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Protests during the 2021 Climate Conference in Glasgow exemplified our dilemma. The establishment perpetuates old thinking, while young people demand a new approach to mitigate the impact of climate change. The authors agree with the young people, and as a solution we propose to replace the current fragmentary approach with a new holistic one. The passive house approach that was conceptualized by the University of Illinois and built in Canada in 1977 showed us that energy consumption can be reduced about half of that used in the traditional design. Seventeen years later, a European passive house was built in Darmstadt. In 2008, a demonstration house in Syracuse, NY, showed that integrated passive measures produced energy use by about half of the NY state code for 2004. At the same time, some advanced houses in the USA showed total energy use of about 70 kWh/(m2∙y). In 2008, at the first Building Enclosure Science and Technology Conference, two equally important objectives for 2030 were proposed by the Lawrence Berkeley National Laboratory: (1) a 90% reduction of energy use in new buildings and (2) 50% for the retrofitting of existing buildings, i.e., to the level achieved in the 1980s. The first objective has recently been achieved in small buildings while the large residential buildings remain on the level obtained in the 2000s. Yet, the retrofitting of existing buildings (the second objective) has been a dismal failure. This paper acknowledges progress in hydronic heating and cooling involving electric heat pumps and hybrid solar panels, building automatics used for operation of HVAC, and modification of air distribution systems that comes from experience with the SARS-CoV-2 pandemic. Furthermore, it highlights that to accelerate energy efficiency and carbon emission reductions, there must be broad public-private educational programs with demonstrations of a new generation of retrofitting. Economically and ecologically retrofitted buildings will create a new approach to real estate investment. [ABSTRACT FROM AUTHOR]

The article reviews the exhibition "Uche Okeke: Works on Paper, 1958-1993" at the Skoto Gallery in New York City on January 15-February 21, 2015.

The grid plays a prominent role in architecture, aiding in space organization and influencing all aspects of planning, ranging from urban design to intricate building details. This paper posits that the grid receives heightened emphasis in Brutalism, particularly in constructivist Brutalism, where materials and construction are intentionally exposed. A question arises regarding the grid's characteristics—despite its subtle appearance, the grid can sometimes be deceptive, ambiguous, and manipulative. The paper analyzes the merits and drawbacks of employing the grid in architecture, shedding light on its contributions to both structural and perceptual comprehensibility, as well as its role in increasing usefulness. To illustrate the application and perception of the grid, the paper examines two primary planning levels: urban planning and building design. The case studies focus on examples from New York City housing developments, specifically those constructed between the 1950s and the 1970s, and projects by architect I. M. Pei, which offer valuable insights into practical implementation. The paper concludes that while the grid can establish order, it may also engender an "uncanny" feeling. [ABSTRACT FROM AUTHOR]

Introduction: Symbol and digit substitution tasks are key instruments in the evaluation of attention, speed of processing, executive functioning, and cognitive dysfunction. The Match is an electronic (app-based) substitution task developed as part of the University of California San Francisco Brain Health Assessment that has been used to demonstrate cognitive impairment. We describe the paper-based oral symbol/number substitution task (Paper-Match), which was developed as part of the 5-Cog battery to assess for cognitive impairment including dementia and demonstrate it's use in an urban, multi-ethnic, socioeconomically disadvantaged primary care population in Bronx NY. Method: 109 participants, mean age 72.61 SD 6.42 and education 11.70 SD 3.82 years, 81% female, 48.6% Hispanic/Latino and 47.7% African American seen as part of 5-Cog. Participants (36.7% tested in Spanish) completed the Paper-Match (scored based on the number of correct matches in 90 seconds) and a comprehensive neuropsychological battery. Descriptive and correlational analysis were conducted. Results: Mean Paper-Match score was 38.24 SD 11.83 items correct (range 4–51). Paper-Match performance was highly correlated with performance on the Symbol Digit Modalities Test (r = .819, p < .001) and moderately correlated with performance on the Montreal Cognitive Assessment (MOCA; r = .604, p < .001). Years of education and primary language impacted performances. Conclusion: The results of this study provide the initial description and validation of the Paper-Match an oral symbol digit substitution task and its use in a diverse population of older primary care patients. Further research on the psychometric properties and construct validity of the Paper-Match are needed. [ABSTRACT FROM AUTHOR]

