Investigation of Bicycle Travel Time Estimation Using Bluetooth Sensors for Low Sampling Rates

Filtering the data for bicycle travel time using Bluetooth sensors is crucial to the estimation of link travel times on a corridor. The current paper describes an adaptive filtering algorithm for estimating bicycle travel times using Bluetooth data, with consideration of low sampling rates. The data for bicycle travel time using Bluetooth sensors has two characteristics. First, the bicycle flow contains stable and unstable conditions. Second, the collected data have low sampling rates (less than 1%). To avoid erroneous inference, filters are introduced to “purify” multiple time series. The valid data are identified within a dynamically varying validity window with the use of a robust data-filtering procedure. The size of the validity window varies based on the number of preceding sampling intervals without a Bluetooth record. Applications of the proposed algorithm to the dataset from Genshan East Road and Moganshan Road in Hangzhou demonstrate its ability to track typical variations in bicycle travel time efficiently, while suppressing high frequency noise signals.</p

Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm

With the purpose of improving the PDP (policy decision point) evaluation performance, a novel and efficient evaluation engine, namely XDNNEngine, based on neural networks and an SGDK-means (stochastic gradient descent K-means) algorithm is proposed. We divide a policy set into different clusters, distinguish different rules based on their own features and label them for the training of neural networks by using the K-means algorithm and an asynchronous SGDK-means algorithm. Then, we utilize neural networks to search for the applicable rule. A quantitative neural network is introduced to reduce a server’s computational cost. By simulating the arrival of requests, XDNNEngine is compared with the Sun PDP, XEngine and SBA-XACML. Experimental results show that 1) if the number of requests reaches 10,000, the evaluation time of XDNNEngine on the large-scale policy set with 10,000 rules is approximately 2.5 ms, and 2) in the same condition as 1), the evaluation time of XDNNEngine is reduced by 98.27%, 90.36% and 84.69%, respectively, over that of the Sun PDP, XEngine and SBA-XACML

Research on the Multiroute Probit-Based Public Transit Assignment Model Based on Bus Stop

A public transit network differs from a general road network. The passenger flow of bus stops and the limited capacity of buses have a greater effect than road traffic flow on the running time of buses. As a result, conventional public transit assignment models that adopt the econometric road network path concept have numerous limitations. Based on the analysis, the generalized bus trip time chain is analyzed, and the concept of a congestion function is proposed to describe the relationship between trip resistance and flow in the current paper. On the premise of this study, the transit network resistance function is formed and the multiroute probit-based loading model is established. With using STOCH or Dial's algorithm, the process of distribution is proposed. Finally, the model is applied to the transit network assignment of Deqing Town in Zhejiang Province. The result indicates that the model can be applied to practical operations with high-precision results

Simultaneous evolutionary expansion and constraint of genomic heterogeneity in multifocal lung cancer.

Recent genomic analyses have revealed substantial tumor heterogeneity across various cancers. However, it remains unclear whether and how genomic heterogeneity is constrained during tumor evolution. Here, we sequence a unique cohort of multiple synchronous lung cancers (MSLCs) to determine the relative diversity and uniformity of genetic drivers upon identical germline and environmental background. We find that each multicentric primary tumor harbors distinct oncogenic alterations, including novel mutations that are experimentally demonstrated to be functional and therapeutically targetable. However, functional studies show a strikingly constrained tumorigenic pathway underlying heterogeneous genetic variants. These results suggest that although the mutation-specific routes that cells take during oncogenesis are stochastic, genetic trajectories may be constrained by selection for functional convergence on key signaling pathways. Our findings highlight the robust evolutionary pressures that simultaneously shape the expansion and constraint of genomic diversity, a principle that holds important implications for understanding tumor evolution and optimizing therapeutic strategies.Across cancer types tumor heterogeneity has been observed, but how this relates to tumor evolution is unclear. Here, the authors sequence multiple synchronous lung cancers, highlighting the evolutionary pressures that simultaneously shape the expansion and constraint of genomic heterogeneity

Setting Thresholds to Varying Blood Pressure Monitoring Intervals Differentially Affects Risk Estimates Associated With White-Coat and Masked Hypertension in the Population

Outcome-driven recommendations about time intervals during which ambulatory blood pressure should be measured to diagnose white-coat or masked hypertension are lacking. We cross-classified 8237 untreated participants (mean age, 50.7 years; 48.4% women) enrolled in 12 population studies, using ≥140/≥90, ≥130/≥80, ≥135/≥85, and ≥120/≥70 mm Hg as hypertension thresholds for conventional, 24-hour, daytime, and nighttime blood pressure. White-coat hypertension was hypertension on conventional measurement with ambulatory normotension, the opposite condition being masked hypertension. Intervals used for classification of participants were daytime, nighttime, and 24 hours, first considered separately, and next combined as 24 hours plus daytime or plus nighttime, or plus both. Depending on time intervals chosen, white-coat and masked hypertension frequencies ranged from 6.3% to 12.5% and from 9.7% to 19.6%, respectively. During 91 046 person-years, 729 participants experienced a cardiovascular event. In multivariable analyses with normotension during all intervals of the day as reference, hazard ratios associated with white-coat hypertension progressively weakened considering daytime only (1.38; P=0.033), nighttime only (1.43; P=0.0074), 24 hours only (1.21; P=0.20), 24 hours plus daytime (1.24; P=0.18), 24 hours plus nighttime (1.15; P=0.39), and 24 hours plus daytime and nighttime (1.16; P=0.41). The hazard ratios comparing masked hypertension with normotension were all significant (

Machine learning-based on cytotoxic T lymphocyte evasion gene develops a novel signature to predict prognosis and immunotherapy responses for kidney renal clear cell carcinoma patients

