Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

This study proposes a novel prediction approach for human breast and colon cancers using different feature spaces. The proposed scheme consists of two stages: the preprocessor and the predictor. In the preprocessor stage, the mega-trend diffusion (MTD) technique is employed to increase the samples of the minority class, thereby balancing the dataset. In the predictor stage, machine-learning approaches of K-nearest neighbor (KNN) and support vector machines (SVM) are used to develop hybrid MTD-SVM and MTD-KNN prediction models. MTD-SVM model has provided the best values of accuracy, G-mean and Matthew's correlation coefficient of 96.71%, 96.70% and 71.98% for cancer/non-cancer dataset, breast/non-breast cancer dataset and colon/non-colon cancer dataset, respectively. We found that hybrid MTD-SVM is the best with respect to prediction performance and computational cost. MTD-KNN model has achieved moderately better prediction as compared to hybrid MTD-NB (Naïve Bayes) but at the expense of higher computing cost. MTD-KNN model is faster than MTD-RF (random forest) but its prediction is not better than MTD-RF. To the best of our knowledge, the reported results are the best results, so far, for these datasets. The proposed scheme indicates that the developed models can be used as a tool for the prediction of cancer. This scheme may be useful for study of any sequential information such as protein sequence or any nucleic acid sequence.     

End-to-End 2D Convolutional Neural Network Architecture for Lung Nodule Identification and Abnormal Detection in Cloud

The extent of the peril associated with cancer can be perceived from the lack of treatment, ineffective early diagnosis techniques, and most importantly its fatality rate. Globally, cancer is the second leading cause of death and among over a hundred types of cancer; lung cancer is the second most common type of cancer as well as the leading cause of cancer-related deaths. Anyhow, an accurate lung cancer diagnosis in a timely manner can elevate the likelihood of survival by a noticeable margin and medical imaging is a prevalent manner of cancer diagnosis since it is easily accessible to people around the globe. Nonetheless, this is not eminently efficacious considering human inspection of medical images can yield a high false positive rate. Ineffective and inefficient diagnosis is a crucial reason for such a high mortality rate for this malady. However, the conspicuous advancements in deep learning and artificial intelligence have stimulated the development of exceedingly precise diagnosis systems. The development and performance of these systems rely prominently on the data that is used to train these systems. A standard problem witnessed in publicly available medical image datasets is the severe imbalance of data between different classes. This grave imbalance of data can make a deep learning model biased towards the dominant class and unable to generalize. This study aims to present an end-to-end convolutional neural network that can accurately differentiate lung nodules from non-nodules and reduce the false positive rate to a bare minimum. To tackle the problem of data imbalance, we oversampled the data by transforming available images in the minority class. The average false positive rate in the proposed method is a mere 1.5 percent. However, the average false negative rate is 31.76 percent. The proposed neural network has 68.66 percent sensitivity and 98.42 percent specificity.     

Binary phase solid-state photopolymerization of acrylates: design,characterization and biomineralization of 3D scaffolds for tissue engineering

Porous polymer scaffolds designed by the cryogel method are attractive materials for a range of tissue engineering applications. However, the use of toxic crosslinker for retaining the pore structure limits their clinical applications. In this research, acrylates (HEA/PEGDA, HEMA/PEGDA and PEGDA) were used in the low-temperature solid-state photopolymerization to produce porous scaffolds with good structural retention. The morphology, pore diameter, mineral deposition and water absorption of the scaffold were characterized by SEM and water absorption test respectively. Elemental analysis and cytotoxicity of the biomineralized scaffold were revealed by using XRD and MTT assay test. The PEGDA-derived scaffold showed good water absorption ability and a higher degree of porosity with larger pore size compared to others. XRD patterns and IR results confirmed the formation of hydroxyapatite crystals from an alternative socking process. The overall cell proliferation was excellent, where PEGDA-derived scaffold had the highest and the most uniform cell growth, while HEMA/PEGDA scaffold showed the least. These results suggest that the cell proliferation and adhesion are directly proportional to the pore size, the shape and the porosity of scaffolds.     

Sign Language to Sentence Formation: A Real Time Solution for Deaf People

Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular words such as I, eat, drink, home are unalike the plural words as school, cars, players. A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately. Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration. The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment. Hence, there is still a demand for specific environment to automate such a communication solution to interact with such type of special people. This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words. Finally, these are converted into the respective words/sentences within a reasonable time. This provide a real time solution for the deaf people to communicate and interact with the society.     

