The death of newspapers: Have we reached the tipping point?

News Corp’s only substantial competitor in the print journalism sector may be on the brink of giving up the ghost, as has long been speculated even by its natural supporters such as Beecher. If it does, hundreds more jobs will go, along with the many hundreds of experienced, skilled journalists and editors already shown the door by the company.

The hydrogen bond: a molecular beam microwave spectroscopist's view with a universal appeal

In this manuscript, we propose a criterion for a weakly bound complex formed in a supersonic beam to be characterized as a `hydrogen bonded complex'. For a `hydrogen bonded complex', the zero point energy along any large amplitude vibrational coordinate that destroys the orientational preference for the hydrogen bond should be significantly below the barrier along that coordinate so that there is at least one bound level. These are vibrational modes that do not lead to the breakdown of the complex as a whole. If the zero point level is higher than the barrier, the `hydrogen bond' would not be able to stabilize the orientation which favors it and it is no longer sensible to characterize a complex as hydrogen bonded. Four complexes, Ar-2-H2O, Ar-2-H2S, C2H4-H2O and C2H4-H2S, were chosen for investigations. Zero point energies and barriers for large amplitude motions were calculated at a reasonable level of calculation, MP2(full)/aug-cc-pVTZ, for all these complexes. Atoms in molecules (AIM) theoretical analyses of these complexes were carried out as well. All these complexes would be considered hydrogen bonded according to the AIM theoretical criteria suggested by Koch and Popelier for C-H center dot center dot center dot O hydrogen bonds (U. Koch and P. L. A. Popelier, J. Phys. Chem., 1995, 99, 9747), which has been widely and, at times, incorrectly used for all types of contacts involving H. It is shown that, according to the criterion proposed here, the Ar-2-H2O/H2S complexes are not hydrogen bonded even at zero kelvin and C2H4-H2O/H2S complexes are. This analysis can naturally be extended to all temperatures. It can explain the recent experimental observations on crystal structures of H2S at various conditions and the crossed beam scattering studies on rare gases with H2O and H2S.

Unsteady Incompressible Three-Dimensional Asymmetric Stagnation-Point Boundary Layers

The unsteady laminar incompressible boundary-layer flow near the three-dimensional asymmetric stagnation point has been studied under the assumptions that the free-stream velocity, wall temperature, and surface mass transfer vary arbitrarily with time. The partial differential equations governing the flow have been solved numerically using an implicit finite-difference scheme. It is found that in contrast with the symmetric flow, the maximum heat transfer occurs away from the stagnation point due to the decrease in the boundary-layer thickness. The effect of the variation of the wall temperature with time on heat transfer is strong. The skin friction and heat transfer due to asymmetric flow only are comparatively less affected by the mass transfer as compared to those of symmetric flow.

Acoustic emission source location and damage detection in a metallic structure using a graph-theory-based geodesic pproach

A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.

Diffusive and ship-mediated spread of dinoflagellates in the Baltic Sea with Prorocentrum minimum as a special case

In this thesis the role played by expansive and introduced species in the phytoplankton ecology of the Baltic Sea was investigated. The aims were threefold. First, the studies investigated the resting stages of dinoflagellates, which were transported into the Baltic Sea via shipping and were able to germinate under the ambient, nutrient-rich, brackish water conditions. The studies also estimated which factors favoured the occurrence and spread of P. minimum in the Baltic Sea and discussed the identification of this morphologically variable species. In addition, the classification of phytoplankton species recently observed in the Baltic Sea was discussed. Incubation of sediments from four Finnish ports and 10 ships ballast tanks revealed that the sediments act as sources of living dinoflagellates and other phytoplankton. Dinoflagellates germinated from all ports detected and from 90% of ballast tanks. The concentrations of cells germinating from ballast tank sediments were mostly low compared with the acceptable cell concentrations set by the International Maritime Organization s (IMO s) International Convention for the Control and Management of Ships Ballast Water and Sediments. However, the IMO allows such high concentrations of small cells in the discharged ballast water that the total number of cells in large ballast water tanks can be very high. Prorocentrum minimum occurred in the Baltic Sea annually but with no obvious trend in the 10-year timespan from 1993 to 2002. The species occurred under wide ranges of temperatures and salinities and the abundance of the species was positively related especially to the presence of organic nitrogen and phosphorus. This indicated that the species was favoured by increased organic nutrient loading and runoff from land and rivers. The cell shape of P. minimum varied from triangular to oval-round, but morphological fine details indicated that only one morphospecies was present. P. minimum also is, according to present knowledge, the only potentially harmful phytoplankton species that has recently expanded widely into new areas of the Baltic Sea.

Stress and developmental responses in Arabidopsis thaliana: regulation through the transcription factor-interacting protein RCD1

Plants constantly face adverse environmental conditions, such as drought or extreme temperatures that threaten their survival. They demonstrate astonishing metabolic flexibility in overcoming these challenges and one of the key responses to stresses is changes in gene expression leading to alterations in cellular functions. This is brought about by an intricate network of transcription factors and associated regulatory proteins. Protein-protein interactions and post-translational modifications are important steps in this control system along with carefully regulated degradation of signaling proteins. This work concentrates on the RADICAL-INDUCED CELL DEATH1 (RCD1) protein which is an important regulator of abiotic stress-related and developmental responses in Arabidopsis thaliana. Plants lacking this protein function display pleiotropic phenotypes including sensitivity to apoplastic reactive oxygen species (ROS) and salt, ultraviolet B (UV-B) and paraquat tolerance, early flowering and senescence. Additionally, the mutant plants overproduce nitric oxide, have alterations in their responses to several plant hormones and perturbations in gene expression profiles. The RCD1 gene is transcriptionally unresponsive to environmental signals and the regulation of the protein function is likely to happen post-translationally. RCD1 belongs to a small protein family and, together with its closest homolog SRO1, contains three distinguishable domains: In the N-terminus, there is a WWE domain followed by a poly(ADP-ribose) polymerase-like domain which, despite sequence conservation, does not seem to be functional. The C-terminus of RCD1 contains a novel domain called RST. It is present in RCD1-like proteins throughout the plant kingdom and is able to mediate physical interactions with multiple transcription factors. In conclusion, RCD1 is a key point of signal integration that links ROS-mediated cues to transcriptional regulation by yet unidentified means, which are likely to include post-translational mechanisms. The identification of RCD1-interacting transcription factors, most of whose functions are still unknown, opens new avenues for studies on plant stress as well as developmental responses.

Redefine: Runtime Reconfigurable Polymorphic ASIC

Emerging embedded applications are based on evolving standards (e.g., MPEG2/4, H.264/265, IEEE802.11a/b/g/n). Since most of these applications run on handheld devices, there is an increasing need for a single chip solution that can dynamically interoperate between different standards and their derivatives. In order to achieve high resource utilization and low power dissipation, we propose REDEFINE, a polymorphic ASIC in which specialized hardware units are replaced with basic hardware units that can create the same functionality by runtime re-composition. It is a ``future-proof'' custom hardware solution for multiple applications and their derivatives in a domain. In this article, we describe a compiler framework and supporting hardware comprising compute, storage, and communication resources. Applications described in high-level language (e.g., C) are compiled into application substructures. For each application substructure, a set of compute elements on the hardware are interconnected during runtime to form a pattern that closely matches the communication pattern of that particular application. The advantage is that the bounded CEs are neither processor cores nor logic elements as in FPGAs. Hence, REDEFINE offers the power and performance advantage of an ASIC and the hardware reconfigurability and programmability of that of an FPGA/instruction set processor. In addition, the hardware supports custom instruction pipelining. Existing instruction-set extensible processors determine a sequence of instructions that repeatedly occur within the application to create custom instructions at design time to speed up the execution of this sequence. We extend this scheme further, where a kernel is compiled into custom instructions that bear strong producer-consumer relationship (and not limited to frequently occurring sequences of instructions). Custom instructions, realized as hardware compositions effected at runtime, allow several instances of the same to be active in parallel. A key distinguishing factor in majority of the emerging embedded applications is stream processing. To reduce the overheads of data transfer between custom instructions, direct communication paths are employed among custom instructions. In this article, we present the overview of the hardware-aware compiler framework, which determines the NoC-aware schedule of transports of the data exchanged between the custom instructions on the interconnect. The results for the FFT kernel indicate a 25% reduction in the number of loads/stores, and throughput improves by log(n) for n-point FFT when compared to sequential implementation. Overall, REDEFINE offers flexibility and a runtime reconfigurability at the expense of 1.16x in power and 8x in area when compared to an ASIC. REDEFINE implementation consumes 0.1x the power of an FPGA implementation. In addition, the configuration overhead of the FPGA implementation is 1,000x more than that of REDEFINE.

