Bose-Einstein condensation of trapped atoms with dipole interactions

The path integral Monte Carlo method is used to simulate dilute trapped Bose gases and to investigate the equilibrium properties at finite temperatures. The quantum particles have a long-range dipole-dipole interaction and a short-range s-wave interaction. Using an anisotropic pseudopotential for the long-range dipolar interaction and a hard-sphere potential for the short-range s-wave interaction, we calculate the energetics and structural properties as a function of temperature and the number of particles. Also, in order to determine the effects of dipole-dipole forces and the influence of the trapping field on the dipolar condensate, we use two cylindrically symmetric harmonic confinements (a cigar-shaped trap and a disk-shaped trap). We find that the net effect of dipole-dipole interactions is governed by the trapping geometry. For a cigar-shaped trap, the net contribution of dipolar interactions is attractive and the shrinking of the density profiles is observed. For a disk-shaped trap, the net effect of long-range dipolar forces is repulsive and the density profiles expand

Finite-temperature properties of quasi-2D Bose-Einstein condensates

Using the finite-temperature path integral Monte Carlo method, we investigate dilute, trapped Bose gases in a quasi-two dimensional geometry. The quantum particles have short-range, s-wave interactions described by a hard-sphere potential whose core radius equals its corresponding scattering length. The effect of both the temperature and the interparticle interaction on the equilibrium properties such as the total energy, the density profile, and the superfluid fraction is discussed. We compare our accurate results with both the semi-classical approximation and the exact results of an ideal Bose gas. Our results show that for repulsive interactions, (i) the minimum value of the aspect ratio, where the system starts to behave quasi-two dimensionally, increases as the two-body interaction strength increases, (ii) the superfluid fraction for a quasi-2D Bose gas is distinctly different from that for both a quasi-1D Bose gas and a true 3D system, i.e., the superfluid fraction for a quasi-2D Bose gas decreases faster than that for a quasi-1D system and a true 3D system with increasing temperature, and shows a stronger dependence on the interaction strength, (iii) the superfluid fraction for a quasi-2D Bose gas lies well below the values calculated from the semi-classical approximation, and (iv) the Kosterlitz-Thouless transition temperature decreases as the strength of the interaction increases.Comment: 6 pages, 5 figure

MildInt: Deep Learning-Based Multimodal Longitudinal Data Integration Framework

As large amounts of heterogeneous biomedical data become available, numerous methods for integrating such datasets have been developed to extract complementary knowledge from multiple domains of sources. Recently, a deep learning approach has shown promising results in a variety of research areas. However, applying the deep learning approach requires expertise for constructing a deep architecture that can take multimodal longitudinal data. Thus, in this paper, a deep learning-based python package for data integration is developed. The python package deep learning-based multimodal longitudinal data integration framework (MildInt) provides the preconstructed deep learning architecture for a classification task. MildInt contains two learning phases: learning feature representation from each modality of data and training a classifier for the final decision. Adopting deep architecture in the first phase leads to learning more task-relevant feature representation than a linear model. In the second phase, linear regression classifier is used for detecting and investigating biomarkers from multimodal data. Thus, by combining the linear model and the deep learning model, higher accuracy and better interpretability can be achieved. We validated the performance of our package using simulation data and real data. For the real data, as a pilot study, we used clinical and multimodal neuroimaging datasets in Alzheimer's disease to predict the disease progression. MildInt is capable of integrating multiple forms of numerical data including time series and non-time series data for extracting complementary features from the multimodal dataset

General Anesthesia, Cognition, and Neurological Comorbidities

General anesthesia is a frequently employed medical intervention that facilitates the induction of a temporary state of unconsciousness, hence facilitating the execution of surgical procedures in patients. Nevertheless, the cognitive capabilities of patients with neurological comorbidities, such as epilepsy or dementia, may be a subject of worry when contemplating the impact of general anesthesia. Studies have indicated that individuals who have pre-existing neurological diseases may encounter negative consequences on their brain function when exposed to anesthesia. These consequences can manifest as a reduction in cognitive abilities or a worsening of their current coexisting medical conditions. Hence, it is imperative for healthcare practitioners to thoroughly assess the potential advantages and disadvantages of general anesthesia in individuals with neurological comorbidities. This evaluation should encompass exploring alternative methodologies or tailoring anesthetic management strategies to mitigate potential complications and enhance patients’ overall results

Family Floer theory, non-abelianization, and Spectral Networks

In this paper, we study the relationship between Gaiotto-Moore-Neitzke's non-abelianization map and Floer theory. Given a complete GMN quadratic differential $\phi$ defined on a closed Riemann surface $C$, let $\tilde{C}$ be the complement of the poles of $\phi$. In the case where the spectral curve $\Sigma_{\phi}$ is exact with respect to the canonical Liouville form on $T^{\ast}\tilde{C}$, we show that an ``almost flat" $GL(1;\mathbb{C})$-local system $\mathcal{L}$ on $\Sigma_{\phi}$ defines a Floer cohomology local system $HF_t(\Sigma_{\phi},\mathcal{L};\mathbb{C})$ on $\tilde{C}$ for $0< t\leq 1$. Then we show that for small enough $t$, the non-abelianization of $\mathcal{L}$ is isomorphic to the family Floer cohomology local system $HF_t(\Sigma_{\phi},\mathcal{L};\mathbb{C})$Comment: 108 pages, 17 figures. Comments welcome

