A comparison of two algorithms for the assignment problem

State-of-the-art computational results have shown that the shortest augmenting path (SAP) methods are more efficient than other primal-dual and primal-simplex based methods for solving the linear assignment problem on uniprocessor computers. There is, however, some controversy concerning their merits when compared with Bertsekas' auction algorithm on multiprocessor computers. In this study we investigate the performance of these competing methods on the Alliant FX/8. For each method, theoretical motivation, sources of parallelism and computational results are presented.     

Lie-group method solution for two-dimensional viscous flow between slowly expanding or contracting walls with weak permeability

The non-linear equations of motion describing the laminar, isothermal and incompressible flow in a rectangular domain bounded by two weakly permeable, moving porous walls, which enable the fluid to enter or exit during successive expansions or contractions, are considered. We apply Lie-group method for determining symmetry reductions of partial differential equations. Lie-group method starts out with a general infinitesimal group of transformations under which given partial differential equations are invariant, then, the determining equations are derived. The determining equations are a set of linear differential equations, the solution of which gives the infinitesimals of the dependent and independent variables. After the group has been determined, a solution to the given partial differential equation may be found from the invariant surface condition such that its solution leads to similarity variables that reduce the number of independent variables in the system. Effect of the permeation Reynolds number R_e and the dimensionless wall dilation rate α on self-axial velocity have been studied both analytically and numerically and the results are plotted.     

Drug–Membrane Interaction on Immobilized Liposome Chromatography Compared to Immobilized Artificial Membrane (IAM), Liposome/Water,and Octan‐1‐ol/Water Systems

The objective of this study was to investigate drug–membrane interaction by immobilized liposome chromatography (ILC; expressed as lipophilicity index log K_s) and the comparison with lipophilicity indices obtained by liposome/H₂O, octan‐1‐ol/H₂O, and immobilized artificial membrane (IAM) systems. A set of structurally diverse monofunctional compounds and drugs (nonsteroidal anti‐inflammatory drugs and β‐blockers) were selected in this study. This set of solutes consists of basic or acidic functionalities which are positively or negatively charged at physiological pH 7.4. No correlation was found between log K_s from ILC and lipophilicity indices from any of the other membrane model systems for the whole set of compounds. For structurally related compounds, significant correlations could be established between log K_s from ILC and lipophilicity indices from IAM chromatography and octan‐1‐ol/H₂O. However, ILC and liposome/H₂O systems only yield parallel partitioning information for structurally related large molecules. For hydrophilic compounds, the balance between electrostatic and hydrophobic interactions dominating drug partitioning is different in these two systems.     

Synthesis of Some Novel Imidazopyrazole and Pyrazolopyrimidine Derivatives

5‐Amino‐3‐anilino‐1H‐pyrazole‐4‐carbonitrile 1 was alkylated with various halo reagents under phase transfer conditions to give the corresponding imidazopyrazole derivatives 2a , 2b , 2c , 3 , 4 , 5 , 6 . Pyrazolo[1,5‐a] pyrimidine derivatives 11 , 12 , 13 , 14 were prepared by treating compound 1 with different dicarbonyl reagents, namely, diethymalonate, ethyl 3‐oxo‐3‐phenylpropanoate, pentane‐2,4‐dione or ethyl 3‐oxobutanoate.     

All optical Flip-Flop based on a nonlinear DFB semiconductor laser: Theoretical study

A new design of an all optical Flip-Flop is proposed. It consists of a nonlinear distributed feedback (DFB) laser. The wave guiding layer of the DFB laser consists of linear grating section followed by a nonlinear one, and both sections are separated by a phase shift section. In the OFF-state, the real part of the refractive index in the wave guiding layer forms a Bragg grating. In the ON-state, it forms a Bragg grating with a phase shift section. Optical gain is achieved by current injection in the semiconductor active layer. Nonlinearity in the nonlinear layers of the semiconductor grating was achieved by direct absorption at the edge of the absorption band (Urbach tail). Numerical simulation shows that the device switches in a nanosecond time scale.     

Compression Helps Deep Learning in Image Classification

The impact of JPEG compression on deep learning (DL) in image classification is revisited. Given an underlying deep neural network (DNN) pre-trained with pristine ImageNet images, it is demonstrated that, if, for any original image, one can select, among its many JPEG compressed versions including its original version, a suitable version as an input to the underlying DNN, then the classification accuracy of the underlying DNN can be improved significantly while the size in bits of the selected input is, on average, reduced dramatically in comparison with the original image. This is in contrast to the conventional understanding that JPEG compression generally degrades the classification accuracy of DL. Specifically, for each original image, consider its 10 JPEG compressed versions with their quality factor (QF) values from {100,90,80,70,60,50,40,30,20,10}. Under the assumption that the ground truth label of the original image is known at the time of selecting an input, but unknown to the underlying DNN, we present a selector called Highest Rank Selector (HRS). It is shown that HRS is optimal in the sense of achieving the highest Top k accuracy on any set of images for any k among all possible selectors. When the underlying DNN is Inception V3 or ResNet-50 V2, HRS improves, on average, the Top 1 classification accuracy and Top 5 classification accuracy on the whole ImageNet validation dataset by 5.6% and 1.9%, respectively, while reducing the input size in bits dramatically—the compression ratio (CR) between the size of the original images and the size of the selected input images by HRS is 8 for the whole ImageNet validation dataset. When the ground truth label of the original image is unknown at the time of selection, we further propose a new convolutional neural network (CNN) topology which is based on the underlying DNN and takes the original image and its 10 JPEG compressed versions as 11 parallel inputs. It is demonstrated that the proposed new CNN topology, even when partially trained, can consistently improve the Top 1 accuracy of Inception V3 and ResNet-50 V2 by approximately 0.4% and the Top 5 accuracy of Inception V3 and ResNet-50 V2 by 0.32% and 0.2%, respectively. Other selectors without the knowledge of the ground truth label of the original image are also presented. They maintain the Top 1 accuracy, the Top 5 accuracy, or the Top 1 and Top 5 accuracy of the underlying DNN, while achieving CRs of 8.8, 3.3, and 3.1, respectively.     

Mangostanaxanthone VIII,a new xanthone from Garcinia mangostana and its cytotoxic activity

A new prenylated xanthone, mangostanaxanthone VIII (7) and six known metabolites: gartanin (1), 1,3,8-trihydroxy-2-(3-methyl-2-butenyl)-4-(3-hydroxy-3-methylbutanoyl)-xanthone (2), rubraxanthone (3), 1,3,6,7-tetrahydroxy-8-prenylxanthone (4), garcinone C (5), and xanthone I (9-hydroxycalabaxanthone) (6) were separated from the EtOAc-soluble fraction of the air-dried pericarps of Garcinia mangostana (Clusiaceae). Their structures have been verified on the basis of spectroscopic data analysis as well as comparison with the literature. The cytotoxic activity of 7 was assessed against MCF7, A549, and HCT116 cell lines using sulforhodamine B (SRB) assay. Compound 7 showed significant cytotoxic potential against MCF7 and A549 cell lines with IC₅₀s 3.01 and 1.96 μM, respectively compared to doxorubicin (0.06 and 0.44 μM, respectively). However, it exhibited moderate activity towards HCT116 cell line.     

Eco-friendly solvent-free synthesis of thiazolylpyrazole derivatives

Highly versatile ethyl 3-thiosemicarbazidobutanoate was ball-milled with phenacyl bromide to afford the corresponding ethyl 3-[(4-phenyl-2-thiazolyl)hydrazono]butanoate which underwent heterocyclization by heating in ethanolic sodium acetate to give thiazolylpyrazolone that coupled chemoselectively with aromatic diazonium salts to furnish arylhydrazonothiazolylpyrazoles. Vilsmeier-Haack reaction of ethyl 3-thiosemicarbazidobutanoate furnished selectively thiazolylpyrazole. A series of pyrazolylthiosemicarbazones were synthesized by solid-state technique which allowed waste-free production. The reaction of pyrazolylthiosemicarbazones with phenacyl bromide afforded the corresponding 2-(arylidenehydrazino)-4-phenylthiazoles in quantitative yields. Correspondence: Samir Bondock, Department of Chemistry, Faculty of Science, Mansoura University, ET-31556 Mansoura, Egypt.     

Electrical characteristics and chemical stability of non-oxidized, methyl-terminated silicon nanowires

Silicon nanowires (Si NWs) modified by covalent Si-CH3 functionality, with no intervening oxide, show atmospheric stability, high conductance values, low surface defect levels, and allow for the formation of air-stable Si NW Field-Effect Transistors (FETs) having on-off ratios in excess of 105 over a relatively small gate voltage swing (+/-2 V).     

The Synergistic Hepatoprotective Activity of Rosemary Essential Oil and Curcumin: The Role of the MEK/ERK Pathway

Background: Curcumin is a natural product obtained from the rhizome of Curcuma longa. Rosemary (Rosmarinus officinalis) is a medicinal and aromatic plant that is widely spread in the Mediterranean region. Both Curcumin and rosemary essential oil are natural products of high medicinal and pharmacological significance. The hepatoprotective effect of both natural products is well-established; however, the mechanism of such action is not fully understood. Thus, this study is an attempt to explore the hepatoprotective mechanism of action of these remedies through their effect on MEK and ERK proteins. Furthermore, the effect of rosemary essential oil on the plasma concentration of curcumin has been scrutinized. Materials and methods: The major constituents of REO were qualitatively and quantitatively determined by GC/MS and GC/FID, respectively. Curcumin and rosemary essential oil were given to mice in a pre-treatment model, followed by induction of liver injury through a high dose of paracetamol. Serum liver enzymes, lipid peroxidation, antioxidant activities, the inflammatory and apoptotic biomarkers, as well as the MEK and ERK portions, were verified. The plasma levels of curcumin were determined in the presence and absence of rosemary essential oil. Results: The major constituents of REO were 1,8-cineole (51.52%), camphor (10.52%), and α-pinene (8.41%). The results revealed a superior hepatoprotective activity of the combination when compared to each natural product alone, as demonstrated by the lowered liver enzymes, lipid peroxidation, mitigated inflammatory and apoptotic biomarkers, and enhanced antioxidant activities. Furthermore, the combination induced the overexpression of MEK and ERK proteins, providing evidence for the involvement of this cascade in the hepatoprotective activity of such natural products. The administration of rosemary essential oil with curcumin enhanced the curcuminoid plasma level. Conclusion: The co-administration of both curcumin and rosemary essential oil together enhanced both their hepatoprotective activity and the level of curcumin in plasma, indicating a synergistic activity between both natural products.