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Objectives: This paper aimed to identify the technology frontiers of artificial intelligence-assisted pathology based on patent citation network. Methods: Patents related to artificial intelligence-assisted pathology were searched and collected from the Derwent Innovation Index (DII), which were imported into Derwent Data Analyzer (DDA, Clarivate Derwent, New York, NY, USA) for authority control, and imported into the freely available computer program Ucinet 6 for drawing the patent citation network. The patent citation network according to the citation relationship could describe the technology development context in the field of artificial intelligence-assisted pathology. The patent citations were extracted from the collected patent data, selected highly cited patents to form a co-occurrence matrix, and built a patent citation network based on the co-occurrence matrix in each period. Text clustering is an unsupervised learning method, an important method in text mining, where similar documents are grouped into clusters. The similarity between documents are determined by calculating the distance between them, and the two documents with the closest distance are combined. The method of text clustering was used to identify the technology frontiers based on the patent citation network, which was according to co-word analysis of the title and abstract of the patents in this field. Results: 1704 patents were obtained in the field of artificial intelligence-assisted pathology, which had been currently undergoing three stages, namely the budding period (1992–2000), the development period (2001–2015), and the rapid growth period (2016–2021). There were two technology frontiers in the budding period (1992–2000), namely systems and methods for image data processing in computerized tomography (CT), and immunohistochemistry (IHC), five technology frontiers in the development period (2001–2015), namely spectral analysis methods of biomacromolecules, pathological information system, diagnostic biomarkers, molecular pathology diagnosis, and pathological diagnosis antibody, and six technology frontiers in the rapid growth period (2016–2021), namely digital pathology (DP), deep learning (DL) algorithms—convolutional neural networks (CNN), disease prediction models, computational pathology, pathological image analysis method, and intelligent pathological system. Conclusions: Artificial intelligence-assisted pathology was currently in a rapid development period, and computational pathology, DL and other technologies in this period all involved the study of algorithms. Future research hotspots in this field would focus on algorithm improvement and intelligent diagnosis in order to realize the precise diagnosis. The results of this study presented an overview of the characteristics of research status and development trends in the field of artificial intelligence-assisted pathology, which could help readers broaden innovative ideas and discover new technological opportunities, and also served as important indicators for government policymaking. [ABSTRACT FROM AUTHOR]

Forest aboveground biomass (AGB) provides valuable information about the carbon cycle, carbon sink monitoring, and understanding of climate change factors. Remote sensing data coupled with machine learning models have been increasingly used for forest AGB estimation over local and regional extents. Landsat series provide a 50-year data archive, which is a valuable source for historical mapping over large areas. As such, this paper proposed a machine learning-based workflow for historical AGB estimation and its change analysis from 2001 to 2019 for the New York State's forests using Landsat historical imagery, airborne LiDAR, and forest plot data. As the object-based image analysis (OBIA) is able to incorporate spectral, contextual, and textural features into the regression model, the proposed method utilizes an OBIA approach and a random forest (RF) regression model implemented on the Google Earth Engine (GEE) cloud computing platform. Results demonstrated that there is a considerable decrease of 983.79 × 106 Mg/ha in the AGB of deciduous forests from 2001 to 2006, followed by an increase of 618.28 × 106 Mg/ha from 2006 to 2011, continued with an increase of 229.12 × 106 Mg/ha of deciduous forests from 2011–2016. Finally, the results demonstrated a slight change in AGB from 2016 to 2019. The transferability of the proposed framework provides a practical solution for monitoring forests in other states or even on a national scale. [ABSTRACT FROM AUTHOR]

In Bourlard and Kamp (Biol Cybern 59(4):291–294, 1998), it was theoretically proven that autoencoders (AE) with single hidden layer (previously called "auto-associative multilayer perceptrons") were, in the best case, implementing singular value decomposition (SVD) Golub and Reinsch (Linear algebra, Singular value decomposition and least squares solutions, pp 134–151. Springer, 1971), equivalent to principal component analysis (PCA) Hotelling (Educ Psychol 24(6/7):417–441, 1993); Jolliffe (Principal component analysis, springer series in statistics, 2nd edn. Springer, New York). That is, AE are able to derive the eigenvalues that represent the amount of variance covered by each component even with the presence of the nonlinear function (sigmoid-like, or any other nonlinear functions) present on their hidden units. Today, with the renewed interest in "deep neural networks" (DNN), multiple types of (deep) AE are being investigated as an alternative to manifold learning Cayton (Univ California San Diego Tech Rep 12(1–17):1, 2005) for conducting nonlinear feature extraction or fusion, each with its own specific (expected) properties. Many of those AE are currently being developed as powerful, nonlinear encoder–decoder models, or used to generate reduced and discriminant feature sets that are more amenable to different modeling and classification tasks. In this paper, we start by recalling and further clarifying the main conclusions of Bourlard and Kamp (Biol Cybern 59(4):291–294, 1998), supporting them by extensive empirical evidences, which were not possible to be provided previously (in 1988), due to the dataset and processing limitations. Upon full understanding of the underlying mechanisms, we show that it remains hard (although feasible) to go beyond the state-of-the-art PCA/SVD techniques for auto-association. Finally, we present a brief overview on different autoencoder models that are mainly in use today and discuss their rationale, relations and application areas. [ABSTRACT FROM AUTHOR]

This paper explores the relevance of social capital in shaping Irish immigrants' reconstructions of their attachment to New York City (NYC) as place. Using extracts from Irish immigrants' previously unpublished oral histories, I make the case for situational capital, a multi-faceted and dynamic place-based resource which connects people in situ by virtue of their literal and metaphorical positionality. The coalescence of individual and collective memories, including childhood memories, underpinned the network of social relationships which fuelled interviewees' quest to recreate and reimagine a sense of 'home' both in NYC and Ireland. The resultant situational capital created by these relationships fostered a reflexive and sustained attachment to place which served to advance the cumulative economic, cultural, political and social prosperity of Irish men and women individually and collectively over time and space. Situational capital was also instrumental in advancing opportunities for Irish men and women and altering the physical characteristics of neighbourhoods. It shaped the genius loci of NYC as reconstructed by those interviewed pivoting around the fluid and ambiguous notion of real and imagined 'home.' [ABSTRACT FROM AUTHOR]

The coronavirus pandemic highlighted the deep-rooted links between poor housing and poor health, particularly for working class communities of colour, for whom the right to the city is systemically undermined by unaffordable, precarious and sub-standard housing. This paper examines these issues against the background of a grassroots movement against evictions in New York during 2021. It describes and discusses the organisation, tactics and strategies of that movement as it attempted to challenge the dominance and norms of the real estate industry. It suggests that the pandemic engendered a radical shift in the demands of tenant and housing justice organisations, which led to New York being virtually eviction free for 22 months. While this success partly arises from the particular circumstances of New York, it is argued that there are lessons to be learned for housing campaigns elsewhere. However, questions are raised about the extent to which 'professionalised activism' represents a sustainable model and the capacity for local mobiisations to influence national political forces at a time of unprecedented volatility in an age of crisis capitalism. [ABSTRACT FROM AUTHOR]

