{"component": "clause", "props": {"groups": [{"size": 13, "snippet_links": [{"key": "air-quality", "type": "definition", "offset": [59, 70]}, {"key": "school-buses", "type": "clause", "offset": [82, 94]}], "snippet": "School bus fleets are aging, and our communities have poor air quality. Replacing school buses with zero emission school buses will address both of these issues.", "samples": [{"hash": "ki5ePsC9eqU", "uri": "/contracts/ki5ePsC9eqU#problem-statement", "label": "Grant Amendment", "score": 29.4156837463, "published": true}, {"hash": "7nCXvBm95Z9", "uri": "/contracts/7nCXvBm95Z9#problem-statement", "label": "Grant Agreement", "score": 29.0254669189, "published": true}, {"hash": "4Nm1Zgu7hNy", "uri": "/contracts/4Nm1Zgu7hNy#problem-statement", "label": "Grant Agreement", "score": 28.961107254, "published": true}], "hash": "9bb4abce6a6c25da7a906cd2e20fc98a", "id": 1}, {"size": 2, "snippet_links": [{"key": "school-district", "type": "clause", "offset": [107, 122]}, {"key": "personal-safety", "type": "clause", "offset": [183, 198]}, {"key": "lack-of", "type": "clause", "offset": [268, 275]}, {"key": "access-to", "type": "definition", "offset": [308, 317]}, {"key": "these-conditions", "type": "clause", "offset": [425, 441]}, {"key": "for-students", "type": "clause", "offset": [464, 476]}, {"key": "ability-to", "type": "clause", "offset": [644, 654]}, {"key": "participate-in", "type": "definition", "offset": [655, 669]}, {"key": "bus-driver", "type": "definition", "offset": [738, 748]}, {"key": "elementary-schools", "type": "clause", "offset": [877, 895]}, {"key": "knowledge-of", "type": "definition", "offset": [980, 992]}, {"key": "transportation-options", "type": "clause", "offset": [993, 1015]}, {"key": "traffic-safety", "type": "clause", "offset": [1191, 1205]}, {"key": "summary-data", "type": "definition", "offset": [1260, 1272]}, {"key": "in-the-city", "type": "definition", "offset": [1383, 1394]}, {"key": "transportation-system", "type": "definition", "offset": [1397, 1418]}, {"key": "for-example", "type": "clause", "offset": [1420, 1431]}, {"key": "other-parts", "type": "clause", "offset": [1568, 1579]}, {"key": "air-quality", "type": "definition", "offset": [1694, 1705]}, {"key": "community-resources", "type": "definition", "offset": [1718, 1737]}, {"key": "communities-of-color", "type": "definition", "offset": [1820, 1840]}, {"key": "limited-english-proficiency", "type": "clause", "offset": [1882, 1909]}, {"key": "college-graduate", "type": "definition", "offset": [1977, 1993]}, {"key": "median-income", "type": "clause", "offset": [2105, 2118]}, {"key": "number-of", "type": "clause", "offset": [2320, 2329]}, {"key": "high-school", "type": "definition", "offset": [2405, 2416]}, {"key": "current-activities", "type": "clause", "offset": [2426, 2444]}, {"key": "associated-agencies", "type": "definition", "offset": [2449, 2468]}, {"key": "service-system", "type": "definition", "offset": [2538, 2552]}, {"key": "community-response", "type": "clause", "offset": [2692, 2710]}, {"key": "dropout-rate", "type": "definition", "offset": [2859, 2871]}, {"key": "services-for", "type": "clause", "offset": [3085, 3097]}, {"key": "community-members", "type": "definition", "offset": [3117, 3134]}, {"key": "community-schools", "type": "clause", "offset": [3171, 3188]}, {"key": "health-services", "type": "definition", "offset": [3306, 3321]}, {"key": "in-addition-to", "type": "clause", "offset": [3451, 3465]}, {"key": "will-provide", "type": "clause", "offset": [3518, 3530]}, {"key": "employment-opportunities", "type": "definition", "offset": [3573, 3597]}], "snippet": "A. Describe the problem(s) this project will try to impact: As students walk & roll to schools in Parkrose School District (PSD), they encounter several barriers & hazards, including personal safety, unsafe driver behavior, inadequate biking & walking infrastructure, lack of multimodal knowledge, & limited access to transit. Additionally, Parkrose families have endured increased hate & bias, bullying, & gun violence. All these conditions make it uncomfortable for students to walk/roll to/from school & around their neighborhoods. For some students these barriers/hazards have also increased absenteeism. For others, it has decreased their ability to participate in after-school programming. Even before the pandemic, PSD experienced bus driver shortages. The pandemic has amplified the shortage & more students are left with limited options for their school commute. At 2 elementary schools, many students no longer receive bussing. Unfortunately, some families & youth lack knowledge of transportation options; & if they do know about options, they may not be familiar with how to use the modes or which routes feel safe. Parkrose students need opportunities to learn & practice basic traffic safety skills & how to use our multimodal system.