Microscale Patterning of Mesoscopic PZN-PT Single Crystal Films by Crystal ion Slicing and Laser-Induced Etching

Advances in the fabrication of solid-solution single crystal relaxor ferroelectrics have made it possible to produce highly efficient piezoelectric crystals, and have attracted renewed interest in the use of these crystals for a new generation of piezoelectric transducers, actuators and sensors. Of particular interest is their incorporation into micro-electromechanical systems (MEMS). In this paper we report on the laser-induced wet chemical etching of lead zinc niobate-lead titanate (PZN-PT) in hydrochloric acid (HCl). Argon-ion laser radiation at power levels up to 4 W is focused to a spot diameter of about 15μm and results in the chemical etching of grooves at patterning speeds up to 5μm/sec. Crystal ion slicing, an ion-implant-based film separation technique, is used in combination with laser etching to form 5 to 10μm-thick patterned and freestanding films for incorporation into micro-electromechanical devices.     

Inference and retrieval of facial images

Attempts have been made to extend SQL to work with multimedia databases. We are reserved on the representation ability of extended SQL to cope with the richness in content of multimedia data. In this paper we present an example of a multimedia database system, Computer Aided Facial Image Inference and Retrieval system (CAFIIR). The system stores and manages facial images and criminal records, providing necessary functions for crime identification. We would like to demonstrate some core techniques for multimedia database with CAFIIR system. Firstly, CAFIIR is a integrated system. Besides database management, there are image analysis, image composition, image aging, and report generation subsystems, providing means for problem solving. Secondly, the richness of multimedia data urges feature-based database for their management. CAFIIR is feature-based. A indexing mechanism,iconic index, has been proposed for indexing facial images using hierarchical self-organization neural network. The indexing method operates on complex feature measures and provides means for visual navigation. Thirdly, special retrieval methods for facial images have been developed, including visual browsing, similarity retrieval, free text retrieval and fuzzy retrieval.     

Comparison of Markov model and fault tree approach in determining initiating event frequency for systems with two train configurations

This study explores the use of Markov models in some areas of systems analysis in which time evolution of the system may be a significant factor in influencing the system reliability or availability. Comparisons are made between the Markov models and the time-averaged fault tree models for determining support system failure initiating event frequency in a nuclear power plant, for both power and shutdown conditions. Factors affecting consistency between the fault tree approach and the Markov model approach are studied for systems with common two train configurations. A correlation is developed to estimate the ratio between initiator frequencies through both approaches for a two parallel component system. Insights are developed as to when time averaged and simplified fault tree models support a good approximation to the more rigorous time-dependent Markov models.     

Value management and common accounting performance measures for corporations

Management is aware that the value of firms is the ultimate measure of company performance. However, management has been using common accounting measures as an operating guide because the linkage between operational planning and value is vague and complex and, therefore, difficult to apply. Managers need to have clear targets and performance measures to track progress. This paper examines if a set of common accounting performance measures are linked tightly to the overall value of the firm. An abductive learning network (ALN) approach, an artificial intelligence technique, is used in this research because an ALN approach is non-parametric and can capture a subtle dynamic relationship between input and output variables, which is not obvious in linear statistical analysis. Empirical results show that an ALN model is very effective in synthesizing the value of the firm using six common accounting variables. The results also provide four strategic variables that can be used for devising strategic and operating plans to maximize the value of firms.     

Flux Jumps and H-T Diagram of Instability for MgB2

We present a study of magneto-thermal instabilities in polycrystalline MgB₂ superconductor, by magnetic hysteresis loop measurements and by investigations of magnetic flux dynamics with a miniature Hall probe. Temperature and magnetic field ranges where the flux jumps may be observed have been determined. On the basis of measurements of the magnetic flux dynamics, an average magnetic diffusivity describing the process of the flux jump is estimated. This parameter is compared with the thermal and magnetic diffusivities calculated on the basis of available data for thermal conductivity, heat capacity and resistivity. It is shown that the estimated value of the field of the first flux jump is influenced significantly by the field dependence of specific heat. In order to explain the observed phenomenon, the temperature reached by the sample during the flux jump at different magnetic fields is calculated.     

