Efficiency Index Values Research Articles

Preparation of Fucoxanthin-Loaded Nanoparticles Composed of Casein and Chitosan with Improved Fucoxanthin Bioavailability.

To facilitate the utilization of fucoxanthin (FX), a valuable marine carotenoid, in the food industry, FX-loaded casein nanoparticles (FX-CN) and chitosan-coated FX-CN (FX-CS-CN) were developed using the FX-enriched fraction from Phaeodactylum tricornutum. Two nanoscale particles (237 ± 13 nm for FX-CN and 277 ± 26 nm for FX-CN-CN) with spherical and smooth surfaces showed over 71% encapsulation efficiency and polydispersity index (PDI) value of 0.31-0.39 in water. Owing to the chitosan coating, FX-CS-CN showed a positive zeta potential (24.00 mV), whereas that of FX-CN was negative (-12.87 mV). In vitro simulated digestion demonstrated better FX bioaccessibility from the nanoparticles versus P. tricornutum powder (Pt-powder) and from FX-CN versus FX-CS-CN. However, in C57BL/6 mice, fucoxanthinol absorption to the blood circulation was two times higher for FX-CS-CN versus FX-CN, possibly due to increased retention or adsorption to mucin by the cationic biopolymer in the chitosan-coated particles. These results demonstrate that FX-CS-CN can enable the application of FX, with improved bioavailability and water dispersibility, in the food industry.

Effect of Bensulfuron-Methyl+Pretilachlor and Other Herbicides on Mixed Weed Flora of Wet Season Transplanted Rice

Field experiments were conducted during the wet season of 2012 and 2013 at farmer's field of village Binuria, Sriniketan, Birbhum, West Bengal, India with rice variety ‘Swarna’ (MTU 7029) to study the effect of bensulfuron-methyl + pretilachlor and other herbicides on growth of different weed species and productivity of transplanted rice. Twelve treatments in the experiment were assigned in a randomized block design with three replications. Results revealed that rice was infested with three categories of weeds viz. grasses, broadleaved and sedges. Cynodon dactylon and Paspalum distichum among the grasses; Fimbristylis miliacea, among the sedges and Ludwigia parviflora and Commelina nudiflora among the broadleaved weeds were predominant throughout the cropping period. Bensulfuron-methyl 0.6%+ pretilachlor 6% at 60+600 g ha−1applied at 3 DAT completely controlled the grasses, broadleaved and sedges at 30 and 60 DAT except Cynodon dactylon and Paspalum distichum. However, the density, as well as dry weight of both the species were significantly reduced. Metsulfuron methyl + chlorimuron-ethyl (Almix) + azimsulfuron at 4+35 g ha−1 at 15 DAT was also quite effective in controlling broad spectrum weeds. Lower values of weed density, total weed dry weight and higher values of herbicide efficiency index and yield of rice were registered with application of bensulfuron-methyl 0.6%+ pretilachlor 6% at 60 + 600 g ha−1 at 3 DAT followed by metsulfuron methyl + chlorimuron-ethyl (Almix) + azimsulfuron at 4+35 g ha−1 at 15 DAT. Weed infestation resulted in grain yield reduction of rice to the tune of 40% Application of bensulfuron-methyl 0.6%+ pretilachlor 6% at 60+600 g ha−1 at 3 DAT or metsulfuron methyl + chlorimuron-ethyl (Almix) + azimsulfuron at 4 + 35 g ha−1 at 15 DAT appeared to be the most promising for managing mixed weed flora and obtaining higher yield of transplanted rice in the lateritic belt of West Bengal, India.

