Coalitions and Cliques in the School Choice Problem

The school choice mechanism design problem focuses on assignment mechanisms matching students to public schools in a given school district. The well-known Gale Shapley Student Optimal Stable Matching Mechanism (SOSM) is the most efficient stable mechanism proposed so far as a solution to this problem. However its inefficiency is well-documented, and recently the Efficiency Adjusted Deferred Acceptance Mechanism (EADAM) was proposed as a remedy for this weakness. In this note we describe two related adjustments to SOSM with the intention to address the same inefficiency issue. In one we create possibly artificial coalitions among students where some students modify their preference profiles in order to improve the outcome for some other students. Our second approach involves trading cliques among students where those involved improve their assignments by waiving some of their priorities. The coalition method yields the EADAM outcome among other Pareto dominations of the SOSM outcome, while the clique method yields all possible Pareto optimal Pareto dominations of SOSM. The clique method furthermore incorporates a natural solution to the problem of breaking possible ties within preference and priority profiles. We discuss the practical implications and limitations of our approach in the final section of the article

Connectivity Based Characterization of Brain Function in Humans and Dogs

Functional magnetic resonance imaging (fMRI) has been widely used to infer brain function in both healthy and clinical populations. Here, we propose novel approaches for connectivity based characterization in both humans and dogs. In humans, these approaches have been applied for characterizing brain network alterations in Alzheimer’s disease (AD) patients. AD, which affects millions of elderly worldwide, is a neurodegenerative disorder with a long pre-morbid period such as mild cognitive impairment (MCI). Brain declines, both functional and structural, are inevitable with age. However, determining how and when the trajectories begin to deviate from healthy elderly individuals is a crucial step to effectively slow down the progression of the disease. Using resting-state fMRI, we first estimated Betweenness Centrality (BC) and a novel nodal characterization approach called Middlemen Power (MP) from directed network that characterize information flow. The directed network were derived from the following populations: Normal Control (NC), Early MCI (EMCI), Late MCI (LMCI) and AD. Our results demonstrate that MP detected more brain regions that progressively deteriorated from NC to EMCI to LMCI to AD, as compared to BC in directed networks. Also, BC did not identify a single node from undirected networks that significantly deteriorated. This demonstrates the MP may represent a more sensitive analytic tool for characterizing biomarkers in both directed and undirected networks. Most connectivity analyses have reported distributed decreases as well as increases in causal relationships among brain regions in MCI and AD. However, it is difficult to interpret these connectivity results because traditionally, our knowledge of brain function is anchored on regions and not connections. Therefore, we employed a novel approach for identifying focal directed connectivity deficits in AD compared to healthy controls. Two foci were identified, locus coeruleus (LC) in the brain stem and right orbitofrontal cortex (OFC). Corresponding disrupted connectivity network associated with the foci showed that the brainstem is the critical focus of disruption in AD. Our findings suggest that fMRI studies of AD, which have been largely cortico-centric, could in future investigate the role of brain stem in AD. Functional brain connectivity based on resting state fMRI has been shown to be correlated with human personality and behavior. In the third study, we sought to know whether capabilities and traits in dogs can be predicted from their resting state connectivity as in humans. We trained awake dogs to keep their head still inside a 3T MRI scanner while resting state fMRI data was acquired. Canine behavior was characterized by an integrated behavioral score. Functional scans and behavioral measures were acquired at three different time points (TPs). We hypothesized that the correlation between resting state FC in the dog brain and behavior measures would significantly change during their detection training process (from TP1 to TP2), and would maintain for the subsequent several months of detection work (from TP2 to TP3). To further study the resting state FC features that can predict the success of training, dogs at TP1 were divided into successful group and failure group. We observed a core brain network which showed relatively stable (with respect to time) patterns of interaction that were significantly stronger in the successful group compared to failure group and whose connectivity strength at TP1 predicted whether a given dog was eventually successful in becoming a detector dog. A second flexible peripheral network was observed whose changes in connectivity strength with detection training tracked corresponding changes in behavior. Our findings suggest that upon replication and refinement, fMRI-based resting state brain connectivity may assist in choosing dogs that are more easily trainable for performing detection tasks

School Choice as a One-Sided Matching Problem: Cardinal Utilities and Optimization

The school choice problem concerns the design and implementation of matching mechanisms that produce school assignments for students within a given public school district. Previously considered criteria for evaluating proposed mechanisms such as stability, strategyproofness and Pareto efficiency do not always translate into desirable student assignments. In this note, we explore a class of one-sided, cardinal utility maximizing matching mechanisms focused exclusively on student preferences. We adapt a well-known combinatorial optimization technique (the Hungarian algorithm) as the kernel of this class of matching mechanisms. We find that, while such mechanisms can be adapted to meet desirable criteria not met by any previously employed mechanism in the school choice literature, they are not strategyproof. We discuss the practical implications and limitations of our approach at the end of the article

GeoAir—A Novel Portable, GPS-Enabled, Low-Cost Air-Pollution Sensor: Design Strategies to Facilitate Citizen Science Research and Geospatial Assessments of Personal Exposure

