Punzi-loss:: a non-differentiable metric approximation for sensitivity optimisation in the search for new particles.

We present the novel implementation of a non-differentiable metric approximation and a corresponding loss-scheduling aimed at the search for new particles of unknown mass in high energy physics experiments. We call the loss-scheduling, based on the minimisation of a figure-of-merit related function typical of particle physics, a Punzi-loss function, and the neural network that utilises this loss function a Punzi-net. We show that the Punzi-net outperforms standard multivariate analysis techniques and generalises well to mass hypotheses for which it was not trained. This is achieved by training a single classifier that provides a coherent and optimal classification of all signal hypotheses over the whole search space. Our result constitutes a complementary approach to fully differentiable analyses in particle physics. We implemented this work using PyTorch and provide users full access to a public repository containing all the codes and a training example.

Measurement of Differential Branching Fractions of Inclusive B→X_{u}ℓ

The first measurements of differential branching fractions of inclusive semileptonic B→X_{u}ℓ^{+}ν_{ℓ} decays are performed using the full Belle data set of 711 fb^{-1} of integrated luminosity at the ϒ(4S) resonance and for ℓ=e, µ. With the availability of these measurements, new avenues for future shape-function model-independent determinations of the Cabibbo-Kobayashi-Maskawa matrix element |V_{ub}| can be pursued to gain new insights in the existing tension with respect to exclusive determinations. The differential branching fractions are reported as a function of the lepton energy, the four-momentum-transfer squared, light-cone momenta, the hadronic mass, and the hadronic mass squared. They are obtained by subtracting the backgrounds from semileptonic B→X_{c}ℓ^{+}ν_{ℓ} decays and other processes, and corrected for resolution and acceptance effects.

Association of insulin-like growth factor-1 receptor polymorphism in dementia.

There is an increasing interest in how oxidative stress can cause cells to go into apoptosis in both normal ageing and in neurodegenerative disorders. Previous research has implicated insulin-like growth factor-1 (IGF-1) as being involved in the pathogenesis in Alzheimer's disease (AD) by protecting the neurons through reducing neuronal susceptibility to oxidative stress. IGF-1 receptor (IGF-1R) polymorphisms alter cerebral and systemic levels of IGF-1 and may alter the function of the receptor. We genotyped the IGF-1R gene by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) to assess whether this gene polymorphism can be linked to dementia. We used leukocyte DNA from 72 patients with AD, 75 patients with vascular dementia (VaD), 14 patients with mixed dementia (AD+VaD), and a control group consisting of 209 individuals without a history of progressive neurological disorders. Analysis of gene frequency for gender revealed a significant difference between female VaD patients and female controls carrying at least one A allele (OR = 1.8, CI 95% 1.1-2.9, p = 0.02), but not for male patients. In addition, we found a strong tendency to a difference between all cases of female dementia patients and controls carrying the A allele (OR = 1.5, CI 95% 0.99-2.2, p = 0.054). Our results suggest that the A allele of IGF-1R may be involved in the pathogenesis of VaD in females.