• Propose a duopoly evolutionary game model for the dynamic ride-hailing market. • Capture bounded rationality, strategic learning, and dynamic competition between platforms. • Identify the existence of stationary points and derive simplified stability conditions. • Establish two extended models to capture the service aggregator and mixed electric/fuel fleets. • Provide a fresh perspective for exploring dynamic ride-hailing competition and market evolution. The platform competition in a real-world ride-hailing market is complex and dynamic. Existing research mainly relies on static competitive equilibrium, lacking an understanding of the dynamic evolution process of platform competition. This paper develops a generic duopoly evolutionary game model to capture dynamic decision adjustments and the evolution of market conditions. Bounded rationality and strategic learning are integrated into the modeling to dissect the interaction and competition between two platforms. The existence of stationary points where the system states remain unchanged over time is identified, and simplified stability conditions are derived. A pure strategy pair is found stable when constituting a strict Nash equilibrium and corresponding to positive payoffs. We establish two extended models to capture the nascent service aggregator and mixed electric/fuel fleets and compare them with the basic model. The model is calibrated employing the ride-hailing data of New York and is applicable for analyzing the market evolution under different states. The impacts of potential demand drop, aggregated services, and mixed fleets on platform decision and driver-passenger choice evolution are unveiled. It is found that the platforms possess self-recovery capability when facing a deteriorated external environment. The decision-making of the small platform exhibits a more substantial inertia and volatility since the large platform's decision can easily influence the market supply and demand. In the initial stage, the service aggregator slightly harms the large platform, but in the long run, it benefits both platforms. Besides, both platforms reduce prices while inflating commission ratios under mixed fleets. This study provides a fresh perspective for exploring the real-world dynamic ride-hailing competition and market evolution. [ABSTRACT FROM AUTHOR]

The U.S. opioid overdose crisis persists. Outpatient behavioral health services (BHS) are essential components of a comprehensive response to opioid use disorder and overdose fatalities. The Helping to End Addiction Long-Term® (HEALing) Communities Study developed the Communities That HEAL (CTH) intervention to reduce opioid overdose deaths in 67 communities in Kentucky, Ohio, New York, and Massachusetts through the implementation of evidence-based practices (EBPs), including BHS. This paper compares the rate of individuals receiving outpatient BHS in Wave 1 intervention communities (n = 34) to waitlisted Wave 2 communities (n = 33). Medicaid data included individuals ≥18 years of age receiving any of five BHS categories: intensive outpatient, outpatient, case management, peer support, and case management or peer support. Negative binomial regression models estimated the rate of receiving each BHS for Wave 1 and Wave 2. Effect modification analyses evaluated changes in the effect of the CTH intervention between Wave 1 and Wave 2 by research site, rurality, age, sex, and race/ethnicity. No significant differences were detected between intervention and waitlisted communities in the rate of individuals receiving any of the five BHS categories. None of the interaction effects used to test the effect modification were significant. Several factors should be considered when interpreting results—no significant intervention effects were observed through Medicaid claims data, the best available data source but limited in terms of capturing individuals reached by the intervention. Also, the 12-month evaluation window may have been too brief to see improved outcomes considering the time required to stand-up BHS. Clinical Trials.gov http://www.clinicaltrials.gov : Identifier: NCT04111939 • Evidence-based practices to reduce opioid overdose deaths implemented in 67 communities. • Outpatient behavioral health services are key element of opioid addiction treatment. • Similar receipt of behavioral services in control and intervention communities. • More research needed to test the impact of comprehensive, community-driven interventions. [ABSTRACT FROM AUTHOR]

In this paper, we study Gromov hyperbolicity and related parameters, that represent how close (locally) a metric space is to a tree from a metric point of view. The study of Gromov hyperbolicity for geodesic metric spaces can be reduced to the study of graph hyperbolicity. The main contribution of this paper is a new characterization of the hyperbolicity of graphs, via a new parameter which we call rooted insize. This characterization has algorithmic implications in the field of large-scale network analysis. A sharp estimate of graph hyperbolicity is useful, e.g., in embedding an undirected graph into hyperbolic space with minimum distortion (Verbeek and Suri, in Symposium on Computational Geometry, ACM, New York, 2014). The hyperbolicity of a graph can be computed in polynomial-time, however it is unlikely that it can be done in subcubic time. This makes this parameter difficult to compute or to approximate on large graphs. Using our new characterization of graph hyperbolicity, we provide a simple factor 8 approximation algorithm (with an additive constant 1) for computing the hyperbolicity of an n-vertex graph G = (V , E) in optimal time O (n 2) (assuming that the input is the distance matrix of the graph). This algorithm leads to constant factor approximations of other graph-parameters related to hyperbolicity (thinness, slimness, and insize). We also present the first efficient algorithms for exact computation of these parameters. All of our algorithms can be used to approximate the hyperbolicity of a geodesic metric space. We also show that a similar characterization of hyperbolicity holds for all geodesic metric spaces endowed with a geodesic spanning tree. Along the way, we prove that any complete geodesic metric space (X, d) has such a geodesic spanning tree. [ABSTRACT FROM AUTHOR]

In a classical survey [Mathematics in Industrial Problems, Springer-Verlag, New York, 1989, Chapter 16.2], Friedman proposed an open problem on the collision of two incompressible jets emerging from two axially symmetric nozzles. In this paper, we are concerned with the mathematical theory on this collision problem, and establish the well-posedness theory on hydrodynamic impinging outgoing jets issuing from two coaxial axially symmetric nozzles. More precisely, we show that for any given mass fluxes in two nozzles, respectively, there exists an incompressible, inviscid impinging outgoing jet with contact discontinuity, which issues from two given semi-infinitely long axially symmetric nozzles and extends to infinity. Moreover, the constant pressure free stream surfaces of the impinging jet initiate smoothly from the mouths of the two nozzles and shrink to some asymptotic conical surface. There exists a smooth surface separating the two incompressible fluids and the contact discontinuity occurs on the surface. Furthermore, we show that there is no stagnation point in the flow field and its closure, except one point on the symmetric axis. Some asymptotic behavior of the impinging jet in upstream and downstream, geometric properties of the free stream surfaces are also obtained. The main results in this paper solve the open problem on the collision of two incompressible axially symmetric jets in [Friedman's book]. [ABSTRACT FROM AUTHOR]

The South Street Seaport, a historic district located at the southern tip of Manhattan, has been the subject of a massive redevelopment scheme. While local actors have opposed the new vision of the developer, the latter, in partnership with the New York Economic Development Corporation, has imposed its own narrative for the district's development so far. This paper looks at the development of a historic district being managed by private parties. Unfolding past events, it critically investigates the district's space production and examines how the different actors have framed the values and narratives over the place. It shows how partnerships have become unbalanced over the years and how it finally led to reactions and the rearrangement of the partnership. The paper aims at contributing to the current debate on the public–private partnership by discussing their implications and bringing in the example of an alternative setting for more open collaboration and negotiation between developers and local actors. [ABSTRACT FROM AUTHOR]

