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Patient: Female, 83 Final Diagnosis: Rupture of infectious thoracic aortitis Symptoms: Cardiac pulmonary arrest Medication: — Clinical Procedure: Medication Specialty: Pathology Objective: Rare disease Background: Infectious aortitis has a poor prognosis and high mortality rate if untreated. Here, we report a case of rupture of infectious aortitis induced by methicillin-resistant staphylococcus aureus (MRSA). Case Report: An 83-year-old female patient was hospitalized due to continuous fever and diarrhea, which was diagnosed as colitis. The colitis was determined to have been induced by small vessel vasculitis upon histological examination. Fasting and central venous hyperalimentation using a peripherally inserted central catheter (PICC) were carried out for rest of the intestine. Swelling and pus were observed at the insertion site of the PICC. Since methicillin resistant staphylococcus aureus (MRSA) was detected in the culture of the pus and the blood, the patient was treated with vancomycin. After confirming that the blood culture became negative, prednisolone (PDL) was started as therapy for the colitis. Her diarrhea and fever improved. After vancomycin was stopped, MRSA-arthritis appeared. She suddenly died due to acute massive hemorrhage into the mediastinum and left thoracic cavity from the atherosclerotic ulcer of the thoracic aorta. It took 98 days from the first detection of MRSA in her blood to her death. We found gram-positive coccus in the ruptured aortic ulcer and we also detected MRSA gene by polymerase chain reaction in the ulcer. These results suggest that MRSA could colonize in the aortic ulcer during the MRSA-bacteremia and the MRSA could contribute to the vulnerability of the aortic wall. Conclusions: After septicemia occurrs in an elderly person, the patient should be followed up by considering infectious aortitis, especially when the patient has several risk factors.

Test strips and similar products are highly feasible tools for the rapid and approximate determination of chemical characteristics. Although the application of both the quantitative observation of coloration and regression modeling has recently enabled these products to become quantitative tools, their precision and accuracy may be further improved. In this study, the pseudocolor imaging of the coloration image, derivative spectrophotometry-like differentiation of the coloration values, and logarithmic conversion of the raw and derivative values were compared in terms of the precision and accuracy of the quantitative determination of corrosiveness, glucose, nitrate, and pH using the products. The best regression models for the determination were provided by the combination of pseudocolor imaging and differentiation (nitrate and pH); pseudocolor imaging, differentiation, and square-conversion (corrosiveness); or all of the techniques (glucose). When compared to the use of the original 10 raw colora...

The management of remote natural resources, e.g., land and water resources, requires frequent visits to these sites which could be costly in time and resources. Telemetry technologies help monitoring, observing and analyzing data at a distance; they use advanced information and communication protocols and have been applied to different applications including agricultural fields. The objective of this study was to evaluate the performance of a new telemetry technology, a field network system, to remotely monitoring natural resources (a citrus grove in the governorate of Nabeul and the dam of Joumine in the governorate of Bizerte) in Tunisia. The field network system, installed in these two remote locations and powered with solar panels, run well during the test periods. Although the system sent data daily, data transfer stability was a challenge that should be further studied and improved. The manuscript further reports on the quantitative and qualitative performance of the system in Tunisia. Overall, the field network system is a tool that could be used for different applications by researchers, agricultural producers, water resources managers, and policy makers.

The effects of a pseudo-colour imaging method were investigated by discriminating among similar agricultural plots in remote sensing images acquired using the Airborne Visible/Infrared Imaging Spectrometer (Indiana, USA) and the Landsat 7 satellite (Fergana, Uzbekistan), and that provided by GoogleEarth (Toyama, Japan). From each dataset, red (R)-green (G)-R-G-blue yellow (RGrgbyB), and RGrgby−1B pseudo-colour images were prepared. From each, cyan, magenta, yellow, key black, L*, a*, and b* derivative grayscale images were generated. In the Airborne Visible/Infrared Imaging Spectrometer image, pixels were selected for corn no tillage (29 pixels), corn minimum tillage (27), and soybean (34) plots. Likewise, in the Landsat 7 image, pixels representing corn (73 pixels), cotton (110), and wheat (112) plots were selected, and in the GoogleEarth image, those representing soybean (118 pixels) and rice (151) were selected. When the 14 derivative grayscale images were used together with an RGB yellow grayscale image, the overall classification accuracy improved from 74 to 94% (Airborne Visible/Infrared Imaging Spectrometer), 64 to 83% (Landsat), or 77 to 90% (GoogleEarth). As an indicator of discriminatory power, the kappa significance improved 1018-fold (Airborne Visible/Infrared Imaging Spectrometer) or greater. The derivative grayscale images were found to increase the dimensionality and quantity of data. Herein, the details of the increases in dimensionality and quantity are further analysed and discussed.

