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This work describes a novel approach for Al-7.5Si/Al-18Si liquid–liquid bimetal casting in sand and metallic moulds. The aim of the work is to facilitate and develop a simple procedure to produce an Al-7.5Si/Al-18Si bimetallic material with a smooth gradient interface structure. The procedure involves the theoretical calculation of total solidification time (TST) of the first liquid metal (M1), pouring the liquid metal (M1), and allowing it to solidify; then, before complete solidification, the second liquid metal (M2) is introduced into the mould. This novel approach has been proven to produce Al-7.5Si/Al-18Si bimetal materials using liquid–liquid casting. The optimum time interval of Al-7.5Si/Al-18Si bimetal casting with modulus of cast Mc ≤ 1 was estimated based on subtracting 5–15 s or 1–5 s from TST of M1 for sand and metallic moulds, respectively. Future work will involve determining the appropriate time interval range for castings having modulus ≥ 1 using the current approach. [ABSTRACT FROM AUTHOR]

Much effort has recently been expended in developing efficient models that can depict the true picture for COVID-19 mortality data and help scientists choose the best-fit models. As a result, this research intends to provide a new G family for both theoretical and practical scientists that solves the concerns typically encountered in both normal and non-normal random events. The new-G distribution family is able to generate efficient continuous univariate and skewed models that may outperform the baseline model. The analytic properties of the new-G family and its sub-model are investigated and described, as well as a theoretical framework. The parameters were estimated using a classical approach along with an extensive simulation study to assess the behaviour of the parameters. The efficiency of the new-G family is discussed using one of its sub-models on COVID-19 mortality data sets. [ABSTRACT FROM AUTHOR]

Nano-structured Mo/Fe intermetallics were synthesized from precursors that contained 72/28% and 30/70% molar ratios of Mo/Fe, which were given as precursors A and B, respectively. These precursors were prepared from the co-precipitation of aqueous hot solutions of ammonium heptamolybdate tetrahydrate (AHM) and ferrous oxalate. The dry precipitates were thermally treated using TG-DSC to follow up their behavior during roasting, in an Ar atmosphere of up to 700 °C (10° K/min). The TG profile showed that 32.5% and 55.5% weight losses were measured from the thermal treatment of precursors A and B, respectively. The DSC heat flow profile showed the presence of endothermic peaks at 196.9 and 392.5–400 °C during the thermal decomposition of the AHM and ferrous oxalate, respectively. The exothermic peak that was detected at 427.5 °C was due to the production of nano-sized iron molybdate [Fe2(MoO4)3]. An XRD phase analysis indicated that iron molybdate was the only phase that was identified in precursor A, while iron molybdate and Fe2O3 were produced in precursor B. Compacts were made from the pressing of the nano-sized precursors, which were roasted at 500 °C for 3 h. The roasted compacts were isothermally reduced in H2 at 600–850 °C using microbalance, and the O2 weight loss that resulted from the reduction reactions was continuously recorded as a function of time. The influence of the reduction temperature and precursor composition on the reduction behavior of the precursors was studied and discussed. The partially and completely reduced compacts were examined with X-ray powder diffraction (XRD), a reflected light microscope (RLM), and a scanning electron microscope (SEM-EDS). Depending on the precursor composition, the reduction reactions of the [Fe2(MoO4)3] and Fe2O3 proceeded through the formation of intermediate lower oxides, prior to the production of the MO/Fe intermetallic alloys. Based on the intermediate phases that were identified and characterized at the early, intermediate, and final reduction degrees, chemical reaction equations were given to follow up the formation of the MoFe and MoFe3 intermetallic alloys. The mechanism of the reduction reactions was predicted from the apparent activation energy values (Ea) that were computed at the different reduction degrees. Moreover, mathematical formulations that were derived from the gas–solid reaction model were applied to confirm the reduction mechanisms, which were greatly dependent on the precursor composition and reduction temperature. However, it can be reported that nano-structured MoFe and MoFe3 intermetallic alloys can be successfully fabricated via a gas–solid reaction technique at lower temperatures. [ABSTRACT FROM AUTHOR]