The mutual development of airport groups and regions is gradually going global with the economic globalization. There is a contradiction between Beijing-Tianjin-Hebei (Jing-Jin-Ji) Airport Group and regional development, which leads to the unbalanced development of aviation enterprises in the region. Therefore, it is of major theoretical and practical significance to analyze the coordinated development relationship between Jing-Jin-Ji Airport Group and the region. This paper selects representative index system, establishes the adaptability evaluation model of airport group and regional development, and quantitatively analyzes the adaptability level of Jing-Jin-Ji Airport Group and radiation area. Taking New York Airport Group as a reference, the synergy degree between Jing-Jin-Ji Airport Group and the region is evaluated by the synergy evaluation model. Analyze the reasons for the development of New York Airport Group, and put forward the measures for the coordinated development of Jing-Jin-Ji Airport Group and the region in the future. The results show that the synergy index (SD) of Jing-Jin-Ji Airport Group is 0.5381, which is lower than that of New York Airport Group (0.7507), and Jing-Jin-Ji Airport Group is barely synergetic. It is necessary to optimize airspace, allocate flight resources, speed up the development of airport economy, and optimize the structure of airport groups. Jing-Jin-Ji Airport Group will be accelerated to enter a high-quality collaborative stage from the aspects of system and resource integration and government leadership. [ABSTRACT FROM AUTHOR]

The recent history of urban public libraries reveals significant changes in the way librarians, city officials, and patrons understood the value of public institutions. Branch libraries in the South Bronx during New York City's financial crisis of the 1970s reveal both the dramatic and seemingly minute developments through which the city shifted toward neoliberalism. This article draws on archives of the New York Public Library and the papers of Local 1930 (The New York Public Library Guild, AFSCME District Council 37). [ABSTRACT FROM AUTHOR]

Urban mobility services face the challenge of planning their operations efficiently while complying with user preferences. In this paper, we introduce a new mathematical model called a choice-driven dial-a-ride problem (CD-DARP) which is a generalization of the dynamic DARP where passenger behavior is integrated in the operational planning using choice models and assortment optimization. We look at two types of mobility services, private and shared. Our problem extends the dynamic DARP by (i) changing its objective function to profit maximization, where both cost and revenue are variables, and (ii) incorporating assortment optimization with routing decisions in a dynamic setting. We propose a pricing scheme based on a choice model designed to offer service alternatives at the time a customer makes a request. We introduce a tailored algorithm to efficiently solve the dynamic CD-DARP. Computational results indicate that our proposed approach outperforms dynamic DARP in terms of reducing routing costs and improving the number of customers served. • A new framework is introduced for DDARP incorporating customer choice. • The routing cost is reduced while satisfying customers' requests. • CD-DARP provides more flexibility for the operator to efficiently manage the fleet. • We evaluate the proposed model on synthetic as well as New York taxi data. • Flexible time windows helps improving the service level. [ABSTRACT FROM AUTHOR]

For station-based bike-sharing systems, the balance between user demand and bike allocation is critical for the operation. As a basic operational index, the short-term prediction of bike numbers (flow) plays an important role in demand forecasting and rebalancing resources of bike-sharing networks. Many different methods have been proposed for bike forecast in recent years, and the deep learning (DL)-based models have dominated this area because of their competitive performance. However, there still exist challenges in such approaches including: (i) how to appropriately select the training input for the DL model, and (ii) how to effectively utilize both the temporal and spatial features in the data for prediction. In particular, the arbitrary input may limit the model optimization, and the separate consideration of temporal and spatial features could change the original data representation. This paper uses a simple autocorrelation function to select the best input candidates and develops a three-dimensional (3 D) residual neural network to learn spatiotemporal features simultaneously. The proposed DL model is trained and validated using two separate bike-sharing datasets from New York and Suzhou cities. The learned features by two-dimensional (2 D) and 3 D CNN kernels under different input methods are compared. Results show that 3 D CNN outperforms other models and that the proposed input selection method yields better learning results for both datasets. The proposed methods help with a comprehensive DL model workflow and better forecasting accuracy. [ABSTRACT FROM AUTHOR]

The paper is concerned with a doubly infinite vortex array introduced by Weihs (Nature 241:290–291, 1973; in: Wu, Brokaw, Brennen (eds) Swimming and flying in nature, Vol. 2, Plenum Press, New York, 1975) as a model problem employed in order to understand the hydrodynamic and energetic benefits of fish schooling. Weihs considered two different 'modes' of swimming: one where the fish swim in anti-phase and one where they swim in phase. The stability properties for the vortex array corresponding to the anti-phase mode of swimming are well understood; but this is not the case for the in-phase mode. A normal mode analysis of perturbations applied to the corresponding vortex array is carried out. The array is found to be always unstable when subjected to general perturbations, but stable solutions exist if all consecutive vortex streets are subjected to the same perturbation. [ABSTRACT FROM AUTHOR]

Research on the prison visitation context has recently grown, yet little is known about the overall composition of who visits. This paper describes visit groups using latent class analysis (LCA) separately for women and men incarcerated two or more years in New York State. In this context where policies support frequent in-person visits, many maintain large, diverse groups of external connections. Although theory suggests that some groups may be more beneficial than others (e.g., prosocial influence or social support), visitor classes did not predict recidivism, but recidivism was higher for those with no/few visits. Policies that restrict visitor types or amounts may diminish valuable external social ties that can be maintained and offer ongoing support in more visit-positive regimes. [ABSTRACT FROM AUTHOR]

Empirical studies have shown that traffic in communication networks exhibits long-range dependence. Cumulative network traffic is often thought to be well modelled by a fractional Brownian motion (fBm). FBm approximations of queueing systems have also been well justified by theoretical results, and most of this achievements are based on one Hurst parameter. However, just as pointed out by Konstantopoulos and Lin (in: Glasserman, Sigman, and Yao (eds) Stochastic Networks: Stability and Rare Events. Lecture Notes in Statistics, Springer-Verlag, New York, 1996), various Hurst parameters may be more appropriate. At the same time, sticky Brownian motions on the half-line have many applications in queueing theory, and could be obtained as heavy traffic limits of queueing systems with exceptional service (arrive) mechanisms. In this paper, reflected operator fractional Brownian motion, sticky operator fractional Brownian motion, and a d-node tandem fluid queue with long-range dependent inputs and sticky boundaries are constructed. Moreover, in heavy traffic environment, it is shown that the scaled buffer-content process of the d-node tandem queue converges weakly to a sticky operator Brownian motion. [ABSTRACT FROM AUTHOR]

The present paper aims to do a parallel between the city of New York and Sao Paulo, which are cities that, in a comparative model, have many differences when it comes to the application of the concepts of smart cities and the objectives of the 2030 Agenda. Speaking in the smart city refers to the idea of safety, modern means of transport with reduction or neutralization in the emission of greenhouse gases, greater locomotive technology, economy, social cohesion, use of renewable energy methods, and greater contact of human beings with nature, as exposed in the IESE Cities in Motion Index 2020. The article will present the notion of a Smart City and will assess whether the cities of New York and Sao Paulo fulfill the requirements to fit into the notion of smart cities. In the end, the text will demonstrate the importance of behavioral regulation, with an emphasis on nudges, for the implementation of smart cities. [ABSTRACT FROM AUTHOR]

