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Eriborus argenteopilosus Cam., is an indigenous solitary larval endoparasitoid of a polyphagous pest Heliothis armigera (Hubn.) in India. Developmental periods of egg, different stages of larva and pupa are described. A detailed description is given on the technique developed for the laboratory mass breeding of E. argenieopilosus on an alternative host, Spodopiera lilura (F.).

Five insecticides and ten fungicides at the recommended field dosages were evaluated for their safety to the encyrtid parasitoid Anagyrus dactylopii (How.) and the coccinellid predator Cryptolaemus montrouzieri Muls. of Maconellicoccus hirsutus (Green). Quinalphos (0.05%), endosulfan (0.07%), malathion (0.1%), carbaryl (0.1%) and fenthion (0.1%) proved highly toxic to both the species. Fungicides except fosetyl-Al, dinobuton and dinocap were found harmless. Carbaryl had significantly high toxic residual activity upto 28 days after treatment against both the biocontrol agents. Fungicides, fosetyl-Al (0.2%) dinobuton (0.1%) and dinocap (0.1%) which int1icted 16-40 % mortality of Crypto1aemus adults on the day of application became non-toxic one day after treatment. Toxic residual activity of endosulfan and fenthion against A. dactylopii and C. montrouzieri decreased significantly in 7 days.

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The egg masses of litchi stink bug, Tessaratonla javanica (Thunberl:) were found parasitized by two very interesting egg parasitoids viz, Anastatus colemani Crawford (Hymenoptera: Eupelmidae) and Ooencyrtus phongi Tryapitsyn, Myartseva and Kostyukov (Hymenoptera: Encyrtidae). The two parasitoids offer great potential for the hiological control of litchi bug T. javanica. Ooencyrtus phongi is being reported for the first time from India. The egg parasitization by A. colemani and O. phongi ranged from 12.9 to 52.9 per cent and 20.6 to 55.7 per cent, respectively during tbe study period. The sex-ratios of the A. colemani and O. phongi ranged from 1:1.83 to 1:4.14 and 1:1.35 to 1:3.83, (male: female), respectively.

In the present investigations a large array of plant species was evaluated for analysing their effect on the Trichogramma chilonis Ishii, for better understanding of the tritrophic interactions. The extracts of the eleven test plants were treated on the Corcyra eggs, which were suhsequently exposed to the adult females of T. chilonis for parasitisation and further observations, were made regarding per cent parasitisation and per cent emergence. Among the various plants tested, egg cards treated with the most commonly available fern in Tarai region Pteridium aquilinum resulted in maximum mean per cent parasitism 78, while maximum mean per cent emergence 85.33 was observed in the cards treated with Eucalyptus rostrata.

The green peach aphid Myzus persicae (Sulz.) has become a major pest of chillies and sweet pepper (Capsicum annuum L.) in India. It is becoming increasingly difficult to control the aphid with insecticides. The investigations on the impact of the natural enemies revealed that the parasitoid Aphidius sp. appeared in large numbers causing upto 93.65% parasitism on M.persicae infesting chillies. In sweet pepper fields, both Aphelinus sp. and Aphidius sp. were recorded on M. persicae but the aphelinid was more abundant than the aphidiid. The rate of parasitism by Aphelillus sp. alone went upto 96.80% in April '92 in sweet pepper fields. The aphid population was effectively suppressed on chillies and sweet pepper by the parasitoids.

Studies were carried out in the laboratory to determine the toxicity of three commonly used fungicides (carbendazim, captafol and captan) against apple scab in Himachal Pradesh to the adults of two important Hymenopterous parasitoids of San Jose scale, viz., Encarsia perniciosi and Aphytis sp. proclia group. Results revealed that carbendazim 0.025%, captafol 0.16% and captan 0.15% were not toxic to the adults of either E. perniciosi or Aphytis sp. proclia group. There were no significant differences in the mortality and longevity of adult parasitoids or both the species in treated and control batches.

Inactivation of Oryctes baculovirus in cattle dung was studied as a function of time. The infective half-life of Oryctes baculovirus was approximately for 5 days and total inactivation of the virus occurred on the 8th day in virus-cattle dung mixtures.

