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The article discusses the second white paper by the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and the American Society for Gastrointestinal Endoscopy. It mentions that the said white paper provides details on the natural orifice transluminal endoscopic surgery (NOTES) in terms of issues such as in gastric closure, and peritoneal access. Moreover, information on the 2010 International NOTES summit meeting held in Chicago, Illinois on July 7-10, 2010 is presented.

In the past two decades, digital libraries (DL) have increasingly supported computational studies of digitized books (Jett et al. The hathitrust research center extracted features dataset (2.0), 2020; Underwood, Distant horizons: digital evidence and literary change, University of Chicago Press, Chicago, 2019; Organisciak et al. J Assoc Inf Sci Technol 73:317–332, 2022; Michel et al. Science 331:176–182, 2011). Nonetheless, there remains a dearth of DL data provisions or infrastructures for research on book reception, and user-generated book reviews have opened up unprecedented research opportunities in this area. However, insufficient attention has been paid to real-world complexities and limitations of using these datasets in scholarly research, which may cause analytical oversights (Crawford and Finn, Geo J 80:491–502, 2015), methodological pitfalls (Olteanu et al. Front Big Data 2:13, 2019), and ethical concerns (Hu et al. Research with user-generated book review data: legal and ethical pitfalls and contextualized mitigations, Springer, Berlin, 2023; Diesner and Chin, Gratis, libre, or something else? regulations and misassumptions related to working with publicly available text data, 2016). In this paper, we present three case studies that contextually and empirically investigate book reviews for their temporal, cultural, and socio-participatory complexities: (1) a longitudinal analysis of a ranked book list across ten years and over one month; (2) a text classification of 20,000 sponsored and 20,000 non-sponsored books reviews; and (3) a comparative analysis of 537 book ratings from Anglophone and non-Anglophone readerships. Our work reflects on both (1) data curation challenges that researchers may encounter (e.g., platform providers' lack of bibliographic control) when studying book reviews and (2) mitigations that researchers might adopt to address these challenges (e.g., how to align data from various platforms). Taken together, our findings illustrate some of the sociotechnical complexities of working with user-generated book reviews by revealing the transiency, power dynamics, and cultural dependency in these datasets. This paper explores some of the limitations and challenges of using user-generated book reviews for scholarship and calls for critical and contextualized usage of user-generated book reviews in future scholarly research. [ABSTRACT FROM AUTHOR]

The increasing pervasiveness of ICT technologies and sensor infrastructures is enabling police departments to gather and store increasing volumes of spatio-temporal crime data. This offers the opportunity to apply data analytics methodologies to extract useful crime predictive models, which can effectively detect spatial and temporal patterns of crime events, and can support police departments in implementing more effective strategies for crime prevention. The detection of crime hotspots from geo-referenced data is a crucial aspect of discovering effective predictive models and implementing efficient crime prevention decisions. In particular, since metropolitan cities are heavily characterized by variable spatial densities of crime events, multi-density clustering seems to be more effective than classic techniques for discovering crime hotspots. This paper presents the design and implementation of MD-CrimePredictor (Multi- Density Crime Predictor), an approach based on multi-density crime hotspots and regressive models to automatically detect high-risk crime areas in urban environments, and to reliably forecast crime trends in each area. The algorithm result is a spatio-temporal crime forecasting model, composed of a set of multi-density crime hotspots, their densities and a set of associated crime predictors, each one representing a predictive model to forecast the number of crimes that are estimated to happen in its specific hotspot. The experimental evaluation of the proposed approach has been performed by analyzing a large area of Chicago, involving more than two million crime events (over a period of 19 years). This evaluation shows that the proposed approach, based on multi-density clustering and regressive models, achieves good accuracy in spatial and temporal crime forecasting over rolling prediction horizons. It also presents a comparative analysis between SARIMA and LSTM models, showing higher accuracy of the first method with respect to the second one. [ABSTRACT FROM AUTHOR]

The article discusses the research made by Marina Wolf of Rosalind Franklin University of Medicine and Science in Chicago, Illinois, together with her colleagues, that demonstrated that an unusual type of receptor is formed in a rat's brain cells after cocaine withdrawal and that these expand the response to drug cues. Accordingly, Wolf's study on the self-regulation of neurons was influenced by the dominant thinking that dopamine neurons drive addiction. Wolf worked with pharmacologist Michela Marinelli to train rats to self-regulate the drug by poking the noses into a hole when given a stimulus that provides information on what to do.

In this article the author comments on the papers presented at the 2007 Association of American Geographers (AAG) sessions in Chicago, Illinois. He says that themes include exurbia and amenity, greater associations of work at spatial scales, and amenity migration. He tackles author Peter Walker's typology of exurbia as a spatially moving target. He explores the papers tackling the importance of geographic scales in amenity migration and exurban growth research.

The four contributions in this special issue on Argumentation Through Languages and Cultures deals with clear cases of such argumentative situations as they develop in different cultures and language groups. One of these papers comes from the Inuit oral culture; three papers from written cultures, Chinese, Muslim and Indian cultures. Among written cultures, the Indian and Muslim cultures have developed sophisticated theories of argument, while the Chinese culture, according to Graham (Disputers of the Tao—Philosophical argument in Ancient China, Open Court, Chicago, 1989, p. 169), combined "a sense of rigorous proof with the indifference to logical forms". [ABSTRACT FROM AUTHOR]

