963 resultados para Performance Reference Compounds
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Purpose: To investigate the spectrum-effect relationships between high performance liquid chromatography (HPLC) fingerprints and duodenum contractility of charred areca nut (CAN) on rats. Methods: An HPLC method was used to establish the fingerprint of charred areca nut (CAN). The promoting effect on contractility of intestinal smooth was carried out to evaluate the duodenum contractility of CAN in vitro. In addition, the spectrum-effect relationships between HPLC fingerprints and bioactivities of CAN were investigated using multiple linear regression analysis (backward method). Results: Fourteen common peaks were detected and peak 3 (5-Hydroxymethyl-2-furfural, 5-HMF) was selected as the reference peak to calculate the relative retention time of 13 other common peaks. In addition, the equation of spectrum-effect relationships {Y = 3.818 - 1.126X1 + 0.817X2 - 0.045X4 - 0.504X5 + 0.728X6 - 0.056X8 + 1.122X9 - 0.247X13 - 0.978X14 (p < 0.05, R2 = 1)} was established in the present study by the multiple linear regression analysis (backward method). According to the equation, the absolute value of the coefficient before X1, X2, X4, X5, X6, X8, X9, X13, X14 was the coefficient between the component and the parameter. Conclusion: The model presented in this study successfully unraveled the spectrum-effect relationship of CAN, which provides a promising strategy for screening effective constituents of areca nut.
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Vanadium compounds mimic most of the metabolic effects of insulin, suggesting that it might be useful to improve utilization of dietary carbohydrate. This work evaluated the effect of dietary ammonium metavanadate (H(4)NO(3)V) on the growth performance and energy metabolism of pacu, an omnivorous South America characin. Two hundred and eighty-eight fish were distributed into four blocks according to the body weight (21.8 +/- 1.7, 28.5 +/- 2.0, 28.4 +/- 1.9, 35.7 +/- 1.9 g), stocked in 24 plastic tanks and fed twice daily with isonitrogenous and isoenergetic diets containing six levels of H(4)NO(3)V (0, 10, 50, 100, 300 and 1000 mg kg(-1)) for 60 days. Increasing levels of dietary ammonium metavanadate did not improve growth (P > 0.05), and the highest level of inclusion (1000 mg kg(-1)) reduced performance (P < 0.05). Blood glucose levels decreased (P < 0.05) in fish fed 300 and 1000 mg kg(-1) H(4)NO(3)V, but no differences were observed in other blood metabolites. A slight increase in muscle lipid content was observed in fish fed a diet containing 300 mg kg(-1) H(4)NO(3)V. Based on the results of this study, there is no benefit in supplementing pacu diets with metavanadate.
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Purpose: To develop a high-performance liquid chromatography (HPLC) fingerprint method for the quality control and origin discrimination of Gastrodiae rhizoma . Methods: Twelve batches of G. rhizoma collected from Sichuan, Guizhou and Shanxi provinces in china were used to establish the fingerprint. The chromatographic peak (gastrodin) was taken as the reference peak, and all sample separation was performed on a Agilent C18 (250 mm×4.6 mmx5 μm) column with a column temperature of 25 °C. The mobile phase was acetonitrile/0.8 % phosphate water solution (in a gradient elution mode) and the flow rate of 1 mL/min. The detection wavelength was 270 nm. The method was validated as per the guidelines of Chinese Pharmacopoeia. Results: The chromatograms of the samples showed 11 common peaks, of which no. 4 was identified as that of Gastrodin. Data for the samples were analyzed statistically using similarity analysis and hierarchical cluster analysis (HCA). The similarity index between reference chromatogram and samples’ chromatograms were all > 0.80. The similarity index of G. rhizoma from Guizhou, Shanxi and Sichuan is evident as follows: 0.854 - 0.885, 0.915 - 0.930 and 0.820 - 0.848, respectively. The samples could be divided into three clusters at a rescaled distance of 7.5: S1 - S4 as cluster 1; S5 - S8 cluster 2, and others grouped into cluster 3. Conclusion: The findings indicate that HPLC fingerprinting technology is appropriate for quality control and origin discrimination of G. rhizoma.
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The dual problems of sustaining the fast growth of human society and preserving the environment for future generations urge us to shift our focus from exploiting fossil oils to researching and developing more affordable, reliable and clean energy sources. Human beings had a long history that depended on meeting our energy demands with plant biomass, and the modern biorefinery technologies realize the effective conversion of biomass to production of transportation fuels, bulk and fine chemicals so to alleviate our reliance on fossil fuel resources of declining supply. With the aim of replacing as much non-renewable carbon from fossil oils with renewable carbon from biomass as possible, innovative R&D activities must strive to enhance the current biorefinery process and secure our energy future. Much of my Ph.D. research effort is centered on the study of electrocatalytic conversion of biomass-derived compounds to produce value-added chemicals, biofuels and electrical energy on model electrocatalysts in AEM/PEM-based continuous flow electrolysis cell and fuel cell reactors. High electricity generation performance was obtained when glycerol or crude glycerol was employed as fuels in AEMFCs. The study on selective electrocatalytic oxidation of glycerol shows an electrode potential-regulated product distribution where tartronate and mesoxalate can be selectively produced with electrode potential switch. This finding then led to the development of AEMFCs with selective production of valuable tartronate or mesoxalate with high selectivity and yield and cogeneration of electricity. Reaction mechanisms of electrocatalytic oxidation of ethylene glycol and 1,2-propanediol were further elucidated by means of an on-line sample collection technique and DFT modeling. Besides electro-oxidation of biorenewable alcohols to chemicals and electricity, electrocatalytic reduction of keto acids (e.g. levulinic acid) was also studied for upgrading biomass-based feedstock to biofuels while achieving renewable electricity storage. Meanwhile, ORR that is often coupled in AEMFCs on the cathode was investigated on non-PGM electrocatalyst with comparable activity to commercial Pt/C. The electro-biorefinery process could be coupled with traditional biorefinery operation and will play a significant role in our energy and chemical landscape.
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With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.
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The fact that most of the large scale solar PV plants are built in arid and semi-arid areas where land availability and solar radiation is high, it is expected the performance of the PV plants in such locations will be affected significantly due to high cell temperature as well as due to soiling. Therefore, it is essential to study how the different PV module technologies will perform in such geographical locations to ensure a consistent and reliable power delivery over the lifetime of the PV power plants. As soiling is strongly dependent on the climatic conditions of a particular location a test station, consisted of about 24 PV modules and a well-equipped weather station, was built within the fences of Scatec’s 75 MW Kalkbult solar PV plant in South Africa. This study was performed to a better understand the effect of soiling by comparing the relative power generation by the cleaned modules to the un-cleaned modules. Such knowledge can enable more quantitative evaluations of the cleaning strategies that are going to be implemented in bigger solar PV power plants. The data collected and recorded from the test station has been analyzed at IFE, Norway using a MatLab script written for this thesis project. This thesis work has been done at IFE, Norway in collaboration with Stellenbosch University in South Africa and Scatec Solar a Norwegian independent power producer company. Generally for the polycrystalline modules it is found that the average temperature corrected efficiency during the period of the experiment has been 15.00±0.08 % and for the thin film-CdTe with ARC is 11.52% and for the thin film without ARC is about 11.13% with standard uncertainty of ±0.01 %. Besides, by comparing the initial relative average efficiency of the polycrystalline-Si modules when all the modules have been cleaned for the first time and the final relative efficiency; after the last cleaning schedule which is when all the reference modules E, F, G, and H have been cleaned for the last time it is found that poly3 performs 2 % and 3 % better than poly1 and poly16 respectively, poly13 performs 1 % better than poly15 as well as poly5 and poly12 performs 1 % and 2 % better than poly10 respectively. Besides, poly5 and poly12 performs a 9 % and 11 % better than poly7. Furthermore, there is no change in performance between poly6 and poly9 as well as poly4 and poly15. However, the increase in performance of poly3 to poly1, poly13 to poly15 as well as poly5 and poly12 to poly10 is insignificant. In addition, it is found that TF22 perform 7% better than the reference un-cleaned module TF24 and similarly; TF21 performs 7% higher than TF23. Furthermore, modules with ARC glass (TF17, TF18, TF19, and TF20) shows that cleaning the modules with only distilled water (TF19) or dry-cleaned after cleaned with distilled water(TF20) decreases the performance of the modules by 5 % and 4 % comparing to its respective reference uncleanedmodules TF17 and TF18 respectively.