The rapid evolution of air sensor technologies has offered enormous opportunities for community-engaged research by enabling citizens to monitor the air quality at any time and location. However, many low-cost portable sensors do not provide sufficient accuracy or are designed only for technically capable individuals by requiring pairing with smartphone applications or other devices to view/store air quality data and collect location data. This paper describes important design considerations for portable devices to ensure effective citizen engagement and reliable data collection for the geospatial analysis of personal exposure. It proposes a new, standalone, portable air monitor, GeoAir, which integrates a particulate matter (PM) sensor, volatile organic compound (VOC) sensor, humidity and temperature sensor, LTE-M and GPS module, Wi-Fi, long-lasting battery, and display screen. The preliminary laboratory test results demonstrate that the PM sensor shows strong performance when compared to a reference instrument. The VOC sensor presents reasonable accuracy, while further assessments with other types of VOC are needed. The field deployment and geo-visualization of the field data illustrate that GeoAir collects fine-grained, georeferenced air pollution data. GeoAir can be used by all citizens regardless of their technical proficiency and is widely applicable in many fields, including environmental justice and health disparity research

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

Measurements of the pp → ZZ production cross section and the Z → 4ℓ branching fraction, and constraints on anomalous triple gauge couplings at √s = 13 TeV

Four-lepton production in proton-proton collisions, pp -> (Z/gamma*)(Z/gamma*) -> 4l, where l = e or mu, is studied at a center-of-mass energy of 13 TeV with the CMS detector at the LHC. The data sample corresponds to an integrated luminosity of 35.9 fb(-1). The ZZ production cross section, sigma(pp -> ZZ) = 17.2 +/- 0.5 (stat) +/- 0.7 (syst) +/- 0.4 (theo) +/- 0.4 (lumi) pb, measured using events with two opposite-sign, same-flavor lepton pairs produced in the mass region 60 4l) = 4.83(-0.22)(+0.23) (stat)(-0.29)(+0.32) (syst) +/- 0.08 (theo) +/- 0.12(lumi) x 10(-6) for events with a four-lepton invariant mass in the range 80 4GeV for all opposite-sign, same-flavor lepton pairs. The results agree with standard model predictions. The invariant mass distribution of the four-lepton system is used to set limits on anomalous ZZZ and ZZ. couplings at 95% confidence level: -0.0012 < f(4)(Z) < 0.0010, -0.0010 < f(5)(Z) < 0.0013, -0.0012 < f(4)(gamma) < 0.0013, -0.0012 < f(5)(gamma) < 0.0013

Case report: Diversity of imaging in cardiac angiosarcoma: two cases with disparate enhancement and metabolic manifestations

Cardiac angiosarcoma, a rare and aggressive malignancy arising from endothelial cells, is difficult to diagnose owing to its nonspecific clinical symptoms and variable imaging features. Two cases of cardiac angiosarcoma (CA) are presented, each with different enhancement and metabolic patterns on imaging. Case 1: A 59-year-old man presented with chest tightness and lower extremity edema. Ultrasound and computed tomography (CT) imaging revealed a hypoechoic/hypodense, non-enhancing mass with pericardial thickening in the right atrium. Positron emission tomography (PET) showed minimal uptake and, given that the patient had elevated D-dimer and fibrinogen levels, a thrombus was initially suspected. However, surgical intervention ultimately led to a diagnosis of CA. Case 2: A 27-year-old man presented with dyspnea and cough. Both ultrasound and CT imaging revealed a mass in the right atrium, with mid-to-low echogenic/hypodense features, heterogeneous enhancement, and pericardial effusion, along with pericardial thickening. A PET scan showed a significant increase in radiotracer uptake within the mass, strongly suggestive of CA. Surgical intervention subsequently confirmed the diagnosis of CA. These two cases demonstrate the presence of distinct enhancement and metabolic patterns on imaging in primary CA and indicate the importance of considering a wide range of enhancement features and metabolic activities in the differential diagnosis of patients presenting with non-specific cardiac symptoms

Periodontal health: A national cross‐sectional study of knowledge, attitudes and practices for the public oral health strategy in China

Aim To assess the status of periodontal health knowledge, attitudes and practices (KAP) among Chinese adults. Materials and Methods A cross‐sectional study was conducted in a nationally representative sample of adults (N = 50,991) aged 20 years or older from ten provinces, autonomous regions, and municipalities. Percentages of Chinese adults with correct periodontal knowledge, positive periodontal attitudes, and practices were estimated. Multiple logistic regression analyses were used to examine the related factors. Results Less than 20% of Chinese adults were knowledgeable about periodontal disease. Very few (2.6%) of Chinese adults use dental floss ≥once a day and undergo scaling ≥once a year and visit a dentist (6.4%) in the case of gingival bleeding. Periodontal health KAP was associated with gender, age, body mass index, marital status, place of residence, education level, income, smoking status, and history of periodontal disease. Conclusions Periodontal health KAP are generally poor among the Chinese adult population. Community‐based health strategies to improve periodontal health KAP need to be implemented. Increasing knowledge of periodontal disease, the cultivation of correct practices in response to gingival bleeding, and the development of good habits concerning the use of dental floss and regular scaling should be public oral health priorities

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements