Precipitation controls on nutrient budgets in subtropical and tropical forests and the implications under changing climate

Biological, geological and hydrological drivers collectively control forest biogeochemical cycling. However, based on a close examination of recent literature, we argue that the role of hydrological control particularly precipitation on nutrient budgets is significantly underestimated in subtropical and tropical forests, hindering our predictions of future forest nutrient status under a changing climate in these systems. To test this hypothesis, we analyzed two decades of monthly nutrient input and output data in precipitation and streamwater from a subtropical forested watershed in Taiwan, one of the few sites that has long-term nutrient input-output data in the tropics and subtropics. The results showed that monthly input and output of all ions and budgets (output – input) of most ions were positively correlated with precipitation quantity and there was a surprisingly greater net ion export during the wet growing season, indicating strong precipitation control on the nutrient budget. The strong precipitation control is also supported by the divergence of acidic precipitation and near neutral acidity of streamwater, with the former being independent from precipitation quantity but the latter being positively related to precipitation quantity. An additional synthesis of annual precipitation quantity and nutrient budgets of 32 forests across the globe showed a strong correlation between precipitation quantity and nutrient output-input budget, indicating that strong precipitation control is ubiquitous at the global scale and is particularly important in the humid tropical and subtropical forests. Our results imply that climate change could directly affect ecosystem nutrient cycling in the tropics through changes in precipitation pattern and amount

Levitation by a dipole electric field

The phenomenon of floating can be fascinating in any field, with its presence seen in art, films, and scientific research. This phenomenon is a captivating and pertinent subject with practical applications, such as Penning traps for antimatter confinement and Ion traps as essential architectures for quantum computing models. In our project, we reproduced the 1893 water bridge experiment using glycerol and first observed that lump-like macroscopic dipole moments can undergo near-periodic oscillations that exhibit floating effects and do not need classical bridge form. By combining experimental analysis, neural networks, investigation of Kelvin force generated by the Finite element method, and exploration of discharging, we gain insights into the mechanisms of motion. Our discovery has overturned the previous impression of a bridge floating in the water, leading to a deeper understanding of the new trap mechanism under strong electric fields with a single pair of electrodes.Comment: 5 pages, 5 figure

Medullary Sponge Kidney on Retrograde Pyelography

A woman aged 31 had recurrent urinary tract infection with bloody urine. A series image of medullary sponge kidney presented by intravenous urography (IVU) was detected dynamically by retrograde pyelography (RP). Other than ultrasonography and IVU, RP is also a reliable method to detect medullary sponge kidney

A hybrid optimization strategy for simplifying the solutions of support vector machines

99學年度林慧珍教師升等參考著作[[abstract]]The main issue is to search for a subset of the support vector solutions produced by an SVM that forms a discriminant function best approximating the original one. The work is accomplished by giving a fitness (objective function) that fairly indicates how well the discriminant function formed by a set of selected vectors approximates the original one, and searching for the set of vectors having the best fitness using PSO, EGA, or a hybrid approach combining PSO and EGA. Both the defined fitness function and the adopted search technique affect the performance. Our method can be applied to SVMs associated with any general kernel. The reduction rate can be adaptively adjusted based on the requirement of the task. The proposed approach is tested on some benchmark datasets. The experimental results show that the proposed method using PSO, EGA, or a hybrid strategy combining PSO and EGA associated with the objective function defined in the paper outperforms both the method proposed by Li et al. (2007) and our previously proposed method (Lin and Yeh, 2009), and that a hybrid strategy of PSO and EGA provides better results than a single strategy of PSO or EGA.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙

Optimal reduction of solutions for support vector machines

99學年度林慧珍教師升等代表著作[[abstract]]Being a universal learning machine, a support vector machine (SVM) suffers from expensive computational cost in the test phase due to the large number of support vectors, and greatly impacts its practical use. To address this problem, we proposed an adaptive genetic algorithm to optimally reduce the solutions for an SVM by selecting vectors from the trained support vector solutions, such that the selected vectors best approximate the original discriminant function. Our method can be applied to SVMs using any general kernel. The size of the reduced set can be used adaptively based on the requirement of the tasks. As such the generalization/complexity trade-off can be controlled directly. The lower bound of the number of selected vectors required to recover the original discriminant function can also be determined.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙

Segmental inner macular layer analysis with spectral-domain optical coherence tomography for early detection of normal tension glaucoma.

PurposeTo segment the inner macular layers (IML) and compare the discriminating abilities of the macular and peripapillary retinal nerve fiber layer (mRNFL and pRNFL, respectively) thicknesses in patients with early-stage normal tension glaucoma (NTG).DesignCross-sectional study.MethodsForty-nine normal subjects and 69 preperimetric glaucoma (PPG) and 60 NTG patients were enrolled. Spectral-domain optical coherence tomography (SD-OCT) was used to obtain pRNFL and macular thickness parameters and segment the IML in all subjects. Area under the receiver operating characteristic (AUROC) curves were used to compare the diagnostic capabilities of different parameters.ResultsThe pRNFL, total macular layer (TML), mRNFL, and macular ganglion cell layer (mGCL) were significantly thinner in the NTG group than in the PPG and normal groups. The global and superotemporal pRNFL and the mGCL in the superior outer area were the three best parameters for detecting early NTG. The discriminating capabilities of the superior and inferior mGCL were comparable to those of the corresponding pRNFL (p = 0.573, 0.841). Concerning location, the mGCL had higher AUROCs in the outer sectors (0.863, 0.837) than in the inner sectors (0.747, 0.747). Pearson's correlation coefficients also revealed significant correlations between the mGCL and pRNFL (superior: r = 0.499, inferior: r = 0.624). The strongest correlation was between the mGCL and mean deviation (MD) (superior: r = 0.434 and inferior: r = 0.402).ConclusionsThe diagnostic value of mGCL thickness is comparable to that of pRNFL thickness. IMLs in the outer sectors had better diagnostic capabilities than those in the inner sector for detecting early NTG