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Jaideep Chandra, Irrawaddy Imperatives: Reviewing India’s Myanmar Strategy. Pentagon Press LLP, 2021, pp. 470, ISBN: 978-93-90095-34-6.

The unexpected local damage may happen in the beam column connections of steel structures under lateral loads, since the connection is the focal point. Adopting reduced beam section (RBS) is an innovative method to dissipate the energy of such structures since it will enable a plastic hinge to be formed in the beam portion, thus reducing large stress concentration in the connection. Also, the formation of plastic hinge will satisfy the seismic criteria of strong column and weak beam combination. This paper focuses on analyzing the efficiency of cruciform connection fabricated with RBS. The structural components comprise of standard I section beam and column connected through welds. Finite element method is applied and model is created for cruciform connections in which different RBSs are used. The models are validated using experimental analysis applied on the specimen. The monotonic load is gradually applied at the two ends of the beams and moment rotation behavior is established. Similar behavior is studied for the RBS model and double reduced beam section (DRBS) as well. The effective connection stiffness is identified for the different models under consideration. It is observed from the results that RBS and DRBS can sustain large inelastic strains besides limiting stress concentration in the connection.

Purpose The use of flexible connections throughout the steel structures provides a high level of stiffness compared to that of fully welded connections. Flexible connections allow for rotation to an extent, which make them perform better during earthquake than welded connections. In hanger connections, the applied load produces tension in the bolts and bolts are designed for tensile forces. When the deformation of the flange plate is equal to that of the bolts, a plastic hinge is formed in the flange plate at the weld line and the bolts are pulled to failure. If the attached plate is allowed to deform, additional tensile forces called prying forces are developed in the bolts. The paper aims to discuss these issues. Design/methodology/approach This paper includes the results of investigation on prying force in T-stub connection fabricated with normal grade bolts and high strength friction grip (HSFG) bolts. Finite element analysis has been carried out by creating models and analyzing the effect of external tensile force and bolt force. For different grades of bolt (4.6, 8.8, 10.9, 12.9), the prying force is calculated. Findings It is found that prying force is increasing with the change in grade of bolt used from normal to HSFG. The results obtained from analysis using IS 800:2007 codal provision are also included. It is observed that HSFG bolts do not allow for any slip between the elements connected and hence rigidity is increased. Originality/value The prying force mainly depends on geometrical parameter of the connection. In this research work, the variation of prying force was studied based on the variation in dimensions of T-stub angle section and bolt grade (4.6, 8.8, 10.9, 12.9). The method of obtaining prying force from bolt load and applied load is a unique approach. The results of FE analysis is validated with the analytical calculation as per IS 800:2007 code provisions, which shows the originality of the research.

In this paper, In Recent Year Machine learning plays important role in analyzing the various time of weather condition all around the world especially Indian Subcontinent. Data is available in the government website to analyze the data for few long years. This should be matched with UCI technique for the machine learning and obtain the condition of different level of data repository. Temperature and humidity level condition of different parameters were analyzed and taken as example of weather condition to monitor the weather condition. We need to design a model to fit the different condition and need to extrapolating the needs of information, and optimize the technique using some algorithm and variation should be targeted and value should be analyzed.

The mental health of young adults and teenagers proves to be vital for having a flourishing life. Neglecting the issue of mental health can lead to anxiety, stress, and depression. These problems need to be addressed in the early stages to ensure better mental health for young adults. This paper provides a comprehensive study by leveraging natural language processing and deep learning techniques to detect depression by examining the relationship between language usage and the psychological characteristics of the communicator. A private dataset DAIC-WOZ has been used to predict the levels of depression. It includes audio, video, and textual information from 189 interviews. This paper focuses on the textual analysis of detecting depression from transcripts of the interviews conducted by an animated virtual interviewer. Due to the disadvantages faced by the context-independent nature of GloVe embeddings, the proposed approach uses transfer learning techniques such as ELMo, ULMFit, and BERT for predicting depression severity from transcripts. Furthermore, a Python Web application has been deployed to identify negative sentiments and depression severity from sentences inputted by the user. The proposed approach uses an ensemble learning method for the application to provide better predictions for classifying the texts into levels of depression. Hence, the inferences made in this paper can be extrapolated to other all demographics around the world to help detect depression in textual data as the algorithms and techniques used are all-encompassing..

Our paper provides an extensive study of detecting fraudulent claims in healthcare insurance by leveraging machine learning algorithms. By using the publicly available medicare dataset, we are able to classify as fraud and non-fraud providers. Moreover, synthetically minority oversampling technique is used to avoid the class imbalance problem. Furthermore, a hybrid approach is used which is based on clustering and classification. Additionally, we have used other machine learning algorithms to check the efficiency of the best-suited algorithm.