\nB. Provide summary data about the problem(s): The Parkrose School District is in East Portland, where deep systemic disparities exist in the city's transportation system. For example, pedestrians in E. Portland, especially East of I-205 are more than twice as likely to be killed in a traffic crash than pedestrians in other parts of Portland. East Portland generally, bears the burden of historic underinvestment in infrastructure and has poor air quality and limited community resources. This is especially troubling because E. Portland also has high concentrations of communities of color, low-income people, and communities with limited English proficiency (LEP). Among the 94 Portland neighborhoods, Parkrose ranks 82nd in college graduate rates, social vulnerability and English proficiency, and 61% of household incomes earning less than the city\u2019s median income ($75,000). Portland\u2019s gun violence has gone up exponentially from 2019 through 2021 \u2013 at 144% increase in its homicide count and a 241% increase in non-fatal shootings that resulted in injury. A large number of these shootings occurred in the Parkrose neighborhood, and nearby Parkrose High School.\nC. List current activities and associated agencies already involved in solving the problem(s): Elevate Oregon & the SUN Service System (SUN) are both well- established, supportive organizations for the Parkrose community. Elevate Oregon was founded in 2010 as a principled, community response to identified inequities & disparities in access, opportunities, & outcomes for at-risk youth. Elevate began its work in PSD to address the growing dropout rate through a mentoring & curriculum model designed to promote achievement, leadership, & self-sufficiency. SUN leads to educational success & family self-sufficiency through an integrated network of social & support services for youth, families, & community members. Within the SUN Service System, SUN Community Schools are school-based delivery sites for a comprehensive set of services: educational, enrichment, recreational, social & health services. Through the Academy, elementary & middle schoolers will learn a variety of safety skills, such as pedestrian & personal safety. In addition to important life & traffic safety skills, the Academy will provide leadership, school credit, & volunteer or employment opportunities for participants. These opportunities can also be an important resume builder for college or careers.", "samples": [{"hash": "9YNWIUf9v86", "uri": "/contracts/9YNWIUf9v86#problem-statement", "label": "Transportation Safety Office Grant Agreement", "score": 31.6559848785, "published": true}, {"hash": "laET9QJLX5y", "uri": "/contracts/laET9QJLX5y#problem-statement", "label": "Transportation Safety Office Grant Agreement", "score": 31.4057731628, "published": true}], "hash": "ec10cbb38b6e0c312f1e8161ed222965", "id": 8}, {"size": 6, "snippet_links": [{"key": "policy-section", "type": "definition", "offset": [129, 143]}, {"key": "large-scale", "type": "definition", "offset": [164, 175]}, {"key": "network-operators", "type": "definition", "offset": [238, 255]}, {"key": "the-risk", "type": "definition", "offset": [324, 332]}, {"key": "caused-by", "type": "clause", "offset": [333, 342]}, {"key": "the-mobile", "type": "clause", "offset": [416, 426]}, {"key": "services-for", "type": "clause", "offset": [606, 618]}, {"key": "users-of-the", "type": "clause", "offset": [623, 635]}, {"key": "other-devices", "type": "clause", "offset": [860, 873]}, {"key": "service-platform", "type": "clause", "offset": [890, 906]}, {"key": "end-customers", "type": "definition", "offset": [933, 946]}, {"key": "device-usage", "type": "clause", "offset": [1017, 1029]}, {"key": "mobile-networks", "type": "clause", "offset": [1148, 1163]}, {"key": "adhere-to", "type": "clause", "offset": [1164, 1173]}, {"key": "basic-principles", "type": "clause", "offset": [1179, 1195]}, {"key": "to-ensure", "type": "clause", "offset": [1282, 1291]}, {"key": "device-performance", "type": "clause", "offset": [1301, 1319]}, {"key": "in-network", "type": "clause", "offset": [1412, 1422]}], "snippet": "1.1. This section, Problem Statement, is included for informational and contextual purposes to support the Network Communication Policy section.