Modeling drop breakage using the full energy spectrum and a specific realization of turbulence anisotropy

The assumption of homogeneous isotropic turbulence when modeling drop breakage in industrially relevant geometries is questionable. We describe the development of an anisotropic breakage model, where the anisotropy is introduced via the inclusion of a perturbed turbulence spectrum. The selection of the perturbed spectrum is itself motivated by our previous large-eddy simulations of high-pressure homogenizers. The model redistributes energy from small to large scales, and assumes that the anisotropic part of the Reynolds stresses is confined to the energy-containing range. The second-order structure function arising from the perturbed spectrum is used in the standard framework of Coulaloglou and Tavlarides to calculate breakage frequency. While the base model exhibits non-monotonic behavior (by predicting a maximum value for a certain drop size), the effect of anisotropy is shown to increase breakage frequency in length scales larger than this peak, thereby reducing non-monotonicity. This effect is more pronounced for small turbulence Reynolds numbers.     

Numerical simulation of atomic layer deposition for thin deposit formation in a mesoporous substrate

ZnO deposition in porous γ-Al₂O₃ via atomic layer deposition (ALD) is the critical first step for the fabrication of zeolitic imidazolate framework membranes using the ligand-induced perm-selectivation process (Science, 361 (2018), 1008–1011). A detailed computational fluid dynamics (CFD) model of the ALD reactor is developed using a finite-volume-based code and validated. It accounts for the transport processes within the feeding system and reaction chamber. The simulated precursor spatiotemporal profiles assuming no ALD reaction were used as boundary conditions in modeling diethylzinc reaction/diffusion in porous γ-Al₂O₃, the predictions of which agreed with experimental electron microscopy measurements. Further simulations confirmed that the present deposition flux is much less than the upper limit of flux, below which the decoupling of reactor/substrate is an accurate assumption. The modeling approach demonstrated here allows for the design of ALD processes for thin-film membrane formation including the synthesis of metal–organic framework membranes.     

Superparamagnetic polyvinylpyrrolidone/chitosan/Fe3O4 electrospun nanofibers as effective U(VI) adsorbents

Magnetoactive electrospun fibrous membranes consisting of polyvinylpyrrolidone (PVP), chitosan (CS) and pre-fabricated, double-layer oleic acid-coated magnetite nanoparticles (OA.OA.Fe₃O₄) were fabricated and evaluated as new adsorbent materials for the removal and recovery of uranium (U(VI)) from aqueous solutions. The adsorption has been investigated by batch-type experiments and the solid material has been characterized by X-ray diffraction spectroscopy (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy/energy dispersive X-ray analysis (TEM/EDX) and vibration sample magnetometry (VSM) measurements prior and after uranium adsorption. The experimental adsorption data were found to be well fitted with the Langmuir isotherm and the pseudo-second order kinetic model. The results indicate that PVP/CS/OA.OA.Fe₃O₄ fibrous adsorbents exhibit good adsorption properties towards U(VI) in aqueous solutions, achieving a q_max value of 0.77 mol kg⁻¹ (183.3 mg g⁻¹) at pH 6.0. The experiments regarding the regeneration and reuse of the magnetoactive adsorbents were carried out using Na₂CO₃, at pH ~11. After four cycles, the percentage relative adsorption remained stable (~100%) whereas the desorption percentage decreased from 31.9% to 21.0%. Generally, the presented results demonstrate that the incorporation of the Fe₃O₄ NPs has a positive effect on the adsorption efficiency of U(VI) from aquatic environments.     

Enforcing Efficient Equilibria in Network Design Games via Subsidies

The efficient design of networks has been an important engineering task that involves challenging combinatorial optimization problems. Typically, a network designer has to select among several alternatives which links to establish so that the resulting network satisfies a given set of connectivity requirements and the cost of establishing the network links is as low as possible. The Minimum Spanning Tree problem, which is well-understood, is a nice example.In this paper, we consider the natural scenario in which the connectivity requirements are posed by selfish users who have agreed to share the cost of the network to be established according to a well-defined rule. The design proposed by the network designer should now be consistent not only with the connectivity requirements but also with the selfishness of the users. Essentially, the users are players in a so-called network design game and the network designer has to propose a design that is an equilibrium for this game. As it is usually the case when selfishness comes into play, such equilibria may be suboptimal. In this paper, we consider the following question: can the network designer enforce particular designs as equilibria or guarantee that efficient designs are consistent with users’ selfishness by appropriately subsidizing some of the network links? In an attempt to understand this question, we formulate corresponding optimization problems and present positive and negative results.     