Energy prices are booming to high levels with the ongoing global events and massive energy demand post-COVID, triggering panic among-st the general public. In this regard, energy demand management can play an important role here by letting both the entities (utility and customer) take control over the consumption pattern long enough until renewables take over the energy supply from the conventional resources using real-time device scheduling algorithms. To achieve this phenomenon, both participating entities need proper prioritization and their interests to be properly taken care of. In this paper sensitivity analysis of varying priorities to the objectives (customer cost and peak-to-average power ratio) representing both the entities has been carried out. A real-time device scheduling algorithm is implemented to improve the consumption pattern of appliances consisting of multiple objectives. Proper way of normalization is developed to retain the original essence of these objectives. The analysis embeds novel swap operations that are incorporated with standard particle swarm optimization (PSO) and its variants under varying pricing schemes. In order to demonstrate the proposed DR-based real-time optimization, a residence in Chicago, Illinois, USA is taken as a case study for this work. The results demonstrate the quickness and proper optimizations of the PSO variants with butterfly-PSO performing the best among-st the rest. Continuous real-time pricing obtained the best solution with apt quickness among-st its counterparts for each time-slot and for cumulative time of the day. An overall reduction in each entity's metrics is obtained in this work. [ABSTRACT FROM AUTHOR]

Crimes tend to concentrate in high-risk places known as crime hotspots. While the size and locations of such hotspots vary between different types of crime as would the underlying conditions that trigger each crime, the extent of overlaps between their hotspots is understudied. Using crime data from Chicago aggregated at the community-area and the census-tract levels, this paper investigates the patterns of overlapping hotspots between different crime types to see whether a specific group of crime types regularly form a joint cluster. Specifically, we identify statistically significant hotspots for each crime and, using the frequent-pattern-growth algorithm, analyse the frequency of each combination of crimes sharing their hotspot locations across the study area. Results suggest that crime hotspots form stable multi-layered colocations and that each area holds its subset: namely, the pervasive, primary colocations consisting of assault, battery and criminal damage to property, which are frequently joined by 7 additional (e.g. street robbery, motor vehicle theft, weapons violation) crimes to comprise secondary colocations, some of which evolving to an even larger, tertiary colocation of hotspots with up to 11 additional crime types (e.g. homicide, criminal sexual assault, narcotics) to form crime-riddled neighbourhoods. This multi-layered structure of colocations as well as the crime colocation diagrams that show the most representative crimes at each colocation size would improve our understanding of the association between different crime types and the crime indicators of other crimes. [ABSTRACT FROM AUTHOR]

The Diversity, Equity, and Inclusion (DEI) committee was established in 2017 within the Department of Pediatrics at Rush University Medical Center (RUMC), an academic medical health center located on the near west side of Chicago, IL. Results from climate surveys highlighted the need for increased DEI initiatives within the department, and a renewed national reckoning on racial tensions sparked an additional sense of urgency for system-level change. This paper outlines the initial creation and ongoing efforts of the DEI committee. Information related to the structure of our committee, aims of our work, progress toward identified goals, as well as ongoing barriers is provided. Academic medical health centers are tasked not only with working and training together, but also to care for a diverse group of patients within a larger community. As such, academic medical health centers represent a unique backdrop and opportunity for individual and system-level change. [ABSTRACT FROM AUTHOR]

This paper proposes a well-grounded theoretical model to assess the factors influencing the intention to ride in autonomous vehicles (AVs). The model is based on the Theory of Planned Behavior (TPB), which has been decomposed to account for key components of the Diffusion of Innovation (DoI) theory and extended to include other influential attitudinal components (such as driving-related sensation seeking, safety perceptions, environmental concerns, and affinity to innovativeness). The extent to which these factors are expected to affect the diffusion of AVs uniformly across different urban settings is also examined. Data were collected through stated preference surveys targeting adult residents in three metropolitan statistical areas, Chicago (Illinois), Indianapolis (Indiana), and Phoenix (Arizona). Confirmatory factor analysis was conducted to test the validity and reliability of the components included in the theoretical model, followed by the estimation of a multi-group structural equation model. The findings of the measurement model show that the survey questions are measured equally across the three areas, and hence, the theoretical model is transferrable. The results of the structural model suggest that the synergistic effects between TPB and DoI can better explain the behavioral intention to ride in AVs. It was also found that the effect of the TBP components is similar across various areas; however, this is not the case for the DoI components. In general, the findings reinforce the need for wider testing of AV technology in urban areas coupled with public education campaigns to harvest public awareness and acceptance. [ABSTRACT FROM AUTHOR]

The article presents information on the symposium, "Infant Mouse and Rat Ultrasonic Vocalizations" that was held on June 27th, 2003 at the 33rd Annual Meeting of the Behavior Genetics Association in Chicago, Illinois. To accomplish integration, each author submitted an initial draft and the set of those drafts was sent to each author who was encouraged to refer to other papers in the issue when those works were relevant to his or her own. Thus, the reader will notice that in many cases, authors "speak to each other" in their papers. In the first paper, Mathias Kölliker sets the stage for discussions of rodent ultrasonic calls and parental responses by placing the interactions among parents and offspring in an evolutionary context.

As the technology of multi-energy carbon-free systems is strikingly developed, renewable-based multi-vector energy integration has become a prevalent trend in the decarbonization procedure of multi-carrier energy networks (MCENs). This paper proposes a fair transactive energy model for structuring an innovative local multi-energy trading market to allow multi-carrier multi-microgrids (MCMGs) with 100% renewable energy sources (RESs) in Chicago for free energy exchange aiming to balance energy in the renewable-dominant environment. Indeed, the main goal of the proposed model is to facilitate the modernization of future MCENs that are targeted to be equipped with 100% RESs and require a holistic model engaged with innovative technologies for the realization. To this end, the transactive energy architecture is designed for techno-environmental-economic assessing hybrid MCMGs to increase their flexibility in unbroken energy serving, decreasing their dependency on the main grid, and improving their economic benefits by considering their contribution level in energy interactions. To effectively model uncertainties of MCENs with 100% RESs, the novel hybrid technique is proposed that considers various stochastic changes of uncertain parameters to achieve confident results. The results highlighted the capability of the proposed model in effectively utilizing fully produced clean energy as well as continuously multi-energy serving of MCMGs in the presence of 100% RESs. Moreover, MCMGs reached techno-environmental-economic benefits by operating under the proposed transactive energy-based model, in which the technical, environmental, and economic goals are respectively realized by considering all constraints of MCENs, producing 100% clean energy by RESs, and reducing the total energy cost from $1,274,742.55 in the based model to $1,159,235.89 in the proposed one. [ABSTRACT FROM AUTHOR]

