Dynamic cellular manufacturing systems design��a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author??s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.     

Biological properties of curcumin-cellular and molecular mechanisms of action

Curcuminoids, a group of phenolic compounds isolated from the roots of Curcuma longa (Zingiberaceae), exhibit a variety of beneficial effects on health and on events that help in preventing certain diseases. A vast majority of these studies were carried out with curcumin (diferuloyl methane), which is a major curcuminoid. The most detailed studies using curcumin include anti-inflammatory, antioxidant, anticarcinogenic, antiviral, and antiinfectious activities. In addition, the wound healing and detoxifying properties of curcumin have also received considerable attention. As a result of extensive research on the therapeutic properties of curcumin, some understanding on the cellular, molecular, and biochemical mechanism of action of curcumin is emerging. These findings are summarized in this review.     

Inhibitory effect of Garcinia kola on lipid peroxidation in rat liver homogenate

Garcinia kola, (a herb grown in Nigeria; calorific value 358.54 k.cal/100 g) inhibited in vitro lipid peroxidation of rat liver homogenate in a dose dependent manner. The inhibitory activity of G.kola was not affected by heating (100 degrees C/10 min). The antioxidant component of G.kola was soluble in aqueous and ethanolic media. The active component(s) in G. kola responsible for its inhibitory activity on lipid peroxidation is tentatively identified as isoflavones.     

Changes in triacylglycerol molecular species and thermal properties of blended and interesterified mixtures of coconut oil or palm oil with rice bran oil or sesame oil

Blended oils were prepared by mixing appropriate amounts of coconut oil (CNO) or palm oil (PO) with rice bran oil (RBO) or sesame oil (SESO) to get approximately equal proportions of saturated/monounsaturated/polyunsaturated fatty acids in the oil. These blended oils were subjected to interesterification reactions using lipase to randomize the fatty acid distribution on the glycerol molecule. The fatty acid compositions of the modified oils were evaluated by gas chromatography while changes in triacylglycerol molecular species were followed by HPLC. The triacylglycerol molecular species of the blended oils reflected those present in the parent oil. Interesterification of the blended oils resulted in the exchange of fatty acids within and between the triacylglycerol molecules, resulting in alterations in the existing triacylglycerol molecules. Emergence of new triacylglycerol molecular species following interesterification was also observed. The thermal profiles of the native, blended and interesterified oils were determined by differential scanning calorimetry. Thermal behaviour, melting and crystallization properties of the modified oils showed significant changes reflecting the changes in the triacylglycerol molecules present in the oil. Therefore, interesterification of oils introduces significant changes in the physical properties of oils, even though the overall fatty acid composition of blended and interesterified oils remains the same.     

Hydrodynamic, thermo-analytical and molecular structural investigations of enzyme interesterified oil and its thermo-oxidative stability by thermogravimetric analysis

This paper deals with the effect of lipase-catalyzed interesterification of oil on hydrodynamic, thermo-analytical, structural properties and its stability. Interesterification of rice bran oil (RBO) and refined, bleached, deodorized palm olein (RBDPO) blend in 1:1 ratio was carried out at 60 ± 1 °C under stirring for 6 h. Results showed that hydrodynamic property of oils decreased from 3.61 × 10⁻⁶ in RBDPO to 2.91 × 10⁻⁶ m² s⁻¹ in enzyme interesterified oil (EI) and heat transfer coefficient increased from 221.0 in RBDPO to 250.7 Wm⁻² °C⁻¹ in EI over 170-190 °C. Peak melting point of triacylglycerols shifted from 10.36 °C in RBDPO to −4.76 °C in EI. Trisaturated triacylglycerols decreased from 4% in RBDPO to 0.6% in EI. The first step of thermal decomposition started at 190, 212.7 and 238.9 °C for RBDPO, RBO and EI, respectively. Sensory evaluation of poori fried using these oils revealed no significant (p > 0.05) differences in sensory attributes of the fried product.     

Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets

This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the binary-nature PBUC problem, the continuous, real-value whale position/location is mapped into binary search space through various transfer functions. This article introduces three variants of BWOA using tangential hyperbolic, inverse tangent (arctan) and sigmoidal transfer functions. The effectiveness of the BWOA approaches is examined in test systems with different market mechanisms, i.e. an energy-only market, and energy and reserve market participation with different reserve payment methods. The simulation results are presented, discussed and compared with other existing approaches. The convergence characteristics, solution quality and consistency of the results across different BWOA variants are discussed. The superiority and statistical significance of the proposed approaches with respect to existing approaches is also presented.     

Lentiform fork sign: Uremia alone or multifactorial causation?

Neurological complications are common in patients with acute or chronic renal failure, especially when there is marked reduction in the glomerular filtration rate (GFR). One such clinical syndrome, uremic encephalopathy (UE), occurs due to widespread dysfunction of central nervous system (CNS). It manifests with myriad clinical features and usually is suggested by bedside elicitation of asterixis (flapping tremor). Symptomatic involvement of the basal ganglia manifesting as choreoathetosis and clinical and radiological resolution with hemodialysis has been reported in the medical literature, but only rarely. The present report details such a case.     

Integration of machine learning and first principles models

Model building and parameter estimation are traditional concepts widely used in chemical, biological, metallurgical, and manufacturing industries. Early modeling methodologies focused on mathematically capturing the process knowledge and domain expertise of the modeler. The models thus developed are termed first principles models (or white-box models). Over time, computational power became cheaper, and massive amounts of data became available for modeling. This led to the development of cutting edge machine learning models (black-box models) and artificial intelligence (AI) techniques. Hybrid models (gray-box models) are a combination of first principles and machine learning models. The development of hybrid models has captured the attention of researchers as this combines the best of both modeling paradigms. Recent attention to this field stems from the interest in explainable AI (XAI), a critical requirement as AI systems become more pervasive. This work aims at identifying and categorizing various hybrid models available in the literature that integrate machine-learning models with different forms of domain knowledge. Benefits such as enhanced predictive power, extrapolation capabilities, and other advantages of combining the two approaches are summarized. The goal of this article is to consolidate the published corpus in the area of hybrid modeling and develop a comprehensive framework to understand the various techniques presented. This framework can further be used as the foundation to explore rational associations between several models.