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This paper analyzes the dependence pattern of net debts inflows on the sovereign debts rating and the fiscal balance, on accounting for the productivity growth rate. The cross-section evidence on a sample of 149 economies for the period from 1990 to 2019 uncovers that a higher sovereign debts rating, a lower fiscal balance or a higher productivity growth is associated with more net debts inflows. Thus, the debts flows are underlined by the store of wealth accumulation across economies. Moreover, there exists a nonlinearity on the pattern of debts flows, for which the fiscal balance determines the impact of sovereign debts rating on the net debts inflows. The results are robust for panel data regression as well as case study of three economies including Japan, Thailand and Vietnam. [ABSTRACT FROM AUTHOR]

This paper deals with the micro–macro-derivation of virus models coupled with a reaction–diffusion system that generates the dynamics in space of the virus particles. The first part of the presentation focuses, starting from [N. Bellomo, K. Painter, Y. Tao and M. Winkler, Occurrence versus absence of taxis-driven instabilities in a May–Nowak model for virus infection, SIAM J. Appl. Math. 79 (2019) 1990–2010; N. Bellomo and Y. Tao, Stabilization in a chemotaxis model for virus infection, Discrete Contin. Dyn. Syst. S 13 (2020) 105–117], on a survey and a critical analysis of some phenomenological models known in the literature. The second part shows how a Hilbert type can be developed to derive models at the macro-scale from the underlying description delivered by the kinetic theory of active particles. The third part deals with the derivation of macroscopic models of various virus models coupled with the reaction–diffusion systems. Then, a forward look to research perspectives is proposed. [ABSTRACT FROM AUTHOR]

This paper presents a survey and critical analysis of the mathematical literature on modeling and simulation of human crowds taking into account behavioral dynamics. The main focus is on research papers published after the review [N. Bellomo and C. Dogbè, On the modeling of traffic and crowds: A survey of models, speculations, and perspectives, SIAM Rev. 53 (2011) 409–463], thus providing important research perspectives related to new, emerging trends. The presentation addresses the scaling problem corresponding to microscopic (individual-based), mesoscopic (kinetic), and macroscopic (hydrodynamic) modeling and analysis. A multiscale vision guides the overall content of the paper. The critical analysis of the overall content naturally leads to research perspectives. A selection of them is brought to the attention of the interested reader together with hints on how to deal with them. [ABSTRACT FROM AUTHOR]

In this paper, we consider the generalized inverse iteration for computing ground states of the Gross–Pitaevskii eigenvector (GPE) problem. For that we prove explicit linear convergence rates that depend on the maximum eigenvalue in magnitude of a weighted linear eigenvalue problem. Furthermore, we show that this eigenvalue can be bounded by the first spectral gap of a linearized Gross–Pitaevskii operator, recovering the same rates as for linear eigenvector problems. With this we establish the first local convergence result for the basic inverse iteration for the GPE without damping. We also show how our findings directly generalize to extended inverse iterations, such as the Gradient Flow Discrete Normalized (GFDN) proposed in [W. Bao and Q. Du, Computing the ground state solution of Bose–Einstein condensates by a normalized gradient flow, SIAM J. Sci. Comput.25 (2004) 1674–1697] or the damped inverse iteration suggested in [P. Henning and D. Peterseim, Sobolev gradient flow for the Gross–Pitaevskii eigenvalue problem: Global convergence and computational efficiency, SIAM J. Numer. Anal.58 (2020) 1744–1772]. Our analysis also reveals why the inverse iteration for the GPE does not react favorably to spectral shifts. This empirical observation can now be explained with a blow-up of a weighting function that crucially contributes to the convergence rates. Our findings are illustrated by numerical experiments. [ABSTRACT FROM AUTHOR]

