Effect of Varied Packages of Yogic Practices on Selected Motor Ability and Physiological Variables among College Level Hockey Players

The purpose of the study was to find out the effect of varied packages of yogic practices on selected motor ability and physiological variables among college level hockey players. To facilitate the study, 90 subjects were selected at random from S.I.V.E.T College Gowrivakkam TamilNadu. Their age was ranged between 18-25 years. They were assigned into three groups Group 1 served as Swami Satyananda Saraswati Yogic Practices group (EX GP1), Group 2 served as Swami Vishnudevananda Yogic Practices group (EX GP 2) and third one as control group. All the subjects were tested prior to and immediately after the six weeks treatment in progression motor ability such as muscular strength and cardio vascular endurance and physiological variables such as vital capacity and VO2 Max. The initial and final scores in selected motor ability, physiological, variables were put in-to statistical treatment using Analysis of Covariance (ANCOVA) to find out the significant mean differences. Scheffe s post hoc test was used to find out the paired mean differences. In all the cases the 0.05 level of confidence was fixed

Cyclic Symmetry of Riemann Tensor in Fuzzy Graph Theory

In this paper, we define a graph-theoretic analog for the Riemann tensor and analyze properties of the cyclic symmetry. We have developed a fuzzy graph-theoretic analog of the Riemann tensor and have analyzed its properties. We have also shown how the fuzzy analog satisfies the properties of the 6X6 matrix of the Riemann tensor by expressing it as a union of the fuzzy complete graph formed by the permuting vertex set and a Levi-Civita graph analog. We have concluded the paper with a brief discussion on the similarities between the properties of the fuzzy graphical analog and the Riemann tensor and how it can be a plausible analogous model for the Petrov-Penrose classification.Comment: 12 pages, 1 figur

Determinants of adoption and preferences for Aman rice mutant variety Binadhan-7 cultivation in Bangladesh

This study was conducted in fourteen agricultural regions of Bangladesh namely-Mymensingh, Jashore, Cumilla, Bogura, Rajshahi, Sylhet, Dinajpur, Rangpur, Dhaka, Khulna, Chattagram, Rangamati, Barishal and Faridpur. The specific objectives of the present study were: i) to examine the determinants to adoption of rice mutant variety Binadhan-7; and ii) to identify the major preferences and constraints of rice mutant variety Binadhan-7 cultivation; A multistage stratified random sampling technique was used to collect the data. Marginal coefficients indicate that if male farmers increased by 100%, the probability of adopting Binadhan-7 variety would increase at 38 times more likely to adopt the variety. If the farm size of Binadhan-7 increased by 100%, the probability of adopting the variety would be increased by 0.07%. A farmer who has access to agricultural extension service is about 39 times more likely to adopt the variety. Again, if the yield increased by 100%, adopting the varieties would increase by 0.08%. The marginal coefficients of duration and soil fertility are negatively significant, indicating that if these two variables increased by 100%, the probability of adopting the varieties would decrease by 0.18% and 28%, respectively. Among the preferences, the highest preference was 88.93% for short duration followed by poverty reduction (88.57%), and lastly high yielding (81.43%). Among the constraints, the highest constraint was 80.71% for high labour price followed by lack of godown (69.64%), marketing problem (67.50%), destroy by bird (66.79%) and lack of quality seed (48.93%)

Optimization of Intracranial Hemorrhage Using CT Scan Images and Feature Extraction

Intracranial bleeding is among the most severe forms of brain stroke. The neurologic effects and artery rupture cause bleeding in the brain and the tissue around it. Haemorrhage is classified based on where the bleeding occurs on the brain. This paper depicts the application of multiple machine-learning approaches to separate CT scan images into normal and pathological categories. Separate analysis is conducted on the functionality of the features extracted from the various texturing approaches, such as the Grey Level Co-occurrence Matrix (GLCM) and Grey Level Run-Length Matrix (GRLM). Particle Swarm Optimisation (PSO) and K-Nearest Neighbours are used to choose relevant characteristics that increase the classification accuracy for feature extraction. The findings demonstrate that these texture features have excellent discrimination accurac

Modelling of an Artificial Neural Network for Electrical Discharge Machining of Hot Pressed Zirconium Diboride-Silicon Carbide Composites

Modelling is carried out to map the relationship between the input process parameters and the output response, considered in the machining process. To represent real-world systems of considerable complexity, an artificial neural network (ANN) model is often utilized to replace the mathematical approximation of the relationship. This paper explains the methodological procedure and the outcome of the ANN modelling process. The percentage of SiC in the workpiece material, the product of thermal conductivity and the melting point of the tool material, the pulse on time, and the pulse off time are considered as input parameters, while the material removal rate (MRR), the tool wear rate (TWR), roughness, roundness, taper angle and overcut are considered as output responses. The network is trained initially with one neuron in the hidden layer, i.e.,-a 4-4-6 topology is considered for training. In the subsequent phases, the number of hidden neurons in the hidden layer is increased gradually and then the network is tested with two hidden layers with the same number of hidden neurons in the second hidden layer. A feed forward back propagation neural network model with one hidden layer having 35 neurons is found to be the optimum network model (4-35-35-6). The model has the mean correlation coefficient of 0.92408

Electro-coagulation coupled Electro-floatation process: Feasible choice in Doxycycline removal from Pharmaceutical effluents

Article CC-BYInternational audienceElectrochemical treatment involving a coupled coagulation and floatation was performed in the removal of Doxycycline Hyclate (DCH) from aqueous solutions. All the experiments were carried out in an electrochemical reactor of 1.5 L which contained aluminium electrodes as cathode and anode. The removal of doxycycline hyclate (DCH) species by EC/EF was determined as a function of electrolysis time, pH, current intensity, flow rate and DCH concentration. From the observed results, it was corroborated that the DCH removal through the EC/EF process was excellent. The effective contribution from initial pH (7.03) and current intensity (5.39 mA cm-2) was very much remarkable and well apparent from flocs of good buoyancy. The removal of DCH was inversely proportional to spacing between electrodes (SBE) and circulating flow rate in the presence of the supporting NaCl electrolyte of 1 g L-1. It was also highly promoted by the addition of NaCl in comparison to NaNO3 and KCl to the electrolytic system. The compliance of four kinetic models was verified with DCH removal system. The free energy values from DKR model suggested the nature of bonding by chemical forces. Characterization by FTIR, SEM and XRD interpreted the assignments of various functional groups, surface morphology and crystalline incorporated amorphous nature, respectively of electro – generated flocs. The current efficiency and specific electrical energy consumption at optimized conditions of the EC/EF system were calculate

Risk factors of musculoskeletal disorders (MSD) among palm oil mill workers

The palm oil industry is the fourth largest contributor to the Malaysian Gross National Income (GNI) but the importance of this industry to the nation’s economy does not preclude them from the risk of being affected by the occurrence of musculoskeletal disorders (MSD) among the workers in palm oil mills. Previous studies carried out have not properly explained the exact reasons for the occurrence of musculoskeletal disorders (MSD) among the palm oil mill workers. Thus, this study aim to determine the association between risk factors and MSD among palm oil mill workers. A total of 120 male workers were consecutively enrolled in this crosssectional study. Information on sociodemographic, working, lifestyle, health and injury factors were collected via questionnaire and face-to-face interviews. A high lifetime prevalence of MSD (71.7 percent) among palm oil mill workers was found. However, the one-year prevalence of MSD among the same population was only 50.8 percent. Logistic regression analysis adjusted for age, Body Mass Index (BMI) and smoking revealed that the risk factors: history of previous injury [2.35, 95 percent CI 1.12-4.93], Osteoarthritis [3.9, 95 percent CI 1.568-9.708] and perception of exertion [8.09, 95 percent CI 1.358-48.170] was found to be significantly associated with MSD symptoms reported in the past 12 months. As a conclusion, exposure to the combination of these risk factors may lead to an increased risk of developing MSD among palm oil mill workers

AN INSIGHT INTO THE VOLUME COMPONENT GENERATED FROM RISAT-1 HYBRID POLARIMETRIC SAR DATA FOR CROP BIOPHYSICAL PARAMETERS RETRIEVAL

