Synthesis and characterization of a titanium phosphate-tellurite glass for Faraday rotators

This work is focused on investigation of thermal, structural, optical, magnetic, and magneto-optical properties of novel titanium phosphate-tellurite glass applied as Faraday rotators. The glass belonging to the system 35Li₂O–10Al₂O₃–5TiO₂–45P₂O₅–5TeO₂ was prepared by a nonconventional wet route of raw materials processing, followed by melting-quenching-annealing steps. Some important physical properties of the investigated glass have been measured and calculated, providing knowledge related to glass compactness, electronic structure, glass forming capability, etc. XRD analysis evidenced an amorphous network structure of the investigated glass. The optical absorption in the Vis domain is mainly due to Ti³⁺ ions and Te₂ clusters formed during the glass melting process. A relatively low optical absorption is noticed over 600 nm that activates a significant Faraday magneto-optical effect. Photoluminescence bands in the blue, red, and infrared domains are observed, caused by Te₂ clusters formed during the glass melting process. The magnetization in dependency on applied magnetic field reveals a complex behavior of the glass, depending on temperature. Thus, it is found a ferromagnetic behavior up to 2000 Oe, a paramagnetic component up to 40 000 Oe, followed by a diamagnetic one over 40 000 Oe. Faraday rotation angle and Verdet constant values in the visible domain are correlated with the reduced TeO₂ content of the glass.     

The production of volatile compounds in model casein systems with varying fat levels as affected by low-frequency ultrasound

The effects of low-frequency ultrasound on the production of volatile compounds in model casein protein systems containing various fat concentrations of 2%, 4% and 6% (w/w) were investigated. Ultrasound application was performed at 20 kHz for up to 10 min which corresponded to energy densities ranging from 9.54 to 190.8 J mL⁻¹. Similar volatile compounds were detected both in pure fat and mixtures of casein and fat (CF) systems. These volatiles belonged to the groups of aldehydes, ketones, esters, alcohols and hydrocarbons, which were the products of oxidation of lipids or protein degradation due to acoustic cavitation. The amount of fat in the casein systems had minor effects on the production of volatiles, whereas the production of volatile compounds was significantly affected by the ultrasound treatment. Short sonication times <5 min generated similar volatile profiles to the untreated samples. In contrast, prolonged sonication for 5 and 10 min considerably increased the production of volatile compounds and the amounts of fatty acids. Thus, the application of low–frequency ultrasound for short periods should be considered to minimise the production of volatile compounds which can ultimately affect the taste.     

Embedding new observations via sparse-coding for non-linear manifold learning

Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data—the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance.     

Advances in Catalyst Systems for the Asymmetric Hydrogenation and Transfer Hydrogenation of Ketones

Hydrogenation of prochiral ketones using chiral transition-metal catalysts represents the cleanest way to access enantiomerically enriched secondary alcohols, which are important building blocks in fine chemicals synthesis. Despite excellent activity, selectivity and compatibility of metal complexes with variety of functional groups, no universal catalysts exist. In this article we summarize the advances in catalyst systems for the asymmetric homogenous and heterogenous hydrogenation of ketones that have been made in past decade. The development of catalysts is oriented in reaching as high as activity with low catalyst loadings, using “greener’’ conditions, and ensuring good recyclability of catalysts. Even though ruthenium complexes represent the largest part of the catalysts, other metals rapidly penetrate this field.     

Surface‐enhanced fluorescence of in situ synthesized polysilanesilver nanoparticles

To produce surface plasmons, silver nanoparticles are synthesized in situ in a pseudo‐template system based on polyhydrosilanes. Adsorption on the silver nanoparticle surface produces a thin layer of polymer with properties different from those of bulk polysilane. The metal‐adsorbed polymer layer serves as a spacer between the polysilane fluorophore and the plasmonic nanoparticle. This prevents quenching of the polysilane emission and leads to a strong surface‐enhanced fluorescence through coupling of surface plasmons having a resonance frequency that matches the emission frequency of the polymeric emitter. Copyright © 2012 Society of Chemical Industry     

