Text sentiment analysis plays an important role in social network information mining. It is also the theoretical foundation and basis of personalized recommendation, circle of interest classification and public opinion analysis. In view of the existing algorithms for feature extraction and weight calculation, we find that they fail to fully take into account the in fluence of sentiment words. Therefore, this paper proposed a fine-grained short text sentiment analysis method based on machine learning. To improve the calculation method of feature selection and weighting and proposed a more suitable sentiment analysis algorithm for features extraction named N-CHI and weight calculation named W-TF-IDF, increasing the proportion and weight of sentiment words in the feature words Through experimental analysis and comparison, the classification accuracy of this method is obviously improved compared with other methods.
This article reports a method for forecasting an earthquake by synchronous anomalies of optical astronomic time-latitude residuals. The so-called optical astronomic time-latitude residuals for a certain astrometric instrument are the rest after deducting the effects of Earth whole motion from the astronomical time and latitude observations determined by the instrument. Forecasting practice for four earthquakes around the Yunnan Observatory occurring after 2010 shows that it does not generate false forecasts, and also does not miss forecasts of major earthquakes. This forecasting practice proves that the synchronous anomalies of astronomical time-latitude residuals can provide effective warning sign for earthquake occurrence around observatory station, thus deserves attention and further study. and Su Youjin, Gao Yuping, Hu Hui.
When measuring cell membrane electrical capacitance in whole cell configuration using alternating currents, the resolution decreases with increasing membrane conductance and pipette resistance. Improved resolution was attained by the dual-frequency method which was modified as to control the voltage amplitude of one of the measuring frequencies. A model circuit was developed for the verification of the method. This circuit allows measurement of calibrated capacitance changes even in the range of 5 to 20 fF. Moreover, the method was applied to capacitance measurements on pancreatic exocrine acinar cells. The results of measurements on the model as well as on pancreatic acinar cells are presented. The principle can also be applied to other hardware and software methods for measuring electrical cell membrane parameters.
A system for the evaluation of temperature changes in living tissue at a dimensional level of a single cell is described. A glass micropipette the tip of which is filled with semiconducting glass (Rech et al. 1992), is used as a microsensor. The changes of conductivity of the sensor due to variations of temperature are evaluated by electronic circuitry based on the measurement of an AC current of sinusoidal waveform flowing through the sensor. Temperature changes in the range of 0.01 K can be detected in this way.
In the present study, a high percentage of Japanese anglerfish, Lophius litulon (Jordan, 1902), contained a microsporidian infection of the nervous tissues. Xenomas were removed and prepared for standard wax histology and transmission electron microscopy (TEM). DNA extractions were performed on parasite spores and used in PCR and sequencing reactions. Fresh spores measured 3.4 × 1.8 µm and were uniform in size with no dimorphism observed. TEM confirmed that only a single developmental cycle and a single spore form were present. Small subunit (SSU) rDNA sequences were >99.5% similar to those of Spraguea lophii (Doflein, 1898) and Glugea americanus (Takvorian et Cali, 1986) from the European and American Lophius spp. respectively. The microsporidian from the nervous tissue of L. litulon undoubtedly belongs in the genus Spraguea Sprague et Vávra, 1976 and the authors suggest a revision to the generic description of Spraguea to include monomorphic forms and the transfer of Glugea americanus to Spraguea americana comb. n. Since no major differences in ultrastructure or SSU rDNA sequence data exist between Spraguea americana and the microsporidian from the Japanese anglerfish, they evidently belong to the same species. This report of Spraguea americana is the first report of a Spraguea species from L. litulon and indeed from the Pacific water mass.
A new Microsporidium sp. infects Rhizophagus grandis Gyllenhall, a beetle which preys on the bark beetle Dendroctonus micans Kugellan in Turkey. Mature spores are single, uninucleate, oval in shape (3.75 ± 0.27 µm in length by 2.47 ± 0.13 µm in width), with a subapically fixed polar filament. The polar filament is anisofilar, coiled in 7-8 normal and 3-4 reduced coils. Other characteristic features of the microsporidium are the four/five nuclear divisions to form 16/32 (commonly 16) spores, subpersistent sporophorous vesicles (pansporoblasts) remaining till formation of the endospore, and the vesicles dissolved with free mature spores. The polaroplast is divided into three zones: an amorphous zone, dense layers, and a lamellar-tubular area extending to the central part of the spore.