Modifying the existing probability models in the literature and introducing new extensions of the existing probability models is a prominent and interesting research topic. However, in the most recent era, the extensions of the probability models via trigonometry methods have received great attention. This paper also offers a novel trigonometric version of the Weibull model called a new alpha power cosine-Weibull (for short, "NACos-Weibull") distribution. The NACos-Weibull distribution is introduced by incorporating the cosine function. Certain distributional properties of the NACos-Weibull model are derived. The estimators of the NACos-Weibull model are derived by implementing the maximum likelihood approach. Three simulation studies are provided for different values of the parameters of the NACos-Weibull distribution. Finally, to demonstrate the effectiveness of the NACos-Weibull model, three applications from the hydrological and engineering sectors are considered. [ABSTRACT FROM AUTHOR]

Iron oxide and silica nanoparticles were individually incorporated in tin-based Babbitt alloy and combined to prepare a novel class of nanocomposites for bearing material applications. The route of liquid metallurgy in combination with the stirring technique was adopted to manufacture nanocomposites. Microstructural evolution and mechanical property evaluation were performed by optical and electron microscopy, EDS, hardness, compression, and wear tests. The morphology of the Cu6Sn5 phase was changed from elongated to spherical in the microstructures of nanocomposites. The solitary addition of 0.5 wt% iron oxide nanoparticles improved the hardness and compressive strength but adversely affected the wear properties by increasing the weight loss and friction coefficient value. In contrast, the addition of 0.5 wt% silica nanoparticles could not significantly increase the hardness and compressive strength but it could improve the tribological properties by reducing the weight loss and friction coefficient value. Tin-based Babbitt alloy showed a compressive strength of 89.22 ± 0.50 MPa after the addition of 0.5 wt% iron oxide showing a rise of ~11%. The combined effect of the addition of both types of nanoparticles showed considerable results, i.e., a rise of ~7.9% (86.75 ± 0.68 MPa). The balanced approach of incorporating dual reinforcements of 0.25 wt% iron oxide and 0.25 wt% silica nanoparticles intermediately improved the hardness, compressive strength, and decreased weight loss. [ABSTRACT FROM AUTHOR]

A fully parametric accelerated failure time (AFT) model with a flexible, novel modified exponential Weibull baseline distribution called the extended exponential Weibull accelerated failure time (ExEW-AFT) model is proposed. The model is presented using the multi-parameter survival regression model, where more than one distributional parameter is linked to the covariates. The model formulation, probabilistic functions, and some of its sub-models were derived. The parameters of the introduced model are estimated using the maximum likelihood approach. An extensive simulation study is used to assess the estimates' performance using different scenarios based on the baseline hazard shape. The proposed model is applied to a real-life right-censored COVID-19 data set from Sudan to illustrate the practical applicability of the proposed AFT model. [ABSTRACT FROM AUTHOR]

The development of nanomaterials and nanotechnology enables the production of nanosized metallic alloys with advanced characteristics from their oxides via a thermal reduction technique. The aim of the present work was to produce metallic iron, nickel, and tungsten through the gaseous reduction of nanosized metal oxide powders as a preliminary step towards the fabrication of nanosized heavy tungsten alloys with unique properties. Nanosized NiO, Fe2O3, and WO3 were isothermally and non-isothermally reduced with H2, and the oxygen weight loss was continuously recorded as a function of time. The Thermogravimetric TG-DTA technique was applied in the non-isothermal reduction up to 1000 °C. The reduction extents were calculated from the TG curve, whereas the accompanying heat of the reaction was measured from the DTA curve. The results revealed that NiO was reduced at <420 °C, Fe2O3 was reduced at <600 °C, and WO3 was reduced at >950 °C. In the isothermal process, metal oxides were reduced with H2 at 700–1000 °C; a micro-force balance was used and the O2 weight loss was continuously recorded. At a given temperature, the rate of reduction increased in the order NiO > Fe2O3 > WO3. The nano-oxide powders and the reduced products were physically and chemically characterized. The activation energy (Ea) values were computed from the isothermal reduction in the initial and later stages to elucidate the corresponding reduction mechanism. The Ea values indicated that the reduction of metal oxides was controlled by the gas diffusion mechanism at both the initial and later stages of reduction. The results of the present study determined the optimal operation parameters at which the thermal gaseous reduction technique could be applied for preparing metallic alloys from nanosized metal oxides. [ABSTRACT FROM AUTHOR]

