Explainable geospatial-artificial intelligence models for the estimation of PM2.5 concentration variation during commuting rush hours in Taiwan.

PM2.5 concentrations are higher during rush hours at background stations compared to the average concentration across these stations. Few studies have investigated PM2.5 concentration and its spatial distribution during rush hours using machine learning models. This study employs a geospatial-artificial intelligence (Geo-AI) prediction model to estimate the spatial and temporal variations of PM2.5 concentrations during morning and dusk rush hours in Taiwan. Mean hourly PM2.5 measurements were collected from 2006 to 2020, and aggregated into morning (7 a.m.-9 a.m.) and dusk (4 p.m.-6 p.m.) rush-hour mean concentrations. The Geo-AI prediction model was generated by integrating kriging interpolation, land-use regression, machine learning, and a stacking ensemble approach. A forward stepwise variable selection method based on the SHapley Additive exPlanations (SHAP) index was used to identify the most influential variables. The performance of the Geo-AI models for morning and dusk rush hours had accuracy scores of 0.95 and 0.93, respectively and these results were validated, indicating robust model performance. Spatially, PM2.5 concentrations were higher in southwestern Taiwan for morning rush hours, and suburban areas for dusk rush hours. Key predictors included kriged PM2.5 values, SO2 concentrations, forest density, and the distance to incinerators for both morning and dusk rush hours. These PM2.5 estimates for morning and dusk rush hours can support the development of alternative commuting routes with lower concentrations.

Assessing the ecological loss of mining areas in Taiwan.

Mines are mostly located in the mountains and national forestlands in Taiwan. The development and use of mines have severely damaged the environment. Despite the long history of mining, the value of forest ecological services lost during mining operations have not yet been incorporated into the expenses borne by miners, and miners are not liable for compensation for ecological damage. This study evaluated the forest ecosystem service benefits lost since mining began, with the aim of providing future reference for calculating ecological damage related to mining. We investigated Mount Taibai mines in Yilan (northeast Taiwan) and Mount Yongshi mines in Hualian (east Taiwan), which are richly forested areas. According to Article 13 of the Mining Act in Taiwan, mining rights have a limitation of 20 years, and the two mines in this study have been in operation for 20 years. By using four ecological services-forest production, carbon sequestration, water resource replenishment, and forest recreation-we estimated the loss of ecological values in both mining regions. The result indicated that the loss of total forest production benefits over 20 years was 7,498.6 k New Taiwanese dollars (NTD) in Mount Taibai mines and 6,543.1 k NTD for Mount Yongshi mines, while the loss for the total carbon sequestration benefits over 20 years was 19,950 k NTD in Mount Taibai mines and 17,400 k NTD in Mount Yongshi mines. The loss of value for the total water conservation benefits over 20 years was 11,160 k NTD in Mount Taibai mines and 5,070 k NTD in Mount Yongshi mines. The loss value of forest recreation over 20 years was 1,443,855 k NTD for the two mines.

The effect of computerized working memory training on working memory and emotion perception for patients with chronic schizophrenia and normal cognition.

BACKGROUND: Cognitive impairment and affective symptoms are hallmark features of patients with schizophrenia. This study determines whether a computerized working memory training program improves the patient's working memory and affective perception. METHODS: Thirty-nine male patients with schizophrenia, aged 25-65, participated in this study. The study uses a single-blind randomized controlled design. Twenty subjects were assigned to the experimental group and received an eight-week working memory computerized training course comprising four modules of the CogniPlus system. Nineteen subjects were assigned to the control group and received treatment as usual. All subjects received the same assessments twice, including the Mini-Mental Status Examination (MMSE), Working Memory Index (WMI) of Wechsler Adult Intelligence Scale-Third Edition, and the subjective rating of pictures of the International affective picture system by Self-Assessment Manikin (SAM). RESULTS: This study shows that computerized working memory training improves WMI and the score for MMSE and produces a significant increase in the pleasure score for S.A.M. for negative pictures, between the pretest and post-test for the experimental group. CONCLUSIONS: Working memory training improves working memory and emotion perception for patients with chronic schizophrenia and normal cognition. The limitations of this study and suggestions for future study are also discussed.

