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AbstractNon-muscle invasive bladder cancer (NMIBC) is one of the most common type of bladder cancer. Here, we have utilized an integrated transcriptomic-computational approach to identify alternate treatments to the NMIBC. In this study, we have performed the comprehensive comparative analysis between three groups of 36 patients with non-relapsed (NR), recurrence and progressive symptoms. Differentially expressed genes involved in the pathways associated with the NMIBC were identified. In silicoprotein–protein interaction (PPI) network was performed to create the network of the hub genes associated with NMIBC. Further, we compared NR individuals with two cohorts of patients with recurrent and progressive symptoms that lead to the identification of three major biomarkers CD34, FLT1 and WHSC1 genes. Concurrently, PPI also suggests that they are significant hub genes responsible for disease recurrence and progression. Furthermore, targeted genes WHSC-1 and FLT-1 were subjected to virtual screening for identification phytochemical inhibitors. Docking and molecular dynamics simulations concluded that the phytochemicals anonymously named ‘UNK’ and ‘6-hydroxycyanidin’ are suitable for the inhibition of the proteins causing the NMIBC. In the future, this study will help for strengthening the strategies development at the molecular level for the control of carcinomas at early as well as detection of active and binding site, receptor–ligand interaction and also make drug designing for the early treatment of the carcinomas.Communicated by Ramaswamy H. Sarma

Multiple van der Waals (vdW) gaps invoke abundant opportunities for contriving artificial architectures and tailoring desired properties via the intercalation route beyond the reach of conventional concepts. Intriguingly, the electrochemical intercalation strategy can precisely and reversibly tune the intercalation stage of charged functional species. This study presents a valid structural editing protocol facilitated by electrochemical intercalation to engineer MXene interlayers, ultimately incorporating in situ constructed carbon nanotube (CNT) electric bridges for enhanced ion storage and transport pathways. The method allows for the precise modulation of electrochemical forces to tailor materials for specific applications. Deep intercalation and in situ growth processes establish robust anchoring sites and connectivity hubs between MXenes and CNTs, ensuring structural homogeneity and stability in advanced electrode materials. The results demonstrate the effectiveness of electrochemistry-mediated interlayer nanoengineering in MXenes, offering a versatile approach to design vdW heterostructures with tailored functionalities for energy storage and conversion applications. This work highlights the potential of electrochemical modulation in advancing materials engineering strategies for next-generation energy storage technologies.

We present FossilMorph, a user-friendly and open access software that offers rapid measurement and statistical analysis based on fossil images. Routine steps of image processing technologies and algorithms designed for three types of organic-walled microfossils (i.e., spheroidal type, filamentous type, and broken type) have been introduced in order to illuminate the rationale of FossilMorph. Two case studies on the form genera Leiosphaeridiaand Siphonophycusare used to test the utility of FossilMorph on the study of micropalaeontology, especially the Proterozoic spheroidal acritarchs. Future development of FossilMorph may be extended to deal with complex morphology and community-type preservation for wider applications.

Single-molecule localization microscopy (SMLM) has gained widespread use for visualizing the morphology of subcellular organelles and structures with nanoscale spatial resolution. However, analysis tools for automatically quantifying and classifying SMLM images have lagged behind. Here we introduce Enhanced Classification of Localized Point clouds by Shape Extraction (ECLiPSE), an automated machine learning analysis pipeline specifically designed to classify cellular structures captured through two-dimensional or three-dimensional SMLM. ECLiPSE leverages a comprehensive set of shape descriptors, the majority of which are directly extracted from the localizations to minimize bias during the characterization of individual structures. ECLiPSE has been validated using both unsupervised and supervised classification on datasets, including various cellular structures, achieving near-perfect accuracy. We apply two-dimensional ECLiPSE to classify morphologically distinct protein aggregates relevant for neurodegenerative diseases. Additionally, we employ three-dimensional ECLiPSE to identify relevant biological differences between healthy and depolarized mitochondria. ECLiPSE will enhance the way we study cellular structures across various biological contexts.