The article presents a sociological view of the press coverage of a sociological convention. The coverage is based on observations carried out by five newsmen-observers who attended the August 1965 American Sociological Association (ASA) meetings in Chicago, Illinois. The general conclusion of this study of the convention was that the confrontation of the sociologist with the representative of the news media was overwhelmingly inadvertent, disconcerting and only partially successful to either party. In terms of efficiency in social communication, it leaves much to be desired and strongly entices one to prescribe therapy. Few suggestions are made in advance of Florida sessions in order to get sociologist into communication with the Miami Press. It is suggested to issue a handbook in advance of the convention to all members of the ASA and once the convention has started, to maintain a special message board near the newsroom which offers a chance for newsmen to indicate their wish to contact writers of papers. It is also suggested the president of the ASA assemble a small, informal committee which would hold daily news briefings alerting them to persons or topics originating outside or inside the formal program of the convention.

In this paper, hierarchical feedback loop analysis is employed to identify changes in the economic interactions among sectors during the process of structural transformation of the Chicago economy. The application in our paper differs from previous studies adopting this methodology as it focuses on the time dimension of change through analysis of feedback loops every 5 years from 1995 to 2010. A total of 36 hierarchical feedback loops for years 1995, 2000, 2005 and 2010 were obtained. The first two feedback loops captured the main character of the economic structure transformation. The linkages strength between five pairs of sectors which include linkages from hotels, personal and business services to construction, from finance and insurance to wholesale and retail trade, etc., accounted for 83.5% of the intensity change in the first feedback loop from 1995 to 2010. Structural change of linkages played little role in the complexity change of the second feedback loop. The change of linkages strength from wholesale and retail trade to construction, from rubber and miscellaneous plastics products to chemicals and allied products accounted for about 83.0% of this latter loop. The economic transformation of Chicago economy showed that the development of services has not come at the expense of the decline of industry. Over the period in question, the Chicago economy became more diversified. [ABSTRACT FROM AUTHOR]

Seeking spatiotemporal patterns about how citizens interact with the urban space is critical for understanding how cities function. Such interactions were studied in various forms focusing on patterns of people's presence, action, and transition in the urban environment, which are defined as human-urban interactions in this paper. Using human activity datasets that utilize mobile positioning technology for tracking the locations and movements of individuals, researchers developed stochastic models to uncover preferential return behaviors and recurrent transitional activity structures in human-urban interactions. Ad-hoc heuristics and spatial clustering methods were applied to derive meaningful activity places in those studies. However, the lack of semantic meaning in the recorded locations makes it difficult to examine the details about how people interact with different activity places. In this study, we utilized geographic context-aware Twitter data to investigate the spatiotemporal patterns of people's interactions with their activity places in different urban settings. To test consistency of our findings, we used geo-located tweets to derive the activity places in Twitter users' location histories over three major U.S. metropolitan areas: Greater Boston Area, Chicago, and San Diego, where the geographic context of each location was inferred from its closest land use parcel. The results showed striking spatial and temporal similarities in Twitter users' interactions with their activity places among the three cities. By using entropy-based predictability measures, this study not only confirmed the preferential return behaviors as people tend to revisit a few highly frequented places but also revealed detailed characteristics of those activity places. [ABSTRACT FROM AUTHOR]

Since 2007, the Oncofertility Consortium Annual Conference has brought together a diverse network of individuals from a wide range of backgrounds and professional levels to disseminate emerging basic and clinical research findings in fertility preservation. This network also developed enduring educational materials to accelerate the pace and quality of field-wide scientific communication. Between 2007 and 2019, the Oncofertility Consortium Annual Conference was held as an in-person event in Chicago, IL. The conference attracted approximately 250 attendees each year representing 20 countries around the world. In 2020, however, the COVID-19 pandemic disrupted this paradigm and precluded an in-person meeting. Nevertheless, there remained an undeniable demand for the oncofertility community to convene. To maintain the momentum of the field, the Oncofertility Consortium hosted a day-long virtual meeting on March 5, 2021, with the theme of "Oncofertility Around the Globe" to highlight the diversity of clinical care and translational research that is ongoing around the world in this discipline. This virtual meeting was hosted using the vFairs ® conference platform and allowed over 700 people to participate, many of whom were first-time conference attendees. The agenda featured concurrent sessions from presenters in six continents which provided attendees a complete overview of the field and furthered our mission to create a global community of oncofertility practice. This paper provides a synopsis of talks delivered at this event and highlights the new advances and frontiers in the fields of oncofertility and fertility preservation around the globe from clinical practice and patient-centered efforts to translational research. [ABSTRACT FROM AUTHOR]

This paper is an extension of a study focused on a small, suburban school district approximately 15 miles outside of Chicago, Illinois, situated in a uniquely diverse community with a host of racial, socioeconomic, linguistic identities. Despite the fact that 95% of its 2016–2017 kindergarten class had some form of preschool experience, gaps were observed in kindergarten readiness between Black and White students, leading to achievement gaps in later years. Consequently, the district has directed its focus on enhancing the levels of equity among its students. The original mixed-methods study explored potential factors of this readiness gap, including the types of services rendered by early education providers and access to high-quality early childhood education in the community. This paper narrows its focus to the experience of Black early learners in this district, particularly as it relates to their preschool experiences and special education rates. Qualitative interviews illuminated the following themes: (1) low levels of readiness and disproportionate special education service identification of Black students; (2) minimal socioeconomic and racial diversity in the community's private preschools; (3) few opportunities for special education services or financial support at private preschools; (4) high rates of minority students attending home-based childcare instead of formal preschool; and (5) differing approaches to family engagement and curriculum between the private schools and the district center. More research and community engagement is needed to fully explore the population of Black students with special needs and those who are not receiving formal childcare prior to enrolling in school. [ABSTRACT FROM AUTHOR]