Real-Time Gauging of the Gelling Maturity of Duck Eggs Pickled in Strong Alkaline Solutions.

Although many ultraviolet-visible-near-infrared transmission spectroscopy techniques have been applied to chicken egg studies, such techniques are not suitable for duck eggs because duck eggshells are much thicker than chicken eggshells. In this study, a high-transmission spectrometer using an equilateral prism as a dispersive element and a flash lamp as a light source was constructed to nondestructively detect the transmission spectrum of duck eggs and monitor the pickling of eggs. The evolution of egg transmittance was highly correlated with the albumen during pickling. The transmittance exponentially decays with time during this period, and the decay rate is related to the pickling rate. The colors of the albumen and yolk remain almost unchanged in the first stage. A multiple linear regression analysis model that realizes a one-to-one association between the days of pickling and the transmission spectra was constructed to determine the pickling duration in the second stage. The coefficient of determination reached 0.88 for a single variable, wavelength, at 590 nm. This method can monitor the maturity of pickled eggs in real time and does not require the evolution of light transmittance.

Erratum to: Kinetic Characterization of Tyrosinase-catalyzed Oxidation of Four Polyphenols.

The article "Kinetic Characterization of Tyrosinase-catalyzed Oxidation of Four Polyphenols", written by Wan-yu LIU, Congming ZOU, Jian-hua HU, Zi-jun XU, Lu-qin SI, Jun-jun LIU, Jian-geng HUANG, was originally published electronically on the publisher's internet portal on May 2020 without open access. With the author(s)' decision to opt for Open Choice, the copyright of the article is changed to © The Author(s) 2020 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ ), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The original article has been corrected.

Kinetic Characterization of Tyrosinase-catalyzed Oxidation of Four Polyphenols.

Phenolic compounds such as chlorogenic acid, cryptochlorogenic acid, neochlorogenic acid and caffeic acid are widely distributed in fruits, vegetables and traditional Chinese medicines with a wide range of biological activities. Tyrosinase plays a critical role in the food industry, but recent studies have proposed unexplored aspects of clinical application. Tyrosinase-catalyzed oxidation of four polyphenols as well as its underlying mechanism remains unclear. In the current work, we investigated the kinetic properties of tyrosinase-catalyzed oxidation of the four polyphenols of interest. To measure the unstable o-quinone products, an analytical method using 3-methyl-2-benzothiazolinone hydrazone (MBTH) was established. The optimal incubation time, buffer pH, temperature and enzyme concentration for the enzyme activity in the presence of each polyphenol of interest were investigated. Under the final optimized conditions, the kinetics and substrate specificity of four polyphenols were examined. Kinetic data showed that tyrosinase had the greatest substrate affnity to chlorogenic acid compared with its isomers and caffeic acid. The catalytic effciency with chlorogenic acid was 8- to 15-fold higher than that with the other 3 polyphenols. Molecular docking study demonstrated that the tight binding of chlorogenic acid at the peripheral site should be the major reason for the specifcity to chlorogenic acid. In light of this, the rational design of high-affnity inhibitors against tyrosinase may focus on the binding of both the Cu site and peripheral site. This study will supply a basis for the selection of phenolic acids in food industry and health care.

Anaerobic Co-Digestion of Vegetable and Fruit Market Waste in LBR + CSTR Two-Stage Process for Waste Reduction and Biogas Production.

