Ultrasonic and LIDAR sensors for electronic canopy characterization in vineyards: advances to improve pesticide application methods

Canopy characterization is a key factor to improve pesticide application methods in tree crops and vineyards. Development of quick, easy and efficient methods to determine the fundamental parameters used to characterize canopy structure is thus an important need. In this research the use of ultrasonic and LIDAR sensors have been compared with the traditional manual and destructive canopy measurement procedure. For both methods the values of key parameters such as crop height, crop width, crop volume or leaf area have been compared. Obtained results indicate that an ultrasonic sensor is an appropriate tool to determine the average canopy characteristics, while a LIDAR sensor provides more accuracy and detailed information about the canopy. Good correlations have been obtained between crop volume (CVU) values measured with ultrasonic sensors and leaf area index, LAI (R2 = 0.51). A good correlation has also been obtained between the canopy volume measured with ultrasonic and LIDAR sensors (R2 = 0.52). Laser measurements of crop height (CHL) allow one to accurately predict the canopy volume. The proposed new technologies seems very appropriate as complementary tools to improve the efficiency of pesticide applications, although further improvements are still needed.

Brown algal phlorotannins: Improving and applying chemical methods

Phlorotannins are the least studied group of tannins and are found only in brown algae. Hitherto the roles of phlorotannins, e.g. in plant-herbivore interactions, have been studied by quantifying the total contents of the soluble phlorotannins with a variety of methods. Little attention has been given to either quantitative variation in cell-wall-bound and exuded phlorotannins or to qualitative variation in individual compounds. A quantification procedure was developed to measure the amount of cell-wall-bound phlorotannins. The quantification of soluble phlorotannins was adjusted for both large- and small-scale samples and used to estimate the amounts of exuded phlorotannins using bladder wrack (Fucus vesiculosus) as a model species. In addition, separation of individual soluble phlorotannins to produce a phlorotannin profile from the phenolic crude extract was achieved by high-performance liquid chromatography (HPLC). Along with these methodological studies, attention was focused on the factors in the procedure which generated variation in the yield of phlorotannins. The objective was to enhance the efficiency of the sample preparation procedure. To resolve the problem of rapid oxidation of phlorotannins in HPLC analyses, ascorbic acid was added to the extractant. The widely used colourimetric method was found to produce a variation in the yield that was dependent upon the pH and concentration of the sample. Using these developed, adjusted and modified methods, the phenotypic plasticity of phlorotannins was studied with respect to nutrient availability and herbivory. An increase in nutrients decreased the total amount of soluble phlorotannins but did not affect the cell-wall-bound phlorotannins, the exudation of phlorotannins or the phlorotannin profile achieved with HPLC. The presence of the snail Thedoxus fluviatilis on the thallus induced production of soluble phlorotannins, and grazing by the herbivorous isopod Idotea baltica increased the exudation of phlorotannins. To study whether the among-population variations in phlorotannin contents arise from the genetic divergence or from the plastic response of algae, or both, algae from separate populations were reared in a common garden. Genetic variation among local populations was found in both the phlorotannin profile and the content of total phlorotannins. Phlorotannins were also genetically variable within populations. This suggests that local algal populations have diverged in their contents of phlorotannins, and that they may respond to natural selection and evolve both quantitatively and qualitatively.

Analytical methods for vancomycin determination in biological fluids and in pharmaceuticals

Vancomycin is a glycopeptide antibiotic employed in the treatment of infections caused by certain methicillin-resistant staphylococci. It is indicated also for patients allergic to penicillin or when there is no response to penicillins or cephalosporins. The adequate vancomycin concentration levels in blood serum lies between 5 and 10 mg/L. Higher values are toxic, causing mainly nephrotoxicity and ototoxicity. Various analytical methods are described in the literature: spectrophotometric, immunologic, biologic and chromatographic methods. This paper reviews the main analytical methods for vancomycin determination in biological fluids and in pharmaceutical preparations.

