Precision farming technology, adoption decisions and productivity of vegetables in resource-poor environments

‘Precision Farming’ or ‘Precision Agriculture’ aims at increasing productivity, decreasing production costs and minimizing the environmental impact of farming. In this context, the present study has been undertaken to understand the impact of precision farming on resource-poor regions and underprivileged farmers. Specifically, the study has looked into productivity, income, employment, and adoption behaviour of technology in agriculture. The study, conducted in the Dharmapuri district, has collected data on precision and non-precision farmings through the interview schedule during the year 2007. Sources of the productivity difference between the precision and conventional farmings have been identified by decomposing the productivity change. Financial impact of adoption has been studied through a two-stage econometric model. The first stage of the model consists of an adoption decision model that describes the factors which influence the likelihood of adopting precision farming. Results of first stage have provided input for the second stage of the model, which has been used to estimate the impact of precision farming on farm financial performance. The study has revealed that adoption of precision farming has led to 80 per cent increase in yield in tomato and 34 per cent in brinjal production. Increase in gross margin has been found as 165 and 67 per cent, respectively in tomato and brinjal farming. The contribution of technology for higher yield in precision farming has been 33.71 per cent and 20.48 per cent, respectively in tomato and brinjal production. The elasticity of 0.39 for the adoption in tomato and 0.28 in brinjal has indicated that as the probability of adoption increases by 10 per cent, net return increases by 39 per cent and 28 per cent in tomato and brinjal cultivation. Lack of finance and credit facilities have been identified as the major constrains in nonadoption of precision farming. The study has suggested that providing of subsidies for water-soluble fertilizers and pump-sets will increase adoption of precision farming.Crop Production/Industries,

A study on management of maternal anemia with infusion of intravenous iron sucrose and its outcome in management of anemia

Background: In India, women become pregnant with low baseline hemoglobin level resulting in high incidence of moderate to severe anemia in pregnancy where oral iron therapy cannot meet the requirement. Pregnant women with moderate anemia are to be treated with parenteral iron therapy. The aim of the study is to the infusion of intravenous iron sucrose and its outcome in the management of anemia.Methods: Totally 100 pregnant females were included in the study. The study period was from January 2018-July 2018 at vanavil medical center in Chennai. 50 Patients of Group A was given oral iron tablets containing100mg of elemental iron. 50 patients of Group B was given a total of 1000 mg of intravenous iron sucrose divided into five doses of 200 mg each at weekly intervals. Estimation of hemoglobin was started 4 weeks after commencement of iron therapy and then repeated every 4 weeks till 36 weeks of gestation, pre-delivery and postpartum.Results: Target hemoglobin levels were achieved in 4 weeks’ time in 19 (76%) patients in the iron sucrose group as compared to 08 (32%) of patients in the oral iron group. There was a significant improvement in the various hematological parameters in iv sucrose group as compared to patients in the oral iron group. There were no significant allergic reactions in iv sucrose group.Conclusions: Our results showed that intravenous iron sucrose therapy was effective to treat moderate anemia in pregnant women. Intramuscular preparations are known to be associated with local side-effects. Iron sucrose complex iv therapy was with negligible side effects. It caused a rapid rise in hemoglobin level and the replacement of stores was faster. Long term comparative studies are required to assess if they can be used at a peripheral level

ANTI CANCER STUDIES OF SELECTIVE MANNICH BASES BY IN SILICO METHOD

Objective: To evaluate the anticancer activities of selective Mannich bases by in silico methods.Methods: X-ray crystallographic structure of Estrogen receptor protein (PDB ID 2YAT) was downloaded from the protein data bank (PDB) and is docked with the target Mannich bases using Accelyrs Discovery Studio client version 2.5 software.Results: Based on the in silico analysis results of the target compounds with standard drug tamoxifen, the best-docked compound is identified and its anticancer activity is confirmed by using in vitro MTS analysis using Raju and Jurkat cell lines.Conclusion: The mannich base compound N-[(Diphenylamino) methyl] acetamide showed fourfold higher activity than standard drug tamoxifen, may be used to overcome the drug resistance of Estrogen receptor protein

BIOLOGICAL AND DOCKING STUDIES OF NOVEL AROYLHYDRAZONES

Objective: Novel aroylhydrazone schiff bases were synthesized and were screened for their biological activities.Methods: Using HCl as a catalyst, all the compounds were synthesized at room temperature and were characterized by IR and NMR techniques. The synthesized Schiff bases were screened for antibacterial, antifungal activities. In silico molecular docking, method was performed to study their anti-tuberculosis activity against enoyl acyl carrier protein reductase (InhA) from Mycobacterium tuberculosis (PDB id: 2NSD). Results: Compound P1 showed good antibacterial activity against gram positive (S. aureus) and gram negative (E. coli) bacterial strains and compound J1 showed good antifungal activity against A. niger. Molecular docking results reveal that compound B1 made two numbers of electrostatic interactions with 2NSD with more negative C docker interaction value. This indicated that the compound B1 was more active with minimum binding potential which is comparable with that of standard compound isoniazid.Conclusion: Aroylhydrazones having good biologically activities compared to that of standards were prepared

Design and Implementation of Low Power Time-To-Digital Converter using MGDI Technique

