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.     

Moisture Sensitive Smart Yarns and Textiles from Self‐Balanced Silk Fiber Muscles

Smart textiles that sense, interact, and adapt to environmental stimuli have provided exciting new opportunities for a variety of applications. However, current advances have largely remained at the research stage due to the high cost, complexity of manufacturing, and uncomfortableness of environment‐sensitive materials. In contrast, natural textile materials are more attractive for smart textiles due to their merits in terms of low cost and comfortability. Here, water fog and humidity‐driven torsional and tensile actuation of thermally set twisted, coiled, plied silk fibers, and weave textiles from these silk fibers are reported. When exposed to water fog, the torsional silk fiber provides a fully reversible torsional stroke of 547° mm^?1. Coiled‐and‐thermoset silk yarns provide a 70% contraction when the relative humidity is changed from 20% to 80%. Such an excellent actuation behavior originates from water absorption‐induced loss of hydrogen bonds within the silk proteins and the associated structural transformation, which are corroborated by atomistic and macroscopic characterization of silk and molecular dynamics simulations. With its large abundance, cost‐effectiveness, and comfortability for wearing, the silk muscles will open up additional possibilities in industrial applications, such as smart textiles and soft robotics.     

Influence of Y~(3+),Yb~(3+),Gd~(3+) cations on structural and electromagnetic properties of CuFe_2O_4 nanoferrites prepared via one step sol-gel method

Rare earths(REs) play a key role in distorting spinel structure by creating some defects at the lattice sites and make them suitable for magnetodielectric applications.In the present study,the nanoferrites of CuRE_(0.02)Fe_(1.98)O_4,where REs=Y~(3+),Yb~(3+),Gd~(3+),were prepared using one step sol-gel method.The prepared samples are copper ferrite(CFO),yttrium doped copper ferrite(Y-CFO),ytterbium doped copper ferrite(Yb-CFO) and gadolinium doped copper ferrite(Gd-CFO),respectively.The single-phase structure of all the REs doped nanoferrites was determined by X-ray diffraction(XRD) analysis.The porosity,agglomerations and grain size of the REs doped copper ferrite were examined using field emission scanning electron microscopy(FESEM) analysis.Fourier transform infrared spectroscopy(FTIR)elaborates the phase formation and environmental effects on the REs doped nanoparticles(NPs).The recorded room temperature M-H loops from a vibrating sample magnetometer(VSM) elucidate the magnetic properties of the REs doped spinel nanoferrites.The magnetic saturation(M_s) was calculated in the range of 23.08 to 51.78 emu/g.The calculated coercivity values(272.6 to 705.60 Oe) confirm the soft magnetic behavior of REs doped copper ferrites.Furthermore,the electromagnetic and dielectric properties were assessed using a Vector network analyzer(VNA) from 1 to 6 GHz.The permeability,permittivity,dielectric tangent loss and electric modulus of the REs doped spinel ferrites illustrate that the prepared NPs may be suitable for microwave and high frequency applications.     

BUILDING USER TASK SPACE BY MINING TEMPORALLY PROXIMATE DESKTOP ACTIONS

Awareness of the user's current context, that is, the task the user resides in, can allow for various ways of supporting their work. In this article we present a novel approach for mining user's regular tasks on the basis of temporal proximity of users’ desktop actions without user intervention in a completely automatic, unobtrusive, and unsupervised manner. The proposed method is based on time-based clustering of a user's desktop actions and, in contrast to previous approaches, it does not enforce fixed time constraints on the mined actions, and typical transition times, when they exist, emerge from the logged activity data for that specific user. The performance of our technique was evaluated on a large data set of 724 days of desktop work by five knowledge workers. The results showed that our approach performed very well and was able to cluster those temporally proximate user actions that commonly used fix time window techniques fail to deal with. Notably, the main improvement is in the recall of the tasks, where our approach recalled 10.18% more actions than the predefined time window technique.     