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In this paper, dynamic simulation was used to compare the energy performance of three innovativeHVAC systems: (A) mechanical ventilation with heat recovery (MVHR) and micro heat pump, (B) exhaustventilation with exhaust air-to-water heat pump and ventilation radiators, and (C) exhaust ventilationwith air-to-water heat pump and ventilation radiators, to a reference system: (D) exhaust ventilation withair-to-water heat pump and panel radiators. System A was modelled in MATLAB Simulink and systems Band C in TRNSYS 17. The reference system was modelled in both tools, for comparison between the two.All systems were tested with a model of a renovated single family house for varying U-values, climates,infiltration and ventilation rates.It was found that A was the best system for lower heating demand, while for higher heating demandsystem B would be preferable. System C was better than the reference system, but not as good as A or B.The difference in energy consumption of the reference system was less than 2 kWh/(m2a) betweenSimulink and TRNSYS. This could be explained by the different ways of handling solar gains, but also bythe fact that the TRNSYS systems supplied slightly more than the ideal heating demand.
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Our aim was to determine the normative reference values of cardiorespiratory fitness (CRF) and to establish the proportion of subjects with low CRF suggestive of future cardio-metabolic risk.
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El propósito del presente estudio era generar los valores normativos de salto largo para niños de 9-17.9 años, e investigar las diferencias de sexo y grupo de edad
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Digital soil mapping is an alternative for the recognition of soil classes in areas where pedological surveys are not available. The main aim of this study was to obtain a digital soil map using artificial neural networks (ANN) and environmental variables that express soillandscape relationships. This study was carried out in an area of 11,072 ha located in the Barra Bonita municipality, state of São Paulo, Brazil. A soil survey was obtained from a reference area of approximately 500 ha located in the center of the area studied. With the mapping units identified together with the environmental variables elevation, slope, slope plan, slope profile, convergence index, geology and geomorphic surfaces, a supervised classification by ANN was implemented. The neural network simulator used was the Java NNS with the learning algorithm "back propagation." Reference points were collected for evaluating the performance of the digital map produced. The occurrence of soils in the landscape obtained in the reference area was observed in the following digital classification: medium-textured soils at the highest positions of the landscape, originating from sandstone, and clayey loam soils in the end thirds of the hillsides due to the greater presence of basalt. The variables elevation and slope were the most important factors for discriminating soil class through the ANN. An accuracy level of 82% between the reference points and the digital classification was observed. The methodology proposed allowed for a preliminary soil classification of an area not previously mapped using mapping units obtained in a reference area
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In chapter one, the autoxidation kinetics of natural oil substrates, including, triglyceric sunflower oil, olive oil, terpenic squalene, and p-cymene were calibrated through differential oximetry methods. Calibration allows their use as reference oxidizable substrates for further studies, e.g. for quantitative testing of antioxidants under biomimetic settings. Several essential oils samples, of different botanical species or different productions of same species were studied for their antioxidant activity in inhibited autoxidation kinetics. Their antioxidant activities were matched with their composition analyzed by GC-MS. In chapter two, the molecular mechanism of the synergy between the common phenolic antioxidants such as tocopherol and catechols with widespread essential component gamma-terpinene was studied through lipid oxidation kinetics. Wherein, gamma-terpinene was able to disclose the key intermediacy HOO·, which acted as a reducing agent regenerating the phenolic antioxidant. This counterintuitive role of HOO· radicals was further investigated in detail and allowed to rationalize for the first time the purported antioxidant behavior of PDA melanin nanoparticles. It will also open to a deeper understanding of the redox biology of quinones. Regarding melanin, its role is broadly important in living organisms and its control, including its inhibition, is of great importance with several relevant applications ranging from food preservation to control of human skin pigmentation. In chapter three, an oximetry method combined with the traditional UV-Vis spectroscopy was developed to study the tyrosinase inhibition kinetics, which allowed identifying Glabridin (from G. glabra, L.), as one of the most effective natural tyrosinase inhibitors.
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This work has been conducted in order to determine the solubility and diffusion coefficients of different aromatic substances in two different grades of polylactic acid (PLA), Amorphous (PDLLA) and Crystalline (PLLA); in particular the focus is on the following terpenes: Linalool, α-Pinene, β-Citronellol and L-Linalool. Moreover, further analyses have been carried out with the aim to verify if the use of neat crystalline PLA, (PLLA), a chiral substrate, may lead to an enantioenrichment of absorbed species in order to use it as membrane in enantioselective processes. The other possible applications of PLA, which has aroused interest in carry out the above-mentioned work, concerns its use in food packaging. Therefore, it is interesting and also very important, to evaluate the barrier properties of PLA, focusing in particular on the transport and absorption of terpenes, by the packaging and, hence, by the PLA. PLA films/slabs of one-millimeter thickness and with square shape, were prepared through the Injection Molding process. On the resulting PLA films heat pretreatment processes of normalizing were then performed to enhance the properties of the material. In order to evaluate solubility and diffusion coefficient of the different penetrating species, the absorption kinetics of various terpenes, in the two different types of PLA, were determined by gravimetric methods. Subsequently, the absorbed liquid was extracted with methanol (MeOH), non- solvent for PLA, and the extract analyzed by the use of High Performance Liquid Chromatography (HPLC), in order to evaluate its possible enantiomeric excess. Moreover, PLA films used were subjected to differential scanning calorimetry (DSC) which allowed to measure the glass transition temperature (Tg) and to determine the degree of crystallinity of the polymer (Xc).
