Studies on induction hardening of powder-metallurgy-processed Fe-Cr/Mo alloys

Induction hardening of dense Fe-Cr/Mo alloys processed via the powder-metallurgy route was studied. The Fe-3Cr-0.5Mo, Fe-1.5Cr-0.2Mo, and Fe-0.85Mo pre-alloyed powders were mixed with 0.4wt%, 0.6wt%, and 0.8wt% C and compacted at 500, 600, and 700 MPa, respectively. The compacts were sintered at 1473 K for 1 h and then cooled at 6 K/min. Ferrite with pearlite was mostly observed in the sintered alloys with 0.4wt% C, whereas a carbide network was also present in the alloys with 0.8wt% C. Graphite at prior particle boundaries led to deterioration of the mechanical properties of alloys with 0.8wt% C, whereas no significant induction hardening was achieved in alloys with 0.4wt% C. Among the investigated samples, alloys with 0.6wt% C exhibited the highest strength and ductility and were found to be suitable for induction hardening. The hardening was carried out at a frequency of 2.0 kHz for 2-3 s. A case depth of 2.5 mm was achieved while maintaining the bulk (interior) hardness of approximately HV 230. A martensitic structure was observed on the outer periphery of the samples. The hardness varied from HV 600 to HV 375 from the sample surface to the interior of the case hardened region. The best combination of properties and hardening depth was achieved in case of the Fe-1.5Cr-0.2Mo alloy with 0.6wt% C.     

Using the ‘Engagement’ Model of Problem Solving to Assist Students in Capstone Learning

The engagement model for problem solving was developed as a response to soft systems methodology being difficult to implement in certain circumstances. In the years since the original paper was published, the model has developed into an iterative problem solving approach for the assessment, creation and implementation of new ideas in difficult problem situations. This case study paper exemplifies the kind of work undertaken through the use of the model and provides a practical scenario for how one might apply it. The case study takes place in a higher education environment and relates to the development of a capstone course for management majors. The paper concludes with suggestions for future research.     

Control of DNA integrity in skeletal muscle under physiological and pathological conditions

Skeletal muscle is a highly oxygen-consuming tissue that ensures body support and movement, as well as nutrient and temperature regulation. DNA damage induced by reactive oxygen species is present in muscles and tends to accumulate with age. Here, we present a summary of data obtained on DNA damage and its implication in muscle homeostasis, myogenic differentiation and neuromuscular disorders. Controlled and transient DNA damage appears to be essential for muscular homeostasis and differentiation while uncontrolled and chronic DNA damage negatively affects muscle health.     

Opposing effects on the cell cycle of T lymphocytes by Fbxo7 via Cdk6 and p27

G₁ phase cell cycle proteins, such as cyclin-dependent kinase 6 (Cdk6) and its activating partners, the D-type cyclins, are important regulators of T-cell development and function. An F-box protein, called F-box only protein 7 (Fbxo7), acts as a cell cycle regulator by enhancing cyclin D-Cdk6 complex formation and stabilising levels of p27, a cyclin-dependent kinase inhibitor. We generated a murine model of reduced Fbxo7 expression to test its physiological role in multiple tissues and found that these mice displayed a pronounced thymic hypoplasia. Further analysis revealed that Fbxo7 differentially affected proliferation and apoptosis of thymocytes at various stages of differentiation in the thymus and also mature T-cell function and proliferation in the periphery. Paradoxically, Fbxo7-deficient immature thymocytes failed to undergo expansion in the thymus due to a lack of Cdk6 activity, while mature T cells showed enhanced proliferative capacity upon T-cell receptor engagement due to reduced p27 levels. Our studies reveal differential cell cycle regulation by Fbxo7 at different stages in T-cell development.     

Melatonin transport into mitochondria

Melatonin is a well-known, nighttime-produced indole found in bacteria, eukaryotic unicellulars, animals or vascular plants. In vertebrates, melatonin is the major product of the pineal gland, which accounts for its increase in serum during the dark phase, but it is also produced by many other organs and cell types. Such a wide distribution is consistent with its multiple and well-described functions which include from the circadian regulation and adaptation to seasonal variations to immunomodulatory and oncostatic actions in different types of tumors. The discovery of its antioxidant properties in the early 1990s opened a new field of potential protective functions in multiple tissues. A special mention should be made regarding the nervous system, where the indole is considered a major neuroprotector. Furthermore, mitochondria appear as one of the most important targets for the indole’s protective actions. Melatonin’s mechanisms of action vary from the direct molecular interaction with free radicals (free radical scavenger) to the binding to membrane (MLT1A and MLT1B) or nuclear receptors (RZR/RORα). Receptor binding has been associated with some, but not all of the indole functions reported to date. Recently, two new mechanisms of cellular uptake involving the facilitative glucose transporters GLUT/SLC2A and the proton-driven oligopeptide transporter PEPT1/2 have been reported. Here we discuss the potential importance that these newly discovered transport systems could have in determining the actions of melatonin, particularly in the mitochondria. We also argue the relative importance of passive diffusion vs active transport in different parts of the cell.     

