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There are numerous experimentally validated simulations for mono-dispersed systems in the literature based on discrete element method (DEM). In practice, however, most of granular systems consist of polydispersed assemblies of particles. Few studies have considered the effect of polydispersity, and yet fewer have experimentally validated the results. In this study, application of a new experimental method for granular flow analysis is presented, capable of validating the results of an in-house developed GPU-based DEM solver in both monodispersed and polydispersed assemblies. Silo discharge is chosen as the case study in which discharge time, flow pattern and more importantly, the outlet composition variation with time (for polydispersed configurations) have been experimentally evaluated and validated with numerical results. The outlet composition, which is the ratio of fine to coarse particles in the outlet stream, is an essential measure of segregation in polydispersed silos, and its numerical prediction can be correct only if the interactions between fine and coarse particles within the silo are modelled precisely. Measuring this parameter is not possible using conventional experimental methods established in silo discharge studies such as high speed photographing or high-frequency weight measurement of the bed. A new apparatus has been developed which can measure this parameter. The device is a compartmented wheel rotating with a motor which gathers the outlet stream of the silo into different compartments. Due to practical limitations, design and function of the apparatus are not ideal. Forward mixing, distribution of particles with the same resident time in different compartments, is the most critical problem. Non-idealities must be compensated by means of post-processing codes so that comparable results are obtained from experiment and simulation.

Combustion of heavy fuels is one of the main sources of greenhouse gases, particulate emissions, ashes, NOx and SOx. Gasification is an advanced and environmentally friendly process that generates combustible and clean gas products such as hydrogen. Some entrained flow gasifiers operate with Heavy Fuel Oil (HFO) feedstock. In this application, HFO atomization is very important in determining the performance and efficiency of the gasifiers. The atomization characteristics of HFO (Mazut) discharging from a pressure-swirl atomizer (PSA) are studied for different pressures difference (Δp) and temperatures in the atmospheric ambient. The investigated parameters include atomizer mass flow rate ( m ), discharge coefficient (CD), spray cone angle (θ), breakup length (Lb), the unstable wavelength of undulations on the liquid sheet (λs), global and local SMD (sauter mean diameter) and size distribution of droplets. The characteristics of Mazut sheet breakup are deduced from the shadowgraph technique. The experiments on Mazut film breakup were compared with the predictions obtained from the liquid film breakup model. Validity of the theory for predicting maximum unstable wavelength was investigated for HFO (as a highly viscous liquid). A modification on the formulation of maximum unstable wavelength was presented for HFO. SMD decreases by getting far from the atomizer. The measurement for SMD and θ were compared with the available correlations. The comparisons of the available correlations with the measurements of SMD and θ show a good agreement for Ballester and Varde correlations, respectively. The results show that the experimental sizing data could be presented by Rosin-Rammler distributions very well at different pressure difference and temperatures.

In the present study, the release of zinc (Zn) from polylactic acid/zinc oxid nanoparticles (PLA/ZnO NPs) nanocomposites to three aqueous food simulants (10% ethanol, 20% ethanol and 95% ethanol) was evaluated (during 15 days at 4, 25, and 40 °C) by atomic absorption spectrometry (AAS). The results indicated that temperature and the simulant type affected the migration of Zn and at a constant temperature; the maximum Zn release was observed in the 95% ethanol simulant. Pseudo-Fickian behavior was observed during the diffusion of Zn and diffusion coefficients (D values) of 0.002–6.08 10−11 cm2 s−1 were obtained in different migration conditions. The obtained partition coefficients (K) were between 21.66 and 0.057 μg g−1. The Zn release data were fitted with the Weibull model, and the b and n model parameters had values ranging from 0.008 to 0.07 and 0.24 to 0.49, respectively. The results of the present study indicated that Zn had little migration from PLA films into food simulants (especially in water at 4–40 °C) which was attributed to the high activation energy (Ea) values for Zn diffusion from PLA/ZnO NPs nanocomposites.

Objectives To evaluate efficacy of addition of duloxetine to usual analgesic regimens in management of burn pain. Methods In a 3-week open label randomized controlled trial, burn patients were assigned to the intervention (duloxetine 60 mg/day + usual analgesic regimens) or control group (usual analgesic regimens: morphine ± acetaminophen ± gabapentin). Intensity and quality of background pain and severity of procedural pain were evaluated using neuropathic pain scale (NPS) and visual analog scale (VAS), respectively. The primary outcome measure was “intensity” item of the NPS (evaluating intensity of the background pain). Results Forty six patients (age: 35.5 ± 6.3 years, TBSA: 36.7 ± 15%) (23 per group) completed the study. At baseline, scores of the “intensity” item were 9.13 ± 1.42 and 9.13 ± 1.86 (P = 1) in the intervention and control group, respectively. Comparison of difference in mean changes from baseline to the end of the study showed that addition of duloxetine only significantly reduced the scores of the “intensity” {1.74 (95% CI: 0.61 to 2.86); P = 0.003}, and “hot” {1.39 (95% CI: 0.166 to 2.614) P = 0.02} items and score of the VAS {2.13 (95% CI: 1.476 to 2.784) P Conclusion Addition of duloxetine may increase efficacy of the other analgesics in reduction of the burn pain.

