Identification of Pathogenicity-Related Genes in Biofilm-Defective Acidovorax citrulli by Transposon Tn5 Mutagenesis

Biofilm formation is important for virulence of a large number of plant pathogenic bacteria. Indeed, some virulence genes have been found to be involved in the formation of biofilm in bacterial fruit blotch pathogen Acidovorax citrulli. However, some virulent strains of A. citrulli were unable to format biofilm, indicating the complexity between biofilm formation and virulence. In this study, virulence-related genes were identified in the biofilm-defective strain A1 of A. citrulli by using Tn5 insertion, pathogenicity test, and high-efficiency thermal asymmetric interlaced PCR (hiTAIL-PCR). Results from this study indicated that 22 out of the obtained 301 mutants significantly decreased the virulence of strain A1 compared to the wild-type. Furthermore, sequence analysis indicated that the obtained 22 mutants were due to the insertion of Tn5 into eight genes, including Aave 4244 (cation diffusion facilitator family transporter), Aave 4286 (hypothetical protein), Aave 4189 (alpha/beta hydrolase fold), Aave 1911 (IMP dehydrogenase/GMP reductase domain), Aave 4383 (bacterial export proteins, family 1), Aave 4256 (Hsp70 protein), Aave 0003 (histidine kinase, DNA gyrase B, and HSP90-like ATPase), and Aave 2428 (pyridoxal-phosphate dependent enzyme). Furthermore, the growth of mutant Aave 2428 was unaffected and even increased by the change in incubation temperature, NaCl concentration and the pH of the LB broth, indicating that this gene may be directly involved in the bacterial virulence. Overall, the determination of the eight pathogenicity-related genes in strain A1 will be helpful to elucidate the pathogenesis of biofilm-defective A. citrulli.     

Health risk assessment of inorganic arsenic intake of Cambodia residents through groundwater drinking pathway

In order to compare the magnitudes and health impacts of arsenic and other toxic trace elements in well water, groundwater and hair samples were collected from three areas with different arsenic exposure scenarios in the Mekong River basin of Cambodia. Ampil commune in Kampong Cham province was selected as an uncontaminated area, Khsarch Andaet commune in Kratie province was selected as a moderately contaminated area, and Kampong Kong commune in Kandal Province was selected as an extremely contaminated area. Results of ICP-MS analyses of the groundwater samples revealed that As, Mn, Fe and Ba concentrations were significantly different among the three study areas (Kruskal-Wallis test, p < 0.0001). Out of 46 observed wells in the Kandal province study area, 100% detected As > 50 μg L⁻¹ and Fe > 300 μg L⁻¹; 52.17% had Mn > 400 μg L⁻¹ and 73.91% found Ba > 700 μg L⁻¹. In the Kratie province study area (n = 12), 25% of wells showed elevated arsenic levels above 10 μg L⁻¹ and 25% had Mn > 400 μg L⁻¹, whereas samples from Kampong Cham province study area (n = 18) were relatively clean, with As < 10 μg L⁻¹. A health risk assessment model derived from the USEPA was applied to calculate individual risks resulting from drinking groundwater. Computational results indicated that residents from Kandal Province study area (n = 297) confronted significantly higher non-carcinogenic and carcinogenic risks than those in Kratie (n = 89) and Kampong Cham (n = 184) province study areas (Kruskal-Wallis test, p < 0.0001). 98.65% of respondents from the Kandal province study area were at risk for the potential non-cancer effect and an average cancer risk index was found to be 5 in 1000 exposure. The calculations also indicated that, in the Kratie province study area, 13.48% of respondents were affected by non-cancer health risks and 33.71% were threatened by cancer, whereas none of respondents in the Kampong Cham province study area appeared to have non-carcinogenic effect. Positively significant correlations of the arsenic content in scalp hair (As_h) with both arsenic levels in groundwater (As_w) (r_s (304) = 0.757, p < 0.0001) and individual average daily doses (ADD) of arsenic (r_s (304) = 0.763, p < 0.0001) undoubtedly indicated that arsenic accumulation in the bodies of Cambodia residents in the Mekong River basin was mainly through a groundwater drinking pathway. To the best of our knowledge, this is the first comprehensive report comparing individual health risk assessments of arsenic exposure through a groundwater drinking pathway to enriched arsenic levels from groundwater in the Mekong River basin, Cambodia. This study indicates that elevated arsenic concentrations in groundwater may lead to thousands of cases of arsenicosis in the near future if mitigating actions are not taken.     

