The MICRO-BOSS scheduling system: Current status and future efforts

In this paper, a micro-opportunistic approach to factory scheduling was described that closely monitors the evolution of bottlenecks during the construction of the schedule, and continuously redirects search towards the bottleneck that appears to be most critical. This approach differs from earlier opportunistic approaches, as it does not require scheduling large resource subproblems or large job subproblems before revising the current scheduling strategy. This micro-opportunistic approach was implemented in the context of the MICRO-BOSS factory scheduling system. A study comparing MICRO-BOSS against a macro-opportunistic scheduler suggests that the additional flexibility of the micro-opportunistic approach to scheduling generally yields important reductions in both tardiness and inventory

Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?

Traffic simulators are used to generate data for learning in intelligent transportation systems (ITSs). A key question is to what extent their modelling assumptions affect the capabilities of ITSs to adapt to various scenarios when deployed in the real world. This work focuses on two simulators commonly used to train reinforcement learning (RL) agents for traffic applications, CityFlow and SUMO. A controlled virtual experiment varying driver behavior and simulation scale finds evidence against distributional equivalence in RL-relevant measures from these simulators, with the root mean squared error and KL divergence being significantly greater than 0 for all assessed measures. While granular real-world validation generally remains infeasible, these findings suggest that traffic simulators are not a deus ex machina for RL training: understanding the impacts of inter-simulator differences is necessary to train and deploy RL-based ITSs.Comment: 12 pages; accepted version, published at the 2023 Winter Simulation Conference (WSC '23

Modeling Integrated Properties and the Polarization of the Sunyaev-Zeldovich Effect

Two little explored aspects of Compton scattering of the CMB in clusters are discussed: The statistical properties of the Sunyaev-Zeldovich (S-Z) effect in the context of a non-Gaussian density fluctuation field, and the polarization patterns in a hydrodynamcially-simulated cluster. We have calculated and compared the power spectrum and cluster number counts predicted within the framework of two density fields that yield different cluster mass functions at high redshifts. This is done for the usual Press & Schechter mass function, which is based on a Gaussian density fluctuation field, and for a mass function based on a chi^2-distributed density field. We quantify the significant differences in the respective integrated S-Z observables in these two models. S-Z polarization levels and patterns strongly depend on the non-uniform distributions of intracluster gas and on peculiar and internal velocities. We have therefore calculated the patterns of two polarization components that are produced when the CMB is doubly scattered in a simulated cluster. These are found to be very different than the patterns calculated based on spherical clusters with uniform structure and simplified gas distribution.Comment: 22 pages, 25 figures, Proceedings of the Francesco Melchiorri memorial conference, New Astronomy Reviews, in pres

A Guide for Policy, Practice and Patients on Wellbeing and Sickle Cell Disorder (SCD)

This guide is based on research examining the shielding experiences of people with sickle cell disorders (SCD) and parents of children with the condition during the COVID-19 pandemic. The aim was to improve NHS services for this population group. Services have duties under the Equality Act 2010 to ensure equity and tackle health inequalities. Since SCD disproportionately affects Black, Asian and Minority Ethnic (BAME) communities, there are also duties not to engage in direct or indirect racist discrimination, nor in harassment or victimization. It is important that anti-racist and anti-bias training is offered in all NHS services and cultural competency encouraged amongst all staff. Additionally, that conditions affecting the BAME population, like SCD, become a mandatory part of all nursing and medical educational and NHS training programmes

Disagreeable Privacy Policies: Mismatches between Meaning and Users’ Understanding

Privacy policies are verbose, difficult to understand, take too long to read, and may be the least-read items on most websites even as users express growing concerns about information collection practices. For all their faults, though, privacy policies remain the single most important source of information for users to attempt to learn how companies collect, use, and share data. Likewise, these policies form the basis for the self-regulatory notice and choice framework that is designed and promoted as a replacement for regulation. The underlying value and legitimacy of notice and choice depends, however, on the ability of users to understand privacy policies. This paper investigates the differences in interpretation among expert, knowledgeable, and typical users and explores whether those groups can understand the practices described in privacy policies at a level sufficient to support rational decision-making. The paper seeks to fill an important gap in the understanding of privacy policies through primary research on user interpretation and to inform the development of technologies combining natural language processing, machine learning and crowdsourcing for policy interpretation and summarization. For this research, we recruited a group of law and public policy graduate students at Fordham University, Carnegie Mellon University, and the University of Pittsburgh (“knowledgeable users”) and presented these law and policy researchers with a set of privacy policies from companies in the e-commerce and news & entertainment industries. We asked them nine basic questions about the policies’ statements regarding data collection, data use, and retention. We then presented the same set of policies to a group of privacy experts and to a group of non-expert users. The findings show areas of common understanding across all groups for certain data collection and deletion practices, but also demonstrate very important discrepancies in the interpretation of privacy policy language, particularly with respect to data sharing. The discordant interpretations arose both within groups and between the experts and the two other groups. The presence of these significant discrepancies has critical implications. First, the common understandings of some attributes of described data practices mean that semi-automated extraction of meaning from website privacy policies may be able to assist typical users and improve the effectiveness of notice by conveying the true meaning to users. However, the disagreements among experts and disagreement between experts and the other groups reflect that ambiguous wording in typical privacy policies undermines the ability of privacy policies to effectively convey notice of data practices to the general public. The results of this research will, consequently, have significant policy implications for the construction of the notice and choice framework and for the US reliance on this approach. The gap in interpretation indicates that privacy policies may be misleading the general public and that those policies could be considered legally unfair and deceptive. And, where websites are not effectively conveying privacy policies to consumers in a way that a “reasonable person” could, in fact, understand the policies, “notice and choice” fails as a framework. Such a failure has broad international implications since websites extend their reach beyond the United States

Sleep, emotional and behavioral difficulties in children and adolescents.

Links between sleep and psychopathology are complex and likely bidirectional. Sleep problems and alteration of normal sleep patterns have been identified in major forms of child psychopathology including anxiety, depression and attention disorders as well as symptoms of difficulties in the full range. This review summarizes some key findings with regard to the links between sleep and associated difficulties in childhood and adolescence. It then proposes a selection of possible mechanisms underlying some of these associations. Suggestions for future research include the need to 1) use multi-methods to assess sleep; 2) measure sleep in large-scale studies; 3) conduct controlled experiments to further establish the effects of sleep variations on emotional and behavioral difficulties; 4) take an interdisciplinary approach to further understand the links between sleep and associated difficulties

Survey of micrometeorological parameters within a forest canopy at Fort Polk, Louisiana, A

CER80-81WZS-FWL-WEM44.Includes bibliographical references (page 44).February 1982.A field investigation of micrometeorological parameters inside and above a forest canopy at Fort Polk, Louisiana, was conducted in conjunction with the Atmospheric Sciences Laboratory Dusty Infrared Test IIIA. The three orthogonal components of the wind, ory- and wet-bulb temperatures and total solar radiation were measured inside this forest canopy by means of an instrumented meteorological tower. In addition, turbulence inside the forest canopy was monitored by means of hot-wire anemometers. Tethersonde balloon sounding above the forest canopy was further performed. The meteorological data was reduced by means of three different statistical methods. Single sample period values, one-minute sample averages and sequential sample values were computed. The latter two methods led to the construction of time series which can readily be used to perform advanced statistical analyses. Totals of 27 h 29 min of meteorological tower data and 2 h 50 min of balloon data were reduced. The results are presented in tabular form in 1422 tables and partially displayed in 1795 figures under separate cover in view of their large volume. Selected samples of the results are, however, presented herein. The results supply a data base for analyses of airflow in a forest canopy. Suggestions for future work of significance for mission-oriented cases and for modeling of airflow in a forest canopy are outlined.Contract DAAG29-76-D-0100 conducted for the U.S. Army Atmospheric Sciences Laboratory, White Sands Missile Range

A framework for applying natural language processing in digital health interventions

BACKGROUND: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. OBJECTIVE: This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. METHODS: We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopathology (including binge eating and purging behaviors) and improving body image. These users generated 37,228 intervention text snippets and exchanged 4285 user-coach messages, which were analyzed using the proposed model. RESULTS: We applied the framework to predict binge eating behavior, resulting in an area under the curve between 0.57 (when applied to new users) and 0.72 (when applied to new symptom reports of known users). In addition, initial evidence indicated that specific text features predicted the therapeutic outcome of reducing ED symptoms. CONCLUSIONS: The case study demonstrates the usefulness of a structured approach to text data analytics. NLP techniques improve the prediction of symptom changes in DHIs. We present a technical framework that can be easily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts

On the over-concentration problem of strong lensing clusters

Lambda cold dark matter paradigm predicts that galaxy clusters follow an universal mass density profile and fit a well defined mass-concentration relation, with lensing clusters being preferentially triaxial haloes elongated along the line of sight. Oddly, recent strong and weak lensing analyses of clusters with a large Einstein radius suggested those haloes to be highly over-concentrated. Here, we investigate what intrinsic shape and orientation an halo should have to account for both theoretical predictions and observations. We considered a sample of 10 strong lensing clusters. We first measured their elongation assuming a given mass-concentration relation. Then, for each cluster we found the intrinsic shape and orientation which are compatible with the inferred elongation and the measured projected ellipticity. We distinguished two groups. The first one (nearly one half) seems to be composed of outliers of the mass-concentration relation, which they would fit only if they were characterised by a filamentary structure extremely elongated along the line of sight, that is not plausible considering standard scenarios of structure formations. The second sample supports expectations of N-body simulations which prefer mildly triaxial lensing clusters with a strong orientation bias.Comment: 11 pages, 8 figures, in press on MNRA