843 resultados para Artificial satellites in search and rescue operations.


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In this paper I will offer a novel understanding of a priori knowledge. My claim is that the sharp distinction that is usually made between a priori and a posteriori knowledge is groundless. It will be argued that a plausible understanding of a priori and a posteriori knowledge has to acknowledge that they are in a constant bootstrapping relationship. It is also crucial that we distinguish between a priori propositions that hold in the actual world and merely possible, non-actual a priori propositions, as we will see when considering cases like Euclidean geometry. Furthermore, contrary to what Kripke seems to suggest, a priori knowledge is intimately connected with metaphysical modality, indeed, grounded in it. The task of a priori reasoning, according to this account, is to delimit the space of metaphysically possible worlds in order for us to be able to determine what is actual.

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Root and butt rot is the most harmful fungal disease affecting Norway spruce in southern Finland. In approximately 90 % of cases the causal agent is Heterobasidion parviporum. Root and butt rot infections have not been reported in Finnish peatlands. However, the increase in logging operations in peatlands means there is a risk that the fungus will eventually spread to these areas. The aim of this study was to find out the impact of growing site on the resistance of Norway spruce to Heterobasidion parviporum infections. This was investigated by artificially inoculating H. parviporum to spruce trees in pristine mire, drained peatland and mineral soil and comparing the defence reactions. Additionally, the effect of genotype on resistance was studied by comparing the responses of spruce clones representing different geographic origins. The roots and stems of the trees to be sampled were wounded and inoculated with wood dowels pre-colonised by H. parviporum hyphae. The resulting necrosis around the point of inoculation was observed. It was presumed that increased length of necrosis indicates high susceptibility of the tree to the disease. The relationship between growth rate and host resistance was also studied. The results indicated that growing site does not have a statistically significant effect on host resistance. The average length of necrosis around the point of inoculation was 35 mm in pristine mire, 37 mm in drained peatland and 40 mm in mineral soil. It was observed that growth rate does not affect resistance, but that the genotype of the tree does have an effect. The most resistant spruce clone was the one with Russian origin. The results suggest that the spruce stands in peatlands are not more resistant to root and butt rot infections than those in mineral soil. These findings should be taken into consideration when logging peatland forests.

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Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.

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This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.

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Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.

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We report our search for and a possible detection of periodic radio pulses at 34.5 MHz from the Fermi Large Area Telescope pulsar J1732-3131. The candidate detection has been possible in only one of the many sessions of observations made with the low-frequency array at Gauribidanur, India, when the otherwise radio weak pulsar may have apparently brightened many folds. The candidate dispersion measure along the sight line, based on the broad periodic profiles from �20min of data, is estimated to be 15.44 ± 0.32 pccc -1. We present the details of our periodic and single-pulse search, and discuss the results and their implications relevant to both, the pulsar and the intervening medium. © 2012 RAS.

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Experimental and simulation studies have uncovered at least two anomalous concentration regimes in water-dimethyl sulfoxide (DMSO) binary mixture whose precise origin has remained a subject of debate. In order to facilitate time domain experimental investigation of the dynamics of such binary mixtures, we explore strength or extent of influence of these anomalies in dipolar solvation dynamics by carrying out long molecular dynamics simulations over a wide range of DMSO concentration. The solvation time correlation function so calculated indeed displays strong composition dependent anomalies, reflected in pronounced non-exponential kinetics and non-monotonous composition dependence of the average solvation time constant. In particular, we find remarkable slow-down in the solvation dynamics around 10%-20% and 35%-50% mole percentage. We investigate microscopic origin of these two anomalies. The population distribution analyses of different structural morphology elucidate that these two slowing down are reflections of intriguing structural transformations in water-DMSO mixture. The structural transformations themselves can be explained in terms of a change in the relative coordination number of DMSO and water molecules, from 1DMSO:2H(2)O to 1H(2)O:1DMSO and 1H(2)O:2DMSO complex formation. Thus, while the emergence of first slow down (at 15% DMSO mole percentage) is due to the percolation among DMSO molecules supported by the water molecules (whose percolating network remains largely unaffected), the 2nd anomaly (centered on 40%-50%) is due to the formation of the network structure where the unit of 1DMSO:1H(2)O and 2DMSO:1H(2)O dominates to give rise to rich dynamical features. Through an analysis of partial solvation dynamics an interesting negative cross-correlation between water and DMSO is observed that makes an important contribution to relaxation at intermediate to longer times.

