Quadratic Fitting Research Articles

Target tracking algorithm based on YOLOv3 and ASMS

In order to solve the problem of loss when the target encounters occlusion or the speed is too fast during the automatic tracking process, a target tracking algorithm based on YOLOv3 and ASMS is proposed. Firstly, the target is detected by the YOLOv3 algorithm and the initial target area to be tracked is determined. After that, the ASMS algorithm is used for tracking. The tracking effect of the target is detected and judged in real time. Reposi-tioning is achieved by quadratic fitting positioning and the YOLOv3 algorithm when the target is lost. Finally, in order to further improve the efficiency of the algorithm, the incremental pruning method is used to compress the algorithm model. Compared with the mainstream algorithms, experimental results show that the proposed algorithm can solve the lost problem when the tracking target is occluded, improving the accuracy of target detection and tracking. It also has advantages of low computational complexity, time-consuming, and high real-time performance.

Three-Dimensional Volumetric Magnetic Resonance Imaging Detects Early Alterations of the Brain Growth in Fetuses With Congenital Heart Disease.

Several published studies have shown alterations of brain development in third-trimester fetuses with congenital heart disease (CHD). However, little is known about the timing and pattern of altered brain development in fetuses with CHD. To investigate the changes in the volume of intracranial structures in fetuses with CHD by three-dimensional (3D) volumetric magnetic resonance imaging (MRI) in the earlier stages of pregnancy (median gestational age [GA], 26 weeks). Retrospective. Forty women carrying a fetus with CHD (including 20 fetuses with GA <26 weeks) and 120 pregnant women carrying a healthy fetus (including 50 fetuses with GA <26 weeks). Two-dimensional single-shot turbo spin echo sequence at 1.5-T. Three-dimensional volumetric parameters from slice-to-volume registered images, including cortical gray matter volume (GMV), subcortical brain tissue volume (SBV), intracranial cavity volume (ICV), lateral ventricles volume (VV), cerebellum, brainstem, and extra-cerebrospinal fluid (e-CSF) were quantified by manual segmentation from one primary and two secondary observers. Volumes were presented graphically with quadratic curve fitting. Scatterplots were produced mapping volumes against GA in normal and CHD fetuses. For GA <26 weeks, Z scores were calculated and Student's t-tests were conducted to compare volumes between the normal and CHD fetuses. In fetuses with CHD GMV, SBV, cerebellum, and brainstem were significantly reduced (all P < 0.05) in early stages of pregnancy (GA <26 weeks), with differences becoming progressively greater with increasing GA. Compared with normal fetuses, e-CSF, e-CSF to ICV ratio, and VV were higher in fetuses with CHD (all P < 0.05). However, ICV volume and the GMV to SBV ratio were not significantly reduced in the CHD group (P=0.94 and P=0.13, respectively) during the middle gestation (GA <26 weeks). There appear to be alterations of brain development trajectory in CHD fetuses that can be detected by 3D volumetric MRI in the earlier stages of pregnancy. 4 TECHNICAL EFFICACY: Stage 3.

Investigation of Brillouin frequency shift error estimated by quadratic fitting and the improved algorithm

A comparison of the performance of the quadratic fitting and the classical Lorentzian, Gaussian, pseudo-Voigt and Voigt fitting according to numerically generated and measured Brillouin spectra has been done. The results reveal that the computational burden of the quadratic fitting is much less than the least-squares ones. However, the Brillouin frequency shift (BFS) error estimated by the former may larger than the errors estimated by the latter. According to a large amount of measured Brillouin spectra with different frequency sweep spans, number of sweeps, signal-to-noise ratios (SNRs), linewidths, deviation of frequency sweep spans and processed by different filters, the influence of the above factors on the BFS error estimated by the quadratic fitting is systematically investigated. The results reveal that the optimal frequency sweep span is about one and a half linewidths. The BFS error decreases as a power of the number of sweep. The BFS error reduces exponentially with SNR (in dB). If the ratio of frequency sweep span and linewidth, and the number of sweep are fixed, the BFS error is approximately proportional to linewidth. Typical filters can significantly improve the accuracy in the estimated BFS and only slightly increase computational burden. An improved quadratic fitting is proposed. In the algorithm, first, Brillouin spectra noise is reduced by typical filter, then one or two linewidths' Brillouin spectra which is symmetric about the peak value are used to estimate BFS by the quadratic fitting. Its accuracy is similar to the classical least-squares fitting. However, its computation time is only one-hundredth of the pseudo-Voigt model based least-squares fitting.