Security is a vital parameter to conserve energy in wireless sensor networks (WSN). Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy data transmission. But the available routing techniques do not involve security in the design of routing techniques. This study develops a novel statistical analysis with dingo optimizer enabled reliable routing scheme (SADO-RRS) for WSN. The proposed SADO-RRS technique aims to detect the existence of attacks and optimal routes in WSN. In addition, the presented SADORRS technique derives a new statistics based linear discriminant analysis (LDA) for attack detection, Moreover, a trust based dingo optimizer (TBDO) algorithm is applied for optimal route selection in the WSN and accomplishes secure data transmission in WSN. Besides, the TBDO algorithm involves the derivation of the fitness function involving different input variables of WSN. For demonstrating the enhanced outcomes of the SADO-RRS technique, a wide range of simulations was carried out and the outcomes demonstrated the enhanced outcomes of the SADO-RRS technique. [ABSTRACT FROM AUTHOR]

Pre-treated low carbon steel specimens with flux or flux + tin mixture were coated by hot-dip aluminizing process. Al alloy (6061) was melted and hold at 750 °C. Fluxed and pre-tinned low carbon steel samples were dipped in a molten bath for time intervals of 0.5, 1, 2.5 and 3.5 min. Applying double coating processes via tinning-aluminizing techniques facilitated the formation of Fe-Al intermetallic interface and increasing the thickness of homogenous coating layer over the substrate material. The presence of Sn facilitates to great extent the formation of a better interlayer-free bond of residual flux and/or oxides. The fluxed–dipped steel substrates have inhomogeneous distribution of Al alloy coating as well as an interface with residual flux and oxides for dipping time up to 2.5 min. A homogenous distribution with good thickness morphology of the Al alloy coating and homogeneous thin intermetallic interface was achieved for tinned steel substrate at all applied dipping times. The comparison between the pre-tinning and pre-fluxing processes on steel substrates showed a significant effect of tinning over fluxing treatment acting on the thickness layer of Al-coating and interface using a short time dipping. For dipping time up to 2.5 min, the hardness of pre-tinning substrates is greater than that of fluxed ones due to the presence of residual flux and void interface in fluxed steel. [ABSTRACT FROM AUTHOR]

Industries are constantly seeking ways to avoid corrective maintenance in order to reduce costs. Performing regular scheduled maintenance can help to mitigate this problem, but not necessarily in the most efficient way. In many real life applications, one wants to predict the future failure time of equipment or devices that are expensive, or with long lifetimes, to save costs and/or time. In this paper, statistical prediction was studied using the classical and Bayesian approaches based on a unified hybrid censoring scheme. Two prediction schemes were used: (1) a one-sample prediction scheme that predicted the unobserved future failure times of devices that did not complete the lifetime experiments; and (2) a two-sample prediction scheme to predict the ordered values of a future independent sample based on past data from a certain distribution. We chose to apply the results of the paper to the Burr-X model, due to the importance of this model in many fields, such as engineering, health, agriculture, and biology. Point and interval predictors of unobserved failure times under one- and two-sample prediction schemes were computed based on simulated data sets and two engineering applications. The results demonstrate the ability of predicting the future failure of equipment using a statistical prediction branch based on collected data from an engineering system. [ABSTRACT FROM AUTHOR]

