ALBERT

Description: It is known that if the objective of a wireless sensor network is not to reconstruct individual sensor readings at a fusion center but rather to compute a linear function of them, then the interference property of the wireless channel can be beneficially harnessed by letting nodes transmit simultaneously. Recently, an analog computation scheme was proposed to show that it is possible to take the advantage of the interference property even if nonlinear functions are to be computed. The scheme involves some pre-processing on the sensor readings and post-processing on the superimposed signals observed by the fusion center. Correspondingly, this paper provides a thorough base for a theory of analog-computing functions over wireless channels by specifying what is the maximum achievable. This means it is determined for networks of arbitrary topology which functions are generally analog-computable over the channel and how many wireless resources are needed. It turns out that the considerations are closely related to the famous 13th Hilbert problem and that analog-computations can be universally performed in the sense that the pre-processing at sensor nodes is independent of the function to be computed. Universality reduces the complexity of transmitters and the signaling overhead, and it is shown that this property is preserved if nodes leave or join the network. Analog-computability is therefore of high practical relevance as it allows for an efficient computation of functions in sensor networks.

Description: We study the application of matrix completion in the process of calibrating physical devices. In particular we propose an algorithm together with reconstruction bounds for calibrating circular ultrasound tomography devices. We use the time-of-flight (ToF) measurements between sensor pairs in a homogeneous medium to calibrate the system. The calibration process consists of a low-rank matrix completion algorithm to de-noise and estimate random and structured missing ToFs, and the classic multi-dimensional scaling method to estimate the sensor positions from the ToF measurements. We provide theoretical bounds on the calibration error. Several simulations are conducted to evaluate the theoretical results presented in this paper.

Description: We propose a particle filtering technique to track multiple maneuvering targets in the presence of clutter. We treat data association and state estimation, which are the two important sub-problems in tracking, as separate problems. We develop a game-theoretic framework to solve the data association, in which we model each tracker as a player and the set of measurements as strategies. We develop utility functions for each player, and then use a regret-based learning algorithm to find the equilibrium of this game. The game-theoretic approach allows us to associate measurements to all the targets simultaneously. Further, in contrast to the traditional Monte-Carlo data association algorithms that use samples of the association vector obtained from a proposal distribution, our method finds the association in a deterministic fashion. We then use Monte-Carlo sampling on the reduced dimensional state of each target, independently, and thereby mitigate the curse-of-dimensionality problem that is known to occur in particle filtering. We provide a number of numerical results to demonstrate the performance of our proposed filtering algorithm.

Description: In this paper we deal with the problem of detecting an extended target embedded in homogeneous Gaussian interference with unknown but structured covariance matrix. We model the possible target echo, from each range bin under test, as a deterministic signal with an unknown scaling factor accounting for the target response. At the design stage, we exploit some a-priori knowledge about the operating environment enforcing the inverse interference plus noise covariance matrix to belong to a set described via unitary invariant continuous functions. Hence, we derive the constrained Maximum Likelihood (ML) estimates of the unknown parameters, under both the $H_{0}$ and $H_{1}$ hypotheses, and design the Generalized Likelihood Ratio Test (GLRT) for the considered decision problem. At the analysis stage, we assess the performance of the devised GLRT for some covariance matrix uncertainty sets of practical relevance both for spatial and Doppler processing. The results highlight that correct use of the a-priori knowledge can lead to a detection performance quite close to the optimum receiver which supposes the perfect knowledge of the interference plus noise covariance matrix.

Description: In this paper, we present a novel memory-efficient high-throughput scalable architecture for multi-level 2-D DWT. We studied the existing DWT architectures and observed that data scanning method has a significant impact on the memory efficiency of DWT architecture. We propose a novel parallel stripe-based scanning method based on the analysis of the dependency graph of the lifting scheme. With the new scanning method for multi-level 2D DWT, a high memory efficient scalable parallel pipelined architecture is developed. The proposed architecture requires no frame memory and a temporal memory of size only $3 N +682$ for the 3-level DWT decomposition with an image of size $N times N$ pixels with 32 pixels processed concurrently. The elimination of frame memory and the small temporal memory lead to significant reduction in overall size. The proposed architecture has a regular structure and achieves 100% hardware utilization. The synthesis results in 90 nm CMOS process show that the proposed architecture achieves a better area-delay product by 60% and higher throughput by 97% when compared to the best existing design for the CDF (Cohen-Daubechies-Favreau) 9/7 2-D DWT.

Description: We consider a multiple-input multiple-output (MIMO) interference channel (IC), where a single data stream per user is transmitted and each receiver treats interference as noise. The paper focuses on the open problem of computing the outermost boundary (so-called Pareto boundary-PB) of the achievable rate region under linear transceiver design. The Pareto boundary consists of the strict PB and non-strict PB. For the two user case, we compute the non-strict PB and the two ending points of the strict PB exactly. For the strict PB, we formulate the problem to maximize one rate while the other rate is fixed such that a strict PB point is reached. To solve this non-convex optimization problem which results from the hard-coupled two transmit beamformers, we propose an alternating optimization algorithm. Furthermore, we extend the algorithm to the multi-user scenario and show convergence. Numerical simulations illustrate that the proposed algorithm computes a sequence of well-distributed operating points that serve as a reasonable and complete inner bound of the strict PB compared with existing methods.

Description: This paper studies secrecy rate optimization in a wireless network with a single-antenna source, a multi-antenna destination and a multi-antenna eavesdropper. This is an unfavorable scenario for secrecy performance as the system is interference-limited. In the literature, assuming that the receiver operates in half duplex (HD) mode, the aforementioned problem has been addressed via use of cooperating nodes who act as jammers to confound the eavesdropper. This paper investigates an alternative solution, which assumes the availability of a full duplex (FD) receiver. In particular, while receiving data, the receiver transmits jamming noise to degrade the eavesdropper channel. The proposed self-protection scheme eliminates the need for external helpers and provides system robustness. For the case in which global channel state information is available, we aim to design the optimal jamming covariance matrix that maximizes the secrecy rate and mitigates loop interference associated with the FD operation. We consider both fixed and optimal linear receiver design at the destination, and show that the optimal jamming covariance matrix is rank-1, and can be found via an efficient 1-D search. For the case in which only statistical information on the eavesdropper channel is available, the optimal power allocation is studied in terms of ergodic and outage secrecy rates. Simulation results verify the analysis and demonstrate substantial performance gain over conventional HD operation at the destination.

Description: A novel filter for nonlinear and non-Gaussian systems is proposed in this paper. The unscented Kalman filter is designed to give a preliminary estimation of the state. An additional RBF-network is added to the UKF innovation term to compensate for the non-Gaussianity of the whole system. The Renyi's entropy of the innovation is introduced and parameters of the RBF-network are updated using minimum entropy criterion at each time step. It has been shown that the proposed algorithm has a high accuracy in estimation because entropy can characterize all the randomness of the residual while UKF only cares for the mean and the covariance. It has been proved that with properly chosen bandwidth $Sigma$ , the minimum entropy problem of the innovation is convex. Therefore, the proposed adaptive nonlinear filter will be globally convergent and the misadjustment will be proportional to the step size $mu$ . The effectiveness of the proposed method is shown by simulation.

Description: Clostridium acetobutylicum has been considered as an attractive platform host for biorefinery due to its metabolic diversity. Considering its capability to overproduce butanol through butyrate, it was thought that butyric acid can also be efficiently produced by this bacterium through metabolic engineering. The pta-ctfB -deficient C. acetobutylicum CEKW, in which genes encoding phosphotransacetylase and CoA-transferase were knocked out, was assessed for its potential as a butyric acid producer in fermentations with four controlled pH values at 5.0, 5.5, 6.0, and 6.4. Butyric acid could be best produced by fermentation of the CEKW at pH 6.0, resulting in the highest titer of 26.6 g/l, which is 6.4 times higher than that obtained with the wild type. However, due to the remaining solventogenic ability of the CEKW, 3.6 g/l solvents were also produced. Thus, the CEKW was further engineered by knocking out the adhE1 -encoding aldehyde/alcohol dehydrogenase to prevent solvent production. Batch fermentation of the resulting C. acetobutylicum HCEKW at pH 6.0 showed increased butyric acid production to 30.8 g/l with a ratio of butyric-to-acetic acid (BA/AA) of 6.6 g/g and a productivity of 0.72 g/l/h from 86.9 g/l glucose, while negligible solvent (0.8 g/l ethanol only) was produced. The butyric acid titer, BA/AA ratio, and productivity obtained in this study were the highest values reported for C. acetobutylicum , and the BA/AA ratio and productivity were also comparable to those of native butyric acid producer Clostridium tyrobutyricum . These results suggested that the simultaneous deletion of the pta-ctfB-adhE1 in C. acetobutylicum resulted in metabolic switch from biphasic to acidogenic fermentation, which enhanced butyric acid production.

Description: In this paper, we explore a sequential Bayesian bound for state-space models focusing on hybrid continuous and discrete random states. We provide an analytic recursion for the sequential Weiss–Weinstein (SWW) bound for linear state-space models with solutions for Gaussian, uniform, and exponential distributions as derived, as well as for a combination of these. We compare the SWW bound for discretized states with the corresponding bound for the continuous states. The SWW bound is contrasted with the sequential Cramér–Rao bound for Gaussian distributions. Practical issues of SWW bounds are discussed and numerical simulation results provide insights into their behavior.

Description: Achieving better imaging of weak sources in the presence of strong interfering sources is a major challenge in various fields of signal processing, such as radio astronomy, SAR imaging, SONAR and wideband signal processing. We present a new algorithm for parameter estimation that can be implemented when a moving array is used. This adaptive beamformer can be employed in a variety of applications, such as radio astronomy with synthetic aperture arrays, SAR imaging, DOA estimation in towed array SONAR and wideband DOA estimation. Analytic performance analysis is provided together with simulations and tests on a new radio astronomy array. All these indicate a significant improvement compared to currently used filterbank techniques such as the MVDR, when strong interference is present, either inside or outside the field of view of the array. The latter case is especially important when directional antennas are used.

Description: This paper addresses the problem of adaptive waveform design for estimation of parameters of linear systems. This problem arises in several applications such as radar, sonar, or tomography. In the proposed technique, the transmit/input signal waveform is optimally determined at each step based on the observations in the previous steps. The waveform is determined to minimize the Bayesian Cramér-Rao bound (BCRB) or the Reuven-Messer bound (RMB) for estimation of the unknown system parameters at each step. The algorithms are tested for spatial transmit waveform design in multiple-input multiple-output radar target angle estimation at very low signal-to-noise ratio. The proposed techniques allow to automatically focusing the transmit beam toward the target direction. The simulations show that the proposed adaptive waveform design methods achieve significantly higher rate of performance improvement as a function of the pulse index, compared to other signal transmission methods, in terms of estimation accuracy.

Description: Disruption of spatiotemporal behavior of intracellular signaling cascades including tumor necrosis factor alpha-related apoptosis-inducing ligand (TRAIL)-mediated signaling in prostate cancer has gained tremendous attention in the past few years. There is an increasing effort in translating the emerging information about TRAIL-mediated signaling obtained through experimental and preclinical data to clinic. Fascinatingly, novel targeting approaches are being developed to enhance the tissue- or subcellular-specific delivery of drugs with considerable focus on prostate cancer. These applications have the potential to revolutionize prostate cancer therapeutic strategies and include the accumulation of drugs in target tissue as well as the selection of internalizing ligands for enhanced receptor-mediated uptake of drugs. In this mini-review, we outline outstanding developments in therapeutic strategies based on the regulation and/or targeting of TRAIL pathway for the treatment of prostate cancer. Moreover, microRNAs (miRNAs), with potential transcriptional and posttranscriptional regulation of gene expression, will be presented for their potential in prostate cancer treatment. Emphasis has been given to the use of delivery approaches, especially based on nanotechnology. Considerably, enhanced information regarding miRNA regulation of TRAIL-mediated signaling in prostate cancer cells may provide potential biomarkers for the characterization of patients as responders and nonresponders of TRAIL-based therapy and could provide rationalized basis for combination therapies with TRAIL death receptor-targeting drugs.