Efficient estimation of chlorophyll a concentration in artificial upwelling

Artificial upwelling is an effective method to boost the primary productivity in the sea area, which provides a strong support for fishery. The chlorophyll a concentration is a key indicator to evaluate the marine productivity. This paper aims to provide a high-precision model to approximate the chlorophyll a concentration of artificial upwelling. After eliminating the abnormal values from the experimental data, we first used the global linear fitting (GLF) and the global quadratic fitting (GQF) models respectively to obtain reference errors. In order to improve the precision, we introduced the idea of the piecewise fitting to the model. The training set was partitioned into two, four and eight segments to find the optimal number of segments that the model can achieve the best precision. These models calculate the least squares solutions of the error function on each segment. To satisfy the engineering requirement, which is the continuity at boundary points, constraints were added to the boundary points of adjacent segments. Further, the quadratic fitting was proposed and applied on segments where the errors of fitting were relatively large when applying the constrained piecewise linear fitting (CPLF) model, namely the local quadratic fitting (LQF) model. Finally, we partitioned one more variable on the piecewise linear fitting model to examine if the predictive precision can be enhanced. Compared with the work of predecessors, where the GLF, GQF models and intelligent algorithms were applied to this issue, the results of our tested models showed higher precision in predicting chlorophyll a concentration and less complexity in model operation.

Dynamic thermal pleasure in outdoor environments - temporal alliesthesia

Thermal comfort research has been historically centred around the concept of “thermal neutrality”. Thermal neutrality originates from the steady-state indoor environment and is increasingly questioned when used to define the optimum sensation in outdoor environments. This calls for new criteria, designated for non-steady state and dynamically evolving outdoor settings. To address this need, we investigated thermal pleasure dynamics in outdoor environments based on thermal alliesthesia – a psychophysiological framework for understanding the hedonic responses elicited by non-steady-state thermal exposures. Detailed field studies were conducted in Sydney, Australia, during a 30-day period covering both summer and winter with a total of 35 subjects. The thermal sensation scale was quantitatively divided into four alliesthesial potential areas – two with moderate and two with strong alliesthesial potential - based on their divergence to the preferred sensation. We find that the temporal pleasure change (dP) can be predicted using thermal sensation change (dT). The results showed that linear regression performed strongly (R2 = 0.77 for summer and R2 = 0.79 for winter) in predicting dP when subjects' preceding sensation was in the strong alliesthesial potential zones – namely the ‘Hot’ and ‘Cold’ areas. When subjects' prior thermal sensation fell in the thermoneutral zone with moderate alliesthesial potential, a quadratic fit against dT provides a more reasonable prediction of dP (R2 = 0.61 for summer and R2 = 0.56 for winter). The dynamic thermal pleasure models provide a more nuanced subjective interpretation of outdoor urban spaces that includes thermal pleasure and delight. This study contributes further empirical support to the thermal alliesthesia framework and extends its application scope into outdoor thermal comfort research.

Dynamic simulation of the relationship between pressure and displacement for the waist of elastic pantyhose in the walking process using the finite element method

