Edge enhancement of gravity anomalies and gravity gradient tensors using an improved small sub-domain filtering method

In order to enhance geological body boundary visual effects in images and improve interpretation accuracy using gravity and magnetic field data, we propose an improved small sub-domain filtering method to enhance gravity anomalies and gravity gradient tensors. We discuss the effect of Gaussian white noise on the improved small sub-domain filtering method, as well as analyze the effect of window size on geological body edge recognition at different extension directions. Model experiments show that the improved small sub-domain filtering method is less affected by noise, filter window size, and geological body edge direction so it can more accurately depict geological body edges than the conventional small sub-domain filtering method. It also shows that deeply buried body edges can be well delineated through increasing the filter window size. In application, the enhanced gravity anomalies and calculated gravity gradient tensors of the Hulin basin show that the improved small sub-domain filtering can recognize more horizontal fault locations than the conventional method.

复方磺胺甲噁唑片《中国药典》2015版微生物限度检查法的建立

目的 建立复方磺胺甲噁唑片的微生物限度检查法。方法 2016年3~5月按照《中国药典》2015年版（四部）微生物限度计数方法适用性试验,采用平皿法、薄膜过滤法、薄膜过滤加入中和剂（1.00%对氨基苯甲酸）法对5种阳性菌的回收率进行测定,探索需氧菌、真菌总数的计数方法和控制菌大肠埃希菌检查方法。结果 需氧菌、真菌总数验证试验中各菌回收率均达70.00%以上,回收率为0.50%~2.00%时试验组可检出大肠埃希菌,该法符合《中国药典》2015版的要求。结论 所建立的方法适用于该品种执行新版药典要求下的微生物限度检查,需氧菌总数和控制菌检查采用薄膜过滤加入中和剂的方法消除复方磺胺甲噁唑片的抑菌作用,真菌总数采用常规法。

Nitrate Leaching in an Irrigated Wheat-Maize Rotation Field in the North China Plain

Soil water deep drainage and nitrate (NO-3) leaching losses below the root zone were investigated in a 1 ha wheat-maize rotation field under traditional agricultural management that local farmers generally follow in the North China Plain, using the soil water balance method and NO3-N concentration in suction samples. Water drainage, and NO3-N distribution and leaching losses exhibited pronounced spatial and temporal variability. Soil water deep drainage and NO3-N leaching loss mostly occurred during the sum…

Microphone Array Speech Enhancement Based on Tensor Filtering Methods

This paper proposes a novel microphone array speech denoising scheme based on tensor filtering methods including truncated HOSVD(High-Order Singular Value Decomposition), low rank tensor approximation and multi-mode Wiener filtering. Microphone array speech signal is represented in three-order tensor space with channel, time, and spectrum modes and then tensor filtering model can be designed to process the multiway array data. As to the first method, noise can be reduced through the truncated HOSVD which is a simple scheme in tensor processing. It is more accurate to find the lower-rank approximation of the three-order tensor with Tucker model. Then MDL(Minimum Description Length) criterion is used to estimate the optimal tensor rank in the second method. Further, multimode Wiener filtering approach upon tensor analysis can be considered as the spanning of one-mode wiener filtering. How to take advantages of tensor model to obtain a set of filters is the heart of the novel scheme. The performances of the proposed three approaches are evaluated with objective indexes and listening quality test. The experimental results indicate that the proposed tenor filtering methods have potential ability of retrieving the target signal from noisy microphone array signal and the multi-mode Wiener filtering method provides the best denoising results among the three ones.

AN EFFICIENT APPROACH TO COMMENT SPAM IDENTIFICATION

This paper proposes a novel approach to comment spam identification based on content analysis. Three main features including the number of links, content repetitiveness, and text similarity are used for comment spam identification. In practice, content repetitiveness is determined by the length and frequency of the longest common substring. Furthermore, text similarity is calculated using vector space model. The precisions of preliminary experiments on comment spam identification conducted on Chinese and English are as high as 93% and 82% respectively. The results show the validity and language independency of this approach. Compared with conventional spam filtering approaches, our method requires no training, no rule sets and no link relationships. The proposed approach can also deal with new comments as well as existing comments.

