RKR_K anomalies and simplified limits on Z′Z' models at the LHC

The LHCb collaboration has recently reported a 2.5 $\sigma$ discrepancy with respect to the predicted value in a test of lepton universality in the ratio $R_{K^*}= \hbox{BR}(B \to K^* \mu^+ \mu^-) / \hbox{BR}(B \to K^* e^+ e^-)$. Coupled with an earlier observation of a similar anomaly in $R_{K}$, this has generated significant excitement. A number of new physics scenarios have been proposed to explain the anomaly. In this work we consider simplified limits on $Z'$ models from ATLAS and CMS searches for new resonances in dilepton and dijet modes, and we use the simplified limits variable $\zeta$ to correlate the results of the resonance and B-decay experiments. By examining minimal $Z'$ models that can accomodate the observed LHCb results, we show that the high-mass resonance search results are begining to be sensitive to these models and that future results will be more informative.Comment: 24 pages, 5 figures. Typo corrected, resulting in strengthened limits. Additional references added; minor corrections found in referee process include

Bayesian neural networks via MCMC: a Python-based tutorial

Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain Monte-Carlo (MCMC) sampling techniques are used to implement Bayesian inference. In the past three decades, MCMC methods have faced a number of challenges in being adapted to larger models (such as in deep learning) and big data problems. Advanced proposals that incorporate gradients, such as a Langevin proposal distribution, provide a means to address some of the limitations of MCMC sampling for Bayesian neural networks. Furthermore, MCMC methods have typically been constrained to use by statisticians and are still not prominent among deep learning researchers. We present a tutorial for MCMC methods that covers simple Bayesian linear and logistic models, and Bayesian neural networks. The aim of this tutorial is to bridge the gap between theory and implementation via coding, given a general sparsity of libraries and tutorials to this end. This tutorial provides code in Python with data and instructions that enable their use and extension. We provide results for some benchmark problems showing the strengths and weaknesses of implementing the respective Bayesian models via MCMC. We highlight the challenges in sampling multi-modal posterior distributions in particular for the case of Bayesian neural networks, and the need for further improvement of convergence diagnosis

Improved model calibration techniques for predicting coastal storm erosion

A number of sophisticated numerical coastal erosion models have been developed which use different formulations (e.g., empirical and process-based) and modelling approaches (e.g., profile and area) to predict the impact of storm events on sandy beaches. As model complexity grows there is generally an accompanying increase in the number of free parameters that require calibration to field data. However, the calibration of coastal erosion models is all too commonly undertaken in a relatively ad-hoc manner and the influence of parameter-induced uncertainty on the overall model error is often neglected. This thesis seeks to provide generalised guidance on the calibration of coastal erosion models, and to evaluate and compare two of the more commonly used existing models based on their skill, calibration data requirements, limitations and predictive uncertainty. The Generalized Likelihood Uncertainty Estimation (GLUE) method was evaluated as a generic and rigorous model calibration technique. When compared to the commonly used manual `trial-and-error’ approach, GLUE is observed to facilitate: a significant improvement in model predictive skill; a more rigorous evaluation of model sensitivity to parameters; the ability to identify distinct differences in model performance dependent on specific processes; and additional insights including the quantification of parameter-induced uncertainty. GLUE techniques were utilised to compare two coastal erosion profile models (semi-empirical SBEACH and process-based XBeach) when applied across multiple storm events, and between adjacent beaches. SBEACH was found to be a more accurate tool when no calibration data was available; however, once calibrated with at least one storm event, XBeach displayed much better model skill. The availability of location-specific calibration data was found to be significant in maximising XBeach model performance. A detailed comparison of the XBeach profile and area modelling approaches was undertaken revealing clear differences in calibrated parameter values, significantly for the key parameter facua that controls the influence of wave asymmetry and skewness on sediment transport. The XBeach area model was observed to perform better with XBeach default parameters and reproduced a significant proportion of the alongshore variability in erosion response. The findings presented in this thesis can provide generic guidance for coastal engineers looking to apply coastal erosion models

