Correlation-based wireless sensor networks performance: the compressed sensing paradigm

Cluster Computing - In this paper, the performance of Wireless Sensor Networks (WSNs) operating for environmental monitoring is investigated. The performance metrics considered are normalized...     

Bursting dynamics remarkably improve the performance of neural networks on liquid computing

Burst firings are functionally important behaviors displayed by neural circuits, which plays a primary role in reliable transmission of electrical signals for neuronal communication. However, with respect to the computational capability of neural networks, most of relevant studies are based on the spiking dynamics of individual neurons, while burst firing is seldom considered. In this paper, we carry out a comprehensive study to compare the performance of spiking and bursting dynamics on the capability of liquid computing, which is an effective approach for intelligent computation of neural networks. The results show that neural networks with bursting dynamic have much better computational performance than those with spiking dynamics, especially for complex computational tasks. Further analysis demonstrate that the fast firing pattern of bursting dynamics can obviously enhance the efficiency of synaptic integration from pre-neurons both temporally and spatially. This indicates that bursting dynamic can significantly enhance the complexity of network activity, implying its high efficiency in information processing.     

Understanding cellular networks to improve hematopoietic stem cell expansion cultures

Efforts to develop culture technologies capable of eliciting robust human blood stem cell growth have met with limited success. Considering that adult stem cell cultures are complex systems, comprising multiple cell types with dynamically changing intracellular signalling environments and cellular compositions, this is not surprising. Typically treated as single-input single-output systems, adult stem cell cultures are better described as complex, non-linear, multiple-input multiple-output systems wherein the proliferation of subpopulations of cells leads to the formation of intercellular endogenously secreted protein interaction networks. Genomic and proteomic tools need to be applied to generate high-throughput (and ideally high-content) biological measurements of stem cell culture evolution. Datasets describing cellular interaction networks need to be integrated into predictive models of in vitro stem cell development. Ultimately, such models will serve as a starting point for the rational design of blood stem cell expansion bioprocesses utilizing dynamic system perturbations to achieve the preferential expansion of target cell populations.     

Use of Capability Index to improve laboratory analytical performance

* For detection of errors where the standard deviation is wide compared to clinical requirements, consider use of the Capability Index (Cps). * Cps is defined as 'Allowable Limit of Error divided by the standard deviation of between-batch QC measurement'. * 'Capable' assays have Cps >4 compared with 'incapable' ones with Cps <4. * Capability of an analyte can be used to optimise the amount of quality control (QC) required and still maintain appropriate error detection. * For EQA material, Cps can be used for continuously monitoring individual analytes, comparing laboratory performance with peers and comparison with industry-wide performance. * The capability approach can result in reducing the number of QCs run per day, reducing costs as well as significantly improving the performance of a number of assays.     

Deconstructing feedback-signaling networks to improve anticancer therapy with mTORC1 inhibitors

Targeting mTOR complex 1 (mTORC1), which regulates general protein translation, represents one of the most attractive approaches to treating cancer, since up-regulation of this pathway is a common hallmark in many tumors. Nevertheless, the use of rapamycin and its analogs in the clinic has revealed that mTORC1 pathway is embedded in a network of signaling cross-talks and feedbacks which might reduce its effectiveness in cancer. We have recently described a novel signaling feedback stemming from mTORC1 inhibition, which leads to the activation of ERK-MAPK (MAPK) pathway. The observation that MAPK is activated by rapamycin and its analogs in vitro, in mouse models, and cancer patient biopsies sets the rationale for the combined use of MAPK and mTORC1 inhibitors in cancer therapy. In this extra-view, we integrate our findings into the mTORC1 signaling network and discuss its relevance for the design of combinatorial therapies with mTORC1 inhibitors.     