Development and validation of RP-LC and uv spectrophotometric methods to assay bromopride in oral and injectable solutions

A reversed-phase liquid chromatographic (LC) and ultraviolet (UV) spectrophotometric methods were developed and validated for the assay of bromopride in oral and injectable solutions. The methods were validated according to ICH guideline. Both methods were linear in the range between 5-25 μg mL-1 (y = 41837x - 5103.4, r = 0.9996 and y = 0.0284x - 0.0351, r = 1, respectively). The statistical analysis showed no significant difference between the results obtained by the two methods. The proposed methods were found to be simple, rapid, precise, accurate, and sensitive. The LC and UV methods can be used in the routine quantitative analysis of bromopride in oral and injectable solutions.

The Methods of Possible Joint Treatment of Manure and Sewage Sludge in the Leningrad Region

The nutrient load to the Gulf of Finland has started to increase as a result of the strong economic recovery in agriculture and livestock farming in the Leningrad region. Also sludge produced from municipal wastewater treatment plant of the Leningrad region causes the great impact on the environment, but still the main options for its treatment is disposal on the sludge beds or Landfills. The aim of this study was to evaluate the implementation of possible joint treatment methods of manure form livestock and poultry enterprises and sewage sludge produced from municipal wastewater treatment plants in the Leningrad region. The study is based on published data. The most attention was put on the anaerobic digestion and incineration methods. The manure and sewage sludge generation for the whole Leningrad region and energy potential produced from their treatment were estimated. The calculations showed that total amount of sewage sludge generation is 1 348 000 t/a calculated on wet matter and manure generation is 3 445 000 t/a calculated on wet matter. The potential heat release from anaerobic digestion process and incineration process is 4 880 000 GJ/a and 5 950 000 GJ/a, respectively. Furthermore, the work gives the overview of the general Russian and Finnish legislation concerning manure and sewage sludge treatment. In the Gatchina district it was chosen the WWTP and livestock and poultry enterprises for evaluation of the centralized treatment plant implementation based on anaerobic digestion and incineration methods. The electricity and heat power of plant based on biogas combustion process is 4.3 MW and 7.8 MW, respectively. The electricity and heat power of plant based on manure and sewage sludge incineration process is 3.0 MW and 6.1 MW, respectively.

Experiences in using a structured method in finding and defining new innovations: the strategic options approach

Investment decision-making on far-reaching innovation ideas is one of the key challenges practitioners and academics face in the field of innovation management. However, the management practices and theories strongly rely on evaluation systems that do not fit in well with this setting. These systems and practices normally cannot capture the value of future opportunities under high uncertainty because they ignore the firm’s potential for growth and flexibility. Real options theory and options-based methods have been offered as a solution to facilitate decision-making on highly uncertain investment objects. Much of the uncertainty inherent in these investment objects is attributable to unknown future events. In this setting, real options theory and methods have faced some challenges. First, the theory and its applications have largely been limited to market-priced real assets. Second, the options perspective has not proved as useful as anticipated because the tools it offers are perceived to be too complicated for managerial use. Third, there are challenges related to the type of uncertainty existing real options methods can handle: they are primarily limited to parametric uncertainty. Nevertheless, the theory is considered promising in the context of far-reaching and strategically important innovation ideas. The objective of this dissertation is to clarify the potential of options-based methodology in the identification of innovation opportunities. The constructive research approach gives new insights into the development potential of real options theory under non-parametric and closeto- radical uncertainty. The distinction between real options and strategic options is presented as an explanans for the discovered limitations of the theory. The findings offer managers a new means of assessing future innovation ideas based on the frameworks constructed during the course of the study.

