Explore the vast range of titles available.

Childhood is marked by the rapid accumulation of knowledge and the prolific production of drawings. We conducted a systematic study of how children create and recognize line drawings of visual concepts. We recruited 2-10-year-olds to draw 48 categories via a kiosk at a children’s museum, resulting in >37K drawings. We analyze changes in the category-diagnostic information in these drawings using vision algorithms and annotations of object parts. We find developmental gains in children’s inclusion of category-diagnostic information that are not reducible to variation in visuomotor control or effort. Moreover, even unrecognizable drawings contain information about the animacy and size of the category children tried to draw. Using guessing games at the same kiosk, we find that children improve across childhood at recognizing each other’s line drawings. This work leverages vision algorithms to characterize developmental changes in children’s drawings and suggests that these changes reflect refinements in children’s internal representations. Children produce drawings prolifically throughout childhood. Here, the authors conducted a systematic study of how children create and recognize line drawings across development and suggest that changes in children’s drawings reflect refinements in how children represent visual concepts.

Data visualizations play a crucial role in communicating patterns in quantitative data, making data visualization literacy a key target of STEM education. However, it is currently unclear to what degree different assessments of data visualization literacy measure the same underlying constructs. Here, we administered two widely used graph comprehension assessments (Galesic and Garcia-Retamero in Med Dec Mak 31:444–457, 2011; Lee et al. in IEEE Trans Vis Comput Graph 235:51–560, 2016) to both a university-based convenience sample and a demographically representative sample of adult participants in the USA ( N =1,113). Our analysis of individual variability in test performance suggests that overall scores are correlated between assessments and associated with the amount of prior coursework in mathematics. However, further exploration of individual error patterns suggests that these assessments probe somewhat distinct components of data visualization literacy, and we do not find evidence that these components correspond to the categories that guided the design of either test (e.g., questions that require retrieving values rather than making comparisons). Together, these findings suggest opportunities for development of more comprehensive assessments of data visualization literacy that are organized by components that better account for detailed behavioral patterns.

From Paleolithic etchings to computational graphics, visualization technologies that enable us to externalize our thoughts have been critical to the communication of ideas to others and across generations. Not only have renderings like simple line-drawings been prolific across cultures, but in recent years, generative text-to-visual systems have dramatically decreased production barriers and have increasingly populated our modern world with rich artifacts of visual communication. The study of visual communication— how people express their knowledge in visual form—presents abundant opportunities and challenges to explore core mechanisms of human communication systems, because it relies on complex interactions between perception and pragmatics. What guides what visualization strategies people use to convey their ideas to others through visual form? My dissertation introduces new experimental methods to explore these strategies. Overall, I find that people’s visual production behaviors shift what kind of information they prioritize depending on their task goals and find that their representational choices directly impact downstream interpretation by viewers. In Chapter 1, I investigate how communicative goals and immediate sensory inputs jointly determine the kind of visual information that people include in their drawings and find that people flexibly adapt their behavior to these different task goals by prioritizing different semantic information about visual object concepts. In Chapter 2, I explore how people adapt their visualization strategies when producing diagrams (called “visual explanations”) of higher-level knowledge (e.g., object function vs. object appearance) and find that while these strategies facilitate inferences about physical mechanism, they do so at the expense visual fidelity and recognition of drawn objects. To evaluate whether such flexible visual communication behavior extends to more domain-specific knowledge, Chapter 3 explores how people evaluate what makes data visualization effective for different task goals and finds that people selectively prioritize different kinds of data visualization designs depending on what supports fast and accurate graph comprehension by viewers. Taken together, insights from these three lines of work build towards developing a more unified theory of visual communication and, ultimately, aim to better inform the development of human-centered visualization technologies guided by cognitive theories of visual communication.

Four experiments show that 4- and 5-year-olds (total N = 112) can identify the referent of underdetermined utterances through their Naïve Utility Calculus—an intuitive theory of people's behavior structured around an assumption that agents maximize utilities. In Experiments 1-2, a puppet asked for help without specifying to whom she was talking (\"Can you help me?\"). In Experiments 3-4, a puppet asked the child to pass an object without specifying what she wanted (\"Can you pass me that one?\"). Children's responses suggest that they considered cost trade-offs between the members in the interaction. These findings add to a body of work showing that reference resolution is informed by commonsense psychology from early in childhood.

Data visualizations play a crucial role in communicating patterns in quantitative data, making data visualization literacy a key target of STEM education. However, it is currently unclear to what degree different assessments of data visualization literacy measure the same underlying constructs. Here, we administered two widely used graph comprehension assessments (Galesic and Garcia-Retamero in Med Dec Mak 31:444–457, 2011; Lee et al. in IEEE Trans Vis Comput Graph 235:51–560, 2016) to both a university-based convenience sample and a demographically representative sample of adult participants in the USA ( N =1,113). Our analysis of individual variability in test performance suggests that overall scores are correlated between assessments and associated with the amount of prior coursework in mathematics. However, further exploration of individual error patterns suggests that these assessments probe somewhat distinct components of data visualization literacy, and we do not find evidence that these components correspond to the categories that guided the design of either test (e.g., questions that require retrieving values rather than making comparisons). Together, these findings suggest opportunities for development of more comprehensive assessments of data visualization literacy that are organized by components that better account for detailed behavioral patterns.

