Affinity microspheres and their application to lysozyme adsorption: Cibacron Blue F3GA and Cu(II) with poly(HEMA-EGDMA)

Lysozyme adsorption onto Cibacron Blue F3GA attached and Cu(II) incorporated poly(2-hydroxyethyl methacrylate–ethylene glycol dimethacrylate) [poly(HEMA-EGDMA)] microspheres was investigated. The microspheres were prepared by suspension polymerization. Various amounts of Cibacron Blue F3GA were attached covalently onto the microspheres by changing the initial concentration of dye in the reaction medium. The microspheres with a swelling ratio of 65%, and carrying different amounts of dye (between 1.4 and 22.5 µmol/g⁻¹) were used in the lysozyme adsorption studies. Lysozyme adsorption on these microspheres from aqueous solutions containing different amounts of lysozyme at different pH values was investigated in batch reactors. The lysozyme adsorption capacity of the dye–metal chelated microspheres (238.2 mg g⁻¹) was greater than that of the dye-attached microspheres (175.1 mg g⁻¹). The maximum lyzozyme adsorption capacities (q_m) and the dissociation constant (k_d) values were found to be 204.9 mg g⁻¹ and 0.0715 mg ml⁻¹ with dye-attached and 270.7 mg g⁻¹ and 0.0583 mg ml⁻¹ with dye–metal chelated microspheres, respectively. More than 90% of the adsorbed lysozyme were desorbed in 60 min in the desorption medium containing 0.5 M KSCN at pH 8.0 or 25 mM EDTA at pH 4.9. © 1999 Society of Chemical Industry     

The Role of Centrosome Distal Appendage Proteins (DAPs) in Nephronophthisis and Ciliogenesis

The primary cilium is found in most mammalian cells and plays a functional role in tissue homeostasis and organ development by modulating key signaling pathways. Ciliopathies are a group of genetically heterogeneous disorders resulting from defects in cilia development and function. Patients with ciliopathic disorders exhibit a range of phenotypes that include nephronophthisis (NPHP), a progressive tubulointerstitial kidney disease that commonly results in end-stage renal disease (ESRD). In recent years, distal appendages (DAPs), which radially project from the distal end of the mother centriole, have been shown to play a vital role in primary ciliary vesicle docking and the initiation of ciliogenesis. Mutations in the genes encoding these proteins can result in either a complete loss of the primary cilium, abnormal ciliary formation, or defective ciliary signaling. DAPs deficiency in humans or mice commonly results in NPHP. In this review, we outline recent advances in our understanding of the molecular functions of DAPs and how they participate in nephronophthisis development.     

Online short text clustering using infinite extensions of discrete mixture models

Short text clustering is one of the fundamental tasks in natural language processing. Different from traditional documents, short texts are ambiguous and sparse due to their short form and the lack of recurrence in word usage from one text to another, making it very challenging to apply conventional machine learning algorithms directly. In this article, we propose two novel approaches for short texts clustering: collapsed Gibbs sampling infinite generalized Dirichlet multinomial mixture model infinite GSGDMM) and collapsed Gibbs sampling infinite Beta-Liouville multinomial mixture model (infinite GSBLMM). We adopt two flexible and practical priors to the multinomial distribution where in the first one the generalized Dirichlet distribution is integrated, while the second one is based on the Beta-Liouville distribution. We evaluate the proposed approaches on two famous benchmark datasets, namely, Google News and Tweet. The experimental results demonstrate the effectiveness of our models compared to basic approaches that use Dirichlet priors. We further propose to improve the performance of our methods with an online clustering procedure. We also evaluate the performance of our methods for the outlier detection task, in which we achieve accurate results.     

Bounded multivariate generalized Gaussian mixture model using ICA and IVA

Pattern Analysis and Applications - A bounded multivariate generalized Gaussian mixture model with a full covariance matrix is proposed for modeling data in a bounded support region. For model...     

Educational UTAUT-based virtual reality acceptance scale: a validity and reliability study

Virtual Reality - This study aims to fill a gap in current research on virtual reality (VR) by developing a valid and reliable educational VR acceptance scale based on the unified theory of...     

Development of educational virtual reality attitude scale: A validity and reliability study

Virtual Reality - The aim of the study is to address a gap in the literature by developing an educational virtual reality (edVR) attitude measurement instrument, which determines college...     

Optimizing the distributed generators integration in electrical distribution networks: efficient modified forensic-based investigation

Neural Computing and Applications - As a result of various loads, including critical installations (industries, nuclear facilities, etc.), electrical distribution networks (EDNs) must operate...     

Plasmonic Superparamagnetic SPION@Ag@chitosan Core-shell: Uptake and Nitric Oxide Inhibition by Colorectal Cell Lines

Using Fusarium oxysporum species (F. oxysporum), a green synthesis of super-paramagnet iron oxide @silver@ Chitosan (SPION@Ag@Cs) was achieved. The physico-chemical characteristics of the SPION@Ag@Cs nanocomposite revealed the development of superparamagnetic phases of iron oxide (Fe₂O₃), as well as fluorescence, Raman absorption, and biocompatibility. Drug and gene delivery, and diagnosis, are all possibilities for the nanocomposite. The uptake of nitric oxide by HT-29 colorectal cell lines is examined in this article, for up to 72 h, the cytotoxicity of the HCT116 cell line was investigated. These characteristics were compared to Streptomyces griseus fungal species (S. griseus) which develops Fe₃O₄ under the same preparation conditions.

     

Optimal Bottleneck-Driven Deep Belief Network Enabled Malware Classification on IoT-Cloud Environment

Cloud Computing (CC) is the most promising and advanced technology to store data and offer online services in an effective manner. When such fast evolving technologies are used in the protection of computer-based systems from cyberattacks, it brings several advantages compared to conventional data protection methods. Some of the computer-based systems that effectively protect the data include Cyber-Physical Systems (CPS), Internet of Things (IoT), mobile devices, desktop and laptop computer, and critical systems. Malicious software (malware) is nothing but a type of software that targets the computer-based systems so as to launch cyber-attacks and threaten the integrity, secrecy, and accessibility of the information. The current study focuses on design of Optimal Bottleneck driven Deep Belief Network-enabled Cybersecurity Malware Classification (OBDDBN-CMC) model. The presented OBDDBN-CMC model intends to recognize and classify the malware that exists in IoT-based cloud platform. To attain this, Z-score data normalization is utilized to scale the data into a uniform format. In addition, BDDBN model is also exploited for recognition and categorization of malware. To effectually fine-tune the hyperparameters related to BDDBN model, Grasshopper Optimization Algorithm (GOA) is applied. This scenario enhances the classification results and also shows the novelty of current study. The experimental analysis was conducted upon OBDDBN-CMC model for validation and the results confirmed the enhanced performance of OBDDBN-CMC model over recent approaches.     

Simulation and Optimization of Back Surface Field for Efficient HIT Solar Cells

Silicon - We investigate an appropriate material for the optimisation of Back Surface Field (BSF) layer in Heterojunction with Intrinsic thin layer (HIT) solar cells:...