Steel products are coated with Aluminum (Al) and Zinc (Zn) alloys to improve their corrosion properties. Bulk steel products are coated in batches; however, steel sheets are coated by a continuous hot-dip galvanizing process. Steel sheets are guided into and out of the molten Al-Zn-Si (AZ) bath with the help of stainless-steel rolls, known as guiding, and sink rolls. These rolls are subjected to excessive surface corrosion with molten AZ bath and, hence, are replaced frequently. The surface deterioration of the immersed rolls has been a long-standing issue in the galvanizing industry. In this study, 316L stainless-steel (SS) rods are immersed in the AZ alloy at 600 °C. The immersion time varied from 1 day to 7 days under the static melt conditions in the iron (Fe)-saturated AZ bath. Microstructural analysis of the immersed SS samples revealed two distinct intermetallic compound (IMC) layers forming between the SS substrate and AZ alloy. The IMC layer 1 (AL-1) formed between the SS substrate and IMC layer 2 (AL-2), growing in thickness from 68 µm to 120 µm within 5 days of immersion. The AL-2, which formed between AL-1 and AZ alloy after 24 h of immersion, then grew in thickness up to 150 µm with an uneven trend. The AL-1 is composed of Fe2Al5 and that of AL-2 is composed of FeAl3 that were predicted by the FactSage thermodynamic analysis. Crack development between AL-1 and AL-2 layers, and disintegration of AL-2 into the AZ bath, are key findings of this study. A drastic hardness increase was observed because the IMC layers produce a hard and brittle sink roll surface. [ABSTRACT FROM AUTHOR]

In this paper, we develop statistical inference of competing risks samples which are collected under a joint Type-II censoring scheme of products with Weibull lifetime distributions. These inferences are drawn from two independent fatal risks and come from two different lines of production with the same facility. The model parameters and the parameters of life (reliability and hazard rate functions) are estimated using maximum likelihood (ML), bootstrap and Bayes methods. Additionally, we constructed asymptotic ML confidence intervals, bootstrap confidence intervals and Bayes credible intervals. Furthermore, the theoretical results are assessed and compared through Monte Carlo simulations. Finally, one real data set is analyzed under the proposed model for illustrative purpose. [ABSTRACT FROM AUTHOR]

Tin matrix nanocomposite coatings containing ZnO and NiO nanoparticles, both individually and combined, were deposited on low carbon steel substrates. The aim was to investigate the effect of reinforcement of nanoparticles on microstructural morphology and thickness of tin coatings, modification in the interfacial layer between coating and substrate, and the corrosion resistance of low carbon steel substrate. Optical and scanning electron microscopy were employed for microstructural observation, while potentiostat-galvanostat was utilized for electrochemical investigation. It was found that the tin nanocomposite coatings with nanoparticles significantly modified the coating thickness, intermetallic layer thickness, and surface corrosion resistance. Coatings through the direct tinning process are considered to be a simple and low-cost route for protecting metallic materials from corrosion, and the presence of ZnO and NiO nanoparticles in tin coatings further increases the corrosion resistance of low carbon steels. [ABSTRACT FROM AUTHOR]

For specialized applications, it is incumbent to develop new materials that enable manufacturers to develop new processes and designs. For better fuel economy, structural integrity, and lightweight applications, the development of bimetallic steel/aluminum (Al) alloys having a strong interfacial bond is required. Therefore, a mild steel/Al-bearing alloy bimetallic composite was investigated in this study. Firstly, a tin (Sn) interlayer was developed between the steel substrate and the Al-bearing alloy by the tinning process. For further improvement in the interfacial integrity, alumina (Al2O3) nanoparticles were added to the Sn powder during the tinning process. Four different wt.% of Al2O3 nanoparticles of 0.25, 0.5, 1, and 1.5 were added and mixed thoroughly with Sn powder before mixing them with flux prior to the tinning process. Finally, molten Al-bearing alloy (Al–Sn-Si–Cu) was poured over the Al2O3 nanoparticles reinforced tinned steel substrate. A cross-section of the steel/Al-bearing alloy bimetallic composite was prepared for optical microscopy (OM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and shear testing. The cross-section microstructure of the steel/Al-bearing alloy bimetallic composite revealed irregular and discontinuous interfacial layers in the case of the low-temperature (170 °C) tinning process. However, a uniform, continuous interfacial layer was fabricated during the tinning process when additional preheat to the steel substrate and tinning process was adopted. It can be reported that low Al2O3 nanoparticles loading (0.25%) and steel substrate preheating were recommended for the better interfacial layer in the steel/Al-bearing alloy bimetallic composite. [ABSTRACT FROM AUTHOR]

