Sediment flux from Lesser Zab River in Dokan Reservoir: Implications for the sustainability of long‐term water resources in Iraq

Prudent management of Iraqi water resources under climate change conditions requires plans to be based on actual figures of the storage capacity of existing reservoirs. With the absence of sediment flushing measures, the actual storage capacity of Dokan Reservoir (operated since 1959) has been affected by the amount of sediment delivered during its operational life leading to an undetermined reduction in its storage capacity. In consequence, there has not been an update on the dam's operational storage capacity curves. In this research, new operational curves were established for the reservoir based on a recent bathymetric survey undertaken in 2014. The reduction in reservoir capacity during the period between 1959 and 2014 was calculated by the mean of the difference between the designed storage capacity and the storage capacity which was concluded from the 2014 bathymetric survey. Moreover, the rate of sediment transported to the reservoir was calculated based on the overall quantities of accumulated sediment and the water discharge of the Lesser Zab River into the reservoir. The results indicate that the dam capacity is reduced by 25% due to sedimentation of an estimated volume of 367 million cubic metres at water level 480 m.a.s.l. The annual sedimentation rate was about 6.6 million cubic metres, and the sediment yield was estimated to be 701.2 t?km^?3?year.     

Artificial Algae Optimization with Deep Belief Network Enabled Ransomware Detection in IoT Environment

The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations. This study develops an Artificial Algae Optimization Algorithm with Optimal Deep Belief Network (AAA-ODBN) Enabled Ransomware Detection in an IoT environment. The presented AAA-ODBN technique mainly intends to recognize and categorize ransomware in the IoT environment. The presented AAA-ODBN technique follows a three-stage process: feature selection, classification, and parameter tuning. In the first stage, the AAA-ODBN technique uses AAA based feature selection (AAA-FS) technique to elect feature subsets. Secondly, the AAA-ODBN technique employs the DBN model for ransomware detection. At last, the dragonfly algorithm (DFA) is utilized for the hyperparameter tuning of the DBN technique. A sequence of simulations is implemented to demonstrate the improved performance of the AAA-ODBN algorithm. The experimental values indicate the significant outcome of the AAA-ODBN model over other models.     

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the PODL-TCIA model initially performs image pre-processing to enhance medical image quality. Followed by, Inception with ResNet-v2 model is employed for feature extraction. Besides, political optimizer (PO) with twin support vector machine (TSVM) model is exploited for image classification process, shows the novelty of the work. The design of PO algorithm assists in the optimal parameter selection of the TSVM model. For ensuring the enhanced outcomes of the PODL-TCIA model, a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.     

Characterization of methylumbilliferone (mendiaxon r)-induced choleresis in the isolated perfused rat liver

The influence of the choleretic drug methylumbilliferone on bile formation in the isolated perfused rat liver is characterized. The compound induces rapidly an elevation of bile flow, bile acid secretion and soium excretion. The increased production of bile is of canalicular origin. The choleretic effect was defined as "bile acid like" choleresis due to excretion of the drug into the bile. It is discussed that the excretion of methylumbilliferone can influence the transport of bile in form of a positive cooperation on transport mechanism.     

Compact Deep Color Features for Remote Sensing Scene Classification

Neural Processing Letters - Aerial scene classification is a challenging problem in understanding high-resolution remote sensing images. Most recent aerial scene classification approaches are based...     

Preparation,characterization, and dynamic adsorption–desorption studies on polypyrrole encapsulated TiO2 nanoparticles

Binary doped polypyrrole (PPy) encapsulated Titania (TiO₂) nanoparticles were prepared by oxidative polymerization using FeCl₃ as oxidant in presence of camphorsulfonic acid (CSA) as surfactant. Both FeCl₃ (oxidant) and camphorsulfonic acid (surfactant) also act as dopant and hence thus prepared polypyrrole/Titania (TiO₂@PPy) is termed as binary doped nanocomposite i.e. FeCl₃ dopes polypyrrole by oxidation mechanism while camphorsulfonic acid dopes polypyrrole by protonic doping mechanism. The TiO₂@PPy coreshell nanocomposites were characterized by Fourier transform infrared spectroscopy (FTIR), X‐ray diffraction (XRD), thermogravimetry, differential scanning calorimetry (DSC), field emission‐scanning electron microscopy (FE‐SEM), and inductance‐capacitance‐resistance (LCR) measurements. The results indicated that the structural and electrical properties of the TiO₂@PPy coreshell nanocomposites were significantly influenced by the extent of TiO₂ nanoparticles loading of polypyrrole. The direct current (DC) electrical conductivity of the as‐prepared TiO₂@PPy coreshell nanocomposites was higher than that of PPy. As‐prepared TiO₂@PPy coreshell nanocomposites were also studied for their dielectric losses for alternating current (AC) which is useful characteristic for their application in the fabrication of charge storing devices. TiO₂@PPy coreshell nanocomposites showed synergistic effect of combining components in improving their alcohol sensing properties. This improvement may be attributed to the adsorption on and desorption from alcohols TiO₂@PPy interface of the nanocomposites and alcohol vapors causing decrease in depletion region. The TiO₂@PPy coreshell nanocomposites were observed to show better reproducibility of electrical conductivity and fast self‐recovery during the alcohol vapor sensing process. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43411.     

Injection Molding Micro‐ and Nanostructures in Thermoplastic Elastomers

Flexible polymers such as poly dimethyl siloxane (PDMS) can be patterned at the micro‐ and nanoscale by casting, for a variety of applications. This replication‐based fabrication process is relatively cheap and fast, yet injection molding offers an even faster and cheaper alternative to PDMS casting, provided thermoplastic polymers with similar mechanical properties can be used. In this paper, a thermoplastic polyurethane is evaluated for its patterning ability with an aim to forming the type of flexible structures used to measure and modulate the contractile forces of cells in tissue engineering experiments. The successful replication of grating structures is demonstrated with feature sizes as low as 100 nm and an analysis of certain processing conditions that facilitate and enhance the accuracy of this replication is presented. The results are benchmarked against an optical storage media grade polycarbonate.

     

Probabilistic Strength at Serviceability Limit State for Normal and SBHS Slender Stiffened Plates Under Uniaxial Compression

International Journal of Steel Structures - Stiffened plates with high slenderness parameters show large out-of-plane deflections, due to elastic buckling, which may occur before the plates reach...     

Role of protein phosphatases in cyclic AMP-mediated stimulation of hepatic Na+/taurocholate cotransport

Cyclic AMP has been proposed to stimulate Na+/taurocholate (TC) cotransport in hepatocytes by translocating Na+/TC cotransport polypeptide (Ntcp) to the plasma membrane and to induce Ntcp dephosphorylation. Whether protein phosphatases 1 and 2A (PP1/2A) are involved in the regulation of Na+/TC cotransport by cAMP was investigated in the present study. Okadaic acid and tautomycin, inhibitors of PP1/2A, inhibited cAMP-mediated increases in TC uptake and cytosolic [Ca2+], and only tautomycin inhibited basal TC uptake. Removal of cAMP reversed cAMP-mediated increases in TC uptake and plasma membrane Ntcp mass. Okadaic acid alone increased Ntcp phosphorylation without affecting Ntcp mass in plasma membranes and homogenates. In the presence of okadaic acid, cAMP failed to increase plasma membrane Ntcp mass, induce Ntcp dephosphorylation, and decrease endosomal Ntcp mass. Phosphorylated Ntcp was detectable in endosomes isolated from okadaic acid-treated hepatocytes but not in endosomes from control and cAMP-treated hepatocytes. PP1 was found to be enriched in plasma membranes, whereas PP2A was mostly in the cytosol. Cyclic AMP did not activate either PP1 or PP2A, whereas okadaic acid inhibited primarily PP2A. These results suggest that 1) the effect of cAMP on Na+/TC cotransport is not mediated via either PP1 or PP2A; rather, cAMP-mediated signaling pathway is maintained by PP2A and inhibition of PP2A overrides cAMP-mediated effects, and 2) okadaic acid, by inhibiting PP2A, inhibits cAMP-mediated increases in Na+/TC cotransport by decreasing the ability of cAMP to increase cytosolic [Ca2+]. It is proposed that cAMP-mediated dephosphorylation of Ntcp leads to an increased retention of Ntcp in the plasma membrane, and okadaic acid, by inhibiting PP2A, inhibits cAMP-mediated stimulation of Na+/TC cotransport by reversing the ability of cAMP to increase cytosolic [Ca2+] and to induce Ntcp dephosphorylation.     

Investigating Schizocarp morphology as a taxonomic tool in study of Apiaceae family by utilizing LM and SEM techniques

In present study, the schizocarp morphology of 14 species belonging to Apiaceae family has been investigated. Light microscopy (LM) and scanning electron microscopy (SEM) have been utilized to highlight qualitative and quantitative features of studied species. Variations have been observed in macro‐ and micro‐morphological features such as color, shape, symmetry, length, width, apex, epicuticular projections, surface patterns, anticlinal, and periclinal wall patterns. Schizocarp shapes observed were oval, round, triangular, linear, elliptic, and globose. Fruit was either homomorphic or heteromorphic. Crystalloids, stellate hair, multicellular spines, and platelets were mostly observed epicuticular projections. Surface patterns on the fruit surface were striate, rugulate‐striate, reticulate, and striato‐knotted. Both macro‐ and micro‐morphological characters can serve as an important tool in classifying Apiaceae family at various taxonomic ranks. Substantial variations observed can assist as useful constraints at various taxonomic levels as they provide reliable and constant details. Disparities observed in schizocarp features can pave a path for Apiaceae family classification based on phylogenetic and molecular studies.