Effects of Economic Pressure on Marital Conflict in Romania.

This study examined the interrelationships among economic pressure, maternal depression, social support, and marital conflict in a sample of 239 mothers in Romania. Data were collected through a school-based survey. Findings indicated that higher levels of economic pressure were associated with higher levels of marital conflict. Economic pressure was also associated with higher marital conflict indirectly through increased maternal depression and lowered social support. The present results were similar to those obtained in studies conducted among U.S. samples. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Humidity sensing and electrical properties of polyaniline/cobalt oxide composites

Polyaniline/cobalt oxide composites were synthesized by an in situ chemical polymerization method with ammonium persulfate as an oxidizing agent. This was a single‐step polymerization process for the direct synthesis of the emeraldine salt phase of the polymer. The polymers were characterized with X‐ray diffraction, scanning electron microscopy, and Fourier transform infrared spectral analysis. The formation of mixed phases of the polymer together with the conducting emeraldine salt phase was confirmed by spectroscopic techniques. High‐temperature conductivity measurements showed thermally activated behavior. A change in the resistance was observed with respect to the relative humidity when the pellets were exposed to a wide humidity range of 10–95%. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 653–658, 2007     

Acetals as nucleating agents for polypropylene

Nucleating agents increase the impact strength, tensile strength, and tensile elasticity modulus of semicrystalline polymers. Nucleating agents also decrease product cycle times, resulting in a cost savings per product unit. We have synthesized and tested 15 compounds as nucleactors for polypropylene. Of these, trinapthylidene sorbitol, tri-(4-methyl-1-naphthylidene)sorbitol, tri-(4-methoxy-1-naphthylidene) sorbitol, and dibenzylidene xylitol are efficient nucleators of polypropylene. Trinaphthylidene sorbitol (tns) has two major diastereomers: The “S” diastereomer yields a faster crystallization rate for polypropylene than does the commercial nucleator dibenzylidene sorbitol (Millad 3905). Crystallization rates are 208 and 88, respectively (t min^?1 × 1000). The “R” diastereomer, however, is a poor nucleator and interferes with the nucleating activity of the “S” diastereomer. A 52/48 mixture of diastereomers does not nucleate polypropylene, even at twice the concentration. This is first time that the importance of stereochemistry has been demonstrated in the nucleating action. © 1994 John Wiley & Sons, Inc.     

Synthesis,characterization, and electrochemical properties of poly(ethylene oxide)-based polyaniline electrolyte complex

The polymer electrolyte based poly(ethylene oxide) complexed with conducting polyaniline (PANI) has been prepared in different weight percentages. The complexation is confirmed by Fourier transform infrared spectroscopy (FTIR).The change in morphology is studied by using scanning electron microscopy. The DC conductivity measurements are carried out using Keithley digital multimeter. It is seen that DC conductivity shows exponential behavior for all PEO : PANI complexes. It is observed that among all the PEO : PANI complexes, 50 wt % of PEO in PANI shows highest conductivity. Electrochemical cell parameters for battery applications at room temperature also have been determined. The samples are fabricated for battery application in the configuration of Na:(PEO : PANI):(I₂ + C + sample), and their experimental data are measured using Wagner polarization technique. The cell parameters results in an open-circuit voltage of 0.4 V and a short-circuit current of 902 μA for PEO : PANI (50 : 50) composite. Hence, these composites can be better candidates for the polymer electrolyte studies. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Assessment of the performance of different compost models to manage urban household organic solid wastes

The environmental, cultural, socio-economic and political conditions of each community greatly affect the municipality’s effort and decision-making in managing household wastes. Composting at home can be used as a sound method of SWM, can manage the waste at source itself thereby can increase their recycling. And vermicomposting is a viable and completely feasible option at household level, provided it is acceptable to family members to handle the worms and to remove worm-casts subsequently. In this regard, the present paper gives a methodological framework for assessing the management of urban household organic wastes using different compost models to influence the actual efficiency and effectiveness of a municipality’s collection and management services. The current study also deals with the challenges of solid waste management with a focus on the segregation of compostable wastes from the non-compostable ones and their composting, recycling or disposal. The non-compostable wastes can be left for recycling and re-use by the concerned authorities. The composting behavior and the efficiency of different compost models have been dealt with, and it is concluded that vermicomposting model is the best option. Urban residents can be educated to vermicompost not only their entire kitchen wastes but also garden wastes to reduce the burden on the municipal councils.     

