Trends in family psychology.

Presents an overview of the recent past, the present, and anticipated future trends in the field of family psychology (i.e., the scientific study of the family in terms of its historical forms and variations; structure and functioning across time, space, culture, and generations; and idiosyncratic and systems attributes). Areas discussed include availability of graduate education in family psychology, internship availability, postgraduate training opportunities, clinical practice, research and publications, ethical and legal concerns, credentialing, and impact on other family therapy organizations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Novel optimized tree-based stack-type architecture for 2n-bit comparator at nanoscale with energy dissipation analysis

Comparator is an essential building block in many digital circuits such as biometric authentication, data sorting, and exponents comparison in floating-point architectures among others. Quantum-dot Cellular Automata (QCA) is a latest nanotechnology that overcomes the drawbacks of Complementary Metal Oxide Semiconductor (CMOS) technology. In this paper, novel area optimized 2n-bit comparator architecture is proposed. To achieve the objective, 1-bit stack-type and 4-bit tree-based stack-type (TB-ST) comparators are proposed using QCA. Then, two tree-based architectures of 4-bit comparators are arranged in two layers to optimize the number of quantum cells and area of an 8-bit comparator. Thus, this design can be extended to any 2n-bit comparator. Simulation results of 4-bit and 8-bit comparators using QCADesigner 2.0.3 show that there is a significant improvement in the number of quantum cells and area occupancy. The proposed TB-ST 8-bit comparator uses 2.5 clock cycles and 622 quantum cells with area occupancy of 0.49 µm² which is an improvement by 10.5% and 38%, respectively, compared to existing designs. Scaling it to a 32-bit comparator, the proposed architecture requires only 2675 quantum cells in an area of 2.05 µm² with a delay of 3.5 clock cycles, indicating 9.35% and 28.8% improvements, respectively, demonstrating the merit of the proposed architecture. Besides, energy dissipation analysis of the proposed TB-ST 8-bit comparator is simulated on QCADesigner-E tool, indicating average energy dissipation reduction of 17.3% compared to existing works.

     

Verfahren zur Anreicherung von Stearidonsäure

Preparation of Stearidonic Acid Concentrates Fatty acids of the n-3 series are precursors of the biochemical synthesis of prostaglandins which are known as inhibitors of blood platelet aggregation. The parent compound of this series, α-linolenic acid (ALA), is transformed to stearidonic acid C18:4 δ6.9, 12.15 (SA) by catalysis by the liver enzyme δ6-desaturase. SA is found in few natural materials such as fish oils and blackcurrent seed oil (BCO) and only at low concentrations. In this context the oil extracted from entrails of squids caught in warm-water seas is reported to present an interesting source of arachidonic acid with contents of up to 8%. A two-step procedure was developed for the preparation of SA concentrates with 15% SA was obtained by urea fractionation. Simultaneously the γ-linolenic acid (GLA) concentration was increased to 80%. Subsequent separation of SA from GLA was carried out by preparative HPLC yielding SA concentrates with a purity of ≧ 90%. These SA concentrates were used for a comparative investigation of the inhibiting effects of some polyunsaturated fatty acids such as GLA, ALA or eicosapentaenoic acid on blood platelet aggregation. It was found that, compared with the other fatty acids. SA inhibits more specifically the aggregation stimulated by thrombine.     

Sodium Coordination Environments in Silica Films

The local structure centered on sodium after diffusion in silica (Na-SiO₂ samples) has been determined by means of extended X-ray absorption fine structure (EXAFS) studies. The Na-SiO₂ samples are of particular interest because (i) their sodium content can be varied over a wide range of concentration and (ii) their local structure is representative of that of soda–silica glass. EXAFS analyses reveal the existence of a well-defined local structure involving oxygen, sodium, and silicon neighbors. The Na-O, Na-Na, and Na-Si bonds lengths, which amount to 0.23, 0.30, and 0.38 nm, respectively, do not depend on sodium concentration. This environment closely resembles that found in soda–silica glass. Moreover, it is compatible with the "target site" and "the site memory effect" suggested by recent theories of the ionic conductivity in oxide glasses.     