\n1.2. The predicted large scale growth of IoT devices will create major challenges for mobile network operators. One major challenge that mobile network operators must overcome is the risk caused by the mass deployment of inefficient, insecure or defective IoT devices on the mobile network operators\u2019 [domestic and roaming] networks. When deployed on a mass scale such devices can cause network signaling traffic to increase exponentially which impacts network services for all users of the mobile network. In the worst cases the mass deployment of such IoT devices can disable a mobile network completely.\n1.3. IoT devices overusing the mobile network can affect not only the devices causing the incident but also other devices on the same IoT service platform or those devices of other end customers.\n1.4. Network signaling resources are dimensioned assuming an overall device usage profile with a sensible balance between traffic and signaling needs. It is therefore important that IoT devices using mobile networks adhere to some basic principles before they can be safely connected to mobile networks.\n1.5. Good design is essential to ensure that IoT Device performance is optimized and to prevent failure mechanisms creating runaway situations which may result in network overload.", "samples": [{"hash": "6N1gadg6TUb", "uri": "/contracts/6N1gadg6TUb#problem-statement", "label": "Terms and Conditions", "score": 32.0480155945, "published": true}, {"hash": "cu8FEeJIR9z", "uri": "/contracts/cu8FEeJIR9z#problem-statement", "label": "Terms and Conditions", "score": 31.5881385803, "published": true}, {"hash": "5YVaRE2NOy9", "uri": "/contracts/5YVaRE2NOy9#problem-statement", "label": "Terms and Conditions", "score": 30.9558067322, "published": true}], "hash": "6f13189be31ed8afa86af070b2b61ece", "id": 2}, {"size": 4, "snippet_links": [{"key": "preliminary-tests", "type": "clause", "offset": [10, 27]}, {"key": "total-volume", "type": "clause", "offset": [114, 126]}, {"key": "the-vehicle", "type": "clause", "offset": [642, 653]}, {"key": "any-time-period", "type": "clause", "offset": [682, 697]}, {"key": "actual-distribution", "type": "definition", "offset": [734, 753]}, {"key": "the-research", "type": "clause", "offset": [1165, 1177]}, {"key": "good-working-condition", "type": "definition", "offset": [1253, 1275]}, {"key": "to-serve", "type": "definition", "offset": [1276, 1284]}, {"key": "representatives-of", "type": "clause", "offset": [1288, 1306]}, {"key": "accuracy-of-the", "type": "clause", "offset": [1377, 1392]}, {"key": "data-quality", "type": "clause", "offset": [1596, 1608]}, {"key": "heavy-weights", "type": "clause", "offset": [1617, 1630]}, {"key": "volume-data", "type": "definition", "offset": [1862, 1873]}, {"key": "very-important", "type": "definition", "offset": [1874, 1888]}, {"key": "performance-monitoring", "type": "definition", "offset": [1910, 1932]}, {"key": "vehicle-detection", "type": "clause", "offset": [2085, 2102]}, {"key": "advantages-and-disadvantages", "type": "clause", "offset": [2328, 2356]}, {"key": "vehicle-speed", "type": "definition", "offset": [2589, 2602]}, {"key": "vehicle-length", "type": "clause", "offset": [2607, 2621]}, {"key": "basis-of", "type": "clause", "offset": [2629, 2637]}, {"key": "the-information", "type": "clause", "offset": [2638, 2653]}, {"key": "cost-of", "type": "clause", "offset": [2754, 2761]}, {"key": "damaged-or-broken", "type": "clause", "offset": [2829, 2846]}, {"key": "distributions-and", "type": "clause", "offset": [3012, 3029]}, {"key": "in-practice", "type": "definition", "offset": [3244, 3255]}, {"key": "traffic-volume", "type": "clause", "offset": [3489, 3503]}, {"key": "the-method", "type": "definition", "offset": [3522, 3532]}, {"key": "large-truck", "type": "definition", "offset": [3557, 3568]}, {"key": "the-fact", "type": "clause", "offset": [3625, 3633]}], "snippet": "Given the preliminary tests performed above, the problems of dual-loop data could be summarized as follows: \u2022 The total volume of vehicles detected and assigned to bins by the dual-loop system for a given time interval was consistently lower than the total volume of vehicles detected by the corresponding single loops for the same interval. In other words, the volume of