Determination of water activities and osmotic and activity coefficients of the system NaCl–BaCl2–H2O at 298.15 K

The water activities of the mixed aqueous electrolyte NaCl–BaCl₂(aq) are measured at total molalities from 0.25 mol kg⁻¹ to about saturation for different ionic strength fractions (y) of NaCl with y=0.33,0.50,0.67. The results allow the deduction of osmotic coefficients. The experimental results are compared with the predictions of the Zdanovskii, Stokes, and Robinson (ZSR), Kusik and Meissner (KM), Robinson and Stokes (RS), Lietzke and Stoughton (LSII), Reilly, Wood, and Robinson (RWR), and Pitzer models. From these measurements, the Pitzer mixing ionic parameters are determined and used to predict the solute activity coefficients in the mixture. The excess Gibbs energy is also determined.     

Suboptimal Exposure to Facial Expressions When Viewing Video Messages From a Small Screen: Effects on Emotion, Attention, and Memory.

The authors examined the effects of suboptimally presented facial expressions on emotional and attentional responses and memory among 39 young adults viewing video (business news) messages from a small screen. Facial electromyography (EMG) and respiratory sinus arrhythmia were used as physiological measures of emotion and attention, respectively. Several congruency priming effects were found. In particular, happy facial primes prompted increased (a) pleasure ratings, (b) orbicularis oculi EMG activity, (c) perceived trustworthiness, and (d) recognition memory for video messages with a positive emotional tone. Emotional and other responses to video messages presented on a small screen can be modified with suboptimal affective primes, but even small differences in the emotional tone of the messages should be allowed for. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A novel chaotic Henry gas solubility optimization algorithm for solving real-world engineering problems

The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm (HGSO). The new algorithm is named chaotic Henry gas solubility optimization (CHGSO). The hybridization is aimed at enhancement of the convergence rate of the original Henry gas solubility optimizer for solving real-life engineering optimization problems. This hybridization provides a problem-independent optimization algorithm. The CHGSO performance is evaluated using various conventional constrained optimization problems, e.g., a welded beam problem and a cantilever beam problem. The performance of the CHGSO is investigated using both the manufacturing and diaphragm spring design problems taken from the automotive industry. The results obtained from using CHGSO for solving the various constrained test problems are compared with a number of established and newly invented metaheuristics, including an artificial bee colony algorithm, an ant colony algorithm, a cuckoo search algorithm, a salp swarm optimization algorithm, a grasshopper optimization algorithm, a mine blast algorithm, an ant lion optimizer, a gravitational search algorithm, a multi-verse optimizer, a Harris hawks optimization algorithm, and the original Henry gas solubility optimization algorithm. The results indicate that with selecting an appropriate chaotic map, the CHGSO is a robust optimization approach for obtaining the optimal variables in mechanical design and manufacturing optimization problems.

     

Characterization of Urine Stem Cell-Derived Extracellular Vesicles Reveals B Cell Stimulating Cargo

Elucidation of the biological functions of extracellular vesicles (EVs) and their potential roles in physiological and pathological processes is an expanding field of research. In this study, we characterized USC–derived EVs and studied their capacity to modulate the human immune response in vitro. We found that the USC–derived EVs are a heterogeneous population, ranging in size from that of micro–vesicles (150 nm–1 μm) down to that of exosomes (60–150 nm). Regarding their immunomodulatory functions, we found that upon isolation, the EVs (60–150 nm) induced B cell proliferation and IgM antibody secretion. Analysis of the EV contents unexpectedly revealed the presence of BAFF, APRIL, IL–6, and CD40L, all known to play a central role in B cell stimulation, differentiation, and humoral immunity. In regard to their effect on T cell functions, they resembled the function of mesenchymal stem cell (MSC)–derived EVs previously described, suppressing T cell response to activation. The finding that USC–derived EVs transport a potent bioactive cargo opens the door to a novel therapeutic avenue for boosting B cell responses in immunodeficiency or cancer.     