Harvesting usable and meaningful disaster-related, spatio-temporal data at a highly granular level poses major challenges in its cleaning and aggregation. This paper presents a strategy related to those challenges with respect to individual behavior near COVID-19 laden healthcare facilities. This is done to enable the visualizing of egress behavior data as interactive, three-dimensional (3D) scenes to investigate human behavior patterns regarding touch-based, disease transmission. Therefore, the aim is to demonstrate how this concept of 3D epidemiology may provide new mechanisms to understand the relative risk and exposure prevalence for data analysis. This paper demonstrates 3D enablement of disaster-related field data through use of first-hand observations of 1,936 individuals egressing New York City healthcare facilities during the onset of COVID-19 in the Spring of 2020. The observations capture egress behavior in terms of where people go (e.g. coffee shop, Subway) and how they physically interact with the surroundings (i.e. what they touch and how long they remain). This paper introduces a mechanism for automated extraction and 3D visualization of such data in Potree, an open-source Web Graphics Library (WebGL) point cloud viewer. Distinctive vertex shaders are used to distinguish specific destination selection and behavioral patterns (e.g. personal protective equipment usage). Two-dimensional heatmaps are paired with 3D scenes to demonstrate the potential of using 3D visualization of spatio-temporal patterns for visualizing disease transmission potential. [ABSTRACT FROM AUTHOR]

Background: In the U.S. there are significant racial and gender disparities in the uptake of pre-exposure prophylaxis (PrEP). Black Americans represented 14% of PrEP users in 2022, but accounted for 42% of new HIV diagnoses in 2021 and in the South, Black people represented 48% of new HIV diagnoses in 2021 but only 21% of PrEP users in 2022. Women who use drugs may be even less likely than women who do not use drugs have initiated PrEP. Moreover, women involved in community supervision programs (CSP) are less likely to initiate or use PrEP, More PrEP interventions that focus on Black women with recent history of drug use in CSPs are needed to reduce inequities in PrEP uptake. Methods: We conducted a secondary analysis from a randomized clinical trial with a sub-sample (n = 336) of the total (N = 352) participants from the parent study (E-WORTH), who tested HIV negative at baseline were considered PrEP-eligible. Black women were recruited from CSPs in New York City (NYC), with recent substance use. Participants were randomized to either E-WORTH (n = 172) an HIV testing plus, receive a 5-session, culturally-tailored, group-based HIV prevention intervention, versus an HIV testing control group (n = 180). The 5 sessions included an introduction to PrEP and access. This paper reports outcomes on improved awareness of PrEP, willingness to use PrEP, and PrEP uptake over the 12-month follow-up period. HIV outcomes are reported in a previous paper. Results: Compared to control participants, participants in this study assigned to E-WORTH had significantly greater odds of being aware of PrEP as a biomedical HIV prevention strategy (OR = 3.25, 95% CI = 1.64–6.46, p = 0.001), and indicated a greater willingness to use PrEP as an HIV prevention method (b = 0.19, 95% CI = 0.06–0.32, p = 0.004) over the entire 12-month follow-up period. Conclusions: These findings underscore the effectiveness of a culturally-tailored intervention for Black women in CSP settings in increasing awareness, and intention to initiate PrEP. Low uptake of PrEP in both arms highlight the need for providing more robust PrEP-on-demand strategies that are integrated into other services such as substance abuse treatment. Trial Registration: ClinicalTrials.gov Identifier: NCT02391233. [ABSTRACT FROM AUTHOR]