Microarray gene expression data plays a prominent role in feature selection that helps in diagnosis and treatment of a wide variety of diseases. Microarray gene expression data contains redundant feature genes of high dimensionality and smaller training and testing samples. This paper proposes a customized similarity measure using fuzzy rough quick reduct algorithm for attribute selection. Information Gain based entropy is used to reduce the dimensionality in the first stage and the proposed fuzzy rough quick reduct method that defines a customized similarity measure for selecting the minimum number of informative genes and removing the redundant genes is employed at the second stage. The proposed method is evaluated using leukemia, lung and ovarian cancer gene expression datasets on a random forest classifier. The proposed method produces 97.22%, 99.45% and 99.6% classifier accuracy on leukemia, lung and ovarian cancer gene expression datasets respectively. The research study is carried out using the R open source software package. The proposed method shows substantial improvement in the performance with respect to various statistical parameters like classification accuracy, precision, recall, f-measure and region of characteristic compared to available methods in literature. Keywords: Feature selection, Information gain, Fuzzy rough quick reduct, Random forest

This study presents the behaviour of punching shear in waffle slabs at slab–column joints subjected to concentric loading. Although it was observed that waffle slabs are very similar to that of flat slabs, the shear capacity is relatively reduced because some of the potential surfaces are lost when it extends into waffle section. The current IS code of practice does not consider the punching shear mechanism of waffle slabs. For the different sizes of waffle slab a square column size of 100 × 100 mm is considered for the designed slab size of 1200 × 1200 mm. Waffle slabs of different sizes are created by increasing the depth of slab by 20%, width of the rib by 25% and also increasing the solid section. The experimental results were compared with theoretical values from IS code. The comparison of the test results reveals that waffle slab gives more strength than conventional slab. The comparison has been made for the waffle slab of different sizes; slab provided with more depth and thickness of ribs gives extra strength to the structure against punching shear and the stiffness of the slab is substantially improved in the case of an increase in the rib size.

Foamed concrete possesses characteristics such as high strength-to-weight ratio and low density. Foamed concrete reduces dead loads on the structure,saves energy and lowers the labour cost during construction. Foam concrete consists of cement, fly ash, water and air voids. The foaming agent used to generate foam is sodium lauryl ether sulphate. Foam concrete can have 10% to 70% air, which results in a material that is light-weight but may compromise the compressive strength and durability properties. Although it has been shown in the research that less connected air voids yield a lower reduction in compressive strength, with the increase in air voids the thermal resistance in increased. The properties like compressive strength and thermal resistance are studied. Six batches of Foamed concrete were prepared with varying air content 15%, 17%, and 20%. The foamed concrete cube and slab are used for compression and thermal testing. The dry density of foamed concrete varies from 860 kg/m3 to 1245 kg/m3, and the compressive strength varies from 2.5 - 6.5 MPa. In this research, the Dry density, compressive strength and thermal conductivity of foamed concrete is compared with the clay bricks. If foamed concrete blocks are used instead of clay bricks, almost 50% of the dead load of the building can be reduced. The thermal conductivity of foamed concrete varies from 0.021 - 0.035 W/mK. Key outcomes revealed that foamed concrete has good potential to be used for lightweight structural applications for low-rise buildings owing to its evolution of mechanical properties, transport properties and thermal resistance.

The study analyses about the growth trend in area, production, and yield of cotton in India as well as Karnataka State. Cotton is an important crop for the sustainable economy of the country and livelihood security of the community Indian Cotton Farming. It is cultivated was 312 lakh hectares across the global level and in around 117 lakh hectares in the country. Thus, India accounts for around 37.5 per cent of the global cotton area and contributes to 26 per cent (i.e 6.20 Million Tonnes) of the global cotton produce of 23.92 Million Tonnes. Cotton continues to enjoy a pre-eminent and the most favored fiber status among the Indian textile mills, as the major raw material for the textile industry. The textile industry, which consumes the cotton, as its principal raw material, contributes about 4% to the GDP and is the major exchange earner for the country. Hence, growth and development of cotton and cotton based textile industry has a vital bearing on the overall development of the Indian economy. This study mainly focused on present status of area, production and yield under cotton. Further, article revealed that the development programmes for improvement in productivity of cotton and skill developments for cotton cultivators in India as well as Karnataka State.