The genesis of Thy-1-lymphomas in NFS mice exposed to X irradiation

The kinetics of the appearance of potentially leukemic cells (PoLCs) for radiation-induced lymphoma in NFS mice was investigated by the opposite sex (male----female) transplantation assay. The origin of the cells of the lymphomas that developed in the host was decided by sex chromosome markers. The bone marrow and the spleen cells collected from mice 30 days after fractionated irradiation (1.7 Gy X 4) gave rise, upon transfer to 4-Gy-irradiated hosts, to tumors of either donor or host origin. Most tumors of donor origin were thymine-1-negative (Thy-1-) and surface immunoglobulin negative and classified as nonthymic lymphoma, while the tumors of host origin were mainly Thy-1-positive thymic lymphoma. In contrast, neither the bone marrow nor the thymus contained any PoLCs for thymic lymphoma 30 days after split-dose irradiation. These results indicate that PoLCs for Thy-1-lymphoma were induced in the bone marrow and spleens of NFS mice by the split-dose regimen which developed exclusively T-cell lymphomas in the absence of cell grafting.     

Negative feedback may suppress variation to improve collective foraging performance

Social insect colonies use negative as well as positive feedback signals to regulate foraging behaviour. In ants and bees individual foragers have been observed to use negative pheromones or mechano-auditory signals to indicate that forage sources are not ideal, for example being unrewarded, crowded, or dangerous. Here we propose an additional function for negative feedback signals during foraging, variance reduction. We show that while on average populations will converge to desired distributions over forage patches both with and without negative feedback signals, in small populations negative feedback reduces variation around the target distribution compared to the use of positive feedback alone. Our results are independent of the nature of the target distribution, providing it can be achieved by foragers collecting only local information. Since robustness is a key aim for biological systems, and deviation from target foraging distributions may be costly, we argue that this could be a further important and hitherto overlooked reason that negative feedback signals are used by foraging social insects.     

Altering meal timing to improve cognitive performance during simulated nightshifts

ABSTRACT

Altering meal timing could improve cognition, alertness, and thus safety during the nightshift. This study investigated the differential impact of consuming a meal, snack, or not eating during the nightshift on cognitive performance (ANZCTR12615001107516). 39 healthy participants (59% male, age mean±SD: 24.5 ± 5.0y) completed a 7-day laboratory study and underwent four simulated nightshifts. Participants were randomly allocated to: Meal at Night (MN; n= 12), Snack at Night (SN; n = 13) or No Eating at Night (NE; n = 14). At 00:30 h, MN consumed a meal and SN consumed a snack (30% and 10% of 24 h energy intake respectively). NE did not eat during the nightshift. Macronutrient intake was constant across conditions. At 20:00 h, 22:30 h, 01:30 h, and 04:00 h, participants completed the 3-min Psychomotor Vigilance Task (PVT-B), 40-min driving simulator, post-drive PVT-B, subjective sleepiness scale, 2-choice Reaction Time task, and Running Memory task. Objective sleep was recorded for each of the day sleeps using Actigraphy and for the third day sleep, Polysomnography was used. Performance was compared between conditions using mixed model analyses. Significant two-way interactions were found. At 04:00 h, SN displayed increased time spent in the safe zone (p < .001; percentage of time spent within 10 km/h of the speed limit and 0.8 m of lane center), and decreases in speed variability (p < .001), lane variability (p < .001), post-drive PVT-B lapses (defined as RT > 355 ms; p < .001), and reaction time on the 2-choice reaction time task (p < .001) and running memory task (p < .001) compared to MN and NE. MN reported greater subjective sleepiness at 04:00 h (p < .001) compared to SN and NE. There was no difference in objective sleep between eating conditions. Eating a large meal during the nightshift impairs cognitive performance and sleepiness above the effects of time of night alone. For improved performance, shiftworkers should opt for a snack at night.     

Ant colony optimization for multicasting in static wireless ad-hoc networks

Nodes of wireless ad-hoc networks are generally equipped with batteries. This makes energy a scarce resource. Therefore, power consumption of network operations is critical and subject to optimization. One of the fundamental problems in ad-hoc networks is multicasting. In this work, we consider the so-called minimum energy multicast (MEM) problem in static ad-hoc networks. This problem can be stated as a combinatorial optimization problem. We develop an ant colony optimization algorithm for networks with omni-directional as well as directional antennas. The results show that our algorithm consistently outperforms existing techniques. This work was supported by grant TIN2007-66523 (FORMALISM) of the Spanish Government, and by the EU project FRONTS (FP7-ICT-2007-1) funded by the European Commission under the FET Proactive Initiative Pervasive Adaptation. In addition, Christian Blum acknowledges support from the Ramón y Cajal program of the Spanish Ministry of Science and Innovation, and Hugo Hernández acknowledges support from the Catalan Government through an FI grant.     

Distributed parallel processing in the vertical vestibulo-ocular reflex: Learning networks compared to tensor theory

The vestibulo-ocular reflex (VOR) is capable of producing compensatory eye movements in three dimensions. It utilizes the head rotational velocity signals from the semicircular canals to control the contractions of the extraocular muscles. Since canal and muscle coordinate frames are not orthogonal and differ from one another, a sensorimotor transformation must be produced by the VOR neural network. Tensor theory has been used to construct a linear transformation that can model the three-dimensional behavior of the VOR. But tensor theory does not take the distributed, redundant nature of the VOR neural network into account. It suggests that the neurons subserving the VOR, such as vestibular nucleus neurons, should have specific sensitivity-vectors. Actual data, however, are not in accord. Data from the cat show that the sensitivity-vectors of vestibular nucleus neurons, rather than aligning with any specific vectors, are dispersed widely. As an alternative to tensor theory, we modeled the vertical VOR as a three-layered neural network programmed using the back-propagation learning algorithm. Units in mature networks had divergent sensitivity-vectors which resembled those of actual vestibular nucleus neurons in the cat. This similarity suggests that the VOR sensorimotor transformation may be represented redundantly rather than uniquely. The results demonstrate how vestibular nucleus neurons can encode the VOR sensorimotor transformation in a distributed manner.     

Structural-guided design to improve the catalytic performance of aldo-keto reductase KdAKR

Aldo-keto reductases (AKRs) are important biocatalysts that can be used to synthesize chiral pharmaceutical alcohols. In this study, the catalytic activity and stereoselectivity of a NADPH-dependent AKR from Kluyveromyces dobzhanskii (KdAKR) toward t-butyl 6-chloro (5S)-hydroxy-3-oxohexanoate ((5S)-CHOH) were improved by mutating its residues in the loop regions around the substrate-binding pocket. And the thermostability of KdAKR was improved by a consensus sequence method targeted on the flexible regions. The best mutant M6 (Y28A/L58I/I63L/G223P/Y296W/W297H) exhibited a 67-fold higher catalytic efficiency compared to the wild-type (WT) KdAKR, and improved R-selectivity toward (5S)-CHOH (de_p value from 47.6% to >99.5%). Moreover, M6 exhibited a 6.3-fold increase in half-life (t_1/2) at 40°C compared to WT. Under the optimal conditions, M6 completely converted 200 g/L (5S)-CHOH to diastereomeric pure t-butyl 6-chloro-(3R, 5S)-dihydroxyhexanoate ((3R, 5S)-CDHH) within 8.0 h, with a space-time yield of 300.7 g/L/day. Our results deepen the understandings of the structure−function relationship of AKRs, providing a certain guidance for the modification of other AKRs.     

A selective learning method to improve the generalization of multilayer feedforward neural networks

Multilayer feedforward neural networks with backpropagation algorithm have been used successfully in many applications. However, the level of generalization is heavily dependent on the quality of the training data. That is, some of the training patterns can be redundant or irrelevant. It has been shown that with careful dynamic selection of training patterns, better generalization performance may be obtained. Nevertheless, generalization is carried out independently of the novel patterns to be approximated. In this paper, we present a learning method that automatically selects the training patterns more appropriate to the new sample to be predicted. This training method follows a lazy learning strategy, in the sense that it builds approximations centered around the novel sample. The proposed method has been applied to three different domains: two artificial approximation problems and a real time series prediction problem. Results have been compared to standard backpropagation using the complete training data set and the new method shows better generalization abilities.     

