Bose-Einstein condensates with attractive 1/r interaction: The case of self-trapping

Amplifying on a proposal by O'Dell et al. for the realization of Bose-Einstein condensates of neutral atoms with attractive $1/r$ interaction, we point out that the instance of self-trapping of the condensate, without external trap potential, is physically best understood by introducing appropriate "atomic" units. This reveals a remarkable scaling property: the physics of the condensate depends only on the two parameters $N^2 a/a_u$ and $\gamma/N^2$, where $N$ is the particle number, $a$ the scattering length, $a_u$ the "Bohr" radius and $\gamma$ the trap frequency in atomic units. We calculate accurate numerical results for self-trapping wave functions and potentials, for energies, sizes and peak densities, and compare with previous variational results. As a novel feature we point out the existence of a second solution of the extended Gross-Pitaevskii equation for negative scattering lengths, with and without trapping potential, which is born together with the ground state in a tangent bifurcation. This indicates the existence of an unstable collectively excited state of the condensate for negative scattering lengths.Comment: 7 pages, 7 figures, to appear in Phys. Rev.

Applications of Sequential Learning for Medical Image Classification

Purpose: The aim of this work is to develop a neural network training framework for continual training of small amounts of medical imaging data and create heuristics to assess training in the absence of a hold-out validation or test set. Materials and Methods: We formulated a retrospective sequential learning approach that would train and consistently update a model on mini-batches of medical images over time. We address problems that impede sequential learning such as overfitting, catastrophic forgetting, and concept drift through PyTorch convolutional neural networks (CNN) and publicly available Medical MNIST and NIH Chest X-Ray imaging datasets. We begin by comparing two methods for a sequentially trained CNN with and without base pre-training. We then transition to two methods of unique training and validation data recruitment to estimate full information extraction without overfitting. Lastly, we consider an example of real-life data that shows how our approach would see mainstream research implementation. Results: For the first experiment, both approaches successfully reach a ~95% accuracy threshold, although the short pre-training step enables sequential accuracy to plateau in fewer steps. The second experiment comparing two methods showed better performance with the second method which crosses the ~90% accuracy threshold much sooner. The final experiment showed a slight advantage with a pre-training step that allows the CNN to cross ~60% threshold much sooner than without pre-training. Conclusion: We have displayed sequential learning as a serviceable multi-classification technique statistically comparable to traditional CNNs that can acquire data in small increments feasible for clinically realistic scenarios

Evidential Uncertainty Quantification: A Variance-Based Perspective

Uncertainty quantification of deep neural networks has become an active field of research and plays a crucial role in various downstream tasks such as active learning. Recent advances in evidential deep learning shed light on the direct quantification of aleatoric and epistemic uncertainties with a single forward pass of the model. Most traditional approaches adopt an entropy-based method to derive evidential uncertainty in classification, quantifying uncertainty at the sample level. However, the variance-based method that has been widely applied in regression problems is seldom used in the classification setting. In this work, we adapt the variance-based approach from regression to classification, quantifying classification uncertainty at the class level. The variance decomposition technique in regression is extended to class covariance decomposition in classification based on the law of total covariance, and the class correlation is also derived from the covariance. Experiments on cross-domain datasets are conducted to illustrate that the variance-based approach not only results in similar accuracy as the entropy-based one in active domain adaptation but also brings information about class-wise uncertainties as well as between-class correlations. The code is available at https://github.com/KerryDRX/EvidentialADA. This alternative means of evidential uncertainty quantification will give researchers more options when class uncertainties and correlations are important in their applications.Comment: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 202

Case report: Severe mercuric sulphate poisoning treated with 2,3-dimercaptopropane-1-sulphonate and haemodiafiltration

INTRODUCTION: Inorganic mercury poisoning is uncommon, but when it occurs it can result in severe, life-threatening features and acute renal failure. Previous reports on the use of extracorporeal procedures such as haemodialysis and haemoperfusion have shown no significant removal of mercury. We report here the successful use of the chelating agent 2,3-dimercaptopropane-1-sulphonate (DMPS), together with continuous veno-venous haemodiafiltration (CVVHDF), in a patient with severe inorganic mercury poisoning. CASE REPORT: A 40-year-old man presented with haematemesis after ingestion of 1 g mercuric sulphate and rapidly deteriorated in the emergency department, requiring intubation and ventilation. His initial blood mercury was 15 580 μg/l. At 4.5 hours after ingestion he was started on DMPS. He rapidly developed acute renal failure and so he was started on CVVHDF for renal support and in an attempt to improve mercury clearance; CVVHDF was continued for 14 days. METHODS: Regular ultradialysate and pre- and post-filtrate blood samples were taken and in addition all ultradialysate generated was collected to determine its mercury content. RESULTS: The total amount of mercury in the ultrafiltrate was 127 mg (12.7% of the ingested dose). The sieving coefficient ranged from 0.13 at 30-hours to 0.02 at 210-hours after ingestion. He developed no neurological features and was discharged from hospital on day 50. Five months after discharge from hospital he remained asymptomatic, with normal creatinine clearance. DISCUSSION: We describe a patient with severe inorganic mercury poisoning in whom full recovery occurred with the early use of the chelating agent DMPS and CVVHDF. There was removal of a significant amount of mercury by CVVHDF. CONCLUSION: We feel that CVVHDF should be considered in patients with inorganic mercury poisoning, particularly those who develop acute renal failure, together with meticulous supportive care and adequate doses of chelation therapy with DMPS