Since January 1, 2020, Thailand has implemented a campaign to stop giving free single-use plastic bags in 75 major retail stores. This study aims to (1) understand the status quo and effectiveness of the plastic bag ban campaign by estimating the number of plastic bags used in Bangkok and Phuket (2) understand the consumers' behavioural on plastic bag consumption and management by integrating a knowledge, attitude, and practice (KAP) model (3) provide policy recommendation to strengthen the country plastic waste management roadmap. The results showed that the ban on plastic bag campaign is effective, especially in the supermarkets and convenience stores in Bangkok. The numbers of plastic bags used per visit at supermarkets and convenience stores are approximately 1.9 bags and 1.7 bags, respectively, whereas the plastic bags used at fresh markets, restaurants, and food delivery services are, on average, up to 3.7, 3.1, and 2.8 bags per visit, respectively. On average, people in Bangkok use approximately 1.2 bags/person/day, while only 0.7 bags/person/day are used in Phuket. According to the KAP model, attitude is more crucial than knowledge towards pro-environmental behaviour. Bangkok residents' trend to show more pro-environmental behaviour than Phuket residents. For policy implication, it is important to continuously communicate the environmental impact of plastics and emphasise the proper knowledge and attitudes toward plastic bags among people to encourage their cooperative behaviours in reducing the use of plastic bags and sorting waste for recycling. [ABSTRACT FROM AUTHOR]

Introduce a new dynamic classifying algorithm in this paper to recognize and monitor fish activity to simultaneously better comprehend their synapomorphies. The pre-trained Mask Regional Convolutional Neural Network (Mask-R-CNN) is trained using a set of test models extracted from recorded video recording. The approach suggested subsequently yields well-enhanced feature vectors. The system's automatic fish detection and tracking capabilities are improved, enhancing underwater investigation for supervising ecological biodiversity. The publicly accessible field-truth dataset assesses recall, F1-score, and classification and tracking precision. Utilizing current tracking R-CNN algorithms like Lowest Output Sum of Siamese Mask (SiamMask), Sequential Non-Maximum Suppression (Seq-NMS), and Squared Errors (MOSSE), comparative performance testing is conducted. In comparison to Siam-Mask (84%), Seq-NMS (78%) and MOSSE (75%), more than 120 of 170 specific bream were detected using the pre-trained Mask-R-CNN of the proposed algorithm (87%). This pre-trained Mask R-CNN system was used in the evaluation, and it was discovered that detection and tracking accuracy had increased significantly. This suggests that the ocean ecosystem could benefit from applying the proposed approach for management of ecology. [ABSTRACT FROM AUTHOR]

This study empirically investigates knowledge creation (KC) in the context of the not-for-profit environment and seeks an understanding of how the dynamic of KC occurs in non-profit organisations (NPOs) in developing countries. The study, qualitative in nature, was applied in international non-profit organisations (INPOs), which is based on the 31 interviews taken at various such organisations in Thailand. The research illustrates the context of interaction dynamic that figures out the exampled NPOs, that is the creation of four types of ba, which enhances the KC process and identifies the specific knowledge types that are managed in these organisations. The investigation offers a holistic approach of the processes of organisational knowledge-creating in the NPOs. Furthermore, it is intended that the evidence presented a critical attitude regarding knowledge management (KM)-NPOs domains, especially in the KC process in the academic community. For NPO practitioners, this paper allows us to discover the organisational practices on the process-creating to enhance KM activities in their organisation. [ABSTRACT FROM AUTHOR]

The countercyclical pattern of saving in Thailand in the 1990s and 2000s raised questions about household saving behaviors in the country. Using constructed pseudo-panel data sets from the Thai Household Socioeconomic Surveys (SESs) from 1992 to 2011, this paper estimates the intensity of the precautionary saving motive, measured by the coefficient of relative prudence of households in Thailand. By using a dynamic pseudo-panel approach to address concerns with regard to individual heterogeneity causing bias in estimation, the estimated relative prudence of Thai households is around 2, which shows a low precautionary saving motive among these households compared to other countries. Estimates based on disaggregation by demographic characteristics show that as a result of the government-assistance policy, older cohorts and those who live in the rural areas show lower prudence. [ABSTRACT FROM AUTHOR]

This paper revisits the causal relationship between education and earnings, or the returns to education, using Thailand's socio-economic household survey data. We show that, with the minimum modeling assumption, the causal effect of education on earnings can be nonparametrically identified only when there is no unobserved ability affecting both education and earning, and when the selection mechanisms are conditionally independent to earnings conditioning on potential experience and education. The causal effects of education on earnings are estimated using a nonparametric approach with selection bias adjustment and parametric approaches with selection bias and ability bias adjustments. The results show different estimates for returns to education across model specifications, indicating the importance of the bias adjustments and parametric assumptions. [ABSTRACT FROM AUTHOR]

In this paper, we derive a new recovery procedure for the reconstruction of extended exponential sums of the form y (t) = ∑ j = 1 M (∑ m = 0 n j γ j , m t m) e 2 π λ j t , where the frequency parameters λ j ∈ ℂ are pairwise distinct. In order to reconstruct y(t) we employ a finite set of classical Fourier coefficients of y with regard to a finite interval (0 , P) ⊂ ℝ with P > 0. For our method, 2N + 2 Fourier coefficients c k (y) are sufficient to recover all parameters of y, where N : = ∑ j = 1 M (1 + n j) denotes the order of y(t). The recovery is based on the observation that for λ j ∉ i P ℤ the terms of y(t) possess Fourier coefficients with rational structure. We employ a recently proposed stable iterative rational approximation algorithm in [Y. Nakatsukasa, O. Sète and L. N. Trefethen, The AAA Algorithm for rational approximation, SIAM J. Sci. Comput.40(3) (2018) A1494A1522]. If a sufficiently large set of L Fourier coefficients of y is available (i.e. L ≥ 2 N + 2), then our recovery method automatically detects the number M of terms of y, the multiplicities n j for j = 1 , ... , M , as well as all parameters λ j , j = 1 , ... , M , and γ j , m , j = 1 , ... , M , m = 0 , ... , n j , determining y(t). Therefore, our method provides a new stable alternative to the known numerical approaches for the recovery of exponential sums that are based on Prony's method. [ABSTRACT FROM AUTHOR]

This paper applies business cycle accounting methodology to analyze the sources of aggregate fluctuations in Thai economy, especially during the recent severe recessions in 1997–1998 and 2008–2009. This exploration helps researchers uncover possible shocks and frictions that drive business cycle in a small and open economy within a minimal model set-up. Under this methodology, a fluctuation in aggregate output can be accounted for by exogenous time-varying wedges, namely efficiency wedge, investment wedge, labor wedge, government wedge, etc. This study found that the efficiency wedge is essential in accounting for aggregate output, consumption and investment fluctuation, while the bond wedge, which only present in an open economy setting, is a prime factor in accounting for movement in current accounts. I conducted counterfactual experiments to see what accounts for the output drop during recent recessions. I find that the efficiency wedge played a key role in recent recessions in Thailand, while the investment wedge was accounted for slow economic recovery after the recessions. [ABSTRACT FROM AUTHOR]

In this paper, we extend the divergence-free VEM of [L. Beirão da Veiga, C. Lovadina and G. Vacca, Virtual elements for the Navier–Stokes problem on polygonal meshes, SIAM J. Numer. Anal.56 (2018) 1210–1242] to the Oseen problem, including a suitable stabilization procedure that guarantees robustness in the convection-dominated case without disrupting the divergence-free property. The stabilization is inspired from [N. Ahmed, G. R. Barrenechea, E. Burman, J. Guzman, A. Linke and C. Merdon, A pressure-robust discretization of Oseen's equation using stabilization in the vorticity equation, SIAM J. Numer. Anal.59 (2021) 2746–2774] and includes local SUPG-like terms of the vorticity equation, internal jump terms for the velocity gradients, and an additional VEM stabilization. We derive theoretical convergence results that underline the robustness of the scheme in different regimes, including the convection-dominated case. Furthermore, as in the non-stabilized case, the influence of the pressure on the velocity error is moderate, as it appears only through higher-order terms. [ABSTRACT FROM AUTHOR]