Longfengshaniais among the few examples of Pre-Cryogenian macroscopic fossils with an unambiguous eukaryotic affinity. It has received great attention since this genus is the earliest known Pre-Cryogenian macroalga with blade, stipe, and holdfast differentiation. However, compared to other macrofossils, such as Chuariaand Tawuia, reported occurrences (lithostratigraphic units) of Longfengshaniaare limited in Tonian strata, restricting the assessment of paleogeographic distribution of Longfengshaniaand therefore hindering our understanding of its paleoecological role in the Tonian oceans. Here, we describe two new localities of Longfengshania, including the Tonian Shiwangzhuang Formation (∼850–720 Ma) in western Shandong and Jiuliqiao Formation (∼950–720 Ma) in northern Anhui, North China. Specimens of Longfengshaniafrom the Shiwangzhuang and Jiuliqiao formations are smaller than specimens from other localities, which has been interpreted as adaptations to relatively stronger hydrodynamic conditions. Biometric and principal component analyses suggest that most other species of Longfengshaniaactually fall within the morphospace range of the type species L. stipitataand therefore a re-examination on previously reported specimens and a taxonomic revision for this genus are needed in future study.

Branded applications (apps) have become core touchpoints for improving consumer shopping experiences in omni-channel retailing, and many firms have developed different types of branded apps to provide additional value. Moreover, continuous usage intention is the key to improving enterprises’ gain efficiency and consumers’ brand loyalty. This study aims to reveal how branded apps achieve continuance intention from the perspective of consumer perceptions by combining the technology acceptance model and investigating the impact of differences in channel features on usage behavior between the two types of branded apps. An experiment was designed comparing transaction- and experience-oriented branded apps. A structural equation modeling technique was employed to validate the model based on the survey data of respondents from the experimental groups. The results show that the supportive role of omni-channel has a unique experience mechanism that promotes continuous usage intention. However, there are two discrepant results regarding the effect of perceived complementarity on perceived usefulness in transaction- and experience-oriented branded apps. The mediating role of perceived usefulness between perceived consistency, complementarity, ease of use and consumer satisfaction was supported in the experience-oriented apps but rejected in the transaction-oriented apps.

The usual linear superconducting resonators (with equal frequency intervals between nearest-neighbor modes) are right-handed electromagnetic devices, wherein cross talks between the nearest-neighbor modes are practically unavoidable. Here, we demonstrate the nonlinear superconducting metamaterial resonators, wherein frequency intervals between the nearest-neighbor modes are unequal, by using the composite right/left-handed transmission lines. The microwave transport properties are analyzed by the developed real-space approach, instead of the usual equivalent circuit method. The devices are fabricated by using the usual electron beam evaporation technique, and their microwave transport parameters are measured at 50 mK temperature. The observations are basically consistent with the relevant theoretical predictions and also numerical simulations. Hopefully, the demonstrated nonlinear devices, with well-isolated modes, could be used to encode the superconducting qubits for microwave quantum information processing.

Because of the blood–brain barrier (BBB), successful drug delivery to the brain has long been a key objective for the medical community, calling for pioneering technologies to overcome this challenge. Convection-enhanced delivery (CED), a form of direct intraparenchymal microinfusion, shows promise but requires optimal infusate design and real-time distribution monitoring. The size of the infused substances appears to be especially critical, with current knowledge being limited. Herein, we examined the intracranial administration of polyethylene glycol (PEG)-coated nanoparticles (NPs) of various sizes using CED in groups of healthy minipigs (n= 3). We employed stealth liposomes (LIPs, 130 nm) and two gold nanoparticle designs (AuNPs) of different diameters (8 and 40 nm). All were labeled with copper-64 for quantitative and real-time monitoring of the infusion via positron emission tomography (PET). NPs were infused via two catheters inserted bilaterally in the putaminal regions of the animals. Our results suggest CED with NPs holds promise for precise brain drug delivery, with larger LIPs exhibiting superior distribution volumes and intracranial retention over smaller AuNPs. PET imaging alongside CED enabled dynamic visualization of the process, target coverage, timely detection of suboptimal infusion, and quantification of distribution volumes and concentration gradients. These findings may augment the therapeutic efficacy of the delivery procedure while mitigating unwarranted side effects associated with nonvisually monitored delivery approaches. This is of vital importance, especially for chronic intermittent infusions through implanted catheters, as this information enables informed decisions for modulating targeted infusion volumes on a catheter-by-catheter, patient-by-patient basis.