A Novel Approach for Mining High‐Utility Sequential Patterns in Sequence Databases

Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real‐world scenarios. In this paper, we propose a novel framework for mining high‐utility sequential patterns for more real‐life applicable information extraction from sequence databases with non‐binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high‐utility sequential patterns, we propose two new algorithms: UtilityLevel is a high‐utility sequential pattern mining with a level‐wise candidate generation approach, and UtilitySpan is a high‐utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high‐utility sequential patterns.     

An application of univariate marginal distribution algorithm in MIMO communication systems

The paper discusses a sequence detector based on univariate marginal distribution algorithm (UMDA) that jointly estimates the symbols transmitted in a multiple input multiple output (MIMO) communication system. While an optimal maximum likelihood detection using an exhaustive search method is prohibitively complex, it has been shown that sphere decoder (SD) achieves the optimal bit error rate (BER) performance with polynomial time complexity for smaller array sizes. However, the worst‐case complexity of SD is exponential in the problem dimensions, this brings in question its practical implementation for larger number of spatial layers and for higher‐order signal constellation. The proposed detector shows promising results for this overly difficult and complicated operating environment, confirmed through simulation results. A performance comparison of the UMDA detector with SD is presented for higher‐order complex MIMO architectures with limited average transmit power. The proposed detector achieves substantial performance gain for higher‐order systems attaining a near optimal BER performance with reduced computational complexity as compared with SD. Copyright © 2009 John Wiley & Sons, Ltd.     

Relevance of peat-draining rivers for the riverine input of dissolved iron into the ocean

Peat bogs have the ability to produce strong chelate ligands (humic and fulvic acids) which enhance the weathering rates of iron-silicate minerals and greatly increase the solubility of the essential trace metal iron in river water. Fluvial networks link peat bogs with the ocean, and thus terrestrial-derived fulvic-iron complexes fuel the ocean's biological productivity and biological carbon pump, but understanding this role is constrained by inconsistent observations regarding the behaviour of riverine iron in the estuarine mixing zone, where precipitation reactions remove iron from the water column. We applied a characterization of the colloidal iron carriers in peatland-draining rivers in North Scotland, using field-flow fractionation (FFF), in combination with end-member mixing experiments of river water sampled near the river mouth and coastal seawater using a ⁵⁹Fe radiotracer method. According to our results, the investigated river contributed “truly dissolved” Fe concentrations of about 3300 nmol L^− 1 to the ocean which is nearly two orders of magnitude higher than the dissolved iron contribution of the “average world” river (∼ 40 nmol L^− 1). Thus we conclude that peatland-draining rivers are important sources of dissolved iron to the ocean margins. We propose highly electrostatic and sterical stabilized iron-organic matter complexes in the size range of < 2 kDa to be responsible for iron transport across the estuarine mixing zone.     

Effect of sparse long‐chain branching on the step‐strain behavior of a series of well‐defined polyethylenes

The effect of sparse long chain branching, LCB, on the shear step‐strain relaxation modulus is analyzed using a series of eight high‐density polyethylene (HDPE) resins. Strains of 1 to 1250% are imposed on materials with LCB content ranging from zero to 3.33 LCB per 10,000 carbon atoms. All materials are observed to obey time–strain separation beyond some characteristic time, τ_k. The presence of LCB is observed to increase the value of τ_k relative to the linear resin. The behavior of the relaxation modulus at times shorter than τ_k is investigated by an analysis of the enhancement seen in the linear relaxation modulus, G⁰(t), as a function of strain and LCB content. This enhancement is seen to (1) increase with increasing strain in all resins, (2) be significantly larger in the sparsely branched HDPE resins relative to the linear HDPE resin, and (3) increase in magnitude with increasing LCB content. The shape and smoothness of the damping function is also investigated. The finite rise time to impose the desired strain is compared to the Rouse relaxation time of linear HDPE resins studied. Sparse LCB is found to increase the magnitude of the relaxation modulus at short times relative to the linear resin. POLYM. ENG. SCI., 2010. © 2010 Society of Plastics Engineers     