Speed Scaling for Maximum Lateness

We consider the power-aware problem of scheduling non-preemptively a set of jobs on a single speed-scalable processor so as to minimize the maximum lateness, under a given budget of energy. In the offline setting, our main contribution is a combinatorial polynomial time algorithm for the case in which the jobs have common release dates. In the presence of arbitrary release dates, we show that the problem becomes strongly \(\mathcal {N}\mathcal {P}\)-hard. Moreover, we show that there is no O(1)-competitive deterministic algorithm for the online setting in which the jobs arrive over time. Then, we turn our attention to an aggregated variant of the problem, where the objective is to find a schedule minimizing a linear combination of maximum lateness and energy. As we show, our results for the budget variant can be adapted to derive a similar polynomial time algorithm and an \(\mathcal {N}\mathcal {P}\)-hardness proof for the aggregated variant in the offline setting, with common and arbitrary release dates respectively. More interestingly, for the online case, we propose a 2-competitive algorithm.     

Texture and shape information fusion for facial expression and facial action unit recognition

A novel method based on fusion of texture and shape information is proposed for facial expression and Facial Action Unit (FAU) recognition from video sequences. Regarding facial expression recognition, a subspace method based on Discriminant Non-negative Matrix Factorization (DNMF) is applied to the images, thus extracting the texture information. In order to extract the shape information, the system firstly extracts the deformed Candide facial grid that corresponds to the facial expression depicted in the video sequence. A Support Vector Machine (SVM) system designed on an Euclidean space, defined over a novel metric between grids, is used for the classification of the shape information. Regarding FAU recognition, the texture extraction method (DNMF) is applied on the differences images of the video sequence, calculated taking under consideration the neutral and the expressive frame. An SVM system is used for FAU classification from the shape information. This time, the shape information consists of the grid node coordinate displacements between the neutral and the expressed facial expression frame. The fusion of texture and shape information is performed using various approaches, among which are SVMs and Median Radial Basis Functions (MRBFs), in order to detect the facial expression and the set of present FAUs. The accuracy achieved using the Cohn–Kanade database is 92.3% when recognizing the seven basic facial expressions (anger, disgust, fear, happiness, sadness, surprise and neutral), and 92.1% when recognizing the 17 FAUs that are responsible for facial expression development.     

A study of suspended roofs for near-source seismic motions

The non-linear behavior of multi-suspended roof systems for seismic loads is studied. The study is based on a formulation that can be easily employed for a preliminary design of multi-suspended roofs subjected to seismic loads. Specifically, applying Lagrange’s equations, the corresponding set of equations of motion for discrete models of multiple suspension roofs is obtained and numerical integration of the equations of motion is performed via the Runge–Kutta scheme. For representative realistic combinations of geometric, stiffness and damping parameters, a non-linear analysis is employed to study the behavior of suspended roofs for near-source and far-field seismic motions. The analysis demonstrates that: (i) code-specified design loads could dramatically underestimate the response of suspended roofs subjected to near-source ground motions and (ii) flexible roofing systems are greatly affected by near-source ground motions, a behavior that is not observed for stiff systems.     

Enhancing self-scheduling algorithms via synchronization and weighting

Existing dynamic self-scheduling algorithms, used to schedule independent tasks on heterogeneous clusters, cannot handle tasks with dependencies because they lack the support for internode communication. To compensate for this deficiency we introduce a synchronization mechanism that provides inter-processor communication, thus, enabling self-scheduling algorithms to handle efficiently nested loops with dependencies. We also present a weighting mechanism that significantly improves the performance of dynamic self-scheduling algorithms. These algorithms divide the total number of tasks into chunks and assign them to processors. The weighting mechanism adapts the chunk sizes to the computing power and current run-queue state of the processors. The synchronization and weighting mechanisms are orthogonal, in the sense that they can simultaneously be applied to loops with dependencies. Thus, they broaden the application spectrum of dynamic self-scheduling algorithms and improve their performance. Extensive testing confirms the efficiency of the synchronization and weighting mechanisms and the significant improvement of the synchronized–weighted versions of the algorithms over the synchronized-only versions.     

Attacking smart card systems: Theory and practice

Smart card technology has evolved over the last few years following notable improvements in the underlying hardware and software platforms. Advanced smart card microprocessors, along with robust smart card operating systems and platforms, contribute towards a broader acceptance of the technology. These improvements have eliminated some of the traditional smart card security concerns. However, researchers and hackers are constantly looking for new issues and vulnerabilities. In this article we provide a brief overview of the main smart card attack categories and their corresponding countermeasures. We also provide examples of well-documented attacks on systems that use smart card technology (e.g. satellite TV, EMV, proximity identification) in an attempt to highlight the importance of the security of the overall system rather than just the smart card.