On the origin of the forward peak and backward oscillations in the F + H2(v = 0) to HF(v' = 2) + H reaction

We present a semiclassical complex angular momentum (CAM) analysis of the forward scattering peak which occurs at a translational collision energy around 32 meV in the quantum mechanical calculations for the F + H2(v = 0, j = 0) ? HF(v' = 2, j' = 0) + H reaction on the Stark–Werner potential energy surface. The semiclassical CAM theory is modified to cover the forward and backward scattering angles. The peak is shown to result from constructive/destructive interference of the two Regge states associated with two resonances, one in the transition state region and the other in the exit channel van der Waals well. In addition, we demonstrate that the oscillations in the energy dependence of the backward differential cross section are caused by the interference between the direct backward scattering and the decay of the two resonance complexes returning to the backward direction after one full rotation.

Discovery and Evidence in Transnational Antitrust Cases: Current Framework and the Way Forward

This paper identifies and analyses the means of accessing and collecting foreign-based evidence in transnational antitrust cases. It makes an original contribution to the existing scholarship by critically addressing the available mechanisms of judicial cooperation, the possibility of reliance on domestic discovery in transnational context, as well as the existing instruments allowing for cooperation between antitrust agencies. It identifies the shortcomings of the current regulatory framework and points out to the existing good practices in those jurisdictions which provide their antitrust agencies with more leeway in sharing confidential information with foreign counterparts.

Autism and ABA: Best Practice in America and the Way Forward for Europe.

According to recent estimates, 1 in each 68 new-borns will be diagnosed with an Autism Spectrum Disorder (ASD) in the USA (Centers for Disease Control and Prevention, 2014), while 1 in every 29 children will be diagnosed with ASD in the UK (Dillenburger, Jordan, McKerr, & Keenan, 2015). Individuals diagnosed with ASD share a set of characteristics at varying levels of severity: impairments in social communication skills and presence of restricted interests and repetitive behaviours (American Psychiatric Association, 2013).Notwithstanding these figures, little effort has been placed in European countries’ policies for reaching an early diagnosis. This has a detrimental effect on future prognosis for children with ASD, since research has clearly shown that when evidence-based interventions are accessed early in life, they can lead to great improvements on the overall functioning of children with ASD, including significant gains in social communication and reduction of inappropriate behaviours (Dawson, Rogers, Munson, Smith, Winter, Greenson, Donaldson, & Varley, 2009).Additionally, when looking at the services available for children with ASD and their families in Europe, it seems that not much improvement has been made in the last decades. Traditional eclectic approaches and a wealth of non-scientific methods seem to be available and often recommended by public bodies, while state-funded evidence-based interventions are not offered as part of the education or health system. Given that there is a wealth of evidence on the effectiveness of interventions based on the science of ABA, it seems that specific action is required to correct the situation, respecting children’s right to effective treatment and inclusion.In the present paper, these issues are fully discussed and recommendations for best practice are offered.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.