Growth requirements of some fungi causing maduromycosis

Three strains ofMadurella mycetomi, two ofM. grisea, and two ofRhinocladiella mansonii have been studied for ossible differences in growth requirements which might be used for distinguishing these species. Under the experimental conditions, an incubation temperature of 37C suitedM. mycetomi about as well as 30C.R. mansonii grew less well at 37C than at 30C, andM. grisea did not grow at the higher temperature. M. grisea andR. mansonii further differed fromM. mycetomi in that they required thiamine for growth. The pH tolerance of all the strains was very wide. Asparagine and potassium nitrate were readily utilized by all the strains, but ammonium salts were not. Urea was poorly used byM. mycetomi; the other species did not use it. A possible relationship ofM. grisea andR. mansonii is discusse

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Stability Training and Measurement System for Sportsperson (P84)

Balance and stability are very important for everybody and especially for sports-person who undergo extreme physical activities. Balance and stability exercises not only have a great impact on the performance of the sportsperson but also play a pivotal role in their rehabilitation. Therefore, it is very essential to have knowledge about a sportsperson’s balance and also to quantify the same. In this work, we propose a system consisting of a wobble board, with a gyro enhanced orientation sensor and a motion display for visual feedback to help the sportsperson improve their stability. The display unit gives in real time the orientation of the wobble board, which can help the sportsperson to apply necessary corrective forces to maintain neutral position. The system is compact and portable. We also quantify balance and stability using power spectral density. The sportsperson is made stand on the wobble board and the angular orientation of the wobble board is recorded for each 0.1 second interval. The signal is analized using discrete Fourier transforms. The power of this signal is related to the stability of the subject. This procedure is used to measure the balance and stability of an elite cricket team. Representative results are shown below: Table 1 represents power comparison of two subjects and Table 2 represents power comparison of left leg and right leg of one subject. This procedure can also be used in clinical practice to monitor improvement in stability dysfunction of sportsperson with injuries or other related problems undergoing rehabilitation.

Structural requirements for the induction and inhibition of 2,3-dihydroxybenzoic acid decarboxylase ofAspergillus niger

2,3-Dihydroxybenzoic acid decarboxylase inAspergillus niger was induced by many substrate analogs including salicylate and gentisate. Catechol, which is the product, induced the enzyme tenfold. The purified enzyme was competitively inhibited by manyortho substituted benzoic acids. The Ki values for salicylate,o-fluoro ando-chloro benzoic acids were 0.12 mM, 0.12 mM, and 0.13 mM respectively; these values were lower than the Km value for the substrate. As the size of the group in theortho position increased, as in the case of bromo- and iodo-derivatives, there was an increase in their Ki values. The C-2 hydroxyl group was essential both for the induction and for interaction with the enzyme. The C-3 hydroxyl group was not necessary for induction or inhibition, but it might be essential for the catalysis.

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.

Minimizing buffer requirements under rate-optimal schedule in regular dataflow networks

Large-grain synchronous dataflow graphs or multi-rate graphs have the distinct feature that the nodes of the dataflow graph fire at different rates. Such multi-rate large-grain dataflow graphs have been widely regarded as a powerful programming model for DSP applications. In this paper we propose a method to minimize buffer storage requirement in constructing rate-optimal compile-time (MBRO) schedules for multi-rate dataflow graphs. We demonstrate that the constraints to minimize buffer storage while executing at the optimal computation rate (i.e. the maximum possible computation rate without storage constraints) can be formulated as a unified linear programming problem in our framework. A novel feature of our method is that in constructing the rate-optimal schedule, it directly minimizes the memory requirement by choosing the schedule time of nodes appropriately. Lastly, a new circular-arc interval graph coloring algorithm has been proposed to further reduce the memory requirement by allowing buffer sharing among the arcs of the multi-rate dataflow graph. We have constructed an experimental testbed which implements our MBRO scheduling algorithm as well as (i) the widely used periodic admissible parallel schedules (also known as block schedules) proposed by Lee and Messerschmitt (IEEE Transactions on Computers, vol. 36, no. 1, 1987, pp. 24-35), (ii) the optimal scheduling buffer allocation (OSBA) algorithm of Ning and Gao (Conference Record of the Twentieth Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, Charleston, SC, Jan. 10-13, 1993, pp. 29-42), and (iii) the multi-rate software pipelining (MRSP) algorithm (Govindarajan and Gao, in Proceedings of the 1993 International Conference on Application Specific Array Processors, Venice, Italy, Oct. 25-27, 1993, pp. 77-88). Schedules generated for a number of random dataflow graphs and for a set of DSP application programs using the different scheduling methods are compared. The experimental results have demonstrated a significant improvement (10-20%) in buffer requirements for the MBRO schedules compared to the schedules generated by the other three methods, without sacrificing the computation rate. The MBRO method also gives a 20% average improvement in computation rate compared to Lee's Block scheduling method.

