Red Phase Research Articles

Earth May Survive the Sun’s Demise

A distant white dwarf hosts an Earth-like planet in an orbit that might be similar to Earth’s if it survives the Sun’s red giant phase.

Advanced classification of hot subdwarf binaries using artificial intelligence techniques and Gaia DR3 data

Context. Hot subdwarf stars are compact blue evolved objects, burning helium in their cores surrounded by a tiny hydrogen envelope. In the Hertzsprung-Russell Diagram they are located by the blue end of the Horizontal Branch. Most models agree on a quite probable common envelope binary evolution scenario in the Red Giant phase. However, the current binarity rate for these objects is yet unsolved, but key, question in this field. Aims. This study aims to develop a novel classification method for identifying hot subdwarf binaries within large datasets using Artificial Intelligence techniques and data from the third Gaia data release (GDR3). The results will be compared with those obtained previously using Virtual Observatory techniques on coincident samples. Methods. The methods used for hot subdwarf binary classification include supervised and unsupervised machine learning techniques. Specifically, we have used Support Vector Machines (SVM) to classify 3084 hot subdwarf stars based on their colour-magnitude properties. Among these, 2815 objects have Gaia DR3 BP/RP spectra, which were classified using Self-Organizing Maps (SOM) and Convolutional Neural Networks (CNN). In order to ensure spectral quality, previously to SOM and CNN classification, our 2815 BP/RP set were pre-analysed with two different approaches: the cosine similarity technique and the Uniform Manifold Approximation and Projection (UMAP) technique. Additional analysis onto a golden sample of 88 well-defined objects, is also presented. Results. The findings demonstrate a high agreement level (∼70–90%) with the classifications from the Virtual Observatory Sed Analyzer (VOSA) tool. This shows that the SVM, SOM, and CNN methods effectively classify sources with an accuracy comparable to human inspection or non-AI techniques. Notably, SVM in a radial basis function achieves 70.97% reproducibility for binary targets using photometry, and CNN reaches 84.94% for binary detection using spectroscopy. We also found that the single–binary differences are especially observable on the infrared flux in our Gaia DR3 BP/BR spectra, at wavelengths larger than ∼700 nm. Conclusions. We find that all the methods used are in fairly good agreement and are particularly effective to discern between single and binary systems. The agreement is also consistent with the results previously obtained with VOSA. In global terms, considering all quality metrics, CNN is the method that provides the best accuracy. The methods also appear effective for detecting peculiarities in the spectra. While promising, challenges in dealing with uncertain compositions highlight the need for caution, suggesting further research is needed to refine techniques and enhance automated classification reliability, particularly for large-scale surveys.

Widely Untargeted Metabolomics Profiling Combined with Transcriptome Analysis Provides New Insight into Amino Acid Biosynthesis at Different Developmental Stages of Rubus Chingii Hu (Chinese Raspberry).

The composition and profile of amino acids in Rubus chingii (R. chingii) Hu serve as critical indicators of its nutritional quality. A comprehensive understanding of the amino acid metabolism within R. chingii is instrumental in the formulation and innovation of functional foods derived from this species. Utilizing advanced techniques such as wide-ranging untargeted metabolomics, transcriptome analysis, interaction network mapping, heat map analysis, and quantitative real-time PCR, we conducted a comprehensive assessment of the quality attributes across four distinct developmental stages of R. chingii. Our meticulous analysis uncovered a rich tapestry of 76 distinct amino acids and their derivatives within the developmental stages of R. chingii. The spectrum of essential amino acids was not only broad but also displayed a high degree of variety. Notably, leucine, lysine, and phenylalanine stood out as the most abundant amino acids, underscoring their significant presence throughout the growth cycle of R. chingii. The proportion of essential amino acids relative to the total amino acid content in R. chingii exhibited a notable trajectory of change throughout its developmental stages. It began with 30.92% in the immature green phase, advanced to 31.04% during the transition from green to yellow, peaked at 33.62% in the yellow to red stage, and then moderated to 30.43% in the full red phase. This pattern suggests a strategic modulation of amino acid composition, aligning with the evolving nutritional requirements and metabolic shifts as the fruit matures. Concurrent analysis of interaction networks and heat maps, alongside comprehensive profiling of amino acid metabolism and transcriptomic examination, was conducted to elucidate the intricate dynamics of cellular processes. The results showed that seven differentially expressed genes (DEGs) played important roles in amino acid metabolism, including PFK, BCAT1, TSB, ASA, ACO, TOM2AH3, and BCAT2. The expression patterns of seven DEGs conformed closely to the findings revealed by the preceding RNA-seq analysis. In this investigation, we elucidated the regulatory mechanisms underlying amino acid metabolism across the four distinct developmental stages of R. chingii through comprehensive amino acid profiling and transcriptomic analysis. These insights lay the groundwork for the development of novel functional food applications utilizing R. chingii.

