Solomon 300 OD (Betacyfluthrin+Imidacloprid): A Combi-Product for the Management of Insect-Pests of Chilli (Capsicum annum L.)

Chilli (Capsicum annum L.) an important commercial vegetable crop is ravaged by a number of insect-pests during both vegetative and reproductive phase resulting into significant crop loss.Thrips, Scirtothripsdorsalis, mite, Polyphagotarsonemuslatus and whitefly, Bemisiatabaci are the key sap feeding insects, their infestation leads to leaf curl, stunted growth and yield loss.During flowering and fruit formation stage, gall midge fly, Asphondyliacapparis (Rubsaaman) infesting flower buds and young fruits andHelicoverpaarmigera (Hubner) feeding on matured green fruits are the important insect pests causing significant crop loss.The pest is known to infest both flower buds and young fruits resulting into malformation of flower buds and twisting of fruits.In order to manage these insect-pests a combi product consisting of imidacloprid and betacyfluthrin (Soloman 300 OD) was evaluated for its bio-efficacy, phytotoxicity and effect on predator activity.Imidacloprid, a systemic insecticide belonging to neo-nicotinoid group, is effective against insect pests such as aphids, whiteflies (sap feeders) and other insectsviz., termites and soil insects.Beta-Cyfluthrin is an insecticide of synthetic pyrethroid group which acts by contact action and ingestion. It acts on the insects' nervous system as sodium channel blocker consequently a disorder of the nervous system occurs leading finally to the death. The field experiments were taken up during 2015 and 2016 at the Main Agricultural Research Station of University of Agricultural Sciences, Dharwad, Karnataka, India.The trials were laid out in a Randomized Block Design (RBD) with three replications using popular land race of Byadagi crop variety.Results indicated that the product at 21.6 + 50.4% gai/ha (240 ml/ha) and 27.9 + 65% gai/ha (310 ml/ha) was found quite effective in controlling thrips (0.00 to 0.66 thrips per six leaves) as against the standard check insecticide recommended for thrips by the University of Agricultural Sciences, Dharwad wherein the density of thrips recorded was significantly higher (1.00 to 2.00 Nos./6 leaves). Similarly, the test insecticide was quite effective against other target insects, whiteflies, fruit borer and gall midge fly as indicated by lower insect population observed in the treatments as compared to standard insecticidal control. The predatory beetle activity was found to be normal in all experimental plots. Highest green fruit yield of 5100-5500 kg/ha was recorded in Soloman 300 OD applied crop at 310 ml/ha rate as compared to 4750 to 5050 kg/ha recorded in check. At present 6-8 sprays of insecticides are recommended for management of these insect-pests on the crop. If combi-products are used in pest management programmes, it is possible to reduce insecticide usages in crop ecosystem.

Effect of Using Crumb Rubber with Warm-Mix-Asphalt Additive in Laboratory and Field Aging

Using a waste material such as crumb rubber (CR) obtained by waste tires has become an important issue in respect to sustainability. However, the CR modified mixture also requires high manufacture temperature as a polymer modified mixture. For this reason in this study, it is intended to produce a CR modified mixture with warm mix asphalt additives in the same mixture. Asphalt mixtures produced by pure, 10%CR, 10%CR+3% Sasobit and 10%CR+0.7% Evotherm were subjected to aging procedure in the laboratory and the field. The indirect tensile repeated tests were applied to aged and original specimens. It was concluded that the fatigue life of the mixtures increased significantly with the increase of aging time. CR+Sasobit modified mixture aged at the both field and laboratory gave the highest load cycle among the mixtures.

Empirical Exploration of Correlations between Software Design Measures: A Replication Study

Software engineers apply different measures to quantify the quality of software design. These measures consider artifacts developed at low or high level software design phases. The results are used to point to design weaknesses and to indicate design points that have to be restructured. Understanding the relationship among the quality measures and among the design quality aspects considered by these measures is important to interpreting the impact of a measure for a quality aspect on other potentially related aspects. In addition, exploring the relationship between quality measures helps to explain the impact of different quality measures on external quality aspects, such as reliability and maintainability. In this paper, we report a replication study that empirically explores the correlation between six well known and commonly applied design quality measures. These measures consider several quality aspects, including complexity, cohesion, coupling, and inheritance. The results indicate that inheritance measures are weakly correlated to other measures, whereas complexity, coupling, and cohesion measures are mostly strongly correlated.  

Design Optimization of the Primary Containment Building of a Pressurized Water Reactor

Primary containment structure is one of the five safety layers of a nuclear facility which is needed to be designed in such a manner that it can withstand the pressure and excessive radioactivity during accidental situations. It is also necessary to ensure minimization of cost with maximum possible safety in order to make the design economically feasible and attractive. This paper attempts to identify the optimum design conditions for primary containment structure considering both mechanical and radiation safety keeping the economic aspects in mind. This work takes advantage of commercial simulation software to identify the suitable conditions without the requirement of costly experiments. Generated data may be helpful for further studies.

Prediction on Housing Price Based on Deep Learning

In order to study the impact of various factors on the housing price, we propose to build different prediction models based on deep learning to determine the existing data of the real estate in order to more accurately predict the housing price or its changing trend in the future. Considering that the factors which affect the housing price vary widely, the proposed prediction models include two categories. The first one is based on multiple characteristic factors of the real estate. We built Convolution Neural Network (CNN) prediction model and Long Short-Term Memory (LSTM) neural network prediction model based on deep learning, and logical regression model was implemented to make a comparison between these three models. Another prediction model is time series model. Based on deep learning, we proposed an LSTM-1 model purely regard to time series, then implementing and comparing the LSTM model and the Auto-Regressive and Moving Average (ARMA) model. In this paper, comprehensive study of the second-hand housing price in Beijing has been conducted from three aspects: crawling and analyzing, housing price predicting, and the result comparing. Ultimately the best model program was produced, which is of great significance to evaluation and prediction of the housing price in the real estate industry.

A Location Routing Model for the Logistic System in the Mining Collection Centers of the Northern Region of Boyacá-Colombia

The main objective of this study is to design a mathematical model for the logistics of mining collection centers in the northern region of the department of Boyacá (Colombia), determining the structure that facilitates the flow of products along the supply chain. In order to achieve this, it is necessary to define a suitable design of the distribution network, taking into account the products, customer’s characteristics and the availability of information. Likewise, some other aspects must be defined, such as number and capacity of collection centers to establish, routes that must be taken to deliver products to the customers, among others. This research will use one of the operation research problems, which is used in the design of distribution networks known as Location Routing Problem (LRP).

Teacher Culture Inquiry of Classroom Observation at an Elementary School in Taiwan

Three dimensions of teacher culture hinder educational improvement: individualism, conservatism and presentism. To promote the professional development of teachers, these three aspects in teacher culture should be eliminated. Classroom observation may be a useful method of eliminating individualism. The Ministry of Education in Taiwan has attempted to reduce the isolation of teachers to promote their professional growth. Because classroom observation discourse varies, teachers are generally unwilling to allow their teaching to be observed. However, classroom observations take place in the country in the form of school evaluations. The main purpose of this study was to explore the differences in teachers’ conservatism, individualism and presentism after classroom observations had been conducted at an elementary school in Taiwan. The research method was a qualitative case study involving interviews with the school principal, the director of academic affairs, and two classroom teachers. The following conclusions were drawn: (1) Educators in different positions viewed classroom observations differently; (2) The classroom teachers did not highly value classroom observation; (3) There was little change in the teachers’ conservatism, individualism and presentism after classroom observation.

Optimization of Carbon Nanotube Content of Asphalt Nanocomposites with Regard to Resistance to Permanent Deformation

This paper presents the results of the development of asphalt nanocomposites containing carbon nanotubes (CNTs) with high resistance to permanent deformation, aiming to increase the performance of asphalt surfaces in relation to the rutting problem. Asphalt nanocomposites were prepared with the addition of different proportions of CNTs (1%, 2% and 3%) in relation to the weight of asphalt binder. The base binder used was a conventional binder (50-70 penetration) classified as PG 58-22. The optimum percentage of CNT addition in the asphalt binder (base) was determined through the evaluation of the rheological and empirical characteristics of the nanocomposites produced. In order to evaluate the contribution and the effects of the nanocomposite (optimized) in relation to the rutting, the conventional and nanomodified asphalt mixtures were tested in a French traffic simulator (Orniéreur). The results obtained demonstrate the efficient contribution of the asphalt nanocomposite containing CNTs to the resistance to permanent deformation of the asphalt mixture.

