Necessity of Risk Management of Various Industry-Associated Pollutants(Case Study of Gavkhoni Wetland Ecosystem)

Since the beginning of human history, human activities have caused many changes in the environment. Today, a particular attention should be paid to gaining knowledge about water quality of wetlands which are pristine natural environments rich in genetic reserves. If qualitative conditions of industrial areas (in terms of both physicochemical and biological conditions) are not addressed properly, they could cause disruption in natural ecosystems, especially in rivers. With regards to the quality of water resources, determination of pollutant sources plays a pivotal role in engineering projects as well as designing water quality control systems. Thus, using different methods such as flow duration curves, dischargepollution load model and frequency analysis by HYFA software package, risk of various industrial pollutants in international and ecologically important Gavkhoni wetland is analyzed. In this study, a station located at Varzaneh City is used as the last station on Zayanderud River, from where the river water is discharged into the wetland. Results showed that elements- concentrations often exceeded the allowed level and river water can endanger regional ecosystem. In addition, if the river discharge is managed on Q25 basis, this basis can lower concentrations of elements, keeping them within the normal level.

A Simulator for Robot Navigation Algorithms

A robot simulator was developed to measure and investigate the performance of a robot navigation system based on the relative position of the robot with respect to random obstacles in any two dimensional environment. The presented simulator focuses on investigating the ability of a fuzzy-neural system for object avoidance. A navigation algorithm is proposed and used to allow random navigation of a robot among obstacles when the robot faces an obstacle in the environment. The main features of this simulator can be used for evaluating the performance of any system that can provide the position of the robot with respect to obstacles in the environment. This allows a robot developer to investigate and analyze the performance of a robot without implementing the physical robot.

Effect of Natural Animal Fillers on Polymer Rheology Behaviour

This paper deals with the evaluation of flow properties of polymeric matrix with natural animal fillers. Technical university of Liberec cooperates on the long-term development of “green materials“ that should replace conventionally used materials (especially in automotive industry). Natural fibres (of animal and plant origin) from all over the world are collected and adapted (drying, cutting etc.) for extrusion processing. Inside the extruder these natural additives are blended with polymeric (synthetic and biodegradable - PLA) matrix and created compound is subsequently cut for pellets in the wet way. These green materials with unique recipes are then studied and their mechanical, physical and processing properties are determined. The main goal of this research is to develop new ecological materials very similar to unfilled polymers. In this article the rheological behaviour of chosen natural animal fibres is introduced considering their shape and surface that were observed with use of SEM microscopy.

Application of Exact String Matching Algorithms towards SMILES Representation of Chemical Structure

Bioinformatics and Cheminformatics use computer as disciplines providing tools for acquisition, storage, processing, analysis, integrate data and for the development of potential applications of biological and chemical data. A chemical database is one of the databases that exclusively designed to store chemical information. NMRShiftDB is one of the main databases that used to represent the chemical structures in 2D or 3D structures. SMILES format is one of many ways to write a chemical structure in a linear format. In this study we extracted Antimicrobial Structures in SMILES format from NMRShiftDB and stored it in our Local Data Warehouse with its corresponding information. Additionally, we developed a searching tool that would response to user-s query using the JME Editor tool that allows user to draw or edit molecules and converts the drawn structure into SMILES format. We applied Quick Search algorithm to search for Antimicrobial Structures in our Local Data Ware House.

The Chemical Composition of Yoghurt Enriched with Flakes from Biologically Activated Hullless Barley Grain and Malt Extract

The influence of flakes from biologically activated hull-less barley grain and malt extract on chemical composition of yoghurt was studied. Pasteurized milk, freeze-dried yoghurt culture YF-L811 (Chr. Hansen, Denmark), flakes from biologically activated hull-less barley grain (Latvia) and malt extract (Ilgezeem, Latvia) were used for experiments. Yoghurt samples with and without flakes from biologically activated hull-less barley grain and malt extract were analyzed for content of total solids, total proteins, fats, amino acids and riboflavin. The addition of flakes from biologically activated hull-less barley grain and malt extract allowed increase of nutritional value of yoghurt samples. There was obtained the increase of total proteins (p>0.05) and the decrease of fat (p>0.05). The presence of flakes from biologically activated hull-less barley grain and malt extract in yoghurt samples provided significant increase of amino acids amount (p

Influence of Paralleled Capacitance Effect in Well-defined Multiple Value Logical Level System with Active Load