工艺参数设置和厚度对电子束熔融加工Ti-6Al-4V合金微观结构的影响

研究了试件尺寸和工艺参数(电子束强度,扫描速度,焦点偏移量和扫描长度)对电子束熔融(EBM)加工Ti-6Al-4V合金微观结构的影响。结果表明,可以观察到EBM加工的Ti-6Al-4V合金的微观结构由原始β相的柱状晶粒组成。在柱状晶粒内部观察到典型的(α+β)结构,即魏氏体α片和在细小的α晶粒的界面上形成的杆状β相。还发现沿原始β柱状晶粒的晶界形成的α层晶界。随着试件厚度、电子束能量密度和扫描长度的增加,先前的β柱状晶粒的直径增大,并且生长的方向与加工方向一致。同时,柱状晶粒直径随着试件高度的增加而减小。随着试件厚度和电子束能量密度的增加,α片会变得更粗大。     

N‐halamine‐modified polyglycolide (PGA) multifilament as a potential bactericidal surgical suture: In vitro study

In this study, new cationic homopolymer and anionic copolymer were synthesized, and deposited onto polyglycolide sutures using a layer‐by‐layer assembly technique. The coated sutures were rendered antibacterial by chlorinating with dilute solution of household bleach solution at pH 7. The chlorination treatment transformed the N? H groups of anionic copolymer into N‐halamine structures. The N‐halamine‐modified sutures were challenged with Staphylococcus aureus and Escherichia coli O157:H7 bacteria at different contact times. The suture with chlorine loading of 0.22% completely inactivated both bacterial strains in 30 min contact time. Fourier transform infrared spectroscopy, scanning electron microscopy, and analytical titration confirmed the successful deposition of the N‐halamine multilayers. The effect of layer‐by‐layer coatings of polyelectrolytes on the chlorine loading and antibacterial efficacy of sutures was evaluated. The straight‐pull and knot‐pull strength tests performed on the sutures reported slight decline in tensile properties after chlorination treatment. The in vitro hemolysis and cytocompatibility tests revealed that the N‐halamines‐based antibacterial sutures were biocompatible. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42483.     

Enhanced Catalytic,Antibacterial and Anti-cancer Activities of Erythromycin Capped Gold Nanoparticles

Journal of Inorganic and Organometallic Polymers and Materials - In this study, the nanosized spherical erythromycin capped gold nanoparticles (eryth-Au(0)NPs) were fabricated for the first time....     

Two new Protecting Groups for the Guanidino Function of arginine

Two new synthons, Fmoc-L-Arg(biphenyl-4-sulphonyl)-OH ( 8 ) and Fmoc-Arg(4-methoxy-3-t-butylbenzenesulphonyl)-OH ( 14 ), are prepared for the synthesis of arginine-containing peptides. These groups are cleaved by commonly employed trifluoroacetic acid and methanesulphonic acid. Kinetic studies reveal that extended bicyclic aromatic conjugation, as in biphenyl, slightly improves the acid lability compared to the electron-donating t-butyl group.     

Pollen morphology and its taxonomic potential in some selected taxa of Caesalpiniaceae observed under light microscopy and scanning electron microscopy

Pollen micromorphology is not only used to check the functional and structural evolution in plants but also to solve the taxonomic problem related to the classification of plants. Therefore, keeping in view the significance of pollen traits, selected taxa of the subfamily Caesalpiniaceae was collected from different geographical regions of Pakistan. The species were then analyzed under both light microscopy and scanning electron microscopy techniques to investigate the importance of micromorphological characters of pollen in the identification and classification of species. Great variation was recorded in equatorial shape, surface ornamentation, tectum, polar diameter, equatorial diameter, and exine thickness. However, little variation was observed in pollen type, polar shape, and fertility of pollen. The equatorial shape of five types was observed: prolate, prolate-spheroidal, spheroidal-subprolate, subspheroidal-prolate, and subspheroidal. Four types of surface ornamentation, psilate, granulate, clavate, and perforate, were recorded. Tectum of five types, intactate, reticulate regulate, medium reticulate, tactate, and striate, was observed. Sexine was thicker than nexine in all studied species. The largest polar diameter was observed in Caesalpinia pulcherrima 64.1 μm while the smallest in Parkinsonia aculeata 26.1 μm. The largest equatorial diameter was found in C. pulcherrima of 70.25 μm whereas the smallest in P. aculeata 27.57 μm. All the pollens analyzed were tricolporate. All studied species have a fertility ratio of more than 90%. A taxonomic key was developed to show the variation in pollen features and delimit species for the correct identification. In conclusion, the pollen traits were found useful to define species boundaries at various taxonomic ranks and will strengthen the taxonomy of this subfamily. Besides, this study also explored the palynological traits and their implication in the taxonomy of the subfamily Caesalpiniaceae.