655 research outputs found
Coherent Quantum Engineering of Free-Space Laser Cooling
We perform a quantitative analysis of the cooling dynamics of three-level
atomic systems interacting with two distinct lasers. Employing sparse-matrix
techniques, we find numerical solutions to the fully quantized master equation
in steady state. Our method allows straightforward determination of
laser-cooling temperatures without the ambiguity often accompanied by
semiclassical calculations, and more quickly than non-sparse techniques. Our
calculations allow us to develop an understanding of the regimes of cooling, as
well as a qualitative picture of the mechanism, related to the phenomenon of
electromagnetically induced transparency. Effects of the induced asymmetric
Fano-type lineshapes affect the detunings required for optimum cooling, as well
as the predicted minimum temperatures which can be lower than the Doppler limit
for either transition.Comment: 5 pages, 3 figure
Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential
The large language model called ChatGPT has drawn extensively attention
because of its human-like expression and reasoning abilities. In this study, we
investigate the feasibility of using ChatGPT in experiments on using ChatGPT to
translate radiology reports into plain language for patients and healthcare
providers so that they are educated for improved healthcare. Radiology reports
from 62 low-dose chest CT lung cancer screening scans and 76 brain MRI
metastases screening scans were collected in the first half of February for
this study. According to the evaluation by radiologists, ChatGPT can
successfully translate radiology reports into plain language with an average
score of 4.27 in the five-point system with 0.08 places of information missing
and 0.07 places of misinformation. In terms of the suggestions provided by
ChatGPT, they are general relevant such as keeping following-up with doctors
and closely monitoring any symptoms, and for about 37% of 138 cases in total
ChatGPT offers specific suggestions based on findings in the report. ChatGPT
also presents some randomness in its responses with occasionally
over-simplified or neglected information, which can be mitigated using a more
detailed prompt. Furthermore, ChatGPT results are compared with a newly
released large model GPT-4, showing that GPT-4 can significantly improve the
quality of translated reports. Our results show that it is feasible to utilize
large language models in clinical education, and further efforts are needed to
address limitations and maximize their potential
Head-Neck Dual-energy CT Contrast Media Reduction Using Diffusion Models
Iodinated contrast media is essential for dual-energy computed tomography
(DECT) angiography. Previous studies show that iodinated contrast media may
cause side effects, and the interruption of the supply chain in 2022 led to a
severe contrast media shortage in the US. Both factors justify the necessity of
contrast media reduction in relevant clinical applications. In this study, we
propose a diffusion model-based deep learning framework to address this
challenge. First, we simulate different levels of low contrast dosage DECT
scans from the standard normal contrast dosage DECT scans using material
decomposition. Conditional denoising diffusion probabilistic models are then
trained to enhance the contrast media and create contrast-enhanced images. Our
results demonstrate that the proposed methods can generate high-quality
contrast-enhanced results even for images obtained with as low as 12.5% of the
normal contrast dosage. Furthermore, our method outperforms selected competing
methods in a human reader study
Deformed Quantum Cohomology and (0,2) Mirror Symmetry
We compute instanton corrections to correlators in the genus-zero topological
subsector of a (0,2) supersymmetric gauged linear sigma model with target space
P1xP1, whose left-moving fermions couple to a deformation of the tangent
bundle. We then deduce the theory's chiral ring from these correlators, which
reduces in the limit of zero deformation to the (2,2) ring. Finally, we compare
our results with the computations carried out by Adams et al.[ABS04] and Katz
and Sharpe[KS06]. We find immediate agreement with the latter and an
interesting puzzle in completely matching the chiral ring of the former.Comment: AMSLatex, 30 pages, one eps figure. V4: typos corrected, final
version appearing in JHE
Case Report Malignant Catatonia Warrants Early Psychiatric-Critical Care Collaborative Management: Two Cases and Literature Review
Malignant catatonia (MC) is a life-threatening manifestation which can occur in the setting of an underlying neuropsychiatric syndrome or general medical illness and shares clinical and pathophysiological features and medical comorbidities with the Neuroleptic Malignant Syndrome (NMS). The subsequent diagnosis and definitive therapy of MC are typically delayed, which increases morbidity and mortality. We present two cases of MC and review recent literature of MC and NMS, illustrating factors which delay diagnosis and management. When clinical features suggest MC or NMS, we propose early critical care consultation and stabilization with collaborative psychiatric management
The ethical debate about the gig economy: a review and critical analysis
The gig economy is a phenomenon that is rapidly expanding, redefining the nature of work and contributing to a significant change in how contemporary economies are organised. Its expansion is not unproblematic. This article provides a clear and systematic analysis of the main ethical challenges caused by the gig economy. Following a brief overview of the gig economy, its scope and scale, we map the key ethical problems that it gives rise to, as they are discussed in the relevant literature. We map them onto three categories: the new organisation of work (what is done), the new nature of work (how it is done), and the new status of workers (who does it). We then evaluate a recent initiative from the EU that seeks to address the challenges of the gig economy. The 2019 report of the European High-Level Expert Group on the Impact of the Digital Transformation on EU Labour Markets is a positive step in the right direction. However, we argue that ethical concerns relating to algorithmic systems as mechanisms of control, and the discrimination, exclusion and disconnectedness faced by gig workers require further deliberation and policy response. A brief conclusion completes the analysis. The appendix presents the methodology underpinning our literature review
The Astropy Problem
The Astropy Project (http://astropy.org) is, in its own words, "a community
effort to develop a single core package for Astronomy in Python and foster
interoperability between Python astronomy packages." For five years this
project has been managed, written, and operated as a grassroots,
self-organized, almost entirely volunteer effort while the software is used by
the majority of the astronomical community. Despite this, the project has
always been and remains to this day effectively unfunded. Further, contributors
receive little or no formal recognition for creating and supporting what is now
critical software. This paper explores the problem in detail, outlines possible
solutions to correct this, and presents a few suggestions on how to address the
sustainability of general purpose astronomical software
Opposing transcriptional programs of KLF5 and AR emerge during therapy for advanced prostate cancer.
