DYNAMIC FREEWAY TRAVEL TIME PREDICTION USING SINGLE LOOP DETECTOR AND INCIDENT DATA

The accurate estimation of travel time is valuable for a variety of transportation applications such as freeway performance evaluation and real-time traveler information. Given the extensive availability of traffic data collected by intelligent transportation systems, a variety of travel time estimation methods have been developed. Despite limited success under light traffic conditions, traditional corridor travel time prediction methods have suffered various drawbacks. First, most of these methods are developed based on data generated by dual-loop detectors that contain average spot speeds. However, single-loop detectors (and other devices that emulate its operation) are the most commonly used devices in traffic monitoring systems. There has not been a reliable methodology for travel time prediction based on data generated by such devices due to the lack of speed measurements. Moreover, the majority of existing studies focus on travel time estimation. Secondly, the effect of traffic progression along the freeway has not been considered in the travel time prediction process. Moreover, the impact of incidents on travel time estimates has not been effectively accounted for in existing studies.The objective of this dissertation is to develop a methodology for dynamic travel time prediction based on continuous data generated by single-loop detectors (and similar devices) and incident reports generated by the traffic monitoring system. This method involves multiple-step-ahead prediction for flow rate and occupancy in real time. A seasonal autoregressive integrated moving average (SARIMA) model is developed with an embedded adaptive predictor. This predictor adjusts the prediction error based on traffic data that becomes available every five minutes at each station. The impact of incidents is evaluated based on estimates of incident duration and the queue incurred.Tests and comparative analyses show that this method is able to capture the real-time characteristics of the traffic and provide more accurate travel time estimates particularly when incidents occur. The sensitivities of the models to the variations of the flow and occupancy data are analyzed and future research has been identified.The potential of this methodology in dealing with less than perfect data sources has been demonstrated. This provides good opportunity for the wide application of the proposed method since single-loop type detectors are most extensively installed in various intelligent transportation system deployments

An improved mixture of probabilistic PCA for nonlinear data-driven process monitoring

An improved mixture of probabilistic principal component analysis (PPCA) has been introduced for nonlinear data-driven process monitoring in this paper. To realize this purpose, the technique of a mixture of probabilistic principal component analyzers is utilized to establish the model of the underlying nonlinear process with local PPCA models, where a novel composite monitoring statistic is proposed based on the integration of two monitoring statistics in modified PPCA-based fault detection approach. Besides, the weighted mean of the monitoring statistics aforementioned is utilized as a metrics to detect potential abnormalities. The virtues of the proposed algorithm are discussed in comparison with several unsupervised algorithms. Finally, Tennessee Eastman process and an autosuspension model are employed to demonstrate the effectiveness of the proposed scheme further

Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation

By integrating two powerful methods of density reduction and intrinsic dimensionality estimation, a new data-driven method, referred to as OLPP-MLE (orthogonal locality preserving projection-maximum likelihood estimation), is introduced for process monitoring. OLPP is utilized for dimensionality reduction, which provides better locality preserving power than locality preserving projection. Then, the MLE is adopted to estimate intrinsic dimensionality of OLPP. Within the proposed OLPP-MLE, two new static measures for fault detection TOLPP2 and SPEOLPP are defined. In order to reduce algorithm complexity and ignore data distribution, kernel density estimation is employed to compute thresholds for fault diagnosis. The effectiveness of the proposed method is demonstrated by three case studies

Inhibition of the m6A reader IGF2BP2 as a strategy against T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignant leukemia with extremely limited treatment for relapsed patients. N6‐methyladenosine (m6A) reader insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) participates in the initiation and growth of cancers by communicating with various targets. Here, we found IGF2BP2 was highly expressed in T-ALL. Gain and loss of IGF2BP2 demonstrated IGF2BP2 was essential for T-ALL cell proliferation in vitro and loss of IGF2BP2 prolonged animal survival in a human T-ALL xenograft model. Mechanistically, IGF2BP2 directly bound to T-ALL oncogene NOTCH1 via an m6A dependent manner. Furthermore, we identified a small-molecule IGF2BP2 inhibitor JX5 and treatment of T-ALL with JX5 showed similar functions as knockdown of IGF2BP2. These findings not only shed light on the role of IGF2BP2 in T-ALL, but also provide an alternative γ‑Secretase inhibitors (GSI) therapy to treat T-ALL.Inhibition of the m6A reader IGF2BP2 as a strategy against T-cell acute lymphoblastic leukemiapublishedVersio

