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All world countries are suffering from repercussions of the global climate change problems and there is an urgent need to mitigate their negative impacts. Improper waste management methods contribute directly to climate change where common waste treatment methods are basically relying on incineration or landfilling. Nowadays, incorporating the circular economy perspective into the business model demonstrates the ability of creating value from wastes and reducing the residuals by adopting the circular supply chains management (CSCM) as a promising alternative to linear supply chains. Studying and analyzing the performance of CSCM through different modeling techniques are crucial stage for supporting decision making process where implementation of CSCM requires deep knowledge about challenges, important factors, and optimal values of critical decision variables. In response, this research presents a review about the proposed models that dealt with CSCM in each modelling field to give insights into models’ objectives and performances and outline the research gaps and future research directions for researchers. Furthermore, this study proposes a conceptual framework of reinforcement learning model which acts as an adaptive model for studying the dynamicity, complexity, and uncertainty in CSCM with respect to lot sizing problem that faces supply chains. This paper recommends further studies in the following areas which are important but received little or no attention: studying the dynamicity and stochastic nature of CSCM environment, conducting a forecasting analysis on important parameters of CSCM, designing a sustainable CSCM network, validating models of CSCM on real case studies.

Patients with dengue virus infection have a different symptoms range from asymptomatic to sever form depending on primary and secondary immune status of host, infecting genotype and patient’s age. The current study aimed to describe the clinical and laboratory profile of dengue fever outbreak and acute pancreatitis as a late complication, in Egypt, as two case reports only were available in literature regarding this issue. This prospective cohort study was carried out on 100 patients confirmed to have dengue disease out of 200 clinically suspected patients. Clinical, laboratory (serology for dengue specific IgM, real-time PCR for dengue virus, serum amylase and lipase) and abdominal multi-slice CT were done to all included patients. All patients presented with fever, headache and fatigue, which are the main clinical manifestations of dengue fever. The mean age of studied patients was 40.34 ± 15.74 years. Thirteen patients (13%), with their mean age 44.57 ± 11.53, presented after 3 months with typical clinical, laboratory and radiological manifestations of acute pancreatitis with positive serum dengue virus IgM, antibodies and negative serum dengue virus PCR. So, acute pancreatitis as a late complication of dengue fever disease should be keep in mind for its early diagnosis and management, thus minimize the morbidity and mortality from dengue fever.

Data about different types of cardiac biomarkers is still limited in children with congenital heart disease (CHD) when compared to that in adults. We evaluated the circulating levels of B-type natriuretic peptide (BNP) in children with different types of CHD and correlated the levels with the calculated Qp/Qs ratio and the outcome of the congenital heart surgery.

Mitogen-Activated Protein Kinases (MAPKs) consist of three major signaling members: extracellular signal-regulated kinase (ERK), p38 and C-JUN N-terminal kinase (JNK). We investigated physiological effects of Pulsed Electromagnetic Field Therapy (PEMFT) and Low Level Laser Therapy (LLLT) on human body, adopting the expression level of mitogen-activated protein kinases as an indicator via assessment of the activation levels of three major families of MAPKS, ERK, p38 and JNK in the peripheral lymphocytes of patients before and after the therapies. Assessment for the expression levels of MAPKs families' were done, in the peripheral lymphocytes of patients recently have appendectomy, using flow cytometric analysis of multiple signaling pathways, pre and post LLLT and PEMFT application (twice daily for 6 successive days) on the appendectomy wound. There were non-significant differences in the expression levels of MAPKs families' pre- therapies application. But there were significant increase in the ERK expression levels post application of LLLT compared to its pre application (p<0.01). Also, there was significant increase in the ERK, p38 and C-Jun N terminal expression level values post application of PEMFT compared to its pre application expression levels (p<0.01 for each). The present study demonstrates that PEMFT has a powerful healing effect more than LLLT as it increase the activation of ERK, P38 and C-Jun-N Terminal while LLLT only increase the activation of ERK. LLLT has more potent pain decreasing effect than PEMFT as it does not activate P38 pathway like PEMFT.

Coronary artery disease (CAD) is the most common cardiovascular disorder in adults. This study was performed to elucidate the role of active leptin, homocysteine, galectin-3, total phospholipids, total, bound, free hexosamines, free-to-bound hexosamines ratio in the pathogenesis of chronic myocardial ischemia and studying the effect of coronary artery bypass grafting (CABG) on their serum levels.

The design of dynamic supply chain (DSC) models has received a great attention in the last two decades. In this paper, a forward supply chain network (SCN) model is developed in which both dynamic facility locations and dynamic distributed quantities of materials and products are assumed. The problem is formulated mathematically using mixed integer linear programming (MILP). The solution methodology adopted is the hybrid genetic algorithm (hGA) comprising genetic algorithm (GA) and pattern search (PS) optimisation techniques. Two experimental studies are conducted to analyse the developed SCN model and the developed hGA. The results of the hGA analysis show that the accuracy of the proposed hGA is improved in the cases of large number of nodes of the SC's echelons, small number of manufactured products and large quantities of products' demands.

