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In a previous research by authors, a methodology was developed to derive J-R curves for Hot Mix Asphalt (HMA) mixtures using an elastic-plastic approach where a comprehensive understanding of crack propagation regime could be achieved. In this research, the effect of crumb rubber modification of HMA binder is studied in terms of R-curves and crack propagation at low temperatures. Mode I Single edge notched beam (SE(B)) fracture tests were conducted in temperature levels of 0 °C, -10 °C, and -20 °C. PG58-22 and PG64-22 binders were used in the fabrication of HMA samples. Modified specimens consist of 20% crumb rubber along with the incorporation of 3% warm mix admixture. Crack growth resistance curves were obtained in SE(B) tests by means of image processing and recording of the progressive crack length. Elastic-plastic J-R curves revealed that crumb rubber modified mixtures exhibit higher crack growth resistance for each bitumen performance grade. As well, increased ductility and cohesive energy can be observed according to the R-curves as the mixtures are modified by crumb rubber.

In this research, a sustainable approach is followed to develop efficient mixtures incorporating recycled fine aggregate (RFA) remained from structure demolition as well as limestone filler (LF) from production of hot mix asphalt (HMA). The LF is a byproduct of the drying process in HMA production plant which is not entirely consumed in the production of the HMA and must be hauled and disposed in landfills. The maximum particle size of the LF is approximately 40 µm. Self-Compacting Concrete (SCC) mixtures were designed replacing 5% and 10% of the cement with LF. Incorporation of 50%, and 100% RFA with the fines in the mixtures were considered with and without addition of the LF. Due to the formwork and prefabrication restrictions, the paste volume and the high range water reducer content were tuned in such a way that the slump flow of the mixtures remained between 660 mm to 700 mm without segregation. Durability and mechanical performance of the mixtures were evaluated by resistance against freeze-thaw scaling exposed to deicing agents and compressive strength. It was observed that the SCC mixtures containing 10% LF outperformed those without the use of LF while 5% SCC mixtures did not exhibit tangible superiority. Incorporation of RFA as the fine fraction degraded the durability of all the mixtures. While replacing all the fine fraction with RFA significantly impaired durability and compressive strength, 50% RF mixtures could be designed containing 10% LF that remained in the allowable limits.

In this paper, a numerical study is presented to investigate wave force on the connections of main parts of a side-anchored straight floating bridge concept for the Bjørnafjorden fjord crossing. The floating bridge is supported by 18 pontoons, and three groups of mooring lines are employed to restrain the bridge against horizontal loads and increase its transverse stiffness. The created wave forces at the connections of pontoon-column and column-girder of the floating bridge considering the effects of short-crested and long-crested waves, varying wave direction, hydrodynamic interaction between pontoons, and mooring system are analyzed. It is found that short-crested and long-crested waves depending on their direction decrease or increase the wave forces on the joints. Considering that the effect of hydrodynamic interaction between pontoons can increase or reduce the wave forces and moments created in the joints, which means the neglect of the hydrodynamic interaction effects between the pontoons to simplify the modeling of this type of floating bridge, may be unacceptable. Moreover, the results showed that the bridge mooring system does not merely reduce the wave forces and moments at joints along the bridge.

This study is part of an environmental experimental program on the use of scrap automobile tires for geotechnical applications. Different types of laboratory tests were conducted to determine the elastic, plastic, and creep parameters of tire derived aggregate (TDA)-sand granulated mixtures. However, this paper emphasizes the plasticity parameters via the development of a critical state model based on the results of triaxial tests. This was attained by considering loose sand specimens, at a predetermined TDA volumetric content, subject to three different confining pressures under a constant axial displacement rate. The calculated deviatoric stress versus axial strain curves, obtained via the modified Cam Clay model, captured the non-linear elastoplastic response obtained in the tests. Results indicated that the level of the shear strength is highly dependent on critical state friction angle which in turn depends on the TDA content. For the loose TDA-sand mixtures used in the present study, the effect of the TDA content demonstrates a reinforcement of the sand matrix. However this reinforcement diminishes as the TDA content increases.

Severe faults have caused many earthquakes around the world throughout history. More recently, earthquakes have occurred in Taiwan, China (Chi-Chi fault), and elsewhere, causing loss of lives and destroying many buildings and structures. These tectonic movements have gained attention from engineers, and in the past 15 years, the focus has been on faulting mechanisms. In this study, a physical model (1 g) was fabricated and used to evaluate the impact of a reverse fault in a field with a tunnel. In the 1 g model, researchers installed additional gauges on the tunnel, so that all the displacements could be adjusted, and all the responses could be monitored during faulting. An experimental study of various soil properties (cohesion and friction angles) in reverse faults on the tunnel lining were carried out and are described herein. A comparison of results for different levels of soil cohesion revealed that it can dramatically reduce the displacement by as much as 40%, and that friction angles of 27° can record approximately 60% more displacements than at 37°. Furthermore, a comparison of fault angles of 30° and 60° indicates that the displacements can be different by more than 43% in cohesionless soil and about 64% for a friction angle of 27°.

In this paper, we study the optimization problem (P) of minimizing a convex function over a constraint set with nonconvex constraint functions. We do this by given new characterizations of Robinson’s constraint qualification, which reduces to the combination of generalized Slater’s condition and generalized sharpened nondegeneracy condition for nonconvex programming problems with nearly convex feasible sets at a reference point. Next, using a version of the strong CHIP, we present a constraint qualification which is necessary for optimality of the problem (P). Finally, using new characterizations of Robinson’s constraint qualification, we give necessary and sufficient conditions for optimality of the problem (P).

Peracetic acid (PAA) is being considered as a disinfectant in membrane-based wastewater reuse systems, but its compatibility with polyamide membranes has not been thoroughly investigated. In this work, we showed that PAA induced much less change in the performance and material characteristics of NF90 membranes than the traditional disinfectant free chlorine (NaOCl). The change in membrane water flux and the rejection of salt and neutral organic compounds after PAA exposure (1–180 g h L−1) is significantly less than that resulting from NaOCl exposure at levels as low as 1 g h L−1. The presence of two wastewater constituents, chloride or Fe(II), did not significantly impact membrane performance upon exposure to PAA. Surface characterization showed that oxygen was incorporated into polyamide by PAA, some of which was attributed to the formation of carboxylic acid groups. Experiments using a model aromatic amide, benzanilide, indicated an unexpected role of PAA in protecting the membrane from radicals formed by Fe(II) and the H2O2 present in commercial PAA formulations. Furthermore, product identification suggests that both amide bond breakage and ring oxidation are possible reaction mechanisms for PAA. Our findings support that PAA is a viable disinfectant candidate for wastewater reuse and warrants further evaluation.