Three similar negative differential resistance (NDR) profiles with both high peak to valley current density ratio (PVCDR) value and high peak current density (PCD) value in unity resonant tunneling electronic circuit (RTEC) element is developed in this paper. The PCD values and valley current density (VCD) values of the three NDR curves are all about 3.5 A and 0.8 A, respectively. All PV values of NDR curves are 0.40 V, 0.82 V, and 1.35 V, respectively. The VV values are 0.61 V, 1.07 V, and 1.69 V, respectively. All PVCDR values reach about 4.4 in three NDR curves. The PCD value of 3.5 A in triple PVCDR RTEC element is better than other resonant tunneling devices (RTD) elements. The high PVCDR value is concluded the lower VCD value about 0.8 A. The low VCD value is achieved by suitable selection of resistors in triple PVCDR RTEC element. The low PV value less than 1.35 V possesses low power dispersion in triple PVCDR RTEC element. The designed multiple value logical level (MVLL) system using triple PVCDR RTEC element provides equidistant logical level. The logical levels of MVLL system are about 0.2 V, 0.8 V, 1.5 V, and 2.2 V from low voltage to high voltage and then 2.2 V, 1.3 V, 0.8 V, and 0.2 V from high voltage back to low voltage in half cycle of sinusoid wave. The output level of four levels MVLL system is represented in 0.3 V, 1.1 V, 1.7 V, and 2.6 V, which satisfies the NMP condition of traditional two-bit system. The remarkable logical characteristic of improved MVLL system with paralleled capacitor are with four significant stable logical levels about 220 mV, 223 mV, 228 mV, and 230 mV. The stability and articulation of logical levels of improved MVLL system are outstanding. The average holding time of improved MVLL system is approximately 0.14 μs. The holding time of improved MVLL system is fourfold than of basic MVLL system. The function of additional capacitor in the improved MVLL system is successfully discovered.

Design of an Innovative Accelerant Detector

Today, canines are still used effectively in acceleration detection situation. However, this method is becoming impractical in modern age and a new automated replacement to the canine is required. This paper reports the design of an innovative accelerant detector. Designing an accelerant detector is a long process as is any design process; therefore, a solution to the need for a mobile, effective accelerant detector is hereby presented. The device is simple and efficient to ensure that any accelerant detection can be conducted quickly and easily. The design utilizes Ultra Violet (UV) light to detect the accelerant. When the UV light shines on an accelerant, the hydrocarbons in the accelerant emit florescence. The advantages of using the UV light to detect accelerant are also outlined in this paper. The mobility of the device is achieved by using a Direct Current (DC) motor to run tank tracks. Tank tracks were chosen as to ensure that the device will be mobile in the rough terrain of a fire site. The materials selected for the various parts are also presented. A Solid Works Simulation was also conducted on the stresses in the shafts and the results are presented. This design is an innovative solution which offers a user friendly interface. The design is also environmentally friendly, ecologically sound and safe to use.

Field and Petrographic Relationships between the Charnockitic and Associated Granitic Rock, Akure Area, Southwestern Nigeria

The charnockitic and associated granitic rocks of Akure area were studied for their field and petrographic relationship's. The outcrops locations were plotted in Surfer 8. The granitic rock exhibits a porphyritic texture and outcrops in the north-eastern side of the study area while the charnockitics outcrop in the central/western part. An essentially dark coloured and fine grained intrusive exhibiting xenoliths and xenocrysts (plagioclase phenocrysts) of the granite outcrops between the granitic and charnockitic rocks. Mineralogically, the central rock combines the content of the other two indicating that it is most likely a product of their hybridization. The charnockitic magma is believed to have intruded and assimilated the granite substantially thereby contaminating itself and consequently emplacing the hybrid. The presented model of emplacement elucidates the hybridization proposal. Conclusively, the charnockitics are believed to be (a) younger than the granite, (b) of Pan-African age and (c) of igneous origin.

Psychological Research of Ethnic Prejudices

In the article the experience of principle new technology development of ethnopsychological experiment on the basis of using other virtual independent experimental variables is presented. It is shown that ethnic prejudices are the result of forming and development of specific semantic barriers, arising up in the conditions of interethnic co-operation and people-s communication. Their overcoming is more successful in the conditions of the special organized process of teaching in a polyethnic environment, characteristic for the modern institute

Hydrogeological Aspects of Washing Waste Reuse in Quarry Lakes Rehabilitation

According to the European laws, there is the possibility of reusing the washing wastes for the environmental requalification of quarry lakes. The paper deals with the hydrogeological aspects involved in this possibility, as the introduction of finest wastes in the quarry lakes can generate alterations of the hydrogeological setting of the area, and problems for the future accessibility of the zone. To evaluate the hydrogeological compatibility of the washing wastes reuse in quarry lakes a groundwater numerical model was carried out, pointing out both the hydrogeological feasibility of this intervention and some guide lines for its optimization, in terms of inflow point with regard the groundwater flow direction and loss of volume in the quarry lake.

Estimation of Critical Period for Weed Control in Corn in Iran

The critical period for weed control (CPWC) is the period in the crop growth cycle during which weeds must be controlled to prevent unacceptable yield losses. Field studies were conducted in 2005 and 2006 in the University of Birjand at the south east of Iran to determine CPWC of corn using a randomized complete block design with 14 treatments and four replications. The treatments consisted of two different periods of weed interference, a critical weed-free period and a critical time of weed removal, were imposed at V3, V6, V9, V12, V15, and R1 (based on phonological stages of corn development) with a weedy check and a weed-free check. The CPWC was determined with the use of 2.5, 5, 10, 15 and 20% acceptable yield loss levels by non-linear Regression method and fitting Logistic and Gompertz nonlinear equations to relative yield data. The CPWC of corn was from 5- to 15-leaf stage (19-55 DAE) to prevent yield losses of 5%. This period to prevent yield losses of 2.5, 10 and 20% was 4- to 17-leaf stage (14-59 DAE), 6- to 12-leaf stage (25-47 DAE) and 8- to 9-leaf stage (31-36 DAE) respectively. The height and leaf area index of corn were significantly decreased by weed competition in both weed free and weed infested treatments (P

Fluorescent-Core Microcavities Based On Silicon Quantum Dots for Oil Sensing Applications

The compatibility of optical resonators with microfluidic systems may be relevant for chemical and biological applications. Here, a fluorescent-core microcavity (FCM) is investigated as a refractometric sensor for heavy oils. A high-index film of silicon quantum dots (QDs) was formed inside the capillary, supporting cylindrical fluorescence whispering gallery modes (WGMs). A set of standard refractive index oils was injected into a capillary, causing a shift of the WGM resonances toward longer wavelengths. A maximum sensitivity of 240 nm/RIU (refractive index unit) was found for a nominal oil index of 1.74. As well, a sensitivity of 22 nm/RIU was obtained for a lower index of 1.48, more typical of fuel hydrocarbons. Furthermore, the observed spectra and sensitivities were compared to theoretical predictions and reproduced via FDTD simulations, showing in general an excellent agreement. This work demonstrates the potential use of FCMs for oil sensing applications and the more generally for detecting liquid solutions with a high refractive index or high viscosity.

Chemical and Biological Properties of Local Cowpea Seed Protein Grown in Gizan Region

The aim of the present study was to investigate the chemical and biological properties of local cowpea seed protein cultivated in Gizan region. The results showed that the cowpea and its products contain high level of protein (22.9-77.6%), high carbohydrates (9.4-64.3%) and low fats (0.1-0.3%). The trypsin and chymotrypsin activities were found to be 32.2 and 15.2 units, respectively. These activities were not affected in both defatted and protein concentrate whereas they were significantly reduced in isolated protein and cooked samples. The phytate content of cooked and concentrated cowpea samples varied from 0.25% -0.32%, respectively. Tannin content was found to be 0.4% and 0.23% for cooked and raw samples, respectively. The in vitro protein digestibility was very high in cowpea seeds (75.04-78.76%). The biological evaluation using rats showed that the group fed with animal feed containing casein gain more weight than those fed with that containing cowpea. However, the group fed with cooked cowpea gain more weight than those fed with uncooked cowpea. On the other hand, in vivo digestion showed high value (98.33%) among the group consumed casein compared to other groups those consumed cowpea contains feed. This could be attributed to low antinutritional factors in casein contains feed compared to those of cowpea contains feed because cooking significantly increased the digestion rate (80.8% to 83.5%) of cowpea contains feed. Furthermore, the biological evaluation was high (91.67%) of casein containing feed compared to that of cowpea containing feed (80.83%-87.5%). The net protein utilization (NPU) was higher (89.67%) in the group fed with casein containing feed than that of cowpea containing feed (56.33%-69.67%).