Endocrine therapies for prostate cancer inhibit the androgen receptor (AR) transcription factor. In most cases, AR activity resumes during therapy and drives progression to castration-resistant prostate cancer (CRPC). However, therapy can also promote lineage plasticity and select for AR-independent phenotypes that are uniformly lethal. Here, we demonstrate the stem cell transcription factor KrĂźppel-like factor 5 (KLF5) is low or absent in prostate cancers prior to endocrine therapy, but induced in a subset of CRPC, including CRPC displaying lineage plasticity. KLF5 and AR physically interact on chromatin and drive opposing transcriptional programs, with KLF5 promoting cellular migration, anchorage-independent growth, and basal epithelial cell phenotypes. We identify ERBB2 as a point of transcriptional convergence displaying activation by KLF5 and repression by AR. ERBB2 inhibitors preferentially block KLF5-driven oncogenic phenotypes. These findings implicate KLF5 as an oncogene that can be upregulated in CRPC to oppose AR activities and promote lineage plasticity
Heartbeats in the Wild: A Field Study Exploring ECG Biometrics in Everyday Life
This paper reports on an in-depth study of electrocardiogram (ECG) biometrics
in everyday life. We collected ECG data from 20 people over a week, using a
non-medical chest tracker. We evaluated user identification accuracy in several
scenarios and observed equal error rates of 9.15% to 21.91%, heavily depending
on 1) the number of days used for training, and 2) the number of heartbeats
used per identification decision. We conclude that ECG biometrics can work in
the wild but are less robust than expected based on the literature,
highlighting that previous lab studies obtained highly optimistic results with
regard to real life deployments. We explain this with noise due to changing
body postures and states as well as interrupted measures. We conclude with
implications for future research and the design of ECG biometrics systems for
real world deployments, including critical reflections on privacy.Comment: 14 pages, 10 figures, CHI'2
Retreatment for hepatitis C virus direct-acting antiviral therapy virological failure in primary and tertiary settings: The REACH-C cohort
Virological failure occurs in a small proportion of people treated for hepatitis C virus (HCV) with direct-acting antiviral (DAA) therapies. This study assessed retreatment for virological failure in a large real-world cohort. REACH-C is an Australian observational study (n = 10,843) evaluating treatment outcomes of sequential DAA initiations across 33 health services between March 2016 to June 2019. Virological failure retreatment data were collected until October 2020. Of 408 people with virological failure (81% male; median age 53; 38% cirrhosis; 56% genotype 3), 213 (54%) were retreated once; 15 were retreated twice. A range of genotype specific and pangenotypic DAAs were used to retreat virological failure in primary (n = 56) and tertiary (n = 157) settings. Following sofosbuvir/velpatasvir/voxilaprevir availability in 2019, the proportion retreated in primary care increased from 21% to 40% and median time to retreatment initiation declined from 294 to 152 days. Per protocol (PP) sustained virological response (SVR12) was similar for people retreated in primary and tertiary settings (80% vs 81%; p = 1.000). In regression analysis, sofosbuvir/velpatasvir/voxilaprevir (vs. other regimens) significantly decreased likelihood of second virological failure (PP SVR12 88% vs. 77%; adjusted odds ratio [AOR] 0.29; 95%CI 0.11â0.81); cirrhosis increased likelihood (PP SVR12 69% vs. 91%; AOR 4.26; 95%CI 1.64â11.09). Indigenous Australians had lower likelihood of retreatment initiation (AOR 0.36; 95%CI 0.15â0.81). Treatment setting and prescriber type were not associated with retreatment initiation or outcome. Virological failure can be effectively retreated in primary care. Expanded access to simplified retreatment regimens through decentralized models may increase retreatment uptake and reduce HCV-related mortality
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