The MIRI Exoplanets Orbiting White dwarfs (MEOW) Survey: Mid-infrared Excess Reveals a Giant Planet Candidate around a Nearby White Dwarf

The MIRI Exoplanets Orbiting White dwarfs survey is a cycle 2 JWST program to search for exoplanets around dozens of nearby white dwarfs via infrared excess and direct imaging. In this Letter, we present the detection of mid-infrared excess at 18 and 21 μm toward the bright (V = 11.4) metal-polluted white dwarf WD 0310–688. The source of the IR excess is almost certainly within the system; the probability of background contamination is <0.1%. While the IR excess could be due to an unprecedentedly small and cold debris disk, it is best explained by a 3.0−1.9+5.5 M Jup cold (248 −61+84 K) giant planet orbiting the white dwarf within the forbidden zone (the region where planets are expected to be destroyed during the star’s red giant phase). We constrain the source of the IR excess to an orbital separation of 0.1–2 au, marking the first discovery of a white dwarf planet candidate within this range of separations. WD 0310–688 is a young remnant of an A- or late B-type star, and at just 10.4 pc, it is now the closest white dwarf with a known planet candidate. Future JWST observations could distinguish the two scenarios by either detecting or ruling out spectral features indicative of a planet atmosphere.

Non-thermal radio emission in Sakurai's Object

The very late thermal pulse (VLTP) affects the evolution of sim 20&lt;!PCT!&gt; of 1--8\,$ M_ stars, repeating the last red giant phases within a few years and leading to the formation of a new, but hydrogen-poor, nebula within the old planetary nebula. The strong dust formation in the latter obscures the optical and near-infrared radiation of the star. We aimed to determine the reheating timescale of the central star in Sakurai's Object, which is an important constraint for the poorly understood VLTP evolution. We observed the radio continuum emission of Sakurai's Object for almost 20 years, from 2004 to 2023. Continuous, multi-frequency observations proved to be essential for distinguishing between phases dominated by photoionization and shock ionization. The flux density fluctuates by more than a factor of 40 within months to years. The spectral index remained negative between 2006 and 2017 and has been close to zero since 2019. The emission region has been only barely resolved since 2021. Non-thermal radio emission observed from 2004 to 2017 traces shocks induced by wind interactions due to discrete mass-loss events. Thermal emission dominates from 2019 to 2023 and may indicate photoionization of the nebula by the central star.

Reversible electronic modulation of polydiacetylenes for sensing in dynamic conditions

AbstractPolydiacetylenes (PDAs) are renowned for their exceptional optical properties intricately linked to the polymer conformation, yet they exhibit poor conductivity in their undoped state. Despite this drawback, PDAs have garnered significant interest as sensing materials owing to their ability to undergo colorimetric shifts from blue to red in response to external stimuli. However, the irreversible nature of this transition has limited their utility in dynamic environments. In this study, we augment the sensing capabilities of PDA films beyond their irreversible optical response by inducing a reversible electronic response through conductivity modulation. We investigated polyamine‐substituted PDAs with enriched hydrogen‐bonding interaction sites for the concurrent changes in colorimetry and conductivity upon acetic acid (AA) vapor exposure. Coated on a flexible interdigitated electrode (IDE), we monitor the conductivity change throughout the blue‐to‐red phase transition. Remarkably, AA molecules act as dopants, significantly amplifying the system's conductivity. Although the PDA coating retains its red phase at postdopant removal, the electronic response reverts to its initial state, demonstrating reversibility. This reversible electronic response offers invaluable real‐time insights into the specific triggers within dynamic environments, underscores the adaptability of responsive conjugated polymers, and highlights a promising avenue for their utilization in various sensing and monitoring applications.