The green lace wing, Chrysopa lacciperda Kimmins is a predator of citrus mealybug Planococcus citri (Risso). A study was conducted to determine the developmental period and the ability of C. lacciperda to consume the nymphs of P. citri under laboratory conditions. Nymphs; 10.15 days old were offered. C. lacciperda took 22.52 days to develop from egg to adult. First, 2nd and 3rd instar larvae consumed a mean of 35.0, 96.0 and 636.1 nymphs respectively. C. lacciperda developed faster and consumed almost double the number of eggs of C. cephalonica when compared to nymphs of P. citri.

Sponsored in part by ONR.

We develop a nonparametric belief propagation method for uncertainty quantification and apply it to model flow in random porous media. The relationship between the high-dimensional input and the multi-output responses is addressed by breaking the global regression problem into smaller local problems using probabilistic links. These links can be well represented in a probabilistic graphical model. The whole framework is designed to be nonparametric (Gaussian mixture) in order to capture the non-Gaussian features of the response. With the known input distribution, a loopy nonparametric belief propagation algorithm is used to find the corresponding marginal distributions of the responses. The probabilistic graphical framework can be used as a surrogate model to predict the responses for new input realizations as well as our confidence on these predictions. Numerical examples are presented to show the accuracy and efficiency of the probabilistic graphical model framework and nonparametric belief propagation method for solving uncertainty quantification problems in flows in porous media using stationary and non-stationary permeability fields., Preprint submitted to Journal of Computational Physics.

Complex bimanual motor learning causes specific changes in activation across brain regions. However, there is little information on how motor learning changes the functional connectivity between these regions, and whether this is influenced by different sensory feedback modalities. We applied graph-theoretical network analysis (GTNA) to examine functional networks based on motor-task-related fMRI activations. Two groups learned a complex 90° out-of-phase bimanual coordination pattern, receiving either visual or auditory feedback. 3T fMRI scanning occurred before (day 0) and after (day 5) training. In both groups, improved motor performance coincided with increased functional network connectivity (increased clustering coefficients, higher number of network connections and increased connection strength, and shorter communication distances). Day×feedback interactions were absent but, when examining network metrics across all examined brain regions, the visual group had a marginally better connectivity, higher connection strength, and more direct communication pathways. Removal of feedback had no acute effect on the functional connectivity of the trained networks. Hub analyses showed an importance of specific brain regions not apparent in the standard fMRI analyses. These findings indicate that GTNA can make unique contributions to the examination of functional brain connectivity in motor learning.

We develop an efficient, Bayesian Uncertainty Quantification framework us- ing a novel treed Gaussian process model. The tree is adaptively constructed using information conveyed by the observed data about the length scales of the underlying process. On each leaf of the tree, we utilize Bayesian Experimental Design techniques in order to learn a multi-output Gaussian process. The constructed surrogate can provide analytical point estimates, as well as error bars, for the statistics of interest. We numerically demonstrate the effectiveness of the suggested framework in identifying discontinuities, local features and unimportant dimensions in the solution of stochastic differential equations., Sponsored in part by AFOSR and Department of Energy grant no. DE-AC02-05CH11231.

The mechanical properties of a deformed workpiece are sensitive to the initial microstructure. Often, the initial microstructure is random in nature and location specific. To model the variability of properties of the workpiece induced by variability in the initial microstructure, one needs to develop a reduced order stochastic input model for the initial microstructure. The location-dependence of microstructures dramatically increases the dimensionality of the stochastic input and causes the curse of dimensionality in a stochastic deformation simulation. To quantify and capture the propagation of uncertainty in multiscale deformation processes, a novel data-driven bi-orthogonal Karhunen-Loeve (KL) decomposition strategy is introduced. The multiscale random field representing random microstructures over the workpiece is decomposed simultaneously into a few modes in the macroscale and mesoscale. The macro modes are further expanded through a second-level KL expansion to separate the random and spatial coordinates. The few resulting random variables are mapped to the uniform distribution via a polynomial chaos (PC) expansion. As a result, the stochastic input complexity is remarkably simplified. Sampling from the reduced random space, new microstructure realizations are reconstructed. By collecting the properties of workpieces with randomly sampled microstructures, the property statistics are computed. A high-dimensional multiscale disk forging example of FCC nickel is presented to show the merit of this methodology, and the effect of random initial crystallographic texture on the macroscopic properties., Preprint submitted to Comput. Mater. Sci. December 19, 2011