Lipopolysaccharide (LPS) presents a significant threat to human health. Herein, a novel method for detecting LPS was developed by coupling hybridization chain reaction (HCR), gold nanoparticles (AuNPs) agglutination (AA) triggered by a Cu(I)-catalyzed azide–alkyne cycloaddition click chemistry (CuAAC), and electrokinetic accumulation (EA) in a microfluidic chip, termed the HCR–AA–EA method. Thereinto, the LPS-binding aptamer (LBA) was coupled with the AuNP-coated Fe3O4nanoparticle, which was connected with the polymer of H1 capped on CuO (H1–CuO) and H2–CuO. Upon LPS recognition by LBA, the polymers of H1– and H2–CuO were released into the solution, creating a “one LPS-multiple CuO” effect. Under ascorbic acid reduction, CuAAC was initiated between the alkyne and azide groups on the AuNPs’ surface; then, the product was observed visually in the microchannel by EA. Finally, LPS was quantified by the integrated density of AuNP aggregates. The limit of detections were 29.9 and 127.2 fM for water samples and serum samples, respectively. The levels of LPS in the injections and serum samples by our method had a good correlation with those from the limulus amebocyte lysate test (r= 0.99), indicating high accuracy. Remarkably, to popularize our method, a low-cost, wall-power-free portable device was developed, enabling point-of-care testing.

Grain refinement is a crucial technique for enhancing the mechanical properties and corrosion resistance of magnesium alloys. In this study, the addition of 0.3 wt% CaO and 0.3 wt% CaCO3successfully refined the AM60 alloy, resulting in a significant reduction in the average grain size from 326 μm to 96 μm (when adding CaCO3). The refined grain size of the as-cast AM60 alloy led to an increase in both tensile strength and yield strength to 118.2 MPa and 72.6 MPa, representing a respective increase of 35% and 23% compared to the alloy without the refiner. As results of EBSD, it is verified that the basal slip system (0001)<112‾0>has a higher Schmid factor after adding CaO, which indicates that this system has higher activity. The substitution reaction between CaO and Mg can produce synergistic effects from the solute effect of Ca and the nucleating effect of residual CaO, which play an important role in grain refinement. Due to the fine grain size and diffuse distribution of the second phase in the AM60-CaCO3alloy and the thermal decomposition of CaCO3, which consumes the aluminum element in the matrix, the content of the β-phase (Mg17Al12) is reduced. Consequently, this reduces the electric coupling effect between the β-phase and the magnesium matrix. The AM60-CaCO3alloy exhibited the most superior corrosion resistance, achieving a corrosion rate of only 1.01 mm y−1, representing a 48.9% reduction in corrosion rate compared to the AM60 alloy.

Back-contact silicon solar cells, valued for their aesthetic appeal because they have no grid lines on the sunny side, find applications in buildings, vehicles and aircraft and enable self-power generation without compromising appearance1–3. Patterning techniques arrange contacts on the shaded side of the silicon wafer, which offers benefits for light incidence as well. However, the patterning process complicates production and results in power loss. We employed lasers to streamline the fabrication of back-contact solar cells and enhance the power-conversion efficiency. Using this approach, we produced a silicon solar cell that exceeded 27% efficiency. Hydrogenated amorphous silicon layers were deposited onto the wafer for surface passivation and to collect light-generated carriers. A dense passivating contact, which differs from conventional technology practice, was developed. Pulsed picosecond lasers operating at different wavelengths were used to create the back-contact patterns. The approach developed is a streamlined process for producing high-performance back-contact silicon solar cells, with a total effective processing time of about one-third that of the emerging mainstream technology. To meet the terawatt demand, we developed indium-less cells at 26.5% efficiency and precious silver-free cells at 26.2% efficiency. Thus, the integration of solar solutions into buildings and transportation is poised to expand with these technological advances.

We consider the variational structure of a time-fractional second-order mean field games (MFG) system. The MFG system consists of time-fractional Fokker–Planck and Hamilton–Jacobi–Bellman equations. In such a situation, the individual agent follows a non-Markovian dynamics given by a subdiffusion process. Hence, the results of this paper extend the theory of variational MFG to the subdiffusive situation.

We analyze asymptotic convergence properties of Newton’s method for a class of evolutive Mean Field Games systems with non-separable Hamiltonian arising in mean field type models with congestion. We prove the well posedness of the Mean Field Game system with non-separable Hamiltonian and of the linear system giving the Newton iterations. Then, by forward induction and assuming that the initial guess is sufficiently close to the solution of problem, we show a quadratic rate of convergence for the approximation of the Mean Field Game system by Newton’s method. We also consider the case of a nonlocal coupling, but with separable Hamiltonian, and we show a similar rate of convergence.