classified vehicles was consistently lower than the volume of actual vehicles detected, reflecting vehicles that were dropped by the dual-loop system during the classification step. \u2022 The existing dual-loop detector systems had problems measuring vehicle lengths; hence the vehicle bin volume distribution for any time period might differ significantly from the actual distribution. Therefore, the detected trucking information did not reflect the true trucking activities during that period at that location. This study quantitatively evaluated the accuracy of WSDOT dual-loop data using video ground truth data and investigated the types and potential causes of dual-loop data inaccuracies. It also sought and recommended methods to improve the quality of dual- loop data. The objectives of the research are summarized below: \u2022 Identify dual-loop detectors in the FLOW system in good working condition to serve as representatives of WSDOT dual-loop detectors for analysis. \u2022 Quantitatively evaluate the accuracy of the sample dual-loop measurements of vehicle volumes and vehicle classifications. \u2022 Identify and interpret the potential causes of dual-loop data inaccuracies. \u2022 Recommend strategies for improving dual-loop data quality. Due to heavy weights and large turning radii, truck movements have characteristics very different from those of passenger cars and smaller vehicles. These differences make the collection of reliable and continuous vehicle classification data and truck volume data very important for reliable freeway performance monitoring. Of course, such data are critical to the specific monitoring of regional freight movements. To date, several different technologies have been used for vehicle detection and classification. These include single-loop detectors, dual-loop detectors, classification with vehicle acoustic signatures, video imaging systems, and laser and night vision systems. Each of these technologies has its own advantages and disadvantages. Dual-loop detectors are often used to collect vehicle classification data. As previously described, a dual-loop detector consists of two consecutive single loops that are only a few feet apart. An algorithm is applied to calculate vehicle speed and vehicle length on the basis of the information that these two single loops provide. The inductive loops are relatively cheap to install but at the cost of some inconvenience, as traffic has to be stopped. The loops can be damaged or broken and, thus, become unreliable. Vehicle classification can also be achieved using single-loop detectors. \u2587\u2587\u2587\u2587 and \u2587\u2587\u2587\u2587\u2587 (\u2587\u2587\u2587\u2587 and \u2587\u2587\u2587\u2587\u2587 2000a) analyzed vehicle-length distributions and developed a nearest-neighbor algorithm to classify vehicles into a short-vehicle (SV) category and a large-truck (LT) category by using only single-loop measurements. This research development is especially useful in practice because most highway systems are, to date, equipped only with single-loop detectors. Comparison of the estimated large-truck volumes with dual-loop observed large-truck volumes showed that this algorithm worked well, especially when traffic volume was low. However, the method tended to underestimate large truck volumes under heavy traffic conditions. This was due to the fact that when traffic volume is heavy, speed is very unstable, and the uniform speed assumption, on which the algorithm is based, is violated.", "samples": [{"hash": "hW8jT330yvS", "uri": "/contracts/hW8jT330yvS#problem-statement", "label": "Research Report Agreement", "score": 19.0, "published": true}, {"hash": "5mVekmrbphR", "uri": "/contracts/5mVekmrbphR#problem-statement", "label": "Research Report Agreement", "score": 19.0, "published": true}, {"hash": "262LVhKVa1C", "uri": "/contracts/262LVhKVa1C#problem-statement", "label": "Research Report Agreement", "score": 19.0, "published": true}], "hash": "d64e23fec6c75553cf02ebf3cbd82391", "id": 3}, {"size": 3, "snippet_links": [{"key": "project-proposal", "type": "definition", "offset": [32, 48]}, {"key": "bank-of", "type": "definition", "offset": [64, 71]}, {"key": "contained-in", "type": "definition", "offset": [87, 99]}, {"key": "is-likely", "type": "definition", "offset": [165, 174]}, {"key": "the-phase", "type": "clause", "offset": [280, 289]}, {"key": "the-late", "type": "clause", "offset": [363, 371]}, {"key": "per-year", "type": "definition", "offset": [539, 