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“\u3cem\u3eThere is no pandemic\u3c/em\u3e”: On Memes, Algorithms and other Interpassive Forms of Right-wing Disbelief
Get PDFThis essay examines several prominent memes that have circulated on Right-wing social media during the Covid-19 pandemic. The memes coordinate what I describe as a mode of interpassive humor, which positions those who “believe” in the crisis as naïve dupes, infantilizing those subjects who have fallen prey to the idea that they should take the pandemic seriously, and thereby delegating fearfulness to the other so that reactionary Covid-19 denialists may continue with their lives unaffected. The essay thereby seeks to draw suggestive lines of affiliation between studies of digital memes, evolutionary mimetics, and psychoanalytic theory, pointing to the algorithmic spread of disinformation during the coronavirus pandemic as a case of interpassive humor
Developing Sustainability Related Attitudes and 21st Century Skills through Informal Learning Opportunities
Get PDFInformal learning environments, like libraries and museums, are known to improve student achievement and motivation (Bartels 2001). A meta-analysis reports on the strong positive effects of after-school programs on feelings and attitudes and school performance (Durlak et al, 2007). When working on after-school programs, middle and high school students may develop skills like communication, collaboration, creativity, critical thinking, information literacy, and digital literacy. Such a program was offered by a 501c(3) organization as an informal learning opportunity. As part of this program, high school student volunteers living in the United States (US) designed and delivered learning experiences for elementary and middle school students living in rural regions in India. Adult volunteers supervised and helped coordinate these events that were delivered virtually on WhatsApp and Zoom. This brief provides preliminary observational results to answer the questions: How effective were the informal learning opportunities (a) in changing environmental sustainability related attitudes and behaviors and (b) in gaining 21st century skills for student volunteers in the US and the students from rural India
Achieving Equity and Excellence: A Multilevel Modeling of the Relationships among School Climate, Students’ Motivation, and Achievement with TIMSS 2019
Get PDFThis study examined the effects of students’ motivational factors and school climate factors on eighth-grade math and science achievement in the U.S. using data from the 2019 Trends in International Mathematics and Science Study (TIMSS). Two-level, cross-sectional hierarchical linear models were developed to analyze the data. The results showed that there was a significant variation in math and science achievement across schools. Only students’ confidence in math and school SES had statistically significant effects on students’ math achievement. School location and school SES had statistically significant effects on science achievement
Thermally Treated to Perfection: Enhancing Wood Color and Properties with Surface Thermal Treatment
Get PDFDarker-colored wood species usually have highervalues, many of which are endangered and underprotection. Chemical stains and finishes might alsoachieve similar color shades, but customers prefernon-chemical alternatives. Thermal treatment (TT)is one of the low-toxicity choices. It could producedarker shades and enhance some materialproperties but requires a large initial investmentand is time-consuming. This study aimed toevaluate a new type of TT: Surface ThermalTreatment (STT). White Ash, Yellow Poplar, and RedOak were selected and treated on a heated pressat varying temperatures and times. Artificial NeuralNetwork (ANN) was employed to model therelationship between temperature, time, and colorchange. Results demonstrated that STT can achieveefficient thermal modification. The combination oftemperature and duration brought differentshades to all 3 species. Application of the ANNmodel can simulate the process results fast with ahigh degree of accuracy (R2 =0.96)
Political Orientation in Ecocriticism: National Allegory in Vietnamese Ecofiction by Trần Duy Phiên
Get PDFSince the late 1990s, theories and practices of ecocriticism have tended to be more politically engaged than in its earliest phase, considering that “environmental problems cannot be solved without addressing issues of wealth and poverty, overconsumption, underdevelopment, and the notion of resource scarcity” (Heise 251-2). This paper engages with the political orientation in ecocriticism by examining presentations of humans and nature in three Vietnamese short stories – “Kiến và người” (The Ants and the Man, 1990), “Mối và người” (The Termite and the Man, 1992), and “Nhện và người” (The Spider and the Man, 2012) by Trần Duy Phiên (born 1942). These presentations center around conflicts between human characters and insect characters, in which the former attempt to dominate and exploit the latter and the latter resist and take revenge on the former. This paper delves into the political context of these presentations which is the Vietnamese government\u27s projects of modernizing the nation since the time it came into power in 1945 and particularly since the time of Reform in 1986. These projects include the making of modern citizens, civilizing the highland, and modernizing the national economy, all have aimed at clearing colonial legacies in material and mental aspects of postcolonial Vietnam. The paper argues that national allegory is a characteristic of Vietnamese ecofiction, which forms Vietnamese intellectuals’ engagement with the postcolonial condition of Vietnam. This argument in its turn affirms political engagements in ecocriticism as a historical situation, particularly in former colonial countries
Rheology of 3D printable ceramic suspensions: effects of non-adsorbing polymer on discontinuous shear thickening
Get PDFConcentrated suspensions of particles at volume fractions (ϕ) ≥ 0.5 often exhibit complex rheological behavior, transitioning from shear thinning to shear thickening as the shear stress or shear rate is increased. These suspensions can be extruded to form 3D structures, with non-adsorbing polymers often added as rheology modifiers to improve printability. Understanding how non-adsorbing polymers affect the suspension rheology, particularly the onset of shear thickening, is critical to the design of particle inks that will extrude uniformly. In this work, we examine the rheology of concentrated aqueous suspensions of colloidal alumina particles and the effects of adding non-adsorbing polyvinylpyrrolidone (PVP). First, we show that suspensions with ϕalumina = 0.560–0.575 exhibited discontinuous shear thickening (DST), where the viscosity increased by up to two orders of magnitude above an onset stress (τmin). Increasing ϕalumina from 0.550 to 0.575 increased the viscosity and yield stress in the shear thinning regime and decreased τmin. Next, PVP was added at concentrations within the dilute and semi-dilute non-entangled regimes of polymer conformation (ϕPVP = 0.005–0.050) to suspensions with constant ϕalumina = 0.550. DST was observed in all cases and increasing ϕPVP increased the viscosity and yield stress. Interestingly, increasing ϕPVP also increased τmin. We posit that the free PVP chains act as lubricants between alumina particles, increasing the stress needed to induce thickening. Finally, we demonstrate through direct comparisons of suspensions with and without PVP how non-adsorbing polymer addition can extend the extrusion processing window due to the increase in τmin
The Role of U.S. Government Regulatioms
No full textProvides detailed coverage of information resources on U.S. Government information resources for federal regulations. Features historical background on these regulations, details on the Federal Register and Code of Federal Regulations, includes information on individuals can participate in the federal regulatory process by commenting on proposed agency regulations via https://regulations.gov/, describes the role of presidential executive orders, refers to recent and upcoming U.S. Supreme Court cases involving federal regulations, and describes current congressional legislation seeking to give Congress greater involvement in the federal regulatory process
Gender and Sexual Orientation Bias in Categorical and Dimensional Models of Personality Pathology
No full textIn addition to replicating examinations of gender bias in the diagnosis of all cluster B personality disorders (PDs), this is the first study to examine the extent to which patient sexual orientation biases the diagnosis of antisocial, histrionic, and narcissistic PDs as well as whether or not such sexual orientation bias differs by patient gender. Furthermore, this study is the first to examine how such gender and sexual orientation biases are moderated by (1) the model of personality pathology used (i.e., traditional DSM vs. dimensional Alternate Model of Personality Disorders [AMPD]) and (2) measurement specificity (i.e., global PD measurement vs. symptomlevel measurement). To undertake these examinations, it utilized a vignette describing a patient whose gender identification (man or woman) and sexual orientation (heterosexual or gay/lesbian) were experimentally manipulated. Clinicians (N=435) were randomly assigned to examine one of the resultant four vignettes, after which they each completed three measures of personality pathology. Though there was evidence of gender bias, such bias was twice-to-four times as weak as gender bias found in past similar studies. There was no evidence of significant diagnostic bias based on patient sexual orientation and sexual orientation bias did not differ by patient gender. Broadly, neither gender nor sexual orientation bias was moderated by the model of personality pathology underlying the measures used, by the specificity with which the pathology was measured, or by clinician characteristics (i.e., age, gender, sexual orientation, licensure status, race). Results suggest a decrease in gender and sexual orientation bias within experimental contexts relative to that which was found by prior studies. Further examinations should elucidate the mechanisms moderating diagnostic bias