NMR imaging and differential scanning calorimetry study on drying of pine,birch, and reed pulps and their mixtures

Drying, water fractions, and water distribution were investigated for pine, birch, and reed pulps and pine–birch, pine–reed, and pine–birch–reed pulp mixtures. Gravimetrically determined drying times showed that the drying rates of the pulps decreased at two to four inflection points. Characterizations of the dried pulps by differential scanning calorimetry (DSC) showed a faster removal of free water than freezing and nonfreezing bound waters; all decreased simultaneously, however. DSC also revealed the critical water contents at which the free water and freezing bound water disappeared. The gravimetrically determined inflection points of the drying curves corresponded with the critical points determined by DSC. NMR line widths and images produced by ¹H‐NMR imaging revealed the nature and regions of the pulp drying. The constant growth rate of the NMR line widths with decreasing water content appeared to change at two inflection points, which fell approximately in the same water content regions as the inflection points of the drying curves. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 937–945, 2006     

Recognizing arabic handwritten characters using deep learning and genetic algorithms

Automated techniques for Arabic content recognition are at a beginning period contrasted with their partners for the Latin and Chinese contents recognition. There is a bulk of handwritten Arabic archives available in libraries, data centers, historical centers, and workplaces. Digitization of these documents facilitates (1) to preserve and transfer the country’s history electronically, (2) to save the physical storage space, (3) to proper handling of the documents, and (4) to enhance the retrieval of information through the Internet and other mediums. Arabic handwritten character recognition (AHCR) systems face several challenges including the unlimited variations in human handwriting and the leakage of large and public databases. In the current study, the segmentation and recognition phases are addressed. The text segmentation challenges and a set of solutions for each challenge are presented. The convolutional neural network (CNN), deep learning approach, is used in the recognition phase. The usage of CNN leads to significant improvements across different machine learning classification algorithms. It facilitates the automatic feature extraction of images. 14 different native CNN architectures are proposed after a set of try-and-error trials. They are trained and tested on the HMBD database that contains 54,115 of the handwritten Arabic characters. Experiments are performed on the native CNN architectures and the best-reported testing accuracy is 91.96%. A transfer learning (TF) and genetic algorithm (GA) approach named “HMB-AHCR-DLGA” is suggested to optimize the training parameters and hyperparameters in the recognition phase. The pre-trained CNN models (VGG16, VGG19, and MobileNetV2) are used in the later approach. Five optimization experiments are performed and the best combinations are reported. The highest reported testing accuracy is 92.88%.

     

Adaptive three-dimensional cellular genetic algorithm for balancing exploration and exploitation processes

This paper presents a new adaptive algorithm that aims to control the exploration/exploitation trade-off dynamically. The algorithm is designed based on three-dimensional cellular genetic algorithms (3D-cGAs). In this study, our methodology is based on the change in the global selection pressure induced by dynamic tuning of the local selection rate. The parameter tuning of the local selection method is a way to define the global selection pressure. A diversity speed measure is used to guide the algorithm. Therefore, the integration of existing techniques helps in achieving our aims. A benchmark of well-known continuous test functions and real world problems was selected to investigate the effectiveness of the algorithm proposed. In addition, we provide a comparison between the proposed algorithm and other static and dynamic algorithms in order to study the different effects on the performance of the algorithms. Overall, the results show that the proposed algorithm provides the most desirable performance in terms of efficiency, efficacy, and speed for most problems considered. The results also confirm that problems of various characteristics require different selection pressures, which are difficult to be identified.     

Efficacy of training procedures in implementing a legislated safety programme

This study examines the effect of training procedures, as measured by the results of a test, on the level of assimilation of a new safety programme in 80 Quebec companies. The Workplace Hazardous Materials Information System (WHMIS) was introduced in the province in 1989. The bipartite safety association representing the manufacturers of transportation equipment and machinery offered two types of WHMIS training services to their members: (a) 4 h employee training courses, and (b) two-day trainer training courses. Companies were free to choose from these and other services to comply with the WHMIS training requirements. A test was issued to a stratified sample of 862 employees approximately one year after the training. On average, the scores were best in plants having employees trained directly by experts from the safety association (type a). The training of internal trainers for companies produced slightly inferior learning results (type b).     

Cryogenic Temperature Measurement Using Silicon Carbide-Based Wireless Optical Sensor

Demonstrated is a novel silicon carbide (SiC)-based wireless optical sensor for cryogenic temperatures. The proposed design uses two wavelength processing and free-space optical beam interrogation of a remoted single crystal SiC chip placed in the cryogenic vacuum chamber to enable wireless temperature measurement. Experimental temperature sensing using the proposed sensor is reported from near room temperature to 100 K with an estimated 0.2 K resolution. The sensor uses eye safe laser wavelengths at 1550 and 1540 nm to implement the signal processing to determine the temperature value