Second-order Polynomial Relationship Research Articles

Quantification of Human Photoreceptor-Retinal Pigment Epithelium Macular Topography with Adaptive Optics-Optical Coherence Tomography.

Photoreceptors (PRs) and retinal pigment epithelial (RPE) cells form a functional unit called the PR-RPE complex. The PR-RPE complex plays a critical role in maintaining retinal homeostasis and function, and the quantification of its structure and topographical arrangement across the macula are important for understanding the etiology, mechanisms, and progression of many retinal diseases. However, the three-dimensional cellular morphology of the PR-RPE complex in living human eyes has not been completely described due to limitations in imaging techniques. We used the cellular resolution and depth-sectioning capabilities of a custom, high-speed Fourier domain mode-locked laser-based adaptive optics-optical coherence tomography (FDML-AO-OCT) platform to characterize human PR-RPE complex topography across the temporal macula from eleven healthy volunteers. With the aid of a deep learning algorithm, key metrics were extracted from the PR-RPE complex of averaged AO-OCT volumes including PR and RPE cell density, PR outer segment length (OSL), and PR/RPE ratio. We found a tight grouping among our cohort for PR density, with a mean (±SD) value of 53,329 (±8106) cells/mm2 at 1° decreasing to 8669 (±737) cells/mm2 at 12°. We observed a power function relationship between eccentricity and both PR density and PR/RPE ratio. We found similar variability in our RPE density measures, with a mean value of 7335 (±681) cells/mm2 at 1° decreasing to 5547 (±356) cells/mm2 at 12°, exhibiting a linear relationship with a negative slope of -123 cells/mm2 per degree. OSL monotonically decreased from 33.3 (±2.4) µm at 1° to 18.0 (±1.8) µm at 12°, following a second-order polynomial relationship. PR/RPE ratio decreased from 7.3 (±0.9) µm at 1° to 1.5 (±0.1) µm at 12°. The normative data from this investigation will help lay a foundation for future studies of retinal pathology.

Sound amplitude of discrete bubbles entrained by an impacting water stream.

Experiments were undertaken to develop a relationship between bubble size and acoustic-emission amplitude for a vertical stream of water impacting a water pool. A particular focus is the formation of the discrete bubbles. Although the relationship between bubble diameter and the natural frequency of sound emissions has been established through Minnaert's work, a comprehensive investigation into the amplitude of sound emissions is missing. Air bubbles were generated from the impact of falling-water streams of varying diameters on an underlying water pool and their acoustic emissions were recorded using a nearby hydrophone. Sound amplitude was found to increase monotonically with bubble size. A second-order polynomial relationship between logarithmic acoustic sound pressure level (L) and bubble diameter (Db) was found, L=-0.0401Db2+1.5781Db+110.7225 within the ±3 dB margin of error. The relationship between linear sound pressure level (P) and bubble diameter (Db) is expressed by the equation P=0.0059Db2+0.0505Db+0.3591, within the ±3 dB margin of error. Results demonstrate that larger bubbles (D > 4 mm) exhibit noise emissions similar to bubbles produced by other mechanisms, such as the underwater nozzle, while smaller diameters tend to produce higher noise levels compared to the same mechanism.

Dietary supplementation with succinic acid improves growth performance and flesh quality of adult Nile tilapia (Oreochromis niloticus) fed a high-carbohydrate diet