Analysis of Asynchronous Band-Limited DS-CDMA with MMSE Multiuser Detector over Generalized-<Emphasis Type="Italic">k</Emphasis> Fading Channels

In this paper, we investigate bit-error-rate (BER) performance of a minimum mean-squared error (MMSE) multiuser receiver for asynchronous band-limited direct- sequence code-division multiple-access (DS-CDMA) systems. We focus on the BER performance in the presence of multitone jamming (MTJ) over frequency-selective multipath fading channels. We consider the generalized-K fading model in our analysis, as it can model a large spectrum of fading-channel characteristics. We also analyze the effects of band- limited pulse shape on the BER performance of the system. Multipath diversity based on the maximal-ratio combining (MRC) scheme is employed to combat fading effects. Our analytical expressions are valid for arbitrary diversity levels and fading parameters. Spectrum raised cosine (SRC) and Beaulieu–Tan–Damen (BTD) pulse shapes are employed for numerical analysis. Numerical results show that in the presence of MTJ and under various channel conditions, the MMSE based receiver gives better BER performance than the one without it. Moreover, the system with BTD pulses outperforms the one with SRC pulses.     

Detection of microscopic glaucoma through fundus images using deep transfer learning approach

Glaucoma disease in humans can lead to blindness if it progresses to the point where it affects the oculus' optic nerve head. It is not easily detected since there are no symptoms, but it can be detected using tonometry, ophthalmoscopy, and perimeter. However, advances in artificial intelligence approaches have permitted machine learning techniques to diagnose at an early stage. Numerous methods have been proposed using Machine Learning to diagnose glaucoma with different data sets and techniques but these are complex methods. Although, medical imaging instruments are used as glaucoma screening methods, fundus imaging specifically is the most used screening technique for glaucoma detection. This study presents a novel DenseNet and DarkNet combination to classify normal and glaucoma affected fundus image. These frameworks have been trained and tested on three data sets of high-resolution fundus (HRF), RIM 1, and ACRIMA. A total of 658 images have been used for healthy eyes and 612 images for glaucoma-affected eyes classification. It has also been observed that the fusion of DenseNet and DarkNet outperforms the two CNN networks and achieved 99.7% accuracy, 98.9% sensitivity, 100% specificity for the HRF database. In contrast, for the RIM1 database, 89.3% accuracy, 93.3% sensitivity, 88.46% specificity has been attained. Moreover, for the ACRIMA database, 99% accuracy, 100% sensitivity, 99% specificity has been achieved. Therefore, the proposed method is robust and efficient with less computational time and complexity compared to the literature available.     

Mechanical and Microstructural Evaluation of Squeeze Cast Al-4%Cu Alloy Using a Full-Factorial Experimental Design

A full factorial design was employed to investigate the effect of squeeze pressure in conjunction with thermal parameters, i.e., melt and die temperatures, on the mechanical properties of a squeeze cast Al-4%Cu alloy. Considerable variations in mechanical properties existed between different test runs, and these were discussed based on cooling rates previously quantified for a squeeze-cast Al-4%Cu alloy. The completeness of a full factorial design not only identified a combination of process parameters for optimum results but also facilitated an evaluation of the minimum pressure required to eliminate porosity and influence the die temperature on the microstructure of the squeeze-cast alloy. In addition to the optimum run, particular importance was given to those runs that had more desirable levels of control factors with respect to energy consumption or tooling life. A microstructural analysis of these runs indicated the possibility of precipitation hardening that can open up further investigations toward the opportunities associated with in situ heat treatment of age-hardening, squeeze cast aluminum alloys.