Composite dark matter from a model with composite Higgs boson

In a previous paper \cite{Khlopov:2007ic}, we showed how the minimal walking technicolor model (WTC) can provide a composite dark matter candidate, by forming bound states between a -2 electrically charged techniparticle and a $^4He^{++}$. We studied the properties of these \emph{techni-O-helium} $tOHe$ "atoms", which behave as warmer dark matter rather than cold. In this paper we extend our work on several different aspects. We study the possibility of a mixed scenario where both $tOHe$ and bound states between +2 and -2 electrically charged techniparticles coexist in the dark matter density. We argue that these newly proposed bound states solely made of techniparticles, although they behave as Weakly Interacting Massive Particles (WIMPs), due to their large elastic cross section with nuclei, can only account for a small percentage of the dark matter density. Therefore we conclude that within the minimal WTC, composite dark matter should be mostly composed of $tOHe$. Moreover in this paper, we put cosmological bounds in the masses of the techniparticles, if they compose the dark matter density. Finally we propose within this setup, a possible explanation of the discrepancy between the DAMA/NaI and DAMA/LIBRA findings and the negative results of CDMS and other direct dark matter searches that imply nuclear recoil measurement, which should accompany ionization.Comment: 23 page

Applied Sensor Fault Detection, Identification and Data Reconstruction

Sensor fault detection and identification (SFD/I) has attracted considerable attention in military applications, especially when safety- or mission-critical issues are of paramount importance. Here, two readily implementable approaches for SFD/I are proposed through hierarchical clustering and self-organizing map neural networks. The proposed methodologies are capable of detecting sensor faults from a large group of sensors measuring different physical quantities and achieve SFD/I in a single stage. Furthermore, it is possible to reconstruct the measurements expected from the faulted sensor and thereby facilitate improved unit availability. The efficacy of the proposed approaches is demonstrated through the use of measurements from experimental trials on a gas turbine. Ultimately, the underlying principles are readily transferable to other complex industrial and military systems

Single-walled carbon nanotube modelling based on Cosserat surface theory

This paper studies the mechanical properties of single-walled carbon nanotubes (SWCNTs). In order to overcome the difficulty of spanning multi-scales from atomistic field to macroscopic space, the Cauchy-Born rule is applied to link the deformation of atom lattice vectors at the atomic level with the material deformation at a macro continuum level. SWCNTs are modelled as Cosserat surfaces, and the modified shell theory is adopted where a displacement field-independent rotation tensor is introduced, which describes the rotation of the inner structure of the surface, i.e. the micro-rotation. Empirical interatomic potentials are employed, so that the force and modulus fields can be computed by the derivations of potential forms from the displacement and rotation fields. A finite element approach is implemented. The Young’s modulus is predicted for SWCNTs in the paper

Fault detection and diagnosis based on extensions of PCA

The paper presents two approaches for fault detection and discrimination based on principal component analysis (PCA). The first approach proposes the concept of y-indices through a transposed formulation of the data matrices utilized in traditional PCA. Residual errors (REs) and faulty sensor identification indices (FSIIs) are introduced in the second approach, where REs are generated from the residual sub-space of PCA, and FSIIs are introduced to classify sensor- or component-faults. Through field data from gas turbines during commissioning, it is shown that in-operation sensor faults can be detected, and sensor- and component-faults can be discriminated through the proposed methods. The techniques are generic, and will find use in many military systems with complex, safety critical control and sensor arrangements

Regional Heterogeneity and China’s International Trade: Sufficient Lumpiness or Not?

This paper explores whether there is sufficient lumpiness or heterogeneity in the relative endowments (capital, labour and skills) of the regions of China to affect China’s specialization and trade patterns. It does so using both the lens condition to identify the violation of factor price equalization across regions, and direct evidence on regional trade and specialization. The results are sensitive to the level of regional aggregation. The paper concludes, however, that China was sufficiently lumpy as recently as 2004 to affect it pattern of international trade.Trade, lumpiness, regions, China

Timed Fault Tree Models of the China Yongwen Railway Accident

Safety is an essential requirement for railway transportation. There are many methods that have been developed to predict, prevent and mitigate accidents in this context. All of these methods have their own purpose and limitations. This paper presents a new useful analysis technique: timed fault tree analysis. This method extends traditional fault tree analysis with temporal events and fault characteristics. Timed Fault Trees (TFTs) can determine which faults need to be eliminated urgently, and it can also provide a safe time window to repair them. They can also be used to determine the time taken for railway maintenance requirements, and thereby improve maintenance efficiency, and reduce risks. In this paper, we present the features and functionality of a railway transportation system based on timed fault tree models. We demonstrate the applicability of our framework via a case study of the China Yongwen line railway accident