Representation in Econometrics: A Historical Perspective

Measurement forms the substance of econometrics. This chapter outlines the history of econometrics from a measurement perspective - how have measurement errors been dealt with and how, from a methodological standpoint, did econometrics evolve so as to represent theory more adequately in relation to data? The evolution is organized in terms of four phases: 'theory and measurement', 'measurement and theory', 'measurement with theory' and 'measurement without theory'. The question of how measurement research has helped in the advancement of knowledge advance is discussed in the light of this history.Econometrics, History, Measurement error

Deep Learning for Real Time Crime Forecasting

Accurate real time crime prediction is a fundamental issue for public safety, but remains a challenging problem for the scientific community. Crime occurrences depend on many complex factors. Compared to many predictable events, crime is sparse. At different spatio-temporal scales, crime distributions display dramatically different patterns. These distributions are of very low regularity in both space and time. In this work, we adapt the state-of-the-art deep learning spatio-temporal predictor, ST-ResNet [Zhang et al, AAAI, 2017], to collectively predict crime distribution over the Los Angeles area. Our models are two staged. First, we preprocess the raw crime data. This includes regularization in both space and time to enhance predictable signals. Second, we adapt hierarchical structures of residual convolutional units to train multi-factor crime prediction models. Experiments over a half year period in Los Angeles reveal highly accurate predictive power of our models.Comment: 4 pages, 6 figures, NOLTA, 201

Effect of n-3 polyunsaturated fatty acid on gene expression of the critical enzymes involved in homocysteine metabolism

<p>Abstract</p> <p>Background</p> <p>Previous studies showed that plasma n-3 polyunsaturated fatty acid (PUFA) was negatively associated with plasma homocysteine (Hcy).</p> <p>Objective</p> <p>We investigated the regulatory effect of n-3 PUFA on mRNA expression of the critical genes encoding the enzymes involved in Hcy metabolism.</p> <p>Methods</p> <p>HepG2 cells were treated with docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), alpha-linolenic acid (ALA) respectively for 48 h. The cells were collected and total RNA was isolated. The mRNA expression levels of the genes were determined by using Real Time-PCR.</p> <p>Results</p> <p>Compared with controls, the mRNA expression levels of 5-methyltetrahydrofolate reductase (MTHFR) were significantly increased in the DHA group (p < 0.05) and ALA group (p < 0.05); Significantly down-regulated mRNA expression of methionine adenosyltransferase (MAT) was observed with the treatments compared with the controls; the level of MAT expression was significant lower in the DHA group than the ALA group (p < 0.05); Cystathionine-γ-lyase (CSE) expression was significantly increased in the DHA (p < 0.05) and EPA groups (p < 0.05) compared with control. No significant changes were shown in mRNA expression levels of S-adenosylhomocysteine hydrolases (SAHH), cystathionine β-synthase (CBS), and 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR).</p> <p>Conclusions</p> <p>Our results suggest that DHA up-regulates CSE and MTHFR mRNA expression and down-regulates MAT mRNA expression involved in Hcy metabolism.</p

Relationship auditing of the FMA ontology

The Foundational Model of Anatomy (FMA) ontology is a domain reference ontology based on a disciplined modeling approach. Due to its large size, semantic complexity and manual data entry process, errors and inconsistencies are unavoidable and might remain within the FMA structure without detection. In this paper, we present computable methods to highlight candidate concepts for various relation- ship assignment errors. The process starts with locating structures formed by transitive structural relationships (part_of, tributary_of, branch_of) and examine their assignments in the context of the IS-A hierarchy. The algorithms were designed to detect five major categories of possible incorrect relationship assignments: circular, mutually exclusive, redundant, inconsistent, and missed entries. A domain expert reviewed samples of these presumptive errors to confirm the findings. Seven thousand and fifty-two presumptive errors were detected, the largest proportion related to part_of relationship assignments. The results highlight the fact that errors are unavoidable in complex ontologies and that well designed algorithms can help domain experts to focus on concepts with high likelihood of errors and maximize their effort to ensure consistency and reliability. In the future similar methods might be integrated with data entry processes to offer real-time error detection

Impact of mesoscale eddy transfer heat uptake in an eddy-parameterizing ocean model

Using a set of experiments with an eddy-parameterizing ocean model, it is found that the strength of the Atlantic meridional overturning circulation (AMOC) intensifies with the decrease of the density-dependent mesoscale eddy transfer. However, the intensification is weaker than that suggested by simple scaling relationships previously applied. Perturbing the model control sea surface temperature (SST) to mimic its change in response to doubling of CO2, it is shown that the associated ocean heat uptake (OHU) increases and penetrates deeper with the decrease of the mesoscale eddy transfer. It is shown that the OHU correlates with the AMOC strength, and both these quantities are affected by the mesoscale eddy transfer. Passive tracer experiments in the ocean model provide a possible explanation for the finding in coupled-model climate simulations that the ocean heat uptake efficiency (OHUE) increases with the AMOC strength and decreases with the eddy energy generated from the mean state. It is also found that the OHU in the SST-perturbation experiments scales with the net downward advection of heat. The contribution of the AMOC to the downward heat flux is illustrated using a streamfunction in depth-temperature space