Broadband’s Role in Agricultural Job Postings In U.S. Counties
No full textThis study’s purpose is to examine the relationship between broadband and online agriculture job postings. While rural broadband has been a wide studied topic, little attention has been focused on broadband’s relationship to agricultural job demand. This research uses a spatial count model that estimates agriculture and digital agriculture jobs by U.S. counties. Data was collected using the Google Jobs API developed by SerpAPI. Job advertisements were collected monthly from June 2021 through June 2022 and again in November 2022. Digital agriculture jobs postings were extracted as a subset from the overall dataset. By searching for key terms in job advertisements, context analysis filtered and identified digital agriculture jobs. Digital agriculture job openings were identified in order to examine how broadband relates to data intensive jobs in agriculture. Jobs focused in digital agriculture require increased levels of technology and increased data throughput. We hypothesized that occurrences of digital agriculture job openings would likely be reliant on broadband. Broadband data in this study represents average download speeds, average upload speeds, the percentage of households with internet access, and the percentage of the population with internet speeds at and above 100 over 20 megabits per second. The approach for modeling this data requires a hurdle negative binomial regression model as our count data encountered many zero observations and suffered from overdispersion. Spatial effects were incorporated into the model to alleviate spatial autocorrelation and help define agricultural job openings among surrounding counties. Our findings support the funding of broadband policies in agriculture. While controlling for outside factors such as demographics and county production, we found that agriculture job openings were positively influenced by broadband. However, we determined that broadband metrics show no relationship with the presence of digital agriculture job openings likely due to rarity and potential seasonality in the data. This information aids as a steppingstone for increasing the knowledge of broadband’s impact on agriculture. This study may aid in supporting future studies that seek to define causal relationships between broadband and agriculture jobs
Detection of Stroke, Blood Vessel Landmarks, and Leptomeningeal Anastomoses in Mouse Brain Imaging
No full textCollateral connections in the brain, also known as Leptomeningeal Anastomoses, are connections between blood vessels originating from different arteries. Despite limited knowledge, they are suggested as an important contributor to cerebral stroke recovery that allows additional blood flow through the affected area. However, few databases and algorithms exist for this specific task of locating them. In this paper, a MATLAB program is developed to find these connections and detect strokes to replace manual labeling by professionals. The limited data available for this study are 23 2D microscopy images of mice cerebral vascular structures highlighted by dyes. In the images, strokes are shown to diminish the pixel count of vessels below 80% compared to the healthy brain. Stroke classification error is greatly reduced by narrowing the scope from comparing the entire hemisphere to one smaller region. A novel way of finding collateral connections is utilizing connected components. Connected components organize all adjacent pixels into a group. All collateral connections can be found on the border of two neighboring arterial flow regions, and belong to the same group of connected components with the arterial source from each side. Along with finding collateral connections, a newly created coordinate system allows regions to be defined relative to the brain landmarks, based on the brain’s center, orientation, and scale. The method newly proposed in this paper combines stroke detection, brain coordinate system extraction, and collateral connection detection in stroke-affected mouse brains using only image processing techniques. This allows a simpler, more explainable result on limited data than other techniques such as supervised machine learning. In addition, the new method does not require ground truth and high image count for training. This automated process was successfully interpreted by medical experts, which allows for further research into automating collateral connection detection in 3D