Description: The development of cellulase-based bioprocess is afflicted by the processing efficiency of enzymes. To address this issue, a method based on artificial oil bodies (AOBs) was proposed to integrate production and immobilization of recombinant cellulase. First, the heterologous endoglucanase ( celA ), cellobiohydrolase ( celK ), and β-glucosidase ( gls ) genes were individually fused with oleosin, a structural protein of plant seed oils. After expression in Escherichia coli , each fusion protein of insolubility was mixed together with plant oils. AOBs were assembled by subjecting the mixture to sonication. Consequently, active CelA, CelK, and Gls were resumed and co-immobilized on AOBs surface. Finally, the assembly condition (including the protein ratio) and the reaction condition were further optimized by response surface methodology. The resulting AOBs-bound cellulase remained stable for 4 cycles of cellulose–hydrolyzed reactions. Overall, the result shows a promise of this proposed approach for processing recombinant cellulase, which may provide a facile method to investigate optimum combination of cellulase components towards various cellulosic materials.

Description: In this paper, we investigate the robust beamforming schemes for a multi-user multiple-input-single-output (MU-MISO) system with per-antenna power constraints and quantized channel direction information (CDI) feedback. Our design objective is to maximize the expectation of the weighted sum-rate performance by means of controlling the interference leakage and properly allocating the power among user equipments (UEs). First, we prove the optimality of the non-robust zero-forcing (ZF) beamforming scheme in the sense of generating the minimum amount of average inter-UE interference under quantized CDI. Then we derive closed-form expressions of the cumulative density function (CDF) of the interference leakage power for the non-robust ZF beamforming scheme, based on which we adjust the leakage thresholds and propose two robust beamforming schemes under per-antenna power constraints with an iterative process to update the per-UE power allocations using the geometric programming (GP). Simulation results show the superiority of the proposed robust beamforming schemes compared with the existing schemes in terms of the average weighted sum-rate performance.

Description: Separation strategies based on size-selective precipitation of DNA fragments with polyethylene glycol (PEG) have been used for achieving desired DNA interval in automated sample preparation for next-generation sequencing. By varying PEG concentration, DNA fragments of different sizes can be precipitated onto surfaces of carboxyl-coated paramagnetic particles selectively, and therefore, the desired DNA interval can be obtained. However, one of the crucial points in this approach is to determine the critical PEG concentration for DNA fragment of a certain size. The aim of this work was to develop a convenient and reliable method for accurately determining the critical PEG concentration. In our method, at a fixed concentration of sodium chloride (NaCl), recovered DNA samples obtained with different PEG concentrations were directly quantified, and their concentrations as a function of the PEG concentration were fitted by the logistic function. The critical PEG value was easily and accurately determined from the fitted logistic function. The repeatability and stability of the critical PEG value were assessed, showing an excellent reliability of the method. Based on this method, critical PEG values of different-size DNA fragments were determined at different NaCl concentrations. The effectiveness of the method was also demonstrated by selective precipitation of DNA fragments.

Description: A recombinant oleate hydratase from Lysinibacillus fusiformis converted ricinoleic acid to a product, whose chemical structure was identified as the novel compound 10,12-dihydroxystearic acid by gas chromatograph/mass spectrometry, Fourier transform infrared, and nuclear magnetic resonance analysis. The reaction conditions for the production of 10,12-dihydroxystearic acid were optimized as follows: pH 6.5, 30 °C, 15 g l −1 ricinoleic acid, 9 mg ml −1 of enzyme, and 4 % ( v / v ) methanol. Under the optimized conditions, the enzyme produced 13.5 g l −1 10,12-dihydroxystearic acid without detectable byproducts in 3 h, with a conversion of substrate to product of 90 % ( w / w ) and a productivity of 4.5 g l −1  h −1 . The emulsifying activity of 10,12-dihydroxystearic acid was higher than that of oleic acid, ricinoleic acid, stearic acid, and 10-hydroxystearic acid, indicating that 10,12-dihydroxystearic acid can be used as a biosurfactant.

Description: Delta-sigma $(Delta Sigma)$ A/D conversion is a popular technique used to achieve high resolution data conversion for low to moderate bandwidth applications. It is commonly accepted that the digital circuitry of the $Delta Sigma$ A/D converters should perform a linear time-invariant (LTI) filtering on the output of the $Delta Sigma$ modulator in order to reconstruct the input signal. However, it has been shown that, when higher order $Delta Sigma$ A/D converters are operated at higher oversampling ratios (OSRs), non-linear reconstruction algorithms extract more information about the input signal than LTI methods. Still, use of non-linear algorithms has been limited due to their complexity and stability issues. Two practical non-linear methods presented in the literature are fast projection onto convex sets (POCS) and direct projection (DP). In this work, we show that the non-linear reconstruction process for $Delta Sigma$ modulated sequences can be treated as a linear feasibility problem (LFP). We then show that if the reconstruction process is defined as an LFP, its implementation is less complex than in the case of the DP method. We further describe how the LFP can be well-conditioned and demonstrate the reconstruction process by using the surrogate constraint algorithm with random constraint selection. The described algorithm considers a small number of constraints at a time, which makes it suitable for serial implementation.

Description: Cognitive radio (CR) systems require awareness of spectrum occupancy in order to operate without causing harmful interference to primary users (PUs). Cyclostationary feature detection (CFD) is a preferred method for spectrum sensing under low signal-to-noise ratio (SNR) or/and noise uncertainty scenarios. To determine the presence, or otherwise, of PU signals, conventional CFD schemes tend to use test statistics over, either, multiple cycle frequencies for a fixed lag set, or, multiple lags for a fixed cycle frequency. This paper proposes a new method that jointly utilizes cycle frequencies and lags to produce more reliable test statistics. As the optimal way to apply this joint utilization requires prior knowledge of the 4th-order cyclic cumulant, which can be challenging to obtain, an alternative sub-optimal scheme independent of this cumulant knowledge will also be provided. It will be shown that, in the low SNR region, where it is most critical for CR applications, the proposed sub-optimal scheme can lead to similar detection performances as the optimal maximum likelihood technique. It will also be demonstrated that, compared to multi-cycle-frequency detection with selection combining, equal gain combining, or maximum ratio combining, the proposed provide superior performance.

Description: In this paper, we study the problem of code design to improve the detection performance of multi-static radar in the presence of clutter (i.e., a signal-dependent interference). To this end, we briefly present a discrete-time formulation of the problem as well as the optimal detector in the presence of Gaussian clutter. Due to the lack of analytical expression for receiver operation characteristic (ROC), code design based on ROC is not feasible. Therefore, we consider several popular information-theoretic criteria including Bhattacharyya distance, Kullback-Leibler (KL) divergence, J-divergence, and mutual information (MI) as design metrics. The code optimization problems associated with different information-theoretic criteria are obtained and cast under a unified framework. We propose two general methods based on Majorization-Minimization to tackle the optimization problems in the framework. The first method provides optimal solutions via successive majorizations whereas the second one consists of a majorization step, a relaxation, and a synthesis stage. Moreover, derivations of the proposed methods are extended to tackle the code design problems with a peak-to-average ratio power (PAR) constraint. Using numerical investigations, a general analysis of the coded system performance, computational efficiency of the proposed methods, and the behavior of the information-theoretic criteria is provided.

Description: Inspired from modern out-of-equilibrium statistical physics models, a matrix product based framework is defined and studied, that permits the formal definition of random vectors and time series whose desired joint distributions are a priori prescribed. Its key feature consists of preserving the writing of the joint distribution as the simple product structure it has under independence, while inputing controlled dependencies amongst components: This is obtained by replacing the product of probability densities by a product of matrices of probability densities. It is first shown that this matrix product model can be remapped onto the framework of Hidden Markov Models. Second, combining this dual perspective enables us both to study the statistical properties of this model in terms of marginal distributions and dependencies (a stationarity condition is notably devised) and to devise an efficient and accurate numerical synthesis procedure. A design procedure is also described that permits the tuning of model parameters to attain targeted statistical properties. Pedagogical well-chosen examples of times series and multivariate vectors aim at illustrating the power and versatility of the proposed approach and at showing how targeted statistical properties can actually be prescribed.

Description: Bacillus amyloliquefaciens FZB42 has been shown to stimulate plant growth and to suppress the growth of plant pathogenic organisms including nematodes. However, the mechanism underlying its effect against nematodes remains unknown. In this study, we screened a random mutant library of B. amyloliquefaciens FZB42 generated by the mariner transposon Tn YLB-1 and identified a mutant strain F5 with attenuated nematicidal activity. Reversible polymerase chain reaction revealed that three candidate genes RAMB_007470 , yhdY , and prkA that were disrupted by the transposon in strain F5 potentially contributed to its decreased nematicidal activity. Bioassay of mutants impaired in the three candidate genes demonstrated that directed deletion of gene RBAM_007470 resulted in loss of nematicidal activity comparable with that of the F5 triple mutant. RBAM_007470 has been reported as being involved in biosynthesis of plantazolicin, a thiazole/oxazole-modified microcin with hitherto unknown function. Electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) analyses of surface extracts revealed that plantazolicin bearing a molecular weight of 1,354 Da was present in wild-type B. amyloliquefaciens FZB42, but absent in the Δ RABM_007470 mutant. Furthermore, bioassay of the organic extract containing plantazolicin also showed a moderate nematicidal activity. We conclude that a novel gene RBAM_007470 and its related metabolite are involved in the antagonistic effect exerted by B. amyloliquefaciens FZB42 against nematodes.

Description: Syngas fermentation is a promising route for resource recovery. Acetate is an important industrial chemical product and also an attractive precursor for liquid biofuels production. This study demonstrated high fraction acetate production from syngas (H 2 and CO 2 ) in a hollow-fiber membrane biofilm reactor, in which the hydrogen utilizing efficiency reached 100 % during the operational period. The maximum concentration of acetate in batch mode was 12.5 g/L, while the acetate concentration in continuous mode with a hydraulic retention time of 9 days was 3.6 ± 0.1 g/L. Since butyrate concentration was rather low and below 0.1 g/L, the acetate fraction was higher than 99 % in both batch and continuous modes. Microbial community analysis showed that the biofilm was dominated by Clostridium spp., such as Clostridium ljungdahlii and Clostridium drakei , the percentage of which was 70.5 %. This study demonstrates a potential technology for the in situ utilization of syngas and valuable chemical production.

Description: Lignosulfonates(LSs), by-products from chemical pulping processes, are low-value products with limited dispersion properties. The ability of commercially available horseradish peroxidase (HRP) to polymerize LS macromolecules and improve the dispersion properties of LSs was investigated. The polymerization of LSs proceeded efficiently under mild reaction conditions in an aqueous solution with HRP/H 2 O 2 . Gel permeation chromatography showed a significant increase in weight-average molecular weight ( M w ) of sulfonated kraft lignin and sodium lignosulfonate (NaLS) by 8.5-fold and 4.7-fold, respectively. The mechanism of polymerization was investigated by elemental analysis, surface charge measurement, headspace gas chromatography, infrared spectroscopy (IR), and hydrogen nuclear magnetic resonance spectrometry ( 1 H-NMR). The functional group measurements indicated that HRP incubation did not reduce the sulfonic group content. However, it decreased the phenolic and methoxyl group contents. As the phenolic group content decreased, M w increased as a power function. The polymerization was proposed to involve the random coupling of phenoxy radical intermediates. The radicals coupled with each other to form different inter-unit linkages, most of which were the β-O-4’ type, as the 1 H-NMR spectra indicated. Moreover, the HRP/H 2 O 2 incubation induced a significant improvement in the adsorption and dispersion properties of LSs. Therefore, the HRP/H 2 O 2 incubation is a promising approach for industrial applications of LSs.

Description: Marine microalga Nannochloropsis oculata possesses nutrients valuable for human health. In this study, we added freeze-dried N. oculata powder to soybean oil and observed a remarkable inhibition in oil oxidation. The amount of microalgae powder added was positively correlated to the increase in oil stability. The addition of 5.0 % ( w / w ) microalgae powder increased the oil stability index (OSI) values of soybean oil more than twofold at the tested temperatures 120 and 130 °C. N . oculata contains high levels of both phenolic compounds and α-tocopherols that could be the contributors to such an increase of the OSI. Two methods were conducted to assay the active ingredients released from microalgae: one employed three solvent systems to extract the microalgae and the other was the soybean oil added with microalgae. Analyses of free radical scavenging and reducing power suggested that the phenolic compounds dominated the antioxidation activities in soybean oil when it was infused with the microalgae powder. Our results suggest that N. oculata could potentially be used as an additive in cooking oil to increase the shelf life and nutritional value of the oil and to reduce the production of free radicals from lipid oxidation when the oil is used at high-temperature cooking processes.

Description: The actinomycete Streptomyces platensis produces two compounds that display antibacterial activity: platensimycin and platencin. These compounds were discovered by the Merck Research Laboratories, and a complex insoluble production medium was reported. We have used this medium as our starting point in our studies. In a previous study, we developed a semi-defined production medium, i.e., PM5. In the present studies, by varying the concentration of the components of PM5, we were able to develop a superior semi-defined medium, i.e., PM6, which contains a higher concentration of lactose. Versions of PM6, containing lower concentrations of all components, were also found to be superior to PM5. The new semi-defined production media contain dextrin, lactose, MOPS buffer, and ammonium sulfate in different concentrations. We determined antibiotic production capabilities using agar diffusion assays and chemical assays via thin-layer silica chromatography and high-performance liquid chromatography. We reduced crude nutrient carryover from the seed medium by washing the cells with distilled water. Using these semi-defined media, we determined that addition of the semi-defined component soluble starch stimulated antibiotic production and that it and dextrin could both be replaced with glucose, resulting in the chemically defined medium, PM7.

Description: Pichia pastoris is widely used as a host system for heterologous protein expression in both academia and industry. Production is typically accomplished by a fed-batch induction process that is known to have negative impacts on cell physiology that impose limits on both protein yields and quality. We have analysed recombinant protein production in chemostat cultures to understand the physiological responses associated with methanol-induced production of two human lysozyme variants with different degrees of misfolding by P . pastoris . Confounding variables associated with nutrient stress or growth-rate are minimised during steady-state growth in chemostats. Comparison of transcriptome-level data obtained during the non-inducing and inducing steady states identified changes in expression of only about 1 % of the genome during production of either an amyloidogenic human lysozyme variant prone to intracellular aggregation (I56T) or a misfolded but secretable variant (T70N), indicating near-complete acclimation to their production. A marked, but temporary, stress response involving both the unfolded protein response (UPR) and ER-associated degradation pathway was observed during the transient between steady states, particularly following induction of the T70N variant synthesis, and was accompanied by changes in expression of around 50 antisense transcripts. The results suggest that optimal heterologous protein production could best be achieved by a continuous process that minimises the number of methanol-induced transients experienced by the cultures. The processing of HAC1 mRNA required for the UPR was found to be constitutive in the culture conditions used, even in the absence of recombinant protein induction.

Description: The Aminobacter sp. strain MSH1 has potential for pesticide bioremediation because it degrades the herbicide metabolite 2,6-dichlorobenzamide (BAM). Production of the BAM-degrading bacterium using aerobic bioreactor fermentation was investigated. A mineral salt medium limited for carbon and with an element composition similar to the strain was generated. The optimal pH and temperature for strain growth were determined using shaker flasks and verified in bioreactors. Glucose, fructose, and glycerol were suitable carbon sources for MSH1 ( μ  = 0.1 h −1 ); slower growth was observed on succinate and acetic acid ( μ  = 0.01 h −1 ). Standard conditions for growth of the MSH1 strain were defined at pH 7 and 25 °C, with glucose as the carbon source. In bioreactors (1 and 5 L), the specific growth rate of MSH1 increased from μ  = 0.1 h −1 on traditional mineral salt medium to μ  = 0.18 h −1 on the optimized mineral salt medium. The biomass yield under standard conditions was 0.47 g dry weight biomass/g glucose consumed. An investigation of the catabolic capacity of MSH1 cells harvested in exponential and stationary growth phases showed a degradation activity per cell of about 3 × 10 −9  μg BAM h −1 . Thus, fast, efficient, large-scale production of herbicide-degrading Aminobacter was possible, bringing the use of this bacterium in bioaugmentation field remediation closer to reality.

Description: Flow-induced Molecular Communication (FMC), where molecular transport is performed via flow, is utilized in microfluidic channels to enhance diffusion-based molecular communication. The incorporation of the microfluidic channel and the transport of molecules by flow, i.e., convection, require a rigorous analysis to develop an end-to-end concentration propagation model and a design for microfluidic channels. To the best of our knowledge, this is the first attempt to analyze concentration propagation in microfluidic channels from FMC perspective and devise them specifically to enhance the FMC. In this paper, a system-theoretic analysis of molecular transport is presented first. The system-theoretic model incorporates the solution of flow velocity in microfluidic channels and yields an end-to-end transfer function for concentration propagation based on building blocks of microfluidic channels. Then, the design of microfluidic channels is performed based on the least-squares Finite Impulse Response (FIR) filtering to achieve the desired end-to-end transfer function in FMC. According to the desired pass and stop bands, the required length and aspect-ratio parameters of the microfluidic channels are obtained for FIR filtering. The transfer functions for FMC is elaborated via numerical results. Furthermore, two example designs of microfluidic channels are presented for least-squares FIR band-pass and band-stop filtering in FMC.

Description: We study the problem of linear filter optimization with finite sample size, which has wide applications such as beamformer design in wireless communications and portfolio optimization in finance. Traditional methods in both fields are not robust against the imprecise channel vector and the noise covariance matrix (or the mean return and the covariance of assets in finance) due to finite sample size. We consider estimation errors both in the channel vector and the noise covariance matrix (or the mean return and the covariance) simultaneously. We resort to high-dimensional asymptotics to account for the fact that the observation dimension is of the same order of magnitude as the number of samples, and use the diagonal loading method (or the shrinkage estimator) to improve the robustness. The channel vector (or mean return) and the noise covariance matrix are estimated from the training data, and then corrected under several widely-used criteria. In an asymptotic setting where the number of samples is comparable to the observation dimension, we obtain linear filters that are as good as the optimal filters with a shrinkage structure and a perfect channel vector (or mean return) under different criteria. Monte Carlo simulations show the advantage of our linear filters in the finite sample size regime.

Description: Soy sauce is a traditional condiment manufactured by natural inoculation and mixed culture fermentation. As is well known, it is the microbial community that plays an important role in the formation of its flavors. However, to date, its dynamic changes during the long period of fermentation process are still unclear, intensively constraining the improvement and control of the soy sauce quality. In this work, we revealed the dynamic changes of the microbial community by combining a cultured dependent method and a cultured independent method of polymerase chain reaction (PCR)-denaturing gradient gel electrophoresis. Results indicated that the two methods verified and complemented each other in profiling microbial community, and that significant dynamics of the microbial community existed during the fermentation process, especially the strong inhibition of the growth of most of the microbes when entering into the mash stage from the koji stage. In the analysis of bacterial community, Staphylococcus and Bacillus were found to be the dominant bacteria and detected in the whole fermentation process. Kurthia and Klebsiella began to appear in the koji stage and then fade away in the early stage of the mash fermentation. In the analysis of fungal community, Aspergillus sojae and Zygosaccharomyces rouxii were found to be the dominant fungi in the koji and mash fermentation, respectively. It was clearly shown that when A. sojae decreased and disappeared in the middle stage of the mash fermentation, Z. rouxii appeared and increased at the meantime. Aspergillus parasiticus , Trichosporon ovoides and Trichosporon asahii also appeared in the koji and the early period of the mash fermentation and disappeared thereafter. Similar to Z. rouxii , Millerozyma farinosa and Peronospora farinosa were also found spontaneously which appeared in the mid-late period of the mash fermentation. The principal component analysis suggested that the microbial community underwent significant changes in the early period of the fermentation and, thereafter, tended to the stabilization in the mid-late periods. This study gave us important clues to understand the fermentation process and can serve as a foundation for improving the quality of soy sauce in the future.

Description: Galactosidases are widespread enzymes that are used for manifold applications, including production of prebiotics, biosynthesis of different transgalactosylated products, improving lactose tolerance and in various analytical approaches. The nature of these applications often require galactosidases to be present in a purified form with clearly defined properties, including precisely determined substrate specificities, low sensitivity to inhibitors, and high efficiency and stability under distinct conditions. In this study, we present the recombinant expression and purification of two previously uncharacterized β-galactosidases from Aspergillus nidulans as well as one β-galactosidase from Aspergillus niger . All enzymes were active toward p -nitrophenyl-β- d -galactopyranoside as substrate and displayed similar temperature and pH optima. The purified recombinant galactosidases digested various complex substrates containing terminal galactose β-1,4 linked to either N -acetylglucosamine or fucose, such as N -glycans derived from bovine fibrin and Caenorhabditis elegans . In our comparative study of the recombinant galactosidases with the commercially available galactosidase from Aspergillus oryzae , all enzymes also displayed various degrees of activity toward complex oligosaccharides containing β-1,3-linked terminal galactose residues. All recombinant enzymes were found to be robust in the presence of various organic solvents, temperature variations, and freeze/thaw cycles and were also tested for their ability to synthesize galactooligosaccharides. Furthermore, the use of fermentors considerably increased the yield of recombinant galactosidases. Taken together, we demonstrate that purified recombinant galactosidases from A. niger and from A. nidulans are suitable for various glycobiological and biotechnological applications.

Description: A Lolium perenne ice-binding protein ( Lp IBP) demonstrates superior ice recrystallization inhibition (IRI) activity and has proposed applications in cryopreservation, food texturing, as well as in being a “green” gas hydrate inhibitor. Recombinant production of Lp IBP has been previously conducted in bacterial and yeast systems for studies of protein characterization, but large-scale applications have been hitherto limited due to high production costs. In this work, a codon-optimized Lp IBP was recombinantly expressed and secreted in a novel one-step vector system from the nuclear genome of the green microalga Chlamydomonas reinhardtii . Both mixotrophic and photoautotrophic growth regimes supported Lp IBP expression, indicating the feasibility of low-cost production using minimal medium, carbon dioxide, and light energy as input. In addition, multiple growth and bioproduct extraction cycles were performed by repetitive batch cultivation trials, demonstrating the potential for semi-continuous production and biomass harvesting. Concentrations of recombinant protein reached in this proof of concept approach were sufficient to demonstrate IRI activity in culture media without additional purification or concentration, with activity further verified by thermal hysteresis and morphology assays. The incorporation of the recombinant Lp IBP into a model gas hydrate offers the promise that algal production may eventually find application as a “green” hydrate inhibitor.

Description: The interest in biofertilizers is increasing and so is the potential for their use in sustainable agriculture. However, many of the products that are currently available worldwide are often of very poor quality, resulting in the loss of confidence from farmers. The formulation of an inoculant is a crucial multistep process that should result in one or several strains of microorganisms included in a suitable carrier, providing a safe environment to protect them from the often harsh conditions during storage and ensuring survival and establishment after introduction into soils. One of the key issues in formulation development and production is the quality control of the products, at each stage of the process. This review presents the different components and the major steps involved in the formulation of good quality biofertilizers, including the techniques used to assess the quality of the products following production. The quality of currently available inoculants is also reviewed, emphasizing the need for better quality control systems worldwide.

Description: The Discrete Gabor Transform (DGT) is the most commonly used transform for signal analysis and synthesis using a linear frequency scale. It turns out that the involved operators are rich in structure if one samples the discrete phase space on a subgroup. Most of the literature focuses on separable subgroups, in this paper we will survey existing methods for a generalization to arbitrary groups, as well as present an improvement on existing methods. Comparisons are made with respect to the computational complexity, and the running time of optimized implementations in the C programming language. The new algorithms have the lowest known computational complexity for nonseparable lattices and the implementations are freely available for download. By summarizing general background information on the state of the art, this article can also be seen as a research survey, sharing with the readers experience in the numerical work in Gabor analysis.