Bayesian Networks for Knowledge-Based Authentication

We consider adaptive index utilization as a fine-grained problem in autonomic databases in which an existing index is dynamically determined to be used or not in query processing. As a special case, we study this problem for structural joins, the core operator in XML query processing, in the main memory. We find that index utilization is beneficial for structural joins only under certain join selectivity and distribution of matching elements. Therefore, we propose adaptive algorithms to decide whether to use an index probe or a data scan for each step of matching during the processing of a structural join operator. Our adaptive algorithms are based on the history, the look-ahead information, or both. We have developed a cost model to facilitate this adaptation and have conducted experiments with both synthetic and real-world data sets. Our results show that adaptively utilizing indexes in a structural join improves the performance by taking advantage of both sequential scans and index probes     

Effect of low-density filler on mechanical properties of syntactic foams of cyanate ester

Syntactic foam composites of cyanate ester with varying volume fractions of resin and glass microballoon were processed and evaluated for tensile, flexural and compressive properties. The effect of nature and volume fraction of microballoon on the mechanical properties was studied. The mechanical properties showed a gradual decrease in strength with increase in volume fraction of microballoon. The specific strength values also manifested a similar order. A similar behaviour was observed for syntactic foams with microballoons of varying true density. The properties increased proportional to the strength of the microballoon in resin-rich systems implying a strong microballoon-resin interface, corroborated by Scanning Electron Microscopy studies. The compressive modulus showed a decreasing trend with enhanced microballoon loading.     

Indole‐based polymer and its silver nanocomposite as advanced antibacterial agents: synthetic path,kinetics of polymerization and applications

Atom transfer radical polymerization of 1‐allylindole‐3‐carbaldehyde (AIC) was studied by employing 2‐bromoisobutyryl bromide as initiator in toluene. It led to controlled radical polymerization of AIC, with an increase of molecular weight along with the conversion of the monomer, and a relatively narrow molar mass distribution was obtained, as determined by gel permeation chromatography. The living nature of poly(1‐allylindole‐3‐carbaldehyde) (PAIC) was confirmed by the chain extension polymerization whereas ¹H NMR analysis showed that the major population of PAIC retained the chain‐end functional group. PAIC and its silver nanocomposite were found to be biologically active against some tested bacterial pathogens. Minimum inhibitory concentration tests revealed that PAIC exhibited antibacterial activity against Staphylococcus aureus, Proteus mirabilis and Klebsiella pneumonae whereas PAIC/Ag nanocomposite showed antibacterial activity against Enterococcus faecalis and K. pneumonae. © 2012 Society of Chemical Industry     

Fabrication and Tunable Dielectric Properties of (Ba0.7Sr0.3)TiO3-Glass-Based Thick-Film Capacitors

Ferroelectric glass–ceramics of composition 0.90 (Ba_0.7Sr_0.3) TiO₃–0.10(B₂O₃:SiO₂) (0.90 BST:0.10 BS) synthesized by sol–gel method have been used for the preparation of dielectric thick-film inks. The particle dispersion of the glass–ceramic powders in the thick-film ink formulations have been studied through rheological measurements for fabricating thick-film capacitors by screen printing technique. The thick films derived from such glass–ceramics are found to sinter at considerably lower temperatures than the pure ceramic, and exhibit good dielectric characteristics with a tunability of 32% at 1 MHz under a dc bias field of 35 kV/cm.     

Deep Multimodal Fusion: A Hybrid Approach

We propose a novel hybrid model that exploits the strength of discriminative classifiers along with the representation power of generative models. Our focus is on detecting multimodal events in time varying sequences as well as generating missing data in any of the modalities. Discriminative classifiers have been shown to achieve higher performances than the corresponding generative likelihood-based classifiers. On the other hand, generative models learn a rich informative space which allows for data generation and joint feature representation that discriminative models lack. We propose a new model that jointly optimizes the representation space using a hybrid energy function. We employ a Restricted Boltzmann Machines (RBMs) based model to learn a shared representation across multiple modalities with time varying data. The Conditional RBMs (CRBMs) is an extension of the RBM model that takes into account short term temporal phenomena. The hybrid model involves augmenting CRBMs with a discriminative component for classification. For these purposes we propose a novel Multimodal Discriminative CRBMs (MMDCRBMs) model. First, we train the MMDCRBMs model using labeled data by training each modality, followed by training a fusion layer. Second, we exploit the generative capability of MMDCRBMs to activate the trained model so as to generate the lower-level data corresponding to the specific label that closely matches the actual input data. We evaluate our approach on ChaLearn dataset, audio-mocap, as well as the Tower Game dataset, mocap-mocap as well as three multimodal toy datasets. We report classification accuracy, generation accuracy, and localization accuracy and demonstrate its superiority compared to the state-of-the-art methods.