Medical costs are often skewed to the right, heteroscedastic, and having a sophisticated relation with covariates. Moreover, medical cost datasets are always massive, such as in the New York Statewide Planning and Research Cooperative System Expenditure Study. Different observations can depend on each other as the spatial distribution of diseases induces complex correlation among patients coming from nearby communities. Therefore, it is not enough if only focus on the mean function regression models with low-dimensional covariates, small sample size and identically independent observations. In this paper, we propose a new quantile regression model to analyze medical costs. A network term is introduced to account for the dependence among different observations. We also consider variable selection for massive datasets. An adaptive lasso penalized variable selection method is applied in a parallel manner, the resulting estimators are combined through minimizing an extra penalized loss function. Simulation studies are conducted to illustrate the performance of the estimation method. We apply our method to the analysis of the New York State's Statewide Planning and Research Cooperative System, 2013. [ABSTRACT FROM AUTHOR]

While enrollment in Catholic schools is rising in the global south, it is declining in many Western countries. Providing a quality and holistic education experience remains essential in both developed and developing countries, especially for disadvantaged groups. But in addition, in developed countries, trade-offs may have to be confronted to stem the decline in enrollment that affects the financial sustainability of schools. Building on a presentation made at the closing plenary of OIEC's World Congress in New York, this paper focuses on the United States where enrollment in Catholic schools has been dropping for more than 50 years. In the absence of state support for Catholic schools and in a context of rising operating costs and therefore tuition, the decline in enrollment is due in part to a lack of affordability of schools given high out-of-pocket costs paid by parents. But other factors related to perceptions about Catholic schools also play a role. To stem the decline in enrollment, market research can help, including to assess how favorably Catholic and other types of schools are perceived in the population. The paper relies on data collected for the National Catholic Education Association to compare favorability ratings by type of schools and assess factors associated with these perceptions. [ABSTRACT FROM AUTHOR]

Building on a presentation made at the closing plenary of OIEC's World Congress in New York, this paper considers two trends affecting Catholic education globally and their potential implications for university research and programs in support of K12 schools. The first trend is the shift of enrollment in K12 Catholic education towards the global south and especially Africa in terms of the sheer number of students enrolled in schools. The second trend relates to the deepening learning crisis in K12 education affecting much of the developing world, and again especially Africa. These two trends have implications for university research and programs in support of K12 Catholic schools on the continent. The paper argues that apart from discussions related to Catholic identity, which are of course important, more attention should be placed by universities, including in the West, on the related but distinct issue of how to improve basic learning for students enrolled in K12 Catholic schools in the global south. [ABSTRACT FROM AUTHOR]

This paper deals with a two-phase fluid free boundary problem in a slot-film cooling. We give two well-posedness results on the existence and uniqueness of the incompressible inviscid two-phase fluid with a jump relation on a free interface. The problem formulates the oblique injection of an incompressible ideal fluid from a slot into a free stream. From the mathematical point of view, this work is motivated by the pioneer work [Arch. Ration. Mech. Anal., 94 (1986), pp. 335--361] by A. Friedman, in which some well-posedness results are obtained in some special case. Furthermore, A. Friedman proposed an open problem in [Mathematics in Industrial Problems, IMA Vol. Math. Appl. 16, Springer, New York, 1988] on the existence and uniqueness of the injection flow problem for the more general case. The main results in this paper solve the open problem and establish the well-posedness results on the physical problem. [ABSTRACT FROM AUTHOR]

Home health aides and home care agencies, who operate in a high work stress environment under normal conditions, were placed under extraordinary demands during the COVID-19 pandemic. In this paper, we examine the unfolding effort at one agency in New York City to offer phone-based support calls to aides. We used a qualitative, single case study design involving semi-structured interviews with call staff and agency leaders (n = 9) and analysis of one year of thematic notes from the calls. We found that the calls resulted in multidirectional communication between agency staff and aides, an increased sense of empathy among staff, and a greater integration of aides into the agency's overall infrastructure. We explore how these calls might contribute to aide retention, worker voice, and mental health. We note the facilitators and barriers to implementing this type of job-based support to help other agencies that may be considering similar models. [ABSTRACT FROM AUTHOR]

Objective: The Buffalo, New York region is one of the leading refugee resettlement areas in the country, settling 94% of African refugees in 2014. However, little is known about their health beliefs, particularly regarding sexual health and HIV. This study's purpose was to describe HIV attitudes and beliefs in a sample of African refugee women, a population that is increasingly present in the country, yet seldom represented in the literature. Design: A convenience sample of 101 African refugee women were recruited via snowball technique in Buffalo, New York. Data were collected from July 2017–July 2018, via paper-pen survey, and were analyzed using descriptive statistics. Results: Participants had low levels of education, but high HIV screening rates. Inconsistencies between knowledge of HIV acquisition and behaviors relating to HIV positive individuals may indicate HIV stigma among the population. Conclusion: Novel strategies geared towards educational levels and societal norms to educate African refugee women about HIV are urgently needed. [ABSTRACT FROM AUTHOR]

In this article, I analyze the emergence of New York City's infrastructure of homeless shelters dialectically, relationally, and historically. The members of Boogie Down Productions met in an incipient New York City homeless shelter in the mid-1980s. Their relationship and music is a window into a critical political consciousness of men living in homeless shelters because the artists gave expression to an emergent structure of feeling of resistance taking hold during intense changes to New York's political economy and its institutions. The paper first analyzes homeless policy and infrastructural change through a reading of archival sources and government reports and documents. The second section understands oral histories conducted with men living in a New York City homeless shelter as blues geographies—insurgent, critical explanations of these institutional spaces. Shelter residents actively challenge the material conditions, relations, and values that produce homeless shelters as essential instruments of the carceral state. I argue that they activate this resistance to the naturalization of shelters, and themselves as homeless, by narrating carceral spaces as abolitionist spaces. [ABSTRACT FROM AUTHOR]

We evaluated caretaker knowledge of and attitudes toward the levonorgestrel-containing intrauterine device (L-IUD) as a treatment option for adolescents and young adults with heavy menstrual bleeding. A survey assessed demographic characteristics, menstrual history, perception of the L-IUD, and knowledge of the indications, risks, and benefits of the L-IUD. Participant recruitment occurred in the offices of a pediatric gynecologist, pediatric hematologist, and adolescent medicine physician in a hospital-based practice in New York. English-speaking caretakers of patients with a chief concern of heavy menstrual bleeding (<21 years old) were invited to participate. Electronic and paper surveys were administered prior to seeing the physician. The primary outcome was participant willingness to allow their daughter to use the L-IUD for heavy menstrual bleeding. Additional outcomes were explored by calculating a mean knowledge score and conducting a descriptive analysis of the perception questions. Forty surveys were included. Seventy percent of participants said they would allow their daughter to use birth control pills for heavy menstrual bleeding, whereas only 10% said the same of the L-IUD. The mean knowledge score was 73.3% (±15.7). Sixty-five percent of participants expressed the need for additional information on the L-IUD. Caretaker acceptance of the L-IUD as treatment for their daughter with heavy menstrual bleeding is limited. Although baseline knowledge was high, many indicated needing additional information. Because heavy menstrual bleeding can negatively impact quality of life, potential caretaker bias must be addressed to ensure full access to this highly effective treatment option. [ABSTRACT FROM AUTHOR]

Take-home naloxone (THN) is provided to non-medically trained people to reverse potential opioid overdoses. There is an increasing range of effective intramuscular (IM) and intranasal (IN) naloxone devices and this paper explores the types preferred by people who use opioids, using consumer behaviour literature to interpret the findings. Data derive from two unconnected qualitative studies involving audio-recorded semi-structured interviews. Study 1 was conducted in the United States (n = 21 users of non-medical/illicit opioids). Study 2 was conducted in Australia (n = 42 users of non-medical/illicit or prescribed opioids). Most participants preferred IN naloxone. Preferences were based on the ease, speed, safety and comfort of each device and underpinned by accounts of overdose revivals as being very rushed and frightening situations. Preferences related to complex interactions between the naloxone device ('product'); the knowledge, skills, experience and attitudes of the lay responder ('consumer'), and when, where and how naloxone was to be used ('usage situation'). THN programs should offer choice of device when possible and nasal naloxone if resources permit. Asking people which devices they prefer and why and treating them as valued consumers of naloxone products can generate insights that improve future naloxone technology and increase THN uptake and usage. [ABSTRACT FROM AUTHOR]

We know relatively little about the conditions that encourage people to jump into the political fray as policy entrepreneurs, advocates who devote substantial time, energy, and resources to campaigning for a policy goal. This paper aims to fill that gap by investigating the catalysts of policy entrepreneurship in municipalities across the State of New York, where between 2008 and 2012, hundreds of local jurisdictions passed measures opposing or supporting high-volume hydraulic fracturing (fracking). These local policy actions were often enthusiastically encouraged and, in some cases, vociferously opposed, by enterprising advocates. I propose a threat-centered theory of policy entrepreneurship, emphasizing the role of loss aversion in pushing actors toward advocacy. The empirical analysis shows that oppositional advocacy within a polity draws would-be policy entrepreneurs into battle. [ABSTRACT FROM AUTHOR]

The mortality risk factors for coronavirus disease (COVID‐19) must be early predicted, especially for severe cases, to provide intensive care before they develop to critically ill immediately. This paper aims to develop an optimized convolution neural network (CNN) for predicting mortality risk factors for COVID‐19 patients. The proposed model supports two types of input data clinical variables and the computed tomography (CT) scans. The features are extracted from the optimized CNN phase and then applied to the classification phase. The CNN model's hyperparameters were optimized using a proposed genetic‐based adaptive momentum estimation (GB‐ADAM) algorithm. The GB‐ADAM algorithm employs the genetic algorithm (GA) to optimize Adam optimizer's configuration parameters, consequently improving the classification accuracy. The model is validated using three recent cohorts from New York, Mexico, and Wuhan, consisting of 3055, 7497,504 patients, respectively. The results indicated that the most significant mortality risk factors are: CD 8+ T Lymphocyte (Count), D‐dimer greater than 1 Ug/ml, high values of lactate dehydrogenase (LDH), C‐reactive protein (CRP), hypertension, and diabetes. Early identification of these factors would help the clinicians in providing immediate care. The results also show that the most frequent COVID‐19 signs in CT scans included ground‐glass opacity (GGO), followed by crazy‐paving pattern, consolidations, and the number of lobes. Moreover, the experimental results show encouraging performance for the proposed model compared with different predicting models. [ABSTRACT FROM AUTHOR]

The job shop scheduling problem (JSSP) is a popular NP-hard scheduling problem that simulates the scheduling problems of different real-world applications in fields such as manufacturing, engineering, and planning. In general, many optimization-based scheduling algorithms are guaranteed to provide an optimal solution for small instances of the JSSP, but do not perform well with large instances of the JSSP. The hybrid cuckoo search and simulated annealing (CSA) algorithm is a new hybrid optimization algorithm for solving continuous optimization problems. It incorporates the optimization operators of the simulated annealing algorithm into the cuckoo search algorithm. In this paper, we present discrete CSA (DCSA) which is a discrete variation of CSA for solving the JSSP. DCSA incorporates four modifications into CSA. First, it uses the opposition-based learning method in the initialization step to produce diverse candidate solutions. Second, it uses a combination of the variable neighborhood search (VNS) and Lévy-flight methods for better exploration of the search space. Third, it uses the elite opposition-based learning method before the abandon step of CSA to jump out of local optima. Finally, it uses the smallest position value with the JSSP to convert the continuous candidate solutions generated by CSA into discrete ones. DCSA was examined and compared to six popular optimization-based scheduling algorithms (DABC (Yin et al. in Sci Res Essays 6:2578–2596, 2011), PSO-VNS (Tasgetiren et al. in Int J Oper Res 3:120–135, 2006), DCS (Quaarab et al., in: Yang (ed) Recent advances in swarm intelligence and evolutionary computation, Springer, New York, 2015), GWO (Jiang and Zhang in IEEE Access 6:26231–26240, 2018), DWPA (Wang et al. in 2019 5th International Conference on Control, Automation and Robotics ICCAR 2019 581–585, 2019) and DGA (Kalshetty et al. in J Sci Res 64:310–321, 2020) using 34 JSSP instances from the OR-Library: Fisher and Thompson (3 instances), and Lawrence (31 instances). The experimental and statistical results indicate that DCSA converges faster to the Best-Known Solution for 29 instances out of the 34 tested JSSP instances and requires less computational time for the 34 tested instances than the computational times of the other algorithms. [ABSTRACT FROM AUTHOR]

Low rates of survey response are a problem that survey organizations increasingly experience across the world. Understanding local socio-demographic reasons for low response, and projecting future response, can inform targeted outreach and messaging to communities. Using the US Census as a case study, we study mail response behavior both cross-sectionally and over time. The cross-sectional part of this study (2010) helps inform the selection of explanatory variables for a two-panel difference model (2000–2010). In turn, the two-panel difference model offers an in-depth understanding of which demographic indicators shape response across time. Increases in response between 2000 and 2010 were found to be associated with growth in the elderly and in the Dominican populations, while growth in blacks, renters, and those with low educational attainment were associated with decreases in response. Coefficients from the two-panel difference model are then applied to demographic changes from 2008–2012 to 2013–2017, to project response rates for the most recent period. While much of our findings are in line with prior survey research, we demonstrate the importance of projecting response behavior using a local perspective, as national-level results do not always apply to smaller jurisdictions. In a diverse country such as the United States, a hyper-diverse city such as New York often carves its own path. To our knowledge, this is the first paper that connects shifts in socio-demographic neighborhood characteristics with changes in response rates. As racial and ethnic diversity increases in cities across western societies, our methodology allows jurisdictions to project response rates using shifts in socio-demographic neighborhood characteristics that are tied to self-response. Such a tailored approach can be replicated across different kinds of surveys, countries, and time points, which will allow for the identification of local factors that drive changes in survey response and help establish a precisely customized outreach plan. [ABSTRACT FROM AUTHOR]

