Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin

This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO₂) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO₂ from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO₂ column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO₂ column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO₂ column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO₂ columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO₂. A detailed analysis of volcanic SO₂ transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO₂ at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO₂ enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO₂. For the first time, we present significant influence of volcanic SO₂ from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO₂ levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively.     

Fuzzy based multi-criteria vertical handover decision modeling in heterogeneous wireless networks

Vertical handover gain significant importance due to the enhancements in mobility models by the Fourth Generation (4G) technologies. However, these enhancements are limited to specific scenarios and hence do not provide support for generic mobility. Similarly, various schemes are proposed based on these mobility models but most of them are suffered from the high packet loss, frequent handovers, too early and late handovers, inappropriate network selection, etc. To address these challenges, a generic vertical handover management scheme for heterogeneous wireless networks is proposed in this article. The proposed scheme works in three phases. In the first phase, a handover triggering approach is designed to identify the appropriate place for initiating handover based on the estimated coverage area of a WLAN access point or cellular base station. In the second phase, fuzzy rule based system is designed to eliminate the inappropriate networks before deciding an optimal network for handover. In the third phase, a network selection scheme is developed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision mechanism. Various parameters such as delay, jitter, Bit Error Rate (BER), packet loss, communication cost, response time, and network load are considered for selecting an optimal network. The proposed scheme is tested in a mobility scenario with different speeds of a mobile node ranging from very low to very high. The simulation results are compared with the existing decision models used for network selection and handover triggering approaches. The proposed scheme outperforms these schemes in terms of energy consumption, handover delay and time, packet loss, good put, etc.     

Laminar convection in the annulus of a double-pipe with triangular fins

A steady and laminar convective flow has been numerically simulated in the fully-developed annular region of a finned double-pipe subjected to the constant heat flux boundary condition imposed at the inner-pipe wall. Finite element method has been employed in this study. Friction factor and Nusselt number have been studied as flow characteristics against variations in the ratio of radii of the inner and the outer pipes, the fin height, the fin half angle and the number of fins. The results show significant enhancement in the heat transfer rate in both the cases when sufficient pumping power is available and when it is not. The minimum and maximum increase in the product of friction factor and Reynolds number relative to the finless geometry is more than one time and more than 40 times respectively while gain in the relative value of Nusselt number lies in the range 1–177. This provides an evidence of more than four times enhancement in the heat transfer coefficient relative to that in the pressure loss as a result of extended fin surfaces.     

Image representation using accurate orthogonal Gegenbauer moments

Image representation by using polynomial moments is an interesting theme. In this paper, image representation by using orthogonal Gegenbauer function is presented. A novel method for accurate and fast computation of orthogonal Gegenbauer moments is proposed. The accurate values of Gegenbauer moments are obtained by mathematically integrating Gegenbauer polynomials multiplied by their weight functions over the digital image pixels. A novel recurrence formula is derived for the kernel generation. The proposed method removes the numerical approximation errors involved in conventional method. A fast algorithm is proposed to accelerate the moment’s computations. A comparison with the conventional method is performed. The obtained results explain the efficiency and the superiority of the proposed method.     

Ab initio determination of heavy oxide perovskite related structures from precession electron diffraction data

Two complex perovskite-related structures were solved by ab initio from precession electron diffraction intensities. Structure models were firstly derived from HREM images and than have been confirmed independently using two and three-dimensional sets of precession intensities. Patterson techniques prove to be effective for ab initio structure resolution, specially in case of projections with no overlapping atoms. Quality of precession intensity data may be suitable enough to resolve unknown heavy oxide structures.     

A method for real power transfer allocation using multivariable regression analysis

A multivariable regression (MVR) approach is proposed to identify the real power transfer between generators and loads. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then, the results of MNE method and load flow information are utilized to determine suitable regression coefficients using MVR model to estimate the power transfer. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the MVR output compared to that of the MNE method. The error of the estimate of MVR method ranges from 0.001 4 to 0.007 9. Furthermore, when compared to MNE method, MVR method computes generator contribution to loads within 26.40 ms whereas the MNE method takes 360 ms for the calculation of same real power transfer allocation. Therefore, MVR method is more suitable for real time power transfer allocation.     

Alzheimer paired helical filaments (PHFs) studied by high-resolution TEM: what can vertical Pt-C replication tell us about the organization of the pronase-digested PHF core?

