Properties of seawater and particulate matter (fluorescence) from a WETLabs Eco-FL sensor mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements made with a WETLabs Eco-FL sensor mounted on the flowthrough system between June 4th, 2011 and March 30th, 2012. Data was recorded approximately every 10s. Two issues affected the data: 1. Periods when the water 0.2µm filtered water were used as blanks and 2. Periods where fluorescence was affected by non-photochemical quenching (NPQ, chlorophyll fluorescence is reduced when cells are exposed to light, e.g. Falkowski and Raven, 1997). Median data and their standard deviation were binned to 5min bins with period of light/dark indicated by an added variable (so that NPQ affected data could be neglected if the user so chooses). Data was first calibrated using HPLC data collected on the Tara (there were 36 data within 30min of each other). Fewer were available when there was no evident NPQ and the resulting scale factor was 0.0106 mg Chl m-3/count. To increase the calibration match-ups we used the AC-S data which provided a robust estimate of Chlorophyll (e.g. Boss et al., 2013). Scale factor computed over a much larger range of values than HPLC was 0.0088 mg Chl m-3/count (compared to 0.0079 mg Chl m-3/count based on manufacturer). In the archived data the fluorometer data is merged with the TSG, raw data is provided as well as manufacturer calibration constants, blank computed from filtered measurements and chlorophyll calibrated using the AC-S. For a full description of the processing of the Eco-FL please see Taillandier, 2015.

Impact of power allocation strategies in long-haul few-mode fiber transmission systems

We report for the first time on the limitations in the operational power range of few-mode fiber based transmission systems, employing 28Gbaud quadrature phase shift keying transponders, over 1,600km. It is demonstrated that if an additional mode is used on a preexisting few-mode transmission link, and allowed to optimize its performance, it will have a significant impact on the pre-existing mode. In particular, we show that for low mode coupling strengths (weak coupling regime), the newly added variable power mode does not considerably impact the fixed power existing mode, with performance penalties less than 2dB (in Q-factor). On the other hand, as mode coupling strength is increased (strong coupling regime), the individual launch power optimization significantly degrades the system performance, with penalties up to ∼6dB. Our results further suggest that mutual power optimization, of both fixed power and variable power modes, reduces power allocation related penalties to less than 3dB, for any given coupling strength, for both high and low differential mode delays. © 2013 Optical Society of America.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Value added products from modified kaolins : new chemical routes to new markets

Chemical treatments of kaolins to produce nanocrystalline or "X-ray amorphous", stable aluminosilicates with variable - but reproducible - types of micro- and meso-porosity have been developed. These materials show cation exchange capacities and surface area values significantly higher (ranging from 10x to 100x) than kaolin and show good acid resistance to pH~3.0. The combination of these properties offers strong potential for many new applications of kaolin-derived materials in large worldwide markets such as environmental remediation and catalysis. Kaolin amorphous derivative (KAD) is well-suited to removal of many toxic metals down to ppb range from acid mine drainage. Engineering development trials of the KAD manufacturing process and the utilisation of KAD in polluted waters such as acid mine drainage indicates that scale-up from bench-scale is not a barrier to market entry.

Plot size matters: interference from intergenotypic competition in plant phenotyping studies

Genetic and physiological studies often comprise genotypes diverse in vigour, size and flowering time. This can make the phenotyping of complex traits challenging, particularly those associated with canopy development, biomass and yield, as the environment of one genotype can be influenced by a neighbouring genotype. Limited seed and space may encourage field assessment in single, spaced rows or in small, unbordered plots, whereas the convenience of a controlled environment or greenhouse makes pot studies tempting. However, the relevance of such growing conditions to commercial field-grown crops is unclear and often doubtful. Competition for water, light and nutrients necessary for canopy growth will be variable where immediate neighbours are genetically different, particularly under stress conditions, where competition for resources and influence on productivity is greatest. Small hills and rod-rows maximise the potential for intergenotypic competition that is not relevant to a crop’s performance in monocultures. Response to resource availability will typically vary among diverse genotypes to alter genotype ranking and reduce heritability for all growth-related traits, with the possible exception of harvest index. Validation of pot experiments to performance in canopies in the field is essential, whereas the planting of multirow plots and the simple exclusion of plot borders at harvest will increase experimental precision and confidence in genotype performance in target environments.