Using the standard colors provided in the instructions, PackTest products can approximate and quickly estimate the chemical characteristics of liquid samples. The combination of PackTest products and deep learning was examined for its accuracy and precision in quantifying chemical oxygen demand, ammonium ion, and phosphate ion using a pseudocolor imaging method. Each PackTest product underwent reactions with standard solutions. The generated color was scanner-read. From the color image, ten grayscale images representing the intensity values of red, green, blue, cyan, magenta, yellow, key black, and L∗, and the values of a∗ and b∗ were generated. Using the grayscale images representing the red, green, and blue intensity values, 73 other grayscale images were generated. The grayscale intensity values were used to prepare datasets for the ten and 83 (=10 + 73) images. For both datasets, chemical oxygen demand quantification was successful, resulting in values of normalized mean absolute error of less than 0.4% and coefficients of determination that were greater than 0.9996. However, the quantification of ammonium and phosphate ions commonly provided false positive results for the standard solution that contained no ammonium ion/phosphate ion. For ammonium ion, multiple regression markedly improved the accuracy using the pseudocolor method. Phosphate ion quantification was also improved by avoiding the use of an estimated value for the reference solution that contained no phosphate ion. Real details of the measurements and the perspectives were discussed.

Digital images of crops and other plants are useful in plant management although the brightness of digital images varies with time. Brightness adjustment of the entire area of color digital images has been quite difficult due to the absence of correlations among color components and brightness. Redness and greenness best correlate with brightness. Hence, red- and green-based pseudo-color models could enable the adjustment of brightness of the entire area of color digital images. A pseudo-color model, a red–green–white mat model, lost most of the information on yellowness when tested with a color gamut. However, a red–green-inverted [red + green] model largely retained the original information. In this color model, the intensity of blue becomes the indicator of darkness. As a complementary color model, a red–green–[red + green] color model was examined. The color model provided pseudo-color images carrying information on redness, greenness, and yellowness. By comparing grayscale images of a single color co...

A variety of test strips for the quick and rough estimation of analytes are commonly and reasonably available. Although the quickness is one of the advantages of test strips, the detection limit can be assumed to be much greater than the actually achievable values, because the quickness suggests the possibility of increasing the sensitivity by extending the reaction time. In this study, a home-use test strip product for urinary glucose detection was examined. When the reaction time of 30 seconds indicated in the instructions was extended to be three hours, the sensitivity increased 56-fold. A detection limit of 3.7 μM glucose was achieved, while the lowest concentration for colour production shown in the instructions was 2.78 mM. The sensitivity is moderately good among the various methods for glucose determination and is comparable to that of widely used high performance liquid chromatography and capillary electrophoresis and recently emerging non-enzymatic sensors. The application was demonstrated by determining glucose generated by the hydrolysis of cellulose in soil–water–cellulose suspensions. The sensitivity-increasing utilization of the convenient, reagentless, safe, cost-effective, and thus highly practical product by extending the originally-instructed reaction time is reported herein.

The system of rice intensification (SRI) is a set of practices in rice cultivation known for higher yields, lower water consumption, and environmentally friendly effects. However, few Thai farmers have adopted SRI even though Thailand is one of the largest rice producing nations. In this study, rice farmers in the northeastern, central, and southern regions of Thailand provided open-ended responses to descriptions of SRI prepared by the Thai government. Of the 66 rice farmers sampled, 11 positive comments were made, while 93 critical comments were directed at the time-critical and labor intensive practices necessary for SRI. Comments were especially critical of the labor intensiveness of the whole system, the slow response by rice to organic matter application, and the necessity of manual transplanting. Based on these results, it was concluded that changing the water regime would be the most feasible among the SRI practices for the farmers. The research incorporates a discussion of the natural and socioec...

Deforestation diminishes the ecological services that a forest provides (e.g., flood prevention). To restore such services, reforestation is often utilized. The full restoration of the original forest ecosystem, however, can take several decades. The present study was conducted to identify the missing key components for rehabilitation of a degraded plot of land in Thailand on which Acacia trees were planted 18 or 19 years ago. Canopy spectral and soil physicochemical profiles of the Acacia plantation plot showed more advanced rehabilitation than in the soil microbial functions, as represented by soil dehydrogenase activity and community-level physiological profiles, when compared with those of a natural evergreen forest. The slower restoration of the soil microbial functions was thought to: (1) be attributed to the loss of certain microbes that played important roles in the evergreen forest soil, and (2) restrict the restoration of the entire forest ecosystem which was found to be still progressing towards a full restoration of the land’s original conditions. Finally, possible measures for further rehabilitation of the ecosystem were discussed.

Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2 greater than 0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique's general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6-11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies' spectral profiles. Future aspects of this technique are discussed herein.

The current study proposes a novel method using Excel Solver to estimate, from limited data, crop coefficient (Kc) in paddy fields under intermittent irrigation (II). The proposed method was examined in a field experiment conducted at Karang Sari Village, Bekasi, West Java, Indonesia during the first rice season of 2007/2008 (December 2007 to April 2008) in the rainy season. As the control, continuous flooding irrigation (CF) was applied to the conventional rice cultivation fields. Based on the observed water storage, Excel Solver was used to estimate crop evapotranspiration. Estimated crop evapotranspiration was used to compute Kc value, then the average Kc values at each growth stage were compared with that for the CF treatment. The estimation method was evaluated by comparing estimated crop evapotranspiration and the crop evapotranspiration derived by the well established FAO procedure. Excel Solver estimated crop evapotranspiration accurately with R2 values higher than 0.81. Accordingly, more than 81% of the FAO crop evapotranspiration was described by the proposed method. Thus, Kc value could be well determined from those estimated crop evapotranspiration. Under the II treatment, the average Kc values were 0.70, 1.06, 1.24 and 1.22 for the initial, crop development, reproductive and late stages, respectively. These values were lower than those under the CF treatment for initial and crop development stages because of a minimal soil evaporation and intense dryness during these stages. However, average Kc values under the II treatment were higher than those under the CF treatment at the reproductive and late stages, indicating that the II treatment promoted more plant activity particularly for dry biomass production as indicated by a greater number of tillers per hill.

This study profiled soils over a land degradation gradient to obtain formulae as integrative measures for describing the gradient as a result of deforestation in Thailand. We applied antibiotic resistance most-probable-number profiling to the soil bacterial communities, and then described the gradient. Soil samples were collected on the gradient represented by dry evergreen forest (the original vegetation), dry deciduous forest (moderately disturbed) and bare ground (the most degraded) in February (dry season), March (shortly after temporal precipitation) and June (rainy season) 2001. In the period of this study, the degradation was consistently shown as soil conditions like sandy texture, high bulk density, lower pH, high exchangeable acidity, poor mineral and organic nutrients and dryness. Soil fertility index and soil evaluation factor, as the integrative measures of the intensity of land degradation, were described by scores on the first or the second principal component derived from the soil bacterial community profiles for each sampling time (R>0.457, p 0.501, p

This study was conducted to test the hypothesis that spatial variations in soil microbial variables in a Thai rice paddy are accurately described by multivariate profiles of the soil bacterial communities. We found that community-level physiological profiles of soil bacterial communities could better describe the population density of Rhizoctonia solani in soil than the physicochemical profi les do. However, soil dehydrogenase levels were closely correlated with soil fertility (P0.05), and these were better described by the physicochemical profiles. Hence, the hypothesis was rejected, and we suspect that soil microbial variables react differently to the same physicochemical changes. The average population density of R. solani (35 colony-forming units/g dry soil) was relatively high in the soil we studied, and the soil fertility was found to be among the poorest in Thailand. The soil quality was comparable to the most degraded bare ground soil in an adjacent bioreserve in terms of Shannon diversity index based on the communitylevel physiological profile as well as values of soil fertility indices. Overall, the soil microbial and physicochemical indicators showed that the paddy soil needs to be supplemented with soil nutrients. Otherwise, R. solani may cause a significant reduction in rice production.

The purpose of this study was to evaluate the effect of the knee position at three different flexion angles in magnetic resonance (MR) delineation of the anterior cruciate ligament (ACL) in the knee and to determine the optimal knee position. Thirteen knees of normal volunteers were examined at 15 degrees, 30 degrees, and 45 degrees of flexion with a surface coil, and three sets of obtained oblique sagittal MR images were evaluated by four observers. MR images at 30 degrees of knee flexion most clearly delineate compared with those at 15 degrees and 45 degrees of knee flexion. We recommended examining the knee in 30 degrees of flexion.

SUMMARY To find a principal component (PC) that quantifies the degree of soil degradation, we analyzed various physicochemical characteristics of soils over a land degradation gradient related to aboveground vegetation in the Sakacrat Environmental Research Station (SERS), Thailand. The aboveground vegetative types representing the degradation gradient were bare ground (BG, highly degraded), dry dipterocarp forest (DDF, moderately disturbed) and dry evergreen forest (DEF, the original vegetation). Soils under these vegetative types were sampled in February (dry season). March just after temporal precipitation) and June (rainy season) 2001. Through the period of this research, the degradation was consistently explained by sandy texture, high bulk density, lower pH, high exchangeable acidity, poor mineral and organic nutrients and dryness. Principal component analysis (PCA) was applied to determine significant principal components (PCs) that clarify the differences in soil properties between the vegetative ...

Multivariate profiling of soil bacterial communities provides information that will possibly contribute to the conservation and rehabilitation of the environment. In the Sakaerat Environmental Research Station, Thailand, the land degradation gradient, represented by a dry evergreen forest (DEF) and bare ground (BG) as a result of deforestation and subsequent land degradation was determined. Profiling was done with the antibiotic resistance most probable number (MPN) method (method 1), the antibiotic disc diffusion method (method 2) and the Biolog method. Compread to the DEF soil, the BG soil had significantly lower moisture content and pH values (at p=0.05), and total C and bacterial MPN count (at p=0.10). Profiles of the soils obtained by the antibiotic and the Biolog methods were analyzed. The profiling methods scored Wilk’s lambda values of 0.001 (method 1, p=0.086), 0.004 (method 2, p=0.157) and 0.000 to 0.110 (Biolog, p=0.040 to 0.708 at 0.2 to 1.4 average well color development values, AWCDs), then gave principal component score plots showing that all the methods successfully determined the degradation gradient with comparable efficiency. Redundancy analysis ordination diagrams for the above data sets indicated that the soil environmental factors that significantly correlated to the bacterial community profiles were: moisture content (p

