, Gholamreza Mesri

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The effectiveness of lime treatment of soils has been commonly evaluated in terms of improved workability and increased undrained unconfined compressive strength in connection to road and airfield construction. The most common method of strength measurement has been the unconfined compression test. However, if the objective of lime treatment is to improve long-term stability of first-time or reactivated landslides in stiff clays and shales, permanent changes in the size and shape of clay particles must be realized to increase drained frictional resistance. Lime-soil interactions that may produce less platy and larger soil particles begin and continue with time under the highly alkaline pH environment. In this research, pH measurements are used to monitor chemical environment and progress of reactions. Atterberg limits are measured to identify changes in particle size and shape indirectly. Also, fully softened and residual strength measurements are used to examine an improvement in frictional resistance due to lime-soil interactions. The main variables are soil plasticity and mineralogy, lime content, water content, and curing period. Lime effect on frictional resistance is examined using samples of clays with different mineralogy and characteristics which may react with lime to various extents. Drained direct shear tests on reconstituted lime-treated clay specimens with various properties have been performed to measure fully softened shear strength. To measure residual shear strength, drained multiple reversal direct shear tests on precut specimens were conducted. This way, soil particles are oriented along the direction of shearing to the maximum possible extent and provide minimum frictional resistance. This is applicable to reactivated and part of first-time landslides. The Brenna clay, which is the highly plastic lacustrine clay of Lake Agassiz causing slope instability along the banks of the Red River, is one of the soil samples used in this study. The Brenna Formation characterized as a uniform, soft to firm, dark grey, glaciolacustrine clay with little or no visible stratification, is full of slickensided surfaces. The major source of sediment for the Brenna Formation was the highly plastic montmorillonitic Pierre Shale bedrock. The other soil used in this study is one of the main sources of slope instability in Harris County Flood Control District (HCFCD), i.e. the Beaumont clay. The shear strengths of untreated and treated clays were obtained under various normal pressures to evaluate the shear envelope nonlinearity.

Keywords: Brenna clay, friction resistance, lime treatment, residual

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Yasir Arafat, Asma Shah, Hua Shao

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Background and Aims: Legume/cereal intercropping is used worldwide for enhancement in biomass and yield of cereal crops. However, because of intercropping, the belowground biological and chemical interactions and their effect on physiological parameters and yield of crops are limited. Methods: Wheat faba bean (WF) intercropping was designed to understand the underlying changes in the soil's chemical environment, soil microbial communities, and effect on growth and yield parameters. Experimental plots were established as having no root partition (NRP), semi-root partition (SRP), complete root partition (CRP), and their sole cropping (CK). Low molecular weight organic acids (LMWOAs) were determined by GC-MS, and high throughput sequencing of the 16S rRNA gene was carried out to screen microbial structure and composition in different root partitions of the WF intercropping system. Results: We show that intercropping induced a shift in the relative abundance of some genera of plant growth promoting rhizobacteria (PGPR) such as Allorhizobium, Neorhizobium, Pararhizobium, and Rhizobium species and resulted in better growth and yield performance of wheat. Moreover, as the plant's distance of wheat from faba beans decreased, the diversity of microbes increased, and a positive effect was observed on physiological traits and crop yield. Furthermore, an abundance and positive correlations of palmitic acid, arachidic acid, stearic acid, and 9-Octadecenoic with PGPR were recorded in the root zone of WF intercropping, which can play an important role in this facilitative mechanism of enhancing growth and yield of cereals. Conclusion: The two treatments clearly affected soil microbial and chemical composition, which can be reflected in growth and yield enhancement.

Keywords: intercropping, microbial community, LMWOAs, PGPR, soil chemical environment

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Authors: Reda Abdel-Aziz

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Agricultural activities in Egypt generate annually around 35 million tons of waste. Composting is one of the most promising technologies to turnover waste in a more economical way, for many centuries. Composting has been used as a mean of recycling organic matter back into the soil to improve soil structure and fertility. Field experiments were conducted in two governorates, Giza and Al-Monofia, to find out the effect of compost with different rates of chemical fertilizers on growth and yield of corn (Zea mays L.) during two constitutive seasons of 2012 and 2013. The experiment, laid out in a randomized complete block design (RCBD), was carried out on five farmers’ fields in each governorate. The treatments were: unfertilized control, full dose of NPK (120, 30, and 50 kg/acre, respectively), compost at rate of 20 ton/acre, compost at rate of 10 ton/acre + 25% of chemical fertilizer, compost at rate of 10 ton/acre + 50% of chemical fertilizer and compost at rate of 10 ton/acre + 75% of chemical fertilizer. Results revealed a superiority of the treatment of compost at rate of 10 ton/acre + 50% of NPK that caused significant improvement in growth, yield and nutrient uptakes of corn in the two governorates during the two constitutive seasons. Results showed that agricultural waste could be composted into value added soil amendment to enhance efficiency of chemical fertilizer. Composting of agricultural waste could also reduce the chemical fertilizers potential hazard to the environment.

Keywords: agricultural waste, compost, chemical fertilizers, corn production, environment

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Edina Koch, Károly Gombás, Márton Maller

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The Little Plain is located along the Danube river, and this area is a “hotbed” of sand boil formation. This is due to the combination of a 100-250 m thick gravel layer beneath the Little Plain with a relatively thin blanket of poor soil spreading the gravel with variable thickness. Sand boils have a tradition and history in this area. It was possible to know which sand boil started and stopped working at what water level, and some of them even have names. The authors present a 2D finite element model of groundwater flow through a selected cross-section of the Danube river, which observed activation of piping phenomena during the 2013 flood event. Soil parametrization is based on a complex site investigation program conducted along the Danube River in the Little Plain.

Keywords: site characterization, groundwater flow, numerical modeling, sand boil

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