The inward displacement perpendicular to body surface produced by external pressure is an important index to evaluate pressure comfort and optimal design of tight clothing products. Because of the limited pressure exerted on the human body after wearing compression clothing, the corresponding displacement is generally small, and it is difficult to obtain an accurate displacement value of the human body using general methods. In this paper, we focused on the functional relationship between pressure and displacement when the human body was in the walking state after dressing in elastic pantyhose, and then the displacement data could be easily obtained using this method. Through computerized tomography scanning, establishing of the waist cross-section, finite element simulation, and curve fitting, we finally obtained the functional relationship between the pressure/displacement ratio and angle when the body is dressed in four sample elastic pantyhose during the walking process in this study. In the formula, pressure data can be easily obtained through the pressure experiment, and the corresponding displacement value at any point of the human body can be calculated using the quadratic fitting curve equation. Results indicated that no matter what state the human body was in (static or dynamic) after wearing elastic pantyhose, the relationship between pressure and displacement at the corresponding point remains basically unchanged. That is to say, the relationship between pressure and displacement was basically not affected by the state of the human body when dressed in a tight garment. The conclusions provide an important reference for evaluating pressure comfort and optimizing clothing structure. This method is also applicable to other types of compression clothing.

Statistical Analysis of Decoding Performances of Diverse Populations of Neurons.

A central theme in computational neuroscience is determining the neural correlates of efficient and accurate coding of sensory signals. Diversity, or heterogeneity, of intrinsic neural attributes is known to exist in many brain areas and is thought to significantly affect neural coding. Recent theoretical and experimental work has argued that in uncoupled networks, coding is most accurate at intermediate levels of heterogeneity. Here we consider this question with data from in vivo recordings of neurons in the electrosensory system of weakly electric fish subject to the same realization of noisy stimuli; we use a generalized linear model (GLM) to assess the accuracy of (Bayesian) decoding of stimulus given a population spiking response. The long recordings enable us to consider many uncoupled networks and a relatively wide range of heterogeneity, as well as many instances of the stimuli, thus enabling us to address this question with statistical power. The GLM decoding is performed on a single long time series of data to mimic realistic conditions rather than using trial-averaged data for better model fits. For a variety of fixed network sizes, we generally find that the optimal levels of heterogeneity are at intermediate values, and this holds in all core components of GLM. These results are robust to several measures of decoding performance, including the absolute value of the error, error weighted by the uncertainty of the estimated stimulus, and the correlation between the actual and estimated stimulus. Although a quadratic fit to decoding performance as a function of heterogeneity is statistically significant, the result is highly variable with low values. Taken together, intermediate levels of neural heterogeneity are indeed a prominent attribute for efficient coding even within a single time series, but the performance is highly variable.

A Process-Oriented Method for Rapid Acquisition of Canopy Height Model From RGB Point Cloud in Semiarid Region

This study addressed the problems of difficult parameter selection of ground point filtering algorithm, slow speed, and susceptibility to wrong classification points of traditional interpolation algorithm in extracting canopy height model (CHM) from dense point cloud produced by structure-from-motion (SfM). Finding the true ground is vital for canopy height estimation using UAV RGB point cloud, especially for semi-arid area where cloud points of short vegetation like shrubs and dwarf trees generally mixed up with the ground points. This paper proposes a ground point extraction strategy that combines the advantages of structural and spectral filtering. Specifically, spectral filtering simplifies the threshold selection for structural filtering, while structural filtering removes the outliers from spectral filtering. Considering the misclassified points in the ground filtering algorithm, a fast, nonparametric ground point interpolation algorithm was used to suppress the wrong classification points. This novel algorithm is based on the basic idea of least square quadratic fitting and prediction of terrain profile (PF). The quantitative results show that compared to Inverse Distance Weighting (IDW), Radial Basis Function (RBF), and Ordinary Kriging (OK), it takes less time (PF: 122s, IDW: 518s, RBF: 1374s, OK: 1129s), and has lower RMSE (PF: 0.301 m, IDW: 0.549 m, RBF: 0.903m, OK: 0.427m).