This paper introduces a novel Time to Digital Converter (TDC) architecture based on the Modified Gate Diffusion Input (MGDI) technique, which is derived from the well-established GDI method. Through the utilization of MGDI-based logic gates and digital circuitry, this innovative approach leads to a substantial reduction in the number of transistors required for implementation. As a result, it offers significant advantages in terms of circuit area, power consumption, and propagation delay, while simultaneously simplifying the complexity of the overall logic design. The functional blocks within the TDC have been optimized to efficiently process an internal clock frequency of 5MHz. This achievement is realized using cutting-edge 90nm MGDI technology, operating at a supply voltage of 1V. Practical implementation of this design can be carried out seamlessly with Cadence Virtuoso tools in the 90nm technology node. In essence, this research effort represents a promising advancement in the realm of time-to-digital conversion. By harnessing the capabilities of MGDI and its transistor-saving attributes, the proposed TDC not only enhances performance but also addresses critical concerns such as power efficiency and chip area utilization. These advancements make it a compelling choice for applications requiring precise time measurements, while the compatibility with contemporary technology nodes ensures its relevance and applicability in modern integrated circuit design

CLOUD COMPUTING IN AGRICULTURE – AN BOON

In India, around 75% of the population earns its livelihood from agriculture. It fulfills the basic need of human beings and animals. It is an important source of raw material for many agro-based industries. India’s geographical condition is unique for agriculture because it provides many favorable conditions. There are plain areas, fertile soil, long growing seasons, wide variation in climatic condition, etc. Apart from unique geographical conditions, India has been consistently making innovative efforts using science and technology to increase production. In that one the major booming sector is cloud computing, i.e., Cloud-agro revolution. Due to my passion in agriculture and tied to implement my research area in cloud. Today’s agriculture is embedded with advance services such as GPS and sensors [1] which is used to communicate with each other and also used to analyses and exchange Agri Information’s among them. IT provides services in the form of cloud to agriculture. Agri-cloud and IT offers expertise service to farmers regarding cultivation of crops, pricing, fertilizers, and diseases details and methods of cure to be used etc. In this field, there are huge discoveries, suggestions regarding modern techniques for cultivation, usage of fertilizers, can obtain cultivation history of the region, etc. In this paper, our study was based on is to design and implement a simple cloud-based application on Agriculture System which is based on agri-cloud that enhance agriculture production and also enhance the availability of data related to research projects in field

Effective Stress v/s Total Stress Ground Response Analyses for a Typical Site in Chennai (India)

This paper presents the results of ground response analyses carried out for a typical sandy site in Chennai city by equivalent linear and nonlinear total and effective stress approaches. The soil profile at the site consists of 26m thick sandy layer with SPT blow count increases from 16 to above 50 with depth. The shear wave velocity profile measured using field Multichannel Analysis of Surface Wave (MASW) test is found to increase from 170 m/s to 400 m/s at 26m depth. The equivalent linear ground response analysis was carried out using SHAKE2000. The nonlinear total and effective stress analyses were performed using D-MOD2000. In the nonlinear total stress analysis, the Modified Kondner and Zelasko (MKZ) constitutive model was used. In the case of nonlinear effective stress analysis, modulus degradation and stress degradation models of Matasovic and Vucetic (1993) were used to incorporate the pore pressure parameters. The analyses were carried out for a time history of bedrock acceleration with PGA of 0.16g obtained from the seismic hazard analysis. The results of the analyses are presented in terms of ground acceleration, shear stress and shear strain. The results of the equivalent linear, nonlinear total and effective stress analyses show similar ground response characteristics except marginal variation in the period corresponding to the peak spectral acceleration due to low intensity of input motion

Intelligent Intrusion Detection System using Enhanced Arithmetic Optimization Algorithm with Deep Learning Model

The widespread use of interoperability and interconnectivity of computing systems is becoming indispensable for enhancing our day-to-day actions. The susceptibilities deem cyber-security systems necessary for assuming communication interchanges. Secure transmission needs security measures for combating the threats and required developments to security measures that counter evolving security risks. Though firewalls were devised to secure networks, in real-time they cannot detect intrusions. Hence, destructive cyber-attacks put forward severe security complexities, requiring reliable and adaptable intrusion detection systems (IDS) that could monitor unauthorized access, policy violations, and malicious activity practically. Conventional machine learning (ML) techniques were revealed for identifying data patterns and detecting cyber-attacks IDSs successfully. Currently, deep learning (DL) methods are useful for designing accurate and effective IDS methods. In this aspect, this study develops an intelligent IDS using enhanced arithmetic optimization algorithm with deep learning (IIDS-EAOADL) method. The presented IIDS-EAOADL model performs data standardization process to normalize the input data. Besides, equilibrium optimizer based feature selection (EOFS) approach is developed to elect an optimal subset of features. For intrusion detection, deep wavelet autoencoder (DWAE) classifier is applied. Since the proper tuning of parameters of the DWNN is highly important, EAOA algorithm is used to tune them. For assuring the simulation results of the IIDS-EAOADL technique, a widespread simulation analysis takes place using a benchmark dataset. The experimentation outcomes demonstrate the improvements of the IIDS-EAOADL model over other existing technique