Sliding window two-thermocouple sensor characterization for variable flow environments

A two-thermocouple sensor characterization method for use in variable flow applications is proposed. Previous offline methods for constant velocity flow are extended using sliding data windows and polynomials to accommodate variable velocity. Analysis of Monte-Carlo simulation studies confirms that the unbiased and consistent parameter estimator outperforms alternatives in the literature and has the added advantage of not requiring a priori knowledge of the time constant ratio of thermocouples. Experimental results from a test rig are also presented. © 2008 The Institute of Measurement and Control.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Characterization of the variable cow's age at last calving as a measurement of longevity by using the Kaplan-Meier estimator and the Cox model

In most studies on beef cattle longevity, only the cows reaching a given number of calvings by a specific age are considered in the analyses. With the aim of evaluating all cows with productive life in herds, taking into consideration the different forms of management on each farm, it was proposed to measure cow longevity from age at last calving (ALC), that is, the most recent calving registered in the files. The objective was to characterize this trait in order to study the longevity of Nellore cattle, using the Kaplan-Meier estimators and the Cox model. The covariables and class effects considered in the models were age at first calving (AFC), year and season of birth of the cow and farm. The variable studied (ALC) was classified as presenting complete information (uncensored = 1) or incomplete information (censored = 0), using the criterion of the difference between the date of each cow's last calving and the date of the latest calving at each farm. If this difference was >36 months, the cow was considered to have failed. If not, this cow was censored, thus indicating that future calving remained possible for this cow. The records of 11 791 animals from 22 farms within the Nellore Breed Genetic Improvement Program ('Nellore Brazil') were used. In the estimation process using the Kaplan-Meier model, the variable of AFC was classified into three age groups. In individual analyses, the log-rank test and the Wilcoxon test in the Kaplan-Meier model showed that all covariables and class effects had significant effects (P < 0.05) on ALC. In the analysis considering all covariables and class effects, using the Wald test in the Cox model, only the season of birth of the cow was not significant for ALC (P > 0.05). This analysis indicated that each month added to AFC diminished the risk of the cow's failure in the herd by 2%. Nonetheless, this does not imply that animals with younger AFC had less profitability. Cows with greater numbers of calvings were more precocious than those with fewer calvings. Copyright © The Animal Consortium 2012.

Poincaré plot indexes of heart rate variability: Relationships with other nonlinear variables

The Poincaré plot for heart rate variability analysis is a technique considered geometrical and non-linear, that can be used to assess the dynamics of heart rate variability by a representation of the values of each pair of R-R intervals into a simplified phase space that describes the system's evolution. The aim of the present study was to verify if there is some correlation between SD1, SD2 and SD1/SD2 ratio and heart rate variability nonlinear indexes either in disease or healthy conditions. 114 patients with arterial coronary disease and 65 healthy subjects underwent 30. minute heart rate registration, in supine position and the analyzed indexes were as follows: SD1, SD2, SD1/SD2, Sample Entropy, Lyapunov Exponent, Hurst Exponent, Correlation Dimension, Detrended Fluctuation Analysis, SDNN, RMSSD, LF, HF and LF/HF ratio. Correlation coefficients between SD1, SD2 and SD1/SD2 indexes and the other variables were tested by the Spearman rank correlation test and a regression analysis. We verified high correlation between SD1/SD2 index and HE and DFA (α1) in both groups, suggesting that this ratio can be used as a surrogate variable. © 2013 Elsevier B.V.

Time Variable Gravity: Contributions of GOCE Satellite Data to Monthly and Bi-monthly GRACE Gravity Estimates

A feasibility study by Pail et al. (Can GOCE help to improve temporal gravity field estimates? In: Ouwehand L (ed) Proceedings of the 4th International GOCE User Workshop, ESA Publication SP-696, 2011b) shows that GOCE (‘Gravity field and steady-state Ocean Circulation Explorer’) satellite gravity gradiometer (SGG) data in combination with GPS derived orbit data (satellite-to-satellite tracking: SST-hl) can be used to stabilize and reduce the striping pattern of a bi-monthly GRACE (‘Gravity Recovery and Climate Experiment’) gravity field estimate. In this study several monthly (and bi-monthly) combinations of GRACE with GOCE SGG and GOCE SST-hl data on the basis of normal equations are investigated. Our aim is to assess the role of the gradients (solely) in the combination and whether already one month of GOCE observations provides sufficient data for having an impact in the combination. The estimation of clean and stable monthly GOCE SGG normal equations at high resolution ( >  d/o 150) is found to be difficult, and the SGG component, solely, does not show significant added value to monthly and bi-monthly GRACE gravity fields. Comparisons of GRACE-only and combined monthly and bi-monthly solutions show that the striping pattern can only be reduced when using both GOCE observation types (SGG, SST-hl), and mainly between d/o 45 and 60.

Variable structure control with chattering reduction of a generalized T-S model

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. New functions for chattering reduction and error convergence without sacrificing invariant properties are proposed. The main feature of the proposed method is that the switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules; together with the state variables. In this work, a tuning of the well known weighting parameters approach is proposed to optimize local and global approximation and modelling capability of the Takagi-Sugeno (T-S) fuzzy model to improve the choice of the performance index and minimize it. The main problem encountered is that the T-S identification method can not be applied when the membership functions are overlapped by pairs. This in turn restricts the application of the T-S method because this type of membership function has been widely used in control applications. The approach developed here can be considered as a generalized version of the T-S method. An inverted pendulum mounted on a cart is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of the proposed estimation approach in comparison with the original T-S model. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the chattering reduction algorithm. In this paper, we prove that the proposed estimation algorithm converge the very fast, thereby making it very practical to use. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved.

Optimización de la aplicación de lodos de depuración de aguas residuales al abonado o mejora de suelos

El objetivo de este trabajo de investigación fue evaluar el efecto de la aplicación de lodos residuales procedentes de una planta de tratamiento de aguas residuales acondicionados como biosólido para el abonado de tres cultivos agrícolas. Esto se realizó a través del estudio de las variables de producción (desarrollo vegetal de cada cultivo) y de la comparación de las características de los suelos utilizados antes y después de los ensayos experimentales. A través de la investigación se confirmó la mejora en la calidad del suelo y mejor rendimiento de cultivo debido a los biosólidos procedentes de tratamiento de aguas residuales. Este trabajo de investigación de tipo descriptivo y experimental, utilizó lodos optimizados que fueron aplicados a tres cultivos agrícolas de ciclo corto. Fueron evaluados dos cultivos (sandía y tomate) bajo riego y un cultivo (arroz) en secano. En la primera fase del trabajo se realizó la caracterización de los lodos, para ellos se realizaron pruebas físico químicas y microbiológicas. Fue utilizado el método de determinación de metales por espectrometría de emisión atómica de plasma acoplado inductivamente, (ICP-AES) para conocer las concentraciones de metales. La caracterización microbiológica para coliformes totales y fecales se realizó utilizando la técnica del Número más probable (NMP), y para la identificación de organismos patógenos se utilizó el método microbiológico propuesto por Kornacki & Johnson (2001), que se fundamenta en dos procesos: pruebas presuntivas y prueba confirmativa. Tanto los resultados para la determinación de metales y elementos potencialmente tóxicos; como las pruebas para la determinación de microorganismos potencialmente peligrosos, estuvieron por debajo de los límites considerados peligrosos establecidos por la normativa vigente en Panama (Reglamento Técnico COPANIT 47-2000). Una vez establecido la caracterización de los lodos, se evalúo el potencial de nutrientes (macro y micro) presentes en los biosólidos para su potencial de uso como abono en cultivos agrícolas. El secado de lodos fue realizado a través de una era de secado, donde los lodos fueron deshidratados hasta alcanzar una textura pastosa. “La pasta de lodo” fue transportada al área de los ensayos de campo para continuar el proceso de secado y molida. Tres ensayos experimentales fueron diseñados al azar con cinco tratamientos y cuatro repeticiones para cada uno de los tres cultivos: sandía, tomate, arroz, en parcelas de 10m2 (sandía y tomate) y 20 m2 (arroz) para cada tratamiento. Tres diferentes dosis de biosólidos fueron evaluadas y comparadas con un tratamiento de fertilizante comercial y un tratamiento control. La dosis de fertilizante comercial utilizada en cada cultivo fue la recomendada por el Instituto de Investigación Agropecuaria de Panamá. Los ensayos consideraron la caracterización inicial del suelo, la preparación del suelo, semilla, y arreglo topográfico de los cultivos siguiendo las recomendaciones agronómicas de manejo de cultivo establecida por el Instituto de Investigación Agropecuaria. Para los ensayos de sandía y tomate se instaló el sistema de riego por goteo. Se determinaron los ácidos húmicos presentes en los cultivos, y se estudiaron las variables de desarrollo de cada cultivo (fructificación, cosecha, peso de la cosecha, dimensiones de tamaño y color de las frutas, rendimiento, y la relación costo – rendimiento). También se estudiaron las variaciones de los macro y micro nutrientes y las variaciones de pH, textura de suelo y MO disponible al inicio y al final de cada uno de los ensayos de campo. Todas las variables y covariables fueron analizadas utilizando el programa estadístico INFOSAT (software para análisis estadístico de aplicación general) mediante el análisis de varianza, el método de comparaciones múltiples propuesto por Fisher (LSD Fisher) para comparar las medias de los cultivares y el coeficiente de correlación de Pearson que nos permite analizar si existe una asociación lineal entre dos variables. En la evaluación de los aportes del biosólido a los cultivos se observó que los macronutrientes N y P se encontraban de los límites requeridos en cada uno de los cultivos, pero que los niveles de K estuvieron por debajo de los requerimientos de los cultivos. A nivel de la fertilización tradicional con fertilizante químico se observó que la dosis recomendada para cada uno de los cultivos del estudio estaba sobreestimada en los tres principales macronutrientes: Nitrógeno, Fosforo y Potasio. Contenían concentraciones superiores de N, P y K a las requeridas teóricamente por el cultivo. El nutriente que se aporta en exceso es el Fósforo. Encontramos que para el cultivo de sandía era 18 veces mayor a lo requerido por el cultivo, en tomate fue 12 veces mayor y en el cultivo de arroz, 34 veces mayor. El fertilizante comercial tuvo una influencia en el peso final y rendimiento final en cada uno de los cultivos del estudio. A diferencia, los biosólidos tuvieron una influencia directa en el desarrollo de los cultivos (germinación, coloración, tamaño, longitud, diámetro, floración y resistencia a enfermedades). Para el caso de la sandía la dosis de biosólido más cercana al óptimo para el cultivo es la mayor dosis aplicada en este ensayo (97.2 gramos de biosólido por planta). En el caso de tomate, el fertilizante comercial obtuvo los mejores valores, pero las diferencias son mínimas con relación al tratamiento T1, de menor dosis de biosólido (16.2 gramos de biosólido por planta). Los resultados generales del ensayo de tomate estuvieron por debajo del rendimiento esperado para el cultivo. Los tratamientos de aplicación de biosólidos aportaron al desarrollo del cultivo en las variables tamaño, color y resistencia a las enfermedades dentro del cultivo de tomate. Al igual que el tomate, en el caso del arroz, el tratamiento comercial obtuvo los mejores