The failure cause of a tinned copper wire clamp in marine atmosphere was studied systematically by X-ray photoelectron spectroscopy, scanning electron microscopy with energy dispersive spectroscopy and electrochemical measurements. The main components of the green rust on the surface of the damaged wire clamp are SnO2, CuO, Cu2Cl(OH)3and CuCO3(OH)2. Much of green rust distributes at the platform edge along the axial direction on the crimp connection, and severe corrosion and corrosion pits occur at the platform edge zone along the axial direction. The enriching Cl−at the marine atmosphere and the existing O2in air collectively enhance the corrosion process of the tin coating and the copper matrix. Finite element model results show that the residual stress and strain of the tin coating are the largest at the platform edge along the axial direction on the crimp connection, and the corresponding electrode potential of the tin coating at this zone drops significantly. The above results indicate that the residual strain increases the driving force of the corrosion electrochemical reactions and accelerates the corrosion rate and the pit corrosion of the tin coating at this zone.

Deep-learning-based fault diagnosis models perform well when the training and test sets have the same label set. However, these models are invalid in practical applications because they misclassify any unknown faults into existing known classes. An effective diagnosis model for practical industrial applications requires the ability to detect unknown faults as well as maintain high classification accuracy on known faults. To address this challenge, this article proposes a generic open-set classification method for vibration signals. We propose a variational encoder-classifier structure to extract the robust latent features that have different specific distributions with respect to their classes. According to the distances between the latent feature distributions, the samples from unknown faults are rejected using extreme value theory (EVT) and empirical threshold. In addition, we devised an EVT-based instance-level regularization weight function to allow the model to enhance the regularization on the samples that around the known and unknown decision boundaries, which can reduce the risk of bias in the empirical threshold setting caused by the hard training samples. Experimental results on five public rotating machinery vibration datasets reveal that the proposed method achieves the best performance for each dataset. This demonstrates the effectiveness and superiority of the proposed method for practical application scenarios.

Unraveling the atomistic synergistic effects of nanoalloys on the electrocatalytic CO2reduction reaction (eCO2RR), especially in the presence of copper, is of paramount importance. However, this endeavor encounters significant challenges due to the lack of the crystallographically determined atomic-level structure of appropriate monometallic and bimetallic analogues. Herein, we report a one-pot synthesis and structure characterization of a AuCu nanoalloy cluster catalyst, [Au15Cu4(DPPM)6Cl4(C≡CR)1]2+(denoted as Au15Cu4). Single-crystal X-ray diffraction analysis reveals that Au15Cu4comprises two interpenetrating incomplete, centered icosahedra (Au9Cu2and Au8Cu3) and is protected by six DPPM, four halide, and one alkynyl ligand. The Au15Cu4cluster and its closest monometal structural analogue, [Au18(DPPM)6Br4]2+(denoted as Au18), as model systems, enable the elucidation of the atomistic synergistic effects of Au and Cu on eCO2RR. The results reveal that Au15Cu4is an excellent eCO2RR catalyst in a gas diffusion electrode-based membrane electrode assembly (MEA) cell, exhibiting a high CO Faradaic efficiency (FECO) of >90%, and this efficiency is substantially higher than that of the undoped Au18(FECO: 60% at −3.75 V). Au15Cu4exhibits an industrial-level CO partial current density of up to −413 mA/cm2at −3.75 V with the gas CO2-fed MEA, which is 2-fold higher than that of Au18. The density functional theory (DFT) calculations demonstrate that the synergistic effects are induced by Cu doping, where the exposed pair of AuCu dual sites was suggested for launching the eCO2RR process. Besides, DFT simulations reveal that these special dual sites synergistically coordinate a moderate shift in the d-state, thus enhancing its overall catalytic performance.