Empirical Analysis of the Influence of Dongguan’s Modern Logistics Industry on Import and Export Trade

In recent years, with the rapid economic development and the deepening of global economic integration, import and export trade has developed rapidly. With the development of international trade, international logistics has emerged. Modern logistics is a necessity for import and export trade, and the development of logistics has a direct influence on the development of import and export. In order to adapt to the rapid development of import and export trade, the modern logistics industry is developing in the direction of quality, diversity and efficiency. As the manufacturing capital, Dongguan has great potential for trade development. Relying on the superior geographical environment and the original industrial system, and further integrating resources on this basis, Dongguan vigorously develops its modern logistics industry and promotes a high degree of connection between international trade and characteristic industries, promoting the development of Dongguan’s import and export trade. Taking Dongguan as the research object and combining the data of Dongguan’s import and export trade and modern logistics industries, this paper established a quadratic curve fitting model to analyze the relationship between the total transportation volume and the total import and export volume, conducted elasticity and marginal analysis based on the empirical results, and put forward feasible suggestions for the development of Dongguan’s logistics and import and export trade.

Neurotransmitter Precursor Amino Acid Ratios Show Differential, Inverse Correlations with Depression Severity in the Low and High Depression Score Range.

The immunomodulatory capacity of mental stress is one of the basic concepts of psychoneuroimmunology. The current prospective longitudinal study was designed to evaluate the effect of acute mental stress on neurotransmitter precursor amino acid levels in individuals with depression at 2 time points. Ten physically healthy patients with a diagnosis of major depressive episode and Montgomery–Åsberg Depression Rating Scale scores (MADRAS) ⩾20 points at inclusion were assessed on 2 study days (once with higher MADRAS scores, once with lower MADRAS scores; median 34.5 days apart) and subjected to a standardized acute mental stress test on each study day. Blood was collected at 4 time points: once prior to and at 3 time points (0, 30 minutes, 60 minutes) following mental stress. Neurotransmitter precursor amino acid levels, that is kynurenine/tryptophan (KYN/TRP) and phenylalanine/tyrosine (PHE/TYR), as well as neopterin and nitrite were analyzed in a total of 80 individual blood samples. Regression and correlation analyses were performed. Regression analyses of PHE/TYR (R2 = .547) and KYN/TRP (R2 = .440) in relation to MADRAS depression severity showed a quadratic curve fit. This was reflected by a negative linear correlation between MADRAS scores and PHE/TYR as well as KYN/TRP in the lower score range (r = −.805, P < .001 and r = −.586, P < .001 respectively) and a positive correlation in the higher MADRAS score range (r = .713, P < .001 and r = .379, P = .016 respectively). No effect of acute mental stress was found. This analysis exemplifies the implications of sampling as well as data distributions on results. The crosstalk of biological mechanisms that orchestrate metabolic and immunological signaling may vary depending on depression severity resulting in non-linear associations that may explain the heterogeneity of results found in the literature.

Experimental study on the influence of temperature and radiation on photovoltaic power generation in summer

The power generation of photovoltaic systems is random and uncertain, which is the result of a variety of factors. However, there are few studies considering the interaction of two or more factors at the same time. Therefore, the influence of air temperature and radiation on photovoltaic power generation is considered in this paper, and based on the physical system, the experimental data is processed and analyzed through SPSS and DPS data analysis software and the multiple nonlinear regression analysis model. The processing results show that whether it is the quadratic and cubic nonlinear regression equations or the quadratic and cubic trend surface fitting degrees all reach a significant level, it can be used to reveal the law of the influence of two factors on the power generation under the test environment. The analysis results found that the combined effect of temperature and radiation on photovoltaic power generation is more complicated, but the overall impact of solar radiation is significant and greater than the air temperature; low temperature and high radiation, high temperature and high radiation and low radiation conditions have side effects on photovoltaic power generation; when the two are enhanced at the same time, it will help increase the photovoltaic power generation; when the two “one increase and one decrease”, the photovoltaic power generation first increases and then decreases, and there is an optimal air temperature, solar radiation, and maximum photovoltaic power generation.

Case Study 2: Practical Analytical Considerations for Conducting In Vitro Enzyme Kinetic Studies.