Description: This study devotes to uncertainty principles under the linear canonical transform (LCT) of a complex signal. A lower-bound for the uncertainty product of a signal in the two LCT domains is proposed that is sharper than those in the existing literature. We also deduce the conditions that give rise to the equal relation of the new uncertainty principle. The uncertainty principle for the fractional Fourier transform is a particular case of the general result for LCT. Examples, including simulations, are provided to show that the new uncertainty principle is truly sharper than the latest one in the literature, and illustrate when the new and old lower bounds are the same and when different.

Description: This paper proposes a new relay selection method based on local channel state information (CSI) for a system consisting of a source, a destination and an arbitrary number of amplify-and-forward relay nodes. A set of candidate relays, whose source-relay (S-R) links are not in outage, is formed. An S-R link is in outage if its signal-to-noise ratio (SNR) is below the predefined threshold value of the destination SNR plus some adjustable margin. The candidate relay that yields the maximum second-hop SNR is then selected at the destination. Unlike the opportunistic relaying (OR) based on full CSI (F-CSI), the proposed method requires to equip the destination node with the instantaneous CSI of the S-R channel corresponding to only the selected relay. It is qualitatively shown that the training overhead of the proposed relay selection is less than or comparable to that of the partial relay selection (PRS) but can be much smaller than that of the OR with F-CSI. However, the proposed scheme requires to estimate a higher number of single-input single-output (SISO) channels than in the PRS scheme. The exact and asymptotic expressions of outage probability are derived and it is shown that the proposed method achieves full diversity. Simulation results verify theoretical analysis, and show that, for the optimized margin, the proposed scheme provides performance which is comparable to the method having F-CSI. The results also show that the proposed method significantly outperforms PRS, which may justify the linear order of the computational complexity associated with the estimation of the additional SISO channels and the low-cost one-dimensional line search used for optimizing the margin.

Description: Pulse-coupled synchronization is attracting increased attention in the sensor network community. Yet its properties have not been fully investigated. Using statistical analysis, we prove analytically that by controlling the number of connections at each node, synchronization can be guaranteed for generally pulse-coupled oscillators even in the presence of a refractory period. The approach does not require the initial phases to reside in half an oscillation cycle, which improves existing results. We also find that a refractory period can be strategically included to reduce idle listening at nearly no sacrifice to the synchronization probability. Given that reduced idle listening leads to higher energy efficiency in the synchronization process, the strategically added refractory period makes the synchronization scheme appealing to cheap sensor nodes, for which energy is a precious system resource. We also analyzed the pulse-coupled synchronization in the presence of unreliable communication links and obtained similar results. QualNet experimental results are given to confirm the effectiveness of the theoretical predictions.

Description: The Gauss-Newton algorithm is a popular and efficient centralized method for solving non-linear least squares (NLLS) problems. In this paper, a multi-agent distributed version of this algorithm is proposed to solve general NLLS problems in a network, named Gossip-based Gauss-Newton (GGN) algorithm. Furthermore, we analyze and present sufficient conditions for its convergence and show numerically that the GGN algorithm achieves performance comparable to the centralized algorithm, with graceful degradation in case of network failures. More importantly, the GGN algorithm provides significant performance gains compared to other distributed first order methods.

Description: Recently, various methods have emerged for sub- Nyquist sampling and reconstruction of signals with finite rate of innovation (FRI). These methods seek to sample parametric signals at close to their information rate and later reconstruct the parameters of interest. Some proposed reconstruction algorithms are based on annihilating filters and root-finding. Stochastic methods based on Gibbs sampling were subsequently proposed with the intent of improving robustness to noise, but these may run too slowly for some real-time applications. We present a fast maximum-likelihood-based deterministic greedy algorithm, IterML, for reconstructing FRI signals from noisy samples. We show in simulation that it achieves comparable or better performance than previous algorithms at a much lower computational cost. We also uncover a fundamental flaw in the application of MMSE (minimum mean squared error) estimation, a technique employed by some existing methods, to the problem in question.

Description: This paper addresses the problem of sampling non-bandlimited signals within the Finite Rate of Innovation (FRI) setting. We had previously shown that, by using sampling kernels whose integer span contains specific exponentials (generalized Strang-Fix conditions), it is possible to devise non-iterative, fast reconstruction algorithms from very low-rate samples. Yet, the accuracy and sensitivity to noise of these algorithms is highly dependent on these exponential reproducing kernels — actually, on the exponentials that they reproduce. Hence, our first contribution here is to provide clear guidelines on how to choose the sampling kernels optimally, in such a way that the reconstruction quality is maximized in the presence of noise. The optimality of these kernels is validated by comparing with Cramér-Rao's lower bounds (CRB). Our second contribution is to relax the exact exponential reproduction requirement. Instead, we demonstrate that arbitrary sampling kernels can reproduce the “best” exponentials within quite a high accuracy in general, and that applying the exact FRI algorithms in this approximate context results in near-optimal reconstruction accuracy for practical noise levels. Essentially, we propose a universal extension of the FRI approach to arbitrary sampling kernels. Numerical results checked against the CRB validate the various contributions of the paper and in particular outline the ability of arbitrary sampling kernels to be used in FRI algorithms.

Description: This paper presents a new method for estimating high dimensional covariance matrices. The method, permuted rank-penalized least-squares (PRLS), is based on a Kronecker product series expansion of the true covariance matrix. Assuming an i.i.d. Gaussian random sample, we establish high dimensional rates of convergence to the true covariance as both the number of samples and the number of variables go to infinity. For covariance matrices of low separation rank, our results establish that PRLS has significantly faster convergence than the standard sample covariance matrix (SCM) estimator. The convergence rate captures a fundamental tradeoff between estimation error and approximation error, thus providing a scalable covariance estimation framework in terms of separation rank, similar to low rank approximation of covariance matrices . The MSE convergence rates generalize the high dimensional rates recently obtained for the ML Flip-flop algorithm , for Kronecker product covariance estimation. We show that a class of block Toeplitz covariance matrices is approximatable by low separation rank and give bounds on the minimal separation rank $r$ that ensures a given level of bias. Simulations are presented to validate the theoretical bounds. As a real world application, we illustrate the utility of the proposed Kronecker covariance estimator for spatio-temporal linear least squares prediction of multivariate wind speed measurements.

Description: Given a limited number of entries from the superposition of a low-rank matrix plus the product of a known compression matrix times a sparse matrix, recovery of the low-rank and sparse components is a fundamental task subsuming compressed sensing, matrix completion, and principal components pursuit. This paper develops algorithms for decentralized sparsity-regularized rank minimization over networks, when the nuclear- and $ell_1$ -norm are used as surrogates to the rank and nonzero entry counts of the sought matrices, respectively. While nuclear-norm minimization has well-documented merits when centralized processing is viable, non-separability of the singular-value sum challenges its decentralized minimization. To overcome this limitation, leveraging an alternative characterization of the nuclear norm yields a separable, yet non-convex cost minimized via the alternating-direction method of multipliers. Interestingly, if the decentralized (non-convex) estimator converges, under certain conditions it provably attains the global optimum of its centralized counterpart. As a result, this paper bridges the performance gap between centralized and in-network decentralized, sparsity-regularized rank minimization. This, in turn, facilitates (stable) recovery of the low rank and sparse model matrices through reduced-complexity per-node computations, and affordable message passing among single-hop neighbors. Several application domains are outlined to highlight the generality and impact of the proposed framework. These include unveiling traffic anomalies in backbone networks, and predicting networkwide path latencies. Simulations with synthetic and real network data confirm the convergence of the novel decentralized algorithm, and its centralized performance guarantees.

Description: Multiple-input multiple-output (MIMO) radar utilizes orthogonal waveforms on each transmit element to achieve virtual aperture extension. Compared to a directed beam radar, MIMO radar has increased Doppler resolution due to the longer integration times required to maintain the same energy on target. However, the requirement for longer integration times can also cause target returns to be spread over multiple range-Doppler bins, which decreases probability of detection. This paper derives an analytical expression for probability of detection that explicitly accounts for range-Doppler migration. The effect of target velocity, target acceleration and integration time on range-Doppler migration is analyzed. A framework for velocity and acceleration compensation and step sizes for full and partial compensation are proposed. Single-target track completeness and track accuracy are compared for directed beam radar, MIMO radar with full compensation, MIMO radar with partial compensation, and uncompensated MIMO radar. Results indicate that compensation is required to prevent degraded probability of detection and track completeness as target velocity and acceleration increase. Full compensation mitigates the effects of range-Doppler migration but requires additional computational complexity. The use of partial compensation reduces computational complexity requirements but has diminished tracking performance due to coasting over missed measurements.

Description: In this paper we address the problem of sparse signal reconstruction. We propose a new algorithm that determines the signal support applying statistical thresholding to accept the active components of the model. This adaptive decision test is integrated into the sparse Bayesian learning method, improving its accuracy and reducing convergence time. Moreover, we extend the formulation to accept multiple measurement sequences of signal contaminated by structured noise in addition to white noise. We also develop analytical expressions to evaluate the algorithm estimation error as a function of the problem sparsity and indeterminacy. By simulations, we compare the performance of the proposed algorithm with respect to other existing methods. We show a practical application processing real data of a polarimetric radar to separate the target signal from the clutter.

Description: In wireless communications, increased spectral efficiency and low error rates can be achieved by means of space- time-frequency coded MIMO-OFDM systems. In this work, we consider a MIMO-OFDM transmit signal design combining space-frequency modulation with a time-varying linear precoding technique which allows spreading and multiplexing the transmitted symbols, in both space, time and frequency domains. For this system, we propose two closed-form semi-blind receivers that exploit differently the multilinear structure of the received signal, which is formulated as a nested PARAllel FACtor (PARAFAC) model. First, we devise a least squares Khatri-Rao factorization (LS-KRF) based receiver for joint channel and symbol estimation by making an efficient use of a short frame of pilot symbols. The LS-KRF receiver provides the same performance at a lower computational complexity compared to the alternating least squares (ALS) based receiver. For further reducing pilot overhead, we develop a simplified closed-form PARAFAC (S-CFP) receiver coupled with a pairing algorithm that yields an unambiguous estimation of the transmitted symbols without the need of a pilot frame. The uniqueness conditions, spectral efficiency and computational complexity of the LS-KRF and S-CFP with pairing receivers are analyzed and compared with the ALS receiver. It is shown that the S-CFP with pairing receiver has the same order of computational complexity as the ALS receiver. Meanwhile, simulation results show that our S-CFP with pairing receiver achieves the same or very similar performance of the competing receivers with extra pilot overhead at sufficiently high signal-to-noise ratio (SNR) conditions. On the other hand, it is slightly inferior to them in terms of channel estimation accuracy and bit error rate at lower SNRs.

Description: In this paper, we consider robust optimization of amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay precoders in presence of deterministic imperfect channel state information (CSI), when the CSI uncertainty lies in a norm bounded region. Two widely used performance metrics, mutual information (MI) and mean square error (MSE), are adopted as design objectives. According to the philosophy of worst-case robustness, the robust optimization problems with respect to maximizing the worst-case MI and minimizing the worst-case MSE are formulated as maximin and minimax problems, respectively. Due to the fact that these two problems do not have a concave-convex or convex-concave structure, we cannot rely on the conventional saddle point theory to find the robust solutions. Nevertheless, by exploiting majorization theory, we show that the formulated maximin and minimax problems both admit saddle points. We further analytically characterize the saddle points, and provide closed-form solutions to robust relay precoder designs. Interestingly, we find that, under both MI and MSE metrics, the robust relay optimization leads to a channel-diagonalizing structure, meaning that eigenmode transmission is optimal from the worst-case robustness perspective. The proposed robust designs can improve the spectral efficiency and reliability of AF MIMO relaying against CSI uncertainties at the similar cost of computational complexity as the existing non-robust schemes.

Description: We develop multi-step gradient methods for network-constrained optimization of strongly convex functions with Lipschitz-continuous gradients. Given the topology of the underlying network and bounds on the Hessian of the objective function, we determine the algorithm parameters that guarantee the fastest convergence and characterize situations when significant speed-ups over the standard gradient method are obtained. Furthermore, we quantify how uncertainty in problem data at design-time affects the run-time performance of the gradient method and its multi-step counterpart, and conclude that in most cases the multi-step method outperforms gradient descent. Finally, we apply the proposed technique to three engineering problems: resource allocation under network-wide budget constraint, distributed averaging, and Internet congestion control. In all cases, our proposed algorithms converge significantly faster than the state-of-the art.

Description: A large number of molds serve as producer strains for the industrial production of pharmaceuticals, foods, or organic chemicals. To optimize strains for production processes, conventional strain development programs use random mutagenesis and, more recently, recombinant technologies to generate microbial strains with novel and advantageous properties. The recent detection of mating type genes in fungal production strains and the discovery of cryptic sexuality in presumably asexual fungi open up novel strategies for generating progeny with new, as yet unobserved properties. Mating type genes, which can be considered as “sex genes,” not only direct sexual development but also regulate a broad range of fungal secondary metabolites. In addition, they control hyphal morphology, which has a direct impact on production processes that are often conducted in huge fermenter tanks. Here, we survey the occurrence and function of mating type genes that have been discovered in a wide range of industrial fungal producer strains. The possibility to obtain progeny from industrial producers by sexual mating provides an exciting alternative to conventional strain improvement programs aiming to generate optimized recombinant production strains.

Description: Endo-1,4-β-xylanases (EC 3.2.1.8) hydrolyze the 1,4-β-D-xylosidic linkages in xylans, the most abundant hemicellulose in plant cell walls. Xylanase enzymes have numerous industrial applications, including the manufacturing of animal feed, bread, juice and wine, pulp and paper, and biofuels. In this study, two glycosyl hydrolase family 10 members designated Gt Xyn10A and Gt Xyn10B and two glycosyl hydrolase family 11 members, Op Xyn11A and Cc Xyn11C, were functionally expressed and subjected to biochemical characterization. The K M , V max , and k cat values of the four xylanases, determined using birchwood xylan, ranged from 0.27 to 1.1 mg/mL, 130 to 980 μmol/min/mg, and 109 to 344 s −1 , respectively, where Op Xyn11A gave the highest and Gt Xyn10B the lowest values for all three parameters. Substrate specificity studies and analysis of the products released during the degradation of xylo-oligosaccharides and three types of xylan revealed significant differences in catalytic properties, particularly between Op Xyn11A and the other xylanases and between the family 10 and the family 11 xylanases. Molecular modeling suggests that the unique substrate specificity of Op Xyn11A can be attributed to the presence of a serine rather that an asparagine or aspartate residue at the +1 substrate binding site. Additionally, all four xylanases exhibited biochemical characteristics of interest for various commercial applications.

Description: Hand, foot, and mouth disease (HFMD) has caused significant morbidity and mortality in the Asia-Pacific regions, particularly in infants and young children. Coxsackievirus A16 (CA16) represents one of the major causative agents for HFMD, and the development of a safe and effective vaccine preventing CA16 infections has become a public health priority. In this study, we have developed a yeast system for the production of virus-like particles (VLPs) for CA16 by co-expressing P1 and 3CD of CA16 in Saccharomyces cerevisiae . These VLPs exhibit similarity in both protein composition and morphology as empty particles from CA16-infected cells. Immunization with CA16 VLPs in mice potently induced CA16-specific IgG and neutralization antibodies in a dose-dependent manner. IgG subclass isotyping revealed that IgG1 and lgG2b were dominantly induced by VLPs. Meanwhile, cytokine profiling demonstrated that immunization with VLPs significantly induced the secretion of IFN-γ, indicating potent cellular immune response. Furthermore, in vivo challenge experiments showed that passive immunization with anti-VLPs sera conferred full protection against lethal CA16 challenge in neonate mice. Taken together, our data demonstrated that VLPs produced in yeast might have the potential to be further developed as a vaccine candidate against HFMD.

Description: Studies were carried out to assess the utility of the cellular and extracellular constituents of Bacillus megaterium for the flotation of sphalerite and galena minerals. Based on the flotation results on the individual minerals, it was observed that sphalerite was preferentially floated compared to galena. A maximum selectivity index (SI) value of 11.7 was achieved in the presence of the soluble fraction of the thermolysed cells, which was higher than that obtained with the intact cells (SI of 6.5) and the insoluble fraction of the thermolysed cells (SI of 9.6). The results of the various enzymatic treatment tests revealed that extracellular DNA played a vital role in the selective flotation of sphalerite. A noteworthy finding was that the single-stranded DNA (ssDNA) had a higher biocollector capacity vis-à-vis the double-stranded DNA (dsDNA), leading to better flotation efficiency. About 95 % recovery of sphalerite could be achieved from the mineral mixture by the combined addition of the ssDNA with the non-DNA components of the bacterial cells, resulting in a maximum SI of 19.1. Calcium and phosphate components of the nutrient media were found to be essential for better selectivity of separation of sphalerite. The mechanisms of microbe–mineral interaction are discussed.

Description: While the use of anaerobic digestion to generate methane as a source of bioenergy is increasing worldwide, our knowledge of the microbial communities that perform biomethanation is very limited. Using next-generation sequencing, bacterial population profiles were determined in three full-scale mesophilic anaerobic digesters operated on dairy farms in the state of Vermont (USA). To our knowledge, this is the first report of a metagenomic analysis on the bacterial population of anaerobic digesters using dairy manure as their main substrate. A total of 20,366 non-chimeric sequence reads, covering the V1-V2 hypervariable regions of the bacterial 16S rRNA gene, were assigned to 2,176 operational taxonomic units (OTUs) at a genetic distance cutoff value of 5 %. Based on their limited sequence identity to validly characterized species, the majority of OTUs identified in our study likely represented novel bacterial species. Using a naïve Bayesian classifier, 1,624 anaerobic digester OTUs could be assigned to 16 bacterial phyla, while 552 OTUs could not be classified and may belong to novel bacterial taxonomic groups that have yet to be described. Firmicutes , Bacteroidetes , and Chloroflexi were the most highly represented bacteria overall, with Bacteroidetes and Chloroflexi showing the least and the most variation in abundance between digesters, respectively. All digesters shared 132 OTUs, which as a “core” group represented 65.4 to 70.6 % of sequences in individual digesters. Our results show that bacterial populations from microbial communities of anaerobic manure digesters can display high levels of diversity despite sharing a common core substrate.

Description: The discovery of Dehalococcoides mccartyi reducing perchloroethene and trichloroethene (TCE) to ethene was a key landmark for bioremediation applications at contaminated sites. D. mccartyi -containing cultures are typically grown in batch-fed reactors. On the other hand, continuous cultivation of these microorganisms has been described only at long hydraulic retention times (HRTs). We report the cultivation of a representative D. mccartyi -containing culture in continuous stirred-tank reactors (CSTRs) at a short, 3-d HRT, using TCE as the electron acceptor. We successfully operated 3-d HRT CSTRs for up to 120 days and observed sustained dechlorination of TCE at influent concentrations of 1 and 2 mM TCE to ≥97 % ethene, coupled to the production of 10 12 D. mccartyi cells L culture −1 . These outcomes were possible in part by using a medium with low bicarbonate concentrations (5 mM) to minimize the excessive proliferation of microorganisms that use bicarbonate as an electron acceptor and compete with D. mccartyi for H 2 . The maximum conversion rates for the CSTR-produced culture were 0.13 ± 0.016, 0.06 ± 0.018, and 0.02 ± 0.007 mmol Cl − L culture −1 h −1 , respectively, for TCE, cis -dichloroethene, and vinyl chloride. The CSTR operation described here provides the fastest laboratory cultivation rate of high-cell density Dehalococcoides cultures reported in the literature to date. This cultivation method provides a fundamental scientific platform for potential future operations of such a system at larger scales.

Description: κ-Carrageenases exhibit apparent distinctions in gene sequence, molecular weight, enzyme properties, and posttranslational processes. In this study, a new κ-carrageenase gene named cgk Z was cloned from the marine bacterium Zobellia sp. ZM-2. The gene comprised an open reading frame of 1,638 bp and encoded 545 amino acids. The natural signal peptide of κ-carrageenase was used successfully for the secretory production of the recombinant enzyme in Escherichia coli . A posttranslational process that removes an amino acid sequence of about 20 kDa from the C-terminal end of κ-carrageenase was first discovered in E. coli . An increase in enzyme activity by 167.3 % in the presence of 5 mM DTT was discovered, and Na + at a certain concentration range was positively correlated with enzyme activity. The κ-carrageenase production of E. coli was 9.0 times higher than that of ZM-2. These results indicate the potential use of the enzyme in the biotechnological industry.

Description: Fifty-five bacterial isolates were obtained from surface-sterilized nodules of woody and shrub legumes growing in Ethiopia: Crotalaria spp., Indigofera spp., and Erythrina brucei , and the food legumes soybean and common bean. Based on partial 16S rRNA gene sequence analysis, the majority of the isolates were identified as Gram-negative bacteria belonging to the genera Achromobacter , Agrobacterium , Burkholderia , Cronobacter , Enterobacter , Mesorhizobium , Novosphingobium , Pantoea , Pseudomonas , Rahnella , Rhizobium , Serratia , and Variovorax . Seven isolates were Gram-positive bacteria belonging to the genera Bacillus , Paenibacillus , Planomicrobium , and Rhodococcus . Amplified fragment length polymorphism (AFLP) fingerprinting showed that each strain was genetically distinct. According to phylogenetic analysis of recA , glnII , rpoB , and 16S rRNA gene sequences, Rhizobium , Mesorhizobium , and Agrobacterium were further classified into six different genospecies: Agrobacterium spp., Agrobacterium radiobacter , Rhizobium sp., Rhizobium phaseoli , Mesorhizobium sp., and putative new Rhizobium species. The strains from R . phaseoli , Rhizobium sp. IAR30, and Mesorhizobium sp. ERR6 induced nodules on their host plants. The other strains did not form nodules on their original host. Nine endophytic bacterial strains representing seven genera, Agrobacterium , Burkholderia , Paenibacillus , Pantoea , Pseudomonas , Rhizobium , and Serratia , were found to colonize nodules of Crotalaria incana and common bean on co-inoculation with symbiotic rhizobia. Four endophytic Rhizobium and two Agrobacterium strains had identical nifH gene sequences with symbiotic Rhizobium strains, suggesting horizontal gene transfer. Most symbiotic and nonsymbiotic endophytic bacteria showed plant growth-promoting properties in vitro, which indicate their potential role in the promotion of plant growth when colonizing plant roots and the rhizosphere.

Description: Escherichia coli BA002, in which the ldhA and pflB genes are deleted, cannot utilize glucose anaerobically due to the inability to regenerate NAD + . To restore glucose utilization, overexpression of nicotinic acid phosphoribosyltransferase (NAPRTase) encoded by the pncB gene, a rate-limiting enzyme of NAD(H) synthesis pathway, resulted in a significant increase in cell mass and succinate production under anaerobic conditions. However, a high concentration of pyruvate accumulated. Thus, co-expression of NAPRTase and the heterologous pyruvate carboxylase (PYC) of Lactococcus lactis subsp. cremoris NZ9000 in recombinant E . coli BA016 was investigated. The total concentration of NAD(H) was 9.8-fold higher in BA016 than in BA002, and the NADH/NAD + ratio decreased from 0.60 to 0.04. Under anaerobic conditions, BA016 consumed 17.50 g l −1 glucose and produced 14.08 g l −1 succinate with a small quantity of pyruvate. Furthermore, when the reducing agent dithiothreitol or reduced carbon source sorbitol was added, the cell growth and carbon source consumption rate of BA016 was reasonably enhanced and succinate productivity increased.

Description: 1,2-Benzenedicarboxaldehyde-3,4,5-trihydroxy-6-methyl (flavipin) was found to be antagonistic against nematodes and fungi. Here we demonstrated that flavipin is a potent antioxidant in vitro and in vivo, which has great potential in the therapy for free radical-associated diseases. Therefore, flavipin-producing bio-source was screened from 80 endophytes in Ginkgo biloba . Seven endophytic fungi were able to synthesize antioxidant substances and identified by ITS rDNA sequences. Among them, Chaetomium globosum CDW7 was a remarkable producer of flavipin. The fermentation parameters of CDW7 were then optimized for high flavipin production. Cultured under the optimal condition (25 °C, 100/250 mL flask, 12 discs/flask, 150 rpm, pH 6.5) for 14 days, CDW7 was able to synthesize flavipin at a production of 315.5 mg/L. In addition, flavipin output was positively correlated to antioxidant activities of crude extracts with a correlation coefficient of 0.8235, indicating that flavipin was the major antioxidant component of CDW7's metabolites. These data demonstrated that CDW7 was a highly yielded bio-source of antioxidant flavipin.

Description: Two bacterial hosts expressing cloned aromatic oxygenases were used to catalyze the oxidation and polymerization of indole and related substrates, creating mixtures of indigoid compounds comprised of novel dimers and trimers. Crude extracts and purified compounds were tested for their ability to inhibit the growth of Gram-positive organisms, in general, and Mycobacterium tuberculosis (TB), in particular. Of the 74 compounds tested against M. tuberculosis , ~66 % had minimum inhibitory concentrations (MIC) of 5 μg/ml or less. The most effective antibiotic found was designated SAB-P1, a heterodimer of indole and anthranil, which had a MIC of 0.16 μg/ml, and did not inhibit kidney cells (IC 50 ) at concentrations of 〉8 μg/ml. Combinatorial biocatalysis was used to create a series of halogenated derivatives of SAB-P1 with a wider therapeutic window. None of the derivatives had MIC values that were superior to SAB-P1, but some had a wider therapeutic window because of decreased kidney cell toxicity. Generally, the indigoid dimers that were effective against TB appeared to be specific for TB. Some of the trimers generated, however, had a broader spectrum of activity inhibiting not only TB (MIC = 1.1 μg/ml) but also the growth of Mycobacterium smegmatis MC2 155, Bacillus cereus , Enterococcus faecalis , Staphylococcus epidermidis , Bacillus subtilis 168, and Clostridium acetobutylicum . The structure of two of the novel dimers (SAB-C4 and SAB-P1) and a trimer (SAB-R1) were solved using X-ray crystallography.

Description: The compartmentalized anaerobic reactor (CAR) is a patent novel high-rate reactor, which consists of three compartments. The reactor has a great potential for application due to its many advantages. In this work, the microbial consortium, spatial distribution, and their relationship with performance of CAR were investigated by means of polymerase chain reaction, denaturing gradient gel electrophoresis, and fluorescence in situ hybridization. The results showed that the predominant archaea were Methanobacterium , Methanosaeta , and Methanospirillum , and the predominant bacteria were Firmicutes , Deltaproteobacteria , Spirochaetes , Actinobacteria , and Gammaproteobacteria in the microbial consortium. The methanogenic archaea (MA), the hydrogen-producing acetogenic bacteria (HAB), and the hydrolytic fermentative bacteria (HFB) were found to be predominant in the upper, middle, and bottom compartments, respectively. The results revealed that the granular sludge took on a stratified microbial structure. The HFB, HAB, and MA were located in the outer shell, middle layer, and core, respectively. The microbial populations from the bottom compartment were relatively homogeneous in the granular sludge, and from the middle and upper compartments, they were relatively heterogeneous in the granular sludge. The microbial consortia and their spatial distribution were in accordance with the organic loading rate and chemical components in the three compartments.

Description: We constructed beta-glucosidase (BGL)-displaying Corynebacterium glutamicum , and direct l -lysine fermentation from cellobiose was demonstrated. After screening active BGLs, Sde1394, which is a BGL from Saccharophagus degradans , was successfully displayed on the C. glutamicum cell surface using porin as an anchor protein, and cellobiose was directly assimilated as a carbon source. The optical density at 600 nm of BGL-displaying C. glutamicum grown on cellobiose as a carbon source reached 23.5 after 48 h of cultivation, which was almost the same as that of glucose after 24 h of cultivation. Finally, Sde1394-displaying C. glutamicum produced 1.08 g/l of l -lysine from 20 g/l of cellobiose after 4 days of cultivation, which was about threefold higher than the amount of produced l -lysine using BGL-secretory C. glutamicum strains (0.38 g/l after 5 days of cultivation). This is the first report on amino acid production using cellobiose as a carbon source by BGL-expressing C. glutamicum .

Description: The risk of antibody-dependent enhancement (ADE) of dengue virus (DENV) infection is a major obstacle for the development of dengue vaccine candidates. Here, we described a novel approach for assessment of ADE by measuring DENV nonstructural protein 1 (NS1) production in culture supernatants with Fcγ receptor-expressing K562 cells in ELISA format (ELISA-ADE). Enhancing activities quantified by measurement of kinetics of NS1 production were in a good agreement with the results of the virus titration assay. In conjunction with the previously established enzyme-linked immunospot-based micro-neutralization test (ELISPOT-MNT) in 96-well format, the observable dose–response profiles of enhancing and neutralizing activities against all four DENV serotypes were produced with two flaviviral envelope cross-reactive monoclonal antibodies and four primary DENV-1-infected human sera. The simple high-throughput ELISA-ADE assay offers advantages for quantitative measurement of infection enhancement that can potentially be applied to large-scale seroepidemiological studies of DENV infection and vaccination.

Description: Increasing concerns over limited petroleum resources and associated environmental problems are motivating the development of efficient cell factories to produce chemicals, fuels, and materials from renewable resources in an environmentally sustainable economical manner. Bacillus spp., the best characterized Gram-positive bacteria, possesses unique advantages as a host for producing microbial enzymes and industrially important biochemicals. With appropriate modifications to heterologous protein expression and metabolic engineering, Bacillus species are favorable industrial candidates for efficiently converting renewable resources to microbial enzymes, fine chemicals, bulk chemicals, and fuels. Here, we summarize the recent advances in developing Bacillus spp. as a cell factory. We review the available genetic tools, engineering strategies, genome sequence, genome-scale structure models, proteome, and secretion pathways, and we list successful examples of enzymes and industrially important biochemicals produced by Bacillus spp. Furthermore, we highlight the limitations and challenges in developing Bacillus spp. as a robust and efficient production host, and we discuss in the context of systems and synthetic biology the emerging opportunities and future research prospects in developing Bacillus spp. as a microbial cell factory.

Description: Glucosamine (GlcN), an amino sugar, is a compound derived from substitution of a hydroxyl group of a glucose molecule with an amino group. GlcN and its acetylated derivative, N -acetylglucosamine (GlcNAc), have been widely used in food, cosmetics, and pharmaceutical industries and are currently produced by acid hydrolysis of chitin (a linear polymer of GlcNAc) extracted from crab and shrimp shells. Microbial fermentation by filamentous fungi or recombinant Escherichia coli , as an alternative method for the production of GlcN and GlcNAc, is attracting increasing attention because it is an environmentally friendly process. Although the microbial production of GlcN and GlcNAc is hampered by low yield and high production cost, considerable advances have been made in recent years. Here we review the applications, commercial market, and production of GlcN and GlcNAc, with emphasis on the metabolic and process engineering strategies used to improve GlcN and GlcNAc production by recombinant microbes.

Description: In this work, the successful coupling of enzymatic oxidation and aldol addition reactions for the synthesis of a Cbz-aminopolyol from a Cbz-amino alcohol was achieved for the first time in a multienzymatic one-pot system. The two-step cascade reaction consisted of the oxidation of Cbz-ethanolamine to Cbz-glycinal catalyzed by chloroperoxidase from the fungus Caldariomyces fumago and aldol addition of dihydroxyacetone phosphate to Cbz-glycinal catalyzed by rhamnulose-1-phosphate aldolase expressed as a recombinant enzyme in Escherichia coli , yielding (3 R ,4 S )-5-{[(benzyloxy)carbonyl]amino}-5-deoxy-1- O -phosphonopent-2-ulose. Tools of enzymatic immobilization, reactor configurations, and modification of the reaction medium were applied to highly increase the production of the target compound. While the use of soluble enzymes yielded only 23.6 % of Cbz-aminopolyol due to rapid enzyme inactivation, the use of immobilized ones permitted an almost complete consumption of Cbz-ethanolamine, reaching Cbz-aminopolyol yields of 69.1 and 71.9 % in the stirred-tank and packed-bed reactor, respectively. Furthermore, the reaction production was 18-fold improved when it was catalyzed by immobilized enzymes in the presence of 5 % ( v / v ) dioxane, reaching a value of 86.6 mM of Cbz-aminopoliol (31 g/L).

Description: The complete genome of Acinetobacter oleivorans DR1 contains AqsR and AqsI genes, which are LuxR and LuxI homolog, respectively. In a previous study, we demonstrated that quorum sensing (QS) signals play an important role in biofilm formation and hexadecane biodegradation. However, the regulation of genes controlled by the QS system in DR1 remains unexplored. We constructed an aqsR mutant and performed RNA sequencing analysis to understand the QS system. A total of 353 genes were differentially expressed during the stationary phase of wild-type cells compared to that of the aqsR mutant. AqsR appears to be an exceptionally important regulator because knockout of aqsR affected global gene expression. Genes involved in posttranslational modification, chaperones, cell wall structure, secondary metabolites biosynthesis, and stress defense were highly upregulated only in the wild type. Among upregulated genes, both the AOLE_03905 (putative surface adhesion protein) and the AOLE_11355 (L-asparaginase) genes have putative LuxR binding sites at their promoter regions. Soluble AqsR proteins were successfully purified in Escherichia coli harboring both aqsR and aqsI . Comparison of QS signals in an AqsI–AqsR co-overexpression strain with N -acyl homoserine lactone standards showed that the cognate N -acyl homoserine lactone binding to AqsR might be 3OH C12HSL. Our electrophoretic mobility shift assays with purified AqsR revealed direct binding of AqsR to those promoter regions. Our data showed that AqsR functions as an important regulator and is associated with several phenotypes, such as hexadecane utilization, biofilm formation, and sensitivity to cumene hydroperoxide.

Description: A membrane-bound, pyrroloquinoline quinone (PQQ)-dependent alcohol dehydrogenase (ADH) was purified from Frateuria aurantia LMG 1558 T . Although F . aurantia belongs to a group of γ-Proteobacteria, the characteristics of its PQQ-ADH were similar to the enzyme characteristics of the typical high-acetic acid-resistant bacterium Gluconacetobacter europaeus from the group of α-Proteobacteria. The PQQ-dependent ADH was solubilized from the membranes and purified after anionic, cationic, and affinity chromatography with specific activity of 117 U/mg. The purified enzyme was estimated to be composed of two subunits of ca. 72 and 45 kDa, as judged by SDS-polyacrylamide gel electrophoresis. The purified enzyme had maximum activity at pH 4.5 and showed the highest substrate specificity to ethanol, isoamyl alcohol, 1-butanol, and 1-propanol. The deduced sequences of cloned genes adhA and adhB encoding subunits I and II of PQQ-ADH showed 80 % amino acid (AA) identity to AdhA and 68 % AA identity to AdhB of Ga . europaeus V3 (LMG 18494). Because of the high similarity between genes encoding subunits I and II of PQQ-ADH and its homologous genes found in a distantly related taxonomic group of acetic acid bacteria, the results suggest the possibility of horizontal gene transfer between these two groups of genera.

Description: Enantioselective oxidation of racemic phenyl-1,2-ethanediol into ( R )-(−)-mandelic acid by a newly isolated Brevibacterium lutescens CCZU12-1 was demonstrated. It was found that optically active ( R )-(−)-mandelic acid ( e.e.p  〉 99.9 %) is produced leaving the other enantiomer ( S )-(+)-phenyl-1,2-ethanediol intact. Using fed-batch method, a total of 172.9 mM ( R )-(−)-mandelic acid accumulated in the reaction mixture after the seventh feed. Moreover, oxidation of phenyl-1,2-ethanediol using calcium alginate-entrapped resting cells was carried out in the aqueous system, and efficient biocatalyst recycling was achieved as a result of cell immobilization in calcium alginate, with a product-to-biocatalyst ratio of 27.94 g ( R )-(−)-mandelic acid g −1 dry cell weight cell after 16 cycles of repeated use.