Evaluation of Weed Emergence Model AlertInf for Maize in Soybean

AlertInf is a recently developed model to predict the daily emergence of three important weed species in maize cropped in northern Italy (common lambsquarters, johnsongrass, and velvetleaf). Its use can improve the effectiveness and sustainability of weed control, and there has been growing interest from farmers and advisors. However, there are two important limits to its use: the low number of weed species included and its applicability only to maize. Consequently, the aim of this study was to expand the AlertInf weed list and extend its use to soybean. The first objective was to add another two important weed species for spring-summer crops in Italy, barnyardgrass and large crabgrass. Given that maize and soybean have different canopy architectures that can influence the interrow microclimate, the second objective was to compare weed emergence in maize and soybean sown on the same date. The third objective was to evaluate if AlertInf was transferable to soybean without recalibration, thus saving time and money. Results showed that predictions made by AlertInf for all five species simulated in soybean were satisfactory, as shown by the high efficiency index (EF) values, and acceptable from a practical point of view. The fact that the algorithm used for estimating weed emergence in maize was also efficient for soybean, at least for crops grown in northeastern Italy with standard cultural practices, encourages further development of AlertInf and the spread of its use.

Dokładność diagnostyki z zastosowaniem wysokoczęstotliwościowej emisji otoakustycznej produktów zniekształceń nieliniowych w badaniach przesiewowych u dzieci w wieku szkolnym z zespołem Downa

BackgroundIt has been suggested that children with Down syndrome (DS) may display high frequency hearing loss much earlier than those in the general population. The purpose of this study was to investigate the diagnostic accuracy of high-frequency distortion-product otoacoustic emissions (HFDPOAEs) as a screening technique for schoolchildren with DS.Material and MethodsExactly 25 children with DS (15 males, 10 females, mean age =9.7 years, SD=2.6) were sampled from six special education schools. HFDPOAE results were compared to the reference test results – high-frequency pure tone audiometry (HFPTA) at 8 and 10 kHz.ResultsTest performance was found to reach adequate levels (≥0.7) of accuracy for HFDPOAE SNR at 8 kHz and 10 kHz. The hit rate at 8 kHz was average, but moderately high at 10 kHz. True negative rates and positive posterior probabilities for the HFDPOAE test were high, and false alarm rates were acceptably low. However, the false negative rate was average at 8 kHz and negative posterior probabilities were moderately high at both frequencies. Efficiency index values were high indicating that a large proportion of HFDPOAE results were correct when compared with HFPTA results.ConclusionsInitial findings support the potential future use of HFDPOAE for screening children with DS for high-frequency hearing loss.

Effects of Scale and Discharge Variation on Similitude and Solute Transport in Water Treatment Tanks

AbstractThis paper addresses the design and experimentation aspects of scaled contact tanks, a key type of treatment units in water works worldwide. The paper covers the effects of scale and discharge variation on the dynamic similitude and hydraulic efficiency of such tanks. The flow patterns tending to complete mixing (CM) and plug flow (PF) were studied, each assessed in a prototype and three further geometrically similar models of L-shaped and serpentine geometries. Tracer experiments were conducted under five discharge values. The sensitivity of each flow pattern to the changing conditions was assessed based on the residence time distribution curves and hydraulic efficiency index values, contrasted for prototypes and their scaled models. Although the CM flow pattern was insensitive to the variation of scale and discharge, within the ranges tested in this study, the PF pattern was affected by both variations when the flow regime was not turbulent in a model tank. A dependency of the dispersion number ...

Intensity-Encoded Polymer Optical Fiber Accelerometer

In this paper, we report the development and experimental implementation of a low-cost, compact, intensity-encoded accelerometer based on polymer optical fibers (POF). The proposed accelerometer sensor element relies on the misalignment between two POFs, being the external acceleration encoded in the optical signal intensity. The accelerometer performance was optimized by simulation, resulting in a coupling efficiency and modulation index values of 0.38 and 1.78, respectively. The implemented device has a sensitivity of ${\rm 33.5}\pm{\rm 0.1}~{\rm mV}/{\rm g}$ and a resonant frequency of ${\rm 51.44}\pm{\rm 0.1}~{\rm Hz}$ , obtained for a signal to noise ratio of 20 dB. This value for the resonant frequency is suitable for applications in several fields, such as structural health monitoring of civil engineering structures.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

