Optimal Drive-by Sensing in Urban Road Networks with Large-scale Ridesourcing Vehicles

The sensing and monitoring of the urban road network contribute to the efficient operation of the urban transportation system and the functionality of urban systems. However, traditional sensing methods, such as inductive loop sensors, roadside cameras, and crowdsourcing data from massive urban travelers (e.g., Google Maps), are often hindered by high costs, limited coverage, and low reliability. This study explores the potential of drive-by sensing, an innovative approach that employs large-scale ridesourcing vehicles (RVs) for urban road network monitoring. We first evaluate RV sensing performance by coverage and reliability through historical road segment visits. Next, we propose an optimal trip-based RV rerouting model to maximize the sensing coverage and reliability while preserving the same level of service for the RVs' mobility service. Furthermore, a scalable column generation-based heuristic is designed to guide the cruising trajectory of RVs, assuming trip independence. The effectiveness of the proposed model is validated through experiments and sensitivity analyses using real-world RV trajectory data of over 20,000 vehicles in New York City. The optimized rerouting strategy has yielded significantly improved results, elevating explicit sensing coverage of the road network by 15.0\% to 17.3\% (varies by time of day) and achieving an impressive enhancement in sensing reliability by at least 24.6\% compared to historical records. Expanding the path-searching space further improved sensing coverage of up to 4.5\% and reliability of over 4.2\%. Moreover, considering incentives for RV drivers, the enhanced sensing performance comes at a remarkably low cost of \$0.10 per RV driver, highlighting its cost-effectiveness

Understanding the Opportunity-Centric Accessibility for Public Charging Infrastructure

In this study, we utilize data from over 28,000 public charging stations (PCSs) and 5.5 million points of interest across twenty U.S. metropolitan areas to underscore the importance of considering the availability of opportunities when assessing accessibility to PCSs, rather than relying solely on spatial proximity. Specifically, we conduct comprehensive comparisons of opportunity-centric accessibility measures with distance-based measures and perform counterfactual analyses under various PCS deployment strategies. Our findings reveal significant inequalities in PCS access across different neighborhoods under distance-based and opportunity-centric measures. However, a greater disparity exists when considering opportunities, with high-income communities having significantly better access to PCSs. Counterfactual analyses suggest that equitable deployment based on distance measures result in the least equitable outcomes when considering opportunities, primarily due to the existing disparity in opportunity distributions in our cities. Our insights highlight the complexity of locating PCSs and can guide nationwide PCS deployment for long-term societal benefits

Finding disease-specific coordinated functions by multi-function genes: Insight into the coordination mechanisms in diseases

AbstractWe developed an approach using multi-function disease genes to find function pairs whose co-deregulation might induce a disease. Analyzing cancer genes, we found many cancer-specific coordinated function pairs co-deregulated by dysfunction of multi-function genes and other molecular changes in cancer. Studying two subtypes of cardiomyopathy, we found they show certain consistency at the functional coordination level. Our approach can also provide important information for finding novel disease genes as well as their mechanisms in diseases

Delayed Antarctic melt season reduces albedo feedback

Article discusses how Antarctica's response to climate change varies greatly both spatially and temporally. The authors used a 43-year record of Antarctic snow melt seasons from space-borne microwave radiometers with a machine-learning algorithm to show that both the onset and the end of the melt season are being delayed

Exome Sequencing Identifies Compound Heterozygous Mutations in CYP4V2 in a Pedigree with Retinitis Pigmentosa

Retinitis pigmentosa (RP) is a heterogeneous group of progressive retinal degenerations characterized by pigmentation and atrophy in the mid-periphery of the retina. Twenty two subjects from a four-generation Chinese family with RP and thin cornea, congenital cataract and high myopia is reported in this study. All family members underwent complete ophthalmologic examinations. Patients of the family presented with bone spicule-shaped pigment deposits in retina, retinal vascular attenuation, retinal and choroidal dystrophy, as well as punctate opacity of the lens, reduced cornea thickness and high myopia. Peripheral venous blood was obtained from all patients and their family members for genetic analysis. After mutation analysis in a few known RP candidate genes, exome sequencing was used to analyze the exomes of 3 patients III2, III4, III6 and the unaffected mother II2. A total of 34,693 variations shared by 3 patients were subjected to several filtering steps against existing variation databases. Identified variations were verified in the rest family members by PCR and Sanger sequencing. Compound heterozygous c.802-8_810del17insGC and c.1091-2A>G mutations of the CYP4V2 gene, known as genetic defects for Bietti crystalline corneoretinal dystrophy, were identified as causative mutations for RP of this family

Three Capsular Polysaccharide Synthesis-Related Glucosyltransferases, GT-1, GT-2 and WcaJ, Are Associated With Virulence and Phage Sensitivity of Klebsiella pneumoniae

Klebsiella pneumoniae (K. pneumoniae) spp. are important nosocomial and community-acquired opportunistic pathogens, which cause various infections. We observed that K. pneumoniae strain K7 abruptly mutates to rough-type phage-resistant phenotype upon treatment with phage GH-K3. In the present study, the rough-type phage-resistant mutant named K7RR showed much lower virulence than K7. Liquid chromatography-tandem mass spectrometry (LC-MS-MS) analysis indicated that WcaJ and two undefined glycosyltransferases (GTs)- named GT-1, GT-2- were found to be down-regulated drastically in K7RR as compared to K7 strain. GT-1, GT-2, and wcaJ are all located in the gene cluster of capsular polysaccharide (CPS). Upon deletion, even of single component, of GT-1, GT-2, and wcaJ resulted clearly in significant decline of CPS synthesis with concomitant development of GH-K3 resistance and decline of virulence of K. pneumoniae, indicating that all these three GTs are more likely involved in maintenance of phage sensitivity and bacterial virulence. Additionally, K7RR and GT-deficient strains were found sensitive to endocytosis of macrophages. Mitogen-activated protein kinase (MAPK) signaling pathway of macrophages was significantly activated by K7RR and GT-deficient strains comparing with that of K7. Interestingly, in the presence of macromolecular CPS residues (>250 KD), K7(ΔGT-1) and K7(ΔwcaJ) could still be bounded by GH-K3, though with a modest adsorption efficiency, and showed minor virulence, suggesting that the CPS residues accumulated upon deletion of GT-1 or wcaJ did retain phage binding sites as well maintain mild virulence. In brief, our study defines, for the first time, the potential roles of GT-1, GT-2, and WcaJ in K. pneumoniae in bacterial virulence and generation of rough-type mutation under the pressure of bacteriophage

Reproducible Cancer Biomarker Discovery in SELDI-TOF MS Using Different Pre-Processing Algorithms

BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS) studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE) peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR) control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers