Nonlinear voter models: the transition from invasion to coexistence

In nonlinear voter models the transitions between two states depend in a nonlinear manner on the frequencies of these states in the neighborhood. We investigate the role of these nonlinearities on the global outcome of the dynamics for a homogeneous network where each node is connected to m = 4 neighbors. The paper unfolds in two directions. We first develop a general stochastic framework for frequency dependent processes from which we derive the macroscopic dynamics for key variables, such as global frequencies and correlations. Explicit expressions for both the mean-field limit and the pair approximation are obtained. We then apply these equations to determine a phase diagram in the parameter space that distinguishes between different dynamic regimes. The pair approximation allows us to identify three regimes for nonlinear voter models: (i) complete invasion; (ii) random coexistence; and - most interestingly - (iii) correlated coexistence. These findings are contrasted with predictions from the mean-field phase diagram and are confirmed by extensive computer simulations of the microscopic dynamic

Identification and differentiation of indigenous non- Basmati aromatic rice genotypes of India using microsatellite markers

Aromatic rice is preferred by consumers all over the world due to its flavor and palatability. Although large number of them is available, little analysis of the genetic diversity has been done at molecularlevel so far. Twelve microsatellite primer pairs, one from each chromosome of rice were used for evaluating the genetic diversity of 38 traditional indigenous non-Basmati aromatic rice cultivars. A totalof 32 different reproducible bands were amplified of which 26 (81.25%) were polymorphic. The number of bands per primer ranged from one to six with an average of 2.6 bands per primer. Ten primers(83.3%) revealed polymorphism between cultivars. Polymorphism information content ranged between 0.00 to 0.83. A dendrogram based on cluster analysis by microsatellite polymorphism grouped all the 38aromatic rice genotypes into three major groups effectively differentiating the slender aromatic rice cultivars from the short bold and long bold aromatic cultivars. Interestingly, Katrani, medium slenderaromatic rice from Bihar had to be grouped separately being genotypically different from other cultivars. It could be concluded that microsatellite markers could efficiently identify indigenous non-Basmati aromatic rice genotypes which can help in genetic  conservation management and support intellectual property protection

Complexity Study and Chaos Control in a Prey-Predator System

A prey-predator system has been investigated with the application of random shock. Since the fluctuations of populations are random, the applied shock is also assumed like a random noise. To study complexities during evolution, numerical simulations have been carried out for both cases, without shock and with shock. Stabilities of fixed points have been discussed for both the cases. Also, bifurcation diagrams for both the cases have been drawn by varying a parameter while keeping other parameters fixed. Numerical calculations have been extended to obtain plots of Lyapunov exponents and topological entropies as the measure of complexity in the system. It has been observed that the random shock has little impact to reduce the chaotic motion in the system. Then, certain periodic changes in a parameter have been allowed to some extent,this results in bringing the system from chaos to regularity. Such changes may happen naturally in a prey-predator system and so there exists the possibility of coexistence. The chaos indicator DLI has been used for clarity in detection of regular and chaotic motion. Finally,the correlation dimension for the chaotic set has also been calculated for certain set of parameter values

Neutron-proton effective mass splitting and thermal evolution in neutron rich matter

The thermal evolution of properties of neutron rich asymmetric nuclear matter such as entropy density, internal energy density, free energy density and pressure are studied in the non-relativistic mean field theory using finite range effective interactions. In this framework the thermal evolution of nuclear matter properties is directly connected to the neutron and proton effective mass properties. Depending on the magnitude of neutron-proton effective mass splittings, two distinct behaviours in the thermal evolution of nuclear matter properties are noticed.Comment: 19 pages, 9 figures, Submitted to J.Phys.G:Nucl.Part.Phy

Vegetative propagation of physic nut (Jatropha curcas L.) through stem cuttings

The selected healthy branches of Jatropha curcas were cut into 15 cm and 25 cm length having 4 to 5 nodes in each category of apical portion (thickness < 1cm), middle portion (1.0 to 1.5 cm) and basal portion (1.5 to 2 cm). The base positions of apical, middle, basal portions of cuttings were dipped in the 100, 200, 400, 800 and 1000 ppm of IAA (Indole-3-acetic acid) and IBA (Indole-3-butyric acid) respectively for four hours. After which the cuttings were planted in the polypots filled with rooting media consists of sand, soil and farm yard manure (FYM) in the ratio of 1:2:1. Maximum sprouting (100%) was observed in 25 cm as well as 15 cm length cuttings of different portions. In case of 25 cm length different sections like apical cuttings when treated with 200 ppm, 800 ppm IAA and 400 ppm IBA, basal cutting with 800 ppm IAA and 200, 400 ppm IBA and middle cuttings with 200 ppm IAA, similarly 15cm length basal portion cutting treated with 400 ppm IAA produce 100 per cent sprouting. Other characters like rooting percentage (93.33%), root length (37.66cm), fresh biomass (73.21g) and dry biomass (34.06g) were observed maximum in apical portion cutting of 25 cm length treated with 100 ppm IBA, 800 ppm IBA, 100 ppm IAA and 100 ppm IAA respectively where as root number (17.0) found maximum in middle portion cutting of 15cm length treated with 1000 ppm IAA. It showed that the apical portion of 25 cm length cuttings treated with IAA and IBA resulted in maximum sprouting, rooting percentage, root length, fresh biomass and dry biomass production

Leaching of nickel laterite using fungus mediated organic acid and synthetic organic acid: a comparative study

A huge amount of overburden (nearly 8 to 10 times of the ore) containing trace amount of nickel and cobalt is generated during Chromite mining at Sukinda valley, Orissa, Chromite overburden contains around 0.4 to 0.9% Ni and 0.02–0.05% Co respectively. The setting up of nickel and cobalt processing plant based on these deposits through conventional methods such as pyrometallurgy and hydrometallurgy is not economical. The microbes and metals interaction have been studied for the exploitation in metals extraction. So an attempt has been made to extract these metals using multi metal resistant indigenous microorganisms, isolated from the Chromite overburden of Sukinda mines. A native strain of Aspergillus species was used for bioleaching. Aspergillus species are well known for their potential to produce a variety of organic acids (oxalic, citric acids etc.). The mineralogical studies indicated that there is no separate nickel bearing mineral phase in the Sukinda Chromite overburden. The mineralogy of the raw lateritic ore reveals the presence of goethite, ferrihydrites as major minerals. In the thermally activated overburden the minerals present were hematite, surimarite, quartz and traces of magnetite. Experiments were carried out with synthetic organic acids at 2.5% pulp density, 350C and 150rpm. Synthetic oxalic acid (0.1 M) leached 5% Ni and 71% Co from raw ore, whereas it leached 43% Ni and 95% Co from thermally activated ore. Citric acid (0.1 M) was not that much efficient. It leached 9% Ni and 14% Co from raw ore and 32% Ni and 45% Co from thermally activated ore. The fungal culture filtrate leached 3% Ni and 12% Co from raw ore. In case of roasted ore it leached 18% Ni and 28% Co at 2.5% pulp density, 35°C and 150rpm. Mineralogical analysis was carried out through X-ray diffraction, FTIR and transmission electron microscopy

Domain-Independent Disperse and Pick method for Robotic Grasping

Picking unseen objects from clutter is a difficult problem because of the variability in objects (shape, size, and material) and occlusion due to clutter. As a result, it becomes difficult for grasping methods to segment the objects properly and they fail to singulate the object to be picked. This may result in grasp failure or picking of multiple objects together in a single attempt. A push-to-move action by the robot will be beneficial to disperse the objects in the workspace and thus assist the grasping and vision algorithm. We propose a disperse and pick method for domain-independent robotic grasping in a highly cluttered heap of objects. The novel contribution of our framework is the introduction of a heuristic clutter removal method that does not require deep learning and can work on unseen objects. At each iteration of the algorithm, the robot either performs a push-to-move action or a grasp action based on the estimated clutter profile. For grasp planning, we present an improved and adaptive version of a recent domain-independent grasping method. The efficacy of the integrated system is demonstrated in simulation as well as in the real-world.Comment: Published at 2022 International Joint Conference on Neural Networks (IJCNN

Multiclass Fuzzy Time-Delay Common Spatio-Spectral Patterns with Fuzzy Information Theoretic Optimization for EEG-Based Regression Problems in Brain-Computer Interface (BCI)

© 2019 IEEE. Electroencephalogram (EEG) signals are one of the most widely used noninvasive signals in brain-computer interfaces. Large dimensional EEG recordings suffer from poor signal-to-noise ratio. These signals are very much prone to artifacts and noise, so sufficient preprocessing is done on raw EEG signals before using them for classification or regression. Properly selected spatial filters enhance the signal quality and subsequently improve the rate and accuracy of classifiers, but their applicability to solve regression problems is quite an unexplored objective. This paper extends common spatial patterns (CSP) to EEG state space using fuzzy time delay and thereby proposes a novel approach for spatial filtering. The approach also employs a novel fuzzy information theoretic framework for filter selection. Experimental performance on EEG-based reaction time (RT) prediction from a lane-keeping task data from 12 subjects demonstrated that the proposed spatial filters can significantly increase the EEG signal quality. A comparison based on root-mean-squared error (RMSE), mean absolute percentage error (MAPE), and correlation to true responses is made for all the subjects. In comparison to the baseline fuzzy CSP regression one versus rest, the proposed Fuzzy Time-delay Common Spatio-Spectral filters reduced the RMSE on an average by 9.94%, increased the correlation to true RT on an average by 7.38%, and reduced the MAPE by 7.09%