Modern pollen dispersal in relation to present vegetation distribution and land use in the Baspa valley, Kinnaur, western Himalayas.

Interpretation of a fossil pollen data for the vegetation and climate reconstruction of any region needs a modern pollen-vegetation analogue for its calibration. We analyzed the surface sediments and moss polsters for the pollen and microcharcoal records to understand the modern pollen-vegetation relationship and human activities in the Baspa Valley, Kinnaur, Himachal Pradesh. Presently, valley is occupied by the arboreal and non-arboreal vegetation of temperate to subalpine habitats and land use activities. The recovered pollen assemblages showed variability in the dispersal behavior of pollen of taxa growing along the valley transect and also captured the signals of human activities over land use. The overall dominance of arboreal pollen in the recovered pollen assemblage corresponds with the dominant growth of conifers and broadleaf tree taxa and represents the valley vegetation at a regional scale. However, the profuse pollen production of a few arboreal taxa and long distance pollen transport from one vegetation zone to other by the strong upthermic valley winds could bias the pollen representation of in-situ vegetation. The high pollen frequency of non-arboreal taxa in the open meadows represents the near vicinity to their plant source. Human activities like fire burning and cultivation by the local population are evident by the recovery of microcharcoal particles and pollen of plants belonging to Cerealia Poaceae, Asteraceae, Amaranthaceae, Polygonaceae, Rosaceae, Juglandaceae, etc. The dataset taken as modern pollen-vegetation analogue is useful to assess past changes in the vegetation and land cover in relation to climate and human factors for future sustenance.

Parameterized MDPs and Reinforcement Learning Problems-A Maximum Entropy Principle-Based Framework.

We present a framework to address a class of sequential decision-making problems. Our framework features learning the optimal control policy with robustness to noisy data, determining the unknown state and action parameters, and performing sensitivity analysis with respect to problem parameters. We consider two broad categories of sequential decision-making problems modeled as infinite horizon Markov decision processes (MDPs) with (and without) an absorbing state. The central idea underlying our framework is to quantify exploration in terms of the Shannon entropy of the trajectories under the MDP and determine the stochastic policy that maximizes it while guaranteeing a low value of the expected cost along a trajectory. This resulting policy enhances the quality of exploration early on in the learning process, and consequently allows faster convergence rates and robust solutions even in the presence of noisy data as demonstrated in our comparisons to popular algorithms, such as Q -learning, Double Q -learning, and entropy regularized Soft Q -learning. The framework extends to the class of parameterized MDP and RL problems, where states and actions are parameter dependent, and the objective is to determine the optimal parameters along with the corresponding optimal policy. Here, the associated cost function can possibly be nonconvex with multiple poor local minima. Simulation results applied to a 5G small cell network problem demonstrate the successful determination of communication routes and the small cell locations. We also obtain sensitivity measures to problem parameters and robustness to noisy environment data.

In vitro propagation and cytological analysis of Sophora mollis Royle: an endangered medicinal shrub.

BACKGROUND: Sophora mollis Royle (family Fabaceae, subfamily-Papilionaceae) is a multipurpose legume distributed in plains and foothills of the North-West Himalaya to Nepal and is facing high risk of extinction due to habitat loss and exploitation by the local people for its fuel and fodder values. Therefore, the present study was conducted to standardize a micropropagation protocol for Sophora mollis by using shoot tip explants and to study the meiotic chromosome count in the species. RESULTS: Multiple shoots were induced in shoot tip explants of Sophora mollis in Murashige and Skoog medium supplemented with different concentrations of cytokinins alone (BAP, TDZ, and Kinetin) and in combination with varying concentrations of NAA. MS medium supplemented with BAP (8.9 µM) was observed to be the optimal medium for multiple shoot induction and maximum 25.32 shoots per explant was obtained with average length of 4.5 ± 0.8 cm. In vitro developed shoots were transferred onto rooting media supplemented with different concentrations of auxin (IAA, IBA, and NAA). Maximum 86% rooting was observed in half-strength MS medium supplemented with 21.20 µM NAA with an average of 21.26 roots per culture. In vitro raised plantlets were adapted to greenhouse for better acclimatization and 60% plants were successfully transferred to the open environment. Based on the chromosome counts available from the literature and the current study, the species tend to show a basic chromosome number of x = 9. CONCLUSION: The micropropagation protocol standardized can be helpful for the ex situ mass multiplication and germplasm conservation of the endangered species. Moreover, the ex situ conservation approach will be helpful in actively bridging the gap between ex situ and in situ approaches through the reintroduction of species in the wild. The cytological studies revealed the basic chromosome number x = 9 of the species.