The available SMD (Sauter mean diameter) correlations on pressure-swirl injectors predict droplet sizing very different from each other, especially for heavy fuels. Also there was a lack in the literature for comparing available correlations. So an experimental study was conducted on a heavy fuel oil (HFO) spray, Mazut 380. A pressure swirl injector was designed and fabricated. The experiments for Mazut at 40 °C and 80 °C were compared with the results for water, including spray half cone angle, breakup length and mean droplet diameter, at different injection pressures. Lower spray angle, higher breakup length and larger droplets were observed for lower injection pressures and higher liquid viscosity. SMD was about 75 μm for water and about 87 μm for Mazut at 80 °C. The results for droplet mean diameter were also compared with correlations from previous studies on pressure swirl atomizers. The SMD results show that for water spray, LISA method was in good agreement, also Babu and Ballester correlations were successful when high viscosity fluid was injected.

High energy storage capacity of tin oxide (SnO2) makes it a promising anode material for high capacity lithium (Li)-ion batteries. Previous experiments reported by Nie et al. (2013) and Huang et al. (2010) have shown that SnO2 lithiation occurs in two stages. First, Li diffuses rapidly through distinct narrow stripes along the electrode axis. This is followed by a second stage where the diffusion/amorphization of the nanowire occurs. In order to understand and possibly predict this complex chemo-mechanical phenomenon, a finite element (FE) model is developed in this work. The model captures the formation of the striped diffusion regime and the corresponding expansion of the nanowire during the lithiation of SnO2. The effect of the stress on the Li diffusion is modeled at the macroscopic level by implementing a stress-dependent expression for the diffusion coefficient. The modeling results clearly show the formation of the striped diffusion regime due to the induced stresses, at low concentrations of Li. This results in a small strain of 0.017 within the nanowire followed by a bulk diffusion and expansion at higher Li concentrations. Thus, the model allows for the spatiotemporally resolved analysis of Li diffusion/intercalation and helps predicting its influence on the mechanical performance of the electrode under the realistic operational conditions.

In the current study, the active packaging films based on poly lactic acid (PLA) containing 1.5% w/w zinc oxide (ZnO) nanoparticles and varying concentrations (0.5, 1, 1.5% w/w) of Zataria multiflora Boiss. essential oil (ZEO) and Menthe piperita L. essential oil (MEO) were produced. The efficacies of the resulted active films on shelf life extension of Otolithes ruber fish during 16 days of refrigerated storage (4 ± 1 °C) were evaluated. The antibacterial activity of the films was tested against five common food-borne pathogens (Escherichia coli, Salmonella enterica, Pseudomonas aeruginosa, Bacillus cereus and Staphylococcus aureus) by disc diffusion method. The fillet samples were analyzed periodically for microbiological (aerobic count, Enterobacteriaceae count, Pseudomonas spp., Lactic acid bacteria (LAB) count and H2S-producing bacteria) and chemical (TBARS and TVB-N). PLA/ZnO/ZEO and PLA/ZnO/MEO films showed enhanced antibacterial (691 and 513.33 mm2, repectively, against S. aureus) and antioxidant (69.14 and 49.08%, repectively) activity than control. Based on the microbial count, the active films significantly increased the shelf life of fillets from 8 to 16 days. The lowest TBARS (0.8 mg MA/kg muscle) and TVB-N (21.23 mg/100 g muccle) values were obtained in fillets wrapped with PLA/ZnO containing 1.5% ZEO. Carvacrol and menthone were found to be the main compounds of ZEO and MEO following GC analysis, respectively. Atomic absorption spectrophotometer showed transfer only a minuscule amount of Zn2+ ions to the meat. Overally, the PLA/ZnO films containing the essential oils could be deemed as a potential alternative to the current common technologies for extending the shelf-life of meat products like ‘Otolithes ruber fillets.

In this study, the efficacy of household sanitizers application on reduction of Escherichia coli O157:H7, ascorbic acid, total phenolics, DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging and overall acceptability of inoculated fresh basil leaves (Ocimum basilicum), at temperature of 40 °C was investigated. Sanitizers containing lactic acid (LA), acetic acid (AA) and citric acid (CA) were used at concentration of 2%, individually or in combination with H2O2 (1% or 2%), and NaCl (7%). Control a and b were unwashed and washed leaves with distilled, deionized and sterilized water, respectively. All sanitizing treatments, in comparison to the control a, reduced the numbers of E. coli O157:H7 (0.24 ± 0.12–3.37 ± 0.48 log CFU/g) at day 1 (1 h after sanitizing). The lowest number of E. coli O157:H7 population (2.35 ± 0.26 log CFU/g) was observed by applying the LA + H2O2 (%2) treatment at first day of chilled storage. The highest amount of ascorbic acid (27.77 ± 0.06 mg/100 g), total phenolic (112.2 ± 0.5 mg gallic acid equivalents/100 g) and DPPH radical scavenging activity (95.2 ± 0.5%) was observed in control a at first day (P

The shelf life of quail carcass was examined after imposing separate and combined treatments of spraying with lactic acid (LA, 1% v/v), dipping in chitosan (CH, 1% w/v) and placing the carcass in modified atmosphere package (MAP, 65% CO2 + 30% N2 + 5% O2) at 4 ± 1 °C for 20 days. The control group was packed under similar atmospheric condition but without any antimicrobial agents. Microbiological populations, physicochemical properties and sensory attributes (color, odor and overall appearance) were monitored at 4-day intervals. All antibacterial treatments effectively lowered microbial numbers, compared to the control during chilled storage. The total viable count, as an indicator of meat spoilage, on day 8 of the storage in treated samples was 0.5–3.4 log CFU/g which was lower than the control. The weakest and strongest effects were caused by LA and LA + CH + MAP treatments, respectively. Similar impact intensity occurred in other microbial tests during refrigerated storage. Binary combination treatments of MAP and chitosan showed synergistic effects on controlling microbial growth, and had no significant difference with LA + CH + MAP. Evaluations on days 4 and 8 showed that all treatments significantly controlled microbial growth, pH value, peroxide value and reactive substances of thiobarbituric acid in comparison with the control (P 7) during the entire chilled storage. It is noteworthy that organoleptic evaluations correlated well with physicochemical and microbiological data. Based on microbiological data and the overall appearance results of the carcasses, the shelf lives of the control, LA, CH, MAP, LA + MAP, LA + CH, CH + MAP and LA + CH + MAP samples were 6, 7, 11, 12, 12, 15, 20 and 20 days, respectively, under chilled conditions.