The effect of soy dietary supplement and low dose of hormone therapy on main cardiovascular health biomarkers: a randomized controlled trial

PURPOSE: To assess the effects of a soy dietary supplement on the main biomarkers of cardiovascular health in postmenopausal women compared with the effects of low-dose hormone therapy (HT) and placebo.METHODS: Double-blind, randomized and controlled intention-to-treat trial. Sixty healthy postmenopausal women, aged 40-60 years, 4.1 years mean time since menopause were recruited and randomly assigned to 3 groups: a soy dietary supplement group (isoflavone 90mg), a low-dose HT group (estradiol 1 mg plus noretisterone 0.5 mg) and a placebo group. Lipid profile, glucose level, body mass index, blood pressure and abdominal/hip ratio were evaluated in all the participants at baseline and after 16 weeks. Statistical analyses were performed using the χ2 test, Fisher's exact test, Kruskal-Wallis non-parametric test, analysis of variance (ANOVA), paired Student's t-test and Wilcoxon test.RESULTS: After a 16-week intervention period, total cholesterol decreased 11.3% and LDL-cholesterol decreased 18.6% in the HT group, but both did not change in the soy dietary supplement and placebo groups. Values for triglycerides, HDL-cholesterol, glucose level, body mass index, blood pressure and abdominal/hip ratio did not change over time in any of the three groups.CONCLUSION: The use of dietary soy supplement did not show any significant favorable effect on cardiovascular health biomarkers compared with HT. Clinical Trial Registry: The trial is registered at the Brazilian Clinical Trials Registry (Registro Brasileiro de Ensaios Clínicos - ReBEC), number RBR-76mm75.

Demand forecasting process design and methods in medium sized enterprise

The purpose of this thesis was to study the design of demand forecasting processes and management of demand. In literature review were different processes found and forecasting methods and techniques interviewed. Also role of bullwhip effect in supply chain was identified and how to manage it with information sharing operations. In the empirical part of study is at first described current situation and challenges in case company. After that will new way to handle demand introduced with target budget creation and how information sharing with 5 products and a few customers would bring benefits to company. Also the new S&OP process created within this study and organization for it.

Comparison and problems between Traditional and Agile software development methods

In today’s world because of the rapid advancement in the field of technology and business, the requirements are not clear, and they are changing continuously in the development process. Due to those changes in the requirements the software development becomes very difficult. Use of traditional software development methods such as waterfall method is not a good option, as the traditional software development methods are not flexible to requirements and the software can be late and over budget. For developing high quality software that satisfies the customer, the organizations can use software development methods, such as agile methods which are flexible to change requirements at any stage in the development process. The agile methods are iterative and incremental methods that can accelerate the delivery of the initial business values through the continuous planning and feedback, and there is close communication between the customer and developers. The main purpose of the current thesis is to find out the problems in traditional software development and to show how agile methods reduced those problems in software development. The study also focuses the different success factors of agile methods, the success rate of agile projects and comparison between traditional and agile software development.

Comparison of methods by TLC and HPTLC for determination of aflatoxin M1 in milk and B1 in eggs

Milk and egg matrixes were assayed for aflatoxin M1 (AFM1) and B1 (AFB1) respectively, by AOAC official and modified methods with detection and quantification by thin layer chromatography (TLC) and high performance thin layer chromatography (HPTLC). The modified methods: Blanc followed by Romer, showed to be most appropriate for AFM1 analysis in milk. Both methods reduced emulsion formation, produced cleaner extracts, no streaking spots, precision and accuracy improved, especially when quantification was performed by HPTLC. The use of ternary mixture in the Blanc Method was advantageous as the solvent could extract AFM1 directly from the first stage (extraction), leaving other compounds in the binary mixture layer, avoiding emulsion formation, thus reducing toxin loss. The relative standard deviation (RSD%) values were low, 16 and 7% when TLC and HPTLC were used, with a mean recovery of 94 and 97%, respectively. As far as egg matrix and final extract are concerned, both methods evaluated for AFB1 need further studies. Although that matrix leads to emulsion with consequent loss of toxin, the Romer modified presented a reasonable clean extract (mean recovery of 92 and 96% for TLC and HPTLC, respectively). Most of the methods studied did not performed as expected mainly due to the matrixes high content of triglicerides (rich on saturated fatty acids), cholesterol, carotene and proteins. Although nowadays most methodology for AFM1 is based on HPLC, TLC determination (Blanc and Romer modified) for AFM1 and AFB1 is particularly recommended to those, inexperienced in food and feed mycotoxins analysis and especially who cannot afford to purchase sophisticated (HPLC,HPTLC) instrumentation.

