Multilevel modeling of self-esteem change during acute inpatient stroke rehabilitation.

Objective: To explore self-esteem change during inpatient stroke rehabilitation and moderators of change. Research Method: One hundred twenty survivors of stroke serially completed the State Self-Esteem Scale (SSES) during inpatient rehabilitation, as well as measures of mood and perceived recovery as potential moderators of change. Age, gender, prior stroke, prestroke depression, stroke laterality, and admission Functional Independence Measure (FIM) self-care, mobility, and cognitive scores were also included as moderators. Results: Multilevel modeling of the repeated administrations of the SSES indicated that self-esteem significantly improved during rehabilitation. Female gender, left hemisphere stroke, prior stroke, and lower admission FIM cognitive scores were associated with lower self-esteem ratings at admission, but only age and admission FIM self-care and mobility scores were associated with self-esteem change. Older individuals showed less self-esteem improvement than younger individuals, and higher self-care and mobility scores at admission were associated with greater self-esteem improvement. While mood change significantly covaried with self-esteem, the rate of mood change did not appear to influence rate of self-esteem change. Greater improvement in self-esteem over time was related to lower levels of perceived recovery, but this was likely because of the relationship between perceived recovery and self-esteem at rehabilitation admission. Implications: These results suggest that self-esteem improves during inpatient rehabilitation, and this change may be partially dependent on functional status. Implications for facilitating self-esteem change by the clinician are discussed, as well as future research directions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Self-esteem level and stability, admission functional status, and depressive symptoms in acute inpatient stroke rehabilitation.

Objectives: Explore the relationship of self-esteem level, self-esteem stability, and admission functional status on discharge depressive symptoms in acute stroke rehabilitation. Research Method: One hundred twenty stroke survivors serially completed a measure of state self-esteem during inpatient rehabilitation and completed a measure of depressive symptoms at discharge. Functional status was rated at admission using the Functional Independence Measure (FIM). Regressions explored main effects and interactions of self-esteem level and stability and admission FIM self-care, mobility, and cognitive functioning on discharge depressive symptoms. Results: After controlling for potential moderating variables, self-esteem level interacted with FIM self-care and cognitive functioning to predict discharge depressive symptoms, such that survivors with lower self-rated self-esteem and poorer functional status indicated higher levels of depressive symptoms. Self-esteem stability interacted with FIM mobility functioning, such that self-esteem instability in the presence of lower mobility functioning at admission was related to higher depressive symptoms at discharge. Implications: These results suggest that self-esteem variables may moderate the relationship between functional status and depressive symptoms. Self-esteem level and stability may differentially moderate functional domains, although this conclusion requires further empirical support. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Synthesis,characterization and charge transport properties of Pr–Ni Co-doped SrFe2O4 spinel for high frequency devices applications

Ferrites are materials of interest due to their broad applications in high technological devices and a lot of research has been focused to synthesize new ferrites. In this regard, an effort has been devoted to synthesize spinel Pr–Ni co-substituted strontium ferrites with a nominal formula of Sr_1-xPr_xFe_2-yNi_yO₄ (0.0 ≤ x ≤ 0.1, 0.0 ≤ y ≤ 1.0). The cubic structure of pure and Pr–Ni co-substituted strontium ferrite samples calcinated at 1073 K for 3 h has been confirmed through X-ray diffraction (XRD). Average sizes of crystallites (18–25 nm) have been estimated from XRD analysis and nanometer particle sizes of synthesized ferrites have been further verified by scanning electron microscopy (SEM). SEM results have also shown that particles are mostly agglomerated and all the samples possess porosity. It has been observed that at 298 K, the values of resistivity (ρ) increase, while that of AC conductivity, dielectric loss, and dielectric constants decrease with increasing amounts of Pr³⁺ and Ni²⁺ ions. The values of dielectric parameters initially decrease with frequency and later become constant and can be explained on the basis of dielectric polarization. Electrochemical impedance spectroscopy (EIS) studies show that the charge transport phenomenon in ferrite materials is mainly controlled via grain boundaries. Overall, synthesized ferrite materials own enhanced resistivity values in the range of 1.38 × 10⁹–1.94 × 10⁹ Ω cm and minimum dielectric losses, which makes them suitable candidates for high frequency devices applications.     