This study investigated the effects of different particle sizes of sterilized wheat bran (100–200, 200–300 and 300–400 μm), their replacement levels at 5, 10, and 15% (based on flour w/w) and also their fermentation by Saccharomyces cerevisiae PTCC 5052 on the qualities of Tafton bread. Measurements indicated how these parameters affected pH, TTA, phytic acid, protein, ash, fat, soluble and insoluble dietary fiber contents in sterilized wheat bran samples. The volume of dough samples and the sensory properties of Tafton bread samples were examined. The lowest amount of phytic acid (2.0 ± 0.12%) was observed in fermented sterilized wheat bran (FSWB) which had particle sizes of 100–200 μm (p

Many experimental and computational studies have identified key protein coding genes in initiation and progression of esophageal squamous cell carcinoma (ESCC). However, the number of researches that tried to reveal the role of long non-coding RNAs (lncRNAs) in ESCC has been limited. LncRNAs are one of the important regulators of cancers which are transcribed dominantly in the genome and in various conditions. The main goal of this study was to use a systems biology approach to predict novel lncRNAs as well as protein coding genes associated with ESCC and assess their prognostic values. By using microarray expression data for mRNAs and lncRNAs from a large number of ESCC patients, we utilized “Weighted Gene Co-expression Network Analysis” (WGCNA) method to make a big coding-non-coding gene co-expression network, and discovered important functional modules. Gene set enrichment and pathway analysis revealed major biological processes and pathways involved in these modules. After selecting some protein coding genes involved in biological processes and pathways related to cancer, we used “LncTar”, a computational tool to predict potential interactions between these genes and lncRNAs. By combining interaction results with Pearson correlations, we introduced some novel lncRNAs with putative key regulatory roles in the network. Survival analysis with Kaplan-Meier estimator and Log-rank test statistic confirmed that most of the introduced genes are associated with poor prognosis in ESCC. Overall, our study reveals novel protein coding genes and lncRNAs associated with ESCC, along with their predicted interactions. Based on the promising results of survival analysis, these genes can be used as good estimators of patients' survival, or even can be analyzed further as new potential signatures or targets for the therapy of ESCC disease.

In the last century, the emergence of in silico tools has improved the quality of healthcare studies by providing high quality predictions. In the case of COVID-19, these tools have been advantageous for bioinformatics analysis of SARS-CoV-2 structures, studying potential drugs and introducing drug targets, investigating the efficacy of potential natural product components at suppressing COVID-19 infection, designing peptide-mimetic and optimizing their structure to provide a better clinical outcome, and repurposing of the previously known therapeutics. These methods have also helped medical biotechnologists to design various vaccines; such as multi-epitope vaccines using reverse vaccinology and immunoinformatics methods, among which some of them have showed promising results through in vitro, in vivo and clinical trial studies. Moreover, emergence of artificial intelligence and machine learning algorithms have helped to classify the previously known data and use them to provide precise predictions and make plan for future of the pandemic condition. At this contemporary review, by collecting related information from the collected literature on valuable data sources; such as PubMed, Scopus, and Web of Science, we tried to provide a brief outlook regarding the importance of in silico tools in managing different aspects of COVID-19 pandemic infection and how these methods have been helpful to biomedical researchers.

Porphyry copper deposits are the world's largest source of copper, but their ultimate source and deep process are disputed. We compare the Sr/Y ratios and Nd isotopes of coeval ore-bearing and ore-barren intermediate rocks from collisional and subduction settings to unravel the sourced depth and nature. During the Miocene mineralization epoch in the Iranian plateau, the median Sr/Y ratios and the median eNd(T) values of ore-bearing rocks (56 ± 38, 1.1 ± 1.5) are slightly higher than those of the ore-barren rocks (30 ± 31, −0.3 ± 2.4), respectively. Such patterns also exist at mineralization epochs during the Miocene collision in the eastern Gangdese, and the early Cretaceous subduction in Southeast China. These results indicate that all ore-bearing and ore-barren rocks are from the thickened (>1.2 Gpa) juvenile dominated (>70% mantle contribution) lower crust, and the ore-bearing rocks are sourced from slightly deeper and more juvenile sources compared to the coeval ore-barren rocks. The subtle geochemical difference but contrasting ore-potentials indicate heterogeneous origins, and the ore-bearing rocks may be related to ore-enriched sources at the lower crust. A deep crustal hot zone with melting at different depths with heterogeneous sources can account for such phenomena. Delamination of a thickened orogenic root induces asthenosphere upwelling and generates abnormal heat flow in the lower crust. The porphyry mineralization is an indication of the balancing between the melting of thickened lower crust and mantle upwelling, which explains the rarity of mineralization compared to the prolonged orogenic magmatism.

The mass and surface stress loadings in microcantilever-based sensors, caused by surface adsorption of target analytes/biomolecules, change their resonance behavior. Despite numerous efforts, the mechanisms of surface stress impact on the resonance behavior of microcantilevers are not fully understood. This results in substantial discrepancies between theoretically predicted and experimentally measured resonance frequency shifts in wide microcantilevers with aspect ratios (width-to-thickness) larger than 10, commonly found in chemical and biological sensing applications. This also impedes the proper decoupling of the effects of mass and surface stress loading and hinders the development of accurate microcantilever-based sensors. In this work, we attempt to decrease the discrepancy found between theoretical models and experiments by introducing a new mechanism that correlates the nonlinear geometric effects associated with surface stress-induced variation of microcantilever biaxial curvature to its frequency and modal responses, with a correlation intensity that strongly depends on the microcantilever aspect ratio. A new comprehensive analytical model combining the new mechanism with currently available theoretical models is proposed and used to study the resonance behavior of microcantilevers with different deformations and sizes. Using the new model, it is shown that in wide microcantilevers, the theoretically predicted resonance frequency shifts agree with experimental and finite element simulations results within 30% whereas the predictions by other currently available theoretical models are off by more than one order of magnitude. The new model is also used to investigate the modal response of microcantilevers where it anticipates the bending-extensional mode coupling associated with the flexural vibration modes of microcantilevers with a coupling strength that depends on the microcantilever curvature. The presented model is expected to provide a new tool to decouple the effects of mass and surface stress loadings on the resonance behavior of microcantilevers used in chemical and biological sensors.

Head and Neck Squamous Cell Carcinoma (HNSCC) is the sixth most common cancer worldwide, which accounts for approximately 6% of all cases and is responsible for an estimated 2% of all cancer deaths. Despite progress in the treatment of squamous cell carcinomas, survival rates remain low. It is a fact that epigenetic modifications have numerous associations with biological processes and complex diseases such as cancer. Hence, a more systematic approach is needed to provide potential screening targets and have an effective therapy method. This study developed a workflow to analyze HM450 methylation arrays with mRNA expression profiles that identified novel signatures of epigenetic regulators for tumor progression. We identified differentially expressed genes and differentially methylated regions and the correlation between associated genes to identify epigenetic modifications underlying regulation roles. We have taken the differentiation direction of expressions into account during the integration of gene expression and DNA methylation modification to detect epigenetic regulators of core genes of tumor-stage progression. Enrichment analysis of selected key genes provides better insight into their functionality. Thus, we have investigated gene copy number alteration and mutations to filter differentially expressed genes, including some members of the fibroblast growth factor family and cyclin-dependent kinase inhibitor family with other potential known regulators. Our analysis has revealed the list of 61 commercial methylation probes positively correlated with 31 differentially expressed genes, which can be associated with HNSC metastasis stages. Most of these genes have already reported potential epigenetic regulators, and their role in cancer progression was studied. We suggest these selected probes of DNA methylation as potential targets of the epigenetic regulators in revealed genes that have displayed significant genetic and epigenetic modification behavior during cancer stage progression and tumor metastasis.

Cancer classification is an important problem in cancer diagnosis and treatment. One of the most effective methods in cancer classification is gene selection. However, selecting a subset of genes which increases the classification accuracy is an NP-Hard problem. A variety of algorithms were proposed for gene selection in cancer classification in previous studies. In this study, a hybrid meta-heuristic algorithm, which is an integration of Genetic Algorithm and Learning Automata (GALA), is proposed for this purpose. The time complexity of GALA is O ( G . m . n 3 ) and it has acceptable accuracy and performance on some well-known cancer datasets. To evaluate the performance of GALA, six different cancer datasets including Colon, ALL_AML, SRBCT, MLL, Tumors_9 and Tumors_11 were selected. Based on the evaluation process, the GALA algorithm provided remarkable results on each dataset compared to some recently proposed algorithms.

Several crosslinked polymeric ionic liquid (PIL)-based sorbent coatings of different nature were prepared by UV polymerization onto nitinol wires. They were evaluated in a direct-immersion solid-phase microextraction (DI-SPME) method in combination with high-performance liquid chromatography (HPLC) and diode array detection (DAD). The studied PIL coatings contained either vinyl alkyl or vinylbenzyl imidazolium-based (ViCnIm- or ViBCnIm-) IL monomers with different anions, as well as different dicationic IL crosslinkers. The analytical performance of these PIL-based SPME coatings was firstly evaluated for the extraction of a group of 10 different model analytes, including hydrocarbons and phenols, while exhaustively comparing the performance with commercial SPME fibers such as polydimethylsyloxane (PDMS), polyacrylate (PA) and polydimethylsiloxane/divinylbenzene (PDMS/DVB), and using all fibers under optimized conditions. Those fibers exhibiting a high selectivity for polar compounds were selected to carry out an analytical method for a group of 5 alkylphenols, including bisphenol-A (BPA) and nonylphenol (n-NP). Under optimum conditions, average relative recoveries of 108% and inter-day precision values (3 non-consecutive days) lower than 19% were obtained for a spiked level of 10 µg L−1. Correlations coefficients for the overall method ranged between 0.990 and 0.999, and limits of detection were down to 1 µg L−1. Tap water, river water, and bottled water were analyzed to evaluate matrix effects. Comparison with the PA fiber was also performed in terms of analytical performance. Partition coefficients (log Kfs) of the alkylphenols to the SPME coating varied from 1.69 to 2.45 for the most efficient PIL-based fiber, and from 1.58 to 2.30 for the PA fiber. These results agree with those obtained by the normalized calibration slopes, pointing out the affinity of these PILs-based coatings.