Trajectory datasets have been widely used in transportation research, but the risk of privacy breach comes with data sharing. Privacy budget allocation is a key step of the differential privacy (DP)-based privacy-preserving data publishing (PPDP) algorithm development, as it directly impacts the data utility of the released dataset. Most prior research used simple logic to allocate privacy budgets, such as evenly distributing them among different tree levels, without theoretical support to reach optimality. This manuscript presents the development of an optimal privacy budget allocation algorithm for transit smart card data, with the goal of publishing non-interactive sanitized trajectory data under a differential privacy definition. To this end, the smart card trajectory data are first stored in a prefix tree structure, and a query probability model is developed to quantitatively measure the probability of a trajectory location pair being queried. Next, the privacy budget is optimized for each prefix tree node to minimize the query error, while satisfying the differential privacy definition. The Lagrangian relaxation method is adopted to derive the optimal privacy budget values, and several propositions on the solution property are proposed and proved. Real-life metro smart card data from Shenzhen, China that include a total of 2.8 million individual travelers and over 220 million records are used in the case study section. The developed algorithm is demonstrated to output a sanitized dataset with the highest utilities when compared with three benchmark algorithms. Sensitivity analysis shows that the resulting data utility remains stable when the privacy budget changes. The runtime of the proposed algorithm is less than 160 seconds in all experiments, exhibiting good computational efficiency.

Small Pd nanoparticles tend to aggregate during the thermal treatment or lose during the reaction process, which lead to the decrease in activity. To solve this problem, the 2D polybenzoxazine-based polymer nanosheets were selected as supports, to prepare carbon supported Pd nanoparticles by the idea of “pyrolysis embedding” in this paper. The polybenzoxazine-based carbon nanosheets supported Pd catalysts were characterized by XRD, FTIR, TEM, SEM, and XPS. The coordination interaction between nitrogen atoms and palladium ions is beneficial for stabilizing Pd nanoparticles. The Pd nanoparticles are uniformly dispersed over the carbon nanosheets, and the average size of the Pd nanoparticles is ~ 2.5 nm. The synthesized catalyst exhibited a remarkable TOF of 1928 h−1with high selectivity to benzaldehyde of > 99% for the aerobic oxidation of benzyl alcohol in aqueous media and also presented good stability.

Most ligand-stabilized metal nanoclusters feature a core–shell or polyhedron-derived metal framework, in which the metal active sites would be blocked by either metal–ligand interfacial shells or surface passive units. We report, in this work, a strategy of largely exposing metal sites and thus promoting catalysis via constructing metal nanoclusters with array-based geometry. Exampled here are a pair of Cu8clusters with polyhedron-derived ([Cu8(RS)6(PPh3)4(MeCN)4H]+, where RS is 3,5-bis(trifluoromethyl)benzenethiol) and array-based ([Cu8(Tf-dpf)4(NO3)2](NO3)2, Tf-dpf is N,N′-di(5-trifluoromethyl-2-pyridyl) formamidinate) structure, respectively. In sharp contrast to the cubic Cu8cluster whose metal core has been totally covered by ligands, the array-based analogue displays largely uncoordinated metal sites. As a result, the array-based Cu8cluster exhibits significantly enhanced activity in catalytic hydrogenation reactions in comparison to the cubic one. In addition, the array-based Cu8cluster shows excellent catalytic performance in the “aldehyde–acetylene–amine” A3-coupling reaction for the synthesis of propargylamines. The reaction can be converted almost perfectly with a rather low amount of cluster, which further reflects its potential catalytic application.

The effects of Na2MoO4and Na2B4O7on corrosion behavior of Q235 steel in resistance reducing agent (RRA) containing sodium bentonite were studied by mass loss, scanning electron microscopy and electrochemical measurement. The results showed that both the independent and mixed additions of Na2MoO4and/or Na2B4O7can reduce the corrosion rate of Q235 steel in RRA containing sodium bentonite. And the inhibition effect of Na2MoO4and/or Na2B4O7increased with their dosage increase. With the same dosage, the inhibition efficiency of the mixed addition of Na2MoO4and Na2B4O7was higher than that of their independent addition. The passivation effect of Q235 steel was easy to obtain in the RRA with the mixed addition of Na2MoO4and Na2B4O7. The optimized inhibitor for the RRA containing sodium bentonite was the mixture of Na2B4O7and Na2MoO4with a total concentration of 1.5 wt.%. Furthermore, the increase in corrosion potentialEcorrand the decrease in corrosion current density icorrin carbon steel were one of the important criteria for the formation of passivation film.

The simultaneous detection of multiple quaternary ammonium pesticides (QAPs) in water is a challenge due to their high solubility in water and similar structures. In this paper, we have developed a quadruple-channel supramolecular fluorescence sensor array for the simultaneous analysis of five QAPs, including paraquat (PQ), diquat (DQ), difenzoquat (DFQ), mepiquat (MQ), and chlormequat (CQ). Not only were QAP samples of different concentrations (10, 50, and 300 μM) in water distinguished with 100% accuracy but also single QAP and binary QAP mixed samples (DFQ-DQ) were sensitively quantified. Our experimental interference study confirmed that the developed array has good anti-interference ability. The array can quickly identify five QAPs in river and tap water samples. In addition, it also qualitatively detected QAP residues in Chinese cabbage and wheat seedlings extract. This array has rich output signals, low cost, easy preparation, and simple technology, demonstrating great potential in environmental analysis.

