New York State 2009 NHTS Comparison Report

The U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel, with the most recent surveys being the 1995 Nationwide Personal Transportation Survey (NPTS) and the 2001 and 2009 National Household Travel Surveys (NHTS). The primary objective of these surveys is to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the socio-economic and demographic characteristics of the traveler and his/her household can be established. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State, NYDOT procured an additional sample of households in the 1995, 2001, and 2009 surveys. The comparisons drawn in this report compare the results from these NYS sampled households to the results from households drawn for the rest of the nation. Many of the differences between NYC counties and others in the state result from the striking differences in private vehicle ownership levels, with less than one in two NYC drivers and only 64% of NYC households owning a vehicle in 2009: versus 9 out of 10 drivers owning a vehicle, and between 1.5 and 2 vehicles owned per household, on the average, in the state's other metro areas. And this situation has changed very little over the past fourteen years covered by the three latest NPTS/NHTS surveys. While households in metro areas outside NYC do not own a vehicle largely due to income constraints, many households in NYC/Manhattan do not own a vehicle by choice. However, the statistics suggest that the mobility of zero-vehicle households in NYC/Manhattan is by no means deterred by the lack of a vehicle. While the private vehicle tripmaking rate of NYC residents was between one half and one third that in the state's other metro areas, and their daily VMT about half that of other metro areas, most of their daily travel needs were met by walking or by public transit. As a result, their daily trip-making rates remain consistent with those of vehicle-owning households when all modes of travel are considered. This again indicates that owning a vehicle or being a driver in NYC was less important for meeting a household's mobility needs than anywhere else in NYS. The high levels of public transit usage within NYC replace a great deal of automobile use, and this plus greater use of walk trips results in significantly lower travel generated carbon dioxide emissions per household in NYC than elsewhere in the state. In contrast, the comparatively limited level of public transit ridership in the state's smaller and medium sized metro areas places a much greater reliance on the privately owned vehicle, be it an automobile or the increasingly popular SUV

An Interpretable Machine Learning Framework to Understand Bikeshare Demand before and during the COVID-19 Pandemic in New York City

In recent years, bikesharing systems have become increasingly popular as affordable and sustainable micromobility solutions. Advanced mathematical models such as machine learning are required to generate good forecasts for bikeshare demand. To this end, this study proposes a machine learning modeling framework to estimate hourly demand in a large-scale bikesharing system. Two Extreme Gradient Boosting models were developed: one using data from before the COVID-19 pandemic (March 2019 to February 2020) and the other using data from during the pandemic (March 2020 to February 2021). Furthermore, a model interpretation framework based on SHapley Additive exPlanations was implemented. Based on the relative importance of the explanatory variables considered in this study, share of female users and hour of day were the two most important explanatory variables in both models. However, the month variable had higher importance in the pandemic model than in the pre-pandemic model

Off-Highway Gasoline Consuption Estimation Models Used in the Federal Highway Administration Attribution Process: 2008 Updates

This report is designed to document the analysis process and estimation models currently used by the Federal Highway Administration (FHWA) to estimate the off-highway gasoline consumption and public sector fuel consumption. An overview of the entire FHWA attribution process is provided along with specifics related to the latest update (2008) on the Off-Highway Gasoline Use Model and the Public Use of Gasoline Model. The Off-Highway Gasoline Use Model is made up of five individual modules, one for each of the off-highway categories: agricultural, industrial and commercial, construction, aviation, and marine. This 2008 update of the off-highway models was the second major update (the first model update was conducted during 2002-2003) after they were originally developed in mid-1990. The agricultural model methodology, specifically, underwent a significant revision because of changes in data availability since 2003. Some revision to the model was necessary due to removal of certain data elements used in the original estimation method. The revised agricultural model also made use of some newly available information, published by the data source agency in recent years. The other model methodologies were not drastically changed, though many data elements were updated to improve the accuracy of these models. Note that components in the Public Use of Gasoline Model were not updated in 2008. A major challenge in updating estimation methods applied by the public-use model is that they would have to rely on significant new data collection efforts. In addition, due to resource limitation, several components of the models (both off-highway and public-us models) that utilized regression modeling approaches were not recalibrated under the 2008 study. An investigation of the Environmental Protection Agency's NONROAD2005 model was also carried out under the 2008 model update. Results generated from the NONROAD2005 model were analyzed, examined, and compared, to the extent that is possible on the overall totals, to the current FHWA estimates. Because NONROAD2005 model was designed for emission estimation purposes (i.e., not for measuring fuel consumption), it covers different equipment populations from those the FHWA models were based on. Thus, a direct comparison generally was not possible in most sectors. As a result, NONROAD2005 data were not used in the 2008 update of the FHWA off-highway models. The quality of fuel use estimates directly affect the data quality in many tables published in the Highway Statistics. Although updates have been made to the Off-Highway Gasoline Use Model and the Public Use Gasoline Model, some challenges remain due to aging model equations and discontinuation of data sources