Untreated paired helical filaments (PHFs) and pronase-digested PHF-core filaments were stereoscopically imaged with a freeze-drying vertical platinum-carbon replication preparation method for TEM. The untreated PHF have an average wide region (W) = 22.8 +/- 2.4 nm, a narrow region (T) = 10.6 +/- 1.7 nm, and a helical turn period (L) = 78.6 +/- 13.4. The surfaces of the untreated PHF's fuzzy coat appears disorganized. The widths of the pronase-treated PHF-core filaments were significantly reduced (W(d) = 14.8 +/- 1.2 nm, T(d) = 5.7 +/- 1.0 nm, and L(d) = 75.4 +/- 17 nm). The surfaces of the untreated PHF contained approximately 1.1 nm strands, the same size as tau monomer ( approximately 1.0 nm). The pronase-digested PHF cores mostly contained approximately 1.6 +/- 0.3 nm strands although strand diameters ranged from 0.6-2.5 nm. The strands sometimes appear to be wrapped around the filament axis; less often, they appear to be roughly parallel to the PHF axis, and otherwise appear to be randomly oriented. Images of pronase-digested PHF core images are discussed in relation to the core's biochemical composition, its proposed beta structure, and structural subunit models. Images of the untreated and the pronase-digested PHF support a helical ribbon morphology.     

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.     

Light microscopy of Pakistani Berberis leaf cuticles and its taxonomic implications

Taxonomy of the genus Berberis is quite complex, due to overlapping morphological characters, making it very difficult to differentiate the species within the genus. In order to resolve this taxonomic complexity, the foliar anatomy of 10 Berberis L. species was carried out, for the first time from Pakistan, using light microscopy (LM). Significant variation in terms of epidermal cells shape, size, cell wall pattern, and stomata type was observed. B. baluchistanica has the largest epidermal cells, Adaxial: length = 45–(53.9 ± 3.6)–62.5 μm; and width = 22.5–(26.3 ± 1.3)–30 μm; Abaxial: length = 37.5–(43.25 ± 2.5)–50 μm; and width = 20–(22.6 ± 0.8)–25. The highest number of stomata was observed in B. glaucocarpa as 62 on the abaxial surface while the lowest number of stomata was recorded in B. baluchistanica as 8 on the adaxial surface. Of 10 investigated species, 6 possess anomocytic type stomata, while 2 species that is, B. aitchisonii and B. parkeriana have both anomocytic and anisocytic stomata while B. baluchistanica and B. calliobotrys have only paracytic type stomata. The highest number of cells per unit area was present on the adaxial surface of B. calliobotrys ranging from 245–(252.4)–260 followed by B. parkeriana with 209–(227.8)–250 on the abaxial surface. Stomatal index (SI) also varied considerably and was the lowest (2.6) percentage in B. baluchistanica and highest (31.9) percentage in B. kunawurensis. A taxonomic key based on micro‐morphological characters is provided for species identification.     

Influence of Y~(3+),Yb~(3+),Gd~(3+) cations on structural and electromagnetic properties of CuFe_2O_4 nanoferrites prepared via one step sol-gel method

Rare earths(REs) play a key role in distorting spinel structure by creating some defects at the lattice sites and make them suitable for magnetodielectric applications.In the present study,the nanoferrites of CuRE_(0.02)Fe_(1.98)O_4,where REs=Y~(3+),Yb~(3+),Gd~(3+),were prepared using one step sol-gel method.The prepared samples are copper ferrite(CFO),yttrium doped copper ferrite(Y-CFO),ytterbium doped copper ferrite(Yb-CFO) and gadolinium doped copper ferrite(Gd-CFO),respectively.The single-phase structure of all the REs doped nanoferrites was determined by X-ray diffraction(XRD) analysis.The porosity,agglomerations and grain size of the REs doped copper ferrite were examined using field emission scanning electron microscopy(FESEM) analysis.Fourier transform infrared spectroscopy(FTIR)elaborates the phase formation and environmental effects on the REs doped nanoparticles(NPs).The recorded room temperature M-H loops from a vibrating sample magnetometer(VSM) elucidate the magnetic properties of the REs doped spinel nanoferrites.The magnetic saturation(M_s) was calculated in the range of 23.08 to 51.78 emu/g.The calculated coercivity values(272.6 to 705.60 Oe) confirm the soft magnetic behavior of REs doped copper ferrites.Furthermore,the electromagnetic and dielectric properties were assessed using a Vector network analyzer(VNA) from 1 to 6 GHz.The permeability,permittivity,dielectric tangent loss and electric modulus of the REs doped spinel ferrites illustrate that the prepared NPs may be suitable for microwave and high frequency applications.