Bose-Einstein Condensation Temperature of a Homogeneous Weakly Interacting Bose Gas : PIMC study

Using a finite-temperature Path Integral Monte Carlo simulation (PIMC) method and finite-size scaling, we have investigated the interaction-induced shift of the phase transition temperature for Bose-Einstein condensation of homogeneous weakly interacting Bose gases in three dimensions, which is given by a proposed analytical expression $T_{c} = T_{c}^{0}\{1 + c_{1}an^{1/3}+[c'_{2}\ln(an^{1/3})+c''_{2}]a^{2}n^{2/3} +O(a^{3}n)\}$, where $T_{c}^{0}$ is the critical temperature for an ideal gas, $a$ is the s-wave scattering length, and $n$ is the number density. We have used smaller number densities and more time slices than in the previous PIMC simulations [Gruter {\it et al.}, Phys. Rev. Lett. {\bf 79}, 3549 (1997)] in order to understand the difference in the value of the coefficient $c_{1}$ between their results and the (apparently) other reliable results in the literature. Our results show that $\{(T_{c}-T_{c}^{0})/T_{c}^{0}\}/(an^{1/3})$ depends strongly on the interaction strength $an^{1/3}$ while the previous PIMC results are considerably flatter and smaller than our results. We obtain $c_{1}$ = 1.32 $\pm$ 0.14, in agreement with results from recent Monte Carlo methods of three-dimensional O(2) scalar $\phi^{4}$ field theory and variational perturbation theory

Effect of matrix constituents on the determination of plutonium and americium in bone

2019 Summer.Includes bibliographical references.There are numerous methods available in the literature for separating and analyzing radionuclides of interest from an array of environmental matrices. The quality of these methods can be affected by the stable elements that are commonly found in many of these samples. The presence of such interfering constituents can result in incomplete separation of the radioisotopes of interest as well as a reduced rate of recovery. This is especially the case when complex matrices such as samples of bone and bone ash are analyzed. Plutonium and americium tend to concentrate in bone, they are therefore often referred to as bone seekers. They accumulate in actively metabolizing portions of bones of mammals including humans. It is therefore extremely important to study and evaluate the accumulation of these radionuclides in human bone by analyzing bone samples. However, calcium, which is present in high concentrations in the hydroxyapatite that constitutes the bone, as well as sodium and potassium, have the potential to strongly affect the efficacy of radiochemical separation methods. The objective of this research is to investigate the influence of the major and minor elemental constituents present in bone on the affinity of plutonium and americium for a variety of commercial extraction chromatographic resins

Self-reported Mental Disorders Negatively Influence Surgical Outcomes After Arthroscopic Treatment of Femoroacetabular Impingement.

Background:Femoroacetabular impingement (FAI) is responsible for hip pain and dysfunction, and surgical outcomes depend on multiple factors. The presence of mental disorders negatively influences outcomes of multiple orthopaedic conditions, although the impact on FAI surgery is unclear. Hypothesis:The authors hypothesized that a preoperative self-reported history of mental disorders would negatively influence patient-reported outcome measures after FAI surgery. Study Design:Cohort study; Level of evidence, 3. Methods:A matched-cohort study was performed by reviewing a prospectively collected database of cases of arthroscopic management of FAI with a single surgeon over a 2-year period. Demographics and radiographic parameters were recorded for all patients. Patients completed the Hip Outcome Score-Activity of Daily Living Subscale (HOS-ADL), Hip Outcome Score-Sport-Specific Subscale (HOS-SSS), and modified Harris Hip Score (mHHS) prior to surgery and 2 years after surgery. Unpaired and paired t tests were used to compare results between and within cohorts at baseline and follow-up. Statistical significance was defined as P &lt; .05. Results:The cohort included 301 patients, with 75 and 226 patients reporting and not reporting a history of mental disorders, respectively. Before treatment, all patient-reported outcome measures were significantly lower among patients reporting a history of mental disorders (P &lt; .01 for HOS-ADL, HOS-SSS, and mHHS). Patients in both groups demonstrated significant improvements (P &lt; .0001) in HOS-ADL, HOS-SSS, and mHHS when preoperative outcome measures were compared with follow-up. Patients with reported mental disorders had significantly lower scores after surgery as compared with patients without mental disorders (P &lt; .0001 for HOS-ADL, HOS-SSS, and mHHS). Conclusion:The presence of a reported mental disorder is associated with lower patient-reported outcomes before and after surgical management of FAI. Statistically significant and clinically relevant improvements were observed for patients who reported mental disorders. The magnitude of these improvements was not as large as that for an age- and sex-matched control group without a self-reported mental disorder