The Evaluation of Antioxidant and Antimicrobial Activities of Essential Oil and Aqueous, Methanol, Ethanol, Ethyl Acetate and Acetone Extract of Hypericum scabrum

Herbal essential oil and extracts are a good source of natural antioxidants and antimicrobial compounds. Hypericum is one of the potential sources of these compounds. In this study, the antioxidant and antimicrobial activity of essential oil and aqueous, methanol, ethanol, ethyl acetate and acetone extract of Hypericum scabrum was assessed. Flowers of Hypericum scabrum were collected from the surrounding mountains of Hamadan province and after drying in the shade, the essential oil of the plant was extracted by Clevenger and water, methanol, ethanol, ethyl acetate and acetone extract was obtained by maceration method. Essential oil compounds were identified using the GC-Mass. The Folin-Ciocalteau and aluminum chloride (AlCl3) colorimetric method was used to measure the amount of phenolic acid and flavonoids, respectively. Antioxidant activity was evaluated using DPPH and FRAP. The minimum inhibitory concentration (MIC) and the minimum bacterial/fungicide concentration (MBC/MFC) of essential oil and extracts were evaluated against Staphylococcus aureus, Bacillus cereus, Pseudomonas aeruginosa, Salmonella typhimurium, Aspergillus flavus and Candida albicans. The essential oil yield of was 0.35%, the lowest and highest extract yield was related to ethyl acetate and water extract. The most component of essential oil was α-Pinene (46.35%). The methanol extracts had the highest phenolic acid (95.65 ± 4.72 µg galic acid equivalent/g dry plant) and flavonoids (25.39 ± 2.73 µg quercetin equivalent/g dry plant). The percentage of DPPH radical inhibition showed positive correlation with concentrations of essential oil or extract. The methanol and ethanol extract had the highest DDPH radical inhibitory. Essential oil and extracts of Hypericum had antimicrobial activity against the microorganisms studied in this research. The MIC and MBC values for essential oils were in the range of 25-25.6 and 25-50 μg/mL, respectively. For the extracts, these values were 1.5625-100 and 3.125-100 μg/mL, respectively. Methanol extracts had the highest antimicrobial activity. Essential oil and extract of Hypericum scabrum, especially methanol extract, have proper antimicrobial and antioxidant activity, and it can be used to control the oxidation and inhibit the growth of pathogenic and spoilage microorganisms. In addition, it can be used as a substitute for synthetic antioxidant and antimicrobial compounds.

Generation of Electro-Encephalography Readiness Potentials by Intention

The readiness potential in brain waves is a brain activity related with an intention whose potential arises even before its conscious intention. This study was carried out in order to understand the generation and mechanism of the readiness potential more. The experiment with two subjects was conducted in two ways following the Oddball task protocol. Firstly, auditory stimuli were randomly presented to the subjects. The subject was allowed to press the keyboard with the right index finger only when the subject heard the target stimulus but not the standard stimulus. Secondly, unlike the first one, the auditory stimuli were randomly presented, and the subjects pressed the keyboard in the same manner, but at the same time with grasping action of the left hand. The readiness potential showed up for both of these experiments. In the first Oddball experiment, the readiness potential was detected only when the target stimulus was presented. However, in the second Oddball experiment with the left hand action of grasping something, the readiness potential was detected at the presentation of for both standard and target stimuli. However, detected readiness potentials with the target stimuli were larger than those of the standard stimuli. We found an interesting phenomenon that the readiness potential was able to be detected even the standard stimulus. This indicates that motor-related readiness potentials can be generated only by the intention to move. These results present a new perspective in psychology and brain engineering since subconscious brain action may be prior to conscious recognition of the intention.