Natural computing refers to computational processes observed in nature and human-designed computing inspired by nature. In recent times, data fusion in the healthcare sector becomes a challenging issue, and it needs to be resolved. At the same time, intracerebral haemorrhage (ICH) is the injury of blood vessels on the brain cells, which is mainly liable for stroke. X-rays and computed tomography (CT) scans are widely applied for locating the haemorrhage position and size. Since manual segmentation of the CT scans by planimetry by the use of radiologists is a time-consuming process, deep learning (DL) is used to attain effective ICH diagnosis performance. This paper presents an automated intracerebral haemorrhage diagnosis using fusion-based deep learning with swarm intelligence (AICH-FDLSI) algorithm. The AICH-FDLSI model operates on four major stages namely preprocessing, image segmentation, feature extraction, and classification. To begin with, the input image is preprocessed using the median filtering (MF) technique to remove the noise present in the image. Next, the seagull optimization algorithm (SOA) with Otsu multilevel thresholding is employed for image segmentation. In addition, the fusion-based feature extraction model using the Capsule Network (CapsNet) and EfficientNet is applied to extract a useful set of features. Moreover, deer hunting optimization (DHO) algorithm is utilized for the hyperparameter optimization of the CapsNet and DenseNet models. Finally, a fuzzy support vector machine (FSVM) is applied as a classification technique to identify the different classes of ICH. A set of simulations takes place to determine the diagnostic performance of the AICH-FDLSI model using the benchmark intracranial haemorrhage data set. The experimental outcome stated that the AICH-FDLSI model has reached a proficient performance over the compared methods in a significant way. [ABSTRACT FROM AUTHOR]

In this paper, the exponentiated gamma distribution (EGD) with generalized Type-I hybrid censored data under constant-stress partially accelerated life test (CSPALT) model is considered. The Bayesian and E-Bayesian estimation methods, as well as the maximum likelihood estimation method, are discussed for the parameter of the distribution and the acceleration factor. The E-Bayesian and Bayesian estimates are derived by using the squared error loss (SEL) and the LINEX loss functions. The MCMC method is applied for deriving the Bayesian and then E-Bayesian estimates. Moreover, a real data set is given for the illustrative purpose. After all, an evaluation is performed for the results of the proposed methods. [ABSTRACT FROM AUTHOR]

This article proposes a novel class of bivariate distributions that are completely defined by stating their conditionals as Poisson exponential distributions. Numerous statistical properties of this distribution are also examined here, including the conditional probability mass function (PMF) and moments of the new class. The techniques of maximum likelihood and pseudolikelihood are used to estimate the model parameters. Additionally, the effectiveness of the bivariate Poisson exponential conditional (BPEC) distribution is compared to that of the bivariate Poisson conditional (BPC), the bivariate Poisson (BP), the bivariate Poisson–Lindley (BPL), and the bivariate negative binomial (BNB) distributions using a real-world dataset. The findings of Akaike information criterion (AIC) and Bayesian information criterion (BIC) reveal that the BPEC distribution performs better than the other distributions considered in this study. As a result, the authors claim that this distribution may be used to fit dependent and overspread count data. [ABSTRACT FROM AUTHOR]

We propose a new two-parameter discrete model, called discrete Type-II half-logistics exponential (DTIIHLE) distribution using the survival discretization approach. The DTIIHLE distribution can be utilized to model COVID-19 data. The model parameters are estimated using the maximum likelihood method. A simulation study is conducted to evaluate the performance of the maximum likelihood estimators. The usefulness of the proposed distribution is evaluated using two real-life COVID-19 data sets. The DTIIHLE distribution provides a superior fit to COVID-19 data as compared with competitive discrete models including the discrete-Pareto, discrete Burr-XII, discrete log-logistic, discrete-Lindley, discrete-Rayleigh, discrete inverse-Rayleigh, and natural discrete-Lindley. [ABSTRACT FROM AUTHOR]