Design and Construction of a Smart Energy Theft Detector on Distribution Lines

This work presents the design and construction of a smart energy theft detector on distribution lines. The escalating challenge of power theft within distribution lines necessitates innovative solutions to safeguard the integrity of power distribution networks. Atmega328-P, Arduino-uno Micro-processor was interphase with Bluetooth module to detect energy theft. Proteus professional software was deployed to determine the functionality of the smart energy theft detector. The work was tested and the result obtained showed a stand-alone system capable of detecting energy theft on different phases of the distribution network. The information sent to the utility operator’s liquid crystal display (LCD) indicates theft detected on either red, blue or yellow phase.

DCoMA: A dynamic coordinative merging assistant strategy for on-ramp vehicles with mixed traffic conditions

Merging sections on highways are identified as traffic bottlenecks, leading to congestion and accidents. The emergence of Connected and Autonomous Vehicles (CAVs) technology promises an optimized solution to on-ramp merging issues. Existing cooperative merging strategies typically focus on determining the merging sequence of vehicles in specific merging areas, overlooking the influence of the macroscopic traffic flow conditions on the merging process. In this paper, we innovatively introduce the Dynamic Cooperative Merging Assistance (DCoMA) strategy, a traffic management approach designed to enhance merging operations under variable traffic demands. At the macroscopic level, DCoMA employs the fundamental diagram of traffic flow to develop a platoon formation algorithm for mainline vehicles, tailored to the dynamic macroscopic states of traffic. The algorithm adaptively adjusts the size of platoons based on the volumes of both the mainline and the on-ramp. Subsequently, the spatio-temporal dynamics of these platoons function as the ’red phase’ of traffic signals, with the intervals between platoons analogous to the ’green phase’. This information is then converted into a time-series format and transmitted to all vehicles on the on-ramp. At the microscopic level, vehicles on the on-ramp alter their driving strategies in response to this time-series data, ensuring a seamless merging into the mainline flow without causing halting. Through simulations and comparative analysis with three existing strategies (i.e., CoopMA, ALINEA, and X-ALINEAQ), the proposed DCoMA strategy exhibits considerable potential for application across diverse traffic volumes and CAV penetration rates. The results indicate that the proposed approach can significantly improve the efficiency of the mainline and on-ramp, achieving a maximum improvement of 18.32%. More importantly, the DCoMA strategy effectively enlarges merging gaps and, coupled with the speed control capabilities of CAVs, significantly mitigates the risk of accidents and reduces exhaust emissions.

Drone-based early detection of bark beetle infested spruce trees differs in endemic and epidemic populations

IntroductionEuropean forests face increasing threats due to climate change-induced stressors, which create the perfect conditions for bark beetle outbreaks. The most important spruce forest pest in Europe is the European Spruce Bark Beetle (Ips typographus L.). Effective management of I. typographus outbreaks necessitates the timely detection of recently attacked spruce trees, which is challenging given the difficulty in spotting symptoms on infested tree crowns. Bark beetle population density is one of many factors that can affect infestation rate and symptoms development. This study compares the appearance of early symptoms in endemic and epidemic bark beetle populations using highresolution Unmanned Aerial Vehicles (UAV) multispectral imagery.MethodsIn spring of 2022, host colonization by bark beetles was induced on groups of spruce trees growing in 10 sites in the Southern Alps, characterized by different population density (5 epidemic and 5 endemic). A multispectral sensor mounted on a drone captured images once every 2 weeks, from May to August 2022. The analyses of a set of vegetational indices allowed the actual infested trees’ reflectance features and symptoms appearance to be observed at each site, comparing them with those of unattacked trees.ResultsResults show that high bark beetles population density triggers a more rapid and intense response regarding the emergence of symptoms. Infested trees were detected at least 1 month before symptoms became evident to the human eye (red phase) in epidemic sites, while this was not possible in endemic sites. Key performing vegetation indices included NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjust Vegetation Index, with a correction factor of 0.44), and NDRE (Normalized Difference Red Edge index).DiscussionThis early-detection approach could allow automatic diagnosis of bark beetles’ infestations and provide useful guidance for the management of areas suffering pest outbreaks.