To evaluate the effects of dietary supplementation with succinic acid on growth performance, flesh quality, glucose, and lipid metabolism of Nile tilapia (Oreochromis niloticus) fed a high-carbohydrate diet (HCD), five iso-nitrogenous and iso-lipidic diets were prepared as follows: HCD (control group) consisting of 55% corn starch and HCD supplemented with 0.5%, 1.0%, 2.0%, and 4.0% succinic acid, respectively. Tilapia with an initial body weight of 204.90 ± 1.23 g randomly assigned to 15 tanks with 3 replicates per group and 10 fish per tank fed for 8 weeks. Increasing dietary succinic acid supplementation resulted in significant second-order polynomial relationship in the weight gain rate (WGR), specific growth rate (SGR), feed conversion ratio (FCR), protein efficiency rate (PER), viscerosomatic index, condition factor, and contents of muscular crude lipid and glycogen (P < 0.05). The hepatosomatic index, mesenteric fat index, liver glycogen content and crude lipid contents of the whole-body and liver demonstrated significantly linear and second-order polynomial relationship (P < 0.05). Quadratic curve model analysis based on WGR, SGR, PER, and FCR demonstrated that optimal supplementation with succinic acid in the HCD of Nile tilapia ranged from 1.83% to 2.43%. Fish fed with 1.0% succinic acid had higher muscular hardness, increased the contents of alkali-soluble hydroxyproline in collagen, docosahexaenoic acid (DHA) and n-3 polyunsaturated fatty acid (n-3PUFA) in muscle, and lower total fatty acid content in muscle (P < 0.05) compared with the control group. Compared to the control group, dietary supplementation with 1.0% succinic acid significantly increased the contents of total bounding amino acid (arginine, histidine, isoleucine, lysine, methionine, alanine, proline), total flavor amino acid (free aspartic acid), the catalase (CAT) activity and total antioxidant capacity, and the mRNA relative expression levels of CAT, superoxide dismutase (SOD), and nuclearfactor erythroidderived 2-like 2 (Nrf2) in muscle (P < 0.05). Furthermore, succinic acid supplementation significantly up-regulated mRNA relative expression levels of glycolysis genes (hexokinase 2 [HK2], phosphofructokinase, muscle-A [PFKMA], and phosphofructokinase, muscle-B [PFKMB]), a key glycogen synthesis gene (glycogen synthase [GYS]), and lipid catabolism genes (carnitine palmitoyltransferase-1B [CPT1B], hormone sensitive lipase [HSL], and lipoprotein lipase [LPL]), while down-regulating the mRNA relative expression level of fatty acid synthase (FASN) in muscle (P < 0.05). In conclusion, dietary supplementation with 1.83% to 2.43% succinic acid improved muscle quality by increasing muscle antioxidant capacity and hardness, changing muscle amino acid and fatty acid composition, and regulating muscle glucose and lipid metabolism.

Modeling the relationship between postharvest storage conditions and grapefruit quality

The postharvest loss in quality of grapefruit during storage can be quantified by determining the change of the quality traits of grapefruit, including total soluble solids (TSS), titratable acidity (TA), TSS/TA, weight loss (WL), and the development of decay (DC) and chilling injury (CI). The objective of this study was, therefore, to develop models that encompass the relationship between both storage conditions and duration and the quality traits of grapefruit to predict the loss of grapefruit quality during storage. The models of TSS, TA and TSS/TA were developed with experimental data collected during the 2007–08 and 2008-09 growing seasons that were obtained from the literature. The models for WL, DC, and CI were developed with experimental data collected in Florida during the 2004–05 and 2005-06 growing seasons. The WL, DC and CI models were applied to determine storage life. The results indicated that there was a second-order polynomial relationship between storage duration and TSS and linear relationships between storage duration and TA and TSS/TA. A longer storage duration resulted in a higher TSS, a lower TA and a higher TSS/TA. There were linear relationships between storage duration and WL, thermal time above a threshold temperature of 0 °C and DC and thermal time below 10 °C and CI, with higher WL, DC and CI resulting from longer storage duration and larger number of thermal times. Model performance for simulating TSS, TA, TSS/TA for storage temperature between 2 °C and 11 °C was good. There is good performance for simulating WL for storage temperature between 4 °C and 12 °C, DC for storage temperature of 21.1 °C, and CI for storage temperature of 4.4 °C. Following model development, it was applied to determine the optimum storage life. Optimum storage condition was a storage temperature of 7.6 °C for approximately 20 d, resulting in less than 5 % of the stored fruits lost due to unacceptable quality based on predictions for WL, DC and CI.

Study of the efficiency of machine learning algorithms based on data of various rocks

Background: Absolute permeability plays an important role in studying the fluids flow in porous media during the development of oil and gas reservoirs, the injection of CO2 into reservoirs for storage, the monitoring of pollutants migration in underground aquifers, and the modeling of catalytic systems. Therefore, an accurate and fast evaluation of its values is an important task.&#x0D; Aim: The purpose of this article is to study the applicability of machine learning methods for predicting the absolute permeability of carbonate samples, as well as ways to improve the prediction of permeability.&#x0D; Materials and methods: The input data is 408 small volumes extracted from four cylindrical carbonate samples composed almost entirely of calcite. Input data includes total and connected porosity, specific surface area, radii of all and only connected pores, coordination number, throat radius and length, tortuosity, and absolute permeability. Permeability prediction is carried out using regression machine learning methods such as random forest, extremely random trees and extended gradient boosting. Parameters (data) of small volumes were determined using pore-scale modeling of water flow in their pore space applying a specialized Avizo software.&#x0D; Results: Data of small volumes extracted from fractured and non-fractured samples were analyzed, and the results showed that there are good relationships between many parameters of small volumes. For example, the connected and total porosity have a second-order polynomial relationship with a high correlation coefficient. Using the above-mentioned regression machine learning methods, absolute permeability values were predicted when input data divided into training and testing data in a ratio of 80/20 and 70/30.&#x0D; Conclusion: Using the logarithm of permeability instead of permeability itself and considering fractured and non-fractured samples separately, can increase the accuracy of absolute permeability prediction using the above-mentioned machine learning methods up to 90%. The extremely random trees method is the most accurate among the three machine learning methods considered for our task.