This paper looks at organizations working on issues of sex work/sex trafficking in Chicago as a strategic action field (SAF): a space where actors engage in collective action with a shared understanding of the field's purposes, rules, and norms. Through analysis of SAFs, scholars focus on how actors intersect, manifesting in a context that simultaneously allows for reproducing the status quo, as well as producing social change. Using qualitative interviews with members of this particular SAF in Chicago, I demonstrate how actors in the field use the SAF concept of social skill to control the policy field. The challenger organization in particular uses social skill to exploit exogenous shocks to their advantage, pursuing legitimacy through their alignment with human service nonprofits. This paper concludes with a consideration of the use of SAF theory to dynamic fields such as sex work/sex trafficking, conceptualizing how field-level social change may occur. [ABSTRACT FROM AUTHOR]

For a given set of spatial locations (e.g., criminal activities, disease outbreak, etc.), circular hotspot detection (CHD) identifies circular zones (or hotspots) of significantly high concentration of activity points in the given space. Furthermore, the prevalence of activities inside these zones is considerably higher than outside them. CHD is essential for numerous societal applications, including criminology, epidemiology, etc. The existing methods for CHD consider one of the given activity points as the center of the circular zone (or hotspot). Hence, these methods are incapable of ignoring small gaps (like mountains, rivers, etc.) in the spatial contiguity of hotspots and are not geographically robust. Geographically robust CHD (GR-CHD) requires enumeration of those candidate circles where the hotspot center is not necessarily an activity point. Unfortunately, this enumeration unreasonably increases the enumerated circles and makes GR-CHD a computationally expensive problem. Therefore, in this paper, GR-CHD is modeled as a single-objective optimization problem. Further, three swarm intelligence (SI) algorithms, namely particle swarm optimization, grey wolf optimizer, and salp swarm algorithm, are applied to the proposed model to detect geographically robust hotspots. Finally, the performances of the presented SI-based schemes and state-of-the-art cubic grid circle (CGC) algorithm have been compared. They are evaluated over the controlled synthetic datasets and the crime dataset of Chicago city for the year 2019. The obtained results indicate that the computational times required by the SI-based schemes are significantly less than the CGC algorithm. Also, the quality of hotspots detected by SI-based algorithms is either improved or at par with the CGC algorithm. [ABSTRACT FROM AUTHOR]

The concept of bias is familiar to linguists primarily from the literature on questions. Following the work of Giannakidou and Mari (Truth and Veridicality in Grammar and Thought: Modality, Mood, and Propositional Attitudes, University of Chicago Press, Chicago, 2021), we assume "nonveridical equilibrium" (implying that p and ¬p as equal possibilities) to be the default for epistemic modals, questions and conditionals. The equilibrium of conditionals, as that of questions, can be manipulated to produce bias (i.e., reduced or higher speaker commitment). In this paper, we focus on three kinds of modal elements in German that create bias in conditionals and questions: the adverb wirklich 'really', the modal verb sollte 'should', and conditional connectives such as falls 'if/in case'. We conducted two experiments collecting participants' inference about speaker commitment in different manipulations, Experiment 1 on sollte/wirklich in ob-questions and wenn-conditionals, and Experiment 2 on sollte/wirklich in wenn/falls/V1-conditionals. Our findings are that both ob-questions and falls-conditionals express reduced speaker commitment about the modified (antecedent) proposition in comparison to wenn-conditionals, which did not differ from V1-conditionals. In addition, sollte/wirklich in the antecedent of conditionals both create negative bias about the antecedent proposition. Our studies are among the first that deal with bias in conditionals (in comparison to questions) and contribute to furthering our understanding of bias. [ABSTRACT FROM AUTHOR]

Accurate demand prediction of bike-sharing is an important prerequisite to reducing the cost of scheduling and improving the user satisfaction. However, it is a challenging issue due to stochasticity and non-linearity in bike-sharing systems. In this paper, a model called pseudo-double hidden layer feedforward neural networks is proposed to approximately predict actual demands of bike-sharing. Specifically, to overcome limitations in traditional back-propagation learning process, an algorithm, an extreme learning machine with improved particle swarm optimization, is designed to construct learning rules in neural networks. The performance is verified by comparing with other learning algorithms on the dataset of Streeter Dr bike-sharing station in Chicago. [ABSTRACT FROM AUTHOR]

This paper examines the effects of the Supplemental Nutrition Assistance Program (SNAP) on obesity among women. We address several of the empirical challenges surrounding the estimation of said effects raised in Currie and Moffitt (in: Moffitt RA, Moffitt R (eds) Means-tested transfer programs in the USA. University of Chicago Press, Chicago, 2003). We do so by employing a battery of recently developed econometric methods that require only cross-sectional data, and alternative identification assumptions relative to the traditional instrumental variable used in the current literature. Our goal is to assess whether the common findings are robust to various methods. Using data from the National Health and Nutrition Examination Survey, we reach two important conclusions. First, the positive effect of SNAP on both obesity and the body mass index is robust to differing statistical and modeling assumptions, while statistical significance may vary. Second, we also find that decreased dietary quality among SNAP participants could be at best a weak candidate for explaining the difference in our findings (if any) on obesity. [ABSTRACT FROM AUTHOR]