resultados. Los resultados finales de peso y rendimiento del cultivo indican que el tratamiento (T2), menor dosis de biosólido (32.4 gramos por parcela), no tuvo diferencias significativas con los resultados obtenidos en las parcelas con aplicación de fertilizante comercial (T1). El tratamiento T4 (mayor dosis de biosólido) obtuvo los mejores valores para las variables germinación, ahijamiento y espigamiento del cultivo, pero al momento de la maduración obtuvo los menores resultados. Los biosólidos aportan nutrientes a los cultivos y al final del ensayo se observó que permanecen disponibles en el suelo, aportando a la mejora del suelo final. En los tres ensayos, se pudo comprobar que los aportes de los biosólidos en el desarrollo vegetativo de los cultivos. También se encontró en todos los ensayos que no hubo diferencias significativas (p > 0.05) entre los tratamientos de biosólidos y fertilizante comercial. Para obtener mejores resultados en estos tres ensayos se requeriría que a la composición de biosólidos (utilizada en este ensayo) se le adicione Potasio, Calcio y Magnesio en las cantidades requeridas por cada uno de los cultivos. ABSTRACT The objective of this investigation was to evaluate the effect of residual sewage sludge obtained from the residual water of a treatment plant conditioned as Biosolid used on three reliable agricultural crops. The effect of the added sewage sludge was evaluated through the measurement of production variables such as crop plant development and the comparison of the soil characteristics used before and after the experimental tests. This investigation confirmed that biosolids from wastewater treatment can contribute to the growth of these crops. In this experimental approach, optimized sludge was applied to three short-cycle crops including two low-risk crops (watermelon and tomato) and one high-risk crop (rice) all grown on dry land. In the first phase of work, the characteristics of the sludge were assessed using chemical, physical and microbiological tests. The concentrations of metals were determined by atomic emission spectrometry inductively coupled plasma, (ICP-AES). Microbiological characterization was performed measuring total coliform and fecal count using the most probable number technique (NMP) and microbiological pathogens were identified using Kornacki & Johnson (2001) method based on two processes: presumptive and confirmatory tests. Both the results for the determination of metals and potentially toxic elements, as testing for the determination of potentially dangerous microorganisms were below the limits established by the applicable standard in Panama (Technical Regulate COPANIT 47-2000). After the metal and bacterial characterization of the sludge, the presence of macro or micronutrients in biosolids was measured to evaluate its potential for use as fertilizer in the growth of agricultural crops. The sludge was dehydrated via a drying process into a muddy slurry. The pulp slurry was transported to the field trial area to continue the process of drying and grinding. Three randomized experimental trials were designed to test with five treatment regimens and four replications for each of the crops: watermelon, tomato, rice. The five treatment regimens evaluated were three different doses of bio solid with commercial fertilizer treatment control and no fertilizer treatment control. Treatment areas for the watermelon and tomato were 10m2 plots land and for rice was 20m2. The amount of commercial fertilizer used to treat each crop was based on the amount recommended by Agricultural Research Institute of Panama. The experimental trials considered initial characterization of soil, soil preparation, seed, and crop topographical arrangement following agronomic crop management recommendations. For the tests evaluating the growth of watermelons and tomatoes and drip irrigation system was installed. The amount of humic acids present in the culture were determined and developmental variable of each crop were studied (fruiting crop harvest weight, size dimensions and color of the fruit, performance and cost effectiveness). Changes in macro and micronutrients and changes in pH, soil texture and OM available were measured at the beginning and end of each field trial. All variables and covariates were analyzed using INFOSAT statistical program (software for statistical analysis of general application) by analysis of variance, multiple comparisons method as proposed by Fisher (LSD Fisher) to compare the means of cultivars and the Pearson ratio that allows us to analyze if there is a linear association between two variables. In evaluating the contribution of biosolids to agricultural crops, the study determined that the macronutrients N & P were within the requirements of crops, but K levels were below the requirements of crops. In terms of traditional chemical fertilizer fertilization, we observed that the recommended dose for each study crop was overestimated for the three major nutrients: nitrogen, phosphorus and potassium. Higher concentrations containing N, P and K to the theoretically required by the crop. The recommended dose of commercial fertilizer for crops study contained greater amounts of phosphorus, crops that need. The level of phosphorous was found to be18 times greater than was required for the cultivation of watermelon; 12 times higher than required for tomato, and 34 times higher than required for rice cultivation. Phosphorus inputs of commercial fertilizer were a primary influence on the weight and performance of each crop. Unlike biosolids had a direct influence on crop development (germination, color, size, length, diameter, flowering and disease resistance). In the case of growth of watermelons, the Biosolid dose closest to the optimum for cultivation was applied the highest dose in this assay (97.2 grams of bio solids per plant). In the case of tomatoes, commercial fertilizer had the best values but the differences were minimal when compared to treatment T1, the lower dose of sewage sludge (Biosolid 16.2 grams per plant). The overall results for the tomato crop yield of the trial were lower than expected. Additionally, the application of biosolids treatment contributed to the development of fruit of variable size, color and disease resistance in the tomato crops. Similar to the tomato crop, commercial fertilizer treatment provided the best results for the rice crop. The final results of weight and crop yield for rice indicated that treatment with T2 amount of biosolids (34.2 grams per plot) was not significantly different from the result obtained in the application plot given commercial fertilizer (T1). The T4 (higher dose of bio solid) treatment had the best values for the germination, tillering and bolting variables of the rice crop but for fruit ripening yielded lower results. In all three trials, biosolids demonstrated the ability to contribute in the vegetative growth of crops. It was also found in all test no significant differences (p>0.05) between treatment of bio solid and commercial fertilizer. Biosolids provided nutrients to the crops and even at the end of the trial remained available in the ground soil, contributing to the improvement of the final ground. The best results from these three trials is that the use of bio solids such as those used in this assay would require the addition of potassium, calcium and magnesium in quantities required for each crop.

LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression

logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth

Estimating variable returns to scale production frontiers with alternative stochastic assumptions

Two stochastic production frontier models are formulated within the generalized production function framework popularized by Zellner and Revankar (Rev. Econ. Stud. 36 (1969) 241) and Zellner and Ryu (J. Appl. Econometrics 13 (1998) 101). This framework is convenient for parsimonious modeling of a production function with returns to scale specified as a function of output. Two alternatives for introducing the stochastic inefficiency term and the stochastic error are considered. In the first the errors are added to an equation of the form h(log y, theta) = log f (x, beta) where y denotes output, x is a vector of inputs and (theta, beta) are parameters. In the second the equation h(log y,theta) = log f(x, beta) is solved for log y to yield a solution of the form log y = g[theta, log f(x, beta)] and the errors are added to this equation. The latter alternative is novel, but it is needed to preserve the usual definition of firm efficiency. The two alternative stochastic assumptions are considered in conjunction with two returns to scale functions, making a total of four models that are considered. A Bayesian framework for estimating all four models is described. The techniques are applied to USDA state-level data on agricultural output and four inputs. Posterior distributions for all parameters, for firm efficiencies and for the efficiency rankings of firms are obtained. The sensitivity of the results to the returns to scale specification and to the stochastic specification is examined. (c) 2004 Elsevier B.V. All rights reserved.