Ecological and growth characteristics of trees after resumption of management in abandoned substitution forest in Japan

Since the 1950s, secondary (substitution) forests known as Satoyama woods have been abandoned due to changes in human lifestyle. The aim of this study was to investigate the relationships between human activity and substitution forests to better understand the traditional management required to prevent succession to evergreen forest. An objective was to identify the tree species, their numbers of trunks (NT), and the basal area (BA) (collectively, the stand density) in the woods today, half a century after people abandoned the substitution forests. Another goal was to compare, over a six-year period, the figures for total NT, BA, and the number of living, dead or fallen trunks between an abandoned substitution forest (a control plot) and a mown plot. NT decreased from 700 trunks/ha to 600 trunks/ha on the control, and from 600 trunks/ha to 400 trunks/ha on the mown plot at ground level over six years. The total BA increased annually on the control plot but decreased from 48m2/ha to 38m2/ha on the mown plot over six years. Many hydrophytes (Alnus japonica, etc.), Quercus serrata, and other trees species were found dead on the mown plots. All Quercus myrsinaefolia (evergreen trees) were still alive by the sixth year. These results demonstrate that the vegetation in these forests succeeded to Quercetum myrsinaefoliae, Tyoische Subass., which is therefore shown as the potential vegetation of succession over this timescale. If it is desired to maintain the traditional vegetation type, then the study suggests that it is necessary to manage the substitution forest. This is in order to prevent succession to evergreen forest and can be achieved by cutting Pleioblastus chino, climbing plants, and shade plants (evergreen trees)

Autonomous microfluidic transport using electrowetting-based valves and integrated cells

Autonomous control of the transport of solutions in microfabricated flow channels using electrowetting-based valves and integrated electrochemical cells is proposed. An electrowetting-based valve formed with a gold electrode was opened when an electrolyte solution reached a zinc electrode in a controlling flow channel and a potential was applied to the gold electrode, causing the transport of the solution in the flow channel. Independent composite electrodes consisting of gold and zinc could function in the same manner without requiring additional electrodes. Controlled autonomous transport of solutions in a network of flow channels could also be carried out using the integrated valves

Binding of Scandium Ions to Metalloporphyrin?Flavin Complexes for Long-Lived Charge Separation

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The Portrayal of Indonesian Image in 2007 Kompas Selected Short Stories: Social Problems, Criticisms and Hopes

Article aimed at exploring social problems reflected in 15 selected short stories printed in Kompas during 2007 both explicitly and implicitly. Specifically, this research is focused on the mapping of dominant social problems raised by the short stories, the social criticisms strongly voiced by the authors and the hopes of a better situation implicitly reflected in these interesting short stories. This study applies the Defamiliarization Effect promoted by Bertolt Brecht and Negative Dialectics or Negative Knowledge by Theodor Adorno, specifically in analyzing the literary works as a criticism tool. The result of the research shows that phenomena of social problems current lately in Indonesian context like identity, poverty, corruption, religious tensions, moral degradation, politics dirtiness, minority group problems, social security, natural disasters and the like are clearly seen and teased in these writings

Formation of supramolecular hetero-triads by controlling the hydrogen bonding of conjugate bases with a diprotonated porphyrin based on electrostatic interaction

The thermodynamic stability of diprotonated saddle-distorted dodecaphenylporphyrin (H4DPP2+(X−)2) was controlled by the hydrogen-bonding strength of conjugate bases (X−) of strong acids (HX) or acids (R+-COOH) having positively charged moieties. The thermodynamic control of H4DPP2+(X−)2 made it possible to achieve selective formation of supramolecular hetero-triads, H4DPP2+(X−)(Cl−)

Magnetized Fast Isochoric Laser Heating for Efficient Creation of Ultra-High-Energy-Density States

The quest for the inertial confinement fusion (ICF) ignition is a grand challenge, as exemplified by extraordinary large laser facilities. Fast isochoric heating of a pre-compressed plasma core with a high-intensity short-pulse laser is an attractive and alternative approach to create ultra-high-energy-density states like those found in ICF ignition sparks. This avoids the ignition quench caused by the hot spark mixing with the surrounding cold fuel, which is the crucial problem of the currently pursued ignition scheme. High-intensity lasers efficiently produce relativistic electron beams (REB). A part of the REB kinetic energy is deposited in the core, and then the heated region becomes the hot spark to trigger the ignition. However, only a small portion of the REB collides with the core because of its large divergence. Here we have demonstrated enhanced laser-to-core energy coupling with the magnetized fast isochoric heating. The method employs a kilo-tesla-level magnetic field that is applied to the transport region from the REB generation point to the core which results in guiding the REB along the magnetic field lines to the core. 7.7 $\pm$ 1.3 % of the maximum coupling was achieved even with a relatively small radial area density core ($\rho R$ $\sim$ 0.1 g/cm$^2$). The guided REB transport was clearly visualized in a pre-compressed core by using Cu-$K_\alpha$ imaging technique. A simplified model coupled with the comprehensive diagnostics yields 6.2\% of the coupling that agrees fairly with the measured coupling. This model also reveals that an ignition-scale areal density core ($\rho R$ $\sim$ 0.4 g/cm$^2$) leads to much higher laser-to-core coupling ($>$ 15%), this is much higher than that achieved by the current scheme

Improving Compound–Protein Interaction Prediction by Self-Training with Augmenting Negative Samples

Identifying compound-protein interactions (CPIs) is crucial for drug discovery. Since experimentally validating CPIs is often time-consuming and costly, computational approaches are expected to facilitate the process. Rapid growths of available CPI databases have accelerated the development of many machine-learning methods for CPI predictions. However, their performance, particularly their generalizability against external data, often suffers from a data imbalance attributed to the lack of experimentally validated inactive (negative) samples. In this study, we developed a self-training method for augmenting both credible and informative negative samples to improve the performance of models impaired by data imbalances. The constructed model demonstrated higher performance than those constructed with other conventional methods for solving data imbalances, and the improvement was prominent for external datasets. Moreover, examination of the prediction score thresholds for pseudo-labeling during self-training revealed that augmenting the samples with ambiguous prediction scores is beneficial for constructing a model with high generalizability. The present study provides guidelines for improving CPI predictions on real-world data, thus facilitating drug discovery