System optimization model of adoption of a new infrastructure with multi-resource and multi-demand sites

This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, spillover effect, demand, initial investment cost, and learning rate influence the adoption of the new infrastructure technology and presents optimization results of the model in different scenarios. The main findings of the study are: from the perspective of system optimization, (1) different distances among different resource-demand pairs will result in different adoption time of a new infrastructure; (2) technological spillover among different resource-demand pairs will accelerate the adoption of a new infrastructure; (3) it is hard to say that higher demand will pull faster adoption of a new infrastructure, and the optimal time of adopting of a new infrastructure is very sensitive to its technological learning rate.     

Social Media as a Mean for Improved Technical Communication

Technical communication (TC) is an important activity in order to provide the users of technical artifacts with necessary information concerning the operation and maintenance of the products they are using. In the current working procedures of TC, however, the users become too passive. They are just receivers of information. Further, there is no effective feedback from the users to the producers of the information. In order to overcome those problems we here propose an application of social media (SM) in future TC. By using SM as a complementary channel for TC it becomes possible for technology firms to boost their competitive advantage and to improve the quality and completeness of their TC. This technique, however, is still more of a potential and less of a reality. Several problems, mostly concerning security and confidentiality remain to be solved. The empirical base for this work comes from TIC, an EU-funded development project involving several Swedish technology companies. Published research results are somewhat scattered but several sources coherently indicate both the need and potential for SM as a vehicle in TC. By scanning the net it is further possible to identify a number of seemingly successful applications of SM in such applications.     

Viral journeys on the intracellular highways

Viruses are obligate intracellular pathogens that are dependent on cellular machineries for their replication. Recent technological breakthroughs have facilitated reliable identification of host factors required for viral infections and better characterization of the virus–host interplay. While these studies have revealed cellular machineries that are uniquely required by individual viruses, accumulating data also indicate the presence of broadly required mechanisms. Among these overlapping cellular functions are components of intracellular membrane trafficking pathways. Here, we review recent discoveries focused on how viruses exploit intracellular membrane trafficking pathways to promote various stages of their life cycle, with an emphasis on cellular factors that are usurped by a broad range of viruses. We describe broadly required components of the endocytic and secretory pathways, the Endosomal Sorting Complexes Required for Transport pathway, and the autophagy pathway. Identification of such overlapping host functions offers new opportunities to develop broad-spectrum host-targeted antiviral strategies.     

Cost and Service-Level-Based Model for a Seru Production System Formation Problem with Uncertain Demand

With increasing demand diversification and short product lifecycles, industries now encounter challenges of demand uncertainty. The Japanese seru production system has received increased attention owing to its high efficiency and flexibility. In this paper, the problem of seru production system formation under uncertain demand is researched. A multi-objective optimization model for a seru production system formation problem is developed to minimize the cost and maximize the service level of the system. The purpose of this paper is to formulate a robust production system that can respond efficiently to the stochastic demand. Sample average approximation (SAA) is used to approximate the expected objective of the stochastic programming. The non-dominated sorting genetic algorithm II (NSGA-II) is improved to solve the multi-objective optimization model. Numerical experiments are conducted to test the tradeoff between cost and service level, and how the performance of the seru production system varies with the number of product types, mean and deviation of product volume, and skill-level-based cost.     

Products Ranking Through Aspect-Based Sentiment Analysis of Online Heterogeneous Reviews

With the rapid growth of online shopping platforms, more and more customers intend to share their shopping experience and product reviews on the Internet. Both large quantity and various forms of online reviews bring difficulties for potential consumers to summary all the heterogenous reviews for reference. This paper proposes a new ranking method through online reviews based on different aspects of the alternative products, which combines both objective and subjective sentiment values. Firstly, weights of these aspects are determined with LDA topic model to calculate the objective sentiment value of the product. During this process, the realistic meaning of each aspect is also summarized. Then, consumers’ personalized preferences are taken into consideration while calculating total scores of alternative products. Meanwhile, comparative superiority between every two products also contributes to their final scores. Therefore, a directed graph model is constructed and the final score of each product is computed by improved PageRank algorithm. Finally, a case study is given to illustrate the feasibility and effectiveness of the proposed method. The result demonstrates that while considering only objective sentiment values of the product, the ranking result obtained by our proposed method has a strong correlation with the actual sales orders. On the other hand, if consumers express subjective preferences towards a certain aspect, the final ranking is also consistent with the actual performance of alternative products. It provides a new research idea for online customer review mining and personalized recommendation.