547]}, {"key": "the-future", "type": "clause", "offset": [608, 618]}, {"key": "the-annual", "type": "clause", "offset": [728, 738]}, {"key": "loss-rate", "type": "definition", "offset": [748, 757]}, {"key": "the-fact", "type": "clause", "offset": [985, 993]}, {"key": "the-opportunity", "type": "clause", "offset": [1173, 1188]}, {"key": "based-on", "type": "definition", "offset": [1289, 1297]}, {"key": "annual-emissions", "type": "definition", "offset": [1427, 1443]}, {"key": "the-us", "type": "clause", "offset": [1453, 1460]}, {"key": "the-model", "type": "clause", "offset": [1741, 1750]}, {"key": "industrial-sector", "type": "definition", "offset": [1926, 1943]}, {"key": "metric-tons", "type": "definition", "offset": [1981, 1992]}, {"key": "for-california", "type": "clause", "offset": [2042, 2056]}, {"key": "per-annum", "type": "definition", "offset": [2199, 2208]}, {"key": "air-resources-board", "type": "definition", "offset": [2264, 2283]}, {"key": "the-total", "type": "clause", "offset": [2334, 2343]}, {"key": "global-warming-potential", "type": "definition", "offset": [2357, 2381]}, {"key": "greenhouse-gases", "type": "definition", "offset": [2382, 2398]}, {"key": "remaining-banks", "type": "definition", "offset": [2438, 2453]}, {"key": "an-annual", "type": "clause", "offset": [2562, 2571]}], "snippet": "As \u2587\u2587\u2587\u2587\u2587 has pointed out in its project proposal, the worldwide bank of blowing agents contained in foams was estimated to exceed 11 billion tons CO2-eq in 2002 and is likely to remain above 9 billion tons CO2-eq in 2015 under most business-as-usual scenarios. However, following the phase-out of the more emissive foam applications that were still using CFCs in the late 1990s, the emissions from foam banks are expected to settle in the range of 180 million tons CO2-eq annually over the next few decades \u2013 i.e., 2% of banked quantities per year. This means that losses from foams could continue well into the future \u2013 perhaps for in excess of 100 years \u2013 particularly if some of those foams are land-filled. However, because the annual baseline loss rate is relatively low, attention typically switches to preventing emissions from more emissive banks \u2013 e.g., refrigerants, where loss rates are often well in excess of 20% of banked quantities annually. This trend persists despite the fact that the foam banks are larger overall. It reflects the fact that measures can be more cost-effective and easier to introduce when preventing refrigerant emissions. Nevertheless, the opportunity for the mitigation of emissions from foams remains highly significant, particularly at end-of-life. Based on the US EPA model data, a 5 billion metric ton CO2-eq bank from ODS/HFC foam sources could be estimated for the USA in 2005, with annual emissions in the 1 The U.S. EPA\u2019s Vintaging Model was developed as a tool for estimating the annual chemical emissions from industrial sectors that have historically used ODSs such as CFCs, HCFCs, and halons in their products. The Vintaging Model also estimates emissions from ODS substitutes such as HFCs. The model name refers to the fact that it tracks the use and emissions of annual \u201cvintages\u201d of equipment that enter service or are disposed in each of several end- uses that make up an industrial sector (\u2587\u2587\u2587\u2587\u2587\u2587, 2003). region of 92 million metric tons CO2-eq. By applying a population factor of 12.8% for California, based on the US census, the California ODS/HFC banks could be estimated at 640 million tons CO2-eq with 12 million tons CO2-eq being emitted per annum from ODS and HFC foam sources (US EPA, 2005). Original Air Resources Board estimates in 2007 noted that approximately 60% of the total bank of high-global warming potential greenhouse gases is from foam sources, with most of the remaining banks from refrigerants. CARB estimated that the foam banks account for some 385 million tons CO2-eq and generate an annual emission of approximately 9 million tons CO2-eq. 