Description: The bacterium Bacillus amyloliquefaciens anti-CA isolated from mangrove system was found to be able to actively kill Candida albicans isolated from clinic. The bacterial strain anti-CA could produce high level of bioactive substance, amylase and protease in the cheap medium containing 2.0 % soybean meal, 2.0 % wheat flour, pH 6.5 within 26 h. After purification, the main bioactive substance was confirmed to be a cyclic lipopeptide containing a heptapeptide, L-Asp→L-Leu→L-Leu→L-Val→L-Val→L-Glu→L-Leu and a 3-OH fatty acid (15 carbons). In addition to C. albicans , the purified lipopeptide can also kill many yeast strains including Metschnikowia bicuspidata , Candida tropicalis , Yarrowia lipolytica and Saccharomyces cerevisiae. After treated by the purified lipopeptide, both the whole cells and protoplasts of C. albicans were destroyed.

Description: This paper presents a new computationally efficient method for direction-of-arrival (DOA) estimation with arbitrary arrays. The total angular field-of-view is first divided into several small sectors and the original noise subspace exploited by the multiple signal classification (MUSIC) algorithm is mapped from one sector to the other sectors by a Hadarmard product transformation. This transformation gives a new noise-like subspace cluster (NLSC), whose intersection is found to be simultaneously orthogonal to the steering vectors associated with the true DOAs and several virtual DOAs. Based on such a multiple orthogonality, a novel compressed MUSIC (C-MUSIC) spatial spectrum at hand is derived. Unlike MUSIC with tremendous spectral search, C-MUSIC involves a limited search over only one sector, and hence it is computationally very attractive. To obtain the intersection of NLSC for more than two sectors, a low-complexity method is also proposed in the present work, which shows advantages over the existing alternative projection method (APM) and singular value decomposition (SVD) techniques. Furthermore, the mean square errors (MSEs) of the proposed estimator is derived. Simulation results illustrate that C-MUSIC trades-off MSEs by complexity and resolution as compared to the standard MUSIC efficiently.

Description: We analyze the performance of a matched subspace detector (MSD) where the test signal vector is assumed to reside in an unknown, low-rank $k$ subspace that must be estimated from finite, noisy, signal-bearing training data. Under both a stochastic and deterministic model for the test vector, subspace estimation errors due to limited training data degrade the performance of the standard plug-in detector, relative to that of an oracle detector. To avoid some of this performance loss, we utilize and extend recent results from random matrix theory (RMT) that precisely quantify the quality of the subspace estimate as a function of the eigen-SNR, dimensionality of the system, and the number of training samples. We exploit this knowledge of the subspace estimation accuracy to derive from first-principles a new RMT detector and to characterize the associated ROC performance curves of the RMT and plug-in detectors. Using more than the a critical number of informative components, which depends on the training sample size and eigen-SNR parameters of training data, will result in a performance loss that our analysis quantifies in the large system limit. We validate our asymptotic predictions with simulations on moderately sized systems.

Description: Standard spatial time-frequency distribution (STFD) estimators, derived based on the Gaussian noise assumption, are known to have poor performance in the case of impulsive noise. Recently, different STFD estimators have been proposed, which, based on simulations, are claimed to be robust. In this paper, we provide an influence function robustness analysis of STFD estimators. We derive the influence functions for the asymptotic and for the finite-sample case and study robustness of the standard, as well as for some recently proposed robust STFD estimators. The empirical influence function gives practitioners a simple way to pre-select STFD estimators for their scenario. Our analysis confirms that, unlike for the standard estimator, the proposed robust estimators yield a bounded influence function and are robust over a broad class of distributions. Future research on STFD estimation will allow for the design of robust and efficient estimators based on the influence function.

Description: In cognitive radio (CR), the soft decision fusion (SDF) rule plays a critical role in cooperative spectrum sensing (CSS). However, the computational cost on obtaining efficient SDF rule becomes infeasible even with a small number of cooperative users. In this paper, the efficiency of SDF rule in inhomogeneous background is studied from the perspective of quantization theory. We formulate the calculation of sensing performance including the probabilities of detection and false alarm when regarding both i) the quantization impact and ii) the inhomogeneous background, and then conclude a condition under which the sensing performance can be calculated by the fast Fourier transform (FFT). Based on this condition, two novel quantization schemes with two optimization methods are proposed to guarantee both the quantizer and decision threshold of SDF rule can be obtained efficiently, at the same time, the SDF can achieve high sensing performance.

Description: We examine the recovery of block sparse signals and extend the recovery framework in two important directions; one by exploiting the signals' intra-block correlation and the other by generalizing the signals' block structure. We propose two families of algorithms based on the framework of block sparse Bayesian learning (BSBL). One family, directly derived from the BSBL framework, require knowledge of the block structure. Another family, derived from an expanded BSBL framework, are based on a weaker assumption on the block structure, and can be used when the block structure is completely unknown. Using these algorithms, we show that exploiting intra-block correlation is very helpful in improving recovery performance. These algorithms also shed light on how to modify existing algorithms or design new ones to exploit such correlation and improve performance.

Description: In this paper, we first propose a generalized fourth-order PARATUCK2 tensor model for multiple-input multiple-output (MIMO) communication systems with space-time-frequency (STF) spreading-multiplexing. The core of the proposed PARATUCK2 model is composed of two third-order interaction tensors that define a joint time and frequency allocation of the data streams to the transmit antennas, thus allowing to adjust the multiplexing degree and spreading redundancy in three domains: space (transmit antennas), time (blocks) and frequency (subcarriers). Then, we investigate the identifiability of the PARATUCK2-STF MIMO system by deriving sufficient conditions which are translated into design recommendations for the STF allocation structure. In particular, essential uniqueness is discussed by interpreting the generalized fourth-order PARATUCK2 model as an equivalent third-order constrained factor (CONFAC) model with two fixed constraint matrices and one variable constraint matrix that depends on the stream-to-antenna allocation structure. We also present a blind receiver using the Levenberg-Marquardt (LM) algorithm based on the generalized fourth-order PARATUCK2 model. Numerical results are provided for a bit-error-rate performance evaluation and a comparison with some competing algorithms.

Description: The standard Capon beamformer (SCB) achieves the maximum output signal-to-interference-plus-noise ratio in the error-free case. However, estimation errors of the signal steering vector and the array covariance matrix can result in severe performance deteriorations of the SCB, especially if the training data contains the desired signal component. A popular technique to improve the robustness against model errors is to compute the Capon beamformer with the maximum output power, considering an uncertainty set for the signal steering vector. However, maximizing the total beamformer output power may result in an insufficient suppression of interferers and noise. As an alternative approach to mitigate the detrimental effect of model errors, we propose to compute the Capon beamformer with the minimum sensitivity, considering the uncertainty set for the signal steering vector. The proposed maximally robust Capon beamformer (MRCB) is at least as robust as the maximum output power Capon beamformer with the same uncertainty set for the signal steering vector. We show that the MRCB can be implemented efficiently using Lagrange duality. Simulation results demonstrate that the MRCB outperforms state-of-the-art robust adaptive beamformers in many scenarios.

Description: The possibility to accurately localize tags by using wireless techniques is of great importance for several emerging applications in the Internet of Things. Precise ranging can be obtained with ultra wideband (UWB) impulse radio (IR) systems, where short impulses are transmitted, and their time-of-arrival (ToA) is estimated at the receiver. Due to the presence of noise and multipath, the estimator has the difficult task of discriminating the time intervals where the received waveform is due to noise only, by those where there are also signal components. Common low-complexity methods use an energy detector (ED), whose output is compared with a threshold, to discriminate the time intervals containing noise only from those containing signal plus noise. Optimal threshold design for these methods requires knowledge of the channel impulse response and of the receiver noise power. We propose a different approach, where ToA estimation is based on model selection by information theoretic criteria (ITC). The resulting ToA algorithms do not use thresholds, and do not require any information about the channel or the noise power level. These blind, universal ToA estimators show, for completely unknown multipath channels and in the presence of noise with unknown power, excellent performance when compared with ideal genie-aided schemes.

Description: Detection of cyclostationary primary user (PU) signals in colored Gaussian noise for cognitive radio systems is considered based on looking for single or multiple cycle frequencies at single or multiple time lags in the cyclic autocorrelation function (CAF) of the noisy PU signal. We explicitly exploit the knowledge that under the null hypothesis of PU signal absent, the measurements originate from possible colored Gaussian noise with unknown correlation function. Our formulation allows us to simplify the spectrum sensing detector and obviates the need for estimating an unwieldy covariance matrix needed in some prior works. We consider both single and multiple antenna receivers, and both nonconjugate and conjugate CAFs. A performance analysis of the proposed detector is carried out. Supporting simulation examples are provided to demonstrate the efficacy of the proposed approaches and to compare them with some existing approaches. Our proposed approaches are computationally cheaper than the Dandawate- Giannakis and related approaches while having quite similar detection performance for a given false alarm rate.

Description: This paper presents a Cramér-Rao lower bound (CRLB) on the variance of unbiased estimates of factor matrices in Canonical Polyadic (CP) or CANDECOMP/PARAFAC (CP) decompositions of a tensor from noisy observations, (i.e., the tensor plus a random Gaussian i.i.d. tensor). A novel expression is derived for a bound on the mean square angular error of factors along a selected dimension of a tensor of an arbitrary dimension. The expression needs less operations for computing the bound, $O(NR^{6})$ , than the best existing state-of-the art algorithm, $O(N^{3}R^{6})$ operations, where $N$ and $R$ are the tensor order and the tensor rank. Insightful expressions are derived for tensors of rank 1 and rank 2 of arbitrary dimension and for tensors of arbitrary dimension and rank, where two factor matrices have orthogonal columns.

Description: Interference alignment (IA) has attracted great attention in the last few years for its breakthrough performance in interference networks. However, despite the numerous works dedicated to IA, the feasibility conditions of IA remains unclear for most network topologies. The IA feasibility analysis is challenging as the IA constraints are sets of high-degree polynomials, for which no systematic tool to analyze the solvability conditions exists. In this work, by developing a new mathematical framework that maps the solvability of sets of polynomial equations to the linear independence of their first-order terms, we propose a sufficient condition that applies to MIMO interference networks with general configurations. We have further proved that this sufficient condition coincides with the necessary conditions under a wide range of configurations. These results further consolidate the theoretical basis of IA.

Description: This paper introduces the novel class of modulated cyclostationary processes, a class of nonstationary processes exhibiting frequency coupling, and proposes a method of their estimation from repeated trials. Cyclostationary processes also exhibit frequency correlation but have Loève spectra whose support lies only on parallel lines in the dual-frequency plane. Such extremely sparse structure does not adequately represent many biological processes. Thus, we propose a model that, in the time domain, modulates the covariance of cyclostationary processes and consequently broadens their frequency support in the dual-frequency plane. The spectra and the cross-coherence of the proposed modulated cyclostationary process are first estimated using multitaper methods. A shrinkage procedure is then applied to each trial-specific estimate to reduce the estimation risk.

Description: Using an infinite sample, the contrast function and the FastICA algorithm are deterministic. In the practical case, we have only a finite sample. Then the contrast function and the FastICA algorithm become estimators of the deterministic case. This paper provides a unified study of the deflation FastICA algorithm assuming a finite or an infinite sample. We consider four random probability distributions based on the finite sample, and construct four FastICA estimators. We show that under mild conditions, each of these estimators are equal to a local minimizer of the contrast function with respect to the underlying random probability distribution. Making use of the existing results of M-estimators, we give a rigorous analysis of the asymptotic errors of FastICA estimators. We derive five criteria for the optimal choice of the nonlinearity function.