Characterization of enzyme kinetics in an experiment is dependent on measurement of a change in concentration of either the substrate (loss of parent) or the product (formation of metabolite). Modern analytical techniques such as ultrahigh pressure liquid chromatography, high resolution mass spectrometry, etc. have allowed accurate characterization of minute changes in concentration. Therefore, complex kinetic data such as a sigmoidal phase at low substrate concentrations or terminal half-life in a PK curve can be evaluated by stretching the limits of analytical quantification. This chapter presents some elementary dos and don'ts and provides insight into some of the underlying principles for utilizing the best possible analytical techniques when investigating enzyme kinetics. The objective of this case study is to answer the following questions: (a) Why is it necessary to determine lower and upper limits of quantification (LLOQ and ULOQ, respectively) of a bioanalytical assay, specifically for enzyme kinetic assays? How do you utilize LLOQ and ULOQ to correctly interpret your kinetic data? (b) Why should one use a linear fit and not a quadratic fit for standard curves? (c) Is quantification of an analyte possible without a reference standard? Can one assume equal signal intensities regardless of analytical technique (MS, UV)? (d) In the absence of reference standards, can you still determine kinetic constants? (e) With the need to keep substrate depletion at less than 20% for linearity assumptions, does bioanalytical variability matter? (f) What buffer do you use for your enzyme systems? How do you choose your buffer ? Does choice of bioanalytical methods (LC, MS) dictate your choice of buffer ?

Variant working vacation Markovian queue with second optional service, unreliable server and retention of reneged customers

In this paper, a variant working vacation queueing system with second optional service, unreliable server, and retention of reneged customers is studied. This model has potential applications in tele-services, banks, manufacturing processes, etc. The expressions of the steady-state probabilities and the system sizes when the server is in different states are obtained using probability generating functions. This paper also discusses an optimisation problem under a given cost structure. Direct search method and quadratic fit search method (QFSM) are applied to obtain the optimum number of working vacations and optimum service rates during regular busy period and working vacation period, respectively.

New temperature and metallicity scale of cool giants from K-band spectra

ABSTRACT We present here quantitative diagnostic tools for cool giants that employ low-resolution near-infrared spectroscopy in the K band for stellar population studies. In this study, a total of 260 cool giants (177 stars observed with X-shooter and 83 stars observed with NIFS) are used covering a wider metallicity range than in earlier works. We measure equivalent widths of some of the selected important K-band spectral features like Na i, Fe i, and 12CO after degrading the spectral resolution (R ∼ 1200) to investigate the spectral behaviour with fundamental parameters (e.g. effective temperature and metallicity). We derive empirical relations to measure effective temperature using the 12CO first-overtone band at 2.29 and 2.32 μm and show a detailed quantitative metallicity dependence of these correlations. We find that the empirical relations based on solar-neighborhood stars can incorporate large uncertainty in evaluating Teff for metal-poor or metal-rich stars. Furthermore, we explore all the spectral lines to establish the empirical relation with metallicity and find that the quadratic fit of the combination of Na i and 12CO at 2.29 μm lines yields a reliable empirical relation at [Fe/H] ≤ –0.4 dex, while a linear fit of any line offers a good metallicity scale for stars having [Fe/H] ≥ 0.0 dex.

Experimental and theoretical P-V-T equation of state for Os2B3

ABSTRACT Thermoelastic behavior of transition metal boride Os2B3 was studied under quasi-hydrostatic and isothermal conditions in a Paris-Edinburgh cell to 5.4 GPa and 1273 K. In-situ Energy Dispersive X-ray diffraction was used to determine interplanar spacings of the hexagonal crystal structure and the P-V-T data were fitted to a 3rd Order Birch–Murnaghan equation of state with a temperature modification to determine thermal elastic constants. The bulk modulus was shown to be K0 = 402 ± 21 GPa when the first pressure derivative was held to K0’ = 4.0 from the room temperature P-V curve. Under a quadratic fit , the thermal expansion coefficients were determined to be K−1, K−2, and K. Density functional theory (DFT) with the quasi-harmonic approximation (QHA) were employed to study Os2B3, including its P-V-T curves, phonon spectra, bulk modulus, specific heat, thermal expansion, and the Grüneisen parameter. A good agreement between the first-principle theory and experimental observations was achieved, highlighting the success of the Armiento-Mattsson 2005 generalized gradient approximation functional employed in this study and QHA for describing thermodynamic properties of Os2B3.