For the first time and by using an entire sample, we discussed the estimation of the unknown parameters θ 1 , θ 2 , and β and the system of stress-strength reliability R = P Y < X for exponentiated inverted Weibull (EIW) distributions with an equivalent scale parameter supported eight methods. We will use maximum likelihood method, maximum product of spacing estimation (MPSE), minimum spacing absolute-log distance estimation (MSALDE), least square estimation (LSE), weighted least square estimation (WLSE), method of Cramér-von Mises estimation (CME), and Anderson-Darling estimation (ADE) when X and Y are two independent a scaled exponentiated inverted Weibull (EIW) distribution. Percentile bootstrap and bias-corrected percentile bootstrap confidence intervals are introduced. To pick the better method of estimation, we used the Monte Carlo simulation study for comparing the efficiency of the various estimators suggested using mean square error and interval length criterion. From cases of samples, we discovered that the results of the maximum product of spacing method are more competitive than those of the other methods. A two real‐life data sets are represented demonstrating how the applicability of the methodologies proposed in real phenomena. [ABSTRACT FROM AUTHOR]

In reliability engineering and lifetime analysis, many units of the product fail with different causes of failure, and some tests require stress higher than normal stress. Also, we need to design the life experiments which present methodology for formulating scientific and engineering problems using statistical models. So, in this paper, we adopted a partially constant stress accelerated life test model to present times to failure in a small period of time for Gompertz life products. Also, considering that, units are failing with the only two independent causes of failure and tested under type-I generalized hybrid censoring scheme the data built. Obtained data are analyzed with two methods of estimations, maximum likelihood and Bayes methods. These two methods are used to construct the point and interval estimators with the help of the MCMC method. The developed results are measured and compared under Monte Carlo studying. Also, a data set is analyzed for illustration purposes. Finally, some comments are presented to describe the numerical results. [ABSTRACT FROM AUTHOR]

The bimetal casting process using the liquid–liquid technique was developed to produce a high-quality hyper-eutectic Al–21Si / hypo-eutectic Al–7.5Si alloy bimetal material. Microstructure and microhardness were investigated as a function of the time interval between pouring hypo-eutectic and hyper-eutectic alloys. A bimetal material was successfully fabricated using a liquid–liquid casting technique with a 10 s time interval in a permanent mould casting. A unique structure comprised of hyper-eutectic Al–21Si, hypo-eutectic Al–7.5Si and a eutectic interface of 70 µ m thickness was obtained. This structure totally differs from that obtained using a higher time interval above 10 s that showed an imperfect interface bond due to the shrinkage cavity and formation of oxides. The hardness variation from the upper zone of 117.5 HV to the lower zone of 76 HV corresponded to the variation in Si and the content of other alloying elements. The proposed total solidification time control method is a promising approach for the successful fabrication of liquid–liquid bimetal material. [ABSTRACT FROM AUTHOR]

The purpose of this work is to investigate the effects of carbon black (CB), carbon nanotubes (CNTs) and nanoclay sheets addition on the creep behavior of polyethylene-based nanocomposites synthesized with an in-house processing method. A blend of 75 wt.% UHMWPE and 25 wt.% HDPE, abbreviated to U75H25, was used as the hybrid PE matrix to accommodate the nanofillers. A 0.5 wt.% of CB, CNTs or nanosheets clay was embedded separately into the blend matrix in order to improve the creep resistance. The scanning electron microscope (SEM) and transmission electron microscope showed that the nanofillers were homogeneously dispersed in the U75H25. The addition of just 0.5 wt.% nanoclay resulted in a significant increase in the creep resistance of the polyethylene blend. Conversely, the addition of CB or CNTs caused a reduction in the creep resistance. The embedding of CNTs into the matrix resulted in creep behavior almost close to the creep behavior of pure UHMWPE. The Burger's model was employed to understand the effect of the nanoparticle addition on the creep mechanism. [ABSTRACT FROM AUTHOR]