The antibiotic disk diffution (ADD) method was compared with the Biolog method in terms of power to discriminate soils and dimension of the discrimination. Soils from a forest and a citrus field in Thailand were profiled with these methods. These methods differentiated the soils in the principal component score plots. Then, Wilk's lambda statistic was determined to estimate power of these methods to discriminate the soils. The ADD method scored Wilk's lambda of 0.003 (p = 0.144) and 0.000 (p=0.020), for direct and ratio-transformed calculation, respectively. The Biolog method recorded Wilk's lambda of 0.001 (p=0.067), 0.003 (p=0.144) and 0.035 (p=0.440), at 0.25, 0.50 and 0.75 average well color developments (AWCDs), respectively. The ADD method showed high discrimination power, or at least comparable to that of the Biolog method. Redundancy analysis (RDA) resulted in ordination diagrams, which revealed a difference in dimension of the soil discrimination among the methods and the AWCDs. The soil environmental factors significantly related to the bacterial profiles at p=0.05 were: available phosphorus (ADD method and Biolog 0.25 AWCD), and pH (Biolog 0.50 and 0.75 AWCD). These results indicated that the profiling methods and the AWCDs revealed the multidimensionality of the discrimination. The possibility of the application of the ADD method to extraction of such pieces of information for effective land management was suggested. O método de Difusão de Disco de Antibiótico (ADD) foi comparado ao método Biolog quanto ao seu poder de discriminar solos e quanto à dimensão da discriminação, analisando-se os solos de uma floresta e de um campo de cítricos na Tailândia. A diferenciação dos solos por esses métodos foi feita de acordo com o score plot do componente principal.Em seguida, determinou-se o valor de lambda de Wilk para estimar o poder discriminatório desses métodos. O método ADD resultou em lambda de Wilk de 0,003 (p=0,144) e 0,035 (p=0,440) para os valores diretos e transformados, respectivamente. Enquanto o método Biolog resultou em valores de lambda de Wilk de 0,001 (p=0,067), 0,003 (p=0,144) e 0,035 (p=0,440) para os valores médios de desenvolvimento de cor (AWCDs) 0,25, 0,50 e 0,75 respectivamente, o método ADD apresentou poder discriminatório elevado, ou, no mínimo semelhante ao do método Biolog. A análise de redundância resultou em diagramas que revelaram uma diferença na dimensão da discriminação entre os métodos e os valores de AWCD. Os fatores ambientais do solo que estiveram significativamente relacionados com os perfis bacterianos (p=0,0) foram: fósforo disponível (método ADD e Biolog 0,25 AWCD) e pH (Biolog 0,50 e 0,75 AWCD). Esses resultados indicaram que os dois métodos e as AWCDs revelaram a multidimensionalidade da discriminação. A aplicação do método ADD para obtenção dessas informações para um gerenciamento eficiente do solo foi sugerida.

The antibiotic disk diffution (ADD) method was compared with the Biolog method in terms of power to discriminate soils and dimension of the discrimination. Soils from a forest and a citrus field in Thailand were profiled with these methods. These methods differentiated the soils in the principal component score plots. Then, Wilk's lambda statistic was determined to estimate power of these methods to discriminate the soils. The ADD method scored Wilk's lambda of 0.003 (p = 0.144) and 0.000 (p=0.020), for direct and ratio-transformed calculation, respectively. The Biolog method recorded Wilk's lambda of 0.001 (p=0.067), 0.003 (p=0.144) and 0.035 (p=0.440), at 0.25, 0.50 and 0.75 average well color developments (AWCDs), respectively. The ADD method showed high discrimination power, or at least comparable to that of the Biolog method. Redundancy analysis (RDA) resulted in ordination diagrams, which revealed a difference in dimension of the soil discrimination among the methods and the AWCDs. The soil environmental factors significantly related to the bacterial profiles at p=0.05 were: available phosphorus (ADD method and Biolog 0.25 AWCD), and pH (Biolog 0.50 and 0.75 AWCD). These results indicated that the profiling methods and the AWCDs revealed the multidimensionality of the discrimination. The possibility of the application of the ADD method to extraction of such pieces of information for effective land management was suggested.O método de Difusão de Disco de Antibiótico (ADD) foi comparado ao método Biolog quanto ao seu poder de discriminar solos e quanto à dimensão da discriminação, analisando-se os solos de uma floresta e de um campo de cítricos na Tailândia. A diferenciação dos solos por esses métodos foi feita de acordo com o score plot do componente principal.Em seguida, determinou-se o valor de lambda de Wilk para estimar o poder discriminatório desses métodos. O método ADD resultou em lambda de Wilk de 0,003 (p=0,144) e 0,035 (p=0,440) para os valores diretos e transformados, respectivamente. Enquanto o método Biolog resultou em valores de lambda de Wilk de 0,001 (p=0,067), 0,003 (p=0,144) e 0,035 (p=0,440) para os valores médios de desenvolvimento de cor (AWCDs) 0,25, 0,50 e 0,75 respectivamente, o método ADD apresentou poder discriminatório elevado, ou, no mínimo semelhante ao do método Biolog. A análise de redundância resultou em diagramas que revelaram uma diferença na dimensão da discriminação entre os métodos e os valores de AWCD. Os fatores ambientais do solo que estiveram significativamente relacionados com os perfis bacterianos (p=0,0) foram: fósforo disponível (método ADD e Biolog 0,25 AWCD) e pH (Biolog 0,50 e 0,75 AWCD). Esses resultados indicaram que os dois métodos e as AWCDs revelaram a multidimensionalidade da discriminação. A aplicação do método ADD para obtenção dessas informações para um gerenciamento eficiente do solo foi sugerida.