Impact of Climate Change on the Number of Frost-free Winter Days in Prairies and Eastern Provinces of Canada

Highlights In northern region of Prairies and eastern provinces of Canada, the change in Frost-Free Days (FFDs) for the period of 1938–2022 is nearly negligible. In the stations located at the south of Ontario (called southern stations here), a maximum increase of 4.4 to 5.8 in FFDs per month was noted during the study period at different locations. The rates of change in FFDs per unit °C of the monthly mean of the daily minimum temperature (MMDMT) vary from a minimum of 0.001 to a maximum value of 2.92 days at the selected stations. Abstract. Although a considerable number of studies related to the impact of climate change on temperature-related variables have been conducted, studies exploring the changes in indices of daily winter temperatures, such as variation in the number of frost-free days (FFDs), for the winter season or for each month of the season are very few. The main objective of this study was to explore temporal trends in FFDs for each month of the winter season as well as examine the relationship between FFDs and the monthly mean of daily minimum temperature (MMDMT) at the selected stations in the central and eastern provinces of Canada. Daily minimum temperature data between 1938 and 2022 from 11 meteorological stations situated along a wide range of latitudes across the Prairies and eastern provinces of Canada has been analyzed. An exceedance probability model is developed to predict the FFDs for each winter month. The analysis leads to the conclusion that the number of FFDs per month exhibited an exponential relationship with the MMDMT for November, April, and the entire winter season, while the relationship for December through March followed a second-order polynomial curve. The results further highlight that the rate of change in FFDs per month varies across stations for each month. Notably, while the change is minimal for stations such as Kuujjuaq, Kuujjuarapik, and The Pas, it has notably increased by 23.1, 17.9, and 14.2 days at the Toronto, Windsor, and London stations, respectively. Additionally, it was observed that the rates of change in FFDs per unit increase in MMDMT (in °C) are consistently positive for all months and selected stations. The rate of change varies, ranging from a minimum of 0.001 at The Pas in December to a maximum value of 2.92 days at Montreal in April.Moreover, coefficient of determination (R2) values of more than 0.96 were observed for both exponential and second-order polynomial relationships in the months of November and April, as well as for the entire winter. A rising trend in MMDMT values, along with a decreasing trend in the MMDMT standard deviation values, was observed across all stations from 1938 to 2022. This trend indicates a more pronounced and predictable rise in temperature over time. Overall, the number of FFDs is increasing for all winter months, albeit with a few exceptions, at central and eastern stations in Canada. These warming trends during the winter months contribute to the expansion in the number of FFDs, which is expected to significantly impact hydrological, agricultural, and environmental processes within the study region. Keywords: Climate change, Exceedance probability model, Frost-free days, Monthly mean of daily minimum temperature.

Study on the heat recovery behavior of horizontal well systems in the Qiabuqia geothermal area of the Gonghe Basin, China

Geothermal energy, as a highly regarded renewable energy source, holds vast potential for widespread applications. However, the methods of geothermal energy extraction need to be optimized and improved according to specific geological conditions. This study aims to provide a multi-level horizontal branch well heat recovery system for the Qiabuqia geothermal field in the Gonghe Basin. To begin, this study systematically investigated the influence of various engineering parameters on production temperature and establishes mathematical models to depict the relationships among these parameters. Subsequently, we unveiled the precise numerical correlation between well length and the limit injection rate, utilizing multiple production indexes to comprehensively characterize the practical production characteristics and effectiveness of the multi-level heat recovery system. Finally, a comprehensive economic evaluation of the system was conducted. The research findings indicate that there exists a linear relationship between production temperature and injection temperature, while a second-order polynomial relationship is observed between production temperature and injection rate, wellbore size, and well length. In single-well heat recovery systems, the ratio of well length to the limit injection rate is 4000, whereas in multi-level branch well system, the limit injection rate is 88 % of that in single-well systems. Furthermore, branch wells located farther from the injection end exhibit greater heat recovery capacity but relatively higher production costs. Nonetheless, overall, the production cost for 1000-m-long branch wells can be reduced to around $0.05 $/kWh, demonstrating significant economic feasibility. These research findings provide momentum for the sustainable development and utilization of hot dry rock resources, simultaneously offering more precise guidance for the design and operation of hot dry rock power generation projects.