Mechanical Properties of Polydiacetylene Multilayers Studied by AFM Force Spectroscopy.

The blue-to-red chromatic phase transition of polydiacetylene (PDA) is accompanied by the twist and rearrangement of its side chains, which results in shortening of the conjugation length in the backbone. However, how these morphological changes affect its mechanical properties remains elusive. In this work, force spectroscopy mapping by atomic force microscopy was employed to quantify mechanical parameters of PDA thin films such as breakthrough force and Young's modulus at the monomer, blue, and red phases during the chromatic transition. We found that the breakthrough force increased by 113% and Young's modulus decreased by 21% during the blue-to-red transition, highlighting that the subtle change in the side-chain configuration has a dramatic impact on its mechanical properties.

Probing the inner Galactic halo with blue horizontal-branch stars

Context. Stars that are found on the blue horizontal-branch (BHB) evolved from low-mass stars that have completed their core hydrogen-burning main sequence (MS) stage and undergone the helium flash at the end of their red giant phase. Hence, they are very old objects that can be used as markers in studying galactic structure and formation history. The fact that their luminosity is virtually constant at all effective temperatures also makes them good standard candles. Aims. We have compiled a catalogue of BHB stars with stellar parameters calculated from spectral energy distributions (SEDs) constructed using data from multiple large-scale photometric surveys. In addition, we update our previous Gaia Early Data Release 3 (EDR3) catalogue of BHB stars with parallax errors less than 20% by using the SED results to define the selection criteria. The purpose of these catalogues is to create a set of BHB star candidates with reliable stellar parameters. In addition, they provide a more complete full-sky catalogue with candidate objects found along the whole BHB from where RR-Lyrae are found on the instability strip to the extreme horizontal-branch (EHB). Methods. We selected a large dataset of Gaia Data Release 3 (DR3) objects based only on their position on the colour-magnitude diagram (CMD), along with the tangential velocity and parallax errors. The SEDs were then used to evaluate contamination levels in the dataset and derive optimised data quality acceptance constraints. This allowed us to extend the Gaia DR3 colour and absolute magnitude criteria further towards the EHB. The level of contamination found using SED analysis was confirmed by acquiring spectra using the Ondrejov Echelle spectrograph, attached to the Perek 2m telescope at the Astronomical Institute of the Czech Academy of Sciences. Results. We present a catalogue of 9172 Galactic halo BHB candidate stars with atmospheric and stellar parameters calculated from synthetic SEDs. We also present an extended Gaia DR3-based catalogue of 22 335 BHB candidate stars with a wider range of effective temperatures and Gaia DR3 parallax errors of less than 20%. This represents an increase of 33% compared to the our 2021 catalogue, with a contamination level of 10%.

Simple analytical models for estimating the queue lengths from probe vehicles at traffic signals: A combinatorial approach for nonparametric models

This study develops a combinatorial approach for nonparametric short-term queue length estimation in terms of cycle-by-cycle partially observed queues from probe vehicles (PV). The method does not assume random arrivals and does not assume any primary parameters or estimation of any parameters but uses simple algebraic expressions that only depend on signal timing. For an approach lane at a traffic intersection, the conditional queue lengths given probe vehicle location, count, time, and analysis interval (e.g., at the end of the red signal phase) are represented by a Negative Hypergeometric distribution. The simple analytical estimators obtained are compared with parametric methods from literature and highway capacity manual methods using field test data and simulation data involving probe vehicles. The analysis indicates that the nonparametric models presented in this paper match the accuracy of the parametric ones used in the field test and simulated data for estimating queue lengths.

