A column generation based heuristic for the capacitated vehicle routing problem with three-dimensional loading constraints

This paper addresses an integrated problem of vehicle routing and three-dimensional loading with additional practical constraints such as stability, fragility and LIFO. A column generation (CG) technique-based heuristic is proposed to handle this problem. To generate new columns in CG technique, first, an elementary shortest path problem is solved to find routes with negative reduced cost. Then an extreme point-based heuristic method is employed to verify feasibility of obtained routes in terms of loading and other constraints. To speed up the CG technique, fast column generation is also performed by applying an efficient heuristic pricing method. The CG technique, tested on the benchmark instances, outperforms the efficient tabu search method developed in the literature in terms of solution quality and computation time.     

Applications of FT-NIRS combined with PLS multivariate methods for the detection & quantification of saccharin adulteration in commercial fruit juices

Detection of adulteration in carbohydrate-rich foods like fruit juices is particularly difficult because of the variety of the commercial sweeteners available that match the concentration profiles of the major carbohydrates in the foods. In present study, a new sensitive and robust assay using Fourier Transform Near-Infrared Spectroscopy (FT-NIRS) combined with partial least square (PLS) multivariate methods has been developed for detection and quantification of saccharin adulteration in different commercial fruit juice samples. For this investigation, six different commercially available fruit juice samples were intentionally adulterated with saccharin at the following percentage levels: 0%, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, 1.50%, 1.70% and 2.00% (weight/volume). Altogether, 198 samples were used including 18 pure juice samples (unadulterated) and 180 juice samples adulterated with saccharin. PLS multivariate methods including partial least-squares discriminant analysis (PLS-DA) and partial least-squares regressions (PLSR) were applied to the obtained spectral data to build models. The PLS-DA model was employed to differentiate between pure fruit juice samples and those adulterated with saccharin. The R² value obtained for the PLS-DA model was 97.90% with an RMSE error of 0.67%. Similarly, a PLS regression model was also developed to quantify the amount of saccharin adulterant in juice samples. The R² value obtained for the PLSR model was 97.04% with RMSECV error of 0.88%. The employed model was then cross-validated by using a test set which included 30% of the total adulterated juice samples. The excellent performance of the model was proved by the low root mean squared error of prediction value of 0.92% and the high correlation factor of 0.97. This newly developed method is robust, nondestructive, highly sensitive and economical.     

Modeling of Ionic Conductivity Enhancement of LiClO4-PVA-C System by TiO2 Addition Using Complex Numerical Model of PDE

PVA-TiO₂ nanocomposite polymer electrolytes (PEs) were produced with different amounts of TiO₂ (0, 5, 10, 15, and 20 wt.%) using the electrospinning process. Morphological studies of PVA-TiO₂ nanofibers were accomplished with SEM. PVA-TiO₂ membranes exhibited a high porosity of 79-91%. The impedance results showed that incorporation of TiO₂ into the nanofiber membrane improved its ionic conductivity from 0.7 × 10^?5 to 2.5 × 10^?5 S/cm at room temperature. Nanofiber PEs showed very good reversibility and electrochemical stability up to 4.7 V. Diffusion coefficient of Li ion into PVA-TiO₂ nanocomposite PEs was estimated by using a complex numerical model of partial differential equation for evaluation of ion transmission. Diffusion coefficient of PVA-TiO₂ PEs containing different amounts of TiO₂ (0, 5, 10, 15, and 20 wt.%) increased with increasing the nanoparticles content.     

Application of Cyclic Spectral Analysis in Diagnosis of Bearing Faults in Complex Machinery

Bearing failure can lead to major damage to rotating components and its diagnosis and prognosis are therefore of paramount importance. Techniques and approaches for detecting bearing faults abound. However, application of these methods is limited for complex systems such as aircraft engines. This stems from the fact that the complex configuration of the system and inaccessibility make it difficult to place the vibration transducers close to the bearings. In most cases, available instrumentation is limited to few vibration transducers on the casing of the machine. In such cases, the vibration due to bearing faults is barely detectable using traditional methods, because it normally makes only a small contribution to the overall energy and this is to some extent dissipated by the transmission path. For bearing fault detection to be effective in such applications, the methodology must be capable of detecting faint bearing signals and also allow consistent trending and tracking. This study examines these requirements in detail and presents an experimental assessment of newly emerging cyclic spectral analysis in this field for such requirements.     

