A model to predict the survivability of cancer comorbidity through ensemble learning approach

Cancer is one of the most common death causes worldwide. Breast and genital cancers in women and prostate cancer in men constitute three of the most common cancers. Detection and prevention of these types of cancers are critical objectives. Recent findings indicate that some patients suffer from cancer comorbidity. The probability of survival among patients with comorbid condition is lower than those with only one type of cancer. The importance of concomitant chronic illnesses during cancer treatment through the SEER data is assessed through many machine‐learning approaches. In order to improve the accuracy of prediction of survival rates in patients with cancer and comorbidity of cancers, the gradient boosting ensemble method is adopted for feature selection and modelling. This proposed method increases the accuracy rate and reduces the error rate, and exhibits a significant predictive improvement of survival rates in comorbid cancer compared with the previous proposed models.     

Data workflow to incorporate thermodynamic energies from Calphad databases into grand-potential-based phase-field models

Journal of Materials Science - In order to approximate Gibbs energy functions, a semi-automated framework is introduced for binary and ternary material systems, using Calphad databases. To generate...     

Efficiency assessment using a multidirectional DDF approach

This paper proposes a new efficiency measure that aims at capturing the overall distance to the efficient frontier and not the distance corresponding to a specific projection, as most oriented and non‐oriented methods compute. The proposed approach uses a grid‐based method to sample all possible improvement directions from a given operating point and for each direction it computes a directional efficiency score solving a directional distance function model. This provides information about the distribution of the distance to the efficient frontier. Therefore, the proposed multidirectional efficiency measure does not provide a single efficiency score but a distribution of efficiency scores. The minimum, the median, the Q1 and Q3 quartiles and the maximum can be singled out as representatives of that distribution. The latter corresponds to the closest among the computed efficient targets. In addition to the efficiency score distribution, the associated efficient targets are also provided. The proposed approach can take into account integer and nondiscretionary variables and a preference structure. An application of the method to assess the efficiency of material recovery facilities is presented.     

Immunomodulatory properties of selectively processed prawn protein fractions assessed using human peripheral blood mononuclear cells

Prawn muscles were treated with acetic acid and high-pressure processing (600 MPa) separately to analyse their antigenicity and immunogenicity. The protein fractions were separated and isolated using preparative HPLC, and their antigenicity was analysed using Immunoglobulin G (IgG) ELISA kit. Out of thirty-nine protein fractions, only four (A10, A11, B10 and C9) were detected with antigenic potentials. The immunogenicity of these protein fractions was analysed using human PBMCs, and supernatants were collected at multiple times from 0 to 144 h. The treated fractions (B10 and C9) analysed using Immunoglobulin E (IgE) ELISA kit showed significantly (P < 0.05) lower pro- and anti-inflammatory cytokine production compared with control (A10). The allergenic fractions were characterised using an LC/MS/MS, which identified nine proteins. Among these, six proteins (tropomyosin, arginine kinase, haemocyanin, enolase, vitellogenin and 14-3-3 zeta) have been established as allergenic in prawn muscle and ovaries. Other three proteins (beta-1,3-glucan-binding protein, translationally controlled tumour protein and farnesoic acid O-methyltransferase short isoform protein) identified in this study need further investigation for their immunogenic properties.     

Modified carbon paste electrodes for Cu(II) determination

A new Cu²⁺ carbon paste electrode (CPE) using 2,2′-(1E,1′E)-1,1′-(2,2′-azanediylbis (ethane-2,1-diyl)bis(azan-1-yl-1-ylidene))bis(ethan-1-yl-1-ylidene)diphenol (ADEZEDP) has been prepared. The influence of variables including sodium tetraphenylborate (NaTPB), ionophore, and amount of multiwalled carbon nanotubes (MWCNT), CdO nanowires, CdS nanoparticles and palladium nanoparticles loaded on ADEZEDP and Nujol on the electrodes response were studied and optimized. At optimum values of all variables, for each nanomaterial the electrode response was linear in concentration range of 1.0 × 10^? 8 to 1.0 × 10^? 1 mol L^? 1 for ADEZEDP with Nernstian slope. The good performance of electrode viz. Wide applicable pH range (2.0–5.0), fast response time (≈ 6 s), and adequate life time (3 months) indicate the utility of the proposed electrodes for evaluation of Cu²⁺ ion content in various situations. Finally, these electrodes have been successfully applied for the determination of Cu²⁺ ions content in various real samples. The selectivity of proposed electrode was evaluated by separation solution method and fixed interference method.     

