Bus Frequency Optimization: When Waiting Time Matters in User Satisfaction

Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this as a bus frequency optimization problem which tries to minimize passengers' average waiting time. However, many investigations have confirmed that the user satisfaction drops faster as the waiting time increases. Consequently, this paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services within the waiting time threshold is maximized. We prove that this problem is NP-hard, and present an index-based algorithm with $(1-1/e)$ approximation ratio. By exploiting the locality property of routes in a bus network, we propose a partition-based greedy method which achieves a $(1-\rho)(1-1/e)$ approximation ratio. Then we propose a progressive partition-based greedy method to further improve the efficiency while achieving a $(1-\rho)(1-1/e-\varepsilon)$ approximation ratio. Experiments on a real city-wide bus dataset in Singapore verify the efficiency, effectiveness, and scalability of our methods

Conductive Carbon Microfibers Derived from Wet-Spun Lignin/Nanocellulose Hydrogels

We introduce an eco-friendly process to dramatically simplify carbon microfiber fabrication from biobased materials. The microfibers are first produced by wet-spinning in aqueous calcium chloride solution, which provides rapid coagulation of the hydrogel precursors comprising wood-derived lignin and 2,2,6,6-tetramethylpiperidine-l-oxyl (TEMPO)-oxidized cellulose nanofibrils (TOCNF). The thermomechanical performance of the obtained lignin/TOCNF filaments is investigated as a function of cellulose nanofibril orientation (wide angle X-ray scattering (WAXS)), morphology (scanning electron microscopy (SEM)), and density. Following direct carbonization of the filaments at 900 degrees C, carbon microfibers (CMFs) are obtained with remarkably high yield, up to 41%, at lignin loadings of 70 wt % in the precursor microfibers (compared to 23% yield for those produced in the absence of lignin). Without any thermal stabilization or graphitization steps, the morphology, strength, and flexibility of the CMFs are retained to a large degree compared to those of the respective precursors. The electrical conductivity of the CMFs reach values as high as 103 S cm(-1), making them suitable for microelectrodes, fiber-shaped supercapacitors, and wearable electronics. Overall, the cellulose nanofibrils act as structural elements for fast, inexpensive, and environmentally sound wet-spinning while lignin endows CMFs with high carbon yield and electrical conductivity

Mesoporous Carbon Microfibers for Electroactive Materials Derived from Lignocellulose Nanofibrils

The growing adoption of biobased materials for electronic, energy conversion, and storage devices has relied on high-grade or refined cellulosic compositions. Herein, lignocellulose nanofibrils (LCNF), obtained from simple mechanical fibrillation of wood, are proposed as a source of continuous carbon microfibers obtained by wet spinning followed by single-step carbonization at 900 °C. The high lignin content of LCNF (∼28% based on dry mass), similar to that of the original wood, allowed the synthesis of carbon microfibers with a high carbon yield (29%) and electrical conductivity (66 S cm–1). The incorporation of anionic cellulose nanofibrils (TOCNF) enhanced the spinnability and the porous morphology of the carbon microfibers, making them suitable platforms for electrochemical double layer capacitance (EDLC). The increased loading of LCNF in the spinning dope resulted in carbon microfibers of enhanced carbon yield and conductivity. Meanwhile, TOCNF influenced the pore evolution and specific surface area after carbonization, which significantly improved the electrochemical double layer capacitance. When the carbon microfibers were directly applied as fiber-shaped supercapacitors (25 F cm–3), they displayed a remarkably long-term electrochemical stability (>93% of the initial capacitance after 10 000 cycles). Solid-state symmetric fiber supercapacitors were assembled using a PVA/H2SO4 gel electrolyte and resulted in an energy and power density of 0.25 mW h cm–3 and 65.1 mW cm–3, respectively. Overall, the results indicate a green and facile route to convert wood into carbon microfibers suitable for integration in wearables and energy storage devices and for potential applications in the field of bioelectronics.</p

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping

Data-Driven Optimization of Public Transit Schedule

Bus transit systems are the backbone of public transportation in the United States. An important indicator of the quality of service in such infrastructures is on-time performance at stops, with published transit schedules playing an integral role governing the level of success of the service. However there are relatively few optimization architectures leveraging stochastic search that focus on optimizing bus timetables with the objective of maximizing probability of bus arrivals at timepoints with delays within desired on-time ranges. In addition to this, there is a lack of substantial research considering monthly and seasonal variations of delay patterns integrated with such optimization strategies. To address these,this paper makes the following contributions to the corpus of studies on transit on-time performance optimization: (a) an unsupervised clustering mechanism is presented which groups months with similar seasonal delay patterns, (b) the problem is formulated as a single-objective optimization task and a greedy algorithm, a genetic algorithm (GA) as well as a particle swarm optimization (PSO) algorithm are employed to solve it, (c) a detailed discussion on empirical results comparing the algorithms are provided and sensitivity analysis on hyper-parameters of the heuristics are presented along with execution times, which will help practitioners looking at similar problems. The analyses conducted are insightful in the local context of improving public transit scheduling in the Nashville metro region as well as informative from a global perspective as an elaborate case study which builds upon the growing corpus of empirical studies using nature-inspired approaches to transit schedule optimization.Comment: 20 pages, 6 figures, 2 table

Spin-orbit torque in Pt/CoNiCo/Pt symmetric devices

Current induced magnetization switching by spin-orbit torques offers an energy-efficient means of writing information in heavy metal/ferromagnet (FM) multilayer systems. The relative contributions of field-like torques and damping-like torques to the magnetization switching induced by the electrical current are still under debate. Here, we describe a device based on a symmetric Pt/FM/Pt structure, in which we demonstrate a strong damping-like torque from the spin Hall effect and unmeasurable field-like torque from Rashba effect. The spin-orbit effective fields due to the spin Hall effect were investigated quantitatively and were found to be consistent with the switching effective fields after accounting for the switching current reduction due to thermal fluctuations from the current pulse. A non-linear dependence of deterministic switching of average Mzon the in-plane magnetic field was revealed, which could be explained and understood by micromagnetic simulation

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

IFN-λ3, not IFN-λ4, likely mediates IFNL3-IFNL4 haplotype-dependent hepatic inflammation and fibrosis

Genetic variation in the IFNL3-IFNL4 (interferon-λ3-interferon-λ4) region is associated with hepatic inflammation and fibrosis. Whether IFN-λ3 or IFN-λ4 protein drives this association is not known. We demonstrate that hepatic inflammation, fibrosis stage, fibrosis progression rate, hepatic infiltration of immune cells, IFN-λ3 expression, and serum sCD163 levels (a marker of activated macrophages) are greater in individuals with the IFNL3-IFNL4 risk haplotype that does not produce IFN-λ4, but produces IFN-λ3. No difference in these features was observed according to genotype at rs117648444, which encodes a substitution at position 70 of the IFN-λ4 protein and reduces IFN-λ4 activity, or between patients encoding functionally defective IFN-λ4 (IFN-λ4-Ser70) and those encoding fully active IFN-λ4-Pro70. The two proposed functional variants (rs368234815 and rs4803217) were not superior to the discovery SNP rs12979860 with respect to liver inflammation or fibrosis phenotype. IFN-λ3 rather than IFN-λ4 likely mediates IFNL3-IFNL4 haplotype-dependent hepatic inflammation and fibrosis