Image analysis techniques are being increasingly used to automate industrial inspection. The manual activity of inspection could be subjective and highly dependent on the experience of human personnel. In this work, the authors introduce a novel visual inspection approach that can be used online to test simultaneously multiple quality characteristics. The approach utilises image processing tools to deal with the product image; and extract features of its geometrical characteristics. Based on tolerance bands of each characteristic, an index is experimentally developed to reflect the deviation of a quality characteristic dimension from its nominal value; and one can decide whether a characteristic complies with the pre-specified tolerance. The index is proved to have a linear association with the deviation from the nominal sizes. The research is extended to test shifts in a quality characteristic position.

Fertiliser production process is characterised by being a dynamic process which is not easy to be predicted and controlled due to uncertain, imprecise and vague parameters' relations. Although mathematical modelling techniques are very well developed, these types of dynamic processes are difficult to be modelled by those techniques and also the regression models are complex to be used for real time control and, usually, their errors are significant. The main and most important quality characteristic in the fertiliser production process is the moisture content. This parameter affects the product shelf life, effectiveness and harmful internal reactions. In this research, two different artificial neural network (ANN) approaches are developed to predict the moisture content of the produced fertiliser: the back-propagation multilayer perceptron (BPMLP) and the radial basic function (RBF) nets. The two models performed satisfactory in predicting the moisture content with low error percent. Predicting the moisture content, the quality of the produced fertiliser can be enhanced either by reheating, adding chemicals, or both.

A filling production system is that characterised by two contradicting nonconforming cost components. The first component is that incurred when the product specification exceeds the upper tolerance limit, called an overfill cost, whereas the second cost component is contributed when the product specification falls below the lower tolerance limit, called an underfill cost. The ratio of the two cost components affects to a high extent the choice of the process parameters, especially the process location parameter that minimises the overall costs. The work in this research is devoted to finding the filling process's optimum parameters; namely the process's mean and variance, considering a Gaussian-distributed process. Firstly, the process's variance is considered constant; and searching for the optimal process mean parameter takes place. An analytical, closed form, solution model is developed that realises such target. The developed model is ended up with a graph that can simply be used by concerned engineers and practitioners. The assumption of a constant process variance is then relaxed; and the developed model is extended to involve the variance reduction cost. An algorithm is introduced to solve the extended model that optimises the filling process' mean and variance.

Several attempts have been made over the past decade to explore the concept of prodrug strategies that exploit PSA as a molecular target for the release of anticancer drugs in prostate tumors using various prostate specific antigen (PSA)-cleavable peptide linkers, but the desired antitumor and antimetastatic efficacy has not yet been fully achieved. We set out to look for new PSA-cleavable peptide substrates that could be cleaved more rapidly and efficiently than the previously used peptides. To look for the most susceptible PSA-cleavable peptide substrates, we used the so-called spot technology. With the following general formula, we designed 25 different fluorogenic heptapeptides; Cellulose-P5-P4-P3-P2-P1-P1′-P2’ (Fluorophore). The increase of the fluorescence in the supernatant of the reaction mixture was monitored using a 96-well fluorometric plate reader with excitation of λex485 nm and λem535 nm. Three sequences showed a high fluorogenic liberation after incubation with PSA, i.e., Arg-Arg-Leu-His-Tyr-Ser-Leu (7), Arg-Arg-Leu-Asn-Tyr-Ser-Leu (8) and Arg-Ser-Ser-Tyr-Arg-Ser-Leu (23). Future incorporation of these optimized substrates in the PSA-cleavable prodrug formulations could further optimize the cleavage pattern and so the release characteristics of these prodrugs to rapidly and efficiently liberate the free cytotoxic agents inside the tumor tissues.

Fertilisation of herbage with Na can increase acceptability to cows, but the influence of fertiliser rate and fertilisation by K is unknown. In experiment 1, ten cows were grazed on pasture plots that had just been fertilised with 0–132 kg-Na ha^-1 (current Na) and had received 0–64 kg-Na ha^-1 in the previous grazing season (residual Na). Herbage Na concentration increased in proportion to current Na from 2·7 to 4·9 g-Na kg^-1 dry matter (DM) and also increased with increasing residual Na from 2·2 to 4·5 g-Na kg^-1 DM. Herbage K concentrations were low (10 g kg^-1 DM at 0 kg-Na ha^-1) and were only slightly reduced by Na fertiliser. Herbage Mg and Ca concentrations and DM digestibility were maximum at 66–99 kg-current-Na ha^-1. Cows grazed current-Na-fertilised plots to a lower height and spent more time grazing them. In experiment 2, pasture plots received no fertiliser, low and high isomolar and independent applications of Na and K or a combination of the two. The herbage was more mature than in experiment 1 and Na concentration of the herbage without Na fertilizer was high (5 g kg^-1 DM). Na fertiliser, therefore, only slightly increased Na concentration, more in clover than in grass, and had little effect on K concentration. K fertiliser increased K concentration from 16 to 20 g kg^-1 DM and reduced Na concentration to 3·5 g kg^-1 DM. Sodium fertiliser, therefore, only increased the acceptability of herbage to cattle when herbage Na concentrations were initially low (less than 5 g kg^-1 DM) and were increased substantially by the application of the fertiliser. © 1998 SCI.