Given a geometric space and a set of weighted spatial points, the Size Constrained k Simple Polygons (SCkSP) problem identifies k simple polygons that maximize the total weights of the spatial points covered by the polygons and meet the polygon size constraint. The SCkSP problem is important for many societal applications including hotspot area detection and resource allocation. The problem is NP-hard; it is computationally challenging because of the large number of spatial points and the polygon size constraint. Our preliminary work introduced the Nearest Neighbor Triangulation and Merging (NNTM) algorithm for SCkSP to meet the size constraint while maximizing the total weights of the spatial points. However, we find that the performance of the NNTM algorithm is dependent on the t-nearest graph. In this paper, we extend our previous work and propose a novel approach that outperforms our prior work. Experiments using Chicago crime and U.S. Federal wildfire datasets demonstrate that the proposed algorithm significantly reduces the computational cost of our prior work and produces a better solution. [ABSTRACT FROM AUTHOR]

This paper examines the historical origins and theoretical underpinnings of the maps of the city of Chicago produced by sociologists at the University of Chicago between 1920 and 1934. I argue that the three mapping schemes produced in those years-the concentric zone map of The City (1925), the base map of 75 community areas and the census tract maps published in three volumes of Census Data of the City of Chicago (1920, 1930, 1934)-draw upon distinct historical antecedents and have distinct theoretical implications. The first scheme exhibits the strong influence of Johann Heinrich von Thünen's location theory and maps produced by early Chicago city boosters, the second most clearly exhibits the influence of the Social Survey Movement and of pragmatist philosophy and the third, the influence of the financial and governmental interests of the organizations that made up the Chicago Census Committee. Literature on early urban sociology and mapping in Chicago has hitherto not adequately differentiated these three mapping schemes or problematized the implications of their differences for our understanding of the theoretical commitments of the 'Chicago School.' [ABSTRACT FROM AUTHOR]

Data mining is an important technology to reveal the patterns from crime data. Although there are many researches about this topic, less work models the relations between rates of different kinds of crime. In this paper, an algorithm based on fuzzy association rules (AR) mining is proposed to discover these relations. Two datasets, which are crimes in Chicago from 2012 to 2017 and crimes in NSW from 2008 to 2012, are used for case studies. At first, crime data is preprocessed, where every kind of crime occurring in every district during every month is counted. For a crime in a combination of district and month, the membership function, which is based on hypothesis testing, is designed to evaluate the degree to which its rate is high, normal or low, and the fuzzy transactional dataset is formed. A bridge between fuzzy transactional dataset and binary AR mining algorithm is built, so those mature tools of binary AR mining can be applied to generate fuzzy ARs. In the results of case studies, the strong relations between rates of different crime can be found. There are many interesting and surprise rules, which are worthy to be further studied by domain experts. [ABSTRACT FROM AUTHOR]

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Objectives: Chicago's Project Safe Neighborhoods focused deterrence program is an effective crime reduction policy. However, similar to other focused deterrence programs, prior evaluations have not empirically established the mechanisms of change believed to underlie the program. The purpose of this paper was to address this gap by examining the influence of offender notification meetings—a key component of the program—on three mechanisms: perceptions of risks associated with future offending, perceptions of police legitimacy, and adherence to community norms. Methods: Over a 1-year period, parolees attending the notification meetings were randomly assigned to complete surveys assessing each of the mechanisms immediately before the meeting (control) or immediately after (treatment). Results: Parolees in the treatment condition had higher perceptions of risk and police legitimacy compared to those in the control condition. Additionally, they were more likely to judge police as procedurally fair. The groups did not differ with respect to adherence to community norms. Within both groups, perception of risk was positively associated with motivation to stay out of prison. Police legitimacy was also positively associated with motivation for the treatment group, while community norm adherence was positively associated with motivation for those in the control condition. Conclusions: This study indicates that the offender notification meetings are working as intended with respect to the underlying mechanisms of change embedded in Chicago's Project Safe Neighborhoods. [ABSTRACT FROM AUTHOR]

Looks at the role of the University of Chicago (UC) Press in the rise of UC's Department of Sociology to preeminence by 1920 in the field of American and international sociology. History of the UC Press; Sales performance of the Press in its first decade; Publication of the `American Journal of Sociology'; UC Press monographs.

This paper operationalizes the idea of a local indicator of spatial association for the situation where the variables of interest are binary. This yields a conditional version of a local join count statistic. The statistic is extended to a bivariate and multivariate context, with an explicit treatment of co-location. The approach provides an alternative to point pattern-based statistics for situations where all potential locations of an event are available (e.g., all parcels in a city). The statistics are implemented in the open-source GeoDa software and yield maps of local clusters of binary variables, as well as co-location clusters of two (or more) binary variables. Empirical illustrations investigate local clusters of house sales in Detroit in 2013 and 2014, and urban design characteristics of Chicago census blocks in 2017. [ABSTRACT FROM AUTHOR]

Objectives: This paper reports the findings of an evaluation of a police training program on the principles of procedural justice. This training was part of a larger organizational change strategy aimed at improving the relationship between the police and the public in Chicago. Methods: The paper reports on the findings of two studies. The short-term effects study was a quasi-experimental test of the immediate effectiveness of the training conducted at the police academy. A longer-term effects study examined the subsequent views of trainees and a comparison group, officers who had not yet been to training. Statistical controls were used to increase confidence in the findings of the second study, which was based on observational data. Results: In the short term, training increased officer support for all of the procedural justice dimensions included in the experiment. Post-training, officers were more likely to endorse the importance of giving citizens a voice, granting them dignity and respect, demonstrating neutrality, and (with the least enthusiasm) trusting them to do the right thing. All of the effects of training were strong, with standardized effect sizes ranging from 1.2 to 1.6. Longer-term, officers who had attended the procedural justice workshop continued to be more supportive of three of the four procedural justice principles introduced in training; the effect of training on trust was not statistically significant. Conclusions: There has been little systematic research on police training. This paper concludes that it can play a role in improving police-community relations. It also presents a discussion of some of the limitations of a training-based organizational change strategy. [ABSTRACT FROM AUTHOR]