Background Regeneration of articular cartilage poses a tremendous challenge due to its limited self-repair capability and inflammation at the damaged site. To generate the desired structures that mimic the structure of native tissue, microtissues with repeated functional units such as cell aggregates have been developed. Multicellular aggregates of mesenchymal stem cells (MSCs) can be used as microscale building blocks of cartilage due to their potential for cell-cell contact, cell proliferation, and differentiation. Methods Chondrogenic microtissues were developed through incorporation of kartogenin-releasing poly (lactic-co-glycolic acid) (PLGA) microparticles (KGN-MP) within the MSC aggregates. The chondrogenic potential of KGN-MP treated MSC aggregates was proven in vitro by studying the chondrogenic markers at the RNA level and histological analysis. In order to address the inflammatory responses at the defect site, the microtissues were delivered in vivo via an injectable, anti-inflammatory hydrogel that contained gelatin methacryloyl (GelMA) loaded with curcumin (Cur). Results The KGN-MPs were fabricated to support MSCs during cartilage differentiation. According to real-time RT-PCR analysis, the presence of KGN in the aggregates led to the expression of cartilage markers by the MSCs. Both toluidine blue (TB) and safranin O (SO) staining demonstrated homogeneous glycosaminoglycan production throughout the KGN-MP incorporated MSC aggregates. The curcumin treatment efficiently reduced the expressions of hypertrophy markers by MSCs in vitro. The in vivo results showed that implantation of chondrogenic microtissues (KGN-MP incorporated MSC aggregates) using the curcumin loaded GelMA hydrogel resulted in cartilage tissue regeneration that had characteristic features close to the natural hyaline cartilage according to observational and histological results. Conclusions The use of this novel construct that contained chondrogenic cell blocks and curcumin is highly desired for cartilage regeneration. Graphical abstract

Biological treatment of oily sludge wastes was studied using an isolated halo-tolerant strain Pseudomonas balearica strain Z8. An oily sludge sample was obtained from oil fields of south waste of Iran and was fully characterized. The initial TPH content was 44,500 mg kg−1. The ability of Pseudomonas balearica strain Z8 in production of biosurfactant was investigated using oil displacement method. Results demonstrated that isolated strain is a biosurfactant producing bacteria. The CMC and emulsification index [E24] of produced biosurfactant were 90 mg L−1 and 44% for crude oil. Effect of operational parameters including nitrogen source, sludge/water ratio and temperature were investigated against the time. The most TPH removal of 35% was observed for nitrogen source of NH4Cl, sludge/ water ratio of 1:7 and temperature of 40 °C.

The green space of parks with its vegetation population of trees and shrubs plays a key role in air purification and the absorption of air pollutions, thereby contributing to the alleviation of environmental pollutions. The present factorial experiment was carried out in urban parks with 18 treatments. The leaf samples of 18 ornamental species were collected in two sites [(1) the margin and (2) the downtown] of Rasht city in north of Iran. Then, they were subjected to the measurement of leaf relative water content, total chlorophyll content, leaf extract pH, and ascorbic acid content to evaluate their air pollution tolerance index (APTI). The tolerance of the species was assessed by two methods: the comparison of their APTI with the average APTI of all species and the use of a constant APTI as a standard. The results showed that the species differed in their tolerance in different sites. Among the studied 18 species, Yucca filamentosa and Berberis thunbergii were identified as air pollution-tolerant species, so they are recommended for the use in parks. Yucca had an APTI of 78.24 and Berberis had an APTI of 67.56. The lowest APTI was obtained from Fraxinus excesio and Ligustrum texanum.

Purpose Assessing the performance of medical laboratories plays an important role in the quality of health services. However, because of imprecise data, reliable results from laboratory performance cannot be obtained easily. The purpose of this paper is to illustrate the use of interval network data envelopment analysis (INDEA) based on sustainable development indicators under uncertainty. Design/methodology/approach In this study, each medical diagnostic laboratory is considered as a decision-making unit (DMU) and an INDEA model is used for calculating the efficiency of each medical diagnostic laboratory under imprecise inputs and outputs. The proposed model helps provide managers with effective performance scores for deficiencies and business improvements. The proposed model with realistic efficiency scores can help administrators manage their deficiencies and ultimately improve their business. Findings The results indicate that uncertainty can lead to changes in performance scores, rankings and performance classifications. Therefore, the use of DEA models under certainty can be potentially misleading. Originality/value The contribution of this study provides useful insights into the use of INDEA as a modeling tool to aid managerial decision-making in assessing efficiency of medical diagnostic laboratories based on sustainable development indicators under uncertainty.

With the availability of a large amount of user-generated online data, discovering users’ sequential behaviour has become an integral part of a Sequential Recommender System (SRS). Combining the recent observed items (i.e., short-term preferences) with prior interacted items (i.e., long-term preferences) has gained increasing attention in recent years. However, the existing methods mostly assume that all the adjacent items in a sequence are highly dependent, which may not be practical in real-world scenarios due to the uncertainty of customers’ shopping behaviours. A user-item interaction sequence may contain some irrelevant items which may in turn lead to false dependencies between items. Moreover, current studies usually assign a static representation to each item when modeling a user’s long-term preferences. Therefore, they cannot differentiate the contributions of the items. Specifically, these two types of users’ preferences have been separately modeled and then linearly combined, which may fail to model complicated user-item interactions. In order to overcome the above mentioned problems, we propose a novel Deep Attention-based Sequential (DAS) model. DAS consists of three different blocks, $(i)$ an embedding block: which embeds users and items into low-dimensional spaces; $(ii)$ an attention block: which aims to discriminatively learn dependencies among items in both users’ long-term and short-term item sets; and $(iii)$ a fully-connected block : which first learns a mixture of users’ preferences representation through a nonlinear way and then combines it with users’ embeddings to have a personalized recommendation. Extensive experiments demonstrate the superiority of our proposed model compared to the state-of-the-art approaches in SRSs.