Sketching is a powerful tool for creating abstract images that are sparse but meaningful. Sketch understanding poses fundamental challenges for general-purpose vision algorithms because it requires robustness to the sparsity of sketches relative to natural visual inputs and because it demands tolerance for semantic ambiguity, as sketches can reliably evoke multiple meanings. While current vision algorithms have achieved high performance on a variety of visual tasks, it remains unclear to what extent they understand sketches in a human-like way. Here we introduce SEVA, a new benchmark dataset containing approximately 90K human-generated sketches of 128 object concepts produced under different time constraints, and thus systematically varying in sparsity. We evaluated a suite of state-of-the-art vision algorithms on their ability to correctly identify the target concept depicted in these sketches and to generate responses that are strongly aligned with human response patterns on the same sketch recognition task. We found that vision algorithms that better predicted human sketch recognition performance also better approximated human uncertainty about sketch meaning, but there remains a sizable gap between model and human response patterns. To explore the potential of models that emulate human visual abstraction in generative tasks, we conducted further evaluations of a recently developed sketch generation algorithm (Vinker et al., 2022) capable of generating sketches that vary in sparsity. We hope that public release of this dataset and evaluation protocol will catalyze progress towards algorithms with enhanced capacities for human-like visual abstraction.

The purpose of this study was to assess the prevalence and risk factors for syphilis infection among female sex workers (FSWs) in Liuzhou City, Guangxi Zhuang Autonomous Region, southern China. A cross-sectional study recruited FSWs using a venue-based method and subsequent snowball sampling with mapping strategies. Questionnaire-based interviews were conducted to collect demographic and behavioral information. Blood was tested for syphilis (RPR with TPPA confirmation) and HIV (EIA with Western blot confirmation) infections. Of the 362 eligible participants, 81.7% were non-local residents (60.5% from other parts of Guangxi and 21.2% were non-Guangxi residents); 58.0% belonged to non-Han minority ethnic groups; 37.5% reported inconsistent condom use with their clients and 71.2% reported inconsistent condom use with their regular sex partners during the past month. Nearly 10% reported having had sex with drug users. The prevalence rates for HIV and syphilis infections were 2.3% and 11.0%, respectively. Almost half (46.6%) of participants reported having had STD symptoms. Inconsistent condom use with clients in the past month (AOR = 5.0; 95% CI = 1.8-13.8), less education (OR = 2.6; 95% CI = 1.1-7.4), and HIV infection (AOR = 8.1; 95% CI = 1.1-68.5) were independently associated with syphilis infection.

Background: Cerebrospinal fluid (CSF) measures of β-amyloid 1–42 and tau differ between patients with Alzheimer’s Disease (AD) and elderly normal controls. The effect of time and APOE genotype on these biomarkers continues to be elucidated. Methods: We assessed CSF β-amyloid 1–42 and tau in 20 mild-to-moderate AD patients, 11 APOE Ε4+ and 9 APOE Ε4–, over a mean time of 3.8 years (range 1–11.1 years). Results: Over the period measured, CSF β-amyloid 1–42 levels were lower in APOE Ε4+ compared to APOE Ε4– patients, and the levels decreased over time. Tau levels were stable over time and did not show an effect of APOE allele. Conclusions: While this is a limited clinical sample, the further decrease in CSF β-amyloid 1–42 (i.e., more abnormal) combined with the CSF tau stability over a mean period of almost 4 years suggests that β-amyloid 1–42 and tau maintain their potential usefulness as diagnostic biomarkers over time. These findings should be taken into account if CSF β-amyloid 1–42 and tau are used as measures of treatment response.

House Minority Leader Hakeem Jeffries said Democrats will still press to extend a slate of expiring health insurance subsidies after Democratic backlash to the shutdown deal. Democrats on the House Oversight Committee released more Epstein files, and they mention President Trump. Weijia Jiang has more on what they say and the White House response. Over the past several weeks, the relationship between the United States and Venezuela reached a boiling point as the U.S. launched a series of strikes against vessels alleged to be carrying drugs. Now, Venezuelan military exercises broadcast on state TV suggest the threat is being felt by its leader, Nicolas Maduro. Margaret Brennan spoke to David Smolansky, one of Venezuela`s opposition leaders, about the country`s future. After 53 days out of session, the U.S. House finally gaveled back in for a high-stakes vote to reopen the government. While diplomatic relations between the United States and Russia are at a post-Cold War low, the U.S. and its NATO allies staged military training exercises in the Baltic Sea. Holly Williams shows how it played out aboard a NATO submarine. By day, a row of plain- looking sheds in sleepy Rockwood, Texas, looks like nothing more than a place to store farm tools and feed. But when the sun dips below the horizon, their roofs peel back in unison to reveal a hidden network of hundreds of telescopes.

Congress is expected to vote this week on billions of dollars for communities ravaged by this summer's hurricanes and floods. Sacred land in California's redwood forests is returned to its original owners. Justice Ketanji Brown makes history as the first Supreme Court justice in a Broadway production. A deadly school shooting occurs in Wisconsin just days before the holiday break. Donald Trump holds his first press conference since being elected. Donald Trump, without evidence, accuses the Biden administration of covering up what's behind the drone mystery that's concerning and perplexing millions of people in New Jersey and other Eastern states. The U.S. conducts airstrikes against ISIS camps in Syria, killing at least a dozen suspected terrorists.