Vegetable and fruit waste (VFW) is becoming a heavy burden of municipal waste disposal because of its huge amount, but it is a potentially valuable resource that can be developed into high value products such as methane. Conventional anaerobic digestion processes are not suitable for solving the problem of easy acidification of VFW. Thus, a two-stage laboratory-scale anaerobic digestion system was assembled for waste reduction and biogas production of VFW in the mesophilic temperatures. The biphasic system consists of a 70-L leach bed reactor (LBR) and a 35-L continuous stirred tank reactor (CSTR). Water is sprinkled over the material to enhance the extraction process of acidification phase. The leachate was then transferred to the CSTR for biogas production. Batch digestion was lasted 120 h until no biogas was produced. Leachate with a volatile fatty acid (VFA) concentration of 7.6 g/L was obtained within 10 h. The results showed that overall 70.9% of the volatile solids (VS) was removed in the solid-phase system. Over 90% of VFAs were reduced in the methanogenic reactor, and it has been observed that the maximum biogas production rate was 51.26 mL/(d gVS). The maximum methane concentration in the produced biogas was 71%.

Thinning Effects on Biomass and Carbon Stock for Young Taiwania Plantations.

Forests play an important role as carbon sinks by sequestrating carbon through photosynthesis. Thinning treatments have large impacts on carbon storage, in addition to strengthening quality and quantity of plantations. This study analyzed the effects of different thinning treatments on carbon stocks in both individual trees and stands of Taiwania (Taiwania cryptomerioides) plantations. Repeated field measurements and allometric equations were used to calculate total C storage and sequestration rates of live trees. The results of this study showed that the total carbon stock of stands with thinning treatments was less than that of the non-thinned stands. The non-thinned 23-year old stands had an estimated carbon stock of 96.8 Mg C ha-1, which is higher than the carbon stock found in either medium- (84.1 Mg C ha-1) or heavily-thinned (74.7 Mg C ha-1) treatment plots of the same age. If the objective of Taiwania plantations was to store large amounts of carbon in the young growth stage, without regard to the initial rate of storage, a better option is no-thinning. However, the medium thinned forests seem to be more promising for carbon sequestration than the no-thinned forests if a longer period is considered.

Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging.

The aim of this work was to investigate the effect of multiple perfusion components on the pseudo-diffusion coefficient D * in the bi-exponential intravoxel incoherent motion (IVIM) model. Simulations were first performed to examine how the presence of multiple perfusion components influences D *. The real data of livers (n = 31), spleens (n = 31) and kidneys (n = 31) of 31 volunteers was then acquired using DWI for in vivo study and the number of perfusion components in these tissues was determined together with their perfusion fraction and D *, using an adaptive multi-exponential IVIM model. Finally, the bi-exponential model was applied to the real data and the mean, standard variance and coefficient of variation of D * as well as the fitting residual were calculated over the 31 volunteers for each of the three tissues and compared between them. The results of both the simulations and the in vivo study showed that, for the bi-exponential IVIM model, both the variance of D * and the fitting residual tended to increase when the number of perfusion components was increased or when the difference between perfusion components became large. In addition, it was found that the kidney presented the fewest perfusion components among the three tissues. The present study demonstrated that multi-component perfusion is a main factor that causes high variance of D * and the bi-exponential model should be used only when the tissues under investigation have few perfusion components, for example the kidney.

Generalization of intravoxel incoherent motion model by introducing the notion of continuous pseudodiffusion variable.

PURPOSE: A generalized intravoxel incoherent motion (IVIM) model, called the GIVIM, was proposed to better account for complex perfusion present in the tissues having various vessels and flow regimes, such as the liver. THEORY AND METHODS: The notions of continuous pseudodiffusion variable as well as perfusion fraction density function were introduced to describe the presence of multiple perfusion components in a voxel. The mean and standard deviation of Gaussian perfusion fraction density function were then used to define two new parameters, the mean pseudodiffusivity ( D¯) and pseudodiffusion dispersion (σ). The GIVIM model was evaluated by testing whether or not it can reflect hepatic perfusion difference caused by flow-compensated imaging sequences having different diffusion times. Also, D¯ was compared with D* in the standard IVIM model. RESULTS: The values of both D* and D¯ decreased after flow compensation and further decreased when shortening diffusion time. D¯ exhibited reduced variance in comparison with D*. In addition, σ also showed its sensitivity to hepatic perfusion difference caused by the flow-compensated imaging sequences. CONCLUSION: The GIVIM model has the ability to better describe multicomponent perfusion without lengthening acquisition time and knowing in advance the number and/or the variety of perfusion components. Magn Reson Med 76:1594-1603, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

Assessment of the Characteristics of Orientation Distribution Functions in HARDI Using Morphological Metrics.