Comparison of resource use by COPD patients on inhaled therapies with long-acting bronchodilators: a database study

<p>Abstract</p> <p>Background</p> <p>The purpose of this analysis was to compare health care costs and utilization among COPD patients who had long-acting beta-2 agonist (LABA) OR long-acting muscarinic antagonist (LAMA); LABA AND LAMA; or LABA, LAMA, AND inhaled corticosteroid (ICS) prescription claims.</p> <p>Methods</p> <p>This was a 12 month pre-post, retrospective analysis using COPD patients in a national administrative insurance database. Propensity score and exact matching were used to match patients 1:1:1 between the LABA or LAMA (formoterol, salmeterol, or tiotropium), LABA and LAMA (tiotropium/formoterol or tiotropium/salmeterol), and LABA, LAMA and ICS (bronchodilators plus steroid) groups. Post-period comparisons were evaluated with analysis of covariance. Costs were evaluated from a commercial payer perspective.</p> <p>Results</p> <p>A total of 523 patients were matched using 29 pre-period variables (e.g., demographics, medication exposure). Post-match assessments indicated balance among the cohorts. COPD-related costs differed among groups (LABA or LAMA $2,051 SE = 91; LABA and LAMA$2,823 SE = 62; LABA, LAMA and ICS $3,546 SE = 89; all p < .0001) with the differences driven by study medication costs. However, non-study COPD medication costs were higher for the LABA or LAMA therapy group ($911 SE = 91) compared to the LABA and LAMA therapy group ($668 SE = 58; p = 0.0238) and non-study respiratory medications were approximately$100 greater for the LABA or LAMA therapy group relative to both LABA and LAMA (p = .0018) and LABA, LAMA, and ICS (p = .0071) therapy groups. While there was no observed difference in outpatient costs, there was a slightly higher number of outpatient visits per patient in the LABA and LAMA (25.5 SE = 0.9, p = 0.0070) relative to the LABA or LAMA therapy group (22.3 SE = 0.8) and higher utilization (89.7% of patients) with COPD visits in the LABA and LAMA therapy group relative to both the LABA or LAMA (73.8%; p < .0001) and LABA, LAMA and ICS therapy groups (85.3; p = 0.0305).</p> <p>Conclusions</p> <p>Significant cost differences driven mainly by pharmaceuticals were observed among LABA or LAMA, LABA and LAMA and LABA, LAMA and ICS therapies. A COPD-related cost offset was observed from single bronchodilator to two bronchodilators. Addition of an ICS with two bronchodilators resulted in higher treatment costs without reduction in other COPD-related costs compared with two bronchodilators.</p

Field-tunable magnetic phases in a semiconductor-based two-dimensional Kondo lattice

We show the existence of intrinsic localized spins in mesoscopic high-mobility GaAs/AlGaAs heterostructures. Non-equilibrium transport spectroscopy reveals a quasi-regular distribution of the spins, and indicates that the spins interact indirectly via the conduction electrons. The interaction between spins manifests in characteristic zero-bias anomaly near the Fermi energy, and indicates gate voltage-controllable magnetic phases in high-mobility heterostructures. To address this issue further, we have also designed electrostatically tunable Hall devices, that allow a probing of Hall characteristics at the active region of the mesoscopic devices. We show that the zero field Hall coefficient has an anomalous contribution, which can be attributed to scattering by the localized spins. The anomalous contribution can be destroyed by an increase in temperature, source drain bias, or field range.Comment: To be published in PhysicaE EP2DS proceedin

Genetic variation in populations of the earthworm, Lumbricus rubellus, across contaminated mine sites

Background&nbsp; Populations of the earthworm, Lumbricus rubellus, are commonly found across highly contaminated former mine sites and are considered to have under-gone selection for mitigating metal toxicity. Comparison of adapted populations with those found on less contaminated soils can provide insights into ecological processes that demonstrate the long-term effects of soil contamination. Contemporary sequencing methods allow for portrayal of demographic inferences and highlight genetic variation indicative of selection at specific genes. Furthermore, the occurrence of L. rubellus lineages across the UK allows for inferences of mechanisms associated with drivers of speciation and local adaptation.&nbsp; Results&nbsp; Using RADseq, we were able to define population structure between the two lineages through the use of draft genomes for each, demonstrating an absence of admixture between lineages and that populations over extensive geographic distances form discrete populations. Between the two British lineages, we were able to provide evidence for selection near to genes associated with epigenetic and morphological functions, as well as near a gene encoding a pheromone. Earthworms inhabiting highly contaminated soils bare close genomic resemblance to those from proximal control soils. We were able to define a number of SNPs that largely segregate populations and are indicative of genes that are likely under selection for managing metal toxicity. This includes calcium and phosphate-handling mechanisms linked to lead and arsenic contaminants, respectively, while we also observed evidence for glutathione-related mechanisms, including metallothionein, across multiple populations. Population genomic end points demonstrate no consistent reduction in nucleotide diversity, or increase in inbreeding coefficient, relative to history of exposure.&nbsp; &nbsp;Conclusions&nbsp; Though we can clearly define lineage membership using genomic markers, as well as population structure between geographic localities, it is difficult to resolve markers that segregate entirely between populations in response to soil metal concentrations. This may represent a highly variable series of traits in response to the heterogenous nature of the soil environment, but ultimately demonstrates the maintenance of lineage-specific genetic variation among local populations. L. rubellus appears to provide an exemplary system for exploring drivers for speciation, with a continuum of lineages coexisting across continental Europe, while distinct lineages exist in isolation throughout the UK

Research protocol: investigating the feasibility of a group self-management intervention for stroke (the GUSTO study)

Background: Life after stroke can be an ongoing struggle with over half of all survivors reporting unmet emotional and social needs. In the United Kingdom's (UK) national clinical guidelines for stroke, self-management is suggested as one approach which can support long-term needs. In the UK NHS, self-management interventions are delivered in various ways. Regardless of the delivery mechanism, a tailored approach and ways to integrate peer support are advocated. Group delivery offers a platform for peer support and has the potential to remain individualised. However, before the efficacy of a group self-management intervention can be tested, the feasibility must be explored. This research investigates the feasibility of a GroUp Self-management intervention for sTrOke (GUSTO). Methods: A randomised waitlist control design will be used to investigate the feasibility of a group self-management intervention adapted from an existing one-to-one intervention called Bridges. A mixed methods approach will be used. Qualitative work will capture participant experience, while quantitative work will allow preliminary comparison between the intervention and waitlist groups (between subjects) and pre-post intervention measures (within subjects). Interviews will be conducted with stroke survivors and focus groups with family and friends to assess acceptability of the intervention. Discussion: There is a growing interest in group-based self-management interventions for stroke as a method of supporting stroke survivors' ongoing unmet needs. This is an area with limited research to date. This study will inform design of a fully powered trial which would assess the efficacy of a group self-management intervention following stroke. Trial registration: ISRCTN19867168

The model of mortality with incident cirrhosis (MoMIC) and the model of long-term outlook of mortality in dcirrhosis (LOMiC)

The purpose of this study was to produce two statistical survival models in those with cirrhosis utilising only routine parameters, including non-liver-related clinical factors that influence survival. The first model identified and utilised factors impacting short-term survival to 90-days post incident diagnosis, and a further model characterised factors that impacted survival following this acute phase. Data were from the Clinical Practice Research Datalink linked with Hospital Episode Statistics. Incident cases in patients ≥18 years were identified between 1998 and 2014. Patients that had prior history of cancer or had received liver transplants prior were excluded. Model-1 used a logistic regression model to predict mortality. Model-2 used data from those patients who survived 90 days, and used an extension of the Cox regression model, adjusting for time-dependent covariables. At 90 days, 23% of patients had died. Overall median survival was 3.7 years. Model-1: numerous predictors, prior comorbidities and decompensating events were incorporated. All comorbidities contributed to increased odds of death, with renal disease having the largest adjusted odds ratio (OR = 3.35, 95%CI 2.97–3.77). Model-2: covariables included cumulative admissions for liver disease-related events and admissions for infections. Significant covariates were renal disease (adjusted hazard ratio (HR = 2.89, 2.47–3.38)), elevated bilirubin levels (aHR = 1.38, 1.26–1.51) and low sodium levels (aHR = 2.26, 1.84–2.78). An internal validation demonstrated reliability of both models. In conclusion: two survival models that included parameters commonly recorded in routine clinical practice were generated that reliably forecast the risk of death in patients with cirrhosis: in the acute, post diagnosis phase, and following this critical, 90 day phase. This has implications for practice and helps better forecast the risk of mortality from cirrhosis using routinely recorded parameters without inputs from specialists