Fossil Signatures of Main-sequence Convective Core Overshoot Estimated through Asteroseismic Analyses

Some physical processes that occur during a star's main-sequence evolution also affect its post-main-sequence evolution. It is well known that stars with masses above approximately 1.1 M ⊙ have well-mixed convective cores on the main sequence; however, the structure of the star in the neighborhood of the convective core regions is currently underconstrained. We use asteroseismology to study the properties of the stellar core, in particular convective boundary mixing through convective overshoot, in such intermediate-mass stars. These core regions are poorly constrained by the acoustic (p) mode oscillations observed for cool main-sequence stars. Consequently, we seek fossil signatures of main-sequence core properties during the subgiant and early first-ascent red giant phases of evolution. During these stages of stellar evolution, modes of mixed character that sample the deep interior can be observed. These modes sample the parts of the stars that are affected by the main-sequence structure of these regions. We model the global and near-core properties of 62 subgiant and early first-ascent red giant branch stars observed by the Kepler, K2, and TESS space missions. We find that the effective overshoot parameter, α ov,eff, increases from M = 1.0 M ⊙ to M = 1.2 M ⊙ before flattening out, although we note that the relationship between α ov,eff and mass will depend on the incorporated modeling choices of internal physics and nuclear reaction network. We also situate these results within existing studies of main-sequence convective core boundaries.

Intelligent Traffic Management System to Improve Mobility at Ayigya, a Commuter City in Ghana

The issue of vehicular traffic congestion is faced by most road users all over the world, including Ghana. The complications intensify day in and day out, especially in most urban areas, due to development and urbanization. The exponential increase in road users awakens concern for an effective road transportation system to convey people and goods from one place to another. In an attempt to mitigate the effect of the problem, a system based on a statistically programmed lighting sequence was introduced. This technique served its purpose for some time and was realized to be inefficient because it controlled traffic flow by assigning a fixed amount of green light time to each phase of traffic, which meant that green light time was sometimes given to lanes even when there was no conflicting traffic. The persistent nature of the problem requires the need for an intelligent traffic management system to effectively coordinate the flow of vehicles through the available road network. The proposed system works based on priority queuing, where green and red phases are dynamically assigned to lanes depending on the present traffic volume. The proposed system uses two methods of counting to determine the highest lane count. They are the Digital Vehicle Counting (DVC) and the Manuel Vehicle Counting (MVC) methods. An effective detection zone of sixty meters is declared away from the traffic intersection. The values produced by both counting methods are fed to the Traffic Phase Router (TPR) for comparison. The lane with the highest vehicle counts from both counters is given the chance to leave the intersection. The proposed system was designed using Simulation of Urban Mobility (SUMO) software. Results obtained after the simulation showed that the proposed system performed better than the existing system based on the Key Performance Indicators (KPIs) used.

Lithium-rich Cepheid V470 Cas

In this Letter, we report the discovery of a new lithium-rich yellow supergiant star -- the Cepheid V470 Cas -- that has a high lithium abundance, $ A(Li)$ = 3.29. This is highly unusual for supergiant stars. V470 Cas is joining a very select group of lithium-rich Cepheids, with only nine members known to date in our Galaxy. For the analysis of our high-resolution echelle spectrum obtained at the Canada-France-Hawaii Telescope, methods based on both local thermodynamic equilibrium (LTE) and non-local thermodynamic equilibrium (NLTE) assumptions were applied. In particular, the lithium abundance was derived by analysing the equivalent width of the 6707 line. Most lithium-rich Cepheids are located near the blue edge of the instability strip near the bottom of the Hertzsprung--Russell diagram. Their main sequence progenitors are distributed over a mass range of three to five solar masses. Of the nine lithium-rich Cepheids known, six are double-mode pulsators, including our programme Cepheid. It is very likely that the stars of this small group are entering the instability strip for the first time and have not yet passed the red giant phase. Therefore, they have not experienced the large-scale mixing event that could destroy lithium in their convective zones.