Discovery and characterization of medaka miRNA genes by next generation sequencing platform

Background MicroRNAs (miRNAs) are endogenous non-protein-coding RNA genes which exist in a wide variety of organisms, including animals, plants, virus and even unicellular organisms. Medaka (Oryzias latipes) is a useful model organism among vertebrate animals. However, no medaka miRNAs have been investigated systematically. It is beneficial to conduct a genome-wide miRNA discovery study using the next generation sequencing (NGS) technology, which has emerged as a powerful sequencing tool for high-throughput analysis. Results In this study, we adopted ABI SOLiD platform to generate small RNA sequence reads from medaka tissues, followed by mapping these sequence reads back to medaka genome. The mapped genomic loci were considered as candidate miRNAs and further processed by a support vector machine (SVM) classifier. As result, we identified 599 novel medaka pre-miRNAs, many of which were found to encode more than one isomiRs. Besides, additional minor miRNAs (also called miRNA star) can be also detected with the improvement of sequencing depth. These quantifiable isomiRs and minor miRNAs enable us to further characterize medaka miRNA genes in many aspects. First of all, many medaka candidate pre-miRNAs position close to each other, forming many miRNA clusters, some of which are also conserved across other vertebrate animals. Secondly, during miRNA maturation, there is an arm selection preference of mature miRNAs within precursors. We observed the differences on arm selection preference between our candidate pre-miRNAs and their orthologous ones. We classified these differences into three categories based on the distribution of NGS reads. Finally, we also investigated the relationship between conservation status and expression level of miRNA genes. We concluded that the evolutionally conserved miRNAs were usually the most abundant ones. Conclusions Medaka is a widely used model animal and usually involved in many biomedical studies, including the ones on development biology. Identifying and characterizing medaka miRNA genes would benefit the studies using medaka as a model organism

Supply Chain Based Solution to Prevent Fuel Tax Evasion: Proof of Concept Final Report

The goal of this research was to provide a proof-of-concept (POC) system for preventing non-taxable (non-highway diesel use) or low-taxable (jet fuel) petrochemical products from being blended with taxable fuel products and preventing taxable fuel products from cross-jurisdiction evasion. The research worked to fill the need to validate the legitimacy of individual loads, offloads, and movements by integrating and validating, on a near-real-time basis, information from global positioning system (GPS), valve sensors, level sensors, and fuel-marker sensors

Synthesis and Anticancer Activities of 4-[(Halophenyl)diazenyl]phenol and 4-[(Halophenyl)diazenyl]phenyl Aspirinate Derivatives against Nasopharyngeal Cancer Cell Lines

Aspirin and azo derivatives have been widely studied and have drawn considerable attention due to diverse biological activities. In this study, a series of 4-[(halophenyl)diazenyl]phenyl aspirinate derivatives were synthesized from the reaction of aspirin with 4-[(halophenyl)diazenyl]phenol via esterification, in the presence of DCC/DMAP in DCM with overall yield of 45–54%. 4- [(Halophenyl)diazenyl]phenol was prepared prior to esterification fromcoupling reaction of aniline derivatives and phenol in basic solution. All compounds were characterized using elemental analysis, FTIR, and 1H and 13C NMR spectroscopies. All compounds were screened for their anticancer activities against nasopharyngeal cancer (NPC) HK-1 cell lines and the viability of cultured cells was determined by MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxylmethoxylphenyl)-2-(4-sulfophenyl)-2H-tetrazolium]- based colorimetric assay. 4-[(E)-(Fluorophenyl)diazenyl]phenol showed the highest anticancer activity against NPC HK-1 cell lines compared to other synthesized compounds. 4-[(Halophenyl)diazenyl]phenyl aspirinate showed low cytotoxicity against NPC HK-1 cell lines compared to 4-[(halophenyl)diazenyl]phenol but better anticancer activity than aspirin alone

The Atacama Large Millimeter/submillimeter Array (ALMA) Band-1 Receiver

The Atacama Large Millimeter/submillimeter Array(ALMA) Band 1 receiver covers the 35-50 GHz frequency band. Development of prototype receivers, including the key components and subsystems has been completed and two sets of prototype receivers were fully tested. We will provide an overview of the ALMA Band 1 science goals, and its requirements and design for use on the ALMA. The receiver development status will also be discussed and the infrastructure, integration, evaluation of fully-assembled band 1 receiver system will be covered. Finally, a discussion of the technical and management challenges encountered will be presented