Fluorescence in situ hybridization of three oncogenes on a leiomyoma

Using fluorescence in situ hybridization technique, expression of three oncogenes, C-myc, RARa, and cyclin-D was tested on a uterine leiomyoma. C-myc and RARa were amplified in approximately 30% and 90% of the cells, respectively. Numerous small signals of C-myc were indicative of the presence of double minutes. Amplification of RARa is being reported for the first time in a leiomyoma. Cyclin-D was normal in diploid cells while it was highly amplified in polyploid cells. Low levels of amplified C-myc and cyclin-D cells seem to be the reason for this tumor to be benign, while RARa could not be effective without the association of some other gene such as PML. Information presented here are significant toward developing new curative strategies such as gene-specific drugs and molecular manipulation to stop the activity of cancer gene. Further study may elucidate that how fibroids grow and maintain their rare benign nature.     

Stores clustering using a data mining approach for distributing automotive spare-parts to reduce transportation costs

Clustering of retail stores in a distribution network with specific geographical limits plays an important and effective role in distribution and transportation costs reduction. In this paper, the relevant data and information for an established automotive spare-parts distribution and after-sales services company (ISACO) for a 3-year period have been analyzed. With respect to the diversity and lot size of the available information such as stores location, order, goods, transportation vehicles and road and traffic information, three effecting factors with specific weights have been defined for the similarity function: 1. Euclidean distance, 2. Lot size 3. Order concurrency. Based on these three factors, the similarity function has been examined through 5 steps using the Association Rules principles, where the clustering of the stores is performed using k-means algorithm and similar stores are allocated to the clusters. These steps include: 1. Similarity function based on the Euclidean distances, 2. Similarity function based on the order concurrency, 3. Similarity function based on the combination of the order concurrency and lot size, 4. Similarity function based on the combination of these three factors and 5. Improved similarity function. The above mentioned clustering operation for each 5 cases addressed in data mining have been carried out using R software and the improved combinational function has been chosen as the optimal clustering function. Then, trend of each retail store have been analyzed using the improved combinational function and along with determining the priority of the depot center establishment for every cluster, the appropriate distribution policies have been formulated for every cluster. The obtained results of this study indicate a significant cost reduction (32%) in automotive spare-parts distribution and transportation costs.     

Failure analysis of unidirectional polymeric matrix composites with two serial pin loaded-holes

The objective of this study is to investigate the effects of geometrical and physical parameters on failure modes and failure loads in unidirectional polymeric matrix composites with two serial pin loaded holes, analytically and experimentally. It is assumed that all of unidirectional fibers in the laminate lie in one direction while loaded by a load p ₀ at infinity, parallel to the direction of the fibers. To derive equilibrium equations based on a Shear-Lag theory, a rectangular arrangement of fibers is considered and with the proper use of boundary and boundness conditions, stress and displacement fields are computed within the laminate, along with the surrounding pinholes. Finally by using the Hashin criterion failure modes and failure loads are estimated. To validate analytical results based on shear-lag theory, an experimental program is carried out. A very good agreement is observed between two procedures. Based on results, in small sizes of two pins, the dominant failure mode is bearing and with the increasing of hole sizes, failure modes are changed to tension and shear modes.     

Behavior of square concrete columns reinforced with Prefabricated Cage System

Behavior of normal strength concrete columns reinforced with a new reinforcement, termed Prefabricated Cage System (PCS) is investigated. A total of 16 small-scale PCS and rebar reinforced column specimens were constructed and tested under monotonic axial displacement. The experimental results indicate that the overall behavior of rebar and PCS reinforced specimens are comparable prior to achieving the peak column load. In general, PCS specimens are more ductile and absorb more energy than similar rebar specimens after the peak load is reached. The effect of different parameters, such as the steel tube thickness, number of longitudinal reinforcements, transverse steel spacing, and crossties on the specimens’ strength and deformation capacity are investigated. A confined concrete model is proposed and used to predict the load–displacement response. The theoretical load–displacement relations obtained from the proposed model are compared with those obtained from the Mander et al. (J Struct Eng 114(8):1804–1826, 1988) confinement model.     

Synthesis and Physical Properties of Mn Doped ZnO Dilute Magnetic Semiconductor Nanostructures

Mn doped ZnO nanostructures have been prepared using low temperature simple, quick, and versatile synthesis approach. The structural, microstructural, and vibrational investigations reveal that as prepared nanostructures with low Mn doping concentration have single hexagonal phase and are grown along the preferred c-axis. The X-rays photoelectron spectroscopy demonstrates that the Mn ions are in mixed oxidation states for high doping concentration of Mn, while are in 2+ oxidation state for low concentration into ZnO lattice. The photoluminescence spectrum (PL) exhibits a significant red-shift of 22 nm in the optical band gap of doped ZnO and shows the improved luminescence properties, which makes it potential for its use in the photocatalyst, optoelectronics and solar cell nanodevices. Furthermore, the magnetic measurement of Mn doped ZnO nanostructures exhibits the ferromagnetism at room temperature.     

Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning.Specifically,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation speed.Diffractive deep neural networks(D²NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D²NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and imaging.Here,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning.After independently training 1252 D²NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D²NNs that collectively improved the image classification accuracy.Through this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D²NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D²NNs within each ensemble.These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.     

Light Spectral Composition Modifies Polyamine Metabolism in Young Wheat Plants

Although light-emitting diode (LED) technology has extended the research on targeted photomorphogenic, physiological, and biochemical responses in plants, there is not enough direct information about how light affects polyamine metabolism. In this study, the effect of three spectral compositions (referred to by their most typical characteristic: blue, red, and the combination of blue and red [pink] lights) on polyamine metabolism was compared to those obtained under white light conditions at the same light intensity. Although light quality induced pronounced differences in plant morphology, pigment contents, and the expression of polyamine metabolism-related genes, endogenous polyamine levels did not differ substantially. When exogenous polyamines were applied, their roborative effect were detected under all light conditions, but these beneficial changes were correlated with an increase in polyamine content and polyamine metabolism-related gene expression only under blue light. The effect of the polyamines on leaf gene expression under red light was the opposite, with a decreasing tendency. Results suggest that light quality may optimize plant growth through the adjustment of polyamine metabolism at the gene expression level. Polyamine treatments induced different strategies in fine-tuning of polyamine metabolism, which were induced for optimal plant growth and development under different spectral compositions.     

Selection of the optimum decomposition level using the discrete wavelet transform for automobile suspension system

Journal of Mechanical Science and Technology - This paper discusses the determination of the optimum decomposition level by using the discrete wavelet transform (DWT) method for an automobile...     

The effect of some alloying elements on the corrosion resistance of lead-antimony alloys — II. Silver

The effect of Ag on the stationary and non-stationary anodic corrosion rates of PbSbCd and PbSb alloys in H₂SO₄ has been studied. Anodic polarization curves were constructed under galvanostatic and potentiostatic conditions. Optical microscopic examination and microprobe analysis of the alloys were conducted. The beneficial effect of Ag was ascribed to a delay in closure of pores in the initial PbSO₄ film. The leaching out of Sb from the outermost layers and the simultaneous nucleation of PbSO₄ and Ag₂SO₄ from supersaturated solutions in the pores is thus made possible.