Chlorophyll and plankton of the Gulf coastal waters of Saudi Arabia bordering a desalination plant

As on land, plants are the real producers in the sea, and on them depend all marine living resources and the basic sustainability of ecosystems. Primary production is performed by chlorophyll-bearing plants ranging from the tiny phytoplankton to the giant kelps through the process ofphotosynthesis. Zooplankton play an important role as secondary producers, and together with phytoplankton they support the vast assemblages of marine food chain with all their diversity and complexity. Data on chlorophyll pigments, phytoplankton and zooplankton are regarded as a sound basis for environmental appraisal of ecosystems. This paper presents a set of data collected from the Saudi Arabian coastal waters near the desalination plants in AI-Jubail. Materials were collected from six different sites covering the intake and discharge zones during cruises carried out in 1997-1998. Analyses of chlorophyll pigments were made using the spectrophotometric method. Plankton samples were collected using a Nansen plankton net with a mesh size of 75 μ and analyzed following standard procedures. Chlorophyll a, b, c and phaeophytin are the most commonly occurring pigments in seawater. Their concentrations showed wide fluctuation. The phytoplankton community was composed of 35 genera representing the Diatoms, Dinoflagellates and blue- green algae. Zooplankton were composed ofProtozoa, Coelenterata, Ctenophora, Aschelminthes, Annelida, Mollusca, Arthropoda, Echinodermata and Chordata. Arthropoda, represented by Cladocera, Copepoda and Crustacean larvae, formed the largest group followed by Chordata. The distribution of phyto- and zooplankton was examined and discussed on a seasonal, annual and inter-annual basis. In terms of species, overall species composition was not affected by plant discharge. The study brings out a greater understanding of the changes experienced by biotic communities as a result of impingement, entrainment and entrapment consequent to water passage through the plant structures. The study reflects the ecological relationships that the phytoplankton and the zooplankton of the region possess with respect to intake and discharge. Further, the study has brought to light a very redeeming feature of the ecosystem to sustain its productivity and planktonic abundance. It was observed that seawater temperature, conductivity and total suspended solids did not act as limiting factors. Besides throwing much light on the little known biological aspects of desalination sites, the data provided constitute a significant addition to the knowledge base of marine living resources in an industrial zone of Gulf coastal waters.     

Low‐temperature synthesis of hierarchical structures of copper oxide and their superior biological activity

In this work, the authors report a facile low‐temperature wet‐chemical route to prepare morphology‐tailored hierarchical structures (HS) of copper oxide. The preparation of copper oxide collides was carried out using varying concentrations of copper acetate and a reducing agent at a constant temperature of 50°C. The prepared HS of CuO were characterised by powdered X‐rays diffraction that indicates phase pure having monoclinic structures. The morphology was further confirmed by field‐emission scanning electron microscope. It reveals a difference in shape and size of copper oxide HS by changing the concentration of reactants. In order to evaluate the effect of H₂ O₂ on CuO NPs, the prepared CuO are modified by treatment with H₂ O₂. In general trend, CuOH₂ O₂ collide showed enhanced protein kinase inhibition, antibacterial (maximum zone 16.34 mm against Staphylococcus aureus) and antifungal activities in comparison to unmodified CuO collides. These results reveal that CuO HS exhibit antimicrobial properties and can be used as a potential candidate in pharmaceutical industries.Inspec keywords: molecular biophysics, antibacterial activity, X‐ray diffraction, microorganisms, copper compounds, nanofabrication, nanoparticles, narrow band gap semiconductors, field emission scanning electron microscopy, enzymes, nanomedicine, particle size, semiconductor growthOther keywords: unmodified CuO collides, low‐temperature synthesis, morphology‐tailored hierarchical structures, copper acetate, reducing agent, monoclinic structures, copper oxide HS, CuO NPs, Staphylococcus aureus, biological activity, copper oxide, powdered X‐ray diffraction, field‐emission scanning electron microscopy, facile low‐temperature wet‐chemical method, protein kinase inhibition, antibacterial activity, antifungal activity, antimicrobial properties, pharmaceutical industries, temperature 50.0 degC, CuO     

A Network Traffic Classification Model Based on Metric Learning

Attacks on websites and network servers are among the most critical threats in network security. Network behavior identification is one of the most effective ways to identify malicious network intrusions. Analyzing abnormal network traffic patterns and traffic classification based on labeled network traffic data are among the most effective approaches for network behavior identification. Traditional methods for network traffic classification utilize algorithms such as Naive Bayes, Decision Tree and XGBoost. However, network traffic classification, which is required for network behavior identification, generally suffers from the problem of low accuracy even with the recently proposed deep learning models. To improve network traffic classification accuracy thus improving network intrusion detection rate, this paper proposes a new network traffic classification model, called ArcMargin, which incorporates metric learning into a convolutional neural network (CNN) to make the CNN model more discriminative. ArcMargin maps network traffic samples from the same category more closely while samples from different categories are mapped as far apart as possible. The metric learning regularization feature is called additive angular margin loss, and it is embedded in the object function of traditional CNN models. The proposed ArcMargin model is validated with three datasets and is compared with several other related algorithms. According to a set of classification indicators, the ArcMargin model is proofed to have better performances in both network traffic classification tasks and open-set tasks. Moreover, in open-set tasks, the ArcMargin model can cluster unknown data classes that do not exist in the previous training dataset.     