Level of Trust can determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for measuring trust in Online Social Networks (OSNs), including social spammer detection, fake news detection, retweet behaviour detection and recommender systems. Trust prediction is the process of predicting a new trust relation between two users who are not currently connected. In applications of trust, trust relations among users need to be predicted. This process faces many challenges, such as the sparsity of user-specified trust relations, the context-awareness of trust and changes in trust values over time. In this paper, we analyse the state-of-the-art in pair-wise trust prediction models in OSNs, classify them based on different factors, and propose some future directions for researchers interested in this field.

The two-electron oxidation of N,N,N',N'-tetramethyl-p-phenylenediamine (TMPD) results in highly unstable TMPD2+ in aqueous solutions. Despite its low redox potential, TMPD2+/TMPD couple is not considered as a suitable charge transfer functional group to modify the electrode due to instability of TMPD2+ in aqueous solutions. The main focus of the present paper is to fabricate an efficient redox-active electrode by coupling TMPD with 4-nitroaniline to be utilized for on-surface chemistry. The nitro functional group in the coupling product N2,N2,N5,N5-tetramethyl-4'-nitro-[1,1'-biphenyl]-2,5-diamine (MNPD) was reduced electrochemically to the corresponding amino derivative (MAPD). The oxidized form of MAPD (MAPD2+) exhibited high stability as well as low reduction potential in aqueous solutions. A redox active electrode was designed via the immobilization of the electro-generated MAPD onto a nanofibrillated mesoporous carbon (IFMC) modified glassy carbon electrode (GCE). The redox signal increased several folds with the deposition of IFMC onto glassy carbon electrode compared to bare GCE. Two functionalization routes, electro-grafting and spontaneous physical immobilization, were examined for the attachment of the redox species to the electrode surface. In the first approach, electro-grafting was attained via the electrochemical reduction of MNPD in the presence of sodium nitrite to produce diazonium ions in situ. The redox centers covalently grafted to the surface showed dense deposition and appreciable stability. In the second route, spontaneous adsorption was performed by the same strategy of electro-grafting in the absence of sodium nitrite. In this case, the hydrophobic nanofiber structure of IFMC was capable of robustly trapping MAPD. The anchored MAPD shows high reactivity in Michael addition reactions in ultrafast reaction times. The post-functionalization of the electrodes was easily performed by the oxidation of the redox centers in the presence of species with nucleophilic properties at the electrode/electrolyte interface. In addition, both the constructed electrodes are introduced as suitable mediators in electro-catalytic implications because of their reversibility, stability, and low oxidation potential. The electro-catalytic activity of the electrodes was established for the indirect electrochemical oxidation of homocysteine as a typical substrate.

Separation of cancerous from normal cells is of broad importance in a large number of cancer diagnosis and treatment methods. One of the most important factors to designate and specify different cells is to study their dielectric and electric cell membrane characteristics. In this research, a label-free cytological slide chip (CSC) is designed and fabricated based on AC electric field stimulation of breast cell lines and blood cells at low frequencies (1 kHz-200 kHz). The AC-CSC traps cells based on their dielectric polarization functions which is distinct between different phenotypes of breast cells and blood cells. We learned that by using AC electric fields, each breast cell line shows a capturing response to a specific range of frequencies. The progression in cancer phenotypes decreases the cell's polarizability. Hence, characteristic frequency responses were achieved for these cells. In this study, thermal potential and electrolysis which were the main bottle neck problems in DC applied fields were completely solved. The AC-CSC could be used in CTC separation from leukocytes, a test performed based on a compound with 1% cancer cells in white blood cells (1% MDA-MB-231 : 99% WBC) which results in 90% capturing efficiency of cancer cells. Frequency dependent capturing brings so much hope that smart slides will be useful at the clinical stage in the near future.

We report calculations of the electronic structure of thermoelectric ternary chalcogenide TlInSe2 in the pressure range 0 30 GPa and the Li substituted compound Tl0.5Li0.5InSe2 using density functional theory. Moreover, with Boltzmann transport theory the electronic transport properties of these com pounds are investigated at the optimal p doping level for a maximized power factor. We follow two possible band engineering routes by applying pressure and elemental substitution with Li to investigate a possible enhancement of the electronic properties for thermoelectric applications. Our study employs several exchange correlation functionals including the spin orbit interaction as well as the B3LYP hybrid functional. The band gap in TlInSe2 obtained by using the Tran Blaha modi amp; 64257;ed Becke Johnson functional is in good agreement with experimental data. We amp; 64257;nd a direct band gap for TlInSe2 at the M point and a slightly larger energy gap at the Z point. The spin orbit SO splitting is extracted from the calculated electronic band structure. When applying pressure to TlInSe2 the Seebeck coef amp; 64257;cient strongly decreases and band crossing results in metallic properties above 20 GPa. In contrast to TlInSe2, an indirect band gap is found for Tl0.5Li0.5InSe2 with the valence band maximum located at an off symmetry point along the M X direction and the conduction band minimum located at an off symmetry point along the X P di rection. In contrast to TlInSe2 at ambient pressure, taking the SO coupling into account for Tl0.5Li0.5InSe2 and TlInSe2 at 20 GPa is necessary as it markedly changes the transport properties. Optimally doped p type TlInSe2 at ambient pressure has the most favorable electronic band structure for thermoelectric applications superior to both, optimally doped p type TlInSe2 under pressure and optimally doped p type Tl0.5Li0.5InSe2

The simultaneous cooperation of π-π stacking and pnicogen bonding the formation of Pyr||X-PhPS2⊥Pyr ternary complexes has been investigated via a computational chemistry at MP2/aug-cc-pVDZ level of theory. We proved by computational NMR data the effect of electron-withdrawing and donating substituents on 1pJ(N-P) across 15N⋯31P pnicogen bond. The interaction energy contributions of Pyr||X-PhPS2 and X-PhPS2⊥Pyr dimers have been investigated by symmetry adapted perturbation theory (SAPT) energy decomposition method. In addition, atoms in molecules (AIM), natural bond orbital analysis (NBO) and molecular electrostatic potentials (MEP) have been performed to unveil the mechanism of these interactions in the title complexes.

