Cryptosporidium parvum causes life-threatening diarrhoea in immunocompromized, especially AIDS patients and the efficiency of proposed anti-cryptosporidial therapies is limited or doubtful. An immunosuppressed adult rat model of C. parvum infection was developed for screening molecules candidate for curative and preventive activity in human cryptosporidiosis. Among 31 drugs tested, lasalocid (2-10 mg/kg/24 h), and sinefungin (2-10 mg/kg/24 h), exhibited some activity against C. parvum infection. Oral sinefungin therapy resulted in a dose related suppression of oocysts shedding, which correlated with oocyst disappearance from ileum sections and was also efficient in preventing infection. Relapses were observed after discontinuation of curative sinefungin therapy, which suggests that the biliary tract, a major location and parasite reservoir which sustains persisting infection, was not cleared of parasites by the drug. Improved therapeutic procedures with sinefungin (or analogues) will result from current pharmacological studies.
This article presents the problem of improving the classifier of handwritten letters from historical alphabets, using letter classification algorithms and transliterating them to Latin. We apply it on Palmyrene alphabet, which is a complex alphabet with letters, some of which are very similar to each other. We created a mobile application for Palmyrene alphabet that is able to transliterate hand-written letters or letters that are given as photograph images. At first, the core of the application was based on MobileNet, but the classification results were not suitable enough. In this article, we suggest an improved, better performing convolutional neural network architecture for hand-written letter classifier used in our mobile application. Our suggested new convolutional neural network architecture shows an improvement in accuracy from 0.6893 to 0.9821 by 142% for hand-written model in comparison with the original MobileNet. Future plans are to improve the photographic model as well.
Voice over Internet Protocol (VoIP) networks are an increasingly important field in the world of telecommunication due to many involved advantages and potential revenue. Measuring speech quality in VoIP networks is an important aspect of such networks for legal, commercial and technical reasons. The E-model is a widely used objective approach for measuring the quality as it is applicable to monitoring live-traffic, automatically and non-intrusively. The E-model suffers from several drawbacks. Firstly, it considers the effect of packet loss on the speech quality collectively without looking at the content of the speech signal to check whether the loss occurred in voiced or unvoiced parts of the signal. Secondly, it depends on subjective tests to calibrate its parameters, which makes it applicable to limited conditions corresponding to specific subjective experiments. In this paper, a solution is proposed to overcome these two problems. The proposed solution improves the accuracy of the E-model by differentiating between packet loss during speech and silence periods. It also avoids the need for subjective tests, which makes it extendable to new network conditions. The proposed solution is based on an Artificial Neural Networks (ANN) approach and is compared with the accurate Perceptual Evaluation of Speech Quality (PESQ) model and the original E-model to confirm its accuracy. Several experiments are conducted to test the effectiveness of the proposed solution on two well-known ITU-T speech codecs; namely, G.723.1 and G.729.