Effect of Loading History on Stress Corrosion Cracking of 7075-T651 Aluminum Alloy in Saline Aqueous Environment

An experimental study of stress corrosion cracking (SCC) was conducted on 7075-T651 aluminum alloy in a chromate-inhibited, acidic 3.5 pct sodium chloride aqueous solution using compact tension specimens with a thickness of 3.8 mm under permanent immersion conditions. The effects of loading magnitude, overload, underload, and two-step high-low sequence loading on incubation time and crack growth behavior were investigated. The results show that the SCC process consists of three stages: incubation, transient crack growth, and stable crack growth. The incubation time is highly dependent on the load level. Tensile overload or compressive underload applied prior to SCC significantly altered the initiation time of corrosion cracking. Transition from a high to a low loading magnitude resulted in a second incubation but much shorter or disappearing transient stage. The stable crack growth rate is independent of stress intensity factor in the range of 10 to 22 MPa ?{textm} . sqrt {text{m}} .     

Estimation of stresses in atmospheric ice during aeolian vibration of power transmission lines

Aeolian vibration in bare and iced cable was simulated using the theory of cable vibration. High frequency vibration creates stresses in the cable and consequently in the ice covering that cable, which may result in ice failure and eventually ice shedding. These stresses were estimated in this study. Displacement of the cable during vibration was determined; furthermore, instantaneous wind loads in vertical and transverse directions, additional stresses induced by the motion in the cable and in the atmospheric ice, as well as torque due to cable springback were calculated. In order to simulate the loading conditions of a chunk of atmospheric ice in the middle of a span, a new model was developed using ABAQUS. Results from this model show in spite of high frequency vibration, the resulting level of stress in atmospheric ice is far less than its failure limit. In other words, the atmospheric ice under the condition assumed in this investigation does not shed due to aeolian vibration.     

Controllable Synthesis of NiSe<Subscript>2</Subscript> Nanostructures via Hydrothermal Process for Photocatalytic and Solar Cell Applications

This paper reports on the synthesis of rice-like NiSe₂ nanoparticles via a simple hydrothermal method by employing [bis(2-hydoxyacetophenato)nickle(II)], [Ni(HAP)₂], as a novel nickel precursor. Effect of nickel source on morphology and size of nanostructures was also investigated. Moreover, the as-synthesized NiSe₂ nanostructures were utilized as the photocatalyst for the degradation of methylene blue (MB) and as the counter electrode in dye-sensitized solar cells. The results showed that structures size and morphology have salient effect on solar cells and using rice-like NiSe₂ nanoparticles leads to an increase in DSSCs efficiency compared to agglomerated sphere-like particles from 6.04 to 8.99?% (~49?% improvement).     

Power management and nonlinear control of a fuel cell–supercapacitor hybrid automotive vehicle with working condition algorithm

This paper deals with the problem of controlling a multi-source system applied in hybrid electrical vehicles. The system consists of a proton exchange membrane fuel cell (PEMFC) and a super capacitor (SC). Fuel cell (FC) provides energy for load as a main power source, and SC helps the system in a load peak or in fast transients. The system is modeled as Port controlled Hamiltonian (PCH), and interconnection and damping assignment passivity based controller (IDA-PBC) is used for a typical hybrid vehicle. The aim is first to support the load power in all circumstances without interruption by combination of FC and SC production, and second to control the DC bus voltage. The purposed system analyzed under standard driving cycle consists of off-load, over-load, and charging conditions of SC. Simulations are accomplished in MATLAB/Simulink software for validation of control strategy and new represented algorithm. The results illustrate that both control method and algorithm can manage power among PEMFC, SC, and the load whereas the DC bus voltage remains near its reference.     

Leaching of a zinc ore and concentrate using the Geocoat™ technology

In this study, the Geocoat™ technology was used for the extraction of zinc from a mineral concentrate obtained from the Kooshk mine (Yazd, Iran) by a culture dominated by the mesophilic bacterium Acidithiobacillusferrooxidans in a packed column bioreactor. A low grade sphalerite ore was used as support for the concentrate coating. During the 100 days of leaching pH, Fe³⁺, Fe^total, microbial population density and zinc extraction were measured. The final zinc extraction from concentrate and low grade support was 97% and 78%, respectively, and it was found that leaching from the support does not proceed significantly before leaching from the coating is completed.