SWAT-QUALKO2 연계 모형을 이용한 관개기 순별 관개수질 모의

The objectives of this study were to develop a linked watershed-waterbody modeling system and to assess the impacts of indirect wastewater reuse on irrigation water quality. The Osan stream watershed within Gyeonggi-do of South Korea was selected for this study. The linked modeling system was composed of the SWAT (Soil and water assessment tool) and QUALKO2 models. The SWAT model was calibrated and validated using the stream discharge and water quality data from 2010 to 2011. Runoff and non-point source pollutants from each subbasin and stream discharge from 1980 to 2009 were simulated by the SWAT model and applied to the QUALKO2 model. The QUALKO2 model was calibrated and validated under the conditions of low water and normal discharges, respectively. Finally, The 10-day irrigation water quality from April to September was simulated. The statistical measures of coefficient of determination (<TEX>$R^2$</TEX>), reliability index (RI), and efficiency index (EI) were used to evaluate the system performance. The <TEX>$R^2$</TEX>, RI and EI values ranged from 0.5 to 1.0, 1.03 to 1.92, and -35.03 to 0.95, respectively. The 10-day irrigation water quality showed the concentrations of BOD and coliform exceeded the water quality guidelines for wastewater reuse. The linked modeling system can be a useful tool to estimate non-point source pollutant loads in watershed and to control the water quality of effluent from a wastewater treatment plant and irrigation water in the downstream waterbody.

Modeling Weed Emergence in Italian Maize Fields

A hydrothermal time model was developed to simulate field emergence for three weed species in maize (common lambsquarters, johnsongrass, and velvetleaf). Models predicting weed emergence facilitate well-timed and efficient POST weed control strategies (e.g., chemical and mechanical control methods). The model, called AlertInf, was created by monitoring seedling emergence from 2002 to 2008 in field experiments at three sites located in the Veneto region in northeastern Italy. Hydrothermal time was calculated using threshold parameters of temperature and water potential for germination estimated in previous laboratory studies with seeds of populations collected in Veneto. AlertInf was validated with datasets from independent field experiments conducted in Veneto and in Tuscany (west central Italy). Model validation resulted in both sites in efficiency index values ranging from 0.96 to 0.99. AlertInf, based on parameters estimated in a single region, was able to predict the timing of emergence in several sites located at the two extremes of the Italian maize growing area.

Exergetic and sustainability performance assessment of geothermal (ground source) ejector heat pumps

Although ejectors have been used in cooling/refrigeration and Heat Pumps (HP) applications for a long time, utilisation of Geothermal Ejector Heat Pump (GEHP) with Ground–Heat Exchanger (GHE) is a new idea, which has recently appeared in the literature. In this study, we model a GEHP system with a GHE in terms of exergetic aspects and apply our model to this system in the heating mode. The system consists of mainly three parts, namely a GEHP unit, a GHE, and a heat distribution system. We determine the exergy transports between the components and the consumptions in each of the components of the whole system and we also calculate exergy efficiency and Sustainability Index (SI) values for the system components to evaluate its performance. In this regard, exergy efficiency values for the GEHP unit and whole system are calculated to be 85.3% and 84.6% on the product/fuel basis at dead (reference) state values for 19°C and 101.325 kPa, respectively. An improvement of about 16.17% in the energetic and exergetic coefficient of performance value of the GEHP unit is obtained by adding an ejector to the HP system. SI values for some system components such as ejector, compressor, condenser and evaporator are also obtained to be 1.82, 2.79, 3.22 and 3.94, respectively.

A study of hydrocyclone classification of coal fines by CFD modeling and laboratory tests

The elimination of ultrafine (<10 µm) clay particles is essential to the treatment of abandoned coal-washing plant tailings for the recovery of the remaining coal fraction by enhanced gravity processing. Effective hydrocyclone classification is required to remove this fraction. The highly variable composition and particle size distribution of such wastes creates significant difficulties in the operation of hydrocyclones for such classifications. Hydrocyclone laboratory investigations and their plant setup require lengthy or time-consuming tests. The use of empirical models of such classifications frequently requires modification to correspond to actual operating conditions. Results of the evaluation of computational fluid dynamics (CFD) modeling to predict hydrocyclone classification of coal-washing plant tailings are presented. Results of the standard k-epsilon turbulence, SSG turbulence and large eddy simulation CFD models are compared with the results obtained from analyzed hydrocyclone classifications. The CFD models tested are shown to be very effective in the simulation of hydrocyclone classifications for the determination of the classification particle size and adequate for determining the efficiency index values for many applications. The large eddy simulation model was identified as the most precise, but it is recommended that all three models be improved simulations of classifications above and below the classification particle size.