Soil biodiversity may relate to environmental changes in the soil. To determine how soil environmental factors relate to soil bacterial diversity, we compared culturable bacterial communities in soils under bare ground (BG, highly degraded), dry dipterocarp forest (DDF, moderately disturbed) and dry evergreen forest (DEF, the original vegetation) that form a degradation gradient in the Sakaerat Environmental Research Station (SERS), Thailand. The Shannon diversity and evenness and Simpson indexes were determined using the sole carbon source most probable number method. Variation patterns of these indexes were analyzed for three data sets obtained during the dry (February) to wet aune) seasonal transition. Only the March data set had significant differences in the diversity indexes among the vegetative types. In March, BG soil had a significantly lower Shannon diversity index (1.77) and evenness index (0.64) than the others (2.34 and 0.84 for DDF and 2.41 and 0.87 for DEF), and a higher Simpson index of 0.23 (0.08 for DDF and 0.07 for DEF). Repeated measures analysis of variance at p=0.05 indicated that both vegetative type and sampling time were significant sources of variation of the Shannon indexes, while only sampling time was a significant source of variation of the Simpson index. Simple and multiple regression analyses and a redundancy analysis ordination diagram showed that throughout the period of the study, soil water content was the most significant soil environmental factor with regard to the Shannon and Simpson diversity indexes. The soil bacterial communities under all the vegetative types had higher diversity and evenness in the wet months. The transition from dry to wet season had a grater effect on variation of the diversity indexes than did the soil degradation gradient.

The correlation between bacterial concentration and the change in electrical conductivity was investigated for the indirect conductimetric assay which measures the conductivity change of an alkaline solution (NaOH) that absorbs the CO2 produced by bacterial growth and metabolism. The conductivity of the NaOH solution for a sample containing a higher bacterial concentration changed faster than that for a sample containing a lower concentration, and the logarithmic initial bacterial concentration (CB0) was related to the time (tD), at which the conductivity of the absorbent changed, in a linear fashion. We derived theoretically the validity of the linear relationship and estimated the generation time (tg) from the relationship. The tg values obtained by the indirect conductimetric assay were almost identical to those obtained by the direct conductimetric assay and the Standard Plate Count method.

Acute tendon rupture of the extensor pollicis longus (EPL) is rare. We present acute EPL tendon rupture associated with avulsed fracture of the second metacarpal at the insertion of extensor carpi radialis longus. Tendon rupture of the EPL was repaired with end-to-end suture and avulsed fracture of the second metacarpal base was treated with open reduction and internal fixation.

In paddy field, monitoring soil moisture is required for irrigation scheduling and water resource allocation, management and planning. The current study proposes an Artificial Neural Networks (ANN) model to estimate soil moisture in paddy field with limited meteorological data. Dynamic of ANN model was adopted to estimate soil moisture with the inputs of reference evapotranspiration (ETo) and precipitation. ETo was firstly estimated using the maximum, average and minimum values of air temperature as the inputs of model. The models were performed under different weather conditions between the two paddy cultivation periods. Training process of model was carried out using the observation data in the first period, while validation process was conducted based on the observation data in the second period. Dynamic of ANN model estimated soil moisture with R2 values of 0.80 and 0.73 for training and validation processes, respectively, indicated that tight linear correlations between observed and estimated values of soil moisture were observed. Thus, the ANN model reliably estimates soil moisture with limited meteorological data., Comment: 5 Pages

