A new feature selection method on classification of medical datasets: Kernel F-score feature selection

In this paper, we have proposed a new feature selection method called kernel F-score feature selection (KFFS) used as pre-processing step in the classification of medical datasets. KFFS consists of two phases. In the first phase, input spaces (features) of medical datasets have been transformed to kernel space by means of Linear (Lin) or Radial Basis Function (RBF) kernel functions. By this way, the dimensions of medical datasets have increased to high dimension feature space. In the second phase, the F-score values of medical datasets with high dimensional feature space have been calculated using F-score formula. And then the mean value of calculated F-scores has been computed. If the F-score value of any feature in medical datasets is bigger than this mean value, that feature will be selected. Otherwise, that feature is removed from feature space. Thanks to KFFS method, the irrelevant or redundant features are removed from high dimensional input feature space. The cause of using kernel functions transforms from non-linearly separable medical dataset to a linearly separable feature space. In this study, we have used the heart disease dataset, SPECT (Single Photon Emission Computed Tomography) images dataset, and Escherichia coli Promoter Gene Sequence dataset taken from UCI (University California, Irvine) machine learning database to test the performance of KFFS method. As classification algorithms, Least Square Support Vector Machine (LS-SVM) and Levenberg–Marquardt Artificial Neural Network have been used. As shown in the obtained results, the proposed feature selection method called KFFS is produced very promising results compared to F-score feature selection.     

Pivotal Role of Phytohormones and Their Responsive Genes in Plant Growth and Their Signaling and Transduction Pathway under Salt Stress in Cotton

The presence of phyto-hormones in plants at relatively low concentrations plays an indispensable role in regulating crop growth and yield. Salt stress is one of the major abiotic stresses limiting cotton production. It has been reported that exogenous phyto-hormones are involved in various plant defense systems against salt stress. Recently, different studies revealed the pivotal performance of hormones in regulating cotton growth and yield. However, a comprehensive understanding of these exogenous hormones, which regulate cotton growth and yield under salt stress, is lacking. In this review, we focused on new advances in elucidating the roles of exogenous hormones (gibberellin (GA) and salicylic acid (SA)) and their signaling and transduction pathways and the cross-talk between GA and SA in regulating crop growth and development under salt stress. In this review, we not only focused on the role of phyto-hormones but also identified the roles of GA and SA responsive genes to salt stress. Our aim is to provide a comprehensive review of the performance of GA and SA and their responsive genes under salt stress, assisting in the further elucidation of the mechanism that plant hormones use to regulate growth and yield under salt stress.     

Effect of phosphoric acid on the performance of low antimony grid of Pb‐acid cell under constant current charging and discharging

Effect of phosphoric acid on the performance of Pb‐1.7%Sb grid of lead‐acid cell is studied in 5 M H₂SO₄ by cyclic galvanostatic polarization and impedance spectroscopy. An increase in capacitance to a maximum is recorded during the initial stages of the electro‐reduction of PbO₂ into Pb(II) compounds and attributed to concurrent compositional and dimensional changes. These changes include removal of O₂ bubbles, insertion of large amounts of H₂SO₄ and H₂O. Efficiency of PbO₂ formation decreases, while its rate of self‐discharge increases with increasing the charging current and in the presence of H₃PO₄. The charge capacity increases with increasing the discharging current due to the decrease in the self‐discharge. The charge capacity is lower in the presence of H₃PO₄. On increasing the cycle number, the corrodibility of the grid increases, because more layers of the surface Pb are involved in the self‐discharge. H₃PO₄ significantly retards the effect of cycle number.     

