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This paper examines a potentially fatal type of pathogen transmission, namely, the spillover of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from COVID-19-positive humans to nonhuman animals. This neglected direction of pathogen transmission ("anthroponosis") was first publicized in March 2020, when eight large felids at a zoo in New York City were infected with SARS-CoV-2 by a COVID-19-positive employee. The paper gathers and problematizes the as-yet sparse evidence of anthroponotic transmissions of SARS-CoV-2 at sites in the animal-industrial complex where animals are held captive in zoos; appointed as human companions; used in scientific experiments; and raised and slaughtered in industrialized agriculture. The great fear is that animals infected with SARS-CoV-2 by COVID-19-positive humans will develop mutant strains of the virus, that these variants will be transmitted back to humans, and that the variants will be immune to the vaccines currently in use or in development. When we harm animals, we harm ourselves. Never has the need for a nonspeciesist approach to public health and safety been more urgent. [ABSTRACT FROM AUTHOR]

Given the need to reduce fuel emissions from transport many research studies have been devoted to the development of technologies and identification of new policies to tackle this problem. The majority of these strategies either increase the costs (e.g., new technology), are more time-consuming (i.e., choosing a more sustainable mode of transport), or encourage consumers to forgo travel plans (i.e., flights to holiday destinations). Implementing any of these changes is challenging for a society where cost, quality and time are the key motivators. The paper differs from previous research, given that the focus is not to slow down global warming, through the development of new technologies, or through inconveniences to lifestyle. Instead, the focus is to improve the sustainability of transport using current technology without increasing the cost or time factor. By using the concept of effective speed, this paper estimates the possible reduction in emissions, external costs and land use if people can be persuaded to choose the most cost-effective mode of transport. The effective speed is calculated by dividing the distance travelled by the time spent (i.e., travelling to work and earning the money to pay for the commute). This case study uses data from a survey of residents in New York City (NYC) and incorporates supporting data about commuting patterns in Germany. If people use their most cost-effective mode of transport in NYC, it is possible to have emission reductions of up to 14.7%, external cost reduction of 11.6% and a reduction in the time–area requirements of 16.5%. The results of this paper highlight that people do not always need to spend more time or money on their transport activity to travel in a more sustainable way. Indeed, encouraging people to use a mode of transport with a faster effective speed may even reduce the external effects for some. [ABSTRACT FROM AUTHOR]

The article offers news briefs. The William Gropper papers which are considered as the largest among the collections in William Gropper papers are included in the different papers that came to the Archives through the New York Office. Arnold Friedman's papers were also given to the Archives. The illustrated envelope and letter written by Alexander Calder to Andrew Gagarin is one of the added acquisitions of the Archives.

In 1947, the Cornell psychiatrist Keeve Brodman and a handful of colleagues began developing what would become one of the most widely used health questionnaires of its time—the Cornell Medical Index (CMI). A rigidly standardized form, the CMI presented 195 yes-no questions designed to capture the health status of "the total patient." Over the following decades, Brodman's project of standardizing medical history taking gradually evolved into a project of mathematizing and computerizing diagnosis: out of the CMI grew the Medical Data Screen (MDS), one of the first computerized methods of deriving diagnoses from patient data. This essay follows the life course of these tools through the second half of the twentieth century. It argues for a genealogy of biomedical computing and computerized diagnosis that takes more seriously the continuities between computer-based digital practices and paper-based analog ones. The computerized MDS evolved from, and rested upon, paper data practices associated with questionnaires and surveys. The interlocking histories of the CMI and the MDS prompt a reconsideration of the material and temporal parameters within which the history of computerized medicine has conventionally been understood. [ABSTRACT FROM AUTHOR]