Attribute selection is an important step in the analysis of gene expression for cancer or illnesses in general. The huge dimensionality of gene expression data that includes many insignificant and redundant genes reduces the classification accuracy. In this study, we propose a hybrid attribute selection method to identify the small set of the most significant genes associated with the cause of cancer. The proposed method integrates the advantages of filter and a wrapper to perform attribute selection by devising a customized fitness function for the genetic algorithm. Three data sets are used that includes leukemia, CNS and colon cancer. Results of our technique are compared with the other standard techniques available in literature. The proposed hybrid approach produces comparably better accuracy than the standard implementation of the genetic algorithm.

Cancer diagnosis is one of the emerging applications in microarray gene expression data. Feature selection plays a crucial role because of the huge dimensionality and less training and testing samples. Finding a small subset of significant genes from a large set of gene expression data is a challenging task. This paper presents the usage of genetic algorithm as a tool to determine the informative gene subset and uses Extreme Learning Machines classifier to determine the classifier accuracy. Experiments are carried out on two microarray datasets and the results reveal that the proposed approach produces better classification rate compared to Support Vector Machines and nearest neighbor classifier.

Magnetic Resonance Imaging (MRI) images of the brain are used for detection of various brain diseases including tumor. In such cases, classification of MRI images captured with respect to ventricular and eye ball regions helps in automated location and classification of such diseases. The methods employed in the paper can segregate the given MRI images of brain into images of brain captured with respect to ventricular region and images of brain captured with respect to eye ball region. First, the given MRI image of brain is segmented using Particle Swarm Optimization (PSO) algorithm, which is an optimized algorithm for MRI image segmentation. The algorithm proposed in the paper is then applied on the segmented image. The algorithm detects whether the image consist of a ventricular region or an eye ball region and classifies it accordingly.

of cancer is one of the most emerging clinical applications in microarray gene expression data. However, cancer classification on microarray gene expression data still remains a difficult problem. The main reason for this is the significantly large number of genes present relatively compared to the number of available training samples. In this paper, a novel approach to feature extraction combining the statistical t-test and absolute scoring is proposed for achieving better classification rate. Suitable classification approaches using the linear Support Vector Machines, the Proximal Support Vector Machines and the Newton Support Vector Machines is also discussed. A comparative analysis on the different techniques for feature extraction is also presented. Microarray cancer data based on Adenoma and Carcinoma with 7086 and 7457 genes of 4 and 18 patients respectively is used for this study. Increase in the classification rate of the proposed new method is clearly demonstrated in the results.

The aim of this research work is to study low cyclic fatigue behavior of extended end plate connection by changing the connection geometrical parameters. In spite of numerous researches performed in end plate connection, works related to cyclic fatigue behavior of steel connections is found to be less. Five number of beam-column connection specimens were tested under cyclic loading condition. The low cyclic fatigue behavior was examined for varied end plate thickness keeping the diameter of bolt as constant and vice versa. The displacement approach as per FEMA 461, was used to investigate the moment capacity of the connection. The moment-rotation hysteresis curve was obtained for each specimen and fatigue life was calculated based on number of cycles required for failure of specimen. Using the relation between plastic strain, fatigue life and moment capacity, total hysteresis energy was calculated. From the comparison of results of five specimens tested, the one used with thicker end plate has shown better performance in terms of moment capacity as well as energy dissipation.

Background/Objectives: Most of the seismic codes used today, incorporate the nonlinear response of a structure by the provision of an appropriate response reduction factor ‘R’ so that a linear elastic force based approach can be used for design. The value of R factor varies from 3 to 5 in IS 1893 for RC moment resisting frames, but it does not provide information on the components of R factor. This study focuses on the evaluation of the actual value of R for stepped buildings. Methods/Statistical Analysis: Three dimensional models with varying number of storeys in each step were created, consisting of both ordinary RC moment resisting frame and special RC moment resisting frame having 3, 6 and 9 storeys. Nonlinear static pushover analysis is carried out on the analytical models using finite element analysis software SAP 2000. The R factor components such as ductility and over strength factors were computed from the results obtained from the nonlinear static pushover analysis and finally the response reduction factor is calculated for all the models. The pattern of variation in R factor with the increase in the number of stories is investigated for both OMRF and SMRF in this study. Findings: The actual value of the R factor was found to be less than the value assumed during the design process and its value was found to decrease with the increase in the number of storeys. A certain percentage reduction in the response reduction factor has to be considered for irregular buildings. Application/Improvements: This study is focused only on the influence of height on the value of response reduction factor. Further research is needed considering a wider set of parameters.