Algorithms for energy efficient mobile object tracking in wireless sensor networks

Wireless sensor networks have found more and more applications in a variety of pervasive computing environments, in their functions as data acquisition in pervasive applications. However, how to get better performance to support data acquisition of pervasive applications over WSNs remains to be a nontrivial and challenging task. The network lifetime and application requirement are two fundamental, yet conflicting, design objectives in wireless sensor networks for tracking mobile objects. The application requirement is often correlated to the delay time within which the application can send its sensing data back to the users in tracking networks. In this paper we study the network lifetime maximization problem and the delay time minimization problem together. To make both problems tractable, we have the assumption that each sensor node keeps working since it turns on. And we formulate the network lifetime maximization problem as maximizing the number of sensor nodes who don’t turn on, and the delay time minimization problem as minimizing the routing path length, after achieving the required tracking tasks. Since we prove the problems are NP-complete and APX-complete, we propose three heuristic algorithms to solve them. And we present several experiments to show the advantages and disadvantages referring to the network lifetime and the delay time among these three algorithms on three models, random graphs, grids and hypercubes. Furthermore, we implement the distributed version of these algorithms.     

Using ant-based agents for congestion control in ad-hoc wireless sensor networks

Ad-hoc wireless sensor networks suffer from problems of congestion, which lead to packet loss and excessive energy consumption. In this paper, we address the issue of congestion in these networks. We propose a new routing protocol for wireless sensor networks namely Ant-based Routing with Congestion Control (ARCC), which takes into account the congestion of the network at a given instant and proposes to reduce it and then finds the optimum paths between the source and the sink nodes. Simulation results show that ARCC performs better with respect to the throughput, the number of packets lost and the priority performance.     

The thermal dependence of fast-start performance in fish

Many fish species use fast-starts to escape predators and capture prey. There is evidence for changes in fast-start behaviour with temperature, over acute, seasonal, developmental and evolutionary time scales. Maximum velocity often increases with acute temperature changes. Thermal acclimation can improve fast-start performance, although responses appear to be reduced in more eurythermal species. Changes in performance with thermal acclimation are often reflected at the molecular, biochemical and cellular levels of organisation. There appears to be little compensation in fast-start performance in Antarctic fish compared to warmer water species.     

Information maintenance and statistical dependence reduction in simple neural networks

This study compares the ability of excitatory, feed-forward neural networks to construct good transformations on their inputs. The quality of such a transformation is judged by the minimization of two information measures: the information loss of the transformation and the statistical dependency of the output. The networks that are compared differ from each other in the parametric properties of their neurons and in their connectivity. The particular network parameters studied are output firing threshold, synaptic connectivity, and associative modification of connection weights. The network parameters that most directly affect firing levels are threshold and connectivity. Networks incorporating neurons with dynamic threshold adjustment produce better transformations. When firing threshold is optimized, sparser synaptic connectivity produces a better transformation than denser connectivity. Associative modification of synaptic weights confers only a slight advantage in the construction of optimal transformations. Additionally, our research shows that some environments are better suited than others for recoding. Specifically, input environments high in statistical dependence, i.e. those environments most in need of recoding, are more likely to undergo successful transformations.     

Exploiting application buffer reuse to improve MPI small message transfer protocols over RDMA-enabled networks

To avoid the memory registration cost for small messages in MPI implementations over RDMA-enabled networks, message transfer protocols involve a copy to intermediate buffers at both sender and receiver. In this paper, we propose to eliminate the send-side copy when an application buffer is reused frequently. We show that it is more efficient to register the application buffer and use it for data transfer. The idea is examined for small message transfer protocols in MVAPICH2, including RDMA Write and Send/Receive based communications, one-sided communications and collectives. The proposed protocol adaptively falls back to the current protocol when the application does not frequently use its buffers. The performance results over InfiniBand indicate up to 14% improvement for single message latency, close to 20% improvement for one-sided operations and up to 25% improvement for collectives. In addition, the communication time in MPI applications with high buffer reuse is improved using this technique.     