Assessment of time allocated to pedestrian crossing: a study in pre-schoolers

It is assumed that a crossing speed of 1.2 m/s ensures safe pedestrian crossing. However, this walking pace might not be suitable for preschoolers. We sought to identify whether the time allocated to pedestrian crossing in the crosswalks with pedestrian crossing lights in an urban area, was enough to allow safe passage of the pre-schoolers. For this purpose, we assessed the mean walking speed of 48 pre-schoolers, and their reaction time. The time elapsed from the onset of the green man phase to the onset of the red man phase of 50 crosswalks located in three Spanish cities was registered. The results indicated a mean walking speed of 0.88 ± 0.2 m/s that was not considered sufficient to ensure safe crossing in 38% of the crosswalks analysed. According to the obtained data, a crossing speed of 1.2 m/s was not considered to be appropriate to ensure safe crossing among pre-schoolers.

Trajectory-based vehicle emission evaluation for signalized intersection using roadside LiDAR data

Signalized intersections are the bottleneck of urban traffic network and often lead to traffic congestion and increased traffic emissions. Studying and analyzing the spatiotemporal emission patterns at intersections is the prerequisite for traffic emission reduction. This study develops a novel framework for vehicle emission estimation using high-resolution trajectory data based on the roadside light detection and ranging sensor. A meshing method was proposed to divide the area and the trajectory repair model was developed by considering multiple influenced factors to obtain refined LiDAR trajectory data. Then, the Virginia Tech microscopic model was used to perform traffic emission spatiotemporal analysis. In the experiments, trajectory repair results indicate that Root Mean Square Error and Mean Absolute Error are 1.1299m and 0.7816m within 3s, which has excellent prediction accuracy and provides a reliable data basis for accurately estimating emissions. Emission results show that vehicle speed and acceleration are positively correlated with emissions, with the highest emissions generated during acceleration, of which CO could reach 0.0037 g/s. From a temporal perspective, emissions gradually decrease during red light phases and increase when vehicles accelerate during green light phases, suggesting recommendations for signal optimization for areas where emissions exceed standards to reduce vehicle's start and stop. From a spatial perspective, emission rates are highest in the downstream area, with CO reaching more than 0.0043 g/s. It can be suggested that relevant authorities could install speed limit signs or plant trees in this area. Overall, these findings have the potential to alleviate emission pressures at intersections.

Constraining stellar and orbital co-evolution through ensemble seismology of solar-like oscillators in binary systems

Context. Binary systems constitute a valuable astrophysics tool for testing our understanding of stellar structure and evolution. Systems containing at least one oscillating component are interesting in this regard because asteroseismology offers independent parameters for the oscillating component that aid in the analysis. Systems of particular interest include those with known inclinations. With ∼0.8 million binary candidates, the two-body orbit catalog (TBO) of Gaia Data Release 3 (DR3) substantially increases the number of known binaries and the quality of the astrometric data available for them. Aims. To enlarge the sample of these astrophysically valuable benchmark objects, we searched for new binary system candidates identified in the Gaia DR3 TBO, for which one component has a detection of solar-like oscillations reported in the literature. Methods. We cross-matched the TBO, the full non-single star (NSS) and eclipsing binary catalogs from Gaia DR3 with catalogs of confirmed solar-like oscillators in the main-sequence and red-giant phase from the NASA Kepler mission and stars in the Southern Continuous Viewing Zone of NASA TESS. The wealth of seismic information is used to characterize the oscillating primary. To test the completeness and robustness of the values reported in the TBO catalog, we performed a similar analysis on stars of the Ninth Catalog of Spectroscopic Binary Orbits (SB9). Results. The analysis of the SB9 reveals an overall completeness factor for the Gaia TBO catalog of up to ∼30% providing reliable orbital parameters for ≥90% of the systems below Porb, SB9 ≲ 250 d. We obtained new 954 unique binary system candidates from Gaia DR3, which host solar-like oscillators, of which we found 45 stars in binary candidates to be on the main sequence and 909 in the red giant phase. Additionally, we report 918 oscillators in potentially long-periodic systems. We present the seismic properties of the full sample and test whether the reported orbital periods are physically possible. For 146 giants, the evolutionary state has been determined from their mixed-mode period spacing, showing a clear trend to long periodic and less eccentric systems in the advanced phases of stellar evolution. Two new eclipsing binary systems, hosting a red-giant primary were found. For another 146 systems hosting oscillating stars, the values for the orbital inclination were found in the TBO. Of 181 TBO candidate systems observed multiple times with APOGEE, 149 (82%) are confirmed as binaries from radial-velocity (RV) measurement. Conclusions. We conclude that the grand majority of the orbital elements reported in the TBO catalog are physically reasonable and realistic. This finding increases the number included in the sample of known solar-like oscillators in binary systems by an order of magnitude. The large fraction of confirmed binaries from APOGEE RV measurements indicates that the TBO catalog is robust. We suggest that due to instrumental noise, the seismically inferred masses and radii of stars observed with the TESS satellite and with an excess of oscillation power of νmax ≲ 30 μHz could be significantly overestimated. The differences in the distributions of the orbital period and eccentricity are due to the accumulative effect of the equilibrium tide acting in these evolved binary systems.

