Microhabitat selection in an assemblage of crickets (Orthoptera: Ensifera) of a tropical evergreen forest in Southern India

1. Habitat selection is a universal aspect of animal ecology that has important fitness consequences and may drive patterns of spatial organisation in ecological communities. 2. Measurements of habitat selection have mostly been carried out on single species and at the landscape level. Quantitative studies examining microhabitat selection at the community level are scarce, especially in insects. 3. In this study, microhabitat selection in a natural assemblage of cricket species was examined for the first time using resource selection functions (RSF), an approach more commonly applied in studies of macrohabitat selection. 4. The availability and differential use of six microhabitats by 13 species of crickets inhabiting a tropical evergreen forest in southern India was examined. The six available microhabitats included leaf litter-covered ground, tree trunks, dead logs, brambles, understorey and canopy foliage. The area offered by the six microhabitats was estimated using standard methods of forest structure measurement. Of the six microhabitats, the understorey and canopy accounted for approximately 70% of the total available area. 5. The use of different microhabitats by the 13 species was investigated using acoustic sampling of crickets to locate calling individuals. Using RSF, it was found that of 13 cricket species examined, 10 showed 100% selection for a specific microhabitat. Of these, two species showed fairly high selection for brambles and dead logs, which were rare microhabitats, highlighting the importance of preserving all components of forest structure.

Coordination driven self-assembly of metallamacrocycles using ambidentate linkers and self-selection of single linkage isomer

Nicotinate-N-oxide and isonicotinate-N-oxide have been employed to synthesize four heterometallic metallamacrocycles (dppf)(2)Pd-2(nicotinate-N-oxide)(2)](OTf)(2) (1), (dppf)(2)Pt-2(nicotinate-N-oxide)(2)](OTf)(2) (2), (dppf) 2Pd2(isonicotinate-N-oxide)(2)](OTf)(2) (3) and (dppf)(2)Pt-2(isonicotinate-N-oxide)(2)](OTf)(2) (4). The complexes represent the first examples of metallamacrocycles driven by solely Pd(II)/Pt(II)-O coordination using carboxylate-N-oxide donor. All the complexes 1-4 are characterized by IR, UV-Vis, multinuclear NMR spectroscopic and ESI-MS studies. The molecular structures of the complexes 1 and 3 are unambiguously determined by single crystal X-ray diffraction analysis. Despite the possibility of formation of several linkage isomers due to ambidentate nature of the donors, exclusive formation of 2 + 2] self-assembled single isomeric metallamacrocycle in each case is interesting observation. (C) 2011 Elsevier B.V. All rights reserved.

Reverse flotation of silica from Kudremukh iron ore .1. Selection of cationic reagents

Four types of cationic collectors were tested and evaluated for their performance in the reverse flotation of silica from the spiral preconcentrate of Kudremukh iron ore. A stagewise flotation was conducted by adding the reagent in three stages. Starch was used to depress hematite. Silica flotation was found to be very sensitive to the amount of cationic reagent added. The performance of the reagents was evaluated based on the percentage of silica and iron in the concentrate and percent recovery of iron obtained in the concentrate. Tests of significance, namely, t-test and F-test were performed to select the best two reagents for further investigations.

Post-seizure EEG fractal dimension of first ECT predicts antidepressant response at two weeks

Background: Duration of seizure by itself is an insufficient criterion for a therapeutically adequate seizure in ECT. Therefore, measures of seizure EEG other than its duration need to be explored as indices of seizure adequacy and predictors of treatment response. We measured the EEG seizure using a geometrical method-fractal dimension (FD) and examined if this measure predicted remission. Methods: Data from an efficacy study on melancholic depressives (n = 40) is used for the present exploration. They received thrice or once weekly ECTs, each schedule at two energy levels - high or low energy level. FD was computed for early-, mid- and post-seizure phases of the ictal EEG. Average of the two channels was used for analysis. Results: Two-thirds of the patients (n = 25) were remitted at the end of 2 weeks. As expected, a significantly higher proportion of patients receiving thrice weekly ECT remitted than in patients receiving once weekly ECT. Smaller post-seizure FD at first ECT is the only variable which predicted remission status after six ECTs. within the once weekly ECT group too, smaller post-seizure FD was associated with remission status. Conclusions: Post-seizure FD is proposed as a novel measure of seizure adequacy and predictor of treatment response. Clinical implications: Seizure measures at first ECT may guide selection of ECT schedule to optimize ECT. Limitations: The study examined short term antidepressant effects only. The results may not be generalized to medication-resistant depressives. (C) 1999 Elsevier Science B.V. All rights reserved.

On Training and Training Voids for Receive Antenna Subset Selection in Time-Varying Channels

Antenna selection (AS) provides most of the benefits of multiple-antenna systems at drastically reduced hardware costs. In receive AS, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. The "best" subset to be used for data reception is determined by means of channel estimates acquired using training sequences. Due to the nature of AS, the channel estimates at different antennas are obtained from different transmissions of the pilot sequence, and are, thus, outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N, we highlight a new issue of "training voids", in which the last pilot transmission is not fully exploited by the receiver. We present a "void-filling" method for fully exploiting these voids, which essentially provides more accurate training for some antennas, and derive the optimal subset selection rule for any void-filling method. We also derive new closed-form equations for the performance of receive AS with optimal subset selection.

A New Full-diversity Criterion and Low-complexity STBCs with Partial Interference Cancellation Decoding

Recently, Guo and Xia gave sufficient conditions for an STBC to achieve full diversity when a PIC (Partial Interference Cancellation) or a PIC-SIC (PIC with Successive Interference Cancellation) decoder is used at the receiver. In this paper, we give alternative conditions for an STBC to achieve full diversity with PIC and PIC-SIC decoders, which are equivalent to Guo and Xia's conditions, but are much easier to check. Using these conditions, we construct a new class of full diversity PIC-SIC decodable codes, which contain the Toeplitz codes and a family of codes recently proposed by Zhang, Xu et. al. as proper subclasses. With the help of the new criteria, we also show that a class of PIC-SIC decodable codes recently proposed by Zhang, Shi et. al. can be decoded with much lower complexity than what is reported, without compromising on full diversity.

A Complete Characterization of an Optimal Timer Based Selection Scheme

Timer-based mechanisms are often used in several wireless systems to help a given (sink) node select the best helper node among many available nodes. Specifically, a node transmits a packet when its timer expires, and the timer value is a function of its local suitability metric. In practice, the best node gets selected successfully only if no other node's timer expires within a `vulnerability' window after its timer expiry. In this paper, we provide a complete closed-form characterization of the optimal metric-to-timer mapping that maximizes the probability of success for any probability distribution function of the metric. The optimal scheme is scalable, distributed, and much better than the popular inverse metric timer mapping. We also develop an asymptotic characterization of the optimal scheme that is elegant and insightful, and accurate even for a small number of nodes.

On optimal timer-based distributed selection for rate-adaptive multi-user diversity systems

We develop an optimal, distributed, and low feedback timer-based selection scheme to enable next generation rate-adaptive wireless systems to exploit multi-user diversity. In our scheme, each user sets a timer depending on its signal to noise ratio (SNR) and transmits a small packet to identify itself when its timer expires. When the SNR-to-timer mapping is monotone non-decreasing, timers of users with better SNRs expire earlier. Thus, the base station (BS) simply selects the first user whose timer expiry it can detect, and transmits data to it at as high a rate as reliably possible. However, timers that expire too close to one another cannot be detected by the BS due to collisions. We characterize in detail the structure of the SNR-to-timer mapping that optimally handles these collisions to maximize the average data rate. We prove that the optimal timer values take only a discrete set of values, and that the rate adaptation policy strongly influences the optimal scheme's structure. The optimal average rate is very close to that of ideal selection in which the BS always selects highest rate user, and is much higher than that of the popular, but ad hoc, timer schemes considered in the literature.

Training and Voids in Receive Antenna Subset Selection in Time-Varying Channels

Receive antenna selection (AS) provides many benefits of multiple-antenna systems at drastically reduced hardware costs. In it, the receiver connects a dynamically selected subset of N available antennas to the L available RF chains. Due to the nature of AS, the channel estimates at different antennas, which are required to determine the best subset for data reception, are obtained from different transmissions of the pilot sequence. Consequently, they are outdated by different amounts in a time-varying channel. We show that a linear weighting of the estimates is necessary and optimum for the subset selection process, where the weights are related to the temporal correlation of the channel variations. When L is not an integer divisor of N , we highlight a new issue of ``training voids'', in which the last pilot transmission is not fully exploited by the receiver. We then present new ``void-filling'' methods that exploit these voids and greatly improve the performance of AS. The optimal subset selection rules with void-filling, in which different antennas turn out to have different numbers of estimates, are also explicitly characterized. Closed-form equations for the symbol error probability with and without void-filling are also developed.

Least path criterion (LPC) for unique indexing in a two-dimensional decagonal quasilattice

The least path criterion or least path length in the context of redundant basis vector systems is discussed and a mathematical proof is presented of the uniqueness of indices obtained by applying the least path criterion. Though the method has greater generality, this paper concentrates on the two-dimensional decagonal lattice. The order of redundancy is also discussed; this will help eventually to correlate with other redundant but desirable indexing sets.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Performance analysis of TCM with generalized selection combining on Rayleigh fading channels

We derive the computational cutoff rate, R-o, for coherent trellis-coded modulation (TCM) schemes on independent indentically distributed (i.i.d.) Rayleigh fading channels with (K, L) generalized selection combining (GSC) diversity, which combines the K paths with the largest instantaneous signal-to-noise ratios (SNRs) among the L available diversity paths. The cutoff rate is shown to be a simple function of the moment generating function (MGF) of the SNR at the output of the (K, L) GSC receiver. We also derive the union bound on the bit error probability of TCM schemes with (K, L) GSC in the form of a simple, finite integral. The effectiveness of this bound is verified through simulations.