The influence of extraction methods on composition and antioxidant properties of rice bran oil

AbstractThe current study was employed to assess the influence of the different extraction methods on total tocols, γ-oryzanol content, and antioxidant properties of Chiang Mai Black rice, Mali Red rice, and Suphanburi-1 Brown rice bran oil. Rice bran oil (RBO) was extracted by Hexane, Hot pressed, Cold pressed, and Supercritical Fluid Extraction (SFe) methods. High yield of RBO was extracted by hexane and SFe methods. Total and subgroups of tocols, and γ-oryzanol content were determined by HPLC. The hexane extracted sample accounts for high content of γ-oryzanol and tocols. Besides, all of RBO extracts contain a significantly high amount of γ-tocotrienol. In vitro antioxidant assay results indicated that superior quality of oil was recovered by hexane extraction. The temperature in the extraction process also affects the value of the oil. Superior quality of oil was recovered by hexane extraction, in terms of phytochemical contents and antioxidant properties compared to other tested extraction methods. Further, thorough study of factors compromising the quality and quantity of RBO recovery is required for the development of enhanced functional foods and other related products.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Simulation-Based Finite-Sample Tests for Heteroskedasticity and ARCH Effects.

A wide range of tests for heteroskedasticity have been proposed in the econometric and statistics literature. Although a few exact homoskedasticity tests are available, the commonly employed procedures are quite generally based on asymptotic approximations which may not provide good size control in finite samples. There has been a number of recent studies that seek to improve the reliability of common heteroskedasticity tests using Edgeworth, Bartlett, jackknife and bootstrap methods. Yet the latter remain approximate. In this paper, we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts. We study procedures based on the standard test statistics [e.g., the Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White and Szroeter criteria] as well as tests for autoregressive conditional heteroskedasticity (ARCH-type models). We also suggest several extensions of the existing procedures (sup-type of combined test statistics) to allow for unknown breakpoints in the error variance. We exploit the technique of Monte Carlo tests to obtain provably exact p-values, for both the standard and the new tests suggested. We show that the MC test procedure conveniently solves the intractable null distribution problem, in particular those raised by the sup-type and combined test statistics as well as (when relevant) unidentified nuisance parameter problems under the null hypothesis. The method proposed works in exactly the same way with both Gaussian and non-Gaussian disturbance distributions [such as heavy-tailed or stable distributions]. The performance of the procedures is examined by simulation. The Monte Carlo experiments conducted focus on : (1) ARCH, GARCH, and ARCH-in-mean alternatives; (2) the case where the variance increases monotonically with : (i) one exogenous variable, and (ii) the mean of the dependent variable; (3) grouped heteroskedasticity; (4) breaks in variance at unknown points. We find that the proposed tests achieve perfect size control and have good power.

Finite-Sample Inference Methods for Simultaneous Equations and Models with Unobserved and Generated Regressors

We propose finite sample tests and confidence sets for models with unobserved and generated regressors as well as various models estimated by instrumental variables methods. The validity of the procedures is unaffected by the presence of identification problems or \"weak instruments\", so no detection of such problems is required. We study two distinct approaches for various models considered by Pagan (1984). The first one is an instrument substitution method which generalizes an approach proposed by Anderson and Rubin (1949) and Fuller (1987) for different (although related) problems, while the second one is based on splitting the sample. The instrument substitution method uses the instruments directly, instead of generated regressors, in order to test hypotheses about the \"structural parameters\" of interest and build confidence sets. The second approach relies on \"generated regressors\", which allows a gain in degrees of freedom, and a sample split technique. For inference about general possibly nonlinear transformations of model parameters, projection techniques are proposed. A distributional theory is obtained under the assumptions of Gaussian errors and strictly exogenous regressors. We show that the various tests and confidence sets proposed are (locally) \"asymptotically valid\" under much weaker assumptions. The properties of the tests proposed are examined in simulation experiments. In general, they outperform the usual asymptotic inference methods in terms of both reliability and power. Finally, the techniques suggested are applied to a model of Tobin’s q and to a model of academic performance.