Flow Characteristics around Rectangular Obstacles with the Varying Direction of Obstacles

The study aims to understand the surface pressure distribution around the bodies such as the suction pressure in the leading edge on the top and side-face when the aspect ratio of bodies and the wind direction are changed, respectively. We carried out the wind tunnel measurement and numerical simulation around a series of rectangular bodies (40d×80w×80h, 80d×80w×80h, 160d×80w×80h, 80d×40w×80h and 80d×160w×80h in mm3) placed in a deep turbulent boundary layer. Based on a modern numerical platform, the Navier-Stokes equation with the typical 2-equation (k-ε model) and the DES (Detached Eddy Simulation) turbulence model has been calculated, and they are both compared with the measurement data. Regarding the turbulence model, the DES model makes a better prediction comparing with the k-ε model, especially when calculating the separated turbulent flow around a bluff body with sharp edged corner. In order to observe the effect of wind direction on the pressure variation around the cube (e.g., 80d×80w×80h in mm), it rotates at 0º, 10º, 20º, 30º, and 45º, which stands for the salient wind directions in the tunnel. The result shows that the surface pressure variation is highly dependent upon the approaching wind direction, especially on the top and the side-face of the cube. In addition, the transverse width has a substantial effect on the variation of surface pressure around the bodies, while the longitudinal length has little or no influence.

CMOS Positive and Negative Resistors Based on Complementary Regulated Cascode Topology with Cross-Coupled Regulated Transistors

Two types of floating active resistors based on a complementary regulated cascode topology with cross-coupled regulated transistors are presented in this paper. The first topology is a high swing complementary regulated cascode active resistor. The second topology is a complementary common gate with a regulated cross coupled transistor. The small-signal input resistances of the floating resistors are derived. Three graphs of the input current versus the input voltage for different aspect ratios are designed and plotted using the Cadence Spectre 0.18-µm Rohm Semiconductor process. The total harmonic distortion graphs are plotted for three different aspect ratios with different input-voltage amplitudes and different input frequencies. From the simulation results, it is observed that a resistance of approximately 8.52 MΩ can be obtained from supply voltage at  ±0.9 V.

Study on Influencing Factors of Walkability of Rail Transit Station Area

Based on the comparative analysis of the relevant evaluation methods of walking environment, this paper selects the combined evaluation method of macro urban morphology analysis and micro urban design quality survey, then investigates and analyzes the walking environment of three rail transit station area in Nanjing to explore the influence factor and internal relation of walkability of rail transit station area. Analysis shows that micro urban design factors have greater impact on the walkability of rail transit station area compared with macro urban morphology factors, the convenience is the key factor in the four aspects of convenience, security, identity and comfortability of the urban design factors, the convenience is not only affected by the block network form, but also related to the quality of the street space. The overall evaluation of walkability comes from the overlapping and regrouping of the walking environment at different levels, but some environmental factors play a leading role. The social attributes of pedestrians also partly influence their walking perception and evaluation.

Application of Artificial Neural Network in Assessing Fill Slope Stability

This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Evaluation for Punching Shear Strength of Slab-Column Connections with Ultra High Performance Fiber-Reinforced Concrete Overlay

This paper presents the test results on 5 slab-column connection specimens with Ultra High Performance Fiber-Reinforced Concrete (UHPFRC) overlay including 1 control specimen to investigate retrofitting effect of UHPFRC overlay on the punching shear capacity. The test parameters were the thickness of the UHPFRC overlay and the amount of steel re-bars in it. All specimens failed in punching shear mode with abrupt failure aspect. The test results showed that by adding a thin layer of UHPFRC over the Reinforced Concrete (RC) substrates, considerable increases in global punching shear resistance up to 82% and structural rigidity were achieved. Furthermore, based on the cracking patterns the composite systems appeared to be governed by two failure modes: 1) diagonal shear failure in RC section and 2) debonding failure at the interface.