This gem of an article by Dr. Kate Marcus was tucked away for decades, comfortably settled in a drawer at the Library-Bookstore of the C. G. Jung Institute of Los Angeles, readily available as a reprint for those who knew to ask. While preparing for a recent presentation, I tracked it down to refresh my memory of it. Marcus's article is the text of a lecture she presented in May 1956 for the Analytical Psychology Club of Los Angeles. In 1971, her paper was published in The Well-Tended Tree: Essays into the Spirit of Our Times, a Festschrift edited by Hilde Kirsch in honor of James Kirsch on his 70th birthday. As we would expect, Dr. Marcus's article reflects the time period in which it was written. Despite some outdated notions about women and men, it provides interesting and useful interpretations of the male stranger in women's dreams—dreams that are still dreamt today, more than 60 years after her paper was written. Marcus saw into and beyond her era, identifying and celebrating the prospective elements such dreams can offer. Psychological Perspectives wanted to make the article available to an audience wider than those who frequent our institute library-bookstore, and we extend our special thanks to Janet Casewell, and the C. G. Jung Foundation of New York, for allowing us to reprint this wonderful article. We trust Dr. Marcus would be pleased to learn her work is still read and remains of value decades after her death. –Pamela Freundl Kirst, PhD [ABSTRACT FROM AUTHOR]

A new hybrid model combining the kernel functions along with the random vector functional link neural network (RVFLN) is proposed in this paper for an effective solar power prediction. The conventional RVFLN is known for its fast learning speed, simple architecture and good generalization capabilities and allows direct connection between input and output nodes along with nonlinear enhancement nodes with random weights. However, the bottleneck of selecting the number of hidden enhancement nodes and mapping functions is still a challenging problem. To overcome these deficiencies of the conventional RVFLN, kernel functions are used for both the direct links and the hidden nodes to provide better stability, generalization and regression accuracy. Instead of using a single kernel for the enhancement nodes, this paper proposes an optimal kernel function that comprises a linear combination of weighted local kernel and a global kernel to improve the prediction accuracy of the solar power generation. This optimal kernel will be known as multi-kernel RVFLN (MK-RVFLN), and its parameters are optimized using an efficient metaheuristic evaporation-based water cycle (EVWCA-MKRVFLN) to provide accurate prediction of solar power. To validate its superior prediction accuracy, two solar power plants of 25 and 100 MW capacity in the states of New York and California are considered for 5-min- and 60-min-ahead prediction in the months of January, April, July and October. The result analysis shows that the MK-RVFLN algorithm attains better performance than many other techniques. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to describe the results of an online program evaluation survey conducted in the USA in 2018 which was designed to understand how members of an enhanced multidisciplinary team (E-MDT) use the expertise of a forensic accountant (FA) in suspected cases of elder financial exploitation. Design/methodology/approach: This paper analyzes responses to an online survey from 54 E-MDT members. Narrative responses to open-ended questions were analyzed by using cross-case thematic analysis. Data from demographic questions and those with nominal response options were analyzed using descriptive statistics. Findings: Overwhelmingly, the E-MDT members described how useful the FA's expertise and subsequent detailed reports are in helping determine whether financial exploitation is taking place and providing information needed to continue an investigation and pursue criminal charges. Practical implications: The increasing longevity and sheer number of older adults present ongoing challenges in the fight to address financial exploitation. Findings suggest that FAs working with E-MDTs can help identify signs, collect evidence and help investigate cases of suspected financial abuse of older adults. The development of training programs focused on educating accountants to fill a need in a growing area of forensic accounting may be needed. Originality/value: This paper adds to the growing evidence of multidisciplinary teams as an effective model for investigating cases of financial elder exploitation by focusing specifically on the expertise of an FA. [ABSTRACT FROM AUTHOR]

• NYSolarCast is an open-source solar forecasting system configurable for any region. • NYSolarCast predicts gridded GHI and both utility-scale and distributed PV power. • NYSolarCast integrates NWP models, machine learning, and real-time weather data. • NYSolarCast was validated for 1 year of 0–6-h GHI and power forecasts in New York. • NYSolarCast GHI forecasts performed comparably to a commercial reference forecast. Solar energy generation capacity will need to be greatly increased to meet aggressive clean energy targets by New York State (NYS), which are 70% renewable energy (RE) generation by 2030, and 100% by 2040. Because solar energy is a variable, weather-driven resource, accurate forecasts of solar energy generation both in nowcast (intra-day) and day-ahead time horizons are necessary for electric utilities and independent system operators, as they maintain grid stability and maximize RE use. Meeting this need for NYS, a gridded, open-source solar power forecasting system called NYSolarCast was developed (https://github.com/ncar/NYSolarCast%5fdelivery). NYSolarCast makes 15-min resolution predictions of global horizontal irradiance (GHI) on a 3-km grid covering all of NYS, which are then used to estimate solar power generation both for select utility-scale PV plants (15-min resolution) and for zone-aggregated distributed PV (1-h resolution). The statewide GHI forecasts are made by applying the StatCast statistical forecasting model, which is trained on over two years of GHI observations from pyranometers at all 126 NYS Mesonet stations and gridded numerical weather prediction forecasts from both the Weather Research and Forecasting model tuned for solar applications (WRF-Solar®) and NOAA's operational High-Resolution Rapid Refresh (HRRR) model. Forecasts are made at each NYS Mesonet site and then blended outward into the rest of the grid. This paper gives an overview of NYSolarCast performance for intra-day (0–6-h) GHI and power forecasts during a one-year period. [ABSTRACT FROM AUTHOR]

The timely transportation of goods to customers is an essential component of economic activities. However, heavy-duty diesel trucks used for goods delivery significantly contribute to greenhouse gas (GHG) emissions within many large metropolitan areas, including Los Angeles, New York, and San Francisco. To reduce GHG emissions by facilitating freight electrification, this paper proposes Joint Routing and Charging (JRC) scheduling for electric trucks. The objective of the associated optimization problem is to minimize the cost of transportation, charging, and tardiness. A large number of possible combinations of road segments as well as a large number of combinations of charging decisions and charging durations leads to a combinatorial explosion in the possible decisions electric trucks can make. The resulting mixed-integer linear programming (MILP) problem is thus extremely challenging because of the combinatorial complexity even in the deterministic case. Therefore, a Surrogate Level-Based Lagrangian Relaxation (SLBLR) method is employed to decompose the overall problem into significantly less complex truck subproblems. In the coordination aspect, each truck subproblem is solved independently of other subproblems based on the values of Lagrangian multipliers. In addition to serving as a means of guiding and coordinating trucks, multipliers can also serve as a basis for transparent and explanatory decision-making by trucks. Testing results demonstrate that even small instances cannot be solved using the off-the-shelf solver CPLEX after several days of solving. The SLBLR method, on the other hand, can obtain near-optimal solutions within a few minutes for small cases, and within 30 min for large ones. Furthermore, it has been demonstrated that as battery capacity increases, the total cost decreases significantly; moreover, as the charging power increases, the number of trucks required decreases as well. • Present a formulation of a joint heavy-duty vehicle fleet routing & charging problem. • Use surrogate level-based Lagrangian relaxation approach to solve the problem. • The proposed method obtains near-optimal solutions for realistic testing cases. [ABSTRACT FROM AUTHOR]