Inferring competitive role patterns in reality TV show through nonverbal analysis

This paper introduces a new facet of social media, namely that depicting social interaction. More concretely, we address this problem from the perspective of nonverbal behavior-based analysis of competitive meetings. For our study, we made use of “The Apprentice” reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person’s role in a meeting: predicting the person with the highest status, and predicting the fired candidates. We address this problem by adopting both supervised and unsupervised strategies. The current study was carried out using nonverbal audio cues. Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. The analysis is based on two types of data: individual and relational measures. Results obtained from the analysis of a full season of the show are promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach has been conveniently compared with the Influence Model, demonstrating its superiority.     

Impact of the initial moisture level and pre-wetting history of recycled concrete aggregates on their water absorption

Initial moisture and pre-wetting method influence on the water absorption of recycled concrete aggregates (RCA) have been studied experimentally. For this purpose, RCA were pre-wetted by three methods: soaking under partial vacuum (simulating long term wetting), soaking under atmospheric pressure, and spraying (simulating short term wetting). The results show that the same initial amount of water in two samples of RCA do not lead to the same total amount of water absorbed by RCA during 5–120 min. The latter depends on the way they have been pre-wetted (either long term or short term). It is suggested that this phenomenon is related to the accessibility filled pores in the different pre-wetting methods. So, the pre-wetting history of RCA could change the amount of total water absorbed by the RCA up to 1%. When mixing and casting concrete are produced with RCA, the corresponding error in the determination of the effective water should have adverse effects on the fresh and hardened concrete characteristics. In this study real applications on mixtures of recycled concrete have been carried out, where the influence of initial moisture content and pre-wetting history of RCA on fresh recycled concrete properties (slump) have been investigated.     

Synthesis,structural and morphological characteristics,magnetic and optical properties of Co doped ZnO nanoparticles

Zn_1−xCo_xO (x==0.05, 0.10, 0.15) nanoparticles have been synthesized by an alternative wet-chemical synthesis route using the SimAdd technique. The as-obtained powders were investigated by FT-IR spectroscopy, X-ray diffraction and thermal analysis correlated with evolved gas analysis (TG–DTA–FT-IR) in order to determine their chemical nature, crystalline structure and to establish the decomposition sequences. The precipitates are generally amorphous, but low-intensity reflection peaks assigned both to the zinc oxalate dihydrate, and zinc hydroxide can be observed in the recorded patterns, indicating that hydroxy-oxalate precipitates were obtained. The structure, morphology and magnetic properties of the thermally treated samples have been investigated by X-ray diffraction, FT-IR, HRTEM, SAED, UV–vis and EPR. XRD studies reveal a hexagonal wurtzite-type structure for all Zn_1−xCo_xO samples. TEM investigations show particle size between 28 and 37 nm, with spherical and polyhedral shapes and with tendency to form aggregates. The presence of a Co₃O₄ secondary phase was evidenced by XRD, UV–vis and EPR for the Zn_0.85Co_0.15O sample. The ferromagnetic behavior of the samples was revealed. The paper highlights that by varying the cobalt concentration it is possible to modulate the structural, morphological, optical and magnetic properties.     

Dynamic method for software test data generation

Test data generation in program testing is the process of identifying a set of test data which satisfies a given testing criterion. Existing pathwise test data generators proceed by selecting program paths that satisfy the selected criterion and then generating program inputs for these paths. One of the problems with this approach is that unfeasible paths are often selected; as a result, significant computational effort can be wasted in analysing those paths. In this paper, an approach to test data generation, referred to as a dynamic approach for test data generation, is presented. In this approach, the path selection stage is eliminated. Test data are derived based on the actual execution of the program under test and function minimization methods. The approach starts by executing a program for an arbitrary program input. During program execution for each executed branch, a search procedure decides whether the execution should continue through the current branch or an alternative branch should be taken. If an undesirable execution flow is observed at the current branch, then a real-valued function is associated with this branch, and function minimization search algorithms are used to locate values of input variables automatically, which will change the flow of execution at this branch.