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However, enthusiasm for TSP in North America has been tempered with concerns that overall traffic performance may be unduly compromised when signal timing plans intended to optimize traffic flow are overridden to provide a travel advantage to transit vehicles (\u2587\u2587\u2587\u2587\u2587 and \u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587 2003). Several recent studies (see, for example, \u2587\u2587\u2587\u2587\u2587\u2587\u2587\u2587 et al. 2002, and \u2587\u2587\u2587\u2587 et al. 2002) have quantitatively evaluated the effects of TSP. While these studies have generally agreed on the benefits for transit operations, the overall impacts of TSP on local traffic networks remain unclear. Also, because the performance of a signal control strategy is closely related to traffic conditions, surrounding land use, traffic regulations, and roadway network geometry, the One involved four intersections on SW 164th Street in south Snohomish County. Phase Two covered 13 intersections on SR 99 in the City of Lynnwood. This report summarizes both the Phase One and Phase Two evaluations.", "samples": [{"hash": "hJ3DqjSGS0F", "uri": "/contracts/hJ3DqjSGS0F#problem-statement", "label": "Final Technical Report Agreement", "score": 19.0, "published": true}, {"hash": "ab2lVS7qpCz", "uri": "/contracts/ab2lVS7qpCz#problem-statement", "label": "Technical Report Agreement", "score": 19.0, "published": true}], "hash": "7fbd9d5bc96bc62bc0d11d80686bf628", "id": 5}, {"size": 2, "snippet_links": [{"key": "checking-in", "type": "clause", "offset": [174, 185]}], "snippet": "We seek to approximate the following trajectory optimiza- tion problem in a numerically tractable way: quires solving a differential equation interaction model and collision checking in continuous time, necessitating a careful {uy}y\u2208Y J(y, xy, uy) (3a) choice of representation for practical implementation.", "samples": [{"hash": "3H9IqYIKKNl", "uri": "/contracts/3H9IqYIKKNl#problem-statement", "label": "Zonotope Agreement of Prediction and Planning for Continuous Time Collision Avoidance With Discrete Time Dynamics", "score": 33.4231910706, "published": true}, {"hash": "bDVM9OempFa", "uri": "/contracts/bDVM9OempFa#problem-statement", "label": "Zonotope Agreement", "score": 31.4621162415, "published": true}], "hash": "c145a2f21c10969772a42ef14d461712", "id": 6}, {"size": 2, "snippet_links": [{"key": "california-registered-vehicle", "type": "definition", "offset": [71, 100]}, {"key": "accounting-for", "type": "clause", "offset": [108, 122]}, {"key": "number-of-vehicles", "type": "clause", "offset": [203, 221]}, {"key": "responsible-for", "type": "clause", "offset": [225, 240]}, {"key": "greenhouse-gas", "type": "definition", "offset": [269, 283]}, {"key": "in-the-state", "type": "definition", "offset": [300, 312]}, {"key": "fuel-efficiency", "type": "clause", "offset": [342, 357]}, {"key": "per-year", "type": "definition", "offset": [396, 404]}, {"key": "nitrogen-oxides", "type": "definition", "offset": [467, 482]}, {"key": "particulate-matter", "type": "definition", "offset": [507, 525]}, {"key": "road-transportation", "type": "clause", "offset": [582, 601]}, {"key": "in-california", "type": "clause", "offset": [602, 615]}, {"key": "ghg-emissions", "type": "definition", "offset": [697, 710]}, {"key": "criteria-emissions", "type": "definition", "offset": [715, 733]}, {"key": "development-of-projects", "type": "clause", "offset": [830, 853]}, {"key": "clean-vehicle", "type": "definition", "offset": [1145, 1158]}, {"key": "cost-of", "type": "clause", "offset": [1203, 1210]}, {"key": "consequences-of", "type": "definition", "offset": [1445, 1460]}, {"key": "the-improvements", "type": "clause", "offset": [1527, 1543]}, {"key": "air-quality", "type": "definition", "offset": [1547, 1558]}, {"key": "educational-attainment", "type": "clause", "offset": [1687, 1709]}], "snippet": "Medium-duty and heavy-duty (MD/HD) vehicles represent a small share of California registered vehicle stock, accounting for about one million out of 31 million vehicles, or 3 percent; however, this small number of vehicles is responsible for about 23 percent of on-road greenhouse gas (GHG) emissions in the state because of comparatively low fuel efficiency and the high number of miles traveled per year. MD/HD vehicles additionally account for nearly 60 percent of Nitrogen Oxides (NOX) and 52 percent of Particulate Matter (2.5 Micrometers and smaller) (PM2.5) emissions from on-road transportation in California. For these reasons, MD/HD vehicles represent a significant opportunity to reduce GHG emissions and criteria emissions while focusing on a small number of vehicles. In response, California has led the nation in the development of projects incentivizing the adoption of MD/HD advanced vehicle technologies. Since 2010, the state has