Microporous and hydrophobic polymers were synthesized and tested as NO oxidation catalysts to overcome water co-adsorption in combustion flue gas streams. The self-cross-linked 4,4′-bis(chloromethyl)-1,1′-biphenyl polymer (PBCMBP), with micropore volume of 0.38 cm3/g and surface area of 1430 m2/g, provided 62% NO oxidation efficiency at 25 °C in dry conditions but its performance dropped to 50% in the presence of 1.6 vol% moisture (wet conditions). To decrease performance loss, PBCMBP was modified with benzene (PBCMBP-BZ) to remove pendant chloromethyl groups, improving resistance to surface reactions with NO2 that add hydrophilicity. In wet conditions, PBCMBP-BZ has 59% NO oxidation efficiency, an 18% increase compared to PBCMBP at 25 °C. PBCMBP was also functionalized with dimethylamine (PBCMBP-DMA) to increase surface basicity, increasing NO oxidation by 11% in dry conditions, but decreasing NO oxidation in wet conditions by 30% due to increased proclivity to react with NO2. The combined impact of temperature and humidity was measured up to 100 °C, showing that moisture’s impact decreases with increasing temperature and that PBCMBP-DMA outperforms other catalysts at higher temperatures. Findings suggest that catalyst surface chemistry can be manipulated to further improve NO oxidation performance, especially in the presence of moisture.

Simulations of stochastic processes play an important role in the quantitative sciences, enabling the characterisation of complex systems. Recent work has established a quantum advantage in stochastic simulation, leading to quantum devices that execute a simulation using less memory than possible by classical means. To realise this advantage it is essential that the memory register remains coherent, and coherently interacts with the processor, allowing the simulator to operate over many time steps. Here we report a multi-time-step experimental simulation of a stochastic process using less memory than the classical limit. A key feature of the photonic quantum information processor is that it creates a quantum superposition of all possible future trajectories that the system can evolve into. This superposition allows us to introduce, and demonstrate, the idea of comparing statistical futures of two classical processes via quantum interference. We demonstrate interference of two 16-dimensional quantum states, representing statistical futures of our process, with a visibility of 0.96 $\pm$ 0.02., Comment: 9 pages, 5 figures

This study aimed at synthesizing a self-polarized electrospun PVDF which eliminates a need for the post treatment process. In addition, the feasibility of using an electrospun PVDF sensor for both active and passive sensing applications has been studied. The pitch-catch approach was considered for an active sensing approach while an acoustic emission monitoring was used as a passive method. Moreover, the experimental program involved studying the several parameters such as the transmitted signal amplitude, frequency and the distance on the received signal by PVDF sensor. The PVDF sensor was found to be effective in detecting the pulsed and continuous generated Lamb wave. The results indicate that the PVDF device is efficient in detecting the transmitted signal from 1 to 100 kHz, but less efficient either at a low-frequency range ( 100 kHz). The results clearly indicate that the sensor can detect different magnitudes of surface acoustic waves propagating on the surface.

In this paper the isogeometric method is used to present a shear refined composite beam model through the concept of dimensional reduction method. A one-dimensional (1D) beam model is extracted from three-dimensional (3D) elasticity problem . The 1D beam model is developed using cross-sectional properties from two-dimensional (2D) beam sectional analysis. The 2D analysis of the cross-section is presented by implementing the transverse shear effects in isogeometric analysis. In beam cross-sectional problem, the influence of linear parameterization is investigated for isogeometric modeling of beam cross-section . Moreover, the effect of delamination on cross-sectional stiffness constants is discussed. Using isogeometric analysis (IGA), less degrees of freedom is needed in contrast to classical finite element method and automatic mesh refinement capability is attained. The present composite beam model eliminates the expensive use of 3D finite element analysis with its high precision and fidelity to 3D problem.

Aluminium alloys have been used in the aerospace, automotive and military industrial applications. However, these alloys have the tendency to corrode when the contact with corrosive solution. Therefore, there are many trends to protect these alloys to increase the corrosion resistant by applying the coating. In this work, the zirconia coating doped with benzotriazole and cerium nitrate inhibitors was deposited on AL7075 Aluminium alloy. In order to evaluate the effect of inhibitor on the corrosion resistance, the different type of zirconia coatings were studied. Furthermore, the corrosion behavior of coating was investigated by electrochemical impedance spectroscopy (EIS) and polarization test. Finally the results showed that the homogeneous, uniformity and nanostructured of the zirconia coating was formed. Additionally, the zirconia coatings doped with BTA (4-layers contained inhibitor) showed the better corrosion resistant than the composite coating of (2-layer contained inhibitor) and the zirconia coatings (4 layers without benzotriazole). Finally, the analytic hierarchy process (AHP) and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methods, depend on the criteria of type coating, inhibitor type and inhibitor concentration were selected. The evaluation of results showed that the zirconia coating doped with BTA (4-layers contained inhibitor) was the best sample.

Android Inter-Component Communication (ICC) is complex, largely unconstrained, and hard for developers to understand. As a consequence, ICC is a common source of security vulnerability in Android apps. To promote secure programming practices, we have reviewed related research, and identified avoidable ICC vulnerabilities in Android-run devices and the security code smells that indicate their presence. We explain the vulnerabilities and their corresponding smells, and we discuss how they can be eliminated or mitigated during development. We present a lightweight static analysis tool on top of Android Lint that analyzes the code under development and provides just-in-time feedback within the IDE about the presence of such smells in the code. Moreover, with the help of this tool we study the prevalence of security code smells in more than 700 open-source apps, and manually inspect around 15% of the apps to assess the extent to which identifying such smells uncovers ICC security vulnerabilities., Comment: Accepted on 28 Nov 2018, Empirical Software Engineering Journal (EMSE), 2018

A biosurfactant producing strain was isolated and the rhamnolipid type biosurfactant was extracted for soil washing of a synthetically and naturally hydrocarbon-contaminated soil. Following the primary screening, Pseudomonas aeruginosa strain R(4) was selected and the effect of the carbon and nitrogen source and the salinity on biosurfactant production was studied. Of the best results were observed for glucose as a carbon source, NH(4)Cl as a nitrogen source and salinity of 1.4%. The produced biosurfactant was a glycolipid type biosurfactant and reduced the surface tension to 32.5 mN/m with a critical micelle concentration (CMC) of 50 mg/L and production yield of 90 mg/L. Using produced biosurfactant, a pyrene desorption rate of 82% was observed in selected conditions for initial pyrene concentration of 200 mg/L.