Aptamers are oligonucleotides with highly structured molecules that can bind to their targets through specific 3-D conformation. Commonly, not all the nucleotides such as primer binding fixed region and some other sequences are vital for aptamers folding and interaction. Elimination of unnecessary regions needs trustworthy prediction tools to reduce experimental efforts and errors. Here we introduced a manipulated in-silico approach to predict the 3-D structure of aptamers and their target interactions. To design an approach for computational analysis of isolated ssDNA aptamers (FLC112, FLC125 and their truncated core region including CRC112 and CRC125), their secondary and tertiary structures were modeled by Mfold and RNA composer respectively. Output PDB files were modified from RNA to DNA in the discovery studio visualizer software. Using ZDOCK server, the aptamer-target interactions were predicted. Finally, the interaction scores were compared with the experimental results. In-silico interaction scores and the experimental outcomes were in the same descending arrangement of FLC112>CRC125>CRC112>FLC125 with similar intensity. The consistent results of innovative in-silico method with experimental outputs, affirmed that the present method may be a reliable approach. Also, it showed that the exact in-silico predictions can be utilized as a credible reference to find aptameric fragments binding potency.

One of the most important health and medical problems in many parts of the world is the spread of infectious diseases and the emergence of extent drug-resistant and innovation such as ESBL. Identification of them requires newer methods. One of the methods for identifying antibiotic resistance classes is Multiplex PCR. The purpose of this study is to identify ESBLs resistant gene using Multiplex PCR technique. In this study, three pair primers for ESBL (TEM, AmpC, KPC) were designed with bioinformatics software. Then, with control positive gene samples set-up of PCR was performed. Finally, additional experiments were performed with negative control samples and 50 isolates of the Escherichia coli isolated from Baqiyatallah hospital. The specificity and sensitivity of designed primers were also investigated. The results of the study showed that primers designed for MBL (SIM, GIM, IND) genes were able to simultaneously identify positive samples containing these genes. The sensitivity of Multiplex PCR for ESBL genes was 1 × 10–14. Also, the results showed that genotypic and phenotypic assays of clinical isolates of Escherichia coli were compatible with each other and the designed primers had good sensitivity (1 pg) and specificity (100%). This study showed that a Multiplex PCR designed with a sensitivity of 1 × 10–14 and a 100% specificity can correctly and fatly detect ESBL genes. Therefore, can suggest appropriate drug and antibiotic resistance to physicians determine the correct drug choice.

The prevalence of hospital acquired infections and antibiotic resistant pathogens necessitates the development of bacteria sensing systems that do not require sample amplification via conventional cell culturing, which can be prohibitively time-consuming. To meet this need, we designed an optofluidic Raman detection platform which utilized a microfluidic driven hollow-core photonic crystal fiber, which in combination with silver nanoparticles, provides a large enhancement to the Raman signal. By confining both light and cells within this fiber, spectral events generated by the flowing cells facilitates a novel method of cell counting to simultaneously quantify and qualify infections. Counting is performed automatically by a genetically optimized support vector machine learning algorithm that was previously developed by our group. The microfluidic system can be regenerated multiple times, and allows for online detection of planktonic bacteria to levels as low as 4 CFU/mL in 15 min. This compares favourably to other methods currently under development such as qPCR and biosensing techniques. Furthermore, Raman spectral differences between bacteria allow for inherent multiplexed detection in serum, by adding another layer to the learning algorithm. Further development of this device has promising potential as a rapid point-of-care system for infection management in the clinic.

The high-dimensionality of microarray data with small number of samples has presented a difficult challenge for the microarray data classification task. The aim of gene selection is to reduce the dimensionality of microarray data in order to enhance the accuracy of the classification task. Existing gene selection methods generally use class labels of the data while due to availability of mislabels or unreliable labels of samples in the microarray data, unsupervised methods could be more essential to the gene selection process. In this paper, we propose an unsupervised gene selection method called MGSACO, which incorporates the ant colony optimization algorithm into the filter approach, by minimizing the redundancy between genes and maximizing the relevance of genes. Moreover, a new fitness function is applied in the proposed method which does not need any learning model to evaluate the subsets of selected genes. Thus, it is classified into the filter approach. The performance of the proposed method is extensively tested upon five publicly available microarray datasets, and it is compared to those of the seven well-known unsupervised and supervised gene selection methods in terms of classification error rates of the three frequently used classifiers including support vector machine, naive Bayes, and decision tree. Experimental results show that MGSACO is significantly superior to the existing methods over different classifiers and datasets. An unsupervised method based on ant colony optimization is proposed for gene selection.A new fitness function is employed to evaluate the subsets of selected genes.The relevant and redundant genes are addressedin the proposed method.The method is compared to the filter methods upon microarray datasets.The results demonstrate that the proposed methodis superior to the existing methods.

In this study thermal behavior of an active cistern is investigated experimentally and numerically for both wind and “no wind” conditions. The cistern is modeled using three-dimensional Finite Volume Method and quasi-steady state condition by considering variations of ambient temperature and intensity and direction of solar radiation. Temperature distributions on the outer surface of the dome and windcatchers are compared with thermography measurements for different hours of a day. Furthermore, natural ventilation caused by the heated dome is calculated by a two-dimensional quasi-steady modeling. The streamlines, velocity vectors, natural plume generated over the dome and temperature distributions are computed for different times during a day. The plume as well as the air motion inside the cistern is determined for different times during a typical day. Natural ventilation through the cistern opening and different wind-catchers are also calculated. Ventilation enhances convection heat transfer which is found non-uniform on the dome. Convection heat transfer coefficient changes between 2–10 W/m2K and 12–37 W/m2K for no-wind and wind-blowing conditions, respectively. The modeling shows that cisterns are appropriate system for storing cool water in hot arid regions.

