Abstract

Painful diabetic neuropathy is poorly controlled by analgesics and requires high doses of opioids, triggering side effects and reducing patient quality of life. This study investigated whether enhanced Rab7-mediated lysosomal targeting of peripheral sensory neuron μ-opioid receptors (MORs) is responsible for diminished opioid responsiveness in rats with streptozotocin-induced diabetes. In diabetic animals, significantly impaired peripheral opioid analgesia was associated with a loss in sensory neuron MOR and a reduction in functional MOR G-protein-coupling. In control animals, MORs were retained mainly on the neuronal cell membrane. In contrast, in diabetic rats, they were colocalized with upregulated Rab7 in LampI-positive perinuclear lysosome compartments. Silencing endogenous Rab7 with intrathecal Rab7-siRNA or, indirectly, by reversing nerve growth factor deprivation in peripheral sensory neurons not only prevented MOR targeting to lysosomes, restoring their plasma membrane density, but also rescued opioid responsiveness toward better pain relief. These findings elucidate in vivo the mechanisms by which enhanced Rab7 lysosomal targeting of MORs leads to a loss in opioid antinociception in diabetic neuropathic pain. This is in contrast to peripheral sensory neuron MOR upregulation and antinociception in inflammatory pain, and provides intriguing evidence that regulation of opioid responsiveness varies as a function of pain pathogenesis.

This paper considers a common problem that all industries contest with in practice ie the breaking down of machines that influence production and cost directly. In a majority of industrial applications, acquiring optimum utilisation of all available resources for existing and future predicted demand is a major function throughout all the levels of management. This paper uses a number of analytical tools and software that support one another ie Witness Simulation, Bayesian Network Modelling and Hugin Software. The use of expert experience and knowledge has been incorporated throughout the study as it is vital to model building and greater understanding of machine breakdown. This study uses discrete event simulation and Bayesian network modelling collectively to understand machine breakdowns to increase efficiency within a cement manufacturing plant ie the Crusher Machine. The Bayesian network modelling implemented by the Hugin Software is used to generate probabilities which are transferred into a discrete event simulation model using Witness Software based on the historical data, expert knowledge and opinions. The model simulates the three parameters of the machine life based on consumption of each parameter. This is translated into a probability failure rate that changes as the model is running. The model demonstrates decisions based on the probability of failure from the Bayesian model and based on life consumption of the different variables in the simulation model.

Abstract

ABSTRACT: This paper surveyed some of the works on fibre reinforced concrete (FRC) in concrete pavements using recycled waste plastics fibres (WPF) and waste synthetic fibres (WSF) which include its specifications, types, features, benefits and physical properties. Fibres in reinforced concrete pavements can improve their toughness, shrinkage and durability. The use of recycled waste plastic fibres from industrial or post-consumer waste in concrete pavement mixes offers additional advantages as well as for plastics waste reduction, lowers construction cost and resources conservation. Keywords: Fibre Reinforced Concrete, Concrete Pavements, Waste Plastics Fibre, Recycled Waste Plastic

Abstract: This paper is intended to explore the application of the logit model in the Soekarno-Hatta Malang 

bridge traffic jam. Logit model is a model which uses regression technique to estimate the probability that an 

event occurs or not. The data which is used in this paper is the vehicles data. The vehicles are classified by

heavy vehicles (trucks, buses, etc), light vehicles (sedan, pick-up, etc), motorcycles, and unmotorcycles. The 

result of this research is 66.8% of motor vehicle will cause traffic jam and 66.9% of unmotor vehicle will cause 

traffic jam. 

Keywords: - logit model, traffic jam, congestion

The aim was to build an educational website to teach preschoolers aged 2-5 years old some skills; related to reading, writing and pronouncing alphabet, numbers, animal names, shapes and other common words. Also, assist parents and teachers by providing digital game-based learning environment to “edutainment” the children. The study illustrated the usability and usefulness of this educational game-based website and provided future insights for researchers and developers to take into account in future work.

Libya as many other regions under arid climates suffer from inadequate water resources to cover all the needs of this rapidly developing country. Increasing water amounts for population supply, agricultural irrigation and use for industry are needed. As groundwater is the main water source in the country it represents a natural resource of the highest economic and social importance. FEFLOW numerical model was implemented in a regional scale to show how the natural situation has been changed after heavy groundwater abstraction having occurred in the last decades in the northwestern part of Libya. Results of the numerical model indicated that the current zones of depression in piezometric surface could have been caused by smaller withdrawn amounts than previously estimated. Indicated differences in assessed withdrawn groundwater volumes seem to be quite high and might influence considerably the future possibilities of groundwater use in the study region.