Band offsets of (100) β -(AlxGa1−x)2O3/ β -Ga2O3 heterointerfaces grown via MOCVD

The valence and conduction band offsets at (100) β-(AlxGa1−x)2O3/β-Ga2O3 heterointerfaces with the increasing Al composition are determined via x-ray photoelectron spectroscopy. The (100) β-(AlxGa1−x)2O3 thin films with the Al composition of 0.10 &amp;lt; x &amp;lt; 0.52 are grown on (100) β-Ga2O3 substrates by the metalorganic chemical vapor deposition method. By examining the onset of inelastic energy loss in core-level atomic spectra, the bandgaps of β-Ga2O3 and β-(AlxGa1−x)2O3 alloys with different Al compositions are measured from 4.83 ± 0.12 eV (x = 0) to 5.85 ± 0.08 eV (x = 0.52). The valence band offsets are determined to be −0.06 ± 0.06 eV (x = 0.10), −0.11 ± 0.06 eV (x = 0.33), and −0.19 ± 0.06 eV (x = 0.52). The conduction band offsets of 0.34 ± 0.17 eV (x = 0.10), 0.62 ± 0.17 eV (x = 0.33), and 1.21 ± 0.16 eV (x = 0.52) are determined from the extracted bandgaps of β-(AlxGa1−x)2O3 alloys. The determined band alignments at β-(AlxGa1−x)2O3/β-Ga2O3 interfaces reveal the formation of type-II (staggered gap) heterojunctions for all Al compositions investigated. The bowing parameters obtained from the quadratic fitting of both conduction band minimum and valence band maximum values are estimated to be 1.25 eV and 0.005 eV, respectively.

White matter integrity disruption in early amyloid accumulators

AbstractBackgroundAmyloid‐β (Aβ) accumulation is the pathological hallmark of Alzheimer’s disease (AD), suggested to be closely followed by white matter (WM) integrity alterations in preclinical subjects. However, reports on the relationship between the two measures have been conflicting. This study aimed to investigate the relationship between amyloid burden and WM integrity in preclinical AD on a regional level.Methods179 subjects from the EMIF‐AD preclinAD study who underwent Diffusion Weighted MRI (DWI) and dynamic [18F]flutemetamol PET imaging (Philips Ingenuity PET‐MR) were included (Table 1). Global and tract‐level Fractional anisotropy (FA) and mean diffusivity (MD) were determined using the JHU WM atlas. Amyloid burden was determined by the non‐displaceable binding potential (BPND+1) with cerebellar grey matter as the reference region. The relationship between amyloid burden and WM integrity was tested using Generalized estimating equations, correcting for family relatedness (Figure 1). Linear and quadratic fits were tested using QIC. Analyses were corrected for age, sex, and white matter hyperintensity load. The strongest associations are shown (significance set at p&lt;0.05, Bonferroni‐corrected).ResultsLow amyloid burden was associated with increased FA and decreased MD, followed by decreased FA and increased MD upon higher amyloid burden. This relationship was most robustly observed in the body of the corpus callosum (body CC), for which a quadratic fit was preferred according to QIC, and was mainly driven by amyloid accumulation in the precuneus (FA: β linear=0.352, β quadratic=‐0.103, ΔQIC=6.7; MD: β linear=‐0.434, β quadratic=0.128, ΔQIC=8.0, Figure 2), PCC (MD: β linear=‐0.393, β quadratic=0.101, ΔQIC=4.0), and to a lesser extent by the insula (MD: β linear=‐0.256, β quadratic=0.063, ΔQIC=2.0).ConclusionEarly amyloid deposition is associated with WM changes, particularly evident in the body CC. Importantly, a quadratic fit was preferred by QIC, and this pattern might reflect multiple stages of axonal damage, with initial oligodendrocyte proliferation and axonal swelling upon lower amyloid burden, and actual axonal degeneration only becoming apparent at a higher amyloid burden. Thus, WM integrity specifically in the body CC could be considered as an indicator of early AD pathology in addition to amyloid burden in preclinical subjects.