Enterocytozoon hepatopenaei (EHP) was first described in Thailand in 2009 and has since been identified as a significant threat to the shrimp aquaculture industry. Recently, intracellular microsporidia were identified as a causative agent of hepatopancreatic microsporidiosis (HPM). To date, HPM has been listed as an emerging threat to shrimp farming industries because of reduced shrimp growth and survival rates which are considered to be a wasting disease. This study investigated the outbreaks of HPM in farmed Penaeus vannamei in Taiwan. Sixty-five shrimp samples were collected from Taiwan. The proportion of HPM-positive cases was 48% (31/65). Additionally, the gross signs in infected shrimp were stunted growth, sloughed hepatopancreas (HP), and lethargy. The smear impression on the HP also revealed the existence of large EHP spores. Nested-PCR findings identified that 9 cases were confirmed to be positive for the EhSWP1 gene in the first step and 22 cases tested positive for the second step. Phylogenetic analysis of EHP from Taiwan showed 100% similarity to EHP from Thailand, India, and the United States. Histopathological analysis of the HP revealed haemocyte infiltration and the presence of EHP spores in the hepatopancreatic tubule epithelial cells. These results demonstrated that EHP is the main cause in shrimp farms in Taiwan. [ABSTRACT FROM AUTHOR]

Siamese trackers, coupled with an efficient cross-correlation layer and benefiting from potent convolutional network technology, draw continuous interest in the field of visual object tracking. However, previous Siamese trackers may suffer from inconsistency of predictions that results in degraded performance during tracking: most of the prevalent Siamese networks employ two parallel branches for different subtasks whereas the corresponding outputs may mismatch with each other to some extent. To attack this issue, we advance a two-stage Siamese tracker named SiamPA for accurate object tracking. It employs center-based anchor-free heads in the first stage for preliminary predictions, meanwhile taking the carefully designed Prediction Alignment and Refinement module (PAR) as the second stage to refine the first-stage output. The PAR module is designed for Alignment and Refinement of multi-branch prediction, which works subtly in a mini-Siam manner. It is equipped with two different prediction branches: one used to align the multiple predictions induced in the first stage and the other to adjust coordinates of proposals. Extensive experiments are conducted to demonstrate the effectiveness of our SiamPA, showing that it achieves favorable performance on several prevalent benchmark datasets. Particularly, SiamPA achieves desirable performance while running at 67 FPS, which is far beyond real-time speed. [ABSTRACT FROM AUTHOR]

The Thai-China High-Speed Railway (HSR) project that connects Thailand, Laos and China is part of the Thai domestic strategy and China's Belt and Road Initiative. Thailand aims to become a regional logistic hub, while China plans to expand her connectivity with Southeast Asia. Approved in 2010, the project started construction in December 2017. Aside from the domestic political conflict, the HSR project was delayed by Thailand's attempt to negotiate with China. [ABSTRACT FROM AUTHOR]

An increasing number of higher education institutions have embraced Cloud Computing Services (CCS) to better respond to the issues arising from the COVID-19 pandemic. Cloud computing has helped to ease the process and lower the cost of offering online education and hybrid learning. However, some universities in Thailand face cloud computing adoption challenges because students lack awareness of the benefits and risks of CCS. Therefore, it is vital to identify the critical factors affecting the initial and continuance adoption of CCS by students in less developed countries. This study adopts a trade-off lens to assess the impact of the perceived usefulness and perceived risks regarding students' attitudes toward the initial and continuing adoption of CCS. Using a survey of CCS from a large public university in Thailand, we found that performance expectation and effort expectation positively affect perceived usefulness, and that authentication risks positively affect perceived risks. We also found that perceived usefulness rather than perceived risks is a deciding factor in adopting CCS. Higher education institutions in Thailand can accelerate the adoption of CCS by improving students' perceived performance and reducing the perceived risks. [ABSTRACT FROM AUTHOR]