Does consumer sentiment predict regional consumption?

This paper tests the ability of consumer sentiment to predict retail spending at the state level. The results here suggest that, although there is a significant relationship between sentiment measures and retail sales growth in several states, consumer sentiment exhibits only modest predictive power for future changes of retail spending. Measures of consumer sentiment, however, contain additional explanatory power aside from the information available in other indicators. We also find that by restricting our attention to fluctuations in retail sales that occur at the business cycle frequency we can uncover a significant relationship between consumer sentiment and retail sales growth in many additional states. In light of these results, we conclude that the practical value of sentiment indices to forecast consumer spending at the state level is, at best, limited.Consumer behavior ; Consumption (Economics) ; Economic indicators

Indirect measures of learning transfer between real and virtual environments

This paper reports on research undertaken to determine the effectiveness of a 3D simulation environment used to train mining personnel in emergency evacuation procedures, designated the Fires in Underground Mines Evacuation Simulator (FUMES). Owing to the operational constraints of the mining facility, methods for measuring learning transfer were employed which did not require real world performance evaluation. Transfer measures that examined simulator performance relative to real world experience, fidelity assessment, and appraisal of the training value of the platform were utilised. Triangulation of results across all three measures indicated the presence of learning transfer, suggesting the viability of indirect measures in instances where real world performance testing is not possible. Furthermore, these indirect measures of learning transfer also provided some insight as to the strengths and weaknesses of the simulation design, which could be used to inform the development of future versions of the product

Previously Unidentified Changes in Renal Cell Carcinoma Gene Expression Identified by Parametric Analysis of Microarray Data

BACKGROUND. Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. METHODS. We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. RESULTS. We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. CONCLUSIONS. The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell carcinogenesis. This highlights the need for rigorous statistical approaches in microarray studies.National Institutes of Healt

Multi-source self-calibration: Unveiling the microJy population of compact radio sources

Context. Very Long Baseline Interferometry (VLBI) data are extremely sensitive to the phase stability of the VLBI array. This is especially important when we reach {\mu}Jy r.m.s. sensitivities. Calibration using standard phase referencing techniques is often used to improve the phase stability of VLBI data but the results are often not optimal. This is evident in blank fields that do not have in-beam calibrators. Aims. We present a calibration algorithm termed Multi-Source Self-Calibration (MSSC) which can be used after standard phase referencing on wide-field VLBI observations. This is tested on a 1.6 GHz wide-field VLBI data set of the Hubble Deep Field-North and the Hubble Flanking Fields. Methods. MSSC uses multiple target sources detected in the field via standard phase referencing techniques and modifies the visibili- ties so that each data set approximates to a point source. These are combined to increase the signal to noise and permit self-calibration. In principle, this should allow residual phase changes caused by the troposphere and ionosphere to be corrected. By means of faceting, the technique can also be used for direction dependent calibration. Results. Phase corrections, derived using MSSC, were applied to a wide-field VLBI data set of the HDF-N comprising of 699 phase centres. MSSC was found to perform considerably better than standard phase referencing and single source self-calibration. All detected sources exhibited dramatic improvements in dynamic range. Using MSSC, one source reached the detection threshold taking the total detected sources to twenty. 60% of these sources can now be imaged with uniform weighting compared to just 45% with standard phase referencing. The Parseltongue code which implements MSSC has been released and made publicly available to the astronomical community (https://github.com/jradcliffe5/multi_self_cal).Comment: 7 pages, 4 figures, accepted to A&

LCANets++: Robust Audio Classification using Multi-layer Neural Networks with Lateral Competition

Audio classification aims at recognizing audio signals, including speech commands or sound events. However, current audio classifiers are susceptible to perturbations and adversarial attacks. In addition, real-world audio classification tasks often suffer from limited labeled data. To help bridge these gaps, previous work developed neuro-inspired convolutional neural networks (CNNs) with sparse coding via the Locally Competitive Algorithm (LCA) in the first layer (i.e., LCANets) for computer vision. LCANets learn in a combination of supervised and unsupervised learning, reducing dependency on labeled samples. Motivated by the fact that auditory cortex is also sparse, we extend LCANets to audio recognition tasks and introduce LCANets++, which are CNNs that perform sparse coding in multiple layers via LCA. We demonstrate that LCANets++ are more robust than standard CNNs and LCANets against perturbations, e.g., background noise, as well as black-box and white-box attacks, e.g., evasion and fast gradient sign (FGSM) attacks.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

The role of household chaos in understanding relations between early poverty and children’s academic achievement

