Values Of Transition Probabilities Research Articles

Studies of luminescence traits and Judd-Ofelt analysis of Sm3+ activated oxyfluoride glasses

Novel Sm3+ activated oxyfluoride glass was synthesized via the melt-quenching approach with subsequent heat treatment. The X-ray diffraction measurement discloses the amorphous nature of prepared glasses. And, FTIR illustrates the molar surplus of Bi2O3 raises the network connectivity by creating bridging oxygen sites in the structure. The Judd-Ofelt (J-O) intensity parameters exhibit Ω4>Ω2>Ω6 trend, witnessing the rigidity of the glass structure and ionic bonding between Sm3+ ions and surrounding ligands. The 4G5/2 → 6H7/2 transition of Sm3+ is the most applicable for reddish-orange lasers due to their higher values of radiative transition probability, branching ratio, and stimulated emission cross-section. The optimum emission intensity is obtained with 30 mol% Bi2O3 and the corresponding decay time is 1.40 ms. Additionally, the F30 glass sample was lit in a reddish-orange region having a CCT value of 1689 K. The thermal luminescence quenching of the prepared glass was studied and the thermal stability parameters activation energy was estimated. Further, the contactless optical thermometry capability of the glass sample was explored within the range of 303 K–603 K using the luminescence intensity ratio (LIR) technique. Thus, the above studies on the glass sample suggest that it can be used as an active medium in lasers, contactless optical temperature sensing, and high-energy scintillator applications.

Cost-effectiveness analysis of hepatitis E vaccination strategies among patients with chronic hepatitis B in China.

This study aimed to evaluate the cost-effectiveness of hepatitis E vaccination strategies in the chronic hepatitis B (CHB) patients. Based on the societal perspective, cost-effectiveness of three hepatitis E vaccination strategies: vaccination without screening, screening-based vaccination, and no vaccination among CHB patients was evaluated using a decision tree-Markov model, and incremental cost-effectiveness ratios (ICERs) were calculated. Values for treatment costs and health utilities were estimated from a prior investigation on disease burden, and values for transition probabilities and vaccination-related costs were obtained from previous studies and government agencies. Sensitivity analyses were performed for assessing model uncertainties. It was estimated that CHB patients superinfected with HEV incurred significantly longer disease course, higher economic burden, and more health loss compared to those with HEV infection alone (all P < 0.05). The ICERs of vaccination without screening and screening-based vaccination compared to no vaccination were 41,843.01 yuan/QALY and 29,147.32 yuan/QALY, respectively, both lower than China's per-capita GDP in 2018. The screening-based vaccination reduced the cost and gained more QALYs than vaccination without screening. One-way sensitivity analyses revealed that vaccine price, vaccine protection rate, and decay rate of vaccine protection had the greatest impact on the cost-effectiveness analysis. Probabilistic sensitivity analyses confirmed the base-case results, and if the willingness-to-pay value reached per-capita GDP, the probability that screening-based vaccination would be cost-effective was approaching 100%. The disease burden in CHB patients superinfected with HEV is relatively heavy in China, and the screening-based hepatitis E vaccination strategy for CHB patients is the most cost-effective option. This article is protected by copyright. All rights reserved.

Cost-Effectiveness Analysis of PET-CT Surveillance After Treatment of Human Papillomavirus-Positive Oropharyngeal Cancer.

To determine the cost-effectiveness of surveillance imaging with PET/CT scan among patients with human papillomavirus-positive oropharyngeal squamous cell carcinoma. Cost-effectiveness analysis. Oncologic care centers in the United States with head and neck oncologic surgeons and physicians. We compared the cost-effectiveness of 2 posttreatment surveillance strategies: clinical surveillance with the addition of PET/CT scan versus clinical surveillance alone in human papillomavirus-positive oropharyngeal squamous cell carcinoma patients. We constructed a Markov decision model which was analyzed from a third-party payer's perspective using 1-year Markov cycles and a 30-year time horizon. Values for transition probabilities, costs, health care utilities, and their studied ranges were derived from the literature. The incremental cost-effectiveness ratio for PET/CT with clinical surveillance versus clinical surveillance alone was $89,850 per quality-adjusted life year gained. Flexible fiberoptic scope exams during clinical surveillance would have to be over 51% sensitive or PET/CT scan cost would have to exceed $1678 for clinical surveillance alone to be more cost-effective. The willingness-to-pay threshold at which imaging surveillance was equally cost-effective to clinical surveillance was approximately $80,000/QALY. Despite lower recurrence rates of human papillomavirus-positive oropharyngeal cancer, a single PET/CT scan within 6 months after primary treatment remains a cost-effective tool for routine surveillance when its cost does not exceed $1678. The cost-effectiveness of this strategy is also dependent on the clinical surveillance sensitivity (flexible fiberoptic pharyngoscopy), and willingness-to-pay thresholds which vary by country.

Neutrino spin-flavour precession in magnetized white dwarf

Due to notoriously small value of the neutrino magnetic moment, the phenomena of neutrino spin flavour precession (SFP) require a very high magnetic field. This makes only a handful of systems suitable to study this phenomenon. By the observation of SFP, the Dirac and Majorana nature of neutrinos is expected to be distinguished. In this work, we point out the potential of the white dwarf (WD) system in studying the spin-flavour oscillation of neutrinos. From recent analysis, it has been found that young isolated WDs may harbour very strong internal magnetic field, even without exhibiting any surface magnetic field. The presence of a magnetic field enhances the cooling process and along with that, renders the spin-flavour oscillation of neutrinos emitted in the neutrino cooling process. Employing the standard WD specifications, we analyse whether a magnetized WD is a suitable environment to distinguish between the Dirac and Majorana nature of the neutrino. Higher value of spin flavour transition probability implies reduced active neutrino flux which is possible to be estimated in terrestrial neutrino detectors. We find that for the current upper bound on the neutrino magnetic moment, the spin flavour transition probability of Dirac neutrinos is much higher in comparison to the Majorana neutrino which converts the active neutrino flavours to sterile in a significant amount. We also examine the sensitivity of the spin flavour transition probability to the neutrino magnetic moment.

Judd-Ofelt analysis, optical and structural features of borate glass doped with erbium oxide

This article presents a description of the structural-optical relationship in amorphous borate glass, with a decent investigation of Judd-Ofelt parameters to understand the effect of structural changes on optical properties due to the erbium oxide addition. Using density measurements, the effect of heavy molecular weight and larger ionic radius of erbium oxide was demonstrated. FT-IR analysis revealed the BO3 to BO4 conversion, confirming the network polymerization and connectivity. Astonishingly, the effect of erbium oxide on the increased band gap energy and the mitigated Urbach energy was demonstrated. Interestingly, Judd-Ofelt analysis was utilized to demonstrate the impact of the composition changes on the relation between the structural changes and optical properties. The influence of excited configurations of Er3+ ions was measured from the line strengths. The hypersensitive transitions from I15/24toH11/24 and G9/24 were observed at 375 nm and 519 nm, which have relatively higher intensities compared to other ones. Thus, they are attractive transitions for light emitting devices, LEDs, and solid lasers. The decreased values of Ω2 parameter is related to the increase in symmetry and high polarization around Er3+ ions. Consequently, the decrement in Ω2 suggests that the bond nature between Er3+ and O2− ions tends to be more ionic. Calculations of radiative parameters such as spontaneous radiative transition probability, radiative lifetime, and branching ratio were presented. The hypersensitive transitions have the highest values of the spontaneous radiative transition probability, predicting their high luminescence efficiency in glass host, besides the effectiveness of their usability in designing photonic devices. The obtained high branching ratio confirmed the lasing action of Er3+ ions in the glass host, especially the hypersensitive transitions of Er3+ ions.

Markov Chain transition probability modeling of radon gas records and future projection possibility determination

Markov Chain models serve two purposes firstly, subdivide the main data based on the mean value and one and two standard deviation plus and minus values around the mean value. The second stage of modeling, after calculating the transition probabilities between these categories from the available data, is completed by repeatedly multiplying the categorization date groups until the steady-state transition probability values are obtained. This procedure provides a convenient modeling approach for radon gas transient measurement records. After a brief presentation of Markov Chain procedure in this paper, the application is carried out by considering five categories that lead to a better transition probability matrix. Such a matrix provides information about the probabilities of future transition at the radon data measuring station. In addition, it is possible to associate these transition probabilities with the possibility of an earthquake.

Efficient Point Mass Predictor for Continuous and Discrete Models with Linear Dynamics

This paper deals with state estimation of stochastic models with linear state dynamics, continuous or discrete in time. The emphasis is laid on a numerical solution to the state prediction by the time-update step of the grid-point-based point-mass filter (PMF), which is the most computationally demanding part of the PMF algorithm. A novel way of manipulating the grid, leading to the time-update in form of a convolution, is proposed. This reduces the PMF time complexity from quadratic to log-linear with respect to the number of grid points. Furthermore, the number of unique transition probability values is greatly reduced causing a significant reduction of the data storage needed. The proposed PMF prediction step is verified in a numerical study.

Prediction analysis of the length of time for changes in the status of positive patients for covid-19 delta and omicron variants using the markov chain model

In this research, a Markov chain model was constructed from the conditions that might be experienced by the people during the Delta or Omicron variant of the COVID-19 pandemic. This condition is divided into 3 states; "0" indicates a healthy condition, "1" indicates the state of being infected with COVID-19, and "2" indicates the death state. Furthermore, from the model obtained, a transition probability matrix is made to determine the transition probability value and calculate the average number of steps needed to get to the death state. From the results of the analysis, the probability of transition to a state of death is 1. This shows that a person will surely die from being healthy or positive for COVID-19 within a certain time. During the Delta variant of the COVID-19 pandemic, the average time that a person reaches a death state from a healthy state is 34.02 years. Meanwhile, the average time taken for someone infected with the Delta variant of COVID-19 to death is 33.79 years. During the Omicron variant of the COVID-19 pandemic, the average time that a person reaches a death state from a healthy state is 37.63 years. Meanwhile, the average time taken for someone infected by the Omicron variant of COVID-19 to death is 37.41. This shows that the average age of a person infected with the Delta variant of COVID-19 has decreased by 2.79 months, while the average age of a person infected with the Omicron variant of COVID-19 has decreased by 2.70 months.

Markov chain pavement deterioration prediction models for local street networks

PurposePavement deterioration prediction models play a crucial role in determining maintenance strategies and future funding needs. While deterioration prediction models have been studied extensively in the past, applications of these models to local street networks have been limited. This study aims to address this gap by sharing the results of network level deterioration prediction models developed at a local level.Design/methodology/approachNetwork level pavement deterioration prediction models are developed using Markov chains for the local street network in Syracuse, New York, based on pavement condition rating data collected over a 15-year time period. Transition probability matrices are generated by calculating the percentage of street sections that transition from one state to another within one duty cycle. Bootstrap sampling with replacement is used to numerically generate 95% confidence intervals around the transition probability values.FindingsThe overall local street network is divided into three cohorts based on street type (i.e. avenues, streets and roads) and two cohorts based on pavement type. All cohorts demonstrated very similar deterioration trends, indicating the existence of a fast-paced deterioration mechanism for the local street network of Syracuse.Originality/valueThis study contributes to the body of knowledge in deterioration modeling of local street networks, especially in the absence of key predictor variables. Furthermore, this study introduces the use of bootstrap sampling with replacement method in generating confidence intervals for transition probability values.

Investigation of luminescence properties of Ho3+ doped barium, zinc and gadolinium based phosphate glasses

10BaO-10ZnO-10Gd2O3-69P2O3-1Ho2O3 (ZBOH) and 10BaO-10ZnO-10GdF3-69P2O3-1Ho2O3 (ZBFH) were developed by the melt-quenched-method. The synthesized ZBOH and ZBFH glass samples were characterized for Uv-Vis-NIR, excitation, emission, decay time profile measurements and physical properties. It is observed that the ZBOH glass have higher density and refractive index as compared to the ZBFH glass. From the band gap calculation, it is observed that the oxyfluoride glasses have lower band gap as compared to the oxide glasses which indicate more \ on bridging oxygen in oxyfluoride glasses. The emission spectra recorded at λex = 449 nm show four emission bands at 5F2 (477 nm), 5F3 (495 nm),5F4 +5S2(545 nm) and5F5 (659 nm) from 5I8-levels. Judd-Ofelt (J-O) theory is used to investigate the J-O intensity parameters, transition probability, stimulated emission cross section and branching ratio. From the results it’s perceived that the radiative transition probability and branching ratio values are higher for 5F4 →5I8 transition as compared to the other transitions.

Enhanced photoluminescence in Dy3+/Au co-doped bismuth borosilicate glass

Several optical applications demand for enhanced optical response of rare earth containing glasses. In the present investigation, modification in spectral features with the dispersion of gold nanoparticles in Dy3+ doped bismuth borosilicate glasses is reported. All the glass samples were prepared using conventional melt-quench technique. Prepared glasses were characterised using Fourier transform infrared spectroscopy (FTIR), dilatometery, field emission scanning electron microscopy (FESEM), Uv–Vis–NIR spectroscopy and photoluminescence. Thermal studies carried out using dilatometer confirms the decrease in glass transition after co-doping of gold nanoparticles and Dy3+. Field emission scanning electron microscopy revealed the existence of gold nanoparticles inside the glassy matrix. A marginal change in the values of Judd-Ofelt parameters of glasses is observed after the incorporation of gold nanoparticles. Significant enhancement in emission intensities is observed after the addition of gold nano-particles. The high stimulated emission cross-section (σemi) and radiative transition probability values for prepared glasses confirms their suitability for the fabrication of yellow light laser.

Exploring and Characterizing Patient Multibehavior Engagement Trails and Patient Behavior Preference Patterns in Pathway-Based mHealth Hypertension Self-Management: Analysis of Use Data.

BackgroundHypertension is a long-term medical condition. Mobile health (mHealth) services can help out-of-hospital patients to self-manage. However, not all management is effective, possibly because the behavior mechanism and behavior preferences of patients with various characteristics in hypertension management were unclear.ObjectiveThe purpose of this study was to (1) explore patient multibehavior engagement trails in the pathway-based hypertension self-management, (2) discover patient behavior preference patterns, and (3) identify the characteristics of patients with different behavior preferences.MethodsThis study included 863 hypertensive patients who generated 295,855 use records in the mHealth app from December 28, 2016, to July 2, 2020. Markov chain was used to infer the patient multibehavior engagement trails, which contained the type, quantity, time spent, sequence, and transition probability value (TP value) of patient behavior. K-means algorithm was used to group patients by the normalized behavior preference features: the number of behavioral states that a patient performed in each trail. The pages in the app represented the behavior states. Chi-square tests, Z-test, analyses of variance, and Bonferroni multiple comparisons were conducted to characterize the patient behavior preference patterns.ResultsMarkov chain analysis revealed 3 types of behavior transition (1-way transition, cycle transition, and self-transition) and 4 trails of patient multibehavior engagement. In perform task trail (PT-T), patients preferred to start self-management from the states of task blood pressure (BP), task drug, and task weight (TP value 0.29, 0.18, and 0.20, respectively), and spent more time on the task food state (35.87 s). Some patients entered the states of task BP and task drug (TP value 0.20, 0.25) from the reminder item state. In the result-oriented trail (RO-T), patients spent more energy on the ranking state (19.66 s) compared to the health report state (13.25 s). In the knowledge learning trail (KL-T), there was a high probability of cycle transition (TP value 0.47, 0.31) between the states of knowledge list and knowledge content. In the support acquisition trail (SA-T), there was a high probability of self-transition in the questionnaire (TP value 0.29) state. Cluster analysis discovered 3 patient behavior preference patterns: PT-T cluster, PT-T and KL-T cluster, and PT-T and SA-T cluster. There were statistically significant associations between the behavior preference pattern and gender, education level, and BP.ConclusionsThis study identified the dynamic, longitudinal, and multidimensional characteristics of patient behavior. Patients preferred to focus on BP, medications, and weight conditions and paid attention to BP and medications using reminders. The diet management and questionnaires were complicated and difficult to implement and record. Competitive methods such as ranking were more likely to attract patients to pay attention to their own self-management states. Female patients with lower education level and poorly controlled BP were more likely to be highly involved in hypertension health education.

Description of the energy levels and electric quadrupole transitions of the 92Nb and 92Mo nuclei using nuclear shell model

In current study ,92Nb and 92Mo isotopes have been determined for calculating energy levels and electric quadrupole transition probabilities. Two interaction have been applied in this study are surface delta and modified surface delta interactions. The calculations have been achieved by using appropriate effective charges for proton and neutron as well as parameter length of harmonic potential. Computed results have been compared with the experimental values. After this comparison, energy and the transition probability values have a good agreement with the experimental values, also there are values of the total angular momentum and parity are determined and confirmed for some of the experimental energies, undetermined and unconfirmed experimentally. Theoretically, new values of quadrupole electric transition probabilities have been explored which have not been known in the experimental data.

Nuclear Structure of Ce Nuclei within Interacting Boson Model-2

Using the Interacting Boson Model-2 (IBM-2), we determined the most appropriate Hamiltonian for the current calculations of energy levels and electromagnetic transition probability values of 124-138Ce nuclei with a mass around A=140 in this study. We estimated energy levels and electromagnetic values and mixing ratios (E2/M1) for a number of transitions in 124-138Ce isotopes using the best fitted values of parameters in the IBM-2 Hamiltonian. When the results were compared to the experimental data, they were found to be in good agreement.

Semi-empirical determination of radiative parameters for metastable Sc II levels

We present a semi-empirical parametrization method for calculation of spontaneous radiative decay rates of forbidden transitions on an example of analysis of experimental data for Sc II. The values of transition probabilities and radiative lifetimes of metastable levels are in perfect agreement with experimental ones. The obtained results are compared with other calculated data available. The predicted values of radiative parameters for all Sc II metastable levels are presented.

Theoretical Study of Isospin Mixing States with T&gt; 0 in sd Even-Even N=Z Nuclei Using Shell Model

Nuclear excited states with T &gt; 0 in sd even-even N=Z nuclei have been studied by using shell model. The calculations have employed the USDB Hamiltonian in order to predict the energy levels, the reduced electric quadrupole transition probabilities and reduced magnetic dipole transition probabilities. The study also include the average number of nucleons in each sd- active orbitals. The results compared with available experimental data. The comparison showed a good agreement between theoretical and experimental energy sates for most of the states studied in this work. On the other hand there was a difference between theoretical and experimental values of transition probabilities, but it can be said that it remained within the acceptable range of the difference.

Automatic human posture estimation for sport activity recognition with robust body parts detection and entropy markov model

Automated human posture estimation (A-HPE) systems need delicate methods for detecting body parts and selecting cues based on marker-less sensors to effectively recognize complex activity motions. Recognition of human activities using vision sensors is a challenging issue due to variations in illumination conditions and complex movements during the monitoring of sports and fitness exercises. In this paper, we propose a novel A-HPE method that intelligently identifies human behaviours by utilizing saliency silhouette detection, robust body parts model and multidimensional cues from full-body silhouettes followed by an entropy Markov model. Initially, images are pre-processed and noise is removed to obtain a robust silhouette. Body parts models are then used to extract twelve key body parts. These key body parts are further optimized to assist the generation of multidimensional cues. These cues include energy, optical flow and distinctive values that are fed into quadratic discriminant analysis to discriminate cues which help in the recognition of actions. Finally, these optimized patterns are further processed by a maximum entropy Markov model as a recognizer engine based on transition and emission probability values for activity recognition. For evaluation, we used a leave-one-out cross validation scheme and the results outperformed existing well-known statistical state-of-the-art methods by achieving better body parts detection and higher recognition accuracy over four benchmark datasets. The proposed method will be useful for man-machine interactions such as 3D interactive games, virtual reality, service robots, e-health fitness, and security surveillance.