Description: The Delsarte-Goethals frame (DGF) has been proposed for deterministic compressive sensing of sparse and compressible signals. Results in compressive sensing theory show that the DGF enables successful recovery of an overwhelming majority of sufficiently sparse signals. However, these results do not give a characterization of the sparse vectors for which the recovery procedure fails. In this paper, we present a formal analysis of the DGF that highlights the presence of clustered sparse vectors within its null space. This in turn implies that sparse recovery performance is diminished for sparse vectors that have their nonzero entries clustered together. Such clustered structure is present in compressive imaging applications, where commonly-used raster scannings of 2-D discrete wavelet transform representations yield clustered sparse representations for natural images. Prior work leverages this structure by proposing specially tailored sparse recovery algorithms that partition the recovery of the input vector into known clustered and unclustered portions. Alternatively, we propose new randomized and deterministic raster scannings for clustered coefficient vectors that improve recovery performance. Experimental results verify the aforementioned analysis and confirm the predicted improvements for both noiseless and noisy measurement regimes.

Description: This article deals with learning dictionaries for sparse approximation whose atoms are both adapted to a training set of signals and mutually incoherent. To meet this objective, we employ a dictionary learning scheme consisting of sparse approximation followed by dictionary update and we add to the latter a decorrelation step in order to reach a target mutual coherence level. This step is accomplished by an iterative projection method complemented by a rotation of the dictionary. Experiments on musical audio data and a comparison with the method of optimal coherence-constrained directions (mocod) and the incoherent k-svd (ink-svd) illustrate that the proposed algorithm can learn dictionaries that exhibit a low mutual coherence while providing a sparse approximation with better signal-to-noise ratio (snr) than the benchmark techniques.

Description: In this paper, we develop a framework to design sensing matrices for compressive sensing applications that lead to good mean squared error (MSE) performance subject to sensing cost constraints. By capitalizing on the MSE of the oracle estimator, whose performance has been shown to act as a benchmark to the performance of standard sparse recovery algorithms, we use the fact that a Parseval tight frame is the closest design - in the Frobenius norm sense - to the solution of a convex relaxation of the optimization problem that relates to the minimization of the MSE of the oracleestimator with respect to the equivalent sensing matrix, subject to sensing energy constraints. Based on this result, we then propose two sensing matrix designs that exhibit two key properties: i) the designs are closed form rather than iterative; ii) the designs exhibit superior performance in relation to other designs in the literature, which is revealed by our numerical investigation in various scenarios with different sparse recovery algorithms including basis pursuit de-noise (BPDN), the Dantzig selector and orthogonal matching pursuit (OMP).

Description: In this paper we consider adaptive detection of a signal embedded in additive disturbance whose multivariate distribution belongs to a very general class, including many statistical models commonly adopted for radar disturbance. We introduce the concept of generalized Constant False Alarm Rate (CFAR) and show that a class of receivers sharing some invariances complies with the quoted property. Then, we devise the Generalized Likelihood Ratio Test (GLRT) and prove that, under some mild technical conditions, it coincides with that obtained under the Gaussian assumption for the observations. We also deal with the existence of the Uniformly Most Powerful Invariant (UMPI) detector either using the Wijsman theorem or directly computing the maximal invariant Likelihood Ratio (LR). At the analysis stage, we focus on a compound matrix variate model for the disturbance component, which is a natural generalization of the Spherically Invariant Random Vector (SIRV). In this context, we assess the performance of some well known invariant decision rules also in comparison with the Most Powerful Invariant (MPI) detector. The results highlight that some among the analyzed receivers exhibit a performance level very close to the MPI test.

Description: This Special Issue seeks to review progress in synthetic aperture radar imaging which has been made possible through new algorithms and enabling hardware. It serves to capture the approaches propelling recent cutting-edge research and scholarly activities in SAR Imagery. SAR has become a valuable tool for civilian remote sensing applications as well as for military surveillance and reconnaissance. SAR operations can take place in all weather and times. SAR data can provide key information about the scene which can be extracted e.g. from the polarimetric features, the phase variation over time, and the reflectivity dependency on frequency. A wide variety of air- and space based sensors for long and short range operation has been realized, operating at frequencies extending from VHF to the upper millimeter wave region. Spectacular missions I ike the Shuttle Radar Topographic Mission, the TanDEM-X satellite pair and the COSMO/SkyMed constellation have underscored the unique and important role of SAR. In addition to the basic SAR modes, across- and along track interferometry have been established. Multi-band operations and the full polarimetric scattering matrix have been effectively utilized. We encourage paper submissions that highlight recent trends and applications of SAR imaging. We welcome contributions showing the marked improvements in SAR imaging and the attributes of efficient data acquisition, fast image computations, high image resolution, and effective image segmentations. This Special Issue aims to present the new developments in radar imaging related to polarimetry, bi- and multi-static sensors including MIMO architectures, novel focusing techniques and algorithms, compressive sensing and sparse imaging reconstructions, and other forthcoming radar imaging techniques. Air- and spaceborne SAR systems and techniques will also be considered.

Description: The robustness and integrity of IP networks require efficient tools for traffic monitoring and analysis, which scale well with traffic volume and network size. We address the problem of optimal large-scale monitoring of computer networks under resource constraints. Specifically, we consider the task of selecting the “best” subset of at most $K$ links to monitor, so as to optimally predict the traffic load at the remaining ones. Our notion of optimality is quantified in terms of the statistical error of network traffic predictors. The optimal monitoring problem at hand is akin to certain combinatorial constraints, which render the algorithms seeking the exact solution impractical. We develop a number of fast algorithms that improve upon existing algorithms in terms of computational complexity and accuracy. Our algorithms exploit the geometry of principal component analysis, which also leads us to new types of theoretical bounds on the prediction error. Finally, these algorithms are amenable to randomization, where the best of several parallel independent instances often yields the exact optimal solution. Their performance is illustrated and evaluated on simulated and real-network traces.

Description: This paper provides a detailed overview of the Digital Video Broadcasting Terrestrial (DVB-T) signal structure and the implications for passive radar systems that use these signals as illuminators of opportunity. In particular, we analyze the ambiguity function and explain its delay and Doppler properties in terms of the underlying structure of the DVB-T signal. Of particular concern for radar range-Doppler processing are ambiguities consistent in range and Doppler with targets of interest. In this paper we adopt a mismatched filtering approach for range-Doppler processing. We also recognize that while the structure of the DVB-T signal introduces ambiguities, the structure can also be exploited to better estimate the transmitted signal and channel, as well as any mismatch between transmitter and receiver (e.g., clock offsets). This study presents a scheme for pre-processing both the reference and surveillance signals obtained by the passive radar to mitigate the effects of the ambiguities and the clutter in range-Doppler processing. The effectiveness of our proposed scheme in enhancing target detection is demonstrated using real-world data from an (Australian) 8k-mode DVB-T system. A 29 dB reduction in residual ambiguity levels over existing techniques is observed, and a 36 dB reduction over standard matched filtering; with only a 1 dB reduction in the zero-delay, zero-Doppler peak.

Description: The epothilones, compounds with anticancer mechanisms similar to that of paclitaxel (Taxol), are produced by strains of the myxobacterium Sorangium cellulosum , and the gene cluster responsible for epothilone biosynthesis is organised as a large operon. In this work, we showed that the 440-bp promoter regions of the operons from eight S. cellulosum strains have 94.27 % DNA sequence identity and 50 % variability in promoter activity in Escherichia coli . A primer extension analysis revealed two transcriptional start sites (TSSs) at 246 (TSS1) and 193 bp (TSS2) upstream of the translation start site (TLS), respectively. Promoter truncation determined that the basal promoter from the So0157-2 strain is located within a 264-bp region containing weak promoter activity; whereas in the 38-bp region upstream, the 264-bp promoter was required for the strong promoter activity, which was dramatically increased by 11-fold in average. There was a conserved stem–loop structure between TSS2 and the TLS, which was identified in E. coli as a negative regulatory element. In addition, the upstream non-conserved 357-bp non-coding region contributes to the promoter activity, increasing it by 1.5-fold. In conclusion, the expression of the epothilone operon non-coding region in E. coli is regulated by a double promoter (with −35 and −10 regions and two distinct TSSs), a stem–loop structure, and a distal non-coding region.

Description: Bacterial community compositions were characterized using denaturing gradient gel electrophoresis analysis of bacterial 16S rRNA gene in the sediments of the Pearl River estuary. Sequencing analyses of the excised bands indicated that Gram-negative bacteria, especially Gammaproteobacteria , were dominant in the Pearl River estuary. The diversity of polycyclic aromatic hydrocarbon ring-hydroxylating dioxygenase (PAH-RHD) gene in this estuary was then assessed by clone library analysis. The phylogenetic analyses showed that all PAH-RHD gene sequences of Gram-negative bacteria (PAH-RHD [GN] ) were closely related to the nagAc gene described for Ralstonia sp. U2 or nahAc gene for Pseudomonas sp. 9816–4, while the PAH-RHD gene sequences of Gram-positive bacteria (PAH-RHD [GP] ) at sampling site A1 showed high sequence similarity to the nidA gene from Mycobacterium species. Meanwhile, molecular diversity of the two functional genes was higher at the upstream of this region, while lower at the downstream. Redundancy analysis indicated that environmental factors, such as NH 4 -N, ∑PAHs, pH, SiO 3 -Si, and water depth, affected the distribution of the PAH-RHD [GN] gene in the Pearl River estuary.

Description: In order to provide a more suitable response to public health concerns, we improved the detection of infectious human adenoviruses in water by optimising the commonly used integrated cell culture–PCR method. Risk evaluation studies seek for rapid detection of infectious adenoviruses, including the enteric types 40 and 41 that are considered as the second most common agents of gastroenteritis in children next to rotaviruses. The here-employed 293A cell line used for infectious status assessment showed its ability to multiply adenoviruses including type 41. Two modifications were moreover applied to the workflow for viral detection. The first occurred at the nucleic acid extraction step performed directly on all infected cells, while the second was the application of real-time quantitative PCR as detection tool. All adaptations led to a 3-day reduction of the response delay and an improved sensitivity especially for the enteric adenoviral types. The infectious status of laboratory strain types 2 and 41 was demonstrated by a more than 2-log 10 increase in genome quantity. These conclusions were confirmed and reinforced by the analysis of water samples applying the improved assay. Naturally occurring infectious adenoviruses were detected in wastewater and river water, within 2 days. Types belonging to the species human adenoviruses C and type 31 were observed, but the most frequently identified type was 41 (71 % of identified sequences, n  = 34). This highlights the usefulness of our method for a wide range of types, and especially for the most prevalent and public health-relevant enteric adenoviruses.

Description: Proteins with a Zn(II) 2 Cys 6 domain, Cys-X 2 -Cys-X 6 -Cys-X 5-12 -Cys-X 2 -Cys-X 6-9 -Cys (hereafter, referred to as the C6 domain), form a subclass of zinc finger proteins found exclusively in fungi and yeast. Genome sequence databases of Saccharomyces cerevisiae and Candida albicans have provided an overview of this family of genes. Annotation of this gene family in most fungal genomes is still far from perfect and refined bioinformatic algorithms are urgently needed. Aspergillus flavus is a saprophytic soil fungus that can produce the carcinogenic aflatoxin. It is the second leading causative agent of invasive aspergillosis. The 37-Mb genome of A . flavus is predicted to encode 12,000 proteins. Two and a half percent of the total proteins are estimated to contain the C6 domain, more than twofold greater than those estimated for yeast, which is about 1 %. The variability in the spacing between cysteines, C 3 -C 4 and C 5 -C 6 , in the zinc cluster enables classification of the domains into distinct subgroups, which are also well conserved in Aspergillus nidulans . Sixty-six percent (202/306) of the A . flavus C6 proteins contain a specific transcription factor domain, and 7 % contain a domain of unknown function, DUF3468. Two A . nidulans C6 proteins containing the DUF3468 are involved in asexual conidiation and another two in sexual differentiation. In the anamorphic A . flavus , a homolog of the latter lacks the C6 domain. A . flavus being heterothallic and reproducing mainly through conidiation appears to have lost some components involved in homothallic sexual development. Of the 55 predicted gene clusters thought to be involved in production of secondary metabolites, only about half have a C6-encoding gene in or near the gene clusters. The features revealed by the A . flavus C6 proteins likely are common for other ascomycete fungi.