invested $530 million in such projects, resulting in the deployment of more than 9,000 new clean vehicles on California\u2019s roads. Critical barriers remain, however, that threaten to slow the pace of clean vehicle adoption. Foremost among these are the high cost of zero-emission vehicle (\u2587\u2587\u2587) infrastructure, the relative scarcity of public incentives for such infrastructure, and a significant knowledge gap among fleet owners about \u2587\u2587\u2587 infrastructure technology, permitting, and installation. The consequences of these barriers are magnified in many of the areas most in need of the improvements in air quality\u2014areas categorized as disadvantaged, low-income, and tribal communities\u2014which often suffer from poverty, unemployment, and lower educational attainment.", "samples": [{"hash": "jHbeb0Xe2nq", "uri": "/contracts/jHbeb0Xe2nq#problem-statement", "label": "Grant Agreement", "score": 30.9102859497, "published": true}, {"hash": "jbq3bbVZiwV", "uri": "/contracts/jbq3bbVZiwV#problem-statement", "label": "Grant Agreement", "score": 28.1821460724, "published": true}], "hash": "f8d3aa9118c815bb6bb38b88292fd990", "id": 7}, {"size": 2, "snippet_links": [{"key": "proposed-solution", "type": "clause", "offset": [40, 57]}, {"key": "costs-of", "type": "clause", "offset": [91, 99]}], "snippet": "\u25cf What business problems/needs does the proposed solution address? \u25cf What are the economic costs of inaction? \u25cf Describe the affected processes and up/downstream stakeholders. Describe the extent of the impacts in a measurable way.", "samples": [{"hash": "eZwqxBr8Sqp", "uri": "/contracts/eZwqxBr8Sqp#problem-statement", "label": "Grant Agreement", "score": 34.7183227539, "published": true}, {"hash": "6n3ejK7IEUu", "uri": "/contracts/6n3ejK7IEUu#problem-statement", "label": "Grant Agreement", "score": 34.0073280334, "published": true}], "hash": "382180a12101e13025313661da748470", "id": 9}, {"size": 2, "snippet_links": [{"key": "ability-to", "type": "clause", "offset": [43, 53]}, {"key": "information-from", "type": "clause", "offset": [78, 94]}, {"key": "based-on", "type": "definition", "offset": [151, 159]}, {"key": "related-to", "type": "definition", "offset": [173, 183]}, {"key": "semantic-interoperability", "type": "clause", "offset": [184, 209]}, {"key": "query-processing", "type": "clause", "offset": [258, 274]}, {"key": "main-characteristics", "type": "definition", "offset": [298, 318]}, {"key": "lack-of", "type": "clause", "offset": [544, 551]}, {"key": "having-a", "type": "definition", "offset": [633, 641]}, {"key": "meaning-of", "type": "definition", "offset": [672, 682]}, {"key": "information-exchanged", "type": "clause", "offset": [687, 708]}, {"key": "by-di", "type": "clause", "offset": [709, 714]}, {"key": "data-sources", "type": "definition", "offset": [775, 787]}, {"key": "exchange-information", "type": "clause", "offset": [811, 831]}, {"key": "to-transfer", "type": "clause", "offset": [943, 954]}, {"key": "geographic-data", "type": "definition", "offset": [1053, 1068]}, {"key": "the-network", "type": "clause", "offset": [1250, 1261]}, {"key": "relevant-data", "type": "clause", "offset": [1350, 1363]}, {"key": "decision-making", "type": "definition", "offset": [1368, 1383]}, {"key": "to-develop", "type": "definition", "offset": [1395, 1405]}, {"key": "common-interest", "type": "clause", "offset": [1428, 1443]}, {"key": "of-the-provider", "type": "clause", "offset": [1650, 1665]}, {"key": "collection-company", "type": "clause", "offset": [1681, 1699]}, {"key": "the-shared", "type": "clause", "offset": [1711, 1721]}, {"key": "land-transportation", "type": "clause", "offset": [1810, 1829]}, {"key": "the-nature", "type": "clause", "offset": [1865, 1875]}, {"key": "type-of", "type": "definition", "offset": [1880, 1887]}, {"key": "development-company", "type": "definition", "offset": [1952, 1971]}, {"key": "representations-of-the", "type": "clause", "offset": [2095, 2117]}, {"key": "refer-to", "type": "definition", "offset": [2142, 2150]}, {"key": "the-research", "type": "clause", "offset": [2165, 2177]}], "snippet": "Decision support increasingly requires the ability to manage, combine and use information from heterogeneous sources. A Framework for decision support based on four pillars related to semantic interoperability, GIS interoperabil- ity, P2P architectures, and query processing. In the following, the main characteristics and issues of the four pillars is