Genetic Heterogeneity in Wild Isolates of Cellular Slime Mold Social Groups

This study addresses the issues of spatial distribution, dispersal, and genetic heterogeneity in social groups of the cellular slime molds (CSMs). The CSMs are soil amoebae with an unusual life cycle that consists of alternating solitary and social phases. Because the social phase involves division of labor with what appears to be an extreme form of "altruism", the CSMs raise interesting evolutionary questions regarding the origin and maintenance of sociality. Knowledge of the genetic structure of social groups in the wild is necessary for answering these questions. We confirm that CSMs are widespread in undisturbed forest soil from South India. They are dispersed over long distances via the dung of a variety of large mammals. Consistent with this mode of dispersal, most social groups in the two species examined for detailed study, Dictyostelium giganteum and Dictyostelium purpureum, are multi-clonal.

Implications of Energy Profile and Storage on Energy Harvesting Sensor Link Performance

Energy harvesting sensors (EHS), which harvest energy from the environment in order to sense and then communicate their measurements over a wireless link, provide the tantalizing possibility of perpetual lifetime operation of a sensor network. The wireless communication link design problem needs to be revisited for these sensors as the energy harvested can be random and small and not available when required. In this paper, we develop a simple model that captures the interactions between important parameters that govern the communication link performance of a EHS node, and analyze its outage probability for both slow fading and fast fading wireless channels. Our analysis brings out the critical importance of the energy profile and the energy storage capability on the EHS link performance. Our results show that properly tuning the transmission parameters of the EHS node and having even a small amount of energy storage capability improves the EHS link performance considerably.

Optimal Sleep-Wake Policies for an Energy Harvesting Sensor Node

We study a sensor node with an energy harvesting source. In any slot,the sensor node is in one of two modes: Wake or Sleep. The generated energy is stored in a buffer. The sensor node senses a random field and generates a packet when it is awake. These packets are stored in a queue and transmitted in the wake mode using the energy available in the energy buffer. We obtain energy management policies which minimize a linear combination of the mean queue length and the mean data loss rate. Then, we obtain two easily implementable suboptimal policies and compare their performance to that of the optimal policy. Next, we extend the Throughput Optimal policy developed in our previous work to sensors with two modes. Via this policy, we can increase the through put substantially and stabilize the data queue by allowing the node to sleep in some slots and to drop some generated packets. This policy requires minimal statistical knowledge of the system. We also modify this policy to decrease the switching costs.

Joint Power Control, Scheduling and Routing for Multihop Energy Harvesting Sensor Networks

We study wireless multihop energy harvesting sensor networks employed for random field estimation. The sensors sense the random field and generate data that is to be sent to a fusion node for estimation. Each sensor has an energy harvesting source and can operate in two modes: Wake and Sleep. We consider the problem of obtaining jointly optimal power control, routing and scheduling policies that ensure a fair utilization of network resources. This problem has a high computational complexity. Therefore, we develop a computationally efficient suboptimal approach to obtain good solutions to this problem. We study the optimal solution and performance of the suboptimal approach through some numerical examples.

Management of bushland vegetation using rainwater harvesting in eastern Kenya.

Microcatchment water harvesting (MCWH) improved the survival and growth of planted trees on heavy soils in eastern Kenya five to six years after planting. In the best method, the cross-tied furrow microcatchments, the mean annual increments (MAI; based on the average biomass of living trees multiplied by tree density and survival) of the total and usable biomass in Prosopis juliflora were 2787 and 1610 kg ha-1 a-1 respectively, when the initial tree density was 500 to 1667 trees per hectare. Based on survival, the indigenous Acacia horrida, A. mellifera and A. zanzibarica were the most suitable species for planting using MCWH. When both survival and yield were considered, a local seed source of the introduced P. juliflora was superior to all other species. The MAI in MCWH was at best distinctly higher than that in the natural vegetation (163­307 and 66­111 kg ha-1 a-1 for total and usable biomass respectively); this cannot satisfy the fuelwood demand of concentrated populations, such as towns or irrigation schemes. The density of seeds of woody species in the topsoil was 40.1 seeds m-2 in the Acacia-Commiphora bushland and 12.6 seeds m-2 in the zone between the bushland and the Tana riverine forest. Rehabilitation of woody vegetation using the soil seed bank alone proved difficult due to the lack of seeds of desirable species. The regeneration and dynamics of woody vegetation were also studied both in cleared and undisturbed bushland. A sub-type of Acacia-Commiphora bushland was identified as Acacia reficiens bushland, in which the dominant Commiphora species is C. campestris. Most of the woody species did not have even-aged populations but cohort structures that were skewed towards young individuals. The woody vegetation and the status of soil nutrients were estimated to recover in 15­20 years on Vertic Natrargid soils after total removal of above-ground vegetation.