Comparative and Microscopic Analysis of Vehicle Startup Behavior in Red Countdown Traffic Lights with Various Display Forms

Background: Countdown-type traffic lights provide drivers with the time remaining before the signal turns green or red. Most countdown devices inform the drivers of the exact signal switching time numerically on a display form. This study focuses on two vehicle startup behaviors when a red signal phase countdown (RC) is displayed: a premature start (PS) and an early reaction (ER). The PS is a vehicle crossing the stop line before the green phase, and the ER is a vehicle starting to move before the green phase. While there are many studies on PS rates under RC, there are only a few studies on ER rates. There are also few studies that have analyzed the relationship between the PS and ER rates and the display forms of RC have also been analyzed in terms of micro-behavior. Objective: This study microscopically analyzes the ER and PS by including data within 1 second at signal switching while comparing 10 types of display forms in RC in order to obtain the ideas of safer and more efficient display forms in signal countdown. Methods: We conducted the experiments with RC traffic lights of different display forms, and the surveys of no countdown (NC). Results: From the very limited conditions of the experiment, we found that there is a threshold at which the ER rates in RC and NC differ significantly. Conclusion: We were also able to analyze the basic characteristics related to the display forms of RC, which is a quick start and which reduces PS and ER.

Process Optimization and Equilibrium, Thermodynamic, and Kinetic Modeling of Toxic Congo Red Dye Adsorption from Aqueous Solutions Using a Copper Ferrite Nanocomposite Adsorbent.

In the present investigation of copper ferrite, a CuFe2O4 nanocomposite adsorbent was synthesized using the sol-gel method, and its relevance in the adsorptive elimination of the toxic Congo red (CR) aqueous phase was examined. A variety of structural methods were used to analyze the CuFe2O4 nanocomposite; the as-synthesized nanocomposite had agglomerated clusters with a porous, irregular, rough surface that could be seen using FE-SEM, and it also contained carbon (23.47%), oxygen (44.31%), copper (10.21%), and iron (22.01%) in its elemental composition by weight. Experiments were designed to achieve the most optimized system through the utilization of a central composite design (CCD). The highest uptake of CR dye at equilibrium occurred when the initial pH value was 5.5, the adsorbate concentration was 125 mg/L, and the adsorbent dosage was 3.5 g/L. Kinetic studies were conducted, and they showed that the adsorption process followed a pseudo-second-order (PSO) model (regression coefficient, R2 = 0.9998), suggesting a chemisorption mechanism, and the overall reaction rate was governed by both the film and pore diffusion of adsorbate molecules. The process through which dye molecules were taken up onto the particle surface revealed interactions involving electrostatic forces, hydrogen bonding, and pore filling. According to isotherm studies, the equilibrium data exhibited strong agreement with the Langmuir model (R2 = 0.9989), demonstrating a maximum monolayer adsorption capacity (qmax) of 64.72 mg/g at pH 6 and 302 K. Considering the obtained negative ΔG and positive ΔHads and ΔSads values across all tested temperatures in the thermodynamic investigations, it was confirmed that the adsorption process was characterized as endothermic, spontaneous, and feasible, with an increased level of randomness. The CuFe2O4 adsorbent developed in this study is anticipated to find extensive application in effluent treatment, owing to its excellent reusability and remarkable capability to effectively remove CR in comparison to other adsorbents.