Training Young Minds for Nanoscience and Technology: Issues and Challenges

This article explores issues and challenges in the field of education in nanoscience and technology with special emphasis with respect to India, where an expanding programme of research in nano science and technology is in place. The article does not concentrate on actual curricula that are needed in nano science and technology education course. Rather it focuses on the desirability of nanoscience and technology education at different levels of education and future prospect of students venturing into this within the economic and cultural milieu of India. We argue that care is needed in developing the education programme in India. However, the risk is worth taking as the education on nanoscience and technology can bridge the man power gap not only in this area of technology but also related technologies of hardware and micro electronics for which the country is a promising destination at global level. This will also unlock the demographical advantage that India will enjoy in the next five decades.

Estimation of BT Interference in OFDM Sub Carriers with Training Signals

While wireless LAN (WLAN) is very popular now a days, its performance deteriorates in the presence of other signals like Bluetooth (BT) signal that operate in the same band as WLAN. Present interference mitigation techniques in WLAN due to BT cancel interference in WLAN sub carrier where BT has hopped but do not cancel interference in the adjacent sub carriers. In this paper BT interference signal in all the OFDM sub carriers is estimated. That is, leakage of BT in other sub carriers including the sub carriers in which it has hopped is also measured. BT signals are estimated using the training signals of OFDM system. Simulation results in AWGN noise show that proposed algorithm agrees closely with theoretical results.

Reducing Buffer Requirements in Core Routers using Dynamic Buffering

Earlier studies have exploited statistical multiplexing of flows in the core of the Internet to reduce the buffer requirement in routers. Reducing the memory requirement of routers is important as it enables an improvement in performance and at the same time a decrease in the cost. In this paper, we observe that the links in the core of the Internet are typically over-provisioned and this can be exploited to reduce the buffering requirement in routers. The small on-chip memory of a network processor (NP) can be effectively used to buffer packets during most regimes of traffic. We propose a dynamic buffering strategy which buffers packets in the receive and transmit buffers of a NP when the memory requirement is low. When the buffer requirement increases due to bursts in the traffic, memory is allocated to packets in the off-chip DRAM. This scheme effectively mitigates the DRAM access bottleneck, as only a part of the traffic is stored in the DRAM. We build a Petri net model and evaluate the proposed scheme with core Internet like traffic. At 77% link utilization, the dynamic buffering scheme has a drop rate of just 0.65%, whereas the traditional DRAM buffering has 4.64% packet drop rate. Even with a high link utilization of 90%, which rarely happens in the core, our dynamic buffering results in a packet drop rate of only 2.17%, while supporting a throughput of 7.39 Gbps. We study the proposed scheme under different conditions to understand the provisioning of processing threads and to determine the queue length at which packets must be buffered in the DRAM. We show that the proposed dynamic buffering strategy drastically reduces the buffering requirement while still maintaining low packet drop rates.

Training-Symbol Embedded, High-Rate, Single-Symbol ML-Decodable, Distributed STBCs for Relay Networks

Distributed space-time block codes (DSTBCs) from complex orthogonal designs (CODs) (both square and nonsquare), coordinate interleaved orthogonal designs (CIODs), and Clifford unitary weight designs (CUWDs) are known to lose their single-symbol ML decodable (SSD) property when used in two-hop wireless relay networks using amplify and forward protocol. For such networks, in this paper, three new classes of high rate, training-symbol embedded (TSE) SSD DSTBCs are constructed: TSE-CODs, TSE-CIODs, and TSE-CUWDs. The proposed codes include the training symbols inside the structure of the code which is shown to be the key point to obtain the SSD property along with the channel estimation capability. TSE-CODs are shown to offer full-diversity for arbitrary complex constellations and the constellations for which TSE-CIODs and TSE-CUWDs offer full-diversity are characterized. It is shown that DSTBCs from nonsquare TSE-CODs provide better rates (in symbols per channel use) when compared to the known SSD DSTBCs for relay networks. Important from the practical point of view, the proposed DSTBCs do not contain any zeros in their codewords and as a result, antennas of the relay nodes do not undergo a sequence of switch on/off transitions within every codeword, and, thus, avoid the antenna switching problem.