BackgroundImmunotherapy resistance has become a difficult point in treating kidney renal clear cell carcinoma (KIRC) patients, mainly because of immune evasion. Currently, there is no effective signature to predict immunotherapy. Therefore, we use machine learning algorithms to construct a signature based on cytotoxic T lymphocyte evasion genes (CTLEGs) to predict the immunotherapy responses of patients, so as to screen patients effective for immunotherapy.MethodsIn public data sets and our in-house cohort, we used 10 machine learning algorithms to screen the optimal model with 89 combinations under the cross-validation framework, and 101 published signatures were collected. The relationship between the CTLEG signature (CTLEGS) and clinical variables was analyzed. We analyzed the role of CTLES in other types of cancer by pan-cancer analysis. The immune cell infiltration and biological characteristics were evaluated. Moreover, the response to immunotherapy and drug sensitivity of different risk groups were investigated. The key gene closely related to the signature was identified by WGCNA. We also conducted cell functional experiments and clinical tissue validation of key gene.ResultsIn public data sets and our in-house cohort, the CTLEGS shows good prediction performance. The CTLEGS can be regard as an independent risk factor for KIRC. Compared with 101 published models, our signature shows considerable superiority. The high-risk group has abundant infiltration of immunosuppressive cells and high expression of T cell depletion markers, which are characterized by immunosuppressive phenotype, minimal benefit from immunotherapy, and resistance to sunitinib and sorafenib. The CTLEGS was also strongly correlated with immunity in pan-cancer. Immunohistochemistry verified that T cell depletion marker LAG3 is highly expressed in high-risk groups in the clinical in-house cohort. The key CTLEG STAT2 can promote the proliferation, migration and invasion of KIRC cell.ConclusionsCTLEGS can accurately predict the prognosis of patients and their response to immunotherapy. It can provide guidance for the precise treatment of KIRC and help clinicians identify patients who may benefit from immunotherapy

Genetic Ablation of PLA2G6 in Mice Leads to Cerebellar Atrophy Characterized by Purkinje Cell Loss and Glial Cell Activation

Infantile neuroaxonal dystrophy (INAD) is a progressive, autosomal recessive neurodegenerative disease characterized by axonal dystrophy, abnormal iron deposition and cerebellar atrophy. This disease was recently mapped to PLA2G6, which encodes group VI Ca2+-independent phospholipase A2 (iPLA2 or iPLA2β). Here we show that genetic ablation of PLA2G6 in mice (iPLA2β-/-) leads to the development of cerebellar atrophy by the age of 13 months. Atrophied cerebella exhibited significant loss of Purkinje cells, as well as reactive astrogliosis, the activation of microglial cells, and the pronounced up-regulation of the pro-inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β). Moreover, glial cell activation and the elevation in TNF-α and IL-1β expression occurred before apparent cerebellar atrophy. Our findings indicate that the absence of PLA2G6 causes neuroinflammation and Purkinje cell loss and ultimately leads to cerebellar atrophy. Our study suggests that iPLA2β-/- mice are a valuable model for cerebellar atrophy in INAD and that early anti-inflammatory therapy may help slow the progression of cerebellar atrophy in this deadly neurodegenerative disease

Increased Mitochondrial Calcium Sensitivity and Abnormal Expression of Innate Immunity Genes Precede Dopaminergic Defects in Pink1-Deficient Mice

BACKGROUND: PTEN-induced kinase 1 (PINK1) is linked to recessive Parkinsonism (EOPD). Pink1 deletion results in impaired dopamine (DA) release and decreased mitochondrial respiration in the striatum of mice. To reveal additional mechanisms of Pink1-related dopaminergic dysfunction, we studied Ca²+ vulnerability of purified brain mitochondria, DA levels and metabolism and whether signaling pathways implicated in Parkinson\u27s disease (PD) display altered activity in the nigrostriatal system of Pink1⁻/⁻ mice. METHODS AND FINDINGS: Purified brain mitochondria of Pink1⁻/⁻ mice showed impaired Ca²+ storage capacity, resulting in increased Ca²+ induced mitochondrial permeability transition (mPT) that was rescued by cyclosporine A. A subpopulation of neurons in the substantia nigra of Pink1⁻/⁻ mice accumulated phospho-c-Jun, showing that Jun N-terminal kinase (JNK) activity is increased. Pink1⁻/⁻ mice 6 months and older displayed reduced DA levels associated with increased DA turnover. Moreover, Pink1⁻/⁻ mice had increased levels of IL-1β, IL-12 and IL-10 in the striatum after peripheral challenge with lipopolysaccharide (LPS), and Pink1⁻/⁻ embryonic fibroblasts showed decreased basal and inflammatory cytokine-induced nuclear factor kappa-β (NF-κB) activity. Quantitative transcriptional profiling in the striatum revealed that Pink1⁻/⁻ mice differentially express genes that (i) are upregulated in animals with experimentally induced dopaminergic lesions, (ii) regulate innate immune responses and/or apoptosis and (iii) promote axonal regeneration and sprouting. CONCLUSIONS: Increased mitochondrial Ca²+ sensitivity and JNK activity are early defects in Pink1⁻/⁻ mice that precede reduced DA levels and abnormal DA homeostasis and may contribute to neuronal dysfunction in familial PD. Differential gene expression in the nigrostriatal system of Pink1⁻/⁻ mice supports early dopaminergic dysfunction and shows that Pink1 deletion causes aberrant expression of genes that regulate innate immune responses. While some differentially expressed genes may mitigate neurodegeneration, increased LPS-induced brain cytokine expression and impaired cytokine-induced NF-κB activation may predispose neurons of Pink1⁻/⁻ mice to inflammation and injury-induced cell death