In this study, a modified mesoporous adsorbent (MSU-S) impregnated by aluminum was used to remove the aromatic sulfur compounds from n-decane as the model fuel. Physical and chemical properties of as-synthesized adsorbent were investigated by XRD (X-Ray Diffraction), SEM (Scanning Electron Microscopy), FTIR (Fourier Transform Infrared spectroscopy) and BET (Brunauer–Emmett–Teller) method. Adsorptive desulfurization of model fuel was studied through batch and continues processes under mild temperature and normal atmospheric pressure. The equilibrium adsorption was modeled by Langmuir, Temkin, and Freundlich and the kinetics of adsorption was studied through first, second and intraparticle diffusion models. It was figured out that Temkin and the pseudo-second-order model were best fitting the adsorption equilibrium and describing the kinetics, respectively.

This paper is presented on the tandem two-dimensional hydrofoils with profiles NACA4412 in single-phase and two-phase flow domains for different submergence depths and different distances in a various angle of attack (AoA). Also, supercavitation is studied at σ = 0.34 by the Zwart cavitation model. Reynolds-averaged Navier–Stokes (RANS) with the shear stress transport (SST) K-ω is employed as a turbulence model in transient analysis of Ansys FLUENT software. The numerical results show that, by increasing depth, the drag coefficient increases for both hydrofoils 1 and 2 as well as the lift coefficient. The drag coefficient of hydrofoil 2 is bigger than hydrofoil 1 for all depths; moreover, it was found that the flow pressure behind the hydrofoil 1 had affected the upper and the lower surface of the hydrofoil 2 at each distance or AoA. These effects are observed in the hydrofoil 2 lift coefficient as well as the flow separation. However, the maximum lift-to-drag ratio is observed at AoA = 8 ° and 3.5c distance. Also, single-phase results reveal that the value of pressure and the hydrodynamic coefficient are very different from the two-phase flow results, due to the elimination of the free surface. So, a two-phase flow domain is recommended for increasing the accuracy of results. In addition, the investigation of supercavitation shows a growth in cavity occurrence on the surface by raising AoA.

Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. Here, we compare three deep learning architectures to classify microfluidic time-lapsed images of dividing yeast cells into categories that represent different stages in the yeast replicative aging process. We found that convolutional neural networks outperformed capsule networks in terms of accuracy, precision, and recall. The capsule networks had the most robust performance at detecting one specific category of cell images. An ensemble of three best-fitted single-architecture models achieves the highest overall accuracy, precision, and recall due to complementary performances. In addition, extending classification classes and augmentation of the training dataset can improve the predictions of the biological categories in our study. This work lays a useful framework for sophisticated deep-learning processing of microfluidics-based assays of yeast replicative aging.

Trust can be employed for finding reliable information in Online Social Networks (OSNs). Since users in OSNs may intentionally change their behavior over time (in some cases for deceiving other users), modeling (pair-wise) trust relations in such complex environment is a challenging task. However, most of the existing trust prediction approaches assume that trust relations are fixed over time and they fail to capture the dynamic behavior of users in OSNs. In this paper, we propose a dynamic deep trust prediction model. As the impact of incidental emotions on trust has been proven in psychology studies, in this paper, we also study this impact on our trust prediction approach. First, we propose a novel deep structure that incorporates users' emotions and their textual contents in OSNs. Second, we use embeddings to represent the users and their self-descriptions provided. Finally, considering different time windows, we dynamically predict pair-wise trust relations. To evaluate our approach, we collected a large twitter dataset. The evaluation results demonstrate the effectiveness of our approach compared to the state-of-the-art approaches.

Herein, we present a new design on the Single Needle Electrochemical Therapy (SNEChT) method by introducing some major improvements, including a nanoporous platinum electrode, tunable in situ anode size that depends on the width and location of the tumor, and the capability of measuring the efficacy of therapy based in intra-therapeutic impedance recording by the same EChT needle. It could have significant implications in optimizing EChT operative conditions. The nanoporous Pt electrode increased the interactive surface with a tumor, and produced a higher amount of current with lower stimulating DC voltage. The tunable anode size prevents the over-acidification of treated or non-desired lesions. Hence, this feature reduced the over distribution of tissue. Monitoring the impedance during the therapy clearly informs us about the local destruction of the tumor in each location. Thus, we can be informed about the threshold of tissue acidosis with the lowest electrical stimulation. The insertion of one needle with a tunable anode length for both precise therapy and impedance-based intra-therapeutic monitoring will shed new light on the applications of EChT.

[Background] Previous research has shown that developers commonly misuse cryptography APIs. [Aim] We have conducted an exploratory study to find out how crypto APIs are used in open-source Java projects, what types of misuses exist, and why developers make such mistakes. [Method] We used a static analysis tool to analyze hundreds of open-source Java projects that rely on Java Cryptography Architecture, and manually inspected half of the analysis results to assess the tool results. We also contacted the maintainers of these projects by creating an issue on the GitHub repository of each project, and discussed the misuses with developers. [Results] We learned that 85% of Cryptography APIs are misused, however, not every misuse has severe consequences. Developer feedback showed that security caveats in the documentation of crypto APIs are rare, developers may overlook misuses that originate in third-party code, and the context where a Crypto API is used should be taken into account. [Conclusion] We conclude that using Crypto APIs is still problematic for developers but blindly blaming them for such misuses may lead to erroneous conclusions., The ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM) 2020