Orientation distribution functions (ODFs) are widely used to resolve fiber crossing problems in high angular resolution diffusion imaging (HARDI). The characteristics of the ODFs are often assessed using a visual criterion, although the use of objective criteria is also reported, which are directly borrowed from classic signal and image processing theory because they are intuitive and simple to compute. However, they are not always pertinent for the characterization of ODFs. We propose a more general paradigm for assessing the characteristics of ODFs. The idea consists in regarding an ODF as a three-dimensional (3D) point cloud, projecting the 3D point cloud onto an angle-distance map, constructing an angle-distance matrix, and calculating metrics such as length ratio, separability, and uncertainty. The results from both simulated and real data show that the proposed metrics allow for the assessment of the characteristics of ODFs in a quantitative and relatively complete manner.

Quantitative representation and description of intravoxel fiber complexity in HARDI.

Diffusion tensor imaging and high angular resolution diffusion imaging are often used to analyze the fiber complexity of tissues. In these imaging techniques, the most commonly calculated metric is anisotropy, such as fractional anisotropy (FA), generalized anisotropy (GA), and generalized fractional anisotropy (GFA). The basic idea underlying these metrics is to compute the deviation from free or spherical diffusion. However, in many cases, the question is not really to know whether it concerns spherical diffusion. Instead, the main concern is to describe and quantify fiber complexity such as fiber crossing in a voxel. In this context, it would be more direct and effective to compute the deviation from a single fiber bundle instead of a sphere. We propose a new metric, called PEAM (PEAnut Metric), which is based on computing the deviation of orientation diffusion functions (ODFs) from a single fiber bundle ODF represented by a peanut. As an example, the proposed PEAM metric is used to classify intravoxel fiber configurations. The results on simulated data, physical phantom data and real brain data consistently showed that the proposed PEAM provides greater accuracy than FA, GA and GFA and enables parallel and complex fibers to be better distinguished.

Multifiber pathway reconstruction using bundle constrained streamline.

Fiber tractography techniques in diffusion magnetic resonance imaging have become a primary tool for studying the fiber architecture of biological tissues both noninvasively and in vivo. Streamline tracking, as a simple and efficient tractography technique, is widely used to reconstruct fiber pathways. It is however very sensitive to noisy estimation of local fiber orientations. In this paper, we propose a bundle constrained streamline method to accurately reconstruct multifiber pathways. The method introduces neighboring fiber consistency constraint in the tracking process and reconstructs fiber pathways that have optimal tradeoff between consistency with local fiber orientation estimations and similarity with neighboring fiber segment orientations. Results on synthetic, physical phantom and real human brain DW images show that the proposed method allows regular fiber pathways to be reconstructed and outperforms existing techniques.

A novel joint problem of routing, scheduling, and variable-width channel allocation in WMNs.

This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.

Feature-preserving smoothing of diffusion weighted images using nonstationarity adaptive filtering.

Although promising for studying the microstructure of in vivo tissues, the performance and the potentiality of diffusion tensor magnetic resonance imaging are hampered by the presence of high-level noise in diffusion weighted (DW) images. This paper proposes a novel smoothing approach, called the nonstationarity adaptive filtering, which estimates the intensity of a pixel by averaging intensities in its adaptive homogeneous neighborhood. The latter is determined according to five constraints and spatiodirectional nonstationarity measure maps. The proposed approach is compared with an anisotropic diffusion method used in DW image smoothing. Experimental results on both synthetic and real human DW images show that the proposed method achieves a better compromise between the smoothness of homogeneous regions and the preservation of desirable features such as boundaries, even for highly noisy data, thus leading to homogeneously consistent tensor fields and consequently more coherent fibers.