An evaluation of the historical issues associated with achieving non-helicopter V/STOL capability and the search for the flying car

Copyright @ 2010 The Royal Aeronautical Society. This article is the final author version of the published paper.Combined Vertical and short take-off and landing, or ‘V/STOL’ capability has been of great demand and interest in the field of aeronautics since the creation of the aircraft. V/STOL capability is a targeted capability for many projected or prototype future aircraft. Past V/STOL aircraft are reviewed and analysed with regard to their performance parameters. This research has found two embedded categories in this class of aircraft based on their propulsion systems, i.e. jet and non-jet propulsion, and highlights the significant performance differences between them. In light of historical experience the performance of a relatively new class of aircraft, the flying cars, has been evaluated

Analysis of water absorbency into knitted spacer structures

The absorbency properties of knitted structures are very important in designing garments that both remove liquid sweat from the skin and provide tactile and sensorial comfort to the wearer. Water absorbency by knitted spacer structures was experimentally investigated using a gravimetric absorbency tester to record absorbency rate, total absorbency, and time taken to saturate the structure. The geometry of spacer structures was analyzed and a model created to define the capillary characteristic in the spacer yarn. Absorbency into the spacer structures was modeled using the fabric parameters, the capillary radius, and the properties of water. Experimental and theoretical results were compared to validate the models

An Object-Based Approach to Modelling and Analysis of Failure Properties

In protection systems, when traditional technology is replaced by software, the functionality and complexity of the system is likely to increase. The quantitative evidence normally provided for safety certification of traditional systems cannot be relied upon in software-based systems. Instead there is a need to provide qualitative evidence. As a basis for the required qualitative evidence, we propose an object-based approach that allows modelling of both the application and software domains. From the object class model of a system and a formal specification of the failure properties of its components, we generate a graph of failure propagation over object classes, which is then used to generate a graph in terms of object instances in order to conduct fault tree analysis. The model is validated by comparing the resulting minimal cut sets with those obtained from the fault tree analysis of the original system. The approach is illustrated on a case study based on a protection system from..

Homology over trivial extensions of commutative DG algebras

Conditions on the Koszul complex of a noetherian local ring $R$ guarantee that $\mathrm{Tor}^{R}_{i}(M,N)$ is non-zero for infinitely many $i$, when $M$ and $N$ are finitely generated $R$-modules of infinite projective dimension. These conditions are obtained from results concerning Tor of differential graded modules over certain trivial extensions of commutative differential graded algebras.Comment: 14 page

Role of robotics in trauma and orthopaedics

There is always an ardent desire to obtain the best outcome in any surgery. To improve the quality of life of their patient is amongst the top priorities of most orthopaedic surgeons. It is a big challenge to accurately match a perfect pre-operative planning and obtain that intra operatively. Robotic technology is fast evolving in many surgical branches with orthopaedics as well, but limited with the price tag it comes with. Nevertheless, robotics is gaining momentum with some encouraging short-term results. Robotic surgery can offer significant improvement in surgical planning, accurate implant or prosthetic placement, which provide good outcomes that ultimately enhance patient safety. We review the various robotic advancements in the field of trauma and orthopaedic surgery.

Coherent Topological Charge Structure in CPN−1CP^{N-1} Models and QCD

In an effort to clarify the significance of the recent observation of long-range topological charge coherence in QCD gauge configurations, we study the local topological charge distributions in two-dimensional $CP^{N-1}$ sigma models, using the overlap Dirac operator to construct the lattice topological charge. We find long-range sign coherence of topological charge along extended one-dimensional structures in two-dimensional spacetime. We discuss the connection between the long range topological structure found in $CP^{N-1}$ and the observed sign coherence along three-dimensional sheets in four-dimensional QCD gauge configurations. In both cases, coherent regions of topological charge form along membrane-like surfaces of codimension one. We show that the Monte Carlo results, for both two-dimensional and four-dimensional gauge theory, support a view of topological charge fluctuations suggested by Luscher and Witten. In this framework, the observed membranes are associated with boundaries between ``k-vacua,'' characterized by an effective local value of $\theta$ which jumps by $\pm 2\pi$ across the boundary.Comment: 26 page

Bioactive molecule prediction using extreme gradient boosting

Following the explosive growth in chemical and biological data, the shift from traditional methods of drug discovery to computer-aided means has made data mining and machine learning methods integral parts of today's drug discovery process. In this paper, extreme gradient boosting (Xgboost), which is an ensemble of Classification and Regression Tree (CART) and a variant of the Gradient Boosting Machine, was investigated for the prediction of biological activity based on quantitative description of the compound's molecular structure. Seven datasets, well known in the literature were used in this paper and experimental results show that Xgboost can outperform machine learning algorithms like Random Forest (RF), Support Vector Machines (LSVM), Radial Basis Function Neural Network (RBFN) and Naïve Bayes (NB) for the prediction of biological activities. In addition to its ability to detect minority activity classes in highly imbalanced datasets, it showed remarkable performance on both high and low diversity datasets

Gauge-Invariant Formulation of Spin-Current-Density Functional Theory

Spin-currents and non-abelian gauge potentials in electronic systems can be treated by spin-current-density functional theory, whose main input is the exchange-correlation (xc) energy expressed as a functional of spin-currents. Constructing a functional of spin currents that is invariant under U(1)$\times$SU(2) transformations is a long-standing challenge. We solve the problem by expressing the energy as a functional of a new variable we call "invariant vorticity". As an illustration we construct the xc energy functional for a two-dimensional electron gas with linear spin-orbit coupling and show that it is proportional to the fourth power of the spin current.Comment: 8 pages, 3 figures, submitte