In this study, we applied a novel method by using correlation coefficient filter for dimensionality reduction followed by fuzzy rough quick reduct algorithm for feature selection. The classification performance was evaluated using the gene subsets obtained from correlation based filter and our proposed method. Later we compared the results with other traditional classifier techniques. After suitable experimental analysis, it has been found that our proposed method has a two-fold advantage namely selection of much lesser number of genes compared to correlation coefficient and improved classifier accuracy in majority of the cases. This approach also reduces the number of misclassifications that might occur in other approaches.

The Meitei is the dominant group in Manipur, the eastern-most state of India. They formed their state in the early part of first century and played a role as an international actor in the Indo-Burma region. Their state was transformed to the state of Manipur in due course of history. The society became a Hindu society in 18th century, by synthesizing their traditional religion with the Hinduism. In the early 19th century, Manipur suffered seven year devastation (1817-1826), locally called Chahi taret khundakpaa, at the hands of the Burmese. Due to this devastation, there was a Meitei Diaspora. It caused a large scale migration of the Meitei to many places in Myanmar, Bangladesh and other Indian states of Assam and Tripura. Today, there are a number of Meitei villages in these states and countries. The paper tries to examine the people's percepts of their identity, relationship between Homeland (Manipur) politics and Diaspora communities in other states. Identity politics is not all homogenous throughout the Meitei world. The local socio-political settings and their immediate historical conditions shape the nature of politics. The homeland is in their cultural mappings but its politics is not part of the Diaspora communities' realities.

This paper discusses the operating parameters of a two-echelon 'm' Vendors - 'n' Buyers Vendor Managed Inventory (VMI) System with outsourcing (MVMBO). The operational parameters to the above model are the selling prices at the buyer's market and the contract prices between the vendors and the buyers. Selling prices depend on sales quantities and determines the channel profit of the supply chain (SC). Contract prices depend on the understanding between partners on their revenue sharing agreement. A mathematical model of the MV MBO model is formulated to find optimal sales quantities (summation of optimal transaction quantities) for maximum channel profit. Optimal outsourcing quantities, selling prices and acceptable contract prices are derived from the obtained optimal transaction quantities. The mathematical model formulation of MV MBO involves mixed integer variable, a non-linear objective function and linear constraints which fall under the category of Mixed Integer Non-linear Programming (MINP) optimization problem. Simulated Annealing Algorithm (SAA) based heuristic is proposed to find the optimal operational parameters of the MVMBO problem. The proposed methodology is evaluated for its solution quality.

Tannase (tannin acyl hydrolase, E.C.3.1.1.20) is an important hydrolysable enzyme with innumerable applications and industrial potential. In the present study, a kinetic model has been developed for the batch fermentation used for the production of tannase by A.flavus MTCC 3783. Maximum tannase activity of 143.30 U/ml was obtained at 96 hours under optimum operating conditions at 35oC, an initial pH of 5.5 and with an inducer tannic acid concentration of 3% (w/v) for a fermentation period of 120 hours. The biomass concentration reaches a maximum of 6.62 g/l at 96 hours and further there was no increase in biomass concentration till the end of the fermentation. Various unstructured kinetic models were analyzed to simulate the experimental values of microbial growth, tannase activity and substrate concentration. The Logistic model for microbial growth , Luedeking - Piret model for production of tannase and Substrate utilization kinetic model for utilization of substrate were capable of predicting the fermentation profile with high coefficient of determination (R2) values of 0.980, 0.942 and 0.983 respectively. The results indicated that the unstructured models were able to describe the fermentation kinetics more effectively., {"references":["C. N Aguilar, and G. Gutiérrez-Sánchez, \"Review: sources, properties,\napplications and potential uses of tannin acyl hydrolase,\" Food Sci.\nTechnol. Int, vol.7, pp. 373-382, 2001.","A. A Esener, J. A Roels, N. W Kossen,\"Theory and applications of\nunstructured growth models: Kinetic and energetic aspects,\" Biotechnol\nBioeng, vol. 25, pp.2803-2841, 1983.","A.E Ghaly, M. Kamal, L. R. Correia,\"Kinetic modeling of continuous\nsubmerged fermentation of cheese whey for single cell protein\nproduction,\" Bioresource Technology, vol. 96, pp. 1143-1152, 2005.","A E. Haggerman, L G. Butler. \"Protein precipitation method for\ndetermination of tannins,\" J. Agric. Food Chem., vol.26, pp.809–812,\n1978.","E. Haslam, J E. Stangroom, \"The esterase and depsidase activities of\ntannase,\" Biochem. J., vol.99, pp.28-31, 1966.","P K. Lekha and B K. Lonsane, \"Production and application of tannin\nacyl hydrolase; state of the art,\" Advances in Applied Microbiology, vol.\n44, pp.215–260, 1997.","W. Madhavakrishna, S M. Bose, Y. Nayudamma, \"Estimation of tannase\nand certain oxidizing enzymes in Indian vegetable tanstuffs,\" Bull. Cent.\nLeath. Res. Instit, vol. 7, pp. 1-11, 1960.","K. C. Mondal, D. Banerjee, M. Jana and B. R. Pati, \"Calorimetric assay\nmethod for determination of the tannase activity,\" Analytical\nBiochemistry, vol. 295, pp. 168-171, 2001.","J. Monod, \"The growth of Bacterial cultures,\" Annual Rev Microbiol,\nvol.3, pp- 371-394, 1949.\n[10] R A Moraine, P Rogovin,\" Xanthan biopolymer production at increased\nconcentration by pH control,\" Biotechnol Bioengg, vol.13, pp.381-391,\n1971.\n[11] G. Narasimha, A. Sridevi, B. Viswanath, M. Subhosh Chandra, B.\nRajasekarreddy, \"Nutrient effects on production of cellulytic enzymes\nby A. niger,\" African Journal of Biotechnology, vol. 5(5), pp. 472-476,\n2005.\n[12] H. Pourrat, F. Regerat, A. Pourrat, D. Jean, \"Production of gallic acid\nfrom tara tannin by a strain of A. niger,\" J. Ferment. Technol., vol.63,\npp. 401-403, 1985.\n[13] K. Schuegerl, H Bellgardt Bioreaction engineering, modeling and\ncontrol. Springer, Berlin Heidelberg New York. 2000.\n[14] A. P. M. Tavares, M. A. Z. Coelho, J. A. P. Cautinho, A. M. R. B.\nXavier, \"Laccase improvement in submerged cultivation: induced\nproduction and kinetic modeling,\" J Chem Technol Biotechnol, vol. 80,\npp. 669- 676, 2005.\n[15] M Thilakavathi, T Basak, T Panda, \"Modeling of enzyme production\nkinetics,\" Appl Microbiol Biotechnol, vol.73, pp.991-1007, 2007.\n[16] R. M. Weiss, D F. Ollis, \"Extracellular microbial polysaccharides:\nSubstrate, biomass and Product kinetic equations for batch xanthan gum\nfermentation,\" Biotechnol. Bioengg, vol.22, pp.859-873."]}