Given that Ecuadorians are one of the largest groups of Hispanics living in New York, they have become a tight community that they now call little Ecuador. Although Ecuadorians living in the diaspora in NYC come from different parts of the country (mostly from the Andean region), they share the same cultural practices they performed in Ecuador that give them the sense of being in their country without bearing the instability and turmoil their country experiences. This shows how the group has fostered a sense of a multifaceted, multidimensional simultaneity between the host country and the motherland. The goal of this paper is to analyze the strategies Ecuadorian migrants use to validate their language and cultural practices to negotiate their identity as a group. Data for this paper come from ethnographic observations, semi-spontaneous conversations, oral interviews with members of the group, along with pictures taken while walking the community and participating in some of their events. Our study reveals that participants hold varying perceptions regarding their linguistic and cultural practices. However, it is noteworthy that they recognize these practices as a manifestation of Ecuadorianness, signifying a sense of solidarity among community members. [ABSTRACT FROM AUTHOR]

The traditional air-assisted side-deep fertilization device has some problems, such as inaccurate control system parameters and poor precision in variable fertilization. It seriously affects the application and popularization of the device. Aiming at the above problems, this paper wanted to realize the precise fertilizer discharge control of an air-assisted side-deep fertilization device. This paper designs an electronically controlled fertilization system based on a PID controller from the past. The system model was constructed in MATLAB, and the mathematical model and transfer function model of a stepper motor, the mathematical model of fertilizer discharge, and the stepper motor rotational speed were established too. In order to improve the accuracy of precise fertilizer discharge control system parameters, the system parameters were optimized based on the particle swarm optimization algorithm and the control system tuner toolbox. We had established a validation test platform to test the performance of a precise fertilizer discharge control system. In the actual experiment, the maximum stability coefficient of variation was 0.91% at the target fertilizer discharge mass level of 350 g/min, and the maximum error of fertilizer discharge was 4.14% at 550 g/min of the target fertilizer discharge mass level. By analyzing the test results of the precise fertilizer discharge control system, the new precise fertilizer discharge control system had good fertilizer discharge stability and could also meet the technical specification for quality evaluation of fertilization machinery (NY/T 1003-2006). This research can improve the fertilizer discharge accuracy of the air-assisted side-deep fertilization control system. [ABSTRACT FROM AUTHOR]

In the mid-twentieth century, growing North American textile and ready-to-wear industries vigorously appropriated Native American aesthetics to cultivate a commercial and design identity apart from Europe. Most studies of the circulation of Indigenous idioms in these industries focus on Southwestern or South Pacific regionalisms, and scholarship on studio and commercial fabric and fashion design from the Northwest Coast in the twentieth century is limited. This paper contributes by raising Indigenous and non-Indigenous use of Northwest Coast design forms during the politically turbulent 1940s–1960s and analyzing the impact of this aesthetic vocabulary within broader North American textiles and fashion. Throughout, I engage with the approaches of critical fashion theory and multiple modernisms, considering the frictions of property and power relations within settler-colonial states, then and now. Drawing from study of objects, periodicals, and archival materials as well as first-person perspectives, I contextualize these representations within entangled art, museum, and design worlds in the Northwest Coast, New York City, and the Southwest. My examination illustrates that Northwest Coast artists and art ideas asserted a peripheral but locatable role in mid-century textiles and fashion, facilitating the development of today's robust Indigenous fashion network on the Northwest Coast and its cultural politics. [ABSTRACT FROM AUTHOR]

The 2022 ASMC, our 33rd, returned to Saratoga Springs, NY as an in-person conference after 2 years as a virtual conference. While we are all grateful for the digital world’s enhancements that allowed this conference to be held remotely, attendees were happy to return to an in-person event where networking is much easier. [ABSTRACT FROM AUTHOR]