Improvement of quantitative testing of liver function in patients with chronic hepatitis C after installment of antiviral therapy

MM： To investigate if and to what extent antiviral therapy influenced a broad panel of quantitative testing of liver function （QTLF）. METHODS： Fifty patients with chronic hepatitis C were either treated with interferon （n = 8）, interferon/ribavirin （n = 19） or peg-interferon/ribavirin （n = 23）. Quantitative testing of liver function, including aminopyrine breath test （ABT）, galactose elimination capacity （GEC）, sorbitol clearance （SCI） and indocyanine green clearance （ICG） was performed before and 3 mo after initiation of antiviral therapy. RESULTS： After 3 mo of antiviral treatment, 36 patients showed normal transaminases and were negative for HCVRNA, 14 patients did not respond to therapy. ABT and GEC as parameters of microsomal and cytosolic liver function were reduced in all patients before therapy initiation and returned to normal values in the 36 therapy responders after 3 too. Parameters of liver perfusion （SCl and ICG） were not affected by antiviral therapy. In the 14 non-responders, no changes in QTLF values were observed during the treatment period. CONCLUSION： ICG and SCI remained unaffected in patients with chronic hepatitis C, while ABT and GEC were significantly compromised. ABT and GEC normalized in responders to antiviral therapy. Early determination of ABT and GEC may differentiate responders from non-responders to antiviral treatment in hepatitis C.

New therapeutic opportunities for Hepatitis C based on small RNA

Hepatitis C virus （HCV） infection is one of the major causes of chronic liver disease, including cirrhosis and liver cancer and is therefore, the most common indication for liver transplantation. Conventional antiviral drugs such as pegylated interferon-alpha, taken in combination with ribavirin, represent a milestone in the therapy of this disease. However, due to different viral and host factors, clinical success can be achieved only in approximately half of patients, making urgent the requirement of exploiting alternative approaches for HCV therapy. Fortunately, recent advances in the understanding of HCV viral replication and host cell interactions have opened new possibilities for therapeutic intervention. The most recent technologies, such as small interference RNA mediated gene-silencing, antisense oligonucleotides （ASO）, or viral vector based gene delivery systems, have paved the way to develop novel therapeutic modalities for HCV. In this review, we outline the application of these technologies in the context of HCV therapy. In particular, we will focus on the newly defined role of cellular microRNA （miR-222） in viral replication and discuss its potential for HCV molecular therapy.

Strategies to Overcome Filter Divergence in the DRP-4-DVar Approach

This paper discusses an important issue related to filter divergence in the dimension-reduced projection,four-dimensional variational data assimilation(DRP-4-DVar) approach.Idealized experiments with the Lorenz-96 model over a period of 200 days showed that the amplitudes of the root mean square errors(RMSEs) reached the same levels as those of the state variables after approximately 100 days because of the accumulation of sampling errors following the cycle of assimilation.Strategies to reduce sampling errors are critical to ensure the quality of ensemble-based assimilation.Numerical experiments showed that localization and reducing observational errors can alleviate,but cannot completely overcome,the filter divergence in the DRP-4-DVar approach,while the method of perturbing observations and the inflation technique can efficiently eliminate the filter divergence problem.

Novel Adaptive Weighted Mean Filter

Based on the advantages and disadvantages of the standard median filter and the standard wean filter, a new Adaptive Weighted Mean Filter（AWFM） was proposed in this paper. The filter window＇s size of every pixel was adaptively adjusted. Then the suspidons noise points were examined by certain rules. After that, the authors calculate the weighting factors of the pixels by weighting function which was canstructed according to the differences between their gray values and the median value of all elements in the window. Finally they use the weighted average of gray values to substitute the gray value of the central pixel in the window. The results indicate that this filtering method is not only effective for impulse noise like median filter, but also better than the standard median filters. Compared with conventional filter, this filter methed can effectivdy suppress the mixture noise of images, and protect image＇s details well.

A new improvement of TCP based on adaptive filtering

On the basis of studying the standard TCP retransmission mechanism, this paper proposes a method to adopt the theory of adaptive filtering in the field for the estimation of round trip time （RTT）. Then this method is embedded in TCP for estimation of RTT, and defined as RTT-AF TCP. In the schemes with Only-TCP flow and with TCP and UDP flow fighting for the link, the experiment results were made and analyzed by using the standard TCP and the RTT-AF TCP. The experimental results show higher throughput and lower loss rate of packets by using RTT-AF TCP for data transmission, and achieve excellent effect.