Sensory information is critical to correct performance errors online during the execution of complex tasks and can be complemented by augmented feedback (FB). Here, 2 groups of participants acquired a new bimanual coordination pattern under different augmented FB conditions: 1) visual input reflecting coordination between the 2 hands and 2) auditory pacing integrating the timing of both hands into a single temporal structure. Behavioral findings revealed that the visual group became dependent on this augmented FB for performance, whereas the auditory group performed equally well with or without augmented FB by the end of practice. Functional magnetic resonance imaging (fMRI) results corroborated these behavioral findings: the visual group showed neural activity increases in sensory-specific areas during practice, supporting increased reliance on augmented FB. Conversely, the auditory group showed a neural activity decrease, specifically in areas associated with cognitive/sensory monitoring of motor task performance, supporting the development of a control mode that was less reliant on augmented FB sources. Finally, some remnants of brain activity in sensory-specific areas in the absence of augmented FB were found for the visual group only, illustrating ongoing reliance on these areas. These findings provide the first neural account for the "guidance hypothesis of information FB," extensively supported by behavioral research.

The aromatic profile of young and white wines is mainly determined during the grape-must fermentation and is characterized by several compounds called flavour markers. These particular compounds are minority by-products produced from ``leaks of metabolism'' of the used yeast. The final objective of this work is to gain more insight about the synthesis of the aromatic profile in order to optimize it. For this purpose, a first necessary step is the development of a model representing the main physiological phenomena observed during the batch fermentation in the wine-making process in order to later extend it with flavour-markers equations. The main-kinetics model described in this paper is based on a set of biological reactions in which nitrogen compounds such as hexose transporters play a central role, in line with experimental evidence deduced from extensive experimental studies (Malherbe, 2003)., Le profil aromatique des vins jeunes et fruités est essentiellement déterminé lors de la fermentation du moût de raisin. Il est caractérisé par différents composés appelés marqueurs aromatiques, des sous-produits minoritaires issus de « fuites du métabolisme » de la levure utilisée. L’objectif final de ces travaux est de mieux comprendre les mécanismes qui régissent la formation du profil aromatique afin d’optimiser celui-ci. Il est cependant d’abord nécessaire de développer un modèle représentant les principaux phénomènes physiologiques apparaissant lors de la fermentation (procédé en batch), pour ensuite l’étendre aux marqueurs aromatiques. Le modèle présenté dans cet article, décrivant les cinétiques principales de fermentation, se base sur des réactions biologiques dans lesquelles les composés azotés tels que les transporteurs d’hexoses jouent un rôle primordial mis en évidence lors d’études expérimentales approfondies (Malherbe, 2003).

Computational design of new materials relies on accurate descriptions of interatomic potentials. Such potentials can be realized within the Multi-Body Expansion (MBE) framework, where the expansions constructed using ab-initio calculations offer a generalized potential that can be used to describe energetics, since energies can be conceived as summations of the small cluster contributions. Furthermore, MBE technique focus on positional degrees of freedom, thus, it would eliminate a significant amount of expensive and time consuming energy minimization required to search for stable phase structures. However, in practice, obtaining the N-body (N>2) potentials is quite a challenging problem and this has been the focus of our work.

A computational methodology is developed to efficiently perform uncertainty quantification for fluid transport in porous media in the presence of both stochastic permeability and multiple scales. In order to capture the small scale heterogeneity a new mixed multiscale finite element method is developed within the framework of the heterogeneous multiscale method (HMM) in the spatial domain. This new method ensures both local and global mass conservation. Starting from a specified covariance function, the stochastic log-permeability is discretized in the stochastic space using a truncated Karhunen-Lo`eve expansion with several random variables. Due to the small correlation length of the covariance function, this often results in a high stochastic dimensionality. Therefore, a newly developed adaptive high dimensional stochastic model representation technique (HDMR) is used in the stochastic space. This results in a set of low stochastic dimensional subproblems which are efficiently solved using the adaptive sparse grid collocation method (ASGC). Numerical examples are presented for both deterministic and stochastic permeability to show the accuracy and efficiency of the developed stochastic multiscale method.