As chemical pesticides have caused serious environmental pollution, fungus-based biological control has become a developing alternative to chemical control. Here, we aimed to determine the molecular mechanism underlying how Metarhizium anisopliaefacilitated invasive infection. We found that the fungus increased its virulence by downregulating glutathione S-transferase(GST) and superoxide dismutase(SOD) throughout termite bodies. Among 13 fungus-induced microRNAs throughout termite bodies, miR-7885-5p and miR-252b upregulation significantly downregulated several mRNAs in response to toxic substances to increase the fungal virulence [e.g., phosphoenolpyruvate carboxykinase(GTP) and heat shock protein homologue SSE1]. In addition, nanodelivered small interfering RNA of GSTand SODand miR-7885-5p and miR-252b mimics increased the virulence of the fungus. These findings provide new insights into the killing mechanism of entomopathogens and their utilization of the host miRNA machinery to reduce host defenses, laying the groundwork to enhance virulence of biocontrol agents for green pest management.

While atomically monodisperse nanostructured materials are highly desirable to unravel the size- and structure-catalysis relationships, their controlled synthesis and the atomic-level structure determination pose challenges. Particularly, copper-containing atomically precise alloy nanoclusters are potential catalyst candidates for the electrochemical CO2reduction reaction (eCO2RR) due to high abundance and tunable catalytic activity of copper. Herein, we report the synthesis and total structure of an alkynyl-protected 21-atom AgCu alloy nanocluster [Ag15Cu6(C≡CR)18(DPPE)2]−, denoted as Ag15Cu6(HC≡CR: 3,5-bis(trifluoromethyl)phenylacetylene;

The purpose of this study was to identify differences in usage trends for 2 specific pulpal therapy treatments in pediatric patients during an 11-year period from January 1, 2010, through December 31, 2020.

ABSTRACTA tumor’s heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heterogeneous cells, evaluate the clonal origin of cancer cells, and determine the selective evolution of different subpopulations of cancer cells. Researchers are able to trace a cell’s mutation and identify different types of tumor cells by measuring the whole transcriptome with single-cell sequencing (scRNA-seq). This technology provides a better understanding of the molecular mechanisms driving tumor growth than that offered by traditional RNA sequencing methods. In addition, it has revealed changes in the mutations and functions of somatic cells as a tumor evolves; it has also clarified immune cell infiltration and activation. Research on scRNA-seq technology has recently advanced significantly, suggesting new strategies for the treatment of cancer. In short, cancer researchers have become increasingly dependent on scRNA-seq. This paper reviews the development, detection principles, and processes of scRNA-seq technology and their application in tumor research. It also considers potential clinical applications.

The Autonomous Truck Mounted Attenuator (ATMA) vehicle system is a technology that leverages connected and automated vehicle (CAV) capabilities for maintenance of transportation infrastructure. Promoted by FHWA and state departments of transportation (DOTs), it is a niche CAV application in leader–follower style, intended to remove DOT workers from the following maintenance truck, to reduce fatalities in work zones. Because practicable guidance for deployment of this technology is largely missing in MUTCD, state DOTs have been making their own deployment criteria. In this manuscript, we focus on the operational design domain (ODD) problem—under what traffic conditions should ATMA be deployed. Modeling efforts are first focused on the derivation of an effective discharge rate that can be associated with a moving bottleneck caused by slow-moving ATMA vehicles on a multilane highway. Then, based on the demand input and discharge rates, microscopic traffic flow models calculate vehicle delay and density, which the Highway Capacity Manual (HCM) suggests are key indicators of a multilane highway’s level of service (LOS). In this way, the linkage between AADT and LOS is analytically established. NGSIM data is used for the model validation and shows that the developed model correctly captures the effective discharge rate discount caused by moving bottlenecks. The modeling results demonstrate that roadway performance is sensitive to the Kfactor and Dfactor, as well as the operating speed of ATMA and, if LOS = C is a desirable design objective, a good AADT threshold to use would be around 40,000 vehicles per day.