Open Educational Resources (OER) have continued to gain traction in higher education, assisting with ever-rising costs of publisher textbooks and supporting pedagogical innovation. Starting in 2017, NY state legislature has allocated funds annually to be split between its two public university systems to support and incentivize the adoption of OER. The author's institution, an included public college, has secured portions of this funding each year. This paper will focus on the initial five years of the statefunded OER initiative at the City University of New York (CUNY) College of Staten Island, with reflections on the successes of the program, the overall process of the annual grant cycle on campus, challenges that arose in the burgeoning OER program, and suggestions for future considerations. The main aim of this paper is to highlight the impact of state funding on the establishment of a library-facilitated OER initiative, to serve as a example for other institutions who are seeking to build an OER program. [ABSTRACT FROM AUTHOR]

Hierarchical Temporal Memory (HTM) is an unsupervised algorithm in machine learning. It models several fundamental neocortical computational principles. Spatial Pooler (SP) is one of the main components of the HTM, which continuously encodes streams of binary input from various layers and regions into sparse distributed representations. In this paper, the goal is to evaluate the sparsification in the SP algorithm from the perspective of information theory by the information bottleneck (IB), Cramer-Rao lower bound, and Fisher information matrix. This paper makes two main contributions. First, we introduce a new upper bound for the standard information bottleneck relation, which we refer to as modified-IB in this paper. This measure is used to evaluate the performance of the SP algorithm in different sparsity levels and various amounts of noise. The MNIST, Fashion-MNIST and NYC-Taxi datasets were fed to the SP algorithm separately. The SP algorithm with learning was found to be resistant to noise. Adding up to 40% noise to the input resulted in no discernible change in the output. Using the probabilistic mapping method and Hidden Markov Model, the sparse SP output representation was reconstructed in the input space. In the modified-IB relation, it is numerically calculated that a lower noise level and a higher sparsity level in the SP algorithm lead to a more effective reconstruction and SP with 2% sparsity produces the best results. Our second contribution is to prove mathematically that more sparsity leads to better performance of the SP algorithm. The data distribution was considered the Cauchy distribution, and the Cramer--Rao lower bound was analyzed to estimate SP's output at different sparsity levels. [ABSTRACT FROM AUTHOR]

Lateral roots, including adventitious roots, are the main component of rapeseed roots with support, absorb, and synthesis functions and their morphological parameters directly affecting the plant's aboveground growth and yield. Root biomass, as a material base for lateral root growth, can be used as a link between plant phenotypes and their physiological processes, as well as to enhance root 3D growth model mechanisms and accuracy. To quantify the relationships between lateral root morphological indices and the corresponding organ biomass for rapeseed, we used two cultivars, NY 22 (conventional) and NZ 1818 (hybrid), and conducted cultivar and fertilizing cylindrical tube experiments during the 2016–2019, with two fertilizer levels, no fertilizer, and 180 kg N ha−1 fertilizer. The lateral root biomass and morphological parameters were determined during the whole growth period. The biomass‐based lateral root morphological parameter models were developed by analyzing the quantitative relationship between the lateral root morphological indices and their corresponding biomass, and the descriptive models were verified with independent experimental data. The results showed that the correlation (r) of simulated and observed values for the lateral root morphological parameters are all greater than 0.9 with significant levels at p < 0.001. The absolute values of the average absolute difference (da) of simulated and observed values for the lateral root length (LLR), lateral root average diameter (ADLR), lateral root surface area (SALR), and lateral root volume (VLR) are −30.408 cm, −0.003 mm, 12.902 cm2, and 0.039 cm3, respectively. The RMSE values are 175.183 cm, 0.010 mm, 59.710 cm2, and 1.513 cm3, respectively. The ratio of da to the average observed values (dap) for the LLR and VLR are all less than 5%, and the ADLR and SALR are all <6%. The models developed in this paper have good performance and reliability for predicting lateral root morphological parameters of rapeseed. The study provides a mechanistic method for linking the rapeseed growth model with the morphological model using corresponding organic biomass and laying a good foundation for establishing a 3D morphological model for rapeseed root system based on biomass. [ABSTRACT FROM AUTHOR]