Voluntary Energy Harvesting Relays and Selection in Cooperative Wireless Networks

The use of energy harvesting (EH) nodes as cooperative relays is a promising and emerging solution in wireless systems such as wireless sensor networks. It harnesses the spatial diversity of a multi-relay network and addresses the vexing problem of a relay's batteries getting drained in forwarding information to the destination. We consider a cooperative system in which EH nodes volunteer to serve as amplify-and-forward relays whenever they have sufficient energy for transmission. For a general class of stationary and ergodic EH processes, we introduce the notion of energy constrained and energy unconstrained relays and analytically characterize the symbol error rate of the system. Further insight is gained by an asymptotic analysis that considers the cases where the signal-to-noise-ratio or the number of relays is large. Our analysis quantifies how the energy usage at an EH relay and, consequently, its availability for relaying, depends not only on the relay's energy harvesting process, but also on its transmit power setting and the other relays in the system. The optimal static transmit power setting at the EH relays is also determined. Altogether, our results demonstrate how a system that uses EH relays differs in significant ways from one that uses conventional cooperative relays.

Harvesting undelimbed Scots pine (Pinus sylvestris L.) from first thinnings for integrated production of kraft pulp and energy

The present study evaluates the feasibility of undelimbed Scots pine (Pinus sylvestris L.) for integrated production of pulp and energy in a kraft pulp mill from the technical, economic and environmental points of view, focusing on the potential of bundle harvesting. The feasibility of tree sections for pulp production was tested by conducting an industrial wood-handling experiment, laboratory cooking and bleaching trials, using conventional small-diameter Scots pine pulpwood as a reference. These trials showed that undelimbed Scots pine sections can be processed in favourable conditions as a blend with conventional small-diameter pulpwood without reducing the pulp quality. However, fibre losses at various phases of the process may increase when using undelimbed material. In the economic evaluation, both pulp production and wood procurement costs were considered, using the relative wood paying capability of a kraft pulp mill as a determinant. The calculations were made for three Scots pine first-thinning stands with the breast-height diameter of the removal (6 12 cm) as the main distinctive factor. The supply chains included in the comparison were based on cut-to-length harvesting, whole-tree harvesting and bundle harvesting (whole-tree bundling). With the current ratio of pulp and energy prices, the wood paying capability declines with an increase in the proportion of the energy fraction of the raw material. The supply system based on the cut-to-length method was the most efficient option, resulting in the highest residual value at stump in most cases. A decline in the pulp price and an increase in the energy price improved the competitiveness of the whole-tree systems. With short truck transportation distances and low pulp prices, however, the harvesting of loose whole trees can result in higher residual value at stump in small-diameter stands. While savings in transportation costs did not compensate for the high cutting and compaction costs by the second prototype of the bundle harvester, an increase in transportation distances improved its competitiveness. Since harvesting undelimbed assortments increases nutrient export from the site, which can affect soil productivity, the whole-tree alternatives included in the present study cannot be recommended on infertile peatlands and mineral soils. The harvesting of loose whole trees or bundled whole trees implies a reduction in protective logging residues and an increase in site traffic or payloads. These factors increase the risk of soil damage, especially on peat soils with poor bearing capacity. Within the wood procurement parameters which were examined, the CO2 emissions of the supply systems varied from 13 27 kg m3. Compaction of whole trees into bundles reduced emissions from transportation by 30 39%, but these reductions were insufficient to compensate for the increased emissions from cutting and compaction.

Power Management and Data Rate Maximization in Wireless Energy Harvesting Sensors

This paper considers the problem of power management and throughput maximization for energy neutral operation when using Energy Harvesting Sensors (EHS) to send data over wireless links. It is assumed that the EHS are designed to transmit data at a constant rate (using a fixed modulation and coding scheme) but are power-controlled. A framework under which the system designer can optimize the performance of EHS when the channel is Rayleigh fading is developed. For example, the highest average data rate that can be supported over a Rayleigh fading channel given the energy harvesting capability, the battery power storage efficiency and the maximum allowed transmit energy per slot is derived. Furthermore, the optimum transmission scheme that guarantees a particular data throughput is derived. The usefulness of the framework developed is illustrated through simulation results for specific examples.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

Throughput Maximization of Delay-Constrained Traffic in Wireless Energy Harvesting Sensors

A wireless Energy Harvesting Sensor (EHS) needs to send data packets arriving in its queue over a fading channel at maximum possible throughput while ensuring acceptable packet delays. At the same time, it needs to ensure that energy neutrality is satisfied, i.e., the average energy drawn from a battery should equal the amount of energy deposited in it minus the energy lost due to the inefficiency of the battery. In this work, a framework is developed under which a system designer can optimize the performance of the EHS node using power control based on the current channel state information, when the EHS node employs a single modulation and coding scheme and the channel is Rayleigh fading. Optimal system parameters for throughput optimal, delay optimal and delay-constrained throughput optimal policies that ensure energy neutrality are derived. It is seen that a throughput optimal (maximal) policy is packet delay-unbounded and an average delay optimal (minimal) policy achieves negligibly small throughput. Finally, the influence of the harvested energy profile on the performance of the EHS is illustrated through the example of solar energy harvesting.

Coupled electro-mechanical response of an electroactive polymer cantilever structure and its application in energy harvesting

Ionic polymer-metal composites (IPMC), piezoelectric polymer composites and nematic elastomer composites are materials, which exhibit characteristics of both sensors and actuators. Large deformation and curvature are observed in these systems when electric potential is applied. Effects of geometric non-linearity due to the chargeinduced motion in these materials are poorly understood. In this paper, a coupled model for understanding the behavior of an ionic polymer beam undergoing large deformation and large curvature is presented. Maxwell's equations and charge transport equations are considered which couple the distribution of the ion concentration and the pressure gradient along length of a cantilever beam with interdigital electrodes. A nonlinear constitutive model is derived accounting for the visco-elasto-plastic behavior of these polymers and based on the hypothesis that the presence of electrical charge stretches/contracts bonds, which give rise to electrical field dependent softening/hardening. Polymer chain orientation in statistical sense plays a role on such softening or hardening. Elementary beam kinematics with large curvature is considered. A model for understanding the deformation due to electrostatic repulsion between asymmetrical charge distributions across the cross-sections is presented. Experimental evidence that Silver(Ag) nanoparticle coated IPMCs can be used for energy harvesting is reported. An IPMC strip is vibrated in different environments and the electric power against a resistive load is measured. The electrical power generated was observed to vary with the environment with maximum power being generated when the strip is in wet state. IPMC based energy harvesting systems have potential applications in tidal wave energy harvesting, residual environmental energy harvesting to power MEMS and NEMS devices.

Power and Discrete Rate Adaptation for Energy Harvesting Wireless Nodes

Energy Harvesting (EH) nodes, which harvest energy from the environment in order to communicate over a wireless link, promise perpetual operation of a wireless network with battery-powered nodes. In this paper, we address the throughput optimization problem for a rate-adaptive EH node that chooses its rate from a set of discrete rates and adjusts its power depending on its channel gain and battery state. First, we show that the optimal throughput of an EH node is upper bounded by the throughput achievable by a node that is subject only to an average power constraint. We then propose a simple transmission scheme for an EH node that achieves an average throughput close to the upper bound. The scheme's parameters can be made to account for energy overheads such as battery non-idealities and the energy required for sensing and processing. The effect of these overheads on the average throughput is also analytically characterized.

Optimal energy management policies for energy harvesting sensor nodes

We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.