The following prospective longitudinal study used an epidemiological sample (N = 1,236) to consider the potential mediating role of early cumulative household chaos (6–58 months) on associations between early family income poverty (6 months) and children's academic achievement in kindergarten. Two dimensions of household chaos, disorganization and instability, were examined as mediators. Results revealed that, in the presence of household disorganization (but not instability) and relevant covariates, income poverty was no longer directly related to academic achievement. Income poverty was, however, positively related to household disorganization, which was, in turn, associated with lower academic achievement. Study results are consistent with previous research indicating that household chaos conveys some of the adverse longitudinal effects of income poverty on children's outcomes and extend previous findings specifically to academic achievement in early childhood

Ticks and Tick-Borne Pathogens in Domestic Animals, Wild Pigs, and Off-Host Environmental Sampling in Guam, USA

Background: Guam, a United States of America (USA) island territory in the Pacific Ocean, is known to have large populations of ticks; however, it is unclear what the risk is to wildlife and humans living on the island. Dog (Canis familiaris), cat (Felis catus), and wild pig (Sus scrofa) sentinels were examined for ticks, and environmental sampling was conducted to determine the ticks present in Guam and the prevalence of tick-borne pathogens in hosts. Methods and Results: From March 2019-November 2020, ticks were collected from environmental sampling, dogs, cats, and wild pigs. Blood samples were also taken from a subset of animals. A total of 99 ticks were collected from 27 environmental samples and all were Rhipicephalus sanguineus, the brown dog tick. Most ticks were collected during the dry season with an overall sampling success rate of 63% (95% CI: 42.4–80.6). 6,614 dogs were examined, and 12.6% (95% CI: 11.8–13.4) were infested with at least one tick. One thousand one hundred twelve cats were examined, and six (0.54%; 95% CI: 0.20–1.1) were found with ticks. Sixty-four wild pigs were examined and 17.2% (95% CI: 9.5–27.8) had ticks. In total, 1,956 ticks were collected and 97.4% of ticks were R. sanguineus. A subset of R. sanguineus were determined to be the tropical lineage. The other tick species found were Rhipicephalus microplus (0.77%), Amblyomma breviscutatum (0.77 %), and a Haemaphysalis sp. (0.51%). Blood samples from 136 dogs, four cats, and 64 wild pigs were tested using polymerase chain reaction (PCR) and DNA sequencing methods. Five different tick-borne pathogens with the following prevalences were found in dogs: Anaplasma phagocytophilum 5.9% (95% CI: 2.6–11.3); Anaplasma platys 19.1% (95% CI: 12.9–26.7); Babesia canis vogeli 8.8% (95% CI: 4.6–14.9); Ehrlichia canis 12.5% (95% CI: 7.5–19.3); Hepatozoon canis 14.7% (95% CI: 9.2–28.8). E. canis was detected in one cat, and no tick-borne pathogens were detected in wild pigs. Overall, 43.4% (95% CI: 34.9–52.1) of dogs had at least one tick-borne pathogen. Serological testing for antibodies against Ehrlichia spp. and Anaplasma spp. showed prevalences of 14.7% (95% CI: 9.2–28.8) and 31.6% (95% CI: 23.9–40), respectively. Conclusion: Four different tick species were found in Guam to include a Haemaphysalis sp., which is a previously unreported genus for Guam. Dogs with ticks have a high prevalence of tick-borne pathogens which makes them useful sentinels

Cultural values and wellness of Native American high school students

Research has suggested that cultural conflicts and the process of acculturation contribute to feelings of boredom, anxiety, depression, isolation, stress, self-doubt, alienation, and rejection in Native American students. These factors also have a negative impact on identity development and wellness of these students. The problem addressed in this study was the relationship between cultural value orientation, level of acculturation, and wellness among Native American high school students. To fully explore this relationship, some comparison to non-Native American high school students was necessary. Exploration of the three variables of cultural value orientation, level of acculturation, and wellness was to include both a between-group value comparison of Native American and non-Native American students and a within-group comparison of Native American students on the three variables

Exploration of cloud computing late start LDRD #149630 : Raincoat. v. 2.1.

This report contains documentation from an interoperability study conducted under the Late Start LDRD 149630, Exploration of Cloud Computing. A small late-start LDRD from last year resulted in a study (Raincoat) on using Virtual Private Networks (VPNs) to enhance security in a hybrid cloud environment. Raincoat initially explored the use of OpenVPN on IPv4 and demonstrates that it is possible to secure the communication channel between two small 'test' clouds (a few nodes each) at New Mexico Tech and Sandia. We extended the Raincoat study to add IPSec support via Vyatta routers, to interface with a public cloud (Amazon Elastic Compute Cloud (EC2)), and to be significantly more scalable than the previous iteration. The study contributed to our understanding of interoperability in a hybrid cloud