In the field of organized crime, John Landesco is best known for his 1929 study titled 'Organized Crime in Chicago,' published as part of the Illinois Crime Survey. It has since been republished in 1968 with an excellent introduction by historian Mark H. Haller. Perceptively, many experts now consider Landesco's early work as a classic academic study, revealing the historic relationships between disorganized neighborhoods, illicit markets, and the political economy of urban America. Unbeknownst to many, Landesco wrote on other subjects while a graduate student at the University of Chicago under the tutelage of none other than Ernest W. Burgess. Within the special collections of the Regenstein Library at the University of Chicago, the personal papers of both Landesco and Burgess reveal the origins of his work on organized crime, an unpublished book, and several lesser known articles that provide a broader picture of his research on organized crime. This article discusses the career of John Landesco as an early theorist on organized crime, underscoring yet again why his 1929 study remains a classic in the field. [ABSTRACT FROM AUTHOR]

In many cities of the global North, city leaders are using greening as a way to compete in the globalized economy. Critiques of this development strategy typically focus on downtown areas, and many have noted that such processes often displace poor and working class people. Less studied are those areas that have not been fully incorporated into the postindustrial economy and where the struggles around social justice, economic development, and ecological restoration are still being played out. It is this insufficiently informed area of knowledge which this paper seeks to address and as to which we ask: What has been the impact of the green economy discourse in relatively more marginalized urban areas? Using industrial areas of Southeast Chicago and South Seattle as case studies, this paper draws on previously unreported qualitative data to argue that community efforts to promote environmental justice in these areas have the potential to redefine practices of green economic growth to incorporate social equity and community coherence. However, their ability to do so is constrained by the difficulty in challenging neoliberal discourses of the primacy of growth and the need of greening to benefit the consumer class. The paper contemplates the implications of the lessons learnt for greening cities in both developed and developing countries. [ABSTRACT FROM AUTHOR]

Accurate shared micromobility demand predictions are essential for transportation planning and management. Although deep learning methods provide robust mechanisms to tackle demand forecasting challenges, current models based on graph neural networks suffer from limited scalability and high computational cost. There is both a need and significant potential to enhance the accuracy and efficiency of existing shared micromobility demand forecasting models. To fill these research gaps, this paper proposes a deep learning model named Interactive Convolutional Network (ICN) to forecast spatiotemporal travel demand for shared micromobility. The proposed model develops a novel channel dilation method by utilizing multi-dimensional spatial information (i.e., demographics, functionality, and transportation supply) based on travel behavior knowledge for building the deep learning model. We use the convolution operation to process the dilated tensor to simultaneously capture temporal and spatial dependencies. Based on a binary-tree-structured architecture and interactive convolution, the ICN model extracts features at different temporal resolutions and then generates predictions using a fully-connected layer. We conducted two practical case studies from Chicago, IL, and Austin, TX to test the proposed model. The results show that the ICN model significantly outperforms all benchmark models. The model predictions have the potential to assist micromobility operators in developing efficient vehicle rebalancing strategies, while also providing cities with guidance on enhancing the management of their shared micromobility system. [ABSTRACT FROM AUTHOR]

The hemibiotrophic Basidiomycete pathogen Ganoderma boninense (Gb) is the dominant causal agent of oil palm basal stem rot disease. Here, we report a complete chromosomal genome map of Gb using a combination of short-read Illumina and long-read Pacific Biosciences (PacBio) sequencing platforms combined with chromatin conformation capture data from the Chicago and Hi-C platforms. The genome was 55.87 Mb in length and assembled to a high contiguity (N50: 304.34 kb) of 12 chromosomes built from 112 scaffolds, with a total of only 4.34 Mb (~ 7.77%) remaining unplaced. The final assemblies were evaluated for completeness of the genome by using Benchmarking Universal Single Copy Orthologs (BUSCO) v4.1.4, and based on 4464 total BUSCO polyporales group searches, the assemblies yielded 4264 (95.52%) of the conserved orthologs as complete and only a few fragmented BUSCO of 42 (0.94%) as well as a missing BUSCO of 158 (3.53%). Genome annotation predicted a total of 21,074 coding genes, with a GC content ratio of 59.2%. The genome features were analyzed with different databases, which revealed 2471 Gene Ontology/GO (11.72%), 5418 KEGG (Kyoto Encyclopedia of Genes and Genomes) Orthologous/KO (25.71%), 13,913 Cluster of Orthologous Groups of proteins/COG (66.02%), 60 ABC transporter (0.28%), 1049 Carbohydrate-Active Enzymes/CAZy (4.98%), 4005 pathogen–host interactions/PHI (19%), and 515 fungal transcription factor/FTFD (2.44%) genes. The results obtained in this study provide deep insight for further studies in the future. [ABSTRACT FROM AUTHOR]

Respiratory Syncytial Virus (RSV) is a leading cause of acute respiratory tract infection, with the greatest impact on infants, immunocompromised individuals, and older adults. RSV prevalence decreased substantially in the United States (US) following the implementation of COVID-19-related non-pharmaceutical interventions but later rebounded with abnormal seasonality. The biological and epidemiological factors underlying this altered behavior remain poorly defined. In this retrospective cohort study from 2009 to 2023 in Chicago, Illinois, US, we examined RSV epidemiology, clinical severity, and genetic diversity. We found that changes in RSV diagnostic platforms drove increased detections in outpatient settings post-2020 and that hospitalized adults infected with RSV-A were at higher risk of intensive care admission than those with RSV-B. While population structures of RSV-A remained unchanged, RSV-B exhibited a genetic shift into geographically distinct clusters. Mutations in the antigenic regions of the fusion protein suggest convergent evolution with potential implications for vaccine and therapeutic development. Non-pharmaceutical interventions for COVID-19 also impacted the transmission of other viruses including respiratory syncytial virus (RSV). Here the authors describe the changing epidemiology, clinical severity, and genetic diversity of RSV in Chicago, Illinois, from July 2010 to April 2023. [ABSTRACT FROM AUTHOR]

The commute mode choice decision is one of the most fundamental aspects of daily travel. Although initial research in this area was limited to explaining mode choice behavior as a function of traveler socioeconomics, travel times, and costs, subsequent studies have included the effect of traveler attitudes and perceptions. This paper extends the existing body of literature by examining public transit choice in the Chicago area. Data from a recent Attitudinal Survey conducted by the Regional Transportation Authority (RTA) in Northeastern Illinois were used to pursue three major steps. First, a factor analysis methodology was used to condense scores on 23 statements related to daily travel into six factors. Second, the factor scores on these six dimensions were used in conjunction with traveler socioeconomics, travel times, and costs to estimate a binary logistic regression of public transit choice. Third, elasticities of transit choice to the six factors were computed, and the factors were ranked in decreasing order of these elasticities. The analysis provided two major findings. First, from a statistical standpoint, the attitudinal factors improved the intuitiveness and goodness-of-fit of the model. Second, from a policy standpoint, the analysis indicated the importance of word-of-mouth publicity in attracting new riders, as well as the need for a marketing message that emphasizes the lower stress level and better commute time productivity due to transit use. [ABSTRACT FROM AUTHOR]

If models can be true, where is their truth located? Giere (Explaining science, University of Chicago Press, Chicago, 1998) has suggested an account of theoretical models on which models themselves are not truth-valued. The paper suggests modifying Giere's account without going all the way to purely pragmatic conceptions of truth-while giving pragmatics a prominent role in modeling and truth-acquisition. The strategy of the paper is to ask: if I want to relocate truth inside models, how do I get it, what else do I need to accept and reject? In particular, what ideas about model and truth do I need? The case used as an illustration is the world's first economic model, that of von Thünen (1826/1842) on agricultural land use in the highly idealized Isolated State. [ABSTRACT FROM AUTHOR]

Both self-report and official crime data have known limitations, leading to the critical question as to whether inferences about the adolescent life-course of crime are different across these data sources. Using both official and self-report arrest data on a sample of subjects drawn from the Project on Human Development in Chicago Neighborhoods (PHDCN) longitudinal cohort study, this paper examines the extent to which individual age-arrest curves are comparable across these data sources. Particular attention is given to examining whether criminal career dimensions, namely participation, frequency of arrest, age of onset, and continuity in behavior, are similar across data sources. Additionally, this paper examines whether the key predictors of youth crime (e.g., family processes, peer influence, and neighborhood disadvantage) function similarly across measurement types. Findings reveal that a sizable number of youth self-report being arrested without having a corresponding official arrest record, and a sizable proportion of those youth with an official arrest record fail to self-report that they had been arrested. Despite significant differences across the two arrest measures on many criminal career dimensions, the effects of family supervision, parent–child conflict, and neighborhood disadvantage operate similarly across data types. [ABSTRACT FROM AUTHOR]

Presents information about various papers presented in the 33rd annual business meeting of the Behavior Genetics Association held on June 28, 2003 at Palmer House Hilton in Chicago, Illinois. Proceedings of this meeting; Abstracts of papers presented in this meeting; Contact information of authors of these papers.

Motivated by both the need to model recent structural economic changes and the need to understand better the nature of environmental-economic interactions, this paper introduces a continuous-time regional econometric input-output model for the Chicago economy that can be used to analyze, at disaggregated sectoral and temporal levels, the economic and environmental implications of changes exogenous to the economy. The model's solution yields estimates of emission inventories, which may be used to analyze environmental implications of various economic changes and policy restrictions. This model is the first integrated economic-environmental model of which we are aware that has been formulated and estimated in continuous time for the regional economy of a metropolitan area. We believe that the model's formulation will enable it to enjoy greater compatibility with natural science-based models, which share such a formulation and flexibility in projecting future emissions corresponding to alternative future economic scenarios and in evaluating emissions policies relevant to such scenarios. [ABSTRACT FROM AUTHOR]

A methodological critique of the Chicago School of legal economic analysis, in particular Posner's approach, is illustrated by an example characterizing Chicago-type 'analysis of law'. Although the discussion of the example referred to may be interesting in its own right, its purpose here is to suggest a more general framework of criticism in order to allow for generalizable conclusions. The suggestion of an alternative interpretation and solution to a particular legal problem serves to point out some limits of the methodology Posner has adopted. This applies more generally to the delineation of the limits of the rôle economics can play in actual litigation in helping judges and juries to arrive at fair as well as socially efficient solutions. [ABSTRACT FROM AUTHOR]

The design of collaborative robotics, such as driver-assisted operations, engineer a potential automation of decision-making predicated on unobtrusive data gathering of human users. This form of 'somatic surveillance' (Hayles, Unthought: the power of the cognitive nonconscious. University of Chicago Press, Chicago, 2017, p. 11) increasingly relies on behavioural biometrics and sensory algorithms to verify the physiology of bodies in cabin interiors. Such processes secure cyber-physical space, but also register user capabilities for control that yield data as insured risk. In this technical re-formation of human–machine interactions for control and communication 'a dissonance of attribution' (Hancock et al., Proc Natl Acad Sci 116(16):7684, 2019. https://doi.org/10.1073/pnas.1805770115) is created between perceptions of phenomena, materials and decision-making. This reconfigures relations not only between humans and machines, objects and subjects, but possibly disrupts attributive functions in the social system of Law. What it requires is shifting a legal accountability for action from a sovereignty of the human to a new materialist account based on a 'cognitive assemblage' between physiological data, computation and algorithmic sensing. This paper investigates the function of law as a guidance system to acknowledge this account of sensory and algorithmic computation as autonomous 'sensing agents' (Hansen, Feed-forward: on the future of twenty-first-century media. University of Chicago Press, Chicago, 2015) that may be accountable in situations of risk. This assemblage of robotic computation and sensory determination requires a clearer legal differentiation across the current static terminologies of person, property, liability and rights that maintain strict separations of object from subject. To neglect this, we argue, law will solely impute attributions of error to humans despite evidence of operation via mutual control. [ABSTRACT FROM AUTHOR]

The importance of early prediction in reducing the impact of crime cannot be overstated. Machine learning algorithms have proven to be effective in this regard, but their inability to capture key features automatically can be a hindrance. To overcome this challenge, we propose a deep neural network model that is capable of extracting salient features automatically for predicting crime categories using real-world crime data sourced from the Chicago open data portal. To ensure the robustness of our proposed model, we carried out an extensive exploratory data analysis to determine the impact of socioeconomic indicators on crime occurrences. Additionally, we implemented a data upsampling technique to handle class imbalance issues, and we leveraged hyperparameter optimization algorithms to fine-tune the model. The results of our study were impressive. Our proposed model outperformed the baseline model and other algorithms, with an average improvement of 6% in macro F1 score. This suggests that our model is highly effective, if not superior, in predicting crime categories accurately. Overall, our study provides a solid framework for using deep neural network models in crime prediction, while highlighting the importance of automatic feature extraction in enhancing the accuracy of predictions. By reducing the impact of crime through early prediction, we can help to create a safer and more secure society. [ABSTRACT FROM AUTHOR]

A citation is a way of giving individuals credit for their creative and intellectual work that you used to support your research. The citation can be used to identify a particular source and to combat plagiarism. By citing and referring consulted material to a piece of educational work, you will not only be able to more easily verify others' views of facts in your work, but you will work in an ethical and honest way. Acknowledgments can be in the form of text citations, footnotes, endnotes and/or bibliographies. Different citing and reference styles cater to the specific needs of different disciplines. [ABSTRACT FROM AUTHOR]

Short-term increases in air pollution levels are linked to large adverse effects on health and productivity. However, existing regulatory monitoring systems lack the spatial or temporal resolution needed to capture localized events. This study uses a dense network of over 100 sensors, deployed across the city of Chicago, Illinois, to capture the spread of smoke from short-term structural fire events. Examining all large structural fires that occurred in the city over a year (N = 21), we characterize differences in PM 2.5 concentrations downwind versus upwind of the fires. On average, we observed increases of up to 10.7 μ g/m 3 (95% CI 5.7–15.7) for sensors within 2 km and up to 7.7 μ g/m 3 (95% CI 3.4–12.0) for sensors 2–5 km downwind of fires. Statistically significant elevated concentrations were evident as far as 5 km downwind of the location of the fire and persisted over approximately 2 h on average. This work shows how low-cost sensors can provide insight on local and short-term pollution events, enabling regulators to provide timely warnings to vulnerable populations. [ABSTRACT FROM AUTHOR]

Redlining and other discriminatory government policies enacted during the first half of the Twentieth Century have had long-lasting negative effects on neighborhoods, especially those inhabited by people of color. This study attempts to link the practice of redlining to current-day indicators of neighborhood concentrated disadvantage and violent crime using spatio-temporal data from Chicago. Specifically, the study seeks to determine whether redlining has been associated with increased levels of concentrated disadvantage since its implementation in the 1930s. In addition, it seeks to determine whether redlining was associated with violent crime, and if that association was mediated by redlining's effect on concentrated disadvantage. The results indicate that redlining was associated with increases in both concentrated disadvantage and violent crime, and that redlining's relationship with violent crime was, indeed, partially mediated by its relationship with concentrated disadvantage. The findings from this study suggest that to reduce violent crime in urban communities, we cannot simply rely on our current punitive criminal justice system. Instead, policies should focus on reducing concentrated disadvantage and racial isolation by helping economically strengthen severely disadvantaged neighborhoods and by increasing residential mobility for individuals currently living in those neighborhoods. [ABSTRACT FROM AUTHOR]

Provides information on an annual meeting held by the American Pancreatic Association (APA) in Chicago, Illinois on November 5-6, 1987. Number of registrants from different countries that attended the meeting; Significance of the event to scientists; Categories of the papers presented in the different sessions.

After the self-criticism of Richard Posner (A failure of capitalism. The crisis of '08 and the descend to depression. Harvard University Press, Cambridge, and some later papers), a position shared in part by Gary Becker, it is right to ask what exactly remains of the Chicago School, which came into being in the early 1930s with Knight and made a name for itself in the 1980s as the new orthodoxy with Lucas ( Reh) and Fama ( Emh). The financial crisis has, in this sense, cast the debate between the Saltwater school (the American universities on the coast) and the Freshwater school (the universities near the Great Lakes, including Chicago) in a new light. This article traces the development of the Chicago School, the consolidation of conservative think-tanks (especially the Mont Pelerin Society whose members have included, among others, von Hayek and Friedman) and the more recent positions of the School, including some that are less organic (Diamond, Kashyap, Rajan, Zingales). At the centre of the debate is the question of the failures of the State vs the failures of the market and the role of institutions. On a methodological level the relationship between law and economics ( L&E) is also in discussion, which leads to an interesting comparison between Chicago (again Posner, past and present) and Yale (Calabresi). After having described the echoes of the debate across the Atlantic (with particular reference to Italy), it will be asked if the anomalies that can be found in the consolidated paradigm ( Reh, Emh, but also L&E) will lead to the abandonment of pre-constituted models in favour of a less rigid theoretical framework ( Ike together with Keynes and the Chicagoan Knight, but also to a certain extent, von Hayek) or simply a pause for reflection. [ABSTRACT FROM AUTHOR]

In the 35 brief chapters that follow, McCloskey takes the reader step-by-tiny-step through the fundamentals of good writing, starting with chapters titled "Writing is a Trade" and "Writing is Thinking." McCloskey is as opinionated about those who give writing advice as she is about writing. While Deirdre Nansen McCloskey has since expanded her intended audience, in this third, revised edition she still targets a reader who needs to be convinced that studying writing matters - so much so that she titled her introductory chapter, "Why You Should Not Stop Reading Here.". [Extracted from the article]