In this study, we attempted multivariate color profiling of soils over a land degradation gradient represented by dry evergreen forest (original vegetation), dry deciduous forest (moderately disturbed by fire), and bare ground (severely degraded) in Sakaerat, Thailand. The soils were sampled in a dry-to-wet seasonal transition. Values of the red-green-blue (RGB), cyan-magenta-yellow-key black (CMYK), L*a*b*, and hue-intensity-saturation (HIS) color models were determined using the digital software Adobe Photoshop. Land degradation produced significant variations (p

This study was conducted to investigate the rehabilitative effects of planting Acacia auriculiformis trees on degraded land by observing variations in soil bacterial community profiles provided by community-level physiological profiling. Soil bacterial and physicochemical comparisons between an original evergreen forest and the Acacia plantation plot, established on an area severely degraded as a result of deforestation, showed that most soil characteristics were rehabilitated 18 to 19 years after the plantation of Acacia according to single variables, Shannon and Simpson diversity indices based on the community-level physiological profiles, principal component analysis and redundancy analysis. However, a more strict statistical comparison, discriminant analysis, completely discriminated between the Acacia plantation and the evergreen forest soils when the community-level physiological profiles were compared. Thus, the Acacia plantation soil was shown to still be in the process to full recovery. Here, we discuss the relevance of planting A. auriculiformis in land rehabilitation schemes in savanna regions.

The purpose of this study was to evaluate the effect of the knee position at three different flexion angles in magnetic resonance (MR) delineation of the anterior cruciate ligament (ACL) in the knee and to determine the optimal knee position. Thirteen knees of normal volunteers were examined at 15 degrees, 30 degrees, and 45 degrees of flexion with a surface coil, and three sets of obtained oblique sagittal MR images were evaluated by four observers. MR images at 30 degrees of knee flexion most clearly delineate compared with those at 15 degrees and 45 degrees of knee flexion. We recommended examining the knee in 30 degrees of flexion.

Plant leaf area reveals various types of abnormalities which can enable appropriate plant/crop management actions. The quantification of plant leaf area is now feasible using commonly available digital photographing tools. Changes in brightness, however, make it difficult to compare leaf areas in digital photographs acquired at multiple time points. This difficulty could be overcome by employing an index of redness/greenness (R/G), which was suggested to be one of the best indices to discriminate between plant leaves and other objects such as soils. R/G and other indices were examined when discriminating cassava leaves from other objects in a field. A surveillance camera captured digital photographs on a daily basis. Of these, 183 photographs were stored. They were pasted into a single image file and simultaneously analyzed. The International Commission on Illumination color model’s a* was the best index in the discrimination, with a distinctiveness score of 1.36. R/G was the second best, with a distinctiveness score of 0.70. The percentage of leaf-likely pixels followed sigmoidal patterns with time, resulting in great coefficients of determination of 0.981 (a*) and 0.965 (R/G). The percentage of leaf-likely pixels and cassava leaf weight had a real-time response relationship. The range of the 95% confidence limit was narrowed from -16 to +14% of a predicted value of 98% leaf-likely pixels for R/G to ±12% for a*. Thus, the simultaneous binarization and the detection of leaf-likely pixels in the photographs acquired under different brightness levels was enabled with improved discrimination accuracy by employing a*.

For optimal management of agricultural fields by remote sensing, discrimination of the crop canopy from weeds and other objects is essential. In a digital photograph, a rice canopy was discriminated from a variety of weed and tree canopies and other objects by overlapping binary image layers of red-green-blue and other color components indicating the pixels with target canopy-specific (intensity) values based on the ranges of means ±( 3 ×) standard deviations. By overlapping and merging the binary image layers, the target canopy specificity improved to 0.0015 from 0.027 for the yellow 1 × standard deviation binary image layer, which was the best among all combinations of color components and means ±( 3 ×) standard deviations. The most target rice canopy-likely pixels were further identified by limiting the pixels at different luminosity values. The discriminatory power was also visually demonstrated in this manner.