How Intelligent CI Instruction Gives Law Students a Competitive Edge

Competitive intelligence (CI) is a term that gets bandied about across many sectors, but how exactly do law firms use it to further their business? Academics are aware of CI as a concept, but teaching students how to conduct competitive intelligence requires a more nuanced understanding of how it is actually used. In a discussion moderated by a newer academic librarian who will be teaching competitive intelligence for the first time, a firm librarian will share insights into how competitive intelligence can and should be used, and an academic librarian who regularly teaches competitive intelligence will offer tips on how to construct CI lessons. Takeaways: Participants will be able to evaluate how firms use competitive intelligence in practice. Participants will be able to assess what competitive intelligence skills firms expect to see in new lawyers. Participants will be able to create learning objectives to focus instruction on providing law students with the competitive intelligence skills they need

The Five W’s of Merger

I’m a big student of the nineteenth century. I love the 1800s, I write about them, and I think about them a lot. There are a lot of questions in modern copyright law where we look back, and we spend time thinking about what was going on in the 1800s and opinions from the 1800s. And so when we came up with this idea to talk about the scope of copyright, I went back to the cases from the 1800s, and the Supreme Court has told us a lot about what is copyrightable and what is not from a perspective of merger—from a perspective of protecting laws or not

Expressive Aphasia and Carotid Dissection

Ultrasound images of a patient presenting to the emergency department with expressive aphasia who was found to have carotid dissection. The first image is a standard two dimensional image that depicts the internal carotid with a visible flap within the lumen. The second image is a color Doppler image showing turbulent flow within the true lumen and visible flow within the false lumen. The case and the patient’s outcome are summarized along with some teaching points about carotid dissection. Also, there is some background and research on using ultrasound to help identify dissection

Conservative and Surgical Management of Unilateral and Bilateral Internuclear Ophthalmoplegia (INO)—A Retrospective Analysis

Aim: To report the outcomes of the natural progression and ophthalmic treatment of patients reviewed in a tertiary hospital trust with unilateral or bilateral internuclear ophthalmoplegia. Method: A retrospective case note analysis was performed and 33 patients diagnosed with unilateral or bilateral internuclear ophthalmoplegia (INO) were identified. The diagnosis, aetiology, presence of diplopia, ophthalmic management options and progression were recorded and analysed. This included both conservative and surgical management. Results: The most common aetiologies of INO within this cohort were stroke/ischaemic (69.7%) and multiple sclerosis (MS) (30.3%). Unilateral INO was more prevalent than bilateral INO, with 20 cases (60.6%) compared to 13 cases (39.4%), respectively. A higher proportion of unilateral INO were attributed to stroke (90%) whilst a higher proportion of bilateral INO were attributed to MS (61.5%). The most prescribed management at primary assessment was occlusion (45.5%) and prisms (24.2%). Some patients required no orthoptic intervention (30.3%). Two patients had surgical management of strabismus secondary to bilateral INO. Conclusion: Occlusion was the most common form of management for symptomatic relief of diplopia. Patients who presented at the first visit with no symptoms were unlikely to need any orthoptic intervention. Of the two patients who went on to require surgical intervention, restoration of binocular single vision (BSV) was achieved post-operatively with the use of a Fresnel prism. However, the differences in both surgical technique and number of surgeries required make this difficult to generalise. Additional research is needed to further explore the surgical management of INO

Aerospike Rockets for Increased Space Launch Capability

The US Department of Defense DOD increasingly depends on space assets for everyday operations. Precision navigation communications and intelligence, surveillance, and reconnaissance satellites are highly leveraged space assets. The launch vehicles that place these satellites in orbit are a major limitation of current space systems. If higher-performing launch vehicles were available, many satellites could accommodate additional capabilities, whether in terms of more sensor channels, types of payloads, electrical power, or propellant for orbital maneuvering and station keeping. Space assets are typically designed to conform to a particular launch vehicle s limitations e.g., engineers might design a satellite to be carried by a Delta IV-2 medium launch vehicle. Essentially, this choice of vehicle fixes the maximum mass of the satellite and, thus, its capabilities. If a launcher capable of placing more mass in the desired orbit were available at similar cost, the satellite s design could allow for additional capability. Furthermore, some payloads are too heavy for present-day launch vehicles to place into a particular orbit. A better-performing launcher would enable us to put those payloads into the desired orbits, permitting new missions and capabilities