Polymer mediated drug delivery system represents a novel promising platform for tumor-targeting with reduced systemic side effects and improved chemotherapeutical efficacy. In this study, we report the preparation and characterization of herceptin targeted, diglycolamic acid (DGA) functionalized polyamidoamine (PAMAM) dendrimer as a potent drug carrier for cisplatin. DGA dendrimers carrying cisplatin demonstrated enhanced anticancer activity when targeted with herceptin. In vitro cell line studies with herceptin-DGA-G4-cisplatin in HER-2 +ve and HER-2 -ve human ovarian cancer cell lines showed that these nanoparticles possessed remarkable features such as lower IC50 value, improved S-phase arrest, and enhanced apoptosis due to increased cellular uptake and accumulation than the untargeted DGA-G4-cisplatin and free cisplatin. Furthermore, in vivo results in SCID mice bearing SKOV-3 tumor xenografts, herceptin-DGA-G4-cisplatin, appeared to be more effective in inducing tumor regression as compared to free cisplatin. Collectively, these results indicate that herceptin targeted DGA functionalized PAMAM-cisplatin conjugates serve as better anti-tumor agents than individual therapeutic agents. � 2015 Elsevier B.V. All rights reserved.

In recent times a lot of work has been carried out in the field of reversible data hiding (RDH) to prevent the secret data from theft, illegal copying and unlawful reproduction. In RDH the cover image will be recovered after extracting the secret data which was embedded in that image. Finding the best location to hide the secret data is an important task so that it will conceal the existence of the message. This paper provides a reversible data hiding technique based on Firefly algorithm (FA). The optimal location to hide the secret data will be found by firefly algorithm. The histogram shifting technique is used to embed the secret data in the cover image. Histogram Techniques have attracted increasing interests due to their low computational complexity, high visual quality and can achieve good performance in terms of PSNR values.

The political culture of Manipur is at a crossroad. Two opposite poles of conformists and deviants are operating in the culture. Because of these poles, the people are divided over various issues. The present paper examines the political stands of the Meiteis to three major issues: Merger of Manipur into India, Political status of Manipur, and Identity Issues. The Meitei is the dominant group in Manipur. The inconsistency of the people in their views and stand over the issues is obviously observed. This inconsistency is mainly due to the incomplete socialization of the people and it is the indication of the failure of the two poles.