Polarimetric parameters have been extensively used for target parameters retrieval than backscattering coefficients. In previous studies, volume component generated from polarimetric SAR data has been considered as the return signal component from vegetation and intern used this for biophysical parameters retrieval. Un-polarized component of the return signal has been considered as volume component. The present study is mainly focused to analyze the volume component generated from C-band RISAT-1 hybrid polarimetric SAR data from wheat crop. Three temporal datasets acquired at ∼31° central incidence angle between Jan and Mar 2016 over parts of Bharatpur and Mathura districts located in Rajasthan and Uttar Pradesh (India) have been used in this study. Water Cloud Model with Gaps has been considered for modeling the first Stokes parameter (g0), which represents total intensity of return signal, from wheat crop using LAI and Interaction factor as vegetation descriptors. The vegetation component derived using calibrated Water Cloud Model with Gaps has been analyzed with volume component derived from RISAT-1 hybrid polarimetric SAR data. The analyses observed that a significant difference during lower LAI values and shown comparably during higher LAI values. The higher values of volume component derived from RISAT-1 SAR data than modeled vegetation component indicates that the volume component can also be generated by underneath soil. It is also observed the difference in derived un-polarized component and modeled vegetation component has shown higher correlation with underneath soil moisture than directly correlating with derived un-polarized component. This study indicates that the volume component derived from hybrid polarimetric SAR data has return signals from vegetation as well as underneath soil

THE SENSITIVITY OF C-BAND HYBRID POLARIMETRIC RISAT-1 SAR DATA TO LEAF AREA INDEX OF PADDY CROP

Active microwave remote sensing data has become an important source to retrieve crop biophysical parameters due to its unique sensitivity towards geometrical, structural and dielectric properties of various crop components. The temporal variability of various crop biophysical parameters during crop cycle has significant impact on the overall crop yield. In this study, two RISAT-1 hybrid polarimetric temporal SAR datasets at ∼32° incidence angle were acquired during 2015 Kharif season. The in-situ leaf area index (LAI) values from seventeen paddy fields were measured in synchrony to the satellite passes during both the campaigns. Analysis observed the decreasing trend of backscattering coefficients (σ°RH, σ°RV) with increase in LAI. Results indicate that the sensitivity of hybrid polarimetric parameters towards LAI, also depends on the change in crop structure due to crop growth. This study investigate the sensitivity of backscattering coefficients (σ°RH, σ°RV) and polarimetric parameters (even bounce, odd bounce and volume component) generated from m-δ, m-χ and m-α space decompositions towards LAI using empirical analysis. An increase of 0.16 in R2 (from 0.63 to 0.79) clearly indicates that the polarimetric parameters (even bounce, odd bounce and volume component) are more sensitive to LAI of paddy crop than the backscattering coefficients (σ°RH, σ°RV). It has been identified that the combined use of backscattering coefficients as well as polarimetric parameters (even bounce, odd bounce and volume component) in the model, can significantly improve the accuracy of the LAI estimation

Complex regulation by Apetala2 domain-containing transcription factors revealed through analysis of the stress-responsive TdCor410b promoter from durum wheat

Expression of the wheat dehydrin gene Cor410b is induced several fold above its non-stressed levels upon exposure to stresses such as cold, drought and wounding. Deletion analysis of the TdCor410b promoter revealed a single functional C-repeat (CRT) element. Seven transcription factors (TFs) were shown to bind to this CRT element using yeast one-hybrid screens of wheat and barley cDNA libraries, of which only one belonged to the DREB class of TFs. The remaining six encoded ethylene response factors (ERFs) belong to three separate subfamilies. Analysis of binding selectivity of these TFs indicated that all seven could bind to the CRT element (GCCGAC), and that three of the six ERFs could bind both to the CRT element and the ethylene-responsive GCC-box (GCCGCC). The TaERF4 subfamily members specifically bound the CRT element, and did not bind either the GCC-box or DRE element (ACCGAC). Molecular modeling and site-directed mutagenesis identified a single residue Pro42 in the Apetala2 (AP2) domain of TaERF4-like proteins that is conserved in monocotyledonous plants and is responsible for the recognition selectivity of this subfamily. We suggest that both DREB and ERF proteins regulate expression of the Cor410b gene through a single, critical CRT element. Members of the TaERF4 subfamily are specific, positive regulators of Cor410b gene expression.Omid Eini, Nannan Yang, Tatiana Pyvovarenko, Katherine Pillman, Natalia Bazanova, Natalia Tikhomirov, Serik Eliby, Neil Shirley, Shoba Sivasankar, Scott Tingey, Peter Langridge, Maria Hrmova, Sergiy Lopat