Development of sustainable energy options for buildings in a sustainable society

Abstract In this study, a building with a volume of 392 m 3 and a net floor area of 140 m 2 is considered as a case study with the indoor and exterior air temperatures of 20 °C and −15 °C, respectively. For heating applications, seven options are studied, namely (i) electric boiler, (ii) cogeneration, (iii) biomass/wood, (iv) ground heat pump water–water (v) heat pump borehole/glycol, (vi) standard boiler and (vii) solar collector as driven by renewable and non-renewable energy sources. Energy and exergy analyses are conducted to assess their performances and compare them through energy and exergy efficiencies and sustainability index. Energy and exergy flows are studied and illustrated accordingly. Also, the energetic and exergetic renewability ratios are employed here along with sustainability index. The results show that overall exergy efficiencies of heating systems are found to be 2.8%, 5.5%, 6.0%, 6.4%, 6.1%, 5.4% and 25.3%, while the sustainability index values for the seven cases considered are calculated to be 1.029, 1.058, 1.063, 1.069, 1.065, 1.057 and 1.338 for options 1 through 7, respectively. So, solar collector-based heating system gives the highest efficiency and sustainability index values.

Performance and sustainability assessment of energy options for building HVAC applications

In this study, a building with a volume of 351 m3 and a net floor area of 117 m2 is considered as a case study with the indoor and exterior air temperatures of 20 and 0 °C, respectively. For the heating applications, four options are studied with (1) a heat pump, (2) a condensing boiler, (3) a conventional boiler and (4) a solar collector, which are driven by renewable and non-renewable energy sources. An energy and exergy analysis is employed to assess their performances and compare them through energy and exergy efficiencies and sustainability index. Energy and exergy flows are investigated and illustrated. Also, the energetic and exergetic renewability ratios are utilized here along with sustainability index. The results show that overall exergy efficiencies of heat pump, condensing boiler, conventional boiler and solar heating systems are found to be 3.66, 3.31, 2.91, and 12.64%, while the sustainability index values for the four cases considered are calculated to be 1.039, 1.034, 1.030 and 1.144, respectively. So, solar collector-based heating system gives the highest efficiency and sustainability index values.

Soil Quality Indices and Relative Production Efficiency for Maize and Wheat Crops in Agroclimates of Northwest India

To illustrate the integrated effect of 10 measured soil and climatic parameters into a single number, a new index, that is, Relative Production Efficiency Index (RPEI), was developed for different agroclimatic zones of extreme northwest India regions representative of overall production efficiency of maize and wheat crops. Besides RPEI, the Relative Soil Quality Index (RSQI) was also developed. On relating the RSQI and RPEI, it was observed that temperate soils had the highest values of RSQI (85), but the RPEI value of this zone was lowest for both maize (71) and wheat (71) compared with two other agroclimatic zones. The highest value of RPEI was noted in the intermediate zone (RPEI, 78 for maize and 76 for wheat crop). The subtropical zone, which had the lowest RSQI value (65), had the lowest RSQI value (65) and had a comparatively higher RPEI compared with RSQI for both maize (73) and wheat (73) crops. Based on the RPEI, the intermediate zone was in cultivable class II followed by subtropical (cultivable class III) and temperate zone (cultivable class IV). The area sown under maize and wheat crops in all the three zones of extreme northwest India were also described by the RPEI. A positive and linear relationship between grain yield and RPEI was observed for both maize and wheat crops. The increase in grain yield with higher values of RPEI was greater for the wheat crop. The area under either maize or wheat crops increased by 2.04 and 2.3 thousand hectares during the last 5 years, respectively. This increase can be attributed to the higher values of relative production efficiency index in this zone. The RPEI developed could be used to project the suitability, in terms of production, of an area for growing maize and wheat crops and thus is useful for making land use decisions.

