Prompting AI Art: An Investigation into the Creative Skill of Prompt Engineering

Humankind is entering a novel era of creativity - an era in which anybody can synthesize digital content. The paradigm under which this revolution takes place is prompt-based learning (or in-context learning). This paradigm has found fruitful application in text-to-image generation where it is being used to synthesize digital images from zero-shot text prompts in natural language for the purpose of creating AI art. This activity is referred to as prompt engineering - the practice of iteratively crafting prompts to generate and improve images. In this paper, we investigate prompt engineering as a novel creative skill for creating prompt-based art. In three studies with participants recruited from a crowdsourcing platform, we explore whether untrained participants could 1) recognize the quality of prompts, 2) write prompts, and 3) improve their prompts. Our results indicate that participants could assess the quality of prompts and respective images. This ability increased with the participants' experience and interest in art. Participants further were able to write prompts in rich descriptive language. However, even though participants were specifically instructed to generate artworks, participants' prompts were missing the specific vocabulary needed to apply a certain style to the generated images. Our results suggest that prompt engineering is a learned skill that requires expertise and practice. Based on our findings and experience with running our studies with participants recruited from a crowdsourcing platform, we provide ten recommendations for conducting experimental research on text-to-image generation and prompt engineering with a paid crowd. Our studies offer a deeper understanding of prompt engineering thereby opening up avenues for research on the future of prompt engineering. We conclude by speculating on four possible futures of prompt engineering.Comment: 29 pages, 10 figure

Text-to-Image Generation: Perceptions and Realities

Generative AI is an emerging technology that will have a profound impact on society and individuals. Only a decade ago, it was thought that creative work would be among the last to be automated - yet today, we see AI encroaching on creative domains. In this paper, we present the key findings of a survey study on people's perceptions of text-to-image generation. We touch on participants' technical understanding of the emerging technology, their ideas for potential application areas, as well as concerns, risks, and dangers of text-to-image generation to society and the individual. The study found that participants were aware of the risks and dangers associated with the technology, but only few participants considered the technology to be a risk to themselves. Additionally, those who had tried the technology rated its future importance lower than those who had not.Comment: Accepted at Generative AI in HCI workshop, CHI '2

Elevated plasma levels of heparin-binding protein in intensive care unit patients with severe sepsis and septic shock

Introduction: Rapid detection of, and optimized treatment for, severe sepsis and septic shock is crucial for successful outcome. Heparin-binding protein (HBP), a potent inducer of increased vascular permeability, is a potentially useful biomarker for predicting outcome in patients with severe infections. Our aim was to study the systemic release and dynamics of HBP in the plasma of patients with severe sepsis and septic shock in the ICU. Methods: A prospective study was conducted of two patient cohorts treated in the ICU at Karolinska University Hospital Huddinge in Sweden. A total of 179 patients was included, of whom 151 had sepsis (126 with septic shock and 25 patients with severe sepsis) and 28 a non-septic critical condition. Blood samples were collected at five time points during six days after admission. Results: HBP levels were significantly higher in the sepsis group as compared to the control group. At admission to the ICU, a plasma HBP concentration of >= 15 ng/mL and/or a HBP (ng/mL)/white blood cell count (10(9)/L) ratio of >2 was found in 87.2% and 50.0% of critically ill patients with sepsis and non-septic illness, respectively. A lactate level of >2.5 mmol/L was detected in 64.9% and 56.0% of the same patient groups. Both in the sepsis group (n = 151) and in the whole group (n = 179), plasma HBP concentrations at admission and in the last measured sample within the 144 hour study period were significantly higher among 28-day non-survivors as compared to survivors and in the sepsis group, an elevated HBP-level at baseline was associated with an increased case-fatality rate at 28 days. Conclusions: Plasma HBP levels were significantly higher in patients with severe sepsis or septic shock compared to patients with a non-septic illness in the ICU. HBP was associated with severity of disease and an elevated HBP at admission was associated with an increased risk of death. HBP that rises over time may identify patients with a deteriorating prognosis. Thus, repeated HBP measurement in the ICU may help monitor treatment and predict outcome in patients with severe infections

Abstractions of linear dynamic networks for input selection in local module identification

In abstractions of linear dynamic networks, selected node signals are removed from the network, while keeping the remaining node signals invariant. The topology and link dynamics, or modules, of an abstracted network will generally be changed compared to the original network. Abstractions of dynamic networks can be used to select an appropriate set of node signals that are to be measured, on the basis of which a particular local module can be estimated. A method is introduced for network abstraction that generalizes previously introduced algorithms, as e.g. immersion and the method of indirect inputs. For this abstraction method it is shown under which conditions on the selected signals a particular module will remain invariant. This leads to sets of conditions on selected measured node variables that allow identification of the target module.Comment: 17 pages, 7 figures. Paper to appear in Automatica, Vol. 117, July 202

Evaluation of the Forsvall biopsy needle in an ex vivo model of transrectal prostate biopsy - a novel needle design with the objective to reduce the risk of post-biopsy infection