Cancer has become known as a complex and systematic disease on macroscopic, mesoscopic and microscopic scales. Systems biology employs state-of-the-art computational theories and high-throughput experimental data to model and simulate complex biological procedures such as cancer, which involves genetic and epigenetic, in addition to intracellular and extracellular complex interaction networks. In this paper, different systems biology modeling techniques such as systems of differential equations, stochastic methods, Boolean networks, Petri nets, cellular automata methods and agent-based systems are concisely discussed. We have compared the mentioned formalisms and tried to address the span of applicability they can bear on emerging cancer modeling and simulation approaches. Different scales of cancer modeling, namely, microscopic, mesoscopic and macroscopic scales are explained followed by an illustration of angiogenesis in microscopic scale of the cancer modeling. Then, the modeling of cancer cell proliferation and survival are examined on a microscopic scale and the modeling of multiscale tumor growth is explained along with its advantages.

Lymphoma is one of the most common malignancies in dogs. Canine lymphoma is similar to human non-Hodgkin's lymphoma (NHL) with shared clinical presentation and histopathological features. This study reports the construction of a comprehensive gene regulatory network (GRN) for canine diffuse large B-cell lymphoma (DLBCL), the most common type of canine lymphoma, and performs analysis for detection of major functional modules and hub genes (the most important genes in a GRN). The canine DLBCL GRN was reconstructed from gene expression data (NCBI GEO dataset: GSE30881) using the STRING and MiMI interaction databases. Reconstructed GRNs were then assessed, using various bioinformatics programmes, in order to analyze network topology and identify major pathways and hub genes. The resultant network from both interaction databases had a logically scale-free pattern. Gene ontology (GO) analysis revealed cell activation, cell cycle phase, immune effector process, immune system development, immune system process, integrin-mediated signalling pathway, intracellular protein kinase cascade, intracellular signal transduction, leucocyte activation and differentiation, lymphocyte activation and differentiation as major GO terms in the biological processes of the networks. Moreover, bioinformatics analysis showed E2F1, E2F4, PTEN, CDKN1A, PCNA, DKC1, MNAT1, NDUFB4, ATP5J, PRKDC, BRCA1, MYCN, RFC4 and POLA1 as the most important hub genes. The phosphatidyl inositol signalling system, P53 signalling pathway, Rac CycD pathway, G1/S checkpoint, chemokine signalling pathway and telomere maintenance were the main signalling pathways in which the protein products of the hub genes are involved.

Using fuzzy analytical hierarchy process (AHP) technique, we propose a method for mineral prospectivity mapping (MPM) which is commonly used for exploration of mineral deposits. The fuzzy AHP is a popular technique which has been applied for multi-criteria decision-making (MCDM) problems. In this paper we used fuzzy AHP and geospatial information system (GIS) to generate prospectivity model for Iron Oxide Copper-Gold (IOCG) mineralization on the basis of its conceptual model and geo-evidence layers derived from geological, geochemical, and geophysical data in Taherabad area, eastern Iran. The FuzzyAHP was used to determine the weights belonging to each criterion. Three geoscientists knowledge on exploration of IOCG-type mineralization have been applied to assign weights to evidence layers in fuzzy AHP MPM approach. After assigning normalized weights to all evidential layers, fuzzy operator was applied to integrate weighted evidence layers. Finally for evaluating the ability of the applied approach to delineate reliable target areas, locations of known mineral deposits in the study area were used. The results demonstrate the acceptable outcomes for IOCG exploration.

This study investigates the exact controllability problem for a vibrating non-classical Euler–Bernoulli micro-beam whose governing partial differential equation (PDE) of motion is derived based on the non-classical continuum mechanics. In this paper, it is proved that via boundary controls, it is possible to obtain exact controllability which consists of driving the vibrating system to rest in finite time. This control objective is achieved based on the PDE model of the system which causes that spillover instabilities do not occur.

To update current situation of the cutaneous leishmaniasis (CL) in Kazerun County, southwest of Iran and to analyse the epidemiological aspects of the disease during 2005-2015.Data on CL were obtained from the Health Center of Kazerun County, and then were analysed and mapped using SPSS and Arc GIS 10.3.A total of 700 cases of CL were recorded during the study period with an overall decreasing trend from 2005 to 2015. More than 60% of the patients were inhabitants of rural areas and males were infected more than females. Although there was not a significant difference between gender, job categories, residence and CL infection (P 0.05), age groups were significantly different (P 0.05). But there was no significant correlation between monthly cases of the disease with average temperature (P 0.05). Most of the acute lesions were found to be present on the hand, leg and face, respectively. The average CL incidence in the study area was calculated as 24.9/100000 population. A hot spot for the disease was found in southern part of the area (P 0.05).This study revealed that CL is present in Kazerun country. Thus, effective monitoring and sustained surveillance system is crucial in counteracting the disease, and if possible, to eliminate it.

Epigenetic changes in certain genes have been shown to strongly contribute to the development of Rheumatoid Arthritis (RA) and the behavior of involved cell types. Microarray methylation datasets were used to analyze DNA methylation in RA. Differentially methylated CpGs were selected using the bioinformatics tools and significant CpG islands were further experimentally analyzed. TNFRSF25 was selected based on differentially methylated CpGs island analysis. The results revealed that the promoter region of the TNFRSF25 gene was consistently non-methylated in PBMCs from healthy controls, in RA patients, and in the synovial fluid of RA patients. Therefore, CpG motifs probably play an essential role in the expression and can be used to distinguish between RA patients and healthy individuals.