The purpose of this work is to investigate the effects of graphene nanosheets (GNSs) addition on the mechanical and thermal properties of high density polyethylene (HDPE). The HDPE/Graphene nanocomposites were synthesized using solution blending approach. HDPE was incorporated with graphene nanosheets in a solvent at various weights of fractions (0.1, 0.2, 0.4 and 0.5 wt%), and then the micro-hardness, elastic modulus, tensile strength, strain at break and thermal properties of the nanocomposites were measured and compared. The results showed that the use of Xylene solvent at high temperature combined with mechanical stirring can fully dissolve HDPE pellets. Scanning electron microscope (SEM) showed that GNSs were homogenously dispersed in the polyethylene matrix at low weights of fractions. The addition of just 0.2 wt% GNSs resulted in 100% increase in the micro-hardness value. The elastic modulus and tensile strength properties are proportionally increased with increasing GNSs content up to 0.4 wt%. However, at higher weight of fraction, a reduction in these properties is observed. The crystallinity and strain at break properties are reduced with the addition of GNSs. [ABSTRACT FROM AUTHOR]

The improvement of the surface properties of ferrous metallic materials has become a crucial criterion for advanced engineering applications. The interfacial microstructure and corrosion behaviour of mild steel coated with alumina nanoparticles doped in tin composite using the direct tinning technique were investigated. A coating layer of tin composite containing different loads of Al2O3 nanoparticles (0.25 wt.%, 0.50 wt.%, 1.00 wt.% and 1.5 wt.%) was prepared and directly deposited on a mild steel substrate. This type of a direct tinning process is considered to be a simple and low-cost route for protecting metallic materials from corrosion. It was found that the thickness of both the composite layer and Fe-Sn intermetallic layer at the coated interfaces was highly affected by the presence of alumina nanoparticles that effectively inhibit the diffusion of Sn atoms into the Fe substrate. For the samples coated with lower content of alumina nanoparticles (0.25 wt.% and 0.50 wt.%), the thickness of the Fe-Sn intermetallic coating (IMC) layer is decreased due to Fe-Sn IMC suppression. Otherwise, for the addition of more alumina nanoparticles (1.00 wt.% and 1.50 wt.%), the thickness of the Fe-Sn IMC layer is slightly increased because of nanoparticle's agglomeration and flotation. It can be reported that the presence of alumina nanoparticles in the coating layer improves, to a great extent, the corrosion resistance of Sn-composites surface on mild steel substrates. Although the tin composite coating layer with a high quantity of alumina nanoparticles (1.0 wt.%) exhibited better corrosion resistance than the other tested samples, such nanoparticle additions have become increasingly difficult to obtain. It was observed that the Al2O3 nanoparticles agglomeration and flotation that were detected in the coating surface may be related to high fraction nanoparticles loading and to the difference in the gravity for Sn and Al2O3 nanoparticles. However, based on our investigation, a coating layer that contains 0.50 wt.% alumina nanoparticles is highly recommended for achieving long lasting and high-performance corrosion resistance for coated mild steel with minimal coating layer defects. [ABSTRACT FROM AUTHOR]

Interfacial bonding highly affects the quality of bimetallic bearing materials, which primarily depend upon the surface quality of a solid metal substrate in liquid–solid compound casting. In many cases, an intermediate thin metallic layer is deposited on the solid substrate before depositing the liquid metal, which improves the interfacial bonding of the opposing materials. The present work aims to develop and optimize the tinning process of a solid carbon steel substrate after incorporating flux constituents with the tin powder. Five ratios of tin-to-flux—i.e., 1:1, 1:5, 1:10, 1:15, and 1:20—were used for tinning process of carbon steel solid substrate. Furthermore, the effect of volume ratios of liquid Al-based bearing alloy to solid steel substrate were also varied—i.e., 5:1, 6.5:1 and 8.5:1—to optimize the microstructural and mechanical performance, which were evaluated by interfacial microstructural investigation, bonding area determination, hardness and interfacial strength measurements. It was found that a tin-to-flux ratio of 1:10 offered the optimum performance in AlSn12Si4Cu1/steel bimetallic materials, showing a homogenous and continuous interfacial layer structure, while tinned steels using other percentages showed discontinuous and thin layers, as in 1:5 and 1:15, respectively. Furthermore, bimetallic interfacial bonding area and hardness increased by increasing the volume ratio of liquid Al alloy to solid steel substrate. A complete interface bonding area was achieved by using the volume ratio of liquid Al alloy to solid steel substrate of ≥8.5. [ABSTRACT FROM AUTHOR]