Cost-Effectiveness Analysis of Antiviral Therapy for Untreated Minimally Active Chronic Hepatitis B to Prevent Liver Disease Progression.

INTRODUCTION:Antiviral therapy (AVT) for chronic hepatitis B (CHB) can prevent liver disease progression. Because of its stringent reimbursement criteria, significant numbers of patients with untreated minimally active (UMA)-CHB exist, although they are still subject to disease progression. We thus performed a cost-effectiveness analysis to assess the rationale for AVT for UMA-CHB.METHODS:We compared cost and effectiveness (quality-adjusted life years, QALYs) in virtual UMA-CHB cohorts of 10,000 50-year-olds receiving AVT (scenario 1) vs no treatment (scenario 2) for 10 years. A Markov model, including 7 health states of CHB-related disease progression, was used. Values for transition probabilities and costs were mostly obtained from recent South Korean data.RESULTS:The simulation of AVT vs no treatment predicted $2,201 incremental costs and 0.175 incremental QALYs per patient for 10 years, with an incremental cost-effectiveness ratio (ICER) of $12,607/QALY, suggesting cost-effectiveness of AVT. In sum, if 10,000 patients received AVT, 720 incident hepatocellular carcinoma and 465 CHB-related more deaths could be averted in 10 years relative to no treatment. When the simulated analysis period was extended to 20 years, AVT was also highly cost-effective with an ICER of $2,036/QALY. Although hepatocellular carcinoma–related mortality was a major factor influencing ICER, its fluctuation can be accepted within willingness to pay of $33,000 in South Korea. According to probabilistic sensitivity analysis with the threshold of willingness to pay, the probability of AVT cost-effectiveness was 83.3%.DISCUSSION:Long-term AVT for patients with UMA-CHB may contribute positively toward individual clinical benefit and national health care budget.

Spatio-temporal simulation of future urban growth trends using an integrated CA-Markov model

Urban growth, a dynamic and demographic phenomenon, refers to the increased spatial value of urban areas, such as cities and towns, due to social and economic forces. Nowadays, urban lands are rapidly increasing, replacing non-urban lands such as agricultural, forest, water, rural, and open lands. In this study, a CA-Markov model was utilized to predict the growth of urban lands and their spatial trends in Seremban, Malaysia. The performance of the CA-Markov model was also assessed. The Markov chain model was applied to produce the quantitative values of transition probabilities for urban and non-urban lands. Subsequently, the CA model was used to predict the dynamic spatial trends of land changes. The change in urban and non-urban land use from 1984 to 2010 was modeled using the CA-Markov model for calibration purposes and to compute optimal CA transition rules, as well as to predict future urban growth. For accuracy assessment, the CA-Markov model was validated using a kappa coefficient. An 83% overall accuracy was observed for the kappa index statistics, which indicates the excellent performance of the proposed model. Finally, based on the CA transition rules and the transition area matrix produced from the Markov chain model-based calibration process, the future urban growth in Seremban for 2020 and 2030 was simulated.

Sales Demand Forecasting Using One of Multivariate Markov Chain Model Parameter

The imbalance between demand and supply is frequently occurred in a market. This is due to the availability of goods that cannot match with the demand or the growth rate of customer. This is not preferable since the profit is not on the track. In contrast, the goods are probably over supplied so that company has to expense additional cost for extra storage. Both situations can be anticipated if the demand is precisely estimated. Therefore, in this study we will estimate demand in market situation by implementing multivariate Markov chain model. Multivariate Markov chain model is popular model for forecasting by observing current state in various applications. This model is compatible with 5 data sequences (product types) defined as product A, product B, product C, product D and product E, with 6 conditions (no sales volume, very slow-moving, slow-moving, standard, fast moving, and very fast moving). As the result, the highest transition probability value for the sales demand in a company is found at the transition probability matrix from product C to product C, from very fast moving to very fast-moving condition, which had the highest probability value 0.625 with the highest frequency 105 times.