Development of a Multi-Factorial Instrument for Accident Analysis Based on Systemic Methods

The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Happiness, Media and Sustainability of Communities in Donkeaw, Mearim District, Chiang Mai, Thailand

This study of the ‘happiness’ and ‘sustainability’ in the community of Donkeaw, Amphoe Mae Rim, Chiang Mai Province during the non-election period in Thailand, noted that their happiness levels are in the middle-average range. This was found using a mixed approach of qualitative and quantitative methods (N = 386, α = 0.05). The study explores indicators for six aspects of well-being and happiness, including, good local governance, administrative support for the health system that maintains people’s mental and physical health, environment and weather, job security and a regular income aids them in managing a sustainable lifestyle. The impact of economic security and community relationships on social and cultural capital, and the way these aspects impact on the life style of the community, affects the sustainable well-being of people. Moreover, living with transparency and participatory communication led to diverse rewards in many areas.

Considerations for Effectively Using Probability of Failure as a Means of Slope Design Appraisal for Homogeneous and Heterogeneous Rock Masses

Probability of failure (PF) often appears alongside factor of safety (FS) in design acceptance criteria for rock slope, underground excavation and open pit mine designs. However, the design acceptance criteria generally provide no guidance relating to how PF should be calculated for homogeneous and heterogeneous rock masses, or what qualifies a ‘reasonable’ PF assessment for a given slope design. Observational and kinematic methods were widely used in the 1990s until advances in computing permitted the routine use of numerical modelling. In the 2000s and early 2010s, PF in numerical models was generally calculated using the point estimate method. More recently, some limit equilibrium analysis software offer statistical parameter inputs along with Monte-Carlo or Latin-Hypercube sampling methods to automatically calculate PF. Factors including rock type and density, weathering and alteration, intact rock strength, rock mass quality and shear strength, the location and orientation of geologic structure, shear strength of geologic structure and groundwater pore pressure influence the stability of rock slopes. Significant engineering and geological judgment, interpretation and data interpolation is usually applied in determining these factors and amalgamating them into a geotechnical model which can then be analysed. Most factors are estimated ‘approximately’ or with allowances for some variability rather than ‘exactly’. When it comes to numerical modelling, some of these factors are then treated deterministically (i.e. as exact values), while others have probabilistic inputs based on the user’s discretion and understanding of the problem being analysed. This paper discusses the importance of understanding the key aspects of slope design for homogeneous and heterogeneous rock masses and how they can be translated into reasonable PF assessments where the data permits. A case study from a large open pit gold mine in a complex geological setting in Western Australia is presented to illustrate how PF can be calculated using different methods and obtain markedly different results. Ultimately sound engineering judgement and logic is often required to decipher the true meaning and significance (if any) of some PF results.

Performance Analysis of Organic Rankine Cycle Technology to Exploit Low-Grade Waste Heat to Power Generation in Indian Industry

The demand for energy is cumulatively increasing with time.  Since the availability of conventional energy resources is dying out gradually, significant interest is being laid on searching for alternate energy resources and minimizing the wastage of energy in various fields.  In such perspective, low-grade waste heat from several industrial sources can be reused to generate electricity. The present work is to further the adoption of the Organic Rankine Cycle (ORC) technology in Indian industrial sector.  The present paper focuses on extending the previously reported idea to the next level through a comparative review with three different working fluids using practical data from an Indian industrial plant. For comprehensive study in the simulation platform of Aspen Hysys®, v8.6, the waste heat data has been collected from a current coke oven gas plant in India.  A parametric analysis of non-regenerative ORC and regenerative ORC is executed using the working fluids R-123, R-11 and R-21 for subcritical ORC system.  The primary goal is to determine the optimal working fluid considering various system parameters like turbine work output, obtained system efficiency, irreversibility rate and second law efficiency under applied multiple heat source temperature (160 °C- 180 °C).  Selection of the turbo-expanders is one of the most crucial tasks for low-temperature applications in ORC system. The present work is an attempt to make suitable recommendation for the appropriate configuration of the turbine. In a nutshell, this study justifies the proficiency of integrating the ORC technology in Indian perspective and also finds the appropriate parameter of all components integrated in ORC system for building up an ORC prototype.

Integration of Big Data to Predict Transportation for Smart Cities

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.