Sn-based Babbitt alloy was reinforced with alumina nanoparticles to prepare a novel class of nanocomposites. The route of liquid metallurgy in combination with stirring mechanism was chosen to prepare nanocomposites with three different loadings of alumina nanoparticles, i.e., 0.25 wt%, 0.50 wt% and 1.0 wt%. The molten mixture of metallic matrix and nanoparticles was poured over carbon steel substrate for solidification to manufacture a bimetallic material for bearing applications. The underlying aim was to understand the effect of nanoparticle addition on microstructural variation of Sn-based Babbitt alloy as well as bimetallic microstructural interface. The addition of 0.25 wt% and 0.50 wt% alumina nanoparticles significantly affected both the morphology and distribution of Cu6Sn5 hard phase in solid solution, which changed from needle and asterisk shape to spherical morphology. Nanocomposites containing up to 0.50 wt% nanoparticles showed more improvement in tensile strength than the one containing 1.0 wt% nanoparticles, due to nanoparticle-agglomeration and micro-cracks at the interface. The addition of 0.5 wt% nanoparticles significantly improved the wear resistance of Sn-based Babbitt alloy. [ABSTRACT FROM AUTHOR]

Background: Cervical cancer is the third most common malignancy in women worldwide, and it remains a leading cause of cancer-related death for women in developing countries Aim and objectives: the aim of the paper is to assess and increase the awareness toward cancer cervix, early detection and prevention of risk factors among Saudi males and females. Materials and Methods: a cross-sectional descriptive study was carried out among 740 Saudi males and females above the age of 16 years. The participants were randomly enrolled in this study. Results: the participants 446 (60.3%) females and 294 (39.7%) males were included in the study. Majority of the participants (n= 547, 73.9%) have heard about cervical cancer but most of them didn't know that it is a preventable disease (n= 359, 48.5%). We found that; only 17.6% of the study group has heard about HPV Vaccine. It could be attributed to low level of knowledge about the virus itself, since only 19.9% of the population knew about the virus. Conclusion: there is a great need to increase the educational standards of the society and improve the information and knowledge about this important disease to reduce the number of patients as well as raising the health status of the populations. [ABSTRACT FROM AUTHOR]

Objective: To determine whether the post-operative complication rate of thyroidectomy can be reduced using surgical loupes to identify parathyroid gland and recurrent laryngeal nerve (RLN) with simultaneous intraoperative neuromonitoring of RLN., Methods: This retrospective chart review was conducted from December 2012 to March 2013 at the Ear, Nose, Throat, and Head-Neck Department of King Saud Hospital, Riyadh, Kingdom of Saudi Arabia. The study group included patients who underwent primary thyroid surgeries performed from July 2007 to September 2011, older than 16 years old, without history of vocal cord palsy, hypocalcemia, and sternotomy. Patient outcomes were analyzed with emphasis on complication rates related to the procedure, operative duration, use of drain, and length of hospital stay., Results: Eighty-eight patients underwent thyroid surgeries during our study period. Sixty-one underwent total thyroidectomy. Temporary hypocalcemia accounted for 14 (15.9%), and permanent hypocalcemia accounted for 5 (5.7%) of the patients. None of the patients showed vocal cord paralysis, wound infections, or thyroid crisis post-operatively. The length of hospital stay was 2-7 days., Conclusion: Careful neuromonitoring of the RLN nerve using surgical loupes will minimize post-surgical complications, decrease hospital stay, and eventually improve surgery outcomes.