Probiotics for cure of Helicobacter pylori infection: A review

Human physiology normally contains pathogenic and non-pathogenic microorganisms in the gastrointestinal flora. Disturbance of these microorganism balance results in the formation of infection. Extensive use of antibiotics for cure of these disturbances like Helicobacter pylori (H. pylori) infection leads to patient discomfort and associated side-effects. There is a need to adopt adjunct or alternative approach in order to minimize such conditions. Probiotics is one of the potential therapies to cure gastrointestinal discomforts especially associated with H. pylori. It competes through non-immune and immune systems. This review article concludes that probiotics are used to eradicate the infection at increased rate, and decreased associated side-effects are caused by triple therapy. A proper evaluation of these probiotics is demanded before their use in future as a commercial product. Furthermore, their effect on immune system requires more research work so that their usage for other chronic disorders can also be considered.     

Silicon Seed Priming Combined with Foliar Spray of Sulfur Regulates Photosynthetic and Antioxidant Systems to Confer Drought Tolerance in Maize (Zea mays L.)

Silicon - The present study evaluated the effect of silicon (Si) seed priming and sulfur (S) foliar spray on drought tolerance of two contrasting maize hybrids viz. drought tolerant Hi-Corn 11 and...     

Emissions from sawdust in packed moving bed dryers and subsequent pellet production

This study quantifies emissions of hydrocarbon terpenes from the drying of sawdust in packed moving bed dryers, through the production chain to the finished pellets, and determines the parameters suitable for emission control. The terpene content in softwood sawdust and pellets was analyzed using gas chromatography. The distribution of VOC emissions over the bed was measured with a flame ionization detector. After drying, 30–40% of the initial terpenes remain in the wood, 20–30% remain after grinding, and 10–15% remain after pelleting. Dryer emissions correlate with residence time and final sawdust moisture content. Pellet press emissions correlate with pellet moisture content.     

Determination of Hydralazine Hydrochloride and Hydrochlorothiazide in Dosage Forms by High Performance Liquid Chromatography

A high performance liquid chr0matOgraphiC method is presented for the simultaneous determination of hydralazine hydrochloride and hydrochlorothiazide in combination dosage forms. ccmpounds are chromatographed on a radialpak cyanopropylsilane cartridge with a mixture of methanol, water and dibutylamine phosphate as mobile phase and W detection at 254 run. hydralazine hydrochloride and hydrochlorothiazide showed linear detector responses over a range of 50-150% of label claim with correlation coefficients of 0.999. Assay recoveries (n = 5) were found to contain an average of 98.9% hydrochloride and 98'.8% 2 1.1 of hydrochlorothiazide. proposed method showed excellent resolution and reproducibility. It will be helpful in routine quality control analysis of such combination dosage forms.     

The ParTriCluster Algorithm for Gene Expression Analysis

Analyzing gene expression patterns is becoming a highly relevant task in the Bioinformatics area. This analysis makes it possible to determine the behavior patterns of genes under various conditions, a fundamental information for treating diseases, among other applications. A recent advance in this area is the Tricluster algorithm, which is the first algorithm capable of determining 3D clusters (genes × samples × timestamps), that is, groups of genes that behave similarly across samples and timestamps. However, even though biological experiments collect an increasing amount of data to be analyzed and correlated, the triclustering problem remains a bottleneck due to its NP-Completeness, so its parallelization seems to be an essential step towards obtaining feasible solutions. In this work we propose and evaluate the implementation of a parallel version of the Tricluster algorithm using the filter-labeled-stream paradigm supported by the Anthill parallel programming environment. The results show that our parallelization scales well with the data size, being able to handle severe load imbalances that are inherent to the problem. Further more, the parallelization strategy is applicable to any depth-first searches.     

Analogy Theory and Application of Pressure Difference of Wind Turbine Blade Profile

风力发电叶片翼型型线理论及应用

张照煌,Aqeel Muhammad,张峻,刘青,李魏魏,宋玉旺

（华北电力大学 能源动力与机械工程学院 ,北京 102206）

中文说明：

经研究发现,在流动空气与风电叶片相互作用规律的过程中,真空中自由下落的空气团的形态与前后压差作用下流动的空气（风）非常相似;因此,本文提出以重量比拟压差设计风电叶片翼型型线的理论,即：空气团流过风电叶片翼型线的时间最短及应有尽可能多的空气团作用于该翼型线;以此为基础,本文推导出风电叶片翼型型线方程并进行了应用研究;通过从现有翼型库中选取三种相似翼型进行模拟对比,结果表明用本文建立的风电叶片翼型线方程设计的翼型线翼型(“SJX翼型”)在攻角变化时的升力及升力系数较所选取的三种翼型有较大的提升,翼型生阻比亦有小幅提升,且流动空气作用在气动中心的力矩均较大,验证了论文建立的风电叶片翼型线方程设计翼型型线的可行性和有效性,从而为风电叶片翼型型线设计理论的发展提供了新尝试和有益借鉴。

关键词：风力发电叶片;重量比拟压差;翼型型线;生阻比;翼型设计