Forest Industry Research Institute

This article summarizes our research on integrated timber investment returns, wood stumpage costs, and forest carbon production costs in 2023 for a representative selection of 15 countries, across 44 planted and 1 natural species/management regimes, using capital budgeting criteria, at a real discount rate of 8%, without land costs. Despite a large amount of disparate research, few, if any, studies have provided integrated estimates of investments, wood fiber costs, and forest carbon costs for CO2 offsets using fundamental primary data and production economics approaches. We expanded our prior research that estimated present values and internal rates of return for timber investments, using planted forest growth and yield, input management costs, and timber products prices by selected countries and species. We extended the production economics and forest investment calculations to estimate average stumpage costs for wood fiber per cubic meter per rotation. In addition, we calculated the costs to produce forest carbon for offsets in terms of carbon dioxide equivalent. Timber investment returns by country and species were the largest in tropical Asia and smallest in the Northern Hemisphere (including the United States and Europe), and South America had calculated returns between the two regions. Based on prior research, more developed countries had less investment risk, and had land markets that were more open for foreign investments. Wood costs and forest carbon production cost outcomes by country and species differed substantially from timber investment returns. The discounted wood costs per m3 were generally cheapest if the establishment costs and management inputs were minimized, or for long rotation planted stands. Forest carbon costs had similar rankings to wood costs, and even similar numbers, but were using a different metric—dollars per tCO2e. The calculated forest carbon costs are certainly among the cheapest of all types of typical carbon offsets. They were equal to or much less than the six primary developed country compliance market prices. However, they were higher than the current depressed public voluntary market prices. These results can be used for private, government, or nongovernment investments and for public policy intervention considerations.

This study focuses on Vietnam, a nation prone to various natural disasters, including storms, typhoons, floods, flash floods, and landslides. Utilizing annual panel data from 2010 to 2020 at the provincial level, we conducted a panel data analysis of provincial natural disaster damage in monetary terms considering meteorological, hydrological, geographic, and socioeconomic factors, including elevation, terrain ruggedness index (TRI), precipitation, gross regional domestic product (GRDP) per capita, and agricultural GRDP. Our hybrid model results indicate that precipitation was a significant contributor to economic damage. Two geographical factors, elevation and TRI, also influenced it. Elevation was associated with a decrease in economic damage, while TRI was associated with an increase. Economic development, as indicated by GRDP per capita, was found to be associated with an increase in natural disaster damage at lower levels of GRDP per capita; however, this relationship shifted to one of decreasing damage after reaching a certain threshold in GRDP per capita. Provinces with higher agricultural GRDP tended to suffer greater damage, but within-province agricultural development was not statistically significant at the 5% level. This finding aligns with the understanding that crop farming and the aquaculture industry are more susceptible to natural disasters because they are more directly exposed to natural elements. This also implies that regions where agriculture comprises a significant share of the economy are less resilient to natural disasters. These findings offer valuable insights for policymakers for sustainable economic development.

Alcohol consumption in Vietnam increased significantly over past decade alongside its economic development. However, in recent years, several alcohol control measures including a new drink-driving law and taxes as well as the COVID-19 pandemic have affected the consumption levels. This study aimed to monitor alcohol use trends in Hanoi over six consecutive years. We conducted a time series analysis of wastewater-based epidemiology (WBE) for alcohol consumption from 2018 to 2023. Ethyl sulfate, a biomarker for alcohol consumption, was measured in wastewater samples collected consecutively for at least 30 days each year from a catchment of approximately 400,000 people. The findings revealed a clear downward trend in alcohol consumption, with an average annual decline of 7.51%. Consumption remained stable across all days of the week, including during the COVID-19 pandemic. The most pronounced reduction occurred during 2020-2021, coinciding with COVID-19 restrictions. From 2022 onwards, signs of a rebound in alcohol consumption were observed, consistent with the national sales trends. Additionally, a marked shift was noted from on-trade (e.g., bars/restaurants) to off-trade (home-based), likely reflecting both pandemic-related restrictions and the enforcement of the strict drink-driving law. Alcohol consumption trends and shifts in drinking settings in Hanoi during the study period were likely influenced by a combination of public health measures and policy interventions, including the COVID-19 pandemic and the strict drink-driving law. This study successfully used WBE for relatively low-cost longitudinal monitoring of alcohol use in resource-limited settings, providing necessary evidence for public health policy formulation.

Abstract We investigate the thermal, structural, and mechanical properties of the CuZr metallic glass using molecular dynamics (MD) simulations, machine learning (ML), and Elastically Collective Nonlinear Langevin Equation (ECNLE) theory. The glass transition temperature (Tg ) and melting temperature (Tm ) are determined via MD and show good agreement with ML predictions trained on experimental datasets with deviations below 5%. The thermal structural evolution is analyzed through radial distribution functions and the Wendt–Abraham parameter to confirm the transition from amorphous to liquid states. Mechanical testing under uniaxial tension yields a Young’s modulus of approximately 85 GPa, consistent with experimental values. The temperature-dependent structural relaxation time predicted by the ECNLE theory using the MD-derived Tg closely agrees simulation data and captures both Arrhenius and super-Arrhenius regimes. This integrated approach demonstrates the effectiveness of combining simulations, data-driven modeling, and theoretical frameworks to explore the complex behavior of metallic glasses.

Most previous works on aboveground biomass (AGB) estimation provide a single estimate of AGB rather than the probability distribution of the predicted values. However, the NGBoost algorithm provides a probabilistic regression and uncertainty estimation solution. In this study, we validate NGBoost for estimating AGB in mangrove forests in northeastern Vietnam. We use spectral bands and image indices extracted from WorldView-2 as independent variables and field data from eight plots as the basis for analysis. By applying a spatial scaling sampling strategy, we derived approximately 290 aggregated samples from the established plots, which served as the dependent variables in subsequent modeling. To augment the training dataset and capture a broader spatial context, window filters of varying sizes were applied, enabling the inclusion of adjacent pixels into the sampling matrix. NGBoost hyperparameters were optimized by the meta-heuristic Fox-inspired Optimization Algorithm using the Root Mean Square Error (RMSE) as the objective function. The trained model ended up at an RMSE of 1.8771, a Mean Absolute Error (MAE) of 1.2898, and an R2 of 0.924. We interpreted the trained model and found that the Green Leaf Index is the most influential factor in AGB estimation, far more than the following factors. Finally, we used the trained model to estimate AGB and its probability distribution for the entire study area.

Keywords: payments for ecosystem services (PES), payments for ecosystem services programs (PESPs), benefits and risks, outcomes, weak sustainability, three-pillar approach, strong sustainability, transdisciplinary approach

Profitabilitas merupakan rasio untuk menilai kemampuan perusahaan dalam mencari keuntungan. Dalam memperoleh profitabilitas, perusahaan perlu kebijakan dan keputusan diantaranya mengenai perputaran kas dan perputaran persediaan. Penelitian ini bertujuan untuk mengetahui pengaruh perputaran perputaran kas dan perputaran persediaan terhadap Return On Investment pada PT.Ace Hardware Indonesia Tbk yang terdaftar di Bursa Efek Indonesia Periode 2019-2022. Teknik analisis data yang digunakan adalah regresi linear berganda yaitu dengan pengujian hipotesis dan determinasi. Metode penelitian ini menggunakan metode kuantitatif, penelitian ini menggunakan jenis data sekunder yaitu berasal dari laporan keuangan yang dipublikasikan di Bursa Efek Indonesia. Subjek penelitian ini adalah perusahaan dagang sub sektor retail dan objek penelitian adalah perputaran kas dan perputaran persediaan serta Return On Investment. Hasil penelitian menunjukkan bahwa perputaran kas berpengaruh signifikan terhadap Return On Investment, perputaran persediaan berpengaruh signifikan terhadap Return On Investment, perputaran kas dan perputaran persediaan secara simultan berpengaruh signifikan terhadap Return On Investment. Kesimpulan dari penelitian ini menunjukan bahwa perputaran Kas memiliki pengaruh positif yang signifikan terhadap Return On Investment (ROI) pada PT.ACE Hardware Indonesia Tbk yang terdaftar pada Bursa Efek Indonesia Periode 2019-2022.

Camellia specimens were collected from Mt. Ba Vi, Ba Vi National Park, during field surveys in 2022 (flowers) and 2023 (fruit). On the basis of morphological analyses, we determined that the morphology of these specimens matched that of Camellia tonkinensis. The characteristics of the specimens included papery-textured, elliptic or broad elliptic leaves with acuminate to narrowly acuminate apices, obtuse to rounded bases, petioles with channeled adaxial surfaces, tomentose gynoecia, 3(–4)-coccate capsules, and 1(–2) seeds per locule. A comparison of the morphological characteristics of the 2022 and 2023 collections (DL 220901, Dl 230201) was made with the type specimen (B. Balansa 3860, 1887) and the 2014 collections from Ngoc Son-Ngo Luong Nature Reserve (N. Q. Hieu et al. CPC616, CPC673, CPC712, CPC776). The characteristics and photographs of the rediscovered species from Mt. Ba Vi are presented herein. From the latest field surveys, the IUCN conservation status of Camellia tonkinensis was assessed as Critically Endangered (CR).

Abstract Prime editing (PE) enables almost all types of precise genome editing in animals and plants. It has been successfully adapted to edit several plants at variable efficiency and versatility. However, this technique is inefficient for dicots for unknown reasons. Here, by employing novel combinations of PE components, including an RNA chaperone and modified epegRNAs driven by a PolII-PolIII composite promoter and a viral replicon system, we obtained up to 9.7% of the desired PE efficiency at the callus stage assessed by targeted deep sequencing. Subsequently, we identified that up to 38.2% of transformants contained desired PE alleles in tomatoes andArabidopsis, marking the first successful heritable PE transmission in dicots. Our PE tools also showed high accuracy, specificity, and multiplexing capability, which unlocked the potential for practical PE applications in dicots, paving the way for transformative advancements in plant sciences.