Digital bundling

Increasingly, we see that firms offer many items on information-intensive channels and the Internet. Especially with low-marginal-cost digital goods, bundling may be a beneficial strategy. Different bundles may help customers become more discriminating and maximize profits. However, the marketplace evidence provides mixed observation of bundling rigorously pursued. In this study, we provide a general framework to analyze when and how bundling may be beneficial. We compare and contrast the firm and customer characteristics on bundling strategy. We analyze when individual sales can be beneficial. We find that when costs do not increase relative to the bundle valuation, firms find it beneficial to limit the number of bundles offered in the market. A low (zero) marginal cost firm benefits from offering just one big bundle. Such a firm obtains a higher profit compared to a firm that offers many bundles. With high marginal costs, the number of bundles increases with increasing customer valuation and/or heterogeneity. When a firm offers all the bundles, prices and profit increase as customer heterogeneity and valuation increase. When the number of offered items is high, individual sale (unbundling) may be preferred over bundling and bundling becomes an inferior strategy. Interestingly, a firm may benefit from unbundling the items when customers have higher valuations.     

Prediction of rotation capacity of wide flange beams using neural networks

This study proposes Neural Networks (NN) as a new approach for the estimation and explicit formulation of available rotation capacity of wide flange beams. Rotation capacity is an important phenomenon which determines the plastic behaviour of steel structures. Thus the database for the NN training is directly based on extensive experimental results from literature. The results of the NN approach are compared with numerical results obtained by a specialized computer. Available rotation capacity is also introduced in a closed form solution based on the proposed NN model. The proposed NN method is seen to be more accurate than numerical results, practical and fast compared to FE models.     

Exact algorithms for the joint object placement and request routing problem in content distribution networks

This paper describes two exact algorithms for the joint problem of object placement and request routing in a content distribution network (CDN). A CDN is a technology used to efficiently distribute electronic content throughout an existing Internet Protocol network. The problem consists of replicating content on the proxy servers and routing the requests for the content to a suitable proxy server in a CDN such that the total cost of distribution is minimized. An upper bound on end-to-end object transfer time is also taken into account. The problem is formulated as a nonlinear integer programming formulation which is linearized in three different ways. Two algorithms, one based on Benders decomposition and the other based on Lagrangean relaxation and decomposition, are described for the solution of the problem. Computational experiments are conducted by comparing the proposed linearizations and the two algorithms on randomly generated Internet topologies.     

Learning goal hierarchies from structured observations and expert annotations

We describe a relational learning by observation framework that automatically creates cognitive agent programs that model expert task performance in complex dynamic domains. Our framework uses observed behavior and goal annotations of an expert as the primary input, interprets them in the context of background knowledge, and returns an agent program that behaves similar to the expert. We map the problem of creating an agent program on to multiple learning problems that can be represented in a “supervised concept learning’’ setting. The acquired procedural knowledge is partitioned into a hierarchy of goals and represented with first order rules. Using an inductive logic programming (ILP) learning component allows our framework to naturally combine structured behavior observations, parametric and hierarchical goal annotations, and complex background knowledge. To deal with the large domains we consider, we have developed an efficient mechanism for storing and retrieving structured behavior data. We have tested our approach using artificially created examples and behavior observation traces generated by AI agents. We evaluate the learned rules by comparing them to hand-coded rules. Editor: Rui Camacho     

Effect of cement type on the resistance of concrete against chloride penetration

In chloride containing environment, chloride permeability of concrete is an important parameter affecting the service life of concrete structures. The primary objective of this experimental study was to study the effect of cement types on the resistance of concrete against chloride penetration for given compressive strength classes. These cements included two different types of granulated blast-furnace slag cement (CEM III/A 32.5N and CEM III/A 42.5N), a sulfate resisting cement (SRC 32.5), and a Portland cement blended with fly ash; all of which compared to an ordinary Portland cement (CEM I 42.5R). For each binder type, four concretes at different strength classes were produced and as a result 20 mixtures were obtained. Rapid chloride ion penetration tests according to ASTM C 1202 were conducted. In addition, electrical resistivity and capillary water absorption tests were carried out. In order to characterize the concrete quality, compressive strength of the specimens were also obtained. The test results clearly demonstrated that the blast-furnace slag cements have the highest resistance against chloride penetration, while the pure Portland cement and sulfate resisting cement have the lowest resistance. Concretes produced with the sulfate resisting cement had substantially higher capillary sorption compared to other mixtures. Test results confirmed the strong relationship between the chloride permeability and electrical resistivity.     

