Nearby States Research Articles

Economic Impact of Periphyton-Based Stunted Fingerling Production in Arunachal Pradesh, India

Non availability of right type quality seed at right time in required quantity is major bottleneck for the growth of aquaculture in Arunachal and major portion of seed are being import from other nearby state especially Assam in particular. To make availability of good quality seed at right time having a regional acclimation for a longer duration in far flung areas of the state, the present investigation was conducted on low cost Periphyton (grown on paddy straw) based stunted yearling production technology to improve the survival and health of stocked material and their economic impact on the fish farmers of district West Kameng during 2018-2021. The average values of pond water quality parameters were observed to vary between both the culture ponds with a significant seasonal differences at all the sites and there were found a greater difference in average survival rate of both the commodities i.e. table size fish as well as stunted yearling during whole culture period. The involved cost of cultivation was recorded higher Rs. 4,70,000 / ha in stunted yearling culture in comparison to Rs.424,940/ha in thetable size carp culture while average gross benefit was just opposite, recorded higher Rs. 6,90,000/ ha in stunted yearling culture in comparison to Rs.199,960/ ha in table size carp culture with the same trend in BCR i.e. 2.46 for stunted fingerling production and 1.47 in the production of table size fishes respectively.

Defining Stable Phases of Open Quantum Systems

The steady states of dynamical processes can exhibit stable nontrivial phases, which can also serve as fault-tolerant classical or quantum memories. For Markovian quantum (classical) dynamics, these steady states are extremal eigenvectors of the non-Hermitian operators that generate the dynamics, i.e., quantum channels (Markov chains). However, since these operators are non-Hermitian, their spectra are an unreliable guide to dynamical relaxation timescales or to stability against perturbations. We propose an alternative dynamical criterion for a steady state to be in a stable phase, which we name uniformity: Informally, our criterion amounts to requiring that, under sufficiently small local perturbations of the dynamics, the unperturbed and perturbed steady states are related to one another by a finite-time dissipative evolution. We show that this criterion implies many of the properties one would want from any reasonable definition of a phase. We prove that uniformity is satisfied in a canonical classical cellular automaton, and we provide numerical evidence that the gap determines the relaxation rate between nearby steady states in the same phase, a situation we conjecture holds generically whenever uniformity is satisfied. We further conjecture some sufficient conditions for a channel to exhibit uniformity and therefore stability. Published by the American Physical Society 2024

Strongly Rotationally Dependent Lifetimes of C2 in the 23Σg- State: Implications for Predissociation in the Vacuum Ultraviolet Region.

The radiative and photodissociative properties of the dicarbon molecule, C2, in high-lying electronic states are of utmost importance for modeling the photochemical processes that occur in various astronomical environments. Despite extensive spectroscopic studies in the last two centuries, the photodissociation properties of C2 are still largely unknown, particularly for quantum states in the vacuum ultraviolet (VUV) region. Here, the lifetimes of C2 for each individual rovibrational level in the recently identified 23Σg- state are measured for the first time using a VUV-pump-UV-probe photoionization scheme. The lifetimes are found to be strongly dependent on the rotational and vibrational quantum levels in the 23Σg- state. The strongly rotationally dependent lifetimes observed here indicate that the 23Σg- state may mainly undergo a predissociation process through couplings with nearby repulsive electronic states. The current observation could have important applications in modeling the interstellar medium and cometary comae.

Are intersectoral GDP contributions similar with nearby states? A semi-model-based spatial cluster analysis

ABSTRACT Intersectoral Gross Domestic Product (GDP) contributions reflect economic development in different industries. A good understanding of clusters of intersectoral GDP contributions among different subregions plays a vital role in making local policies and building economic development strategies. We propose a semi-model-based clustering method, i.e, a Markov random field constraint mixture of finite mixtures model to tackle this issue. Our proposed method has the advantage of 1) data-driven determination of the final number of clusters and 2) allowing for both locally spatially contiguous clusters and globally discontiguous clusters. Posterior inference is performed with an efficient Markov chain Monte Carlo (MCMC) algorithm. We demonstrate the performance of the proposed method using both simulation studies and a real-world example where intersectoral GDP contribution of year 2019 data, obtained from the U.S. Bureau of Economic Analysis, is studied.