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MsRbpA is an RNA polymerase (RNAP) binding protein from Mycobacterium smegmatis. According to previous studies, MsRbpA rescues rifampicin-induced transcription inhibition upon binding to the RNAP. Others have shown that RbpA from Mycobacterium tuberculosis (MtbRbpA) is a transcription activator. In this study, we report that both MsRbpA and MtbRbpA activate transcription as well as rescue rifampicin-induced transcription inhibition. Transcription activation is achieved through the increased formation of closed RNAP-promoter complex as well as enhanced rate of conversion of this complex to a stable transcriptionally competent RNAP promoter complex. When a 16 aa peptide fragment (Asp 58 to Lys 73) was deleted from MsRbpA, the resulting protein showed 1000-fold reduced binding with core RNAP. The deletion results in abolition of transcription activation and rescue of transcription from the inhibitory effect of rifampicin. Through alanine scanning of this essential region of MsRbpA, Gly 67, Val 69, Pro 70 and Pro 72 residues are identified to be important for MsRbpA function. Furthermore, we report here that the protein is indispensable for M. smegmatis, and it appears to help the organism grow in the presence of the antibiotic rifampicin.

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Induced breeding technique by hypophysation is being applied at the Kainji Lake Research Institute Fisheries Division Hatchery complex in New Bussa, Nigeria, for the production of Clarias fry and fingerlings in indoor and outdoor concrete tank systems. The hatchlings are fed on livefood (zooplankton) and artificial feed. Source of zooplankton is from cultured stock which is maintained throughout the breeding season by fertilization. Production values show that an average of over 4,000 hatchlings (larvae) can be produced by a female breeder (over-700g wt) and percentage survival after two months ranges between 70 to 75%. With the proposed modification and expansion project, an estimated production of over 0.5 million fingerlings per breeding season is projected

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The present corpus study aimed to examine whether Basque (OV) resorts more often than Spanish (VO) to certain grammatical operations, in order to minimi ze the number of arguments to be processed before the verb. Ueno & Polinsky (2009) argue that VO/OV languages use certain grammatical resources with different frequencies in order to facilitate real-time processing. They observe that both OV and VO languages in their sample (Japanese, Turkish and Spanish) have a similar frequency of use of subject pro-drop; however, they find that OV languages (Japanese, Turkish) use more intransitive sentences than VO languages (English, Spanish), and conclude this is an OV-specific strategy to facilitate processing. We conducted a comparative corpus study of Spanish (VO) and Basque (OV). Results show (a) that the fre- quency of use of subject pro-drop is higher in Basque than in Spanish; and (b) Basque does not use more intransitive sentences than Spanish; both languages have a similar frequency of intransitive sentences. Based on these findings, we conclude that the frequency of use of grammatical resources to facilitate the processing does not depend on a single typological trait (VO/OV) but it is modulated by the concurrence of other grammatical feature.

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Many particles proposed by theories, such as GUT monopoles, nuclearites and 1/5 charge superstring particles, can be categorized as Slow-moving, Ionizing, Massive Particles (SIMPs).

Detailed calculations of the signal-to-noise ratios in vanous acoustic and mechanical methods for detecting such SIMPs are presented. It is shown that the previous belief that such methods are intrinsically prohibited by the thermal noise is incorrect, and that ways to solve the thermal noise problem are already within the reach of today's technology. In fact, many running and finished gravitational wave detection ( GWD) experiments are already sensitive to certain SIMPs. As an example, a published GWD result is used to obtain a flux limit for nuclearites.

The result of a search using a scintillator array on Earth's surface is reported. A flux limit of 4.7 x 10^(-12) cm^(-2)sr^(-1)s^(-1) (90% c.l.) is set for any SIMP with 2.7 x 10^(-4) less than β less than 5 x 10^(-3) and ionization greater than 1/3 of minimum ionizing muons. Although this limit is above the limits from underground experiments for typical supermassive particles (10^(16)GeV), it is a new limit in certain β and ionization regions for less massive ones (~10^9 GeV) not able to penetrate deep underground, and implies a stringent limit on the fraction of the dark matter that can be composed of massive electrically and/ or magnetically charged particles.

The prospect of the future SIMP search in the MACRO detector is discussed. The special problem of SIMP trigger is examined and a circuit proposed, which may solve most of the problems of the previous ones proposed or used by others and may even enable MACRO to detect certain SIMP species with β as low as the orbital velocity around the earth.

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An experiment was carried out to investigate the effects of Moina, artificial diet (55% CP) and nutrase xyla supplemented artificial diet on growth performances and survival rates of Clarias gariepinus larvae. A combination of Moina and artificial diet (with or without nutrass xyla) resulted in higher growth performance and survival rates during a 12-day nursing time with specific growth rates of 30.04-32.15% d super(-1) and survival rates of 87.5-90%. Best growth performance and survival rate was obtained with a combination of Moina and artificial diet supplemented with nutrias xylem. Feeding of Moina and artificial diet supplemented, with nutrias xyla alone to the larval led to a lower growth performance of 25.60-27.04% d super(-1). However, the survival rate of Monia of larvae fed a combination of Moina and artificial diet (with or without nutrias xylem supplementation) artificial diet without nutrias xylem addition proved relatively less suitable for larval rearing of Clarias gariepinus owing to a low survival rate of 69% and growth performance of 19.7% d super(-1). This study showed the feasibility of feeding a combination of Moina and nutrias xylem supplemented artificial diet to the larvae of Clarias gariepinus

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In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC2) criteria to select tests. We prove that the EC2 criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC2 criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC2 to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.