Improvement in phonation after reconstruction of the recurrent laryngeal nerve in patients with thyroid cancer invading the nerve

We report vocal improvement after reconstruction of the recurrent laryngeal nerve (RLN) in patients with nerve resection, although vocal cord movement was not restored. These methods are not widely recognized. Direct anastomosis, free nerve grafting, or anastomosis to the ansa cervicalis or the vagus nerves with the RLN were performed in 7, 14, 65, and 2 patients with thyroid cancer invading the RLN, respectively. A total of 51 patients had vocal cord paralysis (VCP) pre-operatively. Maximum phonation time (MPT) and vital capacity (VC) were measured before and 1 year after reconstruction. A total of 34 normal subjects and 27 patients with VCP served as controls. Patients with VCP had significantly shorter MPT values than normal subjects. At 1 year after operation, patients with reconstruction had values of MPT similar to those of normal subjects. Men had significantly longer MPT values than women, but the phonation efficiency index (PEI), defined as the MPT/VC ratio, did not differ by sex. The PEI was significantly less in VCP patients than in normal subjects. Patients with reconstruction achieved PEI values similar to those in normal subjects. Phonation efficiency index values at 1 year after operation was significantly greater than pre-operative PEI and was not affected by the presence or absence of VCP pre-operatively, age, reconstruction method, thickness of suture thread, or use of magnification during the operation. In patients with thyroid cancer requiring RLN resection, RLN reconstruction achieved recovery in phonatory function.

Modified NLPM-ANN model and its application

Summary The non-linear perturbation model based on artificial neural network (NLPM-ANN) takes advantage of the consideration of seasonal information by the linear perturbation model (LPM) and the notable non-linear simulation capability of artificial neural network (ANN). However, this model does not take account of antecedent catchment wetness that may effect the simulation and forecasting accuracy. A modified NLPM-ANN model is proposed and developed to take the consideration of antecedent catchment wetness. The output perturbing terms of the response function in the simple linear model (SLM) in an auxiliary component are taken as inputs of ANN to represent catchment wetness. The simulated total runoff is obtained by integrating the outputs of ANN with that of the seasonal model. The rainfall–runoff data of eight catchments were selected and used to compare the modified NLPM-ANN with the NLPM-ANN models. Results show that the modified NLPM-ANN is significantly superior to the NLPM-ANN, and the model component efficiency index values are 16.82% and 16.74% over the NLPM-ANN during calibration and verification periods, respectively.

Slimming treatment efficiency and changes in serum lipids and lipoproteins in obese adolescents.

The efficiency of a slimming treatment, which is the quantity of lean body mass (LBM) lost for each kilogram of body fat reduced, measured by Efficiency Index (EI), was investigated in nineteen obese male adolescents aged 10-14 years who lost weight during four weeks of a treatment combining hypoenergetic diet (0.18 MJ/kg of expected body weight for stature), physical exercise and psychological support. Anthropometric assessment of adiposity including body composition using Parízková and Roth's regression equations was made before onset of treatment and after 7, 14 and 28 days. Simultaneously, blood samples were drawn for serum lipids and lipoproteins. A total of seventy six observations and assessments of treatment efficiency and changes of lipid profile between every two observations were carried out. Significant correlations were found between EI values and changes in Total Cholesterol and Total Cholesterol/HDL Cholesterol ratio at the three evaluations carried out. Though HDL-Cholesterol level increase was not significant, its variations were strongly correlated with EI during the first and second assessments. Differences found in the magnitude of increase in nonesterified fatty acids (delta NEFA), suggest that lipolytic mechanisms were not uniformly impaired. Treatment efficiency and delta NEFA were lower in subjects with lesser adiposity related to muscle mass at the middle third of the upper arm (measured through Energy/Protein Index). Triglycerides and LDL + VLDL Cholesterol levels showed little variations. The achievement of a high treatment efficiency is not only necessary for preserving growth, but also for the significant decrease which occurs in some lipid fractions when EI is below 0.5.