Phthalates are chemicals interfering with the function of testosterone and are suspected to play a role in the emergence of neurodevelopmental diseases. This could be due to interference with brain development for which optimal testosterone levels are essential. We investigated the effect of prenatal and early postnatal exposure to a phthalate mixture on the anogenital distance (AGD), plasma testosterone levels and social behavior in rats. Pregnant rats were exposed to a mixture of diethylhexyl, diisononyl and dibutyl phthalate, each at a dose of 4.5 mg/kg/day, from gestational day 15 to postnatal day 4. A social interaction test was performed to assess sociability in the three ontogenetic stages (weaning, puberty, adulthood). AGD was measured in adulthood to assess changes in prenatal testosterone levels. Plasma testosterone levels were measured in adults by a radioimmunoassay. The total frequency and time of socio-cohesive interactions were decreased in phthalate exposed females in weaning, puberty and adulthood. Phthalate exposed males showed a decrease in the frequency of social interactions in weaning only. Shorter anogenital distance was observed in adult males exposed to phthalates. Decreased testosterone levels were observed in the exposed group in both sexes. Our results suggest that early developmental phthalate exposure may play an important role in the hormonal and behavioral changes associated with several neurodevelopmental diseases.
A mixture of support vector machines (SVMs) is proposed for time series forecasting. The SVMs mixture is composed of a two-stage architecture. In the first stage, self-organizing feature map (SOM) is used as a clustering algorithm to partition the whole input space into several disjointed regions. A tree-structured architecture is adopted in the partition to avoid the problem of predetermining the number of partitioned regions. Then, in the second stage, multiple SVMs, also called SVM mixture, that best fit partitioned regions are constructed by finding the most appropriate kernel function and the optimal free parameters of SVMs. The experiment shows that the SVMs mixture achieves significant improvement in the generalization performance in comparison with the single SVMs model. In addition, the SVMs mixture also converges faster and use fewer support vectors.
The functional structure of our new network is not preset; instead, it
comes into existence in a random, stochastic manner.
The anatomical structure of our model consists of two input “neurons”, hundreds up to five thousands of hidden-layer “neurons” and one output “neuron”.
The proper process is based on iteration, i.e., mathematical operation governed by a set of rules, in which repetition helps to approximate the desired result.
Each iteration begins with data being introduced into the input layer to be processed in accordance with a particular algorithm in the hidden layer; it then continues with the computation of certain as yet very crude configurations of images regulated by a genetic code, and ends up with the selection of 10% of the most accomplished “offspring”. The next iteration begins with the application of these new, most successful variants of the results, i.é., descendants in the continued process of image perfection. The ever new variants (descendants) of the genetic algorithm are always generated randomly. The determinist rule then only requires the choice of 10% of all the variants available (in our case 20 optimal variants out of 200).
The stochastic model is marked by a number of characteristics, e.g., the initial conditions are determined by different data dispersion variance, the evolution of the network organisation is controlled by genetic rules of a purely stochastic nature; Gaussian distribution noise proved to be the best “organiser”.
Another analogy between artificial networks and neuronal structures lies in the use of time in network algorithms.
For that reason, we gave our networks organisation a kind of temporal development, i.e., rather than being instantaneous; the connection between the artificial elements and neurons consumes certain units of time per one synapse or, better to say, per one contact between the preceding and subsequent neurons.
The latency of neurons, natural and artificial alike, is very importaiit as it
enables feedback action.
Our network becomes organised under the effect of considerable noise. Then, however, the amount of noise must subside. However, if the network evolution gets stuek in the local minimum, the amount of noise has to be inereased again. While this will make the network organisation waver, it will also inerease the likelihood that the erisis in the local minimum will abate and improve substantially the state of the network in its self-organisation.
Our system allows for constant state-of-the-network reading by ineaiis of establishing the network energy level, i.e., basically ascertaining progression of the network’s rate of success in self-organisation. This is the principal parameter for the detection of any jam in the local minimum. It is a piece of input information for the formator algorithm which regulates the level of noise in the system.