A Probabilistic Reinforcement-Based Approach to Conceptualization

Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Weighted Clustering Coefficient for Identifying Modular Formations in Protein-Protein Interaction Networks

This paper describes a novel approach for deriving modules from protein-protein interaction networks, which combines functional information with topological properties of the network. This approach is based on weighted clustering coefficient, which uses weights representing the functional similarities between the proteins. These weights are calculated according to the semantic similarity between the proteins, which is based on their Gene Ontology terms. We recently proposed an algorithm for identification of functional modules, called SWEMODE (Semantic WEights for MODule Elucidation), that identifies dense sub-graphs containing functionally similar proteins. The rational underlying this approach is that each module can be reduced to a set of triangles (protein triplets connected to each other). Here, we propose considering semantic similarity weights of all triangle-forming edges between proteins. We also apply varying semantic similarity thresholds between neighbours of each node that are not neighbours to each other (and hereby do not form a triangle), to derive new potential triangles to include in module-defining procedure. The results show an improvement of pure topological approach, in terms of number of predicted modules that match known complexes.

A Novel Digital Calibration Technique for Gain and Offset Mismatch in TIΣΔ ADCs

Time interleaved sigma-delta (TIΣΔ) architecture is a potential candidate for high bandwidth analog to digital converters (ADC) which remains a bottleneck for software and cognitive radio receivers. However, the performance of the TIΣΔ architecture is limited by the unavoidable gain and offset mismatches resulting from the manufacturing process. This paper presents a novel digital calibration method to compensate the gain and offset mismatch effect. The proposed method takes advantage of the reconstruction digital signal processing on each channel and requires only few logic components for implementation. The run time calibration is estimated to 10 and 15 clock cycles for offset cancellation and gain mismatch calibration respectively.

Artificial Neural Network Models of the Ruminal pH in Holstein Steers

In this study four Holstein steers with rumen fistula fed 7 kg of dry matter (DM) of diets differing in concentrate to alfalfa hay ratios as 60:40, 70:30, 80:20, and 90:10 in a 4 × 4 latin square design. The pH of the ruminal fluid was measured before the morning feeding (0.0 h) to 8 h post feeding. In this study, a two-layered feed-forward neural network trained by the Levenberg-Marquardt algorithm was used for modelling of ruminal pH. The input variables of the network were time, concentrate to alfalfa hay ratios (C/F), non fiber carbohydrate (NFC) and neutral detergent fiber (NDF). The output variable was the ruminal pH. The modeling results showed that there was excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 >0.96). Therefore, we suggest using these model-derived biological values to summarize continuously recorded pH data.

Using Artificial Neural Network and Leudeking-Piret Model in the Kinetic Modeling of Microbial Production of Poly-β- Hydroxybutyrate

Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Finite Volume Model to Study The Effect of Voltage Gated Ca2+ Channel on Cytosolic Calcium Advection Diffusion

Mathematical and computational modeling of calcium signalling in nerve cells has produced considerable insights into how the cells contracts with other cells under the variation of biophysical and physiological parameters. The modeling of calcium signaling in astrocytes has become more sophisticated. The modeling effort has provided insight to understand the cell contraction. Main objective of this work is to study the effect of voltage gated (Operated) calcium channel (VOC) on calcium profile in the form of advection diffusion equation. A mathematical model is developed in the form of advection diffusion equation for the calcium profile. The model incorporates the important physiological parameter like diffusion coefficient etc. Appropriate boundary conditions have been framed. Finite volume method is employed to solve the problem. A program has been developed using in MATLAB 7.5 for the entire problem and simulated on an AMD-Turion 32-bite machine to compute the numerical results.

Daily and Seasonal Changes of Air Pollution in Kuwait

This paper focuses on assessment of air pollution in Umm-Alhyman, Kuwait, which is located south to oil refineries, power station, oil field, and highways. The measurements were made over a period of four days in March and July in 2001, 2004, and 2008. The measured pollutants included methanated and nonmethanated hydrocarbons (MHC, NMHC), CO, CO2, SO2, NOX, O3, and PM10. Also, meteorological parameters were measured, which includes temperature, wind speed and direction, and solar radiation. Over the study period, data analysis showed increase in measured SO2, NOX and CO by factors of 1.2, 5.5 and 2, respectively. This is explained in terms of increase in industrial activities, motor vehicle density, and power generation. Predictions of the measured data were made by the ISC-AERMOD software package and by using the ISCST3 model option. Finally, comparison was made between measured data against international standards.