This research is concerned with individuals' symbolic interactions with the Charging Bull statue. We chose this statue because it is an extremely popular tourist attraction and the most visited nonhuman statue in New York City. However, there is no research devoted to understanding how visitors interact with the statue. To fill this gap in the literature, we examine people's interactions as a unique way of communicating with the Charging Bull statue in New York City through a photo analysis approach. Using the general framework of symbolic interactionism, the paper investigates poses, gestures, and more generally interactions of individuals near or with the statue to gain insights into the impact of the Charging Bull beyond a mere visual representation. The findings reveal various forms of interaction, including souvenir photography, active participation, unexpected interactions, and public-made symbolism. This study of these interactions contributes to the literature on collective memory and the study of statues. Additionally, this research highlights the inventiveness of the dynamic relationship between individuals and statues as symbols in the urban environment. [ABSTRACT FROM AUTHOR]

This paper provides a mathematical optimization strategy for optimal municipal solid waste management in the context of the COVID-19 epidemic. This strategy integrates two approaches: optimization and machine learning models. First, the optimization model determines the optimal supply chain for the municipal waste management system. Then, machine learning prediction models estimate the required parameters over time, which helps generate future projections for the proposed strategy. The optimization model was coded in the General Algebraic Modeling System, while the prediction model was coded in the Python programming environment. A case study of New York City was addressed to evaluate the proposed strategy, which includes extensive socioeconomic data sets to train the machine learning model. We found the predicted waste collection over time based on the socioeconomic data. The results show trade-offs between the economic (profit) and environmental (waste sent to landfill) objectives for future scenarios, which can be helpful for possible pandemic scenarios in the following years. [ABSTRACT FROM AUTHOR]

Drones are becoming indispensable in emergency search and rescue (SAR), particularly in intricate urban areas where rapid and accurate response is crucial. This study addresses the pressing need for enhancing drone navigation in such complex, dynamic urban environments, where obstacles like building layouts and varying wind conditions create unique challenges. Particularly, the need for adapting drone autonomous navigation in correspondence with dynamic wind conditions in urban settings is emphasized because it is important for drones to avoid loss of control or crashes during SAR. This paper introduces a pioneering method integrating multiobjective reinforcement learning (MORL) with a convolutional autoencoder to train autonomous drones in comprehending and reacting to aerodynamic features in urban SAR. MORL enables the drone to optimize multiple goals, whereas the convolutional autoencoder generates synthetic wind simulations with a substantially lower computation cost compared to traditional computational fluid dynamics (CFD) simulations. A unique data transfer structure is also proposed, which fosters a seamless integration of perception and decision-making between machine learning (ML) and reinforcement learning (RL) components. This approach uses imagery data, specific to building layouts, allowing the drone to autonomously formulate policies, prioritize navigation decisions, optimize paths, and mitigate the impact of wind, all while negating the necessity for conventional aerodynamic force sensors. The method was validated with a model of New York City, offering substantial implications for enhancing automation algorithms in urban SAR. This innovation enables the possibility of more efficient, precise, and timely drone SAR operations within intricate urban landscapes. [ABSTRACT FROM AUTHOR]