All-aerosol-jet-printed highly sensitive and selective polyaniline-based ammonia sensors: a route toward low-cost,low-power gas detection

Journal of Materials Science - We report the design and scalable fabrication of a low-cost and low-power polyaniline-based (PANI) ammonia (NH3) gas sensor on polyimide (PI) substrates using...     

Testing for Unit Roots in Dynamic Panels with Smooth Breaks and Cross-Sectionally Dependent Errors

We develop the extended unit root testing procedure for dynamic panels characterised by slowly moving trends (SMT) and cross-section dependence (CSD). We allow SMT to follow the smooth logistic transition function and the components error terms to contain the unobserved common factors. We propose the two panel unit root test statistics, one derived by the extended common correlated effects (CCE) estimator and the other based on the Sieve bootstrap. We have conducted extensive simulation exercises and document that the failure to take into account SMT and CSD may lead to misleading inference. On the other hand, we find that both bootstrap and CCE-based tests maintain good power properties in small samples in the presence SMT and CSD. We apply our proposed tests to real interest rates for 17 OECD countries and find overwhelming evidence in favour of the Fisher hypothesis.     

Assessment of ASTER satellite images in landslide inventory mapping: Yenice-Gökçebey (Western Black Sea Region,Turkey)

In the last two decades, developments in Geographic Information Systems and Remote Sensing have allowed rapid and detailed analysis of natural hazards. The Western Black Sea region of Turkey is a major landslide prone area. Landslides in a selected area were assessed using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. Stereoscopic and two-dimensional visual image interpretations were performed at different scales and field studies were carried out such that the landslide inventories could be compared. The study indicated the best approach was stereoscopic image analysis for visual interpretations. The smallest landslide area realistically mapped using the ASTER image was 58,885 m². It is considered that ASTER satellite images provide useful information particularly in regional and/or medium scale landslide inventory studies.     

Bioengineering of a Semiautologous Arterial Vessels with Reconstructed Media and Intima,Longtime Tested In Vivo

Goal was to engineer biological, arterial grafts with antithrombotic, autologous endothelial luminal surface combined with extraluminal smooth vascular muscle layer (VSMC) and to test in vivo. (1) Different decellularisation methods described in literature were compared to identify the most suitable one with focus on the preservation of extracellular fibre matrix. (2) Endothelial precursor cells (EPC), isolated from bone marrow and VSMC from small venous segments of donor animals were cultivated. Cells were seeded sandwich‐like on homologous decellularized venous scaffolds and conditioned under pulsatile circulation in a bioreactor. (3) The semiautologous grafts were implanted in carotidal position on both sides in five Beagle dogs (n = 10; group 2) as interposition. A group of five animals, receiving only acellular grafts in both carotid positions (n = 10; group 1) served as controls. Comparison of four in literature described decellularisation methods showed different preservation of elastic and collagen fibres compared with native veins, whereas decellularity was similar in all methods. This forced us to choose a decellularization protocol with the best preservation of the extracellular matrix. The in vivo experiments showed in group 1 (control) already after one week a complete thrombotic occlusion of the decellularized implants, whereas in group 2 9/10 semiautologous grafts were patent after 98 ± 4 days in ultrasound, angiography and histology (p = 0.0001). A complete incorporation of semiautologous grafts in the surrounding tissue could be shown. The seeding with two different cell types preserved an aneurysmatic degeneration under arterial conditions with patency without anticoagulation.