Study of fracture behaviour of bond coats on nickel superalloy by three-point bending of microbeams

A microbeam testing geometry is designed to study the variation in fracture toughness across a compositionally graded NiAl coating on a superalloy substrate. A bi-material analytical model of fracture is used to evaluate toughness by deconvoluting load-displacement data generated in a three-point bending test. It is shown that the surface layers of a diffusion bond coat can be much more brittle than the interior despite the fact that elastic modulus and hardness do not display significant variations. Such a gradient in toughness allows stable crack propagation in a test that would normally lead to unstable fracture in a homogeneous, brittle material. As the crack approaches the interface, plasticity due to the presence of Ni3Al leads to gross bending and crack bifurcation.

Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition

The rapid increase in genome sequence information has necessitated the annotation of their functional elements, particularly those occurring in the non-coding regions, in the genomic context. Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. In this analysis, we demonstrate that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. We have therefore obtained a set of free energy threshold values, for genomic DNA with varying GC content and used them as generic criteria for predicting promoter regions in several microbial genomes, using an in-house developed tool `PromPredict'. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (50.8% GC) and B. subtilis (43.5% GC) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained.

Steady mixed convection stagnation-point flow of upper convected Maxwell fluids with magnetic field

The steady MHD mixed convection flow of a viscoelastic fluid in the vicinity of two-dimensional stagnation point with magnetic field has been investigated under the assumption that the fluid obeys the upper-convected Maxwell (UCM) model. Boundary layer theory is used to simplify the equations of motion. induced magnetic field and energy which results in three coupled non-linear ordinary differential equations which are well-posed. These equations have been solved by using finite difference method. The results indicate the reduction in the surface velocity gradient, surface heat transfer and displacement thickness with the increase in the elasticity number. These trends are opposite to those reported in the literature for a second-grade fluid. The surface velocity gradient and heat transfer are enhanced by the magnetic and buoyancy parameters. The surface heat transfer increases with the Prandtl number, but the surface velocity gradient decreases.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

Combinatorial Design of Secure Lightweight Data Dispersal Schemes (Work in Progress)

Dispersing a data object into a set of data shares is an elemental stage in distributed communication and storage systems. In comparison to data replication, data dispersal with redundancy saves space and bandwidth. Moreover, dispersing a data object to distinct communication links or storage sites limits adversarial access to whole data and tolerates loss of a part of data shares. Existing data dispersal schemes have been proposed mostly based on various mathematical transformations on the data which induce high computation overhead. This paper presents a novel data dispersal scheme where each part of a data object is replicated, without encoding, into a subset of data shares according to combinatorial design theory. Particularly, data parts are mapped to points and data shares are mapped to lines of a projective plane. Data parts are then distributed to data shares using the point and line incidence relations in the plane so that certain subsets of data shares collectively possess all data parts. The presented scheme incorporates combinatorial design theory with inseparability transformation to achieve secure data dispersal at reduced computation, communication and storage costs. Rigorous formal analysis and experimental study demonstrate significant cost-benefits of the presented scheme in comparison to existing methods.

A Combinatorial Construct for Keyless Message Dispersal (Work in Progress)

We propose a keyless and lightweight message transformation scheme based on the combinatorial design theory for the confidentiality of a message transmitted in multiple parts through a network with multiple independent paths, or for data stored in multiple parts by a set of independent storage services such as the cloud providers. Our combinatorial scheme disperses a message into v output parts so that (k-1) or less parts do not reveal any information about any message part, and the message can only be recovered by the party who possesses all v output parts. Combinatorial scheme generates an xor transformation structure to disperse the message into v output parts. Inversion is done by applying the same xor transformation structure on output parts. The structure is generated using generalized quadrangles from design theory which represents symmetric point and line incidence relations in a projective plane. We randomize our solution by adding a random salt value and dispersing it together with the message. We show that a passive adversary with capability of accessing (k-1) communication links or storage services has no advantage so that the scheme is indistinguishable under adaptive chosen ciphertext attack (IND-CCA2).

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.