Intelligence is the ability to learn from experience and use domain experts&rsquo, knowledge to adapt to new situations. In this context, an intelligent Recommender System should be able to learn from domain experts&rsquo, knowledge and experience, as it is vital to know the domain that the items will be recommended. Traditionally, Recommender Systems have been recognized as playlist generators for video/music services (e.g., Netflix and Spotify), e-commerce product recommenders (e.g., Amazon and eBay), or social content recommenders (e.g., Facebook and Twitter). However, Recommender Systems in modern enterprises are highly data-/knowledge-driven and may rely on users&rsquo, cognitive aspects such as personality, behavior, and attitude. In this paper, we survey and summarize previously published studies on Recommender Systems to help readers understand our method&rsquo, s contributions to the field in this context. We discuss the current limitations of the state of the art approaches in Recommender Systems and the need for our new approach: A vision and a general framework for a new type of data-driven, knowledge-driven, and cognition-driven Recommender Systems, namely, Cognitive Recommender Systems. Cognitive Recommender Systems will be the new type of intelligent Recommender Systems that understand the user&rsquo, s preferences, detect changes in user preferences over time, predict user&rsquo, s unknown favorites, and explore adaptive mechanisms to enable intelligent actions within the compound and changing environments. We present a motivating scenario in banking and argue that existing Recommender Systems: (i) do not use domain experts&rsquo, knowledge to adapt to new situations, (ii) may not be able to predict the ratings or preferences a customer would give to a product (e.g., loan, deposit, or trust service), and (iii) do not support data capture and analytics around customers&rsquo, cognitive activities and use it to provide intelligent and time-aware recommendations.

Assessing the performance of health systems assists health decision-makers to ensure the accountability for their decisions. Medical diagnostic laboratories are one of the most important and sectors in the healthcare system of all countries. Thus, an assessment of the performance of medical diagnostic laboratories is of particular importance. This paper aims to propose a network data envelopment analysis (NDEA) model to assess the performance of medical diagnostic laboratories and decomposing the efficiency of the system with intricate internal structure based on sustainable development indicators. In addition, the proposed model is designed according to the internal structure of the medical diagnostic laboratory, which includes three main laboratory processes (the pre-test, the test and the post-test) with a combination of additional inputs and outputs (including both desirable and undesirable). The proposed model is a multiplicative DEA approach to estimate and decompose the efficiencies of system. Thus, a heuristic method is used as a suitable solution to convert a multiplicative NDEA approach into an equivalent linear program. The performance proposed model is shown through a real study in Iran. The computational results demonstrate the applicability of the proposed model in determining the most efficient laboratory using undesirable sustainability indicators.

In this paper, freshly (non-fixed) dissected tissues obtained from breast cancer surgery were impedimetrically and pathologically scanned, analyzed, and probable electro-pathological mutual matching was investigated. A new electrical model was proposed for pathological scores of breast lesions based on the theory of electric current dispersion by different types of biological tissues. This integrated handheld bioimpedance sensor named EPA would score the clearance or malignancy involvement of dissected tumor margins by introducing two crucial classification parameters named Z1kHz and IPS (impedance phase slope in the frequency ranges of 100-500 kHz). EPA benefits from a precise signal recording and analysis method which leads to the detection of the presence of even about 5% distribution of premalignant cells among healthy breast tissue. EPA can be clinically used by pathologists, as a complementary device, for real-time diagnosis of suspicious margins of dissected tumors to declare more precise intraoperative diagnosis by scanning all around the dissected tissues. Each data sampling and analysis covers 2 mm of the surface in less than 5 s. Measurements on about 313 human breast tumor margins showed more than 90% accuracy and near 93% specificity for EPA as an independent diagnostic tool.

Factors such as app stores or platform choices heavily affect functional and non-functional mobile app requirements. We surveyed 45 companies and interviewed ten experts to explore how factors that impact mobile app requirements are understood by requirements engineers in the mobile app industry. We observed a lack of knowledge in several areas. For instance, we observed that all practitioners were aware of data privacy concerns, however, they did not know that certain third-party libraries, usage aggregators, or advertising libraries also occasionally leak sensitive user data. Similarly, certain functional requirements may not be implementable in the absence of a third-party library that is either banned from an app store for policy violations or lacks features, for instance, missing desired features in ARKit library for iOS made practitioners turn to Android. We conclude that requirements engineers should have adequate technical experience with mobile app development as well as sufficient knowledge in areas such as privacy, security and law, in order to make informed decisions during requirements elicitation., The 24th International Conference on Evaluation and Assessment in Software Engineering (EASE 2020)

Web communication has become an indispensable characteristic of mobile apps. However, it is not clear what data the apps transmit, to whom, and what consequences such transmissions have. We analyzed the web communications found in mobile apps from the perspective of security. We first manually studied 160 Android apps to identify the commonly-used communication libraries, and to understand how they are used in these apps. We then developed a tool to statically identify web API URLs used in the apps, and restore the JSON data schemas including the type and value of each parameter. We extracted 9,714 distinct web API URLs that were used in 3,376 apps. We found that developers often use the java.net package for network communication, however, third-party libraries like OkHttp are also used in many apps. We discovered that insecure HTTP connections are seven times more prevalent in closed-source than in open-source apps, and that embedded SQL and JavaScript code is used in web communication in more than 500 different apps. This finding is devastating; it leaves billions of users and API service providers vulnerable to attack., Comment: 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). London, Ontario, Canada, February 18-21, 2020

Enabling the analysis of behavioral disorders over time in social networks, can help in suicide prevention, (school) bullying detection and extremist/criminal activity prediction. In this paper, we present a novel data analytics pipeline to enable the analysis of patterns of behavioral disorders on social networks. We present a Social Behavior Graph (sbGraph) model, to enable the analysis of factors that are driving behavior disorders over time. We use the golden standards in personality, behavior and attitude to build a domain specific Knowledge Base (KB). We use this domain knowledge to design cognitive services to automatically contextualize the raw social data and to prepare them for behavioral analytics. Then we introduce a pattern-based word embedding technique, namely personality2vec, on each feature extracted to build the sbGraph. The goal is to use mathematical embedding from a space with a dimension per feature to a continuous vector space which can be mapped to classes of behavioral disorders (such as cyber-bullying and radicalization) in the domain specific KB. We implement an interactive dashboard to enable social network analysts to analyze and understand the patterns of behavioral disorders over time. We focus on a motivating scenario in Australian government's office of the e-Safety commissioner, where the goal is to empowering all citizens to have safer, more positive experiences online.