In this paper, the problem of boundary stabilization of a vibrating non-classical micro-scale Euler–Bernoulli beam is considered. In non-classical micro-beams, the governing Partial Differential Equation (PDE) of motion is obtained based on the non-classical continuum mechanics which introduces material length scale parameters. In this research, linear boundary control laws are constructed to stabilize the free vibration of non-classical micro-beams which its governing PDE is derived based on the modified strain gradient theory as one of the most inclusive non-classical continuum theories. Well-posedness and asymptotic stabilization of the closed loop system are investigated for both cases of complete and incomplete boundary control inputs. To illustrate the performance of the designed controllers, the closed loop PDE model of the system is simulated via Finite Element Method (FEM). To this end, new strain gradient beam element stiffness and mass matrices are derived in this work.

An enhanced thermoset polymer matrix with randomly distributed carbon nanofibers (CNFs) is combined with conventional long fibers to form a hybrid composite material for application to impact energy absorbing components. The multi-inclusion method in combination with functionally graded interphase is used for stiffness characterization and shear-lag theory combined with quasi-isotropic lamination approximation is used for strength prediction. Axial crush simulations are performed using MD Nastran with a micromechanics-based progressive failure analysis constitutive model. The stochastic uncertainties in the geometric and material properties of CNF as well as the three-dimensional, non-homogeneous CNF–matrix interphase are represented using probability theory. Through Monte Carlo simulations, these uncertainties are propagated to the homogenized macroscopic properties of the nano-enhanced matrix and subsequently to the stiffness and strength properties of the composite laminate as well as the energy absorbing characteristics of the crush tube. A probabilistic design optimization problem is formulated for minimizing the failure probability associated with the specific energy absorption of the composite tube. A dual surrogate modeling approach is used for approximating the failure probability and solving the optimization problem using sequential quadratic programming. The modeling approach, uncertainty analysis, and probabilistic optimization results are presented and discussed.

A sequential coupled nonlinear finite element analysis framework is developed to investigate the effects of sheet-forming process and product design parameters on energy absorption characteristics of thin-walled, multicorner tubes made of a magnesium alloy. Coupling stems from the use of analysis results from one simulation to form the initial state in the subsequent simulation. High fidelity coupled process-performance simulations are used in design of computer experiments for developing analytical surrogate models of process and performance responses as functions of product geometry and process parameters. Rupture, thinning and springback are treated as the manufacturing responses whereas mean crush force, maximum crush force, and mass are used as structural performance measures. An integrated process-performance optimization problem is setup and solved using the multi-objective genetic algorithm approach. The results of coupled simulations show the importance of manufacturing effects on the crush response while the Pareto optimal set highlights the tradeoff among process and performance attributes.

In this paper, we study the stabilization problem of vibration of linearized three-dimensional nonlocal micropolar elasticity. For this purpose, we need to demonstrate the well-posedness of the system of equations governing the vibration of three-dimensional nonlocal micropolar media for both forced (i.e. with boundary feedback) and unforced cases. We assume the non-homogeneous system of equations for the unforced (uncontrolled) case to establish the well-posedness. It should be pointed out that the well-posedness of the evolution equations in micropolar case has been studied by many authors; but, the well-posedness in the nonlocal micropolar is an open problem. Our tools in well-posedness analysis are the semigroup techniques. Afterwards, we pursue the stabilization problem and show that the vibration of the nonlocal micropolar elastic media will be eventually dissipated under boundary feedback actions consisting of stress and couple stress feedback laws. These control laws are simple, linear and can be easily implemented in practical applications. The stabilization proof is accomplished using Lyapunov stability and LaSalle’s invariant set theorems.

The crush behavior of polycrystalline metallic square tubes under quasi-static axial loading condition is investigated through a mesoscale crystal plasticity model embedded in an explicit finite element simulation code as a concurrent multiscale model. The boundary value problem is defined at the local continuum scale whereas the material behavior is modeled at the mesoscale through crystal plasticity defined in a representative volume element. The anisotropic behavior of the tubes emerges from the texture induced by the large plastic deformations created during the manufacturing process. In this work, this effect is modeled by considering the texture generated by deforming a single element model with an embedded polycrystalline aggregate of face center cubic (FCC) crystals under basic loading paths, including uniaxial tension, uniaxial compression, and simple shear. This initial texture is then used at each integration point in the explicit crush simulations of a square tube model made of an FCC aluminum alloy. As energy absorption is dominated by the plastic collapse mechanisms at the corner elements, the influence of the initial texture and its evolution during crush are found to be significant.

Quasi-static nonlinear finite element simulations are performed to study the energy absorption characteristics of axially crushed thin-walled aluminum tubes with different multi-cell, multi-corner configurations. By considering the kinematically consistent representation of plastic collapse as observed in the crush simulations, an analytical formula for the mean crush force is derived using the super folding element theory. In this model, the isotropic material is treated as rigid-perfectly plastic and the total internal energy is calculated by considering both bending and membrane deformation during the folding process. The simulation results show a strong correlation between the cross-sectional geometry and the crush response of the tubes. The analytical predictions for the mean crush force are compared with the FE results as well as other analytical models reported in the literature.

