Dyeing of poly(lactic acid) fibres with synthesised novel heterocyclic disazo disperse dyes

Poly(lactic acid) (PLA) is the first melt‐processable, renewable, sustainable and biodegradable natural‐based synthetic fibre. It has a broad range of uses and combines ecological advantages with outstanding performance in textiles. PLA fibre, as an aliphatic polyester, can be dyed with disperse dyes. Apart from the limited number of commercial disperse dyes, disperse dye exhaustion on PLA is generally lower than that on  poly(ethylene terephthalate) (PET). In this study, new heterocyclic disazo disperse dyes, substituted with methyl, nitro and chloro groups at their ortho‐, meta‐ and para‐ positions, synthesised in our previous study, were applied to PLA and PET fibres to examine their dyeing performance, and colour fastness and dye exhaustion properties. Different shades of yellow, orange, reddish brown and brown were obtained. Most of the synthesised novel heterocyclic disazo disperse dyes exhibited good build‐up properties with high K/S levels on both fibres. Para‐ bonding substituent provided higher K/S values than meta‐ and ortho‐ positions for –NO₂ and –Cl substituents for both fibres. Overall, the most synthesised novel heterocyclic disazo disperse dyes in this study exhibited good build‐up properties with high K/S, exhaustion and wet fastness levels on both PLA and PET fibres.      

The use of natural (Pinus pinaster) resin in the production of printing ink and the printability effect

Alkyd resins are generally used in the production of printing inks. All industries look for alternative raw materials in the production of ink with the growing inclination toward using natural products. Resins forming the vehicle of the ink to be obtained from natural resources will provide benefits for the environment, nature, and living creatures. The aim of the study was to promote the use of natural resin in the ink system. Natural Pinus pinaster resin was added into vegetable and mineral oil-based solvents in pure form with alkyd resin in different amounts and ink varnishes of different combinations were prepared. Then, printing inks were produced from these varnishes in pure and hybrid form. Following the assessment of the rheological properties of the inks prepared, printing tests were conducted to assess the printing quality parameters. Ideal mixing ratios of the natural resins in the ink were determined for printability. The environmental importance and advantages of the use of natural resins were discussed. Recommendations were given in line with the results to encourage widespread use of natural resins in near future.     

On methods of defuzzification of parametrically represented fuzzy numbers

A comparative analysis of such methods of defuzzification of fuzzy numbers as WABL (Weighted Averaging Based on Levels), centroid, and mean of maxima (MOM) is presented in the study. Analytic formulas are presented for calculating the defuzzification values for parametrically represented fuzzy numbers of triangular and trapezoidal form.     

Towards a comprehensive methodology for KBS development

Abstract: The vitality of effective methods and processes for developing knowledge-based systems (KBS) is examined. The paper discusses what should be expected from a methodology. Have their advocates been getting it all wrong all the way? That is certainly a suggested view put forward. The criticism includes an articulation of the major schools of thought in developing KBS; their implicit assumptions and philosophies, especially the prototyping options, are presented in the light of this paper. After the criticism, the philosophical basis of a new comprehensive KBS development methodology is presented. This breeds the line model of development, which in turn creates what is suspected to be an essential concept of thought in the developer's mind.     

Molecular Genetics of Conjunctival Melanoma and Prognostic Value of TERT Promoter Mutation Analysis

The aim of this study was exploration of the genetic background of conjunctival melanoma (CM) and correlation with recurrent and metastatic disease. Twenty-eight CM from the Rotterdam Ocular Melanoma Study group were collected and DNA was isolated from the formalin-fixed paraffin embedded tissue. Targeted next-generation sequencing was performed using a panel covering GNAQ, GNA11, EIF1AX, BAP1, BRAF, NRAS, c-KIT, PTEN, SF3B1, and TERT genes. Recurrences and metastasis were present in eight (29%) and nine (32%) CM cases, respectively. TERT promoter mutations were most common (54%), but BRAF (46%), NRAS (21%), BAP1 (18%), PTEN (14%), c-KIT (7%), and SF3B1 (4%) mutations were also observed. No mutations in GNAQ, GNA11, and EIF1AX were found. None of the mutations was significantly associated with recurrent disease. Presence of a TERT promoter mutation was associated with metastatic disease (p-value = 0.008). Based on our molecular findings, CM comprises a separate entity within melanoma, although there are overlapping molecular features with uveal melanoma, such as the presence of BAP1 and SF3B1 mutations. This warrants careful interpretation of molecular data, in the light of clinical findings. About three quarter of CM contain drug-targetable mutations, and TERT promoter mutations are correlated to metastatic disease in CM.     

Heat transfer and fluid flow characteristics in flash desalination units

The present work investigates the effects of different operating and geometrical parameters on the flashing efficiency of water in a single stage flashing chamber. This chamber uses a submerged rectangular orifice as flow control area. Experiments were performed to investigate the effects of flow rate, liquid level in the flashing chamber, liquid inlet temperature and flashing range, on the flashing efficiency under various design conditions. These comprise flow with baffle placed in the flashing chamber, and wire meshes placed at the orifice to increase the turbulence level.It was found that the efficiency increased with the increase of the turbulence levels, flashing range and liquid inlet temperature; the efficiency deceased with the increase of the flow rate and liquid level in the flashing chamber. The application of numerical procedure to predict flow pattern and heat transfer in the flashing chamber is introduced as a powerful design tool.     

Artificial Algae Optimization with Deep Belief Network Enabled Ransomware Detection in IoT Environment

The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations. This study develops an Artificial Algae Optimization Algorithm with Optimal Deep Belief Network (AAA-ODBN) Enabled Ransomware Detection in an IoT environment. The presented AAA-ODBN technique mainly intends to recognize and categorize ransomware in the IoT environment. The presented AAA-ODBN technique follows a three-stage process: feature selection, classification, and parameter tuning. In the first stage, the AAA-ODBN technique uses AAA based feature selection (AAA-FS) technique to elect feature subsets. Secondly, the AAA-ODBN technique employs the DBN model for ransomware detection. At last, the dragonfly algorithm (DFA) is utilized for the hyperparameter tuning of the DBN technique. A sequence of simulations is implemented to demonstrate the improved performance of the AAA-ODBN algorithm. The experimental values indicate the significant outcome of the AAA-ODBN model over other models.     

Political Optimizer with Deep Learning-Enabled Tongue Color Image Analysis Model

Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the PODL-TCIA model initially performs image pre-processing to enhance medical image quality. Followed by, Inception with ResNet-v2 model is employed for feature extraction. Besides, political optimizer (PO) with twin support vector machine (TSVM) model is exploited for image classification process, shows the novelty of the work. The design of PO algorithm assists in the optimal parameter selection of the TSVM model. For ensuring the enhanced outcomes of the PODL-TCIA model, a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.     

On disconjugacy and stability criteria for discrete Hamiltonian systems

By making use of new Lyapunov type inequalities, we establish disconjugacy and stability criteria for discrete Hamiltonian systems. The stability criteria are given when the system is periodic.