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Rail transportation has significant importance in the future world. This importance is tightly bounded to accessible, sustainable, efficient and safe railway systems. Precise positioning in railway applications is essential for increasing railway traffic, train-track control, collision avoidance, train management and autonomous train driving. Hence, precise train positioning is a safety-critical application. Nowadays, positioning in railway applications highly depends on a cellular-based system called GSM-R, a railway-specific version of Global System for Mobile Communications (GSM). However, GSM-R is a relatively outdated technology and does not provide enough capacity and precision demanded by future railway networks. One option for positioning is mounting Global Navigation Satellite System (GNSS) receivers on trains as a low-cost solution. Nevertheless, GNSS can not provide continuous service due to signal interruption by harsh environments, tunnels etc. Another option is exploiting cellular-based positioning methods. The most recent cellular technology, 5G, provides high network capacity, low latency, high accuracy and high availability suitable for train positioning. In this thesis, an approach to 5G-based positioning for railway systems is discussed and simulated. Observed Time Difference of Arrival (OTDOA) method and 5G Positioning Reference Signal (PRS) are used. Simulations run using MATLAB, based on existing code developed for 5G positioning by extending it for Non Line of Sight (NLOS) link detection and base station exclusion algorithms. Performance analysis for different configurations is completed. Results show that efficient NLOS detection improves positioning accuracy and implementing a base station exclusion algorithm helps for further increase.
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Artificial Intelligence (AI) is gaining ever more ground in every sphere of human life, to the point that it is now even used to pass sentences in courts. The use of AI in the field of Law is however deemed quite controversial, as it could provide more objectivity yet entail an abuse of power as well, given that bias in algorithms behind AI may cause lack of accuracy. As a product of AI, machine translation is being increasingly used in the field of Law too in order to translate laws, judgements, contracts, etc. between different languages and different legal systems. In the legal setting of Company Law, accuracy of the content and suitability of terminology play a crucial role within a translation task, as any addition or omission of content or mistranslation of terms could entail legal consequences for companies. The purpose of the present study is to first assess which neural machine translation system between DeepL and ModernMT produces a more suitable translation from Italian into German of the atto costitutivo of an Italian s.r.l. in terms of accuracy of the content and correctness of terminology, and then to assess which translation proves to be closer to a human reference translation. In order to achieve the above-mentioned aims, two human and automatic evaluations are carried out based on the MQM taxonomy and the BLEU metric. Results of both evaluations show an overall better performance delivered by ModernMT in terms of content accuracy, suitability of terminology, and closeness to a human translation. As emerged from the MQM-based evaluation, its accuracy and terminology errors account for just 8.43% (as opposed to DeepL’s 9.22%), while it obtains an overall BLEU score of 29.14 (against DeepL’s 27.02). The overall performances however show that machines still face barriers in overcoming semantic complexity, tackling polysemy, and choosing domain-specific terminology, which suggests that the discrepancy with human translation may still be remarkable.
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The current dominance of African runners in long-distance running is an intriguing phenomenon that highlights the close relationship between genetics and physical performance. Many factors in the interesting interaction between genotype and phenotype (eg, high cardiorespiratory fitness, higher hemoglobin concentration, good metabolic efficiency, muscle fiber composition, enzyme profile, diet, altitude training, and psychological aspects) have been proposed in the attempt to explain the extraordinary success of these runners. Increasing evidence shows that genetics may be a determining factor in physical and athletic performance. But, could this also be true for African long-distance runners? Based on this question, this brief review proposed the role of genetic factors (mitochondrial deoxyribonucleic acid, the Y chromosome, and the angiotensin-converting enzyme and the alpha-actinin-3 genes) in the amazing athletic performance observed in African runners, especially the Kenyans and Ethiopians, despite their environmental constraints.