On solving constrained optimization problems with neural networks:a penalty method approach

Deals with the use of neural networks to solve linear and nonlinear programming problems. The dynamics of these networks are analyzed. In particular, the dynamics of the canonical nonlinear programming circuit are analyzed. The circuit is shown to be a gradient system that seeks to minimize an unconstrained energy function that can be viewed as a penalty method approximation of the original problem. Next, the implementations that correspond to the dynamical canonical nonlinear programming circuit are examined. It is shown that the energy function that the system seeks to minimize is different than that of the canonical circuit, due to the saturation limits of op-amps in the circuit. It is also noted that this difference can cause the circuit to converge to a different state than the dynamical canonical circuit. To remedy this problem, a new circuit implementation is proposed.     

Molecular Mechanisms Underlying the Beneficial Effects of Exercise on Brain Function and Neurological Disorders

As life expectancy has increased, particularly in developed countries, due to medical advances and increased prosperity, age-related neurological diseases and mental health disorders have become more prevalent health issues, reducing the well-being and quality of life of sufferers and their families. In recent decades, due to reduced work-related levels of physical activity, and key research insights, prescribing adequate exercise has become an innovative strategy to prevent or delay the onset of these pathologies and has been demonstrated to have therapeutic benefits when used as a sole or combination treatment. Recent evidence suggests that the beneficial effects of exercise on the brain are related to several underlying mechanisms related to muscle–brain, liver–brain and gut–brain crosstalk. Therefore, this review aims to summarize the most relevant current knowledge of the impact of exercise on mood disorders and neurodegenerative diseases, and to highlight the established and potential underlying mechanisms involved in exercise–brain communication and their benefits for physiology and brain function.     

Maternal Exposure to Dibutyl Phthalate (DBP) or Diethylstilbestrol (DES) Leads to Long-Term Changes in Hypothalamic Gene Expression and Sexual Behavior

Xenobiotic exposure during pregnancy and lactation has been linked to perinatal changes in male reproductive outcomes and other endocrine parameters. This pilot study wished to assess whether brief maternal exposure of rats to xenobiotics dibutyl phthalate (DBP) or diethylstilbestrol (DES) might also cause long-term changes in hypothalamic gene expression or in reproductive behavior of the resulting offspring. Time-mated female Sprague Dawley rats were given either DBP (500 mg/kg body weight, every second day from GD14.5 to PND6), DES (125 µg/kg body weight at GD14.5 and GD16.5 only), or vehicle (n = 8–12 per group) and mild endocrine disruption was confirmed by monitoring postnatal anogenital distance. Hypothalamic RNA from male and female offspring at PND10, PND24 and PND90 was analyzed by qRT-PCR for expression of aromatase, oxytocin, vasopressin, ER-alpha, ER-beta, kisspeptin, and GnRH genes. Reproductive behavior was monitored in male and female offspring from PND60 to PND90. Particularly, DES treatment led to significant changes in hypothalamic gene expression, which for the oxytocin gene was still evident at PND90, as well as in sexual behavior. In conclusion, maternal xenobiotic exposure may not only alter endocrine systems in offspring but, by impacting on brain development at a critical time, can have long-term effects on male or female sexual behavior.     

Quest for the Crypto-phosphoproteome

Protein phosphorylation is one of the most studied post-translational modifications (PTMs). Despite the remarkable advances in phosphoproteomics, a chemically less-stable subset of the phosphosites, which we call the crypto-phosphoproteome, has remained underexplored due to technological challenges. In this Viewpoint, we briefly summarize the current understanding of these elusive protein phosphorylations and identify the missing pieces for future studies.