This paper aims to leverage Twitter data to understand travel mode choices during the pandemic. Tweets related to different travel modes in New York City (NYC) are fetched from Twitter in the two most recent years (January 2020–January 2022). Building on these data, we develop travel mode classifiers, adapted from natural language processing (NLP) models, to determine whether individual tweets are related to some travel mode (subway, bus, bike, taxi/Uber, and private vehicle). Sentiment analysis is performed to understand people's attitudinal changes about mode choices during the pandemic. Results show that a majority of people had a positive attitude toward buses, bikes, and private vehicles, which is consistent with the phenomenon of many commuters shifting away from subways to buses, bikes and private vehicles during the pandemic. We analyze negative tweets related to travel modes and find that people were worried about those who did not wear masks on subways and buses. Based on users' demographic information, we conduct regression analysis to analyze what factors affected people's attitude toward public transit. We find that the attitude of users in the service industry was more easily affected by MTA subway service during the pandemic. [ABSTRACT FROM AUTHOR]

The article reports on the research of psychologist Elizabeth Phelps and colleagues from New York University on ways of eliminating fearful memories, such as post-traumatic stress disorder. They found that a person's stored memory is called up and experienced anew and re-stored in a process known as reconsolidation. Moreover, she found that these painful memories can be eradicated by using behavioural manipulation or extinction training.

Focuses on the criticisms against the "New York Post" for running a photograph of Diana Chien who committed suicide in New York City. Defense of chief copy editor, Barry Gross on the use of the picture; Effects of the incident on the manner of reporting suicides in the media.

Shared bicycles provide a green, environmentally friendly, and healthy mode of transportation that effectively addresses the "final mile" problem in urban travel. However, the uneven distribution of bicycles and the imbalance of user demand can significantly impact user experience and bicycle usage efficiency, which makes it necessary to predict bicycle demand. In this paper, we propose a novel shared-bicycle demand prediction method based on station clustering. First, to address the challenge of capturing patterns in station-level bicycle demand, which exhibits significant fluctuations, we employ a clustering method that combines graph information from the bicycle transfer graph and potential energy. This method aggregates closely related stations into corresponding prediction regions. Second, we use the GCN-CRU-AM (Graph Convolutional Network-Gated Recurrent Unit-Attention Mechanism) model to predict bicycle demand in each region. This model extracts the spatial information and correlation between regions, integrates time feature data and local weather data, and assigns weights to the input features. Finally, experimental results based on the data from Citi Bike System in New York City demonstrate that the proposed model achieves a more accurate demand prediction. [ABSTRACT FROM AUTHOR]

The text introduces the Data Challenge Expo 2019, an annual event sponsored by the American Statistical Association. The challenge involves analyzing a data set from the New York City Housing and Vacancy Survey. Participants were asked to explore various research questions related to housing conditions, rent control, gentrification, immigrant residency, and the costs and benefits of renting versus owning in New York City. The winners of the challenge were announced at the Joint Statistical Meetings in 2019, and their analyses are described in this special issue of Computational Statistics. Supplementary materials, including data sets and code, are available for reproducibility purposes. [Extracted from the article]

The physical condition of an occupant's home represents a significant factor in determining the dweller's overall quality of life. This paper provides a statistical framework for measuring housing quality in an urban area through a standardized index. This index is constructed using principal component analysis, incorporating demographic, geographic, and economic factors from the New York City Housing and Vacancy Survey. This metric allows for investigating differences in housing quality based upon ownership status. Analysis of the index demonstrates that renters face more housing quality issues than owners. Several of the index's input variables driving these differences were found to exhibit varying effects on housing quality over time, possibly due to events such as the 2008 financial crisis. Implementing this novel statistical framework, housing quality indices can be constructed for other cities to examine housing disparities and inform policies aimed at improving quality of life for urban residents. [ABSTRACT FROM AUTHOR]

Grace Darling Wetherbee Coolidge's 1917 book Teepee Neighbors is a little-known collection of twenty-nine sketches of Indian life on the Wind River Reservation, Wyoming, where she worked as a missionary from 1902 to 1910. Only recently have Coolidge's personal papers been made publicly available by the Pioneers Museum in Colorado Springs, Colorado, allowing scholars to investigate the true contours of her life for the first time. These primary source materials shed new light on a woman who--though born to great privilege in New York City--rejected a life of leisure and wealth in favor of a subsistence existence on a remote Indian reservation, devoted to charitable acts. This paper offers the first accurate essay-length biographical treatment of Grace Coolidge. It as well analyzes selections of her Teepee Neighbors as an attempt to generate sympathy among white readers for a colonized people, the Arapaho, and to offer a critique of Euro-American society from the standpoint of the communal Indian values she encountered at Wind River. Coolidge's project, however, is ultimately hampered by her own ethnocentrism and admitted inability to understand Indian cultures. [ABSTRACT FROM AUTHOR]

While data on human behavior in COVID-19 rich environments have been captured and publicly released, spatial components of such data are recorded in two-dimensions. Thus, the complete roles of the built and natural environment cannot be readily ascertained. This paper introduces a mechanism for the three-dimensional (3D) visualization of egress behaviors of individuals leaving a COVID-19 exposed healthcare facility in Spring 2020 in New York City. Behavioral data were extracted and projected onto a 3D aerial laser scanning point cloud of the surrounding area rendered with Potree, a readily available open-source Web Graphics Library (WebGL) point cloud viewer. The outcomes were 3D heatmap visualizations of the built environment that indicated the event locations of individuals exhibiting specific characteristics (e.g., men vs. women; public transit users vs. private vehicle users). These visualizations enabled interactive navigation through the space accessible through any modern web browser supporting WebGL. Visualizing egress behavior in this manner may highlight patterns indicative of correlations between the environment, human behavior, and transmissible diseases. Findings using such tools have the potential to identify high-exposure areas and surfaces such as doors, railings, and other physical features. Providing flexible visualization capabilities with 3D spatial context can enable analysts to quickly advise and communicate vital information across a broad range of use cases. This paper presents such an application to extract the public health information necessary to form localized responses to reduce COVID-19 infection and transmission rates in urban areas. [ABSTRACT FROM AUTHOR]

The construction and expansion of subway systems represents an important step towards better livability conditions in a rapidly urbanizing world. However, underground construction has not benefited from well-established ontologies of semantic and geometric representation, such as Building Information Modelling (which is used for standalone structures) and City Geography Markup Language (which is designed for continuous urban elements). To bridge that gap, this paper proposes a novel and highly flexible means to underpin a relevant ontology. The approach uses the ontology log, or olog, a model of knowledge representation based on Category Theory. In an olog, dependencies between objects are restricted to functional relationships (for every object there is a unique correspondence). This robust mathematical formulation allows for a more flexible, yet also informative and user-readable model of the studied entities. In this paper, the olog's usability is demonstrated through the ontological representation of common items in the fare-control areas of two New York City metro stations. Ologs are shown to capture similar underlying structures both across different stations and within the same station. Importantly, the olog allows for further generalization to incorporate pre-existing data, as well as being a transferable framework for conceptualizations of other metro systems. [ABSTRACT FROM AUTHOR]

The article focuses on opinion letters related to business law. It notes that such letters are often presented to clients. It states that the party on the other side of a transaction receives the opinion letter which contains the informed judgment on the transaction to both sides. It mentions the 2006 Legal Opinion Risk Seminar held in New York City and the 1989 Silverado Conference of the American Bar Association (ABA) Section of Business Law which focused on Legal Opinion Accord.

The paper examines how U.S.-American movies stage and convey intercultural encounters. Drawing from the case study of cinematic New York City, it tackles intercultural encounters and spaces emerging from interactions of protagonists that are staged as being 'culturally different'. Theoretical ideas on urban encounters, interculturality, and boundaries are intertwined. A comparative analysis 17 movies reveals three key dimensions of intercultural spaces: boundary drawing, boundary crossing, and boundary commuting. As polysemous staging strategies these provide insight into how movies display everyday intercultural encounters in an urban context. The paper concludes that New York City is imagined as a place in which intercultural encounters are consciously reflected as cultural coexistence—the cinematic city serves as canvas for a culturally separated society. This finding disenchants the medially widespread urban myth of New York City being a harmonious intercultural metropolis. [ABSTRACT FROM AUTHOR]

Presents a preliminary announcement of program schedules for the Eighty-Sixth Annual Meeting of the American Economic Association on December 27-30, 1973 in New York.