3D Nanofabrication of Fluidic Components by Corner Lithography

A reproducible wafer‐scale method to obtain 3D nanostructures is investigated. This method, called corner lithography, explores the conformal deposition and the subsequent timed isotropic etching of a thin film in a 3D shaped silicon template. The technique leaves a residue of the thin film in sharp concave corners which can be used as structural material or as an inversion mask in subsequent steps. The potential of corner lithography is studied by fabrication of functional 3D microfluidic components, in particular i) novel tips containing nano‐apertures at or near the apex for AFM‐based liquid deposition devices, and ii) a novel particle or cell trapping device using an array of nanowire frames. The use of these arrays of nanowire cages for capturing single primary bovine chondrocytes by a droplet seeding method is successfully demonstrated, and changes in phenotype are observed over time, while retaining them in a well‐defined pattern and 3D microenvironment in a flat array.     

A comprehensive study on wastewater treatment using photo-impinging streams reactor: Continuous treatment

The degradation of phenol was investigated in a continuous flow impinging streams system. In the first step, statistical experimental designs were used to optimize the process of phenol degradation in a photo-impinging streams reactor. The more important factors affecting phenol degradation (p<0.05) were screened by a two-level Plackett-Burman design. Four of the latter parameters, namely phenol concentration, catalyst loading, pH and slurry flow rate, were selected for final process optimization, applying central composite design (CCD). The predicted data showed that the maximum removal efficiency of phenol (99%) could be obtained under the optimum operating conditions (phenol concentration=50 mg l ^?1, catalyst loading=2.1 g l ^?1, pH 6.2 and slurry flow rate=550ml min^?1). These predicted values were then verified by certain validating experiments. A good correlation was observed between the predicted data and those determined by the experimental study. This may confirm the validity of the statistical optimum strategy. Finally, continuous degradation of phenol was performed, and the results indicated a higher efficiency and an increased performance capability of the present reactor in comparison with the conventional processes.     

Controlling floodwater mosquitoes by river regulation

Floodwater mosquitoes cause serious problems especially the spread of mosquito‐borne diseases. The main challenge is to implement acceptable general mitigation methods. In recent years, encouraging steps have been taken in favour of developing more sustainable measures such as modern biological methods. The novelty of the present study is in suggesting an alternative green method that can eliminate the use of any secondary biological or chemical agents. The method is based on establishing an alternative river regulation scheme that limits flooding of high‐risk lowland areas. A combined hydrodynamic modelling and optimization method gave effective river regulation schemes. The main idea is to maintain the total power production for a modified inflow hydrograph. The approach was applied to a 30‐km reach of the Österdalälven River located in central Sweden. It was found that with the specific constraints of the site a reduction of about 8% of lowland flood areas is possible if the inflow hydrograph is moderately modified by 20%. Higher reductions are possible by further modification of the hydrograph. The proposed method has a general character controlled by the specific site requirements of a critical flow or a water surface elevation. Based on the foregoing information, the method can be applied to similar sites.     

Statistical optimization of process conditions for photocatalytic degradation of phenol with immobilization of nano TiO<Subscript>2</Subscript> on perlite granules

Response surface methodology (RSM) using D-optimal design was applied to optimization of photocatalytic degradation of phenol by new composite nano-catalyst (TiO₂/Perlite). Effects of seven factors (initial pH, initial phenol concentration, reaction temperature, UV irradiation time, UV light intensity, catalyst calcination temperature, and dosage of TiO₂/perlite) on phenol conversion efficiency were studied and optimized by using the statistical software MODDE 8.02. On statistical analysis of the results from the experimental studies, the optimum process conditions were as follows: initial pH, 10.7; initial phenol concentration, 0.5 mM; reaction temperature, 27 °C; UV irradiation time, 6.5 h; UV light intensity, 250 W; catalyst calcination temperature, 600 °C; and TiO₂/perlite dosage, 6 g/L. Analysis of variance (ANOVA) showed a high coefficient of determination (R²) of 91.8%.