Stochastic analysis of random heterogeneous media provides useful information only if realistic input models of the material property variations are used. These input models are often constructed from a set of experimental samples of the underlying random field. To this end, the Karhunen-Loeve (K-L) expansion, also known as principal component analysis (PCA), is the most popular model reduction method due to its uniform mean-square convergence. However, it only projects the samples onto an optimal linear subspace, which results in an unreasonable representation of the original data if they are non-linearly related to each other. In other words, it only preserves the second-order statistics (covariance) of a random field, which is insufficient for reproducing complex structures. This paper applies kernel principal component analysis (KPCA) to construct a reduced-order stochastic input model for the material property variation in heterogeneous media. KPCA can be considered as a nonlinear version of PCA. Through use of kernel functions, KPCA further enables the preservation of high-order statistics of the random field, instead of just two-point statistics as in the standard Karhunen-Lo`eve (K-L) expansion. Thus, this method can model non-Gaussian, non-stationary random fields. In addition, polynomial chaos (PC) expansion is used to represent the random coefficients in KPCA which provides a parametric stochastic input model. Thus, realizations, which are consistent statistically with the experimental data, can be generated in an efficient way. We showcase the methodology by constructing a low-dimensional stochastic input model to represent channelized permeability in porous media., Submitted for publication in the Journal of Computational Physics.

The effect of diverse sources of uncertainties and the intrinsically multi-scale nature of physical systems poses a considerable challenge in their analysis. Such phenomena are particularly critical in material systems where the microstructural variability and randomness at different scales have a significant impact on the macroscopic behavior of the system. Toward this goal, during the period of this grant, we have developed a sophisticated though efficient and accurate multiscale stochastic framework for uncertainty quantification. A methodology is first developed to incorporate topological uncertainties in microstructures using a non-linear data-driven model reduction technique. This framework seamlessly allows for accessing the effects of microstructural variability on the reliability of macro-scale systems and provides an accurate stochastic input model into our stochastic system. Next, to solve the resulted stochastic partial different equations (SPDEs), an adaptive sparse grid collocation technique has been developed. In this framework, we construct the stochastic collocation points based on the function being represented, thus avoiding computational overhead. We further extended this framework to include the High Dimensional Model Representation (HDMR) technique in the stochastic space to represent the model output as a finite hierarchical correlated function expansion in terms of the stochastic inputs starting from lower-order to higher-order component functions. In this way, we can address the stochastic high dimensional problem for the first time in this area. We applied this framework for the design of general materials processes under uncertainty including the robust design of deformation processes of polycrystalline materials. We developed a unique data-driven strategy to encode the limited information on initial texture and grain distribution in deformation processes and represent it in a finite-dimensional framework., The original document contains color images.

Life tables of two chrysopid predators, viz., Chrysoperla sp. (carnea-group) and Mallada desjardinsi (Navas) on the invasive mealybug, Phenacoccus solenopsis (also reported as P. solani), were prepared in the laboratory to determine the efficacy of the predators as biocontrol agents of the pest. The rate of mortality (qx) during 0-7 days age interval was higher in Chrysoperla sp. (carnea-group) (0.28) than in M. desjardinsi (0.22) while it was reverse during 70-77 days age interval when reared on P. solenopsis. In fact, qx was higher in M. desjardinsi (2.50) than in Chrysoperla sp. (carnea-group) (0.00). The rate of multiplication per day was 0.1159 and 0.1414 females/female for Chrysoperla sp. (carnea-group) and M. desjardinsi, respectively. The intrinsic rate of increase (rm) was found to be 0.11 for both the predators. Chrysoperla sp. (carnea-group) population multiplied 62.80 times in a generation time of 35.72 days on the mealybug, whereas M. desjardinsi multiplied 67.12 times in a time period of 29.75 days. Life table assays help in estimating the total number of the natural enemies to be released in biological control programmes. This study would be of paramount importance in estimating the total number of the natural enemies to be released in biological control programmes against the mealybug, which is exotic.