Diffraction order penalization to improve spectrometer calibrations

Wavelength calibration in diffraction spectroscopy typically depends on identifying strong, well-known lines in the recorded spectra and fitting a calibration function to them. In this paper, we outline a novel method (order penalization) for improving spectroscopic calibrations by extending non-linear least squares fitting of the calibration curve. The method introduces an extra term into the minimized quantity that penalizes disagreement in the positions of spectral lines observed in multiple diffraction orders. The primary advantage of this method is that the lines used do not have to be identified, except for establishing the fact that they are different orders of the same line. This increases the number of constraints on the calibration curve, potentially in spectral regions where no regular calibration lines are available. The mathematical basis of this method is described, and the performance of this method is evaluated on simulated data and experimental data from the National Institute of Standards and Technology (NIST) Electron Beam Ion Trap. We demonstrate the effectiveness of the method on the spectra of highly charged Ag-like Re28+ and nearby charge state ions.

Estimating metastable thermodynamic properties by isochoric extrapolation from stable states.

The description of metastable fluids, those in local but not global equilibrium, remains an important problem of thermodynamics, and it is crucial for many industrial applications and all first order phase transitions. One way to estimate their properties is by extrapolation from nearby stable states. This is often done isothermally, in terms of a virial expansion for gases or a Taylor expansion in density for liquids. This work presents evidence that an isochoric expansion of pressure at a given temperature is superior to an isothermal density expansion. Two different isochoric extrapolation strategies are evaluated, one best suited for vapors and one for liquids. Both are exact for important model systems, including the van der Waals equation of state. Moreover, we present a simple method to evaluate all the coefficients of the isochoric expansion directly from a simulation in the canonical ensemble. Using only the properties of stable states, the isochoric extrapolation methods reproduce simulation results with Lennard-Jones potentials, mostly within their uncertainties. The isochoric extrapolation methods are able to predict deeply metastable pressures accurately even from temperatures well above the critical. Isochoric extrapolation also predicts a mechanical stability limit, i.e., the thermodynamic spinodal. For water, the liquid spinodal pressure is predicted to be monotonically decreasing with decreasing temperature, in contrast to the re-entrant behavior predicted by the direct extension of the reference equation of state.

Compound-Nucleus and Doorway-State Decays of β-Delayed Neutron Emitters ^{51,52,53}K.

We investigated decays of ^{51,52,53}K at the ISOLDE Decay Station at CERN in order to understand the mechanism of the β-delayed neutron-emission (βn) process. The experiment quantified neutron and γ-ray emission paths for each precursor. We used this information to test the hypothesis, first formulated by Bohr in 1939, that neutrons in the βn process originate from the structureless "compound nucleus." The data are consistent with this postulate for most of the observed decay paths. The agreement, however, is surprising because the compound-nucleus stage should not be achieved in the studied β decay due to insufficient excitation energy and level densities in the neutron emitter. In the ^{53}K βn decay, we found a preferential population of the first excited state in ^{52}Ca that contradicted Bohr's hypothesis. The latter was interpreted as evidence for direct neutron emission sensitive to the structure of the neutron-unbound state. We propose that the observed nonstatistical neutron emission proceeds through the coupling with nearby doorway states that have large neutron-emission probabilities. The appearance of "compound-nucleus" decay is caused by the aggregated small contributions of multiple doorway states at higher excitation energy.

Coexistence of Ferromagnetism and Superconductivity at KTaO3 Heterointerfaces.

The coexistence of superconductivity and ferromagnetism is a long-standing issue in superconductivity due to the antagonistic nature of these two ordered states. Experimentally identifying and characterizing novel heterointerface superconductors that coexist with magnetism presents significant challenges. Here, we report the observation of two-dimensional long-range ferromagnetic order in a KTaO3 heterointerface superconductor, showing the coexistence of superconductivity and ferromagnetism. Remarkably, our direct current superconducting quantum interference device measurements reveal an in-plane magnetization hysteresis loop persisting above room temperature. Moreover, first-principles calculations and X-ray magnetic circular dichroism measurements provide decisive insights into the origin of the observed robust ferromagnetism, attributing it to oxygen vacancies that localize electrons in nearby Ta 5d states. Our findings suggest KTaO3 heterointerfaces as time-reversal symmetry breaking superconductors, injecting fresh momentum into the exploration of the intricate interplay between superconductivity and magnetism enhanced by the strong spin-orbit coupling inherent to the heavy Ta in 5d orbitals.

CN stretches around 4.4 microns dominate the IR absorption spectra of cyano-polycyclic aromatic hydrocarbons

ABSTRACT Anharmonic quantum chemical computations reveal a strong, narrow (width = 0.075 $\mu$m) band in the 4.3–4.5 $\mu$m region of the absorption spectra of the cyano-substituted polycyclic aromatic hydrocarbons (CN-PAHs) cyanonaphthalene, cyanoanthracene, cyanophenanthrene, and cyanopyrene. This narrow window with intense IR lines implies that CN-PAHs of various shapes and sizes offer little variation in both wavelength and intensity in this region. Subsequently, this band can be used as a tracer for CN-PAHs. The distinct features making up the band are assigned to mixed vibrational states consisting of the CN stretch fundamental and various combination bands, including in-plane CH bends, CC skeletal bends, and CC skeletal breathing motions. The extraordinarily large intrinsic intensity of the fundamental CN stretch is redistributed to nearby states via anharmonic coupling, which is readily captured when using second order vibrational perturbation theory with resonance polyad matrices. This redistribution of intensity leads to a complex spectrum. The intense bands in this wavelength region may contribute to the baseline continuum and undulating macroscopic structure seen in recent JWST NIRSpec observations.

Long-term changes in qualitative composition of the Buzuluk Pine Forest avifauna (Orenburg Province area) based on retrospective and present-time observations

We conducted a comparative analysis of qualitative composition of the Buzuluk Pine Forest avifauna, mainly based on data collected by ornithologist E.P. Knorre for the period 1928–1941, and modern observations done between 2000 and the present. Retrospective data were obtained from the now-defunct Buzuluk Bor Reserve with an area of 10 503 hectares (now Borovoye-Opytnoe Forestry in the Orenburg Province). Present-time personal avifaunistic observations (using standard methods with referring to literature sources) were carried out on an area of 49 000 hectares, both in Borovoye-Opytnoe and in several adjacent forestries that were part of the Buzuluk Bor National Park within the Orenburg Province. Comparing the historical and current bird lists, we used a relative assessment of changes in the composition of various bird groups based on the observed and expected frequencies according to the χ2 test. Long-term data on average annual temperatures and precipitation from a nearby state weather station were also used. As a result, it is shown that by now the list of birds of E.P. Knorre decreased from 153 to 109 species (28.8%). When comparing by orders, the water birds were found to be the most affected group. The number of species in orders Podicipediformes, Ciconiiformes, Gruiformes decreased by 80–100%, and it dropped by more than 50% in orders Anseriformes and Charadriiformes. There was also a slightly smaller decrease in the number of species in orders Falconiformes and Strigiformes – by about 40%. An assessment of the relative changes in various bird groups from Knorre’s list based on expected and observed frequencies showed significant differences in the portion of avifauna associated with water. It decreased between 23.5% and 9% in the group ‘Limnophiles’ (χ2 = 11.7, df = 1, p = 0.0006) and between 24.8% and 9% in the group of orders represented by waterfowl and waterbird species (χ2 = 13.4, df = 1, p = 0.0002). The change in the portion of birds of prey was statistically non-significant. The same portion assessment method did not statistically confirm the decrease in the rest ecological and order groups. Comparison of groups by occurrence status found no significant changes in the portions of all groups of birds in the past and present, but the largest reduction was recorded in the group of migrating species. The portion of migrants decreased from 8.7% to 3.0% (χ2 = 3.2, df = 1, p = 0.07, Yates corrected χ2 = 2.2, p = 0.1). A dramatic decline in group of bird species associated with wetlands was suggested to be due, among other factors, to the progressive desiccation of the Buzuluk Pine Forest, as E. Knorre himself wrote in his report. The ongoing aridization of the climate, as shown by the graph of average annual air temperatures, has been taking place since at least the 20s of the twentieth century and led to the drying-up of wetlands, and also to migration of groundwater to deeper horizons. The emerging trend towards a reduction in the portion of migrants could be explained by the fact that a number of migratory bird species, mainly ducks and waders, disappeared in the study area, and several other migrants began breeding species. In addition, large-scale fires and logging led to formation of burned wasteland areas inside the forest at the beginning of the twentieth century and also probably contributed to fragmentation and desiccation of this biome.

Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning

Safety in goal directed Reinforcement Learning (RL) settings has typically been handled through constraints over trajectories and have demonstrated good performance in primarily short horizon tasks. In this paper, we are specifically interested in the problem of solving temporally extended decision making problems such as robots cleaning different areas in a house while avoiding slippery and unsafe areas (e.g., stairs) and retaining enough charge to move to a charging dock; in the presence of complex safety constraints. Our key contribution is a (safety) Constrained Search with Hierarchical Reinforcement Learning (CoSHRL) mechanism that combines an upper level constrained search agent (which computes a reward maximizing policy from a given start to a far away goal state while satisfying cost constraints) with a low-level goal conditioned RL agent (which estimates cost and reward values to move between nearby states). A major advantage of CoSHRL is that it can handle constraints on the cost value distribution (e.g., on Conditional Value at Risk, CVaR) and can adjust to flexible constraint thresholds without retraining. We perform extensive experiments with different types of safety constraints to demonstrate the utility of our approach over leading approaches in constrained and hierarchical RL.

Giant microwave–optical Kerr nonlinearity via Rydberg excitons in cuprous oxide

Microwave–optical conversion is key to future networks of quantum devices, such as those based on superconducting technology. Conversion at the single quantum level requires strong nonlinearity, high bandwidth, and compatibility with a millikelvin environment. A large nonlinearity is observed in Rydberg atoms, but combining atomic gases with dilution refrigerators is technically challenging. Here, we demonstrate a strong microwave–optical nonlinearity in a cryogenic, solid-state system by exploiting Rydberg states of excitons in Cu2O. We measure a microwave–optical cross-Kerr coefficient of B0 = 0.022 ± 0.008 m V−2 at 4 K, which is several orders of magnitude larger than other solid-state systems. The results are in quantitative agreement with a nonlinear susceptibility model based on the giant microwave dipole moment between nearby excitonic states. Our results highlight the potential of Rydberg excitons for nonlinear optics and form the basis for a microwave–optical frequency converter based on Cu2O.

State labeling's impact on geographic boundaries of local

AbstractLocal labeling is an important issue within the horticultural industry as many producers have devoted considerable resources to advertising their products as local. Further, all states have implemented some form of local labeling program to increase local purchasing. As states expand the reach of these programs, the programs begin to compete as awareness and perception move across state lines. Using an online survey to study consumers in the Southeastern United States, we look to identify how state labeling programs are viewed in nearby states. Notably, we assess awareness, perception, and its impact on the local definition of these programs in their “home” state as well as nearby states. Specifically, we evaluate the impact of nine Southeastern state‐level branding programs. Our results indicate that consumers are more aware of their home state's local label, but awareness does exist for other states' labels. We also find that a home state label moves some consumers to a more state‐level local boundary, while seeing another state's label increases the boundary for what is perceived as local [EconLit Citation: Q13].

Challenges and epidemiological implications of the first outbreak of dengue and chikungunya in Sudan.

Dengue and chikungunya are mosquito-borne infections that are spreading rapidly worldwide. The highest burden lies in tropical and subtropical countries. In 2022 Sudan encountered the most widespread infection of both diseases. To describe the magnitude of the first outbreak of dengue and chikungunya infections in Tandalti Town, White Nile State, southern part of Sudan. Following the report of a high number of undifferentiated febrile illnesses in 32 health clinics in Tandalti Town, an area with high densities of Aedes aegypti, we collected blood samples from symptomatic suspected cases. The samples were tested for major arboviral infections using arboviral-specific enzyme-linked immunosorbent assays (IgM capture ELISA), and serologically positive samples were confirmed using commercially available Real Time RT-PCR Kits. Out of 773 suspected cases, 63 (8.15%) were confirmed. Eleven (17.46%) of the confirmed cases were DENV, 49 (77.77%) were CHIKV, and 3 (4.76%) were DENV and CHIKV co-infections. The outbreak started at the beginning of October and ended by mid December 2022. Both dengue and chikungunya infection was higher (41(65.08%)) among young females than males (22 (34.92%)). White Nile State may experience larger outbreaks of dengue and chikungunya in the future, there is, therefore, an urgent need for proper vector control interventions in the state and nearby states.

Sensitivity of radio-frequency electric field sensor based on Rydberg Stark effect

Rydberg atoms hold special attraction in electric applications due to their large transition electric dipole moments and huge polarization, which leads to a strong response of atom to electric fields. In radio-frequency (RF) fields, the Rydberg levels are AC Stark shift and splitting, which can realize the study of high-sensitivity electric field sensor of Rydberg atoms. In this work, we use the simpler Shirley’s time-independent Floquet Hamiltonian model to calculate the AC Stark energy spectrum of Cs Rydberg atoms. This model can reduce the basic Hamiltonian into such a Hamiltonian that includes only those Rydberg states that have direct dipole-allowed transitions with the target state, thereby significantly improving the speed of computation. The accuracy of the calculation is proved by fitting with the calculated frequency shift of DC Stark energy levels in the weak fields, and the polarizability of 60D<sub>5/2</sub> and 70D<sub>5/2</sub> Rydberg atomic states are obtained by fitting with the measured ion spectra of DC Stark Cs ultra-cold Rydberg atoms in magneto-optical trap. In addition, we calculate the AC Stark shift of Cs Rydberg atom <inline-formula><tex-math id="M2">\begin{document}$ \left| {60{{\text{D}}_{5/2}},{m_j} = 1/2} \right\rangle $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9-20240162_M2.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9-20240162_M2.png"/></alternatives></inline-formula> state in electric fields with different frequencies with <i>ε</i> = 100 mV/m. Rydberg atoms provide a structured spectrum of sensitivity to electric fields due to strong resonant interaction and off-resonant interaction with many dipole-allowed transitions to nearby Rydberg states. This kind of the frequency response structure is of significance to a broadband sensor. And we calculate the sensitivity and the scaling of the signal-to-noise ratio (SNR), <i>β</i>, varying with detuning from the <inline-formula><tex-math id="M3">\begin{document}$ \left| {60{{\text{D}}_{5/2}}} \right\rangle \to \left| {61{{\text{P}}_{3/2}}} \right\rangle $\end{document}</tex-math><alternatives><graphic specific-use="online" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9-20240162_M3.jpg"/><graphic specific-use="print" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="9-20240162_M3.png"/></alternatives></inline-formula> transition. The value of <i>β</i> allows one to use the result for any Rydberg state sensor to determine the SNR for any <i>Ε</i> in a 1 s measurement. Therefrom, Rydberg sensor can preferentially detect many RF frequencies spreading across its carrier spectral range without modification while effectively rejecting large portions where the atom response is significantly weaker, and the signal depends primarily on the detuning of the RF field to the nearest resonance which does not convey the RF frequency directly.

Drowsiness Detection System Through Eye and Mouth Analysis

Traffic jams are one of the serious issues in many developed countries. After the pandemic, many employees were allowed to travel interstate to work. This contributes to more severe jams, especially in the capital and nearby states. Long-distance driving and congestion can easily make the drivers sleepy and thus lead to traffic accidents. This paper aims to study and analyze facial cues to detect early symptoms of drowsy driving. The proposed method employs a deep learning approach, utilizing ensemble CNNs and Dlib's 68 landmark face detectors to analyze the facial cues. The analyzed symptoms include the frequency of eyes opened or closed and yawning or no yawning. Three individual CNN models and an ensemble CNN structure are built for the classification of the eyes and mouth yawn. The model training and validation accuracy graph and training loss and validation loss graph are plotted to verify that the models have not been overfitted. The ensemble CNN models achieved an approximate accuracy of 97.4% from the eyes and 96.5% from the mouth. It outperforms the other pre-trained models. The proposed system can immediately alert the driver and send text drowsy messages and emails to the third party, ensuring timely intervention to prevent accidents. The proposed method can be integrated into vehicles and transportation systems to ensure driver's safety. It can also be applied to monitor the driving behavior of those who drive long distances

Drowsiness Detection System Through Eye and Mouth Analysis

Traffic jams are one of the serious issues in many developed countries. After the pandemic, many employees were allowed to travel interstate to work. This contributes to more severe jams, especially in the capital and nearby states. Long-distance driving and congestion can easily make the drivers sleepy and thus lead to traffic accidents. This paper aims to study and analyze facial cues to detect early symptoms of drowsy driving. The proposed method employs a deep learning approach, utilizing ensemble CNNs and Dlib's 68 landmark face detectors to analyze the facial cues. The analyzed symptoms include the frequency of eyes opened or closed and yawning or no yawning. Three individual CNN models and an ensemble CNN structure are built for the classification of the eyes and mouth yawn. The model training and validation accuracy graph and training loss and validation loss graph are plotted to verify that the models have not been overfitted. The ensemble CNN models achieved an approximate accuracy of 97.4% from the eyes and 96.5% from the mouth. It outperforms the other pre-trained models. The proposed system can immediately alert the driver and send text drowsy messages and emails to the third party, ensuring timely intervention to prevent accidents. The proposed method can be integrated into vehicles and transportation systems to ensure driver's safety. It can also be applied to monitor the driving behavior of those who drive long distances