Étude observationnelle nationale (Association française d’urologie) de l’impact de la nycturie sur le sommeil des patients porteurs d’une hyperplasie bénigne de la prostate

To assess sleep efficiency in patients presenting with nocturia and symptomatic benign prostatic hypertrophy (BPH).This prospective observational survey was carried out in France by 113 urologists. A total of 1376 patients (mean+/-SD age: 68.8+/-9.0 years) consulting for BPH with greater than two nocturia episodes per 24 hours were assessed with a mean I-PSS score of 15.5+/-6.4 (symptoms greater than 19 [severe] in 26.9% of cases). Patients used a sleep diary to record the previous night's total; sleep efficiency is expressed as percentage ratio, representing the total amount of actual sleep between initial sleep onset and final awakening. Sleep disorders were assessed using HD-43 questionnaire based on International classification of sleep disorders.29.2% of the patients suffered from chronic insomnia, considered as primary insomnia (in 29.5% of cases) or related to either BPH (63.0%); snoring/sleep apnoea in 12.5% of cases. The mean sleep efficiency index was 87.2+/-13.7% and appeared to be significantly lower in BPH-related insomnia. Significantly lower sleep efficiency index values were observed as the severity (I-PSS score) of the BPH symptoms increased (89.5+/-12.1% for mildly symptomatic BPH vs. 84.0+/-15.6% for severely symptomatic BPH, P<0.001). Sleep efficiency index lowered with nocturia frequency (89.8+/-11.3% for two nocturia episodes vs. 80.4+/-17.3% for five nocturia episodes or more, P<0.001) and chronic insomnia frequency increased with nocturia frequency (21.4% for two nocturia episodes vs. 45.2% for five nocturia episodes or more, P<0.001).Insomnia is frequent in patients presenting with BPH-related lower urinary tract symptoms (LUTS) and is mainly secondary to these LUTS. There is a significant correlation between the frequency of nocturia and the severity of insomnia.

A comparative study of three neural network forecast combination methods for simulated river flows of different rainfall—runoff models

The performances of three artificial neural network (NN) methods for combining simulated river flows, based on three different neural network structures, are compared. These network structures are: the simple neural network (SNN), the radial basis function neural network (RBFNN) and the multi-layer perceptron neural network (MLPNN). Daily data of eight catchments, located in different parts of the world, and having different hydrological and climatic conditions, are used to enable comparisons of the performances of these three methods to be made. In the case of each catchment, each neural network combination method synchronously uses the simulated river flows of four rainfall—runoff models operating in design non-updating mode to produce the combined river flows. Two of these four models are black-box, the other two being conceptual models. The results of the study show that the performances of all three combination methods are, on average, better than that of the best individual rainfall—runoff model utilized in the combination, i.e. that the combination concept works. In terms of the Nash-Sutcliffe model efficiency index, the MLPNN combination method generally performs better than the other two combination methods tested. For most of the catchments, the differences in the efficiency index values of the SNN and the RBFNN combination methods are not significant but, on average, the SNN form performs marginally better than the more complex RBFNN alternative. Based on the results obtained for the three NN combination methods, the use of the multi-layer perceptron neural network (MLPNN) is recommended as the appropriate NN form for use in the context of combining simulated river flows.

Effect of influent flow rate distribution on the performance of step-feed biological nitrogen removal process

The step-feed anoxic/oxic biological nitrogen removal process has been proposed as an attractive alternative for the conventional biological nitrogen removal process for the purpose of enhanced nitrogen removal. For step-feed process, the biological nitrogen removal efficiency is a function of influent flow distribution. In this study, the effects of influent flow rate distribution on the performance of nitrogen removal process were investigated. The effects of influent flow rate distribution on COD, ammonia, total nitrogen removal efficiency, nitrification rate and sludge volume index value were also studied. According to the performance characteristic of the step-feed process, the concept of influent flow rate distribution ratio was firstly introduced. The maximum influent flow distribution ratios (λmax) under the condition of different influent C/N ratios were determined, respectively, by trial and error method. The experimental results showed that high total nitrogen removal efficiency, higher than 95%, could be achieved under certain influent flow rate distribution ratio without internal nitrate cycle or addition of external carbon source. It was obvious that nitrification rate of each stage under different influent flow distributions decreased along with the decreasing of sludge loading and volume loading in each stage, and the degree of reduction rise gradually with the increasing of influent flow distribution ratio. The sludge volume index value would also increase along with the increase of influent flow distribution ratio.