Background Transrectal prostate biopsy (TRbx) transfers colonic bacteria into prostatic tissue, potentially causing infectious complications, including sepsis. Our objective was to determine whether biopsy needle shape, surface properties and sampling mechanism affect the number of bacteria transferred through the colon wall, and evaluate a novel needle with improved properties. Methods The standard Tru-Cut biopsy needle used today was evaluated for mechanisms of bacterial transfer in a pilot study. A novel Tru-Cut needle (Forsvall needle prototype) was developed. TRbx was simulated using human colons ex-vivo. Four subtypes of the prototype needle were compared with a standard Tru-Cut needle (BARD 18 G). Prototype and standard needles were used to puncture 4 different colon specimens in 10 randomized sites per colon. Needles were submerged into culture media to capture translocated bacteria. The media was cultured on blood agar and then the total amount of transferred bacteria was calculated for each needle. The primary outcome measure was the percent reduction of bacteria translocated by the prototype needles relative to the standard needle. Secondary outcome measures were the effects of tip design and coating on the percent reduction of translocated bacteria. Results Prototype needles reduced the number of translocated bacteria by, on average, 96.0% (95% confidence interval 93.0-97.7%; p < 0.001) relative to the standard needle. This percent reduction was not significantly affected by prototype needle tip style or surface coating. Conclusions The Forsvall needle significantly reduces colonic bacterial translocation, suggesting that it could reduce infectious complications in prostate biopsy. A clinical trial has been initiated

Handbuch mobile Frühstücksverpflegung

Version 2.0_Frühling_2018 Weitere Informationen unter: https://www.zhaw.ch/de/lsfm/institute-zentren/ifm/ueber-uns/hospitality-management-und-consumer-fm/fm-in-healthcare/spitalgastronomie

Combining [(11)C]-AnxA5 PET imaging with serum biomarkers for improved detection in live mice of modest cell death in human solid tumor xenografts

BACKGROUND: In vivo imaging using Annexin A5-based radioligands is a powerful technique for visualizing massive cell death, but has been less successful in monitoring the modest cell death typically seen in solid tumors after chemotherapy. Here we combined dynamic positron emission tomography (PET) imaging using Annexin A5 with a serum-based apoptosis marker, for improved sensitivity and specificity in assessment of chemotherapy-induced cell death in a solid tumor model. METHODOLOGY/PRINCIPAL FINDINGS: Modest cell death was induced by doxorubicin in a mouse xenograft model with human FaDu head and neck cancer cells. PET imaging was based on (11)C-labeled Sel-tagged Annexin A5 ([(11)C]-AnxA5-ST) and a size-matched control. 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]-FDG) was utilized as a tracer of tissue metabolism. Serum biomarkers for cell death were ccK18 and K18 (M30 Apoptosense® and M65). Apoptosis in tissue sections was verified ex vivo for validation. Both PET imaging using [(11)C]-AnxA5-ST and serum ccK18/K18 levels revealed treatment-induced cell death, with ccK18 displaying the highest detection sensitivity. [(18)F]-FDG uptake was not affected by this treatment in this tumor model. [(11)C]-AnxA5-ST gave robust imaging readouts at one hour and its short half-life made it possible to perform paired scans in the same animal in one imaging session. CONCLUSIONS/SIGNIFICANCE: The combined use of dynamic PET with [(11)C]-AnxA5-ST, showing specific increases in tumor binding potential upon therapy, with ccK18/K18 serum measurements, as highly sensitive markers for cell death, enabled effective assessment of modest therapy-induced cell death in this mouse xenograft model of solid human tumors.VetenskapsrådetPublishe

Mean muscle attenuation correlates with severe acute pancreatitis unlike visceral adipose tissue and subcutaneous adipose tissue

Background: Acute pancreatitis (AP) is a frequent disorder with considerable morbidity and mortality. Obesity has previously been reported to influence disease severity. Objective The aim of this study was to investigate the association of adipose and muscle parameters with the severity grade of AP. Methods: In total 454 patients were recruited. The first contrast-enhanced computed tomography of each patient was reviewed for adipose and muscle tissue parameters at L3 level. Associations with disease severity were analysed through logistic regression analysis. The predictive capacity of the parameters was investigated using receiver operating characteristic (ROC) curves. Results: No distinct variation was found between the AP severity groups in either adipose tissue parameters (visceral adipose tissue and subcutaneous adipose tissue) or visceral muscle ratio. However, muscle mass and mean muscle attenuation differed significantly with p-values of 0.037 and 0.003 respectively. In multivariate analysis, low muscle attenuation was associated with severe AP with an odds ratio of 4.09 (95% confidence intervals: 1.61-10.36, p-value 0.003). No body parameter presented sufficient predictive capability in ROC-curve analysis. Conclusions: Our results demonstrate that a low muscle attenuation level is associated with an increased risk of severe AP. Future prospective studies will help identify the underlying mechanisms and characterise the influence of body composition parameters on AP.Peer reviewe