Drowsiness Detection System Through Eye and Mouth Analysis

Traffic jams are one of the serious issues in many developed countries. After the pandemic, many employees were allowed to travel interstate to work. This contributes to more severe jams, especially in the capital and nearby states. Long-distance driving and congestion can easily make the drivers sleepy and thus lead to traffic accidents. This paper aims to study and analyze facial cues to detect early symptoms of drowsy driving. The proposed method employs a deep learning approach, utilizing ensemble CNNs and Dlib's 68 landmark face detectors to analyze the facial cues. The analyzed symptoms include the frequency of eyes opened or closed and yawning or no yawning. Three individual CNN models and an ensemble CNN structure are built for the classification of the eyes and mouth yawn. The model training and validation accuracy graph and training loss and validation loss graph are plotted to verify that the models have not been overfitted. The ensemble CNN models achieved an approximate accuracy of 97.4% from the eyes and 96.5% from the mouth. It outperforms the other pre-trained models. The proposed system can immediately alert the driver and send text drowsy messages and emails to the third party, ensuring timely intervention to prevent accidents. The proposed method can be integrated into vehicles and transportation systems to ensure driver's safety. It can also be applied to monitor the driving behavior of those who drive long distances

A Nitronyl Nitroxide-Substituted Benzotriazinyl Tetraradical.

High-spin organic tetraradicals with significant intramolecular exchange interactions have high potential for advanced technological applications and fundamental research, but those synthesized to date possess limited stability and processability. In this work, we have designed a tetraradical based on the Blatter's radical and nitronyl nitroxide radical moieties and successfully synthesized it by using the palladium-catalyzed cross-coupling reaction of a triiodo-derivative of the 1,2,4-benzotriazinyl radical with gold(I) nitronyl nitroxide-2-ide complex in the presence of a newly developed efficient catalytic system. The molecular and crystal structure of the tetraradical was confirmed by X-ray diffraction analysis. The tetraradical possesses good thermal stability with decomposition onset at ∼150 °C under an inert atmosphere and exhibits reversible redox waves at -0.54 and 0.45 V versus Ag/AgCl. The magnetic properties of the tetraradical were characterized by SQUID magnetometry of polycrystalline powders and EPR spectroscopy in various matrices. The collected data, analyzed by using high-level quantum chemical calculations, confirmed that the tetraradical has a triplet ground state and a nearby excited quintet state. The unique high stability of the prepared triazinyl-nitronylnitroxide tetraradical is a new milestone in the field of creating high-spin systems.

Excitation Energy-Dependent Decay Dynamics of the S1 State of N-Methyl-2-pyridone.

The UV-induced decay dynamics of N-methyl-2-pyridone is investigated using a femtosecond time-resolved photoelectron spectroscopy method. Irradiation in the wavelength range of 339.3-258.9 nm prepares N-methyl-2-pyridone molecules with very different vibrational levels of the S1(11ππ*) state. For v' = 0 (origin) and a few low-energy vibrational levels slightly above the S1 state origin, the radiative decay channel is in operation for some specific vibrations. This is revealed by the excited-state lifetime of ≫1 ns. In addition, some other nearby S1 vibronic states have a much shorter lifetime in the range of several picoseconds to a few tens of picoseconds, indicating that the radiation-less decay to the ground state (S0) via internal conversion is the dominant channel for them. As the pump wavelength slightly decreases, the radiative decay is suddenly not important at all, and the deactivation rate of the S1 state becomes faster. At shorter pump wavelengths, the lifetime of highly excited vibrational states of the S1 state further decreases with the increase in the vibrational excess energy. This study provides quantitative information about the excitation energy-dependent decay dynamics of the S1 state of N-methyl-2-pyridone. Methyl substitution effects on the excited-state dynamics of 2-pyridone are also discussed.