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 Krüppel-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 0.11–0.81); cirrhosis increased likelihood (PP SVR12 69% vs. 91%; AOR 4.26; 95%CI 1.64–11.09). Indigenous Australians had lower likelihood of retreatment initiation (AOR 0.36; 95%CI 0.15–0.81). 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