[Objective] Tiger nut is a cash crop in southern Xinjiang and its production relies on irrigation. This paper presents the results of an experimental study on the effect of irrigation amounts on physiological traits, yield, and water use efficiency of different varieties of tiger nuts. [Method] The experiment studied two varieties: the Henan Round Grain (HY) and the Inner Mongolia Round Grain (NY), each irrigated by 18 mm (W1), 27 mm (W2), 36 mm (W3), and 45 mm (W4) of water, respectively. In each treatment, we measured the changes in soil water storage, plant height, tiller numbers, photosynthetic traits, yield, water consumption, and water use efficiency of the plants at different growing stages. [Result] Soil water storage and water consumption of both varieties increased with irrigation amount. Compared to W1, W4 increased average soil water storage and water consumption of the plants by 24.84% and 60.57% for the HY, and 18.46% and 55.61% for the NY, respectively. The plant height, tiller numbers, net photosynthesis (Pn), stomatal conductance (Gs), transpiration rate (Tr) and the yield of HY increased with irrigation amount (P<0.05), peaking in W2 with increases of 24.60%, 15.11%, 28.14%, 34.86%, 40.49% and 13.92% compared to W1. Intercellular carbon content (Ci) decreased with increasing irrigation amount. With the increase in irrigation amount, the plant height, tiller numbers, Pn, Gs, Tr, and the yield of NY all increased first followed by a decline; their associated values in W2 were 26.07%, 20.26%, 19.69%, 38.38%, 44.92% and 20.83% higher than those in W1. On average, Ci decreased with irrigation amount, being lowest in W2. Water use efficiency and irrigation water use efficiency of both varieties decreased with irrigation amount. Principal component analysis showed the net photosynthetic rate and water use efficiency can be used as indicators for variety selection. [Conclusion] The optimal irrigation amounts for the varieties HY and NY are 45 mm and 27 mm respectively, which can promote healthy growth, improve yields, and enhance water use efficiency of the plants. [ABSTRACT FROM AUTHOR]

More than 30 years after its premiere, Seinfeld continues its run as a seminally popular television show. On October 1, 2021, five‐year streaming rights to the show were purchased by Netflix for $500 million. Set in New York City, where rent control laws have a long history, several episodes of the show consider the trials of apartment living, including shortages, tastes for discrimination by sellers, bribery, search costs, and quality degradation. Seinfeld also illustrates the informal process through which rent‐controlled apartments are advertised (e.g., less advertising under rent control shortage). This paper argues that popular media can be used as an effective pedagogical tool in learning. This paper analyzes four episodes of Seinfeld to help students identify and differentiate the very real costs of rent control. The paper also guides students to appreciate the difficulty in crafting a policy that is free of unintended consequences. [ABSTRACT FROM AUTHOR]

Researchers have addressed uncertainty in multicriteria decision making from the perspective of the performance values of the alternatives, weighting of the evaluation criteria, and the evaluation methods. Still, they are yet to address the uncertainty caused by the normalization approach. In this paper, we show that different normalization methods, namely sum normalization, min–max normalization, vector normalization, and maximization normalization, can result in different rankings of the alternatives while the performance values and weights are unchanged. We applied the grey system theory to address the problem of uncertainty in this study from three aspects: alternative performance values measurement, criteria weighting, and decision matrix/table normalization within a period. The grey hybrid normalization method is proposed as the main contribution in this paper. Then, we present the rankings of 48 cities under uncertainty to decide the location of a branch office of a Chinese electric vehicle manufacturer as a practical example based on the grey entropy weighting method and grey relational analysis with positive and negative references (GRA-PNR) within the period from the year 2019 to 2021. The research results using this approach ranked New York City the best, with a stock market capitalization of economy validity as the top contributor in terms of weighting. Finally, we used simple additive weighting with grey value and the technique for order of preference by similarity to ideal solution with grey value methods to validate the study results. [ABSTRACT FROM AUTHOR]

In this Article, Jim Hawkins examines in depth the role of expression in the early labor movement. Focusing on the use of the press, publications, petitions, pamphlets and strikes in the labor movement in New York City from 1800 to 1860, the author argues that although the courts failed to protect labor expression, expression nonetheless was an essential weapon in the early labor movement's arsenal. Between 1833 and 1836, the labor movement won three major trials through jury verdicts by appealing directly to the Constitution—an early and successful form of popular constitutionalism. These victories demonstrate the labor movement's ability to influence constitutional culture to broaden the scope of free speech protection for workers and suggest that the early labor movement 's conception of free speech may have paved the way for subsequent movements. [ABSTRACT FROM AUTHOR]