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

Image Denoising Algorithm Considering Nonlocal Texture Pattern

Image denoising is indispensable for image processing.In this paper,image denoising algorithm based on Nonlocal Means(NLM)filter is proposed.Recently,abundant enhancements based on NLM filter have been performed.However,the performance of NLM filter is still inferior to that of other image processing approaches such as K-SVD.In this paper,NLM algorithm with weight refinement is utilized for image denoising.Weight refinement is performed to thoroughly take advantage of self-similarity of the image.Experimental results show good performance of the proposed method.

Dynamic Membrane for Cross-flow Micro-filtration in Treating Activated Sludge

Mixed liquid of activated sludge (AS) were micro-filtrated by dynamic membrane (DM) made of 6000 mesh kaolin. The results illustrated that the permeate quality and flux with DM filtration were superior to that with direct filtration in treating AS. The experiments of membrane washing showed that DM could abate the internal fouling of membranes efficiently, and the permeate flux of renewed membrane reached 90% of that of new membranes. The denser the mixed liquid suspended solids (MLSS) were, the lower the permeate flux was. Increasing of both flow velocity over the membrane surface and trans-membrane pressure (TMP) could lead to some enhancement of permeate flux, while the former approach could be carried out more economically. The feasibility of application of the DM to membrane bioreactor (MBR) has been ascertained.

The Choice Between Three Simple Methods for Glomerular Filtration Rate Assessment in Different Stages of Chronic Parenchymal Renal Diseases

Glomerular filtration rate （GFR） can be measured （mGFR） after intravenous application of indicators that are eliminated by kidneys or estimated （eGFR） using mathematic equations. We have compared eGFR obtained by the chronic kidney diseases epidemiology collaboration （CKD-EPI） and the Modification of diet in renal disease （MDRD） Study equations with GFR measured by technetium-99m diethylene triamine penta-acetic acid （99m^Te-DTPA） renal clearance in different stages of renal diseases in order that obtained results may contribute to more adequate choice of methods for the GFR assessment in relation to the type and stage of kidney disease. The study included a total of 189 participants with diabetes mellitus （DM）, glomerulonephritis （GN）, Balkan endemic nephropathy （BEN） and healthy subjects. 99m^Tc-DTPA clearance （ml/min/1.73 m^2） was calculated from the regression equation based on high correlation between distribution volume of radiopharmaceutical and clearance values obtained by multiple blood samples. For blood sample taken at 3 h and 4 h, clearance was calculated according to the equations： y = -0.0128x^2 ＋ 3.077x - 30.3, and y = -0.00628x^2 ＋ 2.066x - 19.3, where y is clearance, and x is distribution volume. MDRD-GFR （ml/min/l.73 m2） was calculated from equation： 186 × Scr^-1154 × age^-0.203 × 0.742 if female. CKD-EPI-GFR was calculated from equation： 141 × min（Scr/K, 1）^ α ×max（Scr/K, 1）^-1 209 × 0.993age × 1.018 if female, where Scr is serum creatinine, n is 0.7 for females and 0.9 for males, c~ is -0.329 for females and -0.411 for males, min indicates the minimum of Scr/K or 1, and max indicates the maximum of Scr/κ or 1. Irrespective of renal disease, both equations underestimated radionuclide clearance at mGFR 〉 90 ml/min/1.73 m^2 （91.7 ± 18.8 and 88.2 ± 22.0 vs. 121± 19.6, p〈0.0001） and at mGFR 60-89 ml/min/1.73 m^2 （67.1 ±19.9 and 65.8 ± 19.9 vs. 75.8 ± 9.2, p 〈 0.05 and p 〈 0.005）. They were also significantly lower than mGFR in DM patients with GFR 〉_ 90 ml/min/1.73 m^2. In patients with GFR 〉 60 ml/min/1.73 m^2, the median bias of CKD-EPI equation was lower and accuracy （percent of eGFR within 30% of mGFR, P30） was higher than that of MDRD equation. Nevertheless, in DM patients with GFR _〉 90 ml/min the accuracy of the former equation is significantly better than that of MDRD formula. Patients GFR 〈 60 ml/min had the similar bias and accuracy both eGFR equations. As CKD-EPI equation has lesser bias and improved accuracy than MDRD equation in patients with GFR 〉 60 ml/min, we suggest its use for prediction of GFR at higher renal function levels. However, underestimation of renal function by CKD-EPI equation seems not to be quite appropriate in diabetic patients with expected GFR above 90 ml/min because it may miss the patients with glomerular hyperfiltration. Thus, priority may be given to 99m^Tc-DTPA clearance method in the earlier stages of kidney diseases in type 1 diabetes mellitus. At last, in patients with expected GFR 〈 60 ml/min, it is better to monitor disease progression by estimating equations than by 99m^Tc-DTPA renal clearance, due to their simpler implementation.