The m6A Reader IGF2BP2 Regulates Macrophage Phenotypic Activation and Inflammatory Diseases by Stabilizing TSC1 and PPARγ.

peer reviewedPhenotypic polarization of macrophages is regulated by a milieu of cues in the local tissue microenvironment. Currently, little is known about how the intrinsic regulators modulate proinflammatory (M1) versus prohealing (M2) macrophages activation. Here, it is observed that insulin-like growth factor 2 messenger RNA (mRNA)-binding protein 2 (IGF2BP2)-deleted macrophages exhibit enhanced M1 phenotype and promote dextran sulfate sodium induced colitis development. However, the IGF2BP2-/- macrophages are refractory to interleukin-4 (IL-4) induced activation and alleviate cockroach extract induced pulmonary allergic inflammation. Molecular studies indicate that IGF2BP2 switches M1 macrophages to M2 activation by targeting tuberous sclerosis 1 via an N6-methyladenosine (m6A)-dependent manner. Additionally, it is also shown a signal transducer and activators of transcription 6 (STAT6)-high mobility group AT-hook 2-IGF2BP2-peroxisome proliferator activated receptor-γ axis involves in M2 macrophages differentiation. These findings highlight a key role of IGF2BP2 in regulation of macrophages activation and imply a potential therapeutic target of macrophages in the inflammatory diseases

Molecular Programming of Biodegradable Nanoworms via Ionically Induced Morphology Switch toward Asymmetric Therapeutic Carriers

Engineering biodegradable nanostructures with precise morphological characteristics is a key objective in nanomedicine. In particular, asymmetric (i.e., nonspherical) nanoparticles are desirable due to the advantageous effects of shape in a biomedical context. Using molecular engineering, it is possible to program unique morphological features into the self-assembly of block copolymers (BCPs). However, the criteria of biocompatibility and scalability limit progress due to the prevalence of nondegradable components and the use of toxic solvents during fabrication. To address this shortfall, a robust strategy for the fabrication of morphologically asymmetric nanoworms, comprising biodegradable BCPs, has been developed. Modular BCPs comprising poly (ethylene glycol)-block-poly(caprolactone-gradient-trimethylene carbonate) (PEG−PCLgTMC), with a terminal chain of quaternary ammonium-TMC (PTMC-Q), undergo self-assembly via direct hydration into well-defined nanostructures. By controlling the solution ionic strength during hydration, particle morphology switches from spherical micelles to nanoworms (of varying aspect ratio). This ionically-induced switch is driven by modulation of chain packing with salts screening interchain repulsions, leading to micelle elongation. Nanoworms can be loaded with cytotoxic cargo (e.g., doxorubicin) at high efficiency, preferentially interact with cancer cells, and increase tumor penetration. This work showcases the ability to program assembly of BCPs and the potential of asymmetric nanosystems in anticancer drug delivery

The effects of defoliation on tissue turnover and pasture production in perennial ryegrass, prairie grass and smooth bromegrass pasture : a thesis presented in partial fulfilment of the requriements [i.e. requirements] for the degree of Doctor of Philosophy at Massey University