Background: Healthy NYC is an innovative survey panel created by the New York City (NYC) Department of Health and Mental Hygiene (DOHMH) that offers a cost-effective mechanism for collecting priority and timely health information. Between November 2020 and June 2021, invitations for six different surveys were sent to Healthy NYC panelists by postal mail, email, and text messages. Panelists had the option to complete surveys online or via paper survey. Methods: We analyzed whether panelists varied by sociodemographic characteristics based on the contact mode they provided and the type of invitation that led to their response using logistic regression models. Poisson regression models were used to determine whether the number of invitations received before participating in a survey was associated with sociodemographic characteristics. Results: Younger age and higher education were positively associated with providing an email or text contact. Furthermore, age, race, and income were significant predictors for invitation modes that led to a survey response. Black panelists had 72% greater odds (OR 1.72 95% CI: 1.11–2.68) of responding to a mail invite and 33% lesser odds (OR 0.67, 95% CI: 0.54–0.83) of responding to an email invite compared with White panelists. Additionally, in five of the six surveys, more than half of the respondents completed surveys after two invites. Email invitations garnered the highest participation rates. Conclusions: We recommend using targeted invitation modes as an additional strategy to improve participation in panels. For lower-income panelists who do not provide an email address, it may be reasonable to offer additional response options that do not require internet access. Our study's findings provide insight into how panels can tailor outreach to panelists, especially among underrepresented groups, in the most economical and efficient ways. [ABSTRACT FROM AUTHOR]

Human movements in urban areas are essential to understand human–environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose a novel sensor-based approach for spatiotemporal event detection based on the Discrete Empirical Interpolation Method. Specifically, we first identify the key locations, defined as "sensors", which have the strongest correlation with the whole dataset. We then simulate a regular uneventful scenario with the observation data points from those key locations. By comparing the simulated and observation scenarios, events are extracted both spatially and temporally. We apply this method in New York City with taxi trip record data. Results show that this method is effective in detecting when and where events occur. [ABSTRACT FROM AUTHOR]

This paper explores the ways in which Mexican immigrants experience, narrate, and describe stress and the extent to which it impacts their efforts at engaging in physical activity using a biocitizenship framework. Data were derived from a mixed-method study among Mexicans living in New York City recruited from a large Catholic church. The qualitative sample of 25 participated in quantitative and qualitative components of the study and as such we include some of these quantitative indicators as descriptors. Our main qualitative findings reveal that study participants experience stress and time constraint as factors that contribute to the waning of their physical and mental well-being. As such, time constraints for many of our participants were among the factors that contributed to high perceived levels of stress. They attributed this to their difficulty maintaining a physically active lifestyle due to factors like the fast-paced lifestyle in New York, working long hours, and not having enough time to exercise, though some important differences in narratives were noted across gender. Findings have implications for interventions aimed at improving the health of immigrants in general and Mexican immigrants in New York City specifically. [ABSTRACT FROM AUTHOR]

Ridesharing effectively tackles urban mobility challenges by providing a service comparable to private vehicles while minimising resource usage. Our research primarily concentrates on dynamic ridesharing, which conventionally involves connecting drivers with passengers in need of transportation. The process of one-to-one matching presents a complex challenge, particularly when addressing it on a large scale, as the substantial number of potential matches make the attainment of a global optimum a challenging endeavour. This paper aims to address the absence of an optimal approach for dynamic ridesharing by refraining from the conventional heuristic-based methods commonly used to achieve timely solutions in large-scale ride-matching. Instead, we propose a novel approach that provides snapshot-optimal solutions for various forms of one-to-one matching while ensuring they are generated within an acceptable timeframe for service providers. Additionally, we introduce and solve a new variant in which the system itself provides the vehicles. The efficacy of our methodology is substantiated through experiments carried out with real-world data extracted from the openly available New York City taxicab dataset. [ABSTRACT FROM AUTHOR]

This paper presents methods to proactively choose individuals to test for infection during a pandemic such as COVID-19, characterized by high contagion and presence of asymptomatic carriers. We show that by a smart integration of exploration/exploitation balancing, contact tracing, and location-based sampling, one can effectively mitigate the disease spread and significantly reduce the infection rates and death rates. Under different vaccination policies and under different compliance levels to quarantine order and/or testing requests, our smart testing algorithm can bring down the death rate significantly by 20% to 30%, as well as the percentage of infected drops by approximately 30%. The load on hospitals at peak times, a crucial aspect of managing COVID-19, drops, by 50% when implementing smart testing. We also show how procedural fairness can be incorporated into our method and present results that show that this can be done without hurting the effectiveness of the mitigation that can be achieved. This paper presents methods to choose individuals to test for infection during a pandemic such as COVID-19, characterized by high contagion and presence of asymptomatic carriers. The smart-testing ideas presented here are motivated by active learning and multi-armed bandit techniques in machine learning. Our active sampling method works in conjunction with quarantine policies, can handle different objectives, and is dynamic and adaptive in the sense that it continually adapts to changes in real-time data. The bandit algorithm uses contact tracing, location-based sampling and random sampling in order to select specific individuals to test. Using a data-driven agent-based model simulating New York City we show that the algorithm samples individuals to test in a manner that rapidly traces infected individuals. Experiments also suggest that smart-testing can significantly reduce the death rates as compared with current methods, with or without vaccination. While smart testing strategies can help mitigate disease spread, there could be unintended consequences with fairness or bias when deployed in real-world settings. To this end we show how procedural fairness can be incorporated into our method and present results that show that this can be done without hurting the effectiveness of the mitigation that can be achieved. History: Ahmed Abbasi, Senior Editor; Maytal Saar-Tsechansky, Associate Editor. Funding: W. Yahav is supported by the Jeremy Coller Foundation and the Henry Crown Institute of Business Research in Israel. Supplemental Material: The e-companion is available at https://doi.org/10.1287/isre.2023.1215. [ABSTRACT FROM AUTHOR]

The article discusses a selection of 18 early 19th-century ephemera from Germany, Austria, and Switzerland held in the Print Room of The Metropolitan Museum of Art in New York City. The article divides the ephemera into three groups including: printed papers used in conjunction with other objects; useful paper objects bound to wear out; and ephemera saved only temporarily for sentimental reasons. Several highlights of ephemera in the Print Room include Francesco Rosselli's engraved circles, Stefano della Bella's etched playing cards, and 18th-century invitations and tickets.

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]

With the popularity of location-based social networks such as Weibo and Twitter, there are many records of points of interest (POIs) showing when and where people have visited certain locations. From these records, next POI recommendation suggests the next POI that a target user might want to visit based on their check-in history and current spatio-temporal context. Current next POI recommendation methods mainly apply different deep learning models to capture user preferences by learning the nonlinear relations between POIs and user preference and pay little attention to mining or using the information that explicitly reflects user preference. In contrast, this paper proposes to utilize data that explicitly reflect user preference and include these data in a deep learning-based process to better capture user preference. Based on the self-attention network, this paper utilizes the attributes of the month of the check-ins and the categories of check-ins during this time, which indicate the periodicity of the user's work and life and can reflect the habits of users. Moreover, considering that distance has a significant impact on a user's decision of whether to visit a POI, we used a filter to remove candidate POIs that were more than a certain distance away when recommending the next POIs. We use check-in data from New York City (NYC) and Tokyo (TKY) as datasets, and experiments show that these improvements improve the recommended performance of the next POI. Compared with the state-of-the-art methods, the proposed method improved the recall rate by 7.32% on average. [ABSTRACT FROM AUTHOR]

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]