Neighborhood socioeconomic status (SES) and greenspace can affect respiratory health. However, it is unclear whether effects of neighborhood SES and greenspace on respiratory health still exist regardless of temperature variations. This paper conducted a two-stage, age-stratified case time-series study. The first goal is to examine the associations between two temperature metrics (daily mean temperature [DMT] and diurnal temperature range [DTR]) and respiratory emergency department (ED) visits among four age groups in New York City. The second goal is to evaluate whether neighborhood SES and greenspace would be determinants of respiratory ED visits independent from temperature varying factors. A distributed lag nonlinear model was applied on ED data from 135 zip codes (October 2016 - February 2020). Our first-stage analysis indicated that older adults aged 65+ had higher risk of ED visits (RR=2.78, 95% eCI: 2.41, 3.22; with 7 days of lag) on days with low DMT (-10 °C), followed by adults aged 18-64 (RR=2.48, 95% eCI: 2.32, 2.65), children and youth aged 5-17 (RR=1.38, 95% eCI: 1.24, 1.53), and young children aged 0-4 (RR=1.04, 95% eCI: 0.96, 1.13). However, no excess respiratory ED visits were observed on days with high DMT (30 °C). Higher DTR was associated with higher risk, with children and youth more susceptible when DTR was high (DTR 20 °C; RR=5.70, 95% eCI: 3.42, 9.49; with 7 days of lag). The second-stage analysis indicated neighborhood SES and greenspace had significant associations with respiratory ED visits regardless of temperature variations. Specifically, Higher income and greenspace exposure were negatively associated with ED visits among all age groups. Neighborhood SES and greenspace could affect respiratory morbidity regardless of weather conditions. Daily temperature variations accelerated the short-term risk among population subgroups under different weather conditions (e.g., higher risk of days with low DMT among older adults, higher risk of days with high DTR among children and youth aged 5-17), which could create co-effects with neighborhood SES and greenspace on respiratory health. • Respiratory ED visit was significantly associated with both DMT and DTR. • Older adults more vulnerable to low DMT (RR=2.78, 95% eCI: 2.41, 3.22). • Youth aged 5-17 more vulnerable to high DTR (RR=5.70, 95% eCI: 3.42, 9.49). • SES and greenspace associated with respiratory ED visit regardless of temperature. • Intracity examination of impacts of DMT and DTR on health allows local actions. [ABSTRACT FROM AUTHOR]

Cities, like the people that live in them, are subject to the attention economy. Familiar social media platforms aggregate users' tastes and reconstitute them as advertising and curated content. In this paper, I show that American cities are induced by state governments to adopt the attention-grabbing tactics of social media influencers. This is particularly evident in cultural planning as it relates to economic development. While this is a global phenomenon, I have chosen to focus on the Capital Region of New York State, a region approximately 240 kilometres north of New York City. I have chosen the Capital Region because New York's nine-year-old system of Regional Economic Development Councils highlights the competitive and often capricious environment that urbanists increasingly find themselves in. Through an analysis of planning documents, reported events and secondary sources I demonstrate how small to medium cities in Upstate New York are competing to be the purveyors of authentic urban living. I then discuss how authenticity and social media interact to create desires for consumption of identity performance. Finally, I compare the city authentic branding regime with the 'Bilbao effect' and show how the former can summon the effects of the latter without a 'star' architect. [ABSTRACT FROM AUTHOR]

In our recent work [X. Blanc and S. Wolf, Asymptot. Anal., 126 (2021), pp. 129-155], we have studied the homogenization of the Poisson equation in a class of non-periodically perforated domains. In this paper, we examine the case of the Stokes system. We consider a porous medium in which the characteristic distance between two holes, denoted by\varepsilon, is proportional to the characteristic size of the holes. It is well known (see [G. Allaire, Asymptot. Anal., 2 (1989), pp. 203-222; E. Sanchez-Palencia, in Non-Homogeneous Media and Vibration Theory, Springer, New York, 1980, pp. 129-157; L. Tartar, in Non-Homogeneous Media and Vibration Theory, Springer, New York, 1980, Appendix]) that, when the holes are periodically distributed in space, the velocity converges to a limit given by Darcy's law when the size of the holes tends to zero. We generalize these results to the setting of [X. Blanc and S. Wolf, Asymptot. Anal., 126 (2021), pp. 129-155]. The nonperiodic domains are defined as a local perturbation of a periodic distribution of holes. We obtain classical results of the homogenization theory in perforated domains (existence of correctors and regularity estimates uniform in\varepsilon) and we prove H²-convergence estimates for particular force fields. [ABSTRACT FROM AUTHOR]

Some Details regarding the Layout and Construction of the Romanian House and the Organization of its Activities during the New York World’s Fair (1939–1940). Documents from the National Archives and the Archives of the Ministry of Foreign Affairs: 1938–1939. The present text is part of a more complex research on Romania’s participation in the New York World’s Fair (1939–1940). The main objective of this research is to reconstruct the representation of Romania’s national identity at a certain point in time (1939), classifying it as one element in a series of this kind. We will also concentrate on how this representation was perceived by the public opinion of the 1930s. As such, it is not only research on cultural history and public diplomacy (external propaganda, as it was called at the time), but also on bilateral Romanian-American relations (economy, politics etc.). Last but not least, it also represents a study in imagology. This paper, the first of a series, aimed at reconstructing some of the events related to the preparations led by the officials in Bucharest charged with the country’s participation in the New York World’s Fair, for the construction of the pavilion known as the Romanian House, designed by the architect Octav Doicescu and erected for this occasion. I have brought forth information referring to the evolution of the works done at this pavilion and the difficulties encountered throughout the process, such as: changes made to the architectural design, the relation between the entrepreneurs and workers, the transportation of construction materials from overseas, the exhibitions, the negotiations for appointment of the restaurant’s manager etc. All this took place between May 1938 and April 1939. Our sources are to be found at the National Historical Archives (SaintGeorge’s fund and Ministry for Commerce and Industry fund) and at the Archives of the Ministry of Foreign Affairs (Washington fund). To those sources we have added published documents from different public libraries and on-line archives (http://www.cooperativag.ro/, http://octavdoicescu.blogspot.com/ etc.) and details brought forth by specialised literature from 1997–2018 (articles /studies on the subject by Daniel Bogdea, Nicolae Dascălu (Nicolae Ureche), Narcisa Mitu, Raluca Preotu, Zoltan Rostas, Ileana Stanca-Desa, ClaudiuAlexandru Vitanos, Laurențiu Vlad etc.). [ABSTRACT FROM AUTHOR]

The origin of happiness arouses people's curiosity for a long time. Recent research introduces a utility theory for measuring subjective happiness in a social context. The past recent monetary conditions influence the present subjective happiness through two distinct channels: interpersonal comparison and self-adaptation. In this paper, we develop this theory to analyze behavioral patterns. Together with prospect theory's gain-loss utility function, we exploit the theory in predicting psychological phenomena of craving. We explore the relationships between happiness and earnings. Under certain conditions, a high payoff disappoints you immediately and even leads to continuous disappointment across periods. We extend the explanations of the scenarios of New York cabdrivers' labor-supply decisions. The effect of social comparisons may trigger workers' behaviors of quit-working, which deepen related understandings of the literature. [ABSTRACT FROM AUTHOR]

This work presents an analysis of Artificial Neural Network (ANN) based forecasting models for vehicular traffic flow. The forecasting was performed for three periods of time: 1 week, 1 month and 1 year. The vehicular traffic flow data analysed were collected from Interstate 87, a highway located within the U.S. state of New York. Temporal and climate information, such as weekday, time of day, precipitation, visibility and temperature, were provided to the ANNs. Two different architectures were implemented to forecast vehicular traffic flow: Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM). The performance was evaluated using the Root Mean Square Error (RMSE) and comparing the predicted flow with the real data in the evaluated period. The MLP resulted in RMSE of 113.96, 185.98 and 201.19, and MAP of 9.56%, 15.49% and 16.95% for a forecasting interval of 1 week, 1 month and 1 year, respectively. Similarly, the LSTM network resulted in RMSE of 122.20, 179.55 and 203.63 and MAPE of 14.66%, 17.89% and 24.10% for the same time periods. Additionally, the two developed ANNs were evaluated to perform a forecasting vehicular traffic flow for another highway, the Interstate 88. The results from the two ANNs are similar, the MLP network resulted in MAPE of 17.15%, 25.65% and 19.76% for a forecasting interval of 1 week, 1 month and 1 year, respectively. On the other hand, the LSTM network presented RMSE of 19.14%, 31.87% and 22.97%. The results obtained come close to the similar work results when considered shorter prediction periods. The results for longer prediction time could not be compared to the literature due to the lack of work in this area, being a novelty of the current work. Moreover, the models implemented in this paper were precise and stable and can be used as strategy information to help road and cities planning. In addition, results have shown that the model can be replicated for other roads in the same region or either from other states or countries. [ABSTRACT FROM AUTHOR]

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI's application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act swiftly and thereby enhance containment of outbreaks. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of a fair redistribution of resources among agents in an exchange economy á la Shitovitz (Econometrica 41:467–501, 1973), with agents' measure space having both atoms and an atomless sector. We proceed by following the idea of Aubin (Mathematical methods of game economic theory. North-Holland, Amsterdam, New York, Oxford, 1979) to allow for partial participation of individuals in coalitions, that induces an enlargement of the set of ordinary coalitions to the so-called fuzzy or generalized coalitions. We propose a notion of fairness which, besides efficiency, imposes absence of envy towards fuzzy coalitions, and which fully characterizes competitive equilibria and Aubin-core allocations. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has exposed the difficulty of the US public health system to respond effectively to vulnerable subpopulations, causing disproportionate rates of morbidity and mortality. New York Haredi-Orthodox Jewish communities represent a group that have been heavily impacted by Covid-19. Little research has examined their experience or perceptions toward Covid-19 and vaccines. We conducted a cross-sectional, observational study to explore the experience of Covid-19 among Haredim. Paper surveys were self-administered between December 2020 and January 2021 in Haredi neighborhood pediatricians' offices in Brooklyn, New York. Of 102 respondents, 43% reported either a positive SARS-CoV-2 viral or antibody test. Participants trusted their physicians, Orthodox medical organizations, and rabbinic leaders for medical information. Knowledge of Covid-19 transmission and risk was good (69% answered ≥ 4/6 questions correctly). Only 12% of respondents would accept a Covid-19 vaccine, 41% were undecided and 47% were strongly hesitant. Independent predictors of strong vaccine hesitancy included believing natural infection to be better than vaccination for developing immunity (adjusted odds ratio [aOR] 4.28; 95% confidence interval [CI] 1.23–14.86), agreement that prior infection provides a path toward resuming communal life (aOR 4.10; 95% CI 1.22–13.77), and pandemic-related loss of trust in physicians (aOR 5.01; 95% CI 1.05–23.96). The primary disseminators of health information for self-protective religious communities should be stakeholders who understand these groups' unique health needs. In communities with significant Covid-19 experience, vaccination messaging may need to be tailored toward protecting infection-naïve individuals and boosting natural immunity against emerging variants. [ABSTRACT FROM AUTHOR]

We argue against a purely semantic account of the Unique Path Constraint (Goldberg, Adele. 1991. It can't go down the chimney up: Paths and the English resultative. In Proceedings of the seventeenth annual meeting of the Berkeley Linguistics Society, 368–378.), i.e., the constraint that there can only be one result state in a single clause, and in favor of a syntactic restriction regarding event structure. We propose, following Mateu, Jaume & Víctor Acedo-Matellán. 2012. The manner/result complementarity revisited: A syntactic approach. In M. Cristina Cuervo & Yves Roberge (eds.), The end of argument structure? Syntax and semantics, 209–228. New York: Academic Press, that structurally there can only be one result predicate per clause since the little v head selects for one result predicate as its complement. In order to make our claim, we provide novel data that violate the Unique Path Constraint defined as a semantic constraint. Further, we analyze examples that at first blush pose a problem for the present account as they appear to involve two result phrases, e.g., shot him dead off the horse. We argue, however, that the second result phrase is not syntactically a result, but rather constitutes a case of what Acedo-Matellán, Víctor, Josep Ausensi, Josep Maria Fontana & Cristina Real-Puigdollers. forthcoming. Old Spanish resultatives as low depictives. In Chad L. Howe, Timothy Gupton, Margaret Renwick & Pilar Chamorro (eds.), Open romance linguistics 1. Selected papers from the 49th linguistic symposium on romance languages. Berlin: Language Science Press have called low depictives, which join the syntactic derivation through a low applicative head. [ABSTRACT FROM AUTHOR]

This paper builds on a body of work over the decades that examines how East Yorkers give and receive support. We go beyond the earlier work taking into consideration communication technologies and how they play a role in the ways people exchange social support across the life course. We draw on 101 in-depth interviews conducted in 2013–2014 to shed light on the support networks of a sample of East York residents and discern the role of communication technologies in the exchange of different types of social support across age groups. Our findings show that not much has changed since the 1960s in terms of the social ties that our sample of East Yorkers have, and the types of support mobilized via social networks: companionship, small and large services, emotional aid, and financial support. What has changed is how communication technologies interweave in complex ways with different types of social ties (partners, siblings, friends, etc.) to mobilize social support. We found that communication technologies helped siblings and extended kin to increase the frequency of interaction and help exchange support at a distance. Communication technologies helped solidify friendship ties by providing a continuous flow of interaction. We draw implications for theories of social support and for social policy associated with interventions aimed at helping vulnerable groups cope in hard times such as the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]