This thesis reports the results of three experiments, one with perennial ryegrass (Lolium perenne L.) cv. Ellett under rotational sheep grazing, one with prairie grass (Bromus willdenowii Kunth.) cv. Grasslands Matua under rotional dairy cow grazing, and one with smooth bromegrass (Bromus inermis Leyss) under cutting management. The first two experiments were carried out at Massey University, New Zealand, the third at Beijing Agicultural University, China. Each experiment involved management variations set within a range considered to be appropriate to the species under examination, and was complete in itself. The objective of the study reported here was to examine the sensitivity to defoliation of the three grass species, sensitivity being defined principally in terms of adjustment in tiller population density and tissue turnover to variations in defoliation treatment. The results are reported separately, but are drawn together for comparative purposes in an integrating discussion. Flexibility in response to defoliation, measured in terms of the number of live leaves per tiller, the rate of leaf appearance, dry weight per tiller, and tiller population density, differed substantially in perennial ryegrass, prairie grass, and smooth bromegrass, and had a major influence on the sensitivity of the species to contrasting managements. Net herbage production was relatively insensitive to hard (2.5cm, post grazing l000kgDM/ha) and lax grazing (15cm, post grazing 2000kgDM/ha) in perennial ryegrass pasture because of rapid adaptive change in tiller population density, which was usually greater under hard grazing than under lax grazing, and compensating changes in rates of herbage growth and senescence. Net herbage production of prairie grass was greater under lax (12cm, post grazing 2500-3500kgDM/ha) than under hard (6cm, post grazing 1500-2000kgDM/ha) grazing, associated with reduction in tiller population density under the latter treatment, and a greater reduction in herbage growth than in senescence per tiller. In smooth bromegrass, tiller populations were greater under lax (30 cm) than under hard (10 cm) cutting, though the closer cutting treatment resulted in greater green herbage accumulation, because of a greater reduction in the rate of herbage senescence than in the rate of herbage production. In general terms, perennial ryegrass demonstrated substantial genotypic plasticity in the adaptive changes in the balance between tiller population density and tiller size, reflecting the high tillering potential in this species. Rates of leaf production on main and daughter tillers consistently made the major contribution to tissue turnover in this. In contrast, prairie grass showed little adaptive response in tiller population density when tiller size was reduced, and the main component of tissue turnover was generaley stem material. Though tiller size was similar in smooth brome and prairie grass, adaptive changes in the balance between tiller size and population were more complete in the former species and leaf tissue made a greater contribution than stem to tissue turnover. The effect of seasonal change in the enviroment on the growth of grass swards is complicated by progression from vegetative to reproductive development. In ryegrass pasture, there were advantages to spring and summer pasture production from a management which allowed seed head development to anthesis in spring, followed by hard grazing to enhance the subsequent development of new vegetative tillers. For smooth brome grass initial cutting at anthesis resulted in a greater rate of green herbage accumulation subsequently than did cutting one month later. In prairie grass the limited development of replacement daughter tillers contributed to the relatively poor performance of this species under hard grazing. The relationship between the timing and severity of defoliation and the physiological status of the plant was therefore critical in determining subsequent herbage growth in all three species, though there were clearly specific differences in effects on the balance between stem and new tiller production and the expansion of daughter tillers. This study suggested that a better understanding of the limits of adaptitive response in the different species, particularly in tiller population structure and tissue turnover, will provide an objective basis for planning pasture management. Studies of this kind, preferably made under strictly controlled comparative conditions, would be a particularly important component of evaluation programs for new plant genotypes

Along the Oregon Trail: Disaster Preparedness in Oregon Libraries and Archives

Kris Kern discusses the creation of the Western States and Territories Preservation Assistance Service (WESTPAS) in 2007 to assist in protecting Oregon\u27s Library collections

Developing a Strategy for Imputing Missing Traffic Volume Data

Archived ITS-generated data can provide a potential resource for many long-term transportation applications. However, missing and suspicious data are inevitable due to detector and communication malfunctions. This paper presents a comparative analysis of various techniques for imputing missing traffic volume data in the archived data management system in Kentucky. The applicability of the techniques, as well as their reliability in terms of data requirement, is also discussed. An implementation strategy for the Kentucky archive data management system is then developed based on the performance and the applicability/reliability analyses

Archived Data Management System in Kentucky

Archived Data User Service (ADUS) was added to the national ITS architecture in 1999 to enable multiple uses for ITS-generated data. In Kentucky, ARTIMIS and TRIMARC are collecting volume, speed, occupancy, length-based classification, and incident data on a continuous basis. This study developed the Kentucky Archived Data Management System (ADMS) to archive and disseminate data collected by sensors in ARTIMIS and TRIMARC systems. This system is designed to be the prototype of ITS data clearinghouse in Kentucky. The Kentucky ADMS operates on a web server that allows users to retrieve traffic data (i.e., volume, speed, lane occupancy) in 15 minute increments from a GIS-based map. Some freeway performance measures such as AADT are also provided. Data quality control and assurance were also performed to identify the erroneous data items and/or records and to provide statistically more accurate estimates