The pine bark beetle, Dendroctonus armandi, is a native pest restricted to forests in the Qinling Mountains in China. There was an outbreak of this species there that affected over 0.36 million hectares of pine forest. We hypothesized that there are differences between the numbers of beetles captured by traps baited with various combinations of candidate semiochemicals extracted from the hindguts of D. armandi. In order to determine whether a better operational lure could be developed for D. armandi, we analyzed the volatiles in extracts of the hindgut of D. armandi and tested various combinations of candidate semiochemicals. The GC-MS and GC-FID analyses of volatiles in the extracts of the hindguts of D. armandi collected at different stages of the attack revealed that they are mainly a-pinene, b-caryophyllene and (+)-3-carene with minor amounts of myrcene, limonene, verbenol and verbenone. We tested various combinations of these candidate semiochemicals in order to determine an optimal blend. Our results suggest that the addition of b-caryophyllene to either a-pinene, or blends of a-pinene and other candidate semiochemicals, significantly enhanced the attractiveness of the lures for D. armandi. Field trapping experiments indicated that the blends that included b-caryophyllene, myrcene and other candidate semiochemicals resulted in significantly higher trap catches (161–243% higher) than a-pinene alone. Therefore, a simple lure consisting of a-pinene and b-caryophyllene would be an optimal blend for D. armandi. We conclude that this blend of semiochemicals may provide a better method of reducing the numbers of D. armandi in forest ecosystem., Shou-An Xie, Shu-Jie LV., and Obsahuje seznam literatury
Adults of the wingless bagworm moth, Eumeta variegata, show remarkable sexual dimorphism. Final-instar larvae of the male have invaginated wing discs, whereas those of the female are rudimentary. To determine the best method for culturing the wing discs of E. variegata, which in both sexes are attached to the larval integument, two methods of culturing the larval wing discs are compared. Initially, a stationary culture was used. In these cultures necrotic cells and degeneration of wing discs of males were sporadically observed. By contrast, many small vacuoles were observed in the female wing rudiment under these conditions. In order to overcome some of the problems associated with stationary culture, rotating culture was used and resulted in the wing discs of males and females remaining in good condition. A histological analysis revealed that the wing disc morphology was normal when they were cultured in this way. These results indicate that rotating the culture medium is the better procedure for studying the action of hormones on the differentiation and metamorphosis of reduced wing rudiments in E. variegata.
A new pre-processing algorithm for improved discrimination of odor samples is proposed. The pre-processed odor sample outputs from two sensors are input using a learning-vector quantization (LVQ) classifier as a means of odor recognition to be employed within electronic nose applications. The proposed algorithm brings out highly scattered classes while minimizing the within-class scatter of the samples given an odor class. LVQ is observed to operate robustly and reliably in terms of variation of parameters of interest, mainly a learning parameter. Due to the increased performance along with computational simplicity and robustness, the scheme is suitable to sample-by-sample identification of olfactory sensory data and can be easily adapted to hierarchical processing with other sensory data in real-time.
The presence of common mode error (CME) in the coordinate displacement time series of the Global Navigation Satellite System (GNSS) affects geophysical studies using GNSS observations. In order to investigate the effect of CME on the time series in GNSS networks in Shanxi, this paper proposes an improved superposition filtering method by introducing single-day solution accuracy, correlation coefficient, and spherical distance between stations as weights. The filtering effect is evaluated using the GNSS data in Shanxi. By using the improved stacking filtering method, the root mean square (RMS) values for N, E, U are reduced by approximately 27.8%, 29.0%, and 46.0%, respectively. And compared to the traditional stacking filter, our improved method can achieve better results with CME extraction. We investigate the CME spatial-temporal characteristics and its relationship with environmental loading. The results show that the CME between stations decreases as the distance between stations increases. In addition, we analyze the effect of CME on the noise component and velocity estimates. Results show that removing the CME refines the velocity and leads to a significant reduction in the magnitude of noise, indicating that the CME is dominated by the flicker noise in Shanxi Province.
In the general tropospheric tomography model, the tomographic area is divided into a large number of voxels, which provides convenience for reconstructing tomographic observation equations. However, due to the defect of GNSS acquisition geometry, there are plenty of empty voxels for any tomographic epoch. Moreover, an unreasonable assumption that water vapor density is constant within a voxel was imposed on the tomographic model. In this study, we proposed an improved method based on the dynamic node parameterized algorithm to solve both key problems. The proposed approach first tries to select effective GNSS signals and determines the dynamic scope of the tomographic area using the dynamic algorithm. The parameterization of the tomography model is performed by a cubic spline formula and Gauss weighted function. Additionally, a piecewise linear fitting method based on Newton-Cotes interpolation is introduced to estimate the tomographic observation of slant water vapor (SWV). The experimental results show that the average number of effective signals increased by 32.33 % and the mean RMSE of the tomographic results is decreased by 45 % with the proposed method. Further, compared with the tomographic results of the general method, the improved solutions have a more centralized distribution and a smaller bias., Wenyuan Zhang, Shubi Zhang, Nan Ding and Pengxu Ma., and Obsahuje bibliografii