Use of hydrogel coating to improve the performance of implanted glucose sensors

In order to protect implanted glucose sensors from biofouling, novel hydrogels (146-217% water by mass) were developed based on a copolymer of hydroxyethyl methacrylate (HEMA) and 2,3-dihydroxypropyl methacrylate (DHPMA). The porosity and mechanical properties of the hydrogels were improved using N-vinyl-2-pyrrolidinone (VP) and ethyleneglycol dimethacrylate (EGDMA). The results of SEM and DSC FT-IT analyses showed that the hydrogel (VP30) produced from a monomeric mixture of 34.5% HEMA, 34.5% DHPMA, 30% VP and 1% EDGMA (mol%) had an excellent pore structure, high water content at swelling equilibrium (W eq=166% by mass) and acceptable mechanical properties. Two kinds of VP30-coated sensors, Pt/GOx/VP30 and Pt/GOx/epoxy-polyurethane (EPU)/VP30 sensors were examined in glucose solutions during a period of 4 weeks. The Pt/GOx/VP30 sensors produced large response currents but the response linearity was poor. Therefore, further studies were focused on the Pt/GOx/EPU/VP30 sensors. With a diffusion-limiting epoxy-polyurethane membrane, the linearity was improved (2-30 mM) and the response time was within 5 min. Eight Pt/GOx/EPU/VP30 sensors were subcutaneously implanted in rats and tested once per week over 4 weeks. All of the implanted sensors kept functioning for at least 21 days and 3 out of 8 sensors still functioned at day 28. Histology revealed that the fibrous capsules surrounding hydrogel-coated sensors were thinner than those surrounding Pt/GOx/EPU sensors after 28 days of implantation.     

Carbohydrate loading failed to improve 100-km cycling performance in a placebo-controlled trial.

We evaluated the effect of carbohydrate (CHO) loading on cycling performance that was designed to be similar to the demands of competitive road racing. Seven well-trained cyclists performed two 100-km time trials (TTs) on separate occasions, 3 days after either a CHO-loading (9 g CHO. kg body mass(-1). day(-1)) or placebo-controlled moderate-CHO diet (6 g CHO. kg body mass(-1). day(-1)). A CHO breakfast (2 g CHO/kg body mass) was consumed 2 h before each TT, and a CHO drink (1 g CHO. kg(.)body mass(-1). h(-1)) was consumed during the TTs to optimize CHO availability. The 100-km TT was interspersed with four 4-km and five 1-km sprints. CHO loading significantly increased muscle glycogen concentrations (572 +/- 107 vs. 485 +/- 128 mmol/kg dry wt for CHO loading and placebo, respectively; P < 0.05). Total muscle glycogen utilization did not differ between trials, nor did time to complete the TTs (147.5 +/- 10.0 and 149.1 +/- 11.0 min; P = 0.4) or the mean power output during the TTs (259 +/- 40 and 253 +/- 40 W, P = 0.4). This placebo-controlled study shows that CHO loading did not improve performance of a 100-km cycling TT during which CHO was consumed. By preventing any fall in blood glucose concentration, CHO ingestion during exercise may offset any detrimental effects on performance of lower preexercise muscle and liver glycogen concentrations. Alternatively, part of the reported benefit of CHO loading on subsequent athletic performance could have resulted from a placebo effect.     

A simple vector system to improve performance and utilisation of recombinant antibodies

Background  

Isolation of recombinant antibody fragments from antibody libraries is well established using technologies such as phage display. Phage display vectors are ideal for efficient display of antibody fragments on the surface of bacteriophage particles. However, they are often inefficient for expression of soluble antibody fragments, and sub-cloning of selected antibody populations into dedicated soluble antibody fragment expression vectors can enhance expression.