Synthesis and electrochemical,in situ spectroelectrochemical,electrical and gas sensing properties of ball-type homo- and hetero-dinuclear phthalocyanines with four [1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]furan-7,10-diyl] bridges

The new mono-nuclear Fe^II 2 and ball-type homo-dinuclear Fe^II–Fe^II 3 phthalocyanines have been synthesized from the corresponding 4,4′-(1a,8b-dihydronaphtho[b]naphthofuro[3,2-d]-furan-7,10-diyl)bis(oxy)diphthalonitrile 1 while ball-type hetero-dinuclear Fe^II–Co^II phthalocyanine 4 was synthesized from 2. The compounds have been characterized by elemental analysis, UV–vis, IR and MALDI-TOF-mass spectroscopies. The redox behaviours of the complexes were identified by controlled-potential coulometry, cyclic voltammetry and differential pulse voltammetry measurements on Pt in dimethylsulfoxide containing tetrabutylammonium perchlorate. The assignments of the redox processes and the understanding of the interactions between the metal phthalocyanine units in 3 and 4 were achieved by the combined evaluation of the voltammetric and in situ spectroelectrochemical outcomes. Complex 3 showed ring-based mixed-valence behaviour as a result of the considerable interaction between the phthalocyanine rings. On the other hand, the interactions between the two metal phthalocyanine units of 4 were found to be much weaker than those in 3. The potential application of molecular organic semiconductors needs the control adjustment of conductivity. Ac and dc conductivity measurements were performed with the applied external electric filed. At high frequency, the conduction follows the universal power law and conduction mechanism can be explained by classical hopping barriers mechanism for the system.     

Smart Edge Computing for 5 g/6 g Satellite IOT for Reducing Inter Transmission Delay

Mobile Networks and Applications - 5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via...     

Auction-Based Throughput Maximization in Cognitive Radio Networks Under Interference Constraint

Cognitive radio is an emerging technique to improve the utilization of radio frequency spectrum in wireless communication networks. That is, spectrum efficiency can be increased significantly by giving opportunistic access of the frequency bands to a group of cognitive users to whom the band has not been licensed. In this paper, as a cross layer application (MAC and physical layers) of graph theory, we consider the problem of throughput maximization of spectrum allocation in cognitive radio networks under interference constraint. We propose a novel auction-based channel allocation mechanism which tries to maximize both total and primary users’ utilities while satisfying signal to interference ratio constraint on primary receivers so that transmitted packets will be successfully received, without controlling secondary user powers. For comparison we discuss a greedy algorithm as well, however, one that does not handle interference issue. In order to compare results of proposed and greedy algorithms, we propose net throughput by taking into account outage probability of primary receiver. Simulation results show that exposing higher SINR (outage) threshold not only decreases total gain and primary users’ utilities but also worsens channel distribution performance. On the other hand adding auction mechanism significantly increases total gain throughput and primary user’ s utility. Particularly, up to SINR threshold values of 20 dBs, auction provides outstanding performance and proposed algorithm has total throughput results close to those of the greedy one even though no interference constraint is applied in the greedy algorithm. Another noticeable point of simulation results is crossover of net throughputs of proposed and greedy algorithms at a SINR threshold level after which results of ABSA-UNIC and NASA-UNIC are much better. This clearly shows superiority of proposed mechanism.     

Masking the Peroxidase-Like Activity of the Molybdenum Disulfide Nanozyme Enables Label-Free Lipase Detection

Two-dimensional MoS₂ nanoparticles (2D-nps) exhibit artificial enzyme properties that can be regulated at bio-nanointerfaces. We discovered that protein lipase is able to tune the peroxidase-like activity of MoS₂ 2D-nps, offering low-nanomolar, label-free detection and identification in samples with unknown identity. The inhibition of the peroxidase-like activity of the MoS₂ 2D-nps was demonstrated to be concentration dependent, and as low as 5 nm lipase was detected with this approach. The results were compared with those obtained with several other proteins that did not display any significant interference with the nanozyme behavior of the MoS₂ 2D-nps. This unique response of lipase was characterized and exploited for the successful identification of lipase in six unknown samples by using qualitative visual inspection and a quantitative statistical analysis method. The developed methodology in this approach is noteworthy for many aspects; MoS₂ 2D-nps are neither labeled with a signaling moiety nor modified with any ligands for signal readout. Only the intrinsic nanozyme activity of the MoS₂ 2D-nps is exploited for this detection approach. No analytical equipment is necessary for the visual detection of lipase. The synthesis of the water-soluble MoS₂ 2D-nps is low costing and can be performed in bulk scale. Exploring the properties of 2D-nps and their interactions with biological materials reveals highly interesting yet instrumental features that offer the development of novel bioanalytical approaches.