presented. Information heterogeneity can occur at the syntactic, structural and se- mantic level. Semantic interoperability is more acute in dynamic and au- tonomous environments, due to the lack of relationships among sources. Se- mantic interoperability is essentially based on having a common understand- ing of the meaning of the information exchanged by di erent sources. It's a multi-level problem that can occur in data sources, fromats or models. To exchange information and share computational geo-data resources among heterogeneous systems, conversion tools are usually developed to transfer data from one format to other format. GIS composed of image and traditional database, it required geographic data exhibits complex structure, large size, and complex semantics. P2P can provide infrastructure for dynamic environment in which au- tonomous and independent peers can joint or leave the network easily and frequently. However in a diverse and large community, it is hard to discover relevant data for decision making. P2P allow to develop community which share common interest, so that large community will be 'clustered' based on the same interest. Then searching relevant data can be easier. Consider the fragments of export schema of the two provider peers shown in gure 1.1. One of the provider peer is a toll collection company that views the shared transportation network as a point to point network. This provider peer is interested in land transportation network characteristics related to the nature and type of the road ( gure 1.1b). Another provider peer PP 2, a design and development company, requires detail road information such as size, width, length and tra c capacity. The two provider peers generate di erent representations of the same ontology concepts. Refer to above issues, the research focuses on some questions as follow:", "samples": [{"hash": "8OlMLfVbf8k", "uri": "/contracts/8OlMLfVbf8k#problem-statement", "label": "Dissertation", "score": 17.0, "published": true}, {"hash": "6h98VZ86RCR", "uri": "/contracts/6h98VZ86RCR#problem-statement", "label": "Dissertation", "score": 17.0, "published": true}], "hash": "f3bc0bd40780f4c38f11ff755726c2ef", "id": 10}], "next_curs": "CloSVGoVc35sYXdpbnNpZGVyY29udHJhY3RzcjYLEhZDbGF1c2VTbmlwcGV0R3JvdXBfdjU2Ihpwcm9ibGVtLXN0YXRlbWVudCMwMDAwMDAwYQyiAQJlbhgAIAA=", "clause": {"parents": [["introduction", "Introduction"], ["jurisdiction", "JURISDICTION"], ["certification-regarding-debarment-and-suspension", "Certification Regarding Debarment and Suspension"], ["data-quality-objectives", "Data Quality Objectives"], ["application-submission-process", "Application Submission Process"]], "children": [["", ""], ["objectives", "Objectives"], ["channel-model", "Channel Model"], ["secret-key-capacity", "Secret-Key Capacity"], ["objective", "Objective"]], "size": 312, "title": "Problem Statement", "id": "problem-statement", "related": [["compliance-statement", "Compliance Statement", "Compliance Statement"], ["financial-statement-audit", "Financial Statement Audit", "Financial Statement Audit"], ["billing-statement", "Billing Statement", "Billing Statement"], ["progress-report", "Progress Report", "Progress Report"], ["final-statement", "Final Statement", "Final Statement"]], "related_snippets": [], "updated": "2025-07-24T04:27:57+00:00", "also_ask": ["What are the essential elements that must be included in a Problem Statement to avoid ambiguity?", "How can the Problem Statement be strategically drafted to support our negotiation position?", "What are the most common drafting pitfalls or fatal flaws in Problem Statements?", "How do courts typically interpret and enforce Problem Statements in disputes?", "How does the Problem Statement in this agreement compare to industry standards or best practices?"], "drafting_tip": "Clearly articulate the issue, specify affected parties, and outline objectives to ensure mutual understanding, targeted solutions, and measurable outcomes.", "explanation": "The Problem Statement clause defines the specific issue, challenge, or need that the agreement or project aims to address. It typically outlines the context and background, providing a clear description of the problem's scope and impact. By articulating the problem in precise terms, this clause ensures that all parties have a shared understanding of the underlying issue, which guides the development of solutions and objectives throughout the agreement."}, "json": true, "cursor": ""}}