Hard Gelatin and Hypromellose (HPMC) Capsules: Estimation of Rupture Time by Real-time Dissolution Spectroscopy

ABSTRACT

The objective of this study was to measure rupture time of gelatin and hypromellose (hydroxypropyl methylcellulose or HPMC) capsules using a novel approach based on real-time dissolution spectroscopy. Rupture time was measured in standard dissolution apparatus at a constant temperature using a dip-type fiber-optic probe. Labrasol released from the capsules was treated as the marker of the rupture process. Light scatter generated by the emulsified labrasol was detected by an ultrafast monochromator at scan rates approximating 24,000 nm/min. This technique was validated by measuring the dissolution time of gelatin capsules. Rupture times of hypromellose capsules were studied as a function of capsule size, capsule grade, and dissolution medium. Statistical correlations were analyzed by ANOVA. Rupture time of hypromellose capsules was dependent on both the medium and the grade of the capsule, and was independent of capsule size. The composition of the dissolution medium contributes to the rupture time of the capsules and should be considered when fast release and quick biological response is desired. Release delay, however, may not manifest itself in vivo and the time to maximum plasma concentration may not be significant.     

Effect of Armature Design on Thermal and Electromagnetic Distribution of an Electromagnetic Launcher

The purpose of this study is to investigate the effect of armature design on the thermal and magnetic induction distribution of the rails and the armature in an electromagnetic launcher. In our formulation of governing, non-linear differential equations, Maxwell equations coupled with energy equation are applied to the rails and the armatures. To solve the non-linear governing differential equations, a finite difference code based on alternative directional implicit method is utilized. For different armatures, the length, shape, and input current of the rails stay the same. In addition, armature-melting latent heat and the friction force between the armatures and the rails are considered. First, armature speed is calculated; then, temperature and magnetic induction distribution is calculated by the energy equation. Temperature and magnetic induction distribution obtained for the rails and different armatures show that the maximum temperature occurs at the trailing edge of each armature. The best design shows the lowest temperature, which is about 600 K. This is due to aerodynamic shape and stability of this armature. However, for all armatures, the temperature of one meter rail stays around 360 K.     

Mutasynthesis-derived myxalamids and origin of the isobutyryl-CoA starter unit of myxalamid B

Myxalamids are potent inhibitors of the eukaryotic electron transport chain produced by different myxobacteria. Here, we describe the identification of the myxalamid biosynthesis gene cluster from Myxococcus xanthus. Additionally, new myxalamids (5-13) have been obtained by mutasynthesis from bkd mutants of M. xanthus and Stigmatella aurantiaca. Moreover, as these bkd mutants are still able to produce myxalamid B (2), the origin of the isobutyryl-CoA (IB-CoA) starter unit required for its biosynthesis has been determined. In a M. xanthus bkd mutant, IB-CoA originates from valine, but in S. aurantiaca this starter unit is derived from alpha-oxidation of iso-odd fatty acids, thereby connecting primary and secondary metabolism.     

Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion

This paper presents a novel approach for speckle reduction and coherence enhancement of ultrasound images based on nonlinear coherent diffusion (NCD) model. The proposed NCD model combines three different models. According to speckle extent and image anisotropy, the NCD model changes progressively from isotropic diffusion through anisotropic coherent diffusion to, finally, mean curvature motion. This structure maximally low-pass filters those parts of the image that correspond to fully developed speckle, while substantially preserving information associated with resolved-object structures. The proposed implementation algorithm utilizes an efficient discretization scheme that allows for real-time implementation on commercial systems. The theory and implementation of the new technique are presented and verified using phantom and clinical ultrasound images. In addition, the results from previous techniques are compared with the new method to demonstrate its performance.     

Fault tolerance in co-evolutionary communication of EHW modules

Evolvable Hardware (EHW) is a new concept that applies evolutionary algorithms to hardware design. Based on previous work on co-evolutionary communication of EHW modules, this paper investigates the new feature of fault tolerance for this model. A fault model is built for the communication line between EHW modules. The experiment demonstrated in the presentation is the simulation of injecting stuck/bridging faults into an EHW-based serial adder that has been previously developed. The outcomes imply an outstanding feature of fault tolerance in this system with 100% fault coverage, which paves the way for bio-inspired approaches to fault tolerant design instead of the classic ones.     

Controlling gaze with an embodied interactive control architecture

Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.     

Realistically coupled neural mass models can generate EEG rhythms

We study the generation of EEG rhythms by means of realistically coupled neural mass models. Previous neural mass models were used to model cortical voxels and the thalamus. Interactions between voxels of the same and other cortical areas and with the thalamus were taken into account. Voxels within the same cortical area were coupled (short-range connections) with both excitatory and inhibitory connections, while coupling between areas (long-range connections) was considered to be excitatory only. Short-range connection strengths were modeled by using a connectivity function depending on the distance between voxels. Coupling strength parameters between areas were defined from empirical anatomical data employing the information obtained from probabilistic paths, which were tracked by water diffusion imaging techniques and used to quantify white matter tracts in the brain. Each cortical voxel was then described by a set of 16 random differential equations, while the thalamus was described by a set of 12 random differential equations. Thus, for analyzing the neuronal dynamics emerging from the interaction of several areas, a large system of differential equations needs to be solved. The sparseness of the estimated anatomical connectivity matrix reduces the number of connection parameters substantially, making the solution of this system faster. Simulations of human brain rhythms were carried out in order to test the model. Physiologically plausible results were obtained based on this anatomically constrained neural mass model.     

Optimal Weighted Extreme Learning Machine for Cybersecurity Fake News Classification

Fake news and its significance carried the significance of affecting diverse aspects of diverse entities, ranging from a city lifestyle to a country global relativity, various methods are available to collect and determine fake news. The recently developed machine learning (ML) models can be employed for the detection and classification of fake news. This study designs a novel Chaotic Ant Swarm with Weighted Extreme Learning Machine (CAS-WELM) for Cybersecurity Fake News Detection and Classification. The goal of the CAS-WELM technique is to discriminate news into fake and real. The CAS-WELM technique initially pre-processes the input data and Glove technique is used for word embedding process. Then, N-gram based feature extraction technique is derived to generate feature vectors. Lastly, WELM model is applied for the detection and classification of fake news, in which the weight value of the WELM model can be optimally adjusted by the use of CAS algorithm. The performance validation of the CAS-WELM technique is carried out using the benchmark dataset and the results are inspected under several dimensions. The experimental results reported the enhanced outcomes of the CAS-WELM technique over the recent approaches.