Modeling of Grapefruit External Color as Affected by Drought Stress

Grapefruit are well-adapted to arid and warm climatic conditions, but well-irrigated trees usually produce better-quality fruits. Because water is a major component of the fruits, there is a strong relationship between drought stress and fruits quality traits such as fruits size, external fruits color, and juice quality. The object of this study was to develop a computer model to predict postharvest external grapefruit color as a function of drought stress. During model development, drought stress was quantified using a concise water balance model based on crop evapotranspiration, precipitation, and irrigation. Data collected from Murcia, Spain, during the 2007 and 2008 growing seasons were used for model development, and the model was optimized by comparing model predictions and observations for each growing season. The root mean square error and Nash and Sutcliffe coefficient of efficiency (NSE) were used to evaluate model performance. Then, the model was evaluated with independent data collected from Florida during the 2005–06 growing season. A second-order polynomial relationship was found between external fruits color and drought stress, with less drought stress resulting in better external fruits color. Model optimization revealed good model performance for predicting external fruits color in Murcia, with NSE values of 0.975 and 0.979 for the 2007 and 2008 growing seasons, respectively. Model evaluation with the data from Florida showed that model predictions were reliable, with a NSE value of 0.984. A robust model to predict external grapefruit color as affected by drought stress was developed during the present study and could be potentially applied to supply information for suitable irrigation management of various grapefruit cultivars grown under different climatic conditions. Model performance could be confirmed by future research with data collection during further multiple seasons for different cultivars and a range of climatic conditions.

Evaluation of three novel soil bacterial strains for efficient biodegradation of persistent boscalid fungicide: Kinetics and identification of microbial biodegradation intermediates

Boscalid, a new fungicide of anilide group, is intended to prevent and treat grey mould (Botrytis cinerea), primarily in vines and other fruit plants. In many regions, its long half-life in soil and water poses a serious environmental threat. Boscalid is reported to be toxic to a variety of aquatic organisms. One of the best ways to lessen the amount of boscalid that gets into surface and ground waters is to reduce its concentration in soil. Soil microbes are crucial for the degradation of organic pollutants including pesticides. The present study reports the assessment of three novel soil bacterial strains isolated from pesticide-contaminated soil of Crop research centre, Pantnagar, Uttarakhand, India, which possess boscalid degradation ability. Two of these bacterial isolates could degrade boscalid up to 85–95% within 36 h of incubation period under shaking conditions in the minimal medium. The growth pattern of degrading bacterial isolates was monitored by recording the optical density (OD) of bacterial suspension using an ultra violet (UV)-visible spectrophotometer, whereas the concentration of primary boscalid was recorded by High-Performance Liquid Chromatography (HPLC-UV). A linear relationship was observed between the bacterial growth and the decrease in the residual concentration of boscalid. The concentration of boscalid during incubation with different bacterial strains could be best predicted by a second-order polynomial relationship with time and OD of the suspension as independent variables. Three degradation intermediates of boscalid namely, N-(1,1′-biphenyl-2-yl)pyridine-3-carboxamide (C18H14N2O, N-{[1,1′-biphenyl]-2-yl}-2-chloropyridine-3-carboxamide (C18H13N2OCl), and N-{[4′-chloro-1,1′-biphenyl]-2-yl}-2-chloropyridine ({C17H11NCl2}OH) were identified by the liquid chromatography-mass spectrometry (LC-MS) analysis of biodegraded samples. The biodegradation of boscalid through bacterial isolates seemed to be an economical and eco-friendly method for degrading a highly persistent boscalid fungicide.

Modeling the relationship between air temperature and grapefruit quality traits.

Consumers of grapefruit require consistent fruit quality with a good physical appearance and taste. The air temperature during the growing season affects both the external (external color index (ECI)) and internal (titratable acidity (TA) and total soluble solids ratio (TSS/TA)) fruit quality of grapefruit. The objective of this study was to develop computer models that encompass the relationship between preharvest air temperature and fruit quality to predict fruit quality of grapefruit at harvest. There was a logarithmic relationship between the number of days with a daily minimum air temperature ≤13 °C and ECI, with a greater number of days resulting in higher ECI. In addition, there was a second-order polynomial relationship between the number of hours ≥21 °C and both TA and TSS/TA, with a greater number of hours resulting in lower TA and higher TSS/TA. Model performance for predicting the ECI, TA, and TSS/TA during 2004-05 and 2005-06 growing seasons was good, with Nash and Sutcliffe coefficient of efficiency (NSE) values for each season of 0.835 and 0.917 respectively for ECI, 0.896 and 0.965 respectively for TA and 0.898 and 0.966 respectively for TSS/TA. Applying the model to statistical survey data covering 13 growing seasons demonstrated that the TSS/TA model was robust. Statistical models were developed that predicted the development of grapefruit ECI, TA, and TSS/TA. The TSS/TA model was confirmed after application to long-term statistical survey data covering 13 growing seasons. © 2022 Society of Chemical Industry.

An investigation into the feasibility of a hybrid generator–photovoltaic–wind farm with variable load profile: case of headland south-west of Morocco

Abstract A hybrid system proposed by three different specifications for the equipment of a tourist lodge in the headland of south-west Morocco was sized by analysing the limits of load profile constraints, such as hour-to-hour variability (HHR), day-to-day variability (DDR) and the operating reserve rate (ROR). Based on the three-factor Doehlert matrix recommendations, the simulations employed an energy-sizing tool for hybrid renewable-energy systems. Testing was conducted with DDR at 5–30%, HHR at 10–30% and ROR at 0–20%. Under these conditions, a second-order polynomial relationship with a correlation rate of ~90% was found between the net present cost (NPC) of the system, the levelized cost of electricity and the various constraint factors. The first specification, SPC(1), composed of generators and batteries, was introduced to control and validate the simulation independently of renewable energy, which showed a positive manifestation with the imposed constraints. The analysis expanded by introducing solar and wind energy resources. The SPC(2) configuration added PV modules to the SPC(1) and the SPC(3) configuration added wind turbines to SPC(2). The effect of DDR, HHR and ROR in the trials was significant by linear regression. At the same time, only DDR had a significant quadratic regression. The others, with their pairwise interactions, were insignificant. The desirability procedure made it possible to calculate the maximum limits of load profile constraint variables leading to targets of LCOE = 0.41 US$/kWh and NPC = US$320 080.1 of the load profile constraints: the DDR = 15.47% and the HHR = 26.55% at an ROR rate of 17.77%.

Engineering properties of Cassia tora L. seeds and meal as a function of moisture content

Engineering properties are of great importance for Cassia tora L. seeds in aspects of harvesting, handling mechanical design and product processing. The effect of moisture content (7, 10, 13, 16 and 19%) (wet basis) on the properties: physical (length, width, bulk and true density, porosity, thousand seeds mass, coefficient of static friction and angle of repose), mechanical (hardness, fragmentation energy and failure deformations), and thermal (specific heat, thermal conductivity and thermal diffusivity), were systematically studied. As the moisture contents increase from 7 to 19%, the length (L) increased from 4.52 to 5.87 mm, the thickness (T) from 2.51 to 3.21 mm and the width (W) from 2.36 to 3.02 mm, respectively. The bulk and true density of Cassia tora L. seeds decreased from 775.83 to 654.17 kg/m3 and from 1295.21 to 1154.72 kg/m3, respectively, with the moisture content raised from 7 to 19%. The thermal conductivity of Cassia tora L. seeds meal was found to be 0.068–0.098 W m−1 K−1, 0.078–0.112 W m−1 K−1, 0.089–0.125 W m−1 K−1, 0.098–0.136 W m−1 K−1, 0.108–0.148 W m−1 K−1, 0.119–0.159 W m−1 K−1, respectively, at 25 °C, 45 °C, 65 °C, 85 °C, 105 °C and 125 °C in moisture ranges of 7–19%. The thermal diffusivity was found to decrease from 5.21 × 10–8 to 4.53 × 10–8 m2/s, from 5.75 × 10–8 to 4.91 × 10–8 m2/s, from 6.11 × 10–8 to 5.17 × 10–8 m2/s, from 6.52 × 10–8 to 5.36 × 10–8 m2/s, from 7.17 × 10–8 to 5.77 × 10–8 m2/s, from 7.36 × 10–8 to 5.84 × 10–8 m2/s, respectively, at 25 °C, 45 °C, 65 °C, 85 °C, 105 °C and 125 °C in moisture ranges of 7–19%. The results suggested that physical properties exhibited linear relationships with moisture content using the regression model, while mechanical properties showed a second-order polynomial relationship with moisture content. Furthermore, significant variation existed in thermal properties because of differentiate moisture content and temperature. These data and rules are also useful for high efficiency machines design and mechanisms development.

Forest ecosystem service functions and their associations with landscape patterns in Renqiu City.

Forest ecosystems are crucial to the survival and development of human societies. Urbanization is expected to impact forest landscape patterns and consequently the supply of forest ecosystem services. However, the specific ways by which such impacts manifest are unclear. Therefore, to discuss the relationship between them is of great significance for realizing regional sustainable development. Here, we quantitatively assess the intensity of forest ecosystem service functions and forest landscape patterns in Renqiu City of China’s Hebei Province in 2019 using ArcGIS and FRAGSTATS. We characterize the relationships between forest ecosystem service capacity and landscape patterns, and identify strategies for the spatial optimization of forests. We find that the ecosystem service intensity of forests are significantly correlated with their spatial distribution, forest area ratio, and landscape patterns. Specifically, the percentage of landscape (PLAND) index, landscape shape index (LSI), and contagion (CONTAG) index indices display second-order polynomial relationships with various forest ecosystem service functions, with critical values of 80, 5, and 70, respectively. We propose that forest ecosystem functions can be optimized by optimizing forest landscape patterns. Specifically, to maximize the function of forest ecosystem services, managers should consider the integrity of forest ecosystems, optimize their ability to self-succession, repair service functions of key nodes within forests, enhance forests’ structural stability, optimize forest quality and community structure, and strengthen the efficiency of functional transformation per unit area. Finally, we propose a strategy for the spatial optimization of forests in Renqiu to optimize their associated ecosystem services. This involves protecting important areas for forest ecosystems, rationally organizing different ecological patches such as forests and water bodies to maximize their functions, strengthening the connectivity of scattered forests, and supplementing woodland areas.

Determining water use and crop coefficients of drip-irrigated cotton in south Xinjiang of China under various irrigation amounts

Crop evapotranspiration (ETc) and crop coefficient (Kc) can vary among various geographical locations and cultivated species. Therefore, determining regional- and species-specific crop coefficients is fundamental for rational irrigation water management. A two-year field study was conducted in south Xinjiang of northwest China to estimate periodic ETc and reference evapotranspiration (ET0), and thus develop the regional crop coefficient (Kc) at various growth stages of fertigated cotton (Gossypium hirstum L. Xinluzhong No 67) under various irrigation amounts. ETc was determined by the soil water balance method, while ET0 was obtained using the FAO (Food and Agriculture Organization of the United Nations) Penman-Monteith model. The results indicated that increasing irrigation amounts resulted in increased seed cotton yields, but reduced crop water productivity (WP). The water consumption at flowering and boll setting stages accounted approximately for 60% of the seasonal water use of cotton under various irrigation amounts. The average locally developed Kc (Kc-local) values over two seasons were 0.38, 1.30 and 1.09 for initial, mid-season, and end-season stages, respectively. The locally developed initial Kc (Kc-local-ini) (0.38) was higher than the optimized initial-stage Kc (Kc-opt-ini) (0.23) and similar to the FAO recommended Kc (Kc-FAO) (0.35). The optimized Kc (Kc-opt) did not significantly differ from Kc-FAO at mid-season and end-season stages. The locally developed middle-stage Kc (Kc-local-mid) was 10% higher than the optimized middle-stage Kc (Kc-opt-mid) and the FAO recommended middle-stage Kc (Kc-FAO-mid), and the locally developed end-stage Kc (Kc-local-end) was approximately 82% higher than the optimized end-stage Kc (Kc-opt-end) and the FAO recommended end-stage Kc (Kc-FAO-end). The difference between Kc-local, Kc-opt and Kc-FAO was attributed to the variations of climate condition, cultivated variety and field management. Kc-local determined by the soil water balance method in the present study fully considered the regional conditions including weather, species and management practices, which can be adopted to guide the irrigation management in this region. This study provided credible cotton periodic Kc in the arid and semiarid regions of northwest China. A second-order polynomial relationship between cotton Kc and t/T (the days after emergence/the days of total cotton growth period) was established, which can provide a reference for the determination of local cotton Kc and irrigation management.

Spatial distribution of stable isotopes in surface water on the upper Indus River basin (UIRB): Implications for moisture source and paleoelevation reconstruction

Appropriate characterisation of isotope signatures (δ18O and δD) of groundwater, glaciers, and surface water in the Himalayan catchment are important for refining the sources of moisture and developing a modern isotope–elevation relationship for paleoelevation reconstructions. The Indus River located in Western Himalaya is previously unexplored in respect of the variation in water isotopic composition with elevation. In this study, water samples (n = 96) were collected from mainstream, tributaries, streams, glaciers, groundwater, lakes, hot springs, and pond water during the summer season. Results showed that δ18O signatures of the mainstream, tributaries and groundwater range from −15.1‰ to −12.3‰, −16.5‰ to −12‰, −13.8‰ to −12‰, with a mean value of −13.6‰, −14.7‰, −12.8‰, respectively. There was a northward rise in δ18O by 1.30‰ per degree of latitude in the tributary waters. The d-excess and δ18O values suggested that the key source of moisture in the studied river basin was mainly from westerlies and southwest monsoons. Thus, regional moisture recycling and subcloud evaporation contributed little in supplying moisture to the precipitation. The isotopic signature (δ18O) of the tributary stream and its surrounding regions conformed to a best-fit second-order polynomial relationship between δ18O and elevation over 3500 masl. Moreover, an δ18O elevation slope of −2‰/km is also established in this study area. This isotope–elevation relationship will be highly useful and can be applied to the Indus River and other Himalayan rivers for paleoelevation reconstruction.

Azetidinium Lead Halide Ruddlesden-Popper Phases.

A family of Ruddlesden–Popper (n = 1) layered perovskite-related phases, Az2PbClxBr4−x with composition 0 ≤ x ≤ 4 were obtained using mechanosynthesis. These compounds are isostructural with K2NiF4 and therefore adopt the idealised n = 1 Ruddlesden–Popper structure. A linear variation in unit cell volume as a function of anion average radius is observed. A tunable bandgap is achieved, ranging from 2.81 to 3.43 eV, and the bandgap varies in a second-order polynomial relationship with the halide composition.

Characterization of Gafchromic™ film response against radionuclide activity

PurposeIn this study, we used Gafchromic™ film XR-QA2 and RT-QA2 to characterize the film energy response against various radionuclides. We introduce a neutron depletion theoretical model that can describe film response as a function of cumulated activity. The film response was investigated with respect to different backscatter media such as polystyrene, perspex, lead and corrugated fibreboard carton (CFC). The sensitivity of the two types of film to different energies was also studied. Lastly, a film stack method was tested to allow the user to obtain sequential, cumulative doses at different time points. MethodsPieces of Gafchromic™ film XR-QA2 and RT-QA2 were exposed to Am-241, Cs-137, Tc-99m, and I-131 to obtain various cumulative activities. After 24 h, each film piece was digitized by scanning it with an Epson Perfection V330 flatbed scanner to obtain 48-bit RGB TIFF images. Afterwards, each image was processed with the Image J software package. The film response was fitted to a theoretically derived function based on the neutron depletion model and the Beer-Lambert Law and compared with an existing fitting function. Layers of the film were also placed together and irradiated with the above-mentioned radionuclides to investigate the possibility of increasing the sensitivity of the film as a dosimeter. The energy response of the two types of film was investigated by irradiating pieces of film with different photon energies. ResultsThe theoretical response model fits OD vs cumulative activity accurately. XR-QA2 film shows good energy film response by using CFC as a backscatter material when using radionuclides. From the results, it is also evident that XR-QA2 is more sensitive to low energy gamma rays than RT-QA2. Its OD sensitivity can be increased by 2 ± 0.2 when using a double layer film and by 2.8 ± 0.3 when using a triple-layer film. By using a film stack, the experimental time can be decreased by using the second-order polynomial relationship obtained to relate the stacked film data to the single film data. ConclusionsThe neutron depletion theoretical model is accurate and contains less free parameters than higher-order polynomial fits. The Gafchromic™ XR-QA2 film is also better to use in nuclear medicine because of its higher sensitivity. The sensitivity of the film as a dosimeter can also be increased by using multiple layers of film. Experiment times can also be decreased by using the film stack method.

Influence of Environmental Factors on Growth, Survival, and Heavy Metal Accumulation in Oyster, Crassostrea madrasensis (Preston, 1916) Cultivated in Negombo Estuary, Sri Lanka

The growth of marine bivalves is affected by the interactions of several environmental variables, particularly water salinity, temperature, and food supply. Influences of environmental parameters on daily weight gain (DWG), survival and heavy metal accumulation in 225 numbers of oysters, Crassostrea madrasensis (Preston, 1916), placed at five locations in the Negombo estuary, Sri Lanka, were investigated. One-way ANOVA indicated significantly higher (P &lt; 0.05) DWGs (0.22 ± 0.01 and 0.16 ± 0.01 g.day-1) in Pitipana and Munnakaraya, where highest mean salinity (20.9 ± 0.34 ppt) and chlorophyll-a (5.41 ± 1.49 µg.L-1) were observed. Significantly lower growth rate (0.04 ± 0.02 g.day-1) recorded in Thaladuwa, where lowest salinity (13.29 ± 1.13 ppt), highest turbidity (19.26 ± 0.99 NTU) and ammoniacal nitrogen (0.368 ± 0.078 mg.L-1) were recorded. DWG showed a significant second-order polynomial relationships with chlorophyll-a (R² = 0.44, P &lt; 0.05) and salinity (R² = 0.28, P &lt; 0.05). Negative exponential relationships of DWG were evident with higher level of ammoniacal nitrogen (R² = 0.24, P &lt; 0.05) and phosphate (R² = 0.25, P &lt; 0.05). The high concentration of lead (1.883 mg.kg-1) exceeded the EU permissible limit of 1.5 mg.kg-1 (wet weight) in oysters’ tissue where urban wastewater is released to the lagoon. There appeared to be health concerns due to heavy metal accumulation in oyster tissues in polluted areas of the estuary. The findings of this study are useful for understanding the potential impacts of environmental changes on oyster resources and the long-term sustainability of oyster fisheries and aquaculture.

Nigral MRI features of asymptomatic welders

IntroductionManganese (Mn)-induced parkinsonism involves motor symptoms similar to those observed in Parkinson's disease (PD). Previous literature suggests that chronic Mn- exposure may increase PD risk, although Mn-induced clinical syndromes are considered atypical for PD. This study investigated whether asymptomatic welders display differences in the substantia nigra (SN), the key pathological locus of PD. MethodBrain MRI data and occupational exposure history were obtained in welders (N = 43) and matched controls (N = 31). Diffusion tensor imaging fractional anisotropy (FA; estimate of microstructural integrity) and R2* (estimate of iron and other PD-related brain differences) values in the SN pars compacta (SNc), SN reticulata (SNr), and globus pallidus (GP) were compared between the two groups. The MRI markers of the SN and GP within welders were related to exposure estimates. ResultsCompared to controls, welders who had chronic, but low-level, Mn-exposure had similar FA and R2* values in both SN regions (p's > 0.082), but significantly lower FA (p = 0.0013), although not R2* (p = 0.553), in the GP. In welders, FA values in the SN and GP showed a second-order polynomial relationship with cumulative lifetime welding exposure (p's < 0.03). ConclusionNeurotoxic processes associated with Mn-exposure may be different from those in PD when the exposure-level is relatively low. Greater welding duration and level, however, were associated with FA differences in the GP and SN, indicating that welding exposures above a certain level may induce neurotoxicity in the SN, a finding that should be explored further in future studies.

Response of tree community composition, plant diversity and aboveground tree biomass in tropical rainforests of Sri Lanka to variation in altitude

Tropical rain forests (TRFs) are a major carbon sink and play an important role in regulating the global climate. Floristic composition, structure and carbon storage in biomass of TRFs could vary substantially with climatic and edaphic factors. Altitudinal transects represent an excellent setting for investigating the responses of TRFs to environmental change. Objectives of this study were to determine the variation patterns and possible inter-relationships between plant community composition, diversity and aboveground biomass (AGB) in TRFs across an altitudinal gradient from 134 m to 1,667 m above sea level in Sri Lanka. Five permanent sampling plots of 1 ha each, consisting of four plots in lowland rainforests in Kanneliya and Pitadeniya- Sinharaja Forest Reserves and one plot in the tropical montane forest in Rilagala, were established. Trees with DBH≥10 cm were measured and taxonomically identified. A total of 3,781 trees, belonging to 191 species from 106 genera and 53 families were recorded, with a total basal area of 203.68 m2. Floristic composition of sampling plots showed substantial variation with altitude. Tree density and numbers of species, genera and families and plant diversity indices (i.e. Shannon-Wiener and Simpson’s Indices, evenness and richness of tree species) showed negative curvilinear declines with increasing altitude. Mean DBH, tree basal area and AGB increased from low- (348 kg ha-1) to midaltitudes (762 kg ha-1) and decreased from mid- to highaltitudes (70 kg ha-1), thus showing second-order polynomial relationships with altitude. Similar trends were shown between AGB and tree species number and diversity indices, thus indicating that AGB is maximum at intermediate vegetation diversity.