Linking the proteins--elucidation of proteome-scale networks using mass spectrometry

Proteomes are intricate. Typically, thousands of proteins interact through physical association and post-translational modifications (PTMs) to give rise to the emergent functions of cells. Understanding these functions requires one to study proteomes as "systems" rather than collections of individual protein molecules. The abstraction of the interacting proteome to "protein networks" has recently gained much attention, as networks are effective representations, that lose specific molecular details, but provide the ability to see the proteome as a whole. Mostly two aspects of the proteome have been represented by network models: proteome-wide physical protein-protein-binding interactions organized into Protein Interaction Networks (PINs), and proteome-wide PTM relations organized into Protein Signaling Networks (PSNs). Mass spectrometry (MS) techniques have been shown to be essential to reveal both of these aspects on a proteome-wide scale. Techniques such as affinity purification followed by MS have been used to elucidate protein-protein interactions, and MS-based quantitative phosphoproteomics is critical to understand the structure and dynamics of signaling through the proteome. We here review the current state-of-the-art MS-based analytical pipelines for the purpose to characterize proteome-scale networks.     

An enhanced encryption algorithm for video based on multiple Huffman tables

Encryption is one of the fundamental technologies that is used in the security of multimedia data. Unlike ordinary computer applications, multimedia applications generate large amount of data that has to be processed in real time. This work investigates the problem of efficient multimedia data encryption. A scheme known as the Randomized Huffman Table scheme was recently proposed to achieve encryption along with compression. Though this scheme has several advantages it cannot overcome the chosen plaintext attack. An enhancement of this Huffman scheme is proposed in this work which essentially overcomes the attack and improves the security. The proposed encryption approach consists of two modules. The first module is the Randomized Huffman Table module, the output of which is fed to the second XOR module to enhance the performance. Security analysis shows that the proposed scheme can withstand the chosen plaintext attack. The efficiency and security of the proposed scheme makes it an ideal choice for real time secure multimedia applications.     

Ferritin Protein Regulates the Degradation of Iron Oxide Nanoparticles

Proteins implicated in iron homeostasis are assumed to be also involved in the cellular processing of iron oxide nanoparticles. In this work, the role of an endogenous iron storage protein—namely the ferritin—is examined in the remediation and biodegradation of magnetic iron oxide nanoparticles. Previous in vivo studies suggest the intracellular transfer of the iron ions released during the degradation of nanoparticles to endogenous protein cages within lysosomal compartments. Here, the capacity of ferritin cages to accommodate and store the degradation products of nanoparticles is investigated in vitro in the physiological acidic environment of the lysosomes. Moreover, it is questioned whether ferritin proteins can play an active role in the degradation of the nanoparticles. The magnetic, colloidal, and structural follow‐up of iron oxide nanoparticles and proteins in lysosome‐like medium confirms the efficient remediation of potentially harmful iron ions generated by nanoparticles within ferritins. The presence of ferritins, however, delays the degradation of particles due to a complex colloidal behavior of the mixture in acidic medium. This study exemplifies the important implications of intracellular proteins in processes of degradation and metabolization of iron oxide nanoparticles.     

Conjugate mixture models for clustering multimodal data

The problem of multimodal clustering arises whenever the data are gathered with several physically different sensors. Observations from different modalities are not necessarily aligned in the sense there there is no obvious way to associate or compare them in some common space. A solution may consist in considering multiple clustering tasks independently for each modality. The main difficulty with such an approach is to guarantee that the unimodal clusterings are mutually consistent. In this letter, we show that multimodal clustering can be addressed within a novel framework: conjugate mixture models. These models exploit the explicit transformations that are often available between an unobserved parameter space (objects) and each of the observation spaces (sensors). We formulate the problem as a likelihood maximization task and derive the associated conjugate expectation-maximization algorithm. The convergence properties of the proposed algorithm are thoroughly investigated. Several local and global optimization techniques are proposed in order to increase its convergence speed. Two initialization strategies are proposed and compared. A consistent model selection criterion is proposed. The algorithm and its variants are tested and evaluated within the task of 3D localization of several speakers using both auditory and visual data.