A Triple Pore Network Model (T-PNM) for Gas Flow Simulation in Fractured,Micro-porous and Meso-porous Media

Transport in Porous Media - In this study, a novel triple pore network model (T-PNM) is introduced which is composed of a single pore network model (PNM) coupled to fractures and micro-porosities....     

Carbon nanotube dielectrophoresis: Theory and applications

Carbon nanotubes (CNTs) are one of the most extensively studied nanomaterials in the 21st century. Since their discovery in 1991, many studies have been reported advancing our knowledge in terms of their structure, properties, synthesis, and applications. CNTs exhibit unique electrothermal and conductive properties which, combined with their mechanical strength, have led to tremendous attention of CNTs as a nanoscale material in the past two decades. To introduce the various types of CNTs, we first provide basic information on their structure followed by some intriguing properties and a brief overview of synthesis methods. Although impressive advances have been demonstrated with CNTs, critical applications require purification, positioning, and separation to yield desired properties and functional elements. Here, we review a versatile technique to manipulate CNTs based on their dielectric properties, namely dielectrophoresis (DEP). A detailed discussion on the DEP aspects of CNTs including the theory and various technical microfluidic realizations is provided. Various advancements in DEP-based manipulations of single-walled and multiwalled CNTs are also discussed with special emphasis on applications involving separation, purification, sensing, and nanofabrication.     

Active transient elasto-acoustic response damping of a thick-walled liquid-coupled piezolaminated cylindrical vessel

The linear 3D piezoelasticity theory in conjunction with the versatile transfer matrix approach and the wave equation for the internal acoustic domain are employed for active non-stationary vibroacoustic response control of an arbitrarily thick, tri-laminate, fluid-filled, simply supported, piezocomposite cylindrical tank, excited by arbitrary (non-axisymmetric) time-dependent on-surface mechanical loads. The smart structure is composed of a supporting core layer of functionally graded orthotropic material perfectly bonded to inner and outer spatially distributed radially polarized functionally graded piezoceramic sensor and uniform force actuator (FGPM) layers. Active vibration damping is implemented by transferring the accumulated voltage on the sensor layer to the piezoelectric actuator layer in context of proportional and derivative control laws. Durbin's numerical inverse Laplace transform scheme is utilized to calculate the time response histories of the relevant interface displacement/stress components, center-point acoustic pressure, and actuator voltage, for selected loading configurations (i.e., concentrated step, impulse, and moving external loads). Numerical simulations demonstrate the effectiveness of the adopted distributed sensing/actuation configuration together with the active damping control strategy in suppressing the vibroacoustic response of a three-layered (Ba₂NaNb₅O₁₅/Al/PZT4) water-filled piezoelastic cylindrical tank. Limiting cases are considered and the validity of results is established by comparison with the available data as well as with the aid of a commercial finite element package.     

A decision support system for order acceptance/rejection in hybrid MTS/MTO production systems

In this paper, we present a novel decision support system for order acceptance/rejection in a hybrid Make-to-Stock/Make-to-Order production environment. The proposed decision support system is comprised of five steps. At the first step, the customers are prioritized based on a fuzzy TOPSIS method. Rough-cut capacity and rough-cut inventory are calculated in the second step and in case of unavailability in capacity and materials, some undesirable orders are rejected. Also, proper decisions are made about non-rejected orders. At the next step, prices and delivery dates of the non-rejected orders are determined by running a mixed-integer mathematical programming model. At the fourth step, a set of guidelines are proposed to help the organization negotiate over price and due date with the customers. In the next step, if the customer accepts the offered price and delivery date, the order is accepted and later considered in the production schedule of the shop floor, otherwise the order is rejected. Finally, numerical experiments are conducted to show the tractability of the applied mathematical programming model.     

Stretch-induced stress patterns and wrinkles in hyperelastic thin sheets

Wrinkles are commonly observed in stretched thin sheets and membranes. This paper presents a numerical study on stretch-induced wrinkling of hyperelastic thin sheets based on nonlinear finite element analyses. The model problem is set up for uniaxial stretching of a rectangular sheet with two clamped ends and two free edges. A two-dimensional stress analysis is performed first under the plane-stress condition to determine stretch-induced stress distribution patterns in the elastic sheets, assuming no wrinkles. As a prerequisite for wrinkling, development of compressive stresses in the transverse direction is found to depend on both the length-to-width aspect ratio of the sheet and the applied tensile strain in the longitudinal direction. A phase diagram is constructed with four different distribution patterns of the stretch-induced compressive stresses, spanning a wide range of aspect ratio and tensile strain. Next, an eigenvalue analysis is performed to find the potential buckling modes of the elastic sheet under the prescribed boundary conditions. Finally, a nonlinear post-buckling analysis is performed to show evolution of stretch-induced wrinkles. In addition to the aspect ratio and tensile strain, it is found that the critical condition for wrinkling and the post-buckling behavior both depend sensitively on the sheet thickness. In general, wrinkles form only when both the magnitude and the distribution area of the compressive stresses are sufficiently large. The wrinkle wavelength decreases with increasing strain, in good agreement with the prediction by a scaling analysis. However, as the tensile strain increases, the wrinkle amplitude first increases and then decreases, eventually flattened beyond a moderately large critical strain, in contrast to the scaling analysis.     

Direct lactonization of α-amino γ,δ-unsaturated carboxylic acid esters via olefin activation: stereo- and regioselective production of homoserine lactone scaffolds having contiguous stereocenters

Triflic acid-mediated stereoselective direct lactonization of a variety of α-amino γ,δ-unsaturated carboxylic acid esters and the construction of new γ-butyrolactone structural motifs are reported. Several α-amino γ,δ-unsaturated carboxylic acid esters underwent stereo- and regioselective 1,5-cyclization and afforded a variety of highly substituted homoserine lactone scaffolds having contiguous stereocenters. The direct lactonization of the chiral α-amino γ,δ-unsaturated carboxylic acid esters with triflic acid led to the enantioselective synthesis of the novel homoserine lactones. A plausible mechanism for the direct lactonization of α-amino γ,δ-unsaturated carboxylic acid esters is presented. The stereochemistry of major isomers 3f, 7a, 7b, and 7d was unambiguously established from the X-ray structure analysis.     

Production and evaluation of a 67Ga-labeled anti-Ror1 monoclonal antibody in a mouse model of breast cancer

Journal of Radioanalytical and Nuclear Chemistry - Receptor tyrosine kinase Ror1 is widely expressed during embryogenesis but it is absent within most mature tissues. However, expression of Ror1...     

A Review on Machine Learning Approaches for Network Malicious Behavior Detection in Emerging Technologies

Network anomaly detection systems (NADSs) play a significant role in every network defense system as they detect and prevent malicious activities. Therefore, this paper offers an exhaustive overview of different aspects of anomaly-based network intrusion detection systems (NIDSs). Additionally, contemporary malicious activities in network systems and the important properties of intrusion detection systems are discussed as well. The present survey explains important phases of NADSs, such as pre-processing, feature extraction and malicious behavior detection and recognition. In addition, with regard to the detection and recognition phase, recent machine learning approaches including supervised, unsupervised, new deep and ensemble learning techniques have been comprehensively discussed; moreover, some details about currently available benchmark datasets for training and evaluating machine learning techniques are provided by the researchers. In the end, potential challenges together with some future directions for machine learning-based NADSs are specified.