In this study, we have investigated the potential of a native bacterial strain isolated from an Iranian oil field for the production of biosurfactant. The bacterium was identified to be Bacillus mycoides by biochemical tests and 16S ribotyping. The biosurfactant, which was produced by this bacterium, was able to reduce the surface tension of media to 34 mN/m. Compositional analysis of the produced biosurfactant has been carried out by thin layer chromatography (TLC) and FT-IR. The biosurfactant produced by the isolate was characterized as lipopeptide derivative. Biosurfactant production was optimized by the combination of central composite design (CCD) and response surface methodology (RSM). The factor selected for optimization of growth conditions were pH, temperature, glucose and salinity concentrations. The empirical model developed through RSM in terms of effective operational factors mentioned above was found to be adequate to describe the biosurfactant production. Through the analysis, glucose and temperature were found to be the most significant factors, whereas pH and salinity had less effect within the ranges investigated. A maximum reduction in surface tension was obtained under the optimal conditions of 16.55 g/l glucose concentration, 39.03 °C, 55.05 g/l total salt concentration and medium pH 7.37.

This paper presents a solution to the boundary stabilization problem of free vibration of composite plates. It is assumed that an object such as a flange which has mass and mass moment of inertia can be attached to the free portion of the boundary of the plate. Both cases of with and without boundary object have been analyzed for other types of plates by many researches. In the presence of boundary mass and mass moment of inertia, two ordinary differential equations govern their motion. For both cases, the plate dynamics is presented by a linear fourth order partial differential equation (PDE). Linear boundary control laws are constructed to stabilize the composite plates asymptotically. The control forces and moments consist of feedbacks of the velocity and normal derivative of the velocity at the boundaries of the plate. Asymptotic stabilization of free vibration of composite plates in both cases (i.e. with and without boundary object) is achieved via boundary actions. Finally, it is shown that exponentially stability of the hybrid system cannot be fulfilled (in the other words the asymptotical stability is the best). Our main tools in this article are semigroup techniques, spectral theory of the linear operators and Lyapunov stability method.

In this paper, the axial stability of single-walled carbon nanopeapods is studied based on an elastic continuum shell model. In order to model the non-bonded van der Waals interactions between host carbon nanotube and guest fullerenes, an equivalent pressure distribution is proposed and incorporated in the model. Deriving an explicit equation for the determination of critical axial load, it is concluded that the axial stability of a single-walled carbon nanopeapod is less than that of a carbon nanotube under otherwise identical conditions. In addition, it is shown that applying external pressure to the carbon nanopeapod decreases the axial compressive stability through reducing the critical axial load and any increase in the external pressure appears to further weaken the carbon nanopeapod under axial loading.

The stability of single-walled carbon nanopeapods under hydrostatic pressure is investigated using a continuum-based elastic shell model. The model incorporates nonbonded van der Waals interactions between the nested fullerenes and the host carbon nanotube. By deriving an explicit equation, it is shown that the critical hydrostatic pressure for the onset of structural instability of a completely packed C 60 @(10,10) nanopeapod is ∼1.11 GPa, while for the case of the pristine host (10,10) nanotube it is ∼1.84 GPa. Thus, it is concluded that the fullerene encapsulation weakens the host nanotube under hydrostatic pressure. In addition, it is quantitatively shown that any decrease in packing density of fullerenes lessens the weakening effect on the total stability of the nanopeapod.

Torsional buckling of carbon nanopeapods (carbon nanotubes filled with fullerenes) is studied using a continuum-based multi-layered shell model. The model takes into account non-bonded van der Waals interactions between nested fullerenes and the innermost layer of host nanotube. For nanopeapods with linearly arranged nested fullerenes, equivalent pressure distribution is proposed to model these interactions. Deriving explicit equations governing the torsional stability, it is concluded that the critical torsional load of a carbon nanopeapod is less than that of a carbon nanotube under otherwise identical geometric and mechanical conditions. Performing numerical calculations, it is also shown that increasing the number of layers of the host carbon nanotube decreases the weakening effect of encapsulated fullerenes on torsional stability of the nanopeapod.

The applications of composite materials have become common in different industries. These materials introduce lower weight, high strength, and viscoelastic properties. Although composite materials offer many advantages in the designing and manufacturing of structures, they cannot replace the wide range of using metallic materials. Most of the industries especially aerospace try to use composite materials together with metal advantages in order to design a safe and optimized structure. The offshore structure can be reinforced and repaired with composite layers. In this research, the effects of composite reinforcement on the dynamic behavior of metallic plates are studied. Several panels are treated with different lay-ups and the modal testing was conducted to evaluate the effect of such treatments. This reinforcing can change both stiffness and damping properties of structures. The stiffness properties of such reinforced plates can be influenced by fiber properties, while the damping properties come from the viscoelastic property of the matrix. Modal testing is applied to the specimens and the modal parameters are derived experimentally. This study shows that using composite material can modify both stiffness and damping characteristics.

In this study the influence of eccentric circular cutouts on the prebuckling and postbuckling stiffness, and effective widths of compression loaded laminated composite plates are presented. The effective-widths concept is derived based on nonlinear finite element analysis for the plates with and without cutout. Several behavioral trends are described that initially appear to be nonintuitive. The results demonstrate a complex interaction between cutout size and the degree of plate orthotropy that affects the axial stiffness and effective width of plate subjected to compression loads. Also these investigations show that the cutout dimension have a more considerable effect on prebuckling stiffness compare to postbuckling one. It will show that the stiffness ratio of the postbuckling over prebuckling is increased by cutout size. Considering the effective-width ratios concept provide a simple means for incorporating the postbuckling strength and stiffness of plate subcomponents into the design of stiffened structures.