Branes are Waves and Monopoles

In a recent paper it was shown that fundamental strings are null waves in Double Field Theory. Similarly, membranes are waves in exceptional extended geometry. Here the story is continued by showing how various branes are Kaluza-Klein monopoles of these higher dimensional theories. Examining the specific case of the E7 exceptional extended geometry, we see that all branes are both waves and monopoles. Along the way we discuss the O(d; d) transformation of localized brane solutions not associated to an isometry and how true T-duality emerges in Double Field Theory when the background possesses isometries.Comment: 32 pages, Latex, v2, typos correcte

Generalised Kinematics for Double Field Theory

We formulate a kinematical extension of Double Field Theory on a $2d$-dimensional para-Hermitian manifold $(\mathcal{P},\eta,\omega)$ where the $O(d,d)$ metric $\eta$ is supplemented by an almost symplectic two-form $\omega$. Together $\eta$ and $\omega$ define an almost bi-Lagrangian structure $K$ which provides a splitting of the tangent bundle $T\mathcal{P}=L\oplus\tilde{L}$ into two Lagrangian subspaces. In this paper a canonical connection and a corresponding generalised Lie derivative for the Leibniz algebroid on $T\mathcal{P}$ are constructed. We find integrability conditions under which the symmetry algebra closes for general $\eta$ and $\omega$, even if they are not flat and constant. This formalism thus provides a generalisation of the kinematical structure of Double Field Theory. We also show that this formalism allows one to reconcile and unify Double Field Theory with Generalised Geometry which is thoroughly discussed.Comment: 41 pages, v2: typos corrected, references added, published versio

SODAS: Surveillance of Drugs of Abuse Study

Objective: Novel Psychoactive Substance (NPS) as a form of recreational drug use has become increasingly popular. There is a paucity of information with regards the prevalence and clinical sequalae of these drugs. The aim of this study was to detect NPS in patients presenting to the Emergency Department (ED) with suspected toxicological ingestion. Methods: The prospective study was performed in a large Emergency Department (ED) in the UK. During a three month period eighty patients were identified by clinicians as having potentially ingested a toxicological agent. Urine sample were analysed using liquid chromatography-high resolution mass spectrometry and basic clinical data was gathered. Results: 80 patients with a history of illicit or recreational drug consumption had urine screenings performed. 49% (39) of patients undergoing a screen had more than one illicit substance detected. 20% (16) of patients tested positive for at least one NPS. Conclusions: Almost half of patients presenting had ingestion of multiple substances which correlated poorly with self reporting of patients. Developing enhanced strategies to monitor evolving drug trends is crucial to the ability of clinicians to deliver care to this challenging group of patients

Hepatic fatty acid and glucose handling in metabolic disease: potential impact on cardiovascular disease risk

The prevalence of metabolic diseases, including type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatotic liver disease (MASLD) is increasing. Although invariably associated with obesity, the importance of fat deposition in non-adipose tissue organs has yet to be fully explored. Pathological ectopic fat deposition within the liver (known as (MASLD)) has been suggested to underlie the development of T2DM and is now emerging as an independent risk factor for cardiovascular disease (CVD). The process of hepatic de novo lipogenesis (DNL), that is the synthesis of fatty acids from non-lipid precursors (e.g. glucose), has received much attention as it sits at the intersect of hepatic glucose and fatty acid handling. An upregulation of the DNL pathway has been suggested to be central in the development of metabolic diseases (including MASLD, insulin resistance, and T2DM). Here we review the evidence to determine if hepatic DNL may play a role in the development of MASLD and T2DM and therefore underlie an increased risk of CVD

Assessing rotation-invariant feature classification for automated wildebeest population counts

Accurate and on-demand animal population counts are the holy grail for wildlife conservation organizations throughout the world because they enable fast and responsive adaptive management policies. While the collection of image data from camera traps, satellites, and manned or unmanned aircraft has advanced significantly, the detection and identification of animals within images remains a major bottleneck since counting is primarily conducted by dedicated enumerators or citizen scientists. Recent developments in the field of computer vision suggest a potential resolution to this issue through the use of rotation-invariant object descriptors combined with machine learning algorithms. Here we implement an algorithm to detect and count wildebeest from aerial images collected in the Serengeti National Park in 2009 as part of the biennial wildebeest count. We find that the per image error rates are greater than, but comparable to, two separate human counts. For the total count, the algorithm is more accurate than both manual counts, suggesting that human counters have a tendency to systematically over or under count images. While the accuracy of the algorithm is not yet at an acceptable level for fully automatic counts, our results show this method is a promising avenue for further research and we highlight specific areas where future research should focus in order to develop fast and accurate enumeration of aerial count data. If combined with a bespoke image collection protocol, this approach may yield a fully automated wildebeest count in the near future