Electron rescattering in strong-field photodetachment of F-

We present ab initio studies of photoelectron spectra for above threshold detachment (ATD) of F- anions in short, 1300 nm and 1800 nm laser pulses. We identify and assess the importance of electron rescattering in strong-field photodetachment of a negative ion through comparison with an analytic, Keldysh-type approach, demonstrating the capability of ab-initio computation in the challenging near-IR regime. We further assess the influence of the strong electron correlation on the photodetachment.

On the Complexity of Strong and Epistemic Credal Networks

Credal networks are graph-based statistical models whose parameters take values on a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The result of inferences with such models depends on the irrelevance/independence concept adopted. In this paper, we study the computational complexity of inferences under the concepts of epistemic irrelevance and strong independence. We strengthen complexity results by showing that inferences with strong independence are NP-hard even in credal trees with ternary variables, which indicates that tractable algorithms, including the existing one for epistemic trees, cannot be used for strong independence. We prove that the polynomial time of inferences in credal trees under epistemic irrelevance is not likely to extend to more general models, because the problem becomes NP-hard even in simple polytrees. These results draw a definite line between networks with efficient inferences and those where inferences are hard, and close several open questions regarding the computational complexity of such models.

Where the Lake Meets the Sea: Strong Reproductive Isolation Is Associated with Adaptive Divergence between Lake Resident and Anadromous Three-Spined Sticklebacks

Contact zones between divergent forms of the same species are often characterised by high levels of phenotypic diversity over small geographic distances. What processes are involved in generating such high phenotypic diversity? One possibility is that introgression and recombination between divergent forms in contact zones results in greater phenotypic and genetic polymorphism. Alternatively, strong reproductive isolation between forms may maintain distinct phenotypes, preventing homogenisation by gene flow. Contact zones between divergent freshwater-resident and anadromous stickleback (Gasterosteus aculeatus L.) forms are numerous and common throughout the species distribution, offering an opportunity to examine these contrasting hypotheses in greater detail. This study reports on an interesting new contact zone located in a tidally influenced lake catchment in western Ireland, characterised by high polymorphism for lateral plate phenotypes. Using neutral and QTL-linked microsatellite markers, we tested whether the high diversity observed in this contact zone arose as a result of introgression or reproductive isolation between divergent forms: we found strong support for the latter hypothesis. Three phenotypic and genetic clusters were identified, consistent with two divergent resident forms and a distinct anadromous completely plated population that migrates in and out of the system. Given the strong neutral differentiation detected between all three morphotypes (mean FST = 0.12), we hypothesised that divergent selection between forms maintains reproductive isolation. We found a correlation between neutral genetic and adaptive genetic differentiation that support this. While strong associations between QTL linked markers and phenotypes were also observed in this wild population, our results support the suggestion that such associations may be more complex in some Atlantic populations compared to those in the Pacific. These findings provide an important foundation for future work investigating the dynamics of gene flow and adaptive divergence in this newly discovered stickleback contact zone.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Donor chimaerism is a strong indicator of disease free survival following bone marrow transplantation for chronic myeloid leukaemia

Although Chronic Myeloid Leukaemia (CML) can be treated successfully with allogeneic bone marrow transplantation (BMT), leukaemia relapse remains a significant clinical problem. Molecular monitoring of the post transplant marrow can be useful in predicting relapse particularly in CML patients where the Philadelphia chromosome or its molecular counterpart, the BCR-ABL fusion messenger RNA can be used as a leukaemia specific marker of minimal residual disease (MRD). We have investigated chimaerism (using polymerase chain reaction of short tandem repeat sequences (STR-PCR)) and MRD status (using reverse transcriptase PCR of the BCR-ABL fusion mRNA) in a serial fashion in 18 patients who were in clinical and haematological remission post allogeneic BMT for chronic phase CML. Eleven patients exhibited complete donor chimaerism with no evidence of minimal residual disease. Five patients had transient or low level stable MC. Late MC and MRD was observed in two patients who relapsed > 6 years after T cell depleted BMT for CML. Thus STR-PCR is an appropriate screening test in the post transplant setting for CML patients, but those patients exhibiting mixed haemopoietic chimaerism should also be monitored using a leukaemia specific sensitive molecular assay.

Privacy-Protected Facial Biometric Verification via Fuzzy Forest Learning

Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacyrelated applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.

Vacuum birefringence in strong inhomogeneous electromagnetic fields

Birefringence is one of the fascinating properties of the vacuum of quantum electrodynamics (QED) in strong electromagnetic fields. The scattering of linearly polarized incident probe photons into a perpendicularly polarized mode provides a distinct signature of the optical activity of the quantum vacuum and thus offers an excellent opportunity for a precision test of nonlinear QED. Precision tests require accurate predictions and thus a theoretical framework that is capable of taking the detailed experimental geometry into account. We derive analytical solutions for vacuum birefringence which include the spatio-temporal field structure of a strong optical pump laser field and an x-ray probe. We show that the angular distribution of the scattered photons depends strongly on the interaction geometry and find that scattering of the perpendicularly polarized scattered photons out of the cone of the incident probe x-ray beam is the key to making the phenomenon experimentally accessible with the current generation of FEL/high-field laser facilities.

Strong second harmonic generation in SiC, ZnO, GaN two-dimensional hexagonal crystals from first-principles many-body calculations

The second harmonic generation (SHG) intensity spectrum of SiC, ZnO, GaN two-dimensional hexagonal crystals is calculated by using a real-time first-principles approach based on Green's function theory [Attaccalite et al., Phys. Rev. B: Condens. Matter Mater. Phys. 2013 88, 235113]. This approach allows one to go beyond the independent particle description used in standard first-principles nonlinear optics calculations by including quasiparticle corrections (by means of the GW approximation), crystal local field effects and excitonic effects. Our results show that the SHG spectra obtained using the latter approach differ significantly from their independent particle counterparts. In particular they show strong excitonic resonances at which the SHG intensity is about two times stronger than within the independent particle approximation. All the systems studied (whose stabilities have been predicted theoretically) are transparent and at the same time exhibit a remarkable SHG intensity in the range of frequencies at which Ti:sapphire and Nd:YAG lasers operate; thus they can be of interest for nanoscale nonlinear frequency conversion devices. Specifically the SHG intensity at 800 nm (1.55 eV) ranges from about 40-80 pm V(-1) in ZnO and GaN to 0.6 nm V(-1) in SiC. The latter value in particular is 1 order of magnitude larger than values in standard nonlinear crystals.