Filtered-beam-search-based approach for operating theatre scheduling

To improve the efficiency of operating rooms, reduce the hospital＇ s costs and improve the level of service qualities, a scheduling method is presented based on a filtered-beam-search-based algo- rithm. Firstly, a scheduling problem domain is described. Mathematical programming models are al- so set up with an objective function of minimizing related costs of the system. On the basis of the de= scriptions mentioned above, a solving policy of generating feasible scheduling solutions is estab- lished. Combining with the speeific constraints of operation theatres, a filtered-beam-search-based algorithm is put forward to solve scheduling problems. Finally, simulation experiments are designed. The performance of the proposed algorithm is evaluated and compared with that of other approaches through simulations. Results indicate that the proposed algorithm can reduce costs, and are of prac- ticality and effectiveness.

New parameter tuning method of washout filter-aided controller for dynamic behavior adjustment

Stabilizing unstable operating points is an effective way to enhance process benefits and safety, which motivates the development for a variety of advanced control strategies. The washout filter-aided controller(WFC), originally used for electric power system and aircraft, has been introduced to adjust the dynamic behavior of chemical process. However, the parameter tuning method faces two major limitations: the dimension of operating variables must be equal to or greater than that of state variables and only one positive real eigenvalue exists in the open loop system. To overcome the two limitations, this paper proposes a new parameter tuning method, so that the WFC is applicable in most chemical processes. By solving a constrained optimization problem, the controller parameters are determined under the constraint that the reassignment of the eigenvalues of the unstable desired operating point can satisfy the stability condition. Thus parts of the equilibrium manifold including the desired operating point are stabilized without affecting the shape of the equilibrium manifold. Finally, the effectiveness of the WFC improved by the proposed parameter tuning method is illustrated through a case study for propanediol anaerobic fermentation.

A new method for extracting domain terminology

This article proposes a new general, highly efficient algorithm for extracting domain terminologies. This domain-independent algorithm with multi-layers of filters is a hybrid of statistic-oriented and rule-oriented methods. Utilizing the features of domain terminologies and the characteristics that are unique to Chinese, this algorithm extracts domain terminologies by generating multi-word unit （MWU） candidates at first and then fihering the candidates through multi-strategies. Our test resuhs show that this algorithm is feasible and effective.

A Zernike-moment-based non-local denoising filter for cryo-EM images

Cryo-electron microscopy (cryo-EM) plays an important role in determining the structure of proteins, viruses, and even the whole cell. It can capture dynamic structural changes of large protein complexes, which other methods such as X-ray crystallography and nuclear magnetic resonance analysis find difficult. The signal-to-noise ratio of cryo-EM images is low and the contrast is very weak, and therefore, the images are very noisy and require filtering. In this paper, a filtering method based on non-local means and Zernike moments is proposed. The method takes into account the rotational symmetry of some biological molecules to enhance the signal-to-noise ratio of cryo-EM images. The method may be useful in cryo-EM image processing such as the automatic selection of particles, orientation determination, and the building of initial models.

Application of a novel constrained wavelet threshold denoising method in ensemble-based background-error variance

A more efficiem noise filtering technique is needed in ensemble data assimilation, to improve traditional spectral filtering methods that cannot reflect the local characteristics of spatial scales. In this paper, we present the design of a novel constrained wavelet threshold denoising method （CWTDNM） by introducing an improved threshold value and a new constraining parameter. The proposed method aims to filter noise swamped over different scales. We prepared an ideal experiment object based on the two-dimensional barotropic vorticity equation. A suitable wavelet basis function （i.e., Dbl 1） and the optimal number of decomposition levels （i.e., five） were first selected. The results show that, given the wavelet coefficients are constrained by the parameter, the CWTDNM can produce better filtering results with the smallest root mean square error （RMSE） compared to similar methods. In addition, the filtering accuracy of 10 ensemble sample variances using the CWTDNM is equivalent to that estimated directly from 80 ensemble samples, but with the runtime reduced to approximately one-seventh. Furthermore, a large peak signal-to-noise ratio, which implies a low RMSE, suggests that the proposed method suitably preserves most of the information after denoising.