Development of normative data for the Five Point Test using the cognitive reliability and time to failure rate theory

In this study, several theoretically based curve fitting nonlinear models for analyzing the Five Point Test (FPT), a nonverbal fluency test, were examined. One thousand two hundred and one participants from the general population of Germany and the USA completed the FPT. The test scores were analyzed using three process indexes; the number of unique designs, strategy, and repetitions. Participants were stratified by age and level of education, and the resulting data were examined using best-fit nonlinear distribution equations. The study shows that the Weibull Growth three-factor curve fitting model provides equivalent fit as four-factor quadratic or linear curve fitting models for estimates continue normative data the Reliability and Time to Failure Theory of Cognitive Functions. Namely, that neurocognitive abilities remain stable during young adulthood and after reaching a threshold, starts to linearly or exponentially decline. The study also shows that education differentially impacts the asymptote, threshold, and decline rate of the FPT indexes confirming the importance of isolating specific cognitive domains within neuropsychological tests as these indexes might be related to the activation of particular cell assemblies, which in turn are differentially impacted by aging.

Effect of dietary digestible sulphur amino acids level on growth performance, blood metabolites and liver functional enzymes of broilers 1–11 days of age

This experiment was conducted to evaluate the effects of dietary digestible sulphur amino acids (DSAAs) level on growth performance, blood metabolites, and liver functional enzymes of broilers during 1–11 days of age. Additionally, DSAAs requirement was determined from dose nutrient response data. A total of 432 1‐day‐old male Ross 308 broilers were allocated to six dietary treatments, graded levels of supplementary DL-Met (+0.8 g/kg per level) while Cys was equal across groups, led to levels of 0.62, 0.70, 0.78, 0.86, 0.94 and 10.2% DSAAs, with six replicates and 12 birds each. Increasing levels of dietary DSAAs enhanced live body weight (LBW), weight gain (WG), feed efficiency (FE), European Production Efficiency Factor (EPEF), and relative breast weight (RBW), although there was no effect on feed intake. At the end of the starter period, a linear increase in blood serum total protein and albumin concentration was concomitant with decreasing in triglyceride, whole cholesterol, high‐density lipoprotein, low‐density lipoprotein, creatinine, and aspartate aminotransferase concentration when dietary DSAAs level was increased. The DSAAs requirements estimated by linear broken-line (LBL) fit model to optimise LBW, WG, FE, EPEF and RBW were 0.80, 0.81, 0.93, 0.95 and 0.93%, although the estimated values by the quadratic broken line fit model were 14.32, 19.93, 16.85, 23.68 and 5.79% higher than those, respectively. It is concluded, a minimum of 0.95% DSAAs concentration in broiler starter diet is suggested to optimise growth performance. Estimation of DSAAs requirement depended on what production parameter and regression model are taken considered for optimisation. Highlights A minimum of 0.95% digestible sulphur amino acids level is suggested in the broiler starter diet to optimise growth performance.

Experiment and fitting calculation of migration critical velocity of small-sized sediment particles erosion in rainwater pipeline

Abstract The migration critical velocity of small-sized sediment particles was investigated through experiments under different particle sizes, pipe wall roughness, and sediment thickness. Such experiments were carried out to simulate the erosion process of small-sized sediment particles in a rainwater pipeline during rainfall. The mathematical models were established via quadratic fitting to calculate the critical velocity of migration. Results showed that small particles had powerful cohesive force, and aggregates had strong erosion resistance. So, for the small-sized particles (in the range of 0.33–0.83 mm), the smaller the particle size, the larger the critical velocity. When the pipe wall roughness was large, the ‘starting’ particle resistance was high. A large flow dynamic was needed to overcome such resistance. Thus, the critical velocity was great. The critical velocity was also large when the sediment thickness was large. The difference rate between the critical velocity calculated by mathematical models and the measured value was within the range of −3.60% to 5.33% and had good consistency. Under the research conditions, the critical velocity ranges of the four commonly used pipes; namely, plexiglass, steel/PVC, galvanized/clay, and cast iron pipes, were calculated.