Optimal integration of different sensory modalities weights each modality as a function of its degree of certainty (maximum likelihood). Humans rely on near-optimal integration in decision-making tasks (involving e.g., auditory, visual, and/or tactile afferents), and some support for these processes has also been provided for discrete sensorimotor tasks. Here, we tested optimal integration during the continuous execution of a motor task, using a cyclical bimanual coordination pattern in which feedback was provided by means of proprioception and augmented visual feedback (AVF, the position of both wrists being displayed as the orthogonal coordinates of a single cursor). Assuming maximum likelihood integration, the following predictions were addressed: (1) the coordination variability with both AVF and proprioception available is smaller than with only one of the two modalities, and should reach an optimal level; (2) if the AVF is artificially corrupted by noise, variability should increase but saturate toward the level without AVF; (3) if the AVF is imperceptibly phase shifted, the stabilized pattern should be partly adapted to compensate for this phase shift, whereby the amount of compensation reflects the weight assigned to AVF in the computation of the integrated signal. Whereas performance variability gradually decreased over 5 d of practice, we showed that these model-based predictions were already observed on the first day. This suggests not only that the performer integrated proprioceptive feedback and AVF online during task execution by tending to optimize the signal statistics, but also that this occurred before reaching an asymptotic performance level.

The present study examined the principles underlying inter and intralimb coordination constraints during performance of bimanual elbow-wrist movements at different cycling frequencies (from 0.75 Hz to 2.50 Hz). Participants performed eight coordination tasks that consisted of a combination of in-phase (IN) and/or anti-phase (AN) coordination modes between both elbows and wrists (interlimb), with isodirectional (Iso) or non-isodirectional (NonI) coordination modes within each limb (intralimb). As expected, the principle of muscle homology (in-phase coordination), giving rise to mirror symmetrical movements with respect to the mid-sagittal plane, had a powerful influence on the quality of global coordinative behavior both between and within limbs. When this principle was violated (i.e., when the anti-phase mode was introduced in one or both joint pairs), the non-isodirectional intralimb mode exhibited a (de)stabilizing role in coordination, which became more pronounced at higher cycling frequencies. However, pattern loss with increasing cycling frequency resulted not only in convergence toward the more stable in-phase patterns with the elbows and wrists but also to the anti-phase patterns (which were associated with directional compatibility of within-limb motions). Moreover, participants generally preserved their initial mode of coordination (either in-phase or anti-phase) in the proximal joints (i.e., elbows) while shifting from anti-phase to in-phase (or vice versa) with their distal joint pair (i.e., wrists). Taken together, these findings reflect the impact of two immanent types of symmetry in bimanual coordination: mirror-image and translational symmetry.

We present a dynamic optimal control method for autonomous trajectory planning and control of an Unmanned Ground Vehicle (UGV) using real-time information updates. The objective of the UGV is to traverse from an initial start point and reach its goal in minimum time, with maximum robustness, while avoiding both static and dynamic obstacles. This is achieved by deriving the control solution that carries out the initial planning problem while minimizing a cost and satisfying constraints based on the initial global knowledge of the area. To combat the problem of inaccurate global knowledge and a dynamic environment, the UGV uses its sensors to map the locally detected change in the environment and continuously updates its global map to re-compute a control solution that can achieve an optimal trajectory to the goal. Simulation results illustrate successful implementation of the method in various scenarios.

Recently, the Legendre Pseudospectral (PS) method migrated from theory to fight application onboard the International Space Station for performing a finite-horizon, zero- propellant maneuver. A small technical modification to the Legendre PS method is necessary to manage the limiting conditions at infinity for infinite-horizon optimal control problems recently, the Legendre Pseudospectral (PS) method migrated from theory to flight application onboard the International Space Station for performing a finite-horizon, zero-propellant maneuver. A small technical modification to the Legendre PS method is necessary to manage the limiting conditions at infinity for in finite-horizon optimal control problems. Motivated by these technicalities, the concept of primal-dual weighted interpolation, introduced earlier by the authors, is used to articulate a united theory for all PS methods for optimal control. This theory illuminates the previously hidden fact of the unit weight function implicit in the Legendre PS method based on Legendre-Gauss-Lobatto points. The united framework also reveals why this Legendre PS method is the most appropriate method for solving finite-horizon optimal control problems with arbitrary boundary conditions. This conclusion is borne by a proper definition of orthogonality needed to generate convergent approximations in Hilbert spaces. Special boundary conditions are needed to ensure the convergence of the Legendre PS method based on the Legendre-Gauss-Radau (LGR) and the Legendre-Gauss (LG) points. These facts are illustrated by simple examples and counter examples which reveal when and why PS methods based on LGR and LG points fail. A new kind of consistency in the primal-dual weight functions allows us to generate dual maps (such as Hamiltonians, adjoins etc) without resorting to solving difficult two-point boundary-value problems. These concepts are encapsulated in a united Convector Mapping Theorem.

Stemming from previous work that addressed the optimal path planning of an unmanned aerial vehicle (UAV) in obstacle-rich environments, this paper demonstrates the approach's scalability to that of a multi-UAV application. The proposed concept, based on optimal control techniques and Pseudospectral methods, offers the improved system flexibility and autonomy demanded by UAV tactical missions in urban areas. As demonstrated, employing optimal control methods for path planning problems provides a simplistic yet powerful capability of flight trajectory optimization that includes simultaneous collision avoidance between vehicles and terrain obstacles. Departing from traditional techniques that harbor non-optimal architectures, the employed method facilitates real-time, onboard computations that may potentially improve overall system performance. Recent developments in the field of optimal control theory point at an emerging paradigm shift that may involve less dependency on the typical inner-loop control. Extending these developments, this paper provides not only a fresh perspective, but also illustrates a viable technique for efficiently generating maneuvering flight trajectories for single vehicles or multiple vehicle sorties.

Shen and Tsiotras considered the case where the ax symmetric rigid body was subject to only two control torques which spanned the plane perpendicular to the axis of symmetry. They used a cascaded computational scheme which involved both direct and indirect methods of optimization. Additionally, their method required initial costate guesses which further complicated numerical results. They concluded that two torques were sufficient to achieve a time-optimal maneuver. In this work the Legendre Pseudospectral method will be used to solve the two-torque problem with only a two-point guess to demonstrate the method's superiority. Additionally, it will be demonstrated that while reorientation of the spin axis is possible with two control torques spanning the plane perpendicular to the spin axis, the addition of a third control torque about the axis of symmetry further reduces the objective function. It will be shown that this new solution has significantly different characteristics form the previously published work.

Based on the discoveries of a recently proposed algorithm for low-thrust trajectory optimization, we present the Bellman Pseudospectral (PS) method for a generic optimal control problem. In our original algorithm, we combined the properties of PS methods with Bellman's principle to provide an optimal solution to multi-scale and long horizon trajectory optimization problems. In this paper, we generalize this concept to provide a low cost solution to generate feasible solutions to optimal control problems. In the limit, this algorithm converges to our original concept; hence, our current proposal may also be considered as a cheap mesh-refinement technique for trajectory optimization in contrast to the more expensive PS knotting method. To facilitate the generalizations, we replace the convergence requirements in our original algorithm to controllability arguments. An application of the Bellman PS algorithm to an attitude control problem shows that the algorithm compares favorably to the PS knotting method.

In this paper, we further a general framework for the formation design of distributed space systems. Based on constrained nonlinear optimal control theory, the formation of multi-spacecraft is designed by Pseudospectral methods. The approach deals with the full nonlinear dynamics without using any linearization/approximation techniques; and is applicable to elliptical reference orbits. The method is tested on various formation problems including equilateral triangular formation over eccentric orbits. This framework provides a united and straightforward way to design large-scale formation for distributed space systems.

This paper investigates characteristics of minimum-fuel trajectories for an Unmanned Aerial Vehicle (UAV) in high altitude, circling flight under a constant wind. Previous research has shown that periodic circling flight, consisting of a boost arc (maximum thrust) and a coast arc (minimum thrust), improves the fuel consumption when compared to steady-state circling. Since the periodic flight includes ascending flight at the boost arc and descending flight at the coast arc, it is naturally expected that the wind energy influences the trajectories. In this work, numerical simulations are used to investigate the effects of both wind speed and direction on a UAV flying around one loop enclosed in a cylindrical boundary area. The results show that the optimal wind direction manifests as a tail wind just at the coast arc. In addition, the results demonstrate that the optimal wind direction changes with the wind speed and, in some cases, the trajectory under high winds results in smaller fuel consumption than the zero wind case. Thus, the importance of these results is two fold. First, that the periodic flight reveals the existence of an optimal wind direction for the minimum fuel circling. Second, and probably more importantly, generating optimal trajectories without rejecting wind disturbances provides an autonomous capability of using wind to its advantage and therefore improving fuel consumption or perhaps other mission performance metrics.