Power Controlled Reverse Channel Training Achieves an Infinite Diversity Order in a TDD-SIMO System with Perfect CSIR

In this letter, we analyze the Diversity Multiplexinggain Tradeoff (DMT) performance of a training-based reciprocal Single Input Multiple Output (SIMO) system. Assuming Channel State Information (CSI) is available at the Receiver (CSIR), we propose a channel-dependent power-controlled Reverse Channel Training (RCT) scheme that enables the transmitter to directly estimate the power control parameter to be used for the forwardlink data transmission. We show that, with an RCT power of (P) over bar (gamma), gamma > 0 and a forward data transmission power of (P) over bar, our proposed scheme achieves an infinite diversity order for 0 <= g(m) < L-c-L-B,L-tau/L-c min(gamma, 1) and r > 2, where g(m) is the multiplexing gain, L-c is the channel coherence time, L-B,L-tau is the RCT duration and r is the number of receive antennas. We also derive an upper bound on the outage probability and show that it goes to zero asymptotically as exp(-(P) over bar (E)), where E (sic) (gamma - g(m)L(c)/L-c-L-B,L-tau), at high (P) over bar. Thus, the proposed scheme achieves a significantly better DMT performance compared to the finite diversity order achieved by channel-agnostic, fixed-power RCT schemes.

Energy-efficient training for antenna selection in time-varying channels

Training for receive antenna selection (AS) differs from that for conventional multiple antenna systems because of the limited hardware usage inherent in AS. We analyze and optimize the performance of a novel energy-efficient training method tailored for receive AS. In it, the transmitter sends not only pilots that enable the selection process, but also an extra pilot that leads to accurate channel estimates for the selected antenna that actually receives data. For time-varying channels, we propose a novel antenna selection rule and prove that it minimizes the symbol error probability (SEP). We also derive closed-form expressions for the SEP of MPSK, and show that the considered training method is significantly more energy-efficient than the conventional AS training method.

Validation based sparse Gaussian processes for ordinal regression

This paper proposes a sparse modeling approach to solve ordinal regression problems using Gaussian processes (GP). Designing a sparse GP model is important from training time and inference time viewpoints. We first propose a variant of the Gaussian process ordinal regression (GPOR) approach, leave-one-out GPOR (LOO-GPOR). It performs model selection using the leave-one-out cross-validation (LOO-CV) technique. We then provide an approach to design a sparse model for GPOR. The sparse GPOR model reduces computational time and storage requirements. Further, it provides faster inference. We compare the proposed approaches with the state-of-the-art GPOR approach on some benchmark data sets. Experimental results show that the proposed approaches are competitive.

Homology and enzymatic requirements of microhomology-dependent alternative end joining

Nonhomologous DNA end joining (NHEJ) is one of the major double-strand break (DSB) repair pathways in higher eukaryotes. Recently, it has been shown that alternative NHEJ (A-NHEJ) occurs in the absence of classical NHEJ and is implicated in chromosomal translocations leading to cancer. In the present study, we have developed a novel biochemical assay system utilizing DSBs flanked by varying lengths of microhomology to study microhomology-mediated alternative end joining (MMEJ). We show that MMEJ can operate in normal cells, when microhomology is present, irrespective of occurrence of robust classical NHEJ. Length of the microhomology determines the efficiency of MMEJ, 5 nt being obligatory. Using this biochemical approach, we show that products obtained are due to MMEJ, which is dependent on MRE11, NBS1, LIGASE III, XRCC1, FEN1 and PARP1. Thus, we define the enzymatic machinery and microhomology requirements of alternative NHEJ using a well-defined biochemical system.

Analysis of OSNR Requirements for Higher Modulation Schemes for Various Local Oscillator Powers

To meet the growing demands of data traffic in long haul communication, it is necessary to efficiently use the low-loss region(C-band) of the optical spectrum, by increasing the no. of optical channels and increasing the bit rate on each channel But narrow pulses occupy higher spectral bandwidth. To circumvent this problem, higher order modulation schemes such as QPSK and QAM can be used to modulate the bits, which increases the spectral efficiency without demanding any extra spectral bandwidth. On the receiver side, to meet a satisfy, a given BER, the received optical signal requires to have minimum OSNR. In our study in this paper, we analyses for different modulation schemes, the OSNR required with and without preamplifier. The theoretical limit of OSNR requirement for a modulation scheme is compared for a given link length by varying the local oscillator (LO) power. Our analysis shows that as we increase the local oscillator (LO) power, the OSNR requirement decreases for a given BER. Also a combination of preamplifier and local oscillator (LO) gives the OSNR closest to theoretical limit.