Involvement of Acidic Amino Acid Residues in Zn2+ Binding to Respiratory Complex I

Proton transfer across membranes and membrane proteins is a central process in biological systems. Zn²⁺ ions are capable of binding to acidic residues, often found within such specific pathways, thereby leading to a blockage. Here we probed Zn²⁺inhibition of the proton‐pumping NADH:ubiquinone oxidoreductase from Escherichia coli by means of electrochemically induced FTIR difference spectroscopy. Numerous conformational changes were identified including those that arise from the reorganization of the membrane arm upon electron transfer in the peripheral arm of the protein. Signals at very high wavenumbers (1781 and 1756 cm^?1) point to the perturbation of acidic residues in a highly hydrophobic environment upon Zn²⁺ binding. In variant D563N^L, which lacks part of the proton pumping activity (residue located on the horizontal amphipathic helix), the spectral signature of Zn²⁺ binding is changed. Our data support a role for this residue in proton translocation.     

High-fidelity passive force-reflecting virtual environments

Passivity theory is applied to the creation of synthetic, complex multidimensional haptic environments. It can be shown that under appropriate conditions, sufficiently high rendering rates can guarantee the passivity of a simulation produced by a haptic device coupled to a discrete-time realization of a nominally passive environment. The creation of a passive, globally defined, virtual environment is either analytically complex or computationally costly. A method is described whereby a passive environment is created from transitions between locally defined force models that encode static conservative force fields. This is applied to the haptic rendering of tool contact with deformable bodies, in which sparse force-deflection responses are used to define local models. Passivity, continuity, and fidelity are provided by response-function interpolation rather than by interpolation of forces, as in previous methods. The work also includes an illustrative example.     

Zebrafish: A New Promise to Study the Impact of Metabolic Disorders on the Brain

Zebrafish has become a popular model to study many physiological and pathophysiological processes in humans. In recent years, it has rapidly emerged in the study of metabolic disorders, namely, obesity and diabetes, as the regulatory mechanisms and metabolic pathways of glucose and lipid homeostasis are highly conserved between fish and mammals. Zebrafish is also widely used in the field of neurosciences to study brain plasticity and regenerative mechanisms due to the high maintenance and activity of neural stem cells during adulthood. Recently, a large body of evidence has established that metabolic disorders can alter brain homeostasis, leading to neuro-inflammation and oxidative stress and causing decreased neurogenesis. To date, these pathological metabolic conditions are also risk factors for the development of cognitive dysfunctions and neurodegenerative diseases. In this review, we first aim to describe the main metabolic models established in zebrafish to demonstrate their similarities with their respective mammalian/human counterparts. Then, in the second part, we report the impact of metabolic disorders (obesity and diabetes) on brain homeostasis with a particular focus on the blood–brain barrier, neuro-inflammation, oxidative stress, cognitive functions and brain plasticity. Finally, we propose interesting signaling pathways and regulatory mechanisms to be explored in order to better understand how metabolic disorders can negatively impact neural stem cell activity.     

Synthesis of a new magnetic adsorbent using green tea leaf extract and its application in phenol removal by RSM method

Journal of Materials Science: Materials in Electronics - Green synthesis of metal nanoparticles (NPs) has attracted a lot of attention in recent years because of lower costs and being...     

Evaluation of structural,mechanical, and cellular behavior of electrospun poly-3-hydroxybutyrate scaffolds loaded with glucosamine sulfate to develop cartilage tissue engineering

Considering the role of glucosamine sulfate (GS) in the biosynthetic pathways of chondrocytes, an attempt was made to design an electrospun poly-3-hydroxybutyrate (PHB) scaffold loaded with GS to develop cartilage tissue engineering. The study was initiated using the optimal electrospun scaffold conditions for the synthesis of PHB/GS. The resulting scaffolds have shown excellent pore architectures and mechanical behavior compared to pure PHB. UV spectrophotometric analysis, for the evaluation of the GS release behavior, showed zero-order kinetics release. In vitro results indicated excellent cell viability, cell adhesion, and cell penetration of PHB/GS scaffolds compared to pure PHB.     

Modeling the forces of cutting with scissors

Modeling forces applied to scissors during cutting of biological materials is useful for surgical simulation. Previous approaches to haptic display of scissor cutting are based on recording and replaying measured data. This paper presents an analytical model based on the concepts of contact mechanics and fracture mechanics to calculate forces applied to scissors during cutting of a slab of material. The model considers the process of cutting as a sequence of deformation and fracture phases. During deformation phases, forces applied to the scissors are calculated from a torque-angle response model synthesized from measurement data multiplied by a ratio that depends on the position of the cutting crack edge and the curve of the blades. Using the principle of conservation of energy, the forces of fracture are related to the fracture toughness of the material and the geometry of the blades of the scissors. The forces applied to scissors generally include high-frequency fluctuations. We show that the analytical model accurately predicts the average applied force. The cutting model is computationally efficient, so it can be used for real-time computations such as haptic rendering. Experimental results from cutting samples of paper, plastic, cloth, and chicken skin confirm the model, and the model is rendered in a haptic virtual environment.