Effects of repeated frying on physicochemical characteristics,oxidative stress,and free radical scavenging potential of canola oil and ghee

The repeated use of cooking oils and ghee for the deep frying of food materials may affect their nutritional quality. The present study evaluated the effect of repeated frying on the physicochemical characteristics and antiradical potential of canola oil and ghee. The oil and ghee were used for frying of fish and chicken for 2, 4, 6, 8, and 10 frying cycles followed by the analysis of physicochemical, oxidative stress, and antiradical parameters. Regression analysis of the data showed a frying cycle-dependent significant linear increase in saponification (R² = 0.9507–0.9748), peroxide and acid values (R² = 0.956–0.9915), and malondialdehyde (MDA) production (R² = 0.9058–0.9557) of canola oil and ghee subjected to fish and chicken frying but exponential increase in saponification value (R² = 0.9778) and MDA production (R² = 0.7407) of canola oil and ghee used for fish frying. The increase in the number of frying cycles linearly decreased the iodine value (R² = 0.9781–0.9924), and 1, 1-diphenyl-2-picrylhydrazyl, hydroxyl, and 2, 2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) radical scavenging potential (R² = 0.9089–0.9979) of canola oil and ghee. Repeated frying in cooking oil and ghee increases oxidative stress and decreases their physicochemical and antioxidant qualities. Canola oil was comparatively more oxidative resistant than canola ghee. The regression equations derived from regression analysis will guide researchers to conduct similar types of univariate studies.     

SNEE: a query processor for wireless sensor networks

A wireless sensor network (WSN) can be construed as an intelligent, large-scale device for observing and measuring properties of the physical world. In recent years, the database research community has championed the view that if we construe a WSN as a database (i.e., if a significant aspect of its intelligent behavior is that it can execute declaratively-expressed queries), then one can achieve a significant reduction in the cost of engineering the software that implements a data collection program for the WSN while still achieving, through query optimization, very favorable cost:benefit ratios. This paper describes a query processing framework for WSNs that meets many desiderata associated with the view of WSN as databases. The framework is presented in the form of compiler/optimizer, called SNEE, for a continuous declarative query language over sensed data streams, called SNEEql. SNEEql can be shown to meet the expressiveness requirements of a large class of applications. SNEE can be shown to generate effective and efficient query evaluation plans. More specifically, the paper describes the following contributions: (1) a user-level syntax and physical algebra for SNEEql, an expressive continuous query language over WSNs; (2) example concrete algorithms for physical algebraic operators defined in such a way that the task of deriving memory, time and energy analytical cost-estimation models (CEMs) for them becomes straightforward by reduction to a structural traversal of the pseudocode; (3) CEMs for the concrete algorithms alluded to; (4) an architecture for the optimization of SNEEql queries, called SNEE, building on well-established distributed query processing components where possible, but making enhancements or refinements where necessary to accommodate the WSN context; (5) algorithms that instantiate the components in the SNEE architecture, thereby supporting integrated query planning that includes routing, placement and timing; and (6) an empirical performance evaluation of the resulting framework.     

Two layered Genetic Programming for mixed-attribute data classification

The important problem of data classification spans numerous real life applications. The classification problem has been tackled by using Genetic Programming in many successful ways. Most approaches focus on classification of only one type of data. However, most of the real-world data contain a mixture of categorical and continuous attributes. In this paper, we present an approach to classify mixed attribute data using Two Layered Genetic Programming (L2GP). The presented approach does not transform data into any other type and combines the properties of arithmetic expressions (using numerical data) and logical expressions (using categorical data). The outer layer contains logical functions and some nodes. These nodes contain the inner layer and are either logical or arithmetic expressions. Logical expressions give their Boolean output to the outer tree. The arithmetic expressions give a real value as their output. Positive real value is considered true and a negative value is considered false. These outputs of inner layers are used to evaluate the outer layer which determines the classification decision. The proposed classification technique has been applied on various heterogeneous data classification problems and found successful.     

Hierarchical Tree Structure Based Clustering Schemes for Secure Group Communication

In recent years, many network applications are developed based on group communications (GC), in which the security has to be provided in terms of confidentiality, authenticity and integrity of messages delivered between the group members. A Hierarchical tree structure has to be constructed in such a way that it can handle large dynamic groups with the effective key formation and key distribution. In this paper, an Optimal Cluster Hierarchical Tree (OCHT) structure is presented for effective group communication. The proposed OCHT structure provides a novel solution for multicast key management with decentralized architecture to ensure scalability, reliability and cost effectiveness. Simulation results reveal that proposed OCHT based decentralized architectures provide better performance when compared with existing Logical Hierarchical Tree (LKH). The parameters used for simulation are Memory Overhead, Throughput, Packet Delivery Ratio, End-to-End Latency and Energy consumption.     

High‐Performance 2.6 V Aqueous Asymmetric Supercapacitors based on In Situ Formed Na0.5MnO2 Nanosheet Assembled Nanowall Arrays

The voltage limit for aqueous asymmetric supercapacitors is usually 2 V, which impedes further improvement in energy density. Here, high Na content Birnessite Na_0.5MnO₂ nanosheet assembled nanowall arrays are in situ formed on carbon cloth via electrochemical oxidation. It is interesting to find that the electrode potential window for Na_0.5MnO₂ nanowall arrays can be extended to 0–1.3 V (vs Ag/AgCl) with significantly increased specific capacitance up to 366 F g^?1. The extended potential window for the Na_0.5MnO₂ electrode provides the opportunity to further increase the cell voltage of aqueous asymmetric supercapacitors beyond 2 V. To construct the asymmetric supercapacitor, carbon‐coated Fe₃O₄ nanorod arrays are synthesized as the anode and can stably work in a negative potential window of ?1.3 to 0 V (vs Ag/AgCl). For the first time, a 2.6 V aqueous asymmetric supercapacitor is demonstrated by using Na_0.5MnO₂ nanowall arrays as the cathode and carbon‐coated Fe₃O₄ nanorod arrays as the anode. In particular, the 2.6 V Na_0.5MnO₂//Fe₃O₄@C asymmetric supercapacitor exhibits a large energy density of up to 81 Wh kg^?1 as well as excellent rate capability and cycle performance, outperforming previously reported MnO₂‐based supercapacitors. This work provides new opportunities for developing high‐voltage aqueous asymmetric supercapacitors with further increased energy density.     

Influence of Mn Ions’ Insertion in Pseudo-Tetragonal Phased CaBi4Ti4O15-Based Ceramics for Highly Efficient Energy Storage Devices and High-Temperature Piezoelectric Applications

In the present era of advanced technology, the surge for suitable multifunctional materials capable of operating above 300 °C has increased for the utilization of high-temperature piezoelectric devices. For this purpose, a pseudo-tetragonal phased CaBi₄Ti_3.98 (Nb_0.5Fe_0.5)_0.02O₁₅:xwt%MnO₂ (CBTNF:xMn), with x = 0–0.20, ceramic system has been engineered for the investigation of structural, ferroelectric, dielectric and high-temperature-dependent piezoelectric properties. XRD analysis confirms that low-content Mn-ion insertion at the lattice sites of CBTNF does not distort the pseudo-tetragonal phase lattice of CBTNF:xMn ceramics, but enhances the functional behavior of the ceramic system, specifically at x = 0.15 wt%Mn. Compared to pure CBT and CBTNF ceramics, CBTNF:0.15Mn has demonstrated a highly dense relative density (~96%), a saturated polarization (P_S) of 15.89 µC/cm², a storage energy density (W_ST) of ~1.82 J/cm³, an energy-conversion efficiency (ƞ) of ~51% and an upgraded piezoelectric behavior (d₃₃) of 27.1 pC/N at room temperature. Sharp temperature-dependent dielectric constant (ε_r) peaks display the solid ferroelectric behavior of the CBTNF:0.15Mn sample with a Curie temperature (T_C) of 766 °C. The thermally stable piezoelectric performance of the CBTNF:0.15Mn ceramic was observed at 600 °C, with just a 0.8% d₃₃ loss (25 pC/N). The achieved results signify that multi-valence Mn ions have effectively intercalated at the lattice sites of the pseudo-tetragonal phased CBTNF counterpart and enhanced the multifunctional properties of the ceramic system, proving it to be a durable contender for utilization in energy-storage applications and stable high-temperature piezoelectric applications.