Research has shown that cryptographic APIs are hard to use. Consequently, developers resort to using code examples available in online information sources that are often not secure. We have developed a web platform, named CryptoExplorer, stocked with numerous real-world secure and insecure examples that developers can explore to learn how to use cryptographic APIs properly. This platform currently provides 3,263 secure uses, and 5,897 insecure uses of Java Cryptography Architecture mined from 2,324 Java projects on GitHub. A preliminary study shows that CryptoExplorer provides developers with secure crypto API use examples instantly, developers can save time compared to searching on the internet for such examples, and they learn to avoid using certain algorithms in APIs by studying misused API examples. We have a pipeline to regularly mine more projects, and, on request, we offer our dataset to researchers., Comment: 27th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). London, Ontario, Canada, February 18-21, 2020

We studied the web permission API dialog box in popular mobile and desktop browsers, and found that it typically lacks measures to protect users from unwittingly granting web permission when clicking too fast. We developed a game that exploits this issue, and tricks users into granting webcam permission. We conducted three experiments, each with 40 different participants, on both desktop and mobile browsers. The results indicate that in the absence of a prevention mechanism, we achieve a considerably high success rate in tricking 95% and 72% of participants on mobile and desktop browsers, respectively. Interestingly, we also tricked 47% of participants on a desktop browser where a prevention mechanism exists., Comment: The 24th International Conference on Evaluation and Assessment in Software Engineering (EASE 2020)

[Background] Recent investigations into the effects of Test-Driven Development (TDD) have been contradictory and inconclusive. This hinders development teams to use research results as the basis for deciding whether and how to apply TDD. [Aim] To support researchers when designing a new study and to increase the applicability of TDD research in the decision-making process in the industrial context, we aim at identifying the reasons behind the inconclusive research results in TDD. [Method] We studied the state of the art in TDD research published in top venues in the past decade, and analyzed the way these studies were set up. [Results] We identified five categories of factors that directly impact the outcome of studies on TDD. [Conclusions] This work can help researchers to conduct more reliable studies, and inform practitioners of risks they need to consider when consulting research on TDD., Comment: ESEM '20: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), October 8--9, 2020, Bari, Italy

The ubiquity of smartphones, and their very broad capabilities and usage, make the security of these devices tremendously important. Unfortunately, despite all progress in security and privacy mechanisms, vulnerabilities continue to proliferate. Research has shown that many vulnerabilities are due to insecure programming practices. However, each study has often dealt with a specific issue, making the results less actionable for practitioners. To promote secure programming practices, we have reviewed related research, and identified avoidable vulnerabilities in Android-run devices and the "security code smells" that indicate their presence. In particular, we explain the vulnerabilities, their corresponding smells, and we discuss how they could be eliminated or mitigated during development. Moreover, we develop a lightweight static analysis tool and discuss the extent to which it successfully detects several vulnerabilities in about 46,000 apps hosted by the official Android market., Comment: 2017 IEEE 17th International Working Conference on Source Code Analysis and Manipulation (SCAM)

In this study ZnNb2O6 (ZN) powder, which was synthesized using a microwave heating method, was used to prepare ZN ceramics via conventional and microwave sintering methods. The results show that all samples were single phase with no second phases present. The maximum densities obtained for microwave and conventionally sintered samples were 94.6% and 93.8%, respectively, of the theoretical value at 1250°C. SEM analysis showed that for all sintering temperatures, microwave sintered samples exhibit lower grain size values than those sintered via the conventional method. The variations in relative permittivity (er) for samples sintered at different temperatures via both methods followed those of density values. The highest values for er for conventionally and microwave sintered samples, which were observed at 1250°C, were 22.9 and 23.1, respectively. The variation of quality factor (Q × f) with sintering temperature for samples prepared through the microwave method also followed the density data. Q × f values of samples sintered via the conventional method were higher than those for samples sintered in a microwave oven because higher grain sizes were observed for these ceramics. The highest Q × f values for conventionally and microwave sintered samples were 26,197 GHz and 16,200 GHz, respectively.

The main objective of this study is to investigate the application of Photo-Fenton process to treat landfill leachate with minimum energy consumption and maximum COD removal efficiencies, simultaneously. Accordingly, an operational assessment of Photo-Fenton process was conducted in terms of variables, namely oxidation pH, [H2O2]/[Fe2+] molar ratio, and Fe2+ dosage. The Central Composite Design (CCD) based on Response Surface Methodology (RSM) was applied for statistical analysis and optimization of target parameters. To assess the rate of energy consumption in Photo-Fenton process, the EEM parameter (Electric Energy consumed per organic Mass removed) was introduced, and the same Fenton experiments were performed to compare the results. Applying UV light in the Fenton process (i.e. Photo-Fenton process) increased COD removal efficiencies up to 10%. The results showed that the Photo-Fenton treatment is capable of removing COD by over 80% of the initial COD (i.e. 17,200 mg/L of AradKooh landfill leachate), applying 195–265 mM iron concentration, [H2O2]/[Fe2+] molar ratio of 15.50–20.55, and the oxidation pH value of 3.75–5.55 (other conditions were oxidation time of 30 min, coagulation pH of 8, and coagulation time of 25 min). The regeneration of Fe(II) from Fe(III) by UV light irradiation resulted in a larger degradation of COD than that of conventional Fenton process, and also reduced the amount of iron catalyst consumption (approximately 25% reduction observed). Furthermore, the cost of energy in Photo-Fenton process could be covered considering lower amounts of sludge generated than conventional Fenton treatment (note that the cost evaluations in current paper were based on batch studies and should be confirmed on full-scale system).

Steel pitched roof frames with the tapper fabricated members is the common solution for a wide range of industrial structures. In the present research, design optimization of the steel member sections is performed by different apex heights and tapered lengths for steel pitched roof frames. The effective variable definition has helped to reduce the variable domain and ignore the unwanted part of the bounds before starting the optimization process. Nine metaheuristic algorithms are used for the optimization. Results show that selecting apex height and tapered length can change optimum weight of structure by 10%. Additionally, performance of the considered metaheuristic algorithms is compared for this type of frame structures.

The performance of natural draft dry cooling towers (NDDCTs) depends on the environmental conditions. Crosswind is known to have the most destructive effect, whereas the ambient temperature is marked as the next. A 3-D numerical model was developed to investigate the thermal performance of a single as well as three aligned units of NDDCTs under crosswind conditions. The computed results showed major discrepancies between computed velocity patterns and pressure fields around three aligned towers and those of the single tower due to windshield effect of neighboring cooling towers. The thermal performance losses for the single tower under crosswind showed higher values compared with those of towers in the aligned arrangement. The best thermal performance of three aligned NDDCTs was achieved when the crosswind was directed along the towers’ connection line.

We propose a new attack framework based upon cube testers and d-monomial test. The d-monomial test is a general framework for comparing the ANF of the symmetric cipher’s output with ANF of a random Boolean function. In the d-monomial test, the focus is on the frequency of the special monomial in the ANF of Boolean functions, but in the proposed framework, the focus is on the truth table. We attack ACORN-v3 and Grain-128a and demonstrate the efficiency of our framework. We show how it is possible to apply a distinguishing attack for up to 670 initialization rounds of ACORN-v3 and 171 initialization rounds of Grain-128a using our framework. The attack on ACORN-v3 is the best practical attack (and better results can be obtained by using more computing power such as cube attacks). One can apply distinguishing attacks to black box symmetric ciphers by the proposed framework, and we suggest some guidelines to make it possible to improve the attack by analyzing the internal structure of ciphers. The framework is applicable to all symmetric ciphers and hash functions. We discuss how it can reveal weaknesses that are not possible to find by other statistical tests. The attacks were practically implemented and verified.

The present work is investigated the effect of vanadium impurity on electronic and optical properties of Ti3N2 monolayer by using density function theory (DFT) implemented in Wien2k code. In order to study optical properties in two polarization directions of photons, namely E||x and E||z, dielectric function, absorption coefficient, optical conductivity, refraction index, extinction index, reflectivity, and energy loss function of Ti3N2 and Ti3N2-V monolayer have been evaluated within GGA (PBE) approximation. Although, Ti3N2 monolayer is a good infrared reflector and can be used as an infrared mirror, introducing V atom in the infrared area will decrease optical conductivity because optical conductivity of a pure form of a material is higher than its doped form. Keywords: Dielectric function, Optical conductivity, DFT, Ti3N2: V mono-layer

The main objective of this research was to introduce a smart assist-as-needed control system that helps elderly or partially paralyzed individuals. To ensure that a smart and compliant controller, in each cycle of the gait is developed, we adapted the target impedance gains and feed-forward force of the assistive mechanism according to a learning law. A strength metric was defined to determine when the human needs assistance. Then, a cost function was introduced and the gains are modified to reduce the cost function. Applying the proposed controller, the interaction force between patient’s limb and robot was reduced in cases wherein user has sufficient strength for task execution and minimizes the position error in the sub phases where users need assistance. Using the Lyapunov stability theorem, the stability of the closed loop system was proved without and with parameter uncertainty, respectively. The results of simulations and an experiment on an exoskeleton showed that the proposed adaptive impedance control improves performance to a level substantially higher than that achieved with constant impedance control.

This paper aims to investigate the feasibility of using piezoelectric-based sensors to characterize the compressive strength gain process of cement paste blended with supplementary cementitious materials. The electromechanical impedance technique was used for in-situ monitoring of the strength gain of cement pastes. Two different indices of root mean square deviation (RMSD) and correlation coefficient (CC) have been used to establish a quantitative correlation between the conductance signature obtained by lead zirconate titanate (PZT) sensors and the compressive strength of cement paste. Both indices exhibited a reasonable qualitative trend which was compatible with the trend of strength gain of cement pastes. However, the RMSD was found to be more efficient than CC index in estimating the compressive strength of cement paste over time. The experimental results indicate that EMI can be used as a nondestructive testing (NDT) method to enable in-situ measurement of strength gain process of cement paste with supplementary cementitious materials.

The thermodynamic properties and crystallization kinetics of the Co90Sc10 amorphous alloy prepared by rapid quench technique were investigated by X-ray diffractometer (XRD), differential scanning calorimeter (DSC), and simultaneous thermal analyzer (STA). In the isochronal heating process, the activation energy of crystallization is 388 kJ/mol, which was calculated by Kissinger method. The Johnson-Mehl-Avrami (JMA) model was used to describe the isothermal transformation kinetics. The variation of the activation energy of the isothermal process indicated that tiny Co particles precipitate out in the supercooled liquid region and become the nuclei of crystallization that reduce the activation energy at the beginning of crystallization process. Comprehensive results show that a-Co90Sc10 is a promising soft magnetic material for various applications.

Baijiu (Chinese liquor) industry is the world-renowned industry to produce high-quality liquor using mixed biomass feedstocks including sorghum, wheat, and rice bran. A huge amount of Baijiu Diuzao (residual solid waste) is produced every 1–3 months after the fermentation. The present study was focused on evaluating the bioenergy potential of the Chinese liquor industry waste for the very first time. The collected sample was subjected to thermal degradation in an inert environment at three heating rates including 10, 30 and 50 Kmin-1. It was shown that pyrolysis of this waste followed a three-stage degradation pattern, with a loss of 7.49% of the mass during the first stage at T ≤ 130 °C. While the second stage showed two zones ranging from 130 to 373 °C with an overall 51.12% of the mass loss. The third stage occurred above 373 °C and showed 16.08% loss in the mass. The released gases were subjected to TG-FTIR-MS analyses to monitor the composition and abundance of the gases where C O groups (aldehydes, ketonic and carboxylic) and hydrocarbons were shown to be the dominating functional groups. Moreover, the data were subjected to kinetics, thermodynamics and reaction mechanism analyses using KSA (Kissinger-Akahira-Sunose), FWO (Flynn-Wall-Ozawa), Vyazovkin and CR (Coats-Redfern) methods. Where, the activation energies (70–195 kJ mol−1), Gibbs free energy (177–185 kJ mol−1) and lower difference of enthalpy (ΔH = ∼5 kJ mol−1) indicated remarkable bioenergy potential of this waste either through pyrolysis or co-pyrolysis. The artificial neural network (R2 = 0.99) and reaction mechanism analyses indicated that the best